School of International Development, University of East Anglia, Norwich, NR4 7TJ, UK.
Institute for Environment and Climate Research, Jinan University, Guangzhou 510006, P.R. China.
Sci Total Environ. 2018 Jul 1;628-629:697-706. doi: 10.1016/j.scitotenv.2018.02.102. Epub 2018 Feb 20.
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.
排放清单 (EI) 和受体模型 (RM) 是中国环境部推荐的三种源解析 (SA) 方法中的两种,被广泛用于提供排放源识别的独立观点。然而,如何解释它们提供的混合结果研究较少。在这项研究中,在中国一个快速发展和人口密集的城市群——珠江三角洲 (PRD) 地区进行了交叉验证研究。通过利用高度解析的特定物种区域排放清单和全区域网格化挥发性有机化合物 (VOCs) 特定物种测量活动,我们阐明了 EI 和 RM 之间差异的潜在因素,并提出了解释这些差异的方法,旨在实现科学合理的源识别。结果表明,用于比较的物种数量、时间和空间分辨率、活性物种的光化学损失、EI 中潜在缺失的源以及 RM 中使用的示踪剂是导致差异的重要因素。确保 EI 和 RMs 中使用的物种一致,利用更大的空间覆盖范围和更长的时间跨度,解决光化学损失的影响,以及补充缺失源的排放,可以帮助协调两种方法获得的 VOC 源特征的差异。通过利用两种方法的优势和规避其劣势,EI 和 RM 可以发挥协同作用,获得稳健的 SA,以改善空气质量管理实践。