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China is among the top nitrous oxide (N2O)-emitting countries, but existing national inventories do not provide full-scale emissions including both natural and anthropogenic sources. We conducted a four-decade (1980 – 2020) of comprehensive quantification of Chinese N2O inventory using empirical emission factor method for anthropogenic sources and two up-to-date process-based models for natural sources. Total N2O emissions peaked at 2287.4 (1774.8 – 2799.9) Gg N2O yr−1 in 2018, and agriculture-developed regions, like the East, Northeast, and Central, were the top N2O-emitting regions. Agricultural N2O emissions have started to decrease after 2016 due to the decline of nitrogen fertilization applications, while, industrial and energetic sources have been dramatically increasing after 2005. N2O emissions from agriculture, industry, energy, and waste represented 49.3%, 26.4%, 17.5%, and 6.7% of the anthropogenic emissions in 2020, respectively, which revealed that it is imperative to prioritize N2O emission mitigation in agriculture, industry, and energy. Natural N2O sources, dominated by forests, have been steadily growing from 317.3 (290.3 – 344.1) Gg N2O yr−1 in 1980 to 376.2 (335.5 – 407.2) Gg N2O yr−1 in 2020. Our study produces a Full-scale Annual N2O dataset in China (FAN2020), providing emergent counting to refine the current national N2O inventories. [ABSTRACT FROM AUTHOR]

[Display omitted] As one of the world's largest emitters of greenhouse gases, China has set itself the ambitious goal of achieving carbon peaking and carbon neutrality. Therefore, it is crucial to quantify the magnitude and trend of sources and sinks of atmospheric carbon dioxide (CO 2), and to monitor China's progress toward these goals. Using state-of-the-art datasets and models, this study comprehensively estimated the anthropogenic CO 2 emissions from energy, industrial processes and product use, and waste along with natural sources and sinks of CO 2 for all of China during 1980–2021. To recognize the differences among various methods of estimating greenhouse emissions, the estimates are compared with China's National Greenhouse Gas Inventories (NGHGIs) for 1994, 2005, 2010, 2012, and 2014. Anthropogenic CO 2 emissions in China have increased by 7.39 times from 1980 to 12.77 Gt CO 2 a−1 in 2021. While benefiting from ecological projects (e.g., Three Norths Shelter Forest System Project), the land carbon sink in China has reached 1.65 Gt CO 2 a−1 averaged through 2010–2021, which is almost 15.81 times that of the carbon sink in the 1980s. On average, China's terrestrial ecosystems offset 14.69% ± 2.49% of anthropogenic CO 2 emissions through 2010–2021. Two provincial-level administrative regions of China, Xizang and Qinghai, have achieved carbon neutrality according to our estimates, but nearly half of the administrative regions of China have terrestrial carbon sink offsets of less than 10% of anthropogenic CO 2 emissions. This study indicated a high level of consistency between NGHGIs and various datasets used for estimating fossil CO 2 emissions, but found notable differences for land carbon sinks. Future estimates of the terrestrial carbon sinks of NGHGIs urgently need to be verified with process-based models which integrate the comprehensive carbon cycle processes. [ABSTRACT FROM AUTHOR]

Grazing is a significant anthropogenic disturbance to grasslands, impacting their function and composition, and affecting carbon budgets and greenhouse gas emissions. However, accurate evaluations of grazing impacts are limited by the absence of long-term high-resolution grazing intensity data (i.e., the number of livestock per unit area). This study utilized census livestock data and a satellite-based vegetation index to develop the first Long-term High-resolution Grazing Intensity (LHGI) dataset of grassland in seven pastoral provinces in western China from 1980 to 2022. The LHGI dataset effectively captured spatial variations in grazing intensity, with validation at 73 sites showing a correlation coefficient (R 2 ) of 0.78. The county-level validation showed an averaged R 2 values of 0.73 ± 0.03 from 1980 to 2022. This dataset serves as a vital resource for estimating grassland carbon cycling and livestock system CH 4 emissions, as well as contributing to grassland management., (© 2024. The Author(s).)