Industrial Sulfur Dioxide Emissions Research Articles

Assessing the ecological security of tourism in Northeast China

Abstract The ecological security of tourism provides an important guarantee of the sustainable development of regional tourism. In this study, the authors use the Driving Force-Pressure-State-Impact-Response model to construct a system to assess the ecological security of tourism in three provinces of Northeast China. We analyze the characteristics of the dynamic spatiotemporal evolution of the ecological security of tourism in 34 prefecture-level cities, one prefecture, and one region in three provinces of Northeast China from 2010 to 2019 and identify obstacles to this evolution. The results show the following: (1) The ecological security of tourism in Northeast China fluctuated and grew during the study period. Significant changes were observed in the rankings of the provinces in the ecological security of tourism. The pattern of spatial distribution has gradually shifted, from “high in the west and low in the middle” in 2010 to “slightly high in the middle-east and slightly low in the west” in 2019. (2) The ecological security of tourism exhibited prominent characteristics of spatial agglomeration on the whole, where the degree of agglomeration has gradually decreased over time. Economically developed cities in Central China exhibited strong local autocorrelation, and the majority had the characteristics of spatial agglomeration and dependence. (3) There were significant differences in obstacles to the ecological security of tourism among the cities (prefectures and regions) and provinces. Industrial sulfur dioxide emissions and urban population density are the main obstacles to the ecological security of tourism, while the pressure system has emerged as the main hindrance to improvements in it in the three provinces considered here. These results provide insights into the ecological security of tourism in the three provinces of Northeast China, as well as a theoretical reference for formulating and implementing the relevant measures of risk prevention and control. This study shows that increasing the protection of the tourism ecological environment and the construction of new energy sources, building complete tourism infrastructure, coordinating the relationship between tourists and the natural environment, adopting differentiated tourism development measures, and overcoming the obstacles will help to gradually improve the level of tourism ecological security in three provinces of Northeast China.

The impact of industrial sulfur dioxide emissions regulation on agricultural production in China

When environmental regulations do not explicitly target agriculture, it becomes difficult to predict if and how this sector will react. In this study, we delve into this issue by scrutinizing China's flagship program designed to control industrial sulfur dioxide emissions. We employ the difference-in-differences method to analyze extensive agricultural data, quantifying the policy's impact on agriculture from both the intensive and extensive margins. Our results indicate that the policy led to an approximately 9% increase in agricultural value added. This growth mainly stemmed from shifts in land allocation and subsequent changes in fertilizer use, rather than from crop yield improvements. Variations in composite grain yields occurred due to shifts in the crop mix, not from yield improvements in specific crops. Overall, our study found that the policy boosted rural per capita net income by 11.6%.

Study on the impact of central environmental protection inspection on the health of the older adult population-A quasi-natural experiment in China.

In 2015, the central government of China established the Central Environmental Protection Inspection (CEPI) system for oversight of local governments. It enhanced local government enforcement of environmental regulations, which had a considerable influence on the health of the local older adult population. This study quantifies the effects of local government regulation brought about by CEPI on the health of the older adult. It examines the impact mechanism using the DID model and panel data from the China Health and Retirement Longitudinal Study (CHARLS). The results show that (1) local governments' environmental protection regulations implemented by CEPI have a positive impact on the general health of the older adult. The results of the study passed the parallel trend test, PSM test, replacement variable test, and placebo test and remained significant; (2) in terms of the impact mechanism, CEPI has promoted local governments' environmental governance initiatives, which has reduced industrial wastewater emissions, industrial sulfur dioxide emissions, and industrial fumes emissions. This has improved air quality, thereby creating a good living environment for the older adult and improving their overall health; (3) according to heterogeneity research, the health of older adult living in the Yangtze River Basin, urban older adult, and older adult without chronic diseases is more significantly affected by the environmental protection regulations of the local governments brought about by CEPI.

The Effect of Low Carbon on Urban Economy: Romer Model and Empirical Evidence

We investigate the relationship between carbon emissions and the economy, focusing on the environmental and economic conditions of cities in China. The research is conducted within the framework of low-carbon city pilot policies, aiming to determine whether city economies in China are growing, declining, or exhibiting a “U-shape” pattern under low-carbon circumstances. A sample of 29 cities, including municipalities and provincial capitals, was selected from the period between 2011 and 2016. Using regression analysis, we examine the negative correlation between GDP and carbon emissions and total industrial sulfur dioxide emissions. Additionally, we find a positive association between GDP and park green area. The robustness of our findings is confirmed through Budget Revenue tests. Furthermore, Difference-in-Differences (DID) testing reveals the positive impact of control variables on the two main variables under investigation.

Is air pollution joint prevention and control effective in China-evidence from "Air Pollution Prevention and Control Action Plan".

This paper examined the effect of air pollution joint prevention and control on pollution emissions in China. Specifically, based on the panel data of 290 cities from 2007 to 2021, taking the implementation of the "Air Pollution Prevention and Control Action Plan" as a natural experiment, the difference-in-difference-in-difference (DDD) model was used to explore the effect of air pollution joint prevention and control on haze pollution. Results show that air pollution joint prevention has a significant impact on pollutant emissions either as a whole or as a single pollutant. In terms of individual urban agglomeration, whether the Yangtze River Delta or the Pearl River Delta urban agglomerations, the air pollution joint prevention and control policy has a significant impact not only on the overall reduction of pollutant emissions but also on the reduction of single PM2.5 or industrial sulfur dioxide emissions alone. Environmental regulations have also achieved the effect of haze control in general and have a significant impact on the reduction of PM2.5 or industrial sulfur dioxide emissions. Environmental regulations also significantly reduced PM2.5 emissions in these three urban agglomerations. These findings provide a scientific basis and essential reference for understanding the implementation effect of regional joint prevention and control policies comprehensively and objectively.

The impacts of industrial collaborative agglomeration on industrial sulfur dioxide emissions in China: from the novel perspective of spatiotemporal matrix.

This paper explores the impacts of industrial collaborative agglomeration on industrial sulfur dioxide intensity from a spatiotemporal perspective based on panel data on the 284 prefecture-level cities from 2003 to 2019, with systematic consideration of the underlying mechanism of channels and actions. The empirical results show that industrial co-agglomeration significantly intensifies industrial SO2 intensity, especially with increasing agglomeration. In addition, its positive spatial spillover effects are established in geographical proximity to the city. Furthermore, the channel analysis shows that the industrial structure path, industrial efficiency path, and industrial scale path account for a sharp increase in industrial SO2 intensity. The market forces reverse and moderate this exacerbating process more significantly than the government does, which provides evidence for the importance of pursuing a dynamic equilibrium between them. Finally, there exist heterogeneous effects across cities with different administrative levels, innovation capacities, and macropolicies of special emission limits for air pollutant policy. While arguing for the environmental pollution effects of industrial co-agglomeration, this paper also provides solid support and a new perspective for promoting sustainable economic development and achieving win-win economic and environmental benefits.

Spatiotemporal characteristics and socioeconomic factors of PM2.5 heterogeneity in mainland China during the COVID-19 epidemic

Spatiotemporal variation of PM2.5 in 2018 and 2020 were compared to analyze the impacts of COVID-19, the spatial heterogeneity of PM2.5, and meteorological and socioeconomic impacts of PM2.5 concentrations heterogeneity in China in 2020 were investigated. The results showed that the annual average PM2.5 concentration in 2020 was 32.73 μg/m3 existing a U-shaped variation pattern, which has decreased by 6.38 μg/m3 compared to 2018. A consistent temporal pattern was found in 2018 and 2020 with significant high values in winter and low in summer. PM2.5 declined dramatically in eastern and central China, where are densely populated and economically developed areas during the COVID-19 epidemic compared with previous years, indicating that the significantly decline of social activities had an important effect on the reduction of PM2.5 concentrations. The lowest PM2.5 was found in August because that precipitation had a certain dilution effect on pollutants. January was the most polluted due to centralized coal burning for heating in North China. Overall, the PM2.5 concentrations in China were spatially agglomerated. The highly polluted contiguous zones were mainly located in northwest China and the central plains city group, while the coastal area and Inner Mongolia were areas with good air quality. Negative correlations were found between natural factors (temperature, precipitation, wind speed and relative humidity) and PM2.5 concentrations, with precipitation has the greatest impact on PM2.5, which are beneficial for reducing PM2.5 concentrations. Among the socio-economic factors, proportion of the secondary industry, number of taxis, per capita GDP, population, and industrial nitrogen oxide emissions have positive correlation effects on PM2.5, while the overall social electricity consumption, industrial sulfur dioxide emissions, green coverage in built-up areas, and total gas and liquefied gas supply have negative correlation effects on the PM2.5.

Air pollution impacts on public health: Evidence from 110 cities in Yangtze River Economic Belt of China

This study intends to further reveal the relationship between air pollution and public health on a city scale in China and explore the spillover effect among cities. On the basis of collecting the panel data of 110 cities in the Yangtze River Economic Belt from 2010 to 2018, we establish a spatial econometric model to analyze the impacts of air pollution, economic development, and other factors on public health. According to the results, a significant spatial correlation exists between the public health and air pollution levels in all of the cities in the Yangtze River Economic Belt. Air pollution also shows a spillover effect among these cities; the relationships between the industrial fume (dust) emissions, industrial sulfur dioxide emissions, and particulate matter (PM 2.5) concentration and the public health level are not simple linear relationships, but instead U-shaped curvilinear relationships. The economic development in recent years has contributed to the improvement of the public health level of the cities in the Yangtze River Economic Belt. The economic development of their neighboring cities, however, has adversely affected the public health levels of these cities.

Dynamic changes in provincial exhaust emissions in China in the carbon peak and neutrality setting: based on the effects of energy consumption and economic growth.

Reducing exhaust emissions, promoting economic development, and realizing clean energy utilization have always been concerns in China. To measure the relationship between them, this study selects the data related to energy consumption, economic growth, and exhaust emissions from 2000 to 2019 in 30 Chinese provinces. By constructing a panel vector autoregressive (PVAR) model, the dynamic relationship between them in China is quantitatively analyzed. The results show that there is a long-term interaction between energy consumption, economic growth, and exhaust emissions. Among them, economic growth is highly dependent on energy consumption, but it can promote the reduction of exhaust emissions. However, energy consumption will produce a large amount of industrial waste, such as sulfur dioxide and carbon dioxide emissions. Specifically, the industrial structure and energy structure have the most obvious impact on reducing industrial sulfur dioxide emissions and carbon emissions, with the proportion between 0.071-0.090 and 0.031-0.032, respectively. Therefore, the adjustment of industrial structure and energy structure is the key to exhaust emission reduction.

How does high-speed rail construction affect air pollutant emissions? Evidence from the Yangtze River Delta Urban Agglomeration in China

Taking the construction of high-speed rail as a “quasi-natural experiment”, the panel data of 26 cities in the Yangtze River Delta from 2004 to 2018 were selected as samples, and a difference-in-differences model was constructed to study the impact of high-speed rail construction on air pollutant emissions. Furthermore, the meditating effect model and difference-in-differences model were built to explore the paths of high-speed railway construction affecting air pollutant emissions. According to the study, the construction of high-speed rail reduces industrial sulfur dioxide emissions and increases the emission of industrial smoke and dust, which are more obvious in areas with good economic conditions. The role of high-speed rail in reducing emissions is realized through the structure effect, technological effect and substitution effect. However, the construction/renovation process of high-speed rail lines or stations does increase the industrial smoke and dust emissions. In this study, the bidirectional effects of high-speed rail construction on different air pollutant emissions were identified, including the high-speed rail construction process into the research. Multiple paths of action were proposed, bridging the gap of existing studies. The study reveals that controlling the air pollution emissions throughout the full life cycle of the high-speed rail, from the construction process to its operation, was essential.

Study on the impact of electric power and thermal power industry of Beijing–Tianjin–Hebei region on industrial sulfur dioxide emissions—From the perspective of green technology innovation

As one of the largest energy consuming industries, electric power and thermal power industry holds the lifeline of national economy. Although electric power and thermal power industry is the main source of industrial sulfur dioxide emissions, there are few studies on the impact of the electric power and thermal power industry on industrial sulfur dioxide emissions, and even fewer literature on the Beijing–Tianjin–Hebei region as the scope of study. Therefore, with the green technology innovation as the research perspective, this paper empirically analyzes the impact of electric power and thermal power industry of Beijing–Tianjin–Hebei region on industrial sulfur dioxide emissions by constructing a spatial econometric model, panel threshold model and collecting relevant data. The research results show that the electric power and thermal power industry is an important source of industrial sulfur dioxide emissions in Beijing, Tianjin and Tangshan with significant spatial spillover effects of industrial sulfur dioxide emissions from the electric power and thermal power industry. The electric power and thermal power industry can significantly suppress emissions when green technological innovation is greater than 9.3186. Therefore, it is necessary to scientifically reduce industrial sulfur dioxide emissions from the electric power and thermal power industry in key cities such as Beijing, Tianjin and Tangshan, establish a joint prevention and control mechanism for industrial sulfur dioxide, improve the level of green technology innovation in areas with serious environmental pollution, and systematically reduce industrial sulfur dioxide pollution from the electric power and thermal power industry.

大气污染规制对城市空气污染的防治成效——基于准实验分析

PDF HTML阅读 XML下载 导出引用 引用提醒 大气污染规制对城市空气污染的防治成效——基于准实验分析 DOI: 10.5846/stxb202107262020 作者: 作者单位: 作者简介: 通讯作者: 中图分类号: 基金项目: 国家自然科学基金项目（72033005）；中国博士后科学基金项目（2021M701507）；教育部人文社会科学研究项目（20YJC790014）；江西省教育厅科技项目（GJJ200534） The Effect of air pollution regulation on urban air pollution prevention and control: Evidence from a Quasi-Natural Experiment Author: Affiliation: Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:以2003年实施的大气污染防治重点城市政策为准自然实验，运用双重差分模型从区域层面分析了大气污染规制对城市空气污染治理的影响，研究发现：（1）大气污染规制在1%的显著性水平下降低了重点城市的工业二氧化硫排放强度，工业二氧化硫排放量以及城市PM2.5年均浓度值。（2）大气污染防治重点城市政策实施后的9年时间内有效减少了12215.8万t城市工业二氧化硫排放量，并且使得城市PM2.5年均浓度改善2.97μg/m3，下降比分别达到了36.2%和8.5%，平均每年减少了3.7%的城市工业二氧化硫排放量并降低0.944%的城市PM2.5浓度值。（3）大气污染防治重点城市政策对于城市空气污染治理主要是通过减少能源消耗量、增加城市污染治理力度、促进规制地区产业结构转型升级和提升生产技术水平等渠道予以实现。 Abstract:Based on the quasi-natural experiment of the key city policy of air pollution control implemented in 2003, this paper analyzes the impact of air pollution regulation on urban air pollution control from the regional level by using Differences-in-Difference model. The results show that:(1) air pollution regulation significantly reduce the intensity of industrial sulfur dioxide emission, industrial sulfur dioxide emission and PM2.5 annual concentration in key cities. (2) In the nine years after the implementation of the policy, 122.158 million tons of urban industrial sulfur dioxide emissions have been effectively reduced, and the average annual concentration of PM2.5 has been improved by 2.97 μg/m3, with the reduction ratio of 36.2% and 8.5% respectively. The average annual sulfur dioxide emission of urban industry has been reduced by 3.7% and the urban PM2.5 concentration has been reduced by 0.944%. (3) The key city policy of air pollution prevention and control for urban air pollution control is mainly realized by reducing energy consumption, increasing the intensity of urban pollution control, promoting the transformation and upgrading of regional industrial structure and improving the level of production technology. 参考文献 相似文献 引证文献

Energy Costs of Reducing Industrial Sulfur Dioxide Emissions in China

With increasing environmental pollution, China has instituted corresponding environmental regulations to address environmental challenges. Estimating the costs of such environmental regulations can help governments to formulate rational environmental policies. This review estimates the costs of environmental regulations based on a novel perspective of energy consumption. Using panel data for Chinese provincial regions in 2006–2015, we developed a non-parametric directional distance function and estimated different optimal energy inputs based on data envelopment analysis under two scenarios, namely, those with and without emission reduction constraints. The gap between the two groups of optimal energy inputs facilitated the estimation of the energy costs associated with reducing SO2 (sulfur dioxide) emissions in China’s industrial sectors. The results suggest that approximately 13.40 tons of standard coal were required to reduce SO2 emissions by 1 ton, highlighting the discrepancy between energy savings and emission reduction. The energy costs of SO2 emission reduction were the highest in West China (18.63), followed by those in Central and Northeast China; meanwhile, those in East China were the lowest (9.91). The large differences between the energy costs of emission reduction in different regions indicated that economically underdeveloped areas have scope for improvement with respect to energy structures and innovation in the green technology field.

Spatiotemporal Evolution and Trend Prediction of Tourism Economic Vulnerability in China’s Major Tourist Cities

The evaluation and trend prediction of tourism economic vulnerability (TEV) in major tourist cities are necessary for formulating tourism economic strategies scientifically and promoting the sustainable development of regional tourism. In this study, 58 major tourist cities in China were taken as the research object, and an evaluation index system of TEV was constructed from two aspects of sensitivity and adaptive capacity. On the basis of the entropy weight method, TOPSIS model, obstacle diagnosis model, and BP neural network model, this study analyzed the spatiotemporal patterns, obstacle factors, and future trends of TEV in major tourist cities in China from 2004 to 2019. The results show three key findings: (1) In terms of spatiotemporal patterns, the TEV index of most of China’s tourist cities has been on the rise from 2004 to 2019. Cities throughout the coast of China’s Yangtze River Delta and the Pearl River Delta urban agglomeration show high vulnerability, whereas low vulnerability has a scattered distribution in China’s northeast, central, and western regions. (2) The proportion of international tourists out of total tourists, tourism output density, urban industrial sulfur dioxide emissions per unit area, urban industrial smoke and dust emission per unit area, and discharge of urban industrial wastewater per unit area are the five major obstacles affecting the vulnerability degree of the tourism economy. (3) According to the prediction results of TEV from 2021 to 2030, although the TEV of many tourist cities in China is increasing year by year, cities with low TEV levels occupy the dominant position. Research results can provide reference for tourist cities to prevent tourism crises from occurring and to reasonably improve the resilience of the tourism economic system.

Does the Green Industry Policy Reduce Industrial Pollution Emissions?—Evidence from China’s National Eco-Industrial Park

As a regional green industrial policy, the construction of national eco-industrial parks is of great significance to the realization of industrial green transformation, while its environmental effects and mechanisms have not yet been clarified. Using panel data from 308 prefecture-level cities in China from 2003 to 2017, this study takes the establishment of 3 national-level ecological industrial parks as a quasi-natural experiment, also using a time-varying difference in difference model to examine how green industrial policies affect industrial pollution emissions. The study found that the establishment of a national eco-industrial park has significantly reduced industrial sulfur dioxide emissions, and the emission reduction effect has a lag effect and long-term impact. In cities with strong environmental regulations, provincial capitals and municipalities, and cities with a high degree of marketization, eco-industrial parks have better emission reduction effects, while, in cities with greater economic growth incentives and fiscal pressures, eco-industrial parks are difficult to achieve emission reduction effects. The establishment of national eco-industrial parks can reduce industrial pollution emissions by improving pollution treatment efficiency and energy efficiency, as well as promoting industrial agglomeration. China should continue to promote the implementation of green industrial policies, to strengthen the construction of national-level eco-industrial parks at this stage.

An empirical study on industrial eco-efficiency in arid resource exploitation region of northwest China.

Located in the northwest of China, Xinjiang is a typical arid desert area and mineral resources development zone. The lack of water resources and a fragile ecological environment restricts the sustainable development of the region. Based on the industrial panel data of Xinjiang from 2001 to 2015, this paper uses the undesirable output SBM model, Malmquist index model, and Tobit regression model to comprehensively and systematically measure and evaluate the industrial eco-efficiency and its change characteristics from provincial, regional, and prefectural levels. The results show that (1) the industrial eco-efficiency level in Xinjiang is generally low, lower than the national average, but the development trend is good, and it has been steadily rising over time, from 2001 to 2015 and from the "Tenth Five-Year Plan" period to the "Twelfth Five-Year Plan" period. (2) The spatial distribution of industrial ecological efficiency of Xinjiang is not balanced. Northern Xinjiang is larger than that of eastern Xinjiang and the southern Xinjiang. The developments of 14 prefectures are uneven and asynchronous, which can be divided into two development modes: industrial and agriculture and animal husbandry region. (3) Through the decomposition analysis of the Malmquist index, it has been found that the technological progress index is the restriction factor of the changing trend of TFP, while the technical efficiency index and the pure technical efficiency index are the promoting factors. (4) The main factors causing the decline in ecological efficiency are industrial sulfur dioxide emissions, industrial nitrogen oxide emissions, total industrial water consumption, and general industrial solid waste. It can be seen that the emission of air pollutants and excessive industrial water are the main problems in the region. (5) Industrial ecological efficiency is positively correlated with industrial development level, scientific and technological innovations, industrial structure, and environmental planning, whereas negatively correlated with the degree of opening up and industrial agglomeration. (6) Xinjiang is an extremely arid and water-scarce region. These are the keys and prerequisites for saving water resources and strengthening the comprehensive utilization of water resources. Whether in the industrial areas or in the agricultural and animal husbandry areas, water conservation should be given top priority.

Research on the Impact of Economic Growth of the Northeastern Old Industrial Base on Environmental Pollution-Taking Liaoning Province as an Example

This paper takes the impact of economic growth on environmental pollution in Liaoning Province as the research object. After analyzing the status quo of economic growth and environmental pollution in Liaoning Province, four environmental pollution indicators (industrial wastewater discharge, industrial waste gas emissions, industrial sulfur dioxide emissions, and industrial dust emissions) and an economic growth indicator (per capita GDP) are selected. After an economic model is established to focus on the real impact of Liaoning’s economic growth on environmental pollution, it is found that the impact of Liaoning’s economic growth on environmental pollution does not conform to the traditional Environmental Kuznets Curve. Through analysis, it is concluded that economic growth has affected the four environmental indicators to varying degrees. Among them, industrial wastewater discharge, industrial sulfur dioxide emissions, and industrial dust emissions drop after rising, and industrial dust emissions have been on the rise all the time. Considering the realities and characteristics of Liaoning Province, the author has proposed five countermeasures and suggestions for coordinating the relationship between economic growth and environmental protection in Liaoning Province, which are, optimize the industrial structure to promote economic development in the direction of environmental protection; focus on pollution prevention to take a new road to industrialization of circular economy; tap the full potential of market mechanism to realize the innovation of environmental protection system; actively promote the application of low-carbon energy to increase its proportion in total energy consumption; increase investment in environmental protection to improve investment structure and efficiency of environmental protection.

Ecological Security Evaluation Algorithm for Resource-Exhausted Cities Based on the PSR Model

Today, resource depletion threatens a number of resource-based cities in China. The ecological security problem caused by the long-term exploitation of natural resources is a key issue to be solved in the development of resource-exhausted cities. Using 23 indicators, this study evaluated the ecological security status and development trends of 21 resource-exhausted cities in China from 2011 to 2017. The results showed that from 2011 to 2015, the overall ecological security of this type of city was low, with over 60% of the cities at an unsafe level. However, ecological security improved rapidly after 2016, and by 2017, all of the cities had reached the critical safety level. The top 10 indicators of ecological security included industrial sulfur dioxide emissions, water supply, agricultural fertilizer application, and forest coverage. These 10 indicators’ cumulative contribution to ecological security was 48.3%; among them, reducing industrial sulfur dioxide emissions contributed the most at 5.7%. These findings can help governments better understand the ecological security status of resource-exhausted cities, and it can provide a reference for the allocation of funds and other resources to improve the ecological safety of these cities.

Kuznets Curve based Analysis on the Relationship between Economic Growth and Environmental Quality in Beijing

It is well known that the economic growth of big cities may cause risk on the environment, thus it is essential to study the relationship between economic growth and environmental quality. Particularly, this paper establishes the environmental Kuznets curve measurement models between Beijing’s economic growth and environmental pollution levels using 2000-2017 Beijing time series data. Economic development level is measured by GDP per capita. The level of environmental pollution is measured by the discharge of industrial waste water, the discharge of industrial waste gas, the production of industrial solid waste, and the discharge of industrial sulfur dioxide. The empirical results show that the environmental Kuznets curve of Beijing’s economic growth and industrial wastewater discharge has an inverted N-type characteristic. Second, the economic Kuznets curve of Beijing’s economic growth, whether it is related to the amount of industrial exhaust emissions or the amount of industrial solid waste produced, has an inverted U-shaped curve. In addition, the environmental Kuznets curve of Beijing’s economic growth and industrial sulfur dioxide emissions has linear characteristics. Based on the characteristics of these environmental Kuznets curves, this paper finds that there is a relatively good relationship between Beijing’s economic development level and the environment relationship after a comprehensive analysis. On this basis, this paper puts forward the suggestions of Beijing’s environmental Kuznets curve to Beijing’s good environmental level.

Modeling the spatiotemporal dynamics of industrial sulfur dioxide emissions in China based on DMSP-OLS nighttime stable light data.

Due to the rapid economic growth and the heavy reliance on fossil fuels, China has become one of the countries with the highest sulfur dioxide (SO2) emissions, which pose a severe challenge to human health and the sustainable development of social economy. In order to cope with the serious problem of SO2 pollution, this study attempts to explore the spatial temporal variations of industrial SO2 emissions in China utilizing the Defense Meteorological Satellite Program’s Operational Linescan System (DMSP-OLS) nighttime stable light (NSL) data. We first explored the relationship between the NSL data and the statistical industrial SO2 emissions at the provincial level, and confirmed that there was a positive correlation between these two datasets. Consequently, 17 linear regression models were established based on the NSL data and the provincial statistical emissions to model the spatial-temporal dynamics of China’s industrial SO2 emissions from 1997 to 2013. Next, the NSL-based estimated results were evaluated utilizing the prefectural statistical industrial SO2 emissions and emission inventory data, respectively. Finally, the distribution of China’s industrial SO2 emissions at 1 km spatial resolution were estimated, and the temporal and spatial dynamics were explored from multiple scales (national scale, regional scale and scale of urban agglomeration). The results show that: (1) The NSL data can be successfully applied to estimate the dynamic changes of China’s industrial SO2 emissions. The coefficient of determination (R2) values of the NSL-based estimation results in most years were greater than 0.6, and the relative error (RE) values were less than 10%, when validated by the prefectural statistical SO2 emissions. Moreover, compared with the inventory emissions, the adjusted coefficient of determination (Adj.R-Square) reached 0.61, with the significance at the 0.001 level. (2) During the observation period, the temporal and spatial dynamics of industrial SO2 emissions varied greatly in different regions. The high growth type was largely distributed in China’s Western region, Central region, and Shandong Peninsula, while the no-obvious-growth type was concentrated in Western region, Beijing-Tianjin-Tangshan and Middle south of Liaoning. The high grade of industrial SO2 emissions was mostly concentrated in China’s Eastern region, Western region, Shanghai-Nanjing-Hangzhou and Shandong Peninsula, while the low grade mainly concentrated in China’s Western region, Middle south of Liaoning and Beijing-Tianjin-Tangshan. These results of our research can not only enhance the understanding of the spatial-temporal dynamics of industrial SO2 emissions in China, but also offer some scientific references for formulating feasible industrial SO2 emission reduction policies.