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Tri-generation power plant and conventional boilers: pollutant flow rate and atmospheric impact of stack emissions

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Abstract

The atmospheric impact of stack emissions from a power plant (tri-generator and boilers) that will be installed in an urban area in the central Po valley (Northern Italy), characterized by calm wind events, is studied and compared with the impact of the existing plant (conventional boilers). Both the plants are supplied by methane gas. The atmospheric dispersion of NOx emitted is simulated, both in the current and future scenario, by the software package ARIA INDUSTRY. The NOx emission rates are set equal to the regulatory emission limits for existing and future boilers, while the tri-generation system emission rates are set equal to the emission limits certified by the system manufacturer. The simulation periods focus over the 2010 winter season. The simulation estimates the impact of NOx emissions on air quality (vertical concentration profiles and concentration maps at the ground) in the urban area close to the plant. The future power plant impact on air quality results lower than the impact of the existing plant, even if the yearly total mass of pollutants emitted in atmosphere from the new power plant is higher than from the existing plant. The emissions of conventional boilers result the main responsible of the air pollution at the ground in the future scenario.

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References

  • Anfossi D (1985) Analysis of plume rise data from five TVA steam plants. J Clim Appl Meteorol 24:1225–1236

    Article  CAS  Google Scholar 

  • Anfossi D, Bonino G, Bossa F, Richiardone R (1978) Plume rise from multiple sources: a new model. Atmos Environ 12:1821–1826

    Article  Google Scholar 

  • Anfossi D, Ferrero E, Brusasca G, Marzorati A, Tinarelli G (1993) A simple way of computing buoyant plume rise in a Lagrangian stochastic dispersion model. Atmos Environ 27A:1443–1445

    Article  CAS  Google Scholar 

  • Anfossi D, Ferrero E, Sacchetti D, Trini Castelli S (1997) Comparison among empirical probability density functions of the vertical velocity in the surface layer based on higher order correlations. Bound Layer Meteor 82:193–218

    Article  Google Scholar 

  • Armand P, Achim P, Commanay J, Chevallaz-Perrier R, Moussafir J, Moon D, Albergel A (2004) Mesoscale dispersion of xenon along the rhone valley in France: results of a modelling system chaining ADAS, MM5, MINERVE and SPRAY. Proc 9th Int Conf Harm Atmos Dispers Model Regul Purp 209–213

  • Bigi A, Ghermandi G, Harrison RM (2012) Analysis of the air pollution climate at a background site in the po valley. J Environ Monit 14:552

    Article  CAS  Google Scholar 

  • Breznik B, Božnar MZ, Mlakar P, Tinarelli G (2003) Dose projection using dispersion models. Int J Environ Pollut 20:278–285

    CAS  Google Scholar 

  • Calori G, Clemente M, De Maria R, Finardi S, Lollobrigida F, Tinarelli G (2006) Air quality integrated modelling in Turin urban area. Environ Model Softw 21:468–476

    Article  Google Scholar 

  • Chandrasekar A, Philbrick CR, Clark R, Doddridge B, Georgopoulos P (2003) Evaluating the performance of a computationally efficient MM5/CALMET system for developing wind field inputs to air quality models. Atmos Environ 37:3267–3276

    Article  CAS  Google Scholar 

  • Cox RM, Sontowski J, Fry RN, Dougherty CM, Smith TJ (1998) Wind and diffusion modelling for complex terrain. J Appl Meteorol 37:996–1009

    Article  Google Scholar 

  • Cox RM, Sontowski J, Dougherty CM (2005) An evaluation of three diagnostic wind models (CALMET, MCSCIPUF, and SWIFT) with wind data from the Dipole Pride 26 field experiments. Meteorol Appl 12:329–341

    Article  Google Scholar 

  • Deserti M, Savoia E, Cacciamani C, Golinelli M, Kerschbaumer A, Leoncini G, Selvini A, Paccagnella T, Tibaldi S (2001) Operational meteorological pre-processing at Emilia Romagna ARPA meteorological service as a part of a decision support system for air quality management. Int J Environ Poll 16:571–582

    Google Scholar 

  • Desiato F, Finardi S, Brusasca G, Morselli MG (1998) TRANSALP 1989 experimental campaign-I: simulation of 3D flow with diagnostic wind field models. Atmos Environ 32:1141–1156

    Article  CAS  Google Scholar 

  • Dharmadhikari S (1997) Consider tri-generation techniques for process plants. Hydrocarb Process 76:91–100

    Google Scholar 

  • Du S (1997) Universality of the lagrangian velocity structure function constant (C0) across different kinds of turbulence. Bound Lay Meteorol 83:207–219

    Article  Google Scholar 

  • ENEL (2010) Rapporto ambientale ENEL 2010. ENEL http://www.enel.com/it-IT/doc/environmental_report/rapporto_ambientale_2010.pdf. Accessed 07 Jan 2013

  • E.U. (2004) Directive 2004/8/EC of the European Parliament and of the council of 11 February 2004 on the promotion of cogeneration based on a useful heat demand in the internal energy market and amending Directive 92/42/EEC. Official Journal of the European Union, L Serie, L52/50-L52/60

  • E.U. (2008) Directive 2008/50/EC of the European Parliament and of the Council of 21 May 2008 on ambient air quality and cleaner air for Europe. Official Journal of the European Union, L Series, L152/1-L152/144

  • E.U. (2009) Directive 2009/29/EC of the European Parliament and of the Council of 23 April 2009 amending Directive 2003/87/EC so as to improve and extend the greenhouse gas emission allowance trading scheme of the Community (Text with EEA relevance). Official Journal of the European Union, L Serie, L140/63-L 140/87

  • European Environmental Agency (2012a) Combined heat and power (CHP) (ENER 020) http://www.eea.europa.eu/data-and-maps/indicators/ds_resolveuid/49cd316cf53dbd23cf650127e47a0aac. Accessed 11 Mar 2013

  • European Environmental Agency (2012b) Energy efficiency in transformation (ENER 011) http://www.eea.europa.eu/data-and-maps/indicators/energy-efficiency-and-energy-consumption-5/ds_resolveuid/0a010911-6d85-46ed-b6ce-8b1550ebfbcd. Accessed 11 Mar 2013

  • Ferrero E, Anfossi D (1998) Comparison of PDFs, closures schemes and turbulence parameterizations in Lagrangian stochastic models. Int J Environ Poll 9:384–410

    CAS  Google Scholar 

  • Ferrero E, Anfossi D, Tinarelli G (2001) Simulations of atmospheric dispersion in an Urban stable boundary layer. Int J Environ Poll 16:1–6

    CAS  Google Scholar 

  • Ferrero L, Riccio A, Perrone MG, Sangiorgi G, Ferrini BS, Bolzacchini E (2011) Mixing height determination by tethered balloon-based particle soundings and modelling simulations. Atmos Res 102:145–156

    Article  CAS  Google Scholar 

  • Finardi S, Tinarelli G, Faggian P, Brusasca G (1998) Evaluation of different wind field modelling techniques for wind energy applications over complex topography. J Wind Engl Ind Aerod 74–76:283–294

    Article  Google Scholar 

  • Gariazzo C, Pelliccioni A, Bugliolo MP, Scalisi G (2004) Evaluation of a Lagrangian particle model (SPRAY) to assess environmental impact of an industrial facility in complex terrain. Water Air Soil Pollut 155:137–158

    Article  CAS  Google Scholar 

  • Gariazzo C, Papaleo V, Pelliccioni A, Calori G, Radice P, Tinarelli G (2007) Application of a Lagrangian particle model to assess the impact of harbour, industrial and urban activities on air quality in the Taranto area Italy. Atmos Environ 41(30):6432–6444

    Article  CAS  Google Scholar 

  • Geai P (1987) Methode d’interpolation et de reconstitution tridimensionelle d’un champ de vent: Le code d’analyse objective MINERVE. Report ARD-AID: E34-E11, EDF, Chatou, France

  • Ghermandi G, Teggi S, Fabbi S, Bigi A, Zaccanti MM (2011) Atmospheric impact of power plant stack emissions. Proc 14th Int Conf Harmon Atmos Dispers Model Regul Purp 240–244

  • Ghermandi G, Teggi S, Fabbi S, Bigi A, Cecchi R (2012) Model comparison in simulating the atmospheric dispersion of a pollutant plume in low wind conditions. Int J Environ Poll 48:69–77

    Article  CAS  Google Scholar 

  • Houghton JT, Ding Y, Griggs DJ, Noguer M, van der Linden PJ, Dai X, Maskell K, Johnson CA (2001) Climate change 2001: the scientific basis. Cambridge University Press, Cambridge

    Google Scholar 

  • Jackson B, Chau D, Gurer K, Kaduwela A (2006) Comparison of ozone simulations using MM5 and CALMET/MM5 hybrid meteorological fields for the July/August 2000 CCOS episode. Atmos Environ 40(2812):2822

    Google Scholar 

  • Levy JI, Spengler JD (2002) Modelling the benefits of power plant emission controls in massachusetts. J Air Waste Manag Assoc 52:5–18

    Article  CAS  Google Scholar 

  • Meunier F (2002) Co- and tri-generation contribution to climate change control. Appl Therm Eng 22(6):703–718

    Article  CAS  Google Scholar 

  • Pehnt M (2008) Environmental impacts of distributed energy systems: the case of micro cogeneration. Environ Sci Policy 11:25–37

    Article  CAS  Google Scholar 

  • Pernigotti D, Georgieva E, Thunis P, Bessagnet B (2012) Impact of meteorology on air quality modelling over the Po valley in northern Italy. Atmos Environ 51:303–310

    Article  CAS  Google Scholar 

  • Rodean HC (1995) Turbulent diffusion as a stochastic lagrangian process. Environmetrics 6:659–663. doi:10.1002/env.3170060613

    Article  Google Scholar 

  • Slawson PR, Csanady GT (1971) The effect of atmospheric conditions on plume rise. J Fluid Mech 47:33–49. doi:10.1017/S0022112071000910

    Article  Google Scholar 

  • Stull RB (1988) An introduction to boundary layer meteorology (Vol. 13). Springer

  • Thomson DJ (1987) Criteria for the selection of stochastic models of particle trajectories in the turbulent atmosphere. J Fluid Mech 180:529–556

    Article  CAS  Google Scholar 

  • Tinarelli G, Anfossi D, Bider M, Ferrero E, Trini Castelli S (1998) A new high performance version of the Lagrangian particle dispersion model SPRAY, some case studies. Proc 23rd CCMS-NATO Meeting, 499–507. Kluwer: Academic Publishers

  • Trini Castelli S, Anfossi D, Ferrero E (2002) Turbulence Statistics estimation and dispersion simulation scenarios in Urban environment, Proc 8th Int Conf Harmon Atmos Dispers Model Regul Purp 315–319

  • Trini Castelli S, Anfossi D, Ferrero E (2003) Evaluation of the environmental impact of two different heating scenarios in urban area. Int J Environ Poll 20:207–217

    Google Scholar 

  • Tinarelli G, Anfossi D, Trini Castelli S, Bider M, Ferrero E (2000) A new high performance version of the lagrangian particle dispersion model Spray, Some Case Studies. In Air pollution modelling and its application XIII, Gryning, eds. Sven-Erik, Batchvarova, Ekaterina 499–507. US: Springer

  • Yim SHL, Fung JCH, Lau AKH, Kot SC (2007) Developing a high-resolution wind map for a complex terrain with a coupled MM5/CALMET system. J Geophys Res 112:D05106

    Google Scholar 

Download references

Acknowledgments

The authors are thankful to the European Environment Agency for providing CORINE Land Cover 2000, to ARPA Emilia Romagna Weather Service for providing meteorological data, to ARPA Emilia Romagna for providing atmospheric pollutants concentration data and to USGS for providing SRTM DEM data.

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Authors and Affiliations

  1. Department of Engineering Enzo Ferrari, University of Modena and Reggio Emilia, Via Vignolese 905, 41125, Modena, Italy

    G. Ghermandi, S. Teggi, S. Fabbi, A. Bigi & M. M. Zaccanti

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  1. G. Ghermandi
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  2. S. Teggi
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  3. S. Fabbi
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  4. A. Bigi
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  5. M. M. Zaccanti
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Correspondence to G. Ghermandi.

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Ghermandi, G., Teggi, S., Fabbi, S. et al. Tri-generation power plant and conventional boilers: pollutant flow rate and atmospheric impact of stack emissions. Int. J. Environ. Sci. Technol. 12, 693–704 (2015). https://doi.org/10.1007/s13762-013-0463-1

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  • DOI: https://doi.org/10.1007/s13762-013-0463-1

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