ࡱ> q mbjbjt+t+ &AAi ]|||8,(,Y4;((((((($*,(|WUYWW(WP"|(W(?#ny' r|( 4Kp߿ ( EXTERNAL COSTS ASSOCIATED WITH THE CROATIAN POWER SYSTEM Maja Bozicevic, Zeljko Tomsic, Nenad Debrecin Faculty of Electrical Engineering and Computing, Zagreb, Croatia Abstract Because electricity production is one of the major sources of pollution, and at the same time the most centralised one, environmental issues in power system operation and planning are gaining an ever increasing attention. It is very difficult to compare various electricity generation technologies and fuel types because their environmental impacts are extremely divergent. The most widely accepted common denominator today is the so-called external cost by which a monetary value is associated with environmental damage. In this paper damages to human health resulting from Croatian thermal power plants operation are presented. Stack emissions have been translated into ambient concentrations by atmospheric dispersion modelling. Existing data on relations between human health degradation and ground concentrations of the analysed pollutants have been used. Data based on the ExternE project of the European Commission and adjusted to Croatian circumstances have been used to assign a monetary value to the estimated human health damage. External costs resulting from impact of Croatian thermal power plants airborne emissions on human health have been calculated. The total Croatian thermal power system external costs resulting from impacts on human health are given and discussed. Introduction Each electricity generation option aside from its beneficial consequences to society causes some unwanted side effects, the most important being environmental degradation. An objective and thorough comparison of various electricity generation options impacts is still a highly controversial issue, mostly because the caused environmental impacts are very divergent. Electricity production can influence a wide set of end points: soil acidification, noise, visibility, global climate, human health, visual amenity, etc. To be able to compare various electricity production technologies and their environmental impacts, a common denominator must be found. The most widely accepted common denominator today are external costs, i.e. monetary value of various impacts. External costs of electricity generation represent the monetary value of environmental damages it causes. These costs are imposed on society and the environment, and are not accounted for by the producers nor the consumers of electricity. External costs should reflect the price of the environmental damage caused by electricity generation and associated processes. The most important are damages to human health, built environment, crops, forests and ecosystems. The most thoroughly investigated are damages to human health. The power plants analysed in this paper are fossil fuel fired plants. The most significant environmental impact associated with fossil power plants is airborne pollution caused by fossil fuel combustion. The spatial and temporal ranges considered are dependent on the type of impact under assessment. Some impacts will only be experienced over a maximum of a few kilometres, e.g. noise, and some are truly global, e.g. greenhouse effect. Similar variations between impacts exist with respect to the timescales involved - some impacts are short lived, and some persist for thousands of years. In this analysis public health impacts resulting from annual operation of Croatian thermal power plants have been assessed. The most important pollutants stemming from fossil fuel combustion that are affecting human health are primary particulates and sulphate and nitrate aerosols, commonly denoted as particulate matter. Although impactst associated with emission of acidifying pollutants from power stations act over one thousand kilometres or even more, in this study only impacts arising on Croatian territory have been assessed. To be able to account for spatial characteristics of the observed area and of various pollutants' atmospheric dispersion, a Geographic Information System software has been used. A new map has been produced by overlaying a map containing information about ambient concentrations of the analysed pollutants and a map of Croatia, containing information on population density. These features have been combined into a single map and exported to an external relational database in order to gain flexibility and enhance the analysis. Croatian thermal power plants The analysis has been carried out for the eight Croatian thermal power plants. Their locations in Croatia are presented in Figure 1. Figure 1 Locations of Croatian thermal power plants Total emissions in 1998 and emissions per unit of electricity produced in the analysed power plants are given in Figure 2 [1]. The data are referring to the year 1998. Since then a couple of changes in the power system have occurred: TPP ELTO Zagreb has been equipped with two additional 25 MW blocks and another coal fired power plant with capacity of 210 MW (TPP Plomin II) has been built at the same location as TPP Plomin. These additions to the power system have not been included in the analysis because data is not available yet. Figure 2 Emissions originating from Croatian thermal power plants The highest SO2 emission originates from TPP Plomin, both total annual emission and emission per kWh produced. TPP Plomin used to be fuelled by coal with about 4% sulphur content with no flue gas desulphurisation technique applied. However, in the very near future TPP Plomin II will enter operation. Both power plants will be using a desulphurisation unit removing over 90% SO2 from flue gases and SO2 emission is expected to drop. The highest annual emission of NOX and particulates in 1998 originated from TPP Sisak. However, the highest emission of both NOX and particulates per kWh of electricity produced originates from TPP Plomin (Figure 2). Three of the observed power plants, namely TETO Zagreb, ELTO Zagreb and TETO Osijek are cogeneration plants. Emissions originating both from heat and electricity production are associated to electricity production. Therefore the specific emissions (emission per kWh produced) are quite low. Atmospheric dispersion modelling Sulphur dioxide, nitrogen oxides and particulates are formed in fossil fuel combustion process and emitted into the atmosphere directly from stack. Their dispersion is governed by chemical and physical atmospheric conditions. The most important are wind speed, pressure, mixing boundary height and stability class, which set conditions for atmospheric transport. At the same time, the majority of pollutants undergo some chemical transformations which are governed by temperature, insolation, humidity, background ambient concentrations and other atmospheric properties. Sulphur and nitrogen oxides participate in chemical processes in which sulphate and nitrate aerosols are formed. Dispersion has been modelled by the EcoSense program package developed for the European Commission's ExternE Project. The model used is the Harwell trajectory model which belongs to the Lagrangian group of models. Chemical reactions included in the model are presented in Figure 3. Figure 3 Chemical reactions included in the modelling In the EcoSense package data base, Europe has been presented by the EUROGRID co-ordinate system. The entire area is divided into gridcells. Each gridcell has an area of 10,000 km2 and all properties of a gricdcell are assumed to be constant in the entire gridcell. Output data of the modelling process are ambient concentrations of SO2, NOX, particulates, sulphate and nitrate aerosols. Twenty-three gridcells from the EUROGRID co-ordinate system contain the complete Croatian territory. Because of the models limitations, calculated ambient concentrations are constants throughout each gridcell. Input data about the analysed thermal power plants, necessary for atmospheric modelling, are presented in  REF _Ref477081400 \h  \* MERGEFORMAT Table 1. The meteorological data which are needed for dispersion modelling are included in the EcoSense program package data base. Ambient concentrations of the five observed pollutants originating from the described power plants have been calculated and joint impacts have been assessed. It has been assumed that concentrations originating from various power plants are additive. This assumption simplifies the actual relationships. Namely, secondary pollutants concentrations are dependent on the background pollution. In order to calculate pollution originating from a single power plant it would be necessary to establish background concentrations of the relevant pollutants. In this study it has been assumed that level of background pollution is not affected by operation of the analysed power plants. This assumption is acceptable because a single power plant does not contribute significantly to the background concentrations. Table  SEQ Table \* ARABIC 1 Input data for the dispersion modelling ([1], [2]) SisakPlominRijekaJertovecTETO ZagrebELTO ZagrebTETO OsijekPTE Osijekfueloil/gascoaloilgasoil/gasoil/gasoil/gasgasrated capacity, MW4201053208513596.54550net capacity, MW3969830383130904248full load hours per year4,6264,9294,2001,3613,1331,6112,8572,333SO2, mg/m31,4878,6442,43511,2209184181NOX, mg/m3402858670221403246150302particulates, mg/m312143516923767351stack height, m2003402507320020012060flue gas volume, m3/h1,769,340418,049828,180778,5781,283,0771,966,351519,640587,783latitude, 045.4845.1045.4046.0545.7745.7745.5545.55longitude, 016.3714.1514.4516.2016.0216.0218.7518.75 Based on the assumption that background levels are constant, the concentrations of five analysed pollutants originating from the Croatian power plants have been calculated by summing the concentrations from each plant. The ambient concentrations and distribution of the observed pollutants are presented in Figure 4. Figure 4 Ambient concentrations of the observed pollutants The locations of the thermal power plants are presented by the eight dots. The highest concentrations have been observed in the areas with the highest population density, which is highly unfavourable in terms of human health impacts and associated external costs. Because the secondary pollutants (sulphate and nitrate aerosols) are formed in the atmosphere in SO2 and NOX chemical transformation, their concentrations are distributed much more evenly than primary pollutants concentrations. This fact should be stressed out because aerosols significantly influence human health. Because ambient concentrations of the analysed pollutants decrease exponentially when a distance from emission source is increasing, a logarithmic scale has been used to present concentration ranges of the observed pollutants. Public health effects of the incremental air pollution Numerous epidemiological studies show a significant correlation between air pollution and human health disorders. Although some signs that high concentrations of sulphur and nitrogen oxides can influence human health exist, the evidence are not strong enough and those impacts have not been included in this study. On the other hand, impacts of particulates and aerosols, commonly denominated as particulate matter, have been sufficiently proved. A number of studies show that public health impacts differ according to size of particles. Namely, health is the most seriously affected by particulate matter with aerodynamic diameter smaller than 2,5 (m. This fraction of particulate matter is denoted as PM2,5, and consists of sulphate aerosols. Particulate matter with aerodynamic diameter smaller than 10 (m, denoted as PM10, can also harm human health. PM10 consists of nitrate aerosols and 55% of primary particles. Until now no correlation between particles larger than 10 (m and human health have been established. Nine various health endpoints have been assessed: acute mortality; hospital treatment of respiratory diseases; hospital treatment of cerebrovascular diseases; restricted activity day; chronic mortality; chronic cough in children; chronic bronchitis in children; chronic bronchitis in adults; congestive heart failure in elderly individuals. For each of the mentioned health endpoints the so-called exposure response functions have been established. An exposure response function presents a relationship between an incremental change in ambient concentrations of the observed pollutant and additional number of health disorder occurrences. The exposure response functions for the analysed health endpoints both for PM10 and PM2,5 are presented in  REF _Ref477086199 \h Table 2 [3]. It can be seen that PM2,5, e.g. sulphates, is more dangerous to public health than PM10, e.g. nitrates and primary particles. Table  SEQ Table \* ARABIC 2 Additional number of health incidents per (g/m3 PM10 and PM2,5 Number of health incidents per (g/m3PM10PM2,5respiratory diseases hospital admition (RDA)2,07 x 10-63,46 x 10-6congestive heart failure, elderly (CHF)1,85 x 10-53,09 x 10-5cerebrovascular diseases hospital admition (CVA)5,04 x 10-68,42 x 10-6chronic bronchitis, children1,61 x 10-32,69 x 10-3chronic cough, children2,07 x 10-33,46 x 10-3acute mortality*0,040 %0,068 %restricted activity day, adults (RAD)0,0250,042chronic bronchitis, adults4,9 x 10-57,8 x 10-5chronic mortality*0,39 %0,64 %* percentage change It should be noted that both acute and chronic mortality have been given as percentage change of background mortality whereas other impacts are given as additional number of occurrences per (g/m3 of particulate matter. To calculate additional health effects of an incremental PM concentration, number of people exposed should be given. To be able to combine data on population density and calculated ambient concentrations of PM, the Geographic Information Software (GIS) has been used. GIS is a tool which allows for manipulation with geographic information and connection to data bases containing relevant data (number of people exposed, ambient concentrations of PM). By overlaying a map containing the EUROGRID cells and a map of Croatia, a new map has been produced. The map of Croatia consists of twenty counties in which a constant population density has been assumed. The map containing gridcells consists of twenty-three gridcells; for each of them ambient concentrations of the observed pollutants have been calculated. The new map contains 111 polygons; in each of them ambient concentrations and population density are assumed to be constant. The three maps are presented in Figure 5. Figure 5 Maps used in the analysis Based on exposure response functions and incremental concentrations of PM associated with each of the analysed power plants, increase in observed health disorders can be calculated. Additional health disorders caused by an increase in atmospheric concentrations of particulate matter have been calculated according to the following equation: additional disorders = conc x density x area x exp_res conc incremental concentration of PM, (g/m3 density population density in the observed area, km-2 area area, km2 exp_resp number of incidents caused by PM increase of 1 (g/m3, ((g/m3)-1. Number of various health disorder incidents has been established for pollution originating from each of the analysed power plants, for each of the 111 polygons in which population density and PM concentrations are assumed to be constant. Total number of additional incidents have been established by adding the values for the 111 polygons. Increase in the health endpoints associated with each of the power plants is presented in  REF _Ref477086728 \h Table 3. Table  SEQ Table \* ARABIC 3 Increase in health disorders caused by incremental PM10 and PM2,5 concentrations SisakPlominRijekaJertovecTETO ZagrebELTO ZagrebTETO OsijekPTE Osijekacute mortality1,190,810,470,010,450,280,030,01chronic mortality11,287,674,460,104,282,660,320,12respiratory diseases0,540,370,220,000,210,130,020,01cerebrovascular diseases1,330,900,520,010,500,310,040,01congestive heart failure0,730,500,290,010,280,170,020,01chronic bronchitis, children10,336,994,090,103,912,430,290,11chronic bronchitis, adults71,9949,1128,480,6627,3216,952,030,73chronic cough, children92,5863,1636,630,8435,1421,802,610,93restricted activity day5420,253700,762144,8849,242057,531276,21152,5154,48 The power plants' shares in the total number of health incidents are the same for all impacts. The TPP Sisak has the largest share in the total impacts, about 36%, and the TPP Plomin is following with 25%. The TPP Rijeka is in the third place with 14%. The two power plants situated in Zagreb participate in the total number of health incidents with 14% (TETO Zagreb) and 9% (ELTO Zagreb). The three remaining power plants' shares are negligible: TPP Jertovec is a gas fired power plant and pollution caused by its operation is very low; the other two power plants are located in a less populated area, in Osijek, and the number of health disorders provoked by their operation is smaller because the number of people exposed is lower. The shares of the analysed power plants in the total number of health incidents assigned to incremental pollution caused by their operation are presented in Figure 6. Figure 6 Power plants' shares in public health impacts Monetary valuation of public health impacts A monetary value can be attached to each of the analysed health disorders. The values used in this study have been established in various studies carried out mainly in the USA [4]. Similar studies have not been undertaken in Croatia. Because Croatian economy is at a lower stage than the US economy, these values must be scaled down to reflect situation in Croatia rather than in the USA. The lower values of mortality and morbidity impacts occurring in less developed countries should be interpreted only as different amounts that individuals are willing and able to pay in order to avoid certain risks. It is important to stress out that this assumption does not present an assessment of relative worth of individuals in different countries. The axiomatic assumption that all people are of equal value has been adopted in this paper and in all similar studies. The values have been scaled down using a coefficient established by comparison of gross domestic product based on purchasing power parities [5]. This comparison was last undertaken in 1996, when GDP/PPP equalled 6,300 US$ in Croatia and 27,800 US$ in the USA. The costs attached to the analysed health disorders are presented in  REF _Ref477164171 \h Table 4. All values are given in 1995 US$. The exchange rate for Euro was 1,31 US$. Table  SEQ Table \* ARABIC 4 Monetary values attached to the analysed health disorders [4] Cost in the US, $Costs in Croatia, $acute mortality329737472chronic mortality31395271147respiratory diseases2344531cerebrovascular diseases2344531congestive heart failure2344531chronic bronchitis, children6715chronic bronchitis, adults312727087chronic cough, children6715restricted activity day235 The morbidity costs have been calculated by establishing the costs that individuals are willing to pay in order to avoid a certain risk, e.g. disease. The mortality costs are even more controversial. A measure of individual's willingness to pay (WTP) for reducing the risk of premature death is based on the value of statistical life. However, many people whose deaths were linked to air pollution were suspected of having only a short life expectancy. Based on this argument, valuation on the basis of life years lost has been conducted in this paper. The value of a life year lost depends on a number of factors, primarily how long it takes for the exposure to result in the illness and how long a survival period the individual has after contracting the disease. It has been assumed that acute mortality resulting from excessive air pollution shortens the average life expectancy by 9 months, and chronic mortality by 12 years. Based on these assumptions and the 3% discount rate, the costs associated with acute and chronic mortality given in  REF _Ref477164171 \h Table 4 have been established. For ease of implementation, the exposure - response functions are linearised and annualised, assuming an independence of background levels and not taking into account any thresholds. Namely, for the observed pollutants threshold exists at the individual level. However, there is no good evidence of a threshold at the population level because even low concentrations can have certain health impacts for the most vulnerable people. External costs of public health degradation caused by Croatian thermal power plants Each of the analysed healht impacts has a monetary value attached ( REF _Ref477164171 \h Table 4). Number of health impacts caused by Croatian thermal plants operation has been established for each of the 111 areas in the map created by overlaying the map of Croatian counties and the EUROGRID cells (Figure 5). The GIS program package and a relational database attached to the map have been used in the analysis. The relational database facilitates a number of queries, e.g.: What are the total costs associated with each of the analysed power plants? What are the costs of power plants' operation per unit of electricity produced? What are the total costs of public health incidents in each of the counties? How high are power plant's shares in external costs in a particular county, etc. The costs of public health impacts associated with Croatian power plants, both total and per unit of electricity produced, are presented in  REF _Ref477323159 \h Table 5 and Figure 7. All values are based on the costs scaled down to reflect economic situation in Croatia. Table  SEQ Table \* ARABIC 5 Costs of public health impacts associated with the thermal power plants Total costs in 1998, US$Costs per kWh produced, mills US$Sisak4,043,1862.21Plomin2,749,8685.69Rijeka1,599,4671.26TETO Zagreb1,533,0980.96ELTO Zagreb951,7120.72TETO Osijek113,8430.29PTE Osijek41,3780.25Jertovec37,3980.33TOTAL: 11,069,949AVERAGE: 1.46 To make the comparison easier, the values given in  REF _Ref477323159 \h Table 5 are presented graphically in Figure 7. Figure 7 Costs associated with power plants operation Because the TPP Sisak produces the largest part of electricity consumed in Croatia, its total costs in 1998 were the largest among Croatian thermal plants. It is interesting to note that the total cost associated with the TPP Plomin was at the second place, although the amount of the electricity produced in it was at the third place (after TPPs Sisak and Rijeka). Costs per unit of energy produced from TPP Plomin are the highest, almost three times higher than specific costs associated with TPP Sisak. Costs per kWh caused by TETO Zagreb, ELTO Zagreb and TETO Osijek are lower than costs caused by other plants fuelled by oil and natural gas because both heat and electric energy produced are given in kWh. Impacts of a power plant are higher in its vicinity because the atmospheric concentrations are the highest near their source. Impacts and associated costs are higher in areas with higher population density. For example, TPP Rijeka and TPP Sisak use oil with similar characteristics and emissions per kWh originating from the two power plants are practically the same (Figure 2). Nevertheless, the costs per kWh associated with TPP Sisak are higher because it is located closer to Zagreb, which is the most densely populated part of the country. The calculated costs which are the result of public health degradation in each of the Croatian counties and shares of the analysed power plants in total costs in the counties are presented in Figure 8. It can be seen that the highest costs occur in the County of Zagreb, which is the most densely populated part of Croatia. Figure 8 Calculated costs in Croatian counties Conclusion The most important impact of thermal power plants' normal operation is airborne pollution and the most important consequence of incremental airborne pollution is public health degradation. To compare various thermal power plants, differing by their installed capacity, electricity production, fuel used and geographic location, a common denominator must be accepted. The most widely used common denominator today is monetary valuation. For each of the investigated health end points an exposure-response function and a monetary cost have been given. In order to assess costs of public health incidents associated with Croatian power plants operation, exposure-response functions established by literature review have been used. The monetary values used have also been established by literature review and adjusted to the current stage of economic development in Croatia; the adjustment has been made by scaling down the costs attached to each of the observed health disorders according to the Croatian gross domestic product per capita using the power purchase parity. Although atmospheric transport of the majority of pollutants is transboundary, only the health effects in Croatia have been assessed in this study. The costs attached to public health degradation caused by Croatian thermal power plants operation have been assessed. The average calculated cost per unit of energy produced equals 1,46 mills US$/kWh. The highest costs are associated with the coal fired TPP Plomin: they equal 5,69 mills US$/kWh. In the near future another coal fired power plant at the same location will enter operation. Flue gases desulphurisation unit will be installed for both of the plants and the costs associated with TPP Plomin are expected to drop. The external costs caused by human health impacts of Croatian power plants are lower than the calculated values attached to the EU power plants [3] because the number of people exposed is lower and because the costs attached to the analysed health impacts are lower. However, there are possibilities for further reduction of total annual costs and costs per unit of energy produced relative to the 1998 levels. The costs of public health degradation could be reduced by improving power plants efficiencies, by locating pollution sources further from densely populated areas and by introducing the control technologies to reduce harmful emissions. References Croatian Utility and Environment, Croatian Utility, Croatia, 1999 Croatian Utility Annual Report, Croatian Utility, Croatia, 1999 ExternE National Implementation, Germany, IER, 1997 ExternE- Externalities of Energy: The Methodology, Vol. 2, European Commission, 1995 Croatian Statistical Report No 12, State Office for Statistics, Croatia, 1999  KiQR-N !!!! # ###$#4#5#<#=#&&&&&&&1''a(b(h(i(((((((*)+)))))),,,,..S1T1111122#2%2225 jmCJH*CJH*CJ5CJCJmH jCJUCJjU jUH*H*55CJN9g t :JKi#<=0 ,-N$$9g t :JKi#<=0 ,-N  L "#&1'2'8'?'F'O'['g's'~''''''''''''''''''''''''((( (((((.(4(:(@(F(L(R(X(^(_(j(p(v(|(~(((((((((W b  L "#&1'2'8'?'F'O'['g's'~''''''''' $$l 3 ; m8f"W$$W$''''''''''''''''((( (((((.(״(W$ $$l 3 ; m8f"W$$.(4(:(@(F(L(R(X(^(_(j(p(v(|(~(((((((((((װW$ $$l 3 ; m8f"W$$(((((((((((((((((((())) ))))).)8)@)H)P)Z)d)l)t)u)))))))))))))))))))))).+/+j+s,-...22 353e3~33333                       W L(((((((((((((((((())) )))׸׼$$W$ $$l 3 ; m8f"W$$))).)8)@)H)P)Z)d)l)t)u))))))))))))tW$$W$ $$l 3 ; m8f"$$))))))))))).+/+j+s,-...22 353e3~3 & F  $$l 3 ; m8f"W$$~333334[6666666667'737474W$$$$l yU" W$>$$$l4U"W$$W$$v & F 34[6666666667'73747\7h7t7u777777777 88%8&878?8G8H8n8t8z8{888888888889;===?E?q???@@ACBDBJBQBXBaBmByBBBBBBBBBBBBBBBBBBBBBCCCC W    ]555555555555552646a6b6w6x6y6z66666666666666666$7&70727e7g7q7s7777788"8$88888889999?*?+?4?5?;?CCCDC]CbCgClC $$l  f ]"$!$$C C%C*C/C4C9C>CCCDC]CbCgClCqCvC{CCCCCCCCCCCCCCCCCCCCD DDD*D0D6DPSUUUW(XxXXY*ZZZZZZZZZZZZZZ[ [[[[)[.[/[;[C[H[I[U[][b[c[n[u[z[{[[[[[[[[[[0\1\g\]._PabbbbW            X@OAO\ObOgOhOOOOOOOOOO>PSUUUW(XxXXY|x & F $$$$$Tl m gOhOOOOOSSSSSSSSUU>V?VUVVVWV]V^V_VYYYYYYYY0Z1ZFZGZHZIZZZZZZZZZZ[[[[.[/[;[H[I[U[b[c[n[z[{[[[[[[[[[[[\\\\jkU5B*CJhnH 5CJjUjqU5mHjU jUB*CJhnH CJKY*ZZZZZZZZZZZZZZ[ [[[X\\p$$l p# $9$ @$$$$l4 p#W$$W$[[)[.[/[;[C[H[I[U[][b[c[n[u[z[{[[[[[[[hh`XɈ$$$$l p# $9$ @$$W$[[[[0\1\g\]._Pabbbbbdfgi)l*l5lwlll & F $$l p#$$\bb*l5lUlwlllllm@mamm65bbdfgi)l*l5lwlll@mmmmmmmmmmmmmmmm             l@mmmmmmmmmmmmmmmm & F $. 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