Emission of volatile organic compounds from landfill working surfaces: Formation potential of ozone and secondary organic aerosols

Abstract

The working surface of landfills is an important source of volatile organic compounds (VOCs), which have received increasing attention because of their role in potentially forming ozone and secondary organic aerosols (SOAs). In this study, 99 monitoring datasets on VOC emissions from a landfill working surface were obtained in 9 months and used to evaluate their ozone formation potential (OFP) and SOA formation potential (SOAFP) from a statistical perspective and compared using various methods. December was found to have the highest total OFP and SOAFP caused by VOC emissions from the landfill working surface. Both the propylene equivalent concentration (PEC) and maximum incremental reactivity (MIR) methods indicated that oxygenated compounds, especially ethanol, contributed the most to the OFP, accounting for 16.1 %–95.4 % and 44.9 %–98.6 % of the total OFP during the entire observation period, respectively. The fraction aerosol coefficient (FAC) method highlighted the effect of aromatic hydrocarbons which contributed to over 97 % of the total SOAFP. In contrast, the SOA potential (SOAP) method indicated that both aromatic hydrocarbons and oxygenated compounds play important roles, contributing 26.6 %–93.9 % and 21.6 %–73.4 % of the total SOAFP, respectively. Based on their mechanisms and comprehensiveness, PEC and SOAP methods are considered more appropriate for evaluating the OFP and SOAFP of VOCs released from landfill working surfaces. The annual total OFP and SOAFP of VOCs from landfill working surfaces of China in 2020 were thus estimated as 1.5 × 104 t and 135 t, respectively, with high variations among different regions along with the population, waste management system, and the amount of landfilled waste. This study provides a comprehensive understanding of the potential impacts and evaluation methods of local waste landfills in the atmospheric environment from a statistical perspective.