Air Quality Research Using Remote Sensing

Abstract

Air pollution is a worldwide environmental hazard with serious consequences for health and climate as well as for agriculture, ecosystems, and cultural heritage, among others. According to the WHO, there are 8 million premature deaths every year resulting from exposure to ambient air pollution. In addition, more than 90% of the world’s population lives in places where air quality is poor, exceeding the recommended limits; most of these places are in low- or middle-income countries. Air pollution and climate influence each other through complex physicochemical interactions in the atmosphere, altering the Earth’s energy balance, with implications for climate change and air quality. It is vital to measure specific atmospheric parameters and pollutant concentrations, monitor their variations, and analyze different scenarios with the aim of assessing air pollution levels and developing early-warning and forecast systems; such developments provide a means of improving air quality and assuring public health in favor of a reduction in air pollution casualties and a mitigation of climate change phenomena. Eleven research papers were published in this Special Issue, comprising one communication paper [ 1], seven articles [2– 8 ], two technical notes [9 ,10 ], and one letter [11]. The published research signals the potential of applying remote sensing data in air quality studies, including combination with in situ data [1, 3 ,6 ,8], modeling approaches [ 2, 9 ,11 ], and the synergy of different instrumentations and techniques [4 ,5 ,7 ,10 ]. Significant pollutants considered in the studies include aerosols—using PM2.5 and aerosol optical depth (AOD) as quantification variables [1,2 ,4, 5,9]—nitrogen dioxide (NO2 ) [7, 8,11 ], formaldehyde (HCHO) [ 3 ], and carbon monoxide (CO) [6,10], among others [10].