东北地区非道路移动源排放清单研究及情景预测

doi:10.12068/j.issn.1005-3026.2021.03.009

东北大学学报（自然科学版） ›› 2021, Vol. 42 ›› Issue (3): 358-366.DOI: 10.12068/j.issn.1005-3026.2021.03.009

东北地区非道路移动源排放清单研究及情景预测

高成康^{1, 2}，由焕^{1, 2}，巴乔^{1, 2}，梁程序³

(1. 东北大学冶金学院，辽宁沈阳110819; 2. 东北大学国家环境保护生态工业重点实验室，辽宁沈阳110819; 3. 美的集团生活电器事业部，广东佛山528000)

收稿日期:2020-08-17 修回日期:2020-08-17 接受日期:2020-08-17 发布日期:2021-03-12
通讯作者: 高成康
作者简介:高成康(1977-)，女，河南周口人，东北大学教授.
基金资助:
国家重点研发计划项目(2017YFC0212303-03)；国家自然科学基金资助项目(41871212).

Study on a Non-road Mobile Source Emission Inventory and Scenario Prediction in Northeast China

GAO Cheng-kang^{1, 2}， YOU Huan^{1, 2}， BA Qiao^{1, 2}， LIANG Cheng-xu³

1. School of Metallurgy， Northeastern University， Shenyang 110819， China; 2. SEP Key Laboratory of Eco-industry， Northeastern University， Shenyang 110819， China; 3. Midea Group Life Electrical Business Unit， Foshan 528000， China.

Received:2020-08-17 Revised:2020-08-17 Accepted:2020-08-17 Published:2021-03-12
Contact: YOU Huan
About author:-
Supported by:
-

摘要/Abstract

摘要： 与其他地区相比，东北地区冬季低温漫长，有其非道路移动源大气污染物排放清单的独自特征.本文将东北地区分成辽宁省城市群和哈长城市群进行分析.首先，基于《非道路移动源大气污染物排放清单编制技术指南》(试行)中的排放因子法建立非道路移动源排放清单，分析其排放以及时空分布特征.其次，结合相关政策目标基于情景分析预测2030年的排放.最后，提出合理的减排建议.结果表明:1)东北地区非道路移动源PM₁₀，PM_2.5，NO_○x，THC和CO排放量分别是13.0×10³，12.5×10³，205.6×10³，37.0×10³和101.1×10³ t;2)两城市群工程机械占比最大，分别为44.5%和44.8%;3)在基准控制情景和强化控制情景下，总体减排效果可提高50%以上.

关键词: 非道路移动源;大气污染物;排放清单;时空特征;减排情景预测

Abstract: Compared with other regions， Northeast China has its unique characteristics of non-road mobile source emission inventories due to its long and cold winter. In this paper， the analysis was divided into Liaoning Province and Harbin-Changchun Megalopolis. Firstly， the emission inventory of non-road mobile sources was established based on technical guide for preparation of air pollutant emission list of non-road mobile sources (trial)， and its emission and spatial-temporal distribution characteristics were analyzed. Secondly， the emissions in 2030 were forecasted based on the scenario analysis， taking into account of the relevant policy objectives. Finally， reasonable emission reduction recommendations were made. The results show that: 1) the emissions of PM₁₀， PM_2.5， NO_○x， THC， and CO were 13.0×10³， 12.5×10³， 205.6×10³， 37.0×10³ and 101.1×10³ t， respectively; 2) construction machinery accounts for the largest share of emissions in the two urban agglomerations with 44.5%and 44.8%， respectively; 3) the overall emission reduction can be improved by more than 50% under both the baseline scenario and the enhanced control scenario.

Key words: non-road mobile source; air pollution; emission inventory;spatial-temporal characteristics; emission reduction scenario prediction

中图分类号:

X511

高成康，由焕，巴乔，梁程序. 东北地区非道路移动源排放清单研究及情景预测[J]. 东北大学学报（自然科学版）, 2021, 42(3): 358-366.

GAO Cheng-kang ， YOU Huan ， BA Qiao ， LIANG Cheng-xu. Study on a Non-road Mobile Source Emission Inventory and Scenario Prediction in Northeast China[J]. Journal of Northeastern University(Natural Science), 2021, 42(3): 358-366.

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东北地区非道路移动源排放清单研究及情景预测

Study on a Non-road Mobile Source Emission Inventory and Scenario Prediction in Northeast China

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