Development of Land Use Regression Model for Seasonal Variation of Nitrogen Dioxide (NO 2 ) in Lahore, Pakistan

Saimar Pervez, Ryuta Maruyama, Ayesha Riaz and Satoshi Nakai
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Saimar Pervez: Department of Artificial Environment, Graduate School of Environment and Information Sciences, Yokohama National University, Yokohama 240-8501, Japan
Ryuta Maruyama: Department of Artificial Environment, Graduate School of Environment and Information Sciences, Yokohama National University, Yokohama 240-8501, Japan
Ayesha Riaz: Department of Artificial Environment, Graduate School of Environment and Information Sciences, Yokohama National University, Yokohama 240-8501, Japan
Satoshi Nakai: Department of Artificial Environment, Graduate School of Environment and Information Sciences, Yokohama National University, Yokohama 240-8501, Japan

Sustainability, 2021, vol. 13, issue 9, 1-15

Abstract: Ambient air pollution and its exposure has been a worldwide issue and can increase the possibility of health risks especially in urban areas of developing countries having the mixture of different air pollution sources. With the increase in population, industrial development and economic prosperity, air pollution is one of the biggest concerns in Pakistan after the occurrence of recent smog episodes. The purpose of this study was to develop a land use regression (LUR) model to provide a better understanding of air exposure and to depict the spatial patterns of air pollutants within the city. Land use regression model was developed for Lahore city, Pakistan using the average seasonal concentration of NO 2 and considering 22 potential predictor variables including road network, land use classification and local specific variable. Adjusted explained variance of the LUR models was highest for post-monsoon (77%), followed by monsoon (71%) and was lowest for pre-monsoon (70%). This is the first study conducted in Pakistan to explore the applicability of LUR model and hence will offer the application in other cities. The results of this study would also provide help in promoting epidemiological research in future.

Keywords: ambient air pollution; exposure assessment; Pakistan; land use regression; vehicle workshops (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2021
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