O. Tchepel

INTEGRATED MODELING OF ROAD TRAFFIC EMISSIONS: APPLICATION TO LISBON AIR QUALITY MANAGEMENT

The application of three distinct modeling tools to deal with Lisbon atmospheric problems is presented. Information and forecasting system for private and public transport (VISUM), Transport Emission Model for Line Sources (TREM) and Variable Dispersion (VADIS) models were used to characterize the traffic fluxes, to quantify the emission amounts, and finally to evaluate the air quality in a specific area of the city characterized by intense traffic respectively. The results show the benefit of integrated use of the modeling tools VISUM and TREM to estimate the atmospheric emissions induced by traffic. On the other hand, the results obtained with VADIS are in acceptable agreement with the measured air quality data.

Development Of An Emissions Data Base For Air Pollutants From Mobile Sources In Portugal

A methodology to elaborate a traffic emission inventory for Portugal, particularly for urban areas, is presented. This methodology integrates bottom-up approach for area sources and top-down approaches for line sources. Time dependent functions are used for temporal downscale of emission data. The described methodology was applied to the Lisbon Region, for typical summer and winter conditions. The obtained results were presented in a GIS support that is also a fundamental tool to convert emission data in order to be used by air quality models.

Urban Population Exposure to Particulate Air Pollution Induced by Road Transport

In the last years, there has been an increase of scientific studies confirming that longand short-term exposure to particulate matter pollution leads to adverse health effects. The determination of accumulated human exposure in urban areas (in the present study focused on Lisbon) is the main objective of the current work combining information on concentrations at different microenvironments and population timeactivity pattern data. A link between a mesoscale meteorological model and a local scale model (Computational Fluid Dynamics’ based) was developed to define the boundary conditions for the local scale application. The time-activity pattern of the population was derived from statistical information for different sub-population groups and linked to digital city maps. Finally, the hourly PM10 concentrations for indoor and outdoor microenvironments were estimated for the Lisbon city centre based on the local scale air quality model application for a chosen day. The developed methodology is a first approach to estimate population exposure, calculated as the total daily values above the thresholds recommended for longand short-term health effects. Obtained results reveal that, in fact, in Lisbon city centre a large number of persons are exposed to particulate matter (PM) levels overpassing the legislated limit value. To get more accurate and consistent conclusions, a larger study, including a series of single days, should be performed.

Estimation of the Modelling Uncertainty Related with Stochastic Processes

In the present work a methodology for quantification of modelling uncertainty using decomposed measured data is proposed. The original measured data are decomposed to deterministic and short-term components before the statistical evaluation of the modelling results is performed against the measurements. Using Fourier analysis, the spectral density was obtained for different types of air quality monitoring stations. Next, short-term fluctuations were subtracted from the original data using an iterative moving average filter and taking into account the contribution of higher frequencies determined from the spectral analysis. The methodology was used to estimate uncertainties of the results obtained with CHIMERE model for Portugal. The modelling outputs for one year are compared with the measurement data from different types of air quality stations after the subtraction of short-term variations. The comparison shows a better agreement after the application of the decomposed time series methodology.

Monitoring fire-fighters' smoke exposure and related health effects during Gestosa experimental fires

The main objective of this study is to contribute to the scientific knowledge regarding fire-fighters’ exposure to smoke and its related health effects. Forest fire experiments were developed with an extensive number of measurements of individual exposure to smoke pollutants and of medical parameters for a group of fire-fighters. For the smoke exposure monitoring, ten fire-fighters from four different fire brigades were selected. The fire-fighters’ individual exposure to toxic gases and particulate matter was monitored with portable devices, and their location in time was registered with GPS equipment. For all the monitored fire-fighters, air pollutant concentration values acquired during the fire experiments were beyond the limits recommended by the World Health Organization (WHO), namely for PM2.5, CO and NO2. Daily averages of PM2.5 concentration values as high as 738 µg.m -3 were obtained, well above the recommended limit of 25 µg.m -3 . In terms of CO, hourly averaged values higher than 73,000 µg.m -3 were monitored, clearly above the 30,000 µg.m -3

Health impact assessment of exposure to inhalable particles in Lisbon Metropolitan Area

This study is focused on the assessment of potential health benefits in Lisbon Metropolitan Area, Portugal, using the limit values defined by the new European Directive (2008/50/CE) for short and long-term exposure to PM10. For this purpose, the methodology of the WHO for Health Impact Assessment and Apheis guidelines for data collection was applied. The time series of PM10 concentrations measured within the study area at urban background stations together with demographic data and health indicators were considered. An improved methodology using population mobility data that describes daily average Origin-Destination trips is proposed in this work to analyse the number of persons exposed. The results provide quantitative information on the number of attributable cases potentially prevented annually by reducing PM10 concentration to the levels established by the Air Quality Directive and proposed by WHO guidelines for this pollutant. An intercomparison of two approaches to process input data for the health risk analysis provides information on the sensitivity of the applied methodology.