Transactions on Ecology and the Environment vol 8, 1996 WIT Press, ISSN

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1 A sensitivity analysis of a high resolution emission model under different emission scenarios over Madrid area R. San Jose/ J. Cortes/ J.F. Prieto/ J.M. Hernandez/ R.M. Gonzalez*" "Group of Environmental Software and Modelling, Computer Science School, Technical University of Madrid, Campus de Montegancedo, Boadilla del Monte 28660, Madrid, Spain ^Department ofmeteorology, Faculty of Physics, Complutense University of Madrid, Ciudad Universitaria, Madrid, Spain Abstract Emission models are a key module of the Air Quality Systems particularly in the case of modelling the pollutant air concentrations in urban areas. The necessity of detailed emission models is an essential requirement of having an accurate and sensitive Air Quality System to predict the air concentrations on detailed spatial and temporal distribution. Recently, the biogenic emissions have been incorporated in detailed emission models to take into account its influence on the VOC budget. Different emission scenarios are applied into an Air Quality Model (ANA) over Madrid Area. Anthropogenic and biogenic emissions are included in the 250x250 emission model. The Air Quality System takes into account a detailed resistance deposition approach for different pollutants, a LANDSAT satellite landuse classification, an Eulerian Transport Model and a complex detailed mesoscale non-hydrostatic model REMEST. The different emission scenarios are applied to June, 5-7, 1995 period after validating the emission model with observed concentrations at different urban stations. Results show that increase and decrease simulations produce decrease or increase values of ozone in function of the increase (or decrease) percentages and depending on the absolute values of ozone. The results suggest that important reductions on NOx and VOC8 may lead to increments in ozone levels in urban areas. More

2 708 Air Pollution Monitoring, Simulation and Control important reductions in those emissions can lead to reductions in ozone levels. Important increases in those emissions lead to substantial reductions in ozone levels. 1. Introduction Emission inventories are one of the most critical modules in urban photochemical air quality models. The uncertainty of emission estimations for different pollutants is an important source of errors in the Air Quality Models. Because of this, research in the last decades of this subject has been increased. The research on emission models started on around 70's with Bottger et al. (1978)^ and Zimmerman (1979)* and continued during the 80's with the CORINE^ and EPA* 4-year updating emission inventory programs. The NAPAP* report and the Andreani-Aksoyoglu and Keller (1994)* report and Lamb et al. (1993)? are important contributions in the scientific literature to the knowledge of the algorithms and methodologies to understand the emission from natural and anthropogenic sources. The emission inventory included in the ANA model comprises the inventory and localization of emission data of both industrial and non-industrial sources in a mesoscale area in Spain. The area is located in the central part of the nation and it is identified with an autonomous region called Madrid Community. (Fig. 1). The Madrid Area includes the nation capital and this city forms the 75 % of the total population. We have included anthropogenic and biogenic emissions. The biogenic emissions include the isoprene, monoterpene and a-terpenes which are emitted mainly by the caducous and perenneal forests. Most of the forest in the area is composed by caducous leaves and the isoprene emissions are more than 97% of the total biogenic emissions in the actual state of the inventory. The objective of this inventory is to provide a modelling module into the Integrated Air Quality System (ANA) which is continuously interrelated to the transport and deposition modules of the Photochemical Model. Anthropogenic emissions can be described by using the algorithms included into the EPA* and CORJNE^ reports. This inventory model is focused on mesoscale areas -in our case the Madrid area but it can be extended immediately to other areas with compared scales.

3 Air Pollution Monitoring, Simulation and Control 709 Domain Topography Madrid, Spain 80x100 km Navacerrada Guadarrama Mountains MADRID Jarama River 0) Guadarrama River UTM coordinate range of domain: xs km, y= km. Heights given above sea level. Figure 1.- Madrid domain for the emission sensitivity case studies The numerical photochemical models require continues information of the total (and grid) input of pollutants into the atmosphere every very short time steps. This information in only achieved by precise emission inventory models with high quality algorithms to calculate emission factors. At the moment, we do not have european or national programs to achieve this type of information however information for wider spatial and temporal resolution is already available for national and european scales. Increased interest has been shown in recent years on the quantification of the emissions from the biosphere and the consequences on the changes on the physical and chemical properties of the Earth's atmosphere and uptake of trace gases of biota. Neglecting the natural hydrocarbon emissions in air pollution models leads to inaccurate estimations of pollutant concentrations and

4 710 Air Pollution Monitoring, Simulation and Control to ineffective pollutant reduction strategies based on a reduction of anthropogenic hydrocarbons only (Chameides et al.^) Our emission model EMIMA takes into account all above points and underlines the attention on the high spatial (250 m x 250 m) and temporal resolution. The model comprises two coupled information systems: Individual Emission Inventory System and the Collective Emission Inventory system. For a realistic strategy to reduce the emission of the predominant air pollutants such as sulfur dioxide, nitrogen oxides (NOx) and volatile organic compounds (V0C), it is necessary to know the types of the sources as well as their emission rates with some confidence and to predict their future levels. 2. Modelling approach Taken into account above general considerations, we have used a numerical photochemical model to qualify and if possible quantify our emission inventory model EMIMA. The numerical photochemical model ANA includes 33 species and 78 chemical reactions including NOx reactions, Ozone cycle, inorganic reactions, photochemical reactions, sulfur reactions and organic reactions. This model* provides a complete information about the distribution of the different chemical compounds at different grid points and at different predicted times. The model needs a high resolution emission inventory (spatial and temporal) and this information is provided by EMIMA. This is an emission model of atmospheric pollutants in a domain centered in the Madrid metropolitan area following the CORINE methodology. The pollutants which have been taken into account in the actual version of the model (2.0) are: SO?, NOx and anthropogenic and biogenie VOC's (isoprene and monoterpenes). The model domain comprises an area of 80 km x 100 km with " people and more than vehicles. The number of towns is 210. The city of Madrid (capital of the nation) with more than people is the main source of anthropogenic emissions and its influence is key for understanding the atmospheric environment of the area. The time resolution is un hour and the source classification is: line, point and area. The output used in this contribution is 2 km x 2 km for being used in the numerical photochemical air quality system (ANA). It is also possible to obtain the emission per grid cell per pollutant per hour. A more complete description of the model is found in San Jose et 3. Model evaluation A operational evaluation of the model was performed on the base case simulation for June, 5-9, A standard measure for evaluating model performance is to compare spatial patterns of predicted and observed ozone. Five simulation days are shown in Figure 2 to illustrate model performance for the period. On these days the comparison between observed and predicted ozone concentrations for those four stations is quite reasonably.

5 Air Pollution Monitoring, Simulation and Control 711 g Figure 2.- Simulated and observed ozone concentrations for June, 5-9th, 1995 period for different urban and suburban (SREMP) stations. 4. Urban response to emission changes From the above analysis, a very reasonable agreement between observed and predicted ozone air concentrations has been found. From this analysis, the response of the model to three different change modes has been investigated over

6 712 Air Pollution Monitoring, Simulation and Control these stations. The change modes are classified into reduction and increase. The reduction model comprises the scenario 1 and 3. The scenario 1 has been running only until 40 hours after starting the simulation. (The computer simulation started 24 hours before but was eliminated in order to minimize the influence of initial conditions). The scenario 3 was running during 72 hours. The increase mode corresponds to scenario 2 and it was running during 72 hours. Table 1 shows the three scenarios and the increase or decrease percentages for the anthropogenic emissions. Scenario Mode NO* VOC's Types of Scenarios! 1 2 Reduction Increase -26% +60% -28% 4-50% 3 reduction -50% -25% Table 1.- Type of scenarios performed in this contribution. Figure 3 shows the ozone concentrations for the three scenarios at station 19. The stronger reductions are observed for scenario 2 (increase mode) particularly when lower ozone air concentrations are found. The scenario 1 (low reduction mode) leads to little increments in the ozone concentrations. When stronger reductions are performed (scenario 3) the ozone concentrations are reduced again the less the ozone concentrations in the base run the more the ozone reductions. The reduction and increase modes were performed over the anthropogenic sources mainly in the urban area. Figure 4 shows the results for scenario 2 and 3 at 16hOO on the third simulated day (June, 7th, 1995) on spatial surface patterns. Results indicate that stronger changes are observed in the urban area and up to distances over km from the center of the urban area. 5. Conclusions We have applied a mesoscale air quality numerical model (ANA) for the Madrid Area (80 x 100 km) in order to study the performance of three different scenarios. The anthropogenic emissions for NOx and VOC's have been reduced and increased for the different scenarios. Two scenarios were performed in the reduction mode and one scenario on increase mode. Results show a high nonlinear response to the reduction and increase scenarios. The strongest reduction on ozone concentration levels are found on the increase mode and in the two reduction modes, results show that the more the reduction in the anthropogenic emissions are the more the reduction in ozone is for low ozone concentrations. When the reduction is not strong results show an increase in ozone levels particularly for low ozone concentrations.

7 00 *l o Base Run Scenario 1 Scenario 2 Scenario 3 Madrid simulation p. OB If IE s " 8 M sr 0) c o N O o o I OP GO Pu 1 g 8 S L.S.T. June 5th-7th, O CO Ou

8 714 Air Pollution Monitoring, Simulation and Control Figure 4.- Ozone surface concentration patterns for scenarios 2 and 3.

9 Acknowledgements Air Pollution Monitoring, Simulation and Control 715 We would like to thank the Supercomputer Centre in Galicia (Spain) for providing the Fujitsu VP2400 for performing the simulations. References 1.- E.P.A. "Compilation of Air Pollutant Emission Factors", 3"* Ed. Report AP (1977). 2. Bouscaren R., Veldt C. and Zierock K.H. "CORINE: Emission Inventory Project. Final report", Contract , European Communities, Bottger, A., D.H. Ehhalt and G. Gravenhorst "Atmospharische Kreislaufe van Stickoxiden un Ammoniak". Kemforschungsanlage Julich, report nr. Jul (1978). 4.- Zimmerman P.R. "Determination of emission rates of hydrocarbons from indigenous species of vegetation in the Tampa/St. Petesburg, Florida area. EPA- 904/ (1979) 5.- Kohout E.J., Miller D.J., Nieves L.A., Rothman D.S., Saricks C.L., Stodolsky F. and Hanson D.A. NAPAP, "Current emission trends for nitrogen oxides, sulfur dioxide and volatic organic compounds by month and state: methodology and results", ANL/EAIS/TM-25, Argonne National Laboratory, Argonne D. (1990). 6.- Andreani-Aksoyoglu S. and Keller J. "Estimates of monoterpene and isoprene emissions from the forest in Switzerland", submitted to J. Atmos. Chem. (1994) 7.- Lamb B., Gay D., Westberg H. and Pierce T. "A biogenic hydrocarbon emission inventory for the U.S.A. using a simple forest canopy model", Atmospheric Environment, 27A, 11, pp (1993). 8.- "Emission Inventory in the Netherlands: Emissions to Air and Water in 1990", Inspectorate General for Environmental Protection, Department of Emission Inventory and Information Management, PO Box 30945, 2500 GX's-Gravenhage, The Netherlands. February, Chameides W.L., Lindsay R.W., Richardson J. and Kiang C.S. "The role of biogenic hydrocarbons in urban photochemical smog: Atlanta as a case study", Science, 241, pp , (1988) San Jose R., Ramirez-Montesinos A., Marcelo L.M., Sanz M.A. and Rodriguez

10 716 Air Pollution Monitoring, Simulation and Control L.M., "Numerical photochemical modelling over Madrid (Spain) mesoscale urban area", submitted to EUROPTO, LASER'95, Munich, June, INYPSA "Estudio inventario de emisiones contaminantes a la atmosfera de Madrid y su entorno industrial" (1986) San Jos6 R., Sanz M.A., Moreno B., Ramirez-Montesinos A., Hernandez J. and Rodriguez L.M. (1995) "Anthropogenic and biogenic emission model for mesoscale urban areas by using Landsat satellite data: Madrid case study", EU- ROPTO Proceedings, Vol 2506, SPIE, San Jose R., Moreno F.J. and San Feliii M.A. "A field study on 6)3, SO^ and NH3 deposition over a suburban area: Madrid case study", submitted to EUROPTO, LASER'95, Munich, June, 1995.