Comparison and Assessment of Two Emission inventories for the Madrid Region

Emission inventories are databases that aim to describe the polluting activities that occur across a certain geographic domain. According to the spatial scale, the availability of information will vary as well as the applied assumptions, which will strongly influence its quality, accuracy and representativeness. This study compared and contrasted two emission inventories describing the Greater Madrid Region (GMR) under an air quality simulation approach. The chosen inventories were the National Emissions Inventory (NEI) and the Regional Emissions Inventory of the Greater Madrid Region (REI). Both of them were used to feed air quality simulations with the CMAQ modelling system, and the results were compared with observations from the air quality monitoring network in the modelled domain. Through the application of statistical tools, the analysis of emissions at cell level and cell – expansion procedures, it was observed that the National Inventory showed better results for describing on – road traffic activities and agriculture, SNAP07 and SNAP10. The accurate description of activities, the good characterization of the vehicle fleet and the correct use of traffic emission factors were the main causes of such a good correlation. On the other hand, the Regional Inventory showed better descriptions for non – industrial combustion (SNAP02) and industrial activities (SNAP03). It incorporated realistic emission factors, a reasonable fuel mix and it drew upon local information sources to describe these activities, while NEI relied on surrogation and national datasets which leaded to a poorer representation. Off – road transportation (SNAP08) was similarly described by both inventories, while the rest of the SNAP activities showed a marginal contribution to the overall emissions

Improvements of air quality simulations of particulate matter in the Iberian peninsula with road dust resuspension and dust emission modules

The Mediterranean Basin is one of the most sensitive zones in the planet to air pollution. Besides anthropogenic emissions, the Iberian Peninsula is affected by natural particule matter (PM) sources. Dry weather conditions allow road dust to be resuspended by vehicle-induced turbulence. These emissions may be as important as those directly emitted by vehicles (combustion and from road abrasion and tyre and break wear processes). In addition, it is widely documented that crustal particles transported from the Saharan Desert may contribute significantly to ambient PM concentration in Madrid. This poster summarizes the methodology and results of the implementation of a module to account for these sources -not included in current emission inventories- into the Eulerian air quality model CMAQ. Comparison of predicted PM concentrations with ambient air quality measurements and satellite observation point out that this module clearly improves the performance of the standard CMAQ version

Analysis of Contributions to NO2 Ambient Air Quality Levels in Madrid City (Spain) through Modeling. Implications for the Development of Policies and Air Quality Monitoring

As environmental standards become more stringent (e.g. European Directive 2008/50/EC), more reliable and sophisticated modeling tools are needed to simulate measures and plans that may effectively tackle air quality exceedances, common in large cities across Europe, particularly for NO2. Modeling air quality in urban areas is rather complex since observed concentration values are a consequence of the interaction of multiple sources and processes that involve a wide range of spatial and temporal scales. Besides a consistent and robust multi-scale modeling system, comprehensive and flexible emission inventories are needed. This paper discusses the application of the WRF-SMOKE-CMAQ system to the Madrid city (Spain) to assess the contribution of the main emitting sectors in the region. A detailed emission inventory was compiled for this purpose. This inventory relies on bottom-up methods for the most important sources. It is coupled with the regional traffic model and it makes use of an extensive database of industrial, commercial and residential combustion plants. Less relevant sources are downscaled from national or regional inventories. This paper reports the methodology and main results of the source apportionment study performed to understand the origin of pollution (main sectors and geographical areas) and define clear targets for the abatement strategy. Finally the structure of the air quality monitoring is analyzed and discussed to identify options to improve the monitoring strategy not only in the Madrid city but the whole metropolitan area

Implementation of a module for risk of ozone impacts assessment to vegetation in the integrated assessment modelling system for the Iberian peninsula. Evaluation for wheat and holm oak

A module to estimate risks of ozone damage to vegetation has been implemented in the Integrated Assessment Modelling system for the Iberian Peninsula. It was applied to compute three different indexes for wheat and Holm oak; daylight AOT40 (cumulative ozone concentration over 40 ppb), cumulative ozone exposure index according to the Directive 2008/50/EC (AOT40-D) and PODY (Phytotoxic Ozone Dose over a given threshold of Y nmol m−2 s−1). The use of these indexes led to remarkable differences in spatial patterns of relative ozone risks on vegetation. Ozone critical levels were exceeded in most of the modelling domain and soil moisture content was found to have a significant impact on the results. According to the outputs of the model, daylight AOT40 constitutes a more conservative index than the AOT40-D. Additionally, flux-based estimations indicate high risk areas in Portugal for both wheat and Holm oak that are not identified by AOT-based methods

Comunidades de algas como bioindicadores de calidad ambiental en la costa rocosa del Mediterráneo (S. E. Península Ibérica)

Ecological tools are commonly used to monitor ecosystems and improve their evaluation and management. Bioindicadors are a good option to use for this purpose. Macroalgae stand out as good bioindicators of environmental quality. In the present study, algal communities were compared between protected and unprotected marine areas. We compared algal cover in relation with the areas under study, and calculated similarity values to determine the most relevant species and to those, we applied multi-dimensional scaling tests. In total, we identified 13 algal especies.  The cover of  Cystoseira mediterranea and Ellisolandia elongata was higher in the protected area, while Ulva intestinalis and Caulerpa racemosa were predominant in the unprotected area. The latter two species are considered bioindicators of impacted areas.En el seguimiento de los ecosistemas es frecuente el uso de herramientas ecológicas del medio para su evaluacón y gestión, motivo por el cual los bioindicadores constituyen un elemento fiable para tal fin. Las algas se destacan por ser buenos bioindicadores de calidad ambiental, por ello en este estudio se compararon las comunidades de algas de un área marina protegida y una no protegida. Se realizaron análisis comparando la cobertura algal en relación con las áreas estudiadas y se obtuvieron valores de similitud donde se destacaron las especies más relevantes para posteriormente aplicarles que la cobertura de Cystoseira mediterranea y Ellisolandia elongata fue mayor en el área protegida, mientras que Ulva intestinalis y Caulerpa racemosa predominaron en la zona no protegida. Estas últimas se consideran como especies indicadoras de áreas impactadas

Comparasion of road traffic emission models in Madrid (Spain)

Many cities in Europe have difficulties to meet the air quality standards set by the European legislation, most particularly the annual mean Limit Value for NO2. Road transport is often the main source of air pollution in urban areas and therefore, there is an increasing need to estimate current and future traffic emissions as accurately as possible. As a consequence, a number of specific emission models and emission factors databases have been developed recently. They present important methodological differences and may result in largely diverging emission figures and thus may lead to alternative policy recommendations. This study compares two approaches to estimate road traffic emissions in Madrid (Spain): the COmputer Programme to calculate Emissions from Road Transport (COPERT4 v.8.1) and the Handbook Emission Factors for Road Transport (HBEFA v.3.1), representative of the ‘average-speed’ and ‘traffic situation’ model types respectively. The input information (e.g. fleet composition, vehicle kilometres travelled, traffic intensity, road type, etc.) was provided by the traffic model developed by the Madrid City Council along with observations from field campaigns. Hourly emissions were computed for nearly 15 000 road segments distributed in 9 management areas covering the Madrid city and surroundings. Total annual NOX emissions predicted by HBEFA were a 21% higher than those of COPERT. The discrepancies for NO2 were lower (13%) since resulting average NO2/NOX ratios are lower for HBEFA. The larger differences are related to diesel vehicle emissions under “stop & go” traffic conditions, very common in distributor/secondary roads of the Madrid metropolitan area. In order to understand the representativeness of these results, the resulting emissions were integrated in an urban scale inventory used to drive mesoscale air quality simulations with the Community Multiscale Air Quality (CMAQ) modelling system (1 km2 resolution). Modelled NO2 concentrations were compared with observations through a series of statistics. Although there are no remarkable differences between both model runs, the results suggest that HBEFA may overestimate traffic emissions. However, the results are strongly influenced by methodological issues and limitations of the traffic model. This study was useful to provide a first alternative estimate to the official emission inventory in Madrid and to identify the main features of the traffic model that should be improved to support the application of an emission system based on “real world” emission factors

Health impact assessment by the implementation of Madrid City air-quality plan in 2020

OBJECTIVES: Air pollutant concentrations in many urban areas are still above the legal and recommended limits that are set to protect the citizens' health. Madrid is one of the cities where traffic causes high NO2 levels. In this context, Madrid City Council launched the Air Quality and Climate Change Plan for the city of Madrid (Plan A), a local strategy approved by the previous government in 2017. The aim of this study was to conduct a quantitative health impact assessment to evaluate the number of premature deaths that could potentially be prevented by the implementation of Plan A in Madrid in 2020, at both citywide and within-city level. The main purpose was to support decision-making processes in order to maximize the positive health impacts from the implementation of Plan A measures. METHODS: The Regional Statistical Office provided information on population and daily mortality in Madrid. For exposure assessment, we estimated PM2.5, NO2 and O3 concentration levels for Madrid city in 2012 (baseline air-quality scenario) and 2020 (projected air-quality scenario based on the implementation of Plan A), by means of an Eulerian chemical-transport model with a spatial resolution of 1 km × 1 km and 30 vertical levels. We used the concentration-response functions proposed by two relevant WHO projects to calculate the number of attributable annual deaths corresponding to all non-accidental causes (ICD-10: A00-R99) among all-ages and the adult population (>30 years old) for each district and for Madrid city overall. This health impact assessment was conducted dependant on health-data availability. RESULTS: In 2020, the implementation of Plan A would imply a reduction in the Madrid citywide annual mean PM2.5 concentration of 0.6 μg/m3 and 4.0 μg/m3 for NO2. In contrast, an increase of 1 μg/m3 for O3 would be expected. The annual number of all-cause deaths from long-term exposure (95% CI) that could be postponed in the adult population by the expected air-pollutant concentration reduction was 88 (57-117) for PM2.5 and 519 (295-750) for NO2; short-term exposure accounted for 20 (7-32) for PM2.5 and 79 (47-111) for NO2 in the total population. According to the spatial distribution of air pollutants, the highest mortality change estimations were for the city centre - including Madrid Central and mainly within the M-30 ring road -, as compared to peripheral districts. The positive health impacts from the reductions in PM2.5 and NO2 far exceeded the adverse mortality effects expected from the increase in O3. CONCLUSIONS: Effective implementation of Plan A measures in Madrid city would bring about an appreciable decline in traffic-related air-pollutant concentrations and, in turn, would lead to significant health-related benefits.This HIA study was funded by the European Project ICARUS (Integrated Climate forcing and Air pollution Reduction in Urban Systems; Horizon 2020, GA N° 690105) and by SaludAire-España (Contaminación atmosférica y salud en España: morbilidad en atención primaria y mortalidad; Carlos III Health Institute, AESI grant PI18CIII/00022). Air-quality modelling was funded by the Madrid City Council (Environment and Mobility Division of the General Directorate of Sustainability and Environmental Control) within the framework for the development and assessment of Plan A.S

Implementation of road dust resuspension in air quality simulations of particulate matter in Madrid (Spain)

An evaluation of the concentration levels of Particulate Matter (PM) was carried out in Madrid (Spain) by introducing the emissions from road dust resuspension. Road dust resuspension emission factors (EF) for different types of vehicles were calculated from EPA-AP42, a global resuspension factor of 0.097 g veh−1 km−1 as described in Amato et al. (2010) and a rain-dependent correction factor. With these resuspension EFs, a simulation at street canyon level was performed with the OSPM model without rainfall. Subsequently, a simulation using the CMAQ model was implemented adding resuspension emissions affected by the rain. These data were compared with monitored data obtained from air quality stations. OSPM model simulations with resuspension EFs but without the effect of rainfall improve the PM estimates in about 20 μg m−3 compared to the simulation with default EFs. Total emissions were calculated by adding the emissions estimated with resuspension EFs to the default PM emissions to be used by CMAQ. For the study in the Madrid Area, resuspension emissions are approximately of the same order of magnitude as inventoried emissions. On a monthly scale, rain effects are negligible for resuspension emissions due to the dry weather conditions of Spain. With the exception of April and May, the decrease in resuspension emissions is not >3%. The predicted PM10 concentration increases up to 9 μg m−3 on annual average for each station compared to the same scenario without resuspension. However, in both cases, PM10 estimates with resuspension are still underestimating observations. It should be noted that although that accounting for resuspension improves the quality of model predictions, other PM sources (e.g., Saharan dust) were not considered in this study.This project was partially financed by the Spanish Ministry of the Environment (SERCA-058/PC08/3-18.1).Peer reviewedPeer Reviewe