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尼泊尔巴克塔普尔市道路运输排放量估算。

Estimating Emission Load from Road Transportation within the Bhaktapur Municipality, Nepal.

机构信息

Khwopa College, Bhaktapur, Nepal.

Nepal Academy of Science and Technology (NAST), Lalitpur, Nepal.

出版信息

J Environ Public Health. 2020 Nov 6;2020:2828643. doi: 10.1155/2020/2828643. eCollection 2020.

DOI:10.1155/2020/2828643
PMID:33204281
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7665925/
Abstract

Vehicular emissions have been playing a pivotal role in deteriorating air quality in many urban parts of Nepal causing adverse impacts upon the health of commuters and pedestrians attributed to severe respiratory diseases. Primary data such as the number of vehicles () were obtained using two-hour peak (8 am to 10 am) and two-hour nonpeak (1 pm to 3 pm) count, after which average annual vehicle kilometer (VKT) and fuel economy () required for emission load estimation were obtained from vehicle survey using the simple random sampling method, sampling size taken statistically under 5% margin of error. Secondary data in this study include emission factors and derived equations from a published article. The vehicular emission load of Bhaktapur Municipality were found to be 3,310 tons/year including CO, CO, NOx, HC, and PM of which CO accounts for 94.36% of total emissions followed by CO (4.39%), HC (0.72%), NOx (0.35%), and PM (0.18%), respectively. Significant positive correlation was found ( = 0.92, =0.002) between CO and PM ( = 0.87, =0.009), between CO and NOx ( = 0.90, =0.004), between CO and HC ( = 0.74, =0.05), and between NOx and PM, respectively. The scenario analysis shows that the introduction of electric vehicles at different rates within the municipality can reduce the emissions to a significant amount. Exponential growth in vehicular gaseous pollutants potent to jeopardize the environment and welfare can become inevitable in the future if clean energy technology is not promoted early.

摘要

车辆排放物在尼泊尔许多城市地区的空气质量恶化中起着关键作用,导致通勤者和行人的健康受到严重的呼吸道疾病的影响。主要数据,如车辆数量(),是通过两小时高峰(8 点至 10 点)和两小时非高峰(1 点至 3 点)计数获得的,之后使用简单随机抽样方法从车辆调查中获得了排放负荷估算所需的平均年车辆公里数(VKT)和燃料经济性(),抽样大小在 5%的误差幅度下进行了统计。本研究中的次要数据包括排放因子和从已发表文章中推导出的方程。发现巴克拉塔布尔市的车辆排放负荷为 3310 吨/年,包括 CO、CO、NOx、HC 和 PM,其中 CO 占总排放量的 94.36%,其次是 CO(4.39%)、HC(0.72%)、NOx(0.35%)和 PM(0.18%)。发现 CO 和 PM( = 0.92,=0.002)、CO 和 NOx( = 0.90,=0.004)、CO 和 HC( = 0.74,=0.05)以及 NOx 和 PM 之间存在显著的正相关关系。情景分析表明,在自治市以不同的速度引入电动汽车可以显著减少排放。如果不早期推广清洁能源技术,未来车辆气态污染物的指数增长可能会对环境和福利造成威胁。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/aa4e/7665925/9a7f98755957/JEPH2020-2828643.005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/aa4e/7665925/f331a303af9e/JEPH2020-2828643.001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/aa4e/7665925/a41dba774d63/JEPH2020-2828643.002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/aa4e/7665925/6f9d6eb91f66/JEPH2020-2828643.003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/aa4e/7665925/5b7b4a15769e/JEPH2020-2828643.004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/aa4e/7665925/9a7f98755957/JEPH2020-2828643.005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/aa4e/7665925/f331a303af9e/JEPH2020-2828643.001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/aa4e/7665925/a41dba774d63/JEPH2020-2828643.002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/aa4e/7665925/6f9d6eb91f66/JEPH2020-2828643.003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/aa4e/7665925/5b7b4a15769e/JEPH2020-2828643.004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/aa4e/7665925/9a7f98755957/JEPH2020-2828643.005.jpg

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