Abstract

Abstract. Fossil-fuel (FF) burning releases carbon dioxide (CO2) together with many other chemical species, some of which, such as nitrogen dioxide (NO2) and carbon monoxide (CO), are routinely monitored from space. This study examines the feasibility of estimation of FF CO2 emissions from large industrial regions by using NO2 and CO column retrievals from satellite measurements in combination with simulations by a mesoscale chemistry transport model (CTM). To this end, an inverse modeling method is developed that allows estimating FF CO2 emissions from different sectors of the economy, as well as the total CO2 emissions, in a given region. The key steps of the method are (1) inferring "top-down" estimates of the regional budget of anthropogenic NOx and CO emissions from satellite measurements of proxy species (NO2 and CO in the case considered) without using formal a priori constraints on these budgets, (2) the application of emission factors (the NOx-to-CO2 and CO-to-CO2 emission ratios in each sector) that relate FF CO2 emissions to the proxy species emissions and are evaluated by using data of "bottom-up" emission inventories, and (3) cross-validation and optimal combination of the estimates of CO2 emission budgets derived from measurements of the different proxy species. Uncertainties in the top-down estimates of the NOx and CO emissions are evaluated and systematic differences between the measured and simulated data are taken into account by using original robust techniques validated with synthetic data. To examine the potential of the method, it was applied to the budget of emissions for a western European region including 12 countries by using NO2 and CO column amounts retrieved from, respectively, the OMI and IASI satellite measurements and simulated by the CHIMERE mesoscale CTM, along with the emission conversion factors based on the EDGAR v4.2 emission inventory. The analysis was focused on evaluation of the uncertainty levels for the top-down NOx and CO emission estimates and "hybrid" estimates (that is, those based on both atmospheric measurements of a given proxy species and respective bottom-up emission inventory data) of FF CO2 emissions, as well as on examining consistency between the FF NO2 emission estimates derived from measurements of the different proxy species. It is found that NO2 measurements can provide much stronger constraints to the total annual FF CO2 emissions in the study region than CO measurements, the accuracy of the NO2-measurement-based CO2 emission estimate being mostly limited by the uncertainty in the top-down NOx emission estimate. Nonetheless, CO measurements are also found to be useful as they provide additional constraints to CO2 emissions and enable evaluation of the hybrid FF CO2 emission estimates obtained from NO2 measurements. Our most reliable estimate for the total annual FF CO2 emissions in the study region in 2008 (2.71 ± 0.30 Pg CO2) is found to be about 11 and 5 % lower than the respective estimates based on the EDGAR v.4.2 (3.03 Pg CO2) and CDIAC (2.86 Pg CO2) emission inventories, with the difference between our estimate and the CDIAC inventory data not being statistically significant. In general, the results of this study indicate that the proposed method has the potential to become a useful tool for identification of possible biases and/or inconsistencies in the bottom-up emission inventory data regarding CO2, NOx, and CO emissions from fossil-fuel burning in different regions of the world.

Highlights

  • Carbon dioxide (CO2) is commonly recognized as the major greenhouse gas providing the driving force of recent and future climate change (IPCC, 2013)

  • The results are reported for the two estimation cases that involve different seasonal variations of anthropogenic emissions in the model

  • We examined feasibility of estimation of FF CO2 emissions by using NO2 and carbon monoxide (CO) column retrievals from satellite measurements

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Summary

Introduction

Carbon dioxide (CO2) is commonly recognized as the major greenhouse gas providing the driving force of recent and future climate change (IPCC, 2013). Over the past few decades a lot of effort has been put into the compilation of global (e.g., Olivier et al, 2005; GCP, 2010; Ciais et al, 2010a; Janssens-Maenhout et al, 2015) as well as regional (Gurney et al, 2009; Huang et al, 2011; Kurokawa et al, 2013; Zhao et al, 2012; Wang et al, 2013) inventories of CO2 emissions from FF burning and other smaller anthropogenic sources (such as biofuel burning and cement production) Those emission inventories are based on available statistical information regarding economic activities and corresponding technologies. Note that the estimation of uncertainty in emission inventory data is itself a challenging task: in particular, as different inventories are usually based (at least partly) on common sources of information, their intercomparison does not necessarily result in revealing all the uncertainties

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