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

Meng, Ming; Zhou, Jin

doi:10.1016/j.ecolind.2020.106875

Cited by 28 publications

(13 citation statements)

References 40 publications

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“…Generally speaking, greenhouse gas emissions are determined by the technological level, affluence, energy structure, economic structure, population size, etc. The research scopes of decomposition analysis are broad, primarily including countries, regions, and industries (Chen et al 2018;Chai et al 2019;Meng and Zhou 2020).…”

Section: Introductionmentioning

confidence: 99%

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

Jin

Han

2021

Environ Sci Pollut Res

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The manufacturing industry directly reflects national productivity, and it is also an industry with serious carbon emissions, which has attracted wide attention. This study decomposes the influential factors on carbon emissions in China's manufacturing industry from 1995 to 2018 into industry value added (IVA), energy consumption (E), fixed asset investment (FAI), carbon productivity (CP), energy structure (EC), energy intensity (EI), investment carbon intensity (ICI) and investment efficiency (IE) by Generalized Divisia Index Model (GDIM). The decoupling analysis is carried out to investigate the decoupling states of the manufacturing industry under the pressure of "low carbon" and "economy." Considering the technological heterogeneity, we study the influential factors and decoupling status of the light industry and the heavy industry. The results show that: (1) Carbon emissions of the manufacturing industry present an upward trend, and the heavy industry is the main contributor. (2) Fixed asset investment (FAI), industry value added (IVA) are the driving forces of carbon emissions. Investment carbon intensity (ICI), carbon productivity (CP), investment efficiency (IE), and energy intensity (EI) have inhibitory effects. The impact of the energy consumption (E) and energy structure (EC) are fluctuating. (3) The decoupling state of the manufacturing industry has improved. Fixed asset investment (FAI), industry value added (IVA) hinder the decoupling; carbon productivity (CP), investment carbon intensity (ICI), investment efficiency (IE), and energy intensity (EI) promote the decoupling.

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Section: Introductionmentioning

confidence: 99%

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

Jin

Han

2021

Environ Sci Pollut Res

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“…It is noticed that Hebei's EC is nearly two times its GDP proportion, which means it has low energy efficiency and produces environmental pollution. This province owns heavy air pollution and occupies 5 of the top 10 cities with the poorest air quality in 2018 ( 60 ). The serious pollution and bad environment would endanger people's health, impede economic growth, weaken authority credibility, and decrease cities' attractiveness ( 61 ).…”

Section: Data and Empirical Resultsmentioning

confidence: 99%

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

Wang

Liu

Lobonţ

et al. 2021

Front. Public Health

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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.

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“…The maximum average annual emissions from the plant of PM10, PM2.5 and SO2 at 1.5 m above ground level are 0.013 μg/m 3 , 0.005 μg/m 3 , and 0.827 μg/m 3 , respectively. Measurements were made at three levels (20,35, and 50 m) above the intersection, using an DJI Matrice 600 Pro unmanned aerial vehicle (UAV) (MOT < 25 kg, diameter approximately 2 m) equipped with instruments for measuring particulate matter (PM10, PM2.5, PM1) and gas pollutants (H2S, SO2, and VOC). The minimum height of 20 m was chosen to ensure safe flight conditions over the traffic route, street lighting, and tram lines.…”

Section: Methodology Measurement Areamentioning

confidence: 99%

“…Sulphur dioxide is produced mainly by the combustion of solid and liquid fuels (e.g., coal, crude oil) contaminated with sulphur, in internal combustion engines, power plants, and combined heat and power plants. The largest proportion of sulphur dioxide comes from the fuel and energy industry-i.e., combustion processes in industry and combustion processes during energy production [20]. The amount of SO 2 introduced into the environment depends largely on the quality of the fuel.…”

Section: Introductionmentioning

confidence: 99%

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

Cichowicz

Dobrzański

2021

Energies

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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.

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

Cited by 28 publications

References 40 publications

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

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

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

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

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