Characteristics analysis of industrial atmospheric emission sources in Beijing–Tianjin–Hebei and Surrounding Areas using data mining and statistics on different time scales

Xiao, Cuicui; Miao, Chang; Guo, Peikun; Yuan, Ming; Xu, Chongqi; Song, Xiaozhen; Xiong, Xueying; Li, Yang; Li, Zequn

doi:10.1016/j.apr.2019.08.008

Cited by 19 publications

(8 citation statements)

References 28 publications

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“…The investigation of industrial parks is important for China's air quality improvement and carbon neutrality goals. Henan Province is one of the most polluted provinces in China [20], in which seven cities are located in the transmission channel [21] of Beijing-Tianjin-Hebei (BTH) [22]. Although the Chinese government and the Henan provincial government have introduced a series of policies to reduce air pollutants and CO 2 emissions from industrial parks, aimed at improving regional air quality and achieving a carbon peak and carbon neutrality ahead of schedule, there is still a lack of research on the potential for emission reduction and air quality improvement.…”

Section: Introductionmentioning

confidence: 99%

Air Pollutants and CO2 Emissions in Industrial Parks and Evaluation of Their Green Upgrade on Regional Air Quality Improvement: A Case Study of Seven Cities in Henan Province

Hei

Gao

et al. 2022

Atmosphere

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Although central to the promotion of regional economic development, industrial parks discharge large quantities of air pollutants and CO2, counter to the goals of air quality improvement and CO2 reductions in China. In this study, 13 industrial parks in seven cities in Henan Province were chosen to evaluate their emission of air pollutants and CO2 in 2017, their reduction potential under different green measures, and their air quality improvements under a Green Upgrade scenario. The results show that: (1) The total emissions of SO2, NOx, CO, PM10, PM2.5, VOCs and CO2 in the 13 industrial parks were 43, 39, 351, 19, 7, 18, 2 kt and 36 Mt, and would decrease by 72, 56, 19, 30, 26, 77 and 30%, respectively, under the Green Upgrade scenario. (2) The industrial process was the major source of CO, PM2.5, VOCs and NH3, whereas power plants were the largest source of SO2 and NOx, and they would be reduced by 93, 59, 94, 91, 23 and 28%, respectively, under the Green Upgrade scenario. (3) The terminal energy use sector (including industrial boilers and industrial process sources) was the main source of CO2, accounting for 75% of total CO2 emissions, and would be reduced by 76% under the Green Upgrade scenario. (4) WRF-CMAQ simulation results show that, under the Green Upgrade scenario, the concentration of PM2.5 in a transmission channel city would be improved by 1–36 μg/m3, with an annual average value of 9 μg/m3. Our results demonstrate the significant effect of the synergistic reduction in air pollutants and CO2 emissions using Green Technologies in industrial parks and the subsequent improvement in regional air quality.

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Section: Introductionmentioning

confidence: 99%

Air Pollutants and CO2 Emissions in Industrial Parks and Evaluation of Their Green Upgrade on Regional Air Quality Improvement: A Case Study of Seven Cities in Henan Province

Hei

Gao

et al. 2022

Atmosphere

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“…-Industrial processes and product use: NMVOC (44%) and PM2.5 (12%) -Energy use in industry: SOx (20%) and NOx (12%) -Road transport: NOx (36%) and PM2.5 (11%) -Non road transport: NOx (9%) Overall, this condition has generated a strong impact on environmental quality, with positive effects on numerous environmental matrices such as soil and water [32,33], but also negative, for example on waste management [34,35]. Since there is a direct relationship between human activities and emissions of air pollutants, this blocking condition has favoured a significant improvement in environmental quality [36][37][38][39][40][41][42][43][44]. [45][46][47].…”

Section: Introductionmentioning

confidence: 99%

“…34,35 Since there is a direct relationship between human activities and emissions of air pollutants, this blocking condition has favored a significant improvement in environmental quality. [36][37][38][39][40][41][42][43][44][45][46][47] In order to understand the (positive or negative) effect of environmental and socio-economic factors on air quality, approaches are needed that make it possible to connect these aspects, providing an overall assessment in particular of the effect of policies and strategies for improving the air quality. As described by Wang et al, 48 some commonly used approaches include regression analysis, spatial econometric models, Environmental Kuznets Curve (EKC), 49 and many others.…”

Section: Introductionmentioning

confidence: 99%

How changes in human activities during the lockdown impacted air quality parameters: A review

Marinello

Butturi

Gamberini

2021

Env Prog and Sustain Energy

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The health emergency linked to the spread of COVID-19 has led to important reduction in industrial and logistics activities, as well as to a drastic changes in citizens' behaviours and habits. The restrictions on working activities, journeys and relationships imposed by the lockdown have had important consequences, including for environmental quality. This review aims to provide a structured and critical evaluation of the recent scientific bibliography that analysed and described the impact of lockdown on human activities and on air quality. The results indicate an important effect of the lockdown during the first few months of 2020 on air pollution levels, compared to previous periods. The concentrations of particulate matter, nitrogen dioxide, sulphur dioxide and carbon monoxide have decreased. Tropospheric ozone, on the other hand, has significantly increased. These results are important indicators that can become decision drivers for future policies and strategies in industrial and logistics activities (including the mobility sector) aimed at their environmental sustainability. The scenario imposed by COVID-19 has supported the understanding of the link between the reduction of polluting emissions and the state of air quality and will be able to support strategic choices for the future sustainable growth of the industrial and logistics sector.This article has been accepted for publication and undergone full peer review but has not been through the copyediting, typesetting, pagination and proofreading process which may lead to differences between this version and the Version of Record. Please cite this article as

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“…In 2019, 168 cities participated in an air quality index (AQI) evaluation; 16 of the 20 cities with the worst air quality were located in the BTH "2+26" cities, including Anyang, Xingtai, Shijiazhuang, Handan, Tangshan, Taiyuan, Zibo, Jiaozuo, Jincheng, Baoding, Jinan, Liaocheng, 15, and 40 μg/m 3 . Highly polluting activities, such as steel making, iron making, and coking, alongside the cement, coal, and chemical industries are concentrated in the BTH and its surrounding areas [35]. The exposure pattern of the BTH cities showed that Beijing was prone to the highest air quality population exposure.…”

Section: Introductionmentioning

confidence: 99%

Industrial agglomeration and air pollution: A new perspective from enterprises in Atmospheric Pollution Transmission Channel Cities (APTCC) of Beijing-Tianjin-Hebei and its surrounding areas, China

et al. 2021

Self Cite

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Air quality in China has gradually been improving in recent years; however, the Beijing-Tianjin-Hebei (BTH) region continues to be the most polluted area in China, with the worst air quality index. BTH and its surrounding areas experience high agglomeration of heavy-polluting manufacturers that generate electric power, process petroleum and coal, and carry out smelting and pressing of ferrous metals, raw chemical materials, chemical products, and non-metallic mineral products. This study presents evidence of the air pollution impacts of industrial agglomeration using the Ellison–Glaeser index, Herfindahl–Hirschman index, and spatial autocorrelation analysis. This was based on data from 73,353 enterprises in “2+26” atmospheric pollution transmission channel cities in BTH and its surrounding areas (herein referred to as BTH “2+26” cities). The results showed that Beijing, Yangquan, Puyang, Kaifeng, Taiyuan, and Jinan had the highest Ellison–Glaeser index among the BTH “2+26” cities; this represents the highest enterprise agglomeration. Beijing, Langfang, Tianjin, Baoding, and Tangshan also showed a low Herfindahl–Hirschman index of pollutant emissions, which have a relatively high degree of industrial agglomeration in BTH “2+26” cities. There was an inverted U-shaped relationship between enterprise agglomeration and air quality in the BTH “2+26” cities. This means that air quality improved with increased industrial agglomeration up to a certain level; beyond this point, the air quality begins to deteriorate with a decrease in industrial agglomeration.

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Characteristics analysis of industrial atmospheric emission sources in Beijing–Tianjin–Hebei and Surrounding Areas using data mining and statistics on different time scales

Cited by 19 publications

References 28 publications

Air Pollutants and CO2 Emissions in Industrial Parks and Evaluation of Their Green Upgrade on Regional Air Quality Improvement: A Case Study of Seven Cities in Henan Province

Air Pollutants and CO2 Emissions in Industrial Parks and Evaluation of Their Green Upgrade on Regional Air Quality Improvement: A Case Study of Seven Cities in Henan Province

How changes in human activities during the lockdown impacted air quality parameters: A review

Industrial agglomeration and air pollution: A new perspective from enterprises in Atmospheric Pollution Transmission Channel Cities (APTCC) of Beijing-Tianjin-Hebei and its surrounding areas, China

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