The duration size of air pollution events refers to a state in which air pollution indices reflect unhealthy conditions over an extended period of time. Thus, a large duration size implies prolonged air pollution events. Such events exert negative effects on human health, disrupt economic activities, and deteriorate environmental ecosystems. This study proposed the use of power-law models as a tool for evaluating the behaviors of duration size for extreme and unhealthy air pollution events. Four different power-law models were used to analyze the air pollution data in Klang, Malaysia. Results indicated that the discrete power-law distribution is a reliable model that could best describe the power-law mechanism existing at the right tail of the data distribution. In parallel with that, air pollution events with duration sizes greater than 33 h are found to reflect the threshold events that demonstrating a power-law behaviors. Findings highlight the need for authorities to be vigilant when air pollution incidents with duration sizes exceeding 33 h occur.

空气污染事件的持续时间规模是指空气污染指数长时间反映不健康状况的状态。因此，持续时间长意味着空气污染事件持续时间延长。这些事件对人类健康产生负面影响，破坏经济活动，并使环境生态系统恶化。这项研究提出使用幂律模型作为评估极端和不健康空气污染事件持续时间大小行为的工具。马来西亚巴生市使用了四种不同的幂律模型来分析空气污染数据。结果表明，离散的幂律分布是一个可靠的模型，可以最好地描述数据分布右尾处存在的幂律机制。同时，发现持续时间大于33小时的空气污染事件反映了表明幂律行为的阈值事件。调查结果突显了当持续时间超过33小时的空气污染事件发生时，当局需要保持警惕。