Measurement and Modelling of Particulate Pollution over Kashmir Himalaya, India
2021
Bhat, Mudasir Ahmad | Romshoo, Shakil Ahmad | Beig, Gufran
Ground and satellite measurements of particulate pollution play an important role in determining the particulate pollutant-Aerosol Optical Depth (AOD) relationship. The daily observed PM₁₀ and PM₂.₅ concentration varied from 11–757 μg/m³ and 8–630 μg/m³ with the mean concentrations of 137 ± 119 μg/m³ and 86 ± 90 μg/m³, respectively. The long-term mean annual PM₁₀ and PM₂.₅ levels are several times higher than the WHO permissible limits. The 1377 satellite-derived AOD observations from the Moderate Resolution Imaging Spectrometer, ground-based particulate matter (PM) and meteorological observations from 2013–2017 were analysed to develop two-variate linear model (TVM) (AOD versus PM₁₀ or PM₂.₅) and multi-variate regression models (MVMs) (AOD + meteorological parameters versus PM₁₀ or PM₂.₅) for estimation of the ground level PM₁₀ and PM₂.₅ in the Kashmir Himalaya, India. The model evaluation showed that the PM predication estimates are significant at 99% confidence level for all the models. The TVM predicts daily PM₁₀ concentration better than PM₂.₅ explaining 82% and 74% variance in the observed data, respectively. By adding meteorological data to the regression analysis, there is an improvement of 5% and 11% in R² for PM₁₀ and PM₂.₅ estimates which inter alia reduced the RMSE by 11.8% and 20.47%, respectively. Estimation of the particulate pollution, utilising satellite-based AOD, observed PM and meteorology, would encourage satellite-based air quality monitoring in the data-scarce Himalaya. However, it is suggested that more studies are required to improve the operational prediction of PM pollution by incorporating satellite observations of other pollutants, and processes in the model using advanced approaches.
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