Environmental Pollution In China Research Articles

Achieving sustainable development through economic growth, energy consumption, and agricultural productivity in China

AbstractLarge amount of carbon emission is the main hazard to environment and human health. The aim of this research is to investigate the impact of economic growth, forest zone, agricultural productivity, and energy consumption on environmental pollution in China using time series data from 1980 to 2020. The underline research utilized dynamic ordinary least‐squares (DOLS) method, Johansen and Engle–Granger cointegration tests, and the autoregressive‐distributed lag (ARDL) technique to analyze the varying data set. To compare findings, fully modified ordinary least squares (FMOLS) and canonical cointegrating regression (CCR) estimators are estimated. Energy use and population raise CO2 emissions with 1% economic development. Long‐term CO2 emissions may be reduced by 1% agriculture production and forestry zone growth. The Granger causality test showed causation between all variables. Results reveal that China might achieve sustainable development goals by cutting down CO2 emissions and mitigate global climate change. The underline research presents policy recommendations for attaining environmental sustainability in China through green investment by reducing carbon emissions. These policies highlight promoting use of renewable energy, financing green technological progression in agricultural productivity, and the ecological feasibility of China's forests.

Green finance, energy structure, and environmental pollution: Evidence from a spatial econometric approach.

The adjustment of green finance and energy structure is gradually becoming a new engine that reduces environmental pollution in China. In this paper, the energy structure isintroduced in the process of discussing the impact of green finance on environmental pollution. We analyze the spatial correlation of green finance and study whether the adjustment of energy structure is affected by green finance and thus affects environmental pollution using a spatial econometric model. The results of empiricalanalysis show that green finance among provinces presents a significant spatial agglomeration, improving the green finance, and the energy structure can significantly reduce environmental pollution, and there are significant spatial spillover effects. There is inverted U-shaped relationship between energy structure and green finance in the national space, that is, after the green finance is raised to a certain extent, with the level of green finance once more, the energy structure will gradually improve, and then, green finance drives the reduction of environmental pollution by improving the energy structure. The results of the heterogeneity analysis show that compared with other regions, the improvement of the green finance in the eastern region has significantly improved the energy structure, and environmental pollution has also decreased every year.

Tripartite Collaboration among Government, Digital Technology Platform, and Manufacturing Enterprises: Evolutionary Game Model

To solve the problems of economic growth and environmental pollution in China, it is crucial for local governments, as the responsible body for environmental protection, to rely on digital technology platforms to promote the green transformation of manufacturing industries, which is conducive to achieving sustainable social development. This study constructs a tripartite evolutionary game model and simulates and analyzes the influencing factors of manufacturing enterprises, the government and digital technology platforms. The study found that the critical value of the government subsidies for manufacturing enterprises using digital technology platforms is between 0.2 and 0.5. Manufacturing enterprises as “economic agents” should ensure their own profits and the good operation of their business when using digital technology platforms for green upgrading. The government penalties can improve enterprises’ green productivity as tested. This study enriches the research in the field of combining game theory and digital economy. It provides a theoretical reference for behavioral decisions of manufacturing enterprises, the government and digital technology platforms.

The opening of high-speed rail and environmental pollution of the Yangtze River Delta Region in China-based on SDID model test.

In recent years, environmental problems have attracted attention at home and abroad, so exploring the causes of environmental pollution has become a research content for scholars. The opening of high-speed railway has improved the economic development of China's Yangtze River Delta, and with the economic growth, the construction of high-speed railway has also led to environmental pollution in China's Yangtze River Delta. Therefore, using the data from 41 prefecture-level cities in China's Yangtze River Delta from 2003 to 2020, the SDID model was constructed, and the comprehensive index of environmental pollution was calculated by factor analysis to calculate the impact of high-speed railway construction on environmental pollution in China's Yangtze River Delta. The conclusions are as follows: The opening of high-speed railway significantly reduces the overall pollution level in China's Yangtze River Delta. The opening of high-speed rail has played a role in restraining the environmental pollution of the first and second tier cities and the third and fourth tier cities, but the pollution level of the third and fourth tier cities has decreased significantly.

Does the economic growth target overweight induce more polluting activities? Evidence from China.

In China, official promotion evaluation based on economic performance motivates local governments to develop high economic growth targets, which has played an active role in boosting China's economic growth in the past decades, whereas its environmental consequences have not been fully exploited. This paper finds that the economic growth target overweight has a stronger positive impact on the output of high-polluting industries than on the output of low-polluting industries, thus inducing more polluting activities. To deal with the issues of reverse causality and omitted variables bias, we take an instrumental variable approach. Examining mechanisms, we show that economic growth target overweight promotes polluting activities through the deregulation of the polluting activities in high-polluting industries. We also find an increase in the impact of the economic growth target overweight after the 2008 global economic crisis. Our study provides new evidence for explaining the dual presence of rapid economic growth and heavy environmental pollution in China.

The role of green financing, agriculture development, geopolitical risk, and natural resource on environmental pollution in China

Due to climatic uncertainties, the biosphere experienced tremendous growth of anthropogenic activities, which eradicates the sustainable environment for living beings. Thus, the continuous rise in environmental pollution detains the attention of the environmentalist to discover strategic approaches to maintain the green ecological era. Therefore, the present study aims to identify the role of green financing, agriculture development, geopolitical risk, and natural resources on China's environmental pollution (CO2 emission). We use time series data ranging from 1995 to 2020 using the Quantile Autoregressive Distributed Lags (QARDL) method proposed by (Cho et al., 2015). Further, we use Causality-in-Quantile to check the asymmetric association. However, the empirical results of causality signify an asymmetric relationship and bi-directional causality among all the variables. In addition, the results of QARDL indicate the negative and significant p-values of error correction parameters throughout the qualities, which confirmed the reversions to the long-term association between the determinants and CO2 emission. Whereas across all the quantiles, the negative and significant association of green financing (GFIN) with CO2 emission in QARDL is found, and other factors such as geopolitical risk (GRP), agriculture development (AGR), and Natural resources (NNR) show a positive and significant association with CO2 emission mainly in the upper quantiles. While the results of short-run QARDL analysis indicate that GFIN, GPR, and NNR are positively associated with CO2 emission, the significance level varies, GPR and GFIN are highly significant with environmental pollution at upper quantiles (0.05–0.40), and NNR is highly significant at all quantiles (0.05–0.95). Based on these estimations, some concrete implications are proposed for the practitioners to minimize the repercussion of CO2 emissions in China.

Literacy rate impact on innovations and environmental pollution in China

This study examines the impact of literacy rate and innovations on environmental pollution in China from 1990 to 2021. We applied the Quantile Autoregressive Distributed Lag method for the analysis, and our findings suggest that an increase in literacy rate leads to short- and long-term innovations. At the same time, literacy has a positive effect in 1st to 4th quantile in the long run. Furthermore, innovation has a positive effect on environmental pollution. However, in the short run, the literacy rate has negative implications for environmental pollution. These findings imply that education is essential to increase innovation in the economy. Besides, the literacy rate increases the standard of living, and thus, it is recommended that government should adopt environmental protection laws to reduce environmental pollution along with literacy increase. Additionally, China has achieved significant economic growth in the last few decades. To ensure sustainable economic growth government should introduce a carbon tax to minimize production externalities such as environmental pollution.

Study on the environmental effects of two-way foreign direct investment in China’s service industry

A mathematical model was built in this paper to divide the environmental effects of Foreign Direct Investment (FDI) in the service sector in terms of scale effect, structural effect and technical effect. Also, inbound FDI (IFDI) and outbound FDI (OFDI) were put under the same research framework, where the effects of two-way FDI on the emissions of SO2 and chemical oxygen demand (COD) were empirically tested with the 2004-2016 panel data of China’s service sector. The results show that IFDI in the service sector has significantly reduced China’s pollution emissions and improved environmental quality. This is mainly due to the positive technical and structural effects. OFDI in the service sector exhibits different responses to different pollution emission indexes. When there are both IFDI and OFDI in the service sector, SO2 emissions are suppressed to a certain extent, whereas COD emissions are not effectively controlled. In addition, the increased service output scale, per-capita capital stock and R&D input also have varying effects on environmental pollution in China.

Evaluation of Agricultural Eco-Efficiency and Its Spatiotemporal Differentiation in China, Considering Green Water Consumption and Carbon Emissions Based on Undesired Dynamic SBM-DEA

Both agricultural output and environmental pollution in China show certain characteristics of spatiotemporal variation due to the evolution and inter-provincial disparities of resource endowment, economic development level, and production mode. This paper considered the green water consumption, carbon emissions in agricultural production, and the persistent role of fixed asset investment, constructed an undesired dynamic SBM-DEA model, and evaluated the agricultural eco-efficiency (AEE) of 31 provinces in China from 2007 to 2018, analyzing the spatiotemporal differentiation. The results show that, during 2007–2018, the following can be concluded: (1) The AEE of 31 provinces in China showed the characteristics of an overall stable rise from 0.64 to 0.70 but uneven development among regions from 2007 to 2018. (2) The averages of either the agricultural resource consumption efficiency index or pollution emission efficiency index in 31 provinces slightly increased over time, while the average value of the agricultural fixed asset investment efficiency index showed a decline in volatility. The spatial discrepancy of any index mainly stems from the index disparity between groups with a high AEE and groups with a low one, with contribution rates of more than 85%. (3) It is recommended to emphasize strengthening communication and cooperation between provinces with high and low AEE and implement distinct regional strategies to improve AEE.

Exploring industrial agglomeration and green finance impact on regional environmental pollution in China based on system-GMM model.

The boom of building various industrial agglomerations in China has continued for many years. The relationship between industrial agglomeration and environmental pollution is the core issue of this paper. At the same time, green finance is a new financial development model that takes environmental protection as the core, and effectively promotes the sustainable development of the environment, the economy, and society while maintaining its own sustainable development, so green finance is a major direction for future financial development. This paper selects the data of 30 Chinese provinces from 2004 to 2020 as the research object and uses a system-GMM method to verify the relationship between industrial agglomerations, green finance on regional environmental pollution. It provides theoretical reference for improving global climate change and reduces environmental pollution (EP), concludes as follows. (1) Industrial agglomeration can exacerbate EP level in China, and also exacerbates EP in the western region, but the effect of industrial agglomeration on EP in the eastern and central regions has been insignificant. (2) Green finance can improve environmental pollution. The intensity of EP in economically less developed regions is more sensitive to green finance policies. (3) The correlation effect of industrial agglomeration and green finance can improve environmental pollution, i.e., green finance has an important role in improving EP. However, there are significant differences in different regions. The interaction term between industrial agglomeration and green finance with a non-significant positive coefficient in the eastern region, and it is non-significant negative coefficient in the central region, and a significant negative coefficient in the western region. The work has important theoretical value for achieving the goal of regional sustainable development and green transformation.

Environmental Pollution Liability Insurance Pricing and the Solvency of Insurance Companies in China: Based on the Black-Scholes Model.

Environmental pollution liability insurance is becoming increasingly important for China to achieve its emission reduction targets. Insurance pricing is a crucial factor restricting the market share of environment pollution liability insurance, from the perspective of the Black-Scholes pricing model, which in turn has influenced the solvency of insurance companies in China. Firstly, this study analyzes the problems existing in compulsory liability insurance for environmental pollution in China. It proceeds with analyzing the price of compulsory environmental pollution liability insurance using the Black-Scholes pricing model, and derives a high premium insurance rate of 2.44%. Moreover, it performs a multivariate regression analysis using the asset and liability data, taken from the annual report, to identify three key factors affecting the solvency adequacy ratio, namely, capital debt ratio, reflecting the company asset structure; net interest rate on assets, reflecting the asset scale with actual solvency; and claim ratio, reflecting the business quality. Based on the results of regression analysis and robustness test for the China Insurance Clauses (CIC) company, People's Insurance Company of China (PICC), and Asia-Pacific Property & Casualty Insurance (API) company, it is shown that the effect of total asset, total debt, capital debt ratio, claim ratio, and net interest rate on assets on the solvency adequacy ratio is significant, with respect to the size of the coefficients. Based on the Black-Scholes pricing model found in the previous cycle of liability insurance, and keeping in view the existing problems of environmental pollution liability insurance expenditure, this paper presents suggestions that are conducive to improving the solvency of insurance companies in China.

Research on the Development of Green Finance of SPD Bank

With the increasingly serious problem of ecological environment pollution in China, promoting the development of green finance in the banking industry has become an important means to promote the high-quality development of China's economy. As one of the first commercial banks to develop green finance in China, SPD Bank has accumulated rich experience in relevant businesses. This paper selects SPD Bank as the research object, analyzes its development process and current situation in green finance from the perspective of the application of green bonds and green credit, and puts forward suggestions on this basis.

Application of carbon emission prediction based on a combined neural algorithm in the control of coastal environmental pollution in China

The marine ecosystem provides the environment, resources, and services necessary for the development of every human society. In recent years, China's coastal zone has been polluted to varying degrees, which has seriously affected its development. The characteristics of marine environmental data include the variety of data types, the complexity of factors affecting the marine environment, and the unpredictability of marine pollution. Currently, there are few studies applying the clustering analysis algorithm to marine environmental monitoring. Then, carbon emissions (CEs) from coastal areas are predicted using marine environmental data. Therefore, this paper mainly studies the spatial and temporal accumulation characteristics of marine environmental data and uses the fuzzy c-means (FCM) algorithm to mine the data monitored by the marine environment. Meanwhile, it has been focused on the prediction of coastal CEs, and the grey model-back propagation (GM-BP) algorithm has been developed to predict CEs from coastal areas, which solves the problem that the traditional back propagation neural network (BPNN) cannot fully learn data features, which leads to a decline in accuracy. The experimental results showed that the FCM algorithm can divide the marine sample data into corresponding categories to distinguish polluted and unpolluted samples. The improved neural network model has a higher degree of non-linear fit and lower prediction error than a back propagation (BP) neural network. The main contribution of this paper is to first study the spatial and temporal accumulation characteristics of marine environmental data. The academic contribution of this study is to substitute the predictions of the three gray models (GMs) with the neural network structure simulation to finally obtain more accurate predictions. From a practical point of view, this study is helpful to a certain extent in alleviating the pressure of climate change due to increased CEs in global coastal zones. This study can also provide a new method of measuring environmental governance for marine environmental regulatory authorities.

The Impact of Foreign Direct Investments on Environmental Quality: The Case of China

Çin 2018 yılında küresel fosil yakıt tüketiminin %24.57’sinden, küresel CO2 emisyonlarının %28.88’inden sorumlu olmuştur. Ayrıca Çin, çevre kalitesinin başka bir göstergesi olan ekolojik ayakizinde BRICS ülkeleri arasında 2018 yılında 1990 yılına göre %160.19 artışla en fazla çevre kalitesini olumsuz etkileyen ülke olmuştur. Dolayısıyla Çin’de çevre kirliliğini etkileyen faktörlerin belirlenmesi önem taşımaktadır. Bu çalışmanın amacı da 1990-2018 dönemi için Çin’de Doğrudan Yabancı Yatırım (DYY) girişlerinin kirliliği artırıcı mı yoksa azaltıcı mı olduğunu araştırmaktır. Bunun için kişi başı DYY girişi, kişi başı enerji kullanımı ve kişi başı CO2 emisyonu yıllık değişkenlerinin olduğu model kullanılmıştır. Değişkenler arasındaki uzun dönemli ilişkinin varlığı Fourier ADL yöntemiyle araştırılmıştır. Uzun dönem katsayı tahminleri için ise FMOLS, DOLS ve CCR kullanılmıştır. Elde edilen sonuçlara göre, Çin’de DYY girişleri ve enerji tüketimi CO2 emisyonunu azaltmaktadır. Böylece Çin için kirlilik Halo hipotezinin geçerli olduğu görülmüştür.

The Spatial Effect and Threshold Characteristics of Green Technological Innovation on the Environmental Pollution of Thermal Power, etc., Air Pollution-Intensive Industrial Agglomeration in China

Serious air pollution has occurred in China since 2012. With the increasing investment in technological innovation in China, the role of green technological innovation in reducing air pollution has attracted more and more attention. By constructing the spatial Durbin model and threshold regression model and using the statistical data of China’s provinces, this study explores the spatial effects and threshold characteristics of China’s green technology innovation on the environmental pollution of China’s air pollution-intensive industrial agglomeration. The research objective is to find out the spatial effects and threshold characteristics of green technology innovation on the environmental pollution of China’s air pollution-intensive industrial agglomeration. The results show that thermal power, etc., air pollution-intensive industrial are important sources of sulfur dioxide emissions; however, their degree of concentration is gradually increasing, resulting in rising sulfur dioxide emissions in these areas. When the level of green technological innovation is greater than 8.0523, its inhibition effect on sulfur dioxide emissions in these industries is significantly increased. Improving green technology innovation ability in thermal power, etc., air pollution-intensive industrial agglomeration areas can effectively reduce pollution in the atmosphere. The level of green technology innovation in key zones must be increased to adjust the concentration of pollution-intensive industries, improve China’s industrial structure, and reduce atmospheric environment pollution.

Spatio-temporal effect of provincial technological innovation on environmental pollution in China.

The relationship between technological innovation (TL) and environmental pollution (EP) and its action mechanisms are complex and controversial aspects of discussion. Using the spatial autocorrelation analysis, standard deviation ellipse analysis, kernel density function, spatial econometric model, this study analyzed the spatial distribution, evolution characteristics, and influencing factors of the EP and TL from 2000 to 2020 in China. Results found there was a significant spatial autocorrelation between the EP and TL in 2000-2020. The standard deviation ellipse of EP was broadly distributed in the "southwest-northeast" direction, indicating that EP presented a trend of concentration in the direction of "southwest-northeast." The moving trajectory of the center of gravity for the EP in 2000-2020 was essentially moved from the northeast to southwest. Overall, the national level of TL exhibited a "north-south change, high in the east, and low in the west" trend. Regional differences were gradually expanding, and the polarization was evident. Regardless of using least squares method (OLS) or quantile regression (QR) models, TL, human capital (HC), and industrial structure (IS) all had an inhibitory effect on the EP at the effective significance level. Total population (TP), foreign direct investment (FDI), and local fiscal expenditure (LFE) were positively related to the EP.

The Dilemma and Countermeasures of Public Interest Litigation of Marine Environmental Pollution in China

Cases of marine environmental pollution (MEP), such as condensate leakage in the Sanchi case, not only directly infringe on private personal health and property rights, but also cause serious damage to the marine ecological environment. This paper analyzes dozens of MEP cases and summarizes the typical rights, interests, and remedies under Chinese law. Traditional tort liability legislation remedies the problem of infringement of private interests by environmental torts through compensation and punitive damages but it cannot reverse the damage to the marine ecological environment. Traditional civil legislation is built on the basis of rights and interests regarding damages and relief. MEP infringes on a wide range of citizens’ environmental rights and should be addressed by the environmental public interest litigation (EPIL), which is an important way to protect citizens’ environmental rights. This paper analyzes the legal interests, relief measures, and limitations of the existing EPIL legislation that is applicable to MEP cases under Chinese law, so as to make corresponding legislative suggestions.

Understanding the dynamic role of natural resources, green technology, economic integration and social globalization towards sustainable environment in China

To obtain economic stability in this contaminated era is the ultimate success countries are commending; hence concerning this issue, the current study analyses the nexus between green technology and environmental pollution in China, whereas the dynamic role of economic integration and natural resources in social globalization is studied. Thus, authors adopt the methodology of QARDL to investigate the data of China in quantile form to acquire accurate and reliable outcomes. After (QARDL) quantile autoregressive distributed lag, the Wald test, and Granger causality test are run to understand the variables' relationships better. Hence, the outcomes indicate that green technology (GTI) has a negative and significant impact on CO2 emission in the long run across all the quantiles. Still, a contrary effect is seen in the short-run analysis. Whereas natural resources (NRR), economic integration (EIN), and social integration (SIN) have a positive impact in the long run. Still, significant levels differ, i.e. (NRR has no significant impact, EIN has a significant influence on carbon emission in the lower and middle quartile, and SIN has a significant impact at each quantile). Similarly, NNR has no significant associations with CO2 emission is seen across all the quantiles in the short run. However, economic integration and social integration positively and significantly impact lower quantiles. Based on these findings study provides some potential policy implications to overcome the fundamental issue of carbon emission in China.

Spatial-temporal evolution and peak prediction of embodied carbon emissions in China's interregional trade.

The embodied carbon in inter-regional trade has a vital impact on the allocation of carbon emission reduction obligations and the formulation of carbon emission reduction strategies. Fewer studies have examined the spatial-temporal evolution pattern and peak prediction of embodied carbon emissions in China's inter-regional trade compared with the more numerous results on embodied carbon in international commerce. This paper applies the multi-regional input-output method to estimate the embodied carbon in inter-regional trade resulting from value-added transfer and investigates the spatial and temporal evolution of its patterns. The existence of an environmental Kuznets curve model with embodied carbon emissions as the index of environmental pollution in China is examined, and the time of the inflection point is calculated. The environmental Kuznets curve model is divided into four stages, and a two-dimensional model of economic development and embodied carbon emissions is proposed. The empirical findings indicate that the embodied carbon in China's interregional commerce has an overall rising tendency in the temporal dimension and a distribution characteristic of high in the west and north and low in the east and south in the spatial dimension. The Environmental Kuznets curve, which uses embodied carbon emissions as a measure of environmental pollution, has an inverse U-shaped and the time required to reach the inflection point varies by area. Economic development cannot be cross-stage but can shorten the duration of high carbon emissions. The government should promote the development of differentiated carbon emission reduction policies in each region, construct an inter-regional cooperative carbon emission reduction mechanism, encourage the low-carbon development of inter-regional trade, and realize the internal cycle of China's green economy. This study serves as a guide for the regions to establish scientific and acceptable carbon emission reduction strategies in order to achieve quality interregional trade development.

Does anti-corruption contribute to improving environmental pollution in China?

ABSTRACT We examine the effects of anti-corruption efforts on local environmental pollution in China. Using data for China from 2003 to 2017, we find that anti-corruption efforts contribute to reduce local environmental pollution. Second, we show the two possible channels through which the anti-corruption efforts reduce local environmental pollution: political connection effects and deterrent effects. Finally, our results show that the effects of anti-corruption efforts on local environmental pollution are stronger in cities located south of the ‘Qin ling Mountains-Huai he River’, in cities with stronger government and public concern for the environment. Our main results pass a series of robustness tests. Overall, we offer novel evidence that anti-corruption efforts contribute to improving environmental quality.