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Abstract: Papermaking enterprises are major polluters that cause water pollution and air pollution. This paper aims to provide analysis of the energy saving and emission reduction in papermaking enterprises.It is the inevitable choice of establishment industrial ecology park as the leading of the papermaking industry by the implementation of cleaner production and circulation economy. Shandong Haiyun efficient ecological park is taken for example.Researches of the developing strategies and policy support of energy saving and emission reduction is discussed. The paper is divided into five parts, the first part is the preface, the second part introduces the general of Haiyun efficient industrial park, the third part puts forward the scheme of clean production of Haiyun efficient ecological industrial park, the fourth part puts forward ecological industry pattern of Haiyun efficient ecological industrial park, the fifth part puts forward policy guarantee measures, and the sixth part makes the summary. [Copyright &y& Elsevier]

There are a great number of DEA models proposed to deal with ecological efficiency problems with undesirable outputs. However, which model should be used in a specific scenario or how about the discriminability of a given DEA model is hard to decide in practice. This paper uses the ecological Shannon DEA procedure based upon the existing study to obtain an ecological comprehensive efficiency score for each decision units. The procedure is used to appraise the ecological evaluation to 32 paper mills along the Huai River in China. The results seem reasonable since they integrate the results of existing relevant DEA models, and calculate the importance degree of each model. The procedure can also be used to determine the pollutant emission quotas for those paper mills. [ABSTRACT FROM AUTHOR]

Based on data analysis and documentary research, this paper indicates that the main causes which negatively affect the preservation of paper documents in China are acidification and damaging pests such as moths and insects. The priorities for the preservation of Chinese documents are protecting the documents against air pollution and controlling pests and insects. Taking these problems and the Chinese national condition into account, the paper proposes to create a favorable microenvironment for decreasing the acidification of papers and to adopt various measures for controlling pests and insects. [ABSTRACT FROM AUTHOR]

The market-oriented reform of China's power market has gradually transformed power prices from government pricing to market regulation, which not only promotes the production efficiency of industrial enterprises, but also inhibits the excessive consumption and waste of power by residential power users. This paper uses the data from 2006–2018 combined with the precious industrial power price data and macroeconomic data of 100 cities in China, takes the marketization reform of the power market in 2015 as a quasi-natural experiment, and uses the difference-in-differences model to empirically study the causal relationship between power market reform and air pollution for the first time. The study found that power market reform can reduce air pollution, and this conclusion is also supported by a number of robustness tests. Mechanism analysis shows that power market reform can reduce air pollution by improving power market efficiency, promoting technological progress, and reducing power consumption. Heterogeneity analysis shows that power market reform can suppress air pollution more significantly in eastern regions, regions with severe air pollution, and regions with larger populations. This paper not only provides new research perspectives and research ideas for air pollution prevention and control, but also provides empirical evidence for the positive externalities of power market reform. [ABSTRACT FROM AUTHOR]

Air pollution poses a great danger to human health and economic development, and understanding people's willingness to pay for improved air quality (WTPA) impacts environmental protection. This paper investigates WTPA based on the perspective of subjective well-being (SWB) and analyzes the mediating role of social interaction on the relationship between the two. This paper distinguishes social interactions into online and offline interactions and analyzes whether the mediating effect of the two different interactions on SWB and WTPA exists separately. Using data from the 2018 China General Social Survey (CGSS), we find that SWB has a significant positive effect on WTPA, individuals with higher well-being have higher pro-environmental willingness; there is no age, education level, sex of the person, or regional heterogeneity in the effect of SWB on WTPA; offline social interactions play a partially mediating role between SWB and WTPA, while online social interactions failed to mediate between the two. This paper's policy implication is that improving residents' subjective well-being is both an important development goal and an essential way to resolve the conflict between economic development and environmental protection. [ABSTRACT FROM AUTHOR]

Imported air pollution has a significant impact on urban air quality. Relevant studies have shown that many urban air pollution events are not resourced by local emissions but are imported by air pollution from surrounding areas transported across regions. The prevention and control of air pollution is very necessary. However, the existing supervision of urban air quality mostly relies on ground monitoring stations, which are extremely limited in time and space, and cannot satisfy continuous time-space air pollution research. Therefore, aiming at the problem of urban air pollution control, this paper used MERRA-2 reanalysis data and ground monitoring data to establish a "Time-Longitude-Latitude" three-dimensional pollution curve, and then a genetic algorithm was used to optimize its fitting. This study finally reconstructed the imported air pollution transmission route. This paper takes an air pollution event that occurred in Xuzhou City, China, on 12 January 2020, as an example. Through the analysis of aerosol optical depth (AOD), particulate matter (PM), wind speed, and other factors, we found the source, transmission route, and impact time of this pollution. We have verified the correctness and accuracy of the reconstructed contamination transport paths. It is proved that the method is universal and it can quickly and accurately restore the air pollution transmission route and identify the urban imported air pollution transmission entrance. This method will also provide strong data support for the division of responsibilities of environmental protection departments in various regions for severe air pollution transmission events and provide effective governance ideas for the prevention and control of imported air pollution in recipient cities. [ABSTRACT FROM AUTHOR]

As the ownership of vehicles and frequency of utilization increase, vehicle emissions have become an important source of air pollution in Chinese cities. An accurate emission inventory for on-road vehicles is necessary for numerical air quality simulation and the assessment of implementation strategies. This paper presents a bottom-up methodology based on the local emission factors, complemented with the widely used emission factors of Computer Programme to Calculate Emissions from Road Transport (COPERT) model and near real time (NRT) traffic data on road segments to develop a high temporal-spatial resolution vehicle emission inventory (HTSVE) for the urban Beijing area. To simulate real-world vehicle emissions accurately, the road has been divided into segments according to the driving cycle (traffic speed) on this road segment. The results show that the vehicle emissions of NOx, CO, HC and PM were 10.54×104, 42.51×104 and 2.13×104 and 0.41×104 Mg, respectively. The vehicle emissions and fuel consumption estimated by the model were compared with the China Vehicle Emission Control Annual Report and fuel sales thereafter. The grid-based emissions were also compared with the vehicular emission inventory developed by the macro-scale approach. This method indicates that the bottom-up approach better estimates the levels and spatial distribution of vehicle emissions than the macro-scale method, which relies on more information. Additionally, the on-road vehicle emission inventory model and control effect assessment system in Beijing, a vehicle emission inventory model, was established based on this study in a companion paper (He et al., 2015). [ABSTRACT FROM AUTHOR]

Since 2010, the Chinese government has developed several batches of low-carbon pilot provinces and cities continuously. And in the backdrop of carbon peak and carbon neutralisation recently, the carbon emission reduction policies and achievements of China have attracted more and more worldwide attention. In the field of human health, this paper investigates whether the Low-carbon Province Pilot Policy of China has positive effects on residents' health based on the micro data of China Family Panel Studies (CFPS) from 2010 to 2016. Using the time-varying difference-in-difference model to solve the endogeneity problem commonly faced in the literature, we find that Low-carbon Province Pilot Policy has a positive impact on public health through air quality improvement and the unemployment level alleviation mainly. And in urban areas, the policy effect is more obvious than that in rural regions. This paper expands the content of national low-carbon governance effects to residents' health further and contribute to China's low-carbon development. Specifically, it reminds us to focus on the dynamic adjustment and effective continuation of the policy, and also the all-round support for 'the disadvantaged' in environmental governance process. [ABSTRACT FROM AUTHOR]

Affected by the epidemic and other factors, the global economy is in a downturn, and countries around the world are under unprecedented debt pressure. How will this affect environmental protection? Taking China as an example, this paper empirically studies the impact of changes in local government behavior on urban air quality under fiscal pressure. This paper uses the generalized method of moments (GMM) to find that fiscal pressure has significantly reduced PM2.5 emissions, with a unit increase in fiscal pressure will increase PM2.5 by about 2%. The mechanism verification shows that three channels affect PM2.5 emissions: (1) fiscal pressure has prompted local governments to relax the supervision of existing pollution-intensive enterprises. (2) Local governments reduce environmental regulations for attracting more pollution-intensive enterprises. (3) Local governments tend to reduce environmental protection investment to save fiscal expenses. The paper's conclusions provide new policy ideas for promoting environmental protection in China, as well as served as a case for analyzing current changes in environmental protection in other countries. [ABSTRACT FROM AUTHOR]

Collaborative reduction of carbon and air pollutants can more efficiently achieve green technological change, industrial low-carbon transition, and high-quality economic and social development. As a typical environmental policy in China, the pilot carbon Emission Trading Scheme (ETS) has obvious advantages in achieving the collaborative reduction of carbon and air pollutants. Therefore, an evaluation of China's pilot carbon ETS from the perspective of collaborative reduction of carbon and air pollutants is performed in this paper. Compared with previous studies, first, this study innovatively uses the coupled coordination degree (CCD) model to measure the collaborative reduction level of carbon and air pollutants under different scenarios based on the panel data of China's 30 provincial-level regions during 2004–2018. Second, this study uses the DID method to evaluate the impact of China's pilot carbon ETS on the collaborative reduction of carbon and air pollutants and conducts some robustness checks and regional heterogeneity regressions. Third, this study uses the synthetic control method (SCM) further to examine the policy outcomes of the pilot carbon ETS. Scenario analysis shows that attaching importance to reducing air pollution will improve the collaborative reduction effect of carbon and air pollutants. Furthermore, the implementation of China's pilot carbon ETS exerts an effect of roughly 24.7% on reducing carbon, roughly 10.1% on reducing air pollutants, and roughly 22.0% on the collaborative reduction of carbon and air pollutants, ceteris paribus. Regional heterogeneity analysis shows that the impacts of the pilot carbon ETS are significant in all regions, except that the impact on reducing air pollutants in the central region is not significant. In addition, results from SCM indicate that the impacts of the pilot carbon ETS on the collaborative reduction of carbon and air pollutants are significantly efficient in Beijing, Tianjin, Shanghai, Hubei, and Chongqing, while not much efficient in Guangdong and Fujian. The main policy implications include strengthening the top-level design of the ETS in the collaborative reduction of carbon and air pollutants, attaching importance to the governance of air pollution, making the regional governance more targeted, and improving energy efficiency. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has posed a severe challenge to the global economic recovery and China's economic growth. Although China has achieved stage victory against the epidemic, the impact and influence of the epidemic on China's economy will linger. On the positive side, the epidemic has led to a dramatic reduction in air pollution levels and a sharp slowdown in greenhouse gas emissions such as CO2. Forecasting China's CO2 emissions under the impact of the COVID-19 epidemic is crucial for formulating policies that contribute to smooth economic development and rational energy consumption. To this end, this paper improves on the traditional grey model, GM(1, N), by developing a novel fractional multivariate nonlinear grey model, FMNGM(q, N). These improvements include two key points. First, different power exponents are assigned to each relevant factor variable to explain their nonlinear, uncertain, and complicated relationships with the system characteristic variables. Second, the integer accumulation is changed to fractional accumulation to preprocess the data, and the Caputo-type fractional derivative is used to characterize the endogenous relationships among the system characteristic data. In addition, the quantum particle swarm optimization (QPSO) algorithm is used to optimize the above parameters with the goal of minimizing MAPE. The collected data on China's CO2 emission from 2001 to 2018 were divided into two parts according to different stages of economic development: 2001–2009 and 2010–2018. Both sets of data were modelled and analysed separately and compared with other models. Results showed that the proposed model had better prediction accuracy than other models. Finally, the model built using the 2010–2018 data was used to forecast China's CO2 emissions. Results show that China's CO2 emissions in 2020 under the impact of COVID-19 will decrease by approximately 3.15% from 2019 to 9893 million tons. The results bear important policy implications for planners in investment in clean energy and infrastructure to achieving the goal of a low-carbon transition. [ABSTRACT FROM AUTHOR]

Using the environmental tax reform implemented in 2018 in China as a quasi-experiment, this paper employs PSM, DID, and DDD methods to investigate the causal impact of environmental tax on air pollution. Viewing those provinces that choose to set a higher tax rate than the original pollution fee rate as the treatment group and provinces that do not increase the tax rate as the control group, this paper provides robust evidence that the environmental tax reform is effective in reducing PM2.5 and SO2 concentration level, while the effect is smaller and inconsistent for NO2. A back-of-the-envelope welfare analysis suggests that a 1-unit increase in the environmental tax rate is associated with a reduction of 5,616 in total deaths and a welfare gain of $28.256 billion in 2005 USD for all Chinese households. [ABSTRACT FROM AUTHOR]

The Fenwei Plain is listed as one of the most serious air pollution regions in China, along with Beijing-Tianjin-Hebei and Yangtze River Delta regions. This paper proposed a functional data analysis method to study the environmental pollution problem in the Fenwei Plain of China. Functional spatial autoregressive combined (FSAC) model with spatial autocorrelation of both the response variable and error term is developed. The model takes the SO2 concentration of Fenwei Plain as the dependent variable and the dew point temperature as the independent variable and realizes the maximum likelihood estimation using functional principal component analysis to obtain the asymptotic properties of parameter estimation and the confidence interval of the slope function. According to the findings of the empirical analysis of the Fenwei Plain, the SO2 concentration has significant seasonal characteristics and has decreased year over year for three years in a row. Winter is the season with the highest concentration on the Fenwei Plain, followed by spring and autumn, while summer is the season with the lowest concentration. Winter also has a high spatial autocorrelation. The FSAC model is more effective at fitting the concentration and dew point temperature of the Fenwei Plain in China because its mean square error (MSE) is significantly lower than that of the other models. As a result, this paper can more thoroughly study the pollution problem on the Fenwei Plain and offer guidance for prevention and control. [ABSTRACT FROM AUTHOR]

Air pollution and urban innovation are two important issues that have accompanied China's economic growth in the past decade. Based on the quasi-natural experiment of central heating in northern China in winter, this paper uses regression discontinuity design (RDD) to isolate the causal relationship between air pollution and urban innovation in China by matching urban data with multiple micro databases. Further, the possible influencing mechanism is discussed from the perspective of human capital. The results show that—air pollution significantly inhibits urban innovation—specifically, a 1% increase in air pollution significantly reduces urban innovation by 1.463%; compared with non-invention patents, air pollution has a more obvious inhibitory effect on invention patents with higher innovation capacity requirements and technology content. In terms of the impact mechanism, air pollution may undermine urban innovation by impairing healthy human capital and increasing the emigration of high-level human capital from cities. [ABSTRACT FROM AUTHOR]

The low efficiency of environmental policy implementation is an important issue in China's environmental governance. The Environmental Protection Interview (EPI) policy is an administrative means for the central environmental protection department to urge local governments to earnestly fulfill their environmental protection responsibilities. This paper takes China's EPI policy as a quasi-natural experiment. We use panel data of 261 prefecture-level cities in China from 2009 to 2018 as research sample and use spatial difference-in-differences (SDID) model to investigate the effect and mechanism of EPI policy on air pollution. The results show that EPI policy can effectively improve air quality, EPI policy has obvious spatial spillover effects. Namely, the EPI policy can not only reduce the local air pollution, but also reduce the air pollution in neighbouring cities. The EPI policy reduces the air pollution in the neighbouring cities within a spatial attenuation boundary of 400 km.The results of mechanism test show that the EPI policy can improve air quality by promoting industrial structure upgrading and technical advancement. Moreover, the pollution reduction effect of EPI is more significant in resource-based cities. The research results of this paper provide important reference for China and other developing countries to improve air quality. [ABSTRACT FROM AUTHOR]

This paper studies the relationship between the coal-to-gas program and air pollution in China and provides micro-evidence of the mechanism from the perspective of households. Using daily air pollution and meteorological data between January 1, 2016, and January 1, 2020, we assessed the effect of the coal-to-gas program on air pollution by introducing the regression discontinuity designs in time (RDiT). We found that the coal-to-gas program significantly improved air quality and brought significant economic benefits. In the short term, the coal-to-gas program can lead to more than 10 units of reduction in SO2, PM2.5, and AQI in the treatment group, while it can lead to more than 50 units in the long term. Using the difference-in-differences approach, we found that the coal-to-gas program has significantly reduced air pollution. Combined with the micro-panel data of the China Health and Retirement Longitudinal Study from 2011 to 2018, we found that the coal-to-gas program changes the household heating energy choices and that the probability of coal-fired heating of households in pilot areas is decreasing. The study suggests that non-clean energy in households should be further replaced to continue improving air quality. [ABSTRACT FROM AUTHOR]

To cope with the coronavirus disease (COVID-19), national or sub-national regions have carried out many powerful anti-pandemic measures such as locking down, which may improve their regional air quality. This paper examines the relation between regional air pollution and work resumption from a novel post-pandemic perspective. Using a unique panel dataset on China's detailed industrial electricity consumption, this paper does not find a positive relation between post-COVID-19 work resumption and regional air pollution during China's early-stage recovery. This result is obtained after controlling for province and date fixed effects, as well as local weather conditions. However, the positive relations are found in a particular sub-sample of large industrial enterprises and a particular sub-sample of April. These findings indicate that large industrial enterprises may recover first, and the resumption is progressing gradually. Finally, several policy implications are provided, which are essentially helpful for other countries' post-pandemic recovery. [ABSTRACT FROM AUTHOR]

In recent years, digital finance has become a crucial part of the financial system and reshaped the mode of green finance in China. Digital finance has brought certain impact on economic growth, industrial structure, and resident income, which may affect pollution. The nexus of digital finance and environment in China is thus worth exploring. By revising the traditional Environmental Kuznets Curve model with income inequality variable, this paper decomposes the environmental effects of economic activities into income growth effect, industrial structure effect and income inequality effect, and use panel data of China's provinces to conduct an empirical analysis. The results reveal the following: (1) the Environmental Kuznets Curve is still valid in sample, and digital finance can reduce air and water pollution (as measured through SO2 and COD emission) directly; (2) in the influence mechanism, digital finance can alleviate income inequality and promote green industrial structure, thus reducing pollution indirectly, but the scale effect of income growth outweighs the technological effect, which increases pollution indirectly; and (3) digital finance has a threshold effect on improving the environment, then an acceleration effect appears after a certain threshold value. From the regional perspective, digital finance development in eastern regions is generally ahead of central and western regions, and the effects of environmental improvement in the eastern regions are greater. According to the study, this paper suggest that digital finance can be an effective way to promote social sustainability by alleviating income inequality and environmental sustainability by reducing pollution. [ABSTRACT FROM AUTHOR]

Amidst the global upsurge in industrial robot deployment, there remains a notable gap in our understanding of their environmental impact. This paper explores how the introduction of industrial robots has changed air quality at both the local and neighborhood levels in China. Using the Spatial Durbin Model, we investigate the regional spillovers of PM 2.5 concentration and the diffusion of this innovative technology. Our findings reveal that the rise of robots significantly reduces air pollution in the local area, while exacerbating it in neighboring regions. This contrast is mainly because pollution-intensive industries are more inclined to relocate to neighboring regions than their cleaner counterparts, after the local use of robots increases. Throughout the process, internal costs rather than external costs dominate firms' relocation decisions. This study provides novel insights into the complex environmental externalities associated with the spread of industrial robots and highlights the critical issue of growing environmental inequality in the era of emerging technologies. [ABSTRACT FROM AUTHOR]

In recent years, atmospheric composite pollution has become increasingly serious, and accelerating VOC governance has become the focus of and difficulty in atmospheric governance. Volatile organic compounds (VOCs) come from a wide range of sources, and industrial sources are the main source of anthropogenic VOC emissions in China. Chemicals, oil refining, and solvents are three typical VOC-emitting industries, and their control is an important part of accelerating and optimizing VOC governance. It can be controlled by source control, process control, and pipe end treatment; among these, pipe end treatment is divided into recovery technology and destruction technology. In pipeline end treatment, with the key materials of adsorption, absorption, catalytic oxidation, and catalytic combustion, the research and development of adsorbents, absorbents and catalysts has become a hot spot in recent years. This paper summarizes the chemical materials used in typical VOC pipe end-treatment technology (including adsorbents used in the adsorption method, absorbents used in the adsorption method, and catalysts used in the catalytic oxidation and catalytic combustion methods), summarizes the advantages and disadvantages of various materials and their application range, and looks forward to the direction of future developments. [ABSTRACT FROM AUTHOR]

Public investments in subway systems are often motivated by improving local air quality. Recent studies, however, have reached different conclusions on the air quality benefits of subway investment. To reconcile these findings, this paper examines the air quality effects of all 359 subway line openings in China between 2013 and 2018. The machine learning method adopted in this paper substantially improves the consistency and precision of the estimates by purging seasonality, volatility, and the nonlinear effects of meteorological conditions in air quality data. The empirical results suggest an insignificant short-term effect and a significant long-term effect, which is expected as the adjustment of commuting mode takes time. Using the causal forest approach, the heterogeneity analysis find that a city that is experiencing rapid economic growth from a lower income level and currently has fewer subway lines is more likely to experience statistically significant improvements in air quality from a subway opening. These findings help reconcile the different findings in the literature and shed light on air pollution reduction as one of the objectives of public transit investment. [ABSTRACT FROM AUTHOR]

Does air pollution influence traffic safety? To answer this question, this paper empirically investigates the nonlinear impact of air pollution on traffic mortality by employing a balanced panel dataset for 102 Chinese cities covering 2014–2018. Also, this paper then discusses the nonlinear mediation effects of air pollution on traffic safety to test the influential mechanism between these two variables. The following three conclusions are obtained. First, air pollution has a nonlinear impact on traffic safety: a 1 μg/m3 increase in the average annual concentration of PM2.5 could lead to a 0.0439 increase in traffic fatalities per one million people, but the negative impact of PM2.5 on air pollution will be reduced in the long run. Second, heterogeneity analysis indicates that the impact of air pollution on traffic safety in northern cities of China, cities with lower levels of economic development is more serious than that in other cities. Third, air pollution may affect traffic safety by reducing transport efficiency and affecting drivers' physiological status and cognitive abilities. [ABSTRACT FROM AUTHOR]

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The influence of machine learning technologies is rapidly increasing and penetrating almost in every field, and air pollution prediction is not being excluded from those fields. This paper covers the revision of the studies related to air pollution prediction using machine learning algorithms based on sensor data in the context of smart cities. Using the most popular databases and executing the corresponding filtration, the most relevant papers were selected. After thorough reviewing those papers, the main features were extracted, which served as a base to link and compare them to each other. As a result, we can conclude that: (1) instead of using simple machine learning techniques, currently, the authors apply advanced and sophisticated techniques, (2) China was the leading country in terms of a case study, (3) Particulate matter with diameter equal to 2.5 micrometers was the main prediction target, (4) in 41% of the publications the authors carried out the prediction for the next day, (5) 66% of the studies used data had an hourly rate, (6) 49% of the papers used open data and since 2016 it had a tendency to increase, and (7) for efficient air quality prediction it is important to consider the external factors such as weather conditions, spatial characteristics, and temporal features. [ABSTRACT FROM AUTHOR]

With the data of Chinese A-share-listed companies from 2004 to 2017, this paper builds a difference-in-differences model to investigate the impact of air pollution collaborative governance on green technology innovation. The main results show that air pollution collaborative governance promotes green technology innovation, and a series of robustness tests also verify this conclusion. Patent heterogeneity analysis suggests that air pollution collaborative governance increases the number of green utility model patents, but has no obvious impact on green invention patents. In terms of enterprise heterogeneity, air pollution collaborative governance can effectively stimulate the non-heavy-polluting enterprises to innovate green technology, but the incentive effect on heavy-polluting enterprises is not evident. Moreover, by constructing a mediating effect model and a moderating effect model, mechanism analysis reveals that R&D investment plays a positive mediating role in the impact of air pollution collaborative governance on green technology innovation, and the increase of government subsidy also enhances the promotion effect of air pollution collaborative governance on green technology innovation. [ABSTRACT FROM AUTHOR]

Atmospheric resources provide important support for human economic and social systems through their unique ecosystem service functions. Implementing the off-office auditing of atmospheric resources for leading cadres holds great strategic significance for fundamentally solve air pollution problems. Exploring the compilation of an atmospheric resource balance sheet is a necessary pre-step in the implementation of outgoing audits. In this paper, atmospheric resources are innovatively divided into atmospheric capacity resources and atmospheric quality resources from the perspective of the ecosystem service functions of atmospheric resources. The value of atmospheric resource assets is calculated by combining the environmental capacity value method and the environmental loss evaluation method. This study evaluates atmospheric ecological achievements based on the atmospheric resources balance sheet and related accounts as the data carrier and opens up the key "blocking point" of the off-office auditing of atmospheric resources. This paper takes Anhui Province as an example and applies the accounting results of the prepared atmospheric resource balance sheet to evaluate the atmospheric resource ecological achievements of leading cadres from 2016 to 2020. The results clearly reflect the ecological achievements and shortcomings of local leading cadres during their tenure. [ABSTRACT FROM AUTHOR]

Protecting people from air pollution is an important task for developing countries. Over the past several decades, different types of policies have been enacted in developing countries to improve air quality, with policy impact analysis being conducted as well. As for China, while there is some existing literature on the impact of short-term action on air quality, there is much less research to investigate the roles of long-term air quality control mechanism on air quality change. This paper uses the "2 + 26" city cluster in China as a case study area to particularly analyze the roles played by short-term campaigns that compose the Winter Action Plan and a long-term mechanism referred to as the environmental accountability system in pollution control. Based on econometric and descriptive statistical analyses, it is found that the implementation of the Winter Action Plan has significantly improved the air quality, and the environmental accountability system seems to have exerted an impact, as cities with better air quality appear to establish a more stringent environmental accountability system. The paper provides the following insights for other developing countries: short-term campaigns can quickly reduce pollution and protect human health, while long-term mechanisms are needed to ensure sustainable environmental protection. [ABSTRACT FROM AUTHOR]

Rapid economic growth leads to such problems as resource scarcity and environmental degradation. Local governments successively take measures such as technological innovation to solve atmospheric environmental pollution; however, technological innovation fails to fundamentally alleviate atmospheric environmental pollution. Therefore, local governments come to realize the importance of green-technology innovation, which means an inevitable choice for various countries in the world to seek long-term development and win competitive advantage. Under such circumstances, this paper chooses the panel data of 30 provinces and regions in China from 2005 to 2018, takes environmental regulation as the threshold variable, and empirically analyzes the relationship between green-technology innovation and atmospheric environmental pollution by constructing a Spatial Measurement Model and Panel Regression Model. As evinced, green-technology innovation has a significant inhibitory effect and a spatial spillover effect on atmospheric environmental pollution. When environmental regulation reaches a level of intensity, green-technology innovation can effectively curb atmospheric environmental pollution. Accordingly, relevant parties should strengthen green-technology innovation, coordinate the development of the governance system of green-technology innovation, establish a joint prevention and control mechanism, increase the investment in green technology research and development, and augment the role of green-technology innovation. [ABSTRACT FROM AUTHOR]

With rapid urbanization, the economic agglomeration within cities is associated with severe air pollution. Urban spatial structure adjustment has been recognized as an effective strategy for improving air quality. However, the research on how to mitigate air pollution originating from economic agglomeration through urban spatial structure adjustment is unclear. Therefore, based on panel data for municipal cities in the Yangtze River Delta (YRD) region during 2008–2018, this study empirically tests the transmission mechanisms among economic agglomeration, urban spatial structure, and air pollution. We use the combination of the social network analysis (SNA) and two-stage least squares (2SLS) methods to verify the effect of economic agglomeration on air pollution. Economic agglomeration's indirect effect on air pollution through urban spatial structure is further tested using mediating effect model and cross-section comparisons. When exploiting an exogenous order rank of node city importance for instrument variable (IV), our finding shows that increasing economic agglomeration by 10% increases air pollution by 12%. In addition, in market forces, monocentricity brings about economic agglomeration's pollution effect, while polycentricity leads to agglomeration's environmental benefits improvement. However, a government-led exogenous polycentricity greatly mitigates economic agglomeration's pollution effect, while in cities with monocentricity, agglomeration slightly increases air pollution. Compared with market power, our paper stresses government intervention in promoting urban spatial structure in terms of polycentric development could be more helpful for improving agglomeration's environmental benefits in China's YRD region. [ABSTRACT FROM AUTHOR]

This paper investigates the impacts of air pollution on immigrants' willingness to settle in China. We construct a theoretical model that discusses how air pollution impacts immigrants' willingness to return home and move to other cities and illustrates how air pollution decreases the settlement intention of immigrants. The empirical results show that urban air pollution decreases immigrants' settlement intention. Robustness checks using multi-methods and multi-measures of settlement intention and air pollution support this conclusion. Air pollution has heterogeneous impacts on immigrants' settlement intentions. From the individual level, air pollution decreases the settlement intention for immigrants with 30–60 years old, middle-income migrants, and rural migrants. From the city level, air pollution decreases the settlement intention of immigrants in the eastern region, developed cities, and cities with high and low air pollution. [ABSTRACT FROM AUTHOR]

Vehicular emissions are one of the most important sources of pollution in China, and they can increase the ambient concentrations of air pollutants and degrade the air quality. Using data released by the National Bureau of Statistics, vehicular emissions in China in 2006 and 2010 were calculated at a high spatial resolution, by taking the emission standards into consideration. The results show that China's vehicular emissions of CO, NOx, VOCs, NH3, PM2.5, PM10, black carbon (BC), and organic carbon (OC) were 30113.9, 4593.7, 6838.0, 20.9, 400.2, 430.5, 285.6, and 105.1 Gg, respectively, in 2006 and 34175.2, 5167.5, 7029.4, 74.0, 386.4, 417.1, 270.9, and 106.2 Gg, respectively, in 2010. CO, VOCs, and NH3 emissions were mainly from motorcycles and light-duty gasoline vehicles, whereas NOx, PM2.5, PM10, and BC emissions were mainly from rural vehicles and heavy-duty diesel trucks. OC emissions were mainly from motorcycles and heavy-duty diesel trucks. Euro 0 and Euro I vehicles were the primary contributors to all of the pollutant emissions except NH3, which was mainly from Euro III and Euro IV vehicles. The spatial distribution of vehicular emissions in China in 2006 and 2010 were developed at a high resolution of 0.25° × 0.25°, by using the road traffic density to characterize the busyness of a road. This method could overcome the problem of getting traffic flow information and make the spatial allocation more closed to the actual road emissions. The results showed that vehicular emissions presented significant regional spatial distribution, and emissions in the eastern and southern parts of China were much higher than those in western and northern China in both years. The North China Plain, Yangtze River Delta, and Pearl River Delta regions jointly accounted for nearly half of the emissions. NH3 emissions increased greatly in big cities from 2006 to 2010. Emissions of CO, NOx, and VOCs could increase 52%, 9%, and 68%, if the emission standard and oil quality remained in the Euro I stage, so the policies on vehicular emissions implemented in China were demonstrated to be effective. Nevertheless, greater efforts are needed to improve the oil quality so that the new emission standard can implement timely and catch the international level quickly, especially the sulfur level because NOx emission is very sensitive to it. By comparing with coal consumption and NO2 column density observed by SCIA satellite, the increase of NOx emission in China from 2006 to 2010 was mainly caused by coal consumption. [ABSTRACT FROM AUTHOR]

Research on the current strategic interaction of local governments in air pollution control is a key breakthrough. Based on the theory of Chinese style decentralization, this paper puts forward a theoretical framework to explain the incomplete enforcement of air pollution regulation. Using the panel data of 30 provinces in China from 2004 to 2016, this study employs spatial Durbin model, empirically tested the inter-regional strategic interaction of air pollution regulation, and further explores the effect of performance assessment indicators on this strategic interaction. The main conclusions of this paper are as follows: (1) Empirical results confirm that adjacent provinces do exist strategic interaction of air pollution regulation. Furthermore, the strategic interaction of air pollution regulation belongs to complementarities. (2) Meanwhile, from a regional perspective, due to the low level of economic development stock and the low level of air pollution, the interaction effect of air pollution regulation strategies in northwestern region is weaker than that in southeastern region. (3) In addition, under the national sample and the southeast sample, the air environment performance assessment indicators weaken the inter-regional strategic interaction of air pollution regulation, and economic performance assessment indicators on the contrary. [ABSTRACT FROM AUTHOR]

As the Environmental Protection Law was revised and media public opinion supervise them, enterprises need to not only undertake more environmental protection responsibilities but also alleviate the contradiction between development and environment. By applying a multiple regression model, this paper studies the impact of air pollution on the management behavior of enterprises using the panel data of China's A-share polluting enterprises listed in the Shanghai and Shenzhen stock markets between 2014 and 2019. The results of this study are as follows: First, air pollution produces a positive impact on the behavior of corporate green management. Second, media reports have brought more attention to corporate pollution and increased the positive impact of air pollution on corporate green management efforts. By further considering the internal and external heterogeneity of enterprises, the impact of air pollution on corporate green management varies when the degree of enterprise pollution and the degree of local governance differ. Moreover, this paper highlights the fact that air pollution can play a significant role in corporate green management, while media attention, as a third party, plays a regulating role in environmental supervision. This provides suggestions for strengthening green management behavior of enterprises and building comprehensive environmental supervision system. [ABSTRACT FROM AUTHOR]

Foreign direct investment and environmental pollution have been a prominent topic in China's economic development. Therefore, this paper investigates the relationship between foreign direct investment and environmental pollution, and makes practical policy recommendations to support the harmonious development of economy and environment based on the study findings. In this paper, the spatial econometric approach framework with the spatial weight matrix of the Delaunay method is used to examine the influence of foreign direct investment on the level of urban air quality. It uses air quality index as an indicator to measure air pollution comprehensively. Based on the spatial autocorrelation with the aggregation and radiation effects of foreign direct investment, the results show that the distribution of air pollution has considerable spatial impact in terms of spatial nonequilibrium. Through the empirical analysis, our finding reveals that the increase in GDP, the share of secondary industry, and population growth are the important elements affecting the change in air quality. [ABSTRACT FROM AUTHOR]

This paper examines the effects of interventions to reduce air pollution during two international events on air quality in Beijing and its neighbor cities. Air quality data were gathered from China's Ministry of Environmental Protection, meteorological data from the China Meteorological Administration and economic data from the China Statistical Yearbook. The paper uses fixed-effect panel data models to empirically evaluate air quality improvement in Beijing and other affected cities before, during, and after the 2008 Olympic Games and the 2014 Asia-Pacific Economic Cooperation summit. Results show substantial improvement in air quality in Beijing and neighboring cities during the two events. However, some of the air quality improvement achieved reverted within a year after the games and within a week after the summit. Furthermore, the improvement achieved during the summit completely reverted and air quality deteriorated severely five days after the summit. It is also found that air quality in China, at least in the cities included in this study, gradually improved over the past 15 years or so. The findings suggest that sustainable interventions and incentive-based programs to reduce emissions from industry production and traffic are the key to maintaining the air pollution reduction achieved during the events. [ABSTRACT FROM AUTHOR]

Background: Air pollution is an important factor affecting residents' health. Methods: Based on the health data of 9959 residents from 28 provinces in China in the 2017 Chinese General Social Survey (CGSS), this paper uses a hierarchical linear model (HLM) to scientifically analyze the impact of air pollution on residents' health and to explore the moderating role of air pollution in various factors influencing residents' health. Results: Air pollution has significant negative effects on residents' health (coef. −0.103, p < 0.01), while frequency of exercise (coef. 0.070, p < 0.01), education level (coef. 0.012, p < 0.1) and income level (coef. 0.383, p < 0.01) have positive effects on residents' health. Air pollution has a negative moderating effect on the positive impact of exercise frequency on residents' health (coef. −0.015, p = 0.004). Conclusions: Air pollution causes serious damage to residents' health and it is necessary to control air pollution. Increasing residents' income, education level and exercise frequency can help improve residents' health level. Air pollution significantly reduce the positive impact of exercise frequency on residents' health. In order to effectively improve their own health, it is a better choice for residents to exercise when the air quality is good. [ABSTRACT FROM AUTHOR]

In China, blue sky defense is a crucial part of ecological environment governance. Objective environmental governance performance needs to be perceived by the public to more truly affect the public's evaluation of the government's environmental governance. This paper focuses on the public's subjective perception of air pollution and evaluation of the local government's environmental governance. Based on the Chinese General Social Survey data, the matched economic indicators, and air pollution data, we conduct a diachronic study on the public's evaluation of local governments' environmental protection work, and we analyze the relationship between the subjective perception of air pollution, the objective air pollution data, and the evaluation of local governments' environmental protection work. The results showed the following: (1) People's evaluation of local governments' environmental protection work significantly improved from 2013 to 2021. The objective indicator improved, while the subjective perception declined. (2) The subjective perception of air pollution has a significant negative impact on the evaluation of local governments' environmental protection work and needs to be better considered to improve air quality. At the same time, the effect of the objective indicator is insignificant. [ABSTRACT FROM AUTHOR]

This paper proposes a simple model to theoretically analyze the impacts of emissions of waste gases on industrial profit and mainly finds that industrial producers yield products to pursue profit but emit waste gases, protecting atmospheric environment demands for decline in waste gases, emissions impact profit when the process of production is altered as result of public regulations, and actively treating emissions ease the distortions of production and maintain profit. As a comparison, industrial profit is not impacted by emissions when producers are allowed to emit freely. After theoretical analysis, this study also empirically tests the relationship between the emissions of waste gases and profit as evidenced in China and finds that emissions do not significantly impact profit, except for sulfur dioxide with significantly negative impact; industrial producers with increased capacity for treating waste gases obtained more profits. As a result, the cost expended on treating pollution was compensated in the Chinese industrial sector. Successfully declining waste gases for atmospheric environmental protection and maintaining industrial profit for economic output and social development in the Chinese local economy has global implications because many other countries and regions primarily pursue green and sustainable development. [ABSTRACT FROM AUTHOR]

Air-quality monitoring and forecasting are crucial for atmosphere pollution control and management. We propose an innovative data-driven framework for air quality index (AQI) prediction by integrating GNSS radio occultation (GNSS-RO) observation and weather modeling. Empowered by the state-of-the-art machine learning approach, our method can effectively predict regional AQI with a comparable accuracy much more quickly than the traditional numerical modeling and simulation approach. In a real case study using a representative region of China, our data-driven approach achieves a 2000 times speedup; meanwhile, the prediction error measured by rRMSE is only 2.4%. We investigate further the effects of different models, hyperparameters, and meteorological factors on the performance of our AQI prediction framework, and reveal that wind field and atmospheric boundary-layer height are important influencing factors of AQI. This paper showcases a direct application of GNSS-RO observation in assisting in forecasting regional AQI. From a machine learning point of view, it provides a new way to leverage the unique merits of GNSS atmospheric remote sensing technology with the help of the more traditional weather forecasting modeling approach. [ABSTRACT FROM AUTHOR]

Coal combustion is the primary source of air pollution in China, especially the heavy metals (HMs) concentrated in the submicron particles. This paper discusses the enhancement of HMs absorption efficiencies during coal combustion experiments. By adding the modified Ca-based sorbents, the orthogonal design was used in this experiment. Combining with the analysis of variance and capturing rate of HMs, the optimal combination was arrived at. BP neural network model was established and trained using orthogonal capturing tests data to reach the best compositions. Confirmatory trial was conducted, thus the BP neural network model can be used to solve complex nonlinear optimization problems. [ABSTRACT FROM AUTHOR]

This paper provides evidence of regulatory capture in China's environmental regulation by exploring the relationship between subnational leaders' tenure and local firms' environmental protection behaviors. We find that firms discharge more exhaust and make less effort to abate air pollution when mayors' tenure increases. The results are robust to alternative specifications and measures, but show heterogeneity across regions and ownerships. The intensity of regulatory capture depends on institutional factors and firm characteristics. This study enriches the literature by analyzing regulatory capture under a regionally decentralized authoritarian system and provides clear policy implications for preventing regulatory capture. [ABSTRACT FROM AUTHOR]

This paper examines the relationship between air pollution levels and regulators' enforcement levels and observes that air pollution levels in firms' locations reduce enforcement from regulators. Moreover, regulators are more likely to suffer from type II errors when air pollution levels in firms' locations are higher, verifying the effect of regulators' unwillingness to travel due to air pollution. The cross-sectional analysis suggests that enforcement from regulatory authorities in areas with lower air pollution levels than in firms' locations, positioned at great distances from firms' locations, and with greater workloads is less strict when air pollution levels in firms' locations are higher. We further test whether air pollution levels reduce the efficiency of regulators and find that firms with lower earnings quality and weaker corporate governance are less likely to be subjected to enforcement by regulators when air pollution levels in the firms' locations are higher. [ABSTRACT FROM AUTHOR]

As a bridge between economy and ecology, green finance is vital in improving environmental quality and promoting sustainable development. Based on the building of an environmental pollution index system, this paper constructs the STIRPAT - EKC model to deeply explore the specific impact of green finance on environmental pollution using China's provincial panel data from 2007 to 2020. This paper constructs an intermediary model to test the impact mechanism of green finance on reducing environmental pollution and discusses the regional heterogeneity of green finance in reducing environmental pollution. The results show that (1) green finance can significantly reduce environmental pollution, among which green credit has a pronounced effect on reducing environmental pollution, green investment has a relatively small effect, and green securities have not significant effect. (2) Green finance has the best inhibitory effect on solid pollution, less inhibitory effect on air pollution, and no significant improvement effect on water pollution. (3) Green technology innovation, industrial structure upgrading, and environmental regulation play an intermediary role in the process of green finance reducing environmental pollution and improving environmental quality. (4) The effect of green finance in the eastern and carbon emission pilot areas is significantly better than in the central and western regions and non-carbon emission pilot areas respectively. According to the research results of this paper, suggestions are put forward to promote the development of green finance, which is of great significance to reducing environmental pollution and achieving sustainable development goals. [ABSTRACT FROM AUTHOR]

This paper aims to detail the relationships between urbanization, industrialization, the innovation ability of cities and local air quality in 284 cities in China using annual data. For the empirical outputs, the panel quantile regression analysis, which considers the heterogeneous nature of the data set, is employed. Initial findings indicate that (i) urbanization and industrialization negatively affect local air quality. (ii) Innovation capability of cities has a direct and improving impact on local air quality. Then, the paper estimates the moderating role of cities' ability to innovate in the polluting effect of urbanization and industrialization on local air quality. Remarkably, empirical evidence indicates that (iii) the innovation ability of cities also moderates the polluting impact of urbanization and industrialization on local air pollution. Based on the findings, the paper confirms the importance of both direct and moderator effects of the innovative environment in cities in tackling air pollution. [ABSTRACT FROM AUTHOR]

As air pollution becomes more and more serious, PM2.5 is the primary pollutant, inevitably attracts wide public attention. Therefore, a novel PM2.5 concentration forecasting method based on linear fuzzy information granule_dynamic time warping_hierarchical clustering algorithm (LFIG_DTW_HC algorithm) and generalized additive model is proposed in this paper. First, take 30 provincial capitals in China for example, the cities are divided into seven regions by LFIG_DTW_HC algorithm, and descriptive statistics of PM2.5 concentration in each region are carried out. Secondly, it is found that the influencing factors of PM2.5 concentration are different in different regions. The input variables of the PM2.5 concentration forecasting model in each region are determined by combining the variable correlation with the generalized additive model, and the main influencing factors of PM2.5 concentration in each region are analyzed. Finally, the empirical analysis is conducted based on the input variables selected above, the generalized additive model is established to forecast PM2.5 concentration in each region, the comparison of the evaluation indexes of the training set and the test set proves that the novel PM2.5 concentration forecasting method achieves better prediction effect. Then, the generalized additive model is established by selecting cities from each region, and compared with the auto-regressive integrated moving average (ARIMA) model. The results show that the novel PM2.5 concentration forecasting method can achieve better prediction effect on the premise of ensuring high accuracy. [ABSTRACT FROM AUTHOR]

The topic of air pollution and its effect on public health has become a hot policy issue that has attracted worldwide attention, but this attention has seldom been extended to the causal relationship between atmospheric environmental policy (AEP), air pollution, and public health. This paper uses panel data from 30 provinces in China to construct spatial econometric models that analyze the impact of AEP on air pollution, the impact of air pollution on public health, and the mediation effect that air pollution may have between AEP and public health. The results demonstrate that there is a significant positive spatial spillover effect of soot and dust (SD) emission intensity and the overall air pollution level as measured by the Air Pollution Index (API). The AEP has significant inhibitory effects on the intensity of sulfur dioxide and SD emissions, as well as on overall air pollution. An increase in the overall air pollution level has a significant detrimental effect on public health as measured by average life expectancy. Air pollution as measured by API is a mediating factor in the relationship between AEP and public health. The study results could help to effectively control air pollution and promote public health by leading to improvements in regional pollution prevention and control mechanisms and strengthening of the central government's policy formulation and local governments' policy implementation process. [ABSTRACT FROM AUTHOR]

The urbanization process in China has been involved with the internal migration of ethnic minorities for a better habitant environment. The paper identifies the effect of air pollutant PM2.5 (inhalable fine particles less than 2.5 µm diameter) on the migration of ethnic minorities by using individual censuses in China. We use IVprobit model to analyse whether PM2.5 concentration affects the migration decision of ethnic minorities and the extent of this effect. Using average wind speed as instrumental variable to handle the endogeneity problem, we find that the environmental costs of industrialization drive ethnic minorities out of their birthplace and the minority autonomous regions. The estimation results are consistent for both the Han majority and the ethnic minorities in minority autonomous regions. The interaction effects indicate that an ethnic individual's migration decision responding to PM2.5 pollution vary by household registration type, housing sources, income level, the number of children in the family. Ethnic minority groups are more concerned about the environmental quality of their residence places compared with the economic benefits and some preferential policies when considering out-migration. The conclusion of this paper also contributes to the integration and inclusiveness of East Asian economic regions. [ABSTRACT FROM AUTHOR]

Air pollution is an important factor affecting human health and daily life. The Chinese government is making vigorous efforts to control air pollution. The upgrading of the industrial structure is a problem-solving tool in the environment and economic growth cases. This paper aims to explore the relationships among environmental regulation, the upgrading of the industrial structure and air pollution. The PVAR (Panel Vector Auto Regression) model and moderating effect model are used to conduct empirical analysis based on panel data of 30 provinces in China from 2004 to 2020. The analysis of the results provides the following findings. Firstly, environmental regulations can significantly reduce emissions, but the deterioration of air quality does not have a significant impact on the improvement of environmental regulations. Secondly, industrial structure upgrading can reduce air pollution, but the worsening of the air quality will hinder the upgrading of industrial structures. Thirdly, environmental regulation can promote industrial structure upgrading. Lastly, industrial structure upgrading is a moderating variable and can positively moderate the impact of environmental regulations on air pollution. [ABSTRACT FROM AUTHOR]

Large-scale air pollution has an impact on the health and travel of residents in China. First, this article uses the gravity model and finds that China's air quality presents a typical spatial correlation network. The network structure has changed from complex to simple, indicating that China's air quality is gradually improving. Second, this paper uses spatial simultaneous equations to study the effect of air quality on residents' health. The results show that an increase in the air quality index of local and surrounding provinces will have a significant impact on the health of residents. The absolute and relative air quality affects the lives of residents. The decline in the health of residents from the previous period will prompt the government to adopt various pollution reduction policies, which will improve air quality in the current period. Based on the empirical research conclusions, this article makes policy recommendations. [ABSTRACT FROM AUTHOR]

In recent decades, more and more studies have been conducted on source appointment of heavy metals, since they can accumulate in the food chain and have a negative impact on the ecological environment and human health. However, almost never before had scholars tried to make a comprehensive and methodical review in this field from the scientometric and bibliometric perspective. The purpose of this review is to offer insights into the research topics and trend evaluation in terms of source appointment of heavy metals over time using the visualization and analysis software, CiteSpace. We retrieved a total of 2,533 articles from the Web of Science Core Collection (WoSCC) dated between 1994 and 2022, and analysed the progress, hotspots, and trends in this field by synthesized networks of cooperation analysis, co-citation analysis, keyword co-occurrence and cluster analysis, and keywords burst analysis. The overall development of the topic can be divided into four periods, and the rapid development began from 2010. Environmental Sciences was the leading subject category, and the journal Science of the Total Environment had the highest number of publications (9.51%), which was most cited as well (2,390 times). China published the most articles in this field, in which Chinese Academy of Sciences was the leading institution. Said Muhammad and Xinwei Luwere the top two most productive authors. According to citation frequency, Hakanson L was the movers and shakers. Keyword co-occurrence and cluster analysis results showed that "the health risk assessment," "lake sediments", "trace elements," "positive matrix factorization," "air pollution," "road dust," and "megacity" are likely to be hotspots. The "particulate matter," "China," "sediments" and "road dust" demonstrated the research tendencies of this domain by keyword burst analysis. [ABSTRACT FROM AUTHOR]