Evaluating the potential footprints of land use and land cover and climate dynamics on atmospheric pollution in Pakistan

Abstract

Evaluating the potential impacts of land use and land cover change (LULCC) and climate change on air pollution is crucial to unravel the driving forces and mechanisms behind changes in air quality. A multi-faceted approach was adopted, including a land change model (LCM) and Mann–Kendall (MK) test, to evaluate the transition of land cover type, changes in climate, and atmospheric pollutants during 2004–2021 in Pakistan. Moreover, a multiscale geographically weighted regression (MGWR) model and a mathematical model were used to assess the potential contribution of LULCC and climate dynamics to atmospheric pollution. It was revealed that during 2004, croplands covered an area of 9.72 × 104 mile2, accounting for 38% of the total area. However, the area of the croplands increased to 10.1 × 104 mile2, accounting for 40% of the total area in 2021. The MK test showed that the north and west–south regions significantly experienced air pollution, with the increasing trend for nitrogen dioxide (NO2) and sulfur dioxide (SO2) being 0.89× 1015 molecules/cm2 per year and 0.54 DU/year, respectively. For climate variability, mean precipitation (Precp) and mean surface pressure (SP) showed a prominent increasing trend, with a maximum value of 1 mm/year and 0.01 Kpa/year, respectively. The mean temperature maximum (Tmax) showed an increasing and decreasing trend, with the highest value of 0.28°C/year and 0.08°C/year, respectively. In the context of contribution, the conversion of cropland to grasslands increased the trend for SO2 concentrations. The highest increasing trend of 1.5 DU for ozone (O3) was found due to conversion of grasslands to shrublands. Additionally, regional climate played a significant role in making air pollution stagnant across the country. Precp and wind speed (WS) contributed significantly in escalating NO2 concentrations in Pakistan, while Precp contributed most (0.004 DU) to increasing SO2 concentrations. For O3, the most influential climate factor was Precp. These results on a long-term temporal scale demonstrated how maintaining climate variability through comprehensive land use management can help improve ambient air quality in Pakistan.

Assessing the Nonlinear Relationship between Land Cover Change and PM10 Concentration Change in China

“…This study focuses on China, analyzing the spatiotemporal variations in PM 10 , land cover, and the nonlinear relationship between land-cover changes and PM 10 concentration changes from 2015 to 2021. There is a strong link between the spatial distribution of PM 10 and atmospheric conditions [55]. High temperatures increase convective activity in the atmosphere, which may make PM 10 more susceptible to being suspended in the air.…”

Coupling Remote Sensing Insights With Vegetation Dynamics and to Analyze NO2 Concentrations: A Google Earth Engine-Driven Investigation

“…Other research on European tree varieties found that the conversion of NO2 and the lowering of gas levels are caused by the fallen leaves of the trees [25]. Numerous studies show a connection between LST and NO2 in urban areas in combination with vegetation [3], [7], [26]. The analysis in Baltimore, USA, revealed that metropolitan regions with high temperatures experienced more significant amounts of NO2 and O3, and vegetation usually diminishes LST and Urban heat island (UHI) levels [8].…”