Consumption of methane by a landfill cover soil under variable moisture and temperature conditions
Bibliographic record
Abstract
Landfills are one of the largest anthropogenic sources of methane (CH4), and hot-spots of CH4 emissions in landfill cover soils can enrich microbes that oxidize CH4 to carbon dioxide (CO2). CH4 oxidation rates are modulated by multiple variables including soil moisture and temperature, although the interactive effects of these factors on CH4 oxidation rates have not been well-studied. Here, we conducted a closed-headspace batch experiment with cover soil from a former landfill in Ontario, Canada to measure CH4 consumption and CO2 efflux rates associated with variations in soil moisture and temperature simultaneously. Soil samples were incubated under a factorial design of 5 soil moisture contents ranging from 11 to 47% WFPS (water-filled pore space), and 6 temperatures ranging from 1 to 35°C. At each temperature and WFPS combination, CH4 (812 nmol) was spiked into the headspace, and headspace CH4 and CO2 concentrations were measured over 2 hours to calculate CO2 efflux and CH4 consumption rates. The maximum CO2 efflux rate was observed at the maximal WFPS and temperature conditions of this experiment (92 nmol h-1 g dry wt.-1 at 47% WFPS and 35°C), while the maximum CH4 consumption rate was observed at intermediate WFPS and temperature conditions (1.9 nmol h-1 g dry wt.-1 at 25% WFPS and 25°C). The CO2 efflux observed is primarily attributed to the oxidative degradation of soil organic matter. A diffusion-reaction model was fit to the observed data to represent the effects of temperature and soil WFPS on the CH4 consumption and CO2 efflux rates. The model predicted similar optimal conditions as those observed for both the CH4 consumption and the CO2 efflux rates. The modeling and experimental results show that the dominant controls on optimal soil moisture for CH4 consumption are moisture limitation of microbial activity and of gas (CH4 and oxygen) diffusion, versus the interactive effects of moisture limitation of gas (oxygen) diffusion and of solute mobility for CO2 effluxes. These results provide insight into how seasonal changes in soil moisture and temperature could impact CH4 oxidation rates, and therefore also net CH4 emissions, in landfill cover soils and other environments.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".