The Fire and Smoke Model Evaluation Experiment—A Plan for Integrated, Large Fire–Atmosphere Field Campaigns

The Fire and Smoke Model Evaluation Experiment (FASMEE) is designed to collect integrated observations from large wildland fires and provide evaluation datasets for new models and operational systems. Wildland fire, smoke dispersion, and atmospheric chemistry models have become more sophisticated, and next-generation operational models will require evaluation datasets that are coordinated and comprehensive for their evaluation and advancement. Integrated measurements are required, including ground-based observations of fuels and fire behavior, estimates of fire-emitted heat and emissions fluxes, and observations of near-source micrometeorology, plume properties, smoke dispersion, and atmospheric chemistry. To address these requirements the FASMEE campaign design includes a study plan to guide the suite of required measurements in forested sites representative of many prescribed burning programs in the southeastern United States and increasingly common high-intensity fires in the western United States. Here we provide an overview of the proposed experiment and recommendations for key measurements. The FASMEE study provides a template for additional large-scale experimental campaigns to advance fire science and operational fire and smoke models

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

Wildfire smoke, Arctic haze, and aerosol effects on mixed-phase and cirrus clouds over the North Pole region during MOSAiC: an introduction

An advanced multiwavelength polarization Raman lidar was operated aboard the icebreaker Polarstern during the MOSAiC (Multidisciplinary drifting Observatory for the Study of Arctic Climate) expedition to continuously monitor aerosol and cloud layers in the central Arctic up to 30gkm height. The expedition lasted from September 2019 to October 2020 and measurements were mostly taken between 85 and 88.5ggN. The lidar was integrated into a complex remote-sensing infrastructure aboard the Polarstern. In this article, novel lidar techniques, innovative concepts to study aerosol-cloud interaction in the Arctic, and unique MOSAiC findings will be presented. The highlight of the lidar measurements was the detection of a 10gkm deep wildfire smoke layer over the North Pole region between 7-8gkm and 17-18gkm height with an aerosol optical thickness (AOT) at 532gnm of around 0.1 (in October-November 2019) and 0.05 from December to March. The dual-wavelength Raman lidar technique allowed us to unambiguously identify smoke as the dominating aerosol type in the aerosol layer in the upper troposphere and lower stratosphere (UTLS). An additional contribution to the 532gnm AOT by volcanic sulfate aerosol (Raikoke eruption) was estimated to always be lower than 15g%. The optical and microphysical properties of the UTLS smoke layer are presented in an accompanying paper . This smoke event offered the unique opportunity to study the influence of organic aerosol particles (serving as ice-nucleating particles, INPs) on cirrus formation in the upper troposphere. An example of a closure study is presented to explain our concept of investigating aerosol-cloud interaction in this field. The smoke particles were obviously able to control the evolution of the cirrus system and caused low ice crystal number concentration. After the discussion of two typical Arctic haze events, we present a case study of the evolution of a long-lasting mixed-phase cloud layer embedded in Arctic haze in the free troposphere. The recently introduced dual-field-of-view polarization lidar technique was applied, for the first time, to mixed-phase cloud observations in order to determine the microphysical properties of the water droplets. The mixed-phase cloud closure experiment (based on combined lidar and radar observations) indicated that the observed aerosol levels controlled the number concentrations of nucleated droplets and ice crystals

Modelling hourly spatio-temporal PM2.5 concentration in wildfire scenarios using dynamic linear models

Particulate matter with aerodynamic diameter < 2.5 μm (PM2.5) is one of the main pollutants generated in wildfire events with negative impacts on human health. In research involving wildfires and air quality, it is common to use emission models. However, the commonly used emission approach can generate errors and contradict the empirical data. This paper adopted a statistical approach based in evidence of ground level monitoring and satellite data. An hourly PM2.5 spatio-temporal model based on a dynamic linear modelling framework with Bayesian approach was proposed in a territorial context with a reduced number of monitoring stations for particulate matter. The model validation is complicated by the fact that all monitoring stations are used in the model calibration. The novel validation method proposed considered both the particulate matter with aerodynamic diameter < 10 μm (PM10) recorded as daily value from 24-h mean every six days as well as the PM2.5/PM10 ratio. Modelling was carried out to provide satisfactorily the exposure level of PM2.5 in a case study of wildfire event.We acknowledge and thank authorities of Red Metropolitana de Monitoreo Atmosférico de Quito (REMMAQ) for providing complementary information to this work. Joseph Sánchez Balseca is the recipient of a full scholarship from the Secretaria de Educación Superior, Ciencia, Técnología e Innovación (SENESCYT), Ecuador.Peer ReviewedObjectius de Desenvolupament Sostenible::3 - Salut i Benestar::3.9 - Per a 2030, reduir substancialment el nombre de morts i malalties causats per productes químics perillosos i la pol·lució de l’aire, l’aigua i el sòlObjectius de Desenvolupament Sostenible::11 - Ciutats i Comunitats SosteniblesObjectius de Desenvolupament Sostenible::11 - Ciutats i Comunitats Sostenibles::11.6 - Per a 2030, reduir l’impacte ambiental negatiu per capita de les ciutats, amb especial atenció a la qualitat de l’aire, així com a la gestió dels residus municipals i d’altre tipusObjectius de Desenvolupament Sostenible::17 - Aliança per a Aconseguir els ObjetiusObjectius de Desenvolupament Sostenible::17 - Aliança per a Aconseguir els Objetius::17.18 - Per a 2020, millorar la prestació de suport a la formació per als països en desenvolupament, inclosos els països menys avançats i els petits estats insulars en desenvolupament, amb la perspectiva d’augmentar de forma significativa la disponibilitat de dades actualitzades, fiables i de qualitat, desglossades per grups d’ingressos, gènere, edat, raça, origen ètnic, condició migratòria, discapacitat, ubicació geogràfica i altres característiques pertinents segons el context nacionalObjectius de Desenvolupament Sostenible::3 - Salut i BenestarPostprint (author's final draft

Early wildfire detection by air quality sensors on unmanned aerial vehicles: Optimization and feasibility

“Millions of acres of forests are destroyed by wildfires every year, causing ecological, environmental, and economical losses. The recent wildfires in Australia and the Western U.S. smothered multiple states with more than fifty million acres charred by the blazes. The warmer and drier climate makes scientists expect increases in the severity and frequency of wildfires and the associated risks in the future. These inescapable crises highlight the urgent need for early detection and prevention of wildfires. This work proposed an energy management framework that integrated unmanned aerial vehicle (UAV) with air quality sensors for early wildfire detection and forest monitoring. An autonomous patrol solution that effectively detects wildfire events, while preserving the UAV battery for a larger area of coverage was developed. The UAV can send real-time data (e.g., sensor readings, thermal pictures, videos, etc) to nearby communications base stations (BSs) when a wildfire is detected. An optimization problem that minimized the total UAV’s consumed energy and satisfied a certain quality-of-service (QoS) data rate were formulated and solved. More specifically, this study optimized the flight track of a UAV and the transmit power between the UAV and BSs. Finally, selected simulation results that illustrate the advantages of the proposed model were proposed”--Abstract, page iii

Advances in UAS for forest fire fighting

Peer Reviewe

Mobile Ka-Band Polarimetric Doppler Radar Observations Of Wildfire Smoke Plumes

Remote sensing techniques have been more recently used to study and track wildfire smoke plume structure and evolution; however, knowledge gaps remain due to the limited availability of observational datasets aimed at understanding the fine-scale fire-atmosphere interactions and plume microphysics. In this study, we present a new mobile millimeter-wave (Ka-band) Doppler radar system acquired to sample the fine-scale kinematics and microphysical properties of active wildfire smoke plumes from both wildfires and large prescribed fires. Four field deployments were conducted in the fall of 2019 during two wildfires in California and one prescribed burn in Utah. An additional dataset of precipitation observations was obtained prior to the wildfire deployments to compare the Ka-band specific signatures of precipitation and wildfire smoke plumes. Radar parameters investigated in this study include reflectivity, radial velocity, Doppler spectrum width, Differential Reflectivity (ZDR), and copolarized correlation coefficients (HV). Observed radar reflectivity ranged between -15 and 20 dBZ in plume and radial velocity ranged 0 to 16 m s-1. Dual-polarimetric observations revealed that scattering sources within wildfire plumes are primarily nonspherical and oblate shaped targets as indicated by ZDR values measuring above 0 and HV values below 0.8 within the plume. Doppler spectrum width maxima were located near the updraft core location and were associated with radar reflectivity maxima

A decadal satellite analysis of the origins and impacts of smoke in Colorado

We analyze the record of aerosol optical depth (AOD) measured by the MODerate resolution Imaging Spectroradiometer (MODIS) aboard the Terra satellite in combination with surface PM[subscript 2.5] to investigate the impact of fires on aerosol loading and air quality over Colorado from 2000 to 2012, and to evaluate the contribution of local versus transported smoke. Fire smoke contributed significantly to the AOD levels observed over Colorado. During the worst fire seasons of 2002 and 2012, average MODIS AOD over the Colorado Front Range corridor were 20–50% larger than the other 11 yr studied. Surface PM[subscript 2.5] was also unusually elevated during fire events and concentrations were in many occasions above the daily National Ambient Air Quality Standard (35 μg m[superscript −3]) and even reached locally unhealthy levels (> 100 μg m[superscript −3]) over populated areas during the 2012 High Park fire and the 2002 Hayman fire. Over the 13 yr examined, long-range transport of smoke from northwestern US and even California (> 1500 km distance) occurred often and affected AOD and surface PM[subscript 2.5]. During most of the transport events, MODIS AOD and surface PM[subscript 2.5] were reasonable correlated (r[superscript 2] = 0.2–0.9), indicating that smoke subsided into the Colorado boundary layer and reached surface levels. However, that is not always the case since at least one event of AOD enhancement was disconnected from the surface (r[superscript 2]<0.01 and low PM[subscript 2.5] levels). Observed plume heights from the Multi-angle Imaging SpectroRadiometer (MISR) satellite instrument and vertical aerosol profiles measured by the space-based Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP) showed a complex vertical distribution of smoke emitted by the High Park fire in 2012. Smoke was detected from a range of 1.5 to 7.5 km altitude at the fire origin and from ground levels to 12.3 km altitude far away from the source. The variability of smoke altitude as well as the local meteorology were key in determining the aerosol loading and air quality over the Colorado Front Range region. Our results underline the importance of accurate characterization of the vertical distribution of smoke for estimating the air quality degradation associated with fire activity and its link to human health.United States. National Park Service (Grant H2370 094000/J2350103006