Abstract Air pollution is an increasingly concerning problem in many metropolitan areas due to its adverse public health and environmental impacts. Vertical atmospheric conditions have strong effects on vertical mixing of air pollutants, which directly affects surface air quality. The characteristics and magnitude of how vertical atmospheric conditions affect surface air quality, which are critical to future air quality projections, have not yet been fully understood. This study aims to enhance understanding of the annual and seasonal sensitivities of air pollution to both surface and vertical atmospheric conditions. Based on both surface and vertical meteorological characteristics provided by 1994–2003 monthly dynamic downscaling data from the Weather and Research Forecast Model, we develop generalized linear models (GLMs) to study the relationships between surface air pollutants (ozone, respirable suspended particulates, and sulfur dioxide) and atmospheric conditions in the Pearl River Delta (PRD) region. Applying Principal Component Regression (PCR) to address multi-collinearity, we study the contributions of various meteorological variables to pollutants’ concentration levels based on the loading and model coefficient of major principal components. Our results show that relatively high pollutant concentration occurs under relatively low mid-level troposphere temperature gradients, low relative humidity, weak southerly wind (or strong northerly wind) and weak westerly wind (or strong easterly wind). Moreover, the correlations vary among pollutant species, seasons, and meteorological variables at various altitudes. In general, pollutant sensitivity to meteorological variables is found to be greater in winter than in other seasons, and the sensitivity of ozone to meteorology differs from that of the other two pollutants. Applying our GLMs to anomalous air pollution episodes, we find that meteorological variables up to mid troposphere (∼700 mb) play an important role in influencing surface air quality, pinpointing the significant and unique associations between meteorological variables at higher altitudes and surface air quality.

中文翻译：

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评估季节性和垂直大气条件对珠江三角洲地区空气质量的影响

摘要 空气污染因其对公共健康和环境的不利影响而成为许多大都市地区日益关注的问题。垂直大气条件对空气污染物的垂直混合影响很大，直接影响地表空气质量。垂直大气条件如何影响地表空气质量的特征和幅度对未来的空气质量预测至关重要，但尚未完全了解。本研究旨在加强对空气污染对地表和垂直大气条件的年度和季节性敏感性的理解。根据天气和研究预报模型 1994-2003 年月度动态降尺度数据提供的地表和垂直气象特征，我们开发了广义线性模型 (GLM) 来研究珠江三角洲 (PRD) 地区的地表空气污染物（臭氧、可吸入悬浮颗粒物和二氧化硫）与大气条件之间的关系。应用主成分回归 (PCR) 来解决多重共线性问题，我们基于主要主成分的载荷和模型系数研究了各种气象变量对污染物浓度水平的贡献。我们的研究结果表明，在对流层中层温度梯度相对较低、相对湿度较低、偏南风（或强北风）和弱西风（或强东风）的情况下，污染物浓度相对较高。此外，不同高度的污染物种类、季节和气象变量之间的相关性也不同。总的来说，冬季污染物对气象变量的敏感性高于其他季节，臭氧对气象的敏感性不同于其他两种污染物。将我们的 GLM 应用于异常空气污染事件，我们发现直到对流层中层 (~700 mb) 的气象变量在影响地表空气质量方面发挥着重要作用，确定了高海拔气象变量与地表空气质量之间显着而独特的关联。