An integrated approach to air pollution modeling from climate change perspective using ARIMA forecasting

Faiza Naseem, Audil Rashid2, Touqeer Izhar, Muhammad Irfan Khawar, Shabana Bano, Aniqa Ashraf, Mian Nazish Adnan


Exposure to air pollutants and related health implications is challenging for policy makers to overcome research gaps and effectively manage urban environment. To connect this missing link, we analyzed impact of climate variables on air pollution status to identify key determinants essential for future projections. Findings show that meteorological variables (temperature, humidity, wind, solar radiation and precipitation) have definite influence on life cycle persistence of air pollutants in urban environment. This influence was evaluated using a modeling approach ‘time series expert modeler’ called ARIMA which has identified strong climate predictors capable of explaining variations in air pollutants in the model output (Ljung-Box statistics=81.78; stationary R2=0.69; p<0.000). The results showed significant impact of temperature, humidity and precipitation on spatial variability of air pollutant concentrations. In developing countries such as Pakistan where lack of political will has caused problems in the enforcement of environmental regulations, degradation of urban air quality is a serious threat for public health. Therefore, reliance of climate-signals to predict air pollutant concentration and their variability is of great significance. We conclude that in order to overcome the limitations such as absence of national air quality monitoring system due to inefficient governments, universities in Pakistan need to initiate multidisciplinary research groups where expertise of mathematical modelers, geographers, meteorologists, GIS experts and public health scientists could be integrated. In this context, current study provides useful evidence to estimate likely impacts of climate change on air pollution assessments.

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