A novel approach to long-term source contribution of ambient PM2.5 from residential solid fuel burning using the FUSTA methodology

Abstract

Managing ambient fine particulate matter (PM2.5) requires determining how much different sources contribute over time. The present study uses FUSTA (Fuzzy SpatioTemporal Apportionment) to estimate how much residential solid fuel burning (RSFB) contributes to long-term PM2.5 concentrations. FUSTA has been applied to multiyear data for two cities in Chile and one in Poland, at which the impact of RSFB on ambient PM2.5 has been identified. By using the methodology proposed, we have found a spatiotemporal pattern (STP) associated with RSFB and its long-term contribution. The STP that comes from RSFB has distinctive features: high seasonality with peak values in winter, contributions that come from all wind directions, and a diurnal cycle with peak values around midnight. These results were validated by comparison with short-term receptor model estimates for the three cities, leading to Pearson correlations r=0.84, 0.97, and 0.89, showing the consistency of FUSTA methodology. This is the first time that the long-term contribution of RSFB to ambient PM2.5 has been estimated in the three cities studied, without relying on emission inventories nor air quality models. The trends observed in the long-term contribution of RSFB to PM2.5 concentration showed that the regulations implemented for RSFB control should be revisited.