A homogenized daily in situ PM<sub>2.5</sub> concentration dataset from the national air quality monitoring network in China
<p>In situ PM<span class="inline-formula"><sub>2.5</sub></span> concentration observations have long been used as critical data sources in haze-related studies. Due to the frequently occurring haze pollution events, China started to regularly monitor PM<spa...
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doaj-912d3e4a53ed4354b2ecc478786902fb2020-12-07T08:27:25ZengCopernicus PublicationsEarth System Science Data1866-35081866-35162020-11-01123067308010.5194/essd-12-3067-2020A homogenized daily in situ PM<sub>2.5</sub> concentration dataset from the national air quality monitoring network in ChinaK. Bai0K. Bai1K. Bai2K. Li3C. Wu4N.-B. Chang5J. Guo6Key Laboratory of Geographic Information Science (Ministry of Education), East China Normal University, Shanghai, ChinaInstitute of Eco-Chongming, 20 Cuiniao Rd., Chongming, Shanghai, ChinaSchool of Geographic Sciences, East China Normal University, Shanghai, ChinaSchool of Geographic Sciences, East China Normal University, Shanghai, ChinaSchool of Geographic Sciences, East China Normal University, Shanghai, ChinaDepartment of Civil, Environmental, and Construction Engineering, University of Central Florida, Orlando, FL, USAState Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing, China<p>In situ PM<span class="inline-formula"><sub>2.5</sub></span> concentration observations have long been used as critical data sources in haze-related studies. Due to the frequently occurring haze pollution events, China started to regularly monitor PM<span class="inline-formula"><sub>2.5</sub></span> concentration nationwide from the newly established air quality monitoring network in 2013. Nevertheless, the acquisition of these invaluable air quality samples is challenging given the absence of a publicly available data download interface. In this study, we provided a homogenized in situ PM<span class="inline-formula"><sub>2.5</sub></span> concentration dataset that was created on the basis of hourly PM<span class="inline-formula"><sub>2.5</sub></span> data retrieved from the China National Environmental Monitoring Center (CNEMC) via a web crawler between 2015 and 2019. Methods involving missing value imputation, change point detection, and bias adjustment were applied sequentially to deal with data gaps and inhomogeneities in raw PM<span class="inline-formula"><sub>2.5</sub></span> observations. After excluding records with limited samples, a homogenized PM<span class="inline-formula"><sub>2.5</sub></span> concentration dataset comprising of 1309 5-year long PM<span class="inline-formula"><sub>2.5</sub></span> data series at a daily resolution was eventually compiled. This is the first attempt to homogenize in situ PM<span class="inline-formula"><sub>2.5</sub></span> observations in China. The trend estimations derived from the homogenized dataset indicate a spatially homogeneous decreasing tendency of PM<span class="inline-formula"><sub>2.5</sub></span> across China at a mean rate of about <span class="inline-formula">−</span>7.6 % per year from 2015 to 2019. In contrast to raw PM<span class="inline-formula"><sub>2.5</sub></span> observations, the homogenized data record not only has complete data integrity but is more consistent over space and time. This homogenized daily in situ PM<span class="inline-formula"><sub>2.5</sub></span> concentration dataset is publicly accessible at <a href="https://doi.org/10.1594/PANGAEA.917557">https://doi.org/10.1594/PANGAEA.917557</a> (Bai et al., 2020a) and can be applied as a promising dataset for PM<span class="inline-formula"><sub>2.5</sub></span>-related studies such as satellite-based PM<span class="inline-formula"><sub>2.5</sub></span> mapping, human exposure risk assessment, and air quality management.</p>https://essd.copernicus.org/articles/12/3067/2020/essd-12-3067-2020.pdf |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
K. Bai K. Bai K. Bai K. Li C. Wu N.-B. Chang J. Guo |
spellingShingle |
K. Bai K. Bai K. Bai K. Li C. Wu N.-B. Chang J. Guo A homogenized daily in situ PM<sub>2.5</sub> concentration dataset from the national air quality monitoring network in China Earth System Science Data |
author_facet |
K. Bai K. Bai K. Bai K. Li C. Wu N.-B. Chang J. Guo |
author_sort |
K. Bai |
title |
A homogenized daily in situ PM<sub>2.5</sub> concentration dataset from the national air quality monitoring network in China |
title_short |
A homogenized daily in situ PM<sub>2.5</sub> concentration dataset from the national air quality monitoring network in China |
title_full |
A homogenized daily in situ PM<sub>2.5</sub> concentration dataset from the national air quality monitoring network in China |
title_fullStr |
A homogenized daily in situ PM<sub>2.5</sub> concentration dataset from the national air quality monitoring network in China |
title_full_unstemmed |
A homogenized daily in situ PM<sub>2.5</sub> concentration dataset from the national air quality monitoring network in China |
title_sort |
homogenized daily in situ pm<sub>2.5</sub> concentration dataset from the national air quality monitoring network in china |
publisher |
Copernicus Publications |
series |
Earth System Science Data |
issn |
1866-3508 1866-3516 |
publishDate |
2020-11-01 |
description |
<p>In situ PM<span class="inline-formula"><sub>2.5</sub></span> concentration observations have long been used as critical data
sources in haze-related studies. Due to the frequently occurring haze
pollution events, China started to regularly monitor PM<span class="inline-formula"><sub>2.5</sub></span>
concentration nationwide from the newly established air quality monitoring
network in 2013. Nevertheless, the acquisition of these invaluable air
quality samples is challenging given the absence of a publicly available data
download interface. In this study, we provided a homogenized in situ PM<span class="inline-formula"><sub>2.5</sub></span>
concentration dataset that was created on the basis of hourly PM<span class="inline-formula"><sub>2.5</sub></span>
data retrieved from the China National Environmental Monitoring Center
(CNEMC) via a web crawler between 2015 and 2019. Methods involving missing
value imputation, change point detection, and bias adjustment were applied
sequentially to deal with data gaps and inhomogeneities in raw PM<span class="inline-formula"><sub>2.5</sub></span>
observations. After excluding records with limited samples, a homogenized
PM<span class="inline-formula"><sub>2.5</sub></span> concentration dataset comprising of 1309 5-year long
PM<span class="inline-formula"><sub>2.5</sub></span> data series at a daily resolution was eventually compiled. This
is the first attempt to homogenize in situ PM<span class="inline-formula"><sub>2.5</sub></span> observations in China. The
trend estimations derived from the homogenized dataset indicate a spatially
homogeneous decreasing tendency of PM<span class="inline-formula"><sub>2.5</sub></span> across China at a mean rate of
about <span class="inline-formula">−</span>7.6 % per year from 2015 to 2019. In contrast to raw PM<span class="inline-formula"><sub>2.5</sub></span>
observations, the homogenized data record not only has complete data
integrity but is more consistent over space and time. This homogenized daily
in situ PM<span class="inline-formula"><sub>2.5</sub></span> concentration dataset is publicly accessible at
<a href="https://doi.org/10.1594/PANGAEA.917557">https://doi.org/10.1594/PANGAEA.917557</a> (Bai et al., 2020a) and can be
applied as a promising dataset for PM<span class="inline-formula"><sub>2.5</sub></span>-related studies such as
satellite-based PM<span class="inline-formula"><sub>2.5</sub></span> mapping, human exposure risk assessment, and air
quality management.</p> |
url |
https://essd.copernicus.org/articles/12/3067/2020/essd-12-3067-2020.pdf |
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