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Recent studies suggest that hypolimnetic respiration may be responsible for greenhouse gas (GHG) emissions from deep reservoirs. Currently, quantitative evaluation of aerobic vs. anaerobic processes and priming (enhanced processing of organic matter due to the addition of labile carbon) in regulating GHG production and emissions across the reservoir‐downstream continuum remains largely unknown. High‐resolution, annual time‐series observations in a large, subtropical reservoir (Shuikou) experiencing seasonal hypoxia in southeast China indicate that aerobic hypolimnetic CO2 production dominated in most periods of the stratified spring/summer with higher rates at higher temperatures. In addition, anaerobic production of hypolimnetic CO2 occurred in the late stratified spring/summer period, which stimulated hypolimnetic production of CH4 and N2O. Incubation experiments showed that priming in spring enhanced both aerobic and anaerobic production of excess GHGs. A late spring flood event generated the highest daily efflux of CO2 through the flushing of GHG‐enriched hypolimnion waters. Turbine degassing contributed 59%, 93%, and 63% of annual CO2, CH4, and N2O effluxes, respectively. Moreover, annual downstream GHG emissions were similar to those in the transition/lacustrine zone of the Shuikou reservoir. Diurnal variation observations revealed net CO2 emissions even during algal bloom seasons. The reservoir‐downstream river continuum was a year‐round source of GHGs (218.5 ± 18.9 Gg CO2‐equivalent yr−1; CO2 contributed 91%). However, the loss of oxygen also leads to increased production and storage of recalcitrant dissolved organic carbon (RDOC). Thus, identifying mechanisms controlling both GHG emissions and RDOC production is crucial to constrain the carbon neutrality issue of hydroelectric reservoirs in the context of climate change mitigation strategies. [ABSTRACT FROM AUTHOR]

Understanding the impact of different external forcings on regional temperature changes in China and constraining future changes is important for formulating targeted climate mitigation policies. We conducted a detection and attribution analysis to examine the effects of different external forcings on the differences in warming across China and seven subregions. This analysis spanned from 1965 to 2014 and used observations as well as data from the Coupled Model Intercomparison Project Phase 6 (CMIP6) models. The signals of anthropogenic (ANT) forcing can be detected and separated from natural (NAT) forcing in all regions, and the effect of greenhouse gases are found to account for a significant portion of the observed warming in these regions. In the Yangtze River Basin, southeast China and southwest China, the observed warming trends are lower than other subregions. This can be attributed to the relatively weak impact of greenhouse gases, resulting in a temperature increase of only 0.51°C in the Yangtze River Basin, which accounts for 48.57% of the observed warming. While both southeast China and southwest China experience a cooling effect of aerosols, leading to temperature decreases of 0.20 and 0.53°C, respectively, even though the signal of aerosol forcing is not detected. In terms of future projection, the use of attribution constraint approach effectively corrects the biases of the CMIP6 model simulation and reduces projection uncertainty in China and most subregions under the new shared socioeconomic pathway (SSP) SSP2‐4.5 and SSP5‐8.5. The Tibetan Plateau has the largest reduction of the uncertainty range among seven subregions, with the decrease of 39.02% under SSP2‐4.5 scenario in the long‐term (2081–2098). In addition, north China and southwest China will experience the highest and lowest warming in the long‐term (2081–2098) after attribution constraints, increasing by 3.41 and 2.14°C, respectively, under SSP2‐4.5 scenario. [ABSTRACT FROM AUTHOR]

Carbon tax is a policy instrument that facilitate the phase-out of coal as a chemical feedstock and help China achieve an early carbon peak. However, the policy design is challenged by the complex dynamics of global warming potentials (GWP) from upstream methane emissions, which have a short atmospheric lifetime but a high climate impact. In this study, we compared the life-cycle GWP of two propylene production routes in China: Coal-to-Olefin (CTO) and Propane Dehydrogenation (PDH). We also conducted a cost-profit analysis that incorporates the carbon tax, considering uncertainties in the dynamic radiative forcing of methane. We derived a range of optimal carbon tax rates that can enhance the economic competitiveness of low-carbon propylene routes PDH and discourage the expansion of coal-fed CTO propylene routes. Results show that, for the propylene sector in China, the carbon tax rate should be between 86 and 600 Chinese Yuan (CNY) or 12–84 US dollars (USD) per ton of carbon dioxide equivalent (CO2e), which corresponds to 1–10% of the typical propylene price in the Chinese market. Our study provides spatiotemporal insights into the carbon tax for China's propylene sector to decarbonize and control upstream methane emissions. Since propylene is one of the key raw materials for chemical (e.g., plastic) productions, our analysis contributes to the climate benefits of global chemical trade. • Carbon tax contributes to controlling upstream methane emissions from coal-based chemical production. • Time-horizon is crucial for taxing carbon, especially as short-lived greenhouse gas emissions affect propylene producers' profits. • Carbon tax is necessary at provincial scale since the intensity of methane emissions from coal and propane feedstock supply chains vary regionally. [ABSTRACT FROM AUTHOR]

Natural climate solutions (NCS) offer immediate and cost-effective ways to tackle the climate crisis by transforming atmospheric carbon to soil carbon or avoiding greenhouse gas emissions. However, the climate mitigation potential and economic costs of NCS for cropping systems in China remain inconclusive. The major objectives of this study are (i) to estimate the NGHG reduction potential across Chinese main cropping systems caused by NCS, (ii) to quantify the economic costs of adopting optimal management with different abatement potentials. The Denitrification-Decomposition (DNDC) model was used to estimate the NGHG, including SOC sequestration, N 2 O emissions, and CH 4 emissions. After calibration, we ran the DNDC model with derived data at municipality-level. We estimated the NGHG under current management, adopting optimal management individually, and integrated optimal management to project the maximum NGHG reduction potential caused by NCS. We used the marginal abatement cost method to estimate the economic cost. The four natural climate solutions, N fertilization management (NFM), straw returning management (SRM), tillage management (TM), and rice irrigation management (RIM) can reduce national NGHG in main cropping systems by approximately 118.8 Tg CO 2 -eq, 116.3 Tg CO 2 -eq, 35.2 Tg CO 2 -eq, and 74.4 Tg CO 2 -eq, respectively. The integrated optimal management may potentially reduce NGHG by 256.9 Tg CO 2 -eq, equivalent to 90.2% of current NGHG, and 80% of which can be realized at the price of CN¥ 285 (Mg CO 2 -eq)−1. We further identify the priority NCS for different crops and regions and conclude that nitrogen fertilization management should be the priority NCS at the national level. Our findings highlight the great potential of NGHG reduction by adopting NCS precisely and the importance of optimizing agricultural management as a whole, and they will help policy makers to develop smart-agriculture in China. [Display omitted] • Estimating net greenhouse gas emissions (NGHG) reduction potentials of agriculture. • IPCC recommended tier 3 method was applied for seven cropping systems in China. • The integrated optimal management may potentially reduce NGHG by 256.9 Tg CO 2 -eq. • 80% of NGHG mitigation can be realized at the price of CN¥ 285 (Mg CO 2 -eq)−1. • The priority NCS was identified for different crops and regions. [ABSTRACT FROM AUTHOR]

Tillage practices have major impacts on soil properties, grain yield, soil carbon sequestration, and greenhouse gas emissions. Conservation tillage is an agriculture practice aiming to minimize soil disturbance and protect soil structure. It is reported that more and more croplands are being converted from conventional tillage to conservation tillage in China. However, the information is lacking as to where and when conservation tillage practice is implemented at a regional and national scale. The objectives of this study are 1) to develop a new framework for classifying tillage practices with a random forest model and Google Earth Engine platform to overcome the limitations in mapping tillage practices across China; and 2) to map the spatiotemporal patterns of tillage practices across Chinese croplands from 2016 to 2020. We generated a 1 km grid dataset for tillage practices across Chinese croplands during 2016–2020 based on Sentinel-2 imagery. First, we generated two ground reference sample pools about tillage practices based on literature review and high-resolution maps. Then, we produced Sentinel-2 features during the tillage period by composting 18 bands related to the ratios of returned crop residues. Next, we trained an optimal random forest (RF) classifier by conducting a cross-validation. Finally, we applied the optimal RF classifier to composited features to produce tillage maps from 2016 to 2020. The validation with ground reference samples shows that the classification results have an overall accuracy of 0.80. Comparisons at a provincial scale show the estimated proportion of conservation tillage is significantly correlated with statistic data with R2 being 0.88. Results show that conservation tillage practice is adopted in about 36% of Chinese croplands, mainly distributed in northeast China, northwest China, and the North China Plain. The proportion of conservation tillage ranged from 29% to 40% during 2016–2020 although with a large spatial heterogeneity. This study develops a sound framework to map tillage practices and provides more details about the spatiotemporal patterns of tillage practices, supporting regional planning of agricultural management and climate change mitigation. [ABSTRACT FROM AUTHOR]