Environmental Pollution In China Research Articles

Transition towards natural resource rents and green technology to achieve China's COP26 success: A novel insights in the case of trade openness and environmental pollution

This study aimed to investigate the impact of various factors such as natural resource rents, trade openness, green technology innovation, oil prices, and economic growth on environmental pollution in China by covering the period from 1970 to 2021, aligning with the COP26 agenda. These factors included. To accomplish this, we utilized an advanced Quantile Autoregressive Distributed Lag model to scrutinize the short- and long-term quantile patterns for both the dependent and independent variables. The findings reveal that green technologies and natural resource rents play a negative role in reducing emissions, whereas economic growth and trade openness have positive effects on emissions levels in China in the short and long run during different quantile patterns. Additionally, we employed the Wald test to confirm the presence of asymmetric patterns in environmental pollution concerning economic growth, natural resource rents, green technological innovation, and trade openness in both the short and long terms. These results emphasize the significance of prioritizing key policy measures to align with the COP26 agenda, including enhancing green technology via natural resource rents and addressing immediate climate change challenges in China.

Contribution of Livestock Farming to Environmental Pollution in China

Purpose: The aim of the study was to examine contribution of livestock farming to environmental pollution in China. Methodology: This study adopted a desk methodology. A desk study research design is commonly known as secondary data collection. This is basically collecting data from existing resources preferably because of its low cost advantage as compared to a field research. Our current study looked into already published studies and reports as the data was easily accessed through online journals and libraries. Findings: The study found that livestock farming in China significantly contributes to environmental pollution, posing substantial challenges to water, air, and soil quality. Intensive livestock operations, characterized by concentrated animal feeding operations (CAFOs), generate large quantities of animal waste containing nutrients and pathogens that contaminate water bodies. Additionally, livestock farming contributes to air pollution through emissions of ammonia and other pollutants, particularly in areas with intensive farming practices. Soil degradation and nutrient imbalance further exacerbate environmental degradation, with higher livestock densities associated with increased soil compaction and nutrient runoff. Unique Contribution to Theory, Practice and Policy: Tragedy of the Commons & Ecological Modernization Theory may be used to anchor future studies on contribution of livestock farming to environmental pollution in China. Promote the adoption of sustainable livestock management practices through capacity building, training, and extension services for farmers. Encourage the implementation of integrated farming systems that optimize resource use, minimize waste generation, and enhance environmental resilience. Strengthen regulatory frameworks and enforcement mechanisms to ensure compliance with environmental standards and promote responsible livestock production. Implement stringent measures to control water pollution from livestock waste, including mandatory wastewater treatment and monitoring programs.

The Dilemmas and Countermeasures of China’s Energy Development under the Background of Sustainable Development

Energy is a vital resource for human survival as well as the material basis of all production and life. Environmental pollution and excessive resource consumption have become major issues in China due to the rapid consumption of energy driven by the deepening of reform and opening up and the acceleration of economic development. Problems and response strategies in the development and use of renewable energy have been analyzed from the perspective of sustainable environmental development in response to the existing situation of energy scarcity and environmental pollution in China. This analysis stresses the necessity of using renewable energy and its influence on environmentally sustainable development. It also provides prospects to achieve sustainable development in terms of energy utilization, the environment, and energy.

Explaining employment and environmental degradation nexus with environmental employment curve (EEC): A sector-wide threshold estimation for China

China is the world's largest emitter of carbon dioxide and has experienced significant economic growth in the last decade. The country also has significant employment capacity and has witnessed rapid economic growth in the recent years. This study aims to investigate the existence of the environmental employment curve (EEC) in China's main economic sectors. This study examines the relationship between carbon emissions, economic growth, energy consumption, renewable energy consumption and employment (industry, services, agriculture) in China over the period 1990–2020 using threshold autoregressive regression estimation. According to the EEC hypothesis, there exists an inverted U-shaped relationship between environmental pollution and employment rate. Empirical results show that the EEC hypothesis seems to hold in China. Further, an analysis of the impact of employment on environmental pollution in China's three main sectors – industry, service and agriculture – shows that the EEC hypothesis cannot be rejected in the industrial and the agricultural sectors. In addition, empirical results show that a 1% increase in energy consumption leads to a 0.92% increase in carbon emissions, while the use of renewable energy leads to a 0.18% decrease. These results suggest that investments in green energy transformation do not cause employment loss. Hence, it is important to drive policies that promote investments in renewable and clean technologies, stimulate research in renewable energy-related institutions and support public-private partnerships. Additionally, to generate employment without compromising on the environment or prosperity, policymakers should choose to implement alternative technologies that are less polluting or do not produce any carbon emissions.

Assessing the nexus between fintech, natural resources, government effectiveness, and environmental pollution in China: A QARDL study

Despite its pledge and efforts towards sustainability, China has not been able to live up to its environmental expectations. The road towards carbon neutrality still seems to be faraway. There has been light at the end of the tunnel with the various efforts China has undertaken to reduce environmental pollution (ENP). However, such efforts are not enough and the country must adopt some strategies which can be used to curb environmental pollution and promote more sustainable growth for the country in the long run. Hence, this study assess the role of Fintech (FNT), Natural resources (NTR), and government effectiveness (GVT) on environmental pollution. For that purpose, the study uses the novel Quantile Autoregressive Distributed Lag (QARDL) method, which assist in examining the impact of modelled series in multiple quantiles. The findings of the study suggest that Fintech can help to promote the use of digitalization within the financial industry and can be an efficient way to reduce CO2 emissions. Green finance and green investments can also be promoted using FinTech. The use and extraction of Natural resources are detrimental to the environment. Lack of government effectiveness can lead to severe environmental problems in the form of lax laws and corruption. The study recommends China promote the use of green energy, nurture the growth of Fintech and ensure that it works to develop a green image of the government to facilitate the growth of a green economy.

Towards sustainable transport: quantifying and mitigating pollutant emissions from heavy-duty diesel trucks in Northeast China.

Heavy-duty diesel trucks (HDDTs) have caused serious environmental pollution in China. Accurate estimation of their pollutant emission characteristics is essential to reduce emissions and associated environmental and public health impacts. To achieve sustainable development for transport emissions in Northeast China, we developed localized emission factors and a high-resolution emission inventory of HDDTs, based on on-board test, Guidebook and international vehicle emission (IVE) model. The results show that the total emissions of CO, NO, NO2, and PM from HDDTs in Northeast China in 2020 were 172.2 kt, 531.5 kt, 11.2 kt, and 921.4 t, respectively. In terms of spatial distribution, emissions decreased from the city center to the city fringe. Temporally, the NOx emission variation curves of different types of roads presented a "single-peak" emission characteristic, which was different from the peak of traffic flow. Three emission reduction scenarios are further developed in the paper. Scenario analysis shows that elimination of HDDTs that follow the old China III emission standard and installing tailpipe treatment devices are the most effective pollutant reduction measure. The reduction percentages for CO, NO, NO2, and PM ranged from 62.9 to 83.89%. The results of our study could inform policymakers to devise feasible strategies to reduce vehicle pollution in Northeast China.

Do Green Information and Communication Technologies (ICT) and Smart Urbanization Reduce Environmental Pollution in China?

Due to rapid urbanization and industrialization, China faces numerous environmental challenges, including air and water pollution, resource depletion, and climate change. Adopting green ICT and smart urbanization is a critical strategy to address these challenges. At the heart of this study lies the question: Do green ICT adoption and smart urbanization contribute positively to environmental pollution reduction? Therefore, this study intends to scrutinize the influence of green ICT and smart urbanization on environmental pollution in China, focusing on the period from 1996 to 2021. The most up-to-date method of structural modeling, partial least squares structural equation modeling (PLS-SEM), was used to estimate the quantitative connection between green ICT, smart urbanization, and environmental pollution. The findings of the structural model show that only the path coefficient between smart urbanization and environmental pollution is significant and negative. Renewable energy consumption directly and negatively influences environmental pollution, whereas smart urbanization directly and positively affects renewable energy consumption and green ICT. Consequently, renewable energy consumption and green ICT negatively influence environmental pollution. Based on the findings, the study proposes targeted public policy recommendations aimed at fostering the development of green ICT and smart urbanization initiatives in China.

The underlying drivers of environmental pollution: the role of semi-urbanization

ABSTRACT Assessing the impact of the driving forces on environmental pollution has a significant theoretical value for the construction of high-quality economic development. However, to our knowledge, no past study considers how semi-urbanization impacts the environment. This study provides empirical evidence on environmental pollution in China from the perspective of semi-urbanization. Also, the underlying mechanisms of semi-urbanization affecting environmental pollution are explored. The estimation results indicate that semi-urbanization shows prominent spatial agglomeration. We also observed that semi-urbanization in China can achieve a meaningful reduction of environmental pollution. Further, semi-urbanization negatively influences environmental pollution in the local region, but it contributes to environmental pollution growth in neighboring regions. In numerical terms, for every 1% rise in semi-urbanization of the province leads to a decrease in emissions by around 0.19% locally and by around 0.30% in neighboring regions; every 1% rise in semi-urbanization of the province decrease SW emissions by around 0.28% locally and increase by around 0.29% in neighboring regions. The investigation above helps policymakers to formulate effective emission reduction policies for realizing the “win-win” situation of promoting semi-urbanization and curbing environmental pollution.

Analysis of SO2 Emission Reduction Effect of Smart City Construction Based on a Multi-period DID Model

Along with the acceleration of urbanization and industrialization, the problem of environmental pollution in China has become increasingly prominent, putting forward new requirements for city construction. In 2012, the Chinese government proposed to build smart cities. This policy not only strengthened the urban informatization construction, but also provided valid solutions for China's environmental governance. However, there is little literature about the effect of smart city construction on pollution emission. Based on this, this paper used panel data from 284 cities in China during 2003–2019 to evaluate the effect of smart city construction on SO2 emissions by constructing a multi-period DID model. The findings are as follows: (1) The smart city construction could significantly reduce the emission of SO2 and the conclusion was robust. (2) There was a temporal hysteresis in the response of SO2 emissions to the smart city construction, and SO2 emissions began to decrease significantly in the third year after smart city construction. (3) Industrialization could significantly increase SO2 emissions, while opening up to the outside world and the concentration of population could significantly decrease SO2 emissions.

The threshold analysis of economic growth, FDI and trade on environment pollution in China using provincial panel data

The threshold analysis of economic growth, FDI and trade on environment pollution in China using provincial panel data

Legacy persistent organic pollutants (POPs) in eggs of night herons and poultries from the upper Yangtze Basin, Southwest China.

Black-crowned night heron (Nycticorax nycticorax) eggs have been identified as useful indicators for biomonitoring the environmental pollution in China. In this study, we investigated thirty eggs of black-crowned night heron collected from the upper Yangtze River (Changjiang) Basin, Southwest China, for the occurrence of legacy persistent organic pollutants (POPs), including polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/Fs), organochlorine pesticides (OCPs), polychlorinated biphenyls (PCBs), and polybrominated diphenyl ethers (PBDEs). Our results showed a general presence of POPs in night heron eggs with OCPs being the dominant contaminants, having a geometric mean concentration of 22.2 ng g-1 wet weight (ww), followed by PCBs (1.36 ng g-1 ww), PBDEs (0.215 ng g-1 ww), and PCDD/Fs (23.0 pg g-1 ww). The concentration levels were found to be significantly higher in night heron eggs than in poultry eggs by one or two magnitude orders. Among OCP congeners, p,p'-DDE was found to be predominant in night heron eggs, with a geometric mean concentration of 15.1 ng g-1 ww. Furthermore, species-specific congener patterns in eggs suggested similar or different sources for different POPs, possibly associated with contaminated soil and parental dietary sources. Additionally, estimated daily intakes (EDIs) were used to evaluate non-carcinogenic and carcinogenic risk associated with consumption of bird eggs. Our results revealed non-negligible non-cancer and cancer risk for humans who consume wild bird eggs as a regular diet instead of poultry eggs.

The environmental and economic utility of the third-party governance of environmental pollution in China—an analysis based on the business registration information of enterprises

The third-party governance of environmental pollution (TEG) is a market-oriented mechanism designed to attract social capital to participate in ecological environmental protection. Can this mechanism result in positive and significant environmental and economic effects in developing countries? This paper examines the practical effectiveness of China’s pollution governance system reform by analyzing data on the registered business capital of the environmental protection industry in 285 prefecture-level cities during the period of 2003–2019. The study finds the following: TEG can effectively curb urban pollution emissions and improve the urban green total factor productivity (GTFP) of cities; heterogeneity analysis shows that specialization, marketization, and enterprise nature exert important impacts on its effectiveness; mechanism analysis shows that TEG can restrain pollution emissions by strengthening the tendency toward urban green technology progress; and its effects of releasing the industrial production capacity can be leveraged to improve the quality of economic development.

Economic growth and environmental pollution in China: New evidence from government work reports

In China, economic growth targets significantly affect the economic behavior of local governments. This paper analyzes a dataset of the economic growth targets from 230 city government work reports from 2004 to 2019 to reveal how economic growth targets affect local environmental pollution. The empirical results show that the economic growth targets are “overweight” from the higher-level governments to the lower-level governments, which significantly aggravates regional environmental pollution because of environmental regulation relaxation, blocked industrial structure upgrades and technological innovation inhibition. Furthermore, to exceed the economic growth targets, local governments usually adopt the “riding a seesaw” strategy for the treatment of different pollutants. If the economic growth target statements are ambiguous or attainable, then environmental pollution is reduced. Interestingly, the “preemptive” city government, which sets economic growth goals before its province, is more inclined to maintain growth at the expense of the environment. This study provides important evidence for the literature on the impacts of government behavior on environmental pollution.

Can natural resource rent, technological innovation, renewable energy, and financial development ease China's environmental pollution burden? New evidence from the nonlinear-autoregressive distributive lag model

According to growth theories, natural resource rent and financial development benefit economic growth of China. However, they severely affect the environment. Therefore, there is a need to develop a path to determine the asymmetric impacts of natural resource rent, renewable energy, economic growth, and technological innovation on environmental pollution in China. For this purpose, our work applies the new cutting-edge nonlinear-autoregressive distributed lag model to examine the short- and long-run cointegration asymmetric relationship between environmental pollution and its determinants. Our findings show that the asymmetric pattern of China's natural resource rent, technological innovation, and financial development will reduce environmental pollution eventually. However, economic growth positively impacts environmental pollution. Our findings have significant policy implications and emphasize promoting technological innovation and renewable energy to effectively control environmental pollution.

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.

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.

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.