The influence of soil moisture, oxygen, and temperature on naphthalene biodegradation and CO2 and CH4 effluxes
Bibliographic record
Abstract
Petroleum hydrocarbons (PHCs) are essential to the functioning of the industrialized world yet serve a potential threat to human and ecosystem health when they inadvertently enter the environment. In recent decades, recognition of natural attenuation as a viable approach to PHC remediation is increasing. Natural attenuation includes the biodegradation of PHCs through respiration, fermentation, and methanogenesis, processes which are also central to the biodegradation of natural background soil organic matter. Biodegradation of both PHCs and natural soil organic matter are a major component of the global carbon cycle and an important source of atmospheric greenhouse gases (GHGs). As a biologically mediated set of reactions, environmental factors like temperature and moisture are important controls on the rates and pathways of biodegradation. It is therefore important to understand the influence of these environmental factors on PHC biodegradation and associated carbon dioxide (CO2) and methane (CH4) effluxes to improve predictions of PHC remediation efficiency and soil GHG emissions under ongoing and future climate change. \n \nIn Chapter 2, I investigated the effect of soil moisture on PHC biodegradation kinetics, using naphthalene as a representative PHC compound. I performed microcosm incubations with naphthalene-spiked soil at 60, 80, and 100% water-filled pore space (WFPS) under oxic headspace, and at 100% WFPS under anoxic headspace. Incubations lasted 44 days. The results showed that the total naphthalene in soil decreased to below detection after Day 9, 17, and 44 in incubations at 60, 80, and 100% WFPS under oxic headspace, respectively. At 100% WFPS under anoxic headspace, total soil naphthalene concentrations decreased over time but were still detectable past Day 44. Fitting of the naphthalene data to first order decay equations revealed two distinct kinetic regimes of degradation in the oxic incubations: an initial fast regime characterized by an apparent first order rate constant on the order of 10-1 day-1 followed by dominance of a slower degradation regime. In the anoxic incubations, only the slow end-member regime was observed with a corresponding rate constant of 10-2 day-1. Porewater electron acceptor and organic acid data indicated that in the fast regime, naphthalene degradation was dominated by microbial respiration pathways, while in the slow regime fermentative pathways dominated. Results from Chapter 2 imply that spatial and temporal fluctuations in soil moisture – and the associated oxygen (O2) availability – can cause order-of-magnitude variability in the degradation kinetics of PHCs in the vadose zone. \n \nIn Chapter 3, I investigated the effect of temperature and O2 availability on CO2 and CH4 accumulations in the presence of naphthalene. I performed naphthalene-spiked microcosm incubations under oxic or anoxic headspace at temperatures of 10, 20, and 30°C. Time series data of net accumulated CH4, accumulated CO2, consumed O2, accumulated dissolved inorganic carbon (DIC), and consumed organic acids (OAs) were analyzed using Arrhenius temperature sensitivity curve-fitting. Q10 temperature sensitivity quotients were estimated from this analysis, indicating a greater temperature sensitivity of anaerobic CO2 and CH4 production processes than their aerobic equivalents. I observed that methanogenesis under anoxic conditions had a particularly high Q10 of 9. \n \nOverall, findings from this research confirm our understanding of field biodegradation rates. PHC biodegradation in oxic, drier zones is expected to be 10 times faster than in anoxic, saturated zones. The two distinct regimes of biodegradation activity identified in Chapter 2 could also be used as simplified representations of PHC biodegradation when modelling variable moisture and oxygen conditions. Chapter 3 additionally suggests that the CH4:CO2 ratio of soil carbon emissions from anoxic soils may potentially increase with warming temperature. Thus, PHC contaminated sites may see increasing GHG emissions potential, but also increasing contaminant biodegradation rates, in a warming climate, especially those located in saturated soils and cold regions. These expected alterations in soil carbon fluxes are important for the consideration of site managers concerned with site-scale carbon cycling and GHG emissions.
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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 | 0.000 | 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".