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Which approaches lead to better outcomes for participants in environmental education (EE) field trips? This manuscript builds upon previous large-sample quantitative research that identified effective elements of single-day EE field trip programs for early adolescent youth across the USA. In this mixed-methods study, we observed 87 EE-focused school field trips in the USA and then surveyed youth participants immediately afterwards. We used the student surveys to quantitatively distinguish the top-performing quartile of programs from the bottom quartile. We then examined in-depth qualitative fieldnotes on each program in the top and bottom quartiles. Our analyses revealed six key principles that distinguished the programs with the most positive student outcomes from those with the least positive: (1) ensuring basic needs (physiological and safety) are met; (2) ensuring instructional clarity; (3) providing emotional support for students; (4) highlighting the novelty of the activities and setting; (5) maintaining or restoring student attention; and (6) providing a cohesive and thematic experience with clear purpose. There are many ways to embody the six principles. We share examples for each. 

Abstract. Accurate representation of fire emissions is critical for modeling the in-plume, near-source, and remote effects of biomass burning (BB) on atmospheric composition, air quality, and climate. In recent years application of advanced instrumentation has significantly improved knowledge of the compounds emitted from fires, which, coupled with a large number of recent laboratory and field campaigns, has facilitated the emergence of new emission factor (EF) compilations. The Next-generation Emissions InVentory expansion of Akagi (NEIVA) version 1.0 is one such compilation in which the EFs for 14 globally relevant fuel and fire types have been updated to include data from recent studies, with a focus on gaseous non-methane organic compounds (NMOC_g). The data are stored in a series of connected tables that facilitate flexible querying from the individual study level to recommended averages of all laboratory and field data by fire type. The querying features are enabled by assignment of unique identifiers to all compounds and constituents, including thousands of NMOC_g. NEIVA also includes chemical and physical property data and model surrogate assignments for three widely used chemical mechanisms for each NMOC_g. NEIVA EF datasets are compared with recent publications and other EF compilations at the individual compound level and in the context of overall volatility distributions and hydroxyl (OH) reactivity (OHR) estimates. The NMOC_g in NEIVA include ∼4–8 times more compounds with improved representation of intermediate volatility organic compounds, resulting in much lower overall volatility (lowest-volatility bin shifted by as much as 3 orders of magnitude) and significantly higher OHR (up to 90 %) than other compilations. These updates can strongly impact model predictions of the effects of BB on atmospheric composition and chemistry. 

Fires in the wildland-urban interface (WUI) are a global issue with growing importance. However, the impact of WUI fires on air quality and health is less understood compared to that of fires in wildland. We analyze WUI fire impacts on air quality and health at the global scale using a multi-scale atmospheric chemistry model—the Multi-Scale Infrastructure for Chemistry and Aerosols model (MUSICA). WUI fires have notable impacts on key air pollutants [e.g., carbon monoxide (CO), nitrogen dioxide (NO₂), fine particulate matter (PM_2.5), and ozone (O₃)]. The health impact of WUI fire emission is disproportionately large compared to wildland fires primarily because WUI fires are closer to human settlement. Globally, the fraction of WUI fire–caused annual premature deaths (APDs) to all fire–caused APDs is about three times of the fraction of WUI fire emissions to all fire emissions. The developed model framework can be applied to address critical needs in understanding and mitigating WUI fires and their impacts. 

Accurate estimates of biomass burning (BB) emissions are of great importance worldwide due to the impacts of these emissions on human health, ecosystems, air quality, and climate. Atmospheric modeling efforts to represent these impacts require BB emissions as a key input. This paper is presented by the Biomass Burning Uncertainty: Reactions, Emissions and Dynamics (BBURNED) activity of the International Global Atmospheric Chemistry project and largely based on a workshop held in November 2023. The paper reviews 9 of the BB emissions datasets widely used by the atmospheric chemistry community, all of which rely heavily on Moderate Resolution Imaging Spectroradiometer (MODIS) satellite observations of fires scheduled to be discontinued at the end of 2025. In this time of transition away from MODIS to new fire observations, such as those from the Visible Infrared Imaging Radiometer Suite (VIIRS) satellite instruments, we summarize the contemporary status of BB emissions estimation and provide recommendations on future developments. Development of global BB emissions datasets depends on vegetation datasets, emission factors, and assumptions of fire persistence and phase, all of which are highly uncertain with high degrees of variability and complexity and are continually evolving areas of research. As a result, BB emissions datasets can have differences on the order of factor 2–3, and no single dataset stands out as the best for all regions, species, and times. We summarize the methodologies and differences between BB emissions datasets. The workshop identified 5 key recommendations for future research directions for estimating BB emissions and quantifying the associated uncertainties: development and uptake of satellite burned area products from VIIRS and other instruments; mapping of fine scale heterogeneity in fuel type and condition; identification of spurious signal detections and information gaps in satellite fire radiative power products; regional modeling studies and comparison against existing datasets; and representation of the diurnal cycle and plume rise in BB emissions. 

Rapid warming is likely increasing primary production and wildfire occurrence in the Arctic. Projected changes in the abundance and composition of carbonaceous aerosols during the summer are likely to impact atmospheric chemistry and climate, but our understanding of these processes is limited by sparse observations. Here, we characterize carbonaceous aerosol at two field sites, Toolik Field Station in the Interior and the Atmospheric Radiation Measurement facility at Utqiaġvik on the Arctic coast of Alaska, USA, through the summers of 2022 and 2023. We estimated particulate matter ≤2.5 micrometers (PM2.5) and particulate matter ≤10 micrometers (PM10) using laser light scattering (PurpleAir sensors) and examined total carbon (TC) and its organic carbon (OC) and elemental carbon (EC) fractions in total suspended particles (TSP). We also investigated the dominant sources of carbonaceous aerosol using air mass backward-trajectories from the National Oceanic and Atmospheric Administration (NOAA) Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model and radiocarbon source apportionment of TC. We found TC concentrations were about twice as high in the Interior than on the coast and that modern sources were the dominant sources of carbonaceous aerosol at both Toolik (95–99%) and Utqiaġvik (86–89%), with minor contributions from fossil sources. Periods of significantly elevated PM, TC, OC, and EC concentrations coincided with major boreal forest fire activity in North America that brought smoke to the region. The radiocarbon signature of EC measured at Toolik during these wildfire smoke events indicated that over 90% of the EC originated from modern sources. Our measurements demonstrate changing aerosol concentrations in the Arctic during the summer, and emphasize the need for continuous atmospheric monitoring to evaluate and advance our understanding of this rapidly changing atmospheric environment. (Manuscript in prep) 

Abstract. We present the Fire Inventory from National Center for Atmospheric Research (NCAR) version 2.5 (FINNv2.5), a fire emissions inventory that provides publicly available emissions of trace gases and aerosols for various applications, including use in global and regional atmospheric chemistry modeling. FINNv2.5 includes numerous updates to the FINN version 1 framework to better represent burned area, vegetation burned, and chemicals emitted. Major changes include the use of active fire detections from the Visible Infrared Imaging Radiometer Suite (VIIRS) at 375 m spatial resolution, which allows smaller fires to be included in the emissions processing. The calculation of burned area has been updated such that a more rigorous approach is used to aggregate fire detections, which better accounts for larger fires and enables using multiple satellite products simultaneously for emissions estimates. Fuel characterization and emissions factors have also been updated in FINNv2.5. Daily fire emissions for many trace gases and aerosols are determined for 2002–2019 (Moderate Resolution Imaging Spectroradiometer (MODIS)-only fire detections) and 2012–2019 (MODIS + VIIRS fire detections). The non-methane organic gas emissions are allocated to the species of several commonly used chemical mechanisms. We compare FINNv2.5 emissions against other widely used fire emissions inventories. The performance of FINNv2.5 emissions as inputs to a chemical transport model is assessed with satellite observations. Uncertainties in the emissions estimates remain, particularly in Africa and South America during August–October and in southeast and equatorial Asia in March and April. Recommendations for future evaluation and use are given.