Place Bryan K, Hutzell William T, Appel K Wyat, Farrell Sara, Valin Lukas, Murphy Benjamin N, Seltzer Karl M, Sarwar Golam, Allen Christine, Piletic Ivan R, D'Ambro Emma L, Saunders Emily, Simon Heather, Torres-Vasquez Ana, Pleim Jonathan, Schwantes Rebecca H, Coggon Matthew M, Xu Lu, Stockwell William R, Pye Havala O T
Oak Ridge Institute for Science and Engineering (ORISE), Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina, USA.
Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina, USA.
Atmos Chem Phys. 2023 Aug 21;23(16):9173-9190. doi: 10.5194/acp-23-9173-2023.
Chemical mechanisms describe how emissions of gases and particles evolve in the atmosphere and are used within chemical transport models to evaluate past, current, and future air quality. Thus, a chemical mechanism must provide robust and accurate predictions of air pollutants if it is to be considered for use by regulatory bodies. In this work, we provide an initial evaluation of the Community Regional Atmospheric Chemistry Multiphase Mechanism (CRACMMv1.0) by assessing CRACMMv1.0 predictions of surface ozone (O) across the northeastern US during the summer of 2018 within the Community Multiscale Air Quality (CMAQ) modeling system. CRACMMv1.0 O predictions of hourly and maximum daily 8 h average (MDA8) ozone were lower than those estimated by the Regional Atmospheric Chemistry Mechanism with aerosol module 6 (RACM2_ae6), which better matched surface network observations in the northeastern US (RACM2_ae6 mean bias of +4.2 ppb for all hours and +4.3 ppb for MDA8; CRACMMv1.0 mean bias of +2.1 ppb for all hours and +2.7 ppb for MDA8). Box model calculations combined with results from CMAQ emission reduction simulations indicated a high sensitivity of O to compounds with biogenic sources. In addition, these calculations indicated the differences between CRACMMv1.0 and RACM2_ae6 O predictions were largely explained by updates to the inorganic rate constants (reflecting the latest assessment values) and by updates to the representation of monoterpene chemistry. Updates to other reactive organic carbon systems between RACM2_ae6 and CRACMMv1.0 also affected ozone predictions and their sensitivity to emissions. Specifically, CRACMMv1.0 benzene, toluene, and xylene chemistry led to efficient NO cycling such that CRACMMv1.0 predicted controlling aromatics reduces ozone without rural O disbenefits. In contrast, semivolatile and intermediate-volatility alkanes introduced in CRACMMv1.0 acted to suppress O formation across the regional background through the sequestration of nitrogen oxides (NO ) in organic nitrates. Overall, these analyses showed that the CRACMMv1.0 mechanism within the CMAQ model was able to reasonably simulate ozone concentrations in the northeastern US during the summer of 2018 with similar magnitude and diurnal variation as the current operational Carbon Bond (CB6r3_ae7) mechanism and good model performance compared to recent modeling studies in the literature.
化学机制描述了气体和颗粒物排放如何在大气中演变，并用于化学传输模型中评估过去、当前和未来的空气质量。因此，如果监管机构考虑使用某种化学机制，那么它必须能对空气污染物做出可靠且准确的预测。在这项工作中，我们通过评估2018年夏季美国东北部地区在社区多尺度空气质量（CMAQ）建模系统中社区区域大气化学多相机制（CRACMMv1.0）对地表臭氧（O）的预测，对CRACMMv1.0进行了初步评估。CRACMMv1.0对每小时和每日最大8小时平均（MDA8）臭氧的预测低于带有气溶胶模块6的区域大气化学机制（RACM2_ae6）的估计值，RACM2_ae6与美国东北部的地表网络观测结果更匹配（RACM2_ae6所有小时的平均偏差为+4.2 ppb，MDA8为+4.3 ppb；CRACMMv1.0所有小时的平均偏差为+2.1 ppb，MDA8为+2.7 ppb）。箱式模型计算结合CMAQ减排模拟结果表明，O对具有生物源的化合物高度敏感。此外，这些计算表明，CRACMMv1.0和RACM2_ae6对O的预测差异很大程度上是由无机速率常数的更新（反映最新评估值）以及单萜化学表示的更新所解释的。RACM2_ae6和CRACMMv1.0之间其他活性有机碳系统的更新也影响了臭氧预测及其对排放的敏感性。具体而言，CRACMMv1.0的苯、甲苯和二甲苯化学导致有效的NO循环，使得CRACMMv1.0预测控制芳烃可减少臭氧且不会对农村地区的O产生不利影响。相比之下，CRACMMv1.0中引入的半挥发性和中挥发性烷烃通过将氮氧化物（NO ）隔离在有机硝酸盐中，起到抑制区域背景下O形成的作用。总体而言，这些分析表明，CMAQ模型中的CRACMMv1.0机制能够合理模拟2018年夏季美国东北部的臭氧浓度，其量级和日变化与当前运行的碳键（CB6r3_ae7）机制相似，与文献中最近的建模研究相比，模型性能良好。
