A novel approach to screen and compare emission inventories

A methodology is proposed to support the evaluation and comparison of different types of emission inventories, and more specifically the comparison of bottom-up versus top-down approaches. The strengths and weaknesses of the methodology are presented and discussed based on an example. The approach results in a “diamond” diagram useful to flag out anomalous behaviors in the emission inventories and to get insight on possible explanations. In particular, the “diamond” diagram is shown to provide meaningful information in terms of: discrepancies between the total emissions reported by macro-sector and pollutant, contribution of each macro-sector to the total amount of emissions released by pollutant, and the identification and quantification of the different factors causing the discrepancies between total emissions. Its main strength as an indicator is to allow investigating the relative contribution of activity and weighted emission factors. A practical example in Barcelona is used for testing and to provide relevant information for the analyzed emission datasets. The tests show the capability of the proposed methodology to flag inconsistencies in the existing inventories. The proposed methodology system may be useful for regional and urban inventory developers as an initial evaluation of the consistency of their inventories.JRC.H.2-Air and Climat

Comparing air quality model performance for planning applications

The current policy making needs for emission abatement of air pollutants in Europe call for having simple yet robust tools that allow evaluating the effect of measures and sorting those that produce the most significant effects. As a result, the FAIRMODE Planning Working Group (WG4) seeks to develop a consistent framework for streamlining the understanding of models in order to identify more efficiently the relationship between changes in emissions and their effect in ambient concentration through a series of indicators or potencies. The comparison of sector-specific potencies was carried out using the Delta Tool for the AERIS integrated assessment model for the Iberian Peninsula and the SERCA modelling system, on which it is based. Air quality observations from 11 monitoring stations located in Spain and Portugal were used as independent comparison dataset, focusing on a winter and summer month (January and August), as well as on an annual basis. The comparison revealed that the main difference between AERIS and SERCA is the description of the non-linear relationship between changes in emissions and the formation of secondary pollutants (e.g. secondary particles, ground-level ozone). This is a consequence of the linear simplification that was used to construct AERIS, as opposed to the deterministic formulation that is contained in SERCA and is basically composed of the WRF-CMAQ ensemble. The comparison also suggested differences in the ability to reproduce seasonal variations of pollutants, something which is a consequence of the annual character of AERIS. However, AERIS is able to reproduce its parent air quality model (SERCA) and complies with the general modelling performance requirements stipulated under FAIRMODE. Moreover, its simplified approach, as evidenced by the values of the potencies allows identifying the interactions between emissions and concentrations, facilitating choosing mitigation measures depending on the abatement needs. Additionally, the ability of AERIS to reproduce ambient concentrations under a simplified approach makes it a robust alternative to SERCA for informing policy making and planning in Spain

A Correction Method for Use in Multidimensional Time-Splitting Advection Algorithms: Application to Two- and Three-Dimensional Transport

Meteorological and air quality models rely on accurately solving the advection equation in two and three dimensions. While a number of methods have been developed, all suffer from the formation and growth of errors during the solution procedure. Here, a correction method is developed and applied to the piecewise parabolic method for use in multidimensional modeling. This method is a time-split, alternating direction method with a flux correction to account for diagonal advection. The correction removes over- and undershooting while maintaining the method’s accuracy. The analysis also indicates that some methods will have errors that grow significantly in time, while the corrections developed minimize the problem. This analysis found that the buildup of errors was more pronounced in three-dimensional tests, suggesting that this is an import evaluation criteria for other advection algorithms as well