Xing Jia, Ding Dian, Wang Shuxiao, Dong Zhaoxin, Kelly James T, Jang Carey, Zhu Yun, Hao Jiming
State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China.
State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China.
Atmos Chem Phys. 2019;19(21):13627-13646. doi: 10.5194/acp-19-13627-2019.
Designing effective control policies requires efficient quantification of the nonlinear response of air pollution to emissions. However, neither the current observable indicators nor the current indicators based on response-surface modeling (RSM) can fulfill this requirement. Therefore, this study developed new observable RSM-based indicators and applied them to ambient fine particle (PM) and ozone (O) pollution control in China. The performance of these observable indicators in predicting O and PM chemistry was compared with that of the current RSM-based indicators. HO×HCHO/NO and total ammonia ratio, which exhibited the best performance among indicators, were proposed as new observable O- and PM-chemistry indicators, respectively. Strong correlations between RSM-based and traditional observable indicators suggested that a combination of ambient concentrations of certain chemical species can serve as an indicator to approximately quantify the response of O and PM to changes in precursor emissions. The observable RSM-based indicator for O (observable peak ratio) effectively captured the strong NO-saturated regime in January and the NO-limited regime in July, as well as the strong NO-saturated regime in northern and eastern China and their key regions, including the Yangtze River Delta and Pearl River Delta. The observable RSM-based indicator for PM (observable flex ratio) also captured strong NH-poor condition in January and NH-rich condition in April and July, as well as NH-rich in northern and eastern China and the Sichuan Basin. Moreover, analysis of these newly developed observable response indicators suggested that the simultaneous control of NH and NO emissions produces greater benefits in provinces with higher PM exposure by up to 1.2 μg m PM per 10 % NH reduction compared with NO control only. Control of volatile organic compound (VOC) emissions by as much as 40 % of NO controls is necessary to obtain the cobenefits of reducing both O and PM exposure at the national level when controlling NO emissions. However, the VOC-to-NO ratio required to maintain benefits varies significantly from 0 to 1.2 in different provinces, suggesting that a more localized control strategy should be designed for each province.
设计有效的控制政策需要对空气污染对排放的非线性响应进行有效量化。然而，当前的可观测指标以及基于响应面模型（RSM）的现有指标均无法满足这一要求。因此，本研究开发了基于RSM的新型可观测指标，并将其应用于中国的环境细颗粒物（PM）和臭氧（O₃）污染控制。将这些可观测指标在预测O₃和PM化学方面的性能与基于RSM的现有指标进行了比较。在各项指标中表现最佳的HO×HCHO/NO和总氨比，分别被提议作为新的可观测O₃和PM化学指标。基于RSM的指标与传统可观测指标之间的强相关性表明，某些化学物种的环境浓度组合可作为一个指标，大致量化O₃和PM对前体排放变化的响应。基于RSM的O₃可观测指标（可观测峰值比）有效地捕捉到了1月的强NO饱和状态和7月的NO受限状态，以及中国北方和东部及其关键区域（包括长江三角洲和珠江三角洲）的强NO饱和状态。基于RSM的PM可观测指标（可观测弹性比）也捕捉到了1月的强NH₃贫状态、4月和7月的NH₃富状态，以及中国北方和东部及四川盆地的NH₃富状态。此外，对这些新开发的可观测响应指标的分析表明，与仅控制NO排放相比，同时控制NH₃和NO排放，在PM暴露较高的省份能产生更大的效益，每减少10%的NH₃，PM浓度可降低多达1.2 μg/m³。在国家层面控制NO排放时，将挥发性有机化合物（VOC）排放量控制在NO排放量控制量的40%，对于同时降低O₃和PM暴露量是必要的。然而，维持效益所需的VOC与NO的比率在不同省份从0到1.2有显著差异，这表明应为每个省份设计更具针对性的控制策略。
