Mapping air filtering in urban areas. A Land Use Regression model for Ecosystem Services assessment in planning

Abstract

The control of air quality in urban areas is drawing attention, as it generates significant benefits. Land use planning directly affects Ecosystem Services, particularly on air quality. Nonetheless, scientific knowledge of the effects derived by Land Use Changes on air quality is inadequate for planning proposals.This paper proposes an analytical application in the metropolitan area of Milan (North-west of Italy), one of the highly air-polluted areas of Europe. A spatial-based methodology to predict Particulate Matter concentration is tested using the regional emission inventory as a benchmark. The paper assumes that different dynamics cause of air pollution: (i) atmospheric emissions due to different kinds of land use sources; (ii) the rebound/resuspension of particles caused by the impervious degree of soil, and (iii) the absorption through green areas and trees.The methodological innovations introduced by this paper are related to (i) the small gridded distribution of values, and (ii) the emissions dynamics mix up with those on resuspension and absorption.This study experiments the upgrade of the existent Land Use Regression approach for Particulate Matters prediction and establishes a new methodology with a newer set of inputs. Compared to traditional approaches, the study can support the decision-making process for local planning.