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Browsing Computer Science by Subject "Air quality management."

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    Satellite remote sensing of particulate matter and air quality assessment in the Western Cape, South Africa.
    (2016) Padayachi, Yerdashin Rajendran.; Moodley, Deshendran.
    Particulate Matter (PM) is a health risk, even at low ambient concentrations in the atmosphere. The analysis of ambient PM is important in air quality management in South Africa in order to suggest recommendations for pollution abatement. However the cost to monitor or to model surface concentrations are high. Satellite remote sensing retrievals of Aerosol Optical Depth (AOD) are cost effective and have been used in conjunction with surface measurements of PM concentrations for regional air quality studies. The aim of the study was to determine the extent to which AOD could be used as a proxy for air quality analysis of PM pollution in the Western Cape, South Africa. Surface concentrations of particles with diameter 10 μm or less (PM10) measured at Air Quality Monitoring (AQM) stations in George and Malmesbury in 2011 were evaluated using temporal air quality analysis. The AOD were retrieved from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor onboard the Terra and Aqua satellites. Temporal trends of the AOD over Malmesbury and George AQM stations were determined and the extent of the AOD-PM10 relationship quantified through statistical correlation. Additionally meteorological parameters, including wind speed, temperature, rainfall and relative humidity measured at the AQM stations, were included in the study and their impact on AOD-PM10 trends was analysed. The annual AOD-PM10 correlations over Malmesbury in 2011 ranged between 0.24 and 0.36, while the correlations over George ranged between 0.24 and 0.34. A temporal mismatch was observed between seasonal PM10 concentrations and AOD at both sites. The AOD-PM10 relationship over Malmesbury and George were weak, suggesting that the AOD cannot easily be used as a proxy within the air quality analysis of PM10 concentrations measured at Malmesbury and George AQM stations. Specific meteorological conditions were found to be important confounding factors when observing AOD and PM10 trends. In spite of a few weaknesses in current satellite data products identified in this analysis, this study showed that improvements can be made to the use of satellite aerosol remote sensing as a proxy for ground level PM10 mass concentration by addressing the meteorological confounders of the AOD-PM10 relationship.