Abstract

Abstract. Despite the developments in the global modelling of chemistry and of the parameterization of the physical processes, carbon monoxide (CO) concentrations remain underestimated during Northern Hemisphere (NH) winter by most state-of-the-art chemistry transport models. The consequential model bias can in principle originate from either an underestimation of CO sources or an overestimation of its sinks. We address both the role of surface sources and sinks with a series of MOZART (Model for Ozone And Related Tracers) model sensitivity studies for the year 2008 and compare our results to observational data from ground-based stations, satellite observations, and vertical profiles from measurements on passenger aircraft. In our base case simulation using MACCity (Monitoring Atmospheric Composition and Climate project) anthropogenic emissions, the near-surface CO mixing ratios are underestimated in the Northern Hemisphere by more than 20 ppb from December to April, with the largest bias of up to 75 ppb over Europe in January. An increase in global biomass burning or biogenic emissions of CO or volatile organic compounds (VOCs) is not able to reduce the annual course of the model bias and yields concentrations over the Southern Hemisphere which are too high. Raising global annual anthropogenic emissions with a simple scaling factor results in overestimations of surface mixing ratios in most regions all year round. Instead, our results indicate that anthropogenic CO and, possibly, VOC emissions in the MACCity inventory are too low for the industrialized countries only during winter and spring. Reasonable agreement with observations can only be achieved if the CO emissions are adjusted seasonally with regionally varying scaling factors. A part of the model bias could also be eliminated by exchanging the original resistance-type dry deposition scheme with a parameterization for CO uptake by oxidation from soil bacteria and microbes, which reduces the boreal winter dry deposition fluxes. The best match to surface observations, satellite retrievals, and aircraft observations was achieved when the modified dry deposition scheme was combined with increased wintertime road traffic emissions over Europe and North America (factors up to 4.5 and 2, respectively). One reason for the apparent underestimation of emissions may be an exaggerated downward trend in the Representative Concentration Pathway (RCP) 8.5 scenario in these regions between 2000 and 2010, as this scenario was used to extrapolate the MACCity emissions from their base year 2000. This factor is potentially amplified by a lack of knowledge about the seasonality of emissions. A methane lifetime of 9.7 yr for our basic model and 9.8 yr for the optimized simulation agrees well with current estimates of global OH, but we cannot fully exclude a potential effect from errors in the geographical and seasonal distribution of OH concentrations on the modelled CO.

Highlights

  • Carbon monoxide (CO) is a product of incomplete combustion and is produced from oxidation of volatile organic compounds (VOCs) in the atmosphere

  • First we compare our base case simulation (MI), using MACCity anthropogenic and natural emissions, to Global Atmospheric Watch (GAW) observations gathered from the World Data Centre for Greenhouse Gases (WDCGG) database

  • Surface CO mixing ratios as measured by GAW stations averaged over the Northern Hemisphere (NH) were underestimated by more than 20 ppb from December to April, with a maximal bias of 40 ppb in January www.atmos-chem-phys.net/14/9295/2014/

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Summary

Introduction

Carbon monoxide (CO) is a product of incomplete combustion and is produced from oxidation of volatile organic compounds (VOCs) in the atmosphere. With the growing availability of atmospheric CO observation data from surface and in situ observations as well as from satellites, a number of global model inversions have been performed to derive optimized CO sources from these observations (Bergamaschi et al, 2000; Pétron et al, 2002, 2004; Arellano et al, 2004, 2006; Müller and Stavrakou, 2005; Duncan et al, 2007; Pison et al, 2009; Kopacz et al, 2010; Fortems-Cheiney et al, 2011; Hooghiemstra et al, 2011, 2012; Miyazaki et al, 2012) Most of these studies found a significant underestimation of CO sources in their a priori estimates and assigned those to missing emissions in the current inventories.

MOZART
Surface boundary conditions
Surface station data
MOZAIC profiles
MOPITT atmospheric columns
IASI atmospheric columns
MOZART sensitivity simulations
MACCity emissions
Sensitivity to emissions
Sensitivity to dry deposition
Optimized approach
Conclusions
Full Text
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