Exploring the relation between aerosol optical depth and PM&amp;lt;sub&amp;gt;2.5&amp;lt;/sub&amp;gt; at Cabauw, the Netherlands

Schaap, Martijn; Apituley, Arnoud; Timmermans, R. M. A.; Koelemeijer, R.; Leeuw, Gerrit de

doi:10.5194/acpd-8-17939-2008

Cited by 54 publications

(70 citation statements)

References 44 publications

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“…So far, the use of spaceborne AOT for monitoring of surface PM2.5 has much been focused on the USA and China. Only few studies investigate the feasibility of monitoring particulate pollution in Europe (Kacenelenbogen et al, 2006;Pelletier et al, 2007;DiNicolantonio et al, 2009;Glantz et al, 2009;Schaap et al, 2009). Furthermore, little is known about the applicability of the AOT-to-PM2.5 relationship for rather clean conditions with a PM2.5 concentration lower than 20 mg m .…”

Section: Introductionmentioning

confidence: 99%

Spaceborne observations of low surface aerosol concentrations in the Stockholm region

Tesche¹,

Glantz²,

Johansson

2016

Tellus B: Chemical and Physical Meteorology

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A B S T R A C TThis article investigates the feasibility of using spaceborne observations of aerosol optical thickness (AOT) derived with the Moderate Resolution Imaging Spectroradiometer (MODIS) for monitoring of fine particulate matter (PM2.5) in an environment of low aerosol loading. Previous studies of the AOT-to-PM2.5 relationship benefit from the large range of observed values. The Stockholm region features a comprehensive network of ground-based monitoring stations that generally show PM2.5 values B20 mg m (3 . MODIS AOT at 555 nm is usually B0.20 and in good agreement with ground-based sun photometer observations in this region. We use MODIS Collection 5 AOT data with a horizontal resolution of 10 km )10 km and ground-based in-situ PM2.5 observations to derive an AOT-to-PM2.5 relationship that can be used to estimate fields of PM2.5. This has been carried out with respect to the months from April to September of the period 2000Á2013. Relative average absolute deviations of 33Á55 % (mean of 45 %) are obtained between MODIS-retrieved and ground-based PM2.5. The root mean square error is 0.2159 mg m (3 between retrieved and measured PM2.5. From spaceborne lidar observations, it is found that elevated aerosol layers are generally sparse in the Stockholm region. This favours remote sensing of PM2.5 from space. The deviations found between measured and retrieved PM2.5 are mainly attributed to infrequent situations of inhomogeneous aerosol layering for which column-integrated observations cannot be connected to surface conditions. Using MODIS Collection 6 data with a resolution of 3 km)3 km in a case study actually gives far fewer results than the coarser Collection 5 product. This is explained by the complex geography of the Stockholm region with a coastline and an abundance of lakes, which seems to induce biases in the retrieval of AOT at higher spatial resolution.

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Section: Introductionmentioning

confidence: 99%

Spaceborne observations of low surface aerosol concentrations in the Stockholm region

Tesche¹,

Glantz²,

Johansson

2016

Tellus B: Chemical and Physical Meteorology

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“…Advances in satellite remote sensing have provided a cost-effective approach to frequently monitor the spatial distribution and the regional transport of aerosol particles on a large scale [8][9][10][11][12][13][14], though the discontinuous satellite observations could hardly reflect the diurnal variations of particle matters. Aerosol optical thickness (AOT), derived from satellite observations, is a dimensionless measure of aerosol abundance and atmospheric extinction of radiance over the entire air column.…”

Section: Introductionmentioning

confidence: 99%

Retrieval of High-Resolution Atmospheric Particulate Matter Concentrations from Satellite-Based Aerosol Optical Thickness over the Pearl River Delta Area, China

Yang

Wang

2015

Remote Sensing

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Satellite remote sensing offers an effective approach to estimate indicators of air quality on a large scale. It is critically significant for air quality monitoring in areas experiencing rapid urbanization and consequently severe air pollution, like the Pearl River Delta (PRD) in China. This paper starts with examining ground observations of particulate matter (PM) and the relationship between PM10 (particles smaller than 10 μm) and aerosol optical thickness (AOT) by analyzing observations on the sampling sites in the PRD. A linear regression (R 2 = 0.51) is carried out using MODIS-derived 500 m-resolution AOT and PM10 concentration from monitoring stations. Data of atmospheric boundary layer (ABL) height and relative humidity are used to make vertical and humidity corrections on AOT. Results after correction show higher correlations (R 2 = 0.55) between extinction coefficient and PM10. However, coarse spatial resolution of meteorological data affects the smoothness of retrieved maps, which suggests high-resolution and accurate meteorological data are critical to increase retrieval accuracy of PM. Finally, the model provides the spatial distribution maps of instantaneous and yearly average PM10 over the PRD. It is proved that observed PM10 is more relevant to yearly mean AOT than instantaneous values.

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“…Liu et al (2004Liu et al ( , 2005) also showed the Multi-Angle Imaging Spectroradiometer (MISR; Diner et al, 2002) on board Terra to have similar capabilities for air quality applications. Several research efforts have worked towards establishing empirical satellite-based AOD-PM relationships in different regions of the world (e.g., Engel-Cox et al, 2004;Gupta et al, 2006;Schaap et al, 2009), as well as deriving satellitebased AOD products with higher resolution for comparison to urban domains (e.g., Li et al, 2005;Kumar et al, 2007;Wong et al, 2011;Bilal et al, 2013). Meteorological parameters, such as relative humidity (RH), wind direction and speed (e.g., Gupta and Christopher, 2009a, b), are also shown to be important in establishing AOD-PM correlations.…”

Section: Introductionmentioning

confidence: 99%

Relationship between Aerosol Optical Depth and Particulate Matter over Singapore: Effects of Aerosol Vertical Distributions

Chew

Campbell²,

Hyer³

et al. 2016

Aerosol Air Qual. Res.

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As part of the Seven Southeast Asian Studies (7SEAS) program, an Aerosol Robotic Network (AERONET) sun photometer and a Micro-Pulse Lidar Network (MPLNET) instrument have been deployed at Singapore to study the regional aerosol environment of the Maritime Continent (MC). In addition, the Navy Aerosol Analysis and Prediction System (NAAPS) is used to model aerosol transport over the region. From 24 September 2009 to 31 March 2011, the relationships between ground-, satellite-and model-based aerosol optical depth (AOD) and particulate matter with aerodynamic equivalent diameters less than 2.5 µm (PM 2.5 ) for air quality applications are investigated. When MPLNET-derived aerosol scale heights are applied to normalize AOD for comparison with surface PM 2.5 data, the empirical relationships are shown to improve with an increased 11%, 10% and 5% in explained variances, for AERONET, MODIS and NAAPS respectively. The ratios of root mean square errors to standard deviations for the relationships also show corresponding improvements of 8%, 6% and 2%. Aerosol scale heights are observed to be bimodal with a mode below and another above the stronglycapped/deep near-surface layer (SCD; 0-1.35 km). Aerosol extinctions within the SCD layer are well-correlated with surface PM 2.5 concentrations, possibly due to strong vertical mixing in the region.

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Exploring the relation between aerosol optical depth and PM<sub>2.5</sub> at Cabauw, the Netherlands

Cited by 54 publications

References 44 publications

Spaceborne observations of low surface aerosol concentrations in the Stockholm region

Spaceborne observations of low surface aerosol concentrations in the Stockholm region

Retrieval of High-Resolution Atmospheric Particulate Matter Concentrations from Satellite-Based Aerosol Optical Thickness over the Pearl River Delta Area, China

Relationship between Aerosol Optical Depth and Particulate Matter over Singapore: Effects of Aerosol Vertical Distributions

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