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• Published: 16 November 2023

Microbial methane cycling in a landfill on a decadal time scale

• Daniel S. Grégoire   ORCID: orcid.org/0000-0002-1109-7333 1   nAff2 ,
• Nikhil A. George   ORCID: orcid.org/0009-0003-7483-5780 1 &
• Laura A. Hug 1  

Nature Communications volume  14 , Article number:  7402 ( 2023 ) Cite this article

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• Biogeochemistry
• Environmental microbiology
• Metagenomics
• Microbial ecology

Landfills generate outsized environmental footprints due to microbial degradation of organic matter in municipal solid waste, which produces the potent greenhouse gas methane. With global solid waste production predicted to increase substantially in the next few decades, there is a pressing need to better understand the temporal dynamics of biogeochemical processes that control methane cycling in landfills. Here, we use metagenomic approaches to characterize microbial methane cycling in waste that was landfilled over 39 years. Our analyses indicate that newer waste supports more diverse communities with similar composition compared to older waste, which contains lower diversity and more varied communities. Older waste contains primarily autotrophic organisms with versatile redox metabolisms, whereas newer waste is dominated by anaerobic fermenters. Methane-producing microbes are more abundant, diverse, and metabolically versatile in new waste compared to old waste. Our findings indicate that predictive models for methane emission in landfills overlook methane oxidation in the absence of oxygen, as well as certain microbial lineages that can potentially contribute to methane sinks in diverse habitats.

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Introduction.

Landfills worldwide are one of the key mitigation gaps in managing global methane emissions. From 2000 to 2017, landfills produced 60 to 69 Tg of methane per year 1 , 2 . In high GDP per capita countries (i.e., defined by the World Bank as countries with a GDP per capita >49,000 USD in 2022) such as the United States (GDP per capita 76,389 USD in 2022) 3 , landfills can account for up to 20% of net methane emissions 4 . As of 2018, it is estimated that 2.01 billion tonnes (i.e., 2010 Tg) of solid waste has been produced globally, with 35% of this waste being landfilled 5 . With solid waste production predicted to increase to 3.40 billion tonnes (i.e., 3400 Tg) by 2050 5 , there is a pressing need to better understand the biogeochemical processes that control methane’s fate in landfills to enable the development of waste management practices that mitigate greenhouse gas (GHG) emissions.

Landfilled waste is spatially and geochemically heterogeneous, with compositional changes occurring over extended time scales. Part of the challenge in managing GHG emissions from municipal solid waste (MSW) lies in predicting how these variables interact to affect methane cycling over decades of landfill operation.

The major biogeochemical transitions that occur in a sanitary landfill can be summarized using a five-phase conceptual model [ 6 , 7 and references therein]. Phase 1 is the aerobic phase, where chemoheterotrophic microbes consume oxygen to metabolize organic carbon from paper, food waste, and cover soils. Phase 2 is the anaerobic acid phase, where fermentative microbes hydrolyze cellulose-bearing waste and produce labile organic substrates that support fermentation and organic acid production, which decreases pH in the landfill. Phase 3 is characterized by rapid methanogenesis, where labile organic and inorganic carbon substrates stimulate biogenic methane production by anaerobic archaea. Phase 4 is delineated by a transition to slow methanogenesis, where substrates that support methanogenesis have been depleted and methane production slows. In phase 5, oxygen infiltration can occur because substrates that support aerobic heterotrophy have been exhausted, such that aerobic respiration cannot outpace oxygen diffusion from the atmosphere. Phase 5 is considered the point at which MSW has stabilized yet remains the least well-understood of the lifecycle phases because it can take over 20 years to develop and there are limited datasets covering this timespan.

Microbial metabolisms drive every major biogeochemical change that occurs in a landfill. A key 16S rRNA amplicon sequencing survey that sampled 19 landfills in the United States suggested that the age of refuse and local environmental conditions play significant roles in shaping microbial communities in landfill leachate 8 . Several smaller-scale amplicon sequencing studies have suggested that variables including age 9 , nutrient concentrations 10 , physicochemical parameters (e.g., temperature and pH) 11 , and contaminant concentrations 12 , 13 , 14 all shape microbial community structure in landfills. 16S rRNA surveys have also been used to characterize the succession of microbial taxa over the course of waste degradation in controlled settings 15 , 16 , 17 , 18 . Methane cycling guilds in landfills have been examined using 16S rRNA primers specific to methanogens and methanotrophs 19 , 20 . Sequencing the mcrA gene, which codes for the methyl coenzyme M reductase responsible for converting methyl-coenzyme M to methane during methanogenesis 21 , has expanded the diversity of methanogenic taxa associated with landfills 22 , 23 . Similarly, sequencing the pmoA gene, which codes for a key subunit of the particulate methane monooxygenase (pMMO), and the mmoX gene, which codes for a key subunit in the soluble methane monooxygenase (sMMO), has clarified the structure of methanotrophic communities in landfill cover soils 24 , 25 , 26 .

In the case of methanogens, taxonomy determined via amplicon sequencing data is routinely used to infer whether hydrogenotrophic (i.e., H 2 and CO 2 requiring) or acetoclastic (i.e., acetate requiring) methanogenesis contributes to methane production. Taxonomy is also used to determine whether methane oxidation is carried out by bacteria that require low levels of methane and high levels of key trace nutrients (i.e., Type I methanotrophs) or high levels of methane but low levels of other key substrates (i.e., type II methanotrophs) 27 . These approaches are limited when applied to novel methane cycling taxa that are not related to well-characterized model organisms and tend to ignore more diverse methane cycling metabolisms that cannot be captured by the dichotomies indicated above 28 . This includes intra-aerobic and anaerobic methane oxidation metabolisms that do not require exogenous oxygen, which is rarely considered despite landfills being dominated by anoxic habitats conducive to these lifestyles.

The recent application of metagenomic sequencing to landfills offers a promising solution to the limitations of previous work. Metagenomics has allowed valuable insights into the physiological pathways contributing to waste degradation including cellulose metabolism 29 , 30 and plastic biodegradation 31 . Metagenomics has also been used to address human health concerns tied to landfills such as the occurrence of antibiotic resistance in pathogens found in MSW 32 , 33 . Genome-resolved metagenomics 34 can be used to characterize microbial diversity across physicochemical gradients, including identifying factors constraining the distribution of methanogens in MSW 35 and the range of methanotrophic lifestyles that can be supported (e.g., facultative vs. obligate, aerobic vs. microaerophilic vs. anaerobic). Genome-resolved metagenomics also provides the opportunity to consider the contributions of methane-cycling organisms in the broader context of nutrient-cycling pathways and central redox metabolisms that control landfill biogeochemistry 36 . Although amplicon sequencing surveys have shed light on the changes in community structure that occur across landfill habitats, metagenomic surveys that examine the major guilds and physiological pathways controlling biogeochemical cycles over the spatial and temporal scales relevant to landfill lifecycles are lacking.

Here, we use metagenomic sequencing to provide a historical perspective on microbial communities, with an emphasis on methane cycling guilds, in a sanitary landfill across time. In this study, we compare methanogen and methanotroph community structure and metabolic capacity in leachate samples from a landfill spanning the five landfill lifecycle phases. We use phylogenomic analyses and metabolic models to identify adaptations in methanotrophs and expand the diversity of taxa potentially capable of oxidizing methane in oxygen-limited landfill habitats. Finally, we demonstrate how the biodiversity in landfills includes and allows the identification of microbes with uncharacterized methane cycling capabilities whose role in the global methane cycle has been overlooked.

Results and discussion

Landfill lifecycle geochemistry.

Landfill cells A, B, and C represent older waste. Cell A was filling from 1980-1982 (39 years old), cell B was filling from 1982–1988 (37 years old), and cell C was filling from 1988–1993 (31 years old). Landfill cells A and B can be classified to phase 5 of the landfill lifecycle whereas cell C is in phase 4. These classifications stem from the low gas production observed across all three cells and the evidence of oxygen intruding into cells A and B (Fig.  1 ). Gas data aligned with leachate geochemistry, which showed that biological and chemical oxygen demand (BOD and COD, respectively) decreased in line with the low availability of organic substrates at these locations (Figs. S 1 , S 2 ). The weak evidence of oxygen intrusion and the higher BOD/COD ratio recorded in cell C vs. A and B resulted in cell C’s classification to phase 4 (Table  S1 ).

The number of observations for total gas flared and gas composition is n  = 103 for cells A and B, cell C, and cell E West. The number of observations for total gas flared and gas composition is n  = 101 for cells C and D, cell D, and E East. The number of observations for total gas flared and gas composition is n  = 84 for cell F. The bottom and the top of the boxes show the first and third quartiles respectively, the bar in the middle shows the median value, whiskers show the minimum and maximum values within 1.5 times the interquartile range, and values that extend beyond 1.5 times the interquartile range are shown as points above and below the whiskers. Data were provided by the site owners for 2018-2019 to cover seasonal variation over two years and capture current trends in gas emissions. Source Data are provided as a Source Data file.

Landfill cell D contains two sub-cells, D1 which was filling from 1993-1998 (26 years old), and D2 which was filling from 1995–1998 (24 years old). Both locations in cell D were classified to phase 4 of slow methanogenesis based on the low levels of gas produced despite cell D’s comparable size to cells E and F (Fig.  1A and Table  S1 ). The gas at location D2 was largely comprised of methane although the physical connection between the C/D valley vent and location D1 suggests some oxygen may be intruding at D1 (Fig.  1B ). Gas data aligned with aqueous geochemistry wherein peaks in BOD, COD and organic acids have long since passed at both locations (Figs. S 1 , S 2 ). Location D2 showed slightly higher gas production compared to D1, which may be attributed to the higher BOD/COD ratio. This increased BOD/COD ratio at the time of sampling reflects higher concentrations of carbon sources such as acetate (74 mg L −1 vs. 2.3 mg L −1 ) that can support methanogenesis (Figs.  1 , S 2 , and Table  S1 ).

Cell E was filling from 1999–2014 (20 years old) and was classified as being in phase 3 of rapid methanogenesis based on total gas production being almost an order of magnitude higher compared to cells A, B, C, and D and gas being largely comprised of methane (Fig.  1 ). Cell E reached peak BOD and COD over a similar time frame to cell D and showed circumneutral pH and reducing conditions in line with phase 3 of the landfill lifecycle (Figs. S 1 , S 2 ). Notably, cell E showed lower BOD/COD compared to D2 suggesting this is not a sufficient standalone index of methanogenic potential (Table  S1 ). Cell E also experienced historically lower peaks in organic acids compared to cells A, B, C, and D (Fig S 2 ). These results could be attributed to a yard waste diversion program implemented in 2000 or a physical connection to landfill cell D designed to redistribute leachate evenly between cells D and E (Table  S1 ). Lower moisture in cell E would have limited the circulation of nutrients and the maintenance of anoxic habitats required for fermentative acid production such that organic acid concentrations decreased. Cell E also experienced a decline in bicarbonate concentrations, reaching concentrations as low as 851 mg L −1 before increasing to concentrations comparable to the peaks observed for landfill cells A, B, C, and D (i.e., ~3500 mg L −1 ) (Fig S 2 ). Although environmental conditions seem homogenous enough in cell E to support consistent methane production across two different sampling vents, we make note of the decrease in bicarbonate because it occurred on the day of our sampling trip (2019-12-12) which may have impacted the observed microbial community.

Landfill cell F contains two sub-cells, F1 which was filling from 2014-present (5 years old), and F2 which was filling from 2016 to present (3 years old). Cell F is classified as transitioning from phase 2 of anaerobic acid production to phase 3 of rapid methanogenesis based on recent depletions in organic carbon occurring alongside highly variable amounts of methane production. Cell F displayed a similar gas composition to cell E with gas being largely comprised of methane but subject to highly variable total gas production (i.e., maxima recorded of >1000 cubic feet per minute and minima as low as 35 cubic feet per minute) (Fig.  1 ). Location F1 experienced an increase in COD and recent decrease in BOD whereas location F2 saw an increase in COD and BOD alongside peaks in organic acids and the highest BOD/COD ratio recorded across the landfill (Figs. S 1 , S 2 , and Table  S1 ). These observations suggest that an influx of organic acids that can be oxidized is occurring at cell F, which is further supported by increasing bicarbonate concentrations at both locations (Fig S 2 ). These changes in gas and aqueous geochemistry align with what we would expect of a microbial community where methanogens are competing with heterotrophs for organic substrates as the landfill transitions from a state of fermentative acid production to rapid methane production.

Overview of the landfill microbial community

1881 metagenome-assembled genomes (MAGs) were recovered from the landfill samples. The total number of MAGs recovered from older landfill cells was lower compared to newer landfill cells: 93 MAGs were recovered from cell A, 188 MAGs from cell B, 134 from cell C, 220 MAGs from cell D1, 269 from cell D2, 210 from cell E, 294 from cell F1 and 239 from cell F2 (Fig.  2 ).

The Bray-Curtis dissimilarity index was used to generate a distance matrix required for the NMDS analysis. The default command ‘metaMDS’ from the ‘vegan’ package was used to run 20 iterations of the NMDS ordination, which provided a stress value of 0.0487. Landfill sampling sites have been colour-coded, and the size of each point has been scaled to the total number of MAGs recovered from each sample to indicate richness. Source Data are provided as a Source Data file.

MAGs were taxonomically classified to 62 phyla and 325 families (full taxonomy and annotation information for all MAGs is available in Supplementary Data  1 on the Open Science Framework (OSF) at https://doi.org/10.17605/OSF.IO/6X5ZC 37 ). Beta diversity analyses based on relative abundance summed at the family level showed that community composition was more similar in newer landfill cells (i.e., D2, E, F1, and F2) compared to older landfill cells (i.e., cells A, B, and C) (Fig.  2 ). Although location D1 began operating only two years before location D2, the community composition of D1 was more similar to cell B, which began receiving waste 11 years earlier (Fig.  2 ). These differences in community composition for cell D are in line with the discrepancies in the composition of flare gas and the availability of organic carbon noted in the previous section. The community composition in cells A and B was more similar compared to cell C, which aligns with geochemical data indicating these parts of the landfill are in different lifecycle phases (Fig.  2 ). Overall, these observations suggest that newer landfill cells that have experienced methane production more recently support more diverse microbial populations with similar composition compared to older cells where methane production has declined.

Landfill cells D1, D2, E, F1, and F2 harboured more distinct phyla compared to cells A, B, and C, in line with the total number of MAGs recovered from each site (Fig S 3 ). Microbial communities in cells A, B, and C harboured populations classified to the phylum Proteobacteria that ranged in abundance from 34 to 46%. In contrast, Proteobacteria were present at <5% in cells D1, D2, E, F1, and F2 (Fig S 3 ). Members of the Patescibacteria ranged in abundance from 6 to 35% in cells B, D1, D2, and E, although no clear trend was observed for this lineage with respect to the age of each landfill cell (Fig S 3 ). Members of the Bacteroidota displayed high relative abundance ranging from 15 to 39% in landfill cells producing methane or thought to be transitioning to a state of rapid methane production (i.e., D2, E, F1, and F2) (Fig S 3 ). Members of the phylum Campylobacterota dominated landfill cell C with a relative abundance of 48% and occurred at the relative abundance of 28 and 22% in cells A and E, respectively (Fig S 3 ). The relative abundance of the phyla Firmicutes_ A, Halobacterota (renamed to Halobacteriota in GTDB r95), Cloacimonadota , and Firmicutes fluctuated with landfill cell age, ranging from 10 to 20% in newer landfill cells (i.e., D2, E, F1, and F2) (Fig S 3 ). Most other phyla accounted for a minor portion of the community and occurred at low relative abundances, <1%, across the landfill (Fig S 3 ).

Family-level data was interpreted by focussing on the most abundant families occurring across the landfill cells in chronological order based on age. Members of the Gallionellaceae ranged in abundance from 10 to 26% in older landfill cells (i.e., A, B, and C) but decreased to <5% in newer landfill cells (i.e., D1, D2, E, F1, and F2) (Fig S 4 ). The abundance of Gallionellaceae aligns with oxygen intruding in older parts of the landfill given that representative genera such as Gallionella detected in the landfill contain exclusively microaerophilic iron oxidizers capable of autotrophic growth 38 well-suited to such habitats (Supplementary Data  1 on the Open Science Framework (OSF) at https://doi.org/10.17605/OSF.IO/6X5ZC 37 ). Recent work has also shown that unknown species in the Gallionellaceae can support iron oxidation coupled to autotrophy and nitrate reduction 39 , which aligns with the >90% completion of the Calvin cycle and the potential for denitrification observed in Gallionellaceae MAGs from the landfill (Supplementary Data  1 on the Open Science Framework (OSF) at https://doi.org/10.17605/OSF.IO/6X5ZC 37 ). Members of the family Sulfurimonadaceae occurred at similar relative abundance to the Gallionellaceae (i.e., 26%) in cell A but were at much lower abundance in other landfill cells (i.e., B, C, D1, D2, E, F, and F1) (Fig S 4 ). Members of the Sulfurimonadaceae harbour versatile redox metabolisms that can be coupled to autotrophy 40 , 41 , which would be well-suited to landfill cell A but also allow them to persist over redox gradients encountered in other landfill cells. These observations align with the capacity for thiosulphate oxidation and nitrogen reduction, and >70% completion of the Calvin cycle in Sulfurimonadaceae MAGs from the landfill (Supplementary Data  1 on the Open Science Framework (OSF) at https://doi.org/10.17605/OSF.IO/6X5ZC 37 ).

The family Arcobacteraceae dominated the community at landfill cell C with a relative abundance of 44% (Fig S 4 ). This dominance can be attributed to two populations of the genus Aliarcobacter , which displayed the highest genomic coverage for all MAGs analyzed in this data set (i.e., MAGs STC_123 and STC_124 had coverage values of 527.30 and 857.20, respectively) (Supplementary Data  1 on the Open Science Framework (OSF) at https://doi.org/10.17605/OSF.IO/6X5ZC 37 ). Members of the Aliarcobacter genus (previously referred to as Arcobacter ) have been detected in brackish waters, sewage, and food products (summarized in 42 ) and have also been identified as abundant members of landfill microbial communities 8 , 14 , 17 . Members of this genus have been best-studied in the context of enteric and zoonotic pathogenesis 42 , 43 , suggesting they could be introduced to landfills through food, animal, or human waste. Members of the Aliarcobacter can tolerate a wide range of changes in physical conditions and display the capacity for aerobic and microaerophilic growth (reviewed in 44 ), which could make them well-suited to heterogeneous landfill environments. MAGs from the Arcobacteraceae in the landfill encoded the capacity for dissimilatory nitrate reduction, which may offer them an advantage in anoxic landfill habitats (Supplementary Data  1 on the Open Science Framework (OSF) at https://doi.org/10.17605/OSF.IO/6X5ZC 37 ), however further investigation is required to identify which adaptations allow this family to dominate in landfill cell C.

Members of the Dysgonomonadaceae and Cloacimonadaceae displayed comparable relative abundance to the Gallionellaceae and Sulfurimonadaceae (i.e., 12 to 20%) but only in newer landfill cells in states of high methane production (i.e., E, F1, and F2) (Fig S 4 ). Members from both families have repeatedly been detected in landfills 17 , 35 , 45 and could potentially contribute substrates to support methanogenesis. Previous work on members of the Dysgonomonadaceae in anaerobic digestion settings has shown that members of this family can hydrolyze recalcitrant organic substrates to produce acetate, which can be further metabolized to produce carbon dioxide and hydrogen during anaerobic fermentative growth 46 , 47 , 48 . Recent genomic surveys of the phylum Cloacimonadota , in which Cloacimonadaceae is the sole named family, have shown there are distinct clades adapted to landfills that can potentially support methane production through acetogenic metabolism 45 . These observations align with the metabolic potential observed in MAGs classified to the Dysgonomonadaceae and Cloacimonadaceae wherein most MAGs included genes coding for the phosphotransacetylase and acetate kinase that could be used to produce acetate (Supplementary Data  1 on the Open Science Framework (OSF) at https://doi.org/10.17605/OSF.IO/6X5ZC 37 ). Although most MAGs from the Dysgonomonadaceae were largely classified to the genera Proteiniphilum and Fermentimonas , MAGs from the Cloacimonadaceae could not be classified to the genus level (Supplementary Data  1 on the Open Science Framework (OSF) at https://doi.org/10.17605/OSF.IO/6X5ZC 37 ). This observation suggests there is still considerable diversity to uncover in this lineage with important roles in carbon cycling in landfills.

Methanogen community structure

From the initial 1,881 MAGs obtained from landfill metagenomes (Methods and Table  S2 for metagenome statistics), 74 MAGs were identified as putative methanogens coming from leachate samples. The putative methanogen MAGs were taxonomically classified into 3 phyla the following curation: Halobacterota (renamed to Halobacteriota in newer versions of GTDB), Thermoplasmatota , and Euryarchaeota (Fig.  3 ). These phyla spanned 10 families (in alphabetical order): Methanobacteriaceae, Methanocorpusculaceae , Methanocullaceae, Methanofollaceae, Methanomethylophilaceae, Methanomicrobiaceae, Methanoregulaceae Methanosarcinaceae, Methanospirillaceae , and Methanotrichaceae (Figs.  3 , S 5 ). In this instance, we did not classify MAGs from the family Methanoperedenaceae as methanogens, given that they are known anaerobic methane oxidizing Archaea, and are instead discussed in the methanotrophy section (Figs.  3 , S 5 ). Two MAGs could not be classified to the family level: STE_86, classified to the order Methanobacteriales , and STF1_149, the only MAG classified to the order Methanofastidiosales (Figs.  3 , S 5 , and Supplementary Data  1 on the Open Science Framework (OSF) at https://doi.org/10.17605/OSF.IO/6X5ZC 37 ).

The abbreviation CODH/ACS complex denotes the completion of the carbon monoxide dehydrogenase/acetyl-CoA synthase pathway. Relative abundance values have been scaled to the most abundant MAG classified to a methane cycling guild. Solid black vertical lines denote the mean relative abundance calculated for MAGs at the whole-community level and dashed black lines denote the median relative abundance calculated for MAGs at the whole-community level. Source Data are provided as a Source Data file.

Methanogenic families occurred at low relative abundance across the landfill. Members of the Methanocorpusculaceae and Methanocullaceae had the highest relative abundance values of ~6% in newer parts of the landfill (i.e., D2, F1, and F2) whereas most other methanogen families occurred at relative abundance ~2% or lower across the landfill (Figs.  3 , S 5 ). Methanogen MAGs tended to have higher relative abundance compared to the mean and median values for the whole community in cells D2, F1, and F2 rather than cells A, B, and C, which aligns with the higher methane production observed for newer landfill cells (Figs.  1 ,  3 , and S 5 ). Higher numbers of MAGs from different methanogenic families were also recovered from cells D2, F1, and F2, compared to cells A, B, and C suggesting these parts of the landfill also support more diverse methanogenic communities (Figs.  3 , S 5 ). Cells D1 and E displayed intermediate trends with respect to relative abundance and diversity that did not align with geochemical observations, particularly for E, which shows consistently high methane production. These two cases are discussed in detail in the subsequent sections where we examine the taxa and metabolic pathways that could be contributing to methane gradients in the landfill.

Landfill cells A, B, and C contained two, three, and seven putative methanogen MAGs, respectively. These MAGs were classified to the families Methanocorpusculaceae , Methanocullaceae , Methanomethylophilaceae, Methanoregulaceae , and Methanotrichaceae (Fig.  3 and Fig. S 5 ). The relative abundance of putative methanogens was at least an order of magnitude lower than the most abundant MAGs from each site, which included members of the Sulfurimonadaceae (i.e., STA_16 at 15.81%), the Gallionellaceae (i.e. STB_49 at 10.84%), and Arcobacteraceae (i.e., STC_123 at 27.17%) as noted previously (Fig.  3 , Fig S 4 , and Supplementary Data  1 on the Open Science Framework (OSF) at https://doi.org/10.17605/OSF.IO/6X5ZC 37 ).

According to classification rules used in this study (see Methods), all putative methanogen MAGs in landfill cells A and B can be classified as acetoclastic methanogens based on the presence of the acetyl-CoA synthetase (i.e., noted as acetate => methane pt.1 by DRAM), high completion (i.e., >50%) of the carbon monoxide dehydrogenase/acetyl-CoA synthase (CODH/ACS) complex supporting acetyl-CoA dismutation, and high completion (i.e., >75%) of the hydrogenotrophic methanogenesis pathway (Fig.  3 ). The functional potential for methanogenesis from cell C shows a mix of strictly hydrogenotrophic, acetoclastic, and methylotrophic methanogens (Fig.  3 , see Methods).

When considering the metabolic analyses alongside our predictions based on geochemistry, the restricted pathways that can support methanogenesis align with observations of these habitats having limited substrates available that can support methanogenesis. The abundance of microaerophilic autotrophic guilds further supports that oxygen infiltration may be inhibiting methanogenesis in these parts of the landfill, which likely contributes to the lower diversity and abundance of methanogens observed.

Looking at the microbial community from locations D1 and D2, we see contrasting trends in the putative methanogenic community. These trends emulate what was observed at the whole-community scale and suggest cell D is not experiencing homogenous geochemistry that is impacting methanogenesis (Figs.  2 , 3 , and Fig S 5 ). The putative methanogenic community from D1 is comprised of six MAGs that include many families detected in cells A, B, and C, including the Methanotrichaceae, Methanoregulaceae , and Methanocullaceae (Fig.  3 and Fig S 5 ). An additional two MAGs from the Methanoperedenaceae were also recovered from D1 based on the detection of near complete hydrogenotrophic methanogenesis pathways (i.e., STD1_6 and STD1_19) (Fig.  3 and Supplementary Data  1 on the Open Science Framework (OSF) at https://doi.org/10.17605/OSF.IO/6X5ZC 37 ). The detection of the Methanoperedenaceae is noteworthy as they are the only named family of anaerobic methane-oxidizing Archaea (ANME) and these MAGs are discussed within the examination of methanotrophy, below. The relative abundance of putative methanogens was an order of magnitude lower compared to the most abundant MAG STD1_23, which had an abundance of 4.19% and was classified to the unnamed family UBA6257 in the phylum Patescibacteria (Supplementary Data  1 on the Open Science Framework (OSF) at https://doi.org/10.17605/OSF.IO/6X5ZC 37 ).

In contrast to location D1, 17 putative methanogen MAGs were recovered from location D2. There was considerable overlap between the families detected in D2 and cells A, B, C, and location D1, with four additional families identified at location D2 including the Methanobacteriaceae, Methanofollaceae, Methanomicrobiaceae , and Methanosarcinaceae (Figs.  3 , S 5 ). D2 was unique among landfill cells because MAG STD2_64 from the family Methanocorpusculaceae displayed the highest relative abundance of 6.66% among all MAGs at location D2 (Figs.  3 , S 4 , S 5 ). Additional MAGs from the Methanocullaceae (e.g., STD2_217 and STD2_150) and Methanosarcinaceae (e.g., STD2_68 and STD2_179) had lower relative abundance values ranging from 0.5 to 2% but were still more abundant than most other microbial taxa identified at this location (Figs.  3 , S 5 ).

The differing trends observed in cells D1 and D2 extend to the methanogenesis pathways predicted at both locations. The capacity for methanogenesis at D1 resembles that of cells A and B, with MAGs from the Methanotrichaceae, Methanoregulaceae , and Methanocullaceae all classified as acetoclastic methanogens based on the presence of genes coding for the acetyl-CoA synthetase, >50% complete CODH/ACS complexes, and >75% complete hydrogenotrophic methanogenesis pathways (Fig.  3 ). More substrates can potentially support methane production at D2. MAGs from the Methanocorpusculaceae, Methanofollaceae, and Methanomicrobiaceae were classified as strictly hydrogenotrophic methanogens (Fig.  3 ). MAGs from the Methanocullaceae and Methanoregulaceae were classified as acetoclastic methanogens and MAGs from the Methanomethylophilaceae were classified as methylotrophic methanogens. The broadest capacity for methanogenesis was observed in MAGs from the family Methanosarcinaceae (i.e., STD2_68, STD2_179, and STD2_188), which displayed the potential for hydrogenotrophic, acetoclastic, and methylotrophic methanogenesis (Fig.  3 ).

Despite initially classifying both locations in cell D as being in phase 4 of slow methanogenesis, our microbiological observations suggest biogeochemical succession is occurring in a more segregated fashion. Although location D1 houses waste that is only 2 years older than location D2, the whole community structure and methanogenic capacity observed at D1 are more in line with landfill cells that are 10 years older. This discrepancy may be occurring due to cell D’s connection to the C/D valley location where oxygen intrusion is suspected (Fig.  1B ). Alternatively, the location of the gas flaring vent associated with location D2 may not capture a representative signal of the prevailing geochemistry of this habitat.

Methanogens were the most abundant population in D2 and demonstrated broader methanogenic metabolic capabilities suggesting substrates that can support methanogenesis may be more widely available at D2 compared to D1. Concentrations of inorganic carbon were higher at D2 compared to D1 in the timeframe surrounding our sampling expedition (i.e., ~2500 to 3500 mg L −1 vs ~1000 mg L −1 ), which may be contributing to the abundance of hydrogenotrophic methanogens at D2 (Fig.  3 and Fig S 2 ). As previously noted, acetate concentrations were also an order of magnitude higher at D2 vs. D1 prior to sampling, which could also favour acetoclastic methanogens. These observations suggest that D2 is transitioning from phase 3 to phase 4 and frame D2 as a potential methane production hotspot whose contributions may be masked when examining bulk gas flaring data.

Landfill cell E was originally classified as being in phase 3 of rapid methanogenesis. The low abundance and diversity of putative methanogens in cell E is at odds with the original classification based on geochemistry. Only seven putative methanogenic MAGs were recovered from landfill cell E, from the families Methanotrichaceae , also observed in cells A, C, and location D1; the Methanofollaceae and Methanobacteriaceae also observed in D2; and the Methanospirillaceae , which was not detected anywhere else in the landfill (Figs.  3 , S 5 ). One MAG could only be classified to the Methanobacteriales order (Figs.  3 , S 5 , and Supplementary Data  1 on the Open Science Framework (OSF) at https://doi.org/10.17605/OSF.IO/6X5ZC 37 ). The relative abundance of putative methanogens was an order of magnitude lower compared to the most abundant MAG STE_65, which had an abundance of 8.77% and was classified to the family Sulfurovoraceae (Figs.  3 , S 4 , S 5 , and Supplementary Data  1 on the Open Science Framework (OSF) at https://doi.org/10.17605/OSF.IO/6X5ZC 37 ).

The methanogenic community in cell E resembles those associated with waste that is 11 to 19 years older (i.e., cells A, B, and C) despite landfill cell E displaying a similar whole community composition to D2, F1, and F2 (Figs.  2 ,  3 , S 5 ). The methanogenic capabilities potentially supported in landfill cell E were restricted to acetoclastic and hydrogenotrophic methanogenesis despite lower methane-producing areas of the landfill, such as D2, showing broader methanogenic pathways (Figs.  1 ,  3 ). The occurrence of acetoclastic and hydrogenotrophic methanogens in cell E aligns with our initial prediction that a limited number of substrates capable of supporting methane production would be available at this stage in the landfill’s lifecycle; however, the observed low abundance and diversity of methanogens was unexpected given what was observed at location D2.

From a microbiological perspective, these observations suggest cell E has reached the end of phase 3 and will soon enter phase 4 of slow methanogenesis. The revised classification of cell E is difficult to reconcile with the consistently high methane production associated with this part of the landfill. This discrepancy between the methanogenic community structure and the whole community structure in cell E is notable because it suggests that methanogenic guilds are sensitive to a changing variable in landfill cell E.

Potential explanations are threefold: First, the abundance of putative methanogens may be decoupled from their metabolic activity. However, we would expect increased rates of methanogenesis to translate into more biomass and/or genomes given that methanogenesis is energy-conserving. Second, the sharp declines in inorganic carbon that occurred just prior to sampling may have caused a decline in acetoclastic and hydrogenotrophic methanogens using inorganic carbon for methane production (Fig S 2 ). Finally, our characterization of the methanogen community from leachate at a more local scale may not align with gas data obtained for the entire landfill cell. Given that cell E is the only cell that experienced extreme fluctuations in substrates that could support methane production at the time of sampling, we’re inclined to attribute observed disparities to the availability of bicarbonate, though this mechanism needs to be formally tested in the future.

Landfill cell F was originally classified as transitioning from phase 2 of anaerobic acid production to phase 3 of rapid methanogenesis. In contrast to the samples obtained from both locations in cell D, the abundance, diversity, and community structure of putative methanogens were more consistent between both locations sampled from cell F despite their two-year age difference. 20 putative methanogen MAGs were recovered from location F1 and 17 putative methanogen MAGs were recovered from location F2 (Fig.  3 ). The families detected at landfill cell F (i.e., Methanobacteriaceae , Methanocorpusculaceae , Methanocullaceae , Methanofollaceae , Methanomethylophilaceae , Methanomicrobiaceae , Methanoregulaceae , Methanosarcinaceae , and Methanotrichaceae ) were all detected in the landfill cells discussed previously (Figs.  3 , S 5 ). There was considerable overlap in the families detected in F1 and F2 aside from location F1 harbouring MAGs from the Methanofollaceae and Methanomicrobiaceae , families not detected at F2 (Figs.  3 , S 5 ).

Putative methanogen MAGs from location F1 ranged in relative abundance from 0.05 to 3.97% whereas those from F2 displayed a slightly lower range of 0.08 to 1.33% (Figs.  3 , S 5 ). The abundance of putative methanogens at F1 was lower than the most abundant MAG at location F1, MAG STD1_175, which was classified to the family Cloacimonadaceae and had a relative abundance of 7.79% (Figs. S 3 , S 4 , S 5 , and Supplementary Data  1 on the Open Science Framework (OSF) at https://doi.org/10.17605/OSF.IO/6X5ZC 37 ). The abundance of putative methanogens at F2 was almost an order of magnitude lower compared to the most abundant MAG, MAG STF1_112, which was also classified to the family Cloacimonadaceae and had a relative abundance of 9.42% (Figs. S 3 , S 4 , S 5 , and Supplementary Data  1 on the Open Science Framework (OSF) at https://doi.org/10.17605/OSF.IO/6X5ZC 37 ).

The putative methanogenic communities from locations F1 and F2 displayed similar pathways that could support methanogenesis, with hydrogenotrophic and acetoclastic pathways represented in multiple families. All MAGs from the family Methanosarcinaceae could be classified as broad substrate methanogens possessing near complete pathways for acetoclastic and hydrogenotrophic methanogenesis alongside genes required to convert methyl-bearing substrates to methane (i.e., STF1_134, STF1_80, STF1_17, STF1_12, STF2_199, STF2_28, STF2_135) (Fig.  3 ). The predicted capacity for multiple methanogenic pathways in members of the Methanosarcinaceae in cells F and D suggest members of this lineage are generalists capable of accessing a variety of substrates to support methane production over the course of a landfill’s lifecycle. The absence of the Methanosarcinaceae in cells A, B, and C also suggests that generalists from this family are outcompeted by more specialized methanogens as MSW ages (Figs.  3 , S 5 ). Alternatively, this absence could be attributed to different acetate affinities. Members from families such as the Methanotrichaceae have a higher affinity for acetate and would have a physiological advantage in ageing landfills with µM amounts 49 , whereas the members of the Methanosarcinaceae have a growth advantage and outcompete other acetoclastic methanogens at the mM levels more likely to be available in newer landfills.

The sole MAG classified to the order Methanofastidiosales (i.e., STF1_149) carried a homolog for the mtsA gene coding a methyltransferase specific to methylthiol-bearing compounds (see Supplementary Note 1). Members of this order are inferred to carry out methanogenesis in a fastidious manner via the reduction of methylthiol and we predict the same metabolism here 50 .

We note MAGs from the Methanocullaceae family were mixed as to their classification as hydrogenotrophic or acetoclastic methanogens across multiple landfill cells based on the rules we used to classify putative methanogenic metabolisms. Physiological studies on isolates from the Methanoculleus  the only genus from the Methanocullaceae recovered from the landfill (Supplementary Data  1 on the Open Science Framework (OSF) at https://doi.org/10.17605/OSF.IO/6X5ZC 37 ), have shown that acetate is a required carbon source that does not serve as a substrate for methane production under the conditions tested 51 , 52 , 53 , 54 , 55 , 56 , 57 . Members from the Methanobacteriaceae were subject to a similarly mixed classification in our study despite previous work showing that acetate is not a methanogenic substrate (compiled in 58 ). These discrepancies highlight the limits of purely metagenomic approaches, which cannot distinguish between whether the same metabolic machinery contributes to carbon assimilation and/or energy conservation via methanogenesis 59 . Similar limitations must be considered for methanogens that carry genes for hydrogenotrophic pathways to support the disproportionation of methyl-bearing substrates used for methane production 60 , 61 . Such limitations could be resolved by combining metagenomic approaches with metatranscriptomic and isotopic approaches with labelled substrates in future studies.

The abundance and diversity of methanogens in cell F align with our original classification of this landfill cell as transitioning from phase 2 of anaerobic acid production to phase 3 of rapid methanogenesis. Despite the peaks in organic acids being considerably lower in cell F compared to older landfill cells, the presence of varied substrates may support rapid methanogenesis due to limited competition for carbon substrates among methanogens (Fig S 2 ). We posit that generalists and specialists alike have ample resources to support methanogenesis and contribute to high rates of methane production in cell F. This position is supported by the higher relative abundance of taxa that can potentially supply acetate to methanogens in these parts of the landfill, although a full characterization of potential syntrophic relationships is outside the scope of this study (see Supplementary Note 2 and Fig S 6 ).

Methanogen families occurring in landfills

To place the methanogenic taxonomic diversity found at our study site in context, we generated a compilation of presence/absence data for methanogenic taxa identified in landfills in the past 20 years (Fig.  4 ). Our study site harbours some of the most diverse communities of methanogens reported to date (i.e., 11 families detected). Only a 16S rRNA amplicon sequencing survey conducted across six distinct landfills in China showed higher diversity (i.e., 14 families detected, see Fig.  4 ), which displayed considerable overlap in the families observed at our site 20 . The remaining studies compiled, many of which also analyzed more than one landfill, detected lower taxonomic diversity regardless of the method employed (Fig.  4 ).

Where possible, all taxonomic labels have been updated to reflect the Genome Taxonomy Database (GTDB) r89 taxonomy used in our study. Abbreviations denote the following: 16S (shorthand for 16S rRNA amplicon sequencing), FISH (fluorescent in situ hybridization), RFLP (restriction fragment length polymorphism), and qPCR (quantitative polymerase chain reaction). Abbreviated references have been provided and the raw input data used to generate this figure can be found in Supplementary Data  4 on the Open Science Framework (OSF) at https://doi.org/10.17605/OSF.IO/6X5ZC 37 . Data obtained from (in chronological order): 8 , 15 , 16 , 18 , 19 , 20 , 22 , 23 , 35 , 36 , 68 , 117 , 118 , 119 , 120 , 121 , 122 . Source Data are provided as a Source Data file.

Members from the Methanosarcinaceae are the most frequently detected in landfills, occurring in 17 of the 21 studies included (Fig.  4 ). Members of the Methanosarcinaceae are widespread in terrestrial, aquatic, and animal-associated habitats due to their ability to use multiple substrates to support methanogenesis 62 , 63 . This generalist strategy likely contributes to their occurrence in landfills covering a range of ages and geographic locations, and frames members of the Methanosarcinaceae as key players in the landfill methane cycle (see Supplementary Data  2 on the Open Science Framework (OSF) at https://doi.org/10.17605/OSF.IO/6X5ZC 37 for full accounting of methanogenic lineages in landfills).

After the Methanosarcinaceae , the Methanotrichaceae (previously referred to as the Methanosaetaceae in the literature) (15/21 studies), Methanocullaceae (13/21 studies), and Methanobacteriaceae (13/21 studies) families were the next most frequently detected in landfills (Fig.  4 ). Members of the Methanotrichaceae are considered acetoclastic methanogens in line with our metabolic modeling 62 and we have already noted the potential limitations of members of the Methanocullaceae and Methanobacteriaceae as acetoclastic methanogens in the absence of physiological evidence. Regardless of which substrates support methane production, these families were repeatedly detected in newer waste but also waste that was over 20 years old, including in our data, suggesting they are important contributors to long-term methane production in landfills (Supplementary Data  3 on the Open Science Framework (OSF) at https://doi.org/10.17605/OSF.IO/6X5ZC 37 ).

The persistence of families such as the Methanotrichaceae and Methanocullaceae in older waste could be attributable to their increased tolerance to oxidative stress 64 , an important adaptation to heterogeneous landfill habitats subject to large fluctuations in redox potential. Indeed, many of the methanogen families detected in landfills fall within orders forming a distinct clade of methanogens whose genomes are enriched in oxidative stress tolerance genes (e.g., Methanocorpusculaceae , Methanofollaceae , Methanomicrobiaceae , Methanoregulaceae , Methanosarcinaceae , Methanosphaerulaceae , Methanospirillaceae ) 64 (Fig.  4 ).

Families containing more metabolically restricted methanogens were less frequently detected in landfills. Members of the Methanofollaceae and Methanocorpusculaceae , considered to be strictly hydrogenotrophic methanogens, were detected in 8 and 4 of 21 studies, respectively 65 , 66 , 67 (Fig.  4 ). Methylotrophic methanogens from the family Methanomethylophilaceae were detected in 4 of 21 studies and methanogens from the family Methanofastidiosaceae from the order Methanofastidiosales , which are inferred to use methylthiols in methane production, were only detected in one study from our group, suggesting landfill habitats are generally not conducive to supporting this specific methanogenic lifestyle (Fig.  4 ) 35 , 50 , 68 .

These observations do not preclude metabolically restricted methanogens from being important contributors to methane production in landfills. Strictly hydrogenotrophic methanogens were some of the most abundant MAGs recovered from location D2 and likely play an important role in producing methane as organic substrates are depleted. Likewise, multiple MAGs of methylotrophic methanogens from the Methanomethylophilaceae family were detected in cell F suggesting they are active contributors to methane production earlier in the landfill lifecycle when labile organic substrates are more likely to be available. We note that our categorization system did not distinguish between the H 2 -dependent methylotrophic methanogenesis pathway that oxidizes methylated compounds to methane and methylotrophic methanogens that rely on the disproportionation of methylated compounds to form methane 63 . The reported capacity for H 2 -dependent methylotrophic methanogenesis within the order Methanomassiliicoccales 69 , 70 , 71 , which contains the family Methanomethylophilaceae , highlights the importance of considering the dual contributions of methylotrophic methanogens to hydrogen and methane cycling in landfills. The contributions of methylthiol-using methanogens to the methane cycle remain poorly characterized. The detection of members of the Methanofastidiosales in two different landfill studies suggests they also contribute to methane production in MSW.

Methanotrophic community structure

Our initial survey of MAGs containing the pmoA and/or mmoX genes identified 31 MAGs as putative aerobic methanotrophs, with the addition of the 2 ANME MAGs from D1 as putative anaerobic methanotrophs. Within the aerobic methanotrophic MAGs, 15 encoded only pmoA , 5 encoded only mmoX , and 11 carried genes for both pMMO and sMMO complexes (Fig.  5 ). Almost all putative methanotroph MAGs were found in parts of the landfill where oxygen was detected or suspected to be intruding (i.e., cells A, B, C, and location D1) (Figs.  1B ,  5 ).

Shown here is the completion of high and low-affinity complex IV machinery involved in reducing oxygen alongside the presence/absence of genes involved in methane metabolism, nitrogen metabolism, and sulphur metabolism. No putative methanotroph MAGs were recovered from locations D2, F1, and F2, and as such no panels for those sampling locations are shown. Relative abundance values have been scaled to the most abundant MAG classified to a methane cycling guild. Solid black vertical lines denote the mean relative abundance calculated for MAGs at the whole-community level and dashed black lines denote the median relative abundance calculated for MAGs at the whole-community level. Source Data are provided as a Source Data file.

Putative methanotroph MAGs spanned all three phyla with known methanotrophic representatives: the Proteobacteria , Verrucomicrobiota , and Methylomirabilota (Figs.  5 , S 5 ) 72 , 73 . Of these, 25 MAGs belonged to families associated with aerobic or intra-aerobic methanotrophy, including the Methylomonadaceae (20), Methylococcaceae (2), Methylacidiphilaceae (2), and Methylomirabilaceae (1) (Figs.  5 , S 5 ). Six MAGs were recovered from lineages whose capacity for methanotrophy remains poorly characterized or untested. These MAGs were taxonomically classified within the Proteobacteria families Acetobacteraceae (i.e., STB_66 and STC_13) and Nevskiaceae (STE_114), in addition to the phyla Elusimicrobiota (STA_59) , Actinobacteriota (STB_95), and Chloroflexota (STD1_5) (Figs.  5 , S 5 ).

Methanotrophic families occurred at low relative abundance compared to the rest of the community and a slightly lower relative abundance compared to methanogens (Fig. S 5 ). Members of the Methylomonadaceae had relative abundance values between ~2-4% in cells B and D1 but were generally at ~1% or lower in the remaining landfill cells where methanotrophs were detected (i.e., A, C, and E) (Figs.  5 , S 5 ). Most other methanotroph families occurred at relative abundances between 0.1 to 1% (Fig.  5 , S 5 ). The low abundance of methanotrophs and methanogens in all locations except D2 suggests that methane cycling guilds are not dominant members in many of the landfill cells sampled. Despite the low abundance of methanotrophs, we sought to better understand the physiological adaptations they exhibit in landfill habitats where oxygen is limited, given the potential for limiting methane emissions through their activities.

In landfill cell A, four putative methanotroph MAGs were detected. Three MAGs belonged to the family Methylomonadaceae (i.e., STA_49, STA_13, and STA_76) and one belonged to the unnamed family UBA9628 from the phylum Elusimicrobiota (STA_59) (Figs.  5 , S 5 ). Methanotroph MAGs displayed low abundances (<1%) that were comparable to methanogens, suggesting methane cycling is balanced but not a dominant process in this landfill cell (Fig S 5 ).

Putative methanotroph MAGs were more abundant and diverse in landfill cell B compared to cell A, ranging in abundance from 0.12 to 2.36% with 12 MAGs recovered (Figs.  5 , S 5 ). Ten of these MAGs were classified to families with known methanotrophic activities [i.e., Methylomonadaceae (8), Methylococcaceae (1), and Methylacidiphilaceae (1)] wherein the family Methylomonadaceae was the most abundant (Figs.  5 , S 5 ) 73 . The remaining two MAGs were classified to the Acetobacteraceae from the phylum Proteobacteria (STB_66) and the family Mycobacteriaceae from the phylum Actinobacteriota (STB_95) (Figs.  5 , S 5 ). MAG STB_122 from the Methylomonadaceae was the most abundant putative methanotroph recovered with an abundance of 2.36%, which suggests they may be important contributors to methanotrophy in landfill cell B (Fig.  5 ).

The putative methanotrophic community from cell C displayed a similar pattern to cell B with respect to diversity and low relative abundance values ranging from 0.072 to 0.67% (see Figs.  5 , S 5 ). Nine putative methanotrophic MAGs were recovered from cell C. Eight of these MAGs were classified to families with known methanotrophic activities [i.e., Methylomonadaceae (6), Methylococcaceae (1), and Methylacidiphilaceae (1)] 73 and one MAG was classified to the family Acetobacteraceae (STC_13) (Figs.  5 , S 5 ). MAG STC_13 from the Acetobacteraceae had the highest relative abundance among putative methanotrophs at 0.67% but all methanotrophs had lower relative abundance compared to the mean for the whole community in cell C (Figs.  5 , S 5 ).

The detection of two Methylacidiphilaceae populations in cells B and C is of note because, outside of two sequencing studies that detected this family in a corroding sewer pipe 74 and landfill soils 36 , the Methylacidiphilaceae have been largely characterized in acidic geothermal habitats (compiled in 75 ). Phylogenomic analyses show that MAGs STB_62 and STC_89 are distinct from each other and clustered within the Methylacidimicrobium genus, which is considered to be a “mesophilic” clade within the Methylacidiphilaceae 75 , 76 , 77 , 78 (Fig S 7 ). Metabolic reconstructions identified the presence of urease genes in the two landfill Methylacidiphilaceae MAGs that were absent in other Methylacidiphilaceae genomes (full Methylacidiphilaceae annotations provided in Supplementary Data  4 on the Open Science Framework (OSF) at https://doi.org/10.17605/OSF.IO/6X5ZC 37 ). The capacity to hydrolyze urea may represent an adaptation to landfills where the hydrolysis of urea could fulfil the dual role of providing a nitrogen source and inorganic carbon to support biomass production through the Calvin-Benson-Bassham cycle, as seen in geothermal representatives of the Methylacidiphilaceae 76 , 79 (full methanotroph annotations provided in Supplementary Data  5 on the Open Science Framework (OSF) at https://doi.org/10.17605/OSF.IO/6X5ZC 37 ). Our observations add evidence challenging the view that members of the Methylacidiphilaceae are exclusively acidophiles and further support that this family exists in temperate circumneutral habitats where methane is available.

Sampling location D1 displayed a lower abundance and diversity of putative methanotroph MAGs compared to cells B and C, with three MAGs classified to the Methylomonadaceae , one classified to the unnamed family UBA5629 in the phylum Chloroflexota (STD1_5), one classified to the family Methylomirabilaceae (STD1_211), and the two ANME Methanoperedenaceae MAGs (Figs.  3 ,  5 ). MAG STD1_6 from the Methanoperedenaceae was the most abundant putative methanotroph MAG with a relative abundance of ~1% exceeding the mean and median values reported for the whole community whereas most other methanotroph MAGs were below the mean and median relative abundance (Figs.  5 , S 5 ). No methanotrophic lineages were identified in location D2.

Finally, landfill cell E harboured a single putative methanotroph MAG from the family Nevskiaceae (STE_114) (Figs.  5 , S 5 ). This MAG occurred at a low abundance of 0.84% that was similar to the mean and median relative abundance for the whole community and was identical to the most abundant putative methanogenic MAG, STE_164 from the family Methanotrichaceae (Figs.  3 ,  5 , S 5 ). To the best of our knowledge, members of the Nevskiaceae family have yet to be tested for their ability to carry out methanotrophy through the pMMO pathway. No methanotrophic lineages were identified from cell F.

Expanding the breadth of methanotrophic niches in landfills

The occurrence of the Methylomirabilaceae , the only family thought to support intra-aerobic methane oxidation, alongside the Methanoperedenaceae (Fig S 5 ), suggests landfills (here location D1) are conducive to methanotrophic lifestyles that do not rely on exogenous oxygen. Although previous work has demonstrated the anaerobic oxidation of methane (AOM) in landfill-cover soil microcosms and anoxic landfill sites, the contributions of anaerobes to methane oxidation remain understudied compared to aerobes in cover soils 80 , 81 . We identified Methanoperedenaceae and Methylomirabilaceae populations that can potentially contribute to AOM in the landfill and metabolic adaptations in putative aerobic methanotrophs that may support methane oxidation via the pMMO and sMMO pathways coupled to anaerobic metabolism.

Phylogenomic analyses of the Methanoperedenaceae showed that the two MAGs recovered from the landfill were distinct from each other, clustering with unnamed Methanoperedens species sequenced from contaminated groundwater and bioreactor enrichments (Fig S 8 ). MAG STD1_6, which had the highest relative abundance among all mcr -containing MAGs recovered from location D1 (Fig.  3 ), may represent a member of the Methanoperedenaceae with distinct adaptations to contaminated aquatic habitats that merit further investigation.

Previous work has shown that members of the Methanoperedenaceae can oxidize methane via reverse methanogenesis coupled with the reduction of metals, oxidized nitrogen, and oxidized sulphur with the help of sulphate-reducing partners 82 , 83 , 84 , 85 . The Methanoperedenaceae MAGs recovered from the landfill displayed differing redox metabolisms that could potentially be coupled to AOM. MAG STD1_6 lacked the potential to reduce oxidized forms of nitrogen and sulphur, like the unnamed species Methanoperedens sp. 902386115, which is curious given that Methanoperedens sp. 902386115 is more closely related to MAG STD1_19 (Fig S 8 and Supplementary Data  5 on the Open Science Framework (OSF) at https://doi.org/10.17605/OSF.IO/6X5ZC 37 ). MAG STD1_19 demonstrated the potential to reduce nitric oxide to nitrous oxide, a trait observed in 7 of the 13 Methanoperedenaceae genomes analyzed (Supplementary Data  5 on the Open Science Framework (OSF) at https://doi.org/10.17605/OSF.IO/6X5ZC 37 ). MAG STD1_19 lacked the genes required for other steps in denitrification, suggesting it would require a metabolic handoff to acquire nitric oxide as a metabolic substrate to support AOM (Supplementary Data  5 on the Open Science Framework (OSF) at https://doi.org/10.17605/OSF.IO/6X5ZC 37 ).

The Methylomirabilaceae MAG STD1_211 was most closely related to Methylomirabilis limnetica , the only genome for this lineage sequenced from a freshwater habitat to date (Fig S 9 ). These two genomes cluster with Methylomirabilis sp. 002634395 as a sister clade to Methylomirabilis genomes associated with metal-amended bioreactors and ditch sediments (Fig S 9 ). MAG STD1_211 encodes the capacity to reduce nitrate to nitrous oxide in line with all other Methylomirabilaceae genomes analyzed (Supplementary Data  5 on the Open Science Framework (OSF) at https://doi.org/10.17605/OSF.IO/6X5ZC 37 ). This observation supports that the Methylomirabilaceae could participate in the metabolic handoff required by the Methanoperedenaceae populations found at a similar abundance at the same location. The potential for syntrophism between the Methylomirabilaceae and Methanoperedenaceae populations is supported by previous work where these families co-occur in systems where AOM occurred in the presence of oxidized nitrogen 86 , 87 .

The potential to couple methane oxidation to the reduction of oxidized nitrogen species was not limited to MAGs from the Methanoperedenaceae and Methylomirabilaceae families. The majority of putative methanotrophic MAGs in our dataset (27/31) demonstrated the capacity to reduce nitrite to nitric oxide and a smaller proportion could reduce nitrate to nitrous oxide (8/31) (Fig.  5 ). These traits spanned multiple families (e.g., Acetobacteraceae , Methylacidiphilaceae , Methylococcaceae , Methylomirabilaceae , Methylomonadaceae , Mycobacteriaceae , and Nevskiaceae ) (Fig.  5 ). Although the methanotrophic capacity of members from the Acetobacteraceae and Nevskiaceae has yet to be experimentally confirmed, these MAGs (i.e., STB_66, STC_13, and STE_114) displayed the capacity to reduce thiosulfate as a potential electron acceptor that could be coupled to methane oxidation (Fig.  5 ). The majority of putative methanotrophic MAGs (24/31) also displayed high completion for the high affinity complex IV capable of scavenging nanomolar levels of oxygen 88 , 89 , 90 , and a similar proportion (26/31) displayed high completion for the low affinity complex IV (Fig.  5 ). These observations support that pMMO and sMMO-bearing methanotrophs in leachate have versatile redox metabolisms that can help them survive in landfill habitats separated from the atmosphere.

These adaptations could allow methanotrophs to generate energy in the absence of oxygen as a terminal electron acceptor while also allowing methanotrophs to reserve trace amounts of oxygen to support methane oxidation via the pMMO and/or sMMO pathways. Similar explanations have been put forward for observations where members of the Methylomonadaceae were abundant in anoxic aquatic habitats associated with high rates of methane oxidation separate from oxic-anoxic interfaces where aerobic methane oxidation is typically thought to occur 91 , 92 . Notably, members of the Methylomonadaceae have also been detected in studies of landfill cover soils and bioreactors inoculated with leachate subject to oxygen gradients, providing a good proxy for the range of redox conditions considered in our study 10 , 24 , 26 . These observations and the widespread detection of Methylomonadaceae in leachate frame members of this family as key players capable of limiting methane emissions over a wide range of redox potentials in landfills.

Phylogenomic analyses of families with no known capacity for methanotrophy

The detection of putative methanotrophs in the Nevskiaceae , Acetobacteraceae , which are families lacking in vivo evidence of methanotrophy, and the Mycobacteriaceae , which displayed conflicting physiological evidence surrounding the capacity for methanotrophy until very recently 93 , prompted us to examine whether the methanotrophic potential observed for these genomes was unique to the landfill-derived populations or more widespread in each lineage. Phylogenomic analyses revealed that multiple genomes spread throughout each family’s tree carried the genes coding for complete pMMO and/or sMMO complexes, suggesting the capacity for methanotrophy has been acquired on several occasions within each lineage (see Supplementary Note 3 for detailed descriptions; Figs. S 10 , S 11 , S 12 ). Many genomes also displayed near-complete sMMO complexes but consistently lacked the mmoZ gene, possibly due to the mmoZ gene being prone to divergence as seen in the genomes of known methanotrophs 94 (Figs. S 10 , S 11 , S 12 ). Outside of the Mycobacterium holsaticum genome associated with human sputum, almost all putative methanotrophs identified across the three lineages occurred in aquatic, terrestrial, and sediment habitats where methane oxidation occurs 28 , 73 .

These observations suggest that many of these lineages are potentially overlooked as methane oxidizers in these habitats. We highlight the Mycobacteriaceae as a case study in Supplementary Note 3 to place our phylogenomic analyses in the context of the recent discovery of methanotrophy in an isolate from this family, which clarifies the previous conflicting reports concerning methane oxidation in representatives of this family 93 . In the future, it will be important to take advantage of the fact that many of these strains, in the Mycobacteriaceae but also from the other lineages profiled here, exist in culture collections, providing an opportunity to validate their predicted methane oxidation capacity.

Conclusions

This study provides a historical perspective on biogeochemical succession and the resultant shifts in methane cycling guilds over decades of MSW ageing. Our findings show that geochemical monitoring captures the major processes happening in the landfill but lacks nuance from microbiological information essential to predicting methane’s fate in a landfill.

Our metagenomic analyses showed that newer landfill habitats support more diverse microbial communities compared to older landfill habitats where the dominant guilds shift from anaerobic fermentative organisms, to methanogens, to autotrophs with versatile redox metabolisms as waste ages. Methanogens displayed generally low abundance in all but one landfill cell and their community structure in ageing MSW seems to be controlled by the variety and availability of substrates that can support methane production, as well as oxygen infiltration inhibiting methanogenesis. Methanotrophs had a more restricted distribution in terms of how many landfill cells they could be detected in and fewer families with confirmed capacity for methanotrophy were detected compared to families with known methanogens. When present, methanotrophs tended to occur at slightly lower abundance than methanogens. We observed the capacity for methanotrophy across a broad range of metabolisms that likely reflect the steep redox gradients encountered in landfills. The widespread adaptations observed in central redox metabolisms suggest that methanotrophy, even via oxygen-requiring pathways, is important to consider in anoxic landfill habitats.

One of the most exciting findings that emerged from our metagenomic analyses is that pathways and microbial taxa predicted to be involved in the anaerobic oxidation of methane are more diverse than previously described. The abundance of anaerobic methane oxidizers at location D1 among methane cycling microorganisms raises important questions as to what variables result in a habitat favouring anaerobic vs aerobic pathways for methane oxidation. Identifying these variables will be crucial for developing biostimulation strategies that allow landfills to function as giant anaerobic methane-oxidizing bioreactors once methane production has dropped below sustainable bio-energy generation levels. Our work indicates that it is important to dig below cover soils, into the anoxic habitats that dominate landfills, to expand the current concept of the niches and diversity of microbial taxa that contribute to methane oxidation in MSW. Although physiological experiments are required to confirm the methane oxidation capacity in the three different families containing novel putative methanotrophs, this discovery reinforces how the unique microbial communities in landfills can help us better understand biogeochemical cycles across different habitats.

Expanding the known diversity of methane-cycling microorganisms is crucial for improving biogeochemical models that can be used to manage methane emissions in landfills. Such models could increase the effectiveness of waste diversion programs, identify substrate amendments for optimal methane production and recovery for landfills, or limit methane emissions based on waste composition for landfills with higher emission profiles. Our study advocates for emphasizing the biological dimension of landfill lifecycle models so that these tools are not only used for monitoring but also actively mitigating the negative environmental impacts of MSW degradation.

Site description

The site sampled in this study is a sanitary landfill located in the northeastern United States (anonymity by request of site management). The site is equipped with leachate collection and biogas capture systems. MSW at the site is housed in six landfill cells, referred to herein as A, B, C, D, E, and F, which had operated in succession for 39 years at the time of leachate sampling in February 2019 (please refer to Table  S1 throughout this section). A is the oldest cell (receiving waste from 1980 to 1982) and F is the youngest, receiving waste as of 2014. Landfill cells A, B, and C are closed and completely capped from receiving waste. Cells D, E, and F remain partially capped due to the implementation of a phased landfilling approach that will eventually create one contiguous landfill cell. The practice of leachate recirculation has shifted over time as MSW management strategies at the landfill have changed, such that leachate from any landfill cell could be recirculated through the parts of the landfill actively receiving waste. At the time of our sampling, leachate recirculation across the entire landfill site had stopped, which would limit the capacity of older landfill cells to affect the leachate geochemistry of newer ones receiving waste. To facilitate comparisons within such a heterogeneous system, we organized our geochemical analyses around the most active filling periods for each landfill cell.

A total of 8 samples were obtained from landfill cells as part of this campaign [referred to as A, B, C, D1, D2, E, F1, and F2]. Samples D1 and D2 denote leachate collected from two different wells associated with different parts of landfill cell D. These two samples are associated with different drainage areas in cell D that began receiving waste in 1993 and 1995, respectively. The drainage area associated with sample D1 receives leachate from cell D, but also from a valley between cells C and D where the leachate from both cells mixes and where gas is monitored via dedicated sampling ports. Samples F1 and F2 denote leachate collected from two different locations in cell F, which began receiving waste in 2014 and 2016, respectively. Cell F was actively receiving waste at the time of sampling, as were parts of cell D where the cap was removed from areas of cell D that abutted with cell F. Cell E was largely capped at the time of sampling except for the southeast face which is comprised of soil and vegetative cover. Despite these connections, distinct trends in leachate geochemistry were observed at the local scale for each landfill cell. We have used the age of MSW to ground our classification of each cell into the biogeochemical phases of a landfill lifecycle.

Leachate collection and geochemical analyses

Leachate sampling involved purging wells of standing liquid prior to using a peristaltic pump to recover 1 L of leachate in sterile Nalgene bottles. Samples were stored on ice prior to filtration through a 0.22 µm pore size sterivex filter (Millipore Sigma, Burlington, MA). Leachate filtration was performed the same day as sampling and filters were stored at −80 °C until processed for DNA.

Monitoring records for leachate geochemistry were kindly provided by site owners dating back to 1983 (i.e., 36 years of records). Additional gas flaring data associated with each landfill cell were also provided for the years 2018 and 2019 to capture historical seasonal variation in gas production over a time frame relevant to the sampling expedition. All geochemical measurements were conducted by Brickhouse Environmental consultants using a standardized methodology (not provided). Select variables, namely BOD, COD, pH, redox potential (ORP), the concentrations of organic acids (i.e., acetic acid, butyric acid, isobutyric acid, propionic acid, and valeric acid), bicarbonate (i.e., a proxy for dissolved inorganic carbon), volume of gas flared, and the composition of the gas flared were used to classify each landfill cell to a specific phase (i.e., phase 1 to 5) in the landfill conceptual model.

DNA extraction, metagenomic sequencing, and genome assembly

DNA was extracted from biomass on filters using the PowerSoil DNA Isolation Kit (Qiagen) using the manufacturer’s protocol with the exception that diced filters were added to the bead tube in place of soil. Extracted DNA was evaluated for quality using the NanoDrop 1000 (Thermo Scientific, Waltham, MA) and quantified using the Qubit fluorometric method (Thermo Scientific, Waltham, MA) following the manufacturer’s protocol.

Extracted DNA for all samples was sent to The Center for Applied Genomics (Toronto, Canada) for shotgun metagenome sequencing using an Illumina HiSeq platform with paired 2 × 150 bp reads (Illumina, San Diego, CA). Metagenomic reads were quality trimmed using bbduk in the BBTools suite ( https://sourceforge.net/projects/bbmap/ ) and Sickle v1.33 95 . Post-QC, total sequencing ranged from 22.9 (cell E) to 35.1 Gbp (cell F1) (Table  S2 ). Reads were subsequently assembled into scaffolds using SPAdes3 v.3.15.5 96 using -meta and kmers set to 33,55,77,99, and 127. Only scaffolds greater than or equal to 2.5 kbp in length were further analyzed. Metagenomic reads were mapped separately to each curated scaffold assembly using Bowtie2 v2.3.4.1 97 .

Scaffolds from a single metagenome were binned using three binning algorithms: CONCOCT v0.4.0, MaxBin2 v2.2.6, and MetaBAT2 v2.12.1 98 , 99 , 100 . The resulting bins were dereplicated for each landfill leachate sample and scored in a consensus-based manner using DAS Tool v1.1.1 101 . To assess bin quality, DAS Tool-processed bins were used as input in CheckM v1.0.13 102 , which yielded 1,881 metagenome-assembled-genomes (MAGs) with >70% completion and <10% contamination retained for further analyses [full completion/contamination statistics for MAGs presented in Supplementary Data  6 on the Open Science Framework (OSF) at https://doi.org/10.17605/OSF.IO/6X5ZC 37 ]. The retained MAGs captured between 6.7 and 18.7 Gbp of post-QC sequence data (Table  S2 ).

Mean coverage for a MAG was used as the basis for relative abundance calculations to compare microbial communities across the landfill. Mean coverage was calculated by taking the mean coverage values reported for unique scaffold identifiers within a given genome bin. The distribution of the mean coverage values obtained for each MAG is summarized in Fig S 13 and the individual mean coverage and relative abundance associated with each MAG can be found in Supplementary Data  1 on the Open Science Framework (OSF) at https://doi.org/10.17605/OSF.IO/6X5ZC 37 . These mean coverage values were subsequently summed together for each site to provide the denominator that would be used to calculate relative abundance. Relative abundance calculations for individual MAGs were calculated by dividing the mean coverage of an individual MAG by the summed mean coverage of the associated sampling site. Relative abundance at the phylum and family levels was calculated by summing the mean coverage for all MAGs classified at a given taxonomic level. Values were converted to percentages by multiplying by 100.

Genome taxonomy, annotation, and metabolic summaries

Taxonomy was assigned to MAGs using the Genome Taxonomy Database Toolkit application (GTDB-tk) r89 available on DOE-KBase 103 . MAGs were annotated using the Distilled and Refined Annotation of Metabolism (DRAM) tool v1.0 with default parameters 104 but omitting the use of the KEGG and UniRef90 databases for initial annotation of all 1,881 MAGs. In specific cases where <20 genomes from a specific lineage needed to be characterized in additional detail, the UniRef90 database was applied to test whether it improved annotations for key pathways (see Supplementary Data  4 , 5 , and 6 on the Open Science Framework (OSF) at https://doi.org/10.17605/OSF.IO/6X5ZC 37 ). DRAM generates an annotation file that was used alongside the product file and taxonomy data to identify putative methanogens and methanotrophs through additional data manipulation in R v4.2.2 (see Supplementary Data  1 and 7 on the Open Science Framework (OSF) at https://doi.org/10.17605/OSF.IO/6X5ZC 37 , associated R code used to produce all figures can be found at https://github.com/carleton-envbiotech/Methane_metagenomics 105 ).

Overview of microbial community

Relative abundance values calculated at the phylum and family level were used to conduct beta diversity analyses and summarize major differences in the most abundant taxa relative to the methane cycling guilds across the landfill. Non-metric multidimensional scaling (NMDS) analysis using the Bray-Curtis dissimilarity matrix was used to assess beta diversity using relative abundance at the family level. NMDS analysis was carried out using the ‘vegan’ v2.6-4 package in R v4.2.2 and subsequently plotted alongside the total numbers of MAGs recovered from each sample to give a sense of alpha diversity using ‘ggplot2’ v3.4.2. Relative abundance heatmaps were also generated at the phylum and family level with 0.1 and 5 % cutoff values. All R code used to produce data visualizations can be found at: https://github.com/carleton-envbiotech/Methane_metagenomics 105 and Supplementary Data  1 can be found on the Open Science Framework (OSF) at https://doi.org/10.17605/OSF.IO/6X5ZC 37 .

Methane cycling microbial community analyses

DRAM’s product file and GTDB taxonomic classifications were used to identify putative methanogen MAGs by verifying whether MAGs possessed the mcrA gene or a 75 % complete pathway for hydrogenotrophic methanogenesis (equivalent to 6/8 steps being present in the “Methanogenesis, CO 2 => methane” pathway output by DRAM) [Supplementary Data  1 on the Open Science Framework (OSF) at https://doi.org/10.17605/OSF.IO/6X5ZC 37 ]. MAGs classified to methanogenic lineages but lacking the mcrA gene had their annotations verified manually for other genes from the mcr operon prior to further analyses [Supplementary Data  7 on the Open Science Framework (OSF) at https://doi.org/10.17605/OSF.IO/6X5ZC 37 ]. MAGs that had high completion for the hydrogenotrophic methanogenesis pathway that completely lacked mcr genes are discussed separately in Supplementary Note 4. We used the definitions and mechanisms summarized in an authoritative review on methanogens to develop additional rules to classify putative methanogen MAGs as being strictly hydrogenotrophic, acetoclastic, or methylotrophic [Ref. 63 and references therein].

Strictly hydrogenotrophic methanogens can only produce methane by reducing carbon dioxide using hydrogen as an electron donor. MAGs identified as strictly hydrogenotrophic methanogens must have the mcrA gene and/or >75% completion of the hydrogenotrophic methanogenesis pathway. MAGs that lacked the mcrA gene but displayed high completion for the hydrogenotrophic pathway were further investigated to verify they were taxonomically classified to lineages with known methanogens and whether additional genes from the mcr operon were present. MAGs were included in analyses if they harboured any of the mcrBCDG genes found in the mcr operon. MAGs classified as strictly hydrogenotrophic methanogens also needed to lack the carbon monoxide dehydrogenase/acetyl-CoA synthase complex (CODH/ACS), denoted as “Acetyl-CoA pathway, CO 2 => Acetyl-CoA” in DRAM’s output. The completion of this pathway is determined based on the presence of genes catalyzing reversible redox transformations between carbon monoxide and carbon dioxide, and methyl group transfers between the coenzyme M precursor tetrahydromethanopterin (H 4 MPT) and acetyl-CoA 106 , 107 . This enzyme complex is a hallmark of acetoclastic methanogenesis but is also thought to support autotrophic carbon fixation in archaea bearing near complete hydrogenotrophic methanogenesis pathways that lack the mcr operon 107 .

Acetoclastic methanogens convert acetate to acetyl-CoA, which subsequently undergoes dismutation to produce carbon dioxide and a methyl group. The carbon dioxide can be further converted to methane using the hydrogenotrophic pathway whereas the methyl group supplied from acetyl-CoA goes towards forming the precursor to coenzyme M, H 4 MPT-CH 3 . MAGs identified as putative acetoclastic methanogens needed to have the mcrA gene and/or genes coding for enzymes capable of converting acetate to acetyl-CoA. The potential to convert acetate to acetyl-CoA was evaluated based on the presence of genes coding for the acetyl-CoA synthetase alone (labelled as “Acetate pt 1” in DRAM’s output), or the acetate kinase and acetyltransferase together (labelled as “Acetate pt 2 and 3”, respectively). MAGs identified as putative acetoclastic methanogens also required a > 50% complete CODH/ACS pathway. Given that CODH can further oxidize carbon monoxide to carbon dioxide, MAGs identified as acetoclastic methanogens also required >75% completion for the hydrogenotrophic methanogenesis pathway. The annotation of MAGs displaying high completion of the hydrogenotrophic pathway alongside biomarker genes to convert acetate to acetyl-CoA but lacking the mcrA gene were examined to determine whether other genes in the mcr operon were present as a condition to being included in the dataset.

Methylotrophic methanogens can produce methane using methylated compounds. Our categorization in this instance does not distinguish between the H 2 -dependent methylotrophic methanogens that oxidize methylated compounds to methane and methylotrophic methanogens that rely on the disproportionation of methylated compounds to form methane. This is to facilitate metabolic data interpretation. MAGs identified as putative methylotrophic methanogens needed to have the mcrA gene present alongside biomarker genes associated with the methyltransferase enzymes specific to methanol, trimethylamine, dimethylamine, and/or methylamine output by DRAM. DRAM does not output the presence of methylthiol transferases in the product file by default. In cases where methylthiol transferases were suspected as a potential pathway to support methanogenesis, the presence/absence of the mtsA and mtaA genes was manually verified in the annotation file for select genomes 50 . MAGs identified as methylotrophic methanogens were required to lack the CODH/ACS complex and display low completion (<50%) of the hydrogenotrophic methanogenesis pathway so that only methyl-bearing substrates could potentially support methane production.

We also included a category of broad substrate methanogenesis. This category encompasses MAGs bearing the mcrA gene and the potential to access an array of substrates including inorganic carbon, acetate, methanol, and amine-bearing molecules alongside a > 75% complete hydrogenotrophic pathway to produce methane.

MAGs for putative aerobic methanotrophs were identified based on the presence of the pmoA and/or mmoX genes coding for key subunits in the pMMO and sMMO enzyme complexes in DRAM’s product file [see Supplementary Data  1 on the Open Science Framework (OSF) at https://doi.org/10.17605/OSF.IO/6X5ZC 37 ]. MAGs taxonomically assigned to ANME were manually identified and reclassified as predicted methanotrophs. In cases where putative methanotrophs were taxonomically classified to families with no previous record of methanotrophy, annotations were manually verified to ensure multiple pmo and mmo genes occurred on scaffolds with minimum lengths of ~3000 bp prior to subsequent analyses [see Supplementary Data  7 on the Open Science Framework (OSF) at https://doi.org/10.17605/OSF.IO/6X5ZC 37 ].

Compilation of presence/absence data for methanogenic taxa from landfill studies

To compare the occurrence of methanogenic and methanotrophic taxa in this study to previous research, a meta-analysis was conducted for a select number of studies examining landfill microbial communities. The main criterion for inclusion was that these studies examined microbial communities in situ in landfills. Studies that sampled landfills to inoculate enrichment cultures were also considered but data was only collected if the original environmental sample was sequenced, and only that original environmental sample was used in the meta-analysis. Exceptions were made for temporal studies that did not apply selective forces to enrich for specific microbial guilds, but monitored the succession of microbial community associated with solid waste or leachate under conditions that support waste degradation in situ 15 , 16 , 18 .

Presence/absence was determined by first examining the data presented in figures and tables in the published versions of articles. In specific cases where articles cited accessible supporting information, these data were also incorporated into the analyses. A liberal approach was taken for determining presence/absence. Specific taxa reported in the articles were recorded as being present. For amplicon sequencing surveys, which comprised the bulk of the data compiled, any relative abundance >0% for a given taxa was deemed sufficient to indicate that this taxon was present. For studies that used patterns in restriction fragment length polymorphism or closest relative matches to identify the taxa present, the name of the closest relative was recorded to indicate a taxon was present. For metagenomic studies, the taxa names associated with metagenome-assembled-genomes or biomarker genes used to assess abundance were recorded as those taxa being present. In instances where specific microarrays or fluorescent in situ hybridization were employed, the species names reported by the authors in the articles were taken as evidence of those taxa being present.

From all compiled data, the deepest level of taxonomic classification presented was recorded [see Supplementary Data  2 on the Open Science Framework (OSF) at https://doi.org/10.17605/OSF.IO/6X5ZC 37 ]. Given that our study focussed on comparing microbial communities at the family level, studies that did not provide taxonomic classification to the family-level or deeper were discarded from further analyses. Our study used GTDB release 89 as the database for taxonomic classification 103 whereas the data compiled from the literature relied on a variety of databases for 16S rRNA genes over several years (e.g., Greengenes, SILVA, NCBI) 108 , 109 , 110 . To ensure consistent naming between the taxa compiled from the literature and our study, species or genus names compiled from the literature were manually searched in GTDB and the GTDB name was compared to the NCBI name for searches that provided hits. The naming history of the taxon was also manually verified, such that a list of rules was developed to link older species, genera, and family names to the naming convention for families in GTDB release 89 (e.g., a name commonly reported in the literature was the family Methanosaetaceae , which is now Methanotrichaceae in GTDB). Conversions identifying the current family naming convention based on species, genera, and family names originally reported have all been reported in the R code that was used to visualize this data with comments linking the first occurrence of this name to a specific GTDB release (available under the directory “Methanogen_metaanalyses” via https://github.com/carleton-envbiotech/Methane_metagenomics 105 ).

Acetate cycling community analyses

Working from DRAM’s product file, we developed four potential categories to capture a broad range of potential pathways for acetate production 111 . Category (i) included MAGs with minimum 6/7 steps for the Wood-Ljungdahl (WL) pathway (equivalent to >85% completion) and the genes coding for the phosphotransacetylase (SCFA and alcohol conversions: acetate pt. 1) and acetate kinase (SCFA and alcohol conversions: acetate pt. 2). This classification was designed to capture the methyl branch of the WL pathway. Category (ii) included MAGs with 2/2 steps for the carbon monoxide dehydrogenase/Acetyl-CoA synthase (CODH/ACS) and genes coding for the phosphotransacetylase and acetate kinase. This classification was designed to capture the carbonyl branch of the WL pathway. Category (iii) included MAGs possessing 6/7 steps of the WL pathway but lacking phosphotransacetylase and acetate kinase in the initial annotations. This classification was designed to flag potential MAGs that required further investigation into their acetogenic potential. Category (iv) included MAGs with genes coding for phosphotransacetylase and acetate kinase. This is a broad definition designed to capture MAGs that can produce acetate from acetyl-CoA without the proton-reducing steps associated with the WL and CODH/ACS pathways.

Phylogenomic analyses

All phylogenomic analyses were conducted with GToTree v1.5.38 112 , which references the GTDB release 202 taxonomic identifiers 103 , 113 when retrieving publicly available genomes. GToTree was used to collect representative genomes within a lineage of interest and related lineages to build outgroups.

To visualize the distribution of methane oxidation marker genes, Pfam identifiers for the pMMO and sMMO pathways were supplied to GToTree. The metadata file output by GToTree with pmo and mmo gene counts was subsequently used to establish strict criteria for identifying genomes as encoding the pMMO, sMMO, or pMMO and sMMO pathways.

Categories were overlaid onto phylogenetic trees in R v4.1.2 using the packages ‘ggtree’ v3.0.4 114 , 115 and ‘treeio’ v1.16.2 116 . Isolation sources of genomes were manually retrieved using the NCBI biosample number associated with each genome and overlaid onto trees when pertinent. Accession numbers from GToTree were supplied to the ‘bit’ v1.8.53 package to download genomes, which were included as input for metabolic models produced using DRAM. Examples of R notebooks containing the code used to analyze each lineage of interest are provided alongside the input data required to reproduce these analyses at https://github.com/carleton-envbiotech/Methane_metagenomics 105 .

Reporting summary

Further information on research design is available in the  Nature Portfolio Reporting Summary linked to this article.

Data availability

All data necessary to interpret, verify, and extend the research presented in this article are publicly available. The sequencing data generated in this study have been deposited to NCBI under BioProject PRJNA900590 . Within this BioProject, the raw reads files are available on the SRA database, under Biosamples SAMN31696084 – SAMN31696092. The 1,892 MAGs have been deposited to the WGS database under accessions SAMN32731718 – SAMN32731810 (STA), SAMN32731811 – SAMN32731998 (STB), SAMN32733587 – SAMN32733720 (STC), SAMN32734194 – SAMN32734413 (STD1), SAMN32734415 – SAMN32734683 (STD2), SAMN32734737 – SAMN32734946 (STE), SAMN32737191 – SAMN32737484 (STF1), SAMN32737485 – SAMN32737723 (STF2). The geochemical monitoring raw data generated in this study are provided in the Source Data file hosted on the Open Science Framework under https://doi.org/10.17605/OSF.IO/6X5ZC 37 – provider identification is held anonymous at the request of the landfill site engineers. The processed annotation data are provided in the Supplementary Data Files 1-7 which are hosted on the Open Science Framework under https://doi.org/10.17605/OSF.IO/6X5ZC 37 .  Source data are provided with this paper.

Code availability

The input DRAM annotation and product data and accompanying bash and R code used for the analyses in this manuscript has been provided as Supplementary Data for download via https://github.com/carleton-envbiotech/Methane_metagenomics 105 .

Saunois, M. et al. The global methane budget 2000–2017. Earth Syst. Sci. Data 12 , 1561–1623 (2020).

Article   ADS   Google Scholar  

Rosentreter, J. A. et al. Half of global methane emissions come from highly variable aquatic ecosystem sources. Nat. Geosci. 14 , 225–230 (2021).

Article   ADS   CAS   Google Scholar  

The World Bank. World Bank national accounts data and OECD National Accounts data files . https://data.worldbank.org/indicator/NY.GDP.PCAP.CD?locations=XD-XM-XP&most_recent_value_desc=true (2023).

U. S. EPA. ES-2 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2014 . https://www.epa.gov/sites/default/files/2017-04/documents/us-ghg-inventory-2016-chapter-executive-summary.pdf (2016).

Kaza, S., Yao, L., Bhada-Tata, P. & Van Woerden, F. What a Waste 2.0: A Global Snapshot of Solid Waste Management to 2050 . https://datatopics.worldbank.org/what-a-waste/trends_in_solid_waste_management.html#:~:text=Globally%2C (2018).

Kjeldsen, P. et al. Present and long-term composition of MSW landfill leachate: a review. Crit. Rev. Environ. Sci. Technol. 32 , 297–336 (2002).

Article   CAS   Google Scholar  

Pohland, F. G. & Harper, S. R. Critical review and summary of leachate and gas production from landfills . (1985).

Stamps, B. W. et al. Municipal solid waste landfills harbor distinct microbiomes. Front. Microbiol. 7 , 534 (2016).

Article   PubMed   PubMed Central   Google Scholar  

Zhang, W. et al. Bacterial community composition and abundance in leachate of semi-aerobic and anaerobic landfills. J. Environ. Sci. 23 , 1770–1777 (2011).

Lin, B., Monreal, C. M., Tambong, J. T., Miguez, C. B. & Carrasco-Medina, L. Phylogenetic analysis of methanotrophic communities in cover soils of a landfill in Ontario. Can. J. Microbiol. 55 , 1103–1112 (2009).

Article   CAS   PubMed   Google Scholar  

Chukwuma, O. B., Rafatullah, M., Tajarudin, H. A. & Ismail, N. Bacterial diversity and community structure of a municipal solid waste landfill: A source of lignocellulolytic potential. LIFE-BASEL 11 , 493 (2021).

Article   ADS   CAS   PubMed   PubMed Central   Google Scholar  

Thakur, K. et al. Bioprospecting potential of microbial communities in solid waste landfills for novel enzymes through metagenomic approach. World J. Microbiol. Biotechnol. 36 , 34 (2020).

Tas, N., Brandt, B. W., Braster, M., van Breukelen, B. M. & Roling, W. F. M. Subsurface landfill leachate contamination affects microbial metabolic potential and gene expression in the Banisveld aquifer. FEMS Microbiol. Ecol. 94 , 156 (2018).

Article   Google Scholar  

Sekhohola‐Dlamini, L., Selvarajan, R., Ogola, H. J. O. & Tekere, M. Community diversity metrics, interactions, and metabolic functions of bacteria associated with municipal solid waste landfills at different maturation stages. Microbiologyopen 10 , e1118 (2021).

Article   PubMed   Google Scholar  

Staley, B. F., De Los Reyes, F. L., Wang, L. & Barlaz, M. A. Microbial ecological succession during municipal solid waste decomposition. Appl. Microbiol. Biotechnol. 102 , 5731–5740 (2018).

Bareither, C. A., Wolfe, G. L., Mcmahon, K. D. & Benson, C. H. Microbial diversity and dynamics during methane production from municipal solid waste. Waste Manag. 33 , 1982–1992 (2013).

Yang, S., Li, L., Peng, X. & Song, L. Leachate microbiome profile reveals bacteria, archaea and eukaryote dynamics and methanogenic function during solid waste decomposition. Bioresour. Technol. 320 , 124359 (2021).

Fei, X., Zekkos, D. & Raskin, L. Archaeal community structure in leachate and solid waste is correlated to methane generation and volume reduction during biodegradation of municipal solid waste. Waste Manag. 36 , 184–190 (2015).

Huang, L. N. et al. Characterization of methanogenic Archaea in the leachate of a closed municipal solid waste landfill. FEMS Microbiol. Ecol. 46 , 171–177 (2003).

Song, L., Wang, Y., Tang, W. & Lei, Y. Archaeal community diversity in municipal waste landfill sites. Appl. Microbiol. Biotechnol. 99 , 6125–6137 (2015).

Ermler, U., Grabarse, W., Shima, S., Goubeaud, M. & Thauer, R. K. Crystal structure of methyl-coenzyme M reductase: The key enzyme of biological methane formation. Science 278 , 1457–1462 (1997).

Article   ADS   CAS   PubMed   Google Scholar  

Luton, P. E., Wayne, J. M., Sharp, R. J. & Riley, P. W. The mcrA gene as an alternative to 16S rRNA in the phylogenetic analysis of methanogen populations in landfill. Microbiology 148 , 3521–3530 (2002).

Tang, W., Wang, Y., Lei, Y. & Song, L. Methanogen communities in a municipal landfill complex in China. FEMS Microbiol. Lett. 363 , fnw075 (2016).

Henneberger, R., Lüke, C., Mosberger, L. & Schroth, M. H. Structure and function of methanotrophic communities in a landfill-cover soil. FEMS Microbiol. Ecol. 81 , 52–65 (2012).

Mei, J., Wang, L., Han, D. & Zhao, Y. Methanotrophic community structure of aged refuse and its capability for methane bio-oxidation. J. Environ. Sci. 23 , 868–874 (2011).

Chen, Y., Dumont, M. G., Cebron, A. & Murrell, J. C. Identification of active methanotrophs in a landfill cover soil through detection of expression of 16S rRNA and functional genes. Environ. Microbiol. 9 , 2855–2869 (2007).

Hanson, R. S. & Hanson, T. E. Methanotrophic bacteria. Microbiol. Rev. 60 , 439–471 (1996).

Article   CAS   PubMed   PubMed Central   Google Scholar  

Knief, C. Diversity and habitat preferences of cultivated and uncultivated aerobic methanotrophic bacteria evaluated based on pmoA as molecular marker. Front. Microbiol. 6 , 1346 (2015).

Co, R. & Hug, L. A. Prediction, enrichment and isolation identify a responsive, competitive community of cellulolytic microorganisms from a municipal landfill. FEMS Microbiol. Ecol. 97 , fiab065 (2021).

Ransom-Jones, E., McCarthy, A. J., Haldenby, S., Doonan, J. & McDonald, J. E. Lignocellulose-degrading microbial communities in landfill sites represent a repository of unexplored biomass-degrading diversity. mSphere 2 , e00300–17 (2017).

Gaytan, I. et al. Degradation of recalcitrant polyurethane and xenobiotic additives by a selected landfill microbial community and its biodegradative potential revealed by proximity ligation-based metagenomic analysis. Front. Microbiol. 10 , 2986 (2020).

Collins-Fairclough, A. M., Co, R., Ellis, M. C. & Hug, L. A. Widespread antibiotic, biocide, and metal resistance in microbial communities inhabiting a municipal waste environment and anthropogenically impacted river. mSphere 3 , e00346–18 (2018).

Wan, S. et al. Metagenomics analysis reveals the microbial communities, antimicrobial resistance gene diversity and potential pathogen transmission risk of two different landfills in China. DIVERSITY-BASEL 13 , 230 (2021).

Sharon, I. & Banfield, J. F. Genomes from metagenomics. Science 342 , 1057–1058 (2013).

Sauk, A. H. & Hug, L. A. Substrate-restricted methanogenesis and limited volatile organic compound degradation in highly diverse and heterogeneous municipal landfill microbial communities. ISME Commun. 2 , 58 (2022).

Singh, A. K. et al. Mining the landfill soil metagenome for denitrifying methanotrophic taxa and validation of methane oxidation in microcosm. Environ. Res. 215 , 114199 (2022).

Hug, L. A. Grégoire_Decadal_methane_cycling_landfills. Open Science Framework https://osf.io/6x5zc/ (2023) https://doi.org/10.17605/OSF.IO/6X5ZC .

Hallbeck, L. & Pedersen, K. The Family Gallionellaceae. in The Prokaryotes 853–858 (Springer Berlin Heidelberg, 2014). https://doi.org/10.1007/978-3-642-30197-1_398 .

Huang, Y.-M. et al. A novel enrichment culture highlights core features of microbial networks contributing to autotrophic Fe(II) oxidation coupled to nitrate reduction. Microb. Physiol. 31 , 280–295 (2021).

Takai, K. et al. Sulfurimonas paralvinellae sp. nov., a novel mesophilic, hydrogen- and sulfur-oxidizing chemolithoautotroph within the Epsilonproteobacteria isolated from a deep-sea hydrothermal vent polychaete nest, reclassification of Thiomicrospira denitrificans as Sulfurimonas denitrificans comb. nov. and emended description of the genus Sulfurimonas . Int. J. Syst. Evol. Microbiol. 56 , 1725–1733 (2006).

Han, Y. & Perner, M. The globally widespread genus Sulfurimonas : Versatile energy metabolisms and adaptations to redox clines. Front. Microbiol. 6 , 989 (2015).

Ferreira, S., Queiroz, J. A., Oleastro, M. & Domingues, F. C. Insights in the pathogenesis and resistance of Arcobacter : A review. Crit. Rev. Microbiol. 42 , 364–383 (2015).

PubMed   Google Scholar  

Chuan, J. et al. Comparative genomics analysis and virulence-related factors in novel Aliarcobacter faecis and Aliarcobacter lanthieri species identified as potential opportunistic pathogens. BMC Genom. 23 , 471 (2022).

Cervenka, L. Survival and inactivation of Arcobacter spp., a current status and future prospect. Crit. Rev. Microbiol. 33 , 101–108 (2007).

Johnson, L. A. & Hug, L. A. Cloacimonadota metabolisms include adaptations in engineered environments that are reflected in the evolutionary history of the phylum. Environ. Microbiol. Rep. 14 , 520–529 (2022).

Feng, G., Zeng, Y., Wang, H. Z., Chen, Y. T. & Tang, Y. Q. Proteiniphilum and Methanothrix harundinacea became dominant acetate utilizers in a methanogenic reactor operated under strong ammonia stress. Front. Microbiol. 13 , 1098814 (2023).

Hahnke, S., Langer, T., Koeck, D. E. & Klocke, M. Description of Proteiniphilum saccharofermentans sp. nov., Petrimonas mucosa sp. nov. and Fermentimonas caenicola gen. nov., sp. nov., isolated from mesophilic laboratory-scale biogas reactors, and emended description of the genus Proteiniphilum . Int. J. Syst. Evol. Microbiol. 66 , 1466–1475 (2016).

Owusu-Agyeman, I., Plaza, E. & Cetecioglu, Z. Long-term alkaline volatile fatty acids production from waste streams: Impact of pH and dominance of Dysgonomonadaceae . Bioresour. Technol. 346 , 126621 (2022).

Jetten, M. S. M., Stams, A. J. M. & Zehnder, A. J. B. Acetate threshold values and acetate activating enzymes in methanogenic bacteria. FEMS Microbiol. Ecol. 6 , 339–344 (1990).

Nobu, M. K., Narihiro, T., Kuroda, K., Mei, R. & Liu, W. T. Chasing the elusive Euryarchaeota class WSA2: Genomes reveal a uniquely fastidious methyl-reducing methanogen. ISME J. 10 , 2478–2487 (2016).

Maus, I. et al. Complete genome sequence of the hydrogenotrophic, methanogenic archaeon Methanoculleus bourgensis Strain MS2 T , isolated from a sewage sludge digester. J. Bacteriol. 194 , 5487–5488 (2012).

Maus, I. et al. Insights into the annotated genome sequence of Methanoculleus bourgensis MS2 T , related to dominant methanogens in biogas-producing plants. J. Biotechnol. 201 , 43–53 (2015).

Ollivier, B. M., Mah, R. A., Garcia, J. L. & Boone, D. R. Isolation and characterization of Methanogenium bourgense sp. nov. Int. J. Syst. Evol. Microbiol. 36 , 297–301 (1986).

CAS   Google Scholar  

Dianou, D. et al. Methanoculleus chikugoensis sp nov., a novel methanogenic archaeon isolated from paddy field soil in Japan, and DNA-DNA hybridization among Methanoculleus species. Int. J. Syst. Evol. Microbiol. 51 , 1663–1669 (2001).

Barret, M. et al. Phylogenetic identification of methanogens assimilating acetate-derived carbon in dairy and swine manures. Syst. Appl. Microbiol. 38 , 56–66 (2015).

Chen, S. C. et al. Comparative genomic analyses reveal trehalose synthase genes as the signature in genus Methanoculleus . Mar. Genom. 47 , 100673 (2019).

Weng, C.Y. et al. Methanoculleus taiwanensis sp nov., a methanogen isolated from deep marine sediment at the deformation front area near Taiwan. Int. J. Syst. Evol. Microbiol. 65 , 1044–1049 (2015).

Oren, A. The Family Methanobacteriaceae in The Prokaryotes 165–193 (Springer Berlin Heidelberg, 2014). https://doi.org/10.1007/978-3-642-38954-2_411 .

Maialen, B. et al. Identification of Methanoculleus spp. as active methanogens during anoxic incubations of swine manure storage tank samples. Appl. Environ. Microbiol. 79 , 424–433 (2013).

Meuer, J. et al. Genetic analysis of the archaeon Methanosarcina barkeri Fusaro reveals a central role for Ech hydrogenase and ferredoxin in methanogenesis and carbon fixation. Proc. Natl Acad. Sci. USA. 99 , 5632–5637 (2002).

Welander, P. V., Metcalf, W. W., Welander, P. V. & Metcalf, W. W. Mutagenesis of the C1 oxidation pathway in Methanosarcina barkeri : new insights into the Mtr/Mer bypass pathway. J. Bacteriol. 190 , 1928–1936 (2008).

Oren, A. The family Methanotrichaceae in The Prokaryotes 297–306 (Springer Berlin Heidelberg, 2014). https://doi.org/10.1007/978-3-642-38954-2_277 .

Evans, P. N. et al. An evolving view of methane metabolism in the Archaea. Nat. Rev. Microbiol. 17 , 219–232 (2019).

Lyu, Z. & Lu, Y. Metabolic shift at the class level sheds light on adaptation of methanogens to oxidative environments. ISME J. 12 , 411–423 (2018).

Oren, A. The Family Methanocorpusculaceae in The Prokaryotes 225–230 (Springer Berlin Heidelberg, 2014). https://doi.org/10.1007/978-3-642-38954-2_314 .

Imachi, H., Sakai, S., Nagai, H., Yamaguchi, T. & Takai, K. Methanofollis ethanolicus sp. nov., an ethanol-utilizing methanogen isolated from a lotus field. Int. J. Syst. Evol. Microbiol. 59 , 800–805 (2009).

Lai, M. C. & Chen, S. C. Methanofollis aquaemaris sp. nov., a methanogen isolated from an aquaculture fish pond. Int. J. Syst. Evol. Microbiol. 51 , 1873–1880 (2001).

Yadav, S., Kundu, S., Ghosh, S. K. & Maitra, S. S. Molecular analysis of methanogen richness in landfill and marshland targeting 16S rDNA sequences. Archaea 2015 , 1–9 (2015).

Lang, K. et al. New mode of energy metabolism in the seventh Order of methanogens as revealed by comparative genome analysis of “ Candidatus Methanoplasma termitum”. Appl. Environ. Microbiol. 81 , 1338–1352 (2015).

Article   ADS   PubMed   PubMed Central   Google Scholar  

Borrel, G. et al. Comparative genomics highlights the unique biology of Methanomassiliicoccales , a Thermoplasmatales -related seventh order of methanogenic archaea that encodes pyrrolysine. BMC Genom. 15 , 679 (2014).

Lomans, B. P. et al. Isolation and characterization of Methanomethylovorans hollandica gen. nov., sp. nov., isolated from freshwater sediment, a methylotrophic methanogen able to grow on dimethyl sulfide and methanethiol. Appl. Environ. Microbiol. 65 , 3641–3650 (1999).

Smith, G. J. & Wrighton, K. C. Metagenomic approaches unearth methanotroph phylogenetic and metabolic diversity. Curr. Issues Mol. Biol . 33 , 57–84 (2019).

Dedysh, S. N. & Knief, C. Diversity and phylogeny of described aerobic methanotrophs. in Methane Biocatalysis: Paving the Way to Sustainability 17–42 (Springer International Publishing, 2018). https://doi.org/10.1007/978-3-319-74866-5_2 .

Pagaling, E., Yang, K. & Yan, T. Pyrosequencing reveals correlations between extremely acidophilic bacterial communities with hydrogen sulphide concentrations, pH and inert polymer coatings at concrete sewer crown surfaces. J. Appl. Microbiol. 117 , 50–64 (2014).

Schmitz, R. A. et al. Verrucomicrobial methanotrophs: Ecophysiology of metabolically versatile acidophiles. FEMS Microbiol. Rev. 45 , fuab007 (2021).

Van Teeseling, M. C. F. et al. Expanding the verrucomicrobial methanotrophic world: Description of three novel species of Methylacidimicrobium gen. nov. Appl. Environ. Microbiol. 80 , 6782–6791 (2014).

Mohammadi, S. S. et al. The acidophilic methanotroph Methylacidimicrobium tartarophylax 4AC grows as autotroph on H 2 under microoxic conditions. Front. Microbiol. 10 , 2352 (2019).

Sharp, C. E. et al. Distribution and diversity of Verrucomicrobia methanotrophs in geothermal and acidic environments. Environ. Microbiol. 16 , 1867–1878 (2014).

Khadem, A. F. et al. Autotrophic methanotrophy in Verrucomicrobia: Methylacidiphilum fumariolicum SolV uses the Calvin-Benson-Bassham cycle for carbon dioxide fixation. J. Bacteriol. 193 , 4438–4446 (2011).

Grossman, E. L., Cifuentes, L. A. & Cozzarelli, I. M. Anaerobic methane oxidation in a landfill-leachate plume. Environ. Sci. Technol. 36 , 2436–2442 (2002).

Xu, S. & Zhang, H. First evidence for anaerobic oxidation of methane process in landfill cover soils: Activity and responsible microorganisms. Sci. Total Environ. 841 , 156790 (2022).

Haroon, M. F. et al. Anaerobic oxidation of methane coupled to nitrate reduction in a novel archaeal lineage. Nature 500 , 567–570 (2013).

Leu, A. O. et al. Anaerobic methane oxidation coupled to manganese reduction by members of the Methanoperedenaceae . ISME J. 14 , 1030–1041 (2020).

Cai, C. et al. A methanotrophic archaeon couples anaerobic oxidation of methane to Fe(III) reduction. ISME J. 12 , 1929–1939 (2018).

Su, G. et al. Manganese/iron‐supported sulfate‐dependent anaerobic oxidation of methane by archaea in lake sediments. Limnol. Oceanogr. 65 , 863–875 (2020).

Vaksmaa, A. et al. Distribution and activity of the anaerobic methanotrophic community in a nitrogen-fertilized Italian paddy soil. FEMS Microbiol. Ecol. 92 , fiw181 (2016).

Gambelli, L. et al. Community composition and ultrastructure of a nitrate-dependent anaerobic methane-oxidizing enrichment culture. Appl. Environ. Microbiol. 84 , e02186–17 (2018).

Rice, C. W. & Hempfling, W. P. Oxygen-limited continuous culture and respiratory energy conservation in Escherichia coli . J. Bacteriol. 134 , 115–124 (1978).

D’Mello, R., Hill, S. & Poole, R. K. The cytochrome bd quinol oxidase in Escherichia coli has an extremely high oxygen affinity and two oxygen-binding haems: implications for regulation of activity in vivo by oxygen inhibition. Microbiology 142 , 755–763 (1996).

Borisov, V. B., Gennis, R. B., Hemp, J. & Verkhovsky, M. I. The cytochrome bd respiratory oxygen reductases. Biochim. Biophys. Acta - Bioenerg. 1807 , 1398–1413 (2011).

Cabrol, L. et al. Anaerobic oxidation of methane and associated microbiome in anoxic water of Northwestern Siberian lakes. Sci. Total Environ. 736 , 139588 (2020).

Grinsven, S. et al. Methane oxidation in anoxic lake water stimulated by nitrate and sulfate addition. Environ. Microbiol. 22 , 766–782 (2020).

Van Spanning, R. J. M. et al. Methanotrophy by a Mycobacterium species that dominates a cave microbial ecosystem. Nat. Microbiol. 7 , 2089–2100 (2022).

Iguchi, H., Yurimoto, H. & Sakai, Y. Soluble and particulate methane monooxygenase gene clusters of the type I methanotroph Methylovulum miyakonense HT12. FEMS Microbiol. Lett. 312 , 71–76 (2010).

Joshi, N. & Fass, J. Sickle: a sliding-window, adaptive, quality-based trimming tool for FastQ files . https://github.com/najoshi/sickle (2011).

Prjibelski, A., Antipov, D., Meleshko, D., Lapidus, A. & Korobeynikov, A. Using SPAdes de novo assembler. Curr. Protoc. Bioinforma. 70 , e102 (2020).

Langmead, B. & Salzberg, S. L. Fast gapped-read alignment with Bowtie 2. Nat. Methods 9 , 357–359 (2012).

Kang, D. D., Froula, J., Egan, R. & Wang, Z. MetaBAT, an efficient tool for accurately reconstructing single genomes from complex microbial communities. PeerJ 3 , e1165 (2015).

Wu, Y.-W., Simmons, B. A. & Singer, S. W. MaxBin 2.0: an automated binning algorithm to recover genomes from multiple metagenomic datasets. Bioinformatics 32 , 605–607 (2016).

Alneberg, J. et al. Binning metagenomic contigs by coverage and composition. Nat. Methods 11 , 1144–1146 (2014).

Sieber, C. M. K. et al. Recovery of genomes from metagenomes via a dereplication, aggregation and scoring strategy. Nat. Microbiol. 3 , 836–843 (2018).

Parks, D. H., Imelfort, M., Skennerton, C. T., Hugenholtz, P. & Tyson, G. W. CheckM: Assessing the quality of microbial genomes recovered from isolates, single cells, and metagenomes. Genome Res. 25 , 1043–1055 (2015).

Chaumeil, P. A., Mussig, A. J., Hugenholtz, P. & Parks, D. H. GTDB-Tk: A toolkit to classify genomes with the Genome Taxonomy Database. Bioinformatics 36 , 1925–1927 (2019).

Shaffer, M. et al. DRAM for distilling microbial metabolism to automate the curation of microbiome function. Nucleic Acids Res. 48 , 8883–8900 (2020).

Grégoire, D. S. carleton-envbiotech/Methane_metagenomics. GitHub https://zenodo.org/badge/latestdoi/580929360%0A (2023) https://doi.org/10.5281/zenodo.8417138 .

Adam, P. S., Borrel, G. & Gribaldo, S. Evolutionary history of carbon monoxide dehydrogenase/acetyl-CoA synthase, one of the oldest enzymatic complexes. Proc. Natl Acad. Sci. 115 , E1166–E1173 (2018).

Berghuis, B. A. et al. Hydrogenotrophic methanogenesis in archaeal phylum Verstraetearchaeota reveals the shared ancestry of all methanogens. Proc. Natl Acad. Sci. 116 , 5037–5044 (2019).

DeSantis, T. Z. et al. Greengenes, a chimera-checked 16S rRNA gene database and workbench compatible with ARB. Appl. Environ. Microbiol. 72 , 5069–5072 (2006).

Quast, C. et al. The SILVA ribosomal RNA gene database project: Improved data processing and web-based tools. Nucleic Acids Res. 41 , D590–D596 (2012).

Agarwala, R. et al. Database resources of the National Center for Biotechnology Information. Nucleic Acids Res. 46 , D8–D13 (2018).

Ragsdale, S. W. & Pierce, E. Acetogenesis and the Wood–Ljungdahl pathway of CO 2 fixation. Biochim. Biophys. Acta - Proteins Proteom. 1784 , 1873–1898 (2008).

Lee, M. D. GToTree: A user-friendly workflow for phylogenomics. Bioinformatics 35 , 4162–4164 (2019).

Parks, D. H. et al. GTDB: An ongoing census of bacterial and archaeal diversity through a phylogenetically consistent, rank normalized and complete genome-based taxonomy. Nucleic Acids Res. 50 , D785–D794 (2022).

Yu, G. Using ggtree to visualize data on tree-like structures. Curr. Protoc. Bioinforma. 69 , e96 (2020).

Xu, S. et al. ggtreeExtra: Compact visualization of richly annotated phylogenetic data. Mol. Biol. Evol. 38 , 4039–4042 (2021).

Wang, L.-G. et al. Treeio: An R package for phylogenetic tree input and output with richly annotated and associated data. Mol. Biol. Evol. 37 , 599–603 (2020).

Sillas‐Moreno, M. V., Senés‐Guerrero, C., Pacheco, A. & Montesinos‐Castellanos, A. Methane potential and metagenomics of wastewater sludge and a methane‐producing landfill solid sample as microbial inocula for anaerobic digestion of food waste. J. Chem. Technol. Biotechnol. 94 , 1123–1133 (2019).

Dong, J., Ding, L., Wang, X., Chi, Z. & Lei, J. Vertical profiles of community abundance and diversity of anaerobic methanotrophic archaea (ANME) and bacteria in a simple waste landfill in North China. Appl. Biochem. Biotechnol. 175 , 2729–2740 (2015).

Qu, X. et al. Combined monitoring of changes in d 13 CH 4 and archaeal community structure during mesophilic methanization of municipal solid waste. FEMS Microbiol. Ecol. 68 , 236–245 (2009).

Laloui-Carpentier, W., Li, T., Vigneron, V., Mazéas, L. & Bouchez, T. Methanogenic diversity and activity in municipal solid waste landfill leachates. Antonie Van. Leeuwenhoek 89 , 423–434 (2006).

Chen, A. C., Ueda, K., Sekiguchi, Y., Ohashi, A. & Harada, H. Molecular detection and direct enumeration of methanogenic Archaea and methanotrophic Bacteria in domestic solid waste landfill soils. Biotechnol. Lett. 25 , 1563–1569 (2003).

Uz, I., Rasche, M. E., Townsend, T., Ogram, A. V. & Lindner, A. S. Characterization of methanogenic and methanotrophic assemblages in landfill samples. Proc. R. Soc. Lond. Ser. B Biol. Sci. 270 , S202–S205 (2003).

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Acknowledgements

We are sincerely grateful to the landfill site management and their contracted consulting company (anonymity by request) for site access, aid with sampling, and provision of detailed monitoring records. We thank Dr. Jennifer Biddle and her lab group for hosting our team for sample processing prior to shipment. Thanks also to Ms. Rebecca Co and Ms. Alexandra Sauk for help with sampling. This work was supported by an NSERC Discovery Grant (2016-03686) to L.A.H. L.A.H. was supported by a Tier II Canada Research Chair. D.S.G. was supported by an NSERC Banting Postdoctoral Fellowship. N.A.G. was supported by an NSERC CGS-M, an Ontario Graduate Scholarship, an NSERC PGS-D, and a W.S. Rickert Graduate Student Fellowship from the University of Waterloo. We acknowledge the Waterloo Center for Microbial Research for financial support towards open access.

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Daniel S. Grégoire

Present address: Department of Chemistry, Carleton University, Ottawa, ON, K1S 5B6, Canada

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Daniel S. Grégoire, Nikhil A. George & Laura A. Hug

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N.A.G. and L.A.H. contributed to field work in this study. D.S.G. contributed geochemical analyses from records provided by site owners. D.S.G., N.A.G., and L.A.H., contributed to genome assembly and bioinformatics analyses in this study. D.S.G. contributed to the code required for data analyses in this study. D.S.G. and L.A.H. contributed to writing the manuscript.

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Grégoire, D.S., George, N.A. & Hug, L.A. Microbial methane cycling in a landfill on a decadal time scale. Nat Commun 14 , 7402 (2023). https://doi.org/10.1038/s41467-023-43129-x

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Health and Environmental Risks of Residents Living Close to a Landfill: A Case Study of Thohoyandou Landfill, Limpopo Province, South Africa

Prince o. njoku.

1 Department of Ecology and Resource Management, University of Venda, Thohoyandou 0950, South Africa

Joshua N. Edokpayi

2 Department of Hydrology and Water Resources, University of Venda, Thohoyandou 0950, South Africa; [email protected] (J.N.E.); [email protected] (J.O.O.)

John O. Odiyo

The by-products of solid waste deposited in a landfill has adverse effects on the surrounding environment and humans living closer to landfill sites. This study sought to test the hypothesis that the deposition of waste on landfill has an impact on the surrounding environment and residents living closer to it. This was achieved by evaluating the perception of the respondents drawn from people living close (100–500 m) and far (1–2 km) from the landfill site, concerning environmental issues, health problems, and life satisfaction. Results from the study showed that 78% of participants living closer to the landfill site indicated serious contamination of air quality evident from bad odours linked to the landfill site. Illnesses such as flu, eye irritation and weakness of the body were frequently reported by participants living closer to the landfill than those living far from the landfill. More than half of the participants (56%) living closer to the landfill indicated fear of their health in the future. Thus, the participants living closer to the landfill site were less satisfied with the location of their community with respect to the landfill, than those living far from the landfill site. Therefore, the need for a landfill gas (LFG) utilisation system, proper daily covering of waste and odour diluting agents are necessary to reduce the problems of the residents living closer to the landfill site.

1. Introduction

Landfills are a major contributor to the world’s anthropogenic greenhouse gas (GHG) emissions because an enormous amount of CH 4 and CO 2 are generated from the degradation process of deposited waste in landfills [ 1 ]. Landfill operation is usually associated with contamination of surface and groundwater by leachate from the landfill (mostly if the landfill lacks adequate liners), pungent odour, loud disturbing noise from landfill bulldozers, bioaerosol emissions; volatile organic compounds [ 2 , 3 , 4 , 5 , 6 , 7 ]. The storage of leachate in open lagoons can influence the levels of odours experienced in a landfill site. Residents living close to landfill sites have shown concern due to several hazardous pollutants emanating from landfill operations [ 8 ]. Some other pollutants associated with deposition of waste on landfills include litter, dust, excess rodents, unexpected landfill fires, etc. [ 9 , 10 , 11 ]. The factors that influences the by-product or emissions from landfills include the kind and quantity of waste deposited, the age of the landfill, and the climatic conditions of the landfill sites. Complex chemical and microbiological reactions within the landfill often lead to the formation of several gaseous pollutants, persistent organic pollutants (such as dioxins, polycyclic aromatic hydrocarbons), heavy metals and particulate matter [ 8 , 10 , 11 , 12 ].

The continuous inhalation of CH 4 by humans can cause loss of coordination, nausea, vomiting and high concentration can cause death [ 13 , 14 , 15 ]. Acidic gases like nitrogen dioxide, sulphur dioxide, and halides have harmful effects on the health and environment when introduced [ 16 ]. Studies have shown that when nitrogen dioxide and sulphur dioxide are inhaled or ingested by humans, symptoms such as nose and throat irritations, bronchoconstriction, dysproca and respiratory infections are prevalent, especially in asthmatic patients. These effects can trigger asthma attacks in asthmatic patients [ 13 , 17 , 18 , 19 ]. In addition, high contact of NO 2 by humans increases the susceptibility to respiratory infections [ 17 ]. Furthermore, when these acidic gases reach the atmosphere, they tend to acidify the moisture in the atmosphere and fall down as acid rain. Phadi et al. [ 20 ] identified that sulphur dioxide has harmful effects on plant growth and productivity. In addition, humans are at the risk of reduced lung function, asthma, ataxia, paralysis, vomiting emphyserra and lung cancer when heavy metals are inhaled or ingested. Illnesses like, high blood pressure and anaemia have been shown to be caused by heavy metal pollution [ 17 , 21 , 22 ]. Additionally, when in contact in high proportions, heavy metals affect the nervous system which causes neurotoxicity leading to neuropathies with symptoms like memory disturbances, sleep disorders, anger, fatigue, head tremors, blurred vision and slurred speech. It can also cause kidney damage like initial tubular dysfunction, risk of stone formation or nephrocalcinosis, and renal cancer. When humans are exposed to a high amount of lead, it can cause injury to the dopamine system, glutamate system and N-methyl-D-Asphate (NMDA) [ 17 , 21 , 22 , 23 ].

Landfills generate different kinds of trace toxic elements which include carbon monoxide, hydrogen sulphide, xylene, dioxin, etc. Toxic organic micro pollutants also include polychlorinated dibenzo-para-dioxins and polychlorinated dibenzofurans (PCDDs and PCDFs) which are all called dioxins and polycyclic aromatic hydrocarbons (PAHs). Dioxin can be formed from the presence of chlorine-containing substances in the landfill and from landfill fire which is harmful to human health [ 10 , 17 , 24 , 25 ]. Dioxin has been linked with increase in mortality rate caused by ischemic heart disease, when ingested by humans [ 23 ]. PAHs are considered to have potential carcinogenic properties when in contact with humans which could lead to a tumour of the lungs, skin cancer and deficiencies on other parts of the body [ 4 , 17 , 24 ]. When humans inhale particulate matter, studies have shown that it leads to lining inflammation, systemic inflammatory changes and blood coagulation which can further lead to obstruction of blood vessels, angina and myocardial infraction [ 17 ]. A study conducted in a Turkish landfill, on the health risk assessment of BTEX (Benzene, Toluene, Ethylbenzene, and Xylene) emissions on landfill workers in the area shows that BTEX did not pose a health threat to the landfill workers, because the mean concentration of BTEX measured in the landfill was not sufficient and was lower than the United States Environmental Protection Agency (USEPA’s) generally acceptable excess upper-bound lifetime cancer risk of one in 10,000. However, the author noted that landfill effects on humans directly depended on the type of pollutants and the duration of exposure to the people [ 24 ].

Hydrogen sulphide (H 2 S) is a colourless and highly flammable gas. It has an odour of rotten egg and contributes immensely to the odour emissions experienced from landfill sites. It is formed when high sulphate containing compounds (like gypsum and plasterboard) are mixed with the degradable waste in the landfill site. When humans are exposed to high levels of H 2 S it could lead to malfunction of the central nervous system and respiratory paralysis [ 26 ].

Waste management has been closely associated with biological hazards. The decomposition of waste materials in the landfill; vehicle exhaust fumes and favourable weather condition can lead to the formation of bioaerosols and biological agents such as fungi, bacteria and volatile compounds (like endotoxins, β(1-3)-glucans and mycotoxins) [ 27 , 28 ]. Exposure to bioaerosols has been implicated with various respiratory health diseases which can provoke inflammation of the airways. Several studies have shown that occupational risk of waste handlers and landfill workers are high when compared to others [ 27 , 29 , 30 ]. Cancer and other respiratory allergies have been reported by communities living closer to landfill sites. Endotoxins are the most powerful proinflammatory component present in bioaerosols, which are components on the cell wall of Gram-negative bacteria. Heldal et al. [ 27 ], showed that the exposure to low concentration of endotoxins to waste collectors and compost workers can cause an inflammatory response to the upper airways through neutrophil activation and the release of cytokines such as IL6 and IL8 and TNF-alpha. In addition, Gladding et al. [ 29 ] showed that workers exposed to higher amounts of endotoxin and (1→3) -β-D-glucan had an increased risk for respiratory diseases as compared to others with lesser exposure. Most studies focused on biological risk association with waste and landfill workers because of their close proximity to the biological agents over time, therefore, this can be an indication of the possible health risk of people living closer to landfills.

Previous research shows that people living closer to landfill sites suffer from medical conditions such as asthma, cuts, diarrhoea, stomach pain, reoccurring flu, cholera, malaria, cough, skin irritation, cholera, diarrhoea and tuberculosis more than the people living far away from landfill sites [ 31 , 32 , 33 , 34 , 35 , 36 ]. The causes of the health problems are as a result of continuous exposure to chemicals; inhalation of toxic fumes and dust from the landfill sites. Additionally, a review on the “residential proximity to environmental hazards and adverse health outcomes” showed a significant correlation between residential proximity to environmental hazards and adverse health outcomes especially risks for central nervous system defects, congenital heart defects, oral defects, low birth weight, cancer, leukaemia, asthma, chronic respiratory symptoms, etc. The author noted that although residents living closer to the landfill appear to be more prone to adverse effects of health outcomes, the proximity does not equate to the individuals’ level of exposure [ 36 ]. The health hazard is dependent on the level of exposure of the residents to the pollutants and concentration of the pollutants. Landfill proximity to residents will also have significant effects on property value in the area [ 37 , 38 , 39 , 40 ].

Despite the proliferation of the harmful effects in recent years, not much research on health and environmental impacts on the residents living closer to landfill sites has been conducted in many landfills situated in rural and peri-urban centres in South Africa. Though, Bridges et al. [ 34 ] conducted a study in comparison of adverse effects of incinerators and landfill emissions on health. The study did not consider the environmental and economic risk and impact associated with landfill pollutants. Therefore, this study posed several relevant questions which are yet to be addressed. These questions include; (a) are there major social-economic differences between the residents living closer to the landfill and residents living far from the landfill? (b) Do the residents living closer to the landfill find the landfill’s characteristics very disturbing compared to those living far from it? (c) Do the residents living closer to the landfill suffer from some specific illnesses more than the residents living far from the landfill? (d) What is the perception in view of the community life satisfaction between residents living closer to the landfill site and residents living far away from it? This study was therefore aimed at investigating and providing answers to the above research questions.

2. Materials and Methods

Thohoyandou landfill is situated very close to the residential areas at approximately 100 m away. Therefore, this study sought to find out the perceptions of health impact and the way of life for residents living closer to Thohoyandou landfill. Firstly, a reconnaissance survey was conducted around the landfill site to identify the number of households and other functional institutions located in the area. It was observed that the community was located approximately 100 m away from the landfill. Therefore, the study focused on residents living approximately 100 m to 2 km away from the landfill. The households living closer to the landfill were identified to be approximately 100 households, with an average of four people per household [ 41 ]. Then, the participants of the study were strategically identified based on how long they have lived in the community. This led to 100 people identified as the sample size.

According to Brewer [ 42 ], stratified random sampling technique was adopted to identify approximately 50 participants for the study, who lived approximately 100 to 500 m, and 50 participants were identified as the control for the study who lived within 1 to 2 km away from the landfill.

A landfill operator manager and three university students from the University of Venda, South Africa were trained and recruited for data collection. A five-page questionnaire was pretested with 10 participants to identify errors and limitations of the survey tool. Furthermore, after adjustments of the questionnaire, the questionnaires were administered to a total of 100 participants (50 participants—people living closer to landfill; while 50 participants—people living far away from the landfill). At the start of the administration of questionnaires, the majority of the residents were willing to corporate and participate in the study. Additional information, suggestions and recommendations were also given to the researchers by the participants based on the environmental challenges faced by the community. During the fieldwork, four households expressed scepticism and refused to participate in the study. Two other households expressed less concern because they felt the study was not beneficial to them as they were not house owners and not fully responsible for the environmental issues in the community.

Topical issues on the perception of neighbourhood problems, the significance of environmental problems, most frequently experienced sickness and life in general in the community were identified. The questions asked concerning environmental problems were coded as (1) serious, (2) a fairly serious problem and (3) not a serious problem. The participants were provided with seven environmental issues facing the community which included disposal of solid waste, garbage, and litter in the street, unwelcome location of the landfill, air pollution, bad odour, water pollution, noise pollution and dust. An independent sample t -test analysis was conducted to identify the difference in mean, and the significance of results obtained from both communities ( Appendix A ).

In addition, the participants were presented with possible illnesses associated with complaints of people living closer to the landfill site. The participants were asked to indicate whether they or any member of their family experienced each of the identified illnesses frequently (1), fairly frequently (2) or not frequently (3). The data acquired from the field study were analysed with the aid of Statistical Package for the Social Sciences version 25 developed by International Business Machines Corporation, Armonk City, NY, USA. Figure 1 shows the location of the study area.

Thohoyandou landfill site and nearby residents.

3. Results and Discussion

The social and demographic characteristics of the respondents were identified to understand the social and economic characteristics between the two communities. Table 1 shows the results obtained from the study.

Social and demographic characteristics of respondents.

Table 1 shows that there were more female than male participants in both communities due to the availability and the readiness of the female respondents to participate in this study. Participants aged from 21 to 30 years were the most dominant, though participants aged 31–40 years were equally most dominant for participants living closer to the landfill. The participants were mostly part-time workers. However, most of the participants were in high school and tertiary institutions and lived more than 5 years in the community.

3.1. Perception of the Significance of Environmental Problems Faced by the Community

3.1.1. disposal of solid waste.

This indicates the rate of disposition of solid waste in the landfill and considering how serious disposal of Municipal Solid Waste (MSW) activities influence the state and wellness of the people. Table 2 indicates the comparison of participants living closer to the landfill site (CL) and participants living far away from the landfill site (AL) with regards to the significance of the impact of different landfill characteristics on both communities. A total of 70% of participants living closer to landfill site indicated that deposition of MSW in Thohoyandou landfill is a serious problem, whereas 12% of respondents living far from the landfill indicated the same problem. Furthermore, 10% of the participants living closer to the landfill site indicated that the deposition of MSW in the Thohoyandou landfill is not a serious problem to them, whereas 62% of participants living far from the landfill said the same. These responses were as a result of the physical and unpleasant presence of the landfill in the CL community. Cross tabulation between the years of participants who lived in the CL community and the significance of deposition of solid waste shows that for all the different years, solid waste disposal was a serious problem ( Figure 2 ). This study agrees with other studies which have shown that the significant impact of deposition of MSW in landfills located in close proximity to residential areas causes negative effects to the people and the environment [ 24 , 32 , 33 , 35 , 36 , 40 ].

Cross-tabulation between the duration residents that lived in the CL community and the seriousness of solid waste disposal. Note that the no bar section in the figure indicates there was no response by the participant.

Respondents’ rating of the significance of environmental problems in the community.

3.1.2. Garbage and Litter on the Street

A total of 30% of the participants living closer to the landfill indicated that garbage and litter in the surrounding CL community was a serious problem ( Table 2 ), while 26% of participants living far from the landfill indicated the same problem. Meanwhile, 50% of the participants living closer to the landfill indicated that the flow of garbage and litter into the community was not a serious problem to them while 12% of participants living far from the landfill indicated the same. Fifty-six percent (56%) of participants living far from the Thohoyandou landfill indicated that garbage and litter on the street were a fairly serious problem. From the responses, for both communities, garbage and litter seemed not to be a serious problem and this could be attributed to the fencing and constant covering of the MSW deposited in the landfill. A cross tabulation between the duration of years, the participants lived in the CL community and the seriousness of the problem (garbage and litter) indicates that participants who lived less than 1 year, 6–10 years and 11–20 years had high percentages indicating the impact of garbage and litter on the CL community as not a serious problem ( Figure 3 ). Participants that lived within 5 years in the area indicated that it was a serious problem, which is possibly because these participants could have spotted several litters and attributed it to the landfill. This might not be the case, because the majority of the participants indicated that litter on the streets was not a serious problem. In addition, it is possible the litter could have come from dustbins of residents, passers-by and poor waste management system in the community. Adeola [ 33 ] indicated that garbage and litter on the streets were major problems encountered by the participants living closer to the landfill when compared to results derived from the participants living far from the landfill site. Sankoh et al. [ 35 ] conducted a study on the environmental and health impacts of the solid waste dumpsite in Freetown Sierra Leone. The study showed that the presence of the dumpsite increased the amount of filth, garbage and litter in the nearby community. Additionally, Fitaw and Zenebre [ 43 ], conducted a study in Addis Ababa city on the assessment of landfills in the city, the study showed that blowing litter from landfills have been found to be prevalent in areas closer to landfills and are easily carried to nearby residents by wind and has negative effects on the health of residents. Therefore, this shows that a controlled system of solid waste deposition and other precautionary measures are very important to achieve a cleaner environment for communities residing next to a landfill [ 33 , 36 ].

Cross-tabulation between the duration participants lived in the CL community and the seriousness of garbage and litter on the street. Note that the no bar section in the figure indicates there was no response by the participant.

3.1.3. Unwelcome Location of the Landfill

This indicates the suitability and acceptance of the landfill site by the participants from the community. Table 2 shows that 78% of the respondents living closer to the landfill site indicated the unsuitability of the presence of the landfill to them, whereas, 90% of participants living far from the landfill site felt that the site was fine. The cross tabulation in Figure 4 shows that all participants that have lived from less than 1 year to 20 years indicated that the landfill should not be situated closer to their homes, possibly because of the long-term risk associated with it. Studies have shown that residents living closer to the landfill site do not like the idea of the landfill’s location in close proximity to their homes because of its negative impact on their communities [ 3 , 32 , 34 , 36 ]. Bridges et al. [ 34 ] and Sankoh et al. [ 35 ] further showed that the exposure of participants living at least 2 km away from a landfill causes health and environmental effects when compared to participants living far from a landfill site. Thus, the findings above on the suitability of the location of landfill agree with the results found in the studies mentioned.

Cross-tabulation between the duration participants lived in the CL community and the seriousness of the unwelcomed location of the landfill. Note that the no bar section in the figure indicates there was no response by the participant.

3.1.4. Air Pollution and Bad Odour

Air pollution and bad odour have been found by many scholars to be synonymous to landfill operations. This shows the seriousness of air pollution and bad odour emanating from the landfill into the community. Table 2 shows that 78% of participants living closer to the landfill site indicated serious contamination of the air quality and the fact that they often experience a bad odour which they believe is from the landfill site. However, 16% of the participants living far from the landfill indicated serious contamination on air quality and bad odour, thus the majority of the participants living far from the landfill indicated a better air quality devoid of smell or odour. The cross tabulation between the years of participants living in the CL community and air pollution with bad odour in the community was recorded in Figure 5 . The figure shows that all participants that lived for less than 1 to 20 years in the CL community indicated serious contamination in air quality with bad odour from the landfill. It was more pronounced or taken more seriously by participants who have lived longer, up to 20 years, in the CL community. Bouvier et al. [ 38 ] showed that residents living closer to landfill experienced higher contamination of air quality than residents living far from the landfill site. Vrijheid [ 32 ] identified that some components of landfill gas (LFG) like hydrogen sulphide are key contributors to odour emanating from a landfill site. Air pollution and bad odour are as a result of poor management of the landfill by landfill operators like proper compression of waste deposited in the landfill and lack of collection and utilisation of LFG emissions. However, the pungent odour and air pollution can be minimised by a proper daily covering of solid waste immediately when it is deposited in the landfill; the use of a diluting agent which suppresses bad odour from the landfill; and the collection and utilisation of the LFG emitted from the landfill. The electronic nose technique analysis by Xiangzhong [ 44 ] showed that the odour emanating from the landfill and its boundaries were similar to the odour experienced from waste sludge, residential waste and construction waste.

Cross-tabulation between the duration participants lived in the CL community and the seriousness of air pollution and bad odour. Note that the no bar section in the figure indicates there was no response by the participant.

Sakawi et al. [ 4 ] showed in their study that about 83.7% of their respondents indicated that bad smell from landfill has affected the tranquillity and quality of life. In addition, 80.5% of participants indicated that bad odour was associated with their current bad health. The study indicates that the peak of malodour is experienced at night forcing residents to close windows and doors, thus not enjoying cross ventilation at home. Rainfall, wind direction, and intensity increased the intensity of odour emanating from the landfill. De Feo et al. [ 5 ] ascertained how participants living closer to the landfill perceive odour and local pollution. The study showed that fewer residents living closer to the waste facility complained that the facility contributed to local degradation and odour. However, the study showed that monetary compensation was given to the residents; this further influenced their perception towards odour effects from the landfill. Additionally, in 2003 during the operating year of the waste facility, the residents complained heavily of rotten egg odour coming from the landfill and it was increasing as the years went by. However, in 2009, after the closure of the waste facility residents did not complain of odour.

3.1.5. Water and Noise Pollution

In the context of this study, water pollution indicates the presence of polluted water in the community. In addition, noise pollution indicates the level of noise in the community. Table 2 shows that 64% of participants living closer to the landfill indicated that the water supply was clean, while 42% of participants living far from the landfill site indicated that the water was clean. Therefore, the tap water supplied to both communities could be from a different source and not from the groundwater close to the landfill. Cross-tabulation of water and noise pollution with the duration of residents living closer to the landfill site was used to analyse the perceptions of participants who lived in different years in the CL community and how their perceptions influence the results. The cross-tabulation between the years the participants lived and water pollution shows that most participants for all age groups indicated that water pollution is not a regular problem encountered by them ( Figure 6 ). Studies have shown that it is inevitable for landfills not to contaminate groundwater, as leachate percolates into groundwater through cracks of membranes (for sanitary landfills) and contaminates it, because of high bacteria content [ 6 , 7 , 11 , 32 , 45 ]. This study did not carry out laboratory analysis of groundwater in the area, however, the source of drinking water in the vicinity was provided by the Municipality.

Cross-tabulation between the duration participants lived in the CL community and the seriousness of water pollution. Note that the no bar section in the figure indicates there was no response by the participant.

Furthermore, 58% of participants living closer to the landfill indicated that there is no form of noise pollution, while 22% of participants living far from the landfill indicated the same. However, most of the participants living far from the landfill (52%) indicated noise pollution as a fairly serious problem for them. Noise can be generated from different sources and not necessarily from the landfill. Although, it is quite impossible not to notice the heavy trucks and bulldozers in a landfill, the Thohoyandou landfill lacks the adequate number of bulldozers and heavy trucks in the landfill due to lack of funds. On the day of our visit to the landfill, there were complaints about the bulldozers for daily covering of waste not functioning for several months. However, after some months when we went back to the landfill, some bulldozers were functioning. In addition, incoming waste trucks contribute some noise pollution in the landfill but not enough to cause significant pollution to the nearby residents.

Figure 7 indicates that most participants for all the age groups indicated that noise pollution is not a serious problem for them. This study is consistent with other studies that have been conducted [ 11 , 37 ]. Reichert et al. [ 37 ] showed that blowing trash and truck noise was the least significant problem when compared to other environmental factors. A study showed that during landfill operations that residents were a little concerned about noise pollution [ 11 ].

Cross-tabulation between the duration participants lived in the CL community and the seriousness of noise pollution. Note that the no bar section in the figure indicates there was no response by the participant.

3.1.6. Dust

Table 2 shows that 40% of the participants living closer to the landfill indicated that dust was a serious problem to them, while 4% of participants living far from the landfill site indicated that the emission of dust particles in the atmosphere was a serious problem. However, most of the participants living far from the landfill site (60%) indicated that the emission of dust particles to the atmosphere was not a serious problem for them. This shows the significance of dust particles in the atmosphere.

Figure 8 shows cross tabulation between the duration the participants lived in the CL community and dust particles in the atmosphere. All participants that lived less than one year and up to 5 years in the community indicated the emission of dust particles in the atmosphere is not a serious problem to them. However, participants that lived long in the community from 6 years up to 20 years indicated dust percolation as a serious problem in the community. Thus, it takes time for participants to experience serious dust emissions in the atmosphere. Studies have shown that dust particles from landfills have been a major concern in communities [ 10 , 11 , 34 ]. Dust emissions from landfills can be controlled by the continuous spraying of water on the soil; fan-driven misting system; mixing of X-Hension pro with water and spray on the soil; dust destroyers; etc. [ 10 , 46 , 47 , 48 ]. The use of spraying of water on the ground and any other technique has not been adopted in the Thohoyandou landfill and is therefore recommended.

Cross-tabulation between the duration participants lived in the CL community and the seriousness of dust pollution. Note that the no bar section in the figure indicates there was no response by the participant.

Table 2 thus summarizes that the participants in the CL community experienced serious environmental problems with respect to the disposal of solid waste, unwelcome location of the landfill and air pollution with odour. Garbage and litter, and water and noise pollution were perceived not to be serious problems by the participants in the CL community. The participants in the AL community, however, showed lesser serious environmental problems compared to the participants in the CL community. All the environmental problems highlighted were perceived not to be serious problems except noise pollution, garbage, and litter on the street which posed some problems to the participants in the AL community.

The results show that more undesirable environmental conditions posed very serious problems for the participants in the CL community than the AL community. Specifically, disposal of solid waste; unwelcome location of landfill; and air pollution with bad odour; were considered major threats.

A t -test was employed to access whether the differences noted between the ratings on the significance of the environmental problem by the two locations were statistically significant ( p < 0.05). Table 2 shows that the differences were found to be statistically significant for all seven variables in both communities. Figure 9 shows the summary in the graphical representation of the respondent’s rating living in both communities in terms of the seriousness of each of the environmental characteristic.

Comparison between both communities showing the seriousness of each landfill characteristics.

3.2. Perception of Most Reported Illnesses Encountered by the Participants in Both Communities

Respondents living close to the landfill reported that breathing disorders are frequently (24%) and fairly frequently (34%) problems they experience in the CL community. Similarly, respondents from the AL community reported that breathing disorders are frequently (10%) and fairly frequently (24%) experienced. Various studies have also shown that residents living closer to a landfill site are more prone to respiratory diseases as supported by this study [ 8 , 32 , 33 , 34 , 35 ]. Respiratory diseases and breathing disorders can be caused by bioaerosols and biological agents released from landfill sites [ 27 ]. Apart from biological agents and volatile organic compounds released from landfill sites, emissions from cars, trucks and bulldozers used in the landfill can also contribute to emissions from the landfill site [ 28 ]. Such emissions have been reported to be harmful to human health [ 27 , 28 , 29 , 30 ]. It is also not surprising to note that respondents living far from the landfill site also recorded respiratory diseases which were commonly experienced. Air pollution as a result of emissions from cars, biomass burning and bricks making are common anthropogenic activities in the study area and could be responsible for reported cases in the AL community. Brick making and biomass burning releases particulate matter (PM 10 and PM 2.5 ) and various volatile organic compounds that have been implicated in respiratory diseases [ 49 , 50 , 51 , 52 ].

A study on exposed traffic policemen to outdoor air pollution showed that the percentage of participants with a diagnosis of allergy was higher in the exposed traffic policemen than in the control [ 52 ]. Additionally, Heinrich and Wichmann [ 49 ] concluded that traffic related air pollutants can lead to mortality risk, particularly in relation to cardiopulmonary causes. The result also agrees with previous studies which shows that breathing disorders, shortness of breath and respiratory diseases are major health problems associated with landfill emissions and have continued to increase over the years [ 53 , 54 , 55 , 56 ].

Table 3 indicates that residents living in both communities reported the same frequent level (18%) of cancer illness. Fairly frequent cancer levels were reported at 10% and 12% for CL and AL communities, respectively.

Respondents’ rating of how these illnesses are reported by the participants in both communities.

Furthermore, illnesses like flu, eye irritation and weakness of the body were frequently reported by participants living closer to the landfill than participants living far from the landfill ( Table 3 ). Most participants living far from the landfill indicated that they did not experience these illnesses very often. Therefore, we can conclude that there is a higher risk of most of these illnesses to be attributed to the landfill, but it is also imperative to know that these illnesses could also be contracted from various other sources. Though headache was more frequent in the CL community (38%) than AL community (20%), the latter community showed a higher percentage (54%) for fairly frequent which is an indication of significant impact.

Some illnesses recorded in this study like back pain, skin disorders, hearing impairments and asthma were indicated by most participants living closer to the landfill as not often experienced. Likewise, most participants living far from the landfill did not experience these illnesses often, except for asthma. Studies have established that cancer is an illness experienced by people living closer to a landfill or waste dump [ 32 , 33 ]. Similarly, the Health Protection Agency [ 13 ], showed that in several epidemiological studies performed by different scholars showing the relationship of cancer and landfill sites, cancer was a relatively complex illness to identify because of inadequate evidence to back up the claim of increased risk of cancer to communities living closer to landfill sites. Similarly, the review of Jarup et al. [ 57 ], by Small Area Health Statistics Unit (SAHSU) in 2011, showed that there was no excess risk of cancer in a people living closer to the landfill site [ 13 ].

Table 3 thus showed that the participants living closer to the landfill site reported some illnesses more often than participants living far from the landfill site. Figure 10 shows the graphical representation of the comparison of the frequency of reporting the selected illnesses in both communities. A t -test analysis was conducted for the most reported illnesses to understand the significance of the difference of results obtained and the result’s significance ( Appendix B ). Seven out of 11 health problems were statistically significant, that is breathing disorders, flu, eye irritation, weakness of the body, back pain, coughing and tuberculosis, and asthma.

Comparison between both communities showing how frequent the illnesses impact them.

3.3. Perception of Most Disturbing Landfill Site Characteristics

This study highlights eight disturbing characteristics, which are commonly associated with landfill sites. The participants were asked to rate the landfill characteristics based on a scale of (1) disturbing, (2) fairly disturbing or (3) not disturbing to the participants living in both communities as shown in Table 4 .

Respondents’ ratings of how disturbing the external characteristics are observed by the participants living in both communities.

Fear of future health indicates the anticipated health issues that will arise in the future based on the current effects. Table 4 shows that 56% of the participants living far from the landfill site feel that their health will be fine in the future. However, 56% of participants living closer to the landfill indicated that fear of their health in the future was a disturbing issue, while 24% of participants living far from the landfill indicated the same. This result could be attributed to the physical presence of the landfill, odour and possible fear of accumulated intake of gaseous emissions from the landfill. Similarly, Adeola [ 33 ] made a comparison of participants living closer to a landfill and far from a landfill concerning how they feared their health in the future. The study concluded that more participants living closer to the landfill site feared for their health in the future than participants living far from the landfill site.

The viability of properties in the area was also assessed. Results in Table 4 show that 54% of the participants living closer to the landfill site indicated the difficulties in the sale of the property, but 66% of the participants living far from the landfill indicated the property sale as a good business in the community. The respondents targeted to give their views concerning property sales were mainly house owners, tenants and elderly participants that had lived in both communities for a long time. Adeola [ 33 ], in a study, experienced that participants living closer to the landfill site could not sell the property as much as participants living far from the landfill site. Property buyers could be sceptical on the purchase because of close proximity of the property to the landfill site.

Additionally, other external factors on landfill characteristics like friend’s unwillingness to visit, desirable business enterprise staying away and landfill stigmatisation, show that most participants living closer to the landfill site felt that these external factors were disturbing to them. Participants living far from the landfill felt their external factors were not disturbing to them except for landfill stigmatisation. However, these communities are still developing and might still lack some desirable businesses and poor rent for properties. Rodents and mosquitoes were indicated to be more prevalent with participants living closer to the landfill than participants living far from the landfill. Therefore, some participants close the doors and windows of their houses regularly to avoid mosquitoes and rodents. Figure 11 shows the participants’ ratings on how disturbing the external factors of the landfill characteristics were to them. Thus, the participants living closer to the landfill site rated all the external landfill characteristics mostly as disturbing to them. However, the participants living far from the landfill site ranked most of the external landfill characteristics as not disturbing to them. The overall results show that the CL community was more disturbed by the external landfill characteristics than the AL community. Studies have shown that the presence of landfill in close proximity to properties reduces the values of these properties [ 38 , 39 , 40 , 58 ]. Seok Lim and Missios [ 59 ] indicated that the introduction of larger landfills has more impacts on property value than smaller landfills. However, according to Bouvier et al. [ 38 ], some property value depend on the buyers in question. If the buyers are not concerned about the effect of the landfill and only interested in the property, then they may pay a substantial amount for the property.

Comparison between both communities showing how disturbing these external factors were to them.

A t -test was used to test whether the differences noted between the ratings of the disturbances of the external landfill characteristics were statistically significant ( p < 0.05) ( Appendix C ). The CL community rated the landfill characteristics more disturbing than the AL community. Appendix C shows the differences were found to be statistically significant for all the external landfill characteristics.

3.4. Perception of Life Satisfaction Living in the Community

The participants were asked to rank the life satisfaction characteristics of living closer to a landfill and not living close to a landfill from the scale of (1) satisfied, (2) somewhat satisfied or (3) not satisfied as shown in Table 5 . Table 5 also shows the t -test analysis which was performed to understand the significant differences between both communities ( Appendix D ).

Respondents’ ratings of how disturbing the external characteristics are as observed by the participants living in both communities.

The results show that the participants living closer to the landfill site are less satisfied with the variables posed in this study than the participants living far from the landfill site. Figure 12 shows the graphical comparison of the participants’ views on how satisfied they are living in both communities.

Comparison between both communities showing participants’ satisfaction.

The results show that the differences between the two communities were found to be statistically significant for five out of seven variables, that is for life in general; personal health condition; neighbourhood compared to others; community as a place to live in and perceived neighbourhood change. Palmiotto et al. [ 8 ] showed that residents living closer to the landfill experience higher forms of odour annoyance and the residents are concerned about the landfill impacts on the environment and their health. In addition, children living closer to landfills experience increased methane and methanobrevibacter smithii in their intestinal microbiota which caused serious health challenges and unrest in the community [ 60 ]. The study conducted in Nant-y-Gwyddeon landfill in South Wales showed that residents living in close proximity to landfill complain of odour and increased rate of congenital malformation [ 61 ].

4. Conclusions

The study on health and environmental impacts of landfill sites on humans has generated mixed reactions among scholars, therefore, constitutes a complex study. This study evaluated the health and environmental effects of Thohoyandou landfill on the residents living closer to the landfill, which integrates different factors like waste disposal, air and dust pollution, location of the landfill, water and noise pollution, fear of future health, property value, mosquitoes and rodent’s pollution, life in general in the community, etc.

This study concludes that the residents living closer to the landfill sites are at higher health and environmental risks when compared to those living far away from the landfill sites. However, the landfill associated problems have helped the community living closer to the landfill to be more conscious and educated on environmental pollution. The health risk associated with landfill pollutants in this study shows that proper landfill management is very essential. Landfills should be located far away from residential houses and institutions to avoid certain health and environmental related risks.

Independent samples test of environmental problems in the community.

Where df means Degree of Freedom, F: the test statistics of Levene’s test, T is the computed test statistics.

Independent samples test on most reported illnesses encountered by the participants in both communities.

Independent samples test on external characteristics observed by the participants living in both communities.

Independent samples test on life satisfaction with living in the community.

Author Contributions

Conceptualization: P.O.N.; Supervision: J.O.O. and J.N.E.; Writing—original draft: P.O.N. Editing: J.O.O. and J.N.E, Funding acquisition: J.O.O. Writing of final draft: P.O.N; J.O.O. and J.N.E.

This research was funded by Eskom (grant number: E349) and the Research and Innovation Committee of the University of Venda.

Conflicts of Interest

The authors declare no conflict of interest.

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Your Trash Is Emitting Methane In The Landfill. Here's Why It Matters For The Climate

James Bruggers

Phil McKenna

Robert Benincasa

Landfills produce a lot of methane, a heat-trapping gas that contributes to global warming. With scientists calling for cuts in methane emissions, there are challenges to curbing these emissions from landfills, starting with even quantifying them. Pictured here is Waste Management landfill in Livermore, Calif. Michael Macor/San Francisco Chronicle via Getty Images hide caption

A single flip-flop. An empty Chick-fil-A sandwich bag. A mattress. A sneaker, navy with a white sole. A little orange bouncy ball.

Garbage is strewn among thigh-high drifts of dirt, used to bury the filthy, weather-worn items at the Orange County Landfill in Florida and prevent the intrusion of insects, rats and pigs. Bulldozers smooth the dirt into place while tractor-trailers deliver ever more trash. Vultures and seagulls circle above. A bald eagle lands nearby.

"Anything you will see out in the real world you'll see it here," said David Gregory, manager of the solid waste division of the Orange County Utilities Department. "Because when people throw things away, this is where it comes."

According to the Environmental Protection Agency, landfills such as this one on the edge of Orlando are among the nation's largest sources of methane, a greenhouse gas far more potent than carbon dioxide and a major contributor to global warming. A seminal U.N. report published in May found that immediate reductions in methane emissions are the best, swiftest chance the planet has at slowing climate change. Landfills emit methane when organic wastes such as food scraps, wood and paper decompose.

But the challenges to reining in methane are big, beginning with even quantifying how much leaves landfills. Industry operators insist the EPA overestimates emissions. Yet independent research looking at emissions from landfills in California and a top EPA methane expert said that the agency significantly underestimates landfill methane.

The EPA has "been understating methane emissions from landfills by a factor of two," said Susan Thorneloe, a senior chemical engineer at the EPA who has worked on the agency's methane estimation methods since the 1980s.

Part of the problem may be that the EPA's methods for estimating landfill methane emissions are outdated and flawed, Thorneloe said.

Ryan Maher, an attorney with the Environmental Integrity Project, a watchdog group, said landfill methane emissions are "a neglected problem."

Three of the nation's top 10 methane-emitting landfills are in central Florida, including the Orange County Landfill pictured here, according to numbers provided by the facilities to the Environmental Protection Agency. Amy Green/WMFE hide caption

"We're basing our emissions estimates on models rather than direct measurement," said Maher, who recently authored a study that found Maryland's landfill methane emissions were four times higher than that state had estimated. "We do have the capacity to measure these emissions directly. And we just haven't been."

The stakes are high for getting an accurate picture of methane emissions. Reducing methane could almost immediately curb climate change, because it stays in the atmosphere for a short time, unlike carbon dioxide, which lingers for a century or more. Landfills are one of three main sources of human methane pollution, along with livestock and the oil and gas industry. The United States is the third-biggest emitter of methane in the world.

The Biden administration has begun to implement a 2016 rule on landfill methane, but it will only cut a small percentage of emissions. Yet steep reductions in global methane emissions this decade would avoid nearly 0.3 degrees Celsius of additional warming by the 2040s, according to the U.N. assessment. That could go a long way to keeping average global temperatures from rising beyond 1.5 degrees Celsius compared with preindustrial times, and avoiding the worst effects of climate change, a goal of the Paris climate agreement.

"By reducing methane emissions, we can quickly reduce the atmospheric warming effect," said Jeff Chanton, a Florida State University climate scientist who studies methane. "And targeting landfills is a great place to start because by tuning the gas collection system, and getting it to work at its optimum level, you get a lot. You collect more methane, and you don't release it to the atmosphere."

Three of the top 10 methane-emitting landfills are in central Florida

Standing atop a 140-foot summit of refuse at the Orange County landfill, almost all of metro Orlando is in view: downtown high-rises, the control tower and runways of Orlando International Airport, and the looming cylinder-shaped cooling towers of Stanton Energy Center. It powers some 260,000 homes and businesses in Orange and Osceola counties, up to 15,000 of them with methane from this landfill.

Gregory finds value in what is going on under his feet, the rotting and decomposition of organic waste such as kitchen scraps, paper or spoiled canned goods, and the biological processes that turn garbage into methane. Buried within the garbage lies an expansive criss-cross network of more than 500 wells capturing methane gas from the decomposing trash. The wells also keep vast quantities of methane from escaping.

"You have something that's reached the end of its life," he said of the trash. "And one of the things that we do here at the landfill is collect that gas and use it to make energy."

The EPA tracks more than 2,600 municipal solid waste landfills. About 500 collect methane for energy production. The agency estimates that nearly 500 more could cost-effectively have their methane turned into an energy resource.

Projects such as these could play a key role in stemming the worst impacts of climate change.

David Gregory says his department has gone beyond regulations to contain methane emissions at the Orange County Landfill. He says he believes his department is not using the best equation to convey the steps it's taking to mitigate the climate-damaging emissions. Amy Green/WMFE hide caption

Despite landfill operators' efforts nationally, large volumes of this invisible, odorless gas still escape from the sites each year. For all the emissions the Orange County Landfill captures, for example, an additional 32,000 metric tons of methane were released from the facility into the air in 2019, making it the third-largest source of methane emissions from a landfill in the country, according to the most current public information the company reported to the EPA. That represents a large, inexplicable increase from previous years — Orange County hadn't been a top 10 emitter in the decade before 2019, according to EPA data.

The Orange County site isn't alone in central Florida. Three landfills among the nation's top 10 emitters of methane are near Orlando, according to the EPA. Their collective emissions damage the climate in the near-term as much as all the 1.8 million cars and pickups registered in the three counties where the landfills are located.

For Orange County, the high ranking came as a surprise — an unwarranted one, officials said. Community leaders here take pride in sustainability initiatives. They consider the landfill's methane-to-energy system key to reducing greenhouse gas emissions.

Orange County's Gregory said he is reevaluating what the county has reported to the EPA.

"It's not like we have a measurement" of methane emissions, he said. "It's all based on the models. And that's where we need to make sure that we're not overlooking anything."

A spokeswoman for the top methane-emitting landfill in the nation, a facility near Cincinnati operated by Rumpke Waste & Recycling, also said the EPA ranking was misleading.

In an email, spokeswoman Amanda Pratt dismissed the emissions values her company reported as based on "a theoretical methane generation rate that is calculated using facility-provided data and US EPA derived equations."

Outdated methane emissions models create "a mess"

EPA figures may indeed be flawed.

A 2018 National Academy of Sciences report placed "low confidence" in EPA estimates for landfill methane emissions due to uncertainties and insufficient measurements. The report concluded that the agency's method for estimating methane emissions from landfills is "outdated" and was "never field-validated."

Further, the EPA allows for three different ways that individual landfill operators can calculate the amount of methane they generate and two different ways to calculate how much of that methane is emitted into the atmosphere. Depending on which methods an operator chooses, the estimated amount of methane emissions can vary significantly.

The EPA's Thorneloe helped craft the current estimate method, and she said it "was developed over 30 years ago using empirical data for about 40 landfills."

Citing new research out of California, she has come to believe the agency underestimates emissions.

Landfill operators agree that the EPA models are flawed but insisted those flaws lead to overestimating emissions from their sites. In a statement to NPR, David Biderman, chief executive officer of the industry group Solid Waste Association of North America, said, "The model relies on many assumptions and has not been updated to reflect changes in the waste sector such as reduced organic content in the waste stream that can result in overestimation of landfill emissions."

Jean Bogner, a University of Illinois at Chicago emeritus professor and a co-author of the National Academy of Sciences report, calls the EPA's methods "a mess." Bogner, in part, blames the deficiencies on methods first developed by the Intergovernmental Panel on Climate Change, a U.N. body.

"Methods should evolve with the science," Bogner said. "It's becoming more and more important as we move into more intensive climate change mitigation strategies to understand more precisely how much methane is coming out of specific landfills. In the past, you could sort of wave your hands and say, 'This may be a ballpark number,' but we need better numbers now to guide site specific mitigation strategies."

The National Academy of Sciences report made recommendations to improve methane measurement, and the EPA is working to address those that pertain to the agency, an EPA spokesperson said in an email.

More broadly, EPA officials said they continually update estimates. The agency is reviewing scientific studies on landfill waste to better inform the agency's estimates for methane emissions, the spokesperson added.

Thorneloe said better measurement technologies will help EPA staffers make better estimates.

"If we're going to choose particular sources to reduce emissions, we need to know what those emissions are," Thorneloe said. "What I'm trying to do is develop better test methods rather than what we've relied on in the past."

Industry representative Biderman said that "any proposed changes to regulations should be technically feasible and commercially available."

Methane captured at the Orange County Landfill is processed at this Orlando Utilities Commission facility before being sent to the Stanton Energy Center. Amy Green/WMFE hide caption

With landfill gas capture systems, efficiency counts

Capturing methane at a landfill is complex. A lot can go wrong with a landfill's plumbing, said Chanton, the Florida State University climate scientist. "It's very vulnerable to disruption," he said. "It takes a lot of attention."

Landfills aren't like a factory that sends nearly all emissions through individual smokestacks. Landfills can span hundreds of acres and leak at various rates from open areas or sections that have temporarily been covered or permanently closed and capped.

Operators have up to five years to start capturing methane from new landfill sections, called cells. But methane pollution begins much sooner than that, said Morton Barlaz, professor and head of the Department of Civil, Construction and Environmental Engineering at North Carolina State University.

The capacity to collect methane at landfills often depends on gas capture wells and how efficiently the collection system is operating. Landfill operators are required to cover waste disposal areas every night with a thin layer of soil or an alternative such as mulch or even plastic. Some of those materials are more porous than others, resulting in more methane releases, Barlaz said.

Weather can also play a role. Rain can both help produce more methane and flood gas collection systems, making them less effective.

"When you have a situation where your gas collection is impeded, the landfill will emit more methane than EPA estimates might suggest," Chanton said. But a well-run system can collect more methane in its wells while also harnessing methane-digesting microbes in the landfill's soil cover to help neutralize the greenhouse gas before it can escape, he added.

Remote sensing of methane from high-altitude aircraft in April reveals plumes of the gas at the River Birch Landfill outside New Orleans coming from the facility's active portion (left), where new waste is added each day, and from a vent (right). Researchers calculate the rate of methane venting at about 2,000 kilograms per hour, which would be 48 metric tons per day. Riley Duren/University of Arizona, Arizona State University, NASA Jet Propulsion Laboratory and Carbon Mapper hide caption

Flights over landfills identify climate threats from "super emitters"

One hope for getting a better grip on methane emissions involves NASA and monitoring landfills from airplanes or space.

Riley Duren is a former engineer with the space agency's Jet Propulsion Laboratory in California who now works as a research scientist at the University of Arizona. He's also chief executive officer of Carbon Mapper , a new nonprofit consortium. Carbon Mapper announced in April it was launching "a constellation" of methane-sensing satellites with partners that include NASA, the state of California and various universities and organizations.

It's an extension of the California research praised by Thorneloe that, between 2016 and 2018, involved flying over hundreds of California methane emitters such as oil and gas operators, animal manure facilities and landfills. Published in 2019 in Nature , the study identified what Duren, the lead author, described as a small but substantial number of methane "super emitters." As many as 40% of those were landfills.

"Some of these landfills were emitting huge amounts of methane," far more than what the landfills were reporting, Duren said. "I am talking tons per hour of methane."

Many landfill operators take methane controls seriously, Duren said. But the massive leaks occur when gas capture systems are offline or workers are installing new systems. "And in other cases, it's the result of flawed management practices in terms of how the landfill is managing the daily cover," he said.

The satellites could help landfill operators find problems quickly so they can fix them, Duren said. That work is essential if the United States is going to meet the Biden administration's commitment to cut U.S. greenhouse gas emissions by 50% by 2030.

Focusing on super emitters could be an effective step. Duren said: "It's a smaller amount of the infrastructure ... that if we can target, there can be dramatic reductions over the next few years."

Buried within the Orange County Landfill are some 500 wells, which capture methane before it is emitted to the atmosphere. The Stanton Energy Center is visible in the distance. Amy Green/WMFE hide caption

EPA takes a modest step to curb landfill emissions

In May, the EPA implemented a 2016 Obama-era rule that will extend existing requirements for methane collection systems to 93 additional landfills. It lowers the emissions threshold for when landfills must install gas collection systems. Once in place, the rule will cut landfill methane emissions about 7% nationally.

The regulator also told about 40 states with about 1,600 landfills that lack EPA-approved landfill gas capture plans that they needed to get one, or the agency would enforce its own.

Biderman of the Solid Waste Association of North America said the EPA's move "should result in further reductions in emissions, continuing a trend which the industry has been investing in for decades."

To many scientists and advocates, the EPA's action falls far short of what's needed for the climate — and what's possible with existing technology. The agency's plans will have little effect on landfills that were already required to capture methane under an older rule, and the EPA should have lowered even further its threshold for requiring capture systems to make smaller landfills cut methane, said Maher of the Environmental Integrity Project.

In Maryland, for example, state officials are creating a landfill methane regulation. But if the EPA rules get adopted in Maryland, they would "only apply to four out of 40 gas-producing landfills in the state," Maher said.

The recent U.N. methane assessment goes even further. It calls for ending the practice of sending organic waste such as food scraps to landfills. Such waste should instead go to compost facilities or specially designed digesters that reduce or capture methane emissions better.

Eventually garbage such as kitchen scraps and yard waste will rot and decompose, producing a landfill gas made up in large part of methane, a greenhouse gas more potent than carbon dioxide. Amy Green/WMFE hide caption

Landfill operators respond to their high EPA rankings

For their part, some landfill operators are scrambling to show why the EPA rankings are wrong and to explain what they are doing to reduce their emissions.

At the Rumpke landfill near Cincinnati, company spokeswoman Molly Yeager explained its top EPA ranking by pointing to a second alternative emissions model the company also used with some direct measurements that yielded lower emissions estimates. She said that by default, the EPA selected the higher number. An EPA spokeswoman agreed the reporting system defaults to using the higher of the two equations, but she added that landfill operators can choose the results of the other equation if they believe it better represents conditions at the landfill.

Central Florida is among the fastest-growing regions in the nation. In Brevard County, on the state's east coast, keeping up with the booming population and volume of trash presents a challenge to controlling methane emissions, said Thomas Mulligan, assistant director of the Brevard County Solid Waste Management Department.

"I know fully well that we have been in the top 10 for a while now," said Mulligan, who oversees the Brevard landfill some 45 miles east of Orlando. "It is really tough."

Like other industry representatives, he said he believes the EPA's reporting methods overestimate emissions. But he also said Brevard County could do more to reduce landfill emissions. For example, the county could speed installation of a gas collection system in the landfill expansion, he said.

"It's a matter of capital improvement money, and it's a matter of timing," he said.

The JED landfill, situated some 54 miles south of Orlando outside bucolic St. Cloud, is part of a national group of landfills owned by Waste Connections, a Texas company. JED officials declined requests for an interview, but vice president for engineering and sustainability, Kurt Shaner, said in an email the company has been tightening up the landfill's cover system and expanding gas collection.

In Orange County, Gregory said he was recalculating the landfill's emissions and making plans to file an updated report to the EPA, using alternative options the agency provides.

"We think with our robust system," he said, "and the amount of cover and the fact that we have a number of these landfill cells closed ... those numbers are going to come down drastically."

This story is a collaboration between Inside Climate News, NPR member station WMFE in Orlando, Fla., and NPR's Investigations Desk.

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JSmol Viewer

Digitalization and digital applications in waste recycling: an integrative review.

1. Introduction

2. materials and methods, 2.1. data collection for bibliometric analysis, 2.2. data analysis, 3. bibliometric findings, 3.1. word cloud analysis, 3.2. co-word analyses of digitalization in the waste recycling literature in the period 2013–2024, 4. discussion and implications, 4.1. the following themes are most associated with the waste recycling and digitalization literature, 4.2. prominent themes related to digital tools in the waste recycling and digitalization literature, 4.3. the types of waste most relevant to the waste recycling and digitalization literature, 4.4. digital applications used in digital-based waste recycling.

5. Conclusions and Future Directions

Author contributions, institutional review board statement, data availability statement, conflicts of interest.

• Camón Luis, E.; Celma, D. Circular Economy. A Review and Bibliometric Analysis. Sustainability 2020 , 12 , 6381. [ Google Scholar ] [ CrossRef ]
• Ahmed, F.; Hasan, S.; Rana, M.S.; Sharmin, N. A conceptual framework for zero waste management in Bangladesh. Int. J. Environ. Sci. Technol. 2023 , 20 , 1887–1904. [ Google Scholar ] [ CrossRef ]
• Seyyedi, S.R.; Kowsari, E.; Gheibi, M.; Chinnappan, A.; Ramakrishna, S. A comprehensive review integration of digitalization and circular economy in waste management by adopting artificial intelligence approaches: Towards a simulation model. J. Clean. Prod. 2024 , 460 , 142584. [ Google Scholar ] [ CrossRef ]
• Jahani, N.; Sepehri, A.; Vandchali, H.R.; Tirkolaee, E.B. Application of industry 4.0 in the procurement processes of supply chains: A systematic literature review. Sustainability 2021 , 13 , 7520. [ Google Scholar ] [ CrossRef ]
• Mohamed, N.H.; Khan, S.; Jagtap, S. Modernizing Medical Waste Management: Unleashing the Power of the Internet of Things (IoT). Sustainability 2023 , 15 , 9909. [ Google Scholar ] [ CrossRef ]
• Borchard, R.; Zeiss, R.; Recker, J. Digitalization of waste management: Insights from German private and public waste management firms. Waste Manag. Res. 2022 , 40 , 775–792. [ Google Scholar ] [ CrossRef ]
• Czekała, W.; Drozdowski, J.; Łabiak, P. Modern Technologies for Waste Management: A Review. Appl. Sci. 2023 , 13 , 8847. [ Google Scholar ] [ CrossRef ]
• Torraco, R.J. Writing integrative literature reviews: Using the past and present to explore the future. Hum. Resour. Dev. Rev. 2016 , 15 , 404–428. [ Google Scholar ] [ CrossRef ]
• Gough, D.; Thomas, J.; Oliver, S. Clarifying differences between review designs and methods. Syst. Rev. 2012 , 1 , 28. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Soares, C.B.; Hoga, L.A.; Peduzzi, M.; Sangaleti, C.; Yonekura, T.; Silva, D.R. Revisão integrativa: Conceitos e métodos utilizados na enfermagem [Integrative review: Concepts and methods used in nursing]. Rev. Esc. Enferm. USP 2014 , 48 , 335–345. [ Google Scholar ] [ CrossRef ]
• Ariaa, M.; Cuccurullo, C. Bibliometrix: An r-tool for comprehensive science mapping analysis. J. Informetr. J. 2017 , 11 , 959–975. [ Google Scholar ] [ CrossRef ]
• Whittemore, R.; Knafl, K. The integrative review: Updated methodology. J. Adv. Nurs. 2005 , 5 , 546–553. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Moher, D.; Liberati, A.; Tetzlaff, J.; Altman, D.G.; Group, T.P. Preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement. PLoS Med. 2009 , 6 , e1000097. [ Google Scholar ] [ CrossRef ]
• Zupic, I.; Cater, T. Bibliometric methods in management and organization. Organ. Res. Methods 2015 , 18 , 429–472. [ Google Scholar ] [ CrossRef ]
• Van Eck, N.J.; Waltman, L. Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics 2010 , 84 , 523–538. [ Google Scholar ] [ CrossRef ]
• Birkle, C.; Pendlebury, D.A.; Schnell, J.; Adams, J. Web of Science as a data source for research on scientific and scholarly activity. Quant. Sci. Stud. 2020 , 1 , 363–376. [ Google Scholar ] [ CrossRef ]
• Atenstaedt, R. Word cloud analysis of the BJGP. Br. J. Gen. Pract. 2012 , 62 , 148. [ Google Scholar ] [ CrossRef ]
• Mulay, P.; Joshi, R.; Chaudhari, A. Distributed incremental clustering algorithms: A bibliometric and word-cloud review analysis. Sci. Technol. Lib. 2020 , 39 , 289–306. [ Google Scholar ] [ CrossRef ]
• Chen, X.; Chen, J.; Wu, D.; Xie, Y.; Li, J. Mapping the Research Trends by Co-word Analysis Based on Keywords from Funded Project. Procedia Comput. Sci. 2016 , 91 , 547–555. [ Google Scholar ] [ CrossRef ]
• De la Hoz-Correa, A.; Muñoz-Leiva, F.; Bakucz, M. Past Themes and Future Trends in Medical Tourism Research: A Co-Word Analysis. Tour. Manag. 2018 , 65 , 200–211. [ Google Scholar ] [ CrossRef ]
• Muñoz-Leiva, F.; Viedma-del-Jesús, M.I.; Sánchez-Fernández, J.; López-Herrera, A.G. An application of co-word analysis and bibliometric maps for detecting the most highlighting themes in the consumer behaviour research from a longitudinal perspective. Qual Quant. 2012 , 46 , 1077–1095. [ Google Scholar ] [ CrossRef ]
• Coulter, N.; Monarch, I.; Konda, S. Software engineering as seen through its research literature: A study in co-word analysis. J. Am. Soc. Inf. Sci. 1998 , 49 , 1206–1223. [ Google Scholar ] [ CrossRef ]
• Garfield, E. Scientography: Mapping the tracks of science. Curr. Contents Soc. Behav. Sci. 1994 , 7 , 5–10. [ Google Scholar ]
• Nizar, M.; Munir, E.; Irvan, I.; Amir, F. Examining the economic benefits of urban waste recycle based on zero waste concepts. In 1st Aceh Global Conference ; Atlantis Press: Amsterdam, The Netherlands, 2019; pp. 300–309. [ Google Scholar ]
• Blomsma, F.; Brennan, G. The Emergence of Circular Economy: A New Framing Around Prolonging Resource Productivity. J. Ind. Ecol. 2017 , 21 , 603–614. [ Google Scholar ] [ CrossRef ]
• Sarc, R.; Curtis, A.; Kandlbauer, L.; Khodier, K.; Lorber, K.E.; Pomberger, R. Digitalisation and intelligent robotics in value chain of circular economy-oriented waste management—A review. Waste Manag. 2019 , 95 , 476–492. [ Google Scholar ] [ CrossRef ]
• Czekała, W.; Pulka, J.; Jasiński, T.; Szewczyk, P.; Bojarski, W.; Jasiński, J. Waste as substrates for agricultural biogas plants: A case study from Poland. J. Water Land. Dev. 2023 , 56 , 45–50. [ Google Scholar ] [ CrossRef ]
• Kannan, D.; Khademolqorani, S.; Janatyan, N.; Alavi, S. Smart waste management 4.0: The transition from a systematic review to an integrated framework. Waste Manag. 2024 , 174 , 1–14. [ Google Scholar ] [ CrossRef ]
• Sharma, S.; Basu, N.P.; Shetti, M.; Kamali, P.; Walvekar, T.M. Aminabhavi Waste-to-energy nexus: A sustainable development. Environ. Pollut. 2020 , 267 , 115501. [ Google Scholar ] [ CrossRef ]
• Lin, K.; Zhao, Y.; Kuo, J.-H.; Deng, H.; Cui, F.; Zhang, Z.; Zhang, M.; Zhao, C.; Gao, X.; Zhou, T.; et al. Toward smarter management and recovery of municipal solid waste: A critical review on deep learning approaches. J. Clean. Prod. 2022 , 346 , 130943. [ Google Scholar ] [ CrossRef ]
• Goutam Mukherjee, A.; Ramesh Wanjari, U.; Chakraborty, R.; Renu, K.; Vellingiri, B.; George, A.; CR, S.R.; Valsala Gopalakrishnan, A. A Review on Modern and Smart Technologies for Efficient Waste Disposal and Management. J. Environ. Manag. 2021 , 297 , 113347. [ Google Scholar ] [ CrossRef ]
• Mingaleva, Z.; Vukovic, N.; Volkova, I.; Salimova, T. Waste Management in Green and Smart Cities: A Case Study of Russia. Sustain. Sci. Pract. Policy 2019 , 12 , 94. [ Google Scholar ] [ CrossRef ]
• Kumar, S.; Singh, D. Smart cities waste minimization, remanufacturing, reuse, and recycling solutions using IoT and ML. In Proceedings of the 2024 IEEE International Conference on Computing, Power and Communication Technologies (IC2PCT), Greater Noida, India, 9–10 February 2024; IEEE: Piscataway, NJ, USA, 2024; pp. 1546–1552. [ Google Scholar ]
• Shyam, G.K.; Manvi, S.S.; Bharti, P. SmartWaste Management Using Internet-of-Things (IoT). In Proceedings of the 2017 2nd International Conference on Computing and Communications Technologies (ICCCT), Chennai, India, 23–24 February 2017. [ Google Scholar ]
• Rangaswamy, A.; Moch, N.; Felten, C.; van Bruggen, G.; Wieringa, J.E.; Wirtz, J. The role of marketing in digital business platforms. J. Interact. Mark. 2020 , 51 , 72–90. [ Google Scholar ] [ CrossRef ]
• Frishammar, J.; Cenamor, J.; Cavalli-Björkman, H.; Hernell, E.; Carlsson, J. Digital strategies for two-sided markets: A case study of shopping malls. Decis. Support Syst. 2018 , 108 , 34–44. [ Google Scholar ] [ CrossRef ]
• The Digitalisation of Waste Management; Survey Reveals Uncertainty among Disposal Companies. Available online: https://www.netwaste.de/blog/waste-5-0/die-digitalisierung-der-abfallwirtschaft-umfrage-deckt-unsicherheit-bei-entsorgern-auf/#more-496 (accessed on 1 March 2024).
• Ghobakhloo, M.; Fathi, M.; Iranmanesh, M.; Maroufkhani, P.; Morales, M.E. Industry 4.0 ten years on: A bibliometric and systematic review of concepts, sustainability value drivers, and success determinants. J. Clean. Prod. 2021 , 302 , 127052. [ Google Scholar ] [ CrossRef ]
• Alidoosti, Z.; Sadegheih, A.; Govindan, K.; Pishvaee, M.S. Sustainable network design of bioenergies generation based on municipal solid waste (MSW) management under uncertainty. J. Renew. Sustain. Energy 2023 , 15 , 013103. [ Google Scholar ] [ CrossRef ]
• Usman, M.; Jahanger, A.; Makhdum, M.S.A.; Balsalobre-Lorente, D.; Bashir, A. How do financial development, energy consumption, natural resources, and globalization affect Arctic countries’ economic growth and environmental quality? An advanced panel data simulation. Energy 2022 , 241 , 122515. [ Google Scholar ] [ CrossRef ]
• Zota, R.D.; Cîmpeanu, I.A.; Dragomir, D.A.; Lungu, M.A. Practical Approach for Smart and Circular Cities: Chatbots Used in Waste Recycling. Appl. Sci. 2024 , 14 , 3060. [ Google Scholar ] [ CrossRef ]
• Ndou, V.; Rampedi, I.T. Bibliometric Analysis of Municipal Solid Waste Management Research: Global and South African Trends. Sustainability 2022 , 14 , 10229. [ Google Scholar ] [ CrossRef ]
• Luić, L.; Krešimir, L. Information Practices and Digital Perspectives of Municipal Waste Recovery Providers in Europe. Teh. Glas. 2021 , 15 , 392–400. [ Google Scholar ] [ CrossRef ]
• Matuszewska, A.; Owczuk, M.; Biernat, K. Current Trends in Waste Plastics’ Liquefaction into Fuel Fraction: A Review. Energies 2022 , 15 , 2719. [ Google Scholar ] [ CrossRef ]
• Cane, M.; Parra, C. Digital platforms: Mapping the territory of new technologies to fight food waste. Br. Food J. 2020 , 122 , 1647–1669. [ Google Scholar ] [ CrossRef ]
• Bonadonna, A.; Matozzo, A.; Giachino, C.; Peira, G. Farmer behavior and perception regarding food waste and unsold food. Br. Food J. 2019 , 121 , 89–103. [ Google Scholar ] [ CrossRef ]
• Michelini, L.; Principato, L.; Iasevoli, G. Understanding food sharing models to tackle sustainability challenges. Ecol. Econ. 2018 , 145 , 205–217. [ Google Scholar ] [ CrossRef ]
• Li, Q.; Sun, P. Research trend of construction debris reclamation home and abroad. China Build. Mater. Sci. Technol. 2009 , 4 , 119–122. [ Google Scholar ]
• Arya, S.; Kumar, S. E-waste in India at a glance: Current trends, regulations, challenges and management strategies. J. Clean. Prod. 2020 , 271 , 122707. [ Google Scholar ] [ CrossRef ]
• Farjana, M.; Fahad, A.B.; Alam, S.E.; Islam, M.M. An IoT- and Cloud-Based E-Waste Management System for Resource Reclamation with a Data-Driven Decision-Making Process. IoT 2023 , 4 , 202–220. [ Google Scholar ] [ CrossRef ]
• Mahipal, S.S.; Mayuri, K.; Manisha, N.; Shriyash, M.; Gaurav, S.; Bhaskar, C.; Rajeev, K. Effect of Electronic waste on Environmental & Human health-A Review. IOSR J. Environ. Sci. Toxicol. Food Technol. (IOSR-JESTFT) 2016 , 10 , 98–104. [ Google Scholar ]
• Ali, S.S.; Elsamahy, T.; Koutra, E.; Kornaros, M.; El-Sheekh, M.; Abdelkarim, E.A.; Zhu, D.; Sun, J. Degradation of conventional plastic wastes in the environment: A review on current status of knowledge and future perspectives of disposal. Sci. Total Environ. 2021 , 771 , 144719. [ Google Scholar ] [ CrossRef ]
• Dris, R.; Agarwal, S.; Laforsch, C. Plastics: From a success story to an environmental problem and a global challenge. Glob. Chall. 2020 , 4 , 2000026. [ Google Scholar ] [ CrossRef ]
• Wang, Z.; Huo, J.; Duan, Y. The impact of government incentives and penalties on willingness to recycle plastic waste: An evolutionary game theory perspective. Front. Environ. Sci. Eng. 2020 , 14 , 29. [ Google Scholar ] [ CrossRef ]
• Shin, S.K.; Um, N.; Kim, Y.J.; Cho, N.H.; Jeon, T.W. New policy framework with plastic waste control plan for effective plastic waste management. Sustainability 2020 , 12 , 6049. [ Google Scholar ] [ CrossRef ]
• Ding, Q.; Zhu, H. The Key to Solving Plastic Packaging Wastes: Design for Recycling and Recycling Technology. Polymers 2023 , 15 , 1485. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Rajput, S.; Singh, S.P. Industry 4.0 Model for circular economy and cleaner production. J. Clean. Prod. 2020 , 277 , 123853. [ Google Scholar ] [ CrossRef ]
• Kurniawan, T.A.; Oliveira, J.P.; Gamaralalage, P.J.D.; Nagaishi, M. City-to-city level cooperation for generating urban co-benefits: The case of technological cooperation in the waste sector between Surabaya (Indonesia) and Kitakyushu (Japan). J. Clean. Prod. 2013 , 58 , 43–50. [ Google Scholar ] [ CrossRef ]
• Hanson, V.; Ahmadi, L. Mobile applications to reduce food waste within Canada: A review. Can. Geogr./Géographe Can. 2022 , 66 , 402–411. [ Google Scholar ] [ CrossRef ]
• Gu, F.; Zhang, W.; Guo, J.; Hall, P. Exploring “Internet+ Recycling”: Mass balance and life cycle assessment of a waste management system associated with a mobile application. Sci. Total Environ. 2019 , 649 , 172–185. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Statista. Number of Monthly Active WeChat Users from 2nd Quarter 2010 to 2nd Quarter 2017 (in Millions). 2018. Available online: https://www.statista.com/statistics/255778/number-of-active-wechat-messenger-accounts/ (accessed on 15 May 2024).
• Bonino, D.; Alizo, M.T.D.; Pastrone, C.; Spirito, M. WasteApp: Smarter waste recycling for smart citizens. In Proceedings of the 2016 International Multidisciplinary Conference on Computer and Energy Science (SpliTech), Split, Croatia, 13–15 July 2016; pp. 1–6. [ Google Scholar ] [ CrossRef ]
• Ambrosio, L.; Siqueira Paulino, P.L.; Antiquera, J.; Aquino, G.P.; Cesar Vilas Boas, E. EcoWaste: A Smart Waste Platform Enabling Circular Economy. In Proceedings of the 2021 IEEE 19th Student Conference on Research and Development (SCOReD), Kota Kinabalu, Malaysia, 23–25 November 2021; pp. 411–415. [ Google Scholar ] [ CrossRef ]
• Suruliraj, B.; Olagunju, T.; Nkwo, M.S.; Orji, R. Bota: A Personalized Persuasive Mobile App for Sustainable Waste Management. In Proceedings of the International Conference on Persuasive Technology, Aalborg, Denmark, 20–23 April 2020. [ Google Scholar ]
• Nadzir, M.M.; Seowfuddin, N.F.A.S. Reduce, Reuse, Recycle (3Rs) Awareness App: Mobile Learning Application for Supporting Environmental Awareness Initiatives. In Proceedings of the 2019 IEEE Conference on e-Learning, e-Management & e- Services (IC3e), Pulau Pinang, Malaysia, 19–21 November 2019; pp. 31–34. [ Google Scholar ] [ CrossRef ]
• Naskova, J. RecycHongs: Mobile App Co-design. In Proceedings of the 2017 ACM Conference Companion Publication on Designing Interactive Systems (DIS’17 Companion), Edinburgh, UK, 10–14 June 2017; Association for Computing Machinery: New York, NY, USA, 2017; pp. 337–340. [ Google Scholar ] [ CrossRef ]
• Varghese, C.; Pathak, D.; Varde, A.S. SeVa: A Food Donation App for Smart Living. In Proceedings of the 2021 IEEE 11th Annual Computing and Communication Workshop and Conference (CCWC), Virtual, 27–30 January 2021; pp. 0408–0413. [ Google Scholar ] [ CrossRef ]
• Ballaran, P.M.; Corpuz, C.B.A.; Paras, L.A.R.; Fabito, B.S.; Rivera, E.R. Perazuhan: A Mobile Application for Solid Waste Micro-Management Framework, 2019. In Proceedings of the IEEE Student Conference on Research and Development (SCOReD), Bandar Seri Iskandar, Malaysia, 15–17 October 2019; pp. 17–20. [ Google Scholar ] [ CrossRef ]
• Harvey, J.; Smith, A.; Goulding, J.; Branco, I.I. Food Sharing, Redistribution, and Waste Reduction via Mobile Applications: A Social Network Analysis. Ind. Mark. Manag. 2019 , 88 , 437–448. [ Google Scholar ] [ CrossRef ]
• Mastorakis, G.; Kopanakis, I.; Makridis, J.; Chroni, C.; Synani, K.; Lasaridi, K.; Abeliotis, K.; Louloudakis, I.; Daliakopoulos, I.N.; Manios, T. Managing Household Food Waste with the FoodSaveShare Mobile Application. Sustainability 2024 , 16 , 2800. [ Google Scholar ] [ CrossRef ]
• Haas, R.; Aşan, H.; Doğan, O.; Michalek, C.R.; Karaca Akkan, Ö.; Bulut, Z.A. Designing and Implementing the MySusCof App-A Mobile App to Support Food Waste Reduction. Foods 2022 , 11 , 2222. [ Google Scholar ] [ CrossRef ]
• Farr-Wharton, G.; Foth, M.; Choi, J.H. EatChaFood: Challenging technology design to slice food waste production. In Proceedings of the 2013 ACM Conference on Pervasive and Ubiquitous Computing Adjunct Publication (UbiComp’13 Adjunct), Zurich, Switzerland, 8–12 September 2013; Association for Computing Machinery: New York, NY, USA, 2013; pp. 559–562. [ Google Scholar ] [ CrossRef ]
• Frost, S.; Tor, B.; Agrawal, R.; Forbes, A.G. CompostNet: An Image Classifier for Meal Waste. In Proceedings of the 2019 IEEE Global Humanitarian Technology Conference (GHTC), Seattle, WA, USA, 17–20 October 2019; pp. 1–4. [ Google Scholar ] [ CrossRef ]
• Coelho, T.R.; Hino, M.R.M.C.; Vahldick, S.M.O. The use of ICT in the informal recycling sector: The Brazilian case of Relix. Electron. J. Inf. Syst. Dev. Ctries. 2019 , 85 , e12078. [ Google Scholar ] [ CrossRef ]
• More, K.S.; Wolkersdorfer, C. Intelligent Mine Water Management Tools—eMetsi and Machine Learning GUI. Mine Water Environ. 2023 , 42 , 111–120. [ Google Scholar ] [ CrossRef ]
• Hajjdiab, H.; Anzer, A.; Tabaza, H.A.; Ahmed, W. A Food Wastage Reduction Mobile Application. In Proceedings of the 2018 6th International Conference on Future Internet of Things and Cloud Workshops (FiCloudW), Barcelona, Spain, 6–8 August 2018; pp. 152–157. [ Google Scholar ] [ CrossRef ]
• Amadi, E.C.; Chukwudebe, G.; Ayogu, I.; Ikerionwu, C.; Okafor, K.C. Implementation of a Web Application for Stakeholder Inclusion for Sustainable Waste Management. In Proceedings of the 2022 IEEE Nigeria 4th International Conference on Disruptive Technologies for Sustainable Development (NIGERCON), Lagos, Nigeria, 5–7 April 2022; pp. 1–5. [ Google Scholar ] [ CrossRef ]
• Wong, W.T.; Fernando, O.N.N.; Panchapakesan, C.; Jia, J.K.S. Foodscover: Eliminating food waste in the retail sector through technology. In Proceedings of the 2021 International Conference on Cyberworlds (CW), Caen, France, 28–30 September 2021; pp. 85–92. [ Google Scholar ] [ CrossRef ]
• Akmal, M.; Niwanputri, G.S. Spoonful: Mobile Application for Reducing Household Food Waste using Fogg Behavior Model (FBM). In Proceedings of the 2021 International Conference on Data and Software Engineering (ICoDSE), Bandung, Indonesia, 3–4 November 2021; pp. 1–6. [ Google Scholar ] [ CrossRef ]
• Morilla, J.A.R.; Bagsic, F.C.; Dela Cruz, M.K.; Patio, C.D.A.; Yabut, E.R. Foodernity: A Mobile and Web Application for Food Sharing. In Proceedings of the 2021 1st International Conference in Information and Computing Research (iCORE), Manila, Philippines, 11–12 December 2021; pp. 90–95. [ Google Scholar ] [ CrossRef ]
• Yu, Y.; Yi, S.; Nan, X.; Lo, L.Y.; Shigyo, K.; Xie, L.; Wicaksana, J.; Cheng, K.T.; Qu, H. FoodWise: Food Waste Reduction and Behavior Change on Campus with Data Visualization and Gamification. In Proceedings of the 6th ACM SIGCAS/SIGCHI Conference on Computing and Sustainable Societies (COMPASS’23), Cape Town, South Africa, 16–19 August 2023; Association for Computing Machinery: New York, NY, USA, 2023; pp. 76–83. [ Google Scholar ] [ CrossRef ]
• Kanmani, A.; Karthicka Priyadharshni, J.K.; Praharsha, S.; Mano Dharshan, M.P.; Deeraj Kumar, K.K.; Abirami, A.M. Dumpster: Predictive Model to trade Bio-waste from Agricultural Lands. In Proceedings of the 2020 International Conference on Innovative Trends in Information Technology (ICITIIT), Kottayam, India, 13–14 February 2020; pp. 1–6. [ Google Scholar ] [ CrossRef ]
• Manrique, S.; Eulogio, L.; Armas, J. Recycling: A User-Friendly Oriented Mobile and Web Solution for Generators and Recyclers in the City of Lima. In BTSym 2020, Proceedings of the 6th Brazilian Technology Symposium (BTSym’20), Campinas, Brazil, 26–28 October 2020 ; Iano, Y., Saotome, O., Kemper, G., Mendes de Seixas, A.C., Gomes de Oliveira, G., Eds.; Smart Innovation, Systems and Technologies; Springer: Cham, Switzerland, 2021; Volume 233. [ Google Scholar ] [ CrossRef ]

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Onur, N.; Alan, H.; Demirel, H.; Köker, A.R. Digitalization and Digital Applications in Waste Recycling: An Integrative Review. Sustainability 2024 , 16 , 7379. https://doi.org/10.3390/su16177379

Onur N, Alan H, Demirel H, Köker AR. Digitalization and Digital Applications in Waste Recycling: An Integrative Review. Sustainability . 2024; 16(17):7379. https://doi.org/10.3390/su16177379

Onur, Neslihan, Hale Alan, Hüsne Demirel, and Ali Rıza Köker. 2024. "Digitalization and Digital Applications in Waste Recycling: An Integrative Review" Sustainability 16, no. 17: 7379. https://doi.org/10.3390/su16177379

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NASA Discovers a Long-Sought Global Electric Field on Earth

• A rocket team reports the first successful detection of Earth’s ambipolar electric field: a weak, planet-wide electric field as fundamental as Earth’s gravity and magnetic fields.
• First hypothesized more than 60 years ago, the ambipolar electric field is a key driver of the “polar wind,” a steady outflow of charged particles into space that occurs above Earth’s poles.
• This electric field lifts charged particles in our upper atmosphere to greater heights than they would otherwise reach and may have shaped our planet’s evolution in ways yet to be explored.

Using observations from a NASA suborbital rocket, an international team of scientists has, for the first time, successfully measured a planet-wide electric field thought to be as fundamental to Earth as its gravity and magnetic fields. Known as the ambipolar electric field, scientists first hypothesized over 60 years ago that it drove how our planet’s atmosphere can escape above Earth’s North and South Poles. Measurements from the rocket, NASA’s Endurance mission , have confirmed the existence of the ambipolar field and quantified its strength, revealing its role in driving atmospheric escape and shaping our ionosphere — a layer of the upper atmosphere — more broadly.

Understanding the complex movements and evolution of our planet’s atmosphere provides clues not only to the history of Earth but also gives us insight into the mysteries of other planets and determining which ones might be hospitable to life. The paper was published Wednesday, Aug. 28, 2024, in the journal Nature .

An Electric Field Drawing Particles Out to Space

Since the late 1960s, spacecraft flying over Earth’s poles have detected a stream of particles flowing from our atmosphere into space. Theorists predicted this outflow, which they dubbed the “polar wind,” spurring research to understand its causes. 

Some amount of outflow from our atmosphere was expected. Intense, unfiltered sunlight should cause some particles from our air to escape into space, like steam evaporating from a pot of water. But the observed polar wind was more mysterious. Many particles within it were cold, with no signs they had been heated — yet they were traveling at supersonic speeds.

“Something had to be drawing these particles out of the atmosphere,” said Glyn Collinson, principal investigator of Endurance at NASA’s Goddard Space Flight Center in Greenbelt, Maryland, and lead author of the paper. Scientists suspected a yet-to-be-discovered electric field could be at work.

The hypothesized electric field, generated at the subatomic scale, was expected to be incredibly weak, with its effects felt only over hundreds of miles. For decades, detecting it was beyond the limits of existing technology. In 2016, Collinson and his team got to work inventing a new instrument they thought was up to the task of measuring Earth’s ambipolar field.

How the Ambipolar Field Works

A weak electric field in the upper atmosphere may loft charged particles into space..

Scientists theorized this electric field should begin at around 150 miles (250 kilometers) altitude, where atoms in our atmosphere break apart into negatively charged electrons and positively charged ions. Electrons are incredibly light — the slightest kick of energy could send them shooting out to space. Ions are at least 1,836 times heavier and tend to sink toward the ground. If gravity alone were in play, the two populations, once separated, would drift apart over time. But given their opposite electric charges, an electric field forms to tether them together, preventing any separation of charges and counteracting some of the effects of gravity.

This electric field is bidirectional, or “ambipolar,” because it works in both directions. Ions pull the electrons down with them as they sink with gravity. At the same time, electrons lift ions to greater heights as they attempt to escape to space, like a tiny dog tugging on its sluggish owner’s leash. The net effect of the ambipolar field is to extend the height of the atmosphere, lifting some ions high enough to escape with the polar wind. Animation credits: NASA/Conceptual Image Lab/Wes Buchanan/Krystofer Kim

Launching a Rocket from the Arctic

The team’s instruments and ideas were best suited for a suborbital rocket flight launched from the Arctic. In a nod to the ship that carried Ernest Shackleton on his famous 1914 voyage to Antarctica, the team named their mission Endurance. The scientists set a course for Svalbard, a Norwegian archipelago just a few hundred miles from the North Pole and home to the northernmost rocket range in the world.

“Svalbard is the only rocket range in the world where you can fly through the polar wind and make the measurements we needed,” said Suzie Imber, a space physicist at the University of Leicester, UK, and co-author of the paper.

On May 11, 2022, Endurance launched and reached an altitude of 477.23 miles (768.03 kilometers), splashing down 19 minutes later in the Greenland Sea. Across the 322-mile altitude range where it collected data, Endurance measured a change in electric potential of only 0.55 volts.

“A half a volt is almost nothing — it’s only about as strong as a watch battery,” Collinson said. “But that’s just the right amount to explain the polar wind.”

Hydrogen ions, the most abundant type of particle in the polar wind, experience an outward force from this field 10.6 times stronger than gravity. “That’s more than enough to counter gravity — in fact, it’s enough to launch them upwards into space at supersonic speeds,” said Alex Glocer, Endurance project scientist at NASA Goddard and co-author of the paper.

Heavier particles also get a boost. Oxygen ions at that same altitude, immersed in this half-a-volt field, weigh half as much. In general, the team found that the ambipolar field increases what’s known as the “scale height” of the ionosphere by 271%, meaning the ionosphere remains denser to greater heights than it would be without it.

“It’s like this conveyor belt, lifting the atmosphere up into space,” Collinson added.

Endurance’s discovery has opened many new paths for exploration. The ambipolar field, as a fundamental energy field of our planet alongside gravity and magnetism, may have continuously shaped the evolution of our atmosphere in ways we can now begin to explore. Because it’s created by the internal dynamics of an atmosphere, similar electric fields are expected to exist on other planets, including Venus and Mars.

“Any planet with an atmosphere should have an ambipolar field,” Collinson said. “Now that we’ve finally measured it, we can begin learning how it’s shaped our planet as well as others over time.”

By Miles Hatfield and Rachel Lense NASA’s Goddard Space Flight Center, Greenbelt, Md. Media Contact: Sarah Frazier, [email protected]

Endurance was a NASA-funded mission conducted through the Sounding Rocket Program at NASA’s Wallops Flight Facility in Virginia. The Svalbard Rocket Range is owned and operated by Andøya Space. The European Incoherent Scatter Scientific Association (EISCAT) Svalbard radar, located in Longyearbyen, made ground-based measurements of the ionosphere critical to interpreting the rocket data. The United Kingdom Natural Environment Research Council (NERC) and the Research Council of Norway (RCN) funded the EISCAT radar for the Endurance mission. EISCAT is owned and operated by research institutes and research councils of Norway, Sweden, Finland, Japan, China, and the United Kingdom (the EISCAT Associates). The Endurance mission team encompasses affiliates of the Catholic University of America, Embry-Riddle Aeronautical University, the University of California, Berkeley, the University of Colorado at Boulder, the University of Leicester, U.K., the University of New Hampshire, and Penn State University.

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Research on Film Cooling Characteristics and Mechanism of Longitudinal Corrugated Heat Shield in Afterburner

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Fu, S, Liu, H, Wang, Z, Bai, X, & Liu, C. "Research on Film Cooling Characteristics and Mechanism of Longitudinal Corrugated Heat Shield in Afterburner." Proceedings of the ASME Turbo Expo 2024: Turbomachinery Technical Conference and Exposition . Volume 7: Heat Transfer: Combustors; Heat Transfer: Film Cooling . London, United Kingdom. June 24–28, 2024. V007T11A009. ASME. https://doi.org/10.1115/GT2024-126256

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Taking into consideration both the cooling performance of the afterburner and its effect on suppressing combustion oscillations, the longitudinally corrugated heat shield has found widespread application in the afterburner. This paper employs computational fluid dynamics (CFD) and experimental methods to elucidate the influence mechanisms of key parameters such as momentum ratio, open area, and non-dimensional amplitude on the film cooling effectiveness characteristics of the corrugated plate thermal insulation structure. The results indicate that with an increase in the momentum ratio, the effectiveness of gas film cooling rises, and downstream stabilization occurs with the accumulation of the gas film. However, when the momentum ratio exceeds a certain threshold and continues to increase, excessive local momentum downstream results in a decline in gas film cooling efficiency. Additionally, as the non-dimensional amplitude increases, there is a decrease in gas film cooling efficiency, exacerbated by the increasing oscillations of corrugation. Furthermore, at a constant unit area cold air flow rate, the efficiency of gas film cooling increases with an increase in porosity.

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