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Intensive anthropogenic activities have led to drastic changes in land use/land cover (LULC) and impacted the carbon storage in high-groundwater coal basins. In this paper, we conduct a case study on the Yanzhou Coalfield in Shandong Province of China. We further classify waterbodies by using the Google Earth Engine (GEE) to better investigate the process of LULC transformation and the forces driving it in four periods from 1985 to 2020 (i.e., 1985–1995, 1995–2005, 2005–2015, and 2015–2020). We modeled the spatiotemporal dynamics of carbon storage by using InVEST based on the transformation in LULC and its drivers, including mining (M), reclamation (R), urbanization and village relocation (U), and ecological restoration (E). The results indicate that carbon storage had depleted by 19.69 % (321099.06 Mg) owing to intensive transformations in LULC. The area of cropland shrank with the expansion of built-up land and waterbodies, and 56.31 % of the study area underwent transitions in land use in the study period. U was the primary driver of carbon loss while E was the leading driver of carbon gain. While the direct impact of M on carbon loss accounted for only 5.23 % of the total, it affected urbanization and led to village relocation. R led to the recovery of cropland and the reclamation of water for aquaculture, which in turn improved the efficiency of land use. However, it contributed only 2.09 % to the total increase in carbon storage. Numerous complicated and intertwined processes (211) drove the changes in carbon storage in the study area. The work here provides valuable information for decision-makers as well as people involved in reclamation and ecological restoration to better understand the link between carbon storage and the forces influencing it. The results can be used to integrate the goals of carbon sequestration into measures for land management. [Display omitted] • The carbon storage impacted by LULC driving processes in high groundwater coal basins was investigated. • 56.31 % of the study area has undergone land use transition during 1985–2020. • The carbon storage decreased by19.69 % during the study years. • Urbanization and village relocation was the primary driver of carbon loss, ecological restoration was the leading driver of carbon gain. [ABSTRACT FROM AUTHOR]

Water scarcity has threatened the sustainability of human life, ecosystem evolution, and socio-economic development. However, previous studies have often lacked a comprehensive consideration of the impact of water quality and existing solutions, such as inter-basin water transfer and unconventional water resources, on water scarcity. In this paper, an improved approach was proposed to quantify water scarcity levels by comprehensively considering surface water quality and multiple solutions. China's water scarcity was first assessed at a high spatial resolution on a monthly basis over the 5-year period from 2014 to 2018. Then, the driving factors including water quality and solutions were identified by a geographic detector model. Finally, an in-depth investigation was conducted to unravel the effects of water quantity solutions (i.e., inter-basin water transfer and unconventional water use), and water quality solutions (i.e., improving surface water quality) on alleviating water scarcity. Based on monthly assessments considering water quality and multiple existing solutions, the results showed that over half of the national population (∼777 million) faced water scarcity for at least one month of the year. Agricultural water use and inadequate water quality were the main driving factors responsible for China's water scarcity. Over four-fifths of the national population (∼1.10 billion) could benefit from alleviated water scarcity through a combination of water quantity and quality solutions. However, the existing solutions considered were insufficient to completely resolve water scarcity in China, especially in Northern China, persisting as a challenging issue. The results obtained from this study provided a better understanding of China's water scarcity, which could contribute to guiding future efforts aimed at alleviating water scarcity and ensuring water security in China. • Water scarcity assessment incorporated water quality and multiple existing solutions. • China's water scarcity was assessed at a high spatial resolution on a monthly basis. • Over half of the national population faced water scarcity for at least one month of the year. • Agricultural water use and inadequate water quality were the main driving factors. • Over four-fifths of the national population could benefit from alleviated water scarcity by the combined water quantity and quality solutions. [ABSTRACT FROM AUTHOR]

Based on the panel data of 22 inland provinces in China from 2010 to 2020, this study constructs and measures the level of rural ecological environment in China. The impact of the financial performance of green-listed companies on the rural ecological environment and its moderating and threshold effects are analyzed. The following conclusions are drawn: (1) During 2010–2020, China's rural ecological environment shows a trend of "fluctuating-decreasing-rising" with significant regional non-equilibrium characteristics. (2) The financial performance of green-listed companies has a significantly negative impact on rural ecology. This negative impact has a crucial heterogeneous feature, with a more significant negative impact in areas with a higher rural ecological environment index and less substantial performance in regions with a lower rural ecological environment index. (3) There is a significant positive moderating effect of education level and digitalization on the relationship between the financial performance of green-listed companies on the level of rural ecological development. As moderating variables, the digitalization and education level weakens the negative impact of green-listed companies' performance on the ecological environment. The positive impact of the financial performance of green-listed companies on the development level of the rural ecological environment is more vital in areas with higher per capita education levels and digitalization in rural areas. (4) There is a significant threshold effect on the financial performance of green-listed companies on the level of rural ecological development. When the financial performance of green-listed companies exceeds a particular threshold value, the impact of the financial performance of green-listed companies on the development level of the rural ecological environment is significantly positive. Based on the above findings, this paper puts forward corresponding countermeasure suggestions. • From 2010 to 2020, the development level of China's rural ecological environment showed a trend of "fluctuating-decreasing-rising," with noticeable regional differences. • The income level of green-listed companies has a negative impact on the rural ecological environment, and there is regional heterogeneity in this impact. • The rural education and digitalization levels have a positive moderating effect on the ecological environment. • It is found that the impact of green-listed companies on the ecological environment has a threshold effect. [ABSTRACT FROM AUTHOR]

The increasing volume of electronic waste (e-waste) poses significant challenges for efficient collection in China. Despite many measures were taken over the past two decades, the e-waste collection rate was still not high. To this end, the Chinese government issued a new policy, the collection target responsibility (CTR) policy. Under the CTR policy, however, it is essential for participants to know how to share the responsibility of collection and how much reasonable targets are set to ensure the efficiency of the collection models. Therefore, the purpose of this paper is to explore the determination of optimal collection targets and the corresponding performance from the perspective of responsibility sharing to support the successful implementation of the CTR. Firstly, the study focuses on participants including the government, manufacturers, and recyclers, and develops three CTR models, independent collection model, government cost-sharing model, and enterprise collaboration model. Secondly, collection target equations for each model are established by employing dynamic differential game analysis, and corresponding collection performances are derived. Thirdly, through practical case simulations, the evolution of collection performance is dynamically analyzed to determine reasonable collection targets for the three models, as 23.8%, 32.3%, and 34.4%, respectively. The findings highlight the effectiveness of CTR in improving e-waste collection targets and performance, with the highest levels attained when the collection responsibilities are shared by government cost-sharing and enterprise collaboration. This study provides theoretical support for setting reasonable collection targets under CTR, and assists decision-makers in developing targeted CTR implementation measures. • The CTR model frameworks involving the main participants are developed. • Three CTR models are constructed from the perspective of shared responsibility. • The collection target for each CTR model is analyzed and determined. • The performances of CTR models are analyzed and compared. • Differences in the CTR models from cost-sharing and enterprises collaboration are observed. [ABSTRACT FROM AUTHOR]

Throughout the literature, the word "heavy metal" (HM) has been utilized to describe soil contamination; in this context, we characterize it as those elements with a density greater than 5 g per cubic centimeter. Contamination is one of the major global health concerns, especially in China. China's rapid urbanization over the past decades has caused widespread urban water, air, and soil degradation. This study provides a complete assessment of the soil contamination caused by heavy metals in China's mining and smelting regions. The study of heavy metals (HMs) includes an examination of their potential adverse impacts, their origins, and strategies for the remediation of soil contaminated by heavy metals. The presence of heavy metals in soil can be linked to both natural and anthropogenic processes. Studies have demonstrated that soils contaminated with heavy metals present potential health risks to individuals. Children are more vulnerable to the effects of heavy metal pollution than adults. The results highlight the significance of heavy metal pollution caused by mining and smelting operations in China. Soil contaminated with heavy metals poses significant health concerns, both carcinogenic and non-carcinogenic, particularly to children and individuals living in heavily polluted mining and smelting areas. Implementing physical, chemical, and biological remediation techniques is the most productive approach for addressing heavy metal-contaminated soil. Among these methods, phytoremediation has emerged as a particularly advantageous option due to its cost-effectiveness and environmentally favorable characteristics. Monitoring heavy metals in soils is of utmost importance to facilitate the implementation of improved management and remediation techniques for contaminated soils. [Display omitted] • This research investigates deeply the sources, distributions, and risks of heavy metal pollution in soil throughout multiple regions of China resulting from smelting. • The categorization and summarization of mechanisms for heavy metal pollution are presented. • This work is the inaugural investigation into ecologically sustainable approaches for the remediation of smelting byproducts. • This paper examines the remediation approaches for controlling soil heavy metal pollution and evaluates their applicability. [ABSTRACT FROM AUTHOR]

As digital economy develops, its impact on green innovation and energy efficiency has become the focus of current research. To explore the impact of the current development of the digital economy on the energy industry, this paper selects the parameter of green innovation resilience, analyzes the impact mechanism of green innovation resilience on energy efficiency under the shock of digital economic development, and uses relevant data from 284 cities in China from 2011 to 2019 for empirical testing. It is found that: green innovation resilience promotes energy efficiency; low level of green innovation resilience inhibits the improvement of energy efficiency, while high level of resilience promotes energy efficiency; the initial stage of digital economic development generates resource grabbing and the effect of technological constraints, which weakens the role of green innovation resilience in promoting energy efficiency. The results indicate that the resilience of the green innovation system should be strengthened in order to fully tap the potential for promoting energy efficiency; the policy orientation of "digital greening—energy efficient" should be pursued in the development of digital economy; the rational allocation of resources and the implementation of green standards should be strengthened in the process of digital economic development; and the constraints on energy efficiency improvement in the early stage of digital economic development should be broken through by accelerating the digitalization process. • Green innovation resilience can promote energy efficiency. • Early digital economy development can lead to resource grabbing and technology constraints effects. • Pursuing the policy orientation of "digital greening—energy efficient". [ABSTRACT FROM AUTHOR]

This paper reports a novel poplar mosaic disease that occurred on the leaves of Populus alba var. pyramidalis in China. Symptoms: mosaic and chlorosis leaves, leaf abscission, leaf and young branch withering, leaf growth retard, and the destroyed and hollowed cell structures of mesophyll cells in the diseased leaves. Electron microscopy observation showed that some typical (flexible rods, virus particles 10–14 nm in width, and ca. 700 nm in length) and atypical virus particles (1400 or 2000 nm in length) of genus Potyvirus were found in the leaf exudates of the diseased poplar. De novo assembly assembled a nearly complete genome sequence of bean common mosaic virus (BCMV, 10035 nt in length) from the transcriptome sequencing data of poplar leaves. Moreover, field observation illustrated that two larvae of white-striped longhorn beetle (Batocera lineolata) inhabited and almost completely destroyed the main branch and roots of the diseased poplar plant, and a high-density population of two Chaitophorus aphid species once infected poplar plants before the occurrence of mosaic symptoms. Results suggested that BCMV is the pathogen of this novel poplar mosaic disease; moreover, results also suggested beetle and aphids that might involve in the occurrence and development of poplar mosaic disease. • This study reported the symptoms and ultra-structral a novel mosaic disease that occurred in Populus alba var. pyramidalis in China. • Near complete genome sequence of BCMV (bean common mosaic virus) and BCMV-like virus particles suggested that BCMV was associated with the occurrence of poplar mosaic disease. [ABSTRACT FROM AUTHOR]

Promoting green and low-carbon development has become the consensus of the policymakers and the academic, with green transformation of enterprises being the top priority. This paper adopts the difference-in-difference model to investigate the effect of green credit policy on green transition in China, by utilizing the "Green Credit Guidelines" (2012 Guidelines) policy as a quasi-natural experiment. Using panel data from publicly listed companies in China, an empirical investigation is conducted, we explain the dependent variable from two dimensions: economic performance and environmental performance, leading to the following results. First, the green credit policy affects the economic performance and environmental performance of treated firms positively, and the robust tests confirm the reliability of this primary conclusion. Second, the indirect impact of green credit policy on green transition can be explained through two mediating mechanism channels including internal capacity building and external market attention. In addition, the proposal of "Dual Carbon Targets" makes the impact a slight change. Finally, heterogeneous test also shows that the implementation effect of green credit policy is better in non-state-owned enterprises with high political relevance. These findings are providing valuable insights to promote green transition by designing more effective green credit policies. • We identify the effect of green credit policy on green transition. • We employ multiple econometric models to ensure the robustness. • We provide the empirical evidence for heterogeneity. • We investigate the intermediary channels from two ways. [ABSTRACT FROM AUTHOR]

Spatial misallocation of resource elements impedes the coordination in regional co-benefit in carbon emission and pollution reduction. Guided by scope economy principles, this study aims to quantifies co-benefits and explores spatial variation patterns to facilitate mutual synergy. The findings offer valuable insights for identifying optimal focus points and shaping targeted collaborative policies. Based on the multi-source provincial panel data spanning 2000 to 2021, this paper quantitatively assesses the co-benefit through the lens of marginal abatement cost. Then, the Dagum Gini coefficient was employed to investigate the disparities at the spatial level. Additionally, geographical detector is introduced to analyze the source of disparities at the factor level. Results indicate: (1) Under joint reduction, the marginal abatement cost reduces by 57.86% and 79.97% respectively, with an overall 68.77% increase in co-benefit fluctuation. (2) Provinces with low co-benefit significantly decreased after 2007, while provinces with high co-benefit concentrated in the northwest, southwest, and east. (3) Overall disparities decreased, east-central regions hold the lowest spatial disparities in co-benefit and east-west hold the most; intragroup differences and supervariable density primarily contributes to the disparity. (4) FDI significantly influence the co-benefit over the past two decades, with spatial disparities influenced by both endogenous and exogenous factors across development stages. • Joint reduction significantly lowers the marginal abatement cost and enhanced co-benefit. • East-central regions holds the lowest spatial disparity in co-benefit and east-west holds the most. • Intragroup disparities and supervariable density primarily contributed to spatial disparity. • The interplay between internal and external factors increasingly influences spatial disparities. [ABSTRACT FROM AUTHOR]

Numerous studies have discussed the economic impacts of the COVID-19 pandemic in recent years. However, the effectiveness and trade-offs of diverse countermeasures still need to be investigated, particularly under the long-term goal of low-carbon transition, which is crucial for understanding the potential impacts of the future public health emergency (PHE) related economic crisis. Given that China still faces big pressures from the potential PHE and carbon neutrality, this paper assesses the effectiveness of policy instruments in restoring the economy and advancing green development after the PHE using the Dynamic Stochastic General Equilibrium framework. Our findings reveal that the PHE imposes more constraints on the economy because of the decrease in productivity on the supply side and in consumption on the demand side. Compared to the other counterparts, the mixed stimulus can overcome the adverse impacts of the PHE while contributing to carbon reduction. Furthermore, all types of low-carbon policies investigated in this study can contribute to carbon reduction at the expense of economic growth. Meanwhile, the carbon tax realizes the target of reducing emissions with the smallest negative impact on economic growth. Thus, we suggest adopting the carbon tax policy as the most effective low-carbon measure to address uncertainties associated with the PHE. • This study explores pathways for advancing economic recovery and green development after the public health emergency. • We develop a scenario-based dynamic stochastic general equilibrium (DSGE) model. • We characterize public health emergency shocks from a supply and demand perspective. • The model introduces different carbon abatement mechanisms. [ABSTRACT FROM AUTHOR]

Global warming has accentuated the effects of extreme heat on health. Health insurance, functioning as a risk management tool, has the potential to alleviate these impacts. Consequently, this paper investigates the correlation between extreme heat events and the demand for health insurance in China. Using data from the China Health and Nutrition Survey, we have observed a substantial increase in the likelihood of residents purchasing health insurance during extreme heat events. To be specific, for every extra day of extreme heat events annually, there is a 0.3% increase in the probability of purchasing health insurance. This effect is not uniform across different demographic groups. It is particularly pronounced among middle-aged and elderly individuals, rural residents, those with lower educational levels, higher income brackets, and individuals residing in underprivileged areas with limited access to green spaces and healthcare facilities. Furthermore, our study indicates that the increased frequency of extreme heat events not only impacts individuals' physical health but also triggers negative emotions, which in turn drive risk-averse behavior related to health insurance purchases. These findings carry substantial policy implications for mitigating the economic consequences of climate change. • Extreme heat increases the likelihood of residents purchasing health insurance. • Each additional day of extreme heat boosts health insurance purchases by 0.3%. • This effect varies among different populations. • Mechanistic analyses indicate extreme heat impacting physical and mental health. [ABSTRACT FROM AUTHOR]

In this paper, we assess the effectiveness of early climate policy in emerging economies by causally evaluating the impact of China's Low-carbon City Pilot (LCCP) on city-level per-capita CO 2 emissions and CO 2 intensity of GDP over the period 2003–2017. The idiosyncrasies of the policy design pose significant challenges for causal identification, which we overcome within a synthetic control framework. Contrary to previous contributions, our results suggest that the LCCP had no significant impact on either carbon emissions or intensity. The main takeaway of our empirical investigation is that even in emerging economies, effective environmental policy requires transparent, quantifiable targets, and credible enforcement. [ABSTRACT FROM AUTHOR]

In recent years, one of the most important and innovative policy initiatives introduced by the Chinese government in the field of environmental protection and ecological civilization construction is the Central Environmental Protection Inspection (CEPI). CEPI is seen as a vital tool to encourage local implementation of environmental protection responsibility. Over the course of its operation (eight years), CEPI has transformed from the "campaign" phase to the "convention" phase. It is noted that while provincial governments face a common high-pressure environment created by CEPI, governance scenarios, behaviors, and performance vary across the country significantly. To better understand local governments' environmental governance behaviors under the transformation of CEPI, an integrated analysis framework consisting of two key elements, "central dominance" and "local proactiveness", is constructed based on the central-local interactions under the principal-agent model. Based on this framework, we conducted a multi-case comparative analysis of four classic cases, with the following findings. (1) Along with the operation of CEPI and its transformation, the interaction between the central and local governments leads to four governance scenarios: "control-active cooperation", "control-passive cooperation", "guidance-active promotion", and "guidance-passive promotion". (2) Influenced by various factors such as pressure by the central government, local governments' capabilities and governance motivations, local governments form governance behaviors with varying degrees of proactiveness and autonomy. (3) After examining the governance performance of varying behaviors, it is found that local government's "active promotion" behavior can achieve higher governance effectiveness in the "convention" phase. Therefore, it is of policy implication that local governments should be guided to transit from "passive cooperation" to "active promotion". This paper has important guiding significance for understanding local environmental governance behaviors under strong top-down institutional pressure. • CEPI is one of the most important policy initiatives introduced by the Chinese gocernment in eco-environmental protection. • The interaction between the central and local governments leads to four different governance scenarios. • Governance scenarios,behaviors and performance of local goverments vary acorss the country significantly under CEPI. • Local government's "active promotion" behavior can achieve higher governance effectiveness in the "convention" phase. [ABSTRACT FROM AUTHOR]

Accurately predicting carbon trading prices using deep learning models can help enterprises understand the operational mechanisms and regulations of the carbon market. This is crucial for expanding the industries covered by the carbon market and ensuring its stable and healthy development. To ensure the accuracy and reliability of the predictions in practical applications, it is important to evaluate the model's robustness. In this paper, we built models with different parameters to predict carbon trading prices, and proposed models with high accuracy and robustness. The accuracy of the models was assessed using traditional survey indicators. The robustness of the CNN-LSTM model was compared to that of the LSTM model using Z-scores. The CNN-LSTM model with the best prediction performance was compared to a single LSTM model, resulting in a 9% reduction in MSE and a 0.0133 shortening of the Z-score range. Furthermore, the CNN-LSTM model achieved a level of accuracy comparable to other popular models such as CEEMDAN, Boosting, and GRU. It also demonstrated a training speed improvement of at least 40% compared to the aforementioned methods. These results suggest that the CNN-LSTM enhances model resilience. Moreover, the practicality of using Z-score to evaluate model robustness is confirmed. • Deep learning by combined CNN-LSTM networks for carbon price forecasting. • Hyperparameter tuning of deep learning models for improving forecast accuracy. • CNN-LSTM models outperform single CNN models and single LSTM models. • Performance metric of deep learning for abrupt changes in carbon price variation. [ABSTRACT FROM AUTHOR]

Rapid developments in environmental infrastructure have contributed to significant improvements in green total factor productivity, but further investigation is required to provide a detailed assessment to understand the policy mechanisms involved. This paper analyzes environmental progress in China through MMQR, CCEMG, and AMG as empirical strategies for 30 provinces in China. Our empirical results reveal that energy optimization through renewable energy is the most effective channel to improve green total factor productivity, though it is not the only available option. Since environmental regulations, infrastructure development, and green technology innovation also directly impact energy efficiency, adopting these within policy channels will positively impact environmental sustainability. Our empirical approach helps suggest novel environmental policy suggestions. In particular, policymakers must introduce structural changes within energy developments to foster renewable energy. Furthermore, China must increase environmental spending to upgrade its energy infrastructure further and solve ecological issues. These insights offer valuable policy guidance for decision-makers in China and globally, aiming to foster economic and environmental sustainability and achieve zero-carbon transition goals. • The current study analyses the role of green factor productivity in zero carbon transition. • We use 30 chinese provincial datasets from 2005 to 2020. • Energy transition is the most effective channel to improve green total factor productivity. [ABSTRACT FROM AUTHOR]

Theoretically, agricultural insurance influences farmers' use of pesticides by changing the expected income of agricultural production. Full-cost insurance, with high guarantee and high compensation characteristics, may significantly affect farmers' pesticide use. First, this paper constructs a production function to characterize and compare the marginal incomes of insured and uninsured farmers under risk uncertainty and analyses how insured farmers can increase marginal income by increasing or reducing factor inputs. Considering scale differentiation, it discusses pesticide use strategies different types of farmers may adopt to maximize household utility. Second, using survey data of the pilot counties of full-cost insurance for wheat in Henan Province, China, the simultaneous equation model is used for empirical testing. The results reveal the following: (i) Farmers' insurance participation and pesticide application behaviour are not mutually independent. (ii) For the whole sample, full-cost insurance for wheat has a significant pesticide reduction effect. (iii) However, considering scale differentiation, pesticide application decreases significantly among insured ordinary farmers but does not change significantly among insured large-scale farmers. Third, policy measures are proposed to activate the green development function of agricultural insurance. • Construct a production function and a utility function to conduct mechanism analysis. • Estimate simultaneous equation model based on pilot area household level dataset. • Analyse the effect of full-cost insurance on pesticide input behavior. • Find full-cost insurance significantly reduces the pesticide use of ordinary farmers. • But insignificant effect on the pesticide use of large-scale farmers. [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI) has been proved to be an important engine of green economic development, yet how it will affect the internal structure of green economy is unknown. The aim of this study is to examine the impact and its mechanism of AI on green total factor productivity (GTFP) from the internal-structure perspective, by using provincial panel data of China from 2009 to 2021 and global Malmquist index. The main research results show that: (1) the development of AI contributes to China's GTFP growth. And this effect is more significant in undeveloped areas; (2) AI promotes China's GTFP growth mainly by improving resource allocation efficiency, while it exerts little impact through the paths of technological progress and scale efficiency; (3) the transmission mechanism of AI on GTFP varies greatly among China's three main regions. In the eastern region, AI improves GTFP mainly by both advancing technological progress and improving resource allocation efficiency, while in central region AI contributes to GTFP growth mainly through technological progress. Compared with the eastern and central regions, AI in the western region plays a stronger impact on GTFP through the channel of improving scale efficiency. This study helps to understand the pathways of artificial intelligence affecting the transformation of green economic growth and formulate differentiated regional policies in light of local conditions. • This paper studies the effects of AI on China's GTFP from internal-structural perspective. • GTFP is decomposed into three internal factors by the global Malmquist index. • AI has positive effect on GTFP through different impacts on internal factors. • Improving resource allocation efficiency is the most critical channel of AI on GTFP. • AI plays a more significant role in promoting GTFP in less developed areas. [ABSTRACT FROM AUTHOR]

A significant milestone in China's carbon market was reached with the official launch and operation of the National Carbon Emission Trading Market. The accurate prediction of the carbon price in this market is crucial for the government to formulate scientific policies regarding the carbon market and for companies to participate effectively. Nevertheless, it remains challenging to accurately predict price fluctuations in the carbon market because of the volatility and instability caused by several complex factors. This paper proposes a new carbon price forecasting framework that considers the potential factors influencing national carbon prices, including data decomposition and reconstruction techniques, feature selection techniques, machine learning forecasting techniques for intelligent optimisation, and research on model interpretability. This comprehensive framework aims to improve the accuracy and understandability of carbon price projections to respond better to the complexity and uncertainty of carbon markets. The results indicate that (1) the hybrid forecasting framework is highly accurate in forecasting national carbon market prices and far superior to other comparative models; (2) the factors driving national carbon prices vary according to the time scale. High-frequency series are sensitive to short-term economic and energy market indicators. Medium- and low-frequency series are more susceptible to financial markets and long-term economic conditions than high-frequency series. This study provides insights into the factors affecting China's national carbon market price and serves as a reference for companies and governments to develop carbon price forecasting tools. • A hybrid carbon price prediction model named FS-CEEMDAN-VMD-GWO-LightGBM is proposed. • Accurately predicted the national carbon price in China using multi-influence factor time series data. • Using a data decomposition and reconstruction strategy, the model's accuracy was improved. • The SHAP algorithm is used to assess the impact of various influencing factors on the fluctuations of carbon prices. [ABSTRACT FROM AUTHOR]

To address global climate change, achieving carbon peak and carbon neutrality has become a global consensus. However, the means to simultaneously achieve carbon reduction and promote green economic development, particularly in developing countries, require further investigation. This study evaluates the impact of e-commerce on CO 2 emissions. Through an examination of the effects of the National E-Commerce Demonstration City (NEDC) policy from 2006 to 2017, this paper reveals that e-commerce growth facilitated by the NEDC policy resulted in a 7.89% reduction in total CO 2 emissions and a per capita reduction of 1.1146 tons in the pilot cities. Mechanism analysis demonstrates that the upgrading of industrial structure, development of digital finance, and the growth of innovation and entrepreneurship serve as primary pathways for this impact. The robustness of the findings is supported by parallel trend tests, placebo tests, and additional sensitivity analyses. Furthermore, the research reveals that the NEDC policy exhibits a more significant reduction in CO 2 emissions in cities with higher levels of economic development and non-resource-based cities. Welfare analyses show that the NEDC policy has significant socio-economic effects. These findings provide new evidence on the environmental effects of the digital economy and offer insights into achieving carbon neutrality. • The National E-commerce Demonstration Cities (NEDC) policy reduced CO 2 emissions. • Optimizing industrial structure, enhancing digital finance, and promoting innovation and entrepreneurship are mechanisms. • The effect is more pronounced in cities with high economic levels and high resource dependence. • The NEDC policy substantially enhanced social welfare by reducing CO 2 emissions. [ABSTRACT FROM AUTHOR]

In this paper, the Cu and Ni accumulation and contamination levels in agricultural soils and wheat around a smelter in Jinchang City in northwest China were investigated with a combination of field investigations and indoor analytical tests, using a soil–wheat system as the study area. The average Cu and Ni contents in the soil were 119.50 mg kg–1 and 123.40 mg kg–1, respectively, both of which exceeded the local soil background values. The Cu and Ni contents in 46.15% o and 26.92% of sampling sites, respectively, exceeded the screening values for soil contamination risk in agricultural land in China. The average Cu content in different parts of wheat was in the order of roots (24.22 mg kg–1) > leaves (20.11 mg kg–1) > husks (5.51 mg kg–1) > grains (4.05 mg kg–1) > stalks (3.74 mg kg–1). Furthermore, the average Ni content ranked as leaves (24.64 mg kg–1) > roots (21.12 mg kg–1) > husks (6.95 mg kg–1) > stalks (1.75 mg kg–1) > grains (0.38 mg kg–1). The health risk evaluation showed that with average hazard index values of 0.88 for adults and 1.04 for children for Cu and Ni in wheat grain, wheat in this region is unlikely to pose a health risk to adults but may pose a lesser health risk to children. The Ni bio–concentration and translocation factors in the husk and leaves of wheat were greater than those of Cu and smaller than those of Cu in the other parts of wheat. The results of this study provide basic data for the remediation of heavy metal contamination in local agricultural soils. • The soil and wheat around smelters and mining areas are polluted. • Wind power and direction can affect the distribution of heavy metals. • Wheat grains can cause minor health effects for children. • Compared with Ni, Cu is more easily accumulated and transported in wheat. [ABSTRACT FROM AUTHOR]

Accounting for the ecosystem service values (ESVs) and discussing the relationship between the ESVs and economic development can help achieve sustainable ecological development. Therefore, this paper evaluates the county-level ESVs of various land types in China, and depicts the distribution of ESVs in various urban agglomerations. In addition, the nonlinear relationship between ESVs and economic development is revealed. The main findings are as follows: (1) From 2000 to 2018, the ESVs in China decreased, and the decline rate of ESVs in urban agglomerations is much higher than that of China as a whole. (2) The decline rate of ESVs in core cities is much higher than in urban agglomerations, and the decline rate of ESVs is higher in areas close to core cities and lower in areas far from core cities. (3) The ecological Kuznets curve of China has a positive "U" shape, and the ecological Kuznets curve of urban agglomerations has an "N" shape; the ecological Kuznets curve of core cities has a positive "U" shape, while the ESVs of other cities decreases monotonically with the increase of the economic level. • This paper fills the data gap of ESVs at the county level in China. • The reduction rate of ESV in urban agglomeration is larger than the national level. • The reduction rates of ESV in core cities are larger than the urban agglomerations. • The ecological Kuznets curve is "U"-shaped in China. • Non-urban agglomeration cities are still left to the inflection point. [ABSTRACT FROM AUTHOR]

Digital technology is an effective way to realize the carbon neutrality target in China. Therefore, based on panel data at the city level in China from 2006 to 2016, we take the e-commerce pilot policy as a quasi-natural experiment, using the staggered difference-in-differences (DID) method to explore the effect of digital technology development on carbon emissions and its transmission mechanism. The conclusion of this paper shows that (ⅰ) the e-commerce pilot policy has significantly reduced carbon emissions. After a series of robustness tests, this empirical conclusion is still valid. (ⅱ) The inhibitory effect of different waves of e-commerce pilot cities on carbon emissions sequentially decreases. The e-commerce pilot policy has a greater effect on reducing carbon emissions in non-old industrial based cities and non-resource-based cities. (ⅲ) Implementing the e-commerce pilot city policy mainly reduces urban carbon emissions by optimizing resource allocation, reducing energy consumption and upgrading the industrial structure. (ⅳ) In addition, implementing the e-commerce pilot city policy has a significant positive carbon-reducing linkage effect with the carbon trading pilot policy and the low-carbon city pilot policy. The findings of this paper provide empirical evidence for carbon emission reduction, which has implications for upgrading urban construction patterns and promoting green urban development. • The construction of national e-commerce pilot cities has significantly reduced the carbon emission of cities. • The inhibitory effect of different batches of e-commerce pilot cities on carbon emissions sequentially decreases. • Playing more significant effect in non-old industrial based cities and non-resource-based cities. • Reducing urban carbon emissions by optimizing resource allocation and reducing energy consumption. • Having a significant positive carbon-reducing linkage effect with carbon emissions mitigation policies. [ABSTRACT FROM AUTHOR]

This paper examines the drivers of distribution of pollution-intensive enterprises (PIEs) at the intraurban level that are less studied. Employing the complete spatial database of PIEs obtained from the National Economic Census of 2004, 2008, and 2013, the paper analyses the spatial restructuring of PIEs within Foshan, China, a typical manufacturing city in transition. We find that the changing role of environmental regulation induced by the environmental policy regime transformation has resulted in the siting strategy shift of PIEs, and both the 'Pollution Haven Hypothesis' and the 'Porter Hypothesis' have been overly simplified in the research conducted at the regional or global level. Based on the Foshan case, we further conceptualize the pattern of spatial restructuring of PIEs that would help to understand the fast green economy transition taking place in Chinese cities, followed by some policy and research implications. • The relocation and drivers of polluting firms at a local level are studied. • The environmental policy regime shift leads to the siting strategy shift of firms. • Polluting firms initially seek a pollution haven before 2008. • New firms after 2008 site in areas with strict environmental regulation. • The local government motivation is more important in the Chinese context. [ABSTRACT FROM AUTHOR]

This paper is to test the relationship between temperature change and industrial green innovation by combing data of China's average temperature change in cities with green patent database of listed companies.First, the results find that rising annual average temperature can inhibit green innovation. For every 1 °C increases in summer, green innovation reduces by 3.2%, and for every 1 °C increases in winter, green innovation increases by 1.9%. Second, rising summer temperature inhibits green innovation by crowding out research and development (R&D) funds and draining labor. While, rising temperature increases green innovation by increasing environmental responsibility and green venture capital. Third, differences in green R&D difficulty, process and objectives were also compared, temperature change has a stronger inhibition on green process innovation than green product innovation. And rising temperature inhibits green exploratory innovation and promotes green developmental innovation. Fourth, rising temperature increases green innovation in polluting firms as temperature is higher than 21 °C. And it inhibits green innovation in clean firms as temperature is higher than 27 °C. This paper can provide policy implications on climate regulation and promoting green innovation. [Display omitted] • For 1 °C increases in summer, industrial green innovation reduce by 2.1%. • Influence paths include cost inhibition effect and responsibility forcing effect. • Temperature increases green simple innovation and weaken green complex innovation. • Suitable temperature for green innovation is 18°C–27 °C. • Classify green innovation from the difficulty, process and purpose of R&D. [ABSTRACT FROM AUTHOR]

The Chinese government has declared a determination at the 75th United Nations General Assembly that China will improve its independent contribution and adopt more powerful measures to peak the carbon emissions before 2030. However, such strict implementation of carbon reduction policies is bound to bring the cost of sacrificing economic development. In such a context, this paper tries to use shadow price to measure the average social cost of emission reduction, marginal abatement cost to depict the pressure to reduce carbon emissions based on non-radial distance function, and provides an optimal scheme for provincial emission reduction to minimize the national cost of emission reduction based on variable-coefficient model. Results show that: First, the average value of shadow price is 15.91 and varies widely among regions, which means on average reducing one unit of carbon emissions will sacrifice 15.914 yuan RMB of economic output, and there exists possibility of carbon transactions across regions; Second, on the one hand, marginal abatement cost of carbon emission for most regions presents an upward tendency over time, which means greater economic costs have to be sacrificed with economic development in the future; On the other hand, marginal abatement cost is much higher in regions with high economic level than that in the economically undeveloped areas, which indicates reducing carbon emissions is becoming increasingly difficult and would pay more economical cost in economically developed regions; Third, the optional allocation scheme of CO2 reduction derived from this research is better than administrative ways of Grandfathering and Benchmarking in terms of minimizing emission reduction cost. Results of this paper indicate that larger carbon trading market can be implemented in China to economically fulfill the commitment of peaking carbon emissions. • This paper provides a scheme to minimize the carbon emission reduction cost. • Shadow price and marginal cost of carbon emission are estimated. • More comprehensive carbon trading market can be implemented in China. [ABSTRACT FROM AUTHOR]

Modelling flood susceptibility is an indirect way to reduce the loss from flood disaster. Now, flood susceptibility modelling based on data driven model is state-of-the-art method such as ensemble learning and deep learning. However, the effect of deep learning coupling with ensemble learning models in flood susceptibility modelling is still unknown. Therefore, the aim of this paper is to propose three deep learning coupling with ensemble learning models by combining the deep learning (DL) with Filtered Classifier (FC), Rotation forest (RF) and Random Subspace (RSS) and explore the effect of coupling method for modelling flood susceptibility. The key step of this paper is as following: firstly, a Dingnan County which is lied in the Jiangxi Province of China is chosen as a case study, single flood event point and random sampling method was applied to generate the flood and non-flood data, respectively, then frequency ratio was utilized to analyze the relationship between each influencing factor and flood occurrence, based on the value of VIF, Spearman's correlation and One R classifier, the result show that there is no multicollinearity between each influencing factor, ten influencing factors have contribution to the flood occurrence and all of them are applied to construct the coupling model. Finally, the DL, FC-DL, RF-DL and RSS-DL were applied to produce flood susceptibility maps. Then, several statistical indexes such as area under the curve (AUC), Kappa index, accuracy (ACC), and F-measure were used to assess the accomplishment of these coupling models. For the train data, the FC-DL model acquired the highest AUC value (0.996), followed by RF-DL (0.944), RSS-DL (0.934), and DL (0.934). For the validation data, the result showed that all models have a good accomplishment (AUC>0.8). In a word, the deep learning coupling with ensemble learning models demonstrates the more reliable and excellent performance. Hence, the proposed new method will help the government for land use planning and can be applied in other area around the world. • RSS-DL model shows the stable and well ability. • One R classifier were used to select variables. • Deep ensemble learning mode was used to model flood susceptibility. [ABSTRACT FROM AUTHOR]

Policy interaction is an important way to deal with increasingly complex environmental problems. This paper examines the investment-related tax cuts and the policy interaction with environmental regulation on firms' emission reduction strategies. Taking China's value-added tax (VAT) reform as a quasi-natural experiment and considering the interaction with the emission reduction target policy, our difference-in-differences estimation shows that: the average effect of the VAT reform reduces firms' sulfur dioxide (SO 2) emission intensity by 16.6%, due to the adoption of emissions reduction strategies in the production processes; the interaction effect between the VAT reform and environmental regulation incentivizes firms to additionally reduce SO 2 emission intensity, due to the adoption of both production processes and end-of-pipe reduction strategies. Our findings are more evident for firms with tight financial constraints. Overall, this paper reveals the micro-mechanisms of how the tax policies incentivize firms to choose emission reduction strategies and highlights the importance of the interaction effects between environmental and non-environmental policies, thus providing implications for the policy mix of environmental regulation and tax-cut incentives to promote pollution reduction and improve business performance. [ABSTRACT FROM AUTHOR]

Environmental taxation is regarded as an effective tool to improve air quality in China, but its distributional effects causing serious disparity among multi-groups and multi-regions are understudied. Here this paper constructs a multi-regional dynamic recursive computable general equilibrium (CGE) model to explore the distributional effects of China's environmental taxation among different income groups and regions, by specifying the elasticity parameters of urban households' consumption in the model, and combining with various micro-data such as household survey data and environmental statistics database. This paper simulates the air pollution reductions of China's environmental taxation, and the impacts on the income and expenditure of households with various environmental tax rates or manners of tax revenue recycling. Results have shown that China's environmental taxation will widen the gap between different income groups and different regions. Also, such adverse distributional effects will be increased by higher environmental tax rates. However, recycling environmental tax revenues to both households and enterprises can reduce the losses of households' income and consumption. Yet recycling revenues to enterprises is more effective in narrowing the gap between income groups and regions while improving regional economic development. Our findings may pave a way to design appropriate environmental tax rates and tax revenue recycling manners for China's future environmental tax policies at the regional level. [Display omitted] • A multi-regional CGE model is constructed to explore the distributional effects. • Various environmental tax rates and tax revenue recycling manners are considered. • Low-income households and underdeveloped regions will bear more tax burden. • Recycling revenues to enterprises is more effective in reducing wealth disparity. [ABSTRACT FROM AUTHOR]

Green technology innovation (GTI) is an effective way to promote the green development of economy, and government environmental regulations are an important means to encourage enterprises to carry out GTI. Taking Chinese A-share listed enterprises from 2010 to 2019 as samples, this paper divides environmental regulations into three categories: command-based environmental regulation (ER 1), market-based environmental regulation (ER 2) and voluntary environmental regulation (ER 3), studies their impact on enterprise GTI, and discusses the joint effect of enterprise research and development (R&D) investment and government support from the perspective of internal and external linkage of enterprises. In addition, this paper also analyzes the compound effect and time effect of environmental regulation. The research conclusions are as follows: (1) From the perspective of policy types, both ER 1 and ER 2 could stimulate enterprises to carry out GTI, and the promotion effect of green utility model patents is slightly higher than that of green invention patents. ER 3 inhibits enterprise GTI. In addition, this paper finds that the effect of three environmental regulations acting at the same time is greater than that of one of them. (2) The mechanism analysis shows that the R&D investment of enterprise positively could moderate the relationship between ER 2 and green invention at the significance level of 5%, positively moderate the relationship between ER 2 and green utility model patent at the significance level of 1%, and negatively moderate the relationship between ER 3 and green utility model patent at the significance level of 5%. The government support could moderate the relationship between environmental regulation and green utility model patents at the significance level of 5% and 10%. (3) The effect analysis shows that the transformation rate of GTI in China needs to be improved. The three environmental regulations could have an effect on enterprise GTI in a short period, and ER 1 has the fastest effect. (4) Considering the differences in the level of economic development and resource endowments in various regions of China, this paper classifies the sample enterprises and finds that the impact of environmental regulation on enterprise GTI is heterogeneous in terms of location, ownership nature, factor density and industry type. The research results provide the important reference for the formulation and implementation of environmental regulation policies according to local conditions. • ER 1 and ER 2 could stimulate enterprise GTI. • The union effect of ER 1 , ER 2 , and ER 3 is better than one of them. • R&D positively moderates the relationship between ER 2 and GTI. • ER 1 has the fastest effect on GTI in three kinds of environmental regulations. • The effect of ER on GTI shows heterogeneity for different enterprise features. [ABSTRACT FROM AUTHOR]

Shrinking cities are a category of cities characterized by population loss, and the environmental problems of these cities are often neglected. Using panel data from 2012 to 2019, this paper investigates the spatial and temporal distribution characteristics of carbon emissions in shrinking cities in China and the driving factors. The results find that: (1) From 2012 to 2019, carbon emissions tend to increase in shrinking cities and decrease in non-shrinking cities. Due to earlier industrial development and ecological neglect, shrinking cities in Northeast China have higher carbon emissions than other regions. (2) Population size, industrial structure and public services promote the growth of carbon emissions in shrinking cities. The influence of living environment on carbon emissions in shrinking cities is not significant. There is an environmental Kuznets curve (EKC) relationship between economic level and carbon emission. (3) In shrinking cities, the increase in commuting time and distance due to spatial expansion promotes the growth of carbon emissions. Foreign investment decreases with the loss of population, which reduces carbon emissions. Technological progress gradually declines as investment in science and technology decreases, which makes carbon emissions grow. This paper clarifies the driving factors of carbon emissions in shrinking cities in China, and therefore, the findings of this paper have important reference value for the formulation of carbon reduction policies in shrinking cities in developing countries. • Carbon emissions in shrinking cities tend to grow. • Shrinking cities have higher carbon emissions compared to non-shrinking cities. • The characteristic factors of shrinking cities affect carbon emissions. • Carbon emissions from shrinking cities have spatial effects. [ABSTRACT FROM AUTHOR]

This paper analyzes the overall and time-varying efficiency of China's carbon market, which is crucial for carbon risk management and policymaking. Due to the severe illiquidity problems other pilots face, we first select Shenzhen, Guangdong, and Hubei pilots out of the eight carbon pilots for our study based on the statistical analysis. We then test the overall efficiency of the markets using the LM, CD, and Wild-Bootstrap variance ratio test. The sliding window method is combined with the above three variance ratio test methods to validate the time-varying efficiency. The results prove that the overall efficiency of the three carbon pilots has not yet reached a weak form. And we observe that the short-term efficiency is time-varying and may be weak-form. The study further found Hubei to be the most efficient carbon pilot, followed by Guangdong and Shenzhen. Finally, this paper conducts a qualitative analysis on the low efficiency from five aspects namely carbon trading rules, market liquidity, price volatility, trading volume, and types of trading products. Several conclusions and recommendations are proposed for policymakers and investors. • Sliding window method is combined with a series of variance ratio test methods. • The overall and time-varying efficiency of China's carbon market is tested. • China's carbon market has not reached weak-form efficiency. • Hubei is the most efficient carbon pilot. • Reasons for low efficiency are analyzed. [ABSTRACT FROM AUTHOR]

China's urban housing price has dramatically increased in the past decade, surpassing income growth and raising fears of a real estate bubble. The increase in housing price is also accompanied by a growing number of vacant apartments. This paper argues that income inequality is one important factor driving up both the housing price relative to income and the housing vacancy rate. Using data from China's Urban Household Survey, the paper empirically examines the effects of income inequality on the housing price-to-income ratio and housing vacancy rate within each city. We find that the income GINI coefficient is positively related to the housing price-to-income ratio as well as the housing vacancy rate. In particular, a one percentage higher GINI coefficient is associated with increases in the housing price-to-income ratio and housing vacancy rate of 0.026 points and 0.166 percentage points, respectively. During 2002 and 2009, approximately 6% of the increase in the housing price-to-income ratio and 10% of the increase in the housing vacancy rate can be attributed to the increase of the GINI coefficient. Further studies show that the development of the capital market and housing rental market are somewhat helpful in mitigating the associations between income inequality and the housing price-to-income ratio and vacancy rate. [ABSTRACT FROM AUTHOR]

This paper examines why and how public housing provision may affect the supply of market-based housing in urban China. We illustrate how both the demand mechanism and the cost mechanism may lead to the crowding-out effect of public housing provision on market housing provision in post-reform urban China. Based on panels of both provincial-level and city-level data for the period of 1999–2010, our empirical results shows that: (1) the supply of public housing has crowding-out effect on the supply of market housing in China but its degree is generally moderate; (2) the crowding-out effect varies substantially under different scenarios; (3) the crowding effect changes over time but its estimation accuracy is gradually improving in the sample period. The findings in this paper have useful implications to the design of public housing programs in general. [ABSTRACT FROM AUTHOR]

Social media has been playing an increasingly important role in the sharing of individuals' opinions on many financial issues, including credit risk in investment decisions. This paper analyzes whether these opinions, which are transmitted through social media, can accurately predict enterprises' future credit risk. We consider financial statements oriented evaluation results based on logit and probit approaches as the benchmarks. We then conduct textual analysis to retrieve both posts and their corresponding commentaries published on two of the most popular social media platforms for financial investors in China. Professional advice from financial analysts is also investigated in this paper. We surprisingly find that the opinions extracted from both posts and commentaries surpass opinions of analysts in terms of credit risk prediction. [ABSTRACT FROM AUTHOR]

This paper examines how stakeholder demand and compliance capacity jointly shape corporate environmental coping strategies and subsequently environmental protection practices. A four-dimensional classification of coping strategies—formalism, accommodation, referencing, and self-determination—is conceptualized. Drawing on survey and interview data collected from manufacturing enterprises in China between 2010 and 2012, the paper shows that compared with formalism and accommodation, coping strategies of referencing and self-determination are associated with stronger environmental protection practices. Enterprises adjust their coping strategies by taking into account the constraints defined by both their internal and external environments. The results also demonstrate the potential synergetic effects of state and non-state stakeholders working together in promoting better corporate environmental coping strategies and environmental practices in China. [ABSTRACT FROM AUTHOR]

Constructed on the total-factor analysis framework, this paper develops a comprehensive evaluation system and adopts the Super-SBM model to both analyze and enunciate the characteristics of tourism eco-efficiency in China during 2000–2017. This paper also identifies the determinants associated with spatial differentiation of tourism eco-efficiency by employing a novel geographical technique, namely the Geographical Detector Model. The results indicate that the tourism eco-efficiency exhibits great potential for growth. Besides, pure technical efficiency drives the optimized development of eco-efficiency. Also, there is significant spatial variations in eco-efficiency across different provinces and regions in China. Urbanization contributes to tourism eco-efficiency remarkably, followed by openness, technical level, economic scale, industrial structure, capital effect, environmental regulation, and tourism growth. The relational interrelations of tourism eco-efficiency determinants are the bi-enhancement and the nonlinear-enhancement interactions. The implications of research findings are discussed and may be applied to a multitude of corporate environmental-economic management scenarios. • An evaluation framework was developed to identify the macro external determinants that may affect tourism eco-efficiency. • Urbanization contributes to tourism eco-efficiency remarkably. • The relational interrelations of tourism eco-efficiency determinants are the bi-enhancement and the nonlinear-enhancement. • Our results verify the rationality of the tourism-led growth hypothesis (TLGH) and the EKC hypothesis. [ABSTRACT FROM AUTHOR]

As a typical example of an innovative governance environment, innovative city has become the focus of political and academic circles. Discussing the green innovation effect of this policy is beneficial in providing decision support for enhancing urban green innovation capability and solving the dilemma of urban resources. Based on data from 241 cities in China from 2005 to 2017, this paper takes innovative city construction as a "quasi-natural experiment" and uses the difference-in-differences method to empirically study the impact of China's innovative city construction on urban green innovation. The results show that innovative urban construction: has a positive effect on improving urban green innovation, and that this effect will gradually increase with time; promotes urban green innovation by expanding the scope of technology application, improving the efficiency of resource allocation and promoting the adjustment of industrial structure; and presents heterogeneity in cities' location, size and hierarchy. Finally, this paper proposes that the government should promote innovative policies in an orderly manner on the basis of following the principle of adapting measures to local conditions, as well as incorporating green innovation performance into the evaluation system for innovative city construction. • Innovative city has a continuous positive impact on urban green innovation. • Three impact paths of innovative cities on urban green innovation are proposed. • The effect of green innovation is more obvious in the central and western regions. • The city size and green innovation effect develop in an inverted U shape. • Cities with higher hierarchy show stronger response to the green innovation effect. [ABSTRACT FROM AUTHOR]

Bovine rotavirus is the primary pathogen causing diarrhea in cattle and can be transmitted vertically through the placenta. It mainly presents with clinical signs such as depression, loss of appetite, diarrhea, vomiting, and dehydration. A systematic review and meta-analysis were conducted to assess the prevalence of BRV infection in mainland China. We conducted a literature search on the prevalence of BRV infection in pigs between Jan 1, 1979 and Dec 31, 2021 in English and Chinese databases, including PubMed, Google Scholar, Cochrane library, Clinical Trials, VIP, CNKI, and WanFang database. Selections were made based on the title and the abstract of the paper, Search strings included if they reported the cattle samples of more than 15 cattle and provided information that allowed us to establish the prevalence of BRV. Moreover, we excluded repeated studies, reviews, other hosts. Finally, we extracted the number of cattle with BRV infection from the obtained studies and provided information that permitted us to estimate the prevalence of BRV infection in cattle in mainland China. The data of 29 articles (including data on 10677 cattle) are compliant with the standards. The pooled prevalence of BRV in cattle in China was 46%（6635/10677）, the pooled prevalence of BRV in cattle from Northeast China (40%) was significantly lower than those from other regions. In addition, the prevalence of BRV was associated with publication time of paper, detection methods, age of cattle, and clinical symptoms（diarrhea, etc.). Our findings suggest that BRV infection is common among cattle in China. It is, therefore, necessary to carry out further research and monitor the prevalence of BRV infection. Furthermore, powerful and effective regulatory measures should be taken to prevent the transmission and spread of BRV among cattle populations. • The data of 29 articles met the selection criteria, and the prevalence of BRV was 46% in China. • Cattle's age was a risk factor associated with the prevalence rate of BRV. • This study may help to control treatment costs and overuse of antibiotics to improve food safety and public health. [ABSTRACT FROM AUTHOR]

This paper explored the drought propagation phenomenon based on meteorological, hydrological, and agricultural aspects in the Yangtze River basin (YRB), China. To evaluate meteorological, hydrological, and agricultural droughts, this paper used three drought indices, standardized precipitation evapotranspiration index (SPEI), standardized runoff index (SRI), and standardized soil moisture index (SSMI), respectively. The community land model (CLM) in the YRB to generate the monthly evapotranspiration, soil moisture, runoff data, which are required for the estimation of drought index, were applied. Different mean durations (6-and 12-month) were used for drought estimation, and propagations of meteorological to hydrological and meteorological and agricultural droughts were investigated for different durations as SPEI6-SRI6, SPEI6-SSMI6, SPEI12-SRI12, SPEI12-SSMI12. The average drought propagation between 1950 and 2010 presented the highest autocorrelation and correlation with one-month lags in four combinations of drought indices in SPEI6-SRI6, SPEI6-SSMI6, SPEI12-SRI12, and SPEI12-SSMI12. Additionally, this paper estimated the optimal lags of SPEI-SRI and SPEI-SSMI drought propagations using mean 6-and 12-month lag times for six representative drought periods. Therefore, the propagation phenomenon of meteorological to hydrological and to agricultural droughts were confirmed in the YRB. • SPEI, SRI, and SSMI indices have been applied to the Yangtze River basin (YRB). • Propagation analysis of SPEI-SRI and SPEI-SSMI have extended to 1951–2010. • Mean 12-month duration shows clearer drought propagation than mean 6-month duration. • SPEI-SSMI presents 1–7 months propagation time. • SPEI-SRI presents 1–2 months propagation time. [ABSTRACT FROM AUTHOR]

In recent years, China has focused its development on technological innovation, trying to achieve a win–win situation between environmental protection and economic growth, and it has formulated a series of policies to promote technological innovation. Taking China's national independent innovation demonstration zone (NIIDZ) policy as an example, this paper empirically investigates the impact of China's innovation policy on haze pollution by using a difference-in-differences (DID) model. The results show that the NIIDZ policy promotes the governance of urban haze pollution and confirms the applicability of the experimentalist governance model in the practice of innovation policy in developing countries. Dynamic analysis shows that the NIIDZ policy has an experience accumulation effect. This policy can continue to promote haze control for at least 6 years, and the policy effect increases year by year. Action mechanism analysis shows that the NIIDZ policy can inhibit urban haze pollution by promoting urban technological innovation and high-tech industrial agglomeration. The estimation results of the spatial DID model show that the NIIDZ policy not only inhibits haze pollution in NIIDZ cities but also has an inhibitory effect on haze pollution in the surrounding non-NIIDZ cities and the NIIDZ cities, which confirms the positive externality characteristics of policy diffusion theory and environmental governance. The conclusions of this paper have important theoretical value for understanding the ecological effect of innovation policy and provide experience for developing countries to implement an experimentalist governance model. • The NIIDZ policy significantly inhibits urban haze pollution. • The haze control effect of the NIIDZ policy shows a characteristic of increasing year by year. • Technological innovation and high-tech industrial agglomeration play a mediation role. • The NIIDZ policy has spatial spillover effect. [ABSTRACT FROM AUTHOR]

Based on the tightening regulation of carbon emissions, China has launched the pilot carbon emission trading scheme (CETS) since 2013. There is growing empirical evidence of the actual effect of CETS to promote enterprises' productivity which is characterized by total factor productivity (TFP). However, most studies ignored the further analysis of influence mechanisms. This paper aims to explore the impact of CETS on the TFP of enterprises and discuss the mediating role of government participation and carbon trading market efficiency. Using data from A-share listed enterprises from CETS-covered enterprises, this paper employed a combination of the propensity score matching (PSM) and difference-in-differences (DID) strategies and found that the CETS has a statistically significant positive impact on the TFP of enterprises, and the positive effect has been maintained for six years since its inception. The moderation analysis indicated that: (1) two dimensions of government participation in terms of the market incentive and government supervision significantly moderate the positive impact of CETS on TFP of enterprises; (2) two dimensions of carbon trading market efficiency in terms of the market scale and liquidity significantly moderates the positive impact of CETS on TFP of enterprises. In light of Chinese pilots CETS policy, the study highlights the important moderating roles of government participation and high carbon trading market efficiency on enterprise's TFP. [Display omitted] • Chinese pilots CETS significantly improved the TFP of enterprises by 9.48%. • The government participation moderates the positive impact of CETS on enterprises' TFP. • The higher carbon trading market efficiency is, the greater the moderating effect of CETS on TFP is. [ABSTRACT FROM AUTHOR]

With rapid urbanization and industrialization, environmental pollution caused by such activities has drawn much attention due to its adverse impacts on environmental quality and public health. Therefore, under the current background of China's ecological civilization construction, promoting the precise and scientific treatment of environmental pollution holds great significance. This paper proposes an improved perpetual inventory method to systematically measure the capital stock of urban and industrial pollution control. The efficiency of urban and industrial pollution control is measured by adopting the global data envelopment analysis (DEA) model. Then, the influencing factors of pollution control efficiency are empirically analyzed by using the spatial Tobit regression model. The results reveal that, first, the growth rate of the capital input scale of urban pollution control is greater than that of industrial pollution control, and the spatial distribution of capital input is unbalanced. Second, the efficiency of urban and industrial pollution control from 1991 to 2019 was generally low. The current efficiency values of urban and industrial pollution control are less than 0.2 and 0.5, respectively, indicating that urban and industrial pollution control are far from efficient. Third, the efficiency of urban and industrial pollution control is significantly positively related to the level of urbanization and industrialization, has a U-shaped relationship with the economic development level, and has heterogeneous effects on technology, energy intensity, government influence and foreign trade. On this basis, we provide constructive suggestions for optimizing the performance of pollution control. [Display omitted] • This paper systematically, comprehensively and in detail measures EPC's capital input in China. • We analyze the historical performance and influencing factors of EPC. • Results show EPC's efficiency has not been significantly improved from 1991 to 2019. • The current level of urban and industrial EPC is still very low. • Factors have spatial and heterogenous effects on the efficiency of EPC. [ABSTRACT FROM AUTHOR]

The extensive use of land resources and environmental pollution in rural areas are two major problems prevalent in China and even the world. It is unknown whether improving the degree of intensive use of rural land can reduce environmental pollution; whether environmental pollution will be promoted or inhibited still lacks in-depth discussion. This paper first provides a theoretical analysis of the generation process of nonpoint source pollution loads (NPSP) in rural land use (RLU) and the mechanism and path of intensive rural land use (IRLU) to reduce agricultural nonpoint source pollution loads (ANPSP). Then, it takes 31 provinces in China from 1978 to 2019 as the research object to examine the temporal and spatial evolution features of IRLU and ANPSP. Furthermore, the paper uses the decoupling model and the Environmental Kuznets curve (EKC) model to test the linear and nonlinear relationship between the two. The research shows that the degree of IRLU in China decreased from 0.54 in 1978 to 0.27 in 2006, and then continuously increased to 0.56 in 2019. Moreover, the ANPSP continued to increase from 1955.14 t in 1978–3622.74 t in 2019. The decoupling relationship between the degree of IRLU and environmental pollution experienced the evolution process of "negative decoupling-decoupling", and the EKC had an "inverted N-shaped" characteristic. Overall, China shows that the IRLU helps to reduce ANPSP. At the same time, it was also found that there is obvious heterogeneity among the 31 provinces used in this research in China. Among them, the degree of intensive land use (ILU) in the principal grain-producing regions tends to be better and stable, while other areas show fluctuating changes. The ANPSP in economically developed areas gradually decreases, while that in underdeveloped areas continues to increase. More than 80% of the provinces in China show a trend of IRLU to advance the reduction of ANPSP, but there has also been an increase in the over-intensification of RLU in some major grain-producing areas. The research concludes that there is an inevitable relationship between RLU and ANPSP. Appropriately increasing ILU has a positive effect on decreasing ANPSP. • Moderate intensive rural land use (IRLU) helps reduce environmental pollution. • The agricultural nonpoint source pollution loads (ANPSP) continued to increase. • The decoupling relationship shifted from negative decoupling to decoupling. • The panel EKC curve in China showed the characteristic of "inverted-N″ shape. • The IRLU, ANPSP and their relationship are obvious heterogeneity in provinces. [ABSTRACT FROM AUTHOR]

In the process of rapid industrialization and urbanization, China's rural settlements are undergoing rapid differentiation and reorganization. Their spatial pattern and multifunction have attracted much attention. In the Loess Hilly Region of China, topographic factors are deeply involved in the formation and evolution of the spatial pattern and multifunction in rural settlements. Therefore, this paper proposed a new method of topographic gradient analysis based on micro-geomorphic units. Taking Tianshui City in Longzhong Loess Hilly Region as an example, we analyzed the gradient differentiation and spatial correlation of the spatial pattern and multifunction in rural settlements. The results indicated that: (1) The topographic gradient differentiation of spatial pattern in rural settlements was distinct. As the topographic gradients rose, the numerical distributions of TA, AREA_CV, MPI, PR, and SHDI were generally concentrated from high to low values. The numerical distribution of LFI was generally scattered from low to high values. In addition, the numerical distribution of AWMSI and AWMPFD showed the "arch bridge" pattern. (2) The topographic gradient differentiation of multifunction in rural settlements was distinct. The overall level of LF was relatively low, and the numerical difference was small. It had the characteristics of concentrated distribution and marginal distribution in geographical space. The overall level of PF was low, and the spatial distribution had strong urban directivity and significant topographic gradient differences. The overall level of EF was relatively low, and the spatial distribution had significant horizontal zonality and topographic gradient differences. (3) Rural settlements' scale, distribution, and structure were generally synergistic with LF and PF, but there were trade-off relationships with EF. Moreover, the trade-off/synergy relationships between spatial pattern and multifunction had significant spatial heterogeneity in terms of spatial distribution. This paper is significant for formulating settlement development and construction plans, guiding spatial reconstruction and functional reorganization, improving settlement living environment, and promoting rural revitalization. [Display omitted] • A new method of topographic gradient analysis was proposed based on micro-geomorphic units. • The topographic gradient differentiation of the spatial pattern and multifunction in rural settlements were distinct. • Rural settlements' scale, distribution, and structure are generally synergistic with LF and PF but are trade-offs with EF. [ABSTRACT FROM AUTHOR]

In the past decades, China has observed rapid urbanization, the nation's urban population reached 50% in 2000, and is still in steady increase. Rapid urbanization in China has an adverse impact on urban hydrological processes, particularly in increasing the urban flood risks and causing serious urban flooding losses. Urban flooding also increases health risks such as causing epidemic disease break out, polluting drinking water and damaging the living environment. In the highly urbanized area, non-engineering measurement is the main way for managing urban flood risk, such as flood risk warning. There is no mature method and pilot study for urban flood risk warning, the purpose of this study is to propose the urban flood risk warning method for the rapidly urbanized Chinese cities. This paper first presented an urban flood forecasting model, which produces urban flood inundation index for urban flood risk warning. The model has 5 modules. The drainage system and grid dividing module divides the whole city terrain into drainage systems according to its first-order river system, and delineates the drainage system into grids based on the spatial structure with irregular gridding technique; the precipitation assimilation module assimilates precipitation for every grids which is used as the model input, which could either be the radar based precipitation estimation or interpolated one from rain gauges; runoff production module classifies the surface into pervious and impervious surface, and employs different methods to calculate the runoff respectively; surface runoff routing module routes the surface runoff and determines the inundation index. The routing on surface grid is calculated according to the two dimensional shallow water unsteady flow algorithm, the routing on land channel and special channel is calculated according to the one dimensional unsteady flow algorithm. This paper then proposed the urban flood risk warning method that is called DPSIR model based multiple index fuzzy evaluation warning method, and referred to as DMFEW method. DMFEW first selects 5 evaluation indexes based on the DPSIR model for flood risk warning evaluation, including driving force index, pressure index, state index, impact index and response index. Based on the values of all evaluation indexes, one evaluation index for the whole system evaluation result is determined by using the fuzzy comprehensive evaluation method. The flood risk level is divided into 4 levels, having Level 1 the most serious. Every evaluation index is also categorized as 4 levels, and a linear fuzzy subjection function is proposed to do the fuzzy comprehensive evaluation. Dongguan City is used as the study case to validate the proposed method. The urban flood forecasting model is set up with the topographic data, the city map, the underground pipelines and land cover types, and two flood events are simulated with observed precipitation, one is interpolated from the rain gauges data, and another is estimated by digital weather radar. The simulated results are compared with the investigated water depth, and the results show the model has very good performances. The results are further used for the flood risk warning simulation, and are very reasonable. [ABSTRACT FROM AUTHOR]

China has achieved a great success in control and elimination of key parasitic diseases. In 2007, the elimination of lymphatic filariasis was verified by WHO. The schistosomiasis incidence and snail-distributed areas have reduced to the lowest level in the history. The transmission and disease burden of echinococcosis have been contained largely, and the populations infected with soil-transmitted trematode and food-borne parasites have also shown a significantly declining trend. Because of rapid globalization and climate changes, however, many new challenges have arisen. In his paper, the 2020-2030 roadmaps towards the control and elimination of these key parasitic diseases are described. Moreover, China is actively implementing its global health strategy, and will be more and more engaged into global health affairs, in which a series of China-Africa health cooperation projects have been in planning with a wish of making a greater contribution to the SDGs. [ABSTRACT FROM AUTHOR]

As a zoonotic parasitosis caused by the parasitism of Echinococcus larvae, echinococcosis imposes serious disease and economic burdens on human beings and society, and is thus a global public health issue. Its complex life history, wide distribution, the combined influence of various epidemic factors, coupled with the unique natural environment, customs, and religious beliefs in endemic areas, pose a huge challenge to the national echinococcosis control programme in China. Accurate early detection and confirmation of diagnosis of echinococcosis, the use of effective drugs, real-time surveillance of the infection status of populations and various hosts, controlling the source of infection, and blocking the route of transmission are of enormous significance for control. In this paper, the work by NIPD-CTDR on the prevention and control of echinococcosis in China is reviewed, with a view to providing reference for the further promotion of the national echinococcosis control programme. [ABSTRACT FROM AUTHOR]

Influenza A virus, the H9N2 subtype, is an avian influenza virus that has long been circulating in the worldwide poultry industry and is occasionally found to be transmissible to humans. Evidence from genomic analysis suggests that H9N2 provides the genes for the H5N1 and H7N9 subtypes, which have been found to infect mammals and pose a threat to human health. However, due to the lack of a structural model of the interaction between H9N2 and host cells, the mechanism of the extensive adaptability and strong transformation capacity of H9N2 is not fully understood. In this paper, we collected 40 representative H9N2 virus samples reported recently, mainly in China and neighboring countries, and investigated the interactions between H9N2 hemagglutinin and the mammalian receptor, the polysaccharide α-2,6-linked lactoseries tetrasaccharide c, at the atomic level using docking simulation tools. We categorized the mutations of studied H9N2 hemagglutinin according to their effects on ligand-binding interactions and the phylogenetic analysis. The calculations indicated that all the studied H9N2 viruses can establish a tight binding with LSTc although the mutations caused a variety of perturbations to the local conformation of the binding pocket. Our calculations suggested that a marginal equilibrium is established between the conservative ligand-receptor interaction and the conformational dynamics of the binding pocket, and it might be this equilibrium that allows the virus to accommodate mutations to adapt to a variety of environments. Our results provided a way to understand the adaptive mechanisms of H9N2 viruses, which may help predict its propensity to spread in mammals. • 40 HA mutant structures of H9N2 avian influenza virus circulating mostly in China were investigated. • Mutations in 9 of 100 amino acids of the HA protein were found critical to virus adaptability. • Compared with Q226-HA, the binding orientation of L226-HA to mammalian receptors was more stable and concentrated. [ABSTRACT FROM AUTHOR]

Toxocariasis is a neglected parasitic zoonosis. Although some studies have reported the Toxocara prevalence in dogs and cats in mainland China, there is a lack of comprehensive analysis of these data. Here, we conducted the first systematic review based on relevant literatures published in Web of Science, PubMed and CNKI from January 2000 to July 2019 to assess the prevalence of Toxocara infection in dogs and cats in mainland China. A total of 68 eligible papers were retrieved, including 24,490 dogs and 844 cats, with 17.34% (4246/24,490) Toxocara canis prevalence in dogs and 22.04% (186/844) Toxocara cati prevalence in cats by faecal floatation method. The prevalence and risk factors of T. canis and T. cati infection in different geographical regions, years, breeds, ages and genders were estimated in this review. This review indicates that there was high prevalence of Toxocara infection in dogs and cats in China. This finding calls for measures to reduce the potential risk of Toxocara infection and toxocariasis in humans and animals. [ABSTRACT FROM AUTHOR]

Mycoplasma capricolum subsp. capripneumoniae (Mccp), belongs to Mycoplasma mycoides cluster and is a causal pathogen of contagious caprine pleuropneumonia (CCPP). This paper presents the complete annotated genome sequence of Mccp Strain 87001—a strain that was isolated from pneumonia affected goats on a farm in China, and comparative genomics analysis of five Mccp genomes in addition to comparative genomics within Mycoplasma mycoides cluster. The Mccp strain 87001 genome consists of a single circular chromosome 1017333 bp in length and encodes 898 open reading frames (orfs) averaging 944 bp in length. Fifty eight potential virulence genes were identified, including variable surface lipoproteins, hemolysin A, and P60 surface lipoprotein. Comparative genomic analysis revealed eight virulence genes and four extracellular genes which remained unchanged in five Mccp genomes for forty years, which can be used as potential target for drug development and vaccine design. We revealed 183 Mccp unique genes as markers to distinguish Mccp with other mycoplasma strains from goats, and different virulence factors contributing to host specificity and different syndrome of bovine pathogens and caprine pathogens. [ABSTRACT FROM AUTHOR]