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Abstract To reduce pollution emissions and achieve a cleaner production in paper industry, it is essential to understand the inner links between concentrations of gaseous pollutants, types of final products and production techniques. In this study, the concentrations of four potential gaseous pollutants, total volatile organic compounds (TVOC), formaldehyde (HCHO), hydrogen sulfide (H 2 S), and hydrocarbon compounds (C x H y), in the ambient air on thirty sampling points of five pulp and paper mills were detected and analyzed. The results were summarized with respect to the following aspects: (1) Levels of four gaseous pollutants on all the sampling points in five mills. It was obvious that the situation of gaseous pollution from pulp mill was much more serious than those from paper mills. (2) Gaseous pollutant distinctions due to different production processes. The levels of gaseous pollutants from five mills were greatly influenced by the utilized raw materials and the applied paper chemical agents (flavor, coating materials and additives) in mills. (3) Gaseous pollution comparisons at common points. At the two common points in five mills, i.e. the wet end of paper machine and the wastewater treatment process, TVOC and HCHO, C x H y and H 2 S were the main gaseous pollutants, respectively. In addition, some feasible measures to realize a cleaner production in pulping and papermaking process were also put forward in the article. Highlights • We analyze the levels of 4 gaseous pollutants on 30 sites of 5 pulp & paper mills. • Gaseous pollution distinctions due to different production processes are studied. • Feasible measures to realize the cleaner production in the processes are suggested. • Gaseous pollution are greatly affected by raw materials and added paper chemicals. [ABSTRACT FROM AUTHOR]

While combating air pollution may seem to be a corporate responsibility, what individuals contribute can be substantial. This study explores the individual's behavioral intention to reduce the air pollution associated with vehicles, household appliances, and religious practices. An extended theory of planned behavior (TPB), past behavior included, serves as the analytical model, while the approach of partial least squares structural equation modeling (PLS-SEM) is employed in the model's estimation. The results show that subjective norms represent the primary driver of individual intentions to reduce air pollution, followed by perceived behavioral control, past behavior, and attitude, in that order. Surprisingly, advocacy on the part of the government to reduce the burning of incense and joss paper, disregarding years of social conflicts and protests, plays the most important role among all indicators within the construct subjective norms. This result holds even within the subsample of believers in religions that involve the practice of burning incense and joss paper. • Subjective norms represent the primary driver of individual intentions to reduce air pollution. • Governmental advocacy to reduce the burning of incense and joss paper plays an important role. • Individuals' attitudes towards de-carbonization and mitigating air pollution differ. [ABSTRACT FROM AUTHOR]

Air pollution presents a serious public health risk globally, particularly in fast industrializing countries such as China. Effectiveness of local air pollution control measures is influenced by external forces such as atmospheric emission transport and interprovincial trade. However, there is lack of research on comparison of these two indicators and local indicators (e.g. per capita income and emissions) determines the responsibility allocation in pollution control. In this paper, cross-provincial air pollution is stimulated via atmospheric transport (atmospheric linkage indicator) based on Weather Research and Forecasting/Comprehensive Air Quality Model with Extensions (WRF/CAMx) model. The air pollutants embodied in interprovincial trade (trade linkage indicator) was studied by using the latest multi-regional input-output (MRIO) model. This study revealed the significant influence of atmospheric transport on neighboring provinces. However, transport of trade-induced embodied emissions affects both neighboring areas and larger areas. According to aggregation analysis of these two indicators, in most provinces of China, direction of atmospheric transport contradicts to that of the trade-induced transport. These findings are used to analyze the rationality of regional differences in environmental tax rate in the new environmental protection tax law of China. By comparing the local and interregional linkage indicators, we found the current environment tax for air pollutants was mainly affected by per capita income whereas other environment and linkage indicators show little correlation. Therefore, we integrated environment and linkage indicators to propose adjusted provincial environment tax rates plan for air pollutants as a cost sharing mechanism. The results of this paper provide novel perspective for central government to adjust fairness environmental responsibility between provinces of China by tax policy. Image 1 • Cross-provincial air pollution via atmospheric transport was simulated by WRF/CAMx. • Interprovincial air pollution embodied in trade was traced using MRIO model. • The influence range via trade is greater than that of atmospheric transport. • The environmental tax rate is advised to be adjusted base on linkage indicators. [ABSTRACT FROM AUTHOR]

In this paper we investigate the relationship between participation in global value chains and the environment from a spatial perspective. By drawing on an original dataset on global value chain participation, emissions of nitrogen oxides and sulphur oxides, and green patents for European regions, we present novel evidence about the relationship between global value chains, green technologies and air pollution at the regional level. Our findings suggest that although participation in global value chains may lead to lower polluting emissions, this effect largely depends on the capacity of regions to exploit the green knowledge deriving from participation and on the specific form of participation. When European regions are integrated with backward linkages (i.e., importing inputs to produce exports) they record lower levels of air pollution; conversely, participation through forward linkages (i.e., exporting inputs for other places' exports) leads to an increase in air pollution. Backward participation also come out to support the development of green technologies that mediate the effects of global value chains on the environment posited by the "Pollution Haven" hypothesis. Overall, the relationship between global value chains participation and air pollution will depend on the type of participation and on the capacity of territories to profit it for the development of green technologies. • Our research provides new evidence on the relationship between Global Value Chains (GVCs) and the environment by using an original dataset on EU NUTS-2 regions. • GVC integration may lead to lower polluting emissions. This effect largely depends on the green knowledge deriving from GVC participation. • Regions integrated through backward linkages record lower levels of polluting emissions and higher capacities to develop green technologies. • Integration through forward linkages is associated with higher level of polluting emissions but not with green technologies. • We propose a Technological Heaven Hypothesis for EU regions that would contrast the Pollution Haven Hypothesis. [ABSTRACT FROM AUTHOR]

Abstract Those opposed to hosting mega events often claim that it may lead to negative environmental outcomes. This paper investigates the environmental impact of hosting the G20 summit in Hangzhou and asks two questions: (1) has hosting the G20 summit led to urban air quality improvement and (2) if so, is this improvement a short-term or long-term phenomenon? This research uses an event study method and finds that the air quality in Hangzhou was significantly improved during the G20 period and, most importantly, this positive impact seems to be a long-term phenomenon, contrary to previous studies. A placebo analysis on a similar city does not find comparable patterns, offering empirical support for a causal explanation. This paper further analyzes the steps that Hangzhou took in preparation for the G20 summit and finds many long-term oriented measures such as technological upgrades and transition from fossil fuels to clean energies. These findings show that mega events could be used as a catalyst to overcome industrial and individual resistance in improving environmental quality. Highlights • The air quality in Hangzhou was significantly improved during the G20 period. • The improvement seems to persist and the reasons are explained. • Policy makers may utilize mega events for long-term environmental benefits. [ABSTRACT FROM AUTHOR]

Abstract Optimal energy management of microgrids with different objectives such as operation cost, air pollution and wider use of renewable energy sources is investigated in many research works. In this paper, the effect of different operation modes of microgrids to solve environmental/economic dispatch problem is evaluated. Different modes of operation of microgrid include islanding operation, grid-connected and unilateral or bilateral exchange of power with main grid. The imperialist competitive algorithm (ICA) is one of the evolutionary algorithms that can model the competing imperialists to absorb colonies and uses it to find optimum solution. In this paper, a new method to improve the ICA algorithm is proposed in which the movement radius of the colonies toward the imperialist is adaptively adjusted in accordance with their position by means of adding direction and velocity parameters to the colonies. Thus, the colonies are attracted and repelled more intelligently by imperialists. The proposed method can create a trade-off between exploitation (i.e. local search) and exploration (i.e. global search) and prevents premature convergence while minimizing trapping in the local minima. Simulation results and comparison with other algorithms confirm high performance of the proposed algorithm. Graphical abstract Image Highlights • The environmental/economic dispatch problem for microgrids is evaluated. • Different modes of energy management operation of the microgrid have been studied. • A new method to improve the ICA algorithm is proposed. • The efficacy of the proposed improved ICA is extensively investigated. [ABSTRACT FROM AUTHOR]

Although trade does not only boost the economy but also exacerbates environmental transfers but still the evidence for air pollution's unequal exchange embodied in trade among the Belt and Road Initiative (BRI) countries is rarely discussed in the extant literature. From the perspective of an integrated evaluation framework comprising a multi-regional input-output model, system balance theory, and complex network theory, this research paper uncovers the spatial- and temporal changes of trade-induced air pollution inequality among countries along the BRI route for the time period from 2011 to 2016. The study findings point out that there exists an obvious spatial heterogeneity in the unequal relations among BRI economies. This implies that a large number of country pairs demonstrate weak inequalities, whereas a relatively small number of country pairs represent strong inequalities. In addition, the countries' positions indicate a unique characteristic of "duality and inverse", which is majorly manifested as pure causers represented by Moldova and Belarus, net beneficiaries symbolized by China and Russia, and pure victims exemplified by Bhutan. Meanwhile, nearly half of the dual identities are represented by Singapore. Besides this, the proposal and implementation of the BRI exert a positive influence on both system stability and inequality mitigation by supporting the balance of triangles. Finally, this paper posits that the environmental inequality system of the Belt and Road is not as complex as imagined since the 3-node motif classification is relatively simple. Our findings are helpful for mitigating air pollution inequalities so as to support the sustainable development of green BRI. • Evolution of the environmental inequality in BRI countries is studied. • The initiative exerts a positive influence on stability and inequality mitigation. • Most countries illustrate a feature of "duality and inverse". • Five identified subgraphs indicate that the system is predictable. [ABSTRACT FROM AUTHOR]

Air pollution has a significant impact on human health and influences housing choices. Existing studies on determinant factors affecting property prices, including air pollution, mainly employed hedonic and spatial regression models that have limitations in capturing non-linear relationships and local interactions. Neglecting the non-linear relationships can lead to incomplete estimation impacts between explainable features and prices. To fill these gaps, this study used machine learning algorithms and SHAP (SHapley Additive exPlanations) to identify the relative importance of air pollutant variables on land values and their non-linear mechanism. The results showed that the Extreme Gradient Boosting (XGBoost) outperformed Ordinary Least Squares (OLS), Gradient Boosting Decision Tree (GBDT), Random Forest (RF), K-Nearest Neighbors (K-NN), and Extra Tree Regression (ETR) models in price prediction and capturing the non-linear relationship between air pollution and land values. Notably, Ozone (O 3) and Nitric Oxide (NO) concentrations contribute 1.64% and 1.47% to land value variation, respectively. The results confirmed the non-linear relationship and identified that the threshold effect between air pollution and land values is at mean concentration values. Furthermore, we observed that the negative influence of O 3 and NO on land values appears as their concentration level is higher than 29.3 and 13 ppb, respectively. This paper contributes valuable insights by advancing our understanding of the non-linear mechanism impact of air pollution on house and land values, informing environmental policymaking, and shedding light on housing decisions. [ABSTRACT FROM AUTHOR]

Agriculture has a historical significance in human society and its present-day role as a vital sector of the global economy is irrefutable. However, the increase in agricultural production prompted by the rising demands has resulted in negative environmental consequences associated waste generation. Agricultural waste (agro-waste) constitutes a significant portion of the waste generated worldwide, causing environmental contamination and posing health risks when not managed properly. It is therefore crucial to formulate pioneering approaches that effectively mitigate the adverse impacts of agricultural waste, necessitating a deeper understanding of agro-waste. This review provides an overview of agro-waste, offering insights into its generation, categorization, composition and associated environmental implications. The sustainable utilization of the agro-waste is explored addressing pressing waste management and resource optimization issues. The paper engages in a comprehensive discussion regarding how agricultural practices contribute to soil degradation, air and water pollution, emphasising their interconnection and the need for integrated solutions. Promising pathways for utilizing agricultural waste, encompassing composting, production of animal feed, bioenergy generation, fiber extractions and biochar production are explored. Additionally, the review examines the complexities of efficiently managing and utilizing agricultural waste, addressing challenges such as the diverse nature of waste sources, compositional variations, contaminants, and practical feasibility considerations. It also explores potential solutions, including the need for further research, infrastructure development, and the establishment of regulatory frameworks and policies to improve agricultural waste management. [Display omitted] • Concept of agricultural waste: Explores sources, composition, and classifications. • Examines the environmental consequences of improper disposal and mismanagement of agricultural waste. • Discussion on agricultural practices on soil degradation, air pollution and water pollution. • Discusses innovative and sustainable methods for utilizing agricultural waste. • Addresses the various challenges and obstacles in effectively managing and utilizing agricultural waste. [ABSTRACT FROM AUTHOR]

This paper primarily studies the air quality in China's cities during the urbanization stage. Using a cross-sectional data of 282 cities, we discuss the influencing factors and the existence of the Kuznets Curve for three air pollutants based on the EKC (Environmental Kuznets Curve) theory and the BMA (Bayesian Model Average) method. The results show that the concentration of SO 2 and PM 10 presents the characteristics of an inverse-U shape. The urbanization process has a significant and negative effect on air pollutant concentration, which means that cities with higher urbanization rate tends to have lower air pollutant concentration. Population density, possession of civil motor vehicles, the proportion of secondary industry, and annual average temperature are the main influencing factors of air pollution. Based on these results, this paper suggests that China should speed up the “new” type urbanization process, constantly optimize the industrial structure, and promote the harmonious development of the economy and environment. [ABSTRACT FROM AUTHOR]

Most empirical researches in behavioral finance have found that the air pollution can affect the stock market in the developed world, while a few works show some different results in China. This paper deeply discusses the reasons for the difference of air pollution effect, and attributes it to the intensity of public environmental awareness. This paper selects some important environmental events which can enhance the public environmental awareness as samples, to investigate the influence of public environmental awareness on the air pollution effect. The results firstly show that the air pollution effect in Chinese stock market is not significant during a long-term sample period. Secondly, the empirical findings support that these events have significant impacts on the air pollution effect in Chinese stock market. Finally, this paper provides direct evidence on that the air pollution effect has a significant negative change after these events, which is consistent with the expected impact of the air pollution effect's mechanism. This research extends the behavioral financial issue of air pollution effect and provides the empirical evidence for the public environmental awareness's obstacle to the air pollution effect. [ABSTRACT FROM AUTHOR]

Due to the ever-increasing quantity of produced and sold automobiles in China, many side effects such as resource depletion, energy shortages and air pollution have emerged. Remanufacturing, as the highest form of the recycling economy, has been promoted by the Chinese government as a major measure to save resources and energy. The remanufactured products, however, get very low market recognition from Chinese consumers. Thus, understanding how to cultivate consumers potential behavior of purchasing remanufactured products is the first step and also very important for developing the remanufacturing industry. This paper, focusing on heavy truck engines due to their short life expectancy and repair frequency, aims to identify the factors influencing remanufactured heavy truck engine (RHTE) potential purchase and analyze the relationship among those factors and potential purchasing behavior. Based on 301 questionnaires from Chinese heavy truck drivers, this paper develops a conceptual model to hypothesize how the influencing factors affect RHTE potential purchasing behavior. Hierarchical regression results show that individual factors (including product knowledge, product trust and environmental values) mediate the relationship between environmental factors (including product attribute and advertisement) and RHTE purchasing intention. Contextual factors (including incentive policy and purchasing convenience) moderate the relationship between RHTE purchasing intention and potential purchasing behavior. Our results indicate that individual factors are essential in cultivating RHTE purchasing intention and environmental factors are helpful for improving individual factors. Contextual factors can motivate the transformation from RHTE purchasing intention to potential purchasing behavior. [ABSTRACT FROM AUTHOR]

An important area of urban sustainability planning refers to the reduction of environmental impacts. Transport sector is one of the main contributors of these impacts due to its role in air pollution, greenhouse gases and CO 2 emissions. Effective actions are needed to limit the environmental impacts of transport activities. Transition studies focus on these types of actions and plans. The role of local authorities as the closest level of government to the citizens in managing transition process is highlighted because they can better understand, inform, and guide local inhabitants, businesses and industries for achieving sustainability targets. The paper aims at assessing the efforts of local public authorities in transition toward low carbon mobility in Italy. To achieve this aim a mixed method analysis was applied. First, the analysis of qualitative data obtained from interviews with urban mobility stakeholders; used to design a framework for evaluating the role of local government in transition process. Then a quantitative analysis conducted on the data gathered through a questionnaire distributed to a sample of mobility managers (or transport responsible) in municipalities. The analyses provided a final framework showing how municipalities influence low carbon mobility transition process in Italy. In conclusion, municipalities’ strategies and plans have a direct effect on the final goals. These strategies are influenced by financial support and cooperative activities, while the level of cooperation is dependent on the attitudes of deciding authorities. The paper also discusses the need to identify challenges and impediments for sustainable urban mobility transitions which was highlighted by stakeholders but less valued by local authorities. [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]

In contrast to the surge of attention to China's business registration reform per se , the environmental externalities of the reform have been somewhat neglected by mainstream academics. Adopting the difference-in-differences method alongside propensity-score matching, and utilizing the panel data of 283 cities in China from 2000 to 2013, this paper investigates the impacts of the deregulation reform on PM2.5 concentrations. The results indicate that the business registration reform has contributed to PM2.5 air pollution, with above-average impacts in central areas, but insignificant effects in western China. Furthermore, the treatment effects are stronger in cities with larger entry of small and medium enterprises and greater pressure to achieve targets for local GDP growth. Aiming to draw public attention to the problems arising from the reform, our study advocates necessary environmental regulations on business registration, which lends support to the theoretical view of "public interest" rather than "public choice". • Deregulation reform of business registration increases PM2.5 concentrations in China. • Treatment effects of deregulation reform on PM2.5 air pollution vary widely among regions. • More SME entries and higher targets for GDP growth are associated with stronger effects of deregulation reform on PM2.5. • PM2.5 air pollution should be considered during the deregulation reform in China and other developing economies. [ABSTRACT FROM AUTHOR]

With the increasing irreversible damage caused by air pollution, an early warning system to send warning information to human beings so that they can avoid more harm caused by air pollution is required. A reliable warning system can provide valuable information to protect mankind from the effects of pollution and can act as a tool that allows regulators to implement corresponding measures to reduce air pollution. However, the previous most valuable research studies were focused on pollution forecasting and the extent to which pollution affects health, and the aim of only a few studies was to analyze pollution from an application perspective and to construct a reasonable early warning system. In this study, an air pollution early warning system was constructed, which comprises two modules: an air pollution forecasting module and an air quality evaluation module. In the forecasting module, two denoising methods and a multi-objective optimization algorithm are integrated into a novel hybrid forecasting model. In the evaluation module, fuzzy synthetic evaluation is used to evaluate air quality objectively. To verify the performance of the proposed early warning system, hourly pollutants concentration data were used in a case study of three metropolises in China and three numeric simulation experiments were conducted. The simulation results show that the forecasting performance of the L 2,1 RF-ELM model used in this study is better than the traditional neural network, and the forecasting model proposed in this paper is better than the traditional statistical model ARIMA. Moreover,the early warning system performed well in terms of highly accurate forecasting and accurate evaluation in the three research areas. [ABSTRACT FROM AUTHOR]

From 1990 to 2017, the number of vehicles in China increased sharply from 5 million to 310 million, and vehicle emissions became one of the major sources of air pollution. Among the main sources of PM 2.5 in Beijing, the contributions from vehicle sources increased from 5.6% (2000) to 31.1% (2012) to 45% (2017). In 2010, the CO, hydrocarbon (HC), NO x , and particulate matter (PM) emissions of yellow-label vehicles (YLVs) accounted for 46.1%, 47.9%, 63.1% and 86.1% of the total emissions from on-road vehicles. In recent years, China has been implementing a YLV scrappage subsidy policy to control air pollution, and this policy has cost several hundred billion yuan nationwide. However, China has not evaluated the costs and benefits of the policy. Many people question whether the YLV scrappage subsidy policy is worthwhile, but all the stakeholders involved complicate the process of accurately evaluating the true value of the policy. In this study, we evaluated and compared the costs and benefits of the policy in the Beijing-Tianjin-Hebei (BTH) region based on 1.362 million YLVs from 2008 to 2015. Because of the implementation of the policy, the PM 2.5 , PM 10 , NO x , CO and HC emissions in the BTH region decreased by 16.46, 18.12, 174.44, 669.11, and 91.64 kt, respectively, in 2008–2015. The results show that the policy played an important role in reducing pollutant emissions and improving environmental quality in the BTH region. The costs, benefits, and net benefits of the policy were 13.69, 34.03, and 20.34 billion yuan , respectively. The cost-benefit ratio in the BTH region was 1:2.49; at the city scale, Beijing ranked first (1:7.27), and the cost-benefit ratios of Tianjin and Hebei Province were 1:2.06 and 1:1.14, respectively. Of the 13 cities in the BTH region, Beijing had the highest net benefits, amounting to 16.43 billion yuan , while Handan City has the lowest net benefits, amounting to −0.58 billion yuan. The results may provide scientific support for the promotion of older vehicle and diesel vehicle scrappage subsidy policies, the development of cost-benefit analysis (CBA), and effective environmental decision-making in China. • Based on net number of scrappage YLVs, net benefits of the policy are calculated. • This paper estimates costs and benefits of the policy based on 1.27 million YLVs. • The costs, benefits, and net benefits are 13.69, 34.03, and 20.34 billion yuan. • The results help China promote vehicle scrappage subsidy policy on a large scale. • The results promote the development of the cost-benefit analysis in China. [ABSTRACT FROM AUTHOR]

Modern manufacturing enterprises are consuming a considerable amount of energy every year. Improving energy efficiency will not only benefit the enterprises economically, but also help the world to overcome various problems such as energy crisis and air pollution. To achieve this, an accurate energy consumption model is essential. The main objective of this paper is to develop an improved cutting power-based energy consumption model for general end milling process. The proposed model consists of an idle part due to auxiliary components and spindle rotation, and an additional part due to cutting workpiece materials. The first part is modelled as a function of spindle rotation speed, and the other part is considered proportional to the cutting power. Experiments under various milling conditions have demonstrated the effectiveness and efficacy of the proposed model. Comparative studies show that the proposed model is more accurate than other models. Although calibrated from slotting experiments when cutting aluminium alloy, the proposed model is applicable for general milling process. Partial-immersion milling experiments show that the prediction error of the proposed model is as low as 1.74%. When workpiece material changes to titanium alloy, its performance remains decent, with low prediction error of 2.81%. This reveals its capability to provide reliable estimation for different workpiece materials. As such, it could help avoid tedious model calibration, thus saving time, material, and energy. Finally, the energy efficiency of general end milling process is investigated through numerical experiments with the proposed model. By revealing the relationship between energy consumption and various cutting parameters, the proposed model could serve as an excellent platform towards energy-efficient manufacturing/cleaner production. • A new energy consumption model (ECM) for general end milling is proposed. • The ECM's accuracy and reliability is validated by general milling experiments. • The ECM significantly improves the prediction accuracy than other major models. • Energy efficiency can be analyzed with the ECM via numerical experiment. • The ECM contributes to cleaner production by saving time, material, and energy. [ABSTRACT FROM AUTHOR]

Air pollution not only affects residents' work and life, but also affects residents' health, which has negative effects on residents 'subjective well-being. In order to improve air quality, the Chinese government is making vigorous efforts to control air pollution. The purpose of this paper is to explore the impact of air pollution control on urban residents' happiness based on the micro-level survey data conducted in air pollution transmission channel cities. Firstly, the grounded theory is used to obtain the dimensions of the influence of government governance on residents. Then, the impact of these factors on residents' happiness in the context of air pollution control is examined. The empirical results of our study indicates that: (a) living experience was the main factor affecting residents' happiness, and order of effects through three ways on happiness are economic punishment for burning straw > uninterrupted sprinkler in city > prohibition of coal-fired heating; (b) the impact of green travel and public transportation pattern on residents' happiness is not significant; (c) the positive impact of heating supply pattern on residents' subjective well-being is mainly driven by people's general acceptance of "coal to gas" policy; (d) the promotion influence of fiscal policy on residents' subjective well-being is mainly achieved through subsidies for electric vehicles; (e) a good job security is one of the reasons for general improvement of residents' subjective well-being in the process of air pollution control. Image 1013 • The impact of air pollution control on urban residents' happiness is analyzed. • The micro survey data is conducted in air pollution transmission channel cities. • The grounded theory is used to find the dimensions affecting residents' happiness. [ABSTRACT FROM AUTHOR]

Emergency measures are effective measures that can be quickly taken in response to heavy air pollution. They not only have an obvious impact on slowing down the accumulation of particulate matter but also have a significant impact on public health and socio-economic development. Therefore, to analyze the effectiveness of emergency measures, one must assess their environmental, health and economic impacts. In this paper, we use exposure-response functions and a city-level computable general equilibrium (CGE) model to do so for China's Jing-Jin-Ji region. We find that the emergency measures implemented in 2019 significantly improve the region's air quality and enhance public health by reducing risk associated with acute bronchitis. Moreover, those emergency measures notably benefit the Jing-Jin-Ji region economically by expanding labor supply, most notably in Beijing and Tianjin. It seems Beijing and Tianjin should compensate industrial cities in Hebei, which enabled the Jing-Jin-Ji region's better air quality but encountered far fewer economic benefits. Handan, Baoding, and Cangzhou are among the cities in Hebei that are expanding employment in manufacturing and service sectors. These results can provide scientific guidance and policy suggestions for government while using emergency measures to combat regional heavy air pollution considering its health and economic benefits. • Evaluating impacts of inter-regional air pollution controls at city level in China. • Overall evaluate environmental, health, and economic impacts of emergency measures. • Emergency measures improve air quality, enhancing public health by reducing risk. • Emergency measures notably benefit the region economically by expanding labor supply. [ABSTRACT FROM AUTHOR]

Research on the effect of income inequality on pollution shows mixed results. This paper takes a new look at the urban air pollution data set of the U.N.'s Global Environmental Monitoring System (GEMS). We investigate the impact of income inequality on urban air pollution and relate the results to a median-voter model. In this model, more income inequality decreases the median income, reduces pollution controls, and increases output and pollution when the median income is above a threshold. We find that income inequality, measured by the Gini coefficient, increases S O 2 concentration in the rich democracies. The estimated effects are non-negligible in size. For the poor non-democracies, we find no evidence that the Gini coefficient impacts S O 2 concentration. The Gini coefficient is estimated to increase the smoke concentration at the five- or ten-percent significance level in most specifications in a pooled sample. We find no evidence that the Gini coefficient impacts the concentration of particulates in a pooled sample. We conclude that the empirical results largely are consistent with the median-voter model. [ABSTRACT FROM AUTHOR]

Regional collaborative governance has become one of the most significant trends in environmental protection due to its importance in suppressing pollution transfer. This paper employs panel data from 285 cities in China during 2003–2019 and a multi-period difference-in-differences (DID) method to evaluate the influence of regional collaborative governance on air pollution. Results show that regional collaborative governance significantly reduces air pollution. Heterogeneity assessment suggests that the inhibiting impact of regional collaborative governance on air pollution is long-term and increases temporally, whereas the spillover effect of regional collaborative governance is only significant in a specific range and decays spatially. In addition, the mechanism analysis reveals that regional collaborative governance reduces air pollution by increasing environmental regulation intensity, improving environmental governance efficiency, and promoting environmental protection technology. This study provides useful policy insights for policymakers seeking green and sustainable development to curb air pollution and improve environmental quality. • The impact of regional collaborative governance on air pollution is examined. • We employ a multi-period difference-in-differences approach. • Regional collaboration significantly reduces air pollution emissions. • Local effects increase temporally whereas spillover effects decay spatially. • The strongest inhibition comes from promoting environmental protection technology. [ABSTRACT FROM AUTHOR]

Previous studies have often focused on the direct benefits of environmental regulations on health. This paper quantifies the impact of environmental regulations on the cost of prevention for urban residents. The purpose of this study is to examine how environmental regulations affect urban commercial health insurance purchases. Air pollution monitoring stations in China capture exogenous air quality changes to overcome potential endogenous problems. Evidence shows that an increase in the operating days of air pollution monitoring stations will reduce the purchase of commercial health insurance in the city. The mechanism is that the operation of air pollution monitoring stations is conducive to improving local air quality and alleviating residents' health prevention needs. Heterogeneity analysis shows that the impact of air pollution monitoring station operation on the cost of prevention is less effective in more developed cities. Finally, we demonstrate that the number of claims for commercial health insurance dropped with the operation of air pollution monitoring stations. The results show that the benefits of improved air pollution do not only include the direct benefits of increased health, but also include the potential benefits of reduced prevention costs. Ultimately, the results further indicate the importance of air pollution control. [ABSTRACT FROM AUTHOR]

With the rapid economic growth, people's need for environment and atmospheric qualities is getting higher. The Chinese government is taking active measures to deal with it, and the scientific evaluation of atmospheric emission efficiency is necessary for atmospheric environment management. Concerning this reason, this paper uses the non-radial DEA model and the PS (Phillips and Sul) convergence test to study the atmospheric emission efficiency and spatial convergence characteristics in China and analyzes the changing trends and transfer path of atmospheric emission efficiency from a dynamic perspective. We conclude that (1) the overall level of atmospheric emission efficiency in China is low, and further improvement can be done; (2) there is a positive relationship between atmospheric emission efficiency and regional economic development; (3) there are obvious characteristics of unbalanced distribution and regional distribution of atmospheric emission efficiency; (4) the transfer path of atmospheric emission efficiency shows a decreasing trend year by year, which indicates that China's atmospheric environment is gradually being improved. These findings show some directions for the atmospheric environment management in China and can help the cities to deal with atmospheric pollution management issues. [ABSTRACT FROM AUTHOR]

This paper presents a multi-objective optimization model for a green supply chain management scheme that minimizes the inherent risk occurred by hazardous materials, associated carbon emission and economic cost. The model related parameters are capitalized on a big data analysis. Three scenarios are proposed to improve green supply chain management. The first scenario divides optimization into three options: the first involves minimizing risk and then dealing with carbon emissions (and thus economic cost); the second minimizes both risk and carbon emissions first, with the ultimate goal of minimizing overall cost; and the third option attempts to minimize risk, carbon emissions, and economic cost simultaneously. This paper provides a case study to verify the optimization model. Finally, the limitations of this research and approach are discussed to lay a foundation for further improvement. [ABSTRACT FROM AUTHOR]

The spiraling growth of the world's population and unregulated urbanization have resulted in many environmental problems, including poor quality of air, which is associated with a wide range of health issues. Machine learning approaches have been extensively employed to predict air quality, attracting the attention of the scientific community worldwide. Bibliometric studies provide a useful means by which to visualize and analyze published works, helping researchers to make novel scientific contributions by filling existing knowledge gaps in the research. To acquire an in-depth understanding of the topic, this paper presents a bibliometric analysis of all published articles on the use of machine learning networks to predict air quality found in the Web of Science (WoS) search engine from 1992 to 2021. S-curve analysis and social network analysis were used to identify the temporal distribution of articles, productivity by countries/continents, research institutions, and scientific metrics of journal productivity. This study indicated that maximum expansion of the literature witnessed during 2017–2021 (second phase) which represents an expansion or growth stage of machine learning and air quality prediction research. The number of published works increased significantly with 1432 articles accounting for 68.51% of all publications. As a result of the increased interest in machine learning-based prediction tools, the number of articles grew 2.17-fold compared to the 1992–2016 (first phase). In terms of international collaboration impact, Italy emerged as the most successful country (43.44), followed by Greece (31.22) and Spain (23.29). Author keywords analysis was employed to explore and evaluate the emerging research trends on the subject of air quality using machine learning models. Keywords that appear most frequently in this study are 'air pollution', 'air quality', 'machine learning', and 'forecasting'. Citation burst analysis, research productivity analysis, highly influential and highly cited works were also employed to examine various research themes and questions. In this study we also discussed how conventional methods were transformed into machine learning approaches. It is expected that this paper will provide technical guidelines, research priorities, and future opportunities for the precise prediction of air quality and emergency management of air pollution globally. • Interest in air quality prediction through machine learning model is expanding. • China and US were found productive countries in terms of countries collaboration. • Big data, Internet of Things, and Smart city are emerging topic for future research. • Significant difference between citations, funded and non-funded research. • Ensemble modeling is popular in air quality prediction research. [ABSTRACT FROM AUTHOR]

The spiraling growth of the world's population and unregulated urbanization have resulted in many environmental problems, including poor quality of air, which is associated with a wide range of health issues. Machine learning approaches have been extensively employed to predict air quality, attracting the attention of the scientific community worldwide. Bibliometric studies provide a useful means by which to visualize and analyze published works, helping researchers to make novel scientific contributions by filling existing knowledge gaps in the research. To acquire an in-depth understanding of the topic, this paper presents a bibliometric analysis of all published articles on the use of machine learning networks to predict air quality found in the Web of Science (WoS) search engine from 1992 to 2021. S-curve analysis and social network analysis were used to identify the temporal distribution of articles, productivity by countries/continents, research institutions, and scientific metrics of journal productivity. This study indicated that maximum expansion of the literature witnessed during 2017–2021 (second phase) which represents an expansion or growth stage of machine learning and air quality prediction research. The number of published works increased significantly with 1432 articles accounting for 68.51% of all publications. As a result of the increased interest in machine learning-based prediction tools, the number of articles grew 2.17-fold compared to the 1992–2016 (first phase). In terms of international collaboration impact, Italy emerged as the most successful country (43.44), followed by Greece (31.22) and Spain (23.29). Author keywords analysis was employed to explore and evaluate the emerging research trends on the subject of air quality using machine learning models. Keywords that appear most frequently in this study are 'air pollution', 'air quality', 'machine learning', and 'forecasting'. Citation burst analysis, research productivity analysis, highly influential and highly cited works were also employed to examine various research themes and questions. In this study we also discussed how conventional methods were transformed into machine learning approaches. It is expected that this paper will provide technical guidelines, research priorities, and future opportunities for the precise prediction of air quality and emergency management of air pollution globally. • Interest in air quality prediction through machine learning model is expanding. • China and US were found productive countries in terms of countries collaboration. • Big data, Internet of Things, and Smart city are emerging topic for future research. • Significant difference between citations, funded and non-funded research. • Ensemble modeling is popular in air quality prediction research. [ABSTRACT FROM AUTHOR]

China's economic growth is accompanied by air pollution, which has harmed public health. Former scholars have explored the influencing factors of public health from different perspectives with different methods, among which family income and environmental pollution are two important factors. The paper explored the combined effects of economic level and air pollution on public health at the micro and macro level using the multivariate ordered Logit model and panel data regression model. A comparative analysis was also explored between China's eastern and western regions. The results demonstrated that: (1) Both at the micro and macro level, economic level was positively correlated with public health, while air pollution was negatively correlated with it. (2) The improvement of the economic level made public health more susceptible to air pollution at the micro level and at the macro level. (3) The higher the economic level, the lower the effect of economic growth in reducing the adverse effects of air pollution on public health. This paper proposed that sustainable economic growth should be pursued, the emissions of air pollutants should be reduced, regional development should be balanced and the development gap between China's eastern and western regions should be narrowed. [ABSTRACT FROM AUTHOR]

The composition and size of the passenger car fleet is often influenced by legislation and policy, including taxation, scrappage, and vehicle registration policies. Numerous measures at national and international level have been investigated to reduce the air pollution and/or climate change impacts of passenger fleets. However, the objectives of climate change and air pollution policy occasionally are conflicting, and this has resulted in a number of well publicised policy shortcomings. This paper outlines the development of a fleet emissions control (FEC) framework which enables the dynamic and adaptive optimisation of fleet emissions through changes in taxation policy in Ireland. The data for analysis was obtained from national sources including datasets from the national emission inventory and COPERT model. Applications of regression-based modelling and statistical analysis were conducted to predict fleet, mileage, and emissions changes. The results of the FEC framework showed that no increase in NO x emissions, above 2007 levels, could be achieved at a cost of a small increase in CO 2 in 2016 (+1.8%). This could be achieved by taxation policy primarily resulting in a shift away from small engine diesel vehicles (<1.4 L) in the fleet which were responsible for the largest contribution to emissions. In the transition of vehicle fleets to full electrification or full decarbonisation, the FEC framework developed here offers the potential to formulate practical and optimised adjustments in static taxation systems. These adjustments will assist in achieving the requirements of national policies on reducing emission. • A Fleet Emissions Control Framework for passenger cars was developed enabling practical optimisation of fleet emissions. • Incentivising one vehicle category over another, is a complex process with potentially positive and negative outcomes. • Incentivising diesel or petrol each have negative consequences. • Policy should incentivise a fleet composition which optimises the total emission. [ABSTRACT FROM AUTHOR]

Transportation infrastructure plays a fundamental role in reducing pollution emissions to avert global environmental degradation. However, the mechanisms behind these effects remain unclear. This paper aims to provide empirical evidence by investigating the effects of roads on the intensity of air pollutant emissions. Using a city-level data set for the period 2003–2015, we find that roads help to reduce the intensity of pollution emissions in China and induce greener growth performance. Specifically, we test two possible mechanisms through which roads improve environmental performance, and the results suggest that roads have a more positive and significant impact on air pollution reduction when an eco-industrial park is located in a nearby city. There is also evidence that roads can spur green innovation and hence can contribute to regional green performance. • We use city level data to examine transportation infrastructure's effect on air pollution in China. • We propose two possible mechanisms to confirm the effect of transportation infrastructure. • Transportation infrastructure plays an important role in reduction of air pollution emission. • The implications of policy in emerging economies are discussed. [ABSTRACT FROM AUTHOR]

Rapid industrialization, urbanization, and motorization lead to hiking of air pollution in various mega cities including Delhi, India. Studies done to analyze pollution suggests that vehicle exhaust emissions are major contributor to the urban air quality along with many other comparable sources. Hence to check instantaneous pollution increment, government aims to reduce vehicle emission. Traditional policies are working at times for holding sudden increase but long-term effects are not seen which need meso-spatial and small temporal policy. For optimizing meso-spatial policies implementation, many intricacies related to moving and stationary sources in near real-time have to be monitored including vehicular emission, itself. Analyzing these moving source emissions on the meso-spatial level is challenging. Therefore, the present study is an attempt to first understand the need of meso-spatial and near real-time checking policy and then leveraging the usage of previous region specific pollutant survey reports to map real-time pollution monitoring parameters. For that, a real-time vehicle monitoring strategy is proposed to map city-wide traffic congestion and emission using crowd-source data of Google Maps. For comparative study of different meso-spatial regions real-time moving source pollutant parameter 'μ' is calculated using a factor 'F'. Also, the different effects of congestion on vehicular emission in two different meso-spatial areas of Delhi is presented using comparative case study. Analysis of case study revealed that Anand Vihar area is more prone to vehicle emission variability in case of congestion fluctuation. Further the discussion of short temporal and spatial emission calculation, for weekly pollution evaluation is presented in the paper. This will be helpful to the authorities in formulating technological, institutional and traffic management policies. • Traditional pollution checking policy and different emission models are discussed for Delhi region. • A methodology to map real-time congestion for city-wide area on small tempo-spatial basis is provided. • A factor 'F' is introduced for relating congestion to vehicular and dust emission. • Vehicle proportionate area specific moving source emission 'μ' is calculated and analyzed by comparative emission study. • Suggestions on checking policy and the methodology to judge their effectiveness for immediate action is provided. [ABSTRACT FROM AUTHOR]

Abstract Air pollution impact assessment is a major objective for various community councils in large cities, which have lately redirected their attention towards using more low-cost sensing units supported by citizen involvement. However, there is a lack of research studies investigating real-time mobile air-quality measurement through smart sensing units and even more of any data-driven modelling techniques that could be deployed to predict air quality accurately from the generated data-sets. This paper addresses these challenges by: a) proposing a comparative and detailed investigation of various air quality monitoring devices (both fixed and mobile), tested through field measurements and citizen sensing in an eco-neighbourhood from Lorraine, France, and by b) proposing a machine learning approach to evaluate the accuracy and potential of such mobile generated data for air quality prediction. The air quality evaluation consists of three experimenting protocols: a) first, we installed fixed passive tubes for monitoring the nitrogen dioxide concentrations placed in strategic locations highly affected by traffic circulation in an eco-neighbourhood, b) second, we monitored the nitrogen dioxide registered by citizens using smart and mobile pollution units carried at breathing level; results revealed that mobile-captured concentrations were 3–5 times higher than the ones registered by passive-static monitoring tubes and c) third, we compared different mobile pollution stations working simultaneously, which revealed noticeable differences in terms of result variability and sensitivity. Finally, we applied a machine learning modelling by using decision trees and neural networks on the mobile-generated data and show that humidity and noise are the most important factors influencing the prediction of nitrogen dioxide concentrations of mobile stations. Highlights • We proposed an air quality evaluation framework using fixed and mobile sensing units. • It also integrates machine learning methods to predict the air quality from mobile data. • Three experimenting protocols for air pollution monitoring have been implemented. • NO2 pollution at human breathing levels was 3-5 times higher than those of static units. • Decision trees and neural networks can accurately predict mobile air quality. • Humidity and noise are the most important factors affecting the NO2 prediction. [ABSTRACT FROM AUTHOR]

Abstract: China is currently facing the threat of serious air pollution and has adopted a series of governance policies. However, the fact that PM 2.5 indicator in some regions often reached far higher than the official threshold since 2015 has reflected that China's current Air Quality Index system for measuring and evaluating air quality is still not perfect. Therefore, this paper extended the current air quality indicator system officially used by China. Using improved Entropy-weighted Factor Method and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) Method, we calculated the air quality scores of 26 cities in China's most economically developed region - the Yangtze River Delta region based on their daily average concentration numbers of main air pollutants from February 2015 to January 2018. Based on the air quality calculation result, we further studied the effectiveness of air pollution control policies of this region by using the Box-Jenkins Model with fuzzy strategy parameter adjustment. Our findings are: the pollution control policy is more effective to Shanghai, Jiangsu and Zhejiang. The air quality score of Shanghai has improved by 51.07% compared with its level before the policy. Meanwhile, the air quality improvement in Zhejiang province has shown the characteristics of "Campaign-style Governance" right before the G20 Summit, especially that in Hangzhou, the host city of the Summit. On the other hand, maybe due to late start of air pollution control programs, the cities of Anhui province haven't shown obvious improvements in air quality, and some cities have even seen deterioration in air quality scores during our study period. Graphical abstract Image 1 Highlights • We extended the current air quality indicator system officially used by China. • We used the Entropy-weighted Factor Method and TOPSIS Method for assessing. • We studied the control policies by Box-Jenkins Model with fuzzy strategy parameter. • Results and corresponding reasons were analyzed according to provinces and cities. • Policy recommendations for air pollution control in YRD were proposed. [ABSTRACT FROM AUTHOR]

Abstract Environmental-economic perspectives are recently taking growing momentum in the analysis of country-level performances, but few studies take into account the multi-dimensional nature of the phenomenon. The leading measure of pollution still remains only CO2 emission or, at best, CO2 equivalent emission. The few works taking a multi-criteria perspective are mainly related to specific case studies, urban areas, or the localization of renewable power plants. In this paper, we propose a multi-criteria analysis for a macro-perspective assessment of 10 different pollutants in 30 European countries over the period 2008–2015. Methodologically, we propose a new hybrid tool allowing us to merge the consolidated procedure usually employed for environmental evaluation: PROMETHEE, with a more flexible weighing process inspired by Data Envelopment Analysis. The unprecedented use of this tool for developing a macro perspective allows the clustering of European countries according their relative performances without any exogenous assumption about the weights given to the specific pollutants. In addition, the empirical evidence emerging from the analysis provides a comprehensive picture of patterns followed by European economies, which highlights the relative strengths and flaws at country-level for the considered pollutants. [ABSTRACT FROM AUTHOR]

Abstract The severe health damage and massive health costs associated with industrial air pollution have attracted global concern. A spatial lag model with decomposed direct and indirect spatial effects was used to estimate the impact of industrial air pollution on health care expenditures in Chinese provinces from 2002 to 2014. The control variables of health reform, GDP per capita, urbanization, aging, education level, and hospital supplies were considered. Moran's I index was applied to investigate the spatial agglomeration of health care expenditures. The spatial lag model with fixed effects provided the best fit to measure the effect of industrial air pollution on health care expenditures. The global Moran's I of provincial health care expenditures increased from 0.3988 in 2002 to 0.4554 in 2014. The estimated spatial lag coefficient of provincial health care expenditures was 0.188. The estimated direct and indirect effects of industrial air pollution on provincial health care expenditures were 0.032 and 0.0072, respectively. The direct effect of health reform on health care expenditures was −0.006. The results indicate that the strengthening spatial agglomeration of provincial health care expenditures is caused by the joint effect of industrial air pollution, health reform, and other socioeconomic factors. Industrial air pollution increases health care expenditures in the local and neighboring provinces. Most importantly, the effect of industrial air pollution outweighs the reduction effect of health reform on health care expenditures. The final remarks of this paper suggest three main measures to reduce industrial air pollution and its health costs. [ABSTRACT FROM AUTHOR]

Abstract Paddy straw is an abundantly available lignocellulosic biomass in Southern and South-Eastern Asia, which remains in surplus. The surplus straw is either burnt in the farms or dumped openly to get the farms evacuated for next crop, which not only creates the environmental pollution but also loses the potential energy source. It is a vital source of renewable energy and is considered to mitigate the global dependency on fossil fuels by producing sustainable biofuels. Anaerobic digestion is one of the biochemical conversion routes, which utilizes paddy straw for biogas production, and reduces the environmental pollution by preventing straw burning and generating carbon-neutral biofuel. This review paper is focused on anaerobic digestion process as one of the most cost-efficient alternatives for utilization of surplus paddy straw to produce biogas as gaseous biofuel. However, anaerobic digestion of paddy straw faces challenges of relatively low methane yield, high retention time, and instability of anaerobic digestion system due to its recalcitrant structural composition, unbalanced nutrients, and lack of efficient inoculum. These challenges could be conquered by different strategies viz pretreatment of paddy straw, co-digestion with other organic matters, selection of effective inoculum sources, and optimization of process parameters. Thus, the present review highlights the environmental impact and biomethane potential of paddy straw, major challenges and their solutions to enhance the biodigestibility, and factors responsible for process stability. Lastly, few approaches to attain the process sustainability by adopting efficient supply-chain logistics and future advanced technologies have also been discussed. Graphical abstract Image 1 Highlights • Paddy (rice) straw has potential to produce biomethane as source of energy. • Challenges of paddy straw based biomethane production are summarized. • Various strategies to improve biodegradability of paddy straw are discussed. [ABSTRACT FROM AUTHOR]

Abstract Fine particulate matter is becoming a primary component of air pollution in China, damaging public health and economic growth. Although environmental regulation is an important instrument to control air pollution, studies on the effect of environmental regulation are mixed. Do environmental regulations help improve the air quality in urban centers, and what mechanism explains their effects in China? In order to explore the causal relationship between environmental regulations and air quality, the effectiveness of the New Ambient Air Quality Standards —primarily the monitoring of PM2.5—was evaluated using the Difference-in-Differences (DID) method to weaken the endogeneity problems. Our results suggest that the New Standards reduce the concentration of PM2.5 and emissions of SO 2 in pilot cities in neither the short-term nor the long-term. Our heterogeneous analyses show that the monitoring efforts, pollution control efforts, and ownership structures can affect outcomes of New Standards significantly, and that they have different influences on various categories of pollutants. Our paper implies that the Chinese government should make more efforts beyond setting up environmental regulations. Highlights • The average treatment effects in treated group of New Standards on SO 2 and PM2.5 are zero. • Monitoring efforts and pollution investments can reduce SO 2 in treated group, but will not affect PM2.5. • The effect of New Standards will be weakened for SO 2 and PM2.5, in areas with high proportion of state-owned economy. • A reason for an ineffective environmental regulation is that its heterogeneous effects caused by regional features. [ABSTRACT FROM AUTHOR]

Abstract To reduce carbon intensity efficiently, it is important to identify regional differences of China's carbon intensity considering the decoupling relationship between economic output and carbon emissions. This paper divided China's 30 provinces into 4 regions based on the relationship between the average annual growth rates of CO 2 emissions and GDP, and explored the driving forces of carbon intensity in 2000 and 2015 for China's 30 provinces and 4 regions This decomposition method can provide the rankings and specific drivers of carbon intensity, including energy intensity, industrial structure and energy structure. The results show that during 2000–2015, all provinces' carbon intensity decreased except for Hainan. Ningxia, Shanxi, Guizhou, Qinghai and Xinjiang were the five top provincial drivers of the carbon intensity growth in China. Energy intensity was the most important driving factor influencing the change of carbon intensity. Industrial structure and energy structure had small effects on the change of carbon intensity. Moreover, the region III with a high CO 2 emission growth rate and a low GDP growth rate had a poor performance of carbon intensity, due to the large impact of energy intensity. Based on the results of this study, the reduction in carbon intensity could be achieved by further reducing energy intensity, optimizing energy and industrial structure, especially in the provinces with fast CO 2 growth rates and slow GDP growth rates. [ABSTRACT FROM AUTHOR]

Abstract The vehicular emission modelling software COPERT is extensively used in generating emission levels for National Emissions Inventory in Europe and in some other countries internationally. This paper aims to study the uncertainties associated with emission estimates generated from COPERT(v5.1) outputs through sensitivity analysis of the model input parameters. The input parameters considered in this study are temperature, speed, relative humidity, trip length, and driving style (mileage share). Many of these parameters are not directly measured or country-wide average values are investigated in this study. The uncertainties of the emission estimates were obtained through varying the parameter values, within realistic limits, either individually or considering factor interactions by varying two or more parameters simultaneously. The uncertainties of the emission estimates of certain pollutants (CO, VOC and NMVOC) can be significant from −58% to +76%. Some gases, such as CO 2 show almost no sensitivity to input parameter variations. The results indicate that the COPERT outputs are most sensitive to variations in trip length and speed, both of which are not directly measured. Considering the percentage of urban driving share has a huge effect on the national emission estimates, inventories were separately prepared for the Greater Dublin Area (GDA), the largest urban area of Ireland with highest population and vehicle densities. GDA has 48% and 50.37% shares of CO 2 and NOx emissions respectively, compared to the national levels. The consequence of over- or underestimation of emission inventories for Ireland was calculated to be approximately +/− €45million. Considering the major implications of NEI for climate change and other related impacts it is crucial to report the pollutant emission levels appropriately stating uncertainty levels. The findings of this study provide national experts with a methodology to estimate uncertainties of COPERT outputs and to identify the key sources of these uncertainties where policy and emission reduction strategies should be targeted. Graphical abstract Image 100836 Highlights • Vehicular emission levels modelled using COPERT varies significantly based on assumptions. • Sensitivity modelling of COPERT input parameters, values of which are not widely measured. • Individual & interactive effects of temperature, speed, driving style etc. on emission variations. • Uncertainties of CO, VOC, NMVOC, N 2 O levels are greater than uncertainties of CO 2 , NOx, & PM levels. • Damage costs of pollutants under/overestimated by approximately 43.9 mil€. [ABSTRACT FROM AUTHOR]

Abstract Facing the even worse air pollution of many cities in China, the Chinese government is trying to find the best solution about citizenship care problem through high technology. The new energy vehicles (NEVs) technology, as one of the high-tech good samples around the world, can reduce greenhouse gas emissions, protect the environment effectively, and finally accomplish the low-carbon economy of sustainable development. So the Chinese government pays close attention and billions of Research and Development (R&D) subsidies to help the NEVs companies research their generic technology. Based on the lack of the effective decision-making mechanism for R&D subsidies by the government, this paper aims to propose a novel decision-making model and help the policy-maker choose the right objects for R&D subsidies, avoiding the problems like a waste of the public resources, cheating for taking the subsidy and so on. Three-way decision theory is employed to solve the mechanism design, and the government's actions represent subsidize, delay decision-making and do not subsidize. According to the actual case study, the model has verified the validity and rationality. [ABSTRACT FROM AUTHOR]

Abstract Cities, the core of the global climate change mitigation and strategic low-carbon development, are shelters to more than half of the world population and responsible for three quarters of global energy consumption and greenhouse gas (GHG). This special volume (SV) provides a platform that promotes multi- and inter- disciplinary analyses and discussions on the climate change mitigation for cities. All papers are divided into four themes, including GHG emission inventory and accounting, climate change and urban sectors, climate change and sustainable development, and strategies and mitigation action plans. First, this SV provides methods for constructing emission inventory from both production and consumption perspectives. These methods are useful to improve the comprehensiveness and accuracy of carbon accounting for international cities. Second, the climate change affects urban sectors from various aspects; simultaneously, GHG emissions caused by activities in urban sectors affect the climate system. This SV focuses on mitigation policies and assessment of energy, transport, construction, and service sectors. Third, climate change mitigation of cities is closely connected to urban sustainable development. This SV explores the relationships between climate change mitigation with urbanization, ecosystems, air pollution, and extreme events. Fourth, climate change mitigation policies can be divided into two categories: quantity-based mechanism (e.g., carbon emission trading) and price-based mechanism (e.g., carbon tax). This SV provides experiences of local climate change mitigation all over the world and proposes the city-to-city cooperation on climate change mitigation. [ABSTRACT FROM AUTHOR]

Abstract Air pollution is widely believed to cause healthy risks and influence nations' economic dimensions. This paper investigates the impact of air pollution on housing prices in China's 286 prefectural-level cities during 2005–2013. To address the endogeneity problem of PM 2.5 concentrations in our regression, we propose an instrument variable strategy based on ventilation coefficient. The estimation results suggest that a 10% increase in PM 2.5 concentrations causes a 2.4% reduction in local housing prices. Air pollution also hinders the progress of urbanization, limits cities' human capital formation and changes people's expectations of housing prices that we interpret as three potential mechanisms behind our main findings. [ABSTRACT FROM AUTHOR]

Abstract Korea has the highest air pollution among the Organization for Economic Co-operation and Development (OECD) countries. Since the recent environmental analysis (Kim et al., 2017) reported the feasibility of replacing taxis with electric vehicles (EVs) in metropolitan cities from a 'tank-to-wheel' emission perspective, various stakeholders have attempted to reduce air pollution by activating the EV market in Korea in accordance with international trends. Nevertheless, no holistic study has yet been published on the nationwide changes in air quality caused by EV diffusion from the perspective of 'well-to-wheel' emissions. This paper presents the results of estimating the stability of the electric power supply and fine particulate matter emissions in some cases, and the results of examining the structure of public discourse using big social media data. From the findings of our study, we made the following conclusions: (1) If the market share of EVs exceeds 12.5% before 2030 in Korea's domestic market, the supply and demand of stable energy will be threatened. (2) Under traditional energy mix conditions, the popularization of EVs may slightly reduce air pollution over metropolitan roads, but drastically increase air pollution near power plants that utilize fossil fuels. (3) Social media discussions show that the public is neither concerned about EVs being possible sources of pollutants, nor about potential instabilities in the energy market. (4) To obtain a socially acceptable energy mix, energy policy decision makers can select emission-free energy sources, such as nuclear power and renewable energy, depending on their priorities and based on power demand management to suppress excessive electrification. Highlights • The rapid expanding electric car market can threaten the supply and demand of stable enegy. • The effects of improving the air quality by electric cars differ depending on the region. • The public does not concern about electricity supply as well as air pollution by electric cars. • Policy makers can choose either nuclear power or renewable energy depending on their priorities. [ABSTRACT FROM AUTHOR]

Abstract Urban air pollution has become a major concern in China. In the heavily populated and developed Beijing-Tianjin-Hebei (BTH) region, vehicle emissions are major pollution contributors. This paper aims to establish 2014 vehicle emission inventories for five major air pollutants in the BTH region: CO, HC, NO x , PM 10 and PM 2.5 and carry out an emission control policy scenario analysis based on the newly developed inventories. Results showed that total emissions of CO, HC, NO x , PM 10 and PM 2.5 from vehicles in the BTH region were 1622.4 kt, 187.5 kt, 544.7 kt, 23.5 kt, and 26.1 kt, respectively. Based on the emission inventory, high-resolution emission distribution maps of the study area were created at a scale of 1 km × 1 km by incorporating local traffic flow data. The CO, HC and NO x emission levels were higher in the southeast, while the PM 10 and PM 2.5 levels were relatively evenly distributed throughout the BTH region. Based on the emission inventories, four policy scenarios were set to simulate the emission changes, and results showed that eliminating old vehicles and upgrading oil quality could reduce emission efficiently. A policy of eliminating old vehicles was selected to calculate the economic cost. Results showed that the emission reduction efficiencies of unit cost decreased from Hebei, Tianjin to Beijing. The results of this study could help policy makers identify pollution sources and design appropriate control measures. Highlights • We calculated vehicle emission factors in the Beijing-Tianjin-Hebei region. • We generated high spatial resolution emission maps based on traffic flow data. • We set various policy scenarios to evaluate vehicle pollution control measures. • We analyzed governmental and social costs of typical policy scenario. [ABSTRACT FROM AUTHOR]

Abstract Air pollution and its effects on public health have received considerable attention in China. This paper extends discussion of the relationship between pollution and health by focusing on the effects of certain socioeconomic factors from an equality perspective. Hierarchical linear regression models are used to analyze the effects of environmental pollution on the health of residents and explore the inherent mechanisms through which environmental and economic factors contribute to increases in health inequality. The main results indicate that pollution poses significant risks to health. Individual income and life satisfaction are found to be significantly positively related to health and this relationship is intensified by the effects of environmental pollution. The results show that health inequality is prevalent throughout China and is more severe in rural areas. The damage to health caused by pollution further increases the levels of health inequality to varying degrees in groups with different income levels. Pollution also increases the impact of income inequality on health inequality. Overall, the results to some extent validate the concept of an "environment-health-poverty trap." [ABSTRACT FROM AUTHOR]

Abstract Electric vehicles (EVs) are the future of road transport in both Poland and the Czech Republic and offer significant potential for reducing air pollution and increasing life comfort, especially in crowded city centers. This paper presents a comparative life cycle assessment (LCA) of EVs in Poland and the Czech Republic, considering the life cycle from cradle to grave, with a special focus on the production of the electricity required to charge EV batteries. The analyses included the current and future energy systems (from 2015 to 2050) used to charge EV batteries in the both countries. A comparative analysis of EVs and passenger vehicles with internal combustion engines (ICEVs) was carried out. In addition, the analyses considered scenarios of smart grids from which the energy for the charging of EV batteries could be supplied exclusively from renewable sources. The results showed that the environmental burden of current and future EVs is higher in Poland than in the Czech Republic for all analyzed impact categories and that this result is primarily related to the type of electricity used to charge EV batteries. The comparative analysis of EVs and ICEVs showed that greenhouse gas (GHG) emissions and fossil fuel depletion in Poland and the Czech Republic, both at present and in the future, will be lower in the case of EVs than in the case of ICEVs. However, the acidification, eutrophication, human toxicity, and particulate matter formation caused by EVs are higher than those caused by ICEVs. The results showed that EVs coupled with renewable electricity sources offer the potential to reduce the negative impacts on the environment. It was concluded that the main determinant of the environmental impact of EVs is the type of electricity used to charge EV batteries. This is the first attempt at a comparative LCA of EVs in Poland and the Czech Republic. It is also the first approach that includes analyses of the LCA for both the present and future electricity production systems used for charging EV batteries. Highlights • The environmental performance of EVs in Poland and the Czech Republic was assessed. • The main sources affecting EV environmental performance were analyzed. • A comparative LCA of electric and internal combustion vehicles was conducted. • LCA of EV charging with exclusively renewable sources was performed. • The study showed the importance of the energy sources used to charge EV batteries. [ABSTRACT FROM AUTHOR]

A strategy of controlling individual pollutants without considering synergistic effects and ancillary benefit/cost has been followed in the course of air pollution control in China. This policy orientation could lead to divided and costly technology pathways. In this paper, the coal-fired power sector is used as a representative case to investigate the technology schemes and assess their cost effectiveness, so as to provide empirical evidence of technology synergies' impacts on cost-effectiveness and to shed light on the future directions for pollution control strategies. The results indicate that more pollution damage caused by particulate matter and mercury, could be avoided at less cost if the proposed technology schemes can be used more instead of the current mainstream scheme in this sector at the beginning of air pollution regulation. It implies that more detailed evaluation of technology schemes is needed to better control multiple pollutants and alleviate various negative health endpoint effects. The transformation of strategy will rely on a combination of technological developments and policy changes. The lessons learned from coal-fired power sector can contribute to policy-making across sectors within the industry. [ABSTRACT FROM AUTHOR]

Abstract After high speed development on economics during the past decades, China have accumulated a lot of air environment problems. A lot of studies based on data envelopment analysis (DEA) have been done to measure China's air problem by using monthly or annual data. As the development of real-time air quality monitoring, more valuable daily data should be utilized to evaluate air problem. The present paper constructs a set of DEA models for calculating air quality, in which the integral and zero-sum gain constraints are considered to match the characteristics of daily air monitoring data. An empirical analysis have been done to measure the air quality of 31 main cities in China by using the daily Air Quality Index. There are two main finds as follows. Firstly, all the 31 major cities in China need to do more work to improve air quality, while there are significant differences between the performance of different cities. Secondly, the air quality of Chinese cities has changed over month, the best air quality appeared in August and September while the worst occurred in December and January. Also, we calculate the target values for improving the air quality of Chinese cities. Highlights • Daily Air Quality Index data is used to evaluate air quality in China. • A set of DEA approaches are construct by inserting integral and zero-sum gain constraints. • The air quality of Chinese cities have significant tendency of variation during different months. • Specific values are provided for Chinese cities to improve their air quality. [ABSTRACT FROM AUTHOR]

Urban air pollution generated from straw open burning after the harvest seasons in China has been one of the significant problems interfering with the city's proper functioning. This paper applied contingent valuation in a face to face survey to assess the individual willingness of urban residents in Henan, China to pay for corn straw burning ban to policy makers. Such assessments are important for policy makers to determine the investment and policy instruments for regulating environmental impacts of straw open burning. To investigate the determinants of the stated willingness to pay (WtP) a sample of 1890 urban residents in Henan, China was selected. The study used Tobit model. About 62% of respondents stated that they were willing to pay. The expected WtP was about 76.72 Chinese Yuan (RMB) per person per year for the total respondents and 142.70 RMB per person per year for observations with positive WtP bids. Aggregate value was between 3.41 and 3.90 billion RMB indicating that corn straw burning ban is of considerable economic value to Henan. Results from the study show that the experience of environmental protection, expenditure on protecting health from air pollution, influence of straw burning on respondent's health, life, work, household income, education, job place, and family size were significant variables explaining WtP. The results of the study will be useful for policy makers when making up their mind how much funds should be invested and what kinds of policy instruments could be suitable for banning straw burning. [ABSTRACT FROM AUTHOR]

It is often difficult to determine the effects of policies at a sectoral level in the overlapping domains of pollution control and energy conservation, making it difficult to consider co-benefits of energy conservation and air pollution reduction and tensions. In China, the industry sector contributes much more carbon and pollution emissions than other sectors. In this paper, Baoshan District (BSD), one of the most important industrial zones in the Shanghai metropolis, is used as a case study to illustrate the situation and to provide information to assess the effectiveness of environmental sustainable development policies in industries. The policies resulting from China's Eleventh Five-year Plan (FYP) are considered at the level of BSD. In particular, the result of implementing local policies of air pollution control and energy are analysed at BSD. Three indicator systems are adopted for quantitatively and qualitatively evaluating energy saving and air pollution reduction achieved by technical, structural and management measures in industrial enterprises of BSD. Analysis made in the paper shows that the co-benefits of pollution cutting and energy conservation have been achieved at certain scopes and degrees in the industry sector in BSD, e.g. SO 2 and Particulate Matter (PM) were reduced by 35.1% and 7.7% respectively, and the energy density was cut by 26.7%. Due to existing barriers of the lack of co-planning and co-operations in the process of designing and implementing the policies, and the overlooking the leakage of emissions in the whole project area, the overall co-benefits cannot be achieved effectively in BSD. Recommendations are made for future detailed studies of this or similar districts to develop an indicator system of co-benefits to help demonstrate the advantages of joint planning and policies for co-benefits. [ABSTRACT FROM AUTHOR]