The short-term exposure to high concentrations of fine particulate matter (PM_2.5) and ozone increases the mortality burden in megacities. Quickly identifying formation mechanisms of PM_2.5 and ozone is essential for the pollution control in the early stage. Min/max autocorrelation factor analysis (MAFA) is used to analyze hourly data of air pollutants and meteorological variables collected over 7-day periods in high and low PM_2.5 events at the Wuhan Supersite in 2015. The MAFA results determined the interactions of air pollutants and the influences of meteorological variables on the formation of major air pollutants. In the high PM_2.5 event (winter), PM_2.5 and secondary inorganic aerosols (SIAs) are major pollutants mainly affected by variations in temperature (TEMP), relative humidity (RH), planetary boundary layer height (PBLH), and wind speed (WS). The SIAs are produced by the oxidation of precursor pollutants which increases in daytime due to intense industrial and traffic activities. In the low PM_2.5 event (summer), MAFA identified photochemical reaction of the carbon monoxide (CO), and formation of SIAs and ozone (O₃). Serious O₃ pollution occurs in high TEMP, high PBLH, and low RH conditions. The results can serve as a critical reference of quick decision making for local government agencies.

中文翻译：

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利用短期数据快速定量确定 PM2.5 和臭氧的形成机制

短期接触高浓度细颗粒物 (PM _2.5 ) 和臭氧会增加特大城市的死亡率负担。快速识别 PM _2.5和臭氧的形成机制，对于早期污染控制至关重要。最小/最大自相关因子分析 (MAFA) 用于分析2015 年武汉超级站点在高和低 PM _2.5事件中收集的 7 天时间段内的空气污染物和气象变量的每小时数据。 MAFA 结果确定了空气污染物的相互作用以及气象变量对主要大气污染物形成的影响。在高 PM _2.5事件（冬季）中，PM _2.5二次无机气溶胶（SIAs）是主要受温度（TEMP）、相对湿度（RH）、行星边界层高度（PBLH）和风速（WS）变化影响的主要污染物。SIAs 是由前体污染物的氧化产生的，这些污染物在白天由于密集的工业和交通活动而增加。在低 PM _2.5事件（夏季）中，MAFA 确定了一氧化碳 (CO) 的光化学反应，以及 SIA 和臭氧 (O ₃ ) 的形成。严重的 O ₃污染发生在高 TEMP、高 PBLH 和低 RH 条件下。结果可以作为地方政府机构快速决策的重要参考。