Has air pollution emission level in the Beijing-Tianjin-Hebei region peaked? A panel data analysis

Modelling the air pollution induced health effects of energy consumption across varied spaces in OECD countries: An asymmetric analysis

The air pollution-induced health effects of energy consumption remain a grey area in the extant literature. As of yet, there are very limited studies on the subject matter for countries in the Organisation for Economic Co-operation and Development (OECD). To this end, we employ panel data from 1990 to 2019 for 37 OECD countries and panel estimation techniques that control for distributional asymmetry. We also utilize a composite variable of mortality and morbidity to capture the full spectrum of air pollution-induced health burdens. Our findings reveal that renewable energy ameliorates the health burden of air pollution in indoor spaces, evidence for the ameliorating effects of renewable energy in outdoor and occupational spaces was however weak. We also show that income has an ameliorating effect on air pollution-induced health burdens across all spaces and that the effect of non-renewable energy is asymmetric and disparate across all spaces. Furthermore, while technological innovation ameliorates the health burden of air pollution in indoor spaces, it exacerbates the health burden of air pollution in both occupational and outdoor spaces. These findings thus show that the positive health implications of renewable energy policy interventions have more traction in indoor spaces. Capacity needs to be built in the renewable energy sector to reduce the pollution-inducing health burdens emanating from ambient and occupational spaces.

Research on carbon emission quota allocation scheme under "Double Carbon" target: a case study of industrial sector in Henan Province

To achieve China's "Double Carbon" target, overall carbon emissions should be effectively controlled, and carbon emission quota (CEQ) allocation is an important tool. This study develops carbon emission prediction, CEQ allocation, and scheme feasibility evaluation models based on the principles of fairness, efficiency, and economy. The purpose is to propose a suitable CEQ allocation scheme for the Industrial Sector in Henan Province (ISHP). The results show that (1) the allocation model combining the technique for order preference by similarity to ideal solution (TOPSIS) and the zero-sum gains DEA (ZSG-DEA) can trade off the fairness and efficiency principles. (2) The reallocation scheme has an environmental Gini coefficient of 0.393 (< 0.4), which maximizes efficiency while lowering the abatement costs by 126.268 billion yuan, making it an ideal scheme that considers multiple principles. (3) CEQ should be reduced in 7 subsectors of ISHP while increasing in 33 others. Carbon emissions from these 7 subsectors are high, and CEQ should be reduced in accordance with the fairness principle. Even if their abatement costs are high and CEQ rises according to the efficiency principle, the increase is much smaller than the decrease. The findings are useful for optimizing the CEQ allocation under the "Double Carbon" target.

Driving forces and relationship between air pollution and economic growth based on EKC hypothesis and STIRPAT model: evidence from Henan Province, China

The aim of this research is to analyze the main influencing factors and relationship between atmospheric environment and economic society. Using the panel data of 18 cities in Henan Province from 2006 to 2020, this paper employed some advanced econometric estimation included entropy method, extended environmental Kuznets curve (EKC) and STIRPAT model to conduct empirical estimations. The results show that most regions in Henan Province have verified the existence of the EKC hypothesis; and the peak of air pollution level in all cities of Henan Province generally occurred in around 2014. Multiple linear Ridge regression indicated that the positive driving forces of air pollution in most cities in Henan Province are industrial structure and population size; the negative driving forces are urbanization level, technical level and greening degree. Finally, we used the grey GM (1, 1) model to predict the atmospheric environment of Henan Province in 2025, 2030, 2035 and 2040. What should pay close attention to is that air pollution levels in northeastern and central Henan Province will continue to remain high.

Assessment of ambient air quality in heavy industrial localities: a case study of Yanbu industrial city

The objective of this study was to provide an appropriate evaluation of ambient air quality in industrial localities and the surrounding residential areas in its vicinity. Therefore, an assessment of gaseous emissions from industrial sectors was performed. For this purpose, concentrations were measured for SO2, H2S, NO2, O3, CO, PM2.5, and PM10 in five spatially diverse monitoring stations (AQMS) over different temporal intervals (daily, monthly, and annual) for the years 2015-2020. The impact on the environment and public health was evaluated through comparison with the corresponding regional and international standards. In the case study region, a substantial spatiotemporal variation was observed in the gaseous contaminants, due to the predominance of characterized meteorological parameters interfering with contributions from existing chemical facilities and anthropogenic activities. The exceedances for the investigated emissions were routinely violated the standard concentrations. According to AQI classifications, these violations were assigned to be within the acceptable limits for the gaseous emissions, moderately polluted for PM2.5, and unhealthy for sensitive groups for PM10. The proper distribution of the AQMSs within the industrial locality provides enough spatial and temporal observatory data, such that the exceedances were reduced with the subsequent years, hence appropriate evaluation of the relevant measurements revealed effective qualitative policies taken into action by authorities to maintain less accumulation of the gaseous emissions into ambient air beyond the harmful limits for public health and environment.

Decoupling relationship between carbon emissions and economic development and prediction of carbon emissions in Henan Province: based on Tapio method and STIRPAT model

In order to cope with global warming, China has put forward the "30 · 60" plan. We take Henan Province as an example to explore the accessibility of the plan. Tapio decoupling model is used to discuss the relationship between carbon emissions and economy in Henan Province. The influence factors of carbon emissions in Henan Province were studied by using STIRPAT extended model and ridge regression method, and the carbon emission prediction equation was obtained. On this basis, the standard development scenario, low-carbon development scenario, and high-speed development scenario are set according to the economic development model to analyze and predict the carbon emissions of Henan Province from 2020 to 2040. The results show that energy intensity effect and energy structure effect can promote the optimization of the relationship between economy and carbon emissions in Henan Province. Energy structure and carbon emission intensity have a significant negative impact on carbon emissions, while industrial structure has a significant positive impact on carbon emissions. Henan Province can achieve the "carbon peak" goal by 2030 years under the standard and low-carbon development scenario, but it cannot achieve this goal under the high-speed development scenario. Therefore, in order to achieve the goals of "carbon peaking" and "carbon neutralization" as scheduled, Henan Province must adjust its industrial structure, optimize its energy consumption structure, improve energy efficiency, and reduce energy intensity.

Decomposition, decoupling, and future trends of environmental effects in the Beijing-Tianjin-Hebei region: A regional heterogeneity-based analysis

The green growth of Beijing-Tianjin-Hebei (BTH) urban agglomeration plays a leading and exemplary role in overcoming internal resource restrictions, addressing climate change, and supporting China's high-quality growth. From the standpoint of pollution reduction and carbon reduction, this paper first conducts a comprehensive evaluation of the environmental impact based on combined weighting technique. The Logarithmic Mean Divisia Index (LMDI) model is used to decompose the environmental impact drivers in distinct areas. A decoupling effort index is further constructed to measure the effect of various efforts on the decoupling of economic growth and environmental impact, the improved grey Markov model is applied to predict the future trend of regional decoupling efforts. The results of empirical analysis based on data of the BTH region during 2011-2018 show that: 1) the environmental impact index of Beijing is the lowest followed by Tianjin and Hebei; 2) environmental regulation exerts the most significant impact on reducing environmental pressure in Beijing while technology progress and energy intensity have the most significant effect on easing environmental pressure in Tianjin; 3) strong decoupling efforts have been found in Beijing, Tianjin and Hebei, however, such effect is more significant in Beijing; 4) Beijing's decoupling state is mostly driven by regulatory effect, intensity effect, and scale effect, while Tianjin and Hebei's decoupling states are primarily driven by improvements in environmental regulation and energy intensity; 5) according to the forecast outcome of the improved grey Markov technique, a state of strong decoupling effort will be maintained in the BTH area by 2025, and the decoupling effort index in Beijing will remain the highest while the index in Hebei will remain the lowest.

Spatiotemporal characteristics of air pollution in Chengdu-Chongqing urban agglomeration (CCUA) in Southwest, China: 2015-2021

Studying the spatiotemporal characteristics of air pollutants in urban agglomerations and their response factors will help to improve the quality of urban living. In combining air quality monitoring data and wavelet analysis from the Chengdu-Chongqing urban agglomeration (CCUA), this study assessed the spatiotemporal distribution characteristics and influential factors of air pollutants on daily, monthly and annual scales. The results showed that the concentration of air pollutants in the CCUA has decreased year by year, and air quality has improved. Except for O₃, pollutants in autumn and winter were higher than those in summer. The spatial distribution of air pollutants was obvious distributed in Chengdu, Chongqing, Zigong and Dazhou. Pollution incidents were mainly concentrated in winter. The 6 air pollutants and air quality index (AQI) have dominant periods on multiple time scales. AQI showed positive coherence with PM_2.5 and PM₁₀ on multiple time scales, and obvious positive coherence with SO₂, CO, NO₂ and O₃ in the short term scale. AQI was not strongly correlated with the fire point, but exhibited obvious negative coherence in the long term scale. In addition, AQI showed an obvious positive correlation with temperature and sunshine hours in short term, and a clear negative correlation with humidity and rainfall. The research results of this paper will provide a reference for pollution prevention and control in the CCUA.

Analysis of Air Pollution around a CHP Plant: Real Measurements vs. Computer Simulations

This study examines the concentrations of air pollution in the vicinity of a combined heat and power plant (CHP) and a communication route, using computer modeling of pollutant dispersion and spatial analysis based on real measurements in the city of Łódź, Poland, Europe. The research takes into account the concentrations of particulate matter (PM10, PM2.5, PM1.0) and gaseous pollutants (SO2 and VOC) in winter and summer. The spatial distribution of pollutants is discussed, including the presence of areas with increased accumulations of pollutants. Because atmospheric air has no natural boundaries, when analyzing any location, not only local sources of pollution, but also background pollution, should be analyzed. A clear difference was observed between the concentrations of pollutants in the summer and winter seasons, with significantly higher concentrations in the winter (heating) period. The impacts of road transport, individual heating systems, and combined heat and power plants were also assessed. Computer calculations confirmed that road transport accounted for the largest share of both PM and SO2 emissions. The CHP plant was responsible for the smallest percentage of dust emissions and was the next largest producer of SO2 emissions. The share of the total emissions from the individual sources were compared with the results of detailed field tests. The numerical analysis of selected pollution sources in combination with the field analysis shows that the identified pollution sources included in the analysis represent only a part of the total observed pollutant concentrations (suggesting that other background sources account for the rest).

Influencing factors and decoupling analysis of carbon emissions in China's manufacturing industry

The manufacturing industry directly reflects national productivity, and it is also an industry with high energy consumption and severe carbon emissions. This study decomposes the influential factors on carbon emissions in China's manufacturing industry from 1995 to 2018 into industry value added, energy consumption, fixed asset investment, carbon productivity, energy structure, energy intensity, investment carbon intensity, and investment efficiency by Generalized Divisia Index Model. The decoupling analysis of carbon emissions and industry value added is carried out to investigate the states of the manufacturing industry under the pressure of "low carbon" and "economy." Results show that first, fixed asset investment is the driving force of carbon emissions, followed by industry value added; investment carbon intensity, carbon productivity, investment efficiency, and energy intensity are the mitigating factors; simultaneously, the impacts of energy consumption and energy structure are fluctuating. Second, the decoupling of manufacturing has improved, especially in the light industry. Third, the decoupling of carbon emissions and economic development is mainly dominated by the decoupling of energy consumption and industry added value. Therefore, reducing the proportion of coal consumption and optimizing the energy structure are significant ways to promote the low-carbon development of the manufacturing industry.

Pathways to progress sustainability: an accurate ecological footprint analysis and prediction for Shandong in China based on integration of STIRPAT model, PLS, and BPNN

The world has been challenged by achieving the plausible goal of sustainable development. This study aims to evaluate the ecological footprint and ecological carrying capacity and their driving factors of Shandong province in China from 1994 to 2017. Back propagation neural network method is adopted to predict the ecological footprint from 2018 to 2030. The findings are as follows: (1) The growth of ecological footprint has caused the ecological deficit in Shandong. (2) With regards to population, the increase of total population and the urbanization rate will incur the expansion of ecological footprint. (3) In terms of affluence, the elasticity coefficients of GDP per capita, the production value of industrial sectors, and the proportion of output value of the secondary industry in GDP are 0.068, 0.064, and 0.130 respectively. (4) In terms of technology, the elasticity coefficients of internal expenditure on R&D in GDP and patent number are 0.096 and 0.047 respectively, indicating that technological progress can promote ecological footprint in a short term. (6) The results of the prediction show that the ecological footprint of Shandong from 2018 to 2030 in the policy-regulation scenario is far less than that of the business-as-usual scenario. The policy recommendations are suggested to tackle the sustainable development challenges.

City image and eco-efficiency: evidence from China

In this study, we examine the promotion of eco-efficiency from a novel perspective by analyzing whether a city's environmental image contributes to its eco-efficiency. Specifically, we examine the causal effect of the country-level garden city image (CGCI) program on eco-efficiency by using a data set of Chinese prefecture-level cities from 2005 to 2016. We estimate the effects of this program by combining propensity score matching with the difference-in-differences method. Results show the program significantly increases a city's eco-efficiency by expanding its urban green coverage, optimizing its industrial structure, and attracting talented inhabitants. The CGCI certification effects are heterogeneous. Specifically, while its effects in the western regions are positive, its effects in eastern developed cities are insignificant. These results generally point toward the effectiveness and efficiency of the CGCI program in increasing eco-efficiency.

Health and economic benefits of clean air policies in China: A case study for Beijing-Tianjin-Hebei region

Exposure to PM_2.5 is associated with many adverse health effects, leading to additional social costs. The Blue Sky Protection Campaign (BSPC) has been implemented in 2018 in the Beijing-Tianjin-Hebei (BTH) area to control air pollution. This study assesses PM_2.5-related health and economic benefits of the BSPC in the BTH region. Results show that by 2020, PM_2.5 reduction can avoid 3561 thousand morbidity cases (equivalent to a 24% reduction in the 2020 baseline scenario) and 24 thousand premature deaths (12%) in the BTH region, with the majority benefit in Hebei. By 2030, the avoided morbidity and mortality cases will be 2943 (18%) thousand and 20 (9%) thousand, respectively. PM_2.5 reductions are highly effective in reducing work time loss, which will decrease the total annual work time by 1.7 × 10⁸ h (24%) in the BTH region by 2020. From the economic aspect, the reduced PM_2.5 concentration will save 30 million USD (25%) health expenditures and avoid 60 billion USD (13%) economic loss by using the value of statistical life (VSL) by 2020. In 2030, the health expenditures and economic loss will also decrease significantly, with 17 million USD (18%) and 63 billion USD (10%), respectively, in the BTH region. Besides, the economic benefits far exceed the policy costs of the BSPC, and the Δ benefit/Δ cost ratios of Beijing are significantly higher than those of Hebei. The BSPC in BTH has significant positive health and economic impacts. This study can provide a basis for future PM_2.5-related health risk studies at an urban level in China.

Modeling Pollutant Emissions: Influence of Two Heat and Power Plants on Urban Air Quality

Large industrial plants, power plants, and combined heat and power plants are popularly believed to be the main sources of point emissions, affecting both local and global air quality. This is because these installations emit significant amounts of pollutants at high altitudes every year. In this study, we investigate the impact of two solid fuel (hard coal)-fired CHP plants located within the urban agglomeration on the air quality of the city of Lodz in Poland (Europe). We used an OPA03 computer software to model the spatial distribution of pollutants. The results show that the annual average concentrations of pollutants were highest at an altitude of 25 m above ground level and decreased at lower measurement heights. The concentrations did not exceed permissible levels, reaching only 4% of national and international regulatory limits. We also made field measurements during the winter heating period, using an unmanned aerial vehicle (UAV) equipped with sensors to map the distributions of dust and gas pollutants in the areas with the highest concentrations of emissions from the two heat and power plants. Overall, the field measurements confirmed that it is not high-altitude emissions that have the greatest impact on local air quality.

3D Spatial Analysis of Particulate Matter (PM10, PM2.5 and PM1.0) and Gaseous Pollutants (H2S, SO2 and VOC) in Urban Areas Surrounding a Large Heat and Power Plant

In many regions of the world, the winter period is a time of poor air quality, due primarily to the increased use of individual and district heating systems. As a consequence, the atmospheric air contains increased concentrations of both particulate matter and gaseous pollutants (as a result of “low” emissions at altitudes of up to 40 m and “high” emissions more than 40 m above ground level). In winter, the increased pollution is very often exacerbated by meteorological conditions, including air temperature, pressure, air speed, wind direction, and thermal inversion. Here, we analyze the concentrations of particulate matter (PM10, PM2.5, and PM1.0) and gaseous pollutants (H2S, SO2, and VOC) in the immediate vicinity of a large solid fuel-fired heat and power plant located in an urban agglomeration. Two locations were selected for analysis. The first was close to an air quality measurement station in the center of a multi-family housing estate. The second was the intersection of two main communication routes. To determine the impact of “low” and “high” emissions on air quality, the selected pollutants were measured at heights of between 2 and 50 m using an unmanned aerial vehicle. The results were compared with permissible standards for the concentration of pollutants. Temperature inversion was found to have a strong influence on the level of pollutants at various heights, with higher concentrations of particulate matter registered at altitudes above 40 m. The source of PM, H2S, and SO2 pollutants was confirmed to be “low emission” from local transport, industrial plant areas, and the housing estate comprising detached houses located in the vicinity of the measuring points. “High emission” was found to be responsible for the high concentrations of VOC at altitudes of more than 40 m above the intersection and in the area of the housing estate.

Energy Consumption and Health Insurance Premiums in China's Provinces: Evidence From Asymmetric Panel Causality Test

This article employs asymmetric panel causality test to address the causal nexus between energy consumption (EC) and healthcare insurance premiums (IP) for China's different provinces. The empirical results indicate that there exist asymmetric causality runs from positive EC shocks to positive healthcare IPs in Beijing, Hebei, Tianjin, Shanxi, Inner Mongolia, Shaanxi, Gansu, Qinghai, Ningxia, Shandong, Henan, and Anhui. There is no significant link in southern and northeastern provinces mainly because of their industrial structure, high economic development level, strong insurance consciousness, and climate conditions. Therefore, governments should encourage technological innovation and further improve energy efficiency. Meanwhile, we need to optimize EC structure and raise the proportion of renewable energies. The authorities should carry out stricter environmental protection policies and protect people from pollution that comes from fossil fuel burn. The commercial health insurance should be included in the health system and become an important supplement to public health insurance.

Spatial Analysis (Measurements at Heights of 10 m and 20 m above Ground Level) of the Concentrations of Particulate Matter (PM10, PM2.5, and PM1.0) and Gaseous Pollutants (H2S) on the University Campus: A Case Study

Spatial analysis of the distribution of particulate matter PM10, PM2.5, PM1.0, and hydrogen sulfide (H2S) gas pollution was performed in the area around a university library building. The reasons for the subject matter were reports related to the perceptible odor characteristic of hydrogen sulfide and a general poor assessment of air quality by employees and students. Due to the area of analysis, it was decided to perform measurements at two heights, 10 m and 20 m above ground level, using measuring equipment attached to a DJI Matrice 600 unmanned aerial vehicle (UAV). The aim of the measurements was air quality assessment and investigate the convergence of the theory of air flow around the building with the spatial distribution of air pollutants. Considerable differences of up to 63% were observed in the concentrations of pollutants measured around the building, especially between opposite sides, depending on the direction of the wind. To explain these differences, the theory of aerodynamics was applied to visualize the probable airflow in the direction of the wind. A strong convergence was observed between the aerodynamic model and the spatial distribution of pollutants. This was evidenced by the high concentrations of dust in the areas of strong turbulence at the edges of the building and on the leeward side. The accumulation of pollutants was also clearly noticeable in these locations. A high concentration of H2S was recorded around the library building on the side of the car park. On the other hand, the air turbulence around the building dispersed the gas pollution, causing the concentration of H2S to drop on the leeward side. It was confirmed that in some analyzed areas the permissible concentration of H2S was exceeded.