Summary of PM2.5 measurement artifacts associated with the Teledyne T640 PM Mass Monitor under controlled chamber experimental conditions using polydisperse ammonium sulfate aerosols and biomass smoke.

Particulate matter (PM) is a major primary pollutant emitted during wildland fires that has the potential to pose significant health risks to individuals/communities who live and work in areas impacted by smoke events. Limiting exposure is the principle measure available to mitigate health impacts of smoke and therefore the accurate determination of ambient PM concentrations during wildland fire events is critical to protecting public health. However, monitoring air pollutants in smoke impacted environments has proven challenging in that measurement interferences or sampling conditions can result in both positive and negative artifacts. The EPA has performed research on methods for the measurement of PM2.5 in a series of laboratory-based studies including evaluation in smoke. This manuscript will summarize the results of the laboratory-based evaluation of federal equivalent method (FEM) monitors for PM2.5 with particular attention being given to the Teledyne-API Model T640 PM Mass monitor, as compared to the filter-based federal reference method (FRM). The T640 is an optical-based PM monitor and has been gaining wide use by state and local agencies in monitoring for PM2.5 U.S. National Ambient Air Quality Standards (NAAQS) attainment. At present, the T640 (includes both T640 and T640×) comprises ~44% of the PM2.5 FEM monitors in U.S. regulatory monitoring networks. In addition, the T640 has increasingly been employed for the higher time resolution comparison/evaluation of low-cost PM sensors including during smoke impacted events. Results from controlled non-smoke laboratory studies using generated ammonium sulfate aerosols demonstrated a generally negative T640 measurement artifact that was significantly related to the PM2.5 concentration and particle size distribution. Results from biomass burning chamber studies demonstrated positive and negative artifacts significantly associated with PM2.5 concentration and optical wavelength-dependent absorption properties of the smoke aerosol.Implications: The results detailed in this paper will provide state and local air monitoring agencies with the tools and knowledge to address PM2.5 measurement challenges in areas frequently impacted by wildland fire smoke. The observed large positive and negative artifacts in the T640 PM mass determination have the potential to result in false exceedances of the PM2.5 NAAQS or in the disqualification of monitoring data through an exceptional event designation. In addition, the observed artifacts in smoke impacted air will have a detrimental effect on providing reliable public information when wildfires occur and also in identifying reference measurements for small sensor evaluation studies. Other PM2.5 FEMs such as the BAM-1022 perform better in smoke and are comparable to the filter-based FRM. Care must be taken in choosing high time resolution FEM monitors that will be operated at smoke impacted sites. Accurate methods, such as the FRM and BAM-1022 will reduce the burden of developing and reviewing exceptional event request packages, data loss/disqualification, and provide states with tools to adequately evaluate public exposure risks and provide accurate public health messaging during wildfire/smoke events.

Fuel layer specific pollutant emission factors for fire prone forest ecosystems of the western U.S. and Canada.

Wildland fires are a major source of gases and aerosols, and the production, dispersion, and transformation of fire emissions have significant ambient air quality impacts and climate interactions. The increase in wildfire area burned and severity across the United States and Canada in recent decades has led to increased interest in expanding the use of prescribed fires as a forest management tool. While the primary goal of prescribed fire use is to limit the loss of life and property and ecosystem damage by constraining the growth and severity of future wildfires, a potential additional benefit of prescribed fire - reduction in the adverse impacts of smoke production and greenhouse gas (GHG) emissions - has recently gained the interest of land management agencies and policy makers in the United States and other nations. The evaluation of prescribed fire/wildfire scenarios and the potential mitigation of adverse impacts on air quality and GHGs requires fuel layer specific pollutant emission factors (EFs) for fire prone forest ecosystems. Our study addresses this need with laboratory experiments measuring EFs for carbon dioxide (CO2), carbon monoxide (CO), methane (CH4), ethyne (C2H2), formaldehyde (H2CO), formic acid (CH2O2), hydrogen cyanide (HCN), fine particulate matter (PM2.5), nitric oxide (NO), nitrogen dioxide (NO2), sulfur dioxide (SO2), and total reduced sulfur (TRS) for the burning of individual fuel components from three forest ecosystems which account for a large share of wildfire burned area and emissions in the western United States and Canada - Douglas fir, ponderosa pine, and black spruce/jack pine.

Evaluation of Cairpol and Aeroqual Air Sensors in Biomass Burning Plumes.

Cairpol and Aeroqual air quality sensors measuring CO, CO2, NO2, and other species were tested in fresh biomass burning plumes in field and laboratory environments. We evaluated sensors by comparing 1-minute sensor measurements to collocated reference instrument measurements. Sensors were evaluated based on the coefficient of determination (r 2) between the sensor and reference measurements, by the accuracy, collocated precision, root mean square error (RMSE), and other metrics. In general, CO and CO2 sensors performed well (in terms of accuracy and r 2 values) compared to NO2 sensors. Cairpol CO and NO2 sensors had better sensor-versus-sensor agreement (e.g., collocated precision) than Aeroqual CO and NO2 sensors of the same species. Tests of other sensors (e.g., NH3, H2S, VOC, NMHC) provided more inconsistent results and need further study. Aeroqual NO2 sensors had an apparent O3 interference that was not observed in the Cairpol NO2 sensors. Although the sensor accuracy lags that of reference-level monitors, with location-specific calibrations they have the potential to provide useful data about community air quality and personal exposure to smoke impacts.

Comparison of ozone measurement methods in biomass burning smoke: an evaluation under field and laboratory conditions.

In recent years wildland fires in the United States have had significant impacts on local and regional air quality and negative human health outcomes. Although the primary health concerns from wildland fires come from fine particulate matter (PM2.5), large increases in ozone (O3) have been observed downwind of wildland fire plumes (DeBell et al., 2004; Bytnerowicz et al., 2010; Preisler et al., 2010; Jaffe et al., 2012; Bytnerowicz et al., 2013; Jaffe et al., 2013; Lu et al., 2016; Lindaas et al., 2017; McClure and Jaffe, 2018; Liu et al., 2018; Baylon et al., 2018; Buysse et al., 2019). Conditions generated in and around wildland fire plumes, including the presence of interfering chemical species, can make the accurate measurement of O3 concentrations using the ultraviolet (UV) photometric method challenging if not impossible. UV photometric method instruments are prone to interferences by volatile organic compounds (VOCs) that are present at high concentrations in wildland fire smoke. Four different O3 measurement methodologies were deployed in a mobile sampling platform downwind of active prescribed grassland fire lines in Kansas and Oregon and during controlled chamber burns at the United States Forest Service, Rocky Mountain Research Station Fire Sciences Laboratory in Missoula, Montana. We demonstrate that the Federal Reference Method (FRM) nitric oxide (NO) chemiluminescence monitors and Federal Equivalent Method (FEM) gas-phase (NO) chemical scrubber UV photometric O3 monitors are relatively interference-free, even in near-field combustion plumes. In contrast, FEM UV photometric O3 monitors using solid-phase catalytic scrubbers show positive artifacts that are positively correlated with carbon monoxide (CO) and total gas-phase hydrocarbon (THC), two indicator species of biomass burning. Of the two catalytic scrubber UV photometric methods evaluated, the instruments that included a Nafion® tube dryer in the sample introduction system had artifacts an order of magnitude smaller than the instrument with no humidity correction. We hypothesize that Nafion®-permeating VOCs (such as aromatic hydrocarbons) could be a significant source of interference for catalytic scrubber UV photometric O3 monitors and that the inclusion of a Nafion® tube dryer assists with the mitigation of these interferences. The chemiluminescence FRM method is highly recommended for accurate measurements of O3 in wildland fire plume studies and at regulatory ambient monitoring sites frequently impacted by wildland fire smoke.

The U.S. EPA wildland fire sensor challenge: Performance and evaluation of solver submitted multi-pollutant sensor systems.

Wildland fires can emit substantial amounts of air pollution that may pose a risk to those in proximity (e.g., first responders, nearby residents) as well as downwind populations. Quickly deploying air pollution measurement capabilities in response to incidents has been limited to date by the cost, complexity of implementation, and measurement accuracy. Emerging technologies including miniaturized direct-reading sensors, compact microprocessors, and wireless data communications provide new opportunities to detect air pollution in real time. The U.S. Environmental Protection Agency (EPA) partnered with other U.S. federal agencies (CDC, NASA, NPS, NOAA, USFS) to sponsor the Wildland Fire Sensor Challenge. EPA and partnering organizations share the desire to advance wildland fire air measurement technology to be easier to deploy, suitable to use for high concentration events, and durable to withstand difficult field conditions, with the ability to report high time resolution data continuously and wirelessly. The Wildland Fire Sensor Challenge encouraged innovation worldwide to develop sensor prototypes capable of measuring fine particulate matter (PM2.5), carbon monoxide (CO), carbon dioxide (CO2), and ozone (O3) during wildfire episodes. The importance of using federal reference method (FRM) versus federal equivalent method (FEM) instruments to evaluate performance in biomass smoke is discussed. Ten solvers from three countries submitted sensor systems for evaluation as part of the challenge. The sensor evaluation results including sensor accuracy, precision, linearity, and operability are presented and discussed, and three challenge winners are announced. Raw solver submitted PM2.5 sensor accuracies of the winners ranged from ~22 to 32%, while smoke specific EPA regression calibrations improved the accuracies to ~75-83% demonstrating the potential of these systems in providing reasonable accuracies over conditions that are typical during wildland fire events.

Evaluation of small form factor, filter-based PM2.5 samplers for temporary non-regulatory monitoring during wildland fire smoke events.

Wildland fire activity and associated emission of particulate matter air pollution is increasing in the United States over the last two decades due primarily to a combination of increased temperature, drought, and historically high forest fuel loading. The regulatory monitoring networks in the Unites States are mostly concentrated in larger population centers where anthropogenic air pollution sources are concentrated. Smaller population centers in areas more likely to be impacted by wildland fire smoke in many instances lack adequate observational air quality data. Several commercially available small form factor filter-based PM2.5 samplers (SFFFS) were evaluated under typical ambient and simulated near-to mid-field wildland fire smoke conditions to evaluate their accuracy for use in temporary deployments during prescribed and wildfire events. The performance of all the SFFFS tested versus the designated federal reference methods (FRM) was acceptable in determining PM2.5 concentration in both ambient (2.7-14.0 µg m-3) and chamber smoke environments (24.6-3044.6 µg m-3) with accuracies ranging from ~92 to 98%. However, only the ARA Instruments model N-FRM Sampler was found to provide PM2.5 mass measurement accuracies that meet FRM guideline performance specifications under both typical ambient (97.3 ± 1.9%) and simulated wildland fire conditions (98.2 ± 1.4%).

The delayed effect of wildfire season particulate matter on subsequent influenza season in a mountain west region of the USA.

Particularly in rural settings, there has been little research regarding the health impacts of fine particulate matter (PM2.5) during the wildfire season smoke exposure period on respiratory diseases, such as influenza, and their associated outbreaks months later. We examined the delayed effects of PM2.5 concentrations for the short-lag (1-4 weeks prior) and the long-lag (during the prior wildfire season months) on the following winter influenza season in Montana, a mountainous state in the western United States. We created gridded maps of surface PM2.5 for the state of Montana from 2009 to 2018 using spatial regression models fit with station observations and Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol optical thickness data. We used a seasonal quasi-Poisson model with generalized estimating equations to estimate weekly, county-specific, influenza counts for Montana, associated with delayed PM2.5 concentration periods (short-lag and long-lag effects), adjusted for temperature and seasonal trend. We did not detect an acute, short-lag PM2.5 effect nor short-lag temperature effect on influenza in Montana. Higher daily average PM2.5 concentrations during the wildfire season was positively associated with increased influenza in the following winter influenza season (expected 16% or 22% increase in influenza rate per 1 µg/m3 increase in average daily summer PM2.5 based on two analyses, p = 0.04 or 0.008). This is one of the first observations of a relationship between PM2.5 during wildfire season and influenza months later.

Fire behavior and smoke modeling: Model improvement and measurement needs for next-generation smoke research and forecasting systems.

There is an urgent need for next-generation smoke research and forecasting (SRF) systems to meet the challenges of the growing air quality, health, and safety concerns associated with wildland fire emissions. This review paper presents simulations and experiments of hypothetical prescribed burns with a suite of selected fire behavior and smoke models and identifies major issues for model improvement and the most critical observational needs. The results are used to understand the new and improved capability required for the next-generation SRF systems and to support the design of the Fire and Smoke Model Evaluation Experiment (FASMEE) and other field campaigns. The next-generation SRF systems should have more coupling of fire, smoke, and atmospheric processes to better simulate and forecast vertical smoke distributions and multiple sub-plumes, dynamical and high-resolution fire processes, and local and regional smoke chemistry during day and night. The development of the coupling capability requires comprehensive and spatially and temporally integrated measurements across the various disciplines to characterize flame and energy structure (e.g., individual cells, vertical heat profile and the height of well mixing flaming gases), smoke structure (vertical distributions and multiple sub-plumes), ambient air processes (smoke eddy, entrainment and radiative effects of smoke aerosols), fire emissions (for different fuel types and combustion conditions from flaming to residual smoldering), as well as night-time processes (smoke drainage and super-fog formation).

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.

Modeling crop residue burning experiments to evaluate smoke emissions and plume transport.

Crop residue burning is a common land management practice that results in emissions of a variety of pollutants with negative health impacts. Modeling systems are used to estimate air quality impacts of crop residue burning to support retrospective regulatory assessments and also for forecasting purposes. Ground and airborne measurements from a recent field experiment in the Pacific Northwest focused on cropland residue burning was used to evaluate model performance in capturing surface and aloft impacts from the burning events. The Community Multiscale Air Quality (CMAQ) model was used to simulate multiple crop residue burns with 2 km grid spacing using field-specific information and also more general assumptions traditionally used to support National Emission Inventory based assessments. Field study specific information, which includes area burned, fuel consumption, and combustion completeness, resulted in increased biomass consumption by 123 tons (60% increase) on average compared to consumption estimated with default methods in the National Emission Inventory (NEI) process. Buoyancy heat flux, a key parameter for model predicted fire plume rise, estimated from fuel loading obtained from field measurements can be 30% to 200% more than when estimated using default field information. The increased buoyancy heat flux resulted in higher plume rise by 30% to 80%. This evaluation indicates that the regulatory air quality modeling system can replicate intensity and transport (horizontal and vertical) features for crop residue burning in this region when region-specific information is used to inform emissions and plume rise calculations. Further, previous vertical emissions allocation treatment of putting all cropland residue burning in the surface layer does not compare well with measured plume structure and these types of burns should be modeled more similarly to prescribed fires such that plume rise is based on an estimate of buoyancy.

Determination of smoke plume and layer heights using scanning lidar data.

The methodology of using mobile scanning lidar data for investigation of smoke plume rise and high-resolution smoke dispersion is considered. The methodology is based on the lidar-signal transformation proposed recently [Appl. Opt. 48, 2559 (2009)]. In this study, similar methodology is used to create the atmospheric heterogeneity height indicator (HHI), which shows all heights at which the smoke plume heterogeneity was detected by a scanning lidar. The methodology is simple and robust. Subtraction of the initial lidar signal offset from the measured lidar signal is not required. HHI examples derived from lidar scans obtained with the U.S. Forest Service, Fire Sciences Laboratory mobile lidar in areas polluted by wildfires are presented, and the basic details of the methodology are discussed.

High precision measurements of atmospheric nitrous oxide and methane using thermoelectrically cooled mid-infrared quantum cascade lasers and detectors.

A compact, fast response, mid-infrared absorption spectrometer using thermoelectrically (TE) cooled pulsed quantum cascade (QC) lasers and TE detectors has been developed to demonstrate the applicability of QC lasers for high precision measurements of nitrous oxide and methane in the earth's atmosphere. Reduced pressure extractive sampling with a 56 m path length, 0.5 l volume, multiple pass absorption cell allows a time response of <0.1s which is suitable for eddy correlation flux measurements for these gases. Precision of 0.3 ppb (rms, 1s averaging time) or 0.1% of the ambient concentration for N(2)O (4 ppb or 0.2% of ambient for CH(4)), has been demonstrated using QC lasers at 4.5 microm (7.9 microm for CH(4)), corresponding to an absorbance precision of 4 x 10(-5) Hz(-1/2) (8 x 10(-5) Hz(-1/2) for CH(4)). Stabilization of the temperature of the optical bench and the pulse electronics results in a minimum Allan variance corresponding to 0.06 ppb for N(2)O with an averaging time of 100 s (0.7 ppb with an averaging time of 200 s for CH(4)). The instrument is capable of long-term, unattended, continuous operation without cryogenic cooling of either laser or detector.

Response of a deciduous forest to the Mount Pinatubo eruption: enhanced photosynthesis.

Volcanic aerosols from the 1991 Mount Pinatubo eruption greatly increased diffuse radiation worldwide for the following 2 years. We estimated that this increase in diffuse radiation alone enhanced noontime photosynthesis of a deciduous forest by 23% in 1992 and 8% in 1993 under cloudless conditions. This finding indicates that the aerosol-induced increase in diffuse radiation by the volcano enhanced the terrestrial carbon sink and contributed to the temporary decline in the growth rate of atmospheric carbon dioxide after the eruption.