High-resolution emission inventory of gaseous and particulate pollutants in Shandong Province, eastern China

排放清单 环境科学 污染物 空气质量指数 氮氧化物 微粒 燃烧 环境工程 北京 化石燃料 中国 空气污染 环境保护 废物管理 气象学 地理 化学 工程类 考古 有机化学 生物 生态学
作者
Pei-Yu Jiang,Xiaoling Chen,Qiuyu Li,Haihua Mo,Lingyu Li
出处
期刊:Journal of Cleaner Production [Elsevier BV]
卷期号:259: 120806-120806 被引量:71
标识
DOI:10.1016/j.jclepro.2020.120806
摘要

To characterize the anthropogenic emissions of air pollutants (PM2.5, PM10, VOCs, NOx, SO2, and CO) in Shandong Province, eastern China, the high-resolution emission inventories were developed using the "bottom-up" methodology. The emission sources were categorized to biomass burning, dust, fossil fuel combustion, industrial processes, solvent utilization, waste disposal, and on-road vehicles, with five-level classification and 399 subclasses. Emission factors were collected from China's guidelines on the emissions of atmospheric pollutants and literatures with local measurements. Particularly, those for on-road vehicles were calculated by COPERT v5. The county-level activity data were obtained from the governmental statistics. Results showed that the estimated anthropogenic emissions of PM2.5, PM10, VOCs, NOx, SO2, and CO in Shandong Province in 2016 were 5136.8, 5685.4, 3257.1, 1430.6, 240.6, and 19618.8 kt, respectively. The main emission source of PM2.5 and PM10 were dust and it was industrial processes for VOCs and CO. On-road vehicles and fossil fuel combustion contributed the most to NOx and SO2 emissions, respectively. The composition of emissions by sources for each pollutant differed among cities. Emissions in Shandong displayed remarkable spatial variations, with the highest in the central, southern, and coastal areas. This study could be expected to supply sufficient information and basic data for formulating effective environmental management policies and further improving the air quality in Shandong Province and even in Beijing-Tianjin-Hebei region.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
萧瑟秋风今又是完成签到 ,获得积分10
1秒前
fanhuaxuejin完成签到 ,获得积分10
2秒前
老实的雨南关注了科研通微信公众号
3秒前
烟花应助积极的初晴采纳,获得10
4秒前
科研通AI6.2应助Summer采纳,获得10
4秒前
5秒前
JM关注了科研通微信公众号
6秒前
6秒前
6秒前
红猴果发布了新的文献求助10
6秒前
素简完成签到,获得积分10
7秒前
英姑应助负责的如萱采纳,获得10
8秒前
威武的海燕完成签到 ,获得积分10
9秒前
10秒前
10秒前
丁真人发布了新的文献求助10
11秒前
Lilly完成签到,获得积分10
12秒前
平城时代发布了新的文献求助10
12秒前
13秒前
英姑应助哇哈哈哈哈哈采纳,获得10
13秒前
另一个我完成签到,获得积分10
13秒前
14秒前
15秒前
15秒前
zzztsing0213完成签到,获得积分10
15秒前
纯情的阁发布了新的文献求助10
16秒前
乐乐应助怡然的凌兰采纳,获得10
16秒前
Jay完成签到,获得积分10
16秒前
思源应助李瑞程采纳,获得10
18秒前
纯情的阁发布了新的文献求助10
18秒前
wbbbb发布了新的文献求助10
18秒前
HUANG发布了新的文献求助10
18秒前
19秒前
ly发布了新的文献求助10
19秒前
19秒前
71发布了新的文献求助10
20秒前
20秒前
科研通AI2S应助科研通管家采纳,获得10
20秒前
20秒前
完美世界应助科研通管家采纳,获得10
20秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Principles of town planning: translating concepts to applications 1000
Management and the Arts 510
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
核安全综合知识2024版 500
Photothermal Science and Techniques 500
The Effective Clinical Neurologist 3ed 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7715295
求助须知:如何正确求助?哪些是违规求助? 9270476
关于积分的说明 20082239
捐赠科研通 7291644
什么是DOI,文献DOI怎么找? 3298452
关于科研通互助平台的介绍 2452617
邀请新用户注册赠送积分活动 2305889