Source profiles and emission factors of organic and inorganic species in fine particles emitted from the ultra-low emission power plant and typical industries

Highlights: • Eighty-nine organic/inorganic species in PM_2.5 from stationary sources were detected. • Organic species could help to further distinguish the stationary sources. • Indicatory components and ratios were estimated by the equation and randomForest. • Emission factors of components and PM_2.5 from stationary sources were provided. Accurate source markers, source profiles and species-based emission factors (EFs) are currently the key limitations for source apportionment and emission inventory researches. Fine particles (PM_2.5) were collected from stack gases of eight types of stationary sources with a dilution sampling system. The mass percentages and EFs of 89 kinds of chemical species in PM_2.5 including water-soluble ions, elements, carbonaceous species and molecular organic species were obtained. Results showed that water-soluble ions (8%–54%) and elements (5%–45%) were the dominant chemical species. Palmitic acid (0.19%–0.62%) and stearic acid (0.21%–0.59%) were the most abundant organic species. PM_2.5 source profiles of the eight sources were different from each other with the coefficient of divergence values all higher than 0.4. The addition of organic species could help to further distinguish them. The indicatory chemical components and specific species ratios were obtained by both a statistical equation and randomForest. These indicatory chemical components (e.g. F⁻ for glass factory) and species ratios (e.g. K⁺/Mg²⁺ & OC/Mg for pharmaceutical factory) improved the current knowledges of their indicatory performance in source identification of ambient PM_2.5. The EFs of PM_2.5 from the eight stationary sources ranged from 0.019 to 51.6 kg t⁻¹ of fuel used. The EFs of PM_2.5 from the pharmaceutical factory were about 70–2600 times higher than other seven types of sources due to the lack of dust-removing devices. Certain EFs measured in this study were about 10–36,000 times lower than corresponding EFs estimated in previous studies which didn't perform field measurements, indicating the necessity for improving emission inventories continuously. This study contributes to identifying emission sources of PM_2.5 especially for subtypes of stationary sources and to establishing species-based emission inventories.