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Decades of reckless deforestation have caused serious soil erosion and land desertification issues in the Loess Plateau (LP). "Grain for Green" Program (GFGP), one of the world's largest ecological restoration projects, is crucial to improve the ecological environment. Previous studies have demonstrated that GFGP lowers soil erosion in the LP. However, there are trade-offs and synergies between ecological services. Does strengthening soil conservation prevent enhancing other ecosystem services? Consequently, can the GFGP improve many ecological services simultaneously? This study compares changes in NDVI prior to and following the implementation of the GFGP in LP to the enhancement of ecosystem services. During the research period, the LP's overall vegetation cover rose significantly, particularly in the GFGP's major counties. Significant improvements were made to ecosystem services such as carbon sequestration, soil conservation, and habitat quality. The GFGP enhanced the synergistic linkages between ecological services. The implementation of the GFGP decreased water yield, suggesting trade-offs with other ecosystem services. Additionally, we investigate regional trade-offs/synergies between ecosystem services and their influencing factors, which were influenced by topographic and climatic variables. To maximize the benefits of ecological restoration efforts, we need a deeper understanding of the relationships between ecosystem services and the mechanisms that drive them. Thus, policymakers can scientifically exert control over local influences on ecosystem services, either by boosting the provision of specific services or by limiting specific influences in order to maintain ecosystem stability. [ABSTRACT FROM AUTHOR]

Increasing socioecological systems (SESs) sustainability requires establishing a reasonable cross-regional social and ecological interaction. In this study, we examine how cross-regional ecological and social interactions affect synergistic effects. Using InVEST and correlation analysis with data from 2010 through 2020, we assessed ESs (i.e., water retention-WR, nutrient retention-NR, and carbon storage-CS) in the Beijing-Tianjin-Hebei (BTH) region. A small watershed, a river network, and settlement development capacity are used to delineate ecological and social interactions units. Based on a Bayesian network model that considers population, economy, and spatial agglomeration patterns between social units, we assessed the potential for achieving a synergistic improvement of ESs and the driving forces behind them. The results show that ESs in the BTH region compete, only a small percentage (6.38%) shows synergetic improvement across CS, WR, and NR. It is beneficial for upstream watersheds to retain water and nutrients, but to maintain carbon storage they may sacrifice water retention. Upstream areas with less development and higher vegetation density have better ecosystem integrity of up- and down-stream watersheds, and can be enhanced with minimal human impact, as social interactions and settlement spatial structures influence ES synergies. There is a higher risk for ecological issues in downstream areas, but greater awareness and collaboration can lead to better ES synergies. • Upstream and downstream watersheds have opposing synergistic improvement potential. • Urban–rural spatial interactions and settlement structure impact service synergy. • Synergistic improvements in ecosystem management require balanced approaches. • Water and nutrition retention services have improved in the BTH region. [ABSTRACT FROM AUTHOR]

Livestock is an important source of greenhouse gas emissions (GHGE) in China. Understanding the greenhouse gas (GHG) emission trends and reduction strategies in livestock is crucial for promoting low-carbon transformation of the livestock sector (LS) and achieving the goal of "carbon peak and carbon neutralization". First, based on the life cycle assessment and IPCC coefficient methods, we calculated the GHGE of the LS in 31 provinces of China from 2000 to 2020 and identified the temporal and spatial evolution of GHG emission intensity. The LMDI method was then used to analyze the influence of efficiency, structure, economy, and population size on GHGE. Finally, the STIRPAT model was used to simulate the future evolution trend of the LS emissions under the SSPs scenario. The results revealed that the GHGE in the life cycle of livestock production decreased from 535.47 Mt carbon dioxide equivalent (CO 2 e) in 2000 to 532.18 Mt CO 2 e in 2020, and the main source was CH 4 emissions from enteric fermentation of livestock. Economic and efficiency factors markedly influenced the changes in GHGE from the LS in China. Further, economic factors contributed >40% to the increase in GHGE in most provinces. Under the SSP1, SSP2, and SSP4 scenarios, livestock production can achieve the carbon peak target in 2030. Under the baseline scenario (SSP2), the GHGE of China's LS in 2030 and 2060 are expected to be 491.48 Mt CO 2 e and 352.11 Mt CO 2 e, respectively. The focus of mitigation measures for livestock production in the future is to optimize the production structure of the LS, promote the low-carbon transformation of the energy structure of livestock feeding, and establish an efficient and intensive management model. In addition, we focus on emission reduction in key areas, such as Northeast and Northwest China, while optimizing diet and reducing food waste from the consumer side. • GHGE during the livestock production from 2000 to 2020 fluctuated between 500.77 and 670.98 Mt CO 2 e. • GHGE per unit output value of LS were decreasing annually. • Economic and efficiency factors were the main reasons for the change in GHGE from livestock production in China. • The GHGE from the LS are expected first to increase and then decrease between 2021 and 2060. • The LS has the highest emission reduction potential under SSP1, SSP2, and SSP4 scenarios. [ABSTRACT FROM AUTHOR]

Urbanisation and population agglomeration have significantly increased China's CO 2 emissions. Migration has altered the quantity and spatial distribution of CO 2 emissions, yet these changes have not been quantified. This study used a counterfactual analysis to determine the impact of migration on CO 2 emissions. Specifically, we used a multi-scale geographically weighted regression to estimate the marginal effects of net immigration on CO 2 emissions, an environmentally extended multi-regional input-output model to determine how migration impacts the CO 2 emissions of inflow and outflow regions as well as the regional transfer of CO 2 emissions, and structural path analysis to identify key sectors and their emission paths. The results indicate that population emigration from less-developed regions was primarily responsible for reducing CO 2 emissions. Upon migration to urban agglomeration areas, individuals chose cleaner fuels and used public services more frequently, which resulted in a significant reduction in the intensity of local emissions. Furthermore, migration led to a narrowing of spatial disparities in indirect emission reductions. Provinces in eastern and north-eastern China were less affected by indirect CO 2 emissions caused by immigration. Additionally, the eastern and central regions exhibited 'regional agglomeration' and 'self-circulation' in the emission paths of key sectors. • Migratory effects on CO 2 emissions were determined using a counterfactual analysis. • China's CO 2 emissions are projected to increase 9.61% under reverse migration. • Migratory emission reductions may result from emigration from impoverished regions. • Service and energy-intensive sectors are most impacted by migration flows. [ABSTRACT FROM AUTHOR]

Industrial production is key to economic development, yet it significantly influences the water environment. Recent literature has mainly focused on economic development and water pollution separately, lacking an integrated assessment. This study aims to clarify the links between industrial production and water pollution and its driving factors in the Yangtze River Economic Belt (YREB) in 2012–2017 based on environmentally-extended input-output analysis and structural decomposition analysis, thus identifying key regions and sectors for pollution reduction. The results revealed that manufacture of foods and tobacco (MFT) and chemical industry (CI) in Anhui, Jiangsu, Jiangxi, Hunan, and processing of petroleum, coking, processing of nuclear fuel (PPCN) in Chongqing were the primary sources of total chemical oxygen demand (COD), ammoniacal nitrogen (NH 3 –N), total nitrogen (TN), and total phosphorus (TP) discharges. The structural decomposition analysis (SDA) results demonstrated that the discharge intensity effect caused a decrease of 7.91 Mt, 0.22 Mt, 0.25 Mt, and 0.03 Mt of the indirect COD, NH 3 –N, TN, and TP discharge, while the scale effect led to an increase of 1.95 Mt, 0.26 Mt, 0.24 Mt and 0.03 Mt of them in 2012–2017. According to the analysis, water pollution reduction and industrial structure modernization are needed in the YREB. The technological upgrading of highly polluting industries and the structural adjustment between traditional highly polluting industries and high-tech industries were the focus for achieving green development of the YREB, especially in Anhui, Hubei, Guizhou and Yunnan. The establishment of green industrial parks, the development of environmental regulations, and the implementation of supply-side reform policies can benefit water pollution reduction and sustainable development. [Display omitted] • The EEIO model was applied to identify key regions and sectors for water pollution. • MFT, MT, MTCS, PPCN and CI were major sectors for water pollutant discharges. • Jiangsu and Jiangxi were major contributors for water pollutant discharges. • Discharge intensity effect decrease water pollution, scale effect did the opposite. • Green development need focus on industries with high indirect pollutant discharge. [ABSTRACT FROM AUTHOR]

Land degradation directly affects global and regional economic, social development, and food security, which has become a hot and challenging issue in the global ecological field. A successful response to land degradation requires understanding its causes, impacts, and extent. It is also essential to recognize the effects of climate, soil, water, land cover, and socioeconomic factors on land degradation. Therefore, assessing land degradation risk can help prevent and reverse land degradation trends, especially for the main grain production area. The Environmental Sensitivity Area Index (ESAI) was used to identify land degradation sensitive areas in the North China Plain and combined with a random forest model to determine the main drivers affecting land degradation and predict future land degradation sensitive areas. The results show decreasing land degradation risk in the North China Plain. In 2015, the sensitivity of land degradation in the North China Plain had improved. The proportion of land area with high sensitivity to land degradation reduced to 0.02%. Combining the spatial and temporal distribution of ESAI and the prediction results of the random forest model, we know that socio-economic factors have the most significant impact on land degradation sensitivity. Although the risk of land degradation is decreasing, it is still necessary to pay attention to the possible future land degradation risk to stabilize food production. Assessing land degradation risk in North China Plain provides important decision information for rational and sustainable land management and has more vital practical significance. • The land degradation sensitivity in North China Plain improved. • The ESAI and random forest model were combined to predict the future land degradation risk trends in the North China Plain. • The growth of population and GDP are important influencing the potential risk of land degradation. [ABSTRACT FROM AUTHOR]

Community is the disaggregated unit to reflect the transformation of eco-urbanization in China. Eco-urbanization at communities is the ecological landscape and environment-friendly practices, and is directly reflected in residents' satisfaction on the transformation of these ecological elements. In this study, we assess resident's perception of eco-urbanization at community and explore the influencing factors by a field survey in 64 community block groups with 668 questionnaires. Methodologically, we have made the assessment using residents' satisfaction on green space, sanitation, landscape, noise pollution treatment, and optic pollution control. Then regression analysis has been made with the influencing factors from the dimensions of individual characteristics, management, and facilities. In general, residents' satisfaction on sanitation is at the highest level and noise pollution treatment is at the lowest level. The property management and the safety sense greatly influence the residents' perceptions, whereas facilities appear to have less influence. The environmental environment friendly behavior also affects residents' satisfaction on eco-community. The results have also revealed resident's perception of eco-urbanization at community shows great difference in different regions and in different community types. Accordingly, it is necessary to strengthen the comprehensive governance on eco-community, enhance the all-around management and promote human-oriented community in the future. • We assess residents' perception of eco-community and explore the influencing factors by a field survey nationwide. • Residents' satisfaction on green space, sanitation, landscape, noise and optic pollution control is investigated. • Influencing factors are selected from the dimensions of individual characteristics, management, and facilities. • The property management and the safety sense greatly influence the residents' perceptions. • Resident's perception of eco-community shows great difference in different regions and in different community types. [ABSTRACT FROM AUTHOR]

As the largest emerging economy globally, China is facing crop-livestock disconnection, which causes unnecessary synthetic fertiliser use, local food and feed unsatisfied demand, and manure nitrogen (N) surplus. We investigated how crop-livestock regional integration combined with inter-regional transportation of food, feed, and manure, can contribute to food self-sufficiency of easter China (whole and regional level) while avoiding manure N excess. We also investigated how this could increase the local soybean production without harming the self-sufficiency of other food commodities. We proposed an optimisation model of integrated crop-livestock production in eastern China, including the production of food, feed, and livestock manure N in each region and the demand for food (according to healthy diet recommendations), feed and manure N. We optimised the supplier cost-benefit balance considering food and feed production, domestic transportation, and foreign trade, taking food and feed demand satisfaction and manure N surplus avoidance as constraints. This optimisation exercise was performed under different scenarios: optimisation without soybean subsidies (scenario O), optimisation with increasing soybean subsidies (scenario OS+). The two scenarios were compared with the baseline scenario B (non-optimised without soybean subsidies) using balance indices (BI , the gap between production and demand divided by demand) of food, feed, and manure N and transportation indices. Results showed that, for the whole of eastern China, BI were positive for cereals (1.523), vegetables (2.789), meat (0.002), eggs (0.002), milk (0.102), and maize (0.244), and negative for manure N (−0.016) in scenario O. This indicated that most of the food and feed items except soybean were self-sufficient and manure N surplus was avoided after optimisation. Some regions lowered their self-sufficiency for some commodities. As soybean subsidies increased from 0 Yuan ‧ ton-‍1 to 6000 Yuan ‧ ton−1, the BI of soybeans increased by 66.37%. Our results suggested that crop and livestock can be integrated in China for an improved level of food self-sufficiency and manure N surplus avoidance. However, regional self-sufficiency could not be achieved in all regions for all items, and transportation is necessary. In particular, three strategies seem relevant for policy-making: (i) decreasing livestock quantity, for strengthening feed self-sufficiency and avoiding manure N surplus; (ii) increasing soybean production through subsidies; (iii) reducing regional-level self-sufficiency and increasing the transportation for meat and eggs, which would avoid manure N surplus in densely populated regions, while decreasing the maize transportation. [Display omitted] • Inconsistent configuration of crops and livestock may lead to a low level of food self-sufficiency and manure N surplus. • We proposed an optimisation model of an integrated crop-livestock system at the regional level. • We compared the balance indices of food, feed, manure N, and transportation indices in different scenarios. • Food self-sufficiency was strengthened and the manure N surplus was avoided by optimisation exercises in eastern China. • Three principles for policy strategies were suggested based on our results. [ABSTRACT FROM AUTHOR]

Maximizing resource use efficiency is generally recognized as a key strategy for developing an environment-friendly agricultural system. Although there have been many studies on single topic of resource use efficiency or environmental impacts, little is known about the spatially-explicit comprehensive estimation of the potentials in resource use efficiency improvement and environmental impacts mitigation. Here, this study proposed a comprehensive assessment framework to estimate the resource use efficiency and its environmental impacts in rice-production system at a county level, and also analyzed their improving potentials compared with both the domestically excellent province level (DEPL) and globally excellent country level (GECL). Results show that the resource use efficiency in Fujian Province was lower than 0.89 and 0.84 fold for nitrogen use efficiency (NUE), and 0.83 and 0.63 fold for irrigation water productivity (IWP) of those at the DEPL (Hunan Province, China) and GECL (Japan), respectively, while the environmental impacts were more than those in the DEPL and GECL (2.66 and 5.78 fold for grey water footprint (GYWF), 1.10 and 1.20 fold for greenhouse gases (GHG) emissions). The decrease of 26.74% blue water footprint (BWF) in Fujian Province can be achieved by that IWPs in the bottom 50% counties of Fujian Province reached at the GECL. Moreover, improving the NUEs in the bottom 40% counties of Fujian Province to the GECL can not only decrease nitrogen (N) application in Fujian Province by 17.52%, but also decrease GYWF and N 2 O emissions in Fujian Province by 8.49% and 14.71%, respectively. The assessment framework we proposed based on spatially-explicit analysis at a county level can be used broadly for comprehensive assessment of agricultural production inputs and its environmental impacts in other rice production regions. • We proposed an evaluation framework for counties' rice production sustainability. • The use efficiency of N and water have large spatial variations at county level. • The Southeast Fujian have greater environmental mitigation potential than others. • It can be reduced by 18% N and 27% blue water when efficiency reaches Japan level. [ABSTRACT FROM AUTHOR]

Accurate estimates of soil organic carbon (SOC) stocks are important in understanding terrestrial carbon cycling. Based on the fundamental theorem of surfaces, an alternative method, high accuracy surface modelling (HASM) combined with soil depth information was applied to predict the spatial pattern of SOC stocks in Hebei Province, China. In this study, we collected 434 soil samples and key environmental covariates related to soil-forming factors (soil, climate, organisms, topography, and soil depth information) in the study area, and compared the accuracy of 16 spatial prediction models (including single models, hybrid models, and HASM combined with single or hybrid models) on the spatial distribution of SOC stocks. The results confirmed that the method of HASM combined with the generalized additive model (GAM) with soil depth covariate (HASM_GAMD) achieved a better performance than other methods at soil depths of 0–30, 0–100 and 0–200 cm. The root-mean-square error and coefficient of determination values of predicting the spatial pattern of SOC stocks by the HASM_GAMD model demonstrated a 43% and 49% improvement, respectively, compared with models without depth information. The prediction uncertainty of the HASM_GAMD model based on 90% prediction interval was lower than that of other models. The HASM_GAMD model excels in addressing not only the nonlinear relationship between covariates and SOC stocks, but also in incorporating point observation data that varies with soil depth. Furthermore, the model conducts modelling by integrating surface and optimal control theories. Results obtained from the HASM_GAMD demonstrated that the SOC stocks in Hebei Province amounted to 1449.08 Tg C. Our study introduces an alternative model for modelling of SOC stocks and our findings are a valuable reference for assessing carbon stocks in Hebei Province to support sustainable land management and climate change mitigation. • We applied a surface modeling method to predict soil organic carbon stocks. • Combining surface modeling methods with soil depth can improve the performance. • Soil organic carbon stocks are 1449.08 Tg C (60% in >30 cm soil layer) in study area. [ABSTRACT FROM AUTHOR]

The human-environment relationship has always been a research topic of sustainable development. In the past century, many theories about the human-environment relationship, such as environmental determinism, possibilism (probability theory), adaptation theory, cultural landscape theory, and human-environment harmony theory, have been put forward. These theories have reflected the dynamic change of the relationship between human and the natural environment, and advanced human understanding on nature. In the past 30 years, few breakthroughs have occurred in the studies on the human-environment relationship until the 'Two Mountains' theory ('Clear waters and green mountains are as valuable as mountains of gold and silver', or 'lucid waters and lush mountains are invaluable assets') was put forward by President Xi Jinping. The 'Two Mountains' theory is a new theory of the human-environment relationship based on the general trend of world development and the difficult practice in the past 70 years since the founding of the People's Republic of China. It is a qualitative leap in the development of the human-environment relationship theory, and has resonated with the requirements of the times from human-environment separation, human-environment mutual respect to human-environment integration. Furthermore, it has provided Chinese wisdom for the development and innovation of the human-environment relationship theories in the world. From a scientific perspective, the 'Two Mountains' theory contains a rich philosophy about the evolution of the human-environment system, and has interpreted the methods and paths of achieving the intrinsic unity, mutual promotion and coordinated symbiosis between the human development and environment protection. It has inherited and carried forward the traditional Chinese thought of the 'unity of man and nature', and expanded and deepened the Marxist dialectical relationship between man and nature. Enriching and innovating the Xi Jinping Thought on Ecological Civilization in the new era, it has profoundly revealed the basic laws of economic and social development, and laid the theoretical foundation for the construction of a 'modernization characterized by harmonious coexistence between man and nature'. From the perspective of the value of the times, the theory meets the requirements of the national 'five in one' overall layout, and demonstrates the implications of the human-environment relationship from philosophical, economic, social, ecological, and cultural dimensions. It is an important guide for the construction of a beautiful China in the new era. Additionally, the 'Two Mountains' theory enriches and develops the theories of the human-environment relationship in geography and is worthy of in-depth exploration and promotion by scholars from multiple fields. [ABSTRACT FROM AUTHOR]

Water and land (W-L) resources become even more important in the context of urban-rural integration in China's arid northwest region in order to achieve sustainable development goals (SDGs). Our study used Gini coefficients to examine the relationship between natural resources and economic development in China's Xinjiang Uygur Autonomous Region. Cobb-Douglas (C-D) production functions were used to determine the economic impacts of W-L resources on rural-urban economic development. We also examined the spatiotemporal interaction characteristics of the growth drag effect of W-L resources. As a result of the decline in Gini coefficients between 2000 and 2020, Xinjiang experienced a decrease in water resources, land resources, and urban-rural GDP (gross domestic product). The output elasticities of urban-rural land and water resources were 0.3544 and 0.4790, respectively, whereas the output elasticities of urban-rural land resources were 0.1501 and 0.2185, respectively. As a result, water resources contribute to the growth of urban-rural GDP more than land resources, and W-L resources contribute to the economic development of rural areas more than it does to that of urban areas. Land resources were found to have a drag effect on urban and rural economies, respectively, in 7 and 56 counties, respectively, and water resources were found to have a drag effect on urban and rural economies, respectively, in 67 and 58 counties. In Xinjiang, water resources contributed more to economic growth than land resources. Even though W-L resources still have a drag effect on urban-rural economic growth, we can gain greater driving force by optimizing and improving resource use. However, this requires an optimal allocation and efficient use of water resources. • The drag model can analyze the drag effects of natural resource use on the urban-rural economy. • Water resources are more compatible with the urban-rural economy than land resources. • Water constraints affect Xinjiang's economic growth more than land constraints. • Water scarcity reduced Xinjiang's urban economic growth by 0.68%–1.57% from 2000 to 2020. [ABSTRACT FROM AUTHOR]

Urban–rural industry convergence is a critical factor in addressing the dual urban–rural structure, as it has the potential to increase agricultural productivity and update the industry structure. This study aims to assess the mechanisms through which urban–rural industry convergence affects farmers’ incomes in the Xinjiang Uyghur Autonomous Region of China. First, we developed an evaluation framework to measure urban–rural industry convergence and conducted an exploratory spatiotemporal data analysis to assess the trends in convergence across 99 districts and counties in Xinjiang between 2001 and 2020. Thereafter, using an econometric model, we then analyzed the mediating effects of industrial structure upgrading on the relationship between urban–rural industry convergence and farmers’ income, and the implementation path. The results indicated that urban–rural industrial convergence in Xinjiang has fluctuated and declined over time, with a spatial distribution skewed from north to south. Moreover, it was found that urban–rural industry convergence and industrial structure upgrading significantly contribute to the growth of farmers’ income. Additionally, the impact pathway analysis revealed that urban–rural industry convergence promotes industrial structure upgrading, thereby stimulating growth in farmers’ incomes. This positive effect had long-term implications and became more noticeable over time due to cumulative effects. Furthermore, the effects of urban–rural industry convergence on farmers’ income varied depending on income levels. It had a significant positive effect on the income of low-income farmers but a negative effect on high-income farmers. Moreover, the impact of the digital economy on farmers’ incomes varied based on regional and group differences, particularly affecting low, medium, and medium–high-income groups in northern Xinjiang. These findings provided empirical evidence for promoting urban–rural industry convergence and increasing farmers’ incomes, contributing to both theoretical and practical understanding of the subject matter. [ABSTRACT FROM AUTHOR]

In an effort to contribute to climate change mitigation, China has committed to achieving its peak carbon by 2030 and carbon neutrality by 2060. However, reaching these goals will require a massive reduction in carbon emissions. The humans have to consume food to meet their survival needs. Furthermore, the society's demand for food is consistent with the development level of agricultural structures. At present, reducing environmental costs associated with food to adjust the agricultural structure has not received sufficient scientific attention. Because of this, the present study combines food consumption, climate change, and agricultural structure to design future scenarios based on the widely used SSP storyline. Moreover, in order for China to reach its carbon peak in 2030, this study applies a life-cycle approach to uncover the potential carbon reduction of Chinese residents under different dietary structures. From a demand perspective, this study puts forward recommendations for dietary restructuring and guides the direction of future agricultural restructuring in China. It also shows that a diet structure that replaces red meat with plant foods such as vegetables and fruits will have a more significant carbon reduction potential. The traditional agricultural structure consumes a large amount of food and produces a significant amount of greenhouse gases. Reducing meat and high-fat foods consumption may help reduce GHG emissions produced by food consumption. In addition, reducing the proportion of food used for feeding in the agricultural structure will also help achieve peak carbon targets. The shift in diet structure will advance China's agricultural structure and promote green agriculture development. • Food consumption and related carbon emissions within the 2030 scenario will continue to increase, with the highest share of rice consumption. • The carbon emissions of food consumption in the environmentally sustainable scenario will decrease. • Readjusting toward a more balanced diet could significantly contribute to the carbon peak goal. • A shift in dietary structure will promote agricultural restructuring. [ABSTRACT FROM AUTHOR]

Atmospheric carbon dioxide (CO 2) has affected global surface and atmospheric energy balance since the Industrial Revolution. The spatial distribution of CO 2 concentrations derived from satellite observation are introduced into the coupled Beijing Normal University Earth System Model (BNU-ESM) to study the responses of temperature and surface energy balance to non-uniform CO 2 distribution under the Representative Concentration Pathway 8.5 scenario to 2100. Global annual mean atmospheric CO 2 concentrations are set to equal those specified in the standard uniform CO 2 simulations with differences in spatial pattern and seasonal cycles amounting to tens of ppm. Relative to the uniform CO 2 simulation, global annual mean surface air temperature increases by 0.44 ± 0.03 °C over 2071–2100 when forced with non-uniformly distributed CO 2 , in the Arctic by 1.63 ± 0.28 °C and by 0.67 ± 0.08 °C in northern midlatitudes. The non-uniform CO 2 simulation increases global surface energy by 0.68 ± 0.06 W m−2, principally due to a 0.73 ± 0.08 W m−2 increase in net downward surface longwave flux. Surface energy balance increases by 0.33 ± 0.11 W m−2 (7.4%) averaged over oceans indicting a significant increase in ocean heat uptake. Surface energy budget averaged over the Arctic summer increases by 0.91 ± 0.68 W m−2 in the non-uniform CO 2 simulation, which would have impact on sea ice extent and land ice melt rates with associated feedbacks. The increased surface energy fluxes and temperatures imply reduced time and emission space for greenhouse gases before running into scientific and politically flagged temperature limits. • The distributions of CO 2 concentrations are introduced into Earth System Model. • There are some changes in surface energy fluxes due to non-uniform CO 2. • Changes in surface energy fluxes have impact on sea ice extent with its feedbacks. [ABSTRACT FROM AUTHOR]

• Provided a framework to explore the dynamic relevance (DR) between landscape pattern and NST. • DR was different in 2000–2010 and 2010–2020, and it was seasonal various. • DR of landscape composition was more significantly correlated than non-area related spatial configuration metrics. • The proportion of green space was positively correlated with NST in summer in BTH from 2000 to 2020. Landscape management and planning is an important way to mitigate climate change. Previous studies have proved landscape pattern (composition and configuration) was correlated to thermal environment based on a single image data in time, but the static results were inconclusive and contradictory. In this study, a framework to investigate the dynamic relevance between landscape pattern change and near surface air temperature (NST) difference was constructed through the Weather Research and Forecasting Model (WRF) and geospatial methods including landscape metrics. The landscape pattern change of Beijing-Tianjin-Hebei (BTH) urban agglomeration from 2000 to 2020 were examined and their impacts on NST were simulated. Results showed it was dominant that cropland, water and grass land urbanized in the landscape evolution process, which led BTH average NST rise by 0.05℃ and 0.177℃ in January and July, respectively. The dynamic relevance (DR) between landscape composition and configuration and NST of all land classifications over the two decades were investigated quantitatively. Results indicated the DR between the change of landscape pattern and NST in different periods was different and it was seasonal various. DR of composition metric was more significantly correlated than non-area related spatial configuration metrics. In this twenty years, the DR of urban land (UBL) was positive, and it was negative for cropland (CPL). The landscape pattern of water (WTR) was positively correlated with NST in winter and negatively in summer. The DR of green space was an opposite correlation with DR of WTR in winter and summer, due to the newly added green space was mainly transformed from WTR. The dynamic perspective of relevance based on WRF and landscape indicators can enhance the understanding the effects of landscape pattern on thermal environment and provide a methodological framework for evaluating the dynamic relationship of landscape indicators and thermal effects. [ABSTRACT FROM AUTHOR]

• Track interannual variations of surface water area (SWA) in NCP in 1987–2020. • SWA in NCP expanded by 68%, with the most rapid increase in Shandong Province. • Increasing reservoirs/lakes and aquaculture ponds contributed to SWA expansion. • SWA expansion accelerated regional water loss through increasing water evaporation. Water shortage has severely threatened the North China Plain (NCP), a typical grain bowl and highly populated and urbanized area in China. As surface water body area (SWA) is a critical variable for measuring regional water resources, understanding its changes and driving mechanisms is important for sustainable water management. Here, we examine the interannual variations and trends of SWA in the NCP during 1987–2020 by using all the available Landsat imagery, the water indices- and threshold-based water mapping algorithm, and cloud computing platform Google Earth Engine (GEE). The results show that SWA of the NCP significantly (p < 0.05) expanded by 68.0% (from 4740.0 km2 in 1987 to 7963.7 km2 in 2020) at a rate of 101.9 km2/yr. The most remarkable expansion of SWA happened in Shandong Province (75.0 km2/yr), which is an increasingly important aquaculture production region. We find that the increasing artificial reservoirs/lakes due to the implementation of water projects, together with aquaculture development, are the main drivers for the expansion of SWA in the NCP. The expansion of SWA caused a significant increase in water evaporation (0.09 km3/yr) in the NCP as the shallow nature of these artificial reservoirs/lakes and aquaculture ponds could lead to excess evaporation because of the frequent heating and cooling cycles due to their limited abilities to store energy. Similarly, Shandong Province experienced the most rapid increase in water evaporation (0.03 km3/yr), which could accelerate the loss of water storage at a rate of 8.4–14.4 mm/yr in the regions covered by surface water bodies. Continuous temperature rise (0.02–0.06 °C/yr) in the future, as predicted by the climate models (CMIP5) under the two Representative Concentration Pathway (RCP) scenarios of medium (RCP 4.5) and high (RCP 8.5) greenhouse gas emission, could further increase water evaporation, which may add more pressure to regional water shortage. This study warns that, despite an observed significant SWA expansion, water shortage remains a major concern in the NCP. [ABSTRACT FROM AUTHOR]

• Distribution effect of carbon-food nexus for Chinese cities were explored. • Several methods built using the spatial decoupling index were proposed. • Chinese cities exhibited varying degrees of the distribution effect over the period. • Driver pattern of carbon-food nexus has changed over the years. Climate change mitigation and food security are sustainable development goals (SDGs) of the United Nations. Despite extensive studies focused on the nexus of different SDGs and corresponding mechanisms, the distribution effect of carbon-food nexus and its driver has received limited attention, hindering policy making for balancing pathways of regional emission reduction and food production improvement. The present study explored the distribution effect (i.e., spatial performance) of carbon-food nexus from multiple perspectives (namely, status quo, drivers, and trend) based on a unique city-level dataset from 2005 to 2017. To this end, we proposed the spatial decoupling index, the corresponding decomposition and nonparametric models for capturing the multi-perspective distribution effects. The results indicated that Chinese cities, categorized by population scale and economic structure, exhibited varying degrees of distributions of carbon-food nexus over the period. Moreover, the driver pattern of carbon-food nexus was noted to have changed, wherein investment efficiency and scale were positive drivers. Furthermore, we showed that a more developed city's economy was statistically significantly associated with higher carbon emission and lower food production. Therefore, related stakeholders should take more actions such as strengthening capital accumulation and joint management of carbon intensity, for improving the distribution effect of the overall city-level carbon-food nexus. [ABSTRACT FROM AUTHOR]