Origin, variability and age of biomass burning plumes intercepted during BORTAS-B

Abstract

Abstract.We use the GEOS-Chem atmospheric chemistry transport model to interpret aircraft measurements of carbon monoxide (CO) in biomass burning outflow taken during the 2011 BORTAS-B campaign over eastern Canada. The model has some skill reproducing the observed variability, with a Spearman's rank correlation r s = 0.65, but has a positive negative bias for observations <100 ppb and a negative bias for observations > 300 ppb. We find that observed CO variations are largely due to fires over Ontario, as expected, with smaller and less variable contributions from fossil fuel combustion from eastern Asia and NE North America. To help interpret observed variations of CO we develop a Eulerian effective physical age of emissions (Ā) metric, accounting for mixing and chemical decay, which we apply to pyrogenic emissions of CO. We find that during BORTAS-B the age of emissions intercepted over Halifax, Nova Scotia is typically 4-11 days, and on occasion as young as two days. We show thatĀ is typically 1-5 days older than the associated photochemical ages inferred from co-located measurements of different hydrocarbons. We find that the frequency distribution of differences between the age measures ( τ ) in plumes (defined by CH 3 CN > 150 ppt) peaks at 3 days. This corresponds to a chemical retardation of 50 %. We find a strong relationship in biomass burning plumes betweenĀ and τ (r 2 = 0.80), which is not present outwith these plumes (r 2 = 0.28). We argue that these observed relationships, together with a robust observed relationship between CO and black carbon aerosol during BORTAS-B (r 2 > 0.7), form the basis of indirect evidence that aerosols co-emitted with gases during pyrolysis markedly slowed down the plume photochemistry during BORTAS-B with respect to photochemistry at the same latitude and altitude in clear skies.

Summertime tropospheric ozone enhancement associated with a cold front passage due to stratosphere‐to‐troposphere transport and biomass burning: Simultaneous ground‐based lidar and airborne measurements

“…CH 3 CN is a good tracer for biomass burning [ de Gouw et al, ] due to its long lifetime, about 5 months [ Hamm and Warneck , ], and lack of production in the urban plume [ Holzinger et al, ]. The air with CH 3 CN > 150 pptv can be defined as BB plume [ Finch et al, ]. For this flight, neither the peak CH 3 CN (200 pptv) or peak CO (128 ppbv) was very high, probably because of dilution during transport for aged BB smoke.…”

Quantifying the vertical transport of CHBr&lt;sub&gt;3&lt;/sub&gt; and CH&lt;sub&gt;2&lt;/sub&gt;Br&lt;sub&gt;2&lt;/sub&gt; over the western Pacific

“…Model estimates range between 2 and 7 ppt for this contribution (Aschmann et al, 2009;Hossaini et al, 2010;Liang et al, 2010;Ordóñez et al, 2012;Fernandez et al, 2014). This contribution mainly originates from areas of deep convection over the tropical Indian ocean, over the western Pacific, and off the Pacific coast of Mexico Fueglistaler et al, 2004;Aschmann et al, 2009;Ashfold et al, 2012;Hossaini et al, 2012). The stratospheric community has categorized two methods of delivering VSLSs to the stratosphere: (1) source gas injection (SGI), which describes the direct transport of the emitted halogenated compounds (e.g.…”

Biomass burning at Cape Grim: exploring photochemistry using multi-scale modelling

“…TAPM-CTM was used to estimate the physical age of air parcels reaching Cape Grim over the 2-week period of the Robbins Island fire. The method is similar to the Eulerian effective physical age of emission metric, accounting for mix-ing and chemical decay from Finch et al (2014) and has been previously described in Keywood et al (2015). Briefly, two model simulations were run for scenarios that included all sources of nitric oxide (NO) in Australia; the first treated NO as an unreactive tracer, the second with NO decaying at a constant first-order rate.…”

“…In Australia, BB from wild and prescribed fires impacts air quality in both rural and urban areas (Keywood et al, 2015(Keywood et al, , 2011aReisen et al, 2011;Luhar et al, 2008) as well as indoor air quality (Reisen et al, 2011). More generally, as human population density increases, and as wildfires become more frequent (Flannigan et al, 2009;Keywood et al, 2011b), assessing the impact of BB on air quality and human health becomes more urgent (Keywood et al, 2011b;Reisen et al, 2015). In particular, particles emitted from BB frequently lead to exceedances of air quality standards, and exposure to BB particles has been linked to poor health outcomes including respiratory effects, cardiovascular disease and mortality (Reisen et al, 2015;Reid et al, 2016;Dennekamp et al, 2015).…”