Research data supporting ”Insight into PM2.5 sources by applying Positive Matrix factorization (PMF) at an urban and rural site of Beijing”

Dataset

Description

Atmospheric particulate matter (PM) is composed of various chemical components and can affect air quality, visibility, and ecosystems. Several studies have indicated that many adverse health outcomes, such as respiratory and cardiovascular morbidity and mortality, are related to long-term exposure to PM. This study was designed to perform the source apportionment of PM2.5 by applying positive matrix factorization (PMF) on data collected at an urban (Institute of Atmospheric Physics - IAP) and a rural site (Pinggu-PG) in Beijing as part of the Atmospheric Pollution and Human Health in a Chinese megacity (APHH-Beijing) field campaigns.
Date made available17 Sep 2021
PublisherUniversity of Birmingham

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