Environmental Quality In China Research Articles

Can Artificial Intelligence Effectively Improve China’s Environmental Quality? A Study Based on the Perspective of Energy Conservation, Carbon Reduction, and Emission Reduction

The “technological dividends” brought by AI development provide a new model for the country to achieve green governance, enhance enterprises’ ability to manage pollutant emissions during production and operations, and create a new driving force for improving environmental quality. In this regard, this paper systematically examines the impact of AI on environmental quality in China by employing provincial panel data spanning from 2000 to 2020. Focusing on energy conservation, carbon reduction, and emissions mitigation, the analysis is conducted through the application of a two-way fixed-effects model and mediation effects model to explore both the effects and the mechanisms of AI’s influence on environmental quality. The findings indicate that the development and implementation of AI contribute positively to China’s efforts in energy conservation, carbon reduction, and emissions mitigation, ultimately leading to an enhancement in environmental quality. This conclusion remains valid after multiple robustness checks. Mechanism tests reveal that the optimization of regional energy structures, advancements in green technological innovation, and upgrades in industrial structures serve as crucial pathways through which AI facilitates energy conservation, carbon reduction, and emissions mitigation. Heterogeneity analysis uncovers a notable “path dependence” effect in China’s AI development; regions characterized by higher material capital investment, more advanced technological market development, and greater levels of marketization experience a relatively more pronounced impact of AI on the enhancement of environmental quality. This study offers direct references and practical insights for countries globally to foster AI development, enhance environmental quality, and advance high-quality economic growth amid the ongoing wave of digital and intelligent transformation.

Impact of globalization and energy consumption on CO2 emissions in China: Implications for energy transition

Despite the importance of understanding the impact of economic globalization on CO2 emissions through renewable and non-renewable energy consumption, previous studies have yielded contradictory results. This study addresses this gap by examining the relationship between trade openness, foreign direct investment, renewable energy consumption, non-renewable energy consumption, and CO2 emissions in China using wavelet analysis. The methodology allows for simultaneous evaluation of the commonality between variables in both time and frequency domains. The results reveal that the causality between variables varies with frequency, with notable reversals in lead-lag relationships. Economic globalization affects CO2 emissions differently through renewable and non-renewable energy consumption, with distinct short-term and long-term dynamics. The findings highlight the need for credible energy transition programs, increased renewable energy utilization, and strengthened global cooperation to balance economic globalization and environmental quality in China. Future research could explore heterogeneity among provinces, nonlinear and asymmetric effects, and expand the scope to other developing economies.

Female leaders as environmental saviors: Tackling urban pollution in Chinese cities

In the Chinese political context, local government officials have substantial influence over the implementation of policies. The approach to urban environmental management varies significantly between female and male officials, which in turn affects governance outcomes differently. Consequently, the gender of local officials plays a crucial role in shaping urban environmental conditions. This study investigates the impact of female officials on urban environmental pollution in China over the period from 2003 to 2018. Utilizing data from the China Urban Statistical Yearbook combined with individual profiles of officials at the prefecture level, the analysis reveals a notable decrease in urban environmental pollution associated with female leadership. Notably, the effect is more pronounced among younger female officials compared to their older counterparts, and those with higher education levels are particularly effective in curbing pollution emissions. The pollution abatement effect of female officials is found to be stronger in the central regions compared to the eastern and western regions. The robustness of these findings is confirmed through checks against alternative explanatory variables, permutation tests, and treatment effect analyses. Overall, this research contributes new perspectives on management strategies that can sisgnificantly improve urban environmental quality in China.

Fertilizer use and agricultural practices in the paradox of maize crop production and environmental sustainability

The enduring existence of pollution presents a substantial danger to human health, natural systems, and social welfare. Human activities mostly generate greenhouse gas emissions, namely carbon dioxide, which negatively impacts the environment. This study used annual datasets to examine the association between maize crop production, maize yield, fertilizer consumption, agricultural land use, and environmental quality in China. In order to identify the positive and negative shocks with the assessment of short- and long-run dynamics, the study used an asymmetric Nonlinear Autoregressive Distributed Lag (NARDL) approach. A Robust Least Squares method was also used to locate the parameters nexus in order to assess the series' robustness. Results from the long-run interaction indicate that the maize crop production and agricultural land use has a positive impact on CO2 emissions with probability values of (0.000), (0.000), and (0.001), (0.780), respectively, via both positive and negative interruptions. Additionally, maize yield exposed a detrimental effect on environmental quality. Results of the robust least squares analysis showed that maize crop production, fertilizer consumption, and agricultural land use had a positive influence on environmental quality, with probability values of (0.000), (0.004), and (0.949), respectively. However, there is an unfavourable relationship between variable maize yields and CO2 emissions. China should play a significant role in seeking to reduce carbon dioxide emissions and adopt the beneficial policies necessary to ensure the environment's long-term sustainability, since these emissions are now a rising issue around the world.

Testing the Effectiveness of Government Investments in Environmental Governance: Evidence from China

The Chinese government has taken many measures to improve the environment, such as directly investing in pollution control infrastructure, but the effectiveness remains to be tested. This paper employs the Toda–Yamamoto test and the Fourier Toda–Yamamoto test to examine the link between environmental governance investment and environmental quality in China from 2003 to 2020. PM2.5, which measures air quality, is used here as an indicator of the environment. The results reveal that environmental governance investment has notably lessened the average concentration of PM2.5 in certain regions, indicating a positive effect on environmental quality, albeit with regional variations. Taking structural breaks into consideration, the relationship between environmental governance investment and environmental amelioration is significant in a smaller number of regions. Additionally, the cross-sectional correlation is further scrutinized to assess the essential robustness of the causality between the two variables. The findings lend support to the aforementioned conclusion. These conclusions provide valuable guidance for China’s policymakers in optimizing environmental governance investments to curb pollution and achieve sustainable development.

Dynamic nexus between natural resource rents, economic growth, and environmental quality: A comparative study between China and the US

AbstractEconomic development and environmental sustainability have recently become global priorities. This study utilizes the nonlinear autoregressive distribution lag model (NARDL) to investigate the asymmetric effects of natural resource rents on economic growth and environmental quality in China and the United States from 1970 to 2020. The findings indicate that natural resource rents exert asymmetric effects on economic growth and environmental quality in both countries; however, the impact patterns differ between the two countries. In the short term, a decrease in natural resource rents significantly increases GDP per capita in the US, while an increase in natural resource rents has no effect. Moreover, natural resource rents do not influence the ecological footprint in the US. By contrast, China's GDP per capita remains unaffected by natural resource rents, while the ecological footprint is significantly influenced by both positive and negative changes in natural resource rents, exhibiting asymmetric impacts. In the long run, an increase in natural resource rents significantly impacts both GDP per capita and the ecological footprint in the US, while a decrease only impacts the ecological footprint. By contrast, both increases and decreases in natural resource rents impact per capita GDP and the ecological footprint in China. These findings highlight the importance of tailoring country‐specific policies to facilitate sustainable economic development and enhance environmental quality.

Navigating climate challenges: Focusing on the effectiveness of natural resource rents, fintech, green finance, environmental quality, and digitalisation

China indeed has made great efforts to maintain environmental quality. However, it should be noted that climate challenges normally emerge when certain nations heavily depend on non-renewable resources to meet energy demands. It is quite difficult to reduce the dependency because such economies are ranked as a major importer of fossil fuel resources. This means, pollution and emission rates in subsequent economies are increasing with the passage of time. The spontaneous fintech growth and financial inclusion, natural resource volatility and increasing economic activities in China have triggered vicious climate challenges. Therefore, the study intends to explore the relationship between fintech, financial inclusion, green finance, natural resource rent and environmental quality in China over the time period of 1998–2022. Using ARDL technique, it was found that fintech, financial inclusion and green finance enhance environmental quality, whereas natural resource rents are responsible of degrading environmental quality. Therefore, Chinese authorities should use resources related to green finance to facilitate fintech industry. Besides, blending fintech solutions such as NFTs and cryptocurrencies with traditional financing for environmental sustainability, there is also a need to establish standard laws and procedrues for these products.

Characteristics and Release Risk of Phosphorus from Sediments in a Karst Canyon Reservoir, China

With the continuous improvement of surface water environmental quality in China, sediment has gradually become the focus of research on internal pollution in reservoirs. To investigate the forms, distribution, and migration patterns of phosphorus in karst canyon reservoir sediments, we employed an improved sequential graded extraction method to determine phosphorus content in the sediments of the Wanfeng Reservoir. We studied the spatial distribution characteristics and release risk of phosphorus form in the sediments. The results showed that the total phosphorus (TP) content ranged from 79.37 to 438.04 mg·kg−1, while inorganic phosphorus (IP) content ranged from 77.32 to 424.64 mg·kg−1. Iron–aluminum-bound inorganic phosphorus (Fe/Al-Pi) accounted for 36.41% and was found to be the dominant form of IP. Organic phosphorus (OP) content ranged from 1.84 to 13.59 mg·kg−1, with weakly adsorbed organic phosphorus (H2O-Po) being the dominant form of OP. Potentially active inorganic phosphorus (NaHCO3-Pi) showed a highly significant positive correlation (p < 0.01) with Fe/Al-Pi, residual phosphorus (Res-P), and TP. This indicates that potentially active phosphorus (NaHCO3-P) is a significant potential source of phosphorus (P) in the reservoir. Biologically active phosphorus (BAP) content ranged from 66.97 to 201.46 mg·kg−1, with BAP/TP ratios ranging from 55.6% to 59.6%. The risk of phosphorus release from Wanfeng Reservoir sediments is high. The release of various forms of phosphorus from sediments is one of the important factors leading to the deterioration of water quality in the reservoir area in the future. To effectively manage water ecology in karst canyon reservoirs, it is essential to reduce the risk of endogenous phosphorus release.

New insights into the nexus between international trade, urbanization, nonrenewable energy consumption, and environmental quality in China: Evidence from Multivariate Threshold Regression

AbstractInternational trade (TRADE), urbanization (URB), and nonrenewable energy consumption (NRE) can pose significant impacts on environmental quality and economic growth. In addition, TRADE and URB can influence the transition to cleaner energy within an economy. China is one of the largest economies with a massive contribution to global carbon emissions. Thus, there is a need for a comprehensive study that could explore the interrelationships between TRADE, URB, NRE, and environmental quality to assist economic and environmental policymaking in the country. This study explores these relationships and also reveals the precise threshold levels that these factors should not exceed to protect the environment and promote sustainability. The time series data from the Chinese economy from 1980 to 2021 are analyzed by using the Multivariate Threshold Regression (MThR) model. The findings revealed that TRADE has a detrimental impact on environmental quality in the low regime whereas a positive effect in the high regime. In contrast, NRE negatively affects the environment in both regimes, while URB positively influences the environmental quality in both regimes. Furthermore, the threshold levels of variables required to influence sustainability and promote environmental quality were revealed as 46.74% of GDP for TRADE, 45.20% of the total population for URB, and 23448.2TWh for NRE. Moreover, TRADE leads the transition from traditional to modern energy consumption, while URB does not play a leading role in the energy transition. Based on the results, policies are recommended to promote sustainable development.

Path to sustainable development: Can industrial intelligence and technological innovation balance economic growth and environmental quality in China?

AbstractIntelligent industrial transformation and technological innovation fuel China's sustainable development. We examine whether industrial intelligence and technological innovation improve economic growth and environmental quality using provincial data from China from 2006 to 2020. We used panel co‐integration techniques (fully modified OLS and dynamic OLS) for analysis. The results showed that industrial intelligence drives economic growth and environmental quality, whereas technological innovation primarily promotes economic growth. We also found that green technological innovation improves economic growth and environmental quality. The Granger causality technique based on the vector error‐correction model showed a strong interrelationship among industrial intelligence, technological innovation, economic growth, and environmental quality. Furthermore, a heterogeneity analysis shows that the effects and interrelationships of the variables of interest vary significantly by region in China. To achieve sustainable development, the government should accelerate the transformation of industrial intelligence, invest in environment‐friendly technological innovation activities, and focus on the co‐development of industrial intelligence, technological innovation, economic growth, and environmental quality.

Fintech, financial inclusion, mineral resources and environmental quality. An economic advancement perspective from China and Vietnam

From a policy perspective, China and Vietnam have made efforts to achieve environmental sustainability. However, it is important to note that environmental issues mostly arise when certain economies heavily rely on fossil fuel to fulfil energy requirements. It is challenging to reduce such reliance because, periodically, these economies become major importers of fossil fuels. Resultantly, the carbon emission rates of China and Vietnam have been increasing over time. The untapped renewable reserves of these economies encourage academia to explore its exploitation in order to produce renewable electricity. The instant growth of fintech, rapid financial inclusion, volatility of mineral resources, and growing economic advancements in China and Vietnam have initiated various dangerous climate issues. Thus, this study investigates the relationship between fintech, financial inclusion, mineral resource rents, economic advancement, and environmental quality in China and Vietnam over the period 2013–2023. Using FEOLS, DOLS, and FMOLS models, it finds that fintech, economic advancement, and mineral resource rents deteriorate the environmental quality of the selected economies, while financial inclusion has a favourable impact on the quality of the climate. The outcomes are supported by the application of the MMQR model. All quantiles show that fintech, economic advancement, and mineral resource rents pollute the environment while financial inclusion enhances climate quality. It is further observed that the extent and magnitude of the relationship increase with the increase of quantile levels. The findings have interesting and useful policy implications.

Design and Research of Multi-point Water Quality Monitoring System Based on Internet of Things

With the increasing demand for water quality monitoring and the increasing severity of water pollution, the water environmental quality in China faces a worrying situation, and water body monitoring has become an extremely important task. Now more than ever, new strategies for water quality monitoring are needed, and the rapid development of wireless monitoring technology perfectly meets people’s pursuit of low-cost, automated and real-time water quality monitoring. However, there are still problems such as few monitoring points cannot reflect the overall situation of water bodies, high artificial costs, and time-consuming analysis. This paper designs and implements a new water monitoring platform built on an Internet of Things platform. Taking water quality monitoring sensors as the core and small boats as the basic framework, it carries control, positioning, navigation equipment, uses wireless network as the data transmission means, monitors multi-point cruising sampling in different areas, realizes real-time collection, data storage and data analysis to complete related environmental monitoring. The multi-point online water quality monitoring system comprehensively applies sensor technology, Internet of Things technology and cloud computing technology to form an integrated online monitoring system. It aims to solve the problems of harsh working environment, strong repetitiveness and long sampling time of water quality monitoring tasks, and achieve fast, efficient and accurate completion of water quality monitoring tasks.

Green finance, environmental quality and technological innovation in China

AbstractThis research analyses the impact of green finance development on the environmental quality of China. It utilises provincial panel data from 2006 to 2021 and takes technological innovation as the intermediary variable. Through the construction of a comprehensive index of green finance, technological innovation and environmental quality, we verify the hypothesis that green finance development does improve environmental quality. Taking innovation as the intermediary variable, this study examines the hypothesis that green finance enhances environmental quality by improving the level of innovation and also illustrates the importance of developing technology‐intensive industries. Heterogeneity analysis shows that different regions or different levels of green financial development have varying effects on environmental improvement. Finally, the findings validate the environmental Kuznets curve (EKC) by showing an inverted U‐shape link between green finance and environmental quality. The results herein offer a benchmark for policymakers to further strengthen green finance policy, increase the proportion of green investment and raise the support of green finance for technological innovation, thus improving environmental pollution and promoting sustainable economic development.

Analyzing the linkages of rural tourism, GDP, energy utilization, and environment: Exploring a sustainable path for China

Rural tourism spurs economic growth and jobs but harms the Environment due to energy demands. The study accounts for energy use, globalization, and economic growth to assess and mitigate rural tourism's environmental impact. For data covering 2001Q1 to 2019Q4, GMM approaches are utilized to analyze the environmental implications of rural tourist enterprises. The findings suggest that rural tourism-related catering services increased substantial and positive overall environmental quality, except N2O. However, food and beverage services negatively influence greenhouse gas emissions and only PM2.5 in air pollution. Sightseeing hurts greenhouse gas emissions while having a positive impact on air pollution. Furthermore, traveling has a considerable negative influence on CO emissions in air pollutants. Energy use only has a substantial influence on CO2 and CO, but GDP has a negative impact on N2O emissions. Globalization has a negative impact on CO2 and air pollutants other than PM2.5. Catering services associated with rural tourism positively affect overall environmental quality, excluding N2O emissions. Rural tourism's food and beverage services harm greenhouse gas emissions (including CO2) and air pollution (particularly PM2.5). Traveling has a significant negative impact on CO emissions, but sightseeing has a dual impact, both negative on greenhouse gas emissions and positive influence on air pollution. Furthermore, shopping and leisure have little impact on overall environmental quality in China. The crucial efforts' policy ramifications are addressed as well.

Do the effects of aggregate and disaggregate energy consumption on different environmental quality indicators change in the transition to sustainable development? Evidence from wavelet coherence analysis.

In the 2030 Agenda for Sustainable Development, adopted by the United Nations (UN) member states in 2015, half of the target period has been exceeded. However, China, whose energy consumption relies heavily on fossil resources, remains at the top of the list of global polluters. Therefore, investigating the environmental impacts of energy types is essential to China's path towards Sustainable Development Goals (SDG)-7 and SDG-13. Based on this motivation, the paper offers new insights into the energy-environment literature for China with wavelet coherence analysis (WCA). This approach can investigate the relationship between variables in a periodic manner based on the frequency behavior of the models. The paper separately analyzes the effects of primary energy consumption (PEC), fossil energy consumption (FEC), renewable energy consumption (REC), nuclear energy consumption (NEC), GDP, and population (POP) on three different environmental indicators in China. Using two environmental pollution indicators (carbon emission (CO2) and ecological footprint (EF)) and one environmental quality indicator (load capacity factor (LCF)), the paper allows for comparison and robustness checks on the environmental impacts of energy indicators. Empirical findings reveal the following: (i) Except for REC and POP in the CO2 model, the variables in all three models largely move together during the period under observation; (ii) variables other than POP have consistent coefficient signs; (iii) PEC, FEC, NEC, and GDP increase CO2 and EF while decreasing LCF; (iv) the effect of NEC on LCF is more obvious until 2000; (v) unlike the others, REC affects CO2 and EF negatively and LCF positively; (vi) there is bidirectional causality between PEC and environmental indicators but not for REC; (vii) the causality relations of other variables with environmental indicators differ in terms of model, time, and direction of causality. In light of the findings, the paper highlights that only the REC improves environmental quality in China. Other energy indicators contribute to environmental degradation. China, whose ecological deficit has increased dramatically in recent years, urgently needs to reduce its dependence on fossil energy sources by accelerating investments in REC. Governments should also review nuclear energy policies, which are expected to help achieve carbon neutrality.

Do technological innovations and clean energies ensure CO2 reduction in China? A novel nonparametric causality-in-quantiles

Sustainable manufacturing and green growth are prominent concerns for both advanced and emerging countries to reach the sustainable development goals. Most emerging economies rely heavily on fossil fuels to meet their energy needs, which increases greenhouse gas emissions and degrades environmental quality. This study accessed the role of renewable energy, trade globalization, and technological innovations in predicting environmental quality in China using quarterly data from 2001 to 2019. The study employed a novel nonparametric causality-in-quantiles approach, because causality may not exist in the mean, but a higher-order relationship may be observed in the variance. The outcomes revealed that renewable energy, globalization and technology, all have significant and asymmetric power to predict carbon emissions and ecological footprint in China. The main finding of the study is that technology seems to be the most significant predictor of carbon emissions, while the ecological footprint is highly driven by renewable energy. Based on these results, the Chinese government should reduce ecological degradation by increasing investments in technological progress and renewable energy to achieve sustainable development.

Impacts of renewable energy, trade globalization, and technological innovation on environmental development in China: Evidence from various environmental indicators and novel quantile methods

This study analyzes the impact of renewable energy (REN), trade globalization (GLO), and technological innovation (TEI) on environmental quality in China. In doing so, the study considers carbon dioxide (CO2) emissions, ecological footprint (ECF), and load capacity factor (LCF) as environmental indicators. The study uses a quarterly dataset between 1990/Q1 and 2020/Q4 and applies novel quantile-on-quantile regression, nonparametric causality in quantiles, and quantile regression methods. The results report that at higher quantiles: (i) REN decreases CO2 emissions and ECF while stimulating LCF; (ii) GLO increases CO2 emissions and ECF while decreasing LCF; (iii) TEI increases CO2 emissions and ECF at higher quantiles, whereas it decreases LCF at middle quantiles; (iv) the causal effects vary according to changes in the mean and variance. The results show that REN, GLO, and TEI have environmental effects that vary according to environmental indicators and quantiles (levels). It can be concluded that REN, GLO and TEI are significant estimators of environmental quality in China. Accordingly, various policy options for developing environmental quality in China are discussed (e.g., increasing support for RE, channeling trade globalization in a positive direction to reduce negative impacts by allowing the import of environmentally friendly technologies, and managing technological innovations in a more environmentally friendly manner).

Depletion of natural resources and environmental quality: Prospects of energy use, energy imports, and economic growth hindrances

Depletion of natural resources and their impact on environmental quality is a pressing concern that requires urgent attention. As the world's population continues to grow, the demand for energy increases, leading to the potential exhaustion of finite resources. This document aims to explore the prospects of energy use, energy imports, and the hindrances to economic growth related to these issues. This paper examines the depletion of natural resources and environmental quality in China from 1971 to 2019, using energy use, energy imports, and economic growth hindrances as moderator variables. The long-run estimates indicate that a 1% increase in natural resource depletion decreases environmental degradation in China by 0.016554%. Moreover, a 1% increase in energy use increases China's CO2 emissions (environmental degradation) by 1.64283%. The result shows energy use and economic growth are positively related to CO2 emissions. Energy imports and natural resource depletion are negatively associated with CO2 emissions. Moreover, energy use and economic growth, energy imports, and natural resource depletion degrade the environmental quality in China. The Chinese government should take steps to ensure that the depletion of natural resources does not hurt the economy. In particular, the government should seek to create incentives for businesses to invest in sustainable practices and resources. This would have the dual effect of reducing the depletion of natural resources and increasing economic growth. Moreover, the Chinese government must strengthen its legal framework to ensure natural resources are managed responsibly. This includes establishing clear regulations for resource extraction and introducing penalties for companies who violate these regulations.

Testing load capacity and environmental Kuznets curve hypothesis for China: Evidence from novel dynamic autoregressive distributed lags model

Climate changes are occurring faster than expected and affecting human lives through increasing carbon emissions, food scarcity and changes in global temperatures. Following this trend, China is one of the top contributors to global pollution, and at the same time, it is a leading producer of electricity production from renewable sources (ELREC). The current research examines the relationship between ELREC, research and development (REDEV), and economic growth and their impact on three environmental quality indicators: carbon dioxide emissions, ecological footprint, and load capacity factor in China from 1985 to 2018. This research is significant because it helps to identify factors contributing to the environmental deterioration in China and how they can be addressed. Using the autoregressive distributed lag and dynamic autoregressive distributed lag model, the research suggests a load capacity curve (LCC) and simultaneously tests the LCC and environmental Kuznets curve (EKC) hypotheses. The findings indicate that the LCC and EKC hypotheses are viable in China and that ELREC favorably influences environmental quality. Additionally, REDEV has a significant impact on environmental indicators. The findings of this research reveal, in general, that sustainable REDEV, prioritizing environmental protection, and transitioning towards renewable energy sources are crucial elements of China's green development strategy. This study's findings provide valuable insights for policymakers and stakeholders working to improve environmental quality in China.

The Effect of Energy Consumption, Income, and Population Growth on CO2 Emissions: Evidence from NARDL and Machine Learning Models

With population and income growth, the need for energy has increased in developing and emerging economies, which has inevitably led to an increase in carbon dioxide emissions (CO2e). This paper investigates the impact of energy consumption on CO2e influenced by population growth, energy consumption per capita, and income. In particular, this paper investigates whether or not an increase in energy consumption, energy intensity, energy consumption per capita, population growth, and income impacts CO2e in China, India, and the USA. The study applied the non-linear Autoregressive distributed lag (NARDL) and machine learning techniques. We found a significant impact of energy consumption per capita on the CO2 emissions in China, India, and USA. Furthermore, the results revealed that, when income increased, CO2 emissions increased in India, but decreased in the USA. The results confirmed that population growth increases CO2 emissions only in India. The results revealed that a decrease in energy intensity significantly improves the environmental quality in China and India. Finally, we forecasted the CO2e trend from 2017 to 2025. The results revealed an upcoming increase in CO2e levels in China and India. Conversely, the forecasted results demonstrated a downward trend of CO2e emissions in the USA.