Integrated Approach (MCD19A2 and PM₁₀ Datasets) for Spatiotemporal Assessment of Aerosol and Revealing Approachable Predictive Model Across the Mega-Mining Region (Jharkhand), India Along with its Accuracy Measures

Dealing with limited and inconsistent air quality monitoring network in Jharkhand, an attempt has been made to visualize the scenario of aerosol level all through the Jharkhand state by utilizing this high-resolution Multi-Angle Implementation of Atmospheric Correction aerosol optical depth (AOD) data as it provides the global coverage. Google Earth Engine code was used to download and prepare 1 × 1 km AOD map of the study area, Jharkhand, India. Consistently higher and moderate AOD levels found in the Central and North-eastern Plateau and South-eastern Plateau throughout the considered years strongly pointed to the influence of industrial and mining clusters in this region. Multiple Linear Regression Model performed good for predicting the PM₁₀ concentration keeping meteorological parameters and AOD as input variables. In the current analysis, meteorological parameters play a significant role in PM₁₀ prediction; when compared their results obtained from the single variant regression model as indicated by an improved R² value of up to 0.91. The accuracy of the model’s performance was good with lower MAPE (up to 4.23%). Correlation characteristics among AOD_0.55 µm, PM_10, and meteorological factors was also conducted. Seasonally, the order followed by R² values was Winter > post-monsoon > Pre-monsoon > Monsoon. The results obtained from multi-linear regression models exhibited good agreement with five ground stations and thus the present approach can be used to get RSPM values in the absence of ground monitoring.