The state of the art in air quality assessment comprisesinformation and data processing tools using only data fromground-based measurement and atmospheric modelling.Ground measurements are not taken from dense enoughmonitoring networks around the world to permit a satisfactoryanalysis of the influence of air pollution on the health ofvulnerable population groups. Attempts to improve ourestimation of atmospheric pollutant concentrations at theurban and regional scale from combining ground data withnumerical modelling are hampered by the need for highquality and up-to-date emissions inventories, as well asaccurate estimates of initial and boundary conditions of themodels. Information derived from Earth Observation satellitescan bridge the gap between models simulating the transportand chemical transformation of atmospheric pollutants, andanalytical observations.A data fusion methodology was developed to integrate satellitedata with ground-based information and atmospheric modellingto derive PM and ozone loading at the ground level.Physical properties of tropospheric aerosol and ozone arelinked with the atmospheric physical-chemical processes thatdetermine the total mass concentration and size distribution ofparticulate matter and the concentration of ozone. Couplingthese with spatially explicitly exposure-response functions andpopulation data results in refined maps of health riskattributable to air pollution.The methodology was implemented in Athens, Greece andRome, Italy, two capitals characterized by intense photochemicalpollution and long-range transport of dust. Maps ofhealth risk were produced. The spatially scalar nature of theapproach allowed us to evaluate the impact of risk modifierssuch as the existence of urban vegetation and populationsusceptibility. Satellite data can be used efficiently to improvethe spatial link between environmental pollution and humanhealth. The data fusion method proposed herein opens the waytowards the enhanced use of this valuable information inspatial epidemiology and environmental health science.
Spatial health impact assessment of urban air pollutants using Earth observation satellite data / D. A., Sarigiannis; A., Gotti; S., Karakitsios; P., Kalabokas; Manes, Fausto; LA TORRE, Giuseppe. - In: EUROPEAN JOURNAL OF PUBLIC HEALTH. - ISSN 1101-1262. - STAMPA. - 20:Supplement 1(2010), pp. 150-150. ( 3RD EUROPEAN PUBLIC HEALTH CONFERENCE - Integrated Public Helath Amsterdam, The Netherlands 10-13 November 2010) [10.1093/eurpub/ckq129].
Spatial health impact assessment of urban air pollutants using Earth observation satellite data
MANES, Fausto;LA TORRE, Giuseppe
2010
Abstract
The state of the art in air quality assessment comprisesinformation and data processing tools using only data fromground-based measurement and atmospheric modelling.Ground measurements are not taken from dense enoughmonitoring networks around the world to permit a satisfactoryanalysis of the influence of air pollution on the health ofvulnerable population groups. Attempts to improve ourestimation of atmospheric pollutant concentrations at theurban and regional scale from combining ground data withnumerical modelling are hampered by the need for highquality and up-to-date emissions inventories, as well asaccurate estimates of initial and boundary conditions of themodels. Information derived from Earth Observation satellitescan bridge the gap between models simulating the transportand chemical transformation of atmospheric pollutants, andanalytical observations.A data fusion methodology was developed to integrate satellitedata with ground-based information and atmospheric modellingto derive PM and ozone loading at the ground level.Physical properties of tropospheric aerosol and ozone arelinked with the atmospheric physical-chemical processes thatdetermine the total mass concentration and size distribution ofparticulate matter and the concentration of ozone. Couplingthese with spatially explicitly exposure-response functions andpopulation data results in refined maps of health riskattributable to air pollution.The methodology was implemented in Athens, Greece andRome, Italy, two capitals characterized by intense photochemicalpollution and long-range transport of dust. Maps ofhealth risk were produced. The spatially scalar nature of theapproach allowed us to evaluate the impact of risk modifierssuch as the existence of urban vegetation and populationsusceptibility. Satellite data can be used efficiently to improvethe spatial link between environmental pollution and humanhealth. The data fusion method proposed herein opens the waytowards the enhanced use of this valuable information inspatial epidemiology and environmental health science.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
