Opposing seasonal temperature dependencies of CO2 and CH4 emissions from wetlands

Research Status and Development Trend of Greenhouse Gas in Wetlands: A Bibliometric Visualization Analysis

With the intensification of global warming, wetland greenhouse gas (GHG) emissions have attracted worldwide attention. However, the scientific understanding of wetland GHGs is still limited. To gain a comprehensive and systematic understanding of the current research status and development trends in wetland GHGs. We selected 1627 papers related to wetland GHG research from the Web of Science Core Collection database and used the bibliometric visualization analysis method to reveal the annual publication, main core research forces, research hotspots, and trends in this field. The results showed that the research in this field shows a steady upward trend. United States research institutions and scholars play a key role in this field. The research on "climate change" based on three major wetland GHGs (carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O)) has been continuously gaining popularity. In recent years, "water" has become an emerging core topic. More and more studies have focused on enhancing wetland pollutant treatment capacity, improving wetland ecosystem productivity, maintaining water level stability, strengthening blue carbon sink function, exploring remote sensing applications in wetlands, and promoting wetland restoration to reduce GHG emissions. Furthermore, we discussed the influencing factors of the emission of CO2, CH4, and N2O in wetlands and summarized the potential methods to reduce GHG emissions. The findings provide scientific guidance and reference on wetland sustainable development and GHG emission reduction.

Multiple-model based simulation of urban atmospheric methane concentration and the attributions to its seasonal variations: A case study in Hangzhou megacity, China

Cities are treated as global methane (CH4) emission hotspots and the monitoring of atmospheric CH4 concentration in cities is necessary to evaluate anthropogenic CH4 emissions. However, the continuous and in-situ observation sites within cities are still sparsely distributed in the largest CH4 emitter as of China, and although obvious seasonal variations of atmospheric CH4 concentrations have been observed in cities worldwide, questions regarding the drivers for their temporal variations still have not been well addressed. Therefore, to quantify the contributions to seasonal variations of atmospheric CH4 concentrations, year-round CH4 concentration observations from 1st December 2020 to 30th November 2021 were conducted in Hangzhou megacity, China, and three models were chosen to simulate urban atmospheric CH4 concentration and partition its drivers including machine learning based Random Forest (RF) model, atmospheric transport processes based numerical model (WRF-STILT), and regression analysis based Multiple Linear Regression (MLR) model. The findings are as follows: (1) the atmospheric CH4 concentration showed obvious seasonal variations and were different with previous observations in other cities, the seasonality were 5.8 ppb, 21.1 ppb, and 50.1 ppb between spring-winter, summer-winter and autumn-winter, respectively, where the CH4 background contributed by -8.1 ppb, -44.6 ppb, and -1.0 ppb, respectively, and the CH4 enhancements contributed by 13.9 ppb, 65.7 ppb, and 51.1 ppb. (2) The RF model showed the highest accuracy in simulating CH4 concentrations, followed by MLR model and WRF-STILT model. (3) We further partition contributions from different factors, results showed the largest contribution was from temperature-induced increase in microbial process based CH4 emissions including waste treatment and wetland, which ranged from 38.1 to 76.3 ppb when comparing different seasons with winter. The second largest contribution was from seasonal boundary layer height (BLH) variations, which ranged from -13.4 to -6.3 ppb. And the temperature induced seasonal CH4 emission and enhancement variations were overwhelming BLH changes and other meteorological parameters.

Elevating water table reduces net ecosystem carbon losses from global drained wetlands

Drained wetlands are thought to be carbon (C) source hotspots, and rewetting is advocated to restore C storage in drained wetlands for climate change mitigation. However, current assessments of wetland C balance mainly focus on vertical fluxes between the land and atmosphere, frequently neglecting lateral carbon fluxes and land-use effects. Here, we conduct a global synthesis of 893 annual net ecosystem C balance (NECB) measures that include net ecosystem exchange of CO2, along with C input via manure fertilization, and C removal through biomass harvest or hydrological exports of dissolved organic and inorganic carbon, across wetlands of different status and land uses. We find that elevating water table substantially reduces net ecosystem C losses, with the annual NECB decreasing from 2579 (95% interval: 1976 to 3214) kg C ha-1 year-1 in drained wetlands to -422 (-658 to -176) kg C ha-1 year-1 in natural wetlands, and to -934 (-1532 to -399) kg C ha-1 year-1 in rewetted wetlands globally. Climate, land-use history, and time since water table changes introduce variabilities, with drainage for (sub)tropical agriculture or forestry uses showing high annual C losses, while the net C losses from drained wetlands can continue to affect soil C pools for several decades. Rewetting all types of drained wetlands is needed, particularly for those formerly agriculture-used (sub)tropical wetlands where net ecosystem C losses can be largely reduced. Our findings suggest that elevating water table is an important initiative to reduce C losses in degraded wetlands, which could contribute to policy decisions for managing wetlands to enhance their C sequestration.

Methane emissions and microbial communities under differing flooding conditions and seasons in littoral wetlands of urban lake

Wetlands are the largest natural sources of methane (CH4) emissions worldwide. Littoral wetlands of urban lakes represent an ecotone between aquatic and terrestrial ecosystems and are strongly influenced by water levels, environmental conditions, and anthropogenic activities. Despite these littoral zones being potential "hotspots" of CH4 emissions, the status of CH4 emissions therein and the role of physicochemical properties and microbial communities regulating these emissions remain unclear. This study compared the CH4 fluxes, physicochemical properties, and CH4-cycling microbial communities (methanogens and methanotrophs) of three zones (a non-flooded supralittoral zone, a semi-flooded eulittoral zone, and a flooded infralittoral zone) in the littoral wetlands of Lake Pipa, Jiangsu Province, China, for two seasons (summer and winter). The eulittoral zone was a CH4 source (median: 11.49 and 0.02 mg m-2 h-1 in summer and winter, respectively), whereas the supralittoral zone acted as a CH4 sink (median: -0.78 and -0.09 mg m-2 h-1 in summer and winter, respectively). The infralittoral zone shifted from CH4 sink to source between the summer (median: -10.65 mg m-2 h-1) and winter (median: 0.11 mg m-2 h-1). The analysis of the functional genes of methanogenesis (mcrA) and methanotrophy (pmoA) and path analysis showed that CH4 fluxes were strongly regulated by biotic factors (abundance of the mcrA gene and alpha diversity of CH4-cycling microbial communities) and abiotic factors (ammonia nitrogen, moisture, and soil organic carbon). In particular, biotic factors had a major influence on the variation in the CH4 flux, whereas abiotic factors had a minor influence. Our findings provide novel insights into the spatial and seasonal variations in CH4-cycling microbial communities and identify the key factors influencing CH4 fluxes in littoral wetlands. These results are important for managing nutrient inputs and regulating the hydrological regimes of urban lakes.

Including Methane Emissions from Agricultural Ponds in National Greenhouse Gas Inventories

Agricultural ponds are a significant source of greenhouse gases, contributing to the ongoing challenge of anthropogenic climate change. Nations are encouraged to account for these emissions in their national greenhouse gas inventory reports. We present a remote sensing approach using open-access satellite imagery to estimate total methane emissions from agricultural ponds that account for (1) monthly fluctuations in the surface area of individual ponds, (2) rates of historical accumulation of agricultural ponds, and (3) the temperature dependence of methane emissions. As a case study, we used this method to inform the 2024 National Greenhouse Gas Inventory reports submitted by the Australian government, in compliance with the Paris Agreement. Total annual methane emissions increased by 58% from 1990 (26 kilotons CH4 year-1) to 2022 (41 kilotons CH4 year-1). This increase is linked to the water surface of agricultural ponds growing by 51% between 1990 (115 kilo hectares; 1,150 km2) and 2022 (173 kilo hectares; 1,730 km2). In Australia, 16,000 new agricultural ponds are built annually, expanding methane-emitting water surfaces by 1,230 ha yearly (12.3 km2 year-1). On average, the methane flux of agricultural ponds in Australia is 0.238 t CH4 ha-1 year-1. These results offer policymakers insights into developing targeted mitigation strategies to curb these specific forms of anthropogenic emissions. For instance, financial incentives, such as carbon or biodiversity credits, can mobilize widespread investments toward reducing greenhouse gas emissions and enhancing the ecological and environmental values of agricultural ponds. Our data and modeling tools are available on a free cloud-based platform for other countries to adopt this approach.

More enhanced non-growing season methane exchanges under warming on the Qinghai-Tibetan Plateau

Uncertainty in methane (CH4) exchanges across wetlands and grasslands in the Qinghai-Tibetan Plateau (QTP) is projected to increase due to continuous permafrost degradation and asymmetrical seasonal warming. Temperature plays a vital role in regulating CH4 exchange, yet the seasonal patterns of temperature dependencies for CH4 fluxes over the wetlands and grasslands on the QTP remain poorly understood. Here, we demonstrated a stronger warming response of CH4 exchanges during the non-growing season compared to the growing season on the QTP. Analyzing 9745 daily observations and employing four methods -regression fitting of temperature-CH4 flux, temperature dependence calculations, field-based and model-based control experiments-we found that warming intensified CH4 emissions in wetlands and uptakes in grasslands. Specifically, the average reaction intensity in the non-growing season surpasses that in the growing season by 1.89 and 4.80 times, respectively. This stronger warming response of CH4 exchanges during the non-growing season significantly increases the regional CH4 exchange on the QTP. Our research reveals that CH4 exchanges in the QTP have a higher warming sensitivity in non-growing seasons, which meanwhile are dominated by a larger warming rate than the annual average. The combined effects of these two factors will significantly alter the CH4 source/sink on the QTP. Neglecting these impacts would lead to inaccurate estimations of CH4 source/sink over the QTP under climate warming.