Development of a source emission model for atmospheric pollutants in the Barcelona area

Institut de Tecnologia i Modelització Ambiental (ITEMA), Universitat Politècnica de Catalunya (UPC), Apartat de Correus 508, 08220 Terrassa (Barcelona, Spain
Atmospheric Environment (Impact Factor: 3.11). 01/1996; DOI: 10.1016/1352-2310(95)00221-J

ABSTRACT We describe the EMITEMA-EIM atmospheric emission model, and how it has been used along with CORINAIR emission factors to estimate the annual emissions in the Barcelona area in 1990. The study area is a 39 x 39 km2 square with a high population density and important industrial activities. The space and time resolution of the emissions is, respectively, 1 km2 and 1 h. The pollutants considered were NOx, CO, SO2, particles, methane and several VOCs (alkanes, alkenes, aromatics and aldehydes). The emission sources studied were road traffic, air traffic, industrial activities, gas stations, domestic heating and biogenic emission from forests. Methodologies for each of these sources are described in this paper. Finally, we present and analyse the results.

1 Bookmark
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: On-road traffic is the major contributor to pollutant emissions in urban areas. Nowadays different emission abatement strategies are being tested in order to improve urban air quality (e.g. the European Commission currently promotes the use of natural gas as an alternative fuel). Several feasible scenarios regarding the introduction of natural gas vehicles (NGV) are studied in the two main cities of Spain (Barcelona and Madrid) by using the HERMES emission model. The most suitable emission factors to NGV are selected among those available in the literature. The account of emissions in the base case scenario estimated for a typical summertime polluted day of the year 2004 reflects that in Barcelona 86% of primary pollutants come from on-road traffic compared to 93% in Madrid, because of the heavier industrial activity in the former. The introduction of NGV in urban zones would have a positive effect on emissions, whose extent largely depends on the substituted fleets and the conurbation characteristics. Maximum reductions in NO(x) emissions in Madrid are attributed to the substitution of 10% of the oldest diesel and petrol cars, while in Barcelona the change of 50% of the oldest commercial light vehicles becomes more effective. PM(2.5) and SO(2) emissions can be significatively reduced with the introduction of NGV instead of the oldest commercial light vehicles. The substitution of conventional fuels by natural gas must reach around 4% to achieve significative reductions in traffic emissions (larger than 5%). This work focuses on air quality issues, therefore GHG emissions are not included, nevertheless this kind of associated impact has to be considered by the decision makers. Assessing the efficacy of environmental improvement strategies entails a realistic design of emission scenarios and their evaluation. The detailed emission account provides a fundamental basis for the air quality modelling and its comparison among scenarios.
    Science of The Total Environment 06/2009; 407(10):3269-81. · 3.26 Impact Factor
  • Source
    08/2011: pages 279-294; , ISBN: 978-953-307-511-2
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: The aim of the present work is to define top-down approaches to allocate atmospheric emissions from non-industrial combustion plants (residential, institutional and commercial sectors) to a detailed grid system of 100 × 100 m2. The conceptual model adopted permits the use of suitable proxy variables for the scaling down of atmospheric emissions from a provincial to a local scale. 'Resident population', 'building volume' and a statistical combination of both have been used as proxy variables for realizing three emission disaggregation models. The choice of the proxy variables was influenced by both data availability and relevance. The results of the emission disaggregation models have been compared with emission values resulting from a bottom-up approach starting from local data. The selected case study was located in the Emilia-Romagna Region (NE Italy), and NOx was the reference pollutant.
    Atmospheric Environment 11/2013; · 3.11 Impact Factor


Available from
May 22, 2014