STUDIES ON CONTRIBUTION DECISION FOR FAST SIMULATION OF AIR POLLUTION SOURCES OPTMIZATION BASED ON INTEGER PROGRAMMING ALGORITHM

CUI Jiansheng; SANG Minjie; BO Xin; WANG Peng; XUE Xiaoda; GUO Jing; LEI Tuantuan; QU Jiabao; WANG Chengxin; LU Ruijuan; LI Shibei; REN Lihong

doi:10.13205/j.hjgc.202204029

Volume 40 Issue 4

Apr. 2022

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Article Navigation > ENVIRONMENTAL ENGINEERING > 2022 > 40(4): 202-208

CUI Jiansheng, SANG Minjie, BO Xin, WANG Peng, XUE Xiaoda, GUO Jing, LEI Tuantuan, QU Jiabao, WANG Chengxin, LU Ruijuan, LI Shibei, REN Lihong. STUDIES ON CONTRIBUTION DECISION FOR FAST SIMULATION OF AIR POLLUTION SOURCES OPTMIZATION BASED ON INTEGER PROGRAMMING ALGORITHM[J]. ENVIRONMENTAL ENGINEERING , 2022, 40(4): 202-208. doi: 10.13205/j.hjgc.202204029

Citation:

CUI Jiansheng, SANG Minjie, BO Xin, WANG Peng, XUE Xiaoda, GUO Jing, LEI Tuantuan, QU Jiabao, WANG Chengxin, LU Ruijuan, LI Shibei, REN Lihong. STUDIES ON CONTRIBUTION DECISION FOR FAST SIMULATION OF AIR POLLUTION SOURCES OPTMIZATION BASED ON INTEGER PROGRAMMING ALGORITHM[J]. ENVIRONMENTAL ENGINEERING , 2022, 40(4): 202-208. doi: 10.13205/j.hjgc.202204029

Citation:

CUI Jiansheng, SANG Minjie, BO Xin, WANG Peng, XUE Xiaoda, GUO Jing, LEI Tuantuan, QU Jiabao, WANG Chengxin, LU Ruijuan, LI Shibei, REN Lihong. STUDIES ON CONTRIBUTION DECISION FOR FAST SIMULATION OF AIR POLLUTION SOURCES OPTMIZATION BASED ON INTEGER PROGRAMMING ALGORITHM[J]. ENVIRONMENTAL ENGINEERING , 2022, 40(4): 202-208. doi: 10.13205/j.hjgc.202204029

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STUDIES ON CONTRIBUTION DECISION FOR FAST SIMULATION OF AIR POLLUTION SOURCES OPTMIZATION BASED ON INTEGER PROGRAMMING ALGORITHM

doi: 10.13205/j.hjgc.202204029

1. School of Environmental Science and Engineering, Hebei University of Science and Technology, Shijiazhuang 050018, China;
2. Department of Environmental Science and Engineering, Beijing University of Chemical Technology, Beijing 100029, China;
3. BUCT Institute for Carbon-neutrality of Chinese Industries, Beijing 100029, China;
4. 3Clear Technology Co., Ltd, Beijing 100020, China;
5. School of Economics and Management, Beihang University, Beijing 100191, China;
6. Appraisal Center for Environment and Engineering, Ministry of Ecology and Environment, Beijing 100012, China;
7. School of Architecture and Environment, Sichuan University, Chengdu 610065, China;
8. Environmental Protection Science Research Institute of Cangzhou City, Cangzhou 061000, China;
9. Chinese Academy of Environmental Sciences, Beijing 100012, China

Received Date: 2021-07-30
Available Online: 2022-07-06

Abstract

Abstract

Based on the results of the air quality model and the 0~1 integer programming algorithm, the multi-scenario rapid response decision model of emission factors and pollutants’ environmental concentration was established, which realized the rapid decision of the adjustment plan of air pollutant emission sources under the air pollution control target. The model was applied to the high-speed enclosed area of Cangzhou, Hebei. Based on the AERMOD simulation results of atmospheric primary PM₁₀ in 2018, the contribution of each emission source to the national controlled point pollution in the enclosed area was analyzed, and the optimal source group control solution was obtained when the total contribution concentration value was adjusted. The results showed that among the particulate matter emission sources in Cangzhou expressway enclosed area, the contribution of road sources to national controlled points pollution was the highest, followed by non-road mobile sources. In addition, it was optimal to control the source groups of provincial road in Xinhua Distric and soil dust in Yunhe District under the goal of minimizing the total emission in the confined area and reducing the contribution concentration of national control points (Municipal Environmental Protection Bureau Station, Cangxian Urban Construction Bureau Station and TV Transmission Station) by at least 1.5 μg/m³, the total emission of source groups was 791.30 t/a, with a decrease of 15.66 t/a; the average annual contribution concentration of each control point was 7.80 μg/m³, 10.09 μg/m³ and 7.87 μg/m³, decreased by 1.75 μg/m³, 2.00 μg/m³ and 1.52 μg/m³, respectively. This research method realized the rapid effect evaluation under the given air pollution source adjustment plan, and gave the optimal emission reduction plan.
- air pollution control,
- decision support tool,
- 0~1 integer programming,
- source contribution analysis

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References(40)

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