Speciated ground-level aerosol concentrations are required to understand and mitigate health impacts from dust storms, wildfires, and other aerosol emissions. Globally, surface monitoring is limited due to cost and infrastructure demands. While remote sensing can help estimate respirable (i.e. ground level) concentrations, current observations are restricted by inadequate spatiotemporal resolution, uncertainty in aerosol type, particle size, and vertical profile. One key issue with current remote sensing datasets is that they are derived from reflectances observed by polar-orbiting imagers, which means that aerosol is only derived during the daytime and only once or twice per day. Newer quantification methods using geostationary infrared (IR) data have focussed on detecting the presence, or absence, of an event. The determination of aerosol composition or particle size using IR exclusively has received little attention. This manuscript summarizes four scientific papers, published as part of a larger study, and identifies requirements for (a) using infrared radiance observations to obtain continual (i.e. day and night) concentration estimates; (b) increasing temporal resolution by using geostationary satellites; (c) utilizing all infrared channels to maximize spectral differences due to compositional changes; and (d) applying a high-pass filter (brightness temperature differences) to identify compositional variability. Additionally, (e) a preliminary calibration methodology was tested against three severe air quality case study incidents, namely, a dust storm, smoke from prescribed burns, and an ozone smog incident, near Sydney in eastern Australia which highlighted the ability of the method to determine atmospheric stability, clouds, and particle size. Geostationary remote sensing provides near-continuous data at a temporal resolution comparable to monitoring equipment. The spatial resolution (~ 4 km² at NADIR) is adequate for large sources but coarse for localized sources. The spectral sensitivity of aerosol is limited and appears to be dominated by humidity changes rather than concentration or compositional changes. Geostationary remote sensing can be used to determine the timing, duration, and spatial extent of an air quality event. Brightness temperature differences can assist in qualifying composition with an order of magnitude estimate of concentration.

需要特定的地面气溶胶浓度来了解和减轻沙尘暴、野火和其他气溶胶排放对健康的影响。在全球范围内，由于成本和基础设施需求，地面监测受到限制。虽然遥感可以帮助估计可呼吸（即地面）浓度，但目前的观测受到时空分辨率不足、气溶胶类型、颗粒大小和垂直剖面的不确定性的限制。当前遥感数据集的一个关键问题是它们源自极轨成像仪观测到的反射率，这意味着气溶胶仅在白天产生，并且每天仅产生一两次。使用对地静止红外 (IR) 数据的较新量化方法侧重于检测事件是否存在。仅使用红外测定气溶胶成分或颗粒大小很少受到关注。本手稿总结了作为大型研究的一部分发表的四篇科学论文，并确定了以下要求：(a) 使用红外辐射观测来获得连续（即白天和夜间）浓度估计； (b) 利用地球静止卫星提高时间分辨率； (c) 利用所有红外通道来最大化由于成分变化引起的光谱差异； (d) 应用高通滤波器（亮度温度差异）来识别成分变化。此外，(e) 针对澳大利亚东部悉尼附近的三个严重空气质量案例研究事件（即沙尘暴、规定燃烧产生的烟雾和臭氧烟雾事件）对初步校准方法进行了测试，这凸显了该方法能够确定大气稳定性、云和颗粒大小。 对地静止遥感以与监测设备相当的时间分辨率提供近乎连续的数据。空间分辨率（NADIR 处约 4 km ² ）对于大型源来说是足够的，但对于局部源来说是粗糙的。气溶胶的光谱灵敏度是有限的，并且似乎主要受湿度变化而不是浓度或成分变化的影响。对地静止遥感可用于确定空气质量事件的时间、持续时间和空间范围。亮度温度差异可以通过浓度的数量级估计来帮助鉴定成分。