Assessing the impact of mining on cyclic and linear methylsiloxane distribution in Tibetan soils: Source contribution...

The pervasive presence of methylsiloxanes (MSs), comprising linear and cyclic congeners, in the environment poses significant ecological risks, yet the understanding of their transport mechanisms and deposition patterns remains limited. This study analyzed the concentrations of 12 linear-MSs (L3-L14) and 7 cyclic-MSs (D3-D9) in 29 surface soil samples collected across varying altitudes (3726 to 4863 m) near the Jiama mining sector in Tibet, aiming to investigate the distribution and transport dynamics of MSs from the emission source. The distribution of total MS concentration (ranging from 50.1 to 593 ng/g) showed a remarkable correlation with proximity to the mining site, suggesting the emergent source of mining activities for the MSs in the remote environment of the Tibetan Plateau. Employing the innovative model of robust absolute principal component scores-robust geographically weighted regression (RAPCS-RGWR), the analysis predicted that the mining operations contributing 57.1 % of the total soil MSs, would significantly surpass contributions from traffic emissions (14.7 %), residential activities (13.2 %), and the environmental factor of total organic matter content (14.9 %). The Boltzmann equation effectively modeled the distribution pattern of soil MSs, highlighting atmospheric transport and gravitational settling as key distribution mechanisms. However, linear-MSs exhibited longer transport distances than cyclic-MSs and were more profoundly affected by prevailing wind directions, suggesting their differential environmental behaviors and risks. Our study underscored that the mining sector possibly emerged as a significant source of Tibetan MSs, and provided insights into the transport and fate of MSs in remote, high-altitude environments. The findings emphasize the need for targeted pollution control strategies to mitigate the environmental footprint of mining activities in Tibet and similar regions.