Reconciling discrepancies in the source characterization of VOCs between emission inventories and receptor modeling

Abstract

Emission inventory (EI) and receptor model (RM) are two of the three source apportionment (SA) methods recommended by Ministry of Environment of China and used widely to provide independent views on emission source identifications. How to interpret the mixed results they provide, however, were less studied. In this study, a cross-validation study was conducted in one of China's fast-developing and highly populated city cluster- the Pearl River Delta (PRD) region. By utilizing a highly resolved speciated regional EI and a region-wide gridded volatile organic compounds (VOCs) speciation measurement campaign, we elucidated underlying factors for discrepancies between EI and RM and proposed ways for their interpretations with the aim to achieve a scientifically plausible source identification. Results showed that numbers of species, temporal and spatial resolutions used for comparison, photochemical loss of reactive species, potential missing sources in EI and tracers used in RM were important factors contributed to the discrepancies. Ensuring the consensus of species used in EIs and RMs, utilizing a larger spatial coverage and longer time span, addressing the impacts of photochemical losses, and supplementing emissions from missing sources could help reconcile the discrepancies in VOC source characterizations acquired using both approaches. By leveraging the advantages and circumventing the disadvantages in both methods, the EI and RM could play synergistic roles to obtain robust SAs to improve air quality management practices.

Improving VOCs control strategies based on source characteristics and chemical reactivity in a typical coastal city of South China through measurement and emission inventory

“…Therefore, the spatial differences on halocarbons were more related to spatial variations of local anthropogenic emissions. Many studies on VOC SAs revealed that industrial processes and solvent usage are the predominant sources of halocarbons and OVOCs ( Mo et al, 2017 ; Ou et al, 2018 ; Simayi et al, 2020 ). Thus, the abundant OVOCs (predominantly acetone) and halocarbons may be correlated with the local industries emission and solvent utilization.…”

“…This is one possibility for the SA divergences of other industrial processes between EI (13.3%) and RM (22.2%). The incomplete statistics of other industries may also enhance the underestimation of this source proportion in EI ( Ou et al, 2018 ). However, given there is no heating system in Beihai with an average annual temperature of 22.8 °C between 2016 and 2018, always neglected heating consumption in the EIs has little impact on Beihai ( Simayi et al, 2020 ).…”

“…Additionally, alkanes and aromatics contributed 21.6% and 17.4% to OFP, and their contributions to propy-equiv concentration accounted for 30.2% and 23.3 separately. However, both the OH reactivity and OFP of halocarbons were low, mainly due to the strong chemical bonds within the halocarbons ( Ou et al, 2018 ). The species reactivity based on OH reactivity and OFP was not completely consistent.…”

“…VOCs chemical reactivity is not proportional to their concentrations, which exhibits a wide range and act as another important distinguishing characteristic of VOC species. The highly reactive species degrade rapidly, while the less reactive ones are relatively stable, increasing VOC accumulation and exaggerating the potential VOC sources contribution ( Ou et al, 2018 ). In this study, to adequately estimated the chemical reactivity of VOCs, the OH reactivity and ozone formation potential (OFP) were of particular concern.…”

An Integrated Method for Factor Number Selection of PMF Model: Case Study on Source Apportionment of Ambient Volatile Organic Compounds in Wuhan

“…Studies have been conducted to obtain more accurate and reliable VOCs source profiles for on-road vehicle emissions [18,19] and industries [20,21]. However, large and inherent uncertainties exist in current emission inventories owing to inaccurate and incomplete information of emission sources, including source profiles, emission factors, and source activities [22]. The lack of complete emission profiles makes PMF the most used method to identify VOCs source [8,[23][24][25][26][27]].…”