Stable carbon isotopic composition of biomass burning emissions - implications for estimating the contribution of C-3 and C-4 plants

Landscape fires are a significant contributor to atmospheric burdens of greenhouse gases and aerosols. Although many studies have looked at biomass burning products and their fate in the atmosphere, estimating and tracing atmospheric pollution from landscape fires based on atmospheric measurements are challenging due to the large variability in fuel composition and burning conditions. Stable carbon isotopes in biomass burning (BB) emissions can be used to trace the contribution of C-3 plants (e.g. trees or shrubs) and C-4 plants (e.g. savanna grasses) to various combustion products. However, there are still many uncertainties regarding changes in isotopic composition (also known as fractionation) of the emitted carbon compared to the burnt fuel during the pyrolysis and combustion processes. To study BB isotope fractionation, we performed a series of laboratory fire experiments in which we burned pure C-3 and C-4 plants as well as mixtures of the two. Using isotope ratio mass spectrometry (IRMS), we measured stable carbon isotope signatures in the pre-fire fuels and post-fire residual char, as well as in the CO2, CO, CH4, organic carbon (OC), and elemental carbon (EC) emissions, which together constitute over 98 % of the post-fire carbon. Our laboratory tests indicated substantial isotopic fractionation in combustion products compared to the fuel, which varied between the measured fire products. CO2, EC, and residual char were the most reliable tracers of the fuel C-13 signature. CO in particular showed a distinct dependence on burning conditions; flaming emissions were enriched in C-13 compared to smouldering combustion emissions. For CH4 and( )OC, the fractionation was the other way round for C3 emissions (C-13-enriched) and C-4 emissions (C-13-depleted). This indicates that while it is possible to distinguish between fires that were dominated by either C-3 or C-4 fuels using these tracers, it is more complicated to quantify their relative contribution to a mixed-fuel fire based on the delta C-13 signature of emissions. Besides laboratory experiments, we sampled gases and carbonaceous aerosols from prescribed fires in the Niassa Special Reserve (NSR) in Mozambique, using an unmanned aerial system (UAS)-mounted sampling set-up. We also provided a range of C-3:C-4 contributions to the fuel and measured the fuel isotopic signatures. While both OC and EC were useful tracers of the C-3-to-C-4 fuel ratio in mixed fires in the lab, we found particularly OC to be depleted compared to the calculated fuel signal in the field experiments. This suggests that either our fuel measurements were incomprehensive and underestimated the C-3:C-4 ratio in the field or other processes caused this depletion. Although additional field measurements are needed, our results indicate that C-3-vs.-C-4 source ratio estimation is possible with most BB products, albeit with varying uncertainty ranges

Stable carbon isotopic composition of biomass burning emissions – implications for estimating the contribution of C3 and C4 plants

Landscape fires are a significant contributor to atmospheric burdens of greenhouse gases and aerosols. Although many studies have looked at biomass burning products and their fate in the atmosphere, estimating and tracing atmospheric pollution from landscape fires based on atmospheric measurements are challenging due to the large variability in fuel composition and burning conditions. Stable carbon isotopes in biomass burning (BB) emissions can be used to trace the contribution of C3 plants (e.g. trees or shrubs) and C4 plants (e.g. savanna grasses) to various combustion products. However, there are still many uncertainties regarding changes in isotopic composition (also known as fractionation) of the emitted carbon compared to the burnt fuel during the pyrolysis and combustion processes. To study BB isotope fractionation, we performed a series of laboratory fire experiments in which we burned pure C3 and C4 plants as well as mixtures of the two. Using isotope ratio mass spectrometry (IRMS), we measured stable carbon isotope signatures in the pre-fire fuels and post-fire residual char, as well as in the CO2, CO, CH4, organic carbon (OC), and elemental carbon (EC) emissions, which together constitute over 98 % of the post-fire carbon. Our laboratory tests indicated substantial isotopic fractionation in combustion products compared to the fuel, which varied between the measured fire products. CO2, EC, and residual char were the most reliable tracers of the fuel 13C signature. CO in particular showed a distinct dependence on burning conditions; flaming emissions were enriched in 13C compared to smouldering combustion emissions. For CH4 and OC, the fractionation was the other way round for C3 emissions (13C-enriched) and C4 emissions (13C-depleted). This indicates that while it is possible to distinguish between fires that were dominated by either C3 or C4 fuels using these tracers, it is more complicated to quantify their relative contribution to a mixed-fuel fire based on the δ13C signature of emissions. Besides laboratory experiments, we sampled gases and carbonaceous aerosols from prescribed fires in the Niassa Special Reserve (NSR) in Mozambique, using an unmanned aerial system (UAS)-mounted sampling set-up. We also provided a range of C3 : C4 contributions to the fuel and measured the fuel isotopic signatures. While both OC and EC were useful tracers of the C3-to-C4 fuel ratio in mixed fires in the lab, we found particularly OC to be depleted compared to the calculated fuel signal in the field experiments. This suggests that either our fuel measurements were incomprehensive and underestimated the C3 : C4 ratio in the field or other processes caused this depletion. Although additional field measurements are needed, our results indicate that C3-vs.-C4 source ratio estimation is possible with most BB products, albeit with varying uncertainty ranges

Passenger exposure to aerosols on intra-European train travel

Knowledge about personal aerosol exposure in different environments is fundamental for individual and common decision-making, shaping the way we build our infrastructure or change our social behaviours. Aerosols are a leading cause of death and well-known vector for infectious diseases. Yet, passenger exposure to aerosols during long-distance train travel is surprisingly underexplored. Two small, light-weight personal monitoring instruments were employed during a train journey across Europe, to measure the fine particle (PM2.5) and equivalent black carbon (eBC) passenger exposure, respectively. The journey was divided into three legs, inside three different trains, and two layovers in city environments. Highest mean concentrations of PM2.5 and eBC were found within the oldest train type, and revealed PM2.5 concentrations of 58.4 ± 12.7 μg m−3 and eBC of 5.4 ± 2.9 μg m−3. The more modern the train system was, the lower the measured concentrations were to be found. In the newest tested system, the air quality was considerably better inside the train than outdoor air measured by a monitoring network, or simulated by the Copernicus Atmosphere Monitoring Service (CAMS) model ensemble analysis. The mean PM2.5 concentration was roughly 20% lower inside the train than the outdoor air simulated by CAMS. Both the light-weight personal monitoring and the monitoring network indicate that the CAMS ensemble substantially underestimates PM2.5 concentrations for the day of the journey. Effective ventilation and air filtration significantly decrease the passenger’s aerosol exposure, as compared to a stay in outdoor air, leading to a small statistical increase in life expectancy. If this could also reduce the risk of contagion with an infectious disease remains to be explored

Passenger exposure to aerosols on intra-European train travel

Knowledge about personal aerosol exposure in different environments is fundamental for individual and common decision-making, shaping the way we build our infrastructure or change our social behaviours. Aerosols are a leading cause of death and well-known vector for infectious diseases. Yet, passenger exposure to aerosols during long-distance train travel is surprisingly underexplored. Two small, light-weight personal monitoring instruments were employed during a train journey across Europe, to measure the fine particle (PM2.5) and equivalent black carbon (eBC) passenger exposure, respectively. The journey was divided into three legs, inside three different trains, and two layovers in city environments. Highest mean concentrations of PM2.5 and eBC were found within the oldest train type, and revealed PM2.5 concentrations of 58.4 +/- 12.7 mu g m(-3) and eBC of 5.4 +/- 2.9 mu g m(-3). The more modern the train system was, the lower the measured concentrations were to be found. In the newest tested system, the air quality was considerably better inside the train than outdoor air measured by a monitoring network, or simulated by the Copernicus Atmosphere Monitoring Service (CAMS) model ensemble analysis. The mean PM2.5 concentration was roughly 20% lower inside the train than the outdoor air simulated by CAMS. Both the light-weight personal monitoring and the monitoring network indicate that the CAMS ensemble substantially underestimates PM2.5 concentrations for the day of the journey. Effective ventilation and air filtration significantly decrease the passenger's aerosol exposure, as compared to a stay in outdoor air, leading to a small statistical increase in life expectancy. If this could also reduce the risk of contagion with an infectious disease remains to be explored.ISSN:1873-9318ISSN:1873-932

Isotope-based source apportionment of black carbon aerosols in the Eurasian Arctic

Aerosols change the Earth's energy balance. Black carbon (BC) aerosols are a product of incomplete combustion of fossil fuels and biomass burning and cause a net warming through aerosol radiation interactions (ari) and aerosol cloud interactions (aci). BC aerosols have potentially strong implications on the Arctic climate, yet the net global climate effect of BC is very uncertain. Best estimates assume a net warming effect, roughly half to that of CO2. However, the time scales during which CO2 emissions affect the global climate are on the order of hundreds of years, while BC is a short-lived climate pollutant (SLCP) with atmospheric life times of days to weeks. Climate models or atmospheric transport models struggle to emulate the seasonality and amplitude of BC concentrations in the Arctic, which are low in summer and high in winter/spring during the so called Arctic haze season. The high uncertainties regarding BC's climate impact are not only related to ari and aci, but also due to model parameterizations of BC lifetime and transport, and the highly uncertain estimates of global and regional BC emissions. Given the high uncertainties in technology-based emission inventories (EI), there is a need for an observation-based assessment of sources of BC in the atmosphere. We study short-term and long-term observations of elemental carbon (EC), the mass-based analog of optically-defined BC. EC aerosol concentrations and carbon-isotope-based (δ13C and ∆14C) sources were constrained (top-down) for three Arctic receptor sites in Abisko (northern Sweden), Tiksi (East Siberian Russia), and Zeppelin (on Svalbard, Norway). The radiocarbon (∆14C) signature allows to draw conclusion on the EC sources (fossil fuels vs. biomass burning) with high accuracy (&lt;5% variation). Stable carbon isotopic fingerprints (δ13C) give qualitative information of the consumed fuel type, i.e. coal, C3-plants (wood), liquid fossil fuels (diesel) or gas flaring (methane and non-methane hydrocarbons). These fingerprints can be used in conjunction with Bayesian statistics, to estimate quantitative source contributions of the sources. Finally, our observations were compared to predictions from a state of the art atmospheric transport model (coupled to BC emissions), conducted by our collaborators at NILU (Norwegian Institute for Air Research). Observed BC concentrations showed a high seasonality throughout the year, with elevated concentrations in the winter, at all sites. The highest concentrations were measured on Svalbard during a short campaign (Jan-Mar 2009) focusing on BC pollution events. Long-term observations showed that Svalbard (2013) had overall the lowest annual BC concentrations, followed by Abisko (2012) and Tiksi (2013). Isotope constraints on BC combustion sources exhibited a high seasonality and big amplitude all across the Eurasian Arctic. Uniform seasonal trends were observed in all three year-round studies, showing fractions of biomass burning of 60-70% in summer and 10-40% in winter. Europe was the major source region (&gt;80%) for BC emissions arriving at Abisko and the main sources were liquid fossil fuels and biomass burning (wood). The model agreed very well with the Abisko observations, showing good model skill and relatively well constrained sources in the European regions of the EI. However, for the Svalbard and East Siberian Arctic observatories the model-observation agreement was not as good. Here, Russia, Europe and China were the major contributors to the mostly liquid fossil and biomass burning BC emissions. This showed that the EI still needs to be improved, especially in regions where emissions are high but observations are scarce (low ratio of observations to emitted pollutant quantity). Strategies for BC mitigation in the (Eurasian) Arctic are probably most efficient, if fossil fuel (diesel) emissions are tackled during winter and spring periods, all across Eurasia.At the time of the doctoral defense, the following papers were unpublished and had a status as follows: Paper 2: Manuscript. Paper 3: Manuscript.</p

Isotope-Based Source Apportionment of EC Aerosol Particles during Winter High-Pollution Events at the Zeppelin Observatory, Svalbard

Black carbon (BC) aerosol particles contribute to climate warming of the Arctic, yet both the sources and the source-related effects are currently poorly constrained. Bottom-up emission inventory (EI) approaches are challenged for BC in general and the Arctic in particular. For example, estimates from three different EI models on the fractional contribution to BC from biomass burning (north of 60° N) vary between 11% and 68%, each acknowledging large uncertainties. Here we present the first dual-carbon isotope-based (Δ¹⁴C and δ¹³C) source apportionment of elemental carbon (EC), the mass-based correspondent to optically defined BC, in the Arctic atmosphere. It targeted 14 high-loading and high-pollution events during January through March of 2009 at the Zeppelin Observatory (79° N; Svalbard, Norway), with these representing one-third of the total sampling period that was yet responsible for three-quarters of the total EC loading. The top-down source-diagnostic ¹⁴C fingerprint constrained that 52 ± 15% (<i>n</i> = 12) of the EC stemmed from biomass burning. Including also two samples with 95% and 98% biomass contribution yield 57 ± 21% of EC from biomass burning. Significant variability in the stable carbon isotope signature indicated temporally shifting emissions between different fossil sources, likely including liquid fossil and gas flaring. Improved source constraints of Arctic BC both aids better understanding of effects and guides policy actions to mitigate emissions

An Unmanned Aerial System (UAS) based methodology for measuring biomass burning emission factors

Biomass burning (BB) emits large quantities of greenhouse gases (GHG) and aerosols that impact climate and adversely affect human health. Although much research has focused on quantifying BB emissions on regional to global scales, field measurements of BB emission factors (EFs) are sparse, clustered and indicate high spatio-temporal variability. EFs are generally calculated from ground- or aeroplane measurements with respective potential biases towards smouldering or flaming combustion products. Unmanned aerial systems (UAS) have the potential to measure BB EFs in fresh smoke, targeting different parts of the plume at relatively low cost. We propose a light-weight UAS-based method to measure EFs for carbon monoxide (CO), carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O), as well as PM2.5 (TSI Sidepak AM520) and equivalent black carbon (eBC, microAeth AE51) using a combination of a sampling system with Tedlar bags which can be analysed on the ground and airborne aerosol sensors. In this study, we address the main uncertainties associated with this approach (1) the degree to which taking a limited number of samples is representative for the integral smoke plume and including (2) the reliability of the lightweight aerosol sensors. This was done for prescribed burning experiments in the Kruger national park, South Africa where we compared fire-averaged EF from UAS-sampled bags for savanna fires to integrated EFs from co-located mast measurements. Both measurements matched reasonably well with linear R2 ranging from 0.81 to 0.94. Both aerosol sensors are not factory calibrated for BB particles and therefore require additional calibration. In a series of smoke chamber experiments, we compared the lightweight sensors to high-fidelity equipment to empirically determine specific calibration factors (CF) for measuring BB particles. For the PM mass concentration from a TSI Sidepak AM520, we found an optimal CF of 0.27, using a scanning mobility particle sizer and gravimetric reference methods, albeit that the CF varied for different vegetation fuel types. Measurements of eBC from the Aethlabs AE51 aethalometer agreed well with the multi-wavelength aethalometer (AE33) (linear R2 of 0.95 at λ = 880 nm) and the wavelength corrected Multi-Angle Absorption Photometer (MAAP, R2 0.83 measuring at λ = 637 nm). However, the high variability in observed BB mass absorption cross-section (MAC) values (5.2 ± 5.1 m2 g-1) suggested re-calibration may be required for individual fires. Overall, our results indicate that the proposed UAS setup can obtain representative BB EFs for individual savanna fires if proper correction factors are applied and operating limitations are well understood

A quadcopter unmanned aerial system (UAS)-based methodology for measuring biomass burning emission factors

Biomass burning (BB) emits large quantities of greenhouse gases (GHG) and aerosols that impact the climate and adversely affect human health. Although much research has focused on quantifying BB emissions on regional to global scales, field measurements of BB emission factors (EFs) are sparse, clustered and indicate high spatio-temporal variability. EFs are generally calculated from ground or aeroplane measurements with respective potential biases towards smouldering or flaming combustion products. Unmanned aerial systems (UAS) have the potential to measure BB EFs in fresh smoke, targeting different parts of the plume at relatively low cost. We propose a light-weight UAS-based method to measure EFs for carbon monoxide (CO), carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O) as well as PM2.5 (TSI Sidepak AM520) and equivalent black carbon (eBC, microAeth AE51) using a combination of a sampling system with Tedlar bags which can be analysed on the ground and with airborne aerosol sensors. In this study, we address the main challenges associated with this approach: (1) the degree to which a limited number of samples is representative for the integral smoke plume and (2) the performance of the lightweight aerosol sensors. While aerosol measurements can be made continuously in a UAS set-up thanks to the lightweight analysers, the representativeness of our Tedlar bag filling approach was tested during prescribed burning experiments in the Kruger National Park, South Africa. We compared fire-averaged EFs from UAS-sampled bags for savanna fires with integrated EFs from co-located mast measurements. Both measurements matched reasonably well with linear R2 ranging from 0.81 to 0.94. Both aerosol sensors are not factory calibrated for BB particles and therefore require additional calibration. In a series of smoke chamber experiments, we compared the lightweight sensors with high-fidelity equipment to empirically determine specific calibration factors (CF) for measuring BB particles. For the PM mass concentration from a TSI Sidepak AM520, we found an optimal CF of 0.27, using a scanning mobility particle sizer and gravimetric reference methods, although the CF varied for different vegetation fuel types. Measurements of eBC from the Aethlabs AE51 aethalometer agreed well with the multi-wavelength aethalometer (AE33) (linear R2 of 0.95 at λ=880 nm) and the wavelength corrected multi-angle absorption photometer (MAAP, R2 of 0.83 measuring at λ=637 nm). However, the high variability in observed BB mass absorption cross-section (MAC) values (5.2±5.1 m2 g−1) suggested re-calibration may be required for individual fires. Overall, our results indicate that the proposed UAS set-up can obtain representative BB EFs for individual savanna fires if proper correction factors are applied and operating limitations are well understood

Measuring Dielectric and Electro-optic Responses of Thin Films using Plasmonic Devices

ISSN:1094-408