Abstract
Abstract. We present a computationally inexpensive method for individually quantifying the contributions from different sources to local air pollution. It can explicitly distinguish between regional–background and local–urban air pollution, allowing for fully consistent downscaling schemes. The method can be implemented in existing Eulerian chemical transport models and can be used to distinguish the contribution of a large number of emission sources to air pollution in every receptor grid cell within one single model simulation and thus to provide detailed maps of the origin of the pollutants. Hence, it can be used for time-critical operational services by providing scientific information as input for local policy decisions on air pollution abatement. The main limitation in its current version is that nonlinear chemical processes are not accounted for and only primary pollutants can be addressed. In this paper we provide a technical description of the method and discuss various applications for scientific and policy purposes.
Highlights
The origin of atmospheric pollutants within a given region is one of the fundamental questions of air quality research
Typical questions include the following: (a) by what amount can local air pollution be reduced through local measures only, and in which cases will regional or countrywide measures be necessary? (b) What will be the benefit of emission reduction measures imposed on one or several specific emission sectors? (c) Will these measures be efficient on a short time frame or should they be implemented on a longerterm basis?
Chemical transport models (CTMs), in particular, are efficient mathematical tools that treat the emission sources, transport, chemical conversion and loss mechanisms of air pollutants in a consistent way and allow different scenarios to be assessed within a reasonable amount of computing time
Summary
The origin of atmospheric pollutants within a given region is one of the fundamental questions of air quality research. Adjoint models calculate the derivative of a model scalar with respect to all other model parameters in one single simulation and in this way efficiently quantify the contribution from all emission sources to air pollution in a given receptor region. In this paper we present a method that can efficiently calculate the contribution of a significantly larger number of sources (thousands or more) to a limited (but large) number of receptor regions. This method does not provide results that cannot be obtained by other means, but it does so at a lower computational cost and is well suited, especially for time-critical operational applications. In the last section we discuss possible applications of the method and plans for further development
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