Integrating lidar and satellite optical depth with ambient monitoring for 3-dimensional particulate characterization

Engel-Cox, Jill; Hoff, R. M.; Rogers, Raymond R.; Dimmick, Fred; Rush, Alan C.; Szykman, J.; Al-Saadi, J. A.; Chu, D. A.; Zell, E.

doi:10.1016/j.atmosenv.2006.02.039

Cited by 139 publications

(73 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…This paper significantly expands upon previous research by presenting an analysis of the seasonal-and platform-dependent relationships between the satellite-based AOD and in situ PM 2.5 components of an integrated threedimensional air quality system (3D-AQS) database 9,17 for the Baltimore, MD/Washington, DC metropolitan airshed. The PM 2.5 concentrations used in this study are measured at ground-based monitoring sites that include Air Quality System (AQS) Federal Reference Method filter-based monitors, which measure 24-hr average PM 2.5 concentrations, and tapered element oscillating microbalance (TEOM) monitors, which report continuous hourly concentrations of PM 2.5 .…”

Section: Introductionmentioning

confidence: 97%

An Improved Method for Estimating Surface Fine Particle Concentrations Using Seasonally Adjusted Satellite Aerosol Optical Depth

Weber

Engel-Cox²,

Hoff

et al. 2010

Journal of the Air & Waste Management Association

Self Cite

View full text Add to dashboard Cite

Using satellite observations of aerosol optical depth (AOD) to estimate surface concentrations of fine particulate matter (PM 2.5 ) is a well-established technique in the air quality community. In this study, the relationships between PM 2.5 concentrations measured at five monitor locations in the Baltimore, MD/Washington, DC region and AOD from Moderate Resolution Imaging Spectroradiometer (MODIS), Multi-Angle Imaging Spectroradiometer (MISR), and Geostationary Operational Environmental Satellite (GOES) were calculated for the summer of 2004 and all of 2005. Linear regression methods were used to determine the direct quantitative relationships between the satellite AOD values and PM 2.5 concentration measurements. Results show that correlations between AOD and surface PM 2.5 concentrations range from 0.46 to 0.84 for the analyzed time period. Correlations with AOD from MODIS and MISR were higher than those from GOES, likely because of variations in the algorithms used by the different instruments. To determine the relative usefulness of platform-and season-specific AOD PM 2.5 regression analysis, the results from this study were used to estimate surface PM 2.5 concentrations for two representative case studies. This analysis of case studies demonstrates that it is necessary to include season and satellite platform information for more accurate estimates of surface PM 2.5 concentrations from satellite AOD data. Consequently, tools that currently use a constant relationship to estimate surface PM 2.5 concentrations from satellite AOD data, such as the Infusing satellite Data into Environmental Applications (IDEA) website, may need to be revised to include parameters that allow the relationships to vary with season and satellite platform to provide more accurate results.

show abstract

Section: Introductionmentioning

confidence: 97%

An Improved Method for Estimating Surface Fine Particle Concentrations Using Seasonally Adjusted Satellite Aerosol Optical Depth

Weber

Engel-Cox²,

Hoff

et al. 2010

Journal of the Air & Waste Management Association

Self Cite

View full text Add to dashboard Cite

show abstract

“…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. Previous researches have revealed a strong positive relationship between satellite-based measurements of AOT and ground-based measurements of particulate matters smaller than 2.5 μm and 10 μm in aerodynamic diameters (PM2.5 and PM10, respectively) [15][16][17][18][19][20][21][22][23][24][25]. A summary of linear AOT/PM relationships, intercepts and correlation coefficients in several previous studies is shown in Table 1.…”

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

View full text Add to dashboard Cite

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.

show abstract

“…The Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument was launched in 2006 on the Cloud-Aerosol Lidar and Pathfinder Satellite Observations (CALIPSO) spacecraft, and has now provided over 8 yr of nearly continuous global measurements of aerosols and clouds with high vertical and spatial resolution. The vertical distribution of aerosols, provided by lidar, is not only important for radiative forcing (e.g., Satheesh, 2002), but also for other applications including air quality studies (e.g., Al-Saadi et al, 2005;Engel-Cox et al, 2006), and model validation (Dirksen et al, 2009;Koffi et al, 2012).…”

Section: Introductionmentioning

confidence: 99%

Looking through the haze: evaluating the CALIPSO level 2 aerosol optical depth using airborne high spectral resolution lidar data

et al. 2014

View full text Add to dashboard Cite

Abstract. The Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument onboard the Cloud-Aerosol Lidar and Pathfinder Satellite Observations (CALIPSO) spacecraft has provided over 8 yr of nearly continuous vertical profiling of Earth's atmosphere. In this paper we investigate the V3.01 and V3.02 CALIOP 532 nm aerosol layer optical depth (AOD) product (i.e the AOD of individual layers) and the column AOD product (i.e., the sum AOD of the complete column) using an extensive database of coincident measurements. The CALIOP AOD measurements and AOD uncertainty estimates are compared with collocated AOD measurements collected with the NASA High Spectral Resolution Lidar (HSRL) in the North American and Caribbean regions. In addition, the CALIOP aerosol lidar ratios are investigated using the HSRL measurements.In general, compared with the HSRL values, the CALIOP layer AOD are biased high by less than 50 % for AOD < 0.3 with higher errors for higher AOD. Less than 60 % of the HSRL AOD measurements are encompassed within the CALIOP layer 1 SD uncertainty range (around the CALIOP layer AOD), so an error estimate is created to encompass 68 % of the HSRL data. Using this new metric, the CALIOP layer AOD error is estimated using the HSRL layer AOD as ±0.035 ± 0.05 · (HSRL layer AOD) at night and ±0.05 ± 0.05 · (HSRL layer AOD) during the daytime. Furthermore, the CALIOP layer AOD error is found to correlate with aerosol loading as well as aerosol subtype, with the AODs in marine and dust layers agreeing most closely with the HSRL values. The lidar ratios used by CALIOP for polluted dust, polluted continental, and biomass burning layers are larger than the values measured by the HSRL in the CALIOP layers, and therefore the AODs for these types retrieved by CALIOP were generally too large.We estimated the CALIOP column AOD error can be expressed as ±0.05 ± 0.07 · (HSRL column AOD) at night and ±0.08 ± 0.1 · (HSRL column AOD) during the daytime. Multiple sources of error contribute to both positive and negative errors in the CALIOP column AOD, including multiple layers in the column of different aerosol types, lidar ratio errors, cloud misclassification, and undetected aerosol layers. The undetected layers were further investigated and we found that the layer detection algorithm works well at night, although undetected aerosols in the free troposphere introduce a mean underestimate of 0.02 in the column AOD in the data set examined. The decreased signal-to-noise ratio (SNR) during the daytime led to poorer performance of the layer detection. This caused the daytime CALIOP column AOD to be less accurate than during the nighttime, because CALIOP frequently does not detect optically thin aerosol layers with AOD < 0.1. Given that the median vertical extent of aerosol detected within any column was 1.6 km during the nighttime and 1.5 km during the daytime, we can estimate the minimum extinction detection threshold to be 0.012 km −1 at night and 0.067 km −1 during the daytime in a layer median sense.This extensive valida...

show abstract

Integrating lidar and satellite optical depth with ambient monitoring for 3-dimensional particulate characterization

Cited by 139 publications

References 8 publications

An Improved Method for Estimating Surface Fine Particle Concentrations Using Seasonally Adjusted Satellite Aerosol Optical Depth

An Improved Method for Estimating Surface Fine Particle Concentrations Using Seasonally Adjusted Satellite Aerosol Optical Depth

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

Looking through the haze: evaluating the CALIPSO level 2 aerosol optical depth using airborne high spectral resolution lidar data

Contact Info

Product

Resources

About