Abstract Previous studies have contributed to the understanding on the impacts of weather on air pollution. Most of these investigations focused primarily on future climate scenarios, laboratory experiments, or weather trends-related air pollution at regional scale. In particular, an important limitation of the trends studies is that the estimated weather impact on air pollution may be underestimated or overestimated given that the regional scale does not capture the site-to-site variation of air pollution and weather. The primary objective of this research is to addresses this gap by quantifying weather-associated changes in air pollution at site location (air pollution sites) in the U.S between 1988 and 2018. We quantified the past weather-related increases CO, NO2, O3, nitrate, organic carbon, silicon, sodium, sulfate, and SO2 concentration using Generalized Additive Models (GAMs). We used a framework that derives “penalties” (weather penalty, in μg/m3, ppm or ppb per year) for each season (warm and cold). Three pollutants presented significant results (weather penalties), including CO, NO2, and O3. Our findings show significant spatio-temporal variation of climate impact on CO, NO2, and O3. For example, in the warm season we estimated a total penalty over the study period for the sites with the highest penalty on CO (site in Boise, Idaho), NO2 (site in New York City), and O3 (site in Tucson, Arizona) of 6.18 (95%CI: 0.30; 12.0) ppm, 182.04 (95%CI: 39.33; 324.72) ppb, and 0.09 (95%CI: 0.030; 0.150) ppm, respectively. In the cold season, the estimated total penalty for the sites with the highest penalty on CO (site in Los Angeles, California), NO2 (site in Washington, Pennsylvania), and O3 (site in Decatur, Illinois) was 12.01 (95%CI: 1.50; 22.50) ppm, 285.03 (95%CI: 14.37; 555.69) ppb, and −0.066 (95%CI: -0.120; −0.030) ppm, respectively. Our results should be of interest to policy makers to create future strategies related to environmental health and climate change. Climate models typically show large variation in projections of the key variables influencing pollution, and our model based on local scale allowed us to identify statistically robust results.

中文翻译：

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在过去的 30 年中，美国哪些地方的空气质量受到天气变化的影响？

摘要 以往的研究有助于理解天气对空气污染的影响。大多数这些调查主要集中在未来的气候情景、实验室实验或区域尺度上与天气趋势相关的空气污染。特别是，趋势研究的一个重要局限性是，鉴于区域尺度没有捕捉到空气污染和天气的站点间变化，因此估计的天气对空气污染的影响可能被低估或高估。本研究的主要目标是通过量化 1988 年至 2018 年间美国站点位置（空气污染点）与天气相关的空气污染变化来弥补这一差距。我们量化了过去与天气相关的 CO、NO2、O3、硝酸盐、有机碳、硅、钠、硫酸盐、和 SO2 浓度使用广义加性模型 (GAM)。我们使用了一个框架来推导出每个季节（温暖和寒冷）的“惩罚”（天气惩罚，以 μg/m3、ppm 或 ppb 每年为单位）。三种污染物表现出显着的结果（天气惩罚），包括 CO、NO2 和 O3。我们的研究结果表明，气候对 CO、NO2 和 O3 的影响存在显着的时空变化。例如，在暖季，我们估计了研究期间 CO（位于爱达荷州博伊西的站点）、NO2（位于纽约市的站点）和 O3（位于亚利桑那州图森的站点）最高罚分的站点的总罚金) 6.18 (95%CI: 0.30; 12.0) ppm, 182.04 (95%CI: 39.33; 324.72) ppb, 和 0.09 (95%CI: 0.030; 0.150) ppm。在寒冷季节，对 CO 处罚最高的站点（位于加利福尼亚州洛杉矶的站点）的估算​​总罚款，NO2（位于宾夕法尼亚州华盛顿的站点）和 O3（位于伊利诺伊州迪凯特的站点）为 12.01（95%CI：1.50；22.50）ppm、285.03（95%CI：14.37；555.69）ppb 和 -0.066（95%CI） ：-0.120；-0.030) ppm，分别。我们的结果应该让决策者感兴趣，以制定与环境健康和气候变化相关的未来战略。气候模型通常显示影响污染的关键变量的预测变化很大，我们基于局部尺度的模型使我们能够确定统计上稳健的结果。