Mercury (Hg) is a toxic metal with persistent and bioaccumulative properties, primarily dispersed globally through atmospheric circulation. The United Nations Environment Programme (UNEP) published the Global Mercury Assessment 2018 in 2019, estimating that global anthropogenic atmospheric mercury emissions in 2015 amounted to 2,220 tons. East and Southeast Asia were identified as the major emission source regions, contributing 38.6% of global emissions (approximately 859 tons). To simulate atmospheric mercury concentration changes and investigate influencing factors, besides chemical transport models, recent studies have increasingly employed Generalized Additive Models (GAMs) to model variations in air pollutant concentrations and explore the mechanisms affecting these changes.

This study utilizes GAMs to quantify the impact of meteorological factors and air pollutants on the concentration of gaseous elemental mercury (GEM) at a low-altitude station (National Central University, NCU) and a high-altitude station (Lulin Atmospheric Background Station, LABS). The study further explores the mechanisms by which various meteorological factors influence GEM concentrations. The results indicate that from 2019 to 2020, the average GEM concentration measured at NCU was 2.16 ±3.13 ng m-3, while at LABS, it was 1.40 ±0.36 ng m-3. Due to the difference in altitude, air quality at NCU, located in the suburban area of Taoyuan, is affected by local emissions as well as pollutants transported by the northeast monsoon from mainland China. However, in high-altitude regions such as LABS, the primary influences are monsoons and regional factors, such as biomass-burning emissions from the Indochina Peninsula, which are transported over long distances to the high mountain stations in Taiwan.

GAMs analysis revealed that carbon monoxide (CO) had the greatest contribution to GEM variation at both LABS and NCU stations, indicating that both sites were primarily influenced by anthropogenic emissions. At LABS, the next most significant factors were the month and relative humidity (RH), whereas at NCU, the most influential factors were hour and wind direction (WD). Additionally, GEM concentrations at NCU were higher when the wind direction was predominantly from the south and southwest, suggesting the presence of emission sources between the south-southwest and southern directions. When using GAMs to predict GEM concentrations in other years, the model tended to overestimate during the spring and summer at LABS and underestimate in all seasons at NCU. This discrepancy is mainly attributed to the impact of local emissions, where the model struggles to capture extremely high values during pollution events.

¹ Department of Atmospheric Sciences, National Central University, Taoyuan City, Taiwan

* Corresponding author: dennis88913@gmail.com