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Published April 4, 2018 | Published
Journal Article Open

Modelling carbonaceous aerosol from residential solid fuel burning with different assumptions for emissions

Abstract

Evidence is accumulating that emissions of primary particulate matter (PM) from residential wood and coal combustion in the UK may be underestimated and/or spatially misclassified. In this study, different assumptions for the spatial distribution and total emission of PM from solid fuel (wood and coal) burning in the UK were tested using an atmospheric chemical transport model. Modelled concentrations of the PM components were compared with measurements from aerosol mass spectrometers at four sites in central and Greater London (ClearfLo campaign, 2012), as well as with measurements from the UK black carbon network. The two main alternative emission scenarios modelled were Base4x and combRedist. For Base4x, officially reported PM_(2.5) from the residential and other non-industrial combustion source sector were increased by a factor of four. For the combRedist experiment, half of the baseline emissions from this same source were redistributed by residential population density to simulate the effect of allocating some emissions to the smoke control areas (that are assumed in the national inventory to have no emissions from this source). The Base4x scenario yielded better daily and hourly correlations with measurements than the combRedist scenario for year-long comparisons of the solid fuel organic aerosol (SFOA) component at the two London sites. However, the latter scenario better captured mean measured concentrations across all four sites. A third experiment, Redist – all emissions redistributed linearly to population density, is also presented as an indicator of the maximum concentrations an assumption like this could yield. The modelled elemental carbon (EC) concentrations derived from the combRedist experiments also compared well with seasonal average concentrations of black carbon observed across the network of UK sites. Together, the two model scenario simulations of SFOA and EC suggest both that residential solid fuel emissions may be higher than inventory estimates and that the spatial distribution of residential solid fuel burning emissions, particularly in smoke control areas, needs re-evaluation. The model results also suggest the assumed temporal profiles for residential emissions may require review to place greater emphasis on evening (including discretionary) solid fuel burning.

Additional Information

© Author(s) 2018. This work is distributed under the Creative Commons Attribution 4.0 License. Received: 19 Jun 2017 – Discussion started: 25 Aug 2017. Revised: 24 Feb 2018 – Accepted: 28 Feb 2018 – Published: 04 Apr 2018. The authors acknowledge the UK Department for Environment, Food and Rural Affairs (Defra) and the Devolved Administrations for funding aspects of the development of the EMEP4UK model (AQ0727), for partial support regarding the aerosol measurements, as well as access to the AURN data, which were obtained from uk-air.defra.gov.uk and are subject to Crown 2014 copyright, Defra, licensed under the Open Government Licence (OGL). Partial support for the EMEP4UK modelling from the European Commission FP7 ECLAIRE project is gratefully acknowledged. This work was supported in part by the UK Natural Environment Research Council (NERC) ClearfLo project (grant ref. NE/H003169/1). Riinu Ots was supported by a PhD studentship (University of Edinburgh and NERC-CEH contract 587/NEC03805). Dominique E. Young was supported by a NERC PhD studentship (ref. NE/I528142/1). Lu Xu, Leah R. Williams, Scott C. Herndon, and Nga L. Ng acknowledge support from US Department of Energy (grant no. DE-SC000602). NCAR command language (NCL) was used to produce the maps (NCAR, 2015), and R, openair and ggplot2 for the analysis and all other plots (R Core Team, 2016; Carslaw and Ropkins, 2012; Wickham, 2009). Edited by: Michael Schulz Reviewed by: three anonymous referees Code availability. The EMEP model is open-source and can be downloaded from www.emep.int. The WRF model is opensource. The authors declare that they have no conflict of interest. and can be downloaded from https://www.mmm.ucar.edu/ weather-research-and-forecasting-model. Data availability. Processed measurement data used in this study are available through the ClearfLo project archive at the British Atmospheric Data Centre (http://badc.nerc.ac.uk/browse/ badc/clearflo). The model data (input, scripts, relevant output) are archived at the University of Edinburgh and are available on request.

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Created:
August 19, 2023
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October 18, 2023