Lessons learned and recommendations in conducting solutions-driven environmental and public health research.

Solutions-driven research is a transdisciplinary approach that incorporates diverse forms of expertise to identify solutions to stakeholder-identified environmental problems. This qualitative evaluation of early solutions-driven research projects provides transferable recommendations to improve researcher and stakeholder experiences and outcomes in transdisciplinary environmental research projects. Researchers with the U.S. Environmental Protection Agency (EPA) Office of Research and Development recently piloted a solutions-driven research approach in two parallel projects; one addressing nutrient management related to coastal waters and another studying wildland fire smoke impacts on indoor air quality. Studying the experiences of those involved with these pilots can enhance the integration of researcher and experiential expertise, improving solutions-driven research outcomes. Data collection included semi-structured interviews with 17 EPA researchers and 12 other stakeholders and reflective case narratives from the authors. We used conventional content analysis to qualitatively analyze perspectives on implementing innovative engagement and research approaches in a solutions-driven process. Findings that reflect common perspectives include the importance of continuous engagement, the challenges of differing timelines and priorities for researchers and stakeholders, and the need to define consistent markers of success across researchers and stakeholders. Key lessons to improve transdisciplinary research identified from the analysis are (1) improving clarity of roles and responsibilities; (2) planning to provide sufficient, continuous project funding over multiple years; (3) expecting research needs and plans to adapt to evolving circumstances; and (4) clearly defining the end of the project.

Wildfires Increase Concentrations of Hazardous Air Pollutants in Downwind Communities.

Due in part to climate change, wildfire activity is increasing, with the potential for greater public health impact from smoke in downwind communities. Studies examining the health effects of wildfire smoke have focused primarily on fine particulate matter (PM2.5), but there is a need to better characterize other constituents, such as hazardous air pollutants (HAPs). HAPs are chemicals known or suspected to cause cancer or other serious health effects that are regulated by the United States (US) Environmental Protection Agency. Here, we analyzed concentrations of 21 HAPs in wildfire smoke from 2006 to 2020 at 309 monitors across the western US. Additionally, we examined HAP concentrations measured in a major population center (San Jose, CA) affected by multiple fires from 2017 to 2020. We found that concentrations of select HAPs, namely acetaldehyde, acrolein, chloroform, formaldehyde, manganese, and tetrachloroethylene, were all significantly elevated on smoke-impacted versus nonsmoke days (P < 0.05). The largest median increase on smoke-impacted days was observed for formaldehyde, 1.3 µg/m3 (43%) higher than that on nonsmoke days. Acetaldehyde increased 0.73 µg/m3 (36%), and acrolein increased 0.14 µg/m3 (34%). By better characterizing these chemicals in wildfire smoke, we anticipate that this research will aid efforts to reduce exposures in downwind communities.

Seasonal Emission Factors from Rangeland Prescribed Burns in the Kansas Flint Hills Grasslands.

Operational-sized prescribed grassland burns at three mid-West U.S. locations and ten 1-ha-sized prescribed grassland burns were conducted in the Flint Hills of Kansas to determine emission factors and their potential seasonal effects. Ground-, aerostat-, and unmanned aircraft system-based platforms were used to sample plume emissions for a range of gaseous and particulate pollutants. The ten co-located, 1-ha-sized plots allowed for testing five plots in the spring and five in the late summer, allowing for control of vegetation type, biomass loading, climate history, and land use. The operational-sized burns provided a range of conditions under which to determine emission factors relevant to the Flint Hills grasslands. The 1-ha plots showed that emission factors for pollutants such as PM2.5 and BTEX (benzene, toluene, ethylbenzene, and xylene) were higher during the late summer than during the traditional spring burn season. This is likely due to increased biomass density and fuel moisture in the growing season biomass resulting in reduced combustion efficiency.

Beyond Particulate Matter Mass: Heightened Levels of Lead and Other Pollutants Associated with Destructive Fire Events in California.

As the climate warms, wildfire activity is increasing, posing a risk to human health. Studies have reported on particulate matter (PM) in wildfire smoke, yet the chemicals associated with PM have received considerably less attention. Here, we analyzed 13 years (2006-2018) of PM2.5 chemical composition data from monitors in California on smoke-impacted days. Select chemicals (e.g., aluminum and sulfate) were statistically elevated on smoke-impacted days in over half of the years studied. Other chemicals, mostly trace metals harmful to human health (e.g., copper and lead), were elevated during particular fires only. For instance, in 2018, lead was more than 40 times higher on smoke days on average at the Point Reyes monitoring station, due mostly to the Camp Fire, burning approximately 200 km away. There was an association between these metals and the combustion of anthropogenic material (e.g., the burning of houses and vehicles). Although still currently rare, these infrastructure fires are likely becoming more common and can mobilize trace metals in smoke far downwind, at levels generally unseen except in the most polluted areas of the country. We hope a better understanding of the chemicals in wildfire smoke will assist in the communication and reduction of public health risks.

Impact of do-it-yourself air cleaner design on the reduction of simulated wildfire smoke in a controlled chamber environment.

During wildfire smoke events public health agencies release advisories to stay indoors, close doors and windows, and operate a portable air cleaner (PAC). The do-it-yourself (DIY) air cleaner consisting of a box fan and a furnace filter is a widely used low-cost alternative to commercial PACs because of its increased accessibility. In this study, we evaluate the clean air delivery rate (CADR) of different DIY air cleaner designs for reducing simulated wildfire smoke and identify operating parameters that may impact their performance and use. The simplest formulation of a DIY air cleaner (box fan with taped on minimum effectiveness reporting value - [MERV] 13 furnace filter) had a CADR of 111.2 ± 1.3 ft3 /min (CFM). Increasing the fan flow by changing the fan type, increasing the fan setting, or reducing the pressure drop across the filtering surface increased the CADR. Large increases in CADR could be obtained by using a shroud (40%), using a 4″ thick filter (123%) using two filters in a wedge shape (137%), or using four filters in a Corsi-Rosenthal (CR) box design (261%). The CADR was greatly reduced with filters heavily loaded with smoke, pointing to the need for frequent filter changes during smoke events.

Correction and Accuracy of PurpleAir PM2.5 Measurements for Extreme Wildfire Smoke.

PurpleAir particulate matter (PM) sensors are increasingly used in the United States and other countries for real-time air quality information, particularly during wildfire smoke episodes. Uncorrected PurpleAir data can be biased and may exhibit a nonlinear response at extreme smoke concentrations (>300 µg/m3). This bias and nonlinearity result in a disagreement with the traditional ambient monitoring network, leading to the public's confusion during smoke episodes. These sensors must be evaluated during smoke-impacted times and then corrected for bias, to ensure that accurate data are reported. The nearby public PurpleAir sensor and monitor pairs were identified during the summer of 2020 and were used to supplement the data from collocated pairs to develop an extended U.S.-wide correction for high concentrations. We evaluated several correction schemes to identify an optimal correction, using the previously developed U.S.-wide correction, up to 300 µg/m3, transitioning to a quadradic fit above 400 µg/m3. The correction reduces the bias at each air quality index (AQI) breakpoint; most ambient collocations that were studied met the Environmental Protection Agency's (EPA) performance targets (twelve of the thirteen ambient sensors met the EPA's targets) and some smoke-impacted sites (5 out of 15 met the EPA's performance targets in terms of the 1-h averages). This correction can also be used to improve the comparability of PurpleAir sensor data with regulatory-grade monitors when they are collectively analyzed or shown together on public information websites; the methods developed in this paper can also be used to correct future air-sensor types. The PurpleAir network is already filling in spatial and temporal gaps in the regulatory monitoring network and providing valuable air-quality information during smoke episodes.

Monoterpenes are the largest source of summertime organic aerosol in the southeastern United States.

The chemical complexity of atmospheric organic aerosol (OA) has caused substantial uncertainties in understanding its origins and environmental impacts. Here, we provide constraints on OA origins through compositional characterization with molecular-level details. Our results suggest that secondary OA (SOA) from monoterpene oxidation accounts for approximately half of summertime fine OA in Centreville, AL, a forested area in the southeastern United States influenced by anthropogenic pollution. We find that different chemical processes involving nitrogen oxides, during days and nights, play a central role in determining the mass of monoterpene SOA produced. These findings elucidate the strong anthropogenic-biogenic interaction affecting ambient aerosol in the southeastern United States and point out the importance of reducing anthropogenic emissions, especially under a changing climate, where biogenic emissions will likely keep increasing.

Field Evaluation of Low-Cost Particulate Matter Sensors for Measuring Wildfire Smoke.

Until recently, air quality impacts from wildfires were predominantly determined based on data from permanent stationary regulatory air pollution monitors. However, low-cost particulate matter (PM) sensors are now widely used by the public as a source of air quality information during wildfires, although their performance during smoke impacted conditions has not been thoroughly evaluated. We collocated three types of low-cost fine PM (PM2.5) sensors with reference instruments near multiple fires in the western and eastern United States (maximum hourly PM2.5 = 295 µg/m3). Sensors were moderately to strongly correlated with reference instruments (hourly averaged r2 = 0.52-0.95), but overpredicted PM2.5 concentrations (normalized root mean square errors, NRMSE = 80-167%). We developed a correction equation for wildfire smoke that reduced the NRMSE to less than 27%. Correction equations were specific to each sensor package, demonstrating the impact of the physical configuration and the algorithm used to translate the size and count information into PM2.5 concentrations. These results suggest the low-cost sensors can fill in the large spatial gaps in monitoring networks near wildfires with mean absolute errors of less than 10 µg/m3 in the hourly PM2.5 concentrations when using a sensor-specific smoke correction equation.

Assessing PM2.5 Model Performance for the Conterminous U.S. with Comparison to Model Performance Statistics from 2007-2015.

Previous studies have proposed that model performance statistics from earlier photochemical grid model (PGM) applications can be used to benchmark performance in new PGM applications. A challenge in implementing this approach is that limited information is available on consistently calculated model performance statistics that vary spatially and temporally over the U.S. Here, a consistent set of model performance statistics are calculated by year, season, region, and monitoring network for PM2.5 and its major components using simulations from versions 4.7.1-5.2.1 of the Community Multiscale Air Quality (CMAQ) model for years 2007-2015. The multi-year set of statistics is then used to provide quantitative context for model performance results from the 2015 simulation. Model performance for PM2.5 organic carbon in the 2015 simulation ranked high (i.e., favorable performance) in the multi-year dataset, due to factors including recent improvements in biogenic secondary organic aerosol and atmospheric mixing parameterizations in CMAQ. Model performance statistics for the Northwest region in 2015 ranked low (i.e., unfavorable performance) for many species in comparison to the 2007-2015 dataset. This finding motivated additional investigation that suggests a need for improved speciation of wildfire PM2.5emissions and modeling of boundary layer dynamics near water bodies. Several limitations were identified in the approach of benchmarking new model performance results with previous results. Since performance statistics vary widely by region and season, a simple set of national performance benchmarks (e.g., one or two targets per species and statistic) as proposed previously are inadequate to assess model performance throughout the U.S. Also, trends in model performance statistics for sulfate over the 2007 to 2015 period suggest that model performance for earlier years may not be a useful reference for assessing model performance for recent years in some cases. Comparisons of results from the 2015 base case with results from five sensitivity simulations demonstrated the importance of parameterizations of NH3 surface exchange, organic aerosol volatility and production, and emissions of crustal cations for predicting PM2.5 species concentrations.

Light Absorption of Secondary Organic Aerosol: Composition and Contribution of Nitroaromatic Compounds.

Secondary organic aerosol (SOA) can affect the atmospheric radiation balance through absorbing light at shorter visible and UV wavelengths. However, the composition and optical properties of light-absorbing SOA is poorly understood. In this work, SOA filter samples were collected during individual chamber experiments conducted with three biogenic and eight aromatic volatile organic compound (VOC) precursors in the presence of NOX and H2O2. Compared with the SOA generated using the aromatic precursors, biogenic SOA generally exhibits negligible light absorption above 350 nm; the aromatic SOA generated in the presence of NOX shows stronger light absorption than that generated with H2O2. Fifteen nitroaromatic compound (NAC) chemical formulas were identified and quantified in SOA samples. Their contributions to the light absorption of sample extracts were also estimated. On average, the m-cresol/NOX SOA sample has the highest mass contribution from NACs (10.4 ± 6.74%, w/w), followed by naphthalene/NOX (6.41 ± 2.08%) and benzene/NOX (5.81 ± 3.82%) SOA. The average contributions of NACs to total light absorption were at least two times greater than their average mass contributions at 365 and 400 nm, revealing the potential use of chromophoric NACs as brown carbon (BrC) tracers in source apportionment and air quality modeling studies.

Effects of Aftermarket Control Technologies on Gas and Particle Phase Oxidative Potential from Diesel Engine Emissions.

Particulate matter (PM) originating from diesel combustion is a public health concern due to its association with adverse effects on respiratory and cardiovascular diseases and lung cancer. This study investigated emissions from three stationary diesel engines (gensets) and varying power output (230 kW, 400 kW, and 600 kW) at 50% and 90% load to determine concentrations of gaseous (GROS) and PM reactive oxygen species (PMROS). In addition, the influence of three modern emission control technologies on ROS emissions was evaluated: active and passive diesel particulate filters (A-DPF and P-DPF) and a diesel oxidation catalyst (DOC). PMROS made up 30-50% of the total ROS measured without aftermarket controls. All applied controls removed PMROS by more than 75% on average. However, the oxidative potential of PM downstream of these devices was not diminished at the same rate and particles surviving the A-PDF had an even higher oxidative potential on a per PM mass basis compared to the particles emitted by uncontrolled gensets. Further, the GROS as compared to PMROS emissions were not reduced with the same efficiency (<36%). GROS concentrations were highest with the DOC in use, indicating continued formation of GROS with this control. Correlation analyses showed that PMROS and to a lesser extent GROS have a good correlation with semivolatile organic carbon (OC1) subfraction. In addition, results suggest that chemical composition, rather than PM size, is responsible for differences in the PM oxidative potential.

Gas and particle emissions from rifle and pistol firing.

Emissions were sampled from firing an M4 carbine rifle and a M9 (military issue of Beretta 75 FS 9 mm pistol) to develop sampling methods and assess potential exposures and range contamination issues. Breech and muzzle emissions were sampled from the rifle when firing M855A1 ammunition (lead (Pb)-free slugs) in single- and triple-shot burst mode and from single pistol shots when firing 9 mm XM1152 ammunition (not Pb-free). Emissions were sampled for carbon monoxide (CO), carbon dioxide (CO2), methane, hydrogen cyanide, ammonia, particulate matter by size, polycylic aromatic hydrocarbons, and volatile organics. Analyses on the particles included elemental composition, size distribution, carbon composition (black, total, organic, and elemental carbon), and particle composition and morphology. Emission concentrations from both the rifle and pistol were characterized by CO/CO2 ratios between, approximately, 1/1 and 2/1, respectfully, indicating incomplete carbon oxidation. The initial particle size distribution was dominated in number by particles smaller than 40 nm but the high particle concentrations led to rapid agglomeration. The abundance of CO and metals of inhalable particle size are noteworthy and indicate that further assessment of exposure would determine potential inhalation health hazards, particularly in indoor firing ranges.

Self-reported health impacts of do-it-yourself air cleaner use in a smoke-impacted community.

Background: Smoke exposure from wildfires or residential wood burning for heat is a public health problem for many communities. Do-It-Yourself (DIY) portable air cleaners (PACs) are promoted as affordable alternatives to commercial PACs, but evidence of their effect on health outcomes is limited. Objective: Pilot test an evaluation of the effect of DIY PAC usage on self-reported symptoms, and investigate barriers and facilitators of PAC use, among members of a tribal community that routinely experiences elevated concentrations of fine particulate matter (PM2.5) from smoke. Methods: We conducted studies in Fall 2021 ("wildfire study"; N = 10) and Winter 2022 ("wood stove study"; N = 17). Each study included four sequential one-to-two-week phases: 1) initial, 2) DIY PAC usage ≥8 h/day, 3) commercial PAC usage ≥8 h/day, and 4) air sensor with visual display and optional PAC use. We continuously monitored PAC usage and indoor/outdoor PM2.5 concentrations in homes. Concluding each phase, we conducted phone surveys about participants' symptoms, perceptions, and behaviors. We analyzed symptoms associated with PAC usage and conducted an analysis of indoor PM2.5 concentrations as a mediating pathway using mixed effects multivariate linear regression. We categorized perceptions related to PACs into barriers and facilitators of use. Results: No association was observed between PAC usage and symptoms, and the mediation analysis did not indicate that small observed trends were attributable to changes in indoor PM2.5 concentrations. Small sample sizes hindered the ability to draw conclusions regarding the presence or absence of causal associations. DIY PAC usage was low; loud operating noise was a barrier to use. Discussion: This research is novel in studying health effects of DIY PACs during wildfire and wood smoke exposures. Such research is needed to inform public health guidance. Recommendations for future studies on PAC use during smoke exposure include building flexibility of intervention timing into the study design.

Emissions of polycyclic aromatic hydrocarbons, polychlorinated dibenzo-p-dioxins, and dibenzofurans from incineration of nanomaterials.

Disposal of some nanomaterial-laden waste through incineration is inevitable, and nanomaterials' influence on combustion byproduct formation under high-temperature, oxidative conditions is not well understood. This work reports the formation of polycyclic aromatic hydrocarbons (PAHs) and polychlorinated-dibenzo-p-dioxins and dibenzofurans (PCDD/Fs) from incineration of paper and plastic waste containing various nanomaterials, including titania, nickel oxide, silver, ceria, iron oxide, quantum dots, and C60-fullerene, in a laboratory-scale furnace. The presence of nanomaterials in the waste stream resulted in higher emissions of some PAH species and lower emissions of others, depending on the type of waste. The major PAH species formed were phenanthrene and anthracene, and emissions were sensitive to the amount of nanomaterials in the waste. Generally, there were no significant differences in emission factors for the larger PAH species when nanomaterials were added to the waste. The total PAH emission factors were on average ~6 times higher for waste spiked with nanomaterials v. their bulk counterparts. Emissions of chlorinated dioxins from poly(vinyl chloride) (PVC) waste were not detected; however, chlorinated furans were formed at elevated concentrations with wastes containing silver and titania nanomaterials, and toxicity was attributable mainly to 2,3,4,7,8-pentachlorodibenzofuran. The combination of high specific surface area and catalytic, including electrocatalytic, properties of nanomaterials might be responsible for affecting the formation of toxic pollutants during incineration.

Particulate Pb emission factors from wildland fires in the United States.

Wildland fires, which includes both wild and prescribed fires, and agricultural fires in sum are one of the largest sources of fine particulate matter (PM2.5) emissions to the atmosphere in the United States (US). Although wildland fire PM2.5 emissions are primarily composed of carbonaceous material, many other elements including trace metals are emitted at very low levels. Lead (Pb) is a US Environmental Protection Agency (EPA) criteria pollutant that is ubiquitous in the environment at very low concentrations including in biomass that can burn and emit Pb into the atmosphere. Although fires may emit Pb at very low concentrations, they can be a source of sizeable Pb emissions to the atmosphere because of the large quantity of PM2.5 emitted from fires. In this work, we measure Pb concentrations in unburned biomass, ash/residues, and particulate matter <2.5 µm (PM2.5) emitted from wildland fires using in-field measurements near prescribed fires and in laboratory simulations. Emission factors were calculated for multiple biomass types, representative of different regions of the US including grasslands in Oregon and Kansas; forest litter from Oregon, Montana, Minnesota, and North Carolina; and peat cores from Minnesota. Most of the biomass Pb remains in the ash/residues. The small percentage (<10%) that is emitted in PM2.5 is dependent on the biomass Pb concentration. The emissions factors measured here are several orders of magnitude lower than some reported in the literature, but the studies exhibited a wide range of values, which may be due to large uncertainties in the measurement method rather than differences in Pb emissions. Wildland fires are expected to increase in size and frequency in future years and these new emission factors can be used to improve the accuracy of Pb emissions estimates and better constrain our understanding of Pb emissions to the atmosphere.

Hazardous air pollutant emissions estimates from wildfires in the wildland urban interface.

Fires that occur in the wildland urban interface (WUI) often burn structures, vehicles, and their contents in addition to biomass in the natural landscape. Because these fires burn near population centers, their emissions may have a sizeable impact on public health, necessitating a better understanding of criteria and hazardous air pollutants emitted from these fires and how they differ from wildland fires. Previous studies on the toxicity of emissions from the combustion of building materials and vehicles have shown that urban fires may emit numerous toxic species such as hydrogen cyanide, hydrogen fluoride, hydrogen chloride, isocyanates, polycyclic aromatic hydrocarbons (PAHs), dioxins and furans, and a range of toxic organic compounds (e.g. benzene toluene, xylenes, styrene, and formaldehyde) and metals (e.g. lead, chromium, cadmium, and arsenic). We surveyed the literature to create a compendium of emission factors for species emitted from the combustion of building and vehicle materials and compared them with those from wildland fires. Emission factors for some toxic species like PAH and some organic compounds were several orders of magnitude greater than those from wildfires. We used this emission factor compendium to calculate a bounding estimate of the emissions from several notable WUI fires in the western United States to show that urban fuels may contribute a sizeable portion of the toxic emissions into the atmosphere. However, large gaps remain in our understanding of the fuel composition, fuel consumption, and combustion conditions in WUI fires that constrain our ability to estimate the impact of WUI fires.

Development of Volatility Distributions for Organic Matter in Biomass Burning Emissions.

The volatility distribution of organic emissions from biomass burning and other combustion sources can determine their atmospheric evolution due to partitioning/aging. The gap between measurements and models predicting secondary organic aerosol has been partially attributed to the absence of semi- and intermediate volatility organic compounds (S/I-VOC) in models and measurements. However, S/I-VOCs emitted from these sources and typically quantified using the volatility basis framework (VBS) are not well understood. For example, the amount and composition of S/I-VOCs and their variability across different biomass burning sources such as residential woodstoves, open field burns, and laboratory simulated open burning are uncertain. To address this, a novel filter-in-tube sorbent tube sampling method collected S/I-VOC samples from biomass burning experiments for a range of fuels and combustion conditions. Filter-in-tube samples were analyzed using thermal desorption-gas chromatography-mass spectrometry (TD/GC/MS) for compounds across a wide range of volatilities (saturation concentrations; -2 ≤ logC* ≤ 6). The S/I-VOC measurements were used to calculate volatility distributions for each emissions source. The distributions were broadly consistent across the sources with IVOCs accounting for 75% - 90% of the total captured organic matter, while SVOCs and LVOCs were responsible for 6% - 13% and 1% - 12%, respectively. The distributions and predicted partitioning were generally consistent with literature. Particulate matter emission factors spanned two orders of magnitude across the sources. This work highlights the potential of inferring gas-particle partitioning behavior of biomass burning emissions using filter-in-tube sorbent samples analyzed offline. This simplifies both sampling and analysis of S/I-VOCs for studies focused on capturing the full range of organics emitted.

Particle-induced artifacts in the MTT and LDH viability assays.

In vitro testing is a common first step in assessing combustion-generated and engineered nanoparticle-related health hazards. Commercially available viability assays are frequently used to compare the toxicity of different particle types and to generate dose-response data. Nanoparticles, well-known for having large surface areas and chemically active surfaces, may interfere with viability assays, producing a false assessment of toxicity and making it difficult to compare toxicity data. The objective of this study is to measure the extent of particle interference in two common viability assays, the MTT reduction and the lactate dehydrogenase (LDH) release assays. Diesel particles, activated carbon, flame soot, oxidized flame soot, and titanium dioxide particles are assessed for interactions with the MTT and LDH assay under cell-free conditions. Diesel particles, at concentrations as low as 0.05 µg/mL, reduce MTT. Other particle types reduce MTT only at a concentration of 50 µg/mL and higher. The activated carbon, soot, and oxidized soot particles bind LDH to varying extents, reducing the concentration measured in the LDH assay. The interfering effects of the particles explain in part the different toxicities measured in human bronchial epithelial cells (16HBE14o). We conclude that valid particle toxicity assessments can only be assured after first performing controls to verify that the particles under investigation do not interfere with a specific assay at the expected concentrations.