Quantifying the contribution of methane diffusion and ebullition from agricultural ditches.

Agricultural ditches are significant methane (CH4) sources since substantial nutrient inputs stimulate CH4 production and emission. However, few studies have quantified the role of diffusion and ebullition pathways in total CH4 emission from agricultural ditches. This study measured the spatiotemporal variations of diffusive and ebullitive CH4 fluxes from a multi-level ditch system in a typical temperate agriculture area, and assessed their contributions to the total CH4 emission. Results illustrated that the mean annual CH4 flux in the ditch system reached 1475.1 mg m-2 d-1, among which 1376.7 mg m-2 d-1 was emitted via diffusion and 98.5 mg m-2 d-1 via ebullition. Both diffusive and ebullitive fluxes varied significantly across different types of ditches and seasons, with diffusion dominating CH4 emission in middle-size ditches and ebullition dominating in large-size ditches. Diffusion was primarily driven by large nutrient inputs from adjacent farmlands, while hydrological factors like water temperature and depth controlled ebullition. Overall, CH4 emission accounted for 86 % of the global warming potential across the ditch system, with 81 % attributed to diffusion and 5 % to ebullition. This study highlights the importance of agricultural ditches as hotspots for CH4 emissions, particularly the dominant role of the diffusion pathway.

Machine Learning Predicts the Methane Clumped Isotopologue (12CH2D2) Distributions Constrain Biogeochemical Processes and Estimates the Potential Budget.

Methane (CH4) is a matter of environmental concern; however, global methane isotopologue data remain inadequate. This is due to the challenges posed by high-resolution testing technology and the need for larger sample volumes. Here, worldwide methane clumped isotope databases (n = 465) were compiled. We compared machine-learning (ML) models and used random forest (RF) to predict new Δ12CH2D2 distributions, which cover valuable and hard-to-replicate methane clumped isotope experimental data. Our RF model yields a reliable and continuous database including ruminants, acetoclastic methane, multiple pyrolysis, and controlled experiments. We showed the effectiveness of utilizing a new data set to quantify isotopologue fractionations in biogeochemical methane processes, as well as predicting the steady-state atmospheric methane clumped isotope composition (Δ13CH3D of +2.26 ± 0.71‰ and Δ12CH2D2 of +62.06 ± 4.42‰) with notable biological contributions. Our measured summer and winter water emitted gases (n = 6) demonstrated temperature-driven seasonal microbial community evolution determined by atmospheric clumped isotope temporal variations (Δ 13CH3D ∼ -0.91 ± 0.25 ‰ and Δ12CH2D2 ∼ +3.86 ± 0.84 ‰), which in turn is relevant for future models quantifying the contribution of methane sources and sinks. Predicting clumped isotopologues translates our methane geochemical understanding into quantifiable variables for modeling that can continue to improve predictions and potentially inform global greenhouse gas emissions and mitigation policy.

Agricultural ditches are hotspots of greenhouse gas emissions controlled by nutrient input.

Agricultural ditches are pervasive in agricultural areas and are potential greenhouse gas (GHG) hotspots, since they directly receive abundant nutrients from neighboring farmlands. However, few studies measure GHG concentrations or fluxes in this particular water course, likely resulting in underestimations of GHG emissions from agricultural regions. Here we conducted a one-year field study to investigate the GHG concentrations and fluxes from typical agricultural ditch systems, which included four different types of ditches in an irrigation district located in the North China Plain. The results showed that almost all the ditches were large GHG sources. The mean fluxes were 333 µmol m-2 h-1 for CH4, 7.1 mmol m-2 h-1 for CO2, and 2.4 µmol m-2 h-1 for N2O, which were approximately 12, 5, and 2 times higher, respectively, than that in the river connecting to the ditch systems. Nutrient input was the primary driver stimulating GHG production and emissions, resulting in GHG concentrations and fluxes increasing from the river to ditches adjacent to farmlands, which potentially received more nutrients. Nevertheless, the ditches directly connected to farmlands showed lower GHG concentrations and fluxes compared to the ditches adjacent to farmlands, possibly due to seasonal dryness and occasional drainage. All the ditches covered approximately 3.3% of the 312 km2 farmland area in the study district, and the total GHG emission from the ditches in this area was estimated to be 26.6 Gg CO2-eq yr-1, with 17.5 Gg CO2, 0.27 Gg CH4, and 0.006 Gg N2O emitted annually. Overall, this study demonstrated that agricultural ditches were hotspots of GHG emissions, and future GHG estimations should incorporate this ubiquitous but underrepresented water course.

Ecological efficiency in China and its influencing factors-a super-efficient SBM metafrontier-Malmquist-Tobit model study.

Ecological problem is one of the core issues that restrain China's economic development at present, and it is urgently needed to be solved properly and effectively. Based on panel data from 30 regions, this paper uses a super efficiency slack-based measure (SBM) model that introduces the undesirable output to calculate the ecological efficiency, and then uses traditional and metafrontier-Malmquist index method to study regional change trends and technology gap ratios (TGRs). Finally, the Tobit regression and principal component analysis methods are used to analysis the main factors affecting eco-efficiency and impact degree. The results show that about 60% of China's provinces have effective eco-efficiency, and the overall ecological efficiency of China is at the superior middling level, but there is a serious imbalance among different provinces and regions. Ecological efficiency has an obvious spatial cluster effect. There are differences among regional TGR values. Most regions show a downward trend and the phenomenon of focusing on economic development at the expense of ecological protection still exists. Expansion of opening to the outside, increases in R&D spending, and improvement of population urbanization rate have positive effects on eco-efficiency. Blind economic expansion, increases of industrial structure, and proportion of energy consumption have negative effects on eco-efficiency.