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The Spanish project on energy and environment: ENMA
Environment lnternational, Vol. 10, pp. 431-436, 1984
0160-4120/84 $3.00 + .00 Copyright ~ 1985 Pergamon Press Ltd.
Printed in the USA. All rights reserved.
THE SPANISH PROJECT ON ENERGY AND ENVIRONMENT: ENMA J. Ortega-Costa, A. L6pez Garcia, M. Molina Martrn, M. L. Guillam6n Duch, G. Echag0e M~ndez-Vigoa General Secretariat of Energy and Resources, Ministry of Industry and Energy, Madrid, Spain (Received 10 July 1983; Accepted 10 June 1984) The project ENMA assesses the atmospheric pollution caused by the transformation and consumption of energy. The project is in the following stages: (a) estimation of annual overall average emissions; (b) estimation of annual average concentrations of pollutants; and (c) estimation of doses. Estimation of annual overall average emissions is estimated, separately, for urban areas and point sources. Concentrations of pollutants are obtained for urban areas and point-sources by means of two different gaussian models. Finally, doses are calculated assuming that the effects of all pollutants are linear at low doses. Doses for each pollutant, and doses for exposure to several combined pollutants, are defined. The doses on population are also defined, assuming that the significance of pollution depends on the number of people exposed.
INTRODUCTION
STRUCTURE OF THE ENMA PROJECT
Energy processes have a great influence on the environment due to the intensity with which consumption of natural resources is required by them. Generation, transformation, and consumption of energy cause a great amount of waste matter (solid, liquid, or gaseous) which, when set free, are the cause of environmental pollution. The degree and nature of the pollution depends on the technologies in use and the amount and quality of the energy resources. Consequently, when deciding among different energy options, environmental considerations play a fundamental role. Therefore, energy policies directed to the welfare of the community must take into consideration the possible harmful secondary effects resulting from the increase of energy consumption. From this point of view, the assessment of environmental impact is directly related to the tasks of energy planning, and is helpful when considering the factors that limit or optimize energy projects.
Acknowledging the importance of including environmental analysis in energy planning, the Spanish Ministry of Industry has been developping since 1980 a method to assess the impact of the energy on the environment. This study, known as project ENMA (Energia and Medio Ambiente) aims to develop a simple and flexible method of estimating the atmospheric pollution resulting from different theoretical working conditions of an energy system. The project is in three stages: (1) estimation of the annual overall average emissions; (2) estimation of the concentration of pollutants; and (3) calculation of the doses. Estimation of the Annual Overall Average Emissions Emissions due to the consuming sectors. In this part of the project a model is developed which estimates the emissions of the different pollutants caused by the final uses of energy, and branches them out geographically. This model is called EMIR (Emisiones Regionales). The measurements produced by the model are as follows: 1. Consumption of the different types of energy in each of the 50 Spanish provinces and separately in their capital cities. 2. Structure of the consumption of energy for all the provinces and their capital cities.
aCorrespondence should be addressed to: Mariano Molina Martfn, General Secretariat of Energy and Resources, Ministry of Industry and Energy, P. de la Castellana, 160, Madrid 16, Spain 431
432
J. Ortega-Costa et al.
3. Annual average emissions of pollutants (SO2, particulate matter, NO~, and CO) of each type of energy in each of the capital cities of the fifty provinces. The data given to the model are as follows: 1. Population in each province and in its capital city during the period 1970-1980. 2. Historical consumption of energy for each province during the period 1970-1980. 3. Forecast of the demand of energy for the whole country as estimated in the National Energy Plan. 4. Forecast of the Spanish Population estimated by the National Institute of Statistics. 5. Emission factor matrix for the four pollutants mentioned above and for the following types of energy: oil products (liquid petroleum gases, gasoline, gas-oil, fuel-oil, and kerosene); natural gas; and coal (hard coal, Lignite, and Briquettes). This matrix has been calculated using several studies carried out by the Ministry of Industry and Energy of Spain (1978) and other agencies (U.S. EPA, 1973). With these data, the model EMIR works two separate mechanisms (see Fig. 1). First, from the historical series the model calculates the historical structure of the consumption of energy. Using an inertial scenario, it fore-
CONSt~oTION BY TYPE OF ~rERGY
~OGHAPEY
I
I
'
BY ENERGY TYPES
I ~ONSOMI~ION "PER CAPITA~
I NATI )NAL
SC~ARIOS 0
~D TO P~0VI ~ C L ~ ~S~CONSt~3TION ~UR~ B
CONSUMPTION S~RUCTUR~ B
F~ERGY TTPE
~¢~GY CONSL~ION "PER CAPITA"
I NSUMI~ION "PER CAPITA'~ A/MkPTED TO NATIONAL GY PLAN FORECAST |
FOEECA~T OF POPULATION IN CAPITAL CITIES ~ERGY OONbq)7~TION IN CAPITAL CITIES I
CONSUMPTION BY TYPES I OF IRERGY IN CAPITAL CITIEs D ~GU~A~IO@
J
O "I ~IISSIONS
~MISSION FACTORS
Fig. 1. EMIR model
l
casts this structure for the years 1990, 1995, and 2000. Second, the analysis of the two series, total final consumption and population, gives the historical evolution of the final consumption "per capita" and a forecast of this variable, based on the historical trend, for the years 1990, 1995, and 2000. The integration of this variable to obtain the total national consumption is fitted automatically, to meet the forecast of the demand of energy of the National Energy Plan. With the structure of consumption and total consumption, urban consumptions are obtained for the years 1990, 1995, and 2000. Emissions are obtained by application of the emission factor matrix to these values. At this point, the model can easily simulate the emissions that would result when more strict environmental regulations are applied or when new technological systems with less environmental incidence are used. Table 1 shows the results obtained for four capital cities. Emissions due to the Transformation Sector. The National Energy Plan indicates the number of plants that will be necessary to meet the future energy requirements of the country. Plants are classified according to their technologies, the type of fuel they use, and the total amount of energy they produce. The plan also indicates the site of the plants. Measures for environmental control are fixed in each case, based on studies that have been performed before the plant can start operating. With the above information the emissions of sulphur oxides and particulate matter are calculated for the years 1990, 1995, and 2000.
Estimation o f the concentration o f pollutants The estimation of the ground concentrations is in two stages: concentration levels in capital cities due to the consumption of energy, and concentration levels in the vicinity of thermal power plants and refineries. Concentration Levels in Capital Cities Due to the Consumption of Energy. The concentration levels of SO2 and particulate matter have been calculated using an environmental indicator (Ludwig, 1970; Hanna, 1971; Gifford and Hanna, 1973; Pasquill, 1976; Calder, 1977; Echagiie, 1982). This indicator is obtained from the following parameters: 1. Annual average emissions of pollutants in urban areas. They have been obtained with the EMIR model. 2. A matrix of coefficients that depends on the wind run through the urban area and the distribution of the emitting sources throughout the city. 3. Extension and configuration of the city. 4. Height of the mixing level over the city. 5. Wind speed through the mixing level.
1
The indicator of atmospheric pollution obtained according to the above criteria has the following advantages: (1) It is easy to use, (2) experience shows that the parameters on which the indicators is based are the most
Energy and environment in Spain
433 Table 1. Results obtained by the EMIR model. Annual Emissions (103 metric tons)
Capital City
Madrid
Sevilla
Zaragoza
La Corufia
Year
SO2
PSB a
NOx
CO
1980 1990 1995 2000 1980 1990 1995 2000 1980 1990 1995 2000 1980 1990 1995 2000
37.5 34.6 33.8 33.6 9.5 11.9 13.1 14.4 15.5 21.2 24.5 28.1 4.5 5.4 5.6 6.0
14.5 7.7 5.2 5.1 1.3 1.6 1.7 1.9 4.7 4.9 5.2 5.4 1.3 1.4 1.5 1.6
39.7 43.1 44.8 46.4 9.5 11.5 12.5 13.6 15.1 21.0 24.4 28.1 5.4 6.6 7.0 7.3
250.1 297.8 318.3 336.4 38.4 50.6 56.6 62,7 44.9 64.6 75.8 88,2 14,7 19,7 21.2 22.6
a Particulate matter.
adequate in estimating the concentration of pollutants in urban areas; and (3) it takes into account the configuration of the city and the directions in which the wind sweeps the pollutants. Concentration Levels in the Vicinity o f Thermal Power Plants and Refineries. The Pasquill-Gifford model has been used to estimate the concentrations of SOs and particulate matter near the power plants. The rise of the plume has been estimated according to Briggs' formula (Pasquill, 1961; Turner, 1970; McMullen, 1975; U.S. EPA, 1977; Echagiie, 1979; MIE, 1981). A data base was developed containing the following information for each of the Spanish thermal power plants and refineries, as a previous requirement to the application of the model: 1. Annual average emission of SO2 and particulate matter for the period 1970-1980. 2. Characteristics of these emissions (volume, temperature, stack-height, and flue-gas speed). 3. Meteorological parameters of the plant sites. This information has been summarized in the corresponding climatological stability matrixes. 4. Topographical characteristics in a 50-km circle surrounding the plant. 5. Demographic data of the urban centers within the circle. The model provides data on the average concentration of SO2 and particulate matter for yearly periods, the distribution functions of the concentrations (i.e., the probability of surpassing a certain value), and the distribution of population according to pollutant exposure values.
Calculation o f the Doses Definition, Units and Equivalents. For an objective comparison of situations created by exposure to several airborne pollutants within a given social area, systematic criteria must be elaborated to assess simultaneous effects on the resident population. The concentration of pollutants is measured in the weight of pollutants in unit volume of air, e.g., /zg/(N)m3. Present regulations for the control of atmospheric environment limit concentrations on time basis. For short periods the limit is higher. These rules are to prevent high concentrations that would damage the health of the population. These considerations are not sufficient, because they overlook possible long-term effects, and they do not allow comparison of situations where there are several pollutants. Therefore, estimated doses must also be considered, since the possible effect of a given pollutant on the health of the population depends not only on the concentration in the air but also on the time of exposure. When dealing with low concentrations, the biological effects can be considered to be in proportion to the concentration and the time of exposure, in the same way as accepted for most toxic substances. Thus, D (c, 0 = Kct, Where D (c, 0 = dose; K = proportional coefficient; c = concentration of pollution; and t = time of exposure to concentration. This formula is a practical approach to the estimation of the problem; similar expressions are frequently used
J . O r t e g a - C o s t a et al.
434
in the absence of more rigorous biological data (Fulton County, 1971; Thomas et al., 1971; Babcock and Nagda, 1972; Larsen, 1973; Larsen, 1977). In these assumptions, pollution doses must be referred to a unit which has been called CONTI (Concentracion y tiempo). This unit stands for 100/~g/(N)m 3 of SO2 over a period of 1 yr. The definition of the dose in the case of other pollutants could be given in the same way; since the biological effects are different, however, the definition of a general unit is necessary for a comparison of the doses. This unit we shall call CONTI equivalent (Ceq) and it refers to the standard concentration of SO2. To achieve this equivalent, coefficients among the various pollutants must be established. In the supposition that the equivalent coefficient is known, the dose of pollutant i is the product of the annual concentration ci of that pollutant (expressed as #g/(N)m0 by the equivalent coefficient qr That is to say
where C,(t) = annual estimated standard of pollutant i during a period of time t, where t = 1 yr; C,o = standard concentration of pollutant i during the period of time to; and b = coefficient estimated on the established standards. Table 3 shows the values obtained by applying the above formula. Since the assumption of linear relationship between the doses and biological effects can only be considered for low concentrations, the equivalent factors will only refer to annual situations; application of daily and monthly values is more uncertain. Total Dose When several pollutants are present, the total dose in Ceq will be obtained as the sum total of the partial equivalent dose of each pollutant considered:
D~ = c~q. where D, is the equivalent dose of the pollutant i. The difficulty of this definition is in knowing and applying the equivalent coefficients. The lack of precise biological data has forced ENMA to take as the rule of equivalence the Spanish National air quality standards (see Table 2). It has been accepted that the annual national standards allowed by the Spanish regulations have the same significance in their effects on health. Since all the standards have not been defined for yearly periods, it has been estimated that daily and monthly standards can be annually extrapolated by the following formula, based on Larsen assumptions (Larsen, 1969; Larsen, 1977):
c,,,, _-
(+o)'
K D, = ~_. D,, 1
where D, = total dose; D, = equivalent dose of pollutant L and K = number of pollutants. Dose on the population The biological effects of the pollutants will be more important as the density of population exposed increases. For this reason it is convenient to define the overall dose on the population or demographic dose taking as unit the CONTI equivalent man (Cem). The demographic dose is calculated approximately as the product of the average overall annual dose by the number of inhabitants affected.
T a b l e 2. N a t i o n a l a i r q u a l i t y s t a n d a r d s . A l l d a t a i n / z g / ( N ) m 3. Exposure Time Pollutant
IA h r
2 hr
8 hr
SO2
--
700
--
Particulate matter
--
-
--
NOx
--
-
--
CO
--
--
15,000
Pb Hydrocarbons
50 280,000
C1
300
HC!
300
1 month
1 yr
400
255
150
300
202
130
200
--
100
--
--
--
--
--
--
1 4 0 , 0 0 0
--
--
--
1 day
10
--
--
5 0
--
--
--
--
5 0
--
--
20
--
I
10
-
-
40
I
--
10
-
--
-
F
60
-
I
HF
30
-
-
H2S
100
--
I
CS2
30
-
--
Energy and environment in Spain
435 Table 3. Reference concentrations. All data in #g/(N)m s. Concentrations
Pollutant
Constant b
Per day
Per month
Per year
SOs Particulates matter NOx CO Pb Hydrocarbons CI HCI F HF H2S CS2
0.166 0.141 0.166 0.157 0.580 0.179 0.462 0.462 0.283 0.283 0.236 0.283
400 300 200 12,624 5.28 140,000 50 50 20 10 40 10
256 202 114 7,400 0.739 76,200 10.4 10.4 7.6 3.8 17.9 3.8
150 130 100 4,999 0.197 48,800 3.2 3.2 3.7 1.8 9.9 1.8
CASE STUDY Table 4 summarizes an application of the ENMA project to La Corufia, the capital city of a Spanish province, located in the Northwest coast. Three thermal power plants are currently under operation in this province. Two of them (Puentes and Meirama) are coal-fired and produce 1950 MW of installed capacity. The other (Sab6n, 470 MW) is oil-fired. There is also a refinery with a capacity of 7 million of metric tonnes of crude per year. Distances to the town are, respectively, 46, 22, 10, and 9 km.
According to Table 4, estimated emissions of SOs increase in 1990 as Meirama starts to operate in 1981, and descend to a minimum in 2000 when Puentes is near to its cancellation. Concentrations of SOs originated by the plants decrease in 1990, because higher stacks are planned to be installed in the refinery. It is estimated that concentrations of SOs and particulate matter will rise in the consuming sector, where no change in the trends of final use of energy is expected. Finally, the dose on the population rises continuously, as population growth is not compensated by a similar decrease in the total dose.
Table 4. La Corufia: emission, concentrations and doses, a
Emission (10 s metric Tons) Energy sector b SO2 Particulate matter Energy consumption SO2 Particulate matter Total emissions SO2 Particulate matter Concentrations [#g/(b0m s] Energy sector SO2 Particulate matter Energy consumption SOs Particulate matter Total concentrations SO2 Particulate matter Doses (CONTI) SOs Particulate matter Total dose (Ceq) Dose on population (106 Cem)
1980
1990
2000
517.7 9.3
649.2 12.2
469.7 9.9
4.5 1.3
5.4 1.4
6.0 1.6
522.2 10.6
645.6 13.5
475.7 11.5
17.2 0.0
9.0 0.0
9.0 0.0
39.0 21.0
42.0 21.1
45.0 22.2
56.2 21.0
51.0 21.1
54.0 22.2
0.56 0.24 0.80 0.19
0.51 0.24 0.85 0.21
0.54 0.26 0.80 0.24
aThese estimations correspond to the capital city of La Corufia. bEmissions of the energy sector are originated by two coal-fired plants (1,400 and 550 MW), an oil-fired plant (470 MW), and a refinery (7,000,000 metric tons of crude treated per year).
436
SUMMARY AND CONCLUSIONS E N M A is a useful method to assess situations created by atmosphere pollutants originated by the energy sector. It can be used to simulate the impact of a certain energy policy as well as to estimate historical situations. The model can also be used to compare the environmental impact of several different energy options. Definition and application of the dose and the total doses concepts will result in a better understanding of the significance of the effects of air pollutants.
REFERENCES Babcock, L. R. and Nagda, N. L. (1972) Indices of quality, in Environmental Indices, W. A. Thomas, ed., pp. 183-197. University of Chicago, Chicago, IL. Calder, K. L. (1977) A correction to the Holzworth model of meterological potential for urban air pollution, Atmos. Environ. 11, 761-764. Echagiie y Mendez de Vigo, G. (1979) A method to apply the Pasquill-Gifford model to point sources. Department of Physics, Universidad Complutense, Madrid. Echagiie y Mendez de Vigo, G. (1982) An air quality index for urban areas. Its possible usefulness for the Madrid metropolitan area and others urban areas. Some reflections Thereon. Jornadas de Protecci6n del Ambiente Atmosf&ico, Delegaci6n de Saneamiento y Medio Ambiente del Excelentisimo Ayuntamiento de Madrid, Madrid. Fulton County Health Department (1971) Fulton County air pollution index. Fulton County Health Department, Atlanta, GA. Gifford, F. A. and Hanna, S. R. (1973) Modelling urban air pollution. Technical note, Atmos. Environ. 7, 131-136. Hanna, S. A. (1971) A simple method of calculating dispersion from urban area sources, J. Air Pollut. ControlAssoc. 21, 774-777. Larsen, R. J. (1969) A new mathematical model of air pollutant
J. Ortega-Costa et al. concentration averaging time and frequency, J. Air Pollut. Control. Assoc. 19, 24-30. Larsen, R. J. (1973) An air quality data analysis system for interrelating effects standards and needed source reduction, J. Air Pollut. Control Assoc. 23, 933-940. Larsen, R. J. (1977) An air quality data analysis system for Interrelating effects, standard and needed sources reduction: Part 4. A three-parameter averaging-tme model, J. Air Pollut. Control Assoc. 27, 455-459. Ludwing, F. L. (1970) Determination of mixing depths for use with synoptic model. Appendix. Proceedings of Symposium on Multiple-Source-Urban-Diffusion Models, U.S. Environmental Protection Agency, Research Triangle Park, NC. McMullen, R. V. (1975) The change of concentration standard derivations with distance, J. Air Pollut. Control Assoc. 25, 1057-1058. Ministerio de Industria y Energia (1978) National inventory of air pollutant sources. Ministerio de Industria y Energia, Madrid. Ministerio de Industria y Energia (1981) "Handbook for calculating the heights of industrial stacks. Ministerio de Industria y Energia, Madrid. Pasquill, F. (1961) The estimation of the dispersion of windborne material, Meteorol. Mag. 90, 33-49. Pasquill, F. (1976) The gaussian plume model with limited vertical mixing. PB-258-732, U.S. Environmental Protection Agency, Research Triangle Park, NC. Thomas, W. A., Babcock, L. R., and Shulds, W. D. (1971) Oak Ridge air quality index. ORNL-NSF-EP-8, Oak Ridge National Laboratory, Oak Ridge, TN. Turner, D. B. (1970) Workbook of atmospheric dispersion estimates. AP-26, U.S. Environmental Protection Agency, Research Triangle Park, NC. U.S. Environmental Protection Agency (1973) Compilation of air pollutant emission factors. U.S. Environmental Protection Agency, Washington, DC. U.S. Environmental Protection Agency (1977) User's manual for singler source (CRSTER) model. EPA 450/2-77-13, U.S. Environmental Protection Agency, Research Triangle, NC. U.S. Environmental Protection Agency (1978) The new pollutant standards index. U.S. Environmental Protection Agency, Washington, D.C.
0160-4120/84 $3.00 + .00 Copyright ~ 1985 Pergamon Press Ltd.
Printed in the USA. All rights reserved.
THE SPANISH PROJECT ON ENERGY AND ENVIRONMENT: ENMA J. Ortega-Costa, A. L6pez Garcia, M. Molina Martrn, M. L. Guillam6n Duch, G. Echag0e M~ndez-Vigoa General Secretariat of Energy and Resources, Ministry of Industry and Energy, Madrid, Spain (Received 10 July 1983; Accepted 10 June 1984) The project ENMA assesses the atmospheric pollution caused by the transformation and consumption of energy. The project is in the following stages: (a) estimation of annual overall average emissions; (b) estimation of annual average concentrations of pollutants; and (c) estimation of doses. Estimation of annual overall average emissions is estimated, separately, for urban areas and point sources. Concentrations of pollutants are obtained for urban areas and point-sources by means of two different gaussian models. Finally, doses are calculated assuming that the effects of all pollutants are linear at low doses. Doses for each pollutant, and doses for exposure to several combined pollutants, are defined. The doses on population are also defined, assuming that the significance of pollution depends on the number of people exposed.
INTRODUCTION
STRUCTURE OF THE ENMA PROJECT
Energy processes have a great influence on the environment due to the intensity with which consumption of natural resources is required by them. Generation, transformation, and consumption of energy cause a great amount of waste matter (solid, liquid, or gaseous) which, when set free, are the cause of environmental pollution. The degree and nature of the pollution depends on the technologies in use and the amount and quality of the energy resources. Consequently, when deciding among different energy options, environmental considerations play a fundamental role. Therefore, energy policies directed to the welfare of the community must take into consideration the possible harmful secondary effects resulting from the increase of energy consumption. From this point of view, the assessment of environmental impact is directly related to the tasks of energy planning, and is helpful when considering the factors that limit or optimize energy projects.
Acknowledging the importance of including environmental analysis in energy planning, the Spanish Ministry of Industry has been developping since 1980 a method to assess the impact of the energy on the environment. This study, known as project ENMA (Energia and Medio Ambiente) aims to develop a simple and flexible method of estimating the atmospheric pollution resulting from different theoretical working conditions of an energy system. The project is in three stages: (1) estimation of the annual overall average emissions; (2) estimation of the concentration of pollutants; and (3) calculation of the doses. Estimation of the Annual Overall Average Emissions Emissions due to the consuming sectors. In this part of the project a model is developed which estimates the emissions of the different pollutants caused by the final uses of energy, and branches them out geographically. This model is called EMIR (Emisiones Regionales). The measurements produced by the model are as follows: 1. Consumption of the different types of energy in each of the 50 Spanish provinces and separately in their capital cities. 2. Structure of the consumption of energy for all the provinces and their capital cities.
aCorrespondence should be addressed to: Mariano Molina Martfn, General Secretariat of Energy and Resources, Ministry of Industry and Energy, P. de la Castellana, 160, Madrid 16, Spain 431
432
J. Ortega-Costa et al.
3. Annual average emissions of pollutants (SO2, particulate matter, NO~, and CO) of each type of energy in each of the capital cities of the fifty provinces. The data given to the model are as follows: 1. Population in each province and in its capital city during the period 1970-1980. 2. Historical consumption of energy for each province during the period 1970-1980. 3. Forecast of the demand of energy for the whole country as estimated in the National Energy Plan. 4. Forecast of the Spanish Population estimated by the National Institute of Statistics. 5. Emission factor matrix for the four pollutants mentioned above and for the following types of energy: oil products (liquid petroleum gases, gasoline, gas-oil, fuel-oil, and kerosene); natural gas; and coal (hard coal, Lignite, and Briquettes). This matrix has been calculated using several studies carried out by the Ministry of Industry and Energy of Spain (1978) and other agencies (U.S. EPA, 1973). With these data, the model EMIR works two separate mechanisms (see Fig. 1). First, from the historical series the model calculates the historical structure of the consumption of energy. Using an inertial scenario, it fore-
CONSt~oTION BY TYPE OF ~rERGY
~OGHAPEY
I
I
'
BY ENERGY TYPES
I ~ONSOMI~ION "PER CAPITA~
I NATI )NAL
SC~ARIOS 0
~D TO P~0VI ~ C L ~ ~S~CONSt~3TION ~UR~ B
CONSUMPTION S~RUCTUR~ B
F~ERGY TTPE
~¢~GY CONSL~ION "PER CAPITA"
I NSUMI~ION "PER CAPITA'~ A/MkPTED TO NATIONAL GY PLAN FORECAST |
FOEECA~T OF POPULATION IN CAPITAL CITIES ~ERGY OONbq)7~TION IN CAPITAL CITIES I
CONSUMPTION BY TYPES I OF IRERGY IN CAPITAL CITIEs D ~GU~A~IO@
J
O "I ~IISSIONS
~MISSION FACTORS
Fig. 1. EMIR model
l
casts this structure for the years 1990, 1995, and 2000. Second, the analysis of the two series, total final consumption and population, gives the historical evolution of the final consumption "per capita" and a forecast of this variable, based on the historical trend, for the years 1990, 1995, and 2000. The integration of this variable to obtain the total national consumption is fitted automatically, to meet the forecast of the demand of energy of the National Energy Plan. With the structure of consumption and total consumption, urban consumptions are obtained for the years 1990, 1995, and 2000. Emissions are obtained by application of the emission factor matrix to these values. At this point, the model can easily simulate the emissions that would result when more strict environmental regulations are applied or when new technological systems with less environmental incidence are used. Table 1 shows the results obtained for four capital cities. Emissions due to the Transformation Sector. The National Energy Plan indicates the number of plants that will be necessary to meet the future energy requirements of the country. Plants are classified according to their technologies, the type of fuel they use, and the total amount of energy they produce. The plan also indicates the site of the plants. Measures for environmental control are fixed in each case, based on studies that have been performed before the plant can start operating. With the above information the emissions of sulphur oxides and particulate matter are calculated for the years 1990, 1995, and 2000.
Estimation o f the concentration o f pollutants The estimation of the ground concentrations is in two stages: concentration levels in capital cities due to the consumption of energy, and concentration levels in the vicinity of thermal power plants and refineries. Concentration Levels in Capital Cities Due to the Consumption of Energy. The concentration levels of SO2 and particulate matter have been calculated using an environmental indicator (Ludwig, 1970; Hanna, 1971; Gifford and Hanna, 1973; Pasquill, 1976; Calder, 1977; Echagiie, 1982). This indicator is obtained from the following parameters: 1. Annual average emissions of pollutants in urban areas. They have been obtained with the EMIR model. 2. A matrix of coefficients that depends on the wind run through the urban area and the distribution of the emitting sources throughout the city. 3. Extension and configuration of the city. 4. Height of the mixing level over the city. 5. Wind speed through the mixing level.
1
The indicator of atmospheric pollution obtained according to the above criteria has the following advantages: (1) It is easy to use, (2) experience shows that the parameters on which the indicators is based are the most
Energy and environment in Spain
433 Table 1. Results obtained by the EMIR model. Annual Emissions (103 metric tons)
Capital City
Madrid
Sevilla
Zaragoza
La Corufia
Year
SO2
PSB a
NOx
CO
1980 1990 1995 2000 1980 1990 1995 2000 1980 1990 1995 2000 1980 1990 1995 2000
37.5 34.6 33.8 33.6 9.5 11.9 13.1 14.4 15.5 21.2 24.5 28.1 4.5 5.4 5.6 6.0
14.5 7.7 5.2 5.1 1.3 1.6 1.7 1.9 4.7 4.9 5.2 5.4 1.3 1.4 1.5 1.6
39.7 43.1 44.8 46.4 9.5 11.5 12.5 13.6 15.1 21.0 24.4 28.1 5.4 6.6 7.0 7.3
250.1 297.8 318.3 336.4 38.4 50.6 56.6 62,7 44.9 64.6 75.8 88,2 14,7 19,7 21.2 22.6
a Particulate matter.
adequate in estimating the concentration of pollutants in urban areas; and (3) it takes into account the configuration of the city and the directions in which the wind sweeps the pollutants. Concentration Levels in the Vicinity o f Thermal Power Plants and Refineries. The Pasquill-Gifford model has been used to estimate the concentrations of SOs and particulate matter near the power plants. The rise of the plume has been estimated according to Briggs' formula (Pasquill, 1961; Turner, 1970; McMullen, 1975; U.S. EPA, 1977; Echagiie, 1979; MIE, 1981). A data base was developed containing the following information for each of the Spanish thermal power plants and refineries, as a previous requirement to the application of the model: 1. Annual average emission of SO2 and particulate matter for the period 1970-1980. 2. Characteristics of these emissions (volume, temperature, stack-height, and flue-gas speed). 3. Meteorological parameters of the plant sites. This information has been summarized in the corresponding climatological stability matrixes. 4. Topographical characteristics in a 50-km circle surrounding the plant. 5. Demographic data of the urban centers within the circle. The model provides data on the average concentration of SO2 and particulate matter for yearly periods, the distribution functions of the concentrations (i.e., the probability of surpassing a certain value), and the distribution of population according to pollutant exposure values.
Calculation o f the Doses Definition, Units and Equivalents. For an objective comparison of situations created by exposure to several airborne pollutants within a given social area, systematic criteria must be elaborated to assess simultaneous effects on the resident population. The concentration of pollutants is measured in the weight of pollutants in unit volume of air, e.g., /zg/(N)m3. Present regulations for the control of atmospheric environment limit concentrations on time basis. For short periods the limit is higher. These rules are to prevent high concentrations that would damage the health of the population. These considerations are not sufficient, because they overlook possible long-term effects, and they do not allow comparison of situations where there are several pollutants. Therefore, estimated doses must also be considered, since the possible effect of a given pollutant on the health of the population depends not only on the concentration in the air but also on the time of exposure. When dealing with low concentrations, the biological effects can be considered to be in proportion to the concentration and the time of exposure, in the same way as accepted for most toxic substances. Thus, D (c, 0 = Kct, Where D (c, 0 = dose; K = proportional coefficient; c = concentration of pollution; and t = time of exposure to concentration. This formula is a practical approach to the estimation of the problem; similar expressions are frequently used
J . O r t e g a - C o s t a et al.
434
in the absence of more rigorous biological data (Fulton County, 1971; Thomas et al., 1971; Babcock and Nagda, 1972; Larsen, 1973; Larsen, 1977). In these assumptions, pollution doses must be referred to a unit which has been called CONTI (Concentracion y tiempo). This unit stands for 100/~g/(N)m 3 of SO2 over a period of 1 yr. The definition of the dose in the case of other pollutants could be given in the same way; since the biological effects are different, however, the definition of a general unit is necessary for a comparison of the doses. This unit we shall call CONTI equivalent (Ceq) and it refers to the standard concentration of SO2. To achieve this equivalent, coefficients among the various pollutants must be established. In the supposition that the equivalent coefficient is known, the dose of pollutant i is the product of the annual concentration ci of that pollutant (expressed as #g/(N)m0 by the equivalent coefficient qr That is to say
where C,(t) = annual estimated standard of pollutant i during a period of time t, where t = 1 yr; C,o = standard concentration of pollutant i during the period of time to; and b = coefficient estimated on the established standards. Table 3 shows the values obtained by applying the above formula. Since the assumption of linear relationship between the doses and biological effects can only be considered for low concentrations, the equivalent factors will only refer to annual situations; application of daily and monthly values is more uncertain. Total Dose When several pollutants are present, the total dose in Ceq will be obtained as the sum total of the partial equivalent dose of each pollutant considered:
D~ = c~q. where D, is the equivalent dose of the pollutant i. The difficulty of this definition is in knowing and applying the equivalent coefficients. The lack of precise biological data has forced ENMA to take as the rule of equivalence the Spanish National air quality standards (see Table 2). It has been accepted that the annual national standards allowed by the Spanish regulations have the same significance in their effects on health. Since all the standards have not been defined for yearly periods, it has been estimated that daily and monthly standards can be annually extrapolated by the following formula, based on Larsen assumptions (Larsen, 1969; Larsen, 1977):
c,,,, _-
(+o)'
K D, = ~_. D,, 1
where D, = total dose; D, = equivalent dose of pollutant L and K = number of pollutants. Dose on the population The biological effects of the pollutants will be more important as the density of population exposed increases. For this reason it is convenient to define the overall dose on the population or demographic dose taking as unit the CONTI equivalent man (Cem). The demographic dose is calculated approximately as the product of the average overall annual dose by the number of inhabitants affected.
T a b l e 2. N a t i o n a l a i r q u a l i t y s t a n d a r d s . A l l d a t a i n / z g / ( N ) m 3. Exposure Time Pollutant
IA h r
2 hr
8 hr
SO2
--
700
--
Particulate matter
--
-
--
NOx
--
-
--
CO
--
--
15,000
Pb Hydrocarbons
50 280,000
C1
300
HC!
300
1 month
1 yr
400
255
150
300
202
130
200
--
100
--
--
--
--
--
--
1 4 0 , 0 0 0
--
--
--
1 day
10
--
--
5 0
--
--
--
--
5 0
--
--
20
--
I
10
-
-
40
I
--
10
-
--
-
F
60
-
I
HF
30
-
-
H2S
100
--
I
CS2
30
-
--
Energy and environment in Spain
435 Table 3. Reference concentrations. All data in #g/(N)m s. Concentrations
Pollutant
Constant b
Per day
Per month
Per year
SOs Particulates matter NOx CO Pb Hydrocarbons CI HCI F HF H2S CS2
0.166 0.141 0.166 0.157 0.580 0.179 0.462 0.462 0.283 0.283 0.236 0.283
400 300 200 12,624 5.28 140,000 50 50 20 10 40 10
256 202 114 7,400 0.739 76,200 10.4 10.4 7.6 3.8 17.9 3.8
150 130 100 4,999 0.197 48,800 3.2 3.2 3.7 1.8 9.9 1.8
CASE STUDY Table 4 summarizes an application of the ENMA project to La Corufia, the capital city of a Spanish province, located in the Northwest coast. Three thermal power plants are currently under operation in this province. Two of them (Puentes and Meirama) are coal-fired and produce 1950 MW of installed capacity. The other (Sab6n, 470 MW) is oil-fired. There is also a refinery with a capacity of 7 million of metric tonnes of crude per year. Distances to the town are, respectively, 46, 22, 10, and 9 km.
According to Table 4, estimated emissions of SOs increase in 1990 as Meirama starts to operate in 1981, and descend to a minimum in 2000 when Puentes is near to its cancellation. Concentrations of SOs originated by the plants decrease in 1990, because higher stacks are planned to be installed in the refinery. It is estimated that concentrations of SOs and particulate matter will rise in the consuming sector, where no change in the trends of final use of energy is expected. Finally, the dose on the population rises continuously, as population growth is not compensated by a similar decrease in the total dose.
Table 4. La Corufia: emission, concentrations and doses, a
Emission (10 s metric Tons) Energy sector b SO2 Particulate matter Energy consumption SO2 Particulate matter Total emissions SO2 Particulate matter Concentrations [#g/(b0m s] Energy sector SO2 Particulate matter Energy consumption SOs Particulate matter Total concentrations SO2 Particulate matter Doses (CONTI) SOs Particulate matter Total dose (Ceq) Dose on population (106 Cem)
1980
1990
2000
517.7 9.3
649.2 12.2
469.7 9.9
4.5 1.3
5.4 1.4
6.0 1.6
522.2 10.6
645.6 13.5
475.7 11.5
17.2 0.0
9.0 0.0
9.0 0.0
39.0 21.0
42.0 21.1
45.0 22.2
56.2 21.0
51.0 21.1
54.0 22.2
0.56 0.24 0.80 0.19
0.51 0.24 0.85 0.21
0.54 0.26 0.80 0.24
aThese estimations correspond to the capital city of La Corufia. bEmissions of the energy sector are originated by two coal-fired plants (1,400 and 550 MW), an oil-fired plant (470 MW), and a refinery (7,000,000 metric tons of crude treated per year).
436
SUMMARY AND CONCLUSIONS E N M A is a useful method to assess situations created by atmosphere pollutants originated by the energy sector. It can be used to simulate the impact of a certain energy policy as well as to estimate historical situations. The model can also be used to compare the environmental impact of several different energy options. Definition and application of the dose and the total doses concepts will result in a better understanding of the significance of the effects of air pollutants.
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J. Ortega-Costa et al. concentration averaging time and frequency, J. Air Pollut. Control. Assoc. 19, 24-30. Larsen, R. J. (1973) An air quality data analysis system for interrelating effects standards and needed source reduction, J. Air Pollut. Control Assoc. 23, 933-940. Larsen, R. J. (1977) An air quality data analysis system for Interrelating effects, standard and needed sources reduction: Part 4. A three-parameter averaging-tme model, J. Air Pollut. Control Assoc. 27, 455-459. Ludwing, F. L. (1970) Determination of mixing depths for use with synoptic model. Appendix. Proceedings of Symposium on Multiple-Source-Urban-Diffusion Models, U.S. Environmental Protection Agency, Research Triangle Park, NC. McMullen, R. V. (1975) The change of concentration standard derivations with distance, J. Air Pollut. Control Assoc. 25, 1057-1058. Ministerio de Industria y Energia (1978) National inventory of air pollutant sources. Ministerio de Industria y Energia, Madrid. Ministerio de Industria y Energia (1981) "Handbook for calculating the heights of industrial stacks. Ministerio de Industria y Energia, Madrid. Pasquill, F. (1961) The estimation of the dispersion of windborne material, Meteorol. Mag. 90, 33-49. Pasquill, F. (1976) The gaussian plume model with limited vertical mixing. PB-258-732, U.S. Environmental Protection Agency, Research Triangle Park, NC. Thomas, W. A., Babcock, L. R., and Shulds, W. D. (1971) Oak Ridge air quality index. ORNL-NSF-EP-8, Oak Ridge National Laboratory, Oak Ridge, TN. Turner, D. B. (1970) Workbook of atmospheric dispersion estimates. AP-26, U.S. Environmental Protection Agency, Research Triangle Park, NC. U.S. Environmental Protection Agency (1973) Compilation of air pollutant emission factors. U.S. Environmental Protection Agency, Washington, DC. U.S. Environmental Protection Agency (1977) User's manual for singler source (CRSTER) model. EPA 450/2-77-13, U.S. Environmental Protection Agency, Research Triangle, NC. U.S. Environmental Protection Agency (1978) The new pollutant standards index. U.S. Environmental Protection Agency, Washington, D.C.