Estimating urban PM10 and PM2.5 concentrations, based on synergistic MERIS/AATSR aerosol observations, land cover and morphology data

Anton Beloconi; Nektarios Chrysoulakis

doi:10.1016/j.rse.2015.10.017

Estimating urban PM10 and PM2.5 concentrations, based on synergistic MERIS/AATSR aerosol observations, land cover and morphology data

Anton Beloconi, Nektarios Chrysoulakis

Mathematical and Statistical Sciences, School of (SoMSS)

Research output: Contribution to journal › Article › peer-review

60 Scopus citations

Abstract

This study evaluates alternative spatio-temporal approaches for quantitative estimation of daily mean Particulate Matter (PM) concentrations. Both fine (PM2.5) and coarse (PM10) concentrations were estimated over the area of London (UK) for the 2002-2012 time period, using Aerosol Optical Thickness (AOT) derived from MERIS (Medium Resolution Imaging Spectrometer)/AATSR (Advanced Along-Track Scanning Radiometer) synergistic observations at 1. km. ×. 1 km resolution. Relative humidity, temperature and the K-Index obtained from MODIS (Moderate Resolution Imaging Spectroradiometer) sensor were used as additional predictors. High-resolution (100. m. ×. 100. m) local urban land cover and morphology datasets were incorporated in the analysis in order to capture the effects of local scale emissions and sequestration. Spatial (2-D) and spatio-temporal (3-D) kriging were applied to in situ urban PM measurements to investigate their association with satellite-derived AOT while accounting for differences in spatial support. Linear mixed-effects models with day-specific and site-specific random intercepts and slopes were estimated to associate satellite-derived products with kriged PM concentration and their predictive performance was evaluated.

Original language	English (US)
Pages (from-to)	148-164
Number of pages	17
Journal	Remote Sensing of Environment
Volume	172
DOIs	https://doi.org/10.1016/j.rse.2015.10.017
State	Published - Jan 1 2016

Keywords

Aerosol optical thickness
Block kriging
Change of support problem
MERIS/AATSR synergy
Mixed-effects models
Particulate matter

ASJC Scopus subject areas

Soil Science
Geology
Computers in Earth Sciences

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10.1016/j.rse.2015.10.017

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title = "Estimating urban PM10 and PM2.5 concentrations, based on synergistic MERIS/AATSR aerosol observations, land cover and morphology data",

abstract = "This study evaluates alternative spatio-temporal approaches for quantitative estimation of daily mean Particulate Matter (PM) concentrations. Both fine (PM2.5) and coarse (PM10) concentrations were estimated over the area of London (UK) for the 2002-2012 time period, using Aerosol Optical Thickness (AOT) derived from MERIS (Medium Resolution Imaging Spectrometer)/AATSR (Advanced Along-Track Scanning Radiometer) synergistic observations at 1. km. ×. 1 km resolution. Relative humidity, temperature and the K-Index obtained from MODIS (Moderate Resolution Imaging Spectroradiometer) sensor were used as additional predictors. High-resolution (100. m. ×. 100. m) local urban land cover and morphology datasets were incorporated in the analysis in order to capture the effects of local scale emissions and sequestration. Spatial (2-D) and spatio-temporal (3-D) kriging were applied to in situ urban PM measurements to investigate their association with satellite-derived AOT while accounting for differences in spatial support. Linear mixed-effects models with day-specific and site-specific random intercepts and slopes were estimated to associate satellite-derived products with kriged PM concentration and their predictive performance was evaluated.",

keywords = "Aerosol optical thickness, Block kriging, Change of support problem, MERIS/AATSR synergy, Mixed-effects models, Particulate matter",

author = "Anton Beloconi and Nektarios Chrysoulakis",

note = "Funding Information: This work was performed in the framework of the PEFYKA project within the KRIPIS Action of the General Secretariat for Research and Technology. The project is funded by Greece and the European Regional Development Fund of the European Union under the NSRF and the O.P. Competitiveness and Entrepreneurship (Ref: 10575-20/09/2013 ). Anton Beloconi is grateful to the MathMods (Mathematical Modeling in Engineering) program for partially funding this work through a scholarship sponsored by the EACEA under the project No. 2008-0100. Yiannis Kamarianakis was partially supported by the National Science Foundation under Award DMS-1419593 . The authors are grateful to three anonymous reviewers for their constructive comments, to the European Space Agency for providing MERIS and AATSR data based on the Category-1 project (ID: 12018) and to the London Air Quality Monitoring Network for providing the PM10 and PM2.5 measurements. Publisher Copyright: {\textcopyright} 2015 Elsevier Inc.",

year = "2016",

month = jan,

day = "1",

doi = "10.1016/j.rse.2015.10.017",

language = "English (US)",

volume = "172",

pages = "148--164",

journal = "Remote Sensing of Environment",

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T1 - Estimating urban PM10 and PM2.5 concentrations, based on synergistic MERIS/AATSR aerosol observations, land cover and morphology data

AU - Beloconi, Anton

AU - Chrysoulakis, Nektarios

N1 - Funding Information: This work was performed in the framework of the PEFYKA project within the KRIPIS Action of the General Secretariat for Research and Technology. The project is funded by Greece and the European Regional Development Fund of the European Union under the NSRF and the O.P. Competitiveness and Entrepreneurship (Ref: 10575-20/09/2013 ). Anton Beloconi is grateful to the MathMods (Mathematical Modeling in Engineering) program for partially funding this work through a scholarship sponsored by the EACEA under the project No. 2008-0100. Yiannis Kamarianakis was partially supported by the National Science Foundation under Award DMS-1419593 . The authors are grateful to three anonymous reviewers for their constructive comments, to the European Space Agency for providing MERIS and AATSR data based on the Category-1 project (ID: 12018) and to the London Air Quality Monitoring Network for providing the PM10 and PM2.5 measurements. Publisher Copyright: © 2015 Elsevier Inc.

PY - 2016/1/1

Y1 - 2016/1/1

N2 - This study evaluates alternative spatio-temporal approaches for quantitative estimation of daily mean Particulate Matter (PM) concentrations. Both fine (PM2.5) and coarse (PM10) concentrations were estimated over the area of London (UK) for the 2002-2012 time period, using Aerosol Optical Thickness (AOT) derived from MERIS (Medium Resolution Imaging Spectrometer)/AATSR (Advanced Along-Track Scanning Radiometer) synergistic observations at 1. km. ×. 1 km resolution. Relative humidity, temperature and the K-Index obtained from MODIS (Moderate Resolution Imaging Spectroradiometer) sensor were used as additional predictors. High-resolution (100. m. ×. 100. m) local urban land cover and morphology datasets were incorporated in the analysis in order to capture the effects of local scale emissions and sequestration. Spatial (2-D) and spatio-temporal (3-D) kriging were applied to in situ urban PM measurements to investigate their association with satellite-derived AOT while accounting for differences in spatial support. Linear mixed-effects models with day-specific and site-specific random intercepts and slopes were estimated to associate satellite-derived products with kriged PM concentration and their predictive performance was evaluated.

AB - This study evaluates alternative spatio-temporal approaches for quantitative estimation of daily mean Particulate Matter (PM) concentrations. Both fine (PM2.5) and coarse (PM10) concentrations were estimated over the area of London (UK) for the 2002-2012 time period, using Aerosol Optical Thickness (AOT) derived from MERIS (Medium Resolution Imaging Spectrometer)/AATSR (Advanced Along-Track Scanning Radiometer) synergistic observations at 1. km. ×. 1 km resolution. Relative humidity, temperature and the K-Index obtained from MODIS (Moderate Resolution Imaging Spectroradiometer) sensor were used as additional predictors. High-resolution (100. m. ×. 100. m) local urban land cover and morphology datasets were incorporated in the analysis in order to capture the effects of local scale emissions and sequestration. Spatial (2-D) and spatio-temporal (3-D) kriging were applied to in situ urban PM measurements to investigate their association with satellite-derived AOT while accounting for differences in spatial support. Linear mixed-effects models with day-specific and site-specific random intercepts and slopes were estimated to associate satellite-derived products with kriged PM concentration and their predictive performance was evaluated.

KW - Aerosol optical thickness

KW - Block kriging

KW - Change of support problem

KW - MERIS/AATSR synergy

KW - Mixed-effects models

KW - Particulate matter

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U2 - 10.1016/j.rse.2015.10.017

DO - 10.1016/j.rse.2015.10.017

M3 - Article

SN - 0034-4257

VL - 172

SP - 148

EP - 164

JO - Remote Sensing of Environment

JF - Remote Sensing of Environment

ER -

Estimating urban PM10 and PM2.5 concentrations, based on synergistic MERIS/AATSR aerosol observations, land cover and morphology data

Abstract

Keywords

ASJC Scopus subject areas

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