Estimating daily and intra-daily PM10 and PM2.5 in Israel using a spatio-temporal hybrid modeling approach. (October 2018)

• Record Type: Journal Article
• Authors: Shtein, Alexandra; Karnieli, Arnon; Katra, Itzhak; Raz, Raanan; Levy, Ilan; Lyapustin, Alexei; Dorman, Michael; Broday, David M.; Kloog, Itai
• Is Part Of: Atmospheric environment. Volume 191(2018)
• Page Start: 142
• Page End: 152
• Publication Date: 2018-10
• Subjects: Air pollution -- PM10 -- PM2.5 -- Intra-daily estimation -- Aerosol optical depth (AOD) -- MAIAC; Air -- Pollution -- Periodicals; Air -- Pollution -- Meteorological aspects -- Periodicals; 551.51
• DOI: 10.1016/j.atmosenv.2018.08.002
• Languages: English
• ISSNs: 1352-2310

Abstract

Abstract: Satellite-based particulate matter (PM) models provide spatially and temporally resolved estimations, allowing greater spatial-temporal coverage compared to sparse ground monitoring stations. The spatio-temporal resolution of these models can be improved using aerosol optical depth (AOD) products from various satellite platforms with different overpass times which can capture possible changes in diurnal aerosol concentrations. Israel is characterized by diverse geo-climatic regions and it is subjected to frequent dust storms events. Our goal was to estimate PM10 and PM2.5 concentrations in Israel on daily and intra-daily (mean PM around the Aqua and Terra overpasses) temporal resolutions and to assess the differences between these time windows. A hybrid modeling approach that consists of three stages was used enabling spatially continuous PM estimations at 1 × 1 km spatial resolution. The model was calibrated on a daily basis applying a mixed modeling approach using MODIS-based MAIAC AOD and various spatial and temporal predictors. It was found that in certain urban areas the measured and estimated PM concentrations during the satellite overpass (Terra or Aqua) were higher than the mean daily PM. The models performed well showing cross-validated R 2 that ranged between 0.82 and 0.92. Mean estimated PM for the study period (2005–2015) during days with no dust events showed different spatial patterns for the daily and intra-daily estimations and revealed areas in Israel that are affected by high PM concentrations (mainly industrial or dense urban areas). Estimations from these models are useful for epidemiological research and might contribute to environmental regulatory purposes by focusing the efforts of PM pollution reduction at the identified polluted areas. Highlights: Daily and intra-daily PM10 and PM2.5 concentrations were estimated in Israel. The model used satellite-based MAIAC AOD data and various spatio-temporal predictors. Intra-daily PM concentrations were higher than daily concentrations in urban areas. The models performed well with cross-validated R 2 that ranged between 0.82 and 0.92.