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

被引：18

作者：

Xiao, Cuicui ^{[1
]}

Chang, Miao ^{[2
]}

Guo, Peikun ^{[2
]}

Yuan, Mengyun ^{[2
]}

Xu, Chongqi ^{[2
]}

Song, Xinhua ^{[2
]}

Xiong, Xueying ^{[2
]}

Li, Yang ^{[2
]}

Li, Zequn ^{[2
]}

机构：

[1] Univ Sci & Technol Beijing, Sch Humanities & Social Sci, Beijing 100083, Peoples R China

[2] Tsinghua Univ, Sch Environm, Beijing 100084, Peoples R China

来源：

ATMOSPHERIC POLLUTION RESEARCH | 2020年 / 11卷 / 01期

基金：

中国国家自然科学基金;

关键词：

Air pollution transmission channel cities; Industrial emission; Characteristic analysis; Emission intensity; Data mining; AIR-POLLUTION CONTROL; YANGTZE-RIVER DELTA; INTENSITY; CHINA; POLLUTANTS; PREVENTION; EFFICIENCY; QUALITY; PM2.5;

D O I：

10.1016/j.apr.2019.08.008

中图分类号：

X [环境科学、安全科学];

学科分类号：

08 ; 0830 ;

摘要：

Cities of Beijing-Tianjin-Hebei (BTH) and its surrounding areas are a focus of air pollution control in China. This study analyzed the emission characteristics of industrial pollution sources within these cities from the perspective of big data, using 37,123,000 continuous monitoring data for enterprises in 31 cities. Three indicators were proposed to compare the spatial emission characteristics: industrial pollutant emission intensity (IPEI), industrial pollution concentration emission intensity (IPCEI) and the density of waste gas monitoring enterprise (DWGME). The IPEI and IPCEI of Yangquan, Taiyuan, Changzhi, Xingtai, Handan, and Hebi were considerably higher than the average level of the air pollution transmission channel cities (APTCC). The industrial SO2 concentration emission intensity in Yangquan, Hebi, Laiwu were 1826.9, 462.8, 301.4 mg m(-3) per trillion yuan, more than twice the regional average for the 31 cities. We found there was a significant positive correlation between different industrial pollutants in the BTH and surrounding areas. Industrial SO2 emission have a positive correlation with industrial NOx emission in most of BTH cities, the correlation in Xingtai, Hengshui, Taiyuan were respectively 0.855, 0.969,0.696. Data mining and statistics on different time scales could be used to analyze the characteristics of industrial atmospheric emission sources, and could be applied in environmental decision support systems to make air pollution management more objective, reliable, and powerful.

引用

页码：11 / 26

页数：16

共 59 条

[1] Industrial characteristics and air emissions: Long-term determinants in the UK manufacturing sector [J].

Agnolucci, Paolo ;

Arvanitopoulos, Theodoros .

ENERGY ECONOMICS, 2019, 78 :546-566

[2]

[Anonymous], J CLEAN PROD

[3]

[Anonymous], 2017, NAT ENVIRON POLLUT T

[4] Cleaner firms or cleaner products? How product mix shapes emission intensity from manufacturing [J].

Barrows, Geoffrey ;

Ollivier, Helene .

JOURNAL OF ENVIRONMENTAL ECONOMICS AND MANAGEMENT, 2018, 88 :134-158

[5]

Central Pollution Control Board of India Bangalore, 2010, AIR QUAL MON EM INV

[6]

Chai F.H., 2013, ENV PROT, V41, P22

[7]

[陈青 Chen Qing], 2017, [环境污染与防治, Environmental Pollution & Control], V39, P336

[8]

China State Council, 2018, WINN 3 YEAR ACT PLAN

[9] Energy Management in a Manufacturing Industry through Layout Design [J].

Fahad, Muhammad ;

Naqvi, Syed Asad Ali ;

Atir, Muhammad ;

Zubair, Muhammad ;

Shehzad, Muhammad Musharaf .

14TH GLOBAL CONFERENCE ON SUSTAINABLE MANUFACTURING, GCSM 2016, 2017, 8 :168-174

[10]

Findley DF, 1998, J BUS ECON STAT, V16, P127, DOI 10.2307/1392565

← 1 2 3 4 5 6 →