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Particulate matter with an aerodynamic diameter of less than 1 μm (PM 1.0 ) can be extremely hazardous to human health, so it is imperative to accurately estimate the spatial and temporal distribution of PM 1.0 and analyze the impact of related policies on it. In this study, a stacking generalization model was trained based on aerosol optical depth (AOD) data from satellite observations, combined with related data affecting aerosol concentration such as meteorological data and geographic data. Using this model, the PM 1.0 concentration distribution in China during 2016-2019 was estimated, and verified by comparison with ground-based stations. The coefficient of determination (R 2 ) of the model is 0.94, and the root-mean-square error (RMSE) is 8.49 μg/m 3 , mean absolute error (MAE) is 4.10 μg/m 3 , proving that the model has a very high performance. Based on the model, this study analyzed the PM 1.0 concentration changes during the heating period (November and December) in the regions where the "coal-to-gas" policy was implemented in China, and found that the proposed "coal-to-gas" policy did reduce the PM 1.0 concentration in the implemented regions. However, the lack of natural gas due to the unreasonable deployment of the policy in the early stage caused the increase of PM 1.0 concentration. This study can provide a reference for the next step of urban air pollution policy development., Competing Interests: Declaration of competing interest Dear editors, all the authors (Tianqi Shi, Yanran Peng, Xin Ma, Ge Han, Zhipeng Pei, Siwei Li, Huiqin Mao, Xingying Zhang, Wei Gong) declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Response actions to the coronavirus disease 2019 perturbed economies and carbon dioxide (CO 2 ) emissions. The Omicron variant that emerged in 2022 caused more substantial infections than in 2020 and 2021 but it has not yet been ascertained whether Omicron interrupted the temporary post-2021 rebound of CO 2 emissions. Here, using satellite nitrogen dioxide observations combined with atmospheric inversion, we show a larger decline in China's CO 2 emissions between January and April 2022 than in those months during the first wave of 2020. China's CO 2 emissions are estimated to have decreased by 15% (equivalent to -244.3 million metric tons of CO 2 ) during the 2022 lockdown, greater than the 9% reduction during the 2020 lockdown. Omicron affected most of the populated and industrial provinces in 2022, hindering China's CO 2 emissions rebound starting from 2021. China's emission variations agreed with downstream CO 2 concentration changes, indicating a potential to monitor CO 2 emissions by integrating satellite and ground measurements.

Extreme climate events constitute a major risk to global food production. Among these, extreme rainfall is often dismissed from historical analyses and future projections, the impacts and mechanisms of which remain poorly understood. Here we used long-term nationwide observations and multi-level rainfall manipulative experiments to explore the magnitude and mechanisms of extreme rainfall impacts on rice yield in China. We find that rice yield reductions due to extreme rainfall were comparable to those induced by extreme heat over the last two decades, reaching 7.6 ± 0.9% (one standard error) according to nationwide observations and 8.1 ± 1.1% according to the crop model incorporating the mechanisms revealed from manipulative experiments. Extreme rainfall reduces rice yield mainly by limiting nitrogen availability for tillering that lowers per-area effective panicles and by exerting physical disturbance on pollination that declines per-panicle filled grains. Considering these mechanisms, we projected ~8% additional yield reduction due to extreme rainfall under warmer climate by the end of the century. These findings demonstrate that it is critical to account for extreme rainfall in food security assessments., (© 2023. The Author(s), under exclusive licence to Springer Nature Limited.)

As the most biodiversity-rich part of the protected areas system, habitats within the pilot national parks have long been threatened by drastic human-induced land use and land cover changes. The growing concern about habitat loss has spurred China's national park project to shift from pilot to construction phase with the official establishment of China's first group of national parks (CFGNPs) in October 2021. But far too little attention has been paid to the synergistic work concerning the habitat quality (HQ) dynamics of all five national parks. Here, the InVEST model, combined with a satellite-derived land use and land cover product and a hot spot analysis (HSA) method, was used to investigate the HQ dynamics at the park- and pixel-scale within the CFGNPs. Our results demonstrate that the past ecological conservation practices within national parks have been unpromising, especially in Giant Panda National Park, Northeast China Tiger and Leopard National Park (NCTL), and Wuyi Mountain National Park (WYM), where HQ as a whole showed a significant decline. Furthermore, more than half of Hainan Tropical Rainforest National Park (87.2%), WYM (77.4%), and NCTL (52.9%) showed significant HQ degradation from 1980 to 2019. Besides, increasing trends in the area shares of HQ degraded pixels were observed in all five national parks from 1980-1999 to 2000-2019. The HSA implied that the hot spots of high HQ degradation rates tend to occur in areas closer to urban settlements or on the edge of national parks, where human activities are intensive. Despite these disappointing findings, we highlighted from the observed local successes and the HQ plateau that the construction of CFGNPs is expected to reverse the deteriorating HQ trends. Thus, we concluded our paper by proposing an HSA-based regulatory zoning scheme that includes five subzones to guide the future construction of China's national park system., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Global vegetation greening has been widely confirmed in previous studies, yet the changes in the velocity of green-up in each month of green-up period (GUP) remains unclear. Here, we defined the velocity of vegetation green-up as V NDVI (the monthly increase of Normalized Difference Vegetation Index [NDVI] during GUP) and further explored its response to climate change in middle-high-latitude Northern Hemisphere. We found that in early GUP, V NDVI generally showed positive trends from 1982 to 2015, whereas in late GUP, it showed negative trends in most areas. Such contrasting trends were mainly due to a positive temperature effect on V NDVI in early GUP, but this effect turned negative in late GUP. The increase of soil moisture also in part explained the accelerated vegetation green-up, especially in the arid and semi-arid ecosystems of inland areas. Our analyses also indicate that the first month of the GUP was the key stage impacting vegetation greenness in summer. Future warming may continuously speed up the early growth of vegetation, altering the seasonal trajectory of vegetation and its feedbacks to the Earth system., (© 2022 John Wiley & Sons Ltd.)

Quantification of fossil fuel carbon dioxide emissions (CEs) at fine space and time resolution is a critical need in climate change research and carbon cycle. Quantifying changes in spatiotemporal patterns of urban CEs is important to understand carbon cycle and development carbon reduction strategies. The existing spatial data of CEs have low resolution and cannot distinguish the distribution characteristics of CEs of different emission sectors. This study quantified CEs from 15 types of energy sources, including residential, tertiary, and industrial sectors in Shanghai. Additionally, we mapped the CEs for the three sectors using point of interest data and web crawler technology, which is different from traditional methods. At a resolution of 30 m, the improved CEs data has a higher spatial resolution than existing studies. The spatial distribution of CEs based on this study has higher spatial resolution and more details than that based on traditional methods, and can distinguish the spatial distribution characteristics of different sectors. The results indicated that there was a consistent increase in CEs during 2000-2015, with a low rate of increase during 2009-2015. The intensity of CEs increased significantly in the outskirts of the city, mainly due to industrial transfer. Moreover, intensity of CEs reduced in city center. Technological progress has promoted the improvement of energy efficiency, and there has been a decoupling between the economic development and CEs in the city was observed during in 2000-2015., (© 2022. The Author(s).)

Trade-offs between tree planting programs and wetland conservation are unclear. Here, we employ satellite-derived inundation data and a process-based land surface model (ORCHIDEE-Hillslope) to investigate the impacts of tree planting on wetland dynamics in China for 2000-2016 and the potential impacts of near-term tree planting activities for 2017-2035. We find that 160,000-190,000 km 2 (25.3-25.6%) of historical tree planting over wetland grid cells has resulted in 1,300-1,500 km 2 (0.3-0.4%) net wetland loss. Compared to moist southern regions, the dry northern and western regions show a much higher sensitivity of wetland reduction to tree planting. With most protected wetlands in China located in the drier northern and western basins, continuing tree planting scenarios are projected to lead to a > 10% wetland loss relative to 2000 across 4-8 out of 38 national wetland nature reserves. Our work shows how spatial optimization can help the balance of tree planting and wetland conservation targets., (© 2022. The Author(s).)

The ongoing development of the Global Carbon Project (GCP) global methane (CH 4 ) budget shows a continuation of increasing CH 4 emissions and CH 4 accumulation in the atmosphere during 2000-2017. Here, we decompose the global budget into 19 regions (18 land and 1 oceanic) and five key source sectors to spatially attribute the observed global trends. A comparison of top-down (TD) (atmospheric and transport model-based) and bottom-up (BU) (inventory- and process model-based) CH 4 emission estimates demonstrates robust temporal trends with CH 4 emissions increasing in 16 of the 19 regions. Five regions-China, Southeast Asia, USA, South Asia, and Brazil-account for >40% of the global total emissions (their anthropogenic and natural sources together totaling >270 Tg CH 4  yr -1 in 2008-2017). Two of these regions, China and South Asia, emit predominantly anthropogenic emissions (>75%) and together emit more than 25% of global anthropogenic emissions. China and the Middle East show the largest increases in total emission rates over the 2000 to 2017 period with regional emissions increasing by >20%. In contrast, Europe and Korea and Japan show a steady decline in CH 4 emission rates, with total emissions decreasing by ~10% between 2000 and 2017. Coal mining, waste (predominantly solid waste disposal) and livestock (especially enteric fermentation) are dominant drivers of observed emissions increases while declines appear driven by a combination of waste and fossil emission reductions. As such, together these sectors present the greatest risks of further increasing the atmospheric CH 4 burden and the greatest opportunities for greenhouse gas abatement., (© 2021 The Authors. Global Change Biology published by John Wiley & Sons Ltd. This article has been contributed to by US Government employees and their work is in the public domain in the USA.)

The Chinese "coal-to-gas" and "coal-to-electricity" strategies aim at reducing dispersed coal consumption and related air pollution by promoting the use of clean and low-carbon fuels in northern China. Here, we show that on top of meteorological influences, the effective emission mitigation measures achieved an average decrease of fine particulate matter (PM 2.5 ) concentrations of ∼14% in Beijing and surrounding areas (the "2+26" pilot cities) in winter 2017 compared to the same period of 2016, where the dispersed coal control measures contributed ∼60% of the total PM 2.5 reductions. However, the localized air quality improvement was accompanied by a contemporaneous ∼15% upsurge of PM 2.5 concentrations over large areas in southern China. We find that the pollution transfer that resulted from a shift in emissions was of a high likelihood caused by a natural gas shortage in the south due to the coal-to-gas transition in the north. The overall shortage of natural gas greatly jeopardized the air quality benefits of the coal-to-gas strategy in winter 2017 and reflects structural challenges and potential threats in China's clean-energy transition., Competing Interests: The authors declare no competing interest., (Copyright © 2020 the Author(s). Published by PNAS.)

Changes in CO 2 emissions during the COVID-19 pandemic have been estimated from indicators on activities like transportation and electricity generation. Here, we instead use satellite observations together with bottom-up information to track the daily dynamics of CO 2 emissions during the pandemic. Unlike activity data, our observation-based analysis deploys independent measurement of pollutant concentrations in the atmosphere to correct misrepresentation in the bottom-up data and can provide more detailed insights into spatially explicit changes. Specifically, we use TROPOMI observations of NO 2 to deduce 10-day moving averages of NO x and CO 2 emissions over China, differentiating emissions by sector and province. Between January and April 2020, China's CO 2 emissions fell by 11.5% compared to the same period in 2019, but emissions have since rebounded to pre-pandemic levels before the coronavirus outbreak at the beginning of January 2020 owing to the fast economic recovery in provinces where industrial activity is concentrated., (Copyright © 2020 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution License 4.0 (CC BY).)

The nitrogen cycle has been radically changed by human activities 1 . China consumes nearly one third of the world's nitrogen fertilizers. The excessive application of fertilizers 2,3 and increased nitrogen discharge from livestock, domestic and industrial sources have resulted in pervasive water pollution. Quantifying a nitrogen 'boundary' 4 in heterogeneous environments is important for the effective management of local water quality. Here we use a combination of water-quality observations and simulated nitrogen discharge from agricultural and other sources to estimate spatial patterns of nitrogen discharge into water bodies across China from 1955 to 2014. We find that the critical surface-water quality standard (1.0 milligrams of nitrogen per litre) was being exceeded in most provinces by the mid-1980s, and that current rates of anthropogenic nitrogen discharge (14.5 ± 3.1 megatonnes of nitrogen per year) to fresh water are about 2.7 times the estimated 'safe' nitrogen discharge threshold (5.2 ± 0.7 megatonnes of nitrogen per year). Current efforts to reduce pollution through wastewater treatment and by improving cropland nitrogen management can partially remedy this situation. Domestic wastewater treatment has helped to reduce net discharge by 0.7 ± 0.1 megatonnes in 2014, but at high monetary and energy costs. Improved cropland nitrogen management could remove another 2.3 ± 0.3 megatonnes of nitrogen per year-about 25 per cent of the excess discharge to fresh water. Successfully restoring a clean water environment in China will further require transformational changes to boost the national nutrient recycling rate from its current average of 36 per cent to about 87 per cent, which is a level typical of traditional Chinese agriculture. Although ambitious, such a high level of nitrogen recycling is technologically achievable at an estimated capital cost of approximately 100 billion US dollars and operating costs of 18-29 billion US dollars per year, and could provide co-benefits such as recycled wastewater for crop irrigation and improved environmental quality and ecosystem services.

The glacierized Tien Shan - Pamir - Karakoram mountain complex supplies water to about 42 million people. Yet, the knowledge about future glacial runoff in response to future climate is limited. Here, we address this issue using a hydrological model, that includes the three components of glacial runoff: ice melt, snowmelt and the runoff of rainfall over ice. The model is forced by climate projections of the CMIP5 models. We find that the three components exhibit different long-term trajectories, sometimes opposite in sign to the long-term trend in glacier impacts. For the eastern slope basins, streamflow is projected to increase by 28% (ranging from 9 to 44%, from climate model variation (CMV)) by the late 21 st century, under the representative concentration pathway, RCP8.5. Ice melt contributes 39% (25 to 65%, CMV) of the total streamflow increase. However, streamflow from the western slopes is projected to decrease by 5% (-24 to 16%, CMV), due to the smaller contribution of ice melt, less precipitation and higher evapotranspiration. Increasing water supply from the eastern slopes suggests more water availability for currently degraded downstream ecosystems in the Xinjiang province of China, while the likely decreasing streamflow in Central Asian rivers on the western slopes indicates new regulations will be needed.

The net flux of CO 2 exchanged with the atmosphere following grassland-related land-use change (LUC) depends on the subsequent temporal dynamics of soil organic carbon (SOC). Yet, the magnitude and timing of these dynamics are still unclear. We compiled a global data set of 836 paired-sites to quantify temporal SOC changes after grassland-related LUC. In order to discriminate between SOC losses from the initial ecosystem and gains from the secondary one, the post-LUC time series of SOC data was combined with satellite-based net primary production observations as a proxy of carbon input to the soil. Globally, land conversion from either cropland or forest into grassland leads to SOC accumulation; the reverse shows net SOC loss. The SOC response curves vary between different regions. Conversion of cropland to managed grassland results in more SOC accumulation than natural grassland recovery from abandoned cropland. We did not consider the biophysical variables (e.g., climate conditions and soil properties) when fitting the SOC turnover rate into the observation data but analyzed the relationships between the fitted turnover rate and these variables. The SOC turnover rate is significantly correlated with temperature and precipitation (p < 0.05), but not with the clay fraction of soils (p > 0.05). Comparing our results with predictions from bookkeeping models, we found that bookkeeping models overestimate by 56% of the long-term (100 years horizon) cumulative SOC emissions for grassland-related LUC types in tropical and temperate regions since 2000. We also tested the spatial representativeness of our data set and calculated SOC response curves using the representative subset of sites in each region. Our study provides new insight into the impact grassland-related LUC on the global carbon budget and sheds light on the potential of grassland conservation for climate mitigation., (© 2018 John Wiley & Sons Ltd.)