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The impact of air pollution is one of the hotspots attracting continuous scholarly attention, but the comprehensive statistical and visual analysis reviews are few. Employing the method of bibliometric analysis, this paper took the relevant literature from 1996 to April 2022 on the Web of Science as the research object. Through the methods of keyword co-occurrence analysis and burst analysis, the spatiotemporal evolution trend, cooperation network, outstanding scholars, knowledge base, and research focus of air pollution impact research are visually presented. Via constructing a common word matrix of high-frequency words, clustering analysis is used to aggregate high-frequency keywords into 24 clusters. By the strategic coordinate analysis method, the relationships within and between clusters were revealed. The main findings include (1) research on the impact of air pollution mainly focusing on human health; (2) the six keywords with the highest centrality are California, hydrocarbons, dioxide, generation, Asia, and diesel; (3) these 11 clusters may be developed into future research hotspots: particulate matter, nitrogen oxides, mortality, ozone, pollution, air quality, asthma, children, epidemiology, aerosols, and polycyclic aromatic hydrocarbons; and (4) seven topics are research hot: daily mortality, long-term exposure, coronary heart disease, concentration, North China plain, traffic-related air pollution, and air pollution. [ABSTRACT FROM AUTHOR]

The growth of China's OFDI (outward foreign direct investment) is a unique feature of the "Belt and Road" project. Does China's OFDI have a green halo effect on countries along the Belt and Road (B&R)? Is this green halo effect somehow asymmetrical? What is the underlying mechanism? This paper systematically examines how China's OFDI exerts its influence on green technology spillovers, based on 56 B&R countries' 2003–2019 panel data. This study makes three significant findings: Firstly, China's OFDI has positive asymmetric characteristics in promoting green technology spillovers to host countries mentioned, which have lower income levels and openness. Secondly, strict relative environmental regulation can act as a "pressure pool," significantly enhancing the "green halo effect"; Thirdly, China's OFDI can help host countries obtain more green technology spillovers through three channels: expanding host countries' economic scale, upgrading host countries' industrial structure, and suppressing host countries' use of non-renewable energy. These findings point the way for 56 host countries to better accessing green technology spillovers. [ABSTRACT FROM AUTHOR]

• A novel spatial general equilibrium model was constructed and the impact of air pollution on urban residents' welfare in China was studied. • Empirical study shows air pollution significantly reduces urban residents' welfare and migration cost reduces the negative impact of air pollution on the welfare of urban residents. • Policy suggestions suggested that air pollution should be balanced against the welfare of residents, and should not be cleaned up by "one size fits all" in the early stages of economic development. Air pollution and its effects are important issues of human society. However, few literatures on the effect of air pollution on urban residents' welfare considered the cost of migration. This paper constructs a novel spatial general equilibrium model and studies the impact of air pollution on urban residents' welfare in 274 cities at and above the prefectural level in China from 2007 to 2017, and investigates the role of migration costs. The theoretical analysis and empirical research show that air pollution has a significant negative impact on the welfare of residents. Further, the simulation results indicate that the reduction of migration cost and the improvement of air quality accounts for roughly 24.65% improvement of resident's welfare from 2007 to 2017 in China. Another conclusion is that there is an inverted U-shaped relationship between resident's welfare and air pollution. On another side, migration costs play a moderating role in the impact path of air pollution on residents' welfare. When the migration costs fall, it will help residents to move out of cities with poor air quality and improve the resident's welfare. The policy suggestions are as follows: (1) In the process of sustainable development, local governments need to coordinate the phased characteristics between air pollution and residents' welfare, effectively improve the livable degree of city and urban economic sustainability, and prevent the brain drain caused by excessive migration of residents. (2) Local governments should lower the migration costs between cities by deepening the reform of the household registration system, so as to promote the free flow of labor and ultimately improve the welfare of residents. [ABSTRACT FROM AUTHOR]

Multimodal transport is an effective method to reduce the energy consumption and carbon dioxide (CO 2) emissions in transportation sector. Evaluating the low-carbon performance is a prerequisite for developing multimodal transport. This paper establishes the new cross-efficiency (CE) network data envelopment analysis (DEA) approach, and applies it to evaluate low-carbon efficiency of railway-waterway intermodal transportation (RIT) in China from 2017 to 2022. The proposed approach takes advantage of network DEA and considers the internal structure in the RIT system as well as the interconnections between various transportation modes. This article comprehensively analyzes the evaluation results in terms of the overall situation, geographic distribution characteristics, internal stages and links, external influencing factors, and efficiency prediction, and the results find that: (1) the low-carbon efficiency of China's overall RIT needs further improvement. (2) The geographical distribution shows a trend that the efficiency in the Northern Region is higher than that in the Southern Region. (3) The level of urban industry, external transportation conditions, and foreign trade development will all affect the performance of RIT. Finally, according to the empirical results, management strategies are proposed. The main contributions include: proposing a network-structured CE-DEA method focusing on internal states; The advantages of CE network DEA are utilized to study CO 2 emissions of multimodal transport; The low-carbon efficiency of RIT in China is comprehensively analyzed. This study enriches the research on DEA methods, and the results can provide a basis for decision-making by the government and transport enterprises, help promote the development of low-carbon transport in China, and provide a reference for the optimization of multimodal transport in other countries. • Constructed a cross-efficiency DEA approach. • Analyzed the low-carbon efficiency of multimodal transport. • Discussed the distribution and influencing factors of efficiency. [ABSTRACT FROM AUTHOR]

How to reasonably evaluate the performance of scientific research activities in universities has attracted people's extensive attention. This study identifies the scientific research activity of Chinese universities as a two-process system with three sub-stages, including technical accumulation and research commercialization processes. Where, the process of technical accumulation includes the production of scientific research and patenting stage, while the process of research commercialization is a separate stage. First, this study proposes a network DEA model with two processes and three sub-stages to evaluate and decompose the performance of scientific research activities in universities. Secondly, taking 61 Chinese universities in the "Double First-Class" initiative (DFIU) as examples, this study evaluates the overall efficiency, stage efficiency and coordination efficiency of scientific research activities in Chinese universities. The final main conclusions are as follows: (1) The average score associated with the transformation efficiency of scientific research achievements based on the internal structures is only 0.2406, lower than the CCR efficiency and merger efficiency, indicating that most universities are still facing problems such as low resource utilization efficiency or unsatisfactory results. (2) The universities in the "First-class Discipline" construction plan (UFDCP) have outstanding performance in the technical accumulation process and the production of scientific research stage. Professional characteristics universities are generally much less efficient than polytechnic universities and comprehensive universities. (3) The universities in the "First-class Discipline" construction plan (UFDCP) are better than the universities in the "First-class Universities" construction plan (UFUCP) in terms of average efficiency values and polytechnic universities are better than other types of universities in terms of average efficiency values. We can find part of the reason for this difference in average efficiency from the evaluation of coordination efficiency. • This paper analyses the internal structure and internal operating mechanisms of research activities in universities. • Constructed a two-process network model with three sub-stages as a method to deal with unique efficiency decompositions. • The coordination efficiency of university scientific research system is calculated. [ABSTRACT FROM AUTHOR]

Since December 2019, the COVID‐19 epidemic has been spreading continuously in China and many countries in the world, causing widespread concern among the whole society. To cope with the epidemic disaster, most provinces and cities in China have adopted prevention and control measures such as home isolation, blocking transportation, and extending the Spring Festival holiday, which has caused a serious impact on China's output of various sectors, international trade, and labor employment, ultimately generating great losses to the Chinese economic system in 2020. But how big is the loss? How can we assess this for a country? At present, there are few analyses based on quantitative models to answer these important questions. In the following, we describe a quantitative‐based approach of assessing the potential impact of the COVID‐19 epidemic on the economic system and the sectors taking China as the base case. The proposed approach can provide timely data and quantitative tools to support the complex decision‐making process that government agencies (and the private sector) need to manage to respond to this tragic epidemic and maintain stable economic development. Based on the available data, this article proposes a hypothetical scenario and then adopts the Computable General Equilibrium (CGE) model to calculate the comprehensive economic losses of the epidemic from the aspects of the direct shock on the output of seriously affected sectors, international trade, and labor force. The empirical results show that assuming a GDP growth rate of 4–8% in the absence of COVID‐19, GDP growth in 2020 would be ‐8.77 to ‐12.77% after the COVID‐19. Companies and activities associated with transportation and service sectors are among the most impacted, and companies and supply chains related to the manufacturing subsector lead the economic losses. Finally, according to the calculation results, the corresponding countermeasures and suggestions are put forward: disaster recovery for key sectors such as the labor force, transportation sector, and service sectors should be enhanced; disaster emergency rescue work in highly sensitive sectors should be carried out; in the long run, precise measures to strengthen the refined management of disaster risk with big data resources and means should be taken. [ABSTRACT FROM AUTHOR]

In an attempt to investigate the impact of major events on urban air quality in terms of the extent, duration and spatial scope, data on the daily air quality index and the concentrations of individual pollutants are collected in 140 cities of China from January 2, 2015, to November 28, 2017. Based on a spatial differences-in-differences, the impact of major events, such as political conferences, sporting events at the national level, on urban air quality in the dimensions of time and space are explored. It is concluded that major events not only affected the air quality of the host city, but also exercised influence on the air quality of the surrounding areas. Recommendations for mitigating the impact of major events on urban air quality have been proposed, such as establish regional atmospheric environment management system and formulate regional unified standards for pollutant discharge, industrial access and law enforcement. [ABSTRACT FROM AUTHOR]

The rapid development of China's economy and urbanization has given rise to noticeable environmental problems, among which the change of air quality has received extensive attention. The panel data of PM2.5 (particles with an aerodynamic diameter of 2.5 µm or less) in 343 prefecture-level cities in China from 1998 to 2016 were statistically analyzed to reveal the characteristics of the temporal evolution and spatial variation of China's air quality in the past two decades. The results show that: 1) the overall deterioration trend of air quality is obvious throughout the country. The variation trend of PM2.5 was divided into three phases: rapid-growth phase (1998–2007), lag phase (2006–2011) and mildly-incremental phase (2012–2016), with their average growth rates of 7.19%, −3.59% and 0.52%, respectively. 2) The spatial difference of PM2.5 values in China increased significantly with time. Since 2003, the high-value area in the east has expanded rapidly, and polarization became much more pronounced. The change rate of PM2.5 is high in the east and west and low in the middle. The change rates of most areas in the west exceed more than 80%, and in the east lie somewhere between 40% and 60%. In the midlands, the change rate is not large and some regions even show a negative growth. 3) The change rate of PM2.5 is also high in areas with higher values. However, in regions where the change rate of PM2.5 is high, the value of PM2.5 is not always high. The high change rate is mainly attributable to the low base value of PM2.5 and the cities concerned belong to sensitive areas. 4) According to the PM2.5 warning index, the number of strong, medium, weak and non-warning areas in China is 45, 85, 159 and 54, respectively. [ABSTRACT FROM AUTHOR]

As haze intensifies in China, controlling haze emission has become the country's top priority for environmental protection. Because haze moves across different regions, it is necessary to develop a data envelopment analysis (DEA) model underpinned by both competition and cooperation to evaluate the haze emission efficiency in different provinces. This study innovatively adopts the spatial econometrics to construct the co‐opetition matrices of Chinese provinces, then builds the co‐opetition DEA model to evaluate the haze emission efficiency of them, and finally uses the haze data of 2015 as an example to assess the applicability of the model. The results of the study include the following: First, compared with the traditional CCR (A. Charnes & W. W. Cooper & E. Rhodes) model, this study constructs the co‐opetition DEA cross‐efficiency model that integrates haze's feature of cross‐border moving; thus, it is more in line with the reality of haze emission and movement. Second, compared with the efficiency value gained from the CCR model, the haze emission efficiency values for Tianjin and Guangdong, two decision‐making units, register greater variance when using the DEA model. The reason might lie in that they have a different spatial transportation relationship with their surrounding provinces. Third, the haze emission efficiency of provinces, according to the evaluation based on the co‐opetition DEA method, varies greatly: Those with high efficiency are mostly inland provinces with slow economic growth and adverse climatic conditions, whereas many of the provinces with low efficiency are located in the relatively prosperous East China. The specific co‐opetition DEA model constructed in this study enriches the research on the DEA model, which can be applied to the emission efficiency evaluation of similar pollutants around the world and can contribute empirical support to the haze reducing efforts of the government with its empirical results. [ABSTRACT FROM AUTHOR]

Haze pollution is a key obstacle for environmental management faced by China and many other developing countries. The survey on residential families' economic losses and willingness to pay (WTP) are regarded as an essential reference for the implementation of environmental policies for haze treatment. For Jiangsu province of China, the authors of this paper first conducted three qualitative interviews with respectively meteorologists, meteorological administrators, and residents, a questionnaire was then elaborately designed, and subsequent surveys of 1123 families were administered in Jiangsu province. Further, the authors investigated measurements of direct economic losses by using the contingent valuation method (CVM) and explored influential factors of WTP by utilizing the binary logistic regression. From this survey, the estimated total economic loss incurred by haze disasters and total treatment cost for haze-related diseases were respectively 22.38 billion (in RMB) and 8.4 billion for Jiangsu province. 55.9% of residential families were willing to pay 11.6 billion RMB annually (51.97% of total loss) for haze treatment, leaving a shortage of 11.05 billion RMB, which the government is responsible to pay. These findings provide empirical information reflecting the opinions of communities and residential families, useful for the governments and industrial sectors to design environmental policies to meet the requirements of the public and control environmental pollution in an effective way to achieve sustainable development. [ABSTRACT FROM AUTHOR]

The cruise industry, which serves as a prominent exemplar of globalized business, is characterized by unique features that render its supply chain operations highly susceptible to various risk factors, thereby giving rise to significant consequences. Evaluating the risks associated with major disruptive events and enhancing the robustness of the cruise supply chain have become crucial issues of concern for various stakeholders. This study first develops an indicator evaluation system for assessing the risks of China's cruise supply chain, drawing upon relevant literature and expert interview opinions. Secondly, set pair analysis is utilized to identify the scores and trends of risk indicators in China's cruise supply chain. Thirdly, the Set pair analysis-Markov chain model is employed to forecast the future risk status of China's cruise supply chain system, and the influence of different weights on the prediction results is discussed. Finally, the risk evolution network of China's cruise supply chain is constructed to identify common risk consequences and visualize the evolution path of risk events, with the aim of providing reference for the formulation of prevention and control measures. The findings of this article have important consequences for improving risk mitigation strategies and enhancing the resilience of the cruise supply chain. [ABSTRACT FROM AUTHOR]

The transportation industry is the main source of carbon dioxide (CO 2) emissions, and the development of multimodal transport is conducive to reducing transportation carbon emissions. In order to evaluate the low carbon efficiency of multimodal transport, this article proposes a cross efficiency data envelopment analysis (DEA) method for complex network structures from the perspective of fairness, and takes China's rail-water intermodal transport as an example for research. The proposed method includes two secondary goal models that reduce the unreasonable differences between self-evaluation and peer-evaluation and treat all stages within the network system equally. Then, the improved entropy weight method is used to aggregate the cross efficiency. In addition, a numerical example is given to verify the effectiveness of the proposed method. The results of the case study show that the efficiency of Tangshan Port and Rizhao Port is relatively high, and others should learn from the successful experiences and develop improvement strategies based on their own characteristics. The conclusions can provide reference for transportation enterprise management and policy formulation, and the proposed method can be widely applied to the performance analysis of enterprise network, industrial chain, and supply chain. [Display omitted] • A novel cross efficiency DEA model is proposed. • The proposed approach includes two secondary goal models. • The low carbon efficiency of multimodal transport is evaluated. [ABSTRACT FROM AUTHOR]

Based on the related impact factors of precipitation anomaly referred in previous research, eight atmospheric circulation indicators in pre-winter and spring picked out by correlation analysis as the independent variables and the hazard levels of drought/flood sudden alternation index (DFSAI) as the dependent variables were used to construct the nonlinear and nonparametric classification and regression tree (CART) for the threshold determination and hazard evaluation on bimonthly and monthly scales in Huaihe River basin. Results show that the spring indicators about Arctic oscillation index (AOI_S), Asia polar vortex area index (APVAI_S), and Asian meridional circulation index (AMCI_S) were extracted as the three main impact factors, which were proved to be suitable for the hazard levels assessment of the drought/flood sudden alternation (DFSA) disaster based on bimonthly scale. On monthly scale, AOI_S, northern hemisphere polar vortex intensity index in pre-winter (NHPVII_PW), and AMCI_S are the three primary variables in hazard level prediction of DFSA in May and June; NHPVII_PW, AMCI_PW, and AMCI_S are for that in June and July; NHPVII_PW and EASMI are for that in July and August. The type of the disaster (flood to drought/drought to flood/no DFSA) and hazard level under different conditions also can be obtained from each model. The hazard level and type were expressed by the integer from − 3 to 3, which change from the high level of disaster that flood to drought (level − 3) to the high level of the reverse type (level 3). The middle number 0 represents no DFSA. The high levels of the two sides decrease progressively to the neutralization (level 0). When AOI_S less than − 0.355, the disaster of the quick turn from drought to flood is more apt to happen (level 1) on bimonthly scale; when AOI_S less than − 1.32, the same type disaster may occur (level 2) in May and June on monthly scale. When NHPVII_PW less than 341.5, the disaster of the quick turn from flood to drought will occur (level − 1) in June and July on monthly scale. By this analogy, different hazard types and levels all can be judged from the optimal models. The corresponding data from 2011 to 2015 were selected to verify the final models through the comparison between the predicted and actual levels, and the models of M1 (bimonthly scale), M2, and M3 (monthly scale) were proved to be acceptable by the prediction accuracy rate (compared the predicted with the observed levels, 73%, 11/15). The proposed CART method in this research is a new try for the short-term climate prediction. [ABSTRACT FROM AUTHOR]

Under the background of climate change, the haze days in China have increased significantly, which seriously hinders the sustainable development of society and arouses wide attention from the public. However, the researches on the effect of air pollution on the stock yield of heavy pollution enterprise in key control cities are quite limited, This paper collects the Air Quality Index (AQI) from key control cities above prefecture level in China as well as the stock yield data of these cities’ heavy pollution enterprises in December from 2014 to 2016 and through multi-discontinuities regression model, testes the effect of air pollution on the stock yield of heavy pollution enterprise. The results show that: (1) Heavy air pollution (AQI = 300) has negative influence on the stock yield. (2) There exists time effect of air pollution on stock yield. Since the year 2014, heavy air pollution has exerted significantly negative influence on the stock yield in that 2013 may be the “first year” when the Chinese society began to take air pollution seriously. This paper gives a brief discussion on the cause of it and suggests that severe air pollution should be strictly controlled. Only by facing air pollution seriously, can we eliminate air pollution with collective wisdom and concerted efforts and achieve the sustainable development of city. Being the first study to look into the effect of air pollution on stock yield in key control cities in China, this paper provides empirical reference for government supervision departments, stock investors as well as enterprises. [ABSTRACT FROM AUTHOR]

Currently, the hazy weather in China is increasingly serious. It is urgent for China to reduce haze emissions in environmental governance. A feasible way is to control haze emissions by optimizing the input sources. This paper proposed an innovative method in which the haze emission is controlled by readjusting input indicators. The output efficiency of input indicators in 29 provinces in China is calculated through 7 input indicators (namely, SO emissions, NO emissions, soot emissions, coal consumption, car ownership, capital, and labor force) as well as GDP (desirable output) and PM emissions (undesirable output). The results showed that the input indicators are excessive in redundancy on condition that PM emissions and GDP are equal. The input indicators are high in redundancy rate except labor force. The redundancy rates of soot emissions, SO emissions and coal consumption are relatively high and, respectively, are 78, 67.18, and 61.14%. Moreover, all the provinces are redundant in inputs except Beijing, Tianjin, and Shanghai which are optimal in input-output efficiency. The redundancy of middle and western provinces, such as Ningxia, Guizhou, and Shanxi, is relatively large. The ideas and methods proposed in this paper can provide a reference for the future researches that aim to reduce the input indicators of undesirable output, and the empirical results can provide empirical support for the PM abatement in China. [ABSTRACT FROM AUTHOR]

To improve the air pollution of China fundamentally, effective measures should be proposed based on the thorough understanding of the characteristics of air pollution. Based on spatial econometrics, this paper investigates the characteristics and analyzes the determinants of the spatial concentration of PM pollution in China. Results show that: (1) PM pollution is highly concentrated in Central and Eastern China, covering 17 regions which accounts for 75% of the total population and GDP (gross domestic product). (2) The PM values in China show a significant spatial correlation. Provinces such as Shandong, Henan, Anhui, and Hubei are high in PM2.5 concentration. Meanwhile, these provinces are high in population density, GDP, and coal consumptions and have a large amount of civilian cars. (3) PM pollution shows spatial spillover effects. A 1% increase in the PM values of neighboring provinces will lead to a 0.78% increase in that of one province. (4) An upward U-shaped relationship is observed between the density of per capita GDP and PM, and the PM value is far from the turning point of growth. With the further growth of the density of per capita GDP, the PM value is expected to increase rapidly and continuously. (5) Based on the characteristics of spatial concentration and spatial spillover, this paper proposes several prevention-control measures for haze pollution, such as stressing on the treatment of air pollution in severely polluted provinces, avoiding moving pollution industries to neighboring areas, performing joint prevention and control nationwide. Air pollution may only be rooted by transforming the pattern of economic growth. [ABSTRACT FROM AUTHOR]

Competition and cooperation in the environmental governance of cities are popular around the world. However, empirical research based on the prefecture-level city level in China is rare. Since the central government of China proposed to strengthen the construction of ecological civilization, whether there are strategic interactions of "race to the bottom" or "race to the top" among local governments is an important issue of academic and public interest. This paper constructs a game-theoretic model to reveal the strategic interactions of environmental governance among local governments. And then, based on the data of 221 prefecture-level cities collected from 2007 to 2018, the spatial econometric model is used to conduct multi-dimensional testing "race to the bottom" behavior of environmental protection expenditure among local governments. Moreover, this paper further analyses the impact of performance assessment indicators on the strategic interactions of local governments, so as to provide policy reference for improving environmental public welfare. Empirical results suggest that local governments in China show strategic imitation in environmental protection spending decisions, which is manifested as "race to the bottom", and this behavior is gradually weakening with the strengthening of environmental protection assessment. Furthermore, environmental performance indicators relieve the government's strategic imitation, while economic performance indicators intensify the government's strategy imitation. Thus, reasonable performance evaluation indicators are conducive to benign strategic interaction among governments. Finally, the current environmental protection expenditure has not yet significantly affected pollution reduction, providing new evidence for the "race to the bottom" behavior of local governments. Based on the findings of our study, the central government should optimize the performance evaluation system of local officials and strengthen the implementation of the environmental supervision system and accountability mechanism. Meanwhile, the local governments should further increase environmental protection expenditure, and enhance the supervision and utilization efficiency of environmental protection funds. • Strategic interaction among 221 prefecture-level cities in China was multi-dimensionally studied. • It has been found that China's local governments have strategic imitation as "race to the bottom". [ABSTRACT FROM AUTHOR]

Assessment of the health and economic impacts of PM2.5pollution is of great importance for urban air pollution prevention and control. In this study, we evaluate the damage of PM2.5pollution using Beijing as an example. First, we use exposure–response functions to estimate the adverse health effects due to PM2.5pollution. Then, the corresponding labour loss and excess medical expenditure are computed as two conducting variables. Finally, different from the conventional valuation methods, this paper introduces the two conducting variables into the computable general equilibrium (CGE) model to assess the impacts on sectors and the whole economic system caused by PM2.5pollution. The results show that, substantial health effects of the residents in Beijing from PM2.5pollution occurred in 2013, including 20,043 premature deaths and about one million other related medical cases. Correspondingly, using the 2010 social accounting data, Beijing gross domestic product loss due to the health impact of PM2.5pollution is estimated as 1286.97 (95% CI: 488.58–1936.33) million RMB. This demonstrates that PM2.5pollution not only has adverse health effects, but also brings huge economic loss. [ABSTRACT FROM PUBLISHER]

• A novel method that achieves optimal allocation efficiency is proposed. • Our novel method can lead to less economic losses of cities in China. • The deprivation coefficient per capita was used for the fairness of the method. • A case study on 27 polluted cities with high homogeneity in China is conducted. Rational allocation of pollutant emission rights is one of the ways to promote the sustainable economy and environment of cities. Based on the overall goal of emission reduction in the 13th Five-Year Plan proposed by China, the Yangtze River Delta city agglomeration with high homogeneity is selected as the research object, and three allocation models of SO 2 emission rights are established using data envelopment analysis (DEA), shadow price and information entropy. The fairness of the three allocation schemes is evaluated by the per capita relative deprivation coefficient (RDC). The study shows that: (1) the three-objective information entropy allocation model takes into account the principles of maximum output-input efficiency, protection of regional GDP and scheme fairness, and the relative deprivation coefficients (RDCs) are all less than 0.5, which can be used as the best scheme for SO 2 emission rights allocation in the Yangtze River Delta city agglomeration. (2) Cities in Jiangsu province need to reduce SO 2 emissions. (3) Taking city agglomerations with high homogeneity as the research object has more practical significance, which can provide policy advice for sustainable development of similar city agglomerations. [ABSTRACT FROM AUTHOR]

Schematic diagram of the research framework: A new network DEA method. [Display omitted] • A new network DEA allocation model considering cross-border transmission of SO 2. • The WRF-CMAQ is combined with the DEA allocation model for the first time. • The principles of optimal efficiency, GDP protection and fairness is considered. • The per capita relative deprivation coefficient was used to evaluate the fairness. • The new network DEA model is a powerful tool for SO 2 emission rights allocation. Currently SO 2 emission rights are allocated without considering the cross-border transmission characteristics of pollutants, and the allocation scheme cannot reflect the fact that air pollutant overflows in space. In this paper, the WRF (Weather Research and Forecasting Model)-CMAQ (Community Multiscale Air Quality) is combined with the data envelopment analysis (DEA) allocation model for the first time, and a two-stage (Stage-1: SO 2 formation, Stage-2: SO 2 treatment) network DEA allocation model is proposed with the SO 2 spatial transmission taken as the intermediate output or input index between decision-making units. Based on the principles of efficiency, economic protection and fairness, the model is applied to the study of SO 2 emission rights allocation in the Yangtze River Delta city agglomeration with high homogeneity in China. The results show that: (1) When the weight coefficient (α 1) in stage-1 is 0.7, 0.8 or 0.9, the per capita relative deprivation coefficient (PRDC) of each decision-making unit (DMU) is less than 0.5 in the allocation scheme, indicating that our scheme can be used as a reference to allocate emission rights in the Yangtze River Delta city agglomeration. (2) With great robustness and universality, our allocation model allows decision-makers to adjust the GDP constraint coefficient and the weight coefficients in the two stages according to their preferences, so as to obtain the optimal allocation results. The model proposed in this paper can help decision-makers to formulate effective policies to reduce pollutant emission, and promote energy conservation & emission reduction and coordinate environmental governance in regions of city agglomerations. [ABSTRACT FROM AUTHOR]

Resilience is a key term in disaster economic loss assessment. The flood loss rates in different scenarios for the residence, industry, commerce, infrastructure, and agriculture are calculated, and the original depth-damage curves are drawn by collecting the socioeconomic data of Lizhong Town in Lixia River and Houbai Town in Jurong River. Thereafter, by fully considering the resilience factor to draw the new depth-economic loss curves, which are in line with the actual situation, the results show: (1) the disaster reduction capability correction loss rate of different receptors in Lizhong Town is in the range of 16-74 %, and in Houbai Town is in the range of 20-79 %. The residential flood loss, commercial loss, infrastructure loss, and industry loss were reduced by 74, 54.8, 38, and 16 %, respectively, in Lizhong Town, and the residential flood loss, commercial loss, and industry loss were reduced by 79, 60, and 20 %, respectively in Houbai Town. (2) Residential property types and their display heights in families with different income levels have similar flood-damage rate curves in mainland China and Taiwan (Su et al. in Flood damage assessment and related database Implementation for KeeLung River Basin (II), Special research report of National Science Council, Taiwan, ); (3) the loss rate reached the maximum at the depth of 3 m, and the sum of the five receptors' damage is 6.98 million Yuan (RMB) and 2.2 million Yuan (RMB) in Lizhong Town and Houbai Town, respectively. At last, in this paper, several approaches to improving resilience were proposed and possibilities in future researches were put forward. This study is a useful complement to flood economic loss evaluation literature and provides reference for disaster prevention and mitigation decisions in similar areas. [ABSTRACT FROM AUTHOR]

The systematic development of the hydrogen energy industry is inseparable from government subsidies and co llaboration among enterprises in the industrial chain. Unlike existing studies on the overall impact of government subsidies on enterprise economic profits, this study discusses the impact of research and development (R&D) and production subsidies on the economic profits of upstream and midstream enterprises in the hydrogen energy industry chain. The empirical results based on hydrogen-related A-share listed enterprises from 2011 to 2019 in China show that the government's R&D and production subsidies have effectively improved the economic benefits of hydrogen energy enterprises. In particular, government R&D subsidies significantly improve the economic profits of upstream enterprises, whereas production subsidies have insignificant effects. For midstream enterprises that produce hydrogen fuel cells, the economic effect of government production subsidies is more significant than that of R&D subsidies. The results of this study may provide references for optimizing the distribution of subsidies in the hydrogen energy industry chain and promoting the sound development of the hydrogen energy industry worldwide. • Government subsidies promote the profit of hydrogen energy enterprises. • R&D subsidies promote the profit of upstream hydrogen energy enterprises. • Production subsidies are more effective for midstream hydrogen energy enterprises. [ABSTRACT FROM AUTHOR]

Purposes: This study examined the prevalence of addictive Internet use and analyzed the role of parental relationship in affecting this behavior among a random sample of adolescents in Wuhan, China. Methods: Students (n = 1,101) were randomly selected from four schools, including 638 boys and 463 girls with a mean age of 13.8 (standard deviation = 1.2) years. Addictive Internet use, parental relationship, hyperactivity-impulsivity were measured by validated instruments. Prevalence rate, ANOVA and multiple linear regression method were used to analyze the level of Internet addiction and its association with parental relationship, hyperactivity-impulsivity, as well as the interaction of parental relationship with chronological age and hyperactivity-impulsivity. Results: The prevalence rate of Internet addiction was 13.5% (16.5% for boys and 9.5% for girls, p<0.01). Compared to non-addictive users, addictive Internet users were scored significantly lower on parental relationships and significantly higher on hyperactivity-impulsivity. Interaction analysis indicated that better parental relationship was associated with more reductions in risk of addictive Internet use for younger students than for older students, and with more risk of Internet addiction among higher than among lower hyperactivity-impulsivity students. Conclusions: Findings of this study indicate that adolescent addictive Internet use is a significant public health threat in China. Prevention interventions targeting parental relationship must consider adolescent’s age and hyperactivity-impulsivity tendency. [ABSTRACT FROM AUTHOR]

Accurate evaluation of emission governance efficiency can build fundament to develop haze control strategy towards sustainable development. By features of the haze, we view the haze formation stage as the first sub-process and the haze control stage as the second sub-process. This paper proposes an additive aggregation network data envelopment analysis (DEA) model with undesirable intermediate measures and undesirable outputs, which have not been thoroughly studied in previous literature. We found the newly developed network DEA model was nonlinear and cannot be converted into a linear program, and then developed an improved second-order cone programming approach to solve this problem. After analyzing the data of haze control in China, we drew the following conclusions: Firstly, different weights of preference for two sub-process can lead to the variation in the overall efficiency. Under different weights of preference, although the efficiency of the haze formation has a very small change in some provinces, the efficiency of the haze control has a large change. Secondly, decision makers can achieve the adjust goal of reducing haze by adjusting their preferences on the information of the haze formation and haze control stages, which are helpful for policy making in haze control strategy and sustainable development. [ABSTRACT FROM AUTHOR]

With the acceleration of industrialization and urbanization, the problem of air pollution in China has become increasingly serious. Particulate matter (PM) is a representative indicator of pollutants, and it is of great significance to carry out targeted treatment by studying its periodicity of concentration. In this paper, as a data mining information technology, the Empirical Mode Decomposition-Wavelet Analysis (EMD-WA) model is used to conduct a multi-scale periodic study of the PM 2.5 concentration time sequence in the Yangtze River Delta region in China and it is found that: (1) through the decomposition and reconstruction of the EMD-WA model, the period characteristics of four scales from short to long can be obtained, which are seasonal, short, medium and long period terms respectively; (2) the PM 2.5 concentration in the Yangtze River Delta region shows obvious multi-scale periodicity for the four scales, which includes a seasonal cycle of 46 days (about 1.5 months), a short cycle of 101 days (about 3.5 months), a medium cycle of 294 days (about 10 months), and a long cycle of 671 days (about 22.5 months), respectively. (3) The results are consistent in terms of season, short and middle cycle scales, in north (Jiangsu), east (Shanghai), south (Zhejiang) and west (Anhui) of the Yangtze River Delta region, but there are significant differences in the terms of long cycle scales. (4) The PM 2.5 concentration still shows obvious periodicity within 240 h during severe haze in the Yangtze River Delta region. This paper provides a framework for the government to make policies on energy conservation, emission reduction and air pollution control, and also provides a strong basis for haze prediction. [ABSTRACT FROM AUTHOR]

The output loss between cooperation and non-cooperation strategies for areas 1–4 (2012–2016). • Environmental control parameters are set to manipulate multiple situations. • Non-equal proportional change of indices and preference coefficient for ports are proposed. • A distance formula of expected output for PM emission reallocation is provided. • New DEA models are applied to 11 Chinese main ports. The emission of particulate matter (PM) and other atmospheric pollutants in port operations and shipping have caused a huge negative impact on the environment. Consequently, how to evaluate the environmental efficiency of ports and put forward corresponding countermeasures on this basis is becoming a more important issue than ever before from the perspectives of the government, academia, and society. We construct three data envelopment analysis (DEA) models to evaluate the environmental efficiency of ports under the circumstances of environmental control, non-environmental control and PM emission through inter-ports cooperation. The innovation of the DEA models constructed in this paper lies in: (1) Setting environmental control parameters to uniformly manipulate the situations of environmental control and non-environmental control, etc.; (2) Allowing non-equal proportional change of input index, expected output and non-expected output index; (3) Setting preference coefficients for ports to admit favorable decisions; (4) Providing a distance formula of expected output for PM emission reallocation. Further, data from 11 major ports in China are collected to compare the expected output under different PM emission standards assuming the situation of environmental control and non-environmental control, port cooperation, and non-cooperative sewage discharge. The empirical results show that: (1) Ports in the eastern China (Shanghai, Ningbo, and Nanjing) have higher port efficiency; (2) Port cooperation can improve the overall expected output but it will lose its edge with the improvement of PM emission standards. (3) Ports follow the same trend of output loss regardless of favorable decisions. In the end, the author makes a summary, puts forward relevant policy suggestions and makes the recommendation for future research. [ABSTRACT FROM AUTHOR]

Confronted with the constraints of carbon dioxide reduction, R&D improves the production efficiency of enterprises. However, China's diversified economic entity structure makes enterprises with different attributes exhibit different R&D behaviors under the constraints of external carbon dioxide reduction. This paper takes Ten Thousand Enterprises Plan as an example, which belongs to the front-end policy and restricts the enterprise's carbon emission rights, reveals the impact of carbon dioxide reduction constraint on enterprises' R&D investment and alleviates the endogenous bias of previous research. Moreover, this paper explores the moderating effect of ownership structure on the relationship between carbon dioxide reduction policy and enterprises' R&D investment. The results show that the relationship between carbon reduction policy and enterprises' R&D investment in China is manifested as a significant "cost effect", that is, mandatory carbon emission reduction policy limits the expansion of enterprises' R&D investment scale. Comparing state-owned enterprises with non-state-owned enterprises, carbon dioxide reduction policy can hardly stimulate the R&D investment in non-state-owned enterprises, while the state-owned enterprises can easily obtain factor resources, which decreases carbon emission reduction costs and improve R&D investment intention, resulting in stronger R&D behaviors. • Alleviates the endogenous bias of previous research focus on carbon dioxide reduction and R&D based on front-end policy. • Policy implementation limits enterprises' R&D investment through investment intention and carbon dioxide reduction cost. • Carbon dioxide reduction policy hardly stimulates the R&D investment in non-state-owned enterprises. • Incentivizing investment intention and reducing reduction costs are effective ways to enhance the policy effect. [ABSTRACT FROM AUTHOR]

Under the premise that the total emissions of PM (particulate matter) of air pollution is established, the allocation of PM emission rights in various provinces of China is the feasible way to governance the ash haze. In this paper, a data envelopment analysis (DEA) model that takes into account the objectives of efficiency and equity is constructed. On the basis of evaluating the PM emission performance of various provinces in China, the corresponding allocation steps are put forward. Then, the results of the DEA model and information entropy are compared. The research shows that: (1) under the same constraint conditions, the emission right of PM is allocated with DEA model, which leads to lower cost, less fluctuation of distribution amount and higher overall national performance. (2) the population Gini coefficient method is used to evaluate and it is found that the Gini coefficient value is smaller according to the distribution results of DEA model, indicating that the PM emission right amount is more fairly distributed among provinces. The functions of this paper are as follows: (1) a new double-objective DEA model is constructed, which is suitable for multi-agent performance evaluation with multiple objectives; (2) a scheme to allocate PM among provinces is proposed, which can provide reference for the practice of haze reduction in China [ABSTRACT FROM AUTHOR]

Since December 2019, the COVID-19 epidemic has been spreading continuously in China and many countries in the world, causing widespread concern among the whole society. To cope with the epidemic disaster, most provinces and cities in China have adopted prevention and control measures such as home isolation, blocking transportation, and extending the Spring Festival holiday, which has caused a serious impact on China's output of various sectors, international trade, and labor employment, ultimately generating great losses to the Chinese economic system in 2020. But how big is the loss? How can we assess this for a country? At present, there are few analyses based on quantitative models to answer these important questions. In the following, we describe a quantitative-based approach of assessing the potential impact of the COVID-19 epidemic on the economic system and the sectors taking China as the base case. The proposed approach can provide timely data and quantitative tools to support the complex decision-making process that government agencies (and the private sector) need to manage to respond to this tragic epidemic and maintain stable economic development. Based on the available data, this article proposes a hypothetical scenario and then adopts the Computable General Equilibrium (CGE) model to calculate the comprehensive economic losses of the epidemic from the aspects of the direct shock on the output of seriously affected sectors, international trade, and labor force. The empirical results show that assuming a GDP growth rate of 4-8% in the absence of COVID-19, GDP growth in 2020 would be -8.77 to -12.77% after the COVID-19. Companies and activities associated with transportation and service sectors are among the most impacted, and companies and supply chains related to the manufacturing subsector lead the economic losses. Finally, according to the calculation results, the corresponding countermeasures and suggestions are put forward: disaster recovery for key sectors such as the labor force, transportation sector, and service sectors should be enhanced; disaster emergency rescue work in highly sensitive sectors should be carried out; in the long run, precise measures to strengthen the refined management of disaster risk with big data resources and means should be taken., (© 2021 Society for Risk Analysis.)

Disaster insurance is an important tool for achieving sustainable development in modern agriculture. However, in China, the design of such insurance indexes is far from sufficient. In this paper, the single-season rice in Jiangsu Province of China is taken as an example to design the high-temperature damage index in summer and the low-temperature damage index in autumn to construct the formula calculating the weather output and single-season rice yield reduction. The daily highest, lowest and average temperatures between 1999 and 2015 are selected as main variables for the temperature disaster index to quantitatively analyze the relationship between the temperature index and the yield reduction rate of the single-season rice. The temperature disaster index can be put into the relevant model to obtain the yield reduction rate of the year and determine whether to pay the indemnity. Then, the burn analysis is used to determine the insurance premium rate for all cities in Jiangsu Province under four-level deductibles, and the insurance premium rate can be used for the risk division of the Province. The research provides some insights for the design of agricultural weather insurance products, and the empirical results provide a reference for the design of similar single-season rice temperature index insurance products.

Understanding spatial and temporal variations in river water quality and quantitatively evaluating the trend of changes are important in order to study and efficiently manage water resources. In this study, an analysis of Water Pollution Index (WPI), Daniel Trend Test, Cluster Analysis and Discriminant Analysis are applied as an integrated approach to quantitatively explore the spatial and temporal variations and the latent sources of water pollution in the Shanchong River basin, Northwest Basin of Lake Fuxian, China. We group all field surveys into 2 clusters (dry season and rainy season). Moreover, 14 sampling sites have been grouped into 3 clusters for the rainy season (highly polluted, moderately polluted and less polluted sites) and 2 clusters for the dry season (highly polluted and less polluted sites) based on their similarities and the level of pollution during the two seasons. The results show that the main trend of pollution was aggravated during the transition from the dry to the rainy season. The Water Pollution Index of Total Nitrogen is the highest of all pollution parameters, whereas the Chemical Oxygen Demand (Chromium) is the lowest. Our results also show that the main sources of pollution are farming activities alongside the Shanchong River, soil erosion and fish culture at Shanchong River reservoir area and domestic sewage from scattered rural residential area. Our results suggest that strategies to prevent water pollutionat the Shanchong River basin need to focus on non-point pollution control by employing appropriate fertilizer formulas in farming, and take the measures of soil and water conservation at Shanchong reservoir area, and purifying sewage from scattered villages.

Concentrating on consuming coefficient, partition coefficient, and Leontief inverse matrix, relevant concepts and algorithms are developed for estimating the impact of meteorological services including the associated (indirect, complete) economic effect. Subsequently, quantitative estimations are particularly obtained for the meteorological services in Jiangxi province by utilizing the input-output method. It is found that the economic effects are noticeably rescued by the preventive strategies developed from both the meteorological information and internal relevance (interdependency) in the industrial economic system. Another finding is that the ratio range of input in the complete economic effect on meteorological services is about 1 : 108.27-1 : 183.06, remarkably different from a previous estimation based on the Delphi method (1 : 30-1 : 51). Particularly, economic effects of meteorological services are higher for nontraditional users of manufacturing, wholesale and retail trades, services sector, tourism and culture, and art and lower for traditional users of agriculture, forestry, livestock, fishery, and construction industries.

To mitigate and control the eutrophication of the waters in Fuxian Lake bay, 1 hm2 Yaonigou constructed wetland was built on the north Fuxian lakeshore, and the P removal of the wastewater from Yaonigou River was investigated by the techniques of precipitation pond, oxidation pond, and subsurface-and surface flow constructed wetland. The results demonstrated that this constructed wetland had a very strong capacity (7.8% - 81.1%) of total phosphorus (TP) removal. The average removal rate of TP was 54.9%, and the TP retention in the constructed wetland was 265mg x m(-2) x d(-1), of which, plant assimilation was 26.1 mg x m(-2) x d(-1), about 10% of the total. The TP removal was mainly through adsorption and sedimentation, but the seasonal growth dynamics of main plant Oenanthe javanica could have a definite effect on the efficiency of TP removal. During the examination, the TP retention capacity was in order of subsurface flow constructed wetland > oxidation pond > precipitation pond > surface flow constructed wetland.