Wildland Fire Smoke in the United States

This open access book synthesizes current information on wildland fire smoke in the United States, providing a scientific foundation for addressing the production of smoke from wildland fires. This will be increasingly critical as smoke exposure and degraded air quality are expected to increase in extent and severity in a warmer climate. Accurate smoke information is a foundation for helping individuals and communities to effectively mitigate potential smoke impacts from wildfires and prescribed fires. The book documents our current understanding of smoke science for (1) primary physical, chemical, and biological issues related to wildfire and prescribed fire, (2) key social issues, including human health and economic impacts, and (3) current and anticipated management and regulatory issues. Each chapter provides a summary of priorities for future research that provide a roadmap for developing scientific information that can improve smoke and fire management over the next decade

Impacts of urbanisation on birds : Disentangling the effects of multiple pollutants on avian behaviour and physiology

Anthropogenic pollution is a pervasive feature of urbanisation, reaching into ecosystems worldwide and posing novel challenges to wildlife. Not surprisingly, differences in behaviour, and physiology, have been found between urban and rural populations. Most studies on anthropogenic impacts have so far either used a dichotomous approach, comparing urban-rural sites, or investigated impacts of just one stressor. However, urban environments create a complex matrix of co-occuring pollutants, leading to potentially complex interactive effects between stressors. We currently lack a deeper knowledge of the combined and single effects and the underlying mechanisms creating urban-rural phenotypic variation. In this thesis, I investigated the single and combined effects of urban pollutants of avian behaviour and physiology. Specifically, I used the oxidative stress system, immune system, and plasma fatty acid composition, as the key physiological traits responding to human-induced environmental change. Urban pollutants of interest were artificial light at night (ALAN), anthropogenic noise, ozone and soot, and as human-influenced additional factors I looked at impacts of differential diets, and vegetation structure. I utilised full-factorial experimental exposure experiments in the wild and in the laboratory, and a correlative study in the wild, using wild and captive birds.I found that ALAN exposure alone decreases activity and noise exposure alone decreases the proportion of birds found feeding. The combined exposure to these two pollutants led to a non-additive effect on the proportion of birds resting, with ALAN as the driving stressor. ALAN-exposed nestlings mounted a less strong immune response, with a reduction of melatonin levels being the likely mechanistic link to an impaired immune functioning. Simultaneous exposure to ALAN and noise increased levels of an important antioxidant, total glutathione, more than the additive effect from single pollutant effects would have estimated (positive synergistic effect). Furthermore, I found that ozone is a potent pro-oxidant, negatively affecting antioxidant capacity, but we found no increased levels of oxidative damage due to ozone exposure. Soot exposure, on the other hand, did not affect avian oxidative stress status. Dietary ω6- and ω3-polyunsaturated fatty acids (PUFAs) modulated oxidative stress response to ozone exposure, but also act alone, with ω3-PUFAs decreasing non-enzymatic antioxidant capacity. Likewise, ω6:ω3 ratios of circulating PUFAs of wild nestlings are changed by human-influenced environmental factors, as well as their antioxidant capacity is negatively affected by air pollution and number of oak trees around their nest box. We also showed in this latter study, that using multi-stressor approach gives a more profound mechanistic understanding of phenotypic effects, then using a dichotomous comparison, which might obscure certain effects. Overall, I show that pollutants affect behaviour and key fitness related physiological traits and that the combined exposure to multiple stressors can lead to unexpected non-additive effects. This highlights the need of a more thorough mechanistic understanding of multi-stressor effects. A deeper understanding of single and combinatory effects of anthropogenic stressors will help gaining crucial insight into populations and species resilience to environmental change, thereby targeted actions can be proposed to maintain biodiversity in cities and have a future development of sustainable cities

Projecting Wildfire Emissions and Their Air Quality Impacts in the Southeastern U.S. from 2010 to Mid-century

Wildfires can severely impair the health of ecosystems, life forms and regional economies. In the rapidly changing U. S. Southeast, both climate and socioeconomic factors (e.g., population and income) drive wildfires, and need to be represented in wildfire inventories to assess the air quality (AQ) impacts and health risks of wildfires long-term. This motivated the development of a wildfire emissions projection methodology leveraging published models of annual areas burned (AAB) based on county-level socioeconomic and climate projections for 2011-2060. It is applied to project two sets of AAB with different climate downscaling approaches, to estimate wildfire emissions for 2010 and four mid-century years. These are compared with emissions estimated using 18-year historical mean AAB without changes in climate and socioeconomics. Competing climate and socioeconomic factors result in 7% - 32% lower projected AAB than historical values, and 13% - 62% lower fine particulate matter (PM2.5) emissions than estimated from historical AAB in the selected years, with climate driving their temporal variability. Evaluation of the emissions projection methods in air quality (AQ) simulations against those using the National Emissions Inventory (NEI), and network observations for 2010 show little difference among the methods in ozone (0.08% - 0.93%) and PM2.5 (1% - 8%). Larger, comparable biases relative to observations in all three methods for secondary species, especially in winter, are attributable to non-wildfire emissions or secondary chemical production. The projection methods predict primary wildfire PM better than the NEI, providing confidence that they can assess current wildfire AQ impacts, while enabling longer-term AQ assessments unachievable with static inventories. AQ simulations using the projected wildfire emissions, and projected emission reductions in SOx and NOx from energy and transportation (by ~80% at mid-century) show peak periods and locations of wildfire impacts on ozone and PM shifting from autumn in Midwestern locations in 2010, to warmer and drier summers east and south by mid-century, following the AAB spatiotemporal patterns. Although considerably lower than 2010 levels, summertime PM2.5 increases by 4%-5% in 2040-2060 in this emission scenario, driven by increases in OC and unspeciated other PM.Doctor of Philosoph

Ground-level ozone pollution in China: A synthesis of recent findings on influencing factors and impacts

Ozone (O3) in the troposphere is an air pollutant and a greenhouse gas. In mainland China, after the Air Pollution Prevention and Action Plan was implemented in 2013 - and despite substantial decreases in the concentrations of other air pollutants - ambient O3 concentrations paradoxically increased in many urban areas. The worsening urban O3 pollution has fuelled numerous studies in recent years, which have enriched knowledge about O3-related processes and their impacts. In this article, we synthesise the key findings of over 500 articles on O3 over mainland China that were published in the past six years in English-language journals. We focus on recent changes in O3 concentrations, their meteorological and chemical drivers, complex O3 responses to the drastic decrease in human activities during coronavirus disease 2019 lockdowns, several emerging chemical processes, impacts on crops and trees, and the latest government interventions. © 2022 The Author(s). Published by IOP Publishing Ltd

Planning for an unknown future: incorporating meteorological uncertainty into predictions of the impact of fires and dust on US particulate matter

2019 Summer.Includes bibliographical references.Exposure to particulate matter (PM) pollution has well documented health impacts and is regulated by the United States (U.S.) Environmental Protection Agency (EPA). In the U.S. wildfire smoke and wind-blown dust are significant natural sources of PM pollution. This dissertation shows how the environmental conditions that drive wildfires and wind-blown dust are likely to change in the future and what these changes imply for future PM concentrations. The first component of this dissertation shows how human ignitions and environmental conditions influence U.S. wildfire activity. Using wildfire burn area and ignition data, I find that in both the western and southeastern U.S., annual lightning- and human-ignited wildfire burn area have similar relationships with key environmental conditions (temperature, relative humidity, and precipitation). These results suggest that burn area for human- and lightning-ignited wildfires will be similarly impacted by climate change. Next, I quantify how the environmental conditions that drive wildfire activity are likely to change in the future under different climate scenarios. Coupled Model Intercomparison Project phase 5 (CMIP5) models agree that western U.S. temperatures will increase in the 21st century for representative concentration pathways (RCPs) 4.5 and 8.5. I find that averaged over seasonal and regional scales, other environmental variables demonstrated to be relevant to fuel flammability and aridity, such as precipitation, evaporation, relative humidity, root zone soil moisture, and wind speed, can be used to explain historical variability in wildfire burn area as well or better than temperature. My work demonstrates that when objectively selecting environmental predictors using Lasso regression, temperature is not always selected, but that this varies by western U.S. ecoregion. When temperature is not selected, the sign and magnitude of future changes in burn area become less certain, highlighting that predicted changes in burn area are sensitive to the environmental predictors chosen to predict burn area. Smaller increases in future wildfire burn area are estimated whenever and wherever the importance of temperature as a predictor is reduced. The second component of this dissertation examines how environmental conditions that drive fine dust emissions and concentrations in the southwestern U.S. change in the future. I examine environmental conditions that influence dust emissions including, temperature, vapor pressure deficit, relative humidity, precipitation, soil moisture, wind speed, and leaf area index (LAI). My work quantifies fine dust concentrations in the U.S. southwest dust season, March through July, using fine iron as a dust proxy, quantified with measurements from the Interagency Monitoring of PROtected Visual Environments (IMPROVE) network between 1995 and 2015. I show that the largest contribution to the spread in future dust concentration estimates comes from the choice of environmental predictor used to explain observed variability. The spread between different environmental predictor estimates can be larger than the spread between climate scenarios or intermodel spread. Based on linear estimates of how dust concentrations respond to changes in LAI, CMIP5 estimated increases in LAI would result in reduced dust concentrations in the future. However, when I objectively select environmental predictors of dust concentrations using Lasso regression, LAI is not selected in favor of other variables. When using a linear combination of objectively selected environmental variables, I estimate that future southwest dust season mean concentrations will increase by 0.24 μg m−3 (12%) by the end of the 21st century for RCP 8.5. This estimated increase in fine dust concentration is driven by decreases in relative humidity, precipitation, soil moisture, and buffered by decreased wind speeds

Master of Science

thesisA multiple-box model was designed to determine how anthropogenic, biological, and meteorological processes combine to produce diel cycles of carbon dioxide (CO2) concentrations within the urban Salt Lake Valley (uSLV). The model was forced by an anthropogenic CO2 emissions inventory, observed winds, sounding-derived mixing depths, and net biological flux estimates based on temperature, solar radiation, day of year, and ecosystem type. The model was validated using hourly CO2 data from a network of sensors around the uSLV for years 2005-2009. The model accounted for 53% of the observations on an hourly basis and accounted for 90-94% of the mean diel cycle of the observations depending on the season. Salt Lake Valley suffers from prolonged temperature inversions during the winter that trap pollutants and gases at the surface. The CO2 network (co2.utah.edu) was compared with the CO2 multiple-box model to determine whether the model could capture the main drivers of CO2 variability during the Persistent Cold Air Pool Study (PCAPS). Time-height analyses were performed to facilitate investigation and explanation of CO2 variability during PCAPS intensive observation periods (IOPs). The analyzed data included atmospheric soundings, CO2 network data, quasivertical CO2 profiles collected ascending by foot or vehicle, and laser-ceiliometer data