Emission Factor, Relative Ozone Formation Potential and Relative Carcinogenic Risk Assessment of VOCs Emitted from Manufacturing Industries

Abstract

In this study, a few important manufacturing industries located in Central Taiwan were studied (n = 13) for the emission of volatile organic compounds (VOCs), relative ozone formation potential (ROFP) and relative carcinogenic risk (RCR). Higher emission factors of total VOCs (∑VOCs) were observed for stencil printing (423 mg-VOC kg-1) compared to other emission sectors. Alkanes formed the most dominant group of VOCs for steel foundry (41.6%), aluminum foundry (25.1%) and synthetic resin manufacturing (25.0%). However, for the chemical sector (synthetic and polyester resin), oxygenated organics like acetone (55.7%) and ethyl acetate (79.7%) were the predominant VOCs. Moreover, emissions from acrylic resin manufacturing had higher contributions from aromatic compounds (> 95%). Toluene was the topmost compound in terms of its contribution to ∑VOCs in plastic tape manufacturing (44.4%), aluminum foundry (39.6%), steel foundry (11.6%), plastic coating (64.3%) and stencil printing (35.3%). Analysis of ozone formation potentials showed that the metal product & machinery acrylic resin manufacturing and stencil printing had a higher normalized ROFP index and belonged to level-I emission sources. However, in terms of the RCR, integrated iron & steel manufacturing had the highest normalized RCR index belonged to level-I emission sources. Level-I represents the most important VOC emission sources.

Spatiotemporal Variations in Summertime Ground-Level Ozone around Gasoline Stations in Shenzhen between 2014 and 2020

“…Significantly, gasoline stations, which are the primary source of fuel for cars and motor equipment, emit large amounts of VOCs in the process of refueling and unloading [19,20]. The VOCs will promote the formation of ground-level ozone, posing a potential health threat to people living nearby, especially in densely populated urban areas where there is a high demand for transportation [20,21]. To reduce the adverse effects of ground-level ozone exposure on the health of surrounding residents, it is urgent to clarify the spatial and temporal distribution characteristics of GOCs around gasoline stations.…”

“…The statistical model is established using the statistical correlation between GOCs and influencing factors. In comparison to the deterministic model, the statistical model is more practical for GOC retrievals due to its low computational cost, easy development and high precision [21,22]. Typically, retrieval concentrations at spatial resolutions down to 10 km have been used to characterize the spatiotemporal distribution of GOCs [24].…”