SciELO - Scientific Electronic Library Online

 
vol.35 número1Vulnerabilidad y Riesgo por Plaguicidas en Horticultura del Cinturón Verde en Córdoba, Argentina índice de autoresíndice de materiabúsqueda de artículos
Home Pagelista alfabética de revistas  

Servicios Personalizados

Revista

Articulo

Indicadores

Links relacionados

  • En proceso de indezaciónCitado por Google
  • No hay articulos similaresSimilares en SciELO
  • En proceso de indezaciónSimilares en Google

Compartir


Revista Facultad Nacional de Salud Pública

versión impresa ISSN 0120-386X

Resumen

LONDONO-CIRO, Libardo A.; CANON-BARRIGA, Julio E.  y  GIRALDO-OCAMPO, Julián D.. A spatial proximity model to define monitoring sites in urban air quality networks. Rev. Fac. Nac. Salud Pública [online]. 2017, vol.35, n.1, pp.112-122. ISSN 0120-386X.  https://doi.org/10.17533/udea.rfnsp.v35n1a12.

This paper presents a model of spatial proximity to roads, industrial uses of land and green areas, to determine concentrations of particulate matter and locate air quality monitoring sites in urban areas. The model uses monthly average concentration of PM10 (µgm/m3) measured at nine monitoring sites in the city of Medellin between January 2003 and December 2008. With these data, monthly maps were calculated using geostatistical interpolation methods with J-Bessel semivariograms to characterize the concentration of PM10. Three factors of spatial proximity (to main roads, industries and green areas) were calculated along with one combined factor. They were then multiplied by the concentration maps. With this result, a network of monitoring sites was proposed for Medellín. The Spatial analysis techniques and the proximity model allow for the assessment of the distribution of the contaminant on the territory, highlighting the effect of intersections and industrial areas on high concentrations and the dampening effect of green areas. This work may complement the existing regulatory provisions in Colombia for locating critical monitoring sites of the air quality surveillance systems.

Palabras clave : Spatial proximity model; Air Pollution.

        · resumen en Español | Portugués     · texto en Español     · Español ( pdf )