Co-benefits of a more centralized environmental regulatory system to reduce air pollution and carbon emissions in China

Co-benefits of policies to reduce air pollution and carbon emissions in China

This study analyzed the spatiotemporal differences and driving factors of carbon emission in China’s prefecture-level cities for the period 2003–2019. In doing so, we investigated the spatiotemporal differences of carbon emission using spatial correlation analysis, standard deviation ellipse, and Dagum Gini coefficient and identified the main drivers using the geographical detector model. The results demonstrated that 1) on the whole, carbon emission between 2003 and 2019 was still high, with an average of 100.97 Mt. Temporally, carbon emission in national China increased by 12% and the western region enjoyed the fastest growth rate (15.50%), followed by the central (14.20%) and eastern region (12.17%), while the northeastern region was the slowest (11.10%). Spatially, the carbon emission was characterized by a spatial distribution of “higher in the east and lower in the midwest,” spreading along the “northeast–southwest” direction. 2) The carbon emission portrayed a strong positive spatial correlation with an imbalance polarization trend of “east-hot and west-cold”. 3) The overall differences of carbon emission appeared in a slow downward trend during the study period, and the interregional difference was the largest contributor. 4) Transportation infrastructure, economic development level, informatization level, population density, and trade openness were the dominant determinants affecting carbon emission, while the impacts significantly varied by region. In addition, interactions between any two factors exerted greater influence on carbon emission than any one alone. The findings from this study provide novel insights into the spatiotemporal differences of carbon emission in urban China, revealing the potential driving factors, and thus differentiated and targeted policies should be formulated to curb climate change.

With accelerating urbanization, building sector has been becoming more important source of China’s total carbon emission. In this paper, we try to calculate the life-cycle carbon emission, analyze influencing factors of carbon emission, and assess the delinking index of carbon emission in China’s building sector. The results show: (i) Total carbon emission in China’s building industry increase from 984.69 million tons of CO2 in 2005 to 3753.98 million tons of CO2 in 2013. The average annual growth rate is 18.21% per year. Indirect carbon emission from building material consumption accounted to 96–99% of total carbon emission. (ii) The indirect emission intensity effect was leading contributor to change of carbon emission. The following was economic output effects, which always contributed to increase in carbon emission. Energy intensity effect and energy structure effect took negligible role to offset carbon emission. (iii) Delinking index show the status between carbon emission and economic output in China’s building industry during 2005–2006 and 2007–2008 was weak decoupling; during 2006–2007 and during 2008–2010 was expansive decoupling; and during 2010–2013 was expansive negative decoupling.

Economic development has largely contributed to the increment of CO2 emission. This study uses spatial econometric models to investigate the relationship between economic growth and carbon emission in China with data of 30 provinces of China during the period of 2000 to 2012. Results show that the relationship between carbon emission and economic growth in China during the recent decade has the development tendency toward an inverse U-shaped curve, approximately confirming the carbon emission’s Kuznets curve hypothesis in China. There exists a significant spatial correlation between carbon emission and economic growth, implying that carbon emission in a province may be influenced by economic growth in adjacent provinces. When economic growth reaches 279.91 million Yuan/km2 GDP (at a comparable price in 2000), the contradiction between economic growth and carbon emission begins to be gradually alleviated. These findings provide new insights and valuable information for reducing carbon emissions in China.

Most conventional air pollutants and carbon dioxide (CO2) are simultaneously emitted from the same sources, providing a sound theoretical basis for the synergistic governance of these emissions. At present, China faces severe challenges in protecting the eco-environment, such as reducing conventional pollutants, improving environmental quality, and peaking CO2 emissions. Internationally, the control of greenhouse gas (GHG) emissions has been incorporated into the comprehensive environmental management system in major developed economies such as the United States (US) and the European Union (EU), where, based on GHG emissions monitoring and statistical data, decision-making support is provided for the national governments in the form of policy evaluation, thus forming a management mode that enables overall planning, coordination, and unified regulatory at the national level and participation of multiple departments under the national government. The synergistic control of conventional air pollutants and GHGs is becoming an important measure to strengthen the environmental management and achieve low-carbon development. This paper summarizes the synergistic effects of reducing air pollution and carbon emissions from the aspects of synergistic policies, strategic planning, and institutional systems, and conducts an analysis based on existing synergistic practices.

Based on the Environmental Kuznets Curve (EKC), this paper empirically analyzes the impact of green finance development on industrial carbon emissions in China by using the panel data of Chinese mainland province. It is found that the development of green finance has significantly suppressed the industrial carbon emissions in China. Heterogeneity test shows that the inhibition effect on carbon emission in central China is the most obvious, and the inhibition effect on carbon emission in eastern and western regions decreases in turn. Technological progress significantly inhibits carbon emissions, especially in central China, followed by the western region and finally the eastern region. It is suggested to improve the green and low-carbon financing system, support the optimization of energy consumption structure and guide substantive technological progress, so as to promote the realization of carbon emission reduction targets.

Currently, Tangshan confronts the dual challenge of elevated carbon emissions and substantial pollution discharge from the iron and steel industries (ISIs). While significant efforts have been made to mitigate air pollutants and carbon emissions within the ISIs, there remains a gap in comprehending the control of carbon emissions, air pollutant emissions, and their contributions to air pollutant concentrations at the enterprise level. In this study, we devised the Air Pollutant and Carbon Emission and Air Quality (ACEA) model to identify enterprises with noteworthy air pollution and carbon emissions, as well as substantial contributions to air pollutant concentrations. We constructed a detailed inventory of air pollutants and CO2 emissions from the iron and steel industry in Tangshan for the year 2019. The findings reveal that in 2019, Tangshan emitted 5.75 × 104 t of SO2, 13.47 × 104 t of NOx, 3.55 × 104 t of PM10, 1.80 × 104 t of PM2.5, 5.79 × 106 t of CO and 219.62 Mt of CO2. The ACEA model effectively pinpointed key links between ISI enterprises emitting air pollutants and carbon dioxide, notably in pre-iron-making processes (coking, sintering, pelletizing) and the Blast furnace. By utilizing the developed air pollutant emission inventory, the CALPUFF model assessed the impact of ISI enterprises on air quality in the Tangshan region. Subsequently, we graded the performance of air pollutant and CO2 emissions following established criteria. The ACEA model successfully identified eight enterprises with significant air pollution and carbon emissions, exerting notable influence on air pollutant concentrations. Furthermore, the ACEA outcomes offer the potential for enhancing regional air quality in Tangshan and provide a scientific instrument for mitigating air pollutants and carbon emissions. The effective application of the ACEA model in Tangshan’s steel industry holds promise for supporting carbon reduction initiatives and elevating environmental standards in other industrial cities across China.

With the acceleration of urbanization and industrialization, the issues of urban pollution emissions and carbon emissions have become increasingly prominent. The coupling coordination relationship between pollution emissions and carbon emissions has also become a key issue affecting sustainable urban development. This paper, based on a systems coupling perspective and social network analysis methods, examines the spatiotemporal characteristics and driving mechanisms of the coupling coordination between pollution emissions and carbon emissions in China. The findings that: (1) There are significant regional differences in the coupling coordination degree (CCD) of pollution and carbon emissions across various regions in China, exhibiting a gradient decreasing trend. The overall national improvement in coupling coordination is limited, indicating a need to strengthen synergistic governance of pollution reduction and carbon emission reduction. (2) The CCD between cities has undergone phased development from ‘barely coordinated—primary coordination—intermediate coordination’, with most cities still at the primary coordination stage. The central and western regions have yet to reach a more advanced coordination state. (3) Analysis of the driving mechanisms indicates that various complex factors, such as economic development, industrial structure, environmental regulation, and green technological innovation, significantly influence coupling coordination.

Using grey Gompertz model to explore the carbon emission and its peak in 16 provinces of China

The heavy reliance on coal for energy contributes to both air pollutants and CO2 emissions in China. As air pollution control becomes one of the top government priorities in recent years, many measures to tackle air pollution, such as curbing coal consumption, increasing energy efficiency, and encouraging renewable energy investments, can simultaneously reduce carbon emissions. However, air pollution abatement measures are not always aligned with carbon mitigation goals. For instance, installing sulfur scrubbers on coal power plants can significantly reduce air pollutant emissions, but does not mitigate carbon emissions. Given the political saliency of air pollution concerns, it is critical for policymakers to understand the potential synergies and trade-offs between these two objectives: improving air quality and protecting human health in the near term, and achieving deep decarbonization to tackle climate change in the long term.

Humans have altered the earth in unprecedented ways, and these changes have profound implications for global climate change. However, the impacts of human pressures on carbon dioxide (CO2) emissions over long time scales have not yet been clarified. Here, we used the human footprint index (HF), which estimates the ecological footprint of humans in a given location, to explore the impacts of human pressures on CO2 emissions in China from 2000 to 2017. Human pressures (+13.6%) and CO2 emissions (+198.3%) in China are still on the rise during 2000–2017 and are unevenly distributed spatially. There was a significant positive correlation between human pressures and CO2 emissions in China, and northern China is the main driver of this correlation. The increase of CO2 emissions in China slowed down after 2011. Although human pressures on the environment are increasing, high-quality development measures have already had noticeable effects on CO2 emission reductions.

Transportation is an important source of carbon emissions in China. Reduction in carbon emissions in the transportation sector plays a key role in the success of China’s energy conservation and emissions reduction. This paper, for the first time, analyzes the drivers of carbon emissions in China’s transportation sector from 2000 to 2015 using the Generalized Divisia Index Method (GDIM). Based on this analysis, we use the improved Tapio model to estimate the decoupling elasticity between the development of China’s transportation industry and carbon emissions. The results show that: (1) the added value of transportation, energy consumption and per capita carbon emissions in transportation have always been major contributors to China’s carbon emissions from transportation. Energy carbon emission intensity is a key factor in reducing carbon emissions in transportation. The carbon intensity of the added value and the energy intensity have a continuous effect on carbon emissions in transportation; (2) compared with the increasing factors, the decreasing factors have a limited effect on inhibiting the increase in carbon emissions in China’s transportation industry; (3) compared with the total carbon emissions decoupling state, the per capita decoupling state can more accurately reflect the relationship between transportation and carbon emissions in China. The state of decoupling between the development of the transportation industry and carbon emissions in China is relatively poor, with a worsening trend after a short period of improvement; (4) the decoupling of transportation and carbon emissions has made energy-saving elasticity more important than the per capita emissions reduction elasticity effect. Based on the conclusions of this study, this paper puts forward some policy suggestions for reducing carbon emissions in the transportation industry.

This study investigates the impact of renewable and non-renewable energy sources on carbon emissions in the context of China's 14th Five-Year Plan (2021–2025). The plan emphasises a “Dual-control” strategy of simultaneously setting energy consumption limits and reducing energy intensity for GDP (gross domestic product) in order to meet the targets of the five-year plan. Using a comprehensive dataset of Chinese energy and macroeconomic information spanning from 1990 to 2022, we conduct a Granger causality analysis to explore the relationship between energy sources and the level of air pollution. Our findings reveal a unidirectional link, wherein renewable energy contributes to a reduction in air pollution, while non-renewable energy sources lead to an increase. Despite the government's investment in renewable energy, our results show that China's economy remains heavily reliant on traditional energy sources (e.g., fossil fuels). This research is the first systematic examination of the interplay between energy usage and carbon emissions in the Chinese context. Our findings provide valuable insights for policy and market strategies aimed at promoting carbon neutrality and driving technological advancements in both government and industries.

The changes in the carbon emissions in China's provincial construction industries are of high complexity. It is essential to understand the changes in the construction carbon emissions (CCEs) in China on the provincial scale. This study evaluates the factors and structural paths of the changes in provincial CCEs in China between 2012 and 2017 using the structural path decomposition analysis. The results show that the emission intensity effect and production structure effect contributed greatly to the reduction of CCEs across various regions, while the final demand effect had contrary impacts. The local nonmetallic mineral products industry (c13), metal smelting and pressing industry (c14), and electricity industry (c24) generally contributed significantly to the emission intensity effect, production structure effect, and final demand effect across most regions. The consumption of local c13, c14, and c24 by the construction industry (c27), namely “local c13→c27”, “local c14→c27”, and “local c24→c27” were generally the important structural paths of the CCEs changes across various regions. Nonlocal industries such as Hebei c14 and nonlocal structural paths such as “Hebei c14→c27” contributed substantially to the CCEs changes in many regions such as Beijing. The emission intensity effect, first-order production structure effect, and final demand effect typically dominated the effects of the critical structural paths of the CCEs changes across various regions. This study can help policymakers better understand the changes in China's provincial CCEs to formulate region-specific emission reduction measures and provide a comprehensive reference for related research.

Environmental governance remains a critical challenge in developing countries. This paper examines the causal impact of public environmental concern on air pollution and carbon emissions using high-frequency monitoring data and online search index information in China from 2015 to 2021. To address endogeneity, LSTM model was employed to construct an instrumental variable. The findings show that public environmental concern significantly realizes synergistic green benefits, exhibiting an increasing dynamic effect. Based on the signalling theory, we indicate that stricter environmental penalties, enhanced regulation, industrial relocation, and improved corporate green concepts are the main channels through which public concern exerts its co-benefits. Meanwhile, the green benefits are stronger in inland cities, big cities and areas with higher internet development. Furthermore, the inhibitory effect of public environmental concern also has a spatially decaying boundary. Our results shed light on the potential green benefits of informal environmental regulation.