The COVID-19 outbreak affected the world badly in this 21^st century leading to the closure of all types of anthropogenic activities. It is declared that there was an environmental betterment in names of water quality and air quality during the COVID-19 period. In this study, we analyzed the improvement in water quality by evaluating the suspended particulate matter (SPM) using the remote sensing technique in a tropical South Sumatra wetland i.e., Musi River in Southern Sumatra, Indonesia. The SPM values were estimated from Landsat 8 images Level-2 product. A quantitative and spatial analyses of before (20^th May 2019), during (22^nd May 2020), and after COVID-19 (28^th May 2022) periods were also calculated. Results revealed that the mean SPM values during COVID-19 period (4.56 mg/L) were lower than that before COVID-19 period (8.33 mg/L). Surprisingly, SPM showed an increase of 54% in SPM values after COVID-19 period, compared with during COVID-19 period. The role of human activities including industrial and domestic wastes during the restriction period was the main reason for alteration of pollution loads in the river. Outputs of this study can be used to arrange policies for the sustainable management of aquatic environments and water resources.

The air quality monitoring system is the most prominent tool for monitoring air pollution levels, especially in areas where forest fires often occur. The South Sumatra Province of Indonesia is one of the greatest contributors to haze events in Indonesia due to peatlands fires. It does not sufficiently possess a ground monitoring system to cover rural areas, and thus, delayed actions can result in severe air pollution within this region. Therefore, the aim of this current study is to analyze the distribution and classification of PM2.5 observed from 2019 to 2021 within the South Sumatra Province, Indonesia. The acquisition of PM2.5 data was from the Merra-2 Satellite with a spatial resolution of 0.5˚× 0.625˚ and an hourly interval. The hierarchical cluster analysis (HCA) was applied in this study for the clustering method. The result of the study revealed that the daily mean of PM2.5 levels varied from 5.9±0.01 to 21.3±0.03 μg/m³. The study area was classified into three classes: high pollution areas (HPA), moderate pollution areas (MPA) and low pollution areas (LPA), based on the HCA method. The average level of PM2.5 observed in HPA was notably higher, at 16.8±0.02 μg/m³, followed by MPA and LPA. Furthermore, this study indicated that the highest level of PM2.5 was found during 2019, with a severe haze event in the study area due to the intensive burning of forests, bush and peatlands. As a whole, the output of this study can be used by authorities for air quality management due to forest fire events in a certain area.