화학공학소재연구정보센터
Korean Chemical Engineering Research, Vol.57, No.1, 90-104, February, 2019
축사 주변의 악취 및 부유분진의 CALPUFF 모델링: 계사 중심으로
CALPUFF Modeling of Odor/suspended Particulate in the Vicinity of Poultry Farms
E-mail:
초록
본 연구에서는 시간별 실제 기상데이터를 토대로 한 CALPUFF 모델링 수행을 통하여 민원지역에 대한 신뢰성이 있는 모델링 결과를 도출하였다. 무창형 계사 P1 및 P2의 방진망 구조물(chamber) 및 개방형 계사 P3로부터의 오염원 배출 및 확산거동을, 부피오염원으로서의 CALPUFF 모델링 또는 각 방향의 배출면적을 가중치로 한 수직 배기의 평균 선속도인 모델 배출 선속도(U M y)를 적용한 점오염원으로서의 최종 CALPUFF 모델링으로 구현하였다. 또한 계사 P1, P2 및 P3에서의 배출되는 악취 및 분진오염원 배출량에 대한 각각의 제거효율(0, 20, 50 및 80%) 또는 각각 대응되는 emission rate (100, 80, 50 및 20%)에 따른 시나리오를 기본으로, CALPUFF 모델링을 수행하여 각각에 대한 민원지역의 농도예측을 수행하였다. 이러한 민원지역에 대한 암모니아, 황화수소, PM2.5 및 PM10에 대한 농도예측과 악취방 지법 및 대기환경법에서 요구되는 오염물질 농도와 비교하여, 계사 P1, P2 및 P3에 요구되는 암모니아, 황화수소, PM2.5 및 PM10에 대한 제거율을 산정하였다. 그 결과로서, “P1, P2 및 P3에서 각각의 배출농도를 줄인 비율만큼 각각의 discrete receptor에서의 농도가 같은 비율로 감소한다”는 가정(a priori assumption)이 본 CALPUFF 모델링 범위 내에서 적용 가능함이 입증되었다. 한편 부피오염원을 적용한 CALPUFF 모델링을 수행한 경우에서 방지시설의 요구되는 제거효율은, 점오염원을 적용한 CALPUFF 모델링을 수행한 경우와 비교하였을 때에 P1의 경우에는 상호간에 유사하였으나, P2와 P3에서 암모니아와 PM10의 경우에 더 높게 나타났다. 그럼에도 불구하고 민원해결을 위한 안전한 접근 방법으로서 부피오염원으로서 CALPUFF 모델링을 선정하였다. 이에 따라서 본 연구에서는 암모니아, 황화수소, PM2.5 및 PM10와 같은 오염원배출에 대하여 무창형 계사 P1 및 P2에 요구되는 정량적 방지수준을 타당하게 도출하였다.
In this study, CALPUFF modeling was performed, using a real surface and upper air meterological data to predict trustworthy modeling-results. Pollutant-releases from windscreen chambers of enclosed poultry farms, P1 and P2, and from a open poultry farm, P3, and their diffusing behavior were modeled by CALPUFF modeling with volume sources as well as by finally-adjusted CALPUFF modeling where a linear velocity of upward-exit gas averaged with the weight of each directional-emitting area was applied as a model-linear velocity (u M y ) at a stack, with point sources. In addition, based upon the scenario of poultry farm-releasing odor and particulate matter (PM) removal efficiencies of 0, 20, 50 and 80% or their corresponding emission rates of 100, 80, 50 and 20%, respectively, CALPUFF modeling was performed and concentrations of odor and PM were predicted at the region as a discrete receptor where civil complaints had been frequently filed. The predicted concentrations of ammonia, hydrogen sulfide, PM2.5 and PM10 were compared with those required to meet according to the offensive odor control law or the atmospheric environmental law. Subseuquently their required removal efficiencies at poultry farms of P1, P2 and P3 were estimated. As a result, a priori assumption that pollutant concentrations at their discrete receptors are reduced by the same fraction as pollutant concentrations at P1, P2 and P3 as volume source or point source, were controlled and reduced, was proven applicable in this study. In case of volume source-adopted CALPUFF modeling, its required removal efficiencies of P1 compared with those of point source-adopted CALPUFF modeling, were predicted similar each other. However, In case of volume source-adopted CALPUFF modeling, its required removal efficiencies of both ammonia and PM10 at not only P2 but also P3 were predicted higher than those of point source-adopted CALPUFF modeling. Nonetheless, the volume source-adopted CALPUFF modeling was preferred as a safe approach to resolve civil complaints. Accordingly, the required degrees of pollution prevention against ammonia, hydrogen sulfide, PM2.5 and PM10 at P1 and P2, were estimated in a proper manner.
  1. Bokowa AH, Chemical Engineering Transactions,, 23, 31 (2010)
  2. Nicell JA, Atmos. Environ., 43, 196 (2009)
  3. Okutani F, Hirose K, Kobayashi T, Kaba H, Hyodo M, Auris Nasus Larynx., 40, 76 (2013)
  4. Smeets MAM, Bulsing PJ, Rooden SV, Steinmann R, Ru JAD, Ogink NWM, Thriel CV, Dalton PH, Chem Senses., 32, 11 (2007)
  5. Hartung J, Phillips VR, J. Agric. Eng. Res., 57, 173 (1994)
  6. Gustafsson G, J. Agric. Eng. Res., 74, 379 (1999)
  7. Gonzalez-Matute R, Rinker DL, Bioresour. Technol., 97(14), 1679 (2006)
  8. Kim KY, Choi HL, J. Anim. Sci. Technol., 43(6), 1005 (2001)
  9. Kuroda K, Osada T, Yonaga M, Kanematu A, Nitta T, Mouri S, Kojima T, Bioresour. Technol., 56(2-3), 265 (1996)
  10. Jester RCPE, Malone GW, “Respiratory Health on the Poultry Farm, National Ag Safety Database (NASD), http://www.cdc.gov/nasd/docs/d000101-d000200/d000146/d000146.html.
  11. Roumeliotis TS, Van Heyst BJ, J. Appl. Poult. Res., 17, 305 (2008)
  12. Navaratnasamy M, Feddes JJR, PIC Project No 155, Poultry industry council, Alberta, Canada(2004).
  13. Lacey RE, Redwine JS, Panell CB, Trans. ASAE, 46(4), 1203 (2003)
  14. Lim TT, Heber AJ, Ni JQ, Gallien JX, Xin H, Air Pollution from Agricultural Operations III(ASAE Publication Number 701P1403), ASAE conference, October, Research Triangle Park, North carolina(2003).
  15. Gay SW, Schmidt DR, Clanton CJ, Janni KA, Jacobson LD, Weisberg S, Applied Engineering in Agriculture, 347-360(2003).
  16. Hinz T, Linke S, J. Agric. Eng. Res., 70, 119 (1998)
  17. Koerkamp PWG, Merz JHM, Uenk GH, Phillips VR, et al., J. Agric. Eng. Res., 70, 79 (1998)
  18. Wathes CM, Holden MR, Sneath RW, White RP, Phillips VR, British Poultry Science, 38, 14 (1997)
  19. Hadlocon LS, Zhao LY, Bohrer G, Kenny W, Garrity SR, Wang J, Wyslouzil B, Upadhyay, J. Air Waste Manage. Assoc., 65(2), 206 (2015)
  20. Kim, KY, Korean Journal of Odor Research and Engineering, 11(3), 105-111 (2012).
  21. Kim KY, Choi JH, Kim D, J. Korean Soc. Indoor Environ., 10(2), 69 (2013)
  22. Kuroda K, Osada T, Yonaga M, Bioresour. Technol., 56, 265 (1995)
  23. Kulik A, World Wastes, 39, 37 (1996)
  24. Laupsa H, Denby B, Larrsen S, Schaug J, Atmos. Environ., 43, 4733 (2009)
  25. Caputo M, Gimenez M, Schlamp M, Atmos. Environ., 37, 2435 (2003)
  26. Homes NS, Morawska L, Atmos. Environ., 40, 5902 (2006)
  27. Vieira de Melo AM, Santos JM, Mavroidis I, Reis NC, Build. Environ., 56, 8 (2012)
  28. Ranzato L, Barausse A, Mantovani A, Pittarello A, Benzo M, Palmeri L, Atmospheric Environment, 61, 570 (2012)
  29. Ghannam K, Fadel ME, J. Air Waste Manage. Assoc., 63(2), 190 (2013)
  30. Jeong SJ, Asian J. Atmospheric Environment, 5(1), 1 (2011)
  31. Lee EJ, Akhtar MS, Lim KH, Korean Chem. Eng. Res., 54(1), 22 (2016)
  32. Lee EJ, Khan M, Lim KH, Korean Chem. Eng. Res., 54(2), 187 (2016)
  33. Scire JS, Strimaitis DG, Yamartino RJ, A User’s guide for the CALPUFF dispersion model, version 5, Earth Tech, Inc., Concord, MA(2000).
  34. Wang L, Parker DB, Parnell CB, Lacey EE, Shaw BW, Atmospheric Environment, 40, 4663 (2006)
  35. Turner DB, Workbook of Atmospheric Dispersion Estimates, North Carolina(1970).
  36. Air dispersion modeling guidelines for Arizona air quality permits, Air quality division of Arizona department of environmental quality, Arizona(2013).
  37. Hwangbo J, Song JI, Cho KH, Chung BS, Lee BS, Nam BS, Chung CS, Chung IB, J. Anim. Sci. Technol., 44(4), 475 (2002)
  38. Mark Dunlop, “Control of Odor and Dust from Chicken Sheds: Review of “add-on” Technologies,” RIRDC Publication No.09/034, RIRDC Project No. DAQ-341A, Mar. 2009.