Abstract. 1 Introduction

Transcription

1 Development of an emissions data base for air pollutants from mobile sources in Portugal C. Borrego, N. Barros, O. Tchepel, M. Lopes and A. Miranda Department of Environment and Planning, University ofaveiro, 3810AVEIRO, Portugal Abstract 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 approach 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. 1 Introduction The road traffic is continually increasing around the World. Portugal is one of the European Union countries where the transport sector, measured in terms of the number of vehicles multiplied by the number of kilometres travelled, has grown much faster than gross domestic product, while the population has remained stable [1]. According to this source, an unprecedented road-building process has been under way for the last 10 years in Portugal: from 1990 to 1994, the total length of motorway increased from 318 to 587 km, an 84% increase! This trend is expected to continue and emissions from the transport sector, which are mainly related to gasoline and diesel combustion, are expected to increase 46% between 1990 and 2000 and 78% by 2010 [1]. The main pollutants emitted by automobile vehicles are carbon monoxide (CO), nitrogen oxides (NO%) and volatile organic compounds

2 286 Urban Transport and the Environment for the 21st Century (VOC). At present, about 56.5% of CO, 48.3% of NO%, 12.6% of VOC from the total annual emissions are produced, in Portugal, by the transport sector [2]. Attending to the expected increase of this activity's sector, emissions from automobile vehicles should be a source of large concern. This concern would be greater if one considers that 80% of the Portuguese territory contains only 20% of the population, the remaining population being concentrated on the coast, mainly in the large cities of Lisbon and Oporto [1]. One of the main sources contributing to the deterioration of the air quality in urban areas is road traffic. Micrometeorological conditions preventing the dispersion of pollutants also contribute to the overall deterioration of urban air quality and lead to especially acute episodes of air pollution [3]. To design an effective air pollution abatement strategy it is necessary to identify pollution sources and to quantify their emissions. This emission information shall be used afterwards as input data to mathematical dispersion models that can be applied to assess the effectiveness of control strategies. Therefore, the elaboration of a road traffic emission's inventory constitute an important step for atmospheric modelling, models validation, air pollution control strategies and other scientific applications and political decision. The main purpose of this paper is to describe the methodology applied to develop an emission inventory for air pollutants from traffic sources in Portugal, particularly in urban areas. The application of this methodology to an urban case study will be presented. 2 A Case Study Emission inventory developed for Portugal integrates the PolAr database and includes emissions information covering almost all anthropogenic and biogenic sources with high spatial and temporal resolution [4, 7]. In order to estimate traffic urban emissions, the developed methodology was applied to the Lisbon Region, which includes 2 NUT III from CORINAIR90: "Peninsula de Setubal" and "Grande Lisboa". It covers 15 municipalities and 185 submunicipal administrative units ("freguesias"). The Lisbon Region include important urban and industrial zones, with almost 3 million of inhabitants and where the intensive traffic contributes to high emission rates. The gaseous emissions under complex

3 Urban Transport and the Environment for the 21st Century 287 geographical features and mesoscale atmospheric circulation (coastal zone) that occurs on the region plays an important role in the air pollution problems. Emission inventories to be used for air quality and air quality planning require appropriate spatial and temporal resolution [5], in particular urban emission inventories. Generally, there are two approaches for the establishment of temporally and spatially resolved emission data: top-down and bottom-up approaches. The methodology used for establishing urban traffic emission inventory is a combination of these two approaches. 3 Top-down approach The top-down approach uses available inventories for a greater emission area and brake down the overall emissions to sub-units using actual data for source strength and emission generating activities, or - if such is not available - surrogate statistics [5]. The CORINAIR90 National Inventory constitutes the basis for the spatial and temporal downscale of road traffic emissions in Portugal. 3.1 Spatial Downscale The NUT III area emissions data, from the CORJNAIR90 inventory, have been downscaled to municipal level, using the fuel consumption. The fuel and vehicle types were taken into account. The statistical information was combined with the administrative map of Portugal. However, the municipal level has still not enough resolution for dispersion models. As a next step, the population data, such as total population, population in age of economic activity or occupied in industry and services, were used as indicator for downscaling of emissions to sub-municipal level ("freguesia"). This data was obtained from Census 91 of Institute of Statistics [6]. 3.2 Temporal Downscale The general idea of a temporal downscaling adheres to a similar philosophy as the spatial downscale, being in general the temporal basis annual emissions values [5]. The standard for urban air modelling is a time resolution of one hour. The use of standardised fixed emission quotas is a very

4 288 Urban Transport and the Environment for the 21st Century straightforward approach to approximate the temporal emission patterns. The method aims at modelling the 'typical' rather than the 'actual' emission dynamics using surrogate data. The most important step in creating a useful temporal downscale is the selection of adequate data. In order to find the fixed emission quota to apply in Portugal, traffic counts, from numerous roads of Portugal, were available from the Junta Autonoma de Estradas (JAE). This database contains information about daily mean traffic (DMT) for different periods: Summer/Winter and Diurnal/Nocturnal. With the purpose of finding a relation between Summer and Winter traffic and between diurnal and nocturnal traffic, analysis of DMT for all the count locations has been done [4]. The results of analysis show relations of 87/13 and 53/47 for diurnal/nocturnal and Summer/Winter periods respectively. It was assumed that those relations are also applied to the sub-municipal level. Therefore, annual emissions have been downscaled to daily emissions, considering the Summer period between April and September (183 days) and the Winter period between October and March (182 days). Those daily emissions have also been broken down to hourly emissions, assuming that the diurnal period corresponds to 16 hours and the nocturnal to 8 hours. This procedure has been done for all the "freguesias" of Portugal. It should be noticed that there might be regional differences in the emission dynamics that need special consideration and should be taken into account in the near future. 3.3 Application CO, NOx and VOC transport emissions from the CORINAIR90 inventory where broken down, from the NUT III resolution to the municipal level and then to the sub-municipal level using, respectively, statistical data of fuel consumption and statistical data of population. The emissions rates have been calculated within GIS, by dividing estimated values for sub-municipal level to the administrative unit area. The temporal downscale of those annual area emissions to a daily basis was done using the DMT estimates provided by JAE, as described before (see 3.2). Considering day and night emissions as constants, it was possible to obtain hourly emissions, for each "freguesia" of study area. As an example, in figure 1 the results for seasonal hourly CO

5 Urban Transport and the Environment for the 21st Century 289 emissions in the "freguesia" of Amora are present. From the figure it is possible to verify that Summer emissions are greater than Winter's one. Diurnal emissions are, as foreseen, much greater than the nocturnal. Figure 1: Road traffic CO emissions for the "freguesia of Amora". As an example of final result of spatial and temporal downscaling, daily NO% emissions rate for typical Summer day on each "freguesia" of the study area (kg/km^) is presented on figure 2. The obtained results show a coherent distribution pattern with the greater emission level associated to the urban centres. Figure 2: Daily NO% traffic emissions. NOx (kg/km2) >1000

6 290 Urban Transport and the Environment for the 21st Century 4 Bottom-up approach The bottom-up approach provides estimates for a particular region (administrative units) by utilising local data set and applying emission factors. 4.1 Methodology Mobile sources include emissions from road transport, off-road vehicles and machinery, railways, waterways and air traffic. There are three kinds of emissions from road traffic [8]: (i) hot emissions, emissions from the vehicles after they warmed up and their engine is thermally stabilised; (ii) cold start emissions take place while vehicles are warming up; and (iii) evaporative emissions, that account for the evaporation of gasoline. In the scope of this work, only road traffic hot emissions was considered. Due to insufficient direct emission measurements, emissions rates are usually estimated from mass balance calculations, being translated into an emission factor [8]. The emission model developed for principal roads in Portugal is based on CORINAIR methodology. Four vehicle categories have been considered: light-duty gasoline vehicles (or passengers cars), light-duty diesel vehicles, heavy-duty vehicles and two-wheeled vehicles. Concerning the driving modes, following types have been distinguished: urban, rural and highway. Principal roads was processed as a line sources and their emissions were calculated on the basis of emission factors, daily mean traffic and road length: where: E j - daily emission of pollutant / for road segment; ejj - emission factor for pollutant i and vehicle type y; DMT - daily mean traffic; L - road segment length. Highway emission factors have been applied for highways, principal and complementary itineraries. For other roads the rural emission factors has been used. Data related to the DMT was obtained from the JAE [9] and 57 measurement points were considered. Geographical Information Systems were used for road segments length calculation. Line sources have been subdivided, taking into account the existent crossroads. Traffic data applied to each segment resulted from the measurements realised along each segment or, in its

7 Urban Transport and the Environment for the 21st Century 291 absence, along the nearest one. 4.2 Application The result obtained by the application of described methodology is presented on figure 3. The figure shows the considered line sources, the measurements points and the NO% emission rate (kg/km) for a typical Summer day for each road. Atlantic Ocean Figure 3: Daily NO% emissions from line sources on Lisbon Region. It should be noted that greater emissions rates are associated with highways, particularly those stretch near the Lisbon City. This fact was expected attending that traffic flux increase within the urban zone influence. Daily pollutants emissions associated to principal roads were aggregated for each NUT III area. Contribution of line sources to total NUT III emissions were analysed. Figure 4 presents this contribution, for a typical Summer day, for the considered NUT's.

8 292 Urban Transport and the Environment for the 21st Century NOx VOC Figure 4: Contribution of line sources to total traffic emissions. It is possible to verify that line sources contribute more to the total emissions in "Peninsula de Setubal" than in "Grande Lisboa". This should be related to the fact that the road network of Lisbon municipality, treated as area sources, has a significant contribution to the total traffic emissions of the "Grande Lisboa" NUT III. The same methodology described before has been applied to calculate emissions from the road network of Lisbon's city, using on this case information provided by the traffic automatic counting system GERTRUDES. In this paper, and as an example of application, the hourly emissions from two specific roads located on the city centre are presented: "R. do Ouro" and "Av. Da Liberdade". To analyse the emissions seasonal beaver two days have been chosen - a Summer (95/08/23) and Winter (95/11/22) working days. There were available hourly traffic flux data from 5 counters distributed along the considered roads. Figure 5 presents the hourly CO emissions estimated for two roads. Both streets present a similar behaviour along the two chosen days: CO emissions are smaller during the night, start to increase around 7:00 a.m., within maximum value among on the afternoon (between 11:00-13:00 a.m. and 3:00-5:00 p.m.), and decrease again on the evening. This behaviour is associated with the typical daily commercial/business activity that occurs on the centre of a large city as Lisbon. Emissions in the "Av. da Liberdade" are greater than in the "R. do Ouro", in agreement with the different road type of the streets. In fact, "Av da Liberdade" is an avenue with 4 ways and "R. do Ouro" is a one way street.

9 Urban Transport and the Environment for the 21st Century 293 Aw Ha I ihorrtoho /Qg/nSm)... -Av. Da Liberdade (95/11/22) R rln Hi irn (... R. do Ouro (95/11/22) Daily period Figure 5: Hourly CO emissions variation for two urban streets and for two different days (Summer and Winter days). 5 Conclusions Detailed urban transport emissions were obtained by the temporal and spatial downscale of the CORINAIR90 inventory and by the information provided by PolAr database. The developed methodology involves two different approaches: top-down for area sources and bottom-up for line sources, where GIS constitutes an important tool for data processing. The following analysis was performed: a Spatial emissions distribution within the study area; a Daily and seasonal variation of traffic emissions; a Contribution of line sources to total traffic emission; a Hourly emissions variation for specific roads located in Lisbon city centre; Acknowledgements This work is supported by PRAXIS XXI grants and funded by PEAM/P/AMA/603/95, Praxis/3/3.2/EMG/l 949/95, Praxis/3/3.2/AMB/3 8/94 projects.

10 294 Urban Transport and the Environment for the 21st Century References [1] UNFCCC - Report on the in-depth review of the national communication of Portugal, [2] CORINAIR90 - Inventario Nacional de Emissoes Atmosfericas, Lisboa, [3] Miranda, A. I., Concei^ao, M. and Borrego, C. A contribution to the air quality impact assessment of a roadway in Lisbon. The air quality model APOLO. The Science of the Total Environment, 134, pp.1-7, [4] AMAZOC - Relatorio de Progresso 1 ano. Universidade de Aveiro, Portugal, [5] Orthofer, R. and Winiwarter, W., Spatial and temporal disaggregation of emission inventories, Chapter 2, Air Pollution Emissions Inventory, ed. J. Baldasano and H. Power, Vol. 3, Computational Mechanics Publications, Southampton, UK [6] Censos 91, Institute Nacional de Estatistica. [7] Tchepel, O., Barros, N., Borrego, C. and Nunes, T., Mapping Anthropogenic and Biogenic Emissions Data in Portugal. Proc. of the IV Encontro Nacional de utilizadores de Sistemas de Informaqao. Eds. Associa^ao dos Utilizadores de Sistemas de Informa9ao Geografica, Lisboa, [8] Baldasano, J., Guidelines and formulation of an upgrade source emission model for atmospheric pollutants, Chapter I, Air Pollution Emissions Inventory, ed. J. Baldasano and H. Power, Vol. 3, Computational Mechanics Publications, Southampton, UK [9] JAE - Recenseamento de trafego 1990 e sua analise estatistica, Junta Autonoma de Estradas, Direcgao dos Servigos de Conservagao.