Quantifying effects of meteorological parameters on air pollution in Kathmandu valley through regression models.

Abstract

Most studies on air pollution have focused on source apportionment aspect but very few have considered meteorological factors responsible for variation in air pollution levels including studies in Nepal. Consequently, the effects of meteorological parameters including effects of seasonality and lag effects are investigated and quantified for Kathmandu valley, Nepal. Daily temporal data of air pollution for 2017-early 2020 monitored by the Department of Environment and US Embassy, Kathmandu, Nepal, and meteorological data monitored by the Department of Hydrology and Meteorology, Kathmandu, Nepal, are used. Regression models namely exponential, Box-Cox transformed and Gamma generalized linear models are used to quantify the effects supported by regression diagnostics. Results depict high proportions of observed air pollution variations (79-85%) explained by the fitted models with varied effects of meteorological parameters. Around 5% reduction in PM10 (96% CI: 0.034-0.069) and PM1 (95% CI: .0.029-0.063) levels per 1°C increase in average temperature and significant increase in surface O3 level (0.177, 95% CI: 0.126-0.228 Box-Cox transformed value) per 1°C increase in average temperature are detected. Similarly, around 0.7% (95% CI: 0.1-1.3) and 2% (96% CI:1.3-2.5) decrease in PM1 and PM10, respectively per 1% increase in relative humidity, 0.032 (95% CI: 0.024-0.040) decrease in transformed value of PM2.5 per 1mm increase in rainfall, and 7.3% (95% CI: 1.3-15.9) decrease in PM10 per 1m/s increase in wind speed are also detected. In conclusion, meteorological conditions are found significant contributing factors in determining air pollution levels in Kathmandu valley. On the long run, atmospheric conditions can play vital roles in air pollution situation shifts mainly due to climate change characterized by changes in meteorological values.