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Social media approaches to modeling wildfire smoke dispersion: spatiotemporal and social scientific investigations

机译：社交媒体对野火烟雾扩散建模的方法：时空和社会科学研究

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Wildfires have significant effects on human populations, economically, environmentally, and in terms of their general well-being. Smoke pollution, in particular, from either prescribed burns or uncontrolled wildfires, can have significant health impacts. Some estimates suggest that smoke dispersion from fire events may affect the health of one in three residents in the United States, leading to an increased incidence of respiratory illnesses such as asthma and pulmonary disease. Scarcity in the measurements of paniculate matter responsible for these public health issues makes addressing the problem of smoke dispersion challenging, especially when fires occur in remote regions. Crowdsourced data have become an essential component in addressing other societal problems (e.g., disaster relief, traffic congestion) but its utility in monitoring air quality impacts of wildfire events is unexplored. In this study, we assessed if user-generated social media content can be used as a complementary source of data in measuring particulate pollution from wildfire smoke. We found that the frequency of daily tweets within a 40,000 km2 area was a significant predictor of PM2.5 levels, beyond daily and geographic variation. These results suggest that social media can be a valuable tool for the measurement of air quality impacts of wildfire events, particularly in the absence of data from physical monitoring stations. Also, an analysis of the semantic content in people's tweets provided insight into the socio-psychological dimensions of fire and smoke and their impact on people residing in, working in, or otherwise engaging with affected areas.
机译：野火在经济，环境和总体福祉方面对人类产生重大影响。烟尘污染，特别是规定的烧伤或不加控制的野火，可能会对健康产生重大影响。一些估计表明，火灾中的烟雾扩散可能会影响美国三分之一的居民的健康，从而导致呼吸系统疾病（如哮喘和肺病）的发生率增加。测量造成这些公共卫生问题的颗粒物质的稀缺性使得解决烟雾扩散问题变得困难重重，尤其是在偏远地区发生火灾时。众包数据已成为解决其他社会问题（例如救灾，交通拥堵）的重要组成部分，但尚未用于监控野火事件对空气质量的影响。在这项研究中，我们评估了用户生成的社交媒体内容是否可以用作测量野火烟雾颗粒污染的补充数据来源。我们发现，在每天40,000平方公里的区域内，每日推文的频率是PM2.5水平的重要预测指标，超出了每日和地理变化范围。这些结果表明，社交媒体可以成为衡量野火事件对空气质量的影响的宝贵工具，尤其是在没有来自物理监测站的数据的情况下。此外，对人们推文中语义内容的分析还提供了对火灾和烟雾的社会心理维度及其对居住，工作或以其他方式参与受影响地区的人们的影响的深刻见解。

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