TITLE:
Using a Coupled Air Quality Modeling System for the Development of an Air Quality Plan in Madrid (Spain): Source Apportionment and Analysis Evaluation of Mitigation Measures
AUTHORS:
Raúl Arasa, Anna Domingo-Dalmau, Ricardo Vargas
KEYWORDS:
Environmental Assessment, Air Quality Modelling, CMAQ, Emissions, Madrid, Air Quality Plan, Mitigation Measures
JOURNAL NAME:
Journal of Geoscience and Environment Protection,
Vol.4 No.3,
March
18,
2016
ABSTRACT: In this
contribution, we use a coupled air quality modelling system (AQM) as a tool to
design and develop an air quality plan in Madrid. AQM has allowed us to obtain
a preliminary evaluation of the effect of mitigation measures over regional and
local air quality levels. To achieve these goals, we have prepared a sophisticated
AQM, coupling the meteorological model WRF, the emission model AEMM, and the
photochemical model CMAQ. AQM was evaluated using the whole modelling year 2010
working with high horizontal resolution, 3 km for the region of Madrid and 1km
for urban metropolitan area of Madrid. Two different analyses have been
realized: a source apportionment exercise following a zero-out methodology to
obtain the contribution to the air quality levels of the different emission
sector; and an evaluation of the main mitigation measures considered in the air
quality plan using sensitivity analysis. The air quality plan was focused on
the improvement of NO2 levels and AQM analyzed the effect of the
mitigation measures during ten episodes of 2011 where NO2 or O3 levels were the highest of the year; so we analyzed the effect of the
mitigation plan in worst conditions. Results provided by the AQM system show
that it accomplishes the European Directive modelling uncertainty requirements
and the mean absolute gross error for 1-h maximum daily NO2 is 31%
over locations with higher levels of this atmospheric pollutant; the road
traffic is the main contributor to the air quality levels providing a 81% for
NO2, 67% for CO and 46% for PM10; measures defined in the
plan achieve to reduce up to 11 μgm-3 NO2 levels offering
highest reductions over urban areas with traffic influence.