Zachary C. J. Decker

Carbon closure and volatility studies are needed to better constrain atmospheric carbon, but are especially lacking in high altitude sites, as these environments can be challenging to access. During a measurement campaign from 16 August to 20 September 2022 at Jungfraujoch (3580 m.asl, Switzerland), gas- and particle phase carbon was characterized using a broad suite of instruments, including a thermo-denuder upstream of a time-of-flight aerosol chemical speciation monitor to investigate particulate organic carbon (pOC) volatility. As expected in summer, the Jungfraujoch was mainly under planetary boundary layer influence (PBLi), with some periods in the free troposphere (FT). Moreover, a Saharan dust event and two wildfire plumes were identified. The composition of fine particles was dominated by organic aerosol mass for all conditions, and particulate carbon measurements by different techniques captured similar temporal variability but showed systematic differences in absolute concentrations, especially at low concentrations. pOC was dominated by semi-volatile organic carbon, and a substantial part of OC could partition between gas and particle phase depending on pOC concentration and ambient conditions. PBLi conditions, compared to FT, showed higher concentrations of both gas and particle phase compounds, higher contribution of short-lived VOCs and higher pOC volatility. In addition, the wildfires affected OC concentrations and composition and exhibited higher pOC oxidation state and lower inferred pOC volatility, coinciding with high m/z organic fragment signals. These findings contribute to a better understanding of the impacts of local and regional sources, and long-range transported plumes on free tropospheric carbonaceous compounds’ concentrations and properties.

The age of smoke, meaning the time elapsed since it was produced in a fire, is an important parameter for interpreting measurements of evolving smoke composition. This study describes the smoke age estimates developed for large plumes sampled in the 2019 NASA-NOAA FIREX-AQ field experiment. Smoke ages are computed using two methods and applied to observations from two aircraft: the NASA DC-8 and NOAA Chemistry Twin Otter. The first method uses measurements of mean horizontal wind speed, as observed by the sampling aircraft, and distance to the fire to provide a single age estimate for each plume-crossing performed by the aircraft. While this “mean-wind method” uses accurate wind measurements, it can be systematically biased by assumptions that plume rise time is negligible and that winds are homogeneous horizontally and in time during the plume transport. Wind inhomogeneities due to terrain effects and day-to-night transition, among other factors, affected some plumes during FIREX-AQ. The mean-wind method therefore performs best for short-range transport over level terrain with steady winds. The second method relies on upwind air parcel trajectories and plume rise computed with multiple high-resolution meteorological datasets. This “trajectory-based method” quantifies age uncertainty from the meteorological ensemble, plume rise speed, wind speed errors, and fire location. The second method also resolves age differences from the center to edge of a transect. Still, it is susceptible to errors in the meteorological model. With careful comparison of the simulated trajectories to smoke transport observed from geostationary satellite imagery described here, we filter out many trajectory errors and improve the smoke age estimates. Across the two aircraft, the dataset provides ages for over 43 h (815 transects) of in situ measurements in smoke plumes from 115 different fires, with smoke ages ranging from 1 min to 40 h. The two age methods are strongly correlated ( R = 0.89) for the periods during FIREX-AQ when both ages are available. The mean-wind age is systematically 12 % younger than the trajectory-based age and the median absolute difference between them is 15 % (21 % for mean). The favorable agreement between the two age methods reflects that the mean-wind method was selectively applied to plumes with little wind variability. Trajectory-based ages are available for more of the FIREX-AQ smoke observations than the mean-wind ages. The median trajectory-based age uncertainty during FIREX-AQ is 24 % and the mean uncertainty is 37 %, due to a long-tailed distribution. The main source of age uncertainty is spread within the meteorological ensemble, followed by discrepancy between measured and modeled wind speed, then other factors like plume rise. The age uncertainty variable enables the user to identify periods with high or low confidence in the age estimate, thereby informing studies of smoke aging. Smoke ages data are available at https://doi.org/10.5067/ASDC/FIREXAQ_MetNav_ AircraftInSitu_DC8_Data_1 (Bennett et al., 2020) for the NASA DC-8 and https://doi.org/10.5067/ASDC/SUBORBITAL/ FIREXAQ_Analysis_N48_Data_1 (Holmes, 2021a) for the NOAA Chemistry Twin Otter.

Solar radiation modification (SRM) is a proposed temporary intervention to limit global warming while mitigation efforts continue. Understanding its potential consequences for human and natural systems is essential for informed deliberations. We conducted a systematic review of the peer-reviewed literature on SRM impacts published through May 2024, identifying 289 studies, including 261 primary articles and 28 reviews. Studies on the potential impacts of SRM on human systems (9%) and ecosystems (25%) were infrequent. Further, primary literature is dominated (97%) by global models and thus the SRM impacts that are most reported reflect the variables available from global models, such as global mean temperature, global mean precipitation, sea ice and net or gross primary production. Those studies that did report impacts on human systems or ecosystems typically relied on chained modeling frameworks using uncertain regional-scale climate outputs. While studies relying on such frameworks are informative for identifying model sensitivities and parameterization challenges, their results remain highly uncertain. Despite this, model studies constitute an increasing majority of SRM research on human and natural systems. In contrast, empirical research using SRM-analogous events (e.g., volcanic eruptions) was rare and is declining in relative frequency. Analog studies have informed model development, revealed sensitivities rarely examined in global models, and reduced reliance on modeling’s regional-scale compounding uncertainties. Our results indicate that a more integrated research strategy, one that combines climate modeling with analog studies and intermediate-scale modeling approaches, is needed to improve fidelity in assessing potential SRM impacts on human and natural systems.

The age of smoke, meaning the time elapsed since it was produced in a fire, is an important parameter for interpreting measurements of evolving smoke composition. This study describes the smoke age estimates developed for large plumes sampled in the 2019 NASA-NOAA FIREX-AQ field experiment. Smoke ages are computed using two methods and applied to observations from two aircraft: the NASA DC-8 and a NOAA Twin Otter. The first method uses measurements of mean horizontal wind speed, as observed by the sampling aircraft, and distance to the fire to provide a single age estimate for each plume-crossing performed by the aircraft. While this "mean-wind method" uses accurate wind measurements, it can be systematically biased by assumptions that plume rise time is negligible and that winds are homogeneous horizontally and in time during the plume transport. Wind inhomogeneities due to terrain effects and day-to-night transition, among other factors, affected some plumes during FIREX-AQ. The mean-wind method therefore performs best for short-range transport over level terrain with steady winds. The second method relies on upwind air parcel trajectories and plume rise computed with multiple high-resolution meteorological datasets. This "trajectory-based method" quantifies age uncertainty from the meteorological ensemble, plume rise speed, wind speed errors, and fire location. The second method also resolves age differences from the center to edge of a transect. Still, it is susceptible to errors in the meteorological model. With careful comparison of the simulated trajectories to smoke transport observed from geostationary satellite imagery described here, we filter out many trajectory errors and improve the smoke age estimates. The two age methods are strongly correlated (R = 0.93) for the periods during FIREX-AQ when both ages are available. The mean-wind age is systematically 14 % younger than the trajectory-based age and the median absolute difference between them is 19 % (23 % for mean). The favorable agreement between the two age methods reflects that the mean-wind method was selectively applied to plumes with little wind variability. Trajectory-based ages are available for more of the FIREX-AQ smoke observations than the mean-wind ages. The median trajectory-based age uncertainty during FIREX-AQ is 24 % and the mean uncertainty is 37 %, due to a long-tailed distribution. The main source of age uncertainty is spread within the meteorological ensemble, followed by discrepancy between measured and modeled wind speed, then other factors like plume rise. The age uncertainty variable enables the user to identify periods with high or low confidence in the age estimate, thereby informing studies of smoke aging.