Air pollution contributes significantly to climate change and has recently become a significant concern. Previous studies on the interplay between air quality and the environment, such as meteorological variables, have hinted at their relevance in predicting air quality. While air quality prediction has been extensively explored, only a few studies have investigated the causal interactions, and no study has looked into identifying time-delayed causality between individual meteorological factors and air pollutants. In this work, we have deployed sensors in Baguio City, renowned as the “Summer Capital of the Philippines”, and collected data from September 2022 to April 2023. Convergent Cross Mapping (CCM) is then used to infer the time-delayed causation network for PM, PM, PM, VOC, and local meteorological variables. Baguio City faces environmental challenges from urbanization and influx of tourists. Here, the top meteorological variables are identified and characterized according to the strength and delay of influences on air pollutants. Wind direction emerges as a leading influencer driving air quality instantly, while pollutants reciprocate with delayed feedback. Temperature holds sway after a day, with pollutants impacting it after eight days on average. Furthermore, links from wind speed to PM concentrations are observed as mediators in causal pathways. Here, the maximum lag delay is only nine days. This work highlights the intricate interdependence of local meteorological factors and air quality, pioneering the identification of time delays that optimize causal influences between these variables. The results of this work offer valuable insights into environmental management and the formulation of mitigation measures.

中文翻译：

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碧瑶市气象变量与空气污染物时滞因果网络分析

空气污染对气候变化有重大影响，最近已成为一个重大问题。先前关于空气质量与环境（例如气象变量）之间相互作用的研究已经暗示了它们在预测空气质量方面的相关性。虽然空气质量预测已被广泛探索，但只有少数研究调查了因果相互作用，并且没有研究探讨确定单个气象因素与空气污染物之间的时滞因果关系。在这项工作中，我们在被誉为“菲律宾夏季之都”的碧瑶市部署了传感器，并收集了2022年9月至2023年4月的数据。然后使用收敛交叉映射（CCM）来推断时滞因果网络PM、PM、PM、VOC 和当地气象变量。碧瑶市面临着城市化和游客涌入带来的环境挑战。在这里，根据对空气污染物影响的强度和延迟来识别和表征主要气象变量。风向成为直接影响空气质量的主要影响因素，而污染物则以延迟反馈的方式相互影响。一天后温度就会保持不变，平均八天后污染物就会对其产生影响。此外，风速与 PM 浓度之间的联系被视为因果路径中的中介因素。在这里，最大滞后延迟仅为九天。这项工作强调了当地气象因素和空气质量之间错综复杂的相互依赖性，开创了识别时间延迟的先河，从而优化了这些变量之间的因果影响。这项工作的结果为环境管理和缓解措施的制定提供了宝贵的见解。