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Agricultural production contributes to the increase in global carbon emissions. It is crucial to improve output and reduce carbon emissions in the context of agricultural modernization, for which improved carbon emission efficiency is key. However, the role of agricultural modernization in promoting agricultural carbon emission efficiency is not clear. Hence, the aim of this article is to analyze the spatiotemporal evolution of agricultural modernization and agricultural carbon emission efficiency in China from 2000 to 2019 and to reveal the relationship between agricultural modernization and agricultural carbon emission efficiency. The results showed that (1) in China, the overall level of agricultural modernization has been steadily increasing, and the regional differences are widening, showing a spatial pattern characterized by a gradual decline from the eastern and central regions to the western region. (2) China's agricultural carbon emission efficiency continues to grow but has not achieved a data envelopment analysis (DEA) effect, with the eastern and western regions having higher agricultural carbon efficiency than the central region. The regional differences first narrow and then expand. (3) Agricultural modernization significantly promotes agricultural carbon emission efficiency in both the province and the neighboring provinces, and the interprovincial spillover effect exceeds the direct effect within the province. A nonlinear correlation exists between agricultural modernization and agricultural carbon emission efficiency. [ABSTRACT FROM AUTHOR]

Eco-efficiency is a key indicator to measure the level of regional sustainable development. The county is the basic spatial unit of socio-economic activities and sustainable policy implementation in China. Hence, this paper conducts eco-efficiency analysis at the county scale in order to provide reference for the central and local governments to formulate differentiated eco-efficiency enhancement policies, further promote Chinese ecological sustainable development, and advance the construction of ecological civilization with high quality. Based on the Super-Slacks-Based Measure (SBM) model and the Malmquist index, the paper constructed an eco-efficiency measurement method and analyzed the variation characteristics, influencing factors, spatial pattern of eco-efficiency in Chinese counties from 2000 to 2020. The results showed that: (1) The eco-efficiency of the county unit was generally low in China and was roughly distributed in a pyramid. The county-level eco-efficiency had a spatial distribution pattern of being high in the west and low in the east, and high in the south and low in the north, with significant non-equilibrium. There was a positive correlation between eco-efficiency of neighboring counties in China. (2) The per-capita GDP has a significant positive correlation with eco-efficiency, while energy consumption, arable land area and eco-efficiency have a negative correlation. The redundancy rate of input indicators was high in Chinese counties. (3) During the study period, the eco-efficiency of most counties displayed a fluctuating growth trend. The growth was mainly driven by technological progress. [ABSTRACT FROM AUTHOR]

The output intensity of water resources has become a subject of increasing concern. Based on spatial autocorrelation, the Gini coefficient, the Theil index, and geographically and temporally weighted models, this work studied the spatial correlation and regional differences of the output intensity of agricultural water and the main factors influencing the output intensity of agricultural water from a spatial–temporal perspective in China from 2003 to 2019. The results show that the output intensity of agricultural water showed an upward trend and that the output in the central region was higher than the output in the eastern region, and the eastern region had higher output than the western region. By analyzing the spatial autocorrelation, it was found that the output intensity of agricultural water presented a significant spatial dispersion trend and showed the spatial difference. The overall difference in the output intensity of agricultural water in China showed an increasing trend, but the widening difference showed an alleviating trend; the main reason for this increase in the overall differences is that the intra-group differences in the three regions were increasing, with the largest intra-group differences being observed in the western region followed by the eastern region and the central region. Population scale, water use scale, water use structure, effective irrigation scale, urbanization, and industrial structure create significant spatial differences in the output intensity of agricultural water. However, the level of economic development positively impacts the agricultural water output intensity of all provinces. Therefore, water resource management departments should formulate water resource management policies based on regional water conditions and the differences between influencing factors. [ABSTRACT FROM AUTHOR]

The rate of decline in ecosystem services has been exacerbated by inefficient and inequitable natural resource use and management. This study analyzes the natural capital stock and outflow in the Arid and Semi-Arid Northern Region of China (ASRNC) from 2000 to 2020. The Gini coefficient and coefficient of variation are used in the equity assessment of natural capital consumption. Over-appropriation of natural capital is a prerequisite for the inequitable distribution of natural resources, and all variables were accounted for through a geographic probe. Since most of the variables in this study have a nonlinear relationship, an in-depth analysis was conducted using NARDL. The results show that (1) natural capital flow occupancy generally shows an upward and downward trend and peaks in 2015. Natural capital stock occupancy was on a linear upward trend over the study period, rising from 14.580hm2/cap to 18.272hm2/cap. Depletion of natural capital is increasing and construction land has become the land type that leads to deep footprint changes (2) A city's consumption of natural capital matches its ecological carrying capacity to contribute to economic growth. However, the Gini coefficient for the depth of the ecological footprint from 2000 to 2020 is on a fluctuating upward trend. It reached its maximum in 2020 (1.457), indicating that the inequitable use of natural capital stock is increasing. (3) In the long run, population density and urbanization rate have different adverse effects on utilizing natural capital stock. In addition, the equity of planted forest area on natural capital use is heterogeneous in the long and short term. There is a negative effect of planted forest area on natural capital stock under long-term development. The study helps to judge the equity of regional consumption of natural capital and provides a scientific basis for the harmonious development between socio-economic systems and ecosystems. • The inequities in natural capital consumption are accounted for in a condition allowing nonlinear development. • Longitudinally, a chain of three aspects, natural capital accounting - equity measurement - imbalance tracing, is dissected. • In the long term, planted forests can exacerbate regional water shortages and lead to an imbalance in the use of natural capital. • Constructing an equity assessment framework for natural capital depletion can help guide the sustainable development of natural resources in arid and semi-arid regions. [ABSTRACT FROM AUTHOR]

• The achievement of regional sustainable development is at the core of PLES. • The quantitative identification of land use functions forms the foundation of territory spatial planning and management. • The COAL model provides a reference for determining future PLES development. Analysis of the dynamics of regional production-life-ecological space (PLES) can help to mitigate conflicts between economic development and the natural environment and can also promote sustainable and healthy regional development. However, the delineation and optimal integration of PLES at large scales, and predictions about its future, still lack sufficient scientific basis and reliable quantitative analysis. To fill this gap, this paper therefore chooses the city cluster as a research scale and the Lanzhou-Xining City Cluster (LXCC), an area typical of the "human-nature" conflict in northern China, as a case study. A collaborative optimal allocation of land-use (COAL) model was established to explore the future development of PLES in city clusters. In COAL, a morphological spatial pattern analysis (MSPA) and a minimum cumulative resistance model are used to determine the spatial functional areas of the country in 2020. Then, combined with the future land use simulation model, the PLES of LXCC is predicted in a multi-scenario perspective and differential control strategies are implemented for different land use functions. The results show that: (1) The identification and prioritization of source sites with important functions were the basis for enhancing the multiple functions of the land in the region. The ecological "source" of expansion accounts for 42% of the total area of LXCC, mainly in the mountains, forests, and ecological reserves, while the living "source" of expansion accounts for 58% of the total area of the city, mostly scattered on flat terrain. Based on this, five functional zones have been defined. The ecological protection zone was the largest, mainly in the western part of LXCC, and the agricultural buffer zone was the smallest. (2) The integration of different functional areas into the optimal allocation of land use is the premise of PLES delineation under the COAL framework. After a comparative analysis of multiple scenarios, the result of land use optimization under coordinated the city cluster scenario increased the area of productive land to 177,780.68 km2 and the area of living land to 13,947.33 km2. Based on this, the proportion of LXCC ecological, production, and living space were 77.20%, 18.23%, and 4.57% respectively. The optimized results have been proven to serve to meet the future spatial needs for food security and ecological conservation. The results of this study demonstrate that the COAL framework can help the government to determine the future development of PLES and promote balanced regional development in city clusters. [ABSTRACT FROM AUTHOR]

• Markov-FLUS and InVEST models can effectively predict the spatiotemporal changes of LULC and carbon storage. • Carbon storage will continue to increase in the future, with the largest increase in the ecological protection scenario (EP). • The implementation of ecological engineering and economic development had obvious promotion effect on carbon storage. There are more than 2,800 counties in China, including 341 in the Loess Plateau region. The county is the basic unit of administrative management and is considered to be the best scale for land use control, environmental planning and policy implementation. Since the 1990 s, socioeconomic development and the implementation of ecological engineering have greatly changed the land use and land cover (LULC) patterns in the Loess Plateau counties, and presumably in the county's carbon. However, accurate assessment of carbon storage and driving factors remains a challenge. This paper selected Qingcheng County, a typical county in the Loess Plateau, and used multi-source data and comprehensive environmental modeling methods to evaluate and analyze the temporal and spatial trends and driving factors of carbon storage in Qingcheng County from 2000 to 2030. The results showed that: (1) the carbon storage in the terrestrial ecosystem increased from 2000 to 2030 in Qingcheng, and it was mainly distributed in grassland and forest, accounting for 49 %–53 % and 36 %–40 % of the total carbon storage, respectively. (2) The implementation of ecological engineering had obvious promotion effect on carbon storage in the terrestrial ecosystem. The precipitation and temperature in the past 20 years had provided favorable climatic conditions for ecological engineering. In addition, carbon storage was also affected by economic development, land input intensity, and population size. These findings provide recommendations for achieving sustainable socioeconomic and ecological development at county-level. This study contributes to a deeper understanding of the relationship between LULC and carbon storage caused by natural environment and socioeconomic factors. [ABSTRACT FROM AUTHOR]

Public environmental cognition is an important basis for optimizing environmental management and reducing tensions between humans and land. Although the level of environmental cognition is a gradual process under normal conditions, it often changes qualitatively because of major public emergencies. During the 2019 new coronavirus epidemic (COVID-19), the most significant public health event in recent years, 24,188 national samples were obtained based on a network survey. The comprehensive evaluation method was used to assess the impact of major public events on public environmental cognition and the characteristics of spatial and temporal distribution. The findings are as follows. (1) During the epidemic period, sudden public health emergencies effectively promoted the national residents' environmental awareness, whether urban residents or rural; most respondents generally agreed with the concept of "respect nature and cherish life". (2) The environmental cognition of national residents was higher in the northwest and lower in the northeast of China, which is suitable for economic and social development and humanistic tradition. (3) There was a clear positive correlation between environmental awareness and education level. (4) During the epidemic, nervousness of respondents had a negative effect on environmental cognition. This study provides scientific support and a basis for decision making for the government to carry out environmental management optimization and improve the ecological and environmental cognition of the public, as well as devise effective intervention mechanisms with different time and space dimensions for similar future public health emergencies. [ABSTRACT FROM AUTHOR]

In 2021, The People's Republic of China proposed goals for peaking carbon dioxide emissions before 2030 and carbon neutrality before 2060, in the 15 counties (districts) of the Main Stream Area of the Yellow River Basin in Gansu that plays an important role in ecological protection and green development. Next the CO2 equivalents were converted according to the IPCC2 standard, the total agricultural GHG emissions was calculated, the relationship with the agricultural output value was analyzed, and the discretization of the space was analyzed by the coefficient of variation and standard deviation. Firstly, the total agricultural GHG emissions in 15 counties (districts) of the Main Stream Area of the Yellow River Basin increased 55.54% in 2000–2019, and 2.35% annually, roughly divided into three stages: the rapid growth period (2000–2008), the slow decline period (2009–2014) and the rapid decline period (2015–2019). The economic efficiency is significantly improved, with an average annual decline of 6.49%, roughly divided into three stages: the slow-descent stage (2000–2004), the period of slow-growth stage (2005–2008) and the period of fast-decline (2009–2019). Secondly, based on the characteristics of the total GHG emissions, Maqu County has the largest GHG emissions increase, from 26.8842 kt in 2000 to 38.9603 kt, in 2019, an increase of 44.92%, while the smallest GHG emissions, in Anning District, decreased 87.33% from 111 t in 2000 to 14.1 t in 2019; In the rate of increase in the total GHG emissions, Dongxiang County had the largest rate of increase from 2000 to 2019, an increase of 160.28% and an average annual increase of 4.90%. The smallest rate of decrease in GHG emissions was seen in Chengguan District, where they decreased 92.11% from 2000 to 2019, an average annual decrease of 11.93%. The characteristics of agricultural GHG emissions intensity is a significant declining trending and agricultural production efficiency has been significantly improved. Finally, to provide a basis for the formulation of differentiated agricultural energy conservation and emissions reduction policies, reduce agricultural GHG emissions intensity and reduce the use efficiency of resources by formulating differentiated emission targets, tasks and incentive measures. [ABSTRACT FROM AUTHOR]

China is a large agricultural country with a high level of agricultural carbon emissions. Whether market prices can be used in agricultural production as a means of agricultural carbon emissions reduction is of great significance to improve the allocation of agricultural production factors and expand large-scale production. This paper applies an autoregressive distributed lag–pooled mean group(ARDL–PMG) model to evaluate the relationship between agricultural production factor prices, food consumption prices, and agricultural carbon emissions, using Chinese provincial panel data from 1994 to 2018. The results show that agricultural carbon emissions and agricultural production factor prices show environmental Kuznets curve (EKC) characteristics; agricultural carbon emissions and food prices show a U-shaped curve; and agricultural production factors are positively correlated with food price in both directions in the long-term. The results of Granger causality tests show that price is the cause of agricultural carbon emissions; the price of agricultural production factors and the price of food consumption are mutually causal. Such results have implications for price, agriculture, and environmental policies. The analysis implies that the market price can be applied to agricultural carbon reduction, which will help policymakers to implement effective price policies in order to reduce agricultural carbon emissions. One implication is that promoting the marketization of agricultural production factors and reducing price distortions will be conducive to carbon emissions reduction in agriculture, which in turn will increase food consumption prices. Therefore, subsidies are needed at the consumption end, which will eventually achieve further carbon emissions reduction at the production and consumption ends. [ABSTRACT FROM AUTHOR]

Based on household-level survey data collected from Qinghai Province of China, we estimated the greenhouse gas (GHG) and air pollutant emissions from spatial perspectives, including household energy consumption in pastoral, agropastoral, and agricultural zones. The findings suggest that the total annual GHG and pollutant emissions per capita in the area was 2296.32 kg per year. The highest amount of pollutants was emitted from the pastoral zones, followed by the agropastoral and agricultural zones. CO 2 is the primary GHG emitted by household energy consumption. Dung burning was the cause of the high PM 2.5 emissions in the pastoral areas, while the use of coal was the primary cause of GHG and pollutant emissions in the agropastoral and agricultural zones. • We used empirical data from rural households in Qinghai, China. • This paper indicates the reliance of local energy consumption on non-commercial energy. • We estimate greenhouse gas and pollutant emissions resulting from solid-fuel combustion. • We compare indoor pollutant emissions from pastoral, agropastoral, and agricultural zones spatially. • This paper provides policy recommendations for energy transition towards clean energy. Energy consumption in the household sector has become an important issue in China's energy consumption and an important unit of China's clean energy transformation. Currently, the potential air pollution, carbon emissions and health risks caused by energy consumption in many areas cannot be ignored, and refined and regionalized index-based research data necessary to support decision making are lacking. Based on household-level survey data collected from Qinghai Province, China, we estimated greenhouse gas (GHG) and air pollutant emissions from spatial perspectives, including household energy consumption in pastoral, agropastoral, and agricultural zones. The findings suggest that the total annual GHG and pollutant emissions per capita in the area was 2296.32 kg per year. The highest amount of pollutants was emitted from the pastoral zones, followed by the agropastoral and agricultural zones. CO 2 is the primary GHG emitted by household energy consumption. Dung burning was the cause of the high PM 2.5 emissions in the pastoral areas, while the use of coal was the primary cause of GHG and pollutant emissions in the agropastoral and agricultural zones. These findings highlight the need to integrate household energy policies with rural development to enable a complete transition towards cleaner fuels. [ABSTRACT FROM AUTHOR]

A supply of high-quality cultural tourism products effectively promotes people's happiness. This study takes the coupling and coordination relationship between cultural tourism (CT) and objective well-being (OWB) in western China as the research object and constructs an index evaluation system for the development levels of cultural tourism and objective welfare, which are divided into three development stages of dysfunctional, transitional, and coordinated development and 10 coordination levels, including high-quality coordination. The entropy weight method, coupled coordination model, Thiel index, standard deviation, and coefficient of variation were used to calculate the comprehensive development index and coupling coordination degree of the CT and OWB systems in western China from 2007 to 2020, and then their evolution characteristics were analyzed from the perspectives of time and space. The results show the following: (1) The comprehensive development capacity of the CT and OWB systems in the western region shows a relatively consistent growth trend except for 2020, the overall development capacity of objective welfare was relatively high, and the development capacity of cultural tourism was relatively low. (2) The CT and OWB systems were in a state of transition from high coupling and low coordination to high coupling and high coordination, which were divided into three development stages: imbalanced stage (2007-2008), transitional stage (2009-2011), and coordinated development (2012-2020). The coordination degree has developed steadily from moderate misalignment to good coordination over time, and the diversified characteristics of coupling coordination levels are obvious. (3) The spatial equilibrium of the CT and OWB systems is obvious, and the spatial difference in the western region is getting smaller, but the relative gap is widening significantly. (4) The comprehensive development capacity of the cultural tourism system should be enhanced, the spiritual needs of residents based on objective well-being should be met, and the sustainable development of the CT and OWB systems.

Background: Dexmedetomidine (DEX) has a pharmacological profile that should allow rapid recovery and prevent undesirable outcomes such as pulmonary complications., Methods: This large retrospective study compared the beneficial effects of perioperative infusion of DEX with propofol on the postoperative outcome after coronary artery bypass graft surgery. We reviewed patients' medical notes at Luoyang Central Hospital from 1st January 2012 to 31st December 2019. All continuous variables, if normally distributed, were presented as mean ± SD; Otherwise, the non-normally distributed data and categorical data were presented as median (25-75 IQR) or number (percentage). The Mann-Whitney U test and Chi-square test were used to evaluate the difference of variables between the DEX and propofol groups. Multivariate logistic regression analysis was performed on the main related and differential factors in the perioperative period., Results: A total of 1388 patients were included in the study; of those, 557 patients received propofol infusion, and 831 patients received dexmedetomidine. DEX significantly reduced postoperative pulmonary complications compared with propofol, 7.82% vs 13.29%; P < 0.01, respectively. When compared with propofol, DEX significantly shortened the duration of mechanical lung ventilation, 18 (13,25) hours vs 21 (16,37) hours; P < 0.001, the length of stay in the intensive care unit, 51 (42,90) vs 59 (46,94.5) hours; P = 0.001 and hospital stay, 20 (17,24) vs 22 (17,28) days; P < 0.001, respectively. The incidences of postoperative wound dehiscence and infection were significantly reduced with DEX compared with propofol groups, 2.53% vs 6.64%; P < 0.001, respectively. Interestingly, patients receiving DEX had significantly shorter surgical time compared to propofol; 275 (240,310) vs 280 (250,320) minutes respectively (P = 0.005) and less estimated blood loss (P = 0.001)., Conclusion: Perioperative infusion of dexmedetomidine improved the desirable outcomes in patients who had coronary artery bypass graft surgery compared with propofol., (© 2022. The Author(s).)

The change of agricultural production scale is directly related to food security and the stable development of social economy. Particularly, the influence of economic development level and agricultural water use on agricultural production scale cannot be ignored. Therefore, this paper uses the fully modified ordinary least squares ( FMOLS ) and the Dumitrescu-Hurlin panel causality test models to discuss the effects of the level of economic development, agricultural water use, the level of urbanization, and the market price of agricultural products on the scale of agricultural production in China. The analysis results indicated that agricultural water use, the level of urbanization, and the market price of agricultural products promoted an increase of the scale of agricultural production at the total sample level; a 1% increase for these three variables will result in an increase of the scale of agricultural production of 0.634%, 0.377%, and 0.292%, respectively. The influence of economic development level on agricultural production scale accords with Kuznets curve. However, at the regional level, the influence of each variable on the eastern region is consistent with the trend of the total sample. In the central region, the impact of economic development on agricultural production scale shows a U-shaped curve, and the improvement of urbanization level inhibits the expansion of agricultural production scale. In the western region, all variables failed to pass the significance test. The results of the FMOLS model were validated by the fixed effects model. The results of causality tests showed that bidirectional causality existed between the scale of agricultural production and the level of economic development, the scale of agricultural production and agricultural water use, the level of economic development and the market price of agricultural products, and the level of urbanization and the market price of agricultural products. In different regions, there were differences in causality between variables. Therefore, based on the empirical results, we put forward some policy suggestions to maintain the scale of agricultural production.

The study of the carbon emission intensity of agricultural production is of great significance for the formulation of a rational agricultural carbon reduction policy. This paper examines the regional differences, spatial-temporal pattern and dynamic evolution of the carbon emission intensity of agriculture production from 1991 to 2018 through the Theil index and spatial data analysis. The results are shown as follows: The overall differences in carbon emission intensity of agriculture production presents a slightly enlarging trend, while the inter-regional differences in carbon emissions intensity is decreasing, but the intra-regional difference of carbon emissions intensity presented an expanding trend. The difference in carbon emission intensity between the eastern and central regions is not obvious, and the difference in carbon emission intensity in the western region shows a fluctuating and increasing trend. The overall differences caused by intra-regional differences; the average annual contribution of intra-regional differences is 67.84%, of which the average annual contribution of western region differences is 64.24%. The carbon emission intensity of agricultural production in China shows a downward trend, with provinces with high carbon emission intensity remaining stable, while provinces with low intensity are expanding. The Global Moran's I index indicates that China's carbon emission intensity of agricultural production shows a clear trend of spatial aggregation. The agglomeration trend of high agricultural carbon emission remains stable, and the overall pattern of agricultural carbon emission intensity shows a pattern of increasing differentiation from east to west.

Eco-efficiency enhancement is an inherent requirement of green development and an important indicator of high-quality development in general. It aims to achieve the coordinated development of nature, the economy, and society. Therefore, eco-efficiency measurements should focus on not only total factor input, but also process analysis. Based on the "full world" model in ecological economic theory, this study constructed a theoretical framework for a composite economic-environmental-social system that reflects human welfare and sustainability. To this end, using network data envelopment analysis (DEA), this study established a staged eco-efficiency evaluation model that uses economic, environmental, and social factors to measure the overall and staged eco-efficiency of China's provinces from 2003 to 2016 and analyze its spatiotemporal characteristics. A geographically weighted regression (GWR) model was also used to analyze the influencing factors of eco-efficiency changes and the spatial differentiation in their effect intensity. The findings were as follows: (1) China's overall eco-efficiency is still at a low level. It varies significantly from region to region, and only three regions are at the frontier of production. The eastern region has the highest eco-efficiency, followed by the central region, and the gap between the central and western regions has gradually narrowed. In terms of staged efficiency, the level of eco-efficiency in the production stage is less than in the environmental governance stage, which is less than that in the social input stage. (2) In terms of the efficiency of each stage, the efficiency level of the production stage showed a downward trend throughout the entire process, and the decline in the central and western regions was more obvious. The social input stage and the environmental governance stage both showed upward trends. The social input stage showed a higher level, and the increase was relatively flat during the period of study. Efficiency continued to rise during the environmental governance stage from 2003 to 2010 and rose overall, but with some fluctuations from 2011 to 2016. (3) Geographically weighted regression showed that the effects of the influencing factors on eco-efficiency had obvious spatial heterogeneity. The factors affecting overall, production stage, and social input eco-efficiency were, in order of effect intensity from high to low, economic growth level, marketization level, and social input level. In terms of environmental governance, social input level had the greatest impact, followed by economic growth; marketization level did not show a significant impact.