Evaluating the potential of remote sensing imagery in mapping ground-level fine particulate matter (PM2.5) for the Vaal Triangle Priority Area

The quality of air breathed in South Africa is of great concern, especially in industrialised regions where PM2.5 concentrations are high. Long term exposure to PM2.5 is associated with serious adverse health impacts. Traditionally, PM2.5 is monitored by a network of ground-based instruments. However, the coverage of monitoring networks in South Africa is not dense enough to fully capture the spatial variability of PM2.5 concentrations. This study explored whether satellite remote sensing could offer a viable alternative to ground-based monitoring. Using an eight-year record (2009 to 2016) of satellite retrievals (MODIS, MISR and SeaWIFS) for PM2.5 concentrations, spatial variations and temporal trends for PM2.5 are evaluated for the Vaal Triangle Airshed Priority Area (VTAPA). Results are compared to corresponding measurements from the VTAPA surface monitoring stations. High PM2.5 concentrations were clustered around the centre and towards the south-west of the VTAPA over the highly industrialised cities of Vanderbijlpark and Sasolburg. Satellite retrievals tended to overestimate PM2.5 concentrations. Overall, there was a poor spatial agreement between satellite-retrieved PM2.5 estimates and ground-level PM2.5 measurements. Root mean square error values ranged from 6 to 11 µg/m3 and from -0.89 to 0.32 for the correlation coefficient. For satellite remote sensing to be effectively exploited for air quality assessments in the VTAPA and elsewhere, further research to improve the precision and accuracy of satellite-retrieved PM2.5 is required.

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Spatial–Temporal Variations in NO2 and PM2.5 over the Chengdu–Chongqing Economic Zone in China during 2005–2015 Based on Satellite Remote Sensing

Sensors ◽

10.3390/s18113950 ◽

2018 ◽

Vol 18 (11) ◽

pp. 3950 ◽

Cited By ~ 4

Author(s):

Kun Cai ◽

Qiushuang Zhang ◽

Shenshen Li ◽

Yujing Li ◽

Wei Ge

Keyword(s):

Remote Sensing ◽

Satellite Remote Sensing ◽

Fine Particulate Matter ◽

Ground Level ◽

Temporal Variations ◽

Ozone Monitoring Instrument ◽

Economic Zone ◽

Moderate Resolution Imaging Spectroradiometer ◽

High Concentrations ◽

Remote Sensing Techniques

The Chengdu–Chongqing Economic Zone (CCEZ), which is located in southwestern China, is the fourth largest economic zone in China. The rapid economic development of this area has resulted in many environmental problems, including extremely high concentrations of nitrogen dioxide (NO2) and fine particulate matter (PM2.5). However, current ground observations lack spatial and temporal coverage. In this study, satellite remote sensing techniques were used to analyze the variation in NO2 and PM2.5 from 2005 to 2015 in the CCEZ. The Ozone Monitoring Instrument (OMI) and the Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol optical depth (AOD) product were used to retrieve tropospheric NO2 vertical columns and estimate ground-level PM2.5 concentrations, respectively. Geographically, high NO2 concentrations were mainly located in the northwest of Chengdu and southeast of Chongqing. However, high PM2.5 concentrations were mainly located in the center areas of the basin. The seasonal average NO2 and PM2.5 concentrations were both highest in winter and lowest in summer. The seasonal average NO2 and PM2.5 were as high as 749.33 × 1013 molecules·cm−2 and 132.39 µg·m−3 in winter 2010, respectively. Over 11 years, the annual average NO2 and PM2.5 values in the CCEZ increased initially and then decreased, with 2011 as the inflection point. In 2007, the concentration of NO2 reached its lowest value since 2005, which was 230.15 × 1013 molecules·cm−2, and in 2015, the concentration of PM2.5 reached its lowest value since 2005, which was 26.43 µg·m−3. Our study demonstrates the potential use of satellite remote sensing to compensate for the lack of ground-observed data when quantitatively analyzing the spatial–temporal variations in regional air quality.

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A semi-empirical model for predicting hourly ground-level fine particulate matter (PM2.5) concentration in southern Ontario from satellite remote sensing and ground-based meteorological measurements

Remote Sensing of Environment ◽

10.1016/j.rse.2009.09.011 ◽

2010 ◽

Vol 114 (2) ◽

pp. 221-229 ◽

Cited By ~ 104

Author(s):

Jie Tian ◽

Dongmei Chen

Keyword(s):

Remote Sensing ◽

Particulate Matter ◽

Empirical Model ◽

Satellite Remote Sensing ◽

Fine Particulate Matter ◽

Ground Level ◽

Southern Ontario ◽

Fine Particulate ◽

Semi Empirical ◽

Pm2.5 Concentration

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SPARTAN: a global network to evaluate and enhance satellite-based estimates of ground-level particulate matter for global health applications

Atmospheric Measurement Techniques ◽

10.5194/amt-8-505-2015 ◽

2015 ◽

Vol 8 (1) ◽

pp. 505-521 ◽

Cited By ~ 41

Author(s):

G. Snider ◽

C. L. Weagle ◽

R. V. Martin ◽

A. van Donkelaar ◽

K. Conrad ◽

...

Keyword(s):

Remote Sensing ◽

Particulate Matter ◽

Health Effects ◽

Satellite Remote Sensing ◽

Fine Particulate Matter ◽

Ground Level ◽

Water Soluble ◽

Global Network ◽

Spatial Coverage

Abstract. Ground-based observations have insufficient spatial coverage to assess long-term human exposure to fine particulate matter (PM2.5) at the global scale. Satellite remote sensing offers a promising approach to provide information on both short- and long-term exposure to PM2.5 at local-to-global scales, but there are limitations and outstanding questions about the accuracy and precision with which ground-level aerosol mass concentrations can be inferred from satellite remote sensing alone. A key source of uncertainty is the global distribution of the relationship between annual average PM2.5 and discontinuous satellite observations of columnar aerosol optical depth (AOD). We have initiated a global network of ground-level monitoring stations designed to evaluate and enhance satellite remote sensing estimates for application in health-effects research and risk assessment. This Surface PARTiculate mAtter Network (SPARTAN) includes a global federation of ground-level monitors of hourly PM2.5 situated primarily in highly populated regions and collocated with existing ground-based sun photometers that measure AOD. The instruments, a three-wavelength nephelometer and impaction filter sampler for both PM2.5 and PM10, are highly autonomous. Hourly PM2.5 concentrations are inferred from the combination of weighed filters and nephelometer data. Data from existing networks were used to develop and evaluate network sampling characteristics. SPARTAN filters are analyzed for mass, black carbon, water-soluble ions, and metals. These measurements provide, in a variety of regions around the world, the key data required to evaluate and enhance satellite-based PM2.5 estimates used for assessing the health effects of aerosols. Mean PM2.5 concentrations across sites vary by more than 1 order of magnitude. Our initial measurements indicate that the ratio of AOD to ground-level PM2.5 is driven temporally and spatially by the vertical profile in aerosol scattering. Spatially this ratio is also strongly influenced by the mass scattering efficiency.

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