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Application of the DPSIR framework to air quality approaches

  • Helder Relvas
  • Ana Isabel Miranda
Article
  • 20 Downloads

Abstract

Current air quality legislation in Europe will lead to substantial air quality improvements, but without further emission control efforts, the most critical hotspots will persist, with important impacts on the environment and human health. Integrated assessment models (IAM) can be applied to local and regional scale to support the assessment of mitigation opportunities and decision-making process. The mitigation measures need to be sustainable, and subsequently, social, economic, and environmental factors need to be balanced. This paper proposes the use of the well-known DPSIR framework, which is composed by Driving forces, Pressures, State, Impacts, and Responses. The urban area of Porto (Northern Portugal) is the selected case study, and DPSIR radar charts are used to easily compare different IAM approaches and help researchers and policy-makers to achieve the objective of air quality improvement. Results indicate that the MAPLIA system based on scenario approach and the RIAT+ system based on optimization approach provide more detailed and comprehensive information, namely concerning health (Impacts), then the previously designed Porto’s air quality plans.

Keywords

Air quality plans Health effects DPSIR framework, integrated assessment modeling Emissions 

Notes

Acknowledgements

The authors would also like to acknowledge the financial support of FEDER through the COMPETE Programme and the national funds from FCT—Science and Technology Portuguese Foundation for the Ph.D. grant of H. Relvas (SFRH/BD/101660/2014).

References

  1. Achillas C, Vlachokostas C, Moussiopoulos Ν, Banias G (2011) Prioritize strategies to confront environmental deterioration in urban areas: multicriteria assessment of public opinion and experts’ views. Cities 28:414–423CrossRefGoogle Scholar
  2. Aggarwal P, Jain S (2015) Impact of air pollutants from surface transport sources on human health: a modeling and epidemiological approach. Environ Int 83:146–157.  https://doi.org/10.1016/j.envint.2015.06.010 CrossRefGoogle Scholar
  3. Amann M, Bertok I, Borken-Kleefeld J, Cofala J, Heyes C, Höglund-Isaksson L, Klimont Z, Nguyen B, Posch M, Rafaj P, Sandler R, Schöpp W, Wagner F, Winiwarter W (2011) Cost-effective control of air quality and greenhouse gases in Europe: modeling and policy applications. Environ Model Softw 26:1489–1501.  https://doi.org/10.1016/j.envsoft.2011.07.012 CrossRefGoogle Scholar
  4. APA (2014) Portuguese Informative Inventory Report 1990-2014 Submitted under the UNECE convention on longrange transboundary air pollution. Portuguese Environmental Agency, AmadoraGoogle Scholar
  5. APPRAISAL (2013) Review and gaps identification in AQ and HIA methodologies at regional and local scale, Deliverable 2.4 Health Impact Assessment (HIA) (pp. 83)Google Scholar
  6. Bär R, Rouholahnejad E, Rahman K, Abbaspour KC, Lehmann A (2015) Climate change and agricultural water resources: a vulnerability assessment of the Black Sea catchment. Environ Sci Policy 46:57–69.  https://doi.org/10.1016/j.envsci.2014.04.008 CrossRefGoogle Scholar
  7. Belhout D, Kerbachi R, Relvas H, Miranda AI (2018) Air quality assessment in Algiers city. Air Qual Atmos Health.  https://doi.org/10.1007/s11869-018-0589-x
  8. Bickel P, Friedrich R (2005) ExternE: externalities of energy, methodology 2005 update. Tech. Rep., IER, University of StuttgartGoogle Scholar
  9. Borrego C, Tchepel O, Salmim L et al (2004) Integrated modeling of road traffic emissions: application to Lisbon air quality management. Cybern Syst An Int J 35:535–548CrossRefGoogle Scholar
  10. Bradley P, Yee S (2015) Using the DPSIR framework to develop a conceptual model: technical support document. US Environmental Protection Agency, Office of Research and Development, National Health and Environmental Effects Research Laboratory, Atlantic Ecology Division, NarragansettGoogle Scholar
  11. Brudvig LA, Leroux SJ, Albert CH, Bruna EM, Davies KF, Ewers RM, Levey DJ, Pardini R, Resasco J (2017) Evaluating conceptual models of landscape change. Ecography (Cop) 40:74–84CrossRefGoogle Scholar
  12. Carnevale C, Pisoni E, Volta M (2008) A multi-objective nonlinear optimization approach to designing effective air quality control policies. Automatica 44:1632–1641.  https://doi.org/10.1016/j.automatica.2008.04.001 CrossRefGoogle Scholar
  13. Carnevale C, Finzi G, Guariso G, Pisoni E, Volta M (2012a) Surrogate models to compute optimal air quality planning policies at a regional scale. Environ Model Softw 34:44–50.  https://doi.org/10.1016/j.envsoft.2011.04.007 CrossRefGoogle Scholar
  14. Carnevale C, Finzi G, Pisoni E et al (2012b) An integrated assessment tool to define effective air quality policies at regional scale. Environ Model Softw 38:306–315.  https://doi.org/10.1016/j.envsoft.2012.07.004 CrossRefGoogle Scholar
  15. Carnevale C, Finzi G, Pisoni E et al (2012c) Defining a nonlinear control problem to reduce particulate matter population exposure. Atmos Environ 55:410–416.  https://doi.org/10.1016/j.atmosenv.2012.03.033 CrossRefGoogle Scholar
  16. Carnevale C, Finzi G, Pederzoli A et al (2014) Exploring trade-offs between air pollutants through an integrated assessment model. Sci Total Environ 481:7–16.  https://doi.org/10.1016/j.scitotenv.2014.02.016 CrossRefGoogle Scholar
  17. Carnevale C, Douros J, Finzi G et al (2016) Uncertainty evaluation in air quality planning decisions: a case study for Northern Italy. Environ Sci Policy 65:39–47.  https://doi.org/10.1016/j.envsci.2016.02.001 CrossRefGoogle Scholar
  18. CCDR-N (2011) Plan to improve air quality in the northern region – NO2. Technical Report No: IMA 61.11/01.03Google Scholar
  19. CCDR–N (2007) Plan to improve air quality in the northern region: PM10 – 2004, O3 – 2004/2005, Technical Report No. AMB–QA–07/2007. University of AveiroGoogle Scholar
  20. Clappier A, Pisoni E, Thunis P (2015) A new approach to design source–receptor relationships for air quality modelling. Environ Model Softw 74:66–74.  https://doi.org/10.1016/j.envsoft.2015.09.007 CrossRefGoogle Scholar
  21. Diab RD, Motha A (2007) An analysis of key institutional factors influencing air quality in south durban using the DPSIR framework. S Afr Geogr J 89:22–33.  https://doi.org/10.1080/03736245.2007.9713869 CrossRefGoogle Scholar
  22. Duque L, Relvas H, Silveira C, Ferreira J, Monteiro A, Gama C, Rafael S, Freitas S, Borrego C, Miranda AI (2016) Evaluating strategies to reduce urban air pollution. Atmos Environ 127:196–204.  https://doi.org/10.1016/j.atmosenv.2015.12.043 CrossRefGoogle Scholar
  23. EEA (1999) Environmental indicators: typology and overview, technical report No 25/1999Google Scholar
  24. EMEP (2013) European Environment Agency air pollutant emission inventory guidebook 2013. EEA, CopenhagenGoogle Scholar
  25. Gama C, Monteiro A, Pio C, Miranda AI, Baldasano JM, Tchepel O (2018) Temporal patterns and trends of particulate matter over Portugal: a long-term analysis of background concentrations. Air Qual Atmos Health 11:397–407.  https://doi.org/10.1007/s11869-018-0546-8 CrossRefGoogle Scholar
  26. Gari SR, Newton A, Icely JD (2015) A review of the application and evolution of the DPSIR framework with an emphasis on coastal social-ecological systems. Ocean Coast Manag 103:63–77CrossRefGoogle Scholar
  27. Gioli B, Gualtieri G, Busillo C et al (2015) Improving high resolution emission inventories with local proxies and urban eddy covariance flux measurements. Atmos Environ 115:246–256.  https://doi.org/10.1016/j.atmosenv.2015.05.068 CrossRefGoogle Scholar
  28. Goble BJ, Hill TR, Phillips MR et al (2017) An Assessment of Integrated Coastal Management Governance and Implementation Using the DPSIR Framework : KwaZulu-Natal, South Africa An Assessment of Integrated Coastal Management Governance and Implementation Using the DPSIR Framework: KwaZulu-. Coast Manag 45:107–124.  https://doi.org/10.1080/08920753.2017.1278144 CrossRefGoogle Scholar
  29. Guariso G, Maione M, Volta M (2016) A decision framework for integrated assessment modelling of air quality at regional and local scale. Environ Sci Policy 65:3–12.  https://doi.org/10.1016/j.envsci.2016.05.001 CrossRefGoogle Scholar
  30. Guo X, Fu L, Ji M et al (2016) Scenario analysis to vehicular emission reduction in Beijing-Tianjin-Hebei (BTH) region, China. Environ Pollut 216:470–479.  https://doi.org/10.1016/j.envpol.2016.05.082 CrossRefGoogle Scholar
  31. Hurley PJ, Physick WL, Luhar AK (2005) TAPM: a practical approach to prognostic meteorological and air pollution modelling. Environ Model Softw 20:737–752.  https://doi.org/10.1016/j.envsoft.2004.04.006 CrossRefGoogle Scholar
  32. INE, I (2012) Censos 2011 resultados definitivos-Portugal. Instituto Nacional de Estatística, IP, Lisboa-PortugalGoogle Scholar
  33. Joffe M, Mindell J (2006) Complex causal process diagrams for analyzing the health impacts of policy interventions. Am J Public Health 96:473–479CrossRefGoogle Scholar
  34. Kansal A, Khare M, Sharma CS (2009) Health benefits valuation of regulatory intervention for air pollution control in thermal power plants in Delhi, India. J Environ Plan Manag 52:881–899.  https://doi.org/10.1080/09640560903180933 CrossRefGoogle Scholar
  35. Kuenen JJP, Visschedijk AJH, Jozwicka M, Denier Van der Gon HAC (2014) TNO-MACC_II emission inventory: a multi-year (2003–2009) consistent high-resolution European emission inventory for air quality modelling. Atmos Chem Phys 14:10963–10976CrossRefGoogle Scholar
  36. Lewison RL, Rudd MA, Al-Hayek W et al (2016) How the DPSIR framework can be used for structuring problems and facilitating empirical research in coastal systems. Environ Sci Policy 56:110–119.  https://doi.org/10.1016/j.envsci.2015.11.001 CrossRefGoogle Scholar
  37. Maes J, Vliegen J, Van de Vel K et al (2009) Spatial surrogates for the disaggregation of CORINAIR emission inventories. Atmos Environ 43:1246–1254.  https://doi.org/10.1016/j.atmosenv.2008.11.040 CrossRefGoogle Scholar
  38. Miranda A, Silveira C, Ferreira J, Monteiro A, Lopes D, Relvas H, Borrego C, Roebeling P (2015) Current air quality plans in Europe designed to support air quality management policies. Atmos Pollut Res 6:6–443.  https://doi.org/10.5094/APR.2015.048 CrossRefGoogle Scholar
  39. Miranda AI, Ferreira J, Silveira C, Relvas H, Duque L, Roebeling P, Lopes M, Costa S, Monteiro A, Gama C, Sá E, Borrego C, Teixeira JP (2016a) A cost-efficiency and health benefit approach to improve urban air quality. Sci Total Environ 569-570:569–570.  https://doi.org/10.1016/j.scitotenv.2016.06.102 CrossRefGoogle Scholar
  40. Miranda AI, Relvas H, Viaene P, Janssen S, Brasseur O, Carnevale C, Declerck P, Maffeis G, Turrini E, Volta M (2016b) Applying integrated assessment methodologies to air quality plans: Two European cases. Environ Sci Policy 65:65–38.  https://doi.org/10.1016/j.envsci.2016.04.010 CrossRefGoogle Scholar
  41. Monteiro A, Russo M, Gama C et al (2018) How economic crisis influence air quality over Portugal (Lisbon and Porto)? Atmos Pollut Res 9:439–445.  https://doi.org/10.1016/j.apr.2017.11.009 CrossRefGoogle Scholar
  42. Nagl C, Moosmann L, Schneider J (2007) Assessment of plans and programmes reported under 1996/62/EC–final report. Umweltbundesamt GmbH Spittelauer Lände 5:1090Google Scholar
  43. Relvas H, Miranda AI (2018) An urban air quality modeling system to support decision-making: design and implementation. Air Qual Atmos Health.  https://doi.org/10.1007/s11869-018-0587-z
  44. Relvas H, Miranda AI, Carnevale C, Maffeis G, Turrini E, Volta M (2017) Optimal air quality policies and health: a multi-objective nonlinear approach. Environ Sci Pollut Res 24:13687–13699.  https://doi.org/10.1007/s11356-017-8895-7 CrossRefGoogle Scholar
  45. Schöpp W, Amann M, Cofala J et al (1998) Integrated assessment of European air pollution emission control strategies. Environ Model Softw 14:1–9.  https://doi.org/10.1016/S1364-8152(98)00034-6 CrossRefGoogle Scholar
  46. Spanò M, Gentile F, Davies C, Lafortezza R (2017) The DPSIR framework in support of green infrastructure planning: a case study in Southern Italy. Land Use Policy 61:242–250.  https://doi.org/10.1016/j.landusepol.2016.10.051 CrossRefGoogle Scholar
  47. Thunis P, Georgieva E, Pederzoli A (2012) A tool to evaluate air quality model performances in regulatory applications. Environ Model Softw 38:220–230.  https://doi.org/10.1016/j.envsoft.2012.06.005 CrossRefGoogle Scholar
  48. Thunis P, Miranda AI, Baldasano JM et al (2016) Overview of current regional and local scale air quality modelling practices: assessment and planning tools in the EU. Environ Sci Policy 65:13–21.  https://doi.org/10.1016/j.envsci.2016.03.013 CrossRefGoogle Scholar
  49. Vedrenne M, Borge R, Lumbreras J, Rodríguez ME (2014) Advancements in the design and validation of an air pollution integrated assessment model for Spain. Environ Model Softw 57:177–191.  https://doi.org/10.1016/j.envsoft.2014.03.002 CrossRefGoogle Scholar
  50. Vestreng V, Goodwin J, Adams M (2004) Inventory review 2004. Emission data reported to CLRTAP and under the NEC DirectiveGoogle Scholar
  51. Vestreng V, Myhre G, Fagerli H, Reis S, Tarrasón L (2007) Twenty-five years of continuous sulphur dioxide emission reduction in Europe. Atmos Chem Phys 7:3663–3681CrossRefGoogle Scholar
  52. Viaene P, Belis CA, Blond N et al (2016) Air quality integrated assessment modelling in the context of EU policy: a way forward. Environ Sci Policy 65:22–28.  https://doi.org/10.1016/j.envsci.2016.05.024 CrossRefGoogle Scholar
  53. Vlachokostas C, Achillas C, Moussiopoulos Ν, Kalogeropoulos K, Sigalas G, Kalognomou EA, Banias G (2012) Health effects and social costs of particulate and photochemical urban air pollution: a case study for Thessaloniki, Greece. Air Qual Atmos Health 5:325–334.  https://doi.org/10.1007/s11869-010-0096-1 CrossRefGoogle Scholar
  54. WHO (2013) Health risks of air pollution in Europe—HRAPIE project recommendations for concentration–response functions for cost–benefit analysis of particulate matter, ozone and nitrogen dioxide. World Health Organization Regional Office for Europe. World Health Organization, GenevaGoogle Scholar
  55. Zhang X, Xue X (2013) Analysis of marine environmental problems in a rapidly urbanising coastal area using the DPSIR framework: a case study in Xiamen, China. J Environ Plan Manag 56:720–742.  https://doi.org/10.1080/09640568.2012.698985 CrossRefGoogle Scholar
  56. Zhou G, Singh J, Wu J et al (2015) Evaluating low-carbon city initiatives from the DPSIR framework perspective. Habitat Int 50:289–299.  https://doi.org/10.1016/j.habitatint.2015.09.001 CrossRefGoogle Scholar

Copyright information

© Springer Nature B.V. 2018

Authors and Affiliations

  1. 1.CESAM & Department of Environment and PlanningUniversity of AveiroAveiroPortugal

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