Dataset Information

Evaluation of a data fusion approach to estimate daily PM2.5 levels in North China.

ABSTRACT: PM2.5 air pollution has been a growing concern worldwide. Previous studies have conducted several techniques to estimate PM2.5 exposure spatiotemporally in China, but all these have limitations. This study was to develop a data fusion approach and compare it with kriging and Chemistry Module. Two techniques were applied to create daily spatial cover of PM2.5 in grid cells with a resolution of 10km in North China in 2013, respectively, which was kriging with an external drift (KED) and Weather Research and Forecast Model with Chemistry Module (WRF-Chem). A data fusion technique was developed by fusing PM2.5 concentration predicted by KED and WRF-Chem, accounting for the distance from the central of grid cell to the nearest ground observations and daily spatial correlations between WRF-Chem and observations. Model performances were evaluated by comparing them with ground observations and the spatial prediction errors. KED and data fusion performed better at monitoring sites with a daily model R2 of 0.95 and 0.94, respectively and PM2.5 was overestimated by WRF-Chem (R2=0.51). KED and data fusion performed better around the ground monitors, WRF-Chem performed relative worse with high prediction errors in the central of study domain. In our study, both KED and data fusion technique provided highly accurate PM2.5. Current monitoring network in North China was dense enough to provide a reliable PM2.5 prediction by interpolation technique.

SUBMITTER: Liang F

PROVIDER: S-EPMC5612782 | biostudies-literature | 2017 Oct

REPOSITORIES: biostudies-literature

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Evaluation of a data fusion approach to estimate daily PM2.5 levels in North China.

Liang Fengchao F Gao Meng M Xiao Qingyang Q Carmichael Gregory R GR Pan Xiaochuan X Liu Yang Y

Environmental research 20170703

PM2.5 air pollution has been a growing concern worldwide. Previous studies have conducted several techniques to estimate PM2.5 exposure spatiotemporally in China, but all these have limitations. This study was to develop a data fusion approach and compare it with kriging and Chemistry Module. Two techniques were applied to create daily spatial cover of PM2.5 in grid cells with a resolution of 10km in North China in 2013, respectively, which was kriging with an ex ...[more]

PMID: 28599195

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Project description:Atmospheric fine particulate matter (PM2.5) causes severe haze in China and is regarded as a threat to human health. The health effects of PM2.5 vary location by location due to the variation in size distribution, chemical com position, and sources. In this study, the cytotoxicity effect, oxidative stress, and gene expression regulation of PM2.5 in Chengdu and Chongqing, two typical urban areas in southern China, were evaluated. Urban PM2.5 in summer and winter significantly inhibited cell viability and increased reactive oxygen species (ROS) levels in A549 cells. Notably, PM2.5 in winter exhibited higher cytotoxicity and ROS level than summer. Moreover, in this study, PM2.5 commonly induced cancer-related gene expression such as cell adhesion molecule 1(PECAM1), interleukin 24 (IL24), and cytochrome P450 (CYP1A1); meanwhile, PM2.5 commonly acted on cancer-related biological functions such as cell-substrate junction, cell-cell junction, and focal adhesion. In partic ular, PM2.5 in Chengdu in summer had the highest carcinogenic potential among PM2.5 at the two sites in summer and winter. Importantly, cancer-related genes were uniquely targeted by PM2.5, such as epithelial splicing regu latory protein 1 (ESRP1) and membrane-associated ring-CH-type finger 1 (1-Mar) by Chengdu summer PM2.5; collagen type IX alpha 3 chain (COL9A3) by Chengdu winter PM2.5; SH2 domain-containing 1B (SH2D1B) by Chongqing summer PM2.5; and interleukin 1 receptor-like 1 (IL1RL1) and zinc finger protein 42 (ZNF423) by Chongqing winter PM2.5. Meanwhile, important cancer-related biological functions were specially induced by PM2.5, such as cell cycle checkpoint by Chengdu summer PM2.5; macromolecule methylation by Chengdu win ter PM2.5; endoplasmic reticulum-Golgi intermediate compartment membrane by Chongqing summer PM2.5;and cellular lipid catabolic process by Chongqing winter PM2.5. Conclusively, in the typical urban areas of southern China, both summer and winter PM2.5 illustrated significant gene regulation effects. This study contrib utes to evaluating the adverse health effects of PM2.5 in southern China and providing public health suggestions for policymakers.

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Evaluation of a data fusion approach to estimate daily PM2.5 levels in North China.

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Evaluation of a data fusion approach to estimate daily PM<sub>2.5</sub> levels in North China.

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