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An urban trajectory model for sulfur in Asian megacities: model concepts and preliminary application
Atmospheric Environment 33 (1999) 3109}3117
An urban trajectory model for sulfur in Asian megacities: model concepts and preliminary application Giuseppe Calori *, Gregory R. Carmichael International Institute for Applied Systems Analysis (IIASA), Laxenburg, A-2361 Austria Department of Chemical and Biochemical Engineering, University of Iowa, Iowa City, IA 52242, USA Received 15 May 1996; accepted 30 November 1997
Abstract This paper explores the adaptation of a regional Lagrangian approach for making long-term simulations of SO and sulfate ambient concentrations at the resolution needed for health e!ects risk assessment in Asian megacities and their surroundings. A Lagrangian trajectory model (UR-BAT) is described which simulates transport and di!usion of sulfur within and near urban areas, originating from area and major point sources. The long-range contribution is accounted for by the ATMOS model, simulating all Asian sources. The model has been applied to Beijing and Bombay, by using preliminary emission "gures, and the results have been compared with available monitoring data. The computed concentrations in di!erent cities are in the correct range, indicating the potential use of the model in an integrated assessment framework such as RAINS-Asia. 1999 Elsevier Science Ltd. All rights reserved. Keywords: Megacities; Sulfur; Assessment model; Beijing; Bombay
1. Introduction Strong population increase and high economic growth rates are causing in Southeast Asian cities the same environmental problems faced by cities in the highly industrial world. The available information shows that the World Health Organization (WHO) air quality guidelines are systematically exceeded in major urban centres throughout Asia. According to the data from the WHO/UNEP long-term Urban Air Quality Monitoring and Assesment Programme (GEMS/Air), Bangkok, Beijing, Bombay, Calcutta, Delhi, Jakarta, Karachi, Manila, Seoul and Shanghai have serious problems with suspended particulate matter. In these cities both long-term and short-term WHO guidelines are exceeded by more
* Corresponding author. Dipartimento di Elettronica e Informazione, Politecnico di Milano, Via Ponzio 34/5, 20133, Milan, Italy.
than a factor of two (WHO/UNEP, 1992). Sulphur dioxide is a major problem in megacities such as Beijing, Seoul, Shanghai, Delhi and Karachi. Several factors contribute to this situation. Asia is experiencing economic growth rates which are among the highest of the world, its energy demands are being met by heavy usage of indigenous coal as primary fuel source (still dominant in most of the countries), and it is experiencing a persistent urbanization. Six Asian cities currently have more than eight million inhabitants, and 56 have more than one million. Furthermore, throughout Asia the fraction of the population living in urban areas is continuously increasing, and according to current projections, in the next decade the urban population will exceed the rural population (UN, 1991). The large number of people being exposed to high pollution levels in Asian urban areas represents a major environmental problem in the region. The term MetroAgro-Plex has been de"ned to characterize these zones with intermingling of agricultural and urban-industrial activities. The high levels of pollutants can also cause
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direct ecosystem damage, including reductions in crop yelds as discussed by Chameides et al. (1994). 1.1. The rains-ASIA framework The RAINS-Asia project (Foell et al., 1995; Amann, 1994), sponsored by the World Bank, the Asian Development Bank and other Asian and international institutions, is a preliminary study of the impact of the growing energy use in Asian environment. The major purpose of the RAINS-Asia project is to provide modelling support for an integrated risk assessment of acidi"cation in Asia. Following the lines of the European approach (Alcamo, 1990; Hordijk, 1991), the modelling system is organized in sub-models devoted to energy-scenario generation, emission and cost control evaluation, atmospheric dispersion and critical loads assessment (Foell et al., 1995). The emission-deposition relationship is expressed in terms of a transfer matrix, calculated using ATMOS, a multi-layer trajectory model of sulfur transport/deposition (Carmichael and Arndt, 1994, 1995). Computed source/receptor information relate the deposition on each of 13;13 grid cell with the emissions from 250 of the largest point sources, and the remaining area sources of the region, grouped into 94 subregions. It is desirable to include in the analysis a consistent assesssment of health-related problems and direct ecosystem damage arising from high SO levels in the major urban areas. However, the scale of the regional model does not allow one to fully reconstruct the peaks of concentrations in urban areas (see Section 3). An atmo-
spheric model running at higher resolution is in fact required, using more detailed and "ner spatially resolved emission "gures in megacities and their surroundings. The results, conveniently summarized and integrated into the modeling system, would allow the simultaneous analysis of the human health and acidi"cation risks. To explore the possibility of such a coherent approach within the existing framework, the trajectory model already developed and applied at 13 resolution for Asia has been modi"ed and initially tested on a few urban areas. The structure of the model and the results of a few preliminary applications and comparisons with available monitoring data are reported in the following sections. The purpose of this model is to provide a preliminary assessment of the risk to human health, and to ecosystem damage due to exposure of air pollutants and depositions, within the context of an integrated analysis of the environmental impacts associated with the rapid growth in energy consumption in Asia. A further quanti"cation of the impacts in high risk regions clearly requires the use of more detailed modeling activities.
2. Description of the UR-BAT model The UR-BAT (URban } Branching Atmospheric Trajectory) model has been designed to simulate the di!usion of sulfur within and near megacities. It is based on the ATMOS model already developed by Carmichael and Arndt (1994) for long-range transport of sulfur in Southeast Asia (Fig. 1), as the
Fig. 1. RAINS-Asia and ATMOS modelling domain, showing also the location of upper air stations (grid lines every 53).
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atmospheric dispersion section of the RAINS-Asia modelling system. ATMOS is a Lagrangian multi-layer trajectory model, derived from NOAA's Air Resources Laboratory BAT model (He!ter, 1983). The model is source-oriented: every 3 h a new pu! is generated from each source, and placed in a proper vertical layer, according to source type (surface/elevated) and day/night occurrence. During the day, two vertical layer are adopted (Fig. 2): the boundary
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layer, extending from the surface to the bottom of the critical temperature inversion, and the upper layer, extending from there to the top of the domain, "xed at 6000 m. During the night, a surface layer is also present, extending from the ground to a "xed height of 300 m. Pu! trajectories are computed by using average winds for each layer. The critical inversion height as well as the transport wind are computed from upper air sounding data.
Fig. 2. Daytime and nighttime vertical layers in the UR-BAT model.
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Depending on the changes in layer con"guration during day-to-night and night-to-day transitions, the existing pu!s can branch into several new ones or can vertically mix in the new layer. New branches follow independent trajectories, according to the wind of the corresponding layer. The mass of pollutant initially released according to source strength is partitioned among di!erent branches, according to post-transition layer thickness. Along trajectories the mass balance equations are integrated, considering the chemical transformation from SO to sulfate and dry and wet deposition phenomena, all modelled as "rst-order processes. Model parameters employed for Asia depend on geographic as well on meteorological conditions (for details, see Carmichael and Arndt, 1994). The concentrations and deposition at gridpoints or at selected receptors are "nally computed by superposition of the contributions of individual pu!s. In the vertical a uniform mass distribution is assumed within each layer, while in the horizontal a Gaussian distribution is adopted, with a dispersion coe$cient depending on travel time. In order to provide an initial evaluation of air quality for major urban areas, consistent with the regional-scale picture, the ATMOS model has been adapted as described in the following. 2.1. Emissions and transport In the urban model every hour a new pu! is released by each source, carrying a fraction of the total mass emitted by the source during the year. The hourly release frequency, although increasing the total computational time, has been introduced to avoid concentration oscillations when the 3-hour release frequency used in ATMOS is applied to the smaller spatial grid resolution of the URBAT model. The emissions take place in di!erent layers according to the source type (area or point) and the hour of day. Surface sources release pu!s into the boundary layer (during day) or into the surface layer (during night). Elevated point sources always release pu!s into the boundary layer. In daytime conditions the boundary layer extends from the ground up to the critical inversion; during night its base is the top of the surface layer, so the material is kept from reaching the surface. In all layers the pollutant is assumed to be uniformly mixed in the vertical. Emitted pu!s move according to the winds in the di!erent layers, and can be split during day/night transitions into several independent branches (up to 32 branches for each initially emitted pu!). Mass exchange among branches in the di!erent layers are governed by the branching scheme explained later. The pu! trajectories are computed every hour using the same technique (a modi"ed Euler advection algo-
rithm) employed in the ATMOS model, and are based on the upper air soundings data. At each station the horizontal winds are calculated by vertically averaging the measured wind over each layer of interest. If no data are available at a given time within a one degree radius, the data from the surrounding stations can be used. The search radius is progressively incremented, up to a maximum distance of 53, and the available data are interpolated by using weights equal to the inverse square of the distance. If no data are available within a 53 radius, a monthly climatological value is used, computed by interpolating in space the monthly average winds at each sounding station. Corrections have also been introduced in the wind calculation procedure, to treat the cases of missing observational data, especially in the lower layers. If the measured wind data at a given time are available only above the 300 m level, the wind in the low layers is computed by downward interpolating these values, assuming a vertical logarithmic pro"le. If no data are available at the upper levels, then the climatological value is used, for all layers. 2.2. Puw branching and mixing To account for wind shearing of pu!s emitted and moving in di!erent layers, trajectories can branch into independent trajectories. New branches can be generated during day-to-night and night-to-day transitions (Fig. 3), with the mass split according to post-transition layer thickness. Branching and mixing are organized as follows. During day-to-night transitions, a pu! in the boundary layer will branch into the surface and nighttime boundary layers. In the same situation, if a signi"cant lowering ('300 m) of boundary layer top occurs, a further upper layer branch is also generated. During nightto day transitions, pu!s in the surface or in the nighttime boundary layer are mixed in the daytime boundary layer. Also in this case a signi"cant lowering of boundary layer top causes the generation of a new upper layer branch. Pu!s in the upper layer always remain above the boundary layer top, unless it rises signi"cantly ('300 m) during a day-to-night or night-to day transition; in this cases a new boundary layer branch is generated. 2.3. Concentration calculations As in the ATMOS model, two forms of sulfur are treated explicitly: gaseous sulfur dioxide and aerosol sulfate. Sources are assumed to emit both species (the sulfate is assumed as 5% of the total sulfur emitted). The pu! masses change along the trajectories according to the chemical conversion to sulfate and the dry and wet deposition phenomena. A simple "rst-order rate constant is used for chemical conversion, depending on latitude and day of year. This conversion rate parametrization takes
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are depleted by dry deposition, while wet deposition a!ects all the layers. The mass balance equations are integrated with a hourly time step. The concentrations at each grid point in a given layer are computed by summing up the contributions of all the pu!s in that layer (only pu!s in ground-based layers contribute to surface concentrations). The mass of each pu! is assumed to be uniformely mixed in the vertical within a layer, while in the horizontal a univariate Gaussian distribution is assumed, with a standard deviation (p ) assigned according to travel distance and urban/rural conditions. In the short range ((30 km), the Pasquill}Gi!ord} Turner formulation is used for rural conditions, with coe$cients taken as in MESOPUFF II model (Scire et al., 1984), while in urban conditions Briggs &&urban'' p are used, (as reported in Gi!ord, 1976). The location and extent of urban areas is speci"ed in the model in terms of an appropriate urban/rural mask. In the long range, dispersion coe$cients are taken proportional to travel time (He!ter, 1983), computed incrementally from the value at the previous time step as (p( ) "(p ) #0.5dt. R>BR R where dt denotes the computational time step (in s) and p is in meters. For area sources an initial minimum standard deviation, ph is used, depending on the source extent.
3. Preliminary calculations and model experiments
Fig. 3. Branching and mixing scheme (BL: boundary layer; SL: surface layer; UL: upper layer).
into account both gas-phase and liquid-phase processes. The rates typically range from 0.5 to 2.5% h\. The dry and wet removal are also treated as "rst order processes, with seasonally varying rates depending, respectively, on latitude and precipitation rate and on latitude and land/sea occurrence. Parameter values have been choosen to re#ect Asian conditions and are discussed in more detail in Carmichael and Arndt (1994), Arndt and Carmichael (1995), Arndt et al. (1997a and 1997b). Only pu!s travelling in layers in contact with the surface (daytime boundary and nighttime surface layers)
The model has been tested for the megacities of Beijing and Bombay. UR-BAT was run inside the 13 grid cell containing the considered megacity, using a 0.13 resolution simulation and the original emission attached to the 13 grid, apportioned to the "ner grid as discussed later. The computed concentrations were then superimposed on those computed with the ATMOS model, taking into account the e!ect of all remaining Asian sources (large point sources and area sources, both natural and anthropogenic). The results were then compared with available information on air quality in the cities, to provide a preliminary indication on the reliability of the range of the concentrations computed by the model. 3.1. Meteorological input The upper air soundings data provided by US National Climatic Center, NOAA for the year 1990 were used (the location of the reporting stations in Southeast Asia is shown in Fig. 1). The data include 6 hourly vertical pro"les of potential temperature and wind speed from the surface to 500 hPa. These data are used in the model to determine the critical inversion height, which delimits
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the top of the boundary layer, and the average winds of each model layer. The criteria adopted for the critical inversion are taken as in He!ter (1983): *#/*z*0.005 K m\ # !# *2 K 2 where *#/*z is the change of potential temperature # with height z, and # and # are temperatures at the 2 top and the base of the inversion. The monthly climatological wind "elds, used by the model when no measured data are available at a given time and location, have also been computed from upper air soundings, interpolating in space, for each layer, the monthly average winds at the sounding stations. Analyzed US NMC precipitation data provided by the National Centre for Atmospheric Research (NCAR) have been used. These consist of 6-hourly accumulated values on a grid with a mesh size of a 1.46953 latitudinal by 1.48753 longitudinal. Inside the model, the gridded data are assumed to be uniformly distributed within the sixhour interval, and spatially interpolated inside the model by using a bilinear method, to adapt to the model grid system. 3.2. Application to Beijing A 0.13 resolution urban/rural mask for Beijing has been de"ned, and used to distribute the 13 emissions (362 kt yr\ of SO ) estabilished by the RAINS-Asia emissions module for the grid cell. 50% of these emissions have been attributed to the urban area, and uniformily distributed on the 0.13 &&urban'' grid cells; the remaining 50% to the surrounding rural areas, also uniformily distributed on their respective 0.13 grid cells. Although very rough, this emission pattern qualitatively re#ects the main feature of the high emission density of the urban area, and has been used to point out the basic capabilities of the model. Fig. 4a shows the computed average SO concentra tion map for the year 1990. The concentration pattern is generally oriented towards Southeast, according to the prevailing winds during the cold season (Arakawa, 1981). The &&hot spot'' around the urban area is considerabily above the average value (48 lg m) computed by the regional model at 13 resolution, and is in the range of the values given by WHO-UNEP GEMS/AIR stations. The calculated values exceed the long-term WHO guidelines (40}60 lg m\) over large areas around the city. These results are consistent with city centre stations reporting annual means over 100 g m\ (WHO/UNEP, 1992). The occurrence of peak values is also important in the evaluation of the health e!ects. Fig. 4b shows the corresponding map of the percentages of hours in exceedance of the WHO short-term standard (350 lg m). The whole metropolitan area is signi"cantly a!ected by recurring
high pollution episodes. According to the simulation the hourly guideline is exceeded in the immediate surroundings of the urban area in a few percent of cases, and more than 5% in the centre of the city. This is con"rmed by monitoring activities. Measured data indicate that peak values can reach 700 lg m\, and daily means above 500 and 250 lg m\ are reached on 2% of the days in the city centre and in suburbs, respectively (WHO/UNEP, 1992). Elevated SO concentrations can also have direct impact on the ecosystems surrounding the metropolitan area. For example, many crops and trees show declines in yelds and productivity when SO concentrations exceed some threshold value (called critical levels). In a recent study (Hettelingh et al., 1996), critical levels for SO in Asia have been set at 40 lg m\. As shown in Fig. 4, extensive regions around Beijing are predicted to have concentrations which exceed this critical level. Combining this analysis with spatial information on forest and crop lands, could allows an assessment of risks of these ecosystems resulting from exposure to elevated SO concentrations. 3.3 Application to Bombay After the preliminary calculation on Beijing the model was also applied to the Bombay area, to extend the study to a megacity a!ected by di!erent climate and pollution levels. The yearly 1990 emissions evaluated by RAINS-Asia model for the corresponding 13 grid cell (87870 t yr\ of SO ) have been spatially disaggregated on a 0.13 grid (Fig. 5) by using available information on population distribution and industrial sources location (UN, 1986; Gronskei et al., 1995). The estimated emissions are
Fig. 4. Beijing*(a) computed annual average SO concentra tions (lg m\); (b) percentages of hours exceeding 350 lg m\ of SO , on a yearly basis (isolines at 1, 2, 5 and 7.5%).
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Fig. 5. Bombay*Adopted SO emission #ux density.
unevenly distributed, with maxima in the densely populated City, the south districts of Greater Bombay and the banks of Thana Creek. As in the previous application the contribution to concentrations from the remaining Asian sources was calculated with the ATMOS model, and superimposed on UR-BAT model results. Figure 6 shows the calculated yearly average concentration map. Despite the non-uniform source distribution, the yearly ground-level concentration pattern looks fairly regular. An &&urban plume'' oriented eastward over land can be clearly depicted, following the direction of sea breeze and predominant synoptic wind direction during summer monsoon (Takahashi and Arakawa, 1981). In the urban area the computed values are generally above 20 lg m\, with a maximum of 33 lg m\ located north of the City. Also in this case the values are considerably higher than the average computed for the whole area with the regional scale model (9 lg m\), but slightly below the long-term WHO guidelines. These facts are in accordance with available measurements for year 1990: the average of the mean concentrations reported by three GEMS/NEERI monitoring stations in or near the City (42 lg m\; WHO/UNEP, 1992), and the average of mean values from a network of 22 MCGB (Municipal Corporation of Greater Bombay) stations (18 lg m\; Larssen et al., 1995). It is not possible to evaluate the model&&s skill in capturing the spatial distribution due to the fact that most of the MCGB measurement sites are clustered around the center of the city (Fig. 7) and fall within only a few grid cells. The local-scale variability found in these stations (annual mean values ranging from 7 to 50 lg m\) is not reproduced by the simulations, however the general patterns in the predictions are similar with 26 lg m\ for the City (average of
Fig. 6. Bombay*Computed mean annual SO concentrations (lg m\).
values at 6 stations) and 20 lg m\ for Greater Bombay (average of values at 12 stations) (Larssen et al., 1995). As for peak episodes, the simulation shows that although values higher than 100 g m\ occur in 10% of cases, the WHO short-term guidelines are not exceeded. This con"rms, together with yearly average levels, the less critical situation of Bombay for SO , if compared with Beijing (WHO/UNEP, 1992).
3.4. Future scenarios In perspective of the use of the model in an integrated assessment framework, future scenarios have been preliminary considered. For this purpose, the energy-scenario generation module of RAINS-Asia has been applied to create emission "gures projected for the year 2020. The hypothesis of the &&no further control'' (NFC) scenario has been adopted, with future emissions based on projections of socio-economic activities and under the hypothesis of no emission control measures adopted beyond the ones already implemented in the year 1995. On the basis of this emissions scenario the future concentrations for Beijing and Bombay have been then simulated following the same procedure explained in previous paragraphs. Under these conditions, the Bombay metropolitan area, as well as the whole surrounding region, are
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4. Conclusions
Fig. 7. Bombay } Measured mean annual SO concentrations (lg m\; from Gronskei et al., 1995).
Fig. 8. Calculated mean annual SO concentrations (lg m\) in the year 2020, on the basis of RAINS-Asia NFC emission scenario. (a) Beijing; (b) Bombay.
predicted to have yearly average values substantially higher than now (Fig. 8a). Most of the densely populated areas would be exposed to SO levels above 100 lg m\ well above the WHO and the Indian national standards. In the case of Beijing (Fig. 8b) most of the urban population would be exposed to concentrations above 200 lg m\, while the area above 100 lg m\ would extend far beyond the City center and into the surrounding agricultural areas.
The possibility of using a Lagrangian trajectory model for sulfur to assess the air quality inside and near Asian megacities, in a way consistent with the regional-scale analysis, has been explored. The multiple-layer UR-BAT model has been set up, adapted from the ATMOS model already used for the continental scale, and applied to Beijing and Bombay by using currently available information and preliminary emission "gures. Both models have been used in the simulations: ATMOS to account for the contributions of distant sources, UR-BAT for the local ones. The comparison with available monitoring data has shown that the simulated concentrations, as well the peak values in cities with di!erent climatologies and pollution levels are in the correct range. This indicates the possibility of using this approach as a tool for provinding preliminary estimations of health and direct ecological impacts, within the context of the RAINS-Asia (Asia-wide) integrated assessment (i.e. to estimate the contributions of local and distant sources, as well the in#uence of emissions from di!erent economic sectors). In this perspective, a few considerations need to be pointed out. The quality of data involved in the study clearly needs to be improved, especially urban emission estimates and their spatial distribution. Monitoring activities also need to be expanded, both inside the cities and in their immediate surroundings. The current situation for Asian cities of potential interest is that there is insu$cient monitoring data of known quality upon which to perform a comprehensive analysis of model performance (WHO/UNEP, 1992). The availability of local meteorological information is another key issue for the modelling exercise on megacities. In the examples previously shown, only synoptic scale data have been employed. Although most megacities have upper air sounding stations in their neighbourhoods, their data could be usefully integrated with local information from urban or sub-urban meteorological stations. These, when available, should provide a more accurate simulation of the dispersion in the lower layers. The work on megacities within RAINS-Asia project is still ongoing, also on di!erent urban agglomerates, with a focus on developing more reliable emission "gures, carrying out a more extensive model evaluation against monitoring data, and extending the model to include primary particulate matter.
Acknowledgements This reasearch was partially supported by the World Bank and the Asian Development Bank as part of the RAINS-ASIA project. The authors are indebted to
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M. Amann for valuable encouragement and support throughout the period of the study; special thanks also to R. Arndt for code and data assistance. References Alcamo, 1990. The RAINS Model of Acidi"cation, Science and Strategies in Europe. Kluwer Academic Publ., Dordrecht, Netherlands. Amann, M., 1994. Transboundary air pollution: the RAINS model. In: Options. Winter, International Institute for Applied System Analysis, Laxenburg, Austria. Amann, M., Dhoondia, J., 1994. RAINS-Asia } User's manual, International Institute for Applied System Analysis, Laxenburg, Austria. Arakawa, H. (Eds.), 1981. World Survey of Climatology, vol. 8 } Climates of Northern and Eastern Asia. Elsevier, Amsterdam. Arndt, R.L., Carmichael, G.R., 1995. Long-range transport and deposition of sulfur in Asia. Water, Air and Soil Pollution 85, 2283}2288. Arndt, R.L., Carmichael, G.R., Roorda, J.M., 1997a. Seasonal source-receptor relationships in Asia. Atmospheric Environment. Arndt, R.L., Carmichael, G.R., Streets, D.G., Bhatti, N., 1997b. Sulfur dioxide emissions and sectorial contributions to sulfur deposition in Asia. Atmospheric Environment. Carmichael, G.R., Arndt, R.L., 1994. Long range transport and deposition of sulfur in Asia. In An Assessment Model for Acid Rain in Asia. Report from the World Bank sponsored project &&Acid rain and emission reduction in Asia''. Carmichael, G.R., Arndt, R.L., 1995. Sulfur deposition in Asia: an assessment of the present situation and future scenarios. Preprints of 21st NATO/CCMS Technical Meeting on Air Pollution Modelling and its Applications, Baltimora (MD, USA) 5}10 November. Chameides, W.P., Kasibhatla, H., Levy, H., Moxim, W., 1994. Growth of continental-scale metro-agro-plexes, regional ozone pollution and world food production. Science 264, 74}77.
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Foell, W., Green, C., Amann, M., Bhattacharya, S., Carmichael, G., Chadwick, M., Cinderby, S., Haugland, T., Hettelingh, J.-P., Hordijk, L., Kuylenstierna, J., Shah, J., Sherestha, R., Streets, D., Zhao, D., 1995. Energy use, emissions, and air pollution reduction strategies in Asia. Water, Air and Soil Pollution 85, 2277}2282. Gi!ord, F.A., 1976. Turbulent di!usion } typing schemes: a review. Nuclear Safety 17, 68}86. Gronskei, K., Gram, F., Hagen, L., Larssenn, S., Jansen, H., Olsthoorn, X., 1995. Urban Air Quality management Strategies in Asia (URBAIR). NILU Report, July 1995, Norwegian Institute for for Air Research, Lillestr+m, Norway. He!ter, J.L., 1983. Branching Atmospheric Trajectory (BAT) model. NOAA Technical Memorandum ERL ARL-121. Hettelingh, J.P., Sverdrup, H., Zhao, D., 1996. Deriving critical loads for Asia. Water, Air and Soil Pollution, in press. Hordijk, L., 1991. The use of the RAINS models in acid rains negotiations in Europe. Environmental Science and Technology 25, 596}603. Larssen, S., Gram, F., Hagen, L.O., Jansen, H., Olsthoorn, X., Aundhe, R.V., Joglekar, U., Mehta K.H., Mahashur, A.A., 1995. URBAIR*Urban Air Quality Management Strategies in Asia } Greater Bombay } City Speci"c Report, NILU Report OR 56/95, December 1995, Norwegian Institute for for Air Research, Lillestr+m, Norway. Scire, J.S., Lurman, F.W., Bass, A., Hanna, S.R., 1984. User's guide to the MESOPUFF II Model and Related Processor Programs. EPA Publication No. EPA 600/8-84-013, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina. Takahashi, K., Arakawa, H. (Eds.), 1981. World Survey of Climatology, Vol. 9 } Climates of Southern and Western Asia. Elsevier, Amsterdam. UN, 1986. Population Growth and Policies in Megacities } Bombay. ST/ESA/SER.R/67, United Nations, New York. UN, 1991. World Urbanization Prospects 1990. United Nations, New York. WHO, 1984. Urban Air Pollution, 1973}1980. World Health Organization, Geneva. WHO/UNEP, 1992. Urban Air Pollution in Megacities of the World. Blackwell Publishers, Oxford.
An urban trajectory model for sulfur in Asian megacities: model concepts and preliminary application Giuseppe Calori *, Gregory R. Carmichael International Institute for Applied Systems Analysis (IIASA), Laxenburg, A-2361 Austria Department of Chemical and Biochemical Engineering, University of Iowa, Iowa City, IA 52242, USA Received 15 May 1996; accepted 30 November 1997
Abstract This paper explores the adaptation of a regional Lagrangian approach for making long-term simulations of SO and sulfate ambient concentrations at the resolution needed for health e!ects risk assessment in Asian megacities and their surroundings. A Lagrangian trajectory model (UR-BAT) is described which simulates transport and di!usion of sulfur within and near urban areas, originating from area and major point sources. The long-range contribution is accounted for by the ATMOS model, simulating all Asian sources. The model has been applied to Beijing and Bombay, by using preliminary emission "gures, and the results have been compared with available monitoring data. The computed concentrations in di!erent cities are in the correct range, indicating the potential use of the model in an integrated assessment framework such as RAINS-Asia. 1999 Elsevier Science Ltd. All rights reserved. Keywords: Megacities; Sulfur; Assessment model; Beijing; Bombay
1. Introduction Strong population increase and high economic growth rates are causing in Southeast Asian cities the same environmental problems faced by cities in the highly industrial world. The available information shows that the World Health Organization (WHO) air quality guidelines are systematically exceeded in major urban centres throughout Asia. According to the data from the WHO/UNEP long-term Urban Air Quality Monitoring and Assesment Programme (GEMS/Air), Bangkok, Beijing, Bombay, Calcutta, Delhi, Jakarta, Karachi, Manila, Seoul and Shanghai have serious problems with suspended particulate matter. In these cities both long-term and short-term WHO guidelines are exceeded by more
* Corresponding author. Dipartimento di Elettronica e Informazione, Politecnico di Milano, Via Ponzio 34/5, 20133, Milan, Italy.
than a factor of two (WHO/UNEP, 1992). Sulphur dioxide is a major problem in megacities such as Beijing, Seoul, Shanghai, Delhi and Karachi. Several factors contribute to this situation. Asia is experiencing economic growth rates which are among the highest of the world, its energy demands are being met by heavy usage of indigenous coal as primary fuel source (still dominant in most of the countries), and it is experiencing a persistent urbanization. Six Asian cities currently have more than eight million inhabitants, and 56 have more than one million. Furthermore, throughout Asia the fraction of the population living in urban areas is continuously increasing, and according to current projections, in the next decade the urban population will exceed the rural population (UN, 1991). The large number of people being exposed to high pollution levels in Asian urban areas represents a major environmental problem in the region. The term MetroAgro-Plex has been de"ned to characterize these zones with intermingling of agricultural and urban-industrial activities. The high levels of pollutants can also cause
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direct ecosystem damage, including reductions in crop yelds as discussed by Chameides et al. (1994). 1.1. The rains-ASIA framework The RAINS-Asia project (Foell et al., 1995; Amann, 1994), sponsored by the World Bank, the Asian Development Bank and other Asian and international institutions, is a preliminary study of the impact of the growing energy use in Asian environment. The major purpose of the RAINS-Asia project is to provide modelling support for an integrated risk assessment of acidi"cation in Asia. Following the lines of the European approach (Alcamo, 1990; Hordijk, 1991), the modelling system is organized in sub-models devoted to energy-scenario generation, emission and cost control evaluation, atmospheric dispersion and critical loads assessment (Foell et al., 1995). The emission-deposition relationship is expressed in terms of a transfer matrix, calculated using ATMOS, a multi-layer trajectory model of sulfur transport/deposition (Carmichael and Arndt, 1994, 1995). Computed source/receptor information relate the deposition on each of 13;13 grid cell with the emissions from 250 of the largest point sources, and the remaining area sources of the region, grouped into 94 subregions. It is desirable to include in the analysis a consistent assesssment of health-related problems and direct ecosystem damage arising from high SO levels in the major urban areas. However, the scale of the regional model does not allow one to fully reconstruct the peaks of concentrations in urban areas (see Section 3). An atmo-
spheric model running at higher resolution is in fact required, using more detailed and "ner spatially resolved emission "gures in megacities and their surroundings. The results, conveniently summarized and integrated into the modeling system, would allow the simultaneous analysis of the human health and acidi"cation risks. To explore the possibility of such a coherent approach within the existing framework, the trajectory model already developed and applied at 13 resolution for Asia has been modi"ed and initially tested on a few urban areas. The structure of the model and the results of a few preliminary applications and comparisons with available monitoring data are reported in the following sections. The purpose of this model is to provide a preliminary assessment of the risk to human health, and to ecosystem damage due to exposure of air pollutants and depositions, within the context of an integrated analysis of the environmental impacts associated with the rapid growth in energy consumption in Asia. A further quanti"cation of the impacts in high risk regions clearly requires the use of more detailed modeling activities.
2. Description of the UR-BAT model The UR-BAT (URban } Branching Atmospheric Trajectory) model has been designed to simulate the di!usion of sulfur within and near megacities. It is based on the ATMOS model already developed by Carmichael and Arndt (1994) for long-range transport of sulfur in Southeast Asia (Fig. 1), as the
Fig. 1. RAINS-Asia and ATMOS modelling domain, showing also the location of upper air stations (grid lines every 53).
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atmospheric dispersion section of the RAINS-Asia modelling system. ATMOS is a Lagrangian multi-layer trajectory model, derived from NOAA's Air Resources Laboratory BAT model (He!ter, 1983). The model is source-oriented: every 3 h a new pu! is generated from each source, and placed in a proper vertical layer, according to source type (surface/elevated) and day/night occurrence. During the day, two vertical layer are adopted (Fig. 2): the boundary
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layer, extending from the surface to the bottom of the critical temperature inversion, and the upper layer, extending from there to the top of the domain, "xed at 6000 m. During the night, a surface layer is also present, extending from the ground to a "xed height of 300 m. Pu! trajectories are computed by using average winds for each layer. The critical inversion height as well as the transport wind are computed from upper air sounding data.
Fig. 2. Daytime and nighttime vertical layers in the UR-BAT model.
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Depending on the changes in layer con"guration during day-to-night and night-to-day transitions, the existing pu!s can branch into several new ones or can vertically mix in the new layer. New branches follow independent trajectories, according to the wind of the corresponding layer. The mass of pollutant initially released according to source strength is partitioned among di!erent branches, according to post-transition layer thickness. Along trajectories the mass balance equations are integrated, considering the chemical transformation from SO to sulfate and dry and wet deposition phenomena, all modelled as "rst-order processes. Model parameters employed for Asia depend on geographic as well on meteorological conditions (for details, see Carmichael and Arndt, 1994). The concentrations and deposition at gridpoints or at selected receptors are "nally computed by superposition of the contributions of individual pu!s. In the vertical a uniform mass distribution is assumed within each layer, while in the horizontal a Gaussian distribution is adopted, with a dispersion coe$cient depending on travel time. In order to provide an initial evaluation of air quality for major urban areas, consistent with the regional-scale picture, the ATMOS model has been adapted as described in the following. 2.1. Emissions and transport In the urban model every hour a new pu! is released by each source, carrying a fraction of the total mass emitted by the source during the year. The hourly release frequency, although increasing the total computational time, has been introduced to avoid concentration oscillations when the 3-hour release frequency used in ATMOS is applied to the smaller spatial grid resolution of the URBAT model. The emissions take place in di!erent layers according to the source type (area or point) and the hour of day. Surface sources release pu!s into the boundary layer (during day) or into the surface layer (during night). Elevated point sources always release pu!s into the boundary layer. In daytime conditions the boundary layer extends from the ground up to the critical inversion; during night its base is the top of the surface layer, so the material is kept from reaching the surface. In all layers the pollutant is assumed to be uniformly mixed in the vertical. Emitted pu!s move according to the winds in the di!erent layers, and can be split during day/night transitions into several independent branches (up to 32 branches for each initially emitted pu!). Mass exchange among branches in the di!erent layers are governed by the branching scheme explained later. The pu! trajectories are computed every hour using the same technique (a modi"ed Euler advection algo-
rithm) employed in the ATMOS model, and are based on the upper air soundings data. At each station the horizontal winds are calculated by vertically averaging the measured wind over each layer of interest. If no data are available at a given time within a one degree radius, the data from the surrounding stations can be used. The search radius is progressively incremented, up to a maximum distance of 53, and the available data are interpolated by using weights equal to the inverse square of the distance. If no data are available within a 53 radius, a monthly climatological value is used, computed by interpolating in space the monthly average winds at each sounding station. Corrections have also been introduced in the wind calculation procedure, to treat the cases of missing observational data, especially in the lower layers. If the measured wind data at a given time are available only above the 300 m level, the wind in the low layers is computed by downward interpolating these values, assuming a vertical logarithmic pro"le. If no data are available at the upper levels, then the climatological value is used, for all layers. 2.2. Puw branching and mixing To account for wind shearing of pu!s emitted and moving in di!erent layers, trajectories can branch into independent trajectories. New branches can be generated during day-to-night and night-to-day transitions (Fig. 3), with the mass split according to post-transition layer thickness. Branching and mixing are organized as follows. During day-to-night transitions, a pu! in the boundary layer will branch into the surface and nighttime boundary layers. In the same situation, if a signi"cant lowering ('300 m) of boundary layer top occurs, a further upper layer branch is also generated. During nightto day transitions, pu!s in the surface or in the nighttime boundary layer are mixed in the daytime boundary layer. Also in this case a signi"cant lowering of boundary layer top causes the generation of a new upper layer branch. Pu!s in the upper layer always remain above the boundary layer top, unless it rises signi"cantly ('300 m) during a day-to-night or night-to day transition; in this cases a new boundary layer branch is generated. 2.3. Concentration calculations As in the ATMOS model, two forms of sulfur are treated explicitly: gaseous sulfur dioxide and aerosol sulfate. Sources are assumed to emit both species (the sulfate is assumed as 5% of the total sulfur emitted). The pu! masses change along the trajectories according to the chemical conversion to sulfate and the dry and wet deposition phenomena. A simple "rst-order rate constant is used for chemical conversion, depending on latitude and day of year. This conversion rate parametrization takes
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are depleted by dry deposition, while wet deposition a!ects all the layers. The mass balance equations are integrated with a hourly time step. The concentrations at each grid point in a given layer are computed by summing up the contributions of all the pu!s in that layer (only pu!s in ground-based layers contribute to surface concentrations). The mass of each pu! is assumed to be uniformely mixed in the vertical within a layer, while in the horizontal a univariate Gaussian distribution is assumed, with a standard deviation (p ) assigned according to travel distance and urban/rural conditions. In the short range ((30 km), the Pasquill}Gi!ord} Turner formulation is used for rural conditions, with coe$cients taken as in MESOPUFF II model (Scire et al., 1984), while in urban conditions Briggs &&urban'' p are used, (as reported in Gi!ord, 1976). The location and extent of urban areas is speci"ed in the model in terms of an appropriate urban/rural mask. In the long range, dispersion coe$cients are taken proportional to travel time (He!ter, 1983), computed incrementally from the value at the previous time step as (p( ) "(p ) #0.5dt. R>BR R where dt denotes the computational time step (in s) and p is in meters. For area sources an initial minimum standard deviation, ph is used, depending on the source extent.
3. Preliminary calculations and model experiments
Fig. 3. Branching and mixing scheme (BL: boundary layer; SL: surface layer; UL: upper layer).
into account both gas-phase and liquid-phase processes. The rates typically range from 0.5 to 2.5% h\. The dry and wet removal are also treated as "rst order processes, with seasonally varying rates depending, respectively, on latitude and precipitation rate and on latitude and land/sea occurrence. Parameter values have been choosen to re#ect Asian conditions and are discussed in more detail in Carmichael and Arndt (1994), Arndt and Carmichael (1995), Arndt et al. (1997a and 1997b). Only pu!s travelling in layers in contact with the surface (daytime boundary and nighttime surface layers)
The model has been tested for the megacities of Beijing and Bombay. UR-BAT was run inside the 13 grid cell containing the considered megacity, using a 0.13 resolution simulation and the original emission attached to the 13 grid, apportioned to the "ner grid as discussed later. The computed concentrations were then superimposed on those computed with the ATMOS model, taking into account the e!ect of all remaining Asian sources (large point sources and area sources, both natural and anthropogenic). The results were then compared with available information on air quality in the cities, to provide a preliminary indication on the reliability of the range of the concentrations computed by the model. 3.1. Meteorological input The upper air soundings data provided by US National Climatic Center, NOAA for the year 1990 were used (the location of the reporting stations in Southeast Asia is shown in Fig. 1). The data include 6 hourly vertical pro"les of potential temperature and wind speed from the surface to 500 hPa. These data are used in the model to determine the critical inversion height, which delimits
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the top of the boundary layer, and the average winds of each model layer. The criteria adopted for the critical inversion are taken as in He!ter (1983): *#/*z*0.005 K m\ # !# *2 K 2 where *#/*z is the change of potential temperature # with height z, and # and # are temperatures at the 2 top and the base of the inversion. The monthly climatological wind "elds, used by the model when no measured data are available at a given time and location, have also been computed from upper air soundings, interpolating in space, for each layer, the monthly average winds at the sounding stations. Analyzed US NMC precipitation data provided by the National Centre for Atmospheric Research (NCAR) have been used. These consist of 6-hourly accumulated values on a grid with a mesh size of a 1.46953 latitudinal by 1.48753 longitudinal. Inside the model, the gridded data are assumed to be uniformly distributed within the sixhour interval, and spatially interpolated inside the model by using a bilinear method, to adapt to the model grid system. 3.2. Application to Beijing A 0.13 resolution urban/rural mask for Beijing has been de"ned, and used to distribute the 13 emissions (362 kt yr\ of SO ) estabilished by the RAINS-Asia emissions module for the grid cell. 50% of these emissions have been attributed to the urban area, and uniformily distributed on the 0.13 &&urban'' grid cells; the remaining 50% to the surrounding rural areas, also uniformily distributed on their respective 0.13 grid cells. Although very rough, this emission pattern qualitatively re#ects the main feature of the high emission density of the urban area, and has been used to point out the basic capabilities of the model. Fig. 4a shows the computed average SO concentra tion map for the year 1990. The concentration pattern is generally oriented towards Southeast, according to the prevailing winds during the cold season (Arakawa, 1981). The &&hot spot'' around the urban area is considerabily above the average value (48 lg m) computed by the regional model at 13 resolution, and is in the range of the values given by WHO-UNEP GEMS/AIR stations. The calculated values exceed the long-term WHO guidelines (40}60 lg m\) over large areas around the city. These results are consistent with city centre stations reporting annual means over 100 g m\ (WHO/UNEP, 1992). The occurrence of peak values is also important in the evaluation of the health e!ects. Fig. 4b shows the corresponding map of the percentages of hours in exceedance of the WHO short-term standard (350 lg m). The whole metropolitan area is signi"cantly a!ected by recurring
high pollution episodes. According to the simulation the hourly guideline is exceeded in the immediate surroundings of the urban area in a few percent of cases, and more than 5% in the centre of the city. This is con"rmed by monitoring activities. Measured data indicate that peak values can reach 700 lg m\, and daily means above 500 and 250 lg m\ are reached on 2% of the days in the city centre and in suburbs, respectively (WHO/UNEP, 1992). Elevated SO concentrations can also have direct impact on the ecosystems surrounding the metropolitan area. For example, many crops and trees show declines in yelds and productivity when SO concentrations exceed some threshold value (called critical levels). In a recent study (Hettelingh et al., 1996), critical levels for SO in Asia have been set at 40 lg m\. As shown in Fig. 4, extensive regions around Beijing are predicted to have concentrations which exceed this critical level. Combining this analysis with spatial information on forest and crop lands, could allows an assessment of risks of these ecosystems resulting from exposure to elevated SO concentrations. 3.3 Application to Bombay After the preliminary calculation on Beijing the model was also applied to the Bombay area, to extend the study to a megacity a!ected by di!erent climate and pollution levels. The yearly 1990 emissions evaluated by RAINS-Asia model for the corresponding 13 grid cell (87870 t yr\ of SO ) have been spatially disaggregated on a 0.13 grid (Fig. 5) by using available information on population distribution and industrial sources location (UN, 1986; Gronskei et al., 1995). The estimated emissions are
Fig. 4. Beijing*(a) computed annual average SO concentra tions (lg m\); (b) percentages of hours exceeding 350 lg m\ of SO , on a yearly basis (isolines at 1, 2, 5 and 7.5%).
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Fig. 5. Bombay*Adopted SO emission #ux density.
unevenly distributed, with maxima in the densely populated City, the south districts of Greater Bombay and the banks of Thana Creek. As in the previous application the contribution to concentrations from the remaining Asian sources was calculated with the ATMOS model, and superimposed on UR-BAT model results. Figure 6 shows the calculated yearly average concentration map. Despite the non-uniform source distribution, the yearly ground-level concentration pattern looks fairly regular. An &&urban plume'' oriented eastward over land can be clearly depicted, following the direction of sea breeze and predominant synoptic wind direction during summer monsoon (Takahashi and Arakawa, 1981). In the urban area the computed values are generally above 20 lg m\, with a maximum of 33 lg m\ located north of the City. Also in this case the values are considerably higher than the average computed for the whole area with the regional scale model (9 lg m\), but slightly below the long-term WHO guidelines. These facts are in accordance with available measurements for year 1990: the average of the mean concentrations reported by three GEMS/NEERI monitoring stations in or near the City (42 lg m\; WHO/UNEP, 1992), and the average of mean values from a network of 22 MCGB (Municipal Corporation of Greater Bombay) stations (18 lg m\; Larssen et al., 1995). It is not possible to evaluate the model&&s skill in capturing the spatial distribution due to the fact that most of the MCGB measurement sites are clustered around the center of the city (Fig. 7) and fall within only a few grid cells. The local-scale variability found in these stations (annual mean values ranging from 7 to 50 lg m\) is not reproduced by the simulations, however the general patterns in the predictions are similar with 26 lg m\ for the City (average of
Fig. 6. Bombay*Computed mean annual SO concentrations (lg m\).
values at 6 stations) and 20 lg m\ for Greater Bombay (average of values at 12 stations) (Larssen et al., 1995). As for peak episodes, the simulation shows that although values higher than 100 g m\ occur in 10% of cases, the WHO short-term guidelines are not exceeded. This con"rms, together with yearly average levels, the less critical situation of Bombay for SO , if compared with Beijing (WHO/UNEP, 1992).
3.4. Future scenarios In perspective of the use of the model in an integrated assessment framework, future scenarios have been preliminary considered. For this purpose, the energy-scenario generation module of RAINS-Asia has been applied to create emission "gures projected for the year 2020. The hypothesis of the &&no further control'' (NFC) scenario has been adopted, with future emissions based on projections of socio-economic activities and under the hypothesis of no emission control measures adopted beyond the ones already implemented in the year 1995. On the basis of this emissions scenario the future concentrations for Beijing and Bombay have been then simulated following the same procedure explained in previous paragraphs. Under these conditions, the Bombay metropolitan area, as well as the whole surrounding region, are
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4. Conclusions
Fig. 7. Bombay } Measured mean annual SO concentrations (lg m\; from Gronskei et al., 1995).
Fig. 8. Calculated mean annual SO concentrations (lg m\) in the year 2020, on the basis of RAINS-Asia NFC emission scenario. (a) Beijing; (b) Bombay.
predicted to have yearly average values substantially higher than now (Fig. 8a). Most of the densely populated areas would be exposed to SO levels above 100 lg m\ well above the WHO and the Indian national standards. In the case of Beijing (Fig. 8b) most of the urban population would be exposed to concentrations above 200 lg m\, while the area above 100 lg m\ would extend far beyond the City center and into the surrounding agricultural areas.
The possibility of using a Lagrangian trajectory model for sulfur to assess the air quality inside and near Asian megacities, in a way consistent with the regional-scale analysis, has been explored. The multiple-layer UR-BAT model has been set up, adapted from the ATMOS model already used for the continental scale, and applied to Beijing and Bombay by using currently available information and preliminary emission "gures. Both models have been used in the simulations: ATMOS to account for the contributions of distant sources, UR-BAT for the local ones. The comparison with available monitoring data has shown that the simulated concentrations, as well the peak values in cities with di!erent climatologies and pollution levels are in the correct range. This indicates the possibility of using this approach as a tool for provinding preliminary estimations of health and direct ecological impacts, within the context of the RAINS-Asia (Asia-wide) integrated assessment (i.e. to estimate the contributions of local and distant sources, as well the in#uence of emissions from di!erent economic sectors). In this perspective, a few considerations need to be pointed out. The quality of data involved in the study clearly needs to be improved, especially urban emission estimates and their spatial distribution. Monitoring activities also need to be expanded, both inside the cities and in their immediate surroundings. The current situation for Asian cities of potential interest is that there is insu$cient monitoring data of known quality upon which to perform a comprehensive analysis of model performance (WHO/UNEP, 1992). The availability of local meteorological information is another key issue for the modelling exercise on megacities. In the examples previously shown, only synoptic scale data have been employed. Although most megacities have upper air sounding stations in their neighbourhoods, their data could be usefully integrated with local information from urban or sub-urban meteorological stations. These, when available, should provide a more accurate simulation of the dispersion in the lower layers. The work on megacities within RAINS-Asia project is still ongoing, also on di!erent urban agglomerates, with a focus on developing more reliable emission "gures, carrying out a more extensive model evaluation against monitoring data, and extending the model to include primary particulate matter.
Acknowledgements This reasearch was partially supported by the World Bank and the Asian Development Bank as part of the RAINS-ASIA project. The authors are indebted to
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M. Amann for valuable encouragement and support throughout the period of the study; special thanks also to R. Arndt for code and data assistance. References Alcamo, 1990. The RAINS Model of Acidi"cation, Science and Strategies in Europe. Kluwer Academic Publ., Dordrecht, Netherlands. Amann, M., 1994. Transboundary air pollution: the RAINS model. In: Options. Winter, International Institute for Applied System Analysis, Laxenburg, Austria. Amann, M., Dhoondia, J., 1994. RAINS-Asia } User's manual, International Institute for Applied System Analysis, Laxenburg, Austria. Arakawa, H. (Eds.), 1981. World Survey of Climatology, vol. 8 } Climates of Northern and Eastern Asia. Elsevier, Amsterdam. Arndt, R.L., Carmichael, G.R., 1995. Long-range transport and deposition of sulfur in Asia. Water, Air and Soil Pollution 85, 2283}2288. Arndt, R.L., Carmichael, G.R., Roorda, J.M., 1997a. Seasonal source-receptor relationships in Asia. Atmospheric Environment. Arndt, R.L., Carmichael, G.R., Streets, D.G., Bhatti, N., 1997b. Sulfur dioxide emissions and sectorial contributions to sulfur deposition in Asia. Atmospheric Environment. Carmichael, G.R., Arndt, R.L., 1994. Long range transport and deposition of sulfur in Asia. In An Assessment Model for Acid Rain in Asia. Report from the World Bank sponsored project &&Acid rain and emission reduction in Asia''. Carmichael, G.R., Arndt, R.L., 1995. Sulfur deposition in Asia: an assessment of the present situation and future scenarios. Preprints of 21st NATO/CCMS Technical Meeting on Air Pollution Modelling and its Applications, Baltimora (MD, USA) 5}10 November. Chameides, W.P., Kasibhatla, H., Levy, H., Moxim, W., 1994. Growth of continental-scale metro-agro-plexes, regional ozone pollution and world food production. Science 264, 74}77.
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