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30220130403001

  1. 1. INTERNATIONAL JOURNAL OF PRODUCTION TECHNOLOGY AND International Journal of Production Technology and (IJPTM) (IJPTM), ISSN 0976 – 6383 MANAGEMENT Management (Print), ISSN 0976 – 6391 (Online) Volume 4, Issue 3, September - December (2013), © IAEME ISSN 0976- 6383 (Print) ISSN 0976 - 6391 (Online) Volume 4, Issue 3, September - December (2013), pp. 01-13 © IAEME: www.iaeme.com/ijptm.asp Journal Impact Factor (2013): 4.3285 (Calculated by GISI) www.jifactor.com IJPTM ©IAEME ENDPOINT DAMAGE OF COAL-FIRED POWER PLANT IN THAILAND Chantima Rewlay-ngoen1 and Sate Sampattagul2 1 Energy Engineering Program, Faculty of Engineering, Chiang Mai University, Chiang Mai 50200, Thailand 2 Department of Mechanical Engineering, Faculty of Engineering, Chiang Mai University, Chiang Mai 50200, Thailand ABSTRACT The aim of this research is therefore to adjust the life cycle impact assessment method so that it becomes suitable for Thailand, within the context of characterization, damage, and weighting factors. The results show that the coefficient of those factors. Additionally, this study was conducted to analyze the acidification damage factors—the damage arises from coal-fired power plant—using the coefficients of those factors. Finally, the results of this study will help us to minimize the damage costs from the coal-fired power plant in order that they become more environmentally friendly. Keywords: Characterization, Damage Assessment, Weighting, Contingent Valuation, CoalFired Power Plant 1. INTRODUCTION Thailand is set to achieve its electricity capacity plant during the period 2012–2030, which requires an annual increase in coal-fired power plant of up to 800 MW (EPPO, 2013). However, the increasing of the number of capacity coal-fired power plants should be based on clean energy and a reduction in environmental problems. Life Cycle Assessment (LCA) is a tool used in compiling and evaluating inputs, outputs, and potential environmental impacts of products and services throughout their life cycles [1]. LCA assists companies in identifying the production in terms of selecting input raw materials, production process, or management policy to achieve the least environment impact [2]. Among the undesired environmental impacts are emission of greenhouse gases of CO2, N2O, and CH4, which is the 1
  2. 2. International Journal of Production Technology and Management (IJPTM), ISSN 0976 – 6383 (Print), ISSN 0976 – 6391 (Online) Volume 4, Issue 3, September - December (2013), © IAEME cause of global warming and many health hazards, in addition to the damages caused to various social assets. In this work, we focus on the environmental assessment of coal-fired power plant because of their importance in providing clean energy for electricity capacity plants in Thailand. There are various methods of environmental assessment, of which there exists no common method that can be used to analyze the LCIA phase for Thailand. Instead, foreign methods are often employed for such a purpose. For example, Malakulet al. [3] and Sampattagulet al. [4] used different LCA methods for analyzing the life-cycle environmental impacts of biodiesel production from palm oil. When comparing its Global Warming Potential (GWP), Malakulet al. used CML baseline 2000, while Sampattagulet al. used EDIP2003. Accordingly, their results were vastly different. For example, Malakulet al. showed the GWP to be 1.42 kg CO2 eq./liter, while Sampattagulet al. showed that it is 22.45 kg CO2 eq./liter. This variation in results is in addition to the fact that both these methods might not be appropriate for Thailand. Taking this into account, this research aims to adjust an LCIA method by adapting the existing models so that it is suitable for Thailand. Currently, there are many environmental assessment methods, such as EDIP2003 (Environmental Design of Industrial Products 2003), IMPACT 2002+, LUCAS (an LCIA method used for a Canadian-specific context), and LIME (Life–cycle Impact assessment Method based on Endpoint modeling). It is only the LIME method that consists of the cause– effect chain of the environmental problems. Take, for example, the case of CO2 causing global warming and eventually a loss of biodiversity that is called the endpoint damage. LIME is the only method that consists of the cause and effect relationship of the environmental problems, which would be adjusted method for Thailand. The environmental problems caused by coal-fired power plant are mainly in power generation, and its operation discharges CO2, SO2, and NOX, which cause global warming and acidification [5]. Thus, this study aims to perform an environmental assessment on a coal-fired power plant regarding the issues of global warming and acidification based on the LIME method. 2. MATERIAL AND METHODS 2.1 Goal and scope of this study The goal of this LCA research is to identify the environmental emission from each process of coal-fired production, from cradle to grid of electricity production, and to compare the environmental impacts from the emissions released during the generation process. The main system boundary included from all the life-cycle phase-coal mining, coal transportation, and power plant operation is normalized to one kWh of electricity delivered from a power plant (Fig. 1). The data used secondary data from the Electricity Generating Authority of Thailand (EGAT). 2
  3. 3. International Journal of Production Technology and Management (IJPTM), ISSN 0976 – 6383 (Print), ISSN 0976 – 6391 (Online) Volume 4, Issue 3, September - December (2013), © IAEME Figure 1: The system boundary of a coal-fired power plant 2.1.2 Functional unit The functional unit for this research is one kWh net electricity generation from a coalfired power plant. 2.2 Life-cycle inventory Coal-fired power plant is the case study. Coal from Mae Moh mine is the major fuel resource. Diesel is a reserve fuel. Coal from the Mae Moh mine contains 2.88% sulfur, a percentage that is considerably higher than that in the other fossil fuel power plant as a result of the high volume of combustion. Nonetheless, the coal-fired power plant has installed highefficiency dust collectors and flue-gas desulfurization (FGD) systems (92–95% efficiency) so that the concentration of sulfur dioxide emitted from the power plant stacks is lower than the standard emission baseline for lignite power plants in Europe and the United States. This case study considers acidification from material acquisition (coal mining, chemical substances, and fuel production), transportation, electricity production, as well as FGD systems and ash management of the power plant. The inventory data of coal-fired power production from cradle to grid is presented in Table 1. 3
  4. 4. International Journal of Production Technology and Management (IJPTM), ISSN 0976 – 6383 (Print), ISSN 0976 – 6391 (Online) Volume 4, Issue 3, September - December (2013), © IAEME Table 1: Inventory Data of Coal-fired Power Production from Cradle to Grid (kgsubstance/kWh) Common name 1 2 12 Ammonia Carbon dioxide Ethane, 1,1,1,2-tetrafluoro-, HFC-134a Hydrogen chloride Methane, bromotrifluoro-, Halon 1301 Methane, chlorodifluoro-, HCFC-22 Methane, chlorotrifluoro-, CFC-13 Methane, dichlorodifluoro-, CFC-12 Methane, dichlorofluoro-, HCFC-21 Methane, trichlorofluoro-, CFC-11 Methane, trifluoro-, HFC23 Nitrogen dioxide 13 Nitrogen oxides 14 15 Sulfur dioxide Sulfur hexafluoride 3 4 5 6 7 8 9 10 11 NH3 CO2 Raw material extraction 2.05E-06 1.66E-02 C2H3F3 2.96E-13 0.00E+00 1.12E-14 3.07E-13 HCl 1.14E-07 2.23E-18 1.23E-09 1.16E-07 CBrF3 4.63E-11 9.20E-23 2.18E-12 4.85E-11 CHClF2 6.74E-11 0.00E+00 8.89E-13 6.83E-11 CClF3 1.71E-13 0.00E+00 0.00E+00 1.71E-13 CCl2F2 6.76E-13 0.00E+00 4.17E-15 6.80E-13 CHCl2F 6.45E-11 0.00E+00 8.11E-18 6.45E-11 CCl3F 1.26E-12 0.00E+00 1.32E-17 1.26E-12 CHF3 1.35E-13 0.00E+00 2.58E-15 1.38E-13 NO2 NOX as NO2 SO2 SF6 4.12E-08 6.84E-18 0.00E+00 4.12E-08 4.95E-05 2.60E-06 2.98E-03 3.03E-03 1.86E-05 2.84E-11 6.02E-08 0.00E+00 1.26E-03 1.86E-12 1.28E-03 3.03E-11 Chemical formula No. 7.20E-16 2.49E-04 Power plant operation 9.61E-10 1.10E+00 2.05E-06 1.12E+00 Transportation Total 2.2 Life-cycle impact assessment 2.2.1 LIME method concept The present endpoint impact assessment method mainly uses damage models to quantify environmental impact. Based on the endpoint damage concept in the LIME method [6], the method consisted of three steps: characterization, damage evaluation, and integration. Each step can be calculated as shown in equations (1)–(3) [7]: Characterization CI impact = ∑ ( CF impact ( X ) ⋅ Inv ( X ) ) (1) X Damage evaluation DI ( safe ) = ∑ ∑ DF impact ( safe, X ) ⋅ Inv ( X ) (2) impact X Integration SI = ∑ ∑ IF impact ( X ) ⋅ Inv ( X ) (3) impact X 4
  5. 5. International Journal of Production Technology and Management (IJPTM), ISSN 0976 – 6383 (Print), ISSN 0976 – 6391 (Online) Volume 4, Issue 3, September - December (2013), © IAEME where X stands for the environmental burden materials, impact is the impact domain, safe is the protection area, CI impact is the calculation result of characterization, DI ( safe ) is the calculation result of damage evaluation, SI is the calculation result of integration, CF impact is the characterization coefficient, DF impact ( safe, X ) is the damage coefficient, and IF impact ( X ) is the integration coefficient. In this research evaluated impact categories only two categories are global warming and acidification, which the adjustment data for Thailand. For integration index used primary data from random sampling in Thailand by using Contingent Valuation Method (CVM) technique. Figure 2: The principal framework of LIME [8] ODS = Ozone Depleting Substances; GHG = Greenhouse Gas; AP = Acidifying Pollutants. 2.2.2 Characterization and damage factor application for global warming The characterization factor of global warming was based on the IPCC third report [9]. As for the damage factor, LIME focused on human health and social assets as far as global warming damage is concerned, but regarding development damage, the focus was put on ongoing biodiversity [10, 11]. However, those factors have not been published yet. Thus, damage on human health can be calculated using the following equation, equation (4) [11]: DFs , g = ∑∑∑ ( ∆TEMP s ,t , g d where DFs , g r × ∆RRd , r × INCs , d ,r ,t × CAPs ,r ,t × HDs ,d ,r ,t ) (4) t is human health damage factor of GHG g in the SRES s scenario; ∆TEMPs ,t , g is additional increment of the Global Mean Temperature (GMT) in time t and s ∆RRd ,r scenario caused by the additional emission of 1 kg GHG g (°C/kg); is increment of relative risk of health burden d in region r against 1°C increment of GMT (%/°C); 5
  6. 6. International Journal of Production Technology and Management (IJPTM), ISSN 0976 – 6383 (Print), ISSN 0976 – 6391 (Online) Volume 4, Issue 3, September - December (2013), © IAEME INCs ,d , r ,t is baseline mortality rate of health burden d in region r, time t, and scenario s (%); CAPs ,r ,t is future population in region r, time t, and scenario s (person); HDs ,d ,r ,t is DALYs(0,0) for 1 death by health burden d in region r, time t, and scenario s (DALYs/person). This research only adjusted in terms of ∆TEMP by using data from [12], and for the social asset factor, the estimation was done by using the unit transfer with income adjustment, as shown in equation (5): BTH Y  = BJP ⋅  TH   YJP  β (5) where BTH is the adjusted policy–site benefit for Thailand, BJP is the original benefit based on Japan, YTH and Y JP are the domestic product at purchasing power parity per capita (GDP(PPP)percap), and β is the income elasticity of demand for the analyzed environmental good, which is assumed to be equal to one [13]. The original values based on Japanese rates, which are taken to be of soybean and rice as they are goods of agricultural production, were estimated at 240 yen/kg and 243 yen/kg, respectively. The GDP ( PPP ) percap of Thailand and Japan were 8,703 Baht and 34,298 Baht according to the values in the year 2012 (exchange rate = 38.70 Baht/100 Yen) [14]. The rates of soybean and rice, goods of agricultural production, were 60.90 Baht/kg and 61.66 Baht/kg, respectively. However, it is worth mentioning that Rewlay-ngoen et al. [15] developed global warming damage based on primary production, which is also included in this research. 2.2.3 Characterization factor and damage factor of acidification Both the characterization factor and the damage factor of acidification were studied by Rewlay-ngoenet al. [5]. Damage on both terrestrial and social assets is included in the model. 2.2.4 Integration Damage assessment has a limited number of safeguard areas compared with that of impact categories due to the fact that indexes can be aggregated into endpoints: human health, social assets, biodiversity, and primary production. In addition, damage assessment cannot provide a single index. Thus, this research provided weighting factors for comparing the importance of safeguard subjects by using the Contingent Valuation (CV) technique. Ciriacy-Wantrup [16] was the first to propose CV theory as a method for eliciting market valuation of a non-market good. Several researches applied the CV technique to an estimation of values, such as value based on travel costs and value based on environmental damage. The key output of a CV study is an estimate of the maximum Willingness-to-Pay (WTP) for the good of interest. The questionnaire put together while conducting CV can be classified into two types: open-ended and choice experiments [17]. Choice experiments have become a very popular elicitation format in recent years because it very closely chooses the attributes of the good of interest. The ultimate goal of the research is to determine an amount of WTP for 6
  7. 7. International Journal of Production Technology and Management (IJPTM), ISSN 0976 – 6383 (Print), ISSN 0976 – 6391 (Online) Volume 4, Issue 3, September - December (2013), © IAEME avoiding a unit quantity of damage for every safeguard area: human health, social assets, biodiversity, and primary production. 2.2.4.1 Design of field experiment The data were collected during August 2012–April 2013. The main study included two main groups: group 1 as the expert in economics, environment, science, and LCA, and group 2 in various backgrounds and categories. This study was a face–to–face survey conducted with the interviewee by using a single-bounded question, close-ended survey to put forward the questionnaires using the four starting bids of 100, 200, 500, and 1,000 Baht per year per individual and collecting the data over all the sub-regions in Thailand, which gave a total of 418 samples. 2.2.4.2 Econometric estimation of model The CV technique does the estimation using the conditional probit model, based on Random Utility Maximum (RUM). The following discussions are based on studies conducted in [17]–[18]. In terms of RUM, it is assumed to be utility for a particular alternative, and a utility function involving a definite term V and an unobservable component term e is given by U i j = Vi j + ε ij (6) where U i j is the utility of the j alternative to the i agent, Vi j is the utility function that can be written as f i ( X j ) where X j is a vector of the parameter for the j alternative. The probability of the respondent answer yes can be represented in terms of the WTP distribution by { } Pr ( Response is ' yes ' ) = Pr C ( q 0 , q1 , p, y; ε ) ≥ A ≡1 − GC ( A ) (7) where C ( q 0 , q1 , p, y; ε ) is a random variable, A is the bid, and GC is the cumulative distribution function. These parameters can be estimated by the BOX-COX model, as given by α + η  C = exp    β  (8) where η is the standard normal random variable, and α/β are estimated by the maximum likelihood method. The response probability formula for the RUM version of the BOX-COX model is given by α + η  Pr ( Response is ' yes ' ) =1 − Pr  ≤ A  β  (9) Bishop and Heberlein [19] introduced the utility of a yes response, which is close-ended, single-bounded, by which the following is obtained: Pr ( Response is ' yes ' ) = exp  − exp ( −α + β ln A )    if (-η) has the standard extreme value distribute. 7 (10)
  8. 8. International Journal of Production Technology and Management (IJPTM), ISSN 0976 – 6383 (Print), ISSN 0976 – 6391 (Online) Volume 4, Issue 3, September - December (2013), © IAEME Table 2 shows the econometrical estimate WTP of each safeguard area and the statistics of the response results obtained in the above in the manner based on the RUM theory. Table 2: Calculated Results of Contingent Valuation Analysis WTP Human health Social assets Biodiversity Primary production Note: Mean WTP1,e (Baht/unit1) 856.80 835.51 787.94 95% confidence Standard error z Pseudo R2 Log likelihood Lower Upper 89.04 89.92 81.25 9.62 9.29 9.70 0.1168 0.0878 0.0896 -234.15 -244.34 -247.34 682.28 659.28 628.70 1031.34 1011.74 684.83 86.10 9.40 0.0872 -246.88 640.31 947.19 809.06 1 Human health is unit DALY/person; Social asset is unit Baht/person; Biodiversity is unit EINES/person; Primary production is unit kg/person. The characterization, damage factor, and weighting coefficient of global warming and acidification are presented in Table 3 and Table 4. 2.4 Life cycle interpretation The data collected from the inventory analysis which are analyzed and classified into the two relevant impact categories of global warming and acidification can be interpreted for endpoint damage. The interpretation of results can provide an explanation of the impact generated from the different processes of power production at coal-fired power plant. Table 3: Characterization, Damage, and Weighting Coefficients of Global Warming No. 1 2 3 4 5 6 7 8 9 Common name Carbon dioxide Ethane, 1,1,1,2tetrafluoro-, HFC-134a Methane, bromotrifluoro-, Halon 1301 Methane, chlorodifluoro-, HCFC-22 Methane, chlorotrifluoro-, CFC13 Methane, dichlorodifluoro-, CFC-12 Methane, dichlorofluoro-, HCFC-21 Methane, trichlorofluoro-, CFC11 Sulfur hexafluoride Global warming characterizati on factor (kg CO2 eq.) Human health (DALY/kg) Social assets (Baht/kg) Primary production (kg/kg) Human health Social assets Primary production 1 5.50E-07 6.39E-12 4.98E-05 4.71E-04 5.34E-09 4.03E-02 C2H3F3 1430 8.60E-04 9.99E-09 7.79E-02 7.37E-01 8.35E-06 6.30E+01 CBrF3 7140 -3.66E-02 -4.25E-07 -3.31E+00 -3.14E+01 -3.55E-04 -2.68E+03 CHClF2 1810 8.80E-04 1.02E-08 7.97E-02 7.54E-01 8.54E-06 6.45E+01 CClF3 14420 8.68E-03 1.01E-07 7.86E-01 7.44E+00 8.42E-05 6.36E+02 CCl2F2 10890 1.39E-03 1.61E-08 1.25E-01 1.19E+00 1.34E-05 1.01E+02 CHCl2F 151 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00 CCl3F 4750 -6.86E-04 -7.97E-09 -6.21E-02 -5.88E-01 -6.66E-06 -5.03E+01 SF6 22810 1.27E-01 1.48E-06 1.15E+01 1.09E+02 1.24E-03 9.33E+03 Chemica l formula CO 2 Damage 8 Weighting (Baht/kg)
  9. 9. International Journal of Production Technology and Management (IJPTM), ISSN 0976 – 6383 (Print), ISSN 0976 – 6391 (Online) Volume 4, Issue 3, September - December (2013), © IAEME Table 4: Characterization, Damage, and Weighting Coefficients of Acidification Common name No. 1 Ammonia Hydrogen chloride Nitrogen dioxide Sulfur dioxide 2 3 4 Chemical formula Acidification characterization factor (kg SO2 eq.) Damage Weighting (Baht/kg) Social assets (Baht/kg) Primary production (kg/kg) Social assets Primary production NH3 2.63E-04 8.00E-02 9.73E-04 6.68E+01 7.87E-01 HCl 1.02E-04 3.00E-02 3.78E-04 2.51E+01 3.06E-01 NO2 5.40E-02 1.75E+01 2.00E-01 1.46E+04 1.62E+02 SO2 1 3.22E+02 3.71E+00 2.69E+05 3.00E+03 3. RESULTS AND DISCUSSION The environmental impact related to the life cycle of coal-fired power plant is the topic of discussion in the section below. 3.1 Characterization of coal-fired power plant 3.1.1 Global warming potential (GWP) The global warming potential (GWP) is contributed to mainly by CO2 emission with a small contribution from SF6, CBrF3, and CHClF2. There is significant potential for the same from power plants. The most significant process contributing to GWP is power plant operation which contributes about 98.49%. The next significant contribution is from coal mining (material extraction) (1.49%), followed by transportation (0.02%). However, the most significant air pollution is due to the emission of CO2 from coal-fired plants, which contributes to 98.49% of the total GWP. In the whole life cycle of a coal-fired power plant, it contributes GWP of about 1.12 kg CO2 eq./kWh. A comparison of the results of such a study was done by Spathet al. [20] who studied the coal-fired plants’ life cycle. The GWP considered for the literature study was about 1.04 kg CO2 eq./kWh (which only included CO2, CH4, and N2O), which is a value similar to the one in this study. The environmental impact of GWP resulting from the air-polluting emissions from coal-fired power plants during the production of 1 kWh of power is as presented in Table 5. Table 5: Global Warming Potential of Coal-fired Power Plant GWP (kg CO2 eq./kWh) No. 1 2 3 4 5 6 7 8 9 Substance CO2 C2H3F3 CBrF3 CHClF2 CClF3 CCl2F2 CHCl2F CCl3F SF6 Total Raw material extraction 1.66E-02 4.23E-10 3.31E-07 1.22E-07 2.47E-09 7.36E-09 9.74E-09 5.99E-09 6.48E-07 1.66E-02 Transportation 2.49E-04 0.00E+00 6.57E-19 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00 2.49E-04 9 Power plant operation 1.10E+00 1.60E-11 1.56E-08 1.61E-09 0.00E+00 4.54E-11 1.22E-15 6.27E-14 4.24E-08 1.10E+00
  10. 10. International Journal of Production Technology and Management (IJPTM), ISSN 0976 – 6383 (Print), ISSN 0976 – 6391 (Online) Volume 4, Issue 3, September - December (2013), © IAEME 3.1.2 Acidification potential (AP) The acidification potential (AP) is contributed by the SO2 and NO2 emissions. SO2 is the bigger contributor at about 99.89% of the total AP. The operation of the plant contributes to this greatly, followed by coal mining and transportation. The amount of coal-fired power plant acidification throughout the life cycle is estimated to be 3.84E-03 kg SO2 eq./kWh. The environmental impact of AP resulting from the air polluting emissions for the production of 1 kWh of coal-fired power plant is as presented in Table 6. Table 6: Acidification Potential of Coal-fired Power Plant AP (kg SO2 eq./kWh) No. Substance Raw material Power plant Transportation extraction operation 1 NH3 5.39E-10 1.89E-19 2.53E-13 2 HCl 1.16E-11 2.27E-22 1.25E-13 3 NO2 2.22E-09 3.69E-19 0.00E+00 4 SO2 1.86E-05 6.02E-08 1.26E-03 Total 1.86E-05 6.02E-08 1.26E-03 3.2 Damage assessment of coal-fired power plant As far as the damage assessment on Human Health (HH) is concerned, the major damage is caused by CO2 and SF6. A negative value substance means that it has a net cooling effect on the global temperature [15]. As for damage on Social Assets (SA) and Net Primary Production (NPP), the major damage is caused by SO2. The total damage on HH, SA, and NPP are 6.16E-07 DALY/kWh, 4.17E-1 Baht/kWh, and 4.80E-3 kgNPP/kWh. The data regarding the environmental damage on human health, social assets, and primary production of coal-fired power plant are presented in Table 7. Table 7: Damage Impact of Coal-fired Power Plant Life Cycle No. Substance 1 2 3 4 5 6 7 8 9 10 11 12 13 NH3 CO2 C2H3F3 HCl CBrF3 CHClF2 CClF3 CCl2F2 CHCl2F CCl3F NO2 SO2 SF6 Total Total 2.05E-06 1.12E+00 3.07E-13 1.16E-07 4.85E-11 6.83E-11 1.71E-13 6.80E-13 6.45E-11 1.26E-12 4.12E-08 1.28E-03 3.03E-11 Human health (DALY/kWh) 6.16E-07 2.64E-16 -1.77E-12 6.01E-14 1.48E-15 9.42E-16 0.00E+00 -8.64E-16 3.86E-12 6.16E-07 10 Social assets (Baht/kWh) 1.64E-07 7.16E-12 3.07E-21 3.48E-09 -2.06E-17 6.98E-19 1.72E-20 1.09E-20 0.00E+00 -1.00E-20 7.21E-07 4.12E-01 4.48E-17 4.12E-01 Primary production (kg/kWh) 1.99E-09 5.58E-05 2.39E-14 4.38E-11 -1.61E-10 5.44E-12 1.34E-13 8.53E-14 0.00E+00 -7.83E-14 8.24E-09 4.75E-03 3.49E-10 4.80E-03
  11. 11. International Journal of Production Technology and Management (IJPTM), ISSN 0976 – 6383 (Print), ISSN 0976 – 6391 (Online) Volume 4, Issue 3, September - December (2013), © IAEME 3.3 Integrated index of coal-fired power plant The integration involved the impacts of emitted GWP and AP, such as CO2 and SO2, and their impacts on health, social assets, and primary production. This integration coefficient was based on the primary factors for Thailand and was calculated by using the CV technique. In this study, the damage caused by the emission of SO2 is the major environmental influence area in terms of both the SA and the NPP at the operation plant. Reducing the emissions can improve the technologies and the capacity [21]; in addition, the use of the coal–bituminous [7] can reduce the SO2 environmental impact. The results of the endpoint damage of coalfired power plant are presented in Table 8. Table 8: Endpoint Damage of Coal-fired Power Plant (Baht/kWh) Raw material extraction No. Transportation Power plant operation Substance HH SA NPP HH SA NPP HH SA NPP 1 NH 3 - 1.37E-04 1.61E-06 - 4.81E-14 5.67E-16 - 6.42E-08 7.57E-10 2 CO 2 7.82E-06 8.86E-11 6.69E-04 1.17E-07 1.33E-12 1.00E-05 5.18E-04 0.00E+00 4.43E-02 2.18E-13 2.47E-18 1.87E-11 0.00E+00 0.00E+00 0.00E+00 7.14E-13 0.00E+00 7.06E-13 - 2.86E-06 3.49E-08 - 5.59E-17 6.82E-19 - 3.12E-08 3.12E-08 -6.84E-11 -7.74E-16 -5.84E-09 3 C2H 3F3 4 HCl 5 CBrF3 -1.45E-09 -1.64E-14 -1.24E-07 -2.88E-21 -3.27E-26 -2.47E-19 6 CHClF2 5.08E-11 5.75E-16 4.34E-09 0.00E+00 0.00E+00 0.00E+00 6.70E-13 7.59E-18 5.73E-11 7 CClF3 1.27E-12 1.44E-17 1.09E-10 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00 8 CCl2F2 8.02E-13 9.09E-18 6.86E-11 0.00E+00 0.00E+00 0.00E+00 4.95E-15 5.60E-20 4.23E-13 9 CHCl2F 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00 10 CCl3F -7.41E-13 -8.39E-18 -6.33E-11 0.00E+00 0.00E+00 0.00E+00 -7.76E-18 -8.79E-23 -6.63E-16 11 NO 2 - 6.02E-04 6.67E-06 - 1.00E-13 1.11E-15 - 0.00E+00 0.00E+00 12 SO2 - 1.33E+01 1.49E-01 - 6.98E-01 7.80E-03 - 8.01E+02 8.94E+00 13 SF6 3.10E-09 3.51E-14 2.65E-07 0.00E+00 0.00E+00 0.00E+00 1.75E-08 1.75E-08 1.75E-08 Total 7.83E-06 1.33E+01 1.49E-01 1.17E-07 6.98E-01 7.81E-03 5.18E-04 8.01E+02 8.99E+00 4. CONCLUSIONS AND RECOMMENDATIONS The aim of this study was to assess the environmental impacts of the whole life cycle of coal-fired power plant and to adjust the standard LCIA method by adapting the existing models so that it becomes suitable for Thailand. The results of this study help identify the major environmental impact aspects of power production from coal-fired power plant. It is clear that the impact potentials, damage, and integrated emission affect the unit of cost. In the future, the characterization and the damage coefficients should be improved to suit the situation of Thailand, and the uncertainty analyses for the major relevant parameters will provide helpful information on the reliability of the calculated damage. As for weighting, this study found that the environmental damage in Thailand had a positive WTP for environmental protection to decrease the loss of human health, social assets, biodiversity, and primary production. Although the respondents were willing to pay for environmental protection, they did not seem to be aware of the major problems. Thus, it is more important that the Thai people are made to become aware and conscious about the significance of 11
  12. 12. International Journal of Production Technology and Management (IJPTM), ISSN 0976 – 6383 (Print), ISSN 0976 – 6391 (Online) Volume 4, Issue 3, September - December (2013), © IAEME environment protection than just creating funds for environmental protection. Thus, the study could not directly certify that the respondents are WTP for the protection of the environment in order to reduce the loss of human health, social assets, biodiversity, and primary production. Finally, the results will also be useful for further research on developing impact assessment models based on the Thai circumstances. 5. ACKNOWLEDGMENT The authors would like to thank Prof. Dr. NorihiroItsubo for suggestion and advice on the Life-cycle Impact assessment based on Endpoint modeling (LIME) method. Our appreciation also goes to the Electricity Generating Authority of Thailand for providing the data and information on power plant. Finally, the authors would like to express their profound gratitude to the National Science and Technology Development Agency (NSTDA) and the Graduate School, Chiang Mai University, for the financial support. 7. REFERENCES [1] ISO 14040, Environmental management: Life Cycle Assessment–Principles and framework, International Organisation for Standardization, 1997. [2] M. Pehnt, Dynamic life cycle assessment (LCA) of renewable energy technologies, Renewable energy, 31, 2006, 55-71. [3] P. Malakul, S. Papong,T. Chom-in, and S. Noksa-nga, Life-cycle energy and environmental analysis of biofuels production in Thailand, Kasetsart Engineering Journal 75(24), 2010, 25–40. [4] S. Sampattagul, P. Nutongkaew, and T. Kiatsiriroat, Life cycle assessment of palm oil biodiesel production in Thailand, International Journal of Renewable Energy 6(1), 2011, 1–13. [5] C. Rewlay-ngoen, S. Papong, and S. Sampattagul, The NPP and social asset impacts of acidification from coal-fired power plant in Thailand, 2013 Alternative Energy in Developing Countries and Emerging Economies, 30-31 May 2013, Pullman Bangkok King Power, Bangkok, Thailand, 2013. [6] N. Itsubo, and A. Inaba, A new LCIA method: LIME has been completed, Int. J. LCA. 8(5), 2003, 305. [7] H. Feng, H.A. Gabbar, S. Tanaka, H.E. Sayed, K. Suzuki, and W. Gruver, Integrated life cycle assessment and environmental analysis: application to power plant, AsiaPacific Journal of Chemical Engineering, 2, 2007, 213-224. [8] A.S.G. Andrae, Chapter3: Environmental Life Cycle Assessment from a LIME Perspective,In:Global Life Cycle Impact Assessments of Material Shifts Global Life Cycle Impact Assessments of Material Shifts, London: Springer, 2010, 23–58. [9] Intergovernmental Panel on Climate Change (IPCC), Good Practice Guidance and Uncertainty Management in National Greenhouse Gas Inventories, Intergovernmental Panel on Climate Change, National Greenhouse Gas Inventories Programme Montreal: IPCC–XVI, 2000. [10] N. Itsubo, M. Sakagami, T. Washida, K. Kokubu, and A. Inaba, Weighting across safeguard subjects for LCIA through the application of conjoint analysis, Int. J. Life Cycle Assess 9 (3), 2004, 196–205. 12
  13. 13. International Journal of Production Technology and Management (IJPTM), ISSN 0976 – 6383 (Print), ISSN 0976 – 6391 (Online) Volume 4, Issue 3, September - December (2013), © IAEME [11] R. II., L. Tang, K., Tokimatsu, M. Nishio, and N. Itsubo, Damage assessment of global warming in LIME3, EcoBalance 2012: International conference on EcoBalance-Since 1994, Yokohama, Japan, 2012. [12] A.M. de Schryver, K.W. Brakkee, M.J. Goedkoop, and M.A.J. Huijbregts, Characterization factors for global warming in life cycle assessment based on damages to humans and ecosystems,Environmental Science & Technology 43 (6), 2009, 1689–1695. [13] European Communities, ExternE: Externalities of Energy Methodology 2005 Update, Edited by Bickel, P., and Friedrich, R. Available online: http://europa.eu.int, 2005. [14] Bank of Thailand, Historical foreign exchange rates: 1 January 2012 to 31 December 2012, Available online: http://www.bot.or.th,2013. [15] C. Rewlay-ngoen, S. Papong, P. Piumsomboon, P. Malakul, and S. Sampattagul, Life cycle impact modeling of global warming on net primary production: A case study of biodiesel in Thailand, Environment and Natural Resources J. 11 (1), 2013, 30-22. [16] S.V. Ciriacy-Wantrup, Capital returns from soil-conservation practices, Journal Farm Economics, 29, 1947, 1181-1196. [17] R.T. Carson, and W.M. Hanemann, Chapter 17: Contingent Valuation, Handbook of Environmental Economics, 2, Edited by K.G. Mäler and J.R. Vincent, 2005, 821-936. [18] A. Lopea-Feldman, Introduction to contingent valuation using stata, Munich Personal RePEc Archive (MPRA), available online: http://mpra.ub.uni-muenchen.de/41018., 2012. [19] R.C. Bishop, and T.A. Heberlein, Measuring values of extra market goods, American Journal of Agricultural Economics 61, 1979, 926-930. [20] P.L. Spath, M.K. Mann, and D.R. Kerr, Life Cycle Assessment of Coal-fired Power Production, Including contributions on process definition and data acquisition from J. Marano and M. Ramerzan, Federal Energy Technology Center, National Renewable Energy Laboratory (NREL), Prepared under Task No. BP911030, 1999. [21] M. Rozpondek, and M. Siudel, Pollution control technologies applied to coal-fired power plant operation. ActaMontanisticaSlovaca 14 (2), 2009, 156–160. [22] Wani Ahmad, MSK Prasad, Bhat Javed and V Thangapandian, “Coal Accident Analysis, Risk Quantification and Suggestive Scheme Improvements in Coal Bunkers of Abstract Thermal Power Plants”, International Journal of Industrial Engineering Research and Development (IJIERD), Volume 3, Issue 2, 2012, pp. 18 - 25, ISSN Online: 0976 - 6979, ISSN Print: 0976 – 6987. 13

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