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Changes in climate and land-use have significantly increased both the frequency and intensity of wildland fires globally, exacerbating the potential for hazardous impacts on human health. A better understanding of particle exposure concentrations and scenarios is crucial for developing mitigation strategies to reduce the health risks. Here, PM2.5 and black carbon (BC) concentrations were monitored during wildland fires between 2022 and 2024, in fire-prone areas in Catalonia (NE Spain), by means of personal monitors (AirBeam2 and Micro-aethalometers AE51 and MA200). Results revealed that exposures to combustion aerosols (PM2.5 and BC) were significant and comparable during wildfires and prescribed burns (mean PM2.5 during wildfires = 152 μg/m3 vs. 110-145 μg/m3 for prescribed burns). Overall, BC/PM2.5 ratios showed a large variability as a function of the monitoring scenario, indicating varying contributions from mineral aerosols to the emissions mix originating from fire management and extinction tasks. Specifically, mop-up tasks (final extinction tasks involving stirring top soil using handheld tools) were identified as a significant contributor to PM2.5 exposures, with 1-min PM2.5 peak concentrations reaching up to 1190 μg/m3. These results may be especially valuable for emissions modelling. Source apportionment of multi-wavelength BC datasets provided deeper insights into emissions and their impact on exposure profiles: line operators (who control the fire perimeter) were predominantly exposed to biomass burning smoke BCbb (61%) when compared to BC from fossil-fuel combustion (BCff = 39%), while torchers (in charge of initiating technical fires using fossil-fuel drip-torches) were predominantly exposed to BCff (77% vs. 23% BCbb). These findings highlight the value of portable monitors in the assessment of wildfire emissions and impacts on human exposure and environment. The combination of these tools, reporting data in real-time and with high time-resolution, is key to the design and implementation of effective mitigation strategies for environmental and health concerns related to wildland fires.
Aerosols, Air Pollutants, Environmental Exposure, Aethalometer model, http://metadata.un.org/sdg/3, http://metadata.un.org/sdg/9, Fires, Wildfires, Black carbon, Make cities and human settlements inclusive, safe, resilient and sustainable, Build resilient infrastructure, promote inclusive and sustainable industrialization and foster innovation, Soot, Spain, Humans, Particulate Matter, Wildland fire, http://metadata.un.org/sdg/11, Ångström absorption exponent, Delta-C, Ensure healthy lives and promote well-being for all at all ages, Environmental Monitoring
Aerosols, Air Pollutants, Environmental Exposure, Aethalometer model, http://metadata.un.org/sdg/3, http://metadata.un.org/sdg/9, Fires, Wildfires, Black carbon, Make cities and human settlements inclusive, safe, resilient and sustainable, Build resilient infrastructure, promote inclusive and sustainable industrialization and foster innovation, Soot, Spain, Humans, Particulate Matter, Wildland fire, http://metadata.un.org/sdg/11, Ångström absorption exponent, Delta-C, Ensure healthy lives and promote well-being for all at all ages, Environmental Monitoring
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 7 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
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