A new method for interpolation of missing air quality data at monitor stations
文献类型：期刊论文
| 作者 | Xu, Chengdong1,2; Wang, Jinfeng1,2; Hu, Maogui2; Wang, Wei2 |
| 刊名 | ENVIRONMENT INTERNATIONAL
 |
| 出版日期 | 2022-11-01 |
| 卷号 | 169页码:8 |
| 关键词 | Interpolation Air quality dataset Heterogeneous population Sparse sample |
| ISSN号 | 0160-4120 |
| DOI | 10.1016/j.envint.2022.107538 |
| 通讯作者 | Hu, Maogui(humg@lreis.ac.cn) |
| 英文摘要 | Studies in environmental fields often suffer from air quality datasets incomplete at certain places and times. Here, a Spatial-Temporal Point Interpolation based on Biased Sentinel Hospitals Areal Disease Estimation (STPI-BSHADE) interpolation method was introduced to address this issue. The method was based on the spatial statistic trinity theory, where the statistical error is determined by the population properties, the condition of the sample, and the method of estimation. In our study, the spatial association of the variables was quantified by the covariance and the ratio of air quality data between stations, resulting in linear unbiased estimates of the missing data. STPI-BSHADE was compared with two widely used statistical methods, inverse distance weighting (IDW) and Kriging. Theoretically, IDW and Kriging are short of the capacity of using the heterogeneous characteristics of the population and remedying the sample bias. Empirically, the accuracy of the STPI-BSHADE method was assessed using hourly particulate matter 2.5 data, collected from May 13 to December 31, 2014, in the Beijing -Tianjin-Hebei areas, where air quality presents spatial heterogeneity. The experimental results also demonstrated that STPI-BSHADE significantly outperformed the traditional methods. |
| WOS关键词 | PM2.5 CONCENTRATIONS ; SPATIAL INTERPOLATION ; GLOBAL BURDEN ; POLLUTION ; EXPOSURE ; MORTALITY |
| 资助项目 | National Science Foundation of China ; National Key R & D Program of China ; [41971357] ; [42130713] ; [2018YFE0100100] ; [2020YFC1807404] |
| WOS研究方向 | Environmental Sciences & Ecology |
| 语种 | 英语 |
| WOS记录号 | WOS:000869108700013 |
| 出版者 | PERGAMON-ELSEVIER SCIENCE LTD |
| 资助机构 | National Science Foundation of China ; National Key R & D Program of China |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/186269]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Hu, Maogui |
| 作者单位 | 1.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 2.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing, Peoples R China |
| 推荐引用方式 GB/T 7714 | Xu, Chengdong,Wang, Jinfeng,Hu, Maogui,et al. A new method for interpolation of missing air quality data at monitor stations[J]. ENVIRONMENT INTERNATIONAL,2022,169:8. |
| APA | Xu, Chengdong,Wang, Jinfeng,Hu, Maogui,&Wang, Wei.(2022).A new method for interpolation of missing air quality data at monitor stations.ENVIRONMENT INTERNATIONAL,169,8. |
| MLA | Xu, Chengdong,et al."A new method for interpolation of missing air quality data at monitor stations".ENVIRONMENT INTERNATIONAL 169(2022):8. |
入库方式： OAI收割
来源：地理科学与资源研究所
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