Human exposure to particulate matter and other environmental species is difficult to estimate in large populations. Individuals can encounter significant and acute variations in exposure over small spatiotemporal scales. Exposure is strongly tied to both the environmental and activity contexts that individuals experience. Here we present the development of an agent-based model to simulate human exposure at high spatiotemporal resolutions. The model is based on simulated activity and location trajectories on a per-person basis for large geographical areas. We demonstrate that the model can successfully estimate trajectories and that activity patterns have been validated against traffic patterns and that can be integrated with exposure-agent geographical distributions to estimate total human exposure.

中文翻译：

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STHAM：一种基于代理的模型，用于模拟跨高分辨率时空域的人类暴露。

人类对颗粒物和其他环境物种的暴露在大量人群中难以估计。个人可能会在小时空尺度上遇到显着和急剧的暴露变化。暴露与个人经历的环境和活动背景密切相关。在这里，我们介绍了基于代理的模型的开发，以模拟高时空分辨率下的人类暴露。该模型基于针对大型地理区域的每个人的模拟活动和位置轨迹。我们证明该模型可以成功地估计轨迹，并且活动模式已经根据交通模式进行了验证，并且可以与暴露代理地理分布相结合来估计总的人类暴露。