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Atmospheric Chemistry and Physics An interactive open-access journal of the European Geosciences Union
https://doi.org/10.5194/acp-2017-431
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
Research article
12 Jun 2017
Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Atmospheric Chemistry and Physics (ACP).
A multi-model approach to monitor emissions of CO2 and CO from an urban-industrial complex
Ingrid Super1,2, Hugo A. C. Denier van der Gon2, Michiel K. van der Molen1, Hendrika A. M. Sterk3, Arjan Hensen4, and Wouter Peters1,5 1Meteorology and Air Quality Group, Wageningen University, P.O. Box 47, 6700 AA Wageningen, Netherlands
2Department of Climate, Air and Sustainability, TNO, P.O. Box 80015, 3508 TA Utrecht, Netherlands
3National Institute for Public Health and the Environment, P.O. Box 1, 3720 BA Bilthoven, Netherlands
4Energy Research Centre of the Netherlands, P.O. Box 1, 1755 ZG Petten, Netherlands
5Centre for Isotope Research, Energy and Sustainability Research Institute Groningen, University of Groningen, Nijenborgh 4, 9747 AG Groningen, Netherlands
Abstract. Monitoring urban-industrial emissions is often challenging, because observations are scarce and regional atmospheric transport models are too coarse to represent the high spatiotemporal variability in the resulting concentrations. In this paper we apply a new combination of a Eulerian model (WRF with chemistry) and a Gaussian plume model (OPS). The modelled mixing ratios are compared to observed CO2 and CO mole fractions at four sites along a transect from an urban-industrial complex (Rotterdam, Netherlands) towards rural conditions for October–December 2014. Urban plumes are well-mixed at our semi-urban location, making this location suited for an integrated emission estimate over the whole study area. The signals at our urban measurement site (with average enhancements of 11 ppm CO2 and 40 ppb CO over the baseline) are highly variable due to the presence of distinct source areas dominated by road traffic/residential heating emissions or industrial activities. This causes different emission signatures that are translated into a large variability in observed ΔCO : ΔCO2 ratios, which can be used to identify dominant source types. We find that WRF-Chem is able to represent synoptic variability in CO2 and CO (e.g. the median CO2 mixing ratio is 9.7 ppm (observed) against 8.7 ppm (modelled)) , but it fails to reproduce the hourly variability of daytime urban plumes at the urban site (R2 up to 0.05). For the urban site, a plume model should be added to the model framework to adequately represent plume transport especially from stack emissions. The explained variance in hourly, daytime CO2 enhancements from point source emissions increases from 30 % with WRF-Chem to 52 % with WRF-Chem in combination with the most detailed OPS simulation. The simulated variability in ΔCO : ΔCO2 ratios decreases drastically from 1.5 to 0.6 ppb ppm−1 which agrees better with the observed standard deviation of 0.4 ppb ppm−1. This is partly due to improved wind fields (increase in R2 of 0.10), but also due to improved point source representation (increase in R2 of 0.05) and dilution (increase in R2 of 0.07). Based on our analysis we conclude that a plume model with detailed and accurate dispersion parameters is inevitable for top-down monitoring of greenhouse gas emissions in urban environments with large point source contributions within a ~ 10 km radius from the observation sites.

Citation: Super, I., Denier van der Gon, H. A. C., van der Molen, M. K., Sterk, H. A. M., Hensen, A., and Peters, W.: A multi-model approach to monitor emissions of CO2 and CO from an urban-industrial complex, Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2017-431, in review, 2017.
Ingrid Super et al.
Ingrid Super et al.
Ingrid Super et al.

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