Abstract

<strong class="journal-contentHeaderColor">Abstract.</strong> Road traffic emits not only carbon dioxide (CO<span class="inline-formula"><sub>2</sub></span>) and particulate matter, but also other pollutants such as nitrogen oxides (NO<span class="inline-formula"><sub><i>x</i></sub></span>), volatile organic compounds (VOCs) and carbon monoxide (CO). These chemical species influence the atmospheric chemistry and produce ozone (O<span class="inline-formula"><sub>3</sub></span>) in the troposphere. Ozone acts as a greenhouse gas and thus contributes to anthropogenic global warming. Technological trends and political decisions can help to reduce the O<span class="inline-formula"><sub>3</sub></span> effect of road traffic emissions on climate. In order to assess the O<span class="inline-formula"><sub>3</sub></span> response of such mitigation options on climate, we developed a chemistry–climate response model called TransClim (Modelling the effect of surface <i>Trans</i>portation on <i>Clim</i>ate). The current version considers road traffic emissions of NO<span class="inline-formula"><sub><i>x</i></sub></span>, VOC and CO and determines the O<span class="inline-formula"><sub>3</sub></span> change and its corresponding stratosphere-adjusted radiative forcing. Using a tagging method, TransClim is further able to quantify the contribution of road traffic emissions to the O<span class="inline-formula"><sub>3</sub></span> concentration. Thus, TransClim determines the contribution to O<span class="inline-formula"><sub>3</sub></span> as well as the change in total tropospheric O<span class="inline-formula"><sub>3</sub></span> of a road traffic emission scenario. Both quantities are essential when assessing mitigation strategies. The response model is based on lookup tables which are generated by a set of emission variation simulations performed with the global chemistry–climate model EMAC (ECHAM5 v5.3.02, MESSy v2.53.0). Evaluating TransClim against independent EMAC simulations reveals low deviations of all considered species (0.01 %–10 %). Hence, TransClim is able to reproduce the results of an EMAC simulation very well. Moreover, TransClim is about 6000 times faster in computing the climate effect of an emission scenario than the complex chemistry–climate model. This makes TransClim a suitable tool to efficiently assess the climate effect of a broad range of mitigation options for road traffic or to analyse uncertainty ranges by employing Monte Carlo simulations.

Highlights

  • Ozone acts as a greenhouse gas and contributes to anthropogenic global warming

  • 90 The aim of TransClim is to assess the effect of road traffic emissions of nitrogen oxides (NOx), volatile organic compounds (VOC) and carbon monoxide (CO) on tropospheric O3 and its respective effect on climate

  • Each output variable has its own LUT. 120 To obtain the desired variable xnew for a given road traffic emission scenario, the corresponding emission scaling factors for each emission region i are used as input and the change ∆x(i) for each emission region is calculated by linearly interpolating within the respective LUT

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Summary

Introduction

Mobility is getting more and more important in today’s society. As residences, workplaces, schools and recreation areas are often spatially separated, there is an increasing demand on our transportation system. The perturbation method does not take non-linear relations, such as the tropospheric O3 chemistry, into account (Grewe et al, 2010) It quantifies only the impact of road traffic emissions on O3. Grewe et al (2010) propose to apply the so-called tagging method It follows the most important reaction pathways for the formation and destruction of O3 and determines the contribution of road traffic emissions to the O3 concentration. 60 Typically, complex chemistry-climate models are applied to assess the climate effect of traffic emissions These simulations are computational expensive and require a substantial amount of time. We developed a new tool called TransClim (Modelling the effect of surface Transportation on Climate) It is a chemistry-climate response model which efficiently determines the O3 effect of a broad range of road traffic emission scenarios on climate. Significant parts of the text already appeared in Rieger (2018)

Model idea
Requirements
Algorithm emission region 1 x – xref emission region 2 x – xref xnew x ref
Emission regions
Model description of EMAC
Setup of EMAC emission variation simulations sCO sVOC
Workflow of TransClim
Model evaluation
Comparison with equivalent EMAC simulation
Comparison with VEU1 simulations
Findings
390 7 Summary and conclusions
Full Text
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