Spatial assessment of the seasonal impact of brickfields on air pollution in Dhaka metropolitan area using ordination techniques

Monitoring air pollution and its sources are vital especially in and around megacities like Dhaka. This study tries to determine the contribution of spatial pattern of brickfields on air pollution in the Dhaka metropolitan area. Concentrations of CO, NO 2 , and SO 2 emissions are analysed to determine the distribution of air pollution contributed by brickfields in the area. To detect the spatial pattern of the brickfields in the area, a deep learning-based single shot detector (SSD) object detection model was used to locate brickfields in the study area using high-resolution optical satellite imagery. The model accuracy was calculated to be 90%. The application of ordination techniques to determine the dominant factors causing air pollution was explored. Both unconstrained and constrained ordination techniques were used to determine the influence of brick fields on air pollution. Principal component analysis (unconstrained ordination) was used to analyse the independent variables (factors influencing pollution in the region). The unconstrained analysis showed that meteorological variables such as relative humidity and atmospheric pressure explained the distribution of air pollution better. However, redundancy analysis determined that the proximity of brickfields to nearby roads had the highest influence on the spatial pattern of air pollution. This indicates that brickfields closer to road networks have a higher contribution to air pollution. This study presents a new workflow using ordination techniques to model the impact of brickfields on air pollution based on freely available satellite imagery. This is vital for developing monitoring systems for assessing the impact of the spatial distribution of brickfields on air pollution in and around a megacity. This system will ultimately play a role in ensuring long-term spatial planning for brickfields which is a vital step towards achieving Target 13.b (Promoting mechanisms to raise capacity for planning and management) of SDG 13 Climate Action.