MULTIPLE POINT SOURCE DISPERSION ANALYSIS OF CO, NO 2, PM 10 AND SO 2 FROM PAITON POWER PLANT USING CALPUFF

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1 International Journal of Civil Engineering and Technology (IJCIET) Volume 9, Issue 1, January 2018, pp , Article ID: IJCIET_09_01_081 Available online at ISSN Print: and ISSN Online: IAEME Publication Scopus Indexed MULTIPLE POINT SOURCE DISPERSION ANALYSIS OF CO, NO 2, PM 10 AND SO 2 FROM PAITON POWER PLANT USING CALPUFF Arie Dipareza Syafei, Reska Putri Tansida Anung Wuri Department of Environmental Engineering, Faculty of Civil, Environmental and Geo Engineering, Institut Teknologi Sepuluh Nopember, Surabaya, Indonesia ABSTRACT The flue gas from burning coal consists of SO 2, NO 2, CO, and particulate matter (PM 10 ). When this flue gas leaves the stack it is dispersed vertically and horizontally. This dispersion can cause air pollution inside or outside of the power plant area. This research investigated the dispersion of CO, NO 2, PM 10, and SO 2 emitted from the Paiton power plant complex in Indonesia. Some scenarios involved individual CO, NO 2, PM 10, and SO 2 emission rates in minimum, average, and maximum conditions. The dispersion was in each case was modeled using a CALPUFF model. The results show that the dispersion of the air pollutants are still considered safe and will not harm humans, animals, or plants even when the power plant emits its maximum emission load. Key words: Air dispersion, Multiple Point Source, Coal Power Plant, and CALPUFF. Cite this Article: Arie Dipareza Syafei, Reska Putri Tansida Anung Wuri, Multiple Point Source Dispersion Analysis of CO, NO 2, PM 10 and SO 2 from Paiton Power Plant Using CALPUFF. International Journal of Civil Engineering and Technology, 9(1), 2018, pp INTRODUCTION A coal power plant is a power plant that utilizes fossil fuels like coal and oil to produce high pressure steam. The steam drives turbines at high speed to produce electricity (World Coal Institute, 2009) [6]. The Paiton power plant complex in Indonesia contains eight plants. The amount of electricity that is channeled from Paiton to an interconnected system in Java, Maduram, and Bali averages GWh annually (PT PJB, 2018) [2]. Paiton is one of two coal-fired power plants in Indonesia whose primary fuel is coal, and it requires approximately million tons of coal per year to operate. The use of coal and oil as fuel for a power plant can produce emissions of CO, CO 2, NO 2, and SO 2 gas, all of which cause air pollution (Finahari, 2007) [1]. When it comes out of the stack, the flue gas is dispersed. Dispersion is the process of spreading the gasses from the source to a specific region (Vesilind, 1994) [5]. The CALPUFF model is a multi-layer, non editor@iaeme.com

2 Arie Dipareza Syafei, Reska Putri Tansida Anung Wuri steady-state puff dispersion model designed to model the dispersion of particles and gases using space and time varying meteorology (Scire et all, 2000) [3]. In this paper, we calculated the CO, NO 2, SO 2, and particulate matter (PM 10 ) emissions from the Pembangkit Listrik Tenaga Uap Steam Powered Generator Plant (PLTU) Paiton complex, which included point and area sources and used CALPUFF models to predict the concentration distribution of the pollutants. Furthermore, the resulting data were compared to national standard concentrations for CO, NO 2, SO 2 and PM 10. It is hoped that the results of this study will help to improve the air quality in the study area Model Description CALPUFF is a non-steady-state, multi-layer Langrangian puff model used for estimating deposition or concentration patterns for multiple air pollutants by considering the effect of space-time varying meteorological conditions. This model assumes that the emission of a stack can be subdivided into a series of pollutant puffs that have a Gaussian concentration profile in all directions. Each puff follows wind speed and direction independently of the other puffs. Puff models are more accurate than plume models. Puff models perform well for distances of up to at least 50 km and are routinely used for distances up to 200 km. The CALPUFF modeling system includes three main components, which are CALMET, CALPUFF, and CALPOST. CALMET is a meteorological model which includes a diagnostic wind field generator containing objective analysis and parameterized treatments of slope flows, kinematics terrain effects, terrain blocking effects, a divergence minimization procedure, and a micro-meteorological model for overland and overwater boundary layers. CALPUFF simulates dispersion and transformation processes and contains modules for complex terrain effects, overwater transport, coastal interaction effects, building downwash, wet and dry removal, and simple chemical transformations. CALPOST is a post-processing program with an option for computing time-averaged concentrations and deposition fluxes predicted by the CALPUFF model, which are used to summarize the results of the simulation (Scire et all, 2000) [3] Emission Source Data The emission source used in this modeling consists of the emissions from six stacks of an eight-unit, electricity-generating boiler using coal and oil as its fuel. Emission load data from boiler activity was obtained from CEMS (Continuous Emission System). A CEMS is the only equipment necessary for determining a gas or particulate matter concentration or emission rate. It does so by using pollutant analyzer measurements and a conversion equation, graph, or computer program to produce results in the units of the applicable emission limitation or standard (US EPA, 2016) [4] Geophysical and Meteorological Data of the Study Area This study take place at the Paiton power plant complex located approximately 35 km to the east of Surabaya City, the capital of East Java ( S, E), about halfway between Probolinggo and Situbondo. This coal power plant complex consists of eight units with a combined electrical capacity of MW, which supplies the electricity for all of Java and Bali. The eight units are operated by four different companies, so they have different types of exhaust gas controlling procedures. Figure 1 shows the location for each power plant stack in the Paiton complex editor@iaeme.com

3 Multiple Point Source Dispersion Analysis of CO, NO 2, PM 10 and SO 2 from Paiton Power Plant Using CALPUFF Figure 1 Stack Locations at the Paiton Power Plant Complex Other data required for modeling are geophysical, which includes land use and terrain elevation data, and meteorological, which consists of surface and upper air data. Data from the terrain data processor SRTM3 (global coverage ~90 m) and land coverage data from the Global Land Cover Characterization (GLCC) with global coverage ~1 km are also used. All these data were obtained from the National Aeronautics and Space Administration (NASA) website. The domain grid used for modeling goes out 40 km in every direction from a centered reference point at ( S, E). This grid covers parts of Probolinggo, Lumajang, Bondowoso, and Situbondo. Figure 2 shows the area modelled. Figure 2 Modeling Domain editor@iaeme.com

4 Arie Dipareza Syafei, Reska Putri Tansida Anung Wuri Figure 3 Wind Rose from Juanda Station May 2015 Figure 4 Wind Rose from Ngurah Rai Station May editor@iaeme.com

5 Multiple Point Source Dispersion Analysis of CO, NO 2, PM 10 and SO 2 from Paiton Power Plant Using CALPUFF For meteorological data, surface data was collected from the two closest surface s at Juanda and Ngurah Rai. The Juanda surface is located at Surabaya City on S, E, and Ngurah Rai is located at Badung Regency on ,99 S, ,72 E. Upper air data was obtained only from Juanda. The Paiton power plant, itself, is located mid-way between the two surface s. Surface data consists of wind speed, wind direction, temperature, humidity, and air pressure and was obtained from a fixed point, usually at 10 m of height. This data can be obtained online from the National Oceanic and Atmospheric Administration (NOAA) data center website. The upper air data was obtained from the Juanda Station, only. Figures 1 and 2 show wind rose data from the Juanda and Ngurah Rai monitoring s, respectively, during May The figures show that the wind blew mostly from east to west at both monitoring s. At the Juanda, 18% of the wind blowing to the east had a speed of m/s, and 20% had a speed of m/s. At the Ngurah Rai, 10% of the wind blowing to the east had a speed of m/s, and 15% of had a speed of m/s. These two data sets will be used to generate a diagnostic meteorological field around the modeled area using the CALMET pre-processor. 2. RESULTS AND DISCUSSION In this dispersion analysis, three scenarios are created for each pollutant via emission load variation. These scenarios are created to discover how varied emission loads affect the pollutant s dispersion. Note the all of these scenarios use the same stack characteristics. Scenario 1 used a maximum value for emission load, Scenario 2 used an average value, and Scenario 3 used a minimum value. The maximum emission load of each pollutant did not exceed the emission threshold based on Regulation of Ministry of Environment No. 21 Year Tables 1, 2, and 3 show emission load for each scenario for each emission source. Table 1 Maximum Emission Load May 2015 Emission Source CO (g/s) NO 2 (g/s) PM10 (g/s) SO 2 (g/s) Unit Unit Unit Unit 5& Unit 7& Unit Table 2 Average Emission Load May 2015 Emission Source CO (g/s) NO 2 (g/s) PM10 (g/s) SO 2 (g/s) Unit Unit Unit Unit 5& Unit 7& Unit Table 3 Minimum Emission Load May 2015 Emission Source CO (g/s) NO 2 (g/s) PM10 (g/s) SO 2 (g/s) Unit Unit Unit Unit 5& Unit 7& editor@iaeme.com

6 Arie Dipareza Syafei, Reska Putri Tansida Anung Wuri Emission Source CO (g/s) NO 2 (g/s) PM10 (g/s) SO 2 (g/s) Unit Figure 5 Emission Dispersion Pattern of CO from Scenario 1 Figure 6 Emission Dispersion Pattern of NO 2 from Scenario 1 Figure 7 Emission Dispersion Pattern of PM 10 from Scenario 1 Figure 8 Emission Dispersion Pattern of SO 2 from Scenario 1 Figure 9 Emission Dispersion Pattern of CO from Scenario 2 Figure 10 Emission Dispersion Pattern of NO 2 from Scenario 2 Figure 11 Emission Dispersion Pattern of PM 10 from Scenario 2 Figure 12 Emission Dispersion Pattern of SO 2 from Scenario editor@iaeme.com

7 Multiple Point Source Dispersion Analysis of CO, NO 2, PM 10 and SO 2 from Paiton Power Plant Using CALPUFF Figure 13 Emission Dispersion Pattern of CO from Scenario 3 Figure 14 Emission Dispersion Pattern of NO 2 from Scenario 3 Figure 15 Emission Dispersion Pattern of PM 10 from Scenario 3 Figure 16 Emission Dispersion Pattern of SO 2 from Scenario 3 Scenario 1 covers dispersion when the power plant emits an maximum emission load. The maximum concentration for CO is 79.7 µg/m 3, for NO 2, it is 38.9 µg/m 3, PM 10 has 2.21 µg/m 3, and SO 2 is at 183 µg/m 3. With that maximum emission load, the maximum concentration in the modeled area still did not exceed the threshold for ambient air based on Government Regulation No. 41 Year 1999 about Control of Air Pollution. This means that the dispersion will not harm humans, animals, or plants, nor will it disrupt the aesthetics of the environment. Dispersion when the power plant emits an average emission load is covered in Scenario 2. In this scenario, the maximum concentrations are lower, i.e., they are 23.3 µg/m 3 for CO, 28.2 µg/m 3 for NO 2, 1.97 µg/m 3 for PM 10, and 125 µg/m 3 for SO 2. When average conditions occur, the concentration of pollutants in the ambient air around power plant is safe because no thresholds have been exceeded for any of the parameters modeled. Scenario 3 shows how emissions affect the environment around the Paiton power plant when it emits a minimum amount. With this minimum emission, there is no place with maximum concentration that exceeds the threshold for ambient air quality. The maximum concentration for CO is 1.35 µg/m 3, NO µg/m 3, PM µg/m 3, and SO µg/m 3. This mean that the effect of the minimum emission dispersion is safe and not harmful for humans, animals, or plants. The dispersion patterns are similar, but have differences as well. The differences occur due to emission load variation. This emission load variation creates different pollutant concentrations in each scenario, but with a similar pattern. The pollutants disperse mostly to the west side of the complex. Wind conditions create an important rule for air dispersion since the pollutants follow the wind direction and are affected by the wind speed. Mostly, the wind editor@iaeme.com

8 Arie Dipareza Syafei, Reska Putri Tansida Anung Wuri blows from east to west, as seen previously. Pollutant concentrations slowly increase with distance until the peak is reached, and then the concentrations slowly decrease. Simulation results show that maximum concentrations for all scenarios occur at the same point, ( m, m) or S, E, with a ground elevation of 14 m above sea level. This is located 4.3 km away from the complex on the south-west side. It is a coastal area near the sea, and there are no residential areas on that site. Next, a validation model was created to examine how the results of CALPUFF compare to the actual conditions in the ambient air. Data for actual conditions from three monitoring points located on the west side of the power plant are obtained. The three monitoring points are Ash Disposal ( m, m), ( m, m), and Guest House ( m, m). The validation models are created by plugging actual emission rates into the models that were developed, then the results of that model are compared to ambient air monitoring results at those three sites. Tables 4, 5, 6, and 7 show the comparison of real air quality and air quality modeled by CALPUFF. Point Table 4 CO Concentration Comparison of and Model Result Date Time CO Concentration from Ash Disposal 28 Mei Ash Disposal 28 Mei Ash Disposal 28 Mei Mei Mei Mei Guest House 28 Mei Guest House 28 Mei Guest House 28 Mei Point CO Concentration from CALPUFF Table 5 NO 2 Concentration Comparison of and Model Result Date Time NO 2 Concentration from Ash Disposal 28 Mei Ash Disposal 28 Mei Ash Disposal 28 Mei Mei Mei Mei Guest House 28 Mei Guest House 28 Mei Guest House 28 Mei NO 2 Concentration from CALPUFF editor@iaeme.com

9 Multiple Point Source Dispersion Analysis of CO, NO 2, PM 10 and SO 2 from Paiton Power Plant Using CALPUFF Point Table 6 SO 2 Concentration Comparison of and Model Result Date Time SO 2 Concentration from Ash Disposal 28 Mei <0.5 Ash Disposal 28 Mei Ash Disposal 28 Mei < Mei < Mei < Mei <0.5 Guest House 28 Mei Guest House 28 Mei <0.5 Guest House 28 Mei <0.5 Point SO 2 Concentration from CALPUFF Table 7 PM 10 Concentration Comparison of and Model Result Date Time PM 10 Concentration from Ash Disposal 28 Mei Ash Disposal 28 Mei Ash Disposal 28 Mei Mei Mei Mei Guest House 28 Mei Guest House 28 Mei Guest House 28 Mei Table 8 Maximum Concentration of Each Scenario PM 10 Concentration from CALPUFF Gas Maximum Concentration Threshold of Scenario 1 Scenario 2 Scenario 3 ambient CO ,000 NO PM SO CONCLUSIONS Air emission from the power plant stacks dispersed to the west side, following the dominant wind direction. The patterns of dispersion for all scenarios are similar because there are no differences in the meteorological data applied to those scenarios. The emission concentrations in ambient air slowly increase until reaching a peak concentration, then decrease as they travel further. Scenario 1 is the worst scenario of all, since the concentrations are highest. The maximum concentration for each scenario is shown in Table 8. This research shows that even with the maximum emission load, the maximum concentrations of all pollutants dispersed still do not exceed thresholds for ambient air based on PP No. 41 Year This means that the editor@iaeme.com

10 Arie Dipareza Syafei, Reska Putri Tansida Anung Wuri activity at the power plant complex will not harm people, plants, or animals, nor will it disrupt the aesthetic around its location. However, air pollution monitoring and control still must be done because the emissions on that site stem not only from power plant boiler activity, but also from other sources, such as transportation and other residential activities. Emission load also can increase during plant expansion or when another power generator is added. REFERENCES [1] Finahari, I. N. dkk. Gas CO 2 dan Radioaktif dari PLTU Batubara. Jurnal Pengembangan Energi Nuklir, 9(1), [2] PT PJB UP Paiton. Informasi Umum Power Plant. PT PJB UP Paiton, (accessed on January 15th, 2018) [3] Scire, J.S., Strimaitis. D.G., and Yamartino, R.J. A User s Guide for The CALPUFF Dispersion Model. Concord : Earth Tech, Inc., [4] US EPA. EMC: Continuous Emission Systems Information and Guidelines, (accessed on Dec 15th 2016) [5] Vesilind, P. A. dkk. Environmental Engineering 3th Edition. Boston : B utterworth- Heinemann, [6] World Coal Institute. Sumber Daya Batubara. Tinjauan Lengkap Mengenai Batu Bara, editor@iaeme.com