Source apportionment of PM2.5 concentrations with a Bayesian hierarchical model on latent source profiles
學年 108
學期 2
出版（發表）日期 2020-07-10
作品名稱 Source apportionment of PM2.5 concentrations with a Bayesian hierarchical model on latent source profiles
作品名稱（其他語言）
著者 Jia-Hong Tang; Shih-Chun Candice Lung; Jing-Shiang Hwang
單位
出版者
著錄名稱、卷期、頁數 Atmospheric Pollution Research 11(10), p. 1715-1727
摘要 Identifying realistic pollution source profiles and quantifying the contributions of atmospheric particulate matter are crucial for the development of pollution mitigation strategies to protect public health. In this paper, we proposed a multivariate source apportionment model by using a Bayesian framework for latent source profiles to incorporate expert knowledge regarding emissions that can facilitate source profile estimation, and atmospheric effects, such as meteorological conditions, can improve source concentration estimations. This approach can maintain positivity and summation constraints for source contributions and profiles. Furthermore, available expert knowledge regarding source profiles is incorporated as prior knowledge to avoid restrictive assumptions regarding the presence or absence of chemical constituent tracers in source profile modeling. We used long-term PM2.5 measurements collected from two locations with different environmental characteristics in northern Taiwan to demonstrate the feasibility of the proposed model and evaluated its performance by using simulated data.
關鍵字 Air pollution; Bayesian methods; Particulate matter; Source apportionment
語言 en_US
ISSN 1309-1042
期刊性質 國外
收錄於 SCI Scopus
產學合作
通訊作者 Jing-Shiang Hwang
審稿制度 是
國別 NLD
公開徵稿
出版型式 ,電子版
相關連結

機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/128431 )

SDGS 永續城市與社區,氣候行動,夥伴關係,良好健康和福祉,優質教育