Estimation of exposure and premature mortality from near-roadway fine particulate matter concentrations emitted by heavy-duty diesel trucks in Beijing

北京 卡车 环境科学 微粒 柴油 人口 环境卫生 暴露评估 环境工程 排放清单 气象学 环境保护 地理 空气质量指数 废物管理 医学 工程类 生态学 生物 航空航天工程 考古 中国
作者
Beibei Zhang,Shifen Cheng,Feng Lu,Mei Lei
出处
期刊:Environmental Pollution [Elsevier]
卷期号:311: 119990-119990 被引量:1
标识
DOI:10.1016/j.envpol.2022.119990
摘要

Traffic exhaust is a main source of fine particulate matter (PM2.5) in cities. Heavy-duty diesel trucks (HDDTs), the primary mode of freight transport, contribute significantly to PM2.5, posing a great threat to public health. However, existing research based on dispersion models to simulate pollutant concentrations lacks high-spatiotemporal-resolution emission inventories of HDDTs as input data, and the public health effects of such emissions in different populations have not been thoroughly assessed. To fill this gap, we focused on Beijing as the research area and developed a high-resolution PM2.5 emission inventory for HDDTs based on Global Navigation Satellite System-equipped vehicle trajectory data. We then simulated the fine-scale spatial distribution of diesel-related PM2.5 and assessed the population exposure by integrating the dispersion model and population distributions. Further, we quantified the mortality attributable to noncommunicable diseases (NCDs) plus lower respiratory infections (LRIs) related to PM2.5 emissions from HDDTs. Results showed that 3.3% of Beijing people lived in areas with high PM2.5 HDDT emissions, which were near intercity highways. Furthermore, the estimated number of NCD + LRI annual premature deaths attributed to PM2.5 HDDT emissions in Beijing was 339 (95% CI: 276-401). The NCD + LRI mortality increased with age, and deaths were more frequent in males than females. Our results aid the identification of HDDT PM2.5 emission exposure hotspots for the formulation of effective mitigation measures and provide important insights into the adverse health impacts of HDDT emissions.
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
刚刚
紫紫吃菠菜完成签到,获得积分10
1秒前
2秒前
2秒前
哈哈哈完成签到 ,获得积分10
3秒前
vvdd发布了新的文献求助10
4秒前
4秒前
情怀应助石籽采纳,获得10
4秒前
老丫大侠完成签到 ,获得积分10
5秒前
Jasper应助兮阳采纳,获得10
5秒前
耍酷芙蓉发布了新的文献求助10
5秒前
武雨寒发布了新的文献求助10
6秒前
7秒前
今后应助生产队的建设者采纳,获得10
8秒前
Lucas应助完美亦云采纳,获得10
9秒前
爆米花应助always采纳,获得10
9秒前
niuhuhu发布了新的文献求助30
9秒前
关节软骨完成签到,获得积分20
9秒前
思源应助。.。采纳,获得10
10秒前
弄香完成签到,获得积分10
11秒前
11秒前
ZHANGJIAN完成签到 ,获得积分10
12秒前
MchemG应助是程璐啦采纳,获得100
12秒前
12秒前
13秒前
hamzhang0426发布了新的文献求助10
14秒前
14秒前
sisyphus发布了新的文献求助10
16秒前
招水若离完成签到,获得积分10
17秒前
自由文博完成签到 ,获得积分10
17秒前
一一发布了新的文献求助10
17秒前
朴实山兰发布了新的文献求助10
18秒前
19秒前
19秒前
19秒前
21秒前
幸福的雪枫完成签到 ,获得积分10
22秒前
汉堡包应助sisyphus采纳,获得10
22秒前
SciGPT应助走四方采纳,获得10
22秒前
FashionBoy应助sisyphus采纳,获得10
22秒前
高分求助中
Востребованный временем 2500
Agaricales of New Zealand 1: Pluteaceae - Entolomataceae 1040
Healthcare Finance: Modern Financial Analysis for Accelerating Biomedical Innovation 1000
지식생태학: 생태학, 죽은 지식을 깨우다 600
海南省蛇咬伤流行病学特征与预后影响因素分析 500
Neuromuscular and Electrodiagnostic Medicine Board Review 500
ランス多機能化技術による溶鋼脱ガス処理の高効率化の研究 500
热门求助领域 (近24小时)
化学 医学 材料科学 生物 工程类 有机化学 生物化学 纳米技术 内科学 物理 化学工程 计算机科学 复合材料 基因 遗传学 物理化学 催化作用 细胞生物学 免疫学 电极
热门帖子
关注 科研通微信公众号,转发送积分 3463229
求助须知:如何正确求助?哪些是违规求助? 3056638
关于积分的说明 9053048
捐赠科研通 2746497
什么是DOI,文献DOI怎么找? 1506946
科研通“疑难数据库(出版商)”最低求助积分说明 696243
邀请新用户注册赠送积分活动 695849