Articles | Volume 10, issue 11
https://doi.org/10.5194/gmd-10-4245-2017
https://doi.org/10.5194/gmd-10-4245-2017
Methods for assessment of models
 | 
24 Nov 2017
Methods for assessment of models |  | 24 Nov 2017

Source apportionment and sensitivity analysis: two methodologies with two different purposes

Alain Clappier, Claudio A. Belis, Denise Pernigotti, and Philippe Thunis

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Cited articles

Belis, C. A., Karagulian, F., Larsen, B. R., and Hopke, P. K.: Critical review and meta-analysis of ambient particulate matter source apportionment using receptor models in Europe, Atmos. Environ., 69, 94–108, 2013.
Bhave, P. V., Pouliot, G. A., and Zheng, M.: Diagnostic model evaluation for carbonaceous PM2.5 using organic markers measured in the southeastern U.S., Environ. Sci. Technol., 41, 1577–1583, 2007.
Blanchard, C. L.: Methods for attributing ambient air pollutants to emission sources, Annu. Rev. Ener. Env., 24, 329–365, 1999.
Burr, M. J. and Zhang, Y.: Source-apportionment of fine particulate matter over the Eastern U.S. Part II: source apportionment simulations using CAMx/PSAT and comparisons with CMAQ source sensitivity simulations, Atmos. Pollut. Res., 2, 318–336, 2011a.
Burr, M. J. and Zhang, Y.: Source-apportionment of fine particulate matter over the Eastern U.S. Part II: source sensitivity simulations using CMAQ with the Brute Force method, Atmos. Pollut. Res., 2, 300–317, 2011b.
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Short summary
This work demonstrates that when the relationship between emissions and concentrations is nonlinear, sensitivity approaches, generally used for air quality planning, are not suitable to retrieve source contributions and source apportionment methods are not appropriate to evaluate the impact of abatement strategies on air quality. A simple theoretical example is used highlighting differences and potential implications for policy.