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

Abstract

Abstract. This work reviews the existing methodologies for source apportionment and sensitivity analysis to identify key differences and stress their implicit limitations. The emphasis is laid on the differences between source "impacts" (sensitivity analysis) and "contributions" (source apportionment) obtained by using four different methodologies: brute-force top-down, brute-force bottom-up, tagged species and decoupled direct method (DDM). A simple theoretical example to compare these approaches is used highlighting differences and potential implications for policy. When the relationships between concentration and emissions are linear, impacts and contributions are equivalent concepts. In this case, source apportionment and sensitivity analysis may be used indifferently for both air quality planning purposes and quantifying source contributions.However, this study demonstrates that when the relationship between emissions and concentrations is nonlinear, sensitivity approaches are not suitable to retrieve source contributions and source apportionment methods are not appropriate to evaluate the impact of abatement strategies. A quantification of the potential nonlinearities should therefore be the first step prior to source apportionment or planning applications, to prevent any limitations in their use. When nonlinearity is mild, these limitations may, however, be acceptable in the context of the other uncertainties inherent to complex models.Moreover, when using sensitivity analysis for planning, it is important to note that, under nonlinear circumstances, the calculated impacts will only provide information for the exact conditions (e.g. emission reduction share) that are simulated.

The contribution of aviation NOx emissions to climate change: are we ignoring methodological flaws?

“…This is called sensitivity or perturbation approach. Clappier et al (2017) [1] (in agreement with other studies, e.g. [2,30]) have clearly stated that 'when the relationship between emissions and concentrations is nonlinear, sensitivity approaches are not suitable to retrieve source contributions'.…”

“…The second implication relates to the question of how to evaluate mitigation options in strongly nonlinear relationships, such as the NO x -ozone relationship. While Clappier et al [1] raised the point that 'source apportionment methods 3 are not appropriate to evaluate the impact of abatement strategies', Grewe et al [3] clearly stated that 'the use of the tagging method (see footnote 1) makes the evaluation of mitigation measures more robust', since this evaluation becomes largely independent on other conditions, e.g. the timing of the mitigation option, implementation of other mitigation options, and background concentrations.…”

“…Such methodological simplifications largely underestimate the contribution of the aviation NO x emissions to climate change by a factor of 6 to 7 and can thereby be considered as flaws. Note that the contribution of an emission to climate change (='status report') and the contribution of a change in emissions to climate change (='mitigation option') require different calculation methods [1,2]. While for calculating the contribution of emissions to atmospheric compositions (and hence climate change), to which we are referring here, a clear recommendation was made (e.g.…”

“…While for calculating the contribution of emissions to atmospheric compositions (and hence climate change), to which we are referring here, a clear recommendation was made (e.g. [1]), the methodological approach for evaluating mitigation measures might still be ambiguous, but should certainly not ignore the results of contribution calculations [3].…”

Current and Future Disease Burden From Ambient Ozone Exposure in India

“…Overestimated O 3 production in polluted regions may bias the source attribution of O 3 more toward local sources due to the shorter production time scales (Wild & Prather, 2006). The response of O 3 concentrations to changes in emissions is nonlinear, meaning an emission removal approach to quantify attributions can differ from a source tracking approach (Clappier et al, 2017;Mertens et al, 2018).…”