Utilization of a Low-Cost Sensor Array for Mobile Methane Monitoring.

The use of low-cost sensors (LCSs) for the mobile monitoring of oil and gas emissions is an understudied application of low-cost air quality monitoring devices. To assess the efficacy of low-cost sensors as a screening tool for the mobile monitoring of fugitive methane emissions stemming from well sites in eastern Colorado, we colocated an array of low-cost sensors (XPOD) with a reference grade methane monitor (Aeris Ultra) on a mobile monitoring vehicle from 15 August through 27 September 2023. Fitting our low-cost sensor data with a bootstrap and aggregated random forest model, we found a high correlation between the reference and XPOD CH4 concentrations (r = 0.719) and a low experimental error (RMSD = 0.3673 ppm). Other calibration models, including multilinear regression and artificial neural networks (ANN), were either unable to distinguish individual methane spikes above baseline or had a significantly elevated error (RMSDANN = 0.4669 ppm) when compared to the random forest model. Using out-of-bag predictor permutations, we found that sensors that showed the highest correlation with methane displayed the greatest significance in our random forest model. As we reduced the percentage of colocation data employed in the random forest model, errors did not significantly increase until a specific threshold (50 percent of total calibration data). Using a peakfinding algorithm, we found that our model was able to predict 80 percent of methane spikes above 2.5 ppm throughout the duration of our field campaign, with a false response rate of 35 percent.

Photochemical Aging of Atmospheric Particulate Matter in the Aqueous Phase.

This study focused on the photoaging of atmospheric particulate matter smaller than 2.5 µm (PM2.5) in the aqueous phase. PM2.5 was collected during a winter, a spring, and a summer campaign in urban and rural settings in Colorado and extracted into water. The aqueous extracts were photoirradiated using simulated sunlight, and the production rate (r•OH) and the effects of hydroxyl radicals (•OH) were measured as well as the optical properties as a function of the photoaging of the extracts. r•OH was seen to have a strong seasonality with low mean values for the winter and spring extracts (4.8 and 14 fM s-1 mgC-1 L, respectively) and a higher mean value for the summer extracts (65.4 fM s-1 mgC-1 L). For the winter extracts, •OH was seen to mostly originate from nitrate photolysis while for the summer extracts, a correlation was seen between r•OH and iron concentration. The extent of photobleaching of the extracts was correlated with r•OH, and the correlation also indicated that non-•OH processes took place. Using the •OH measurements and singlet oxygen (1O2) measurements, the half-life of a selection of compounds was modeled in the atmospheric aqueous phase to be between 1.9 and 434 h.

Health impacts of a randomized biomass cookstove intervention in northern Ghana.

BACKGROUND: Household air pollution (HAP) from cooking with solid fuels has adverse health effects. REACCTING (Research on Emissions, Air quality, Climate, and Cooking Technologies in Northern Ghana) was a randomized cookstove intervention study that aimed to determine the effects of two types of "improved" biomass cookstoves on health using self-reported health symptoms and biomarkers of systemic inflammation from dried blood spots for female adult cooks and children, and anthropometric growth measures for children only. METHODS: Two hundred rural households were randomized into four different cookstove groups. Surveys and health measurements were conducted at four time points over a two-year period. Chi-square tests were conducted to determine differences in self-reported health outcomes. Linear mixed models were used to assess the effect of the stoves on inflammation biomarkers in adults and children, and to assess the z-score deviance for the anthropometric data for children. RESULTS: We find some evidence that two biomarkers of oxidative stress and inflammation, serum amyloid A and C-reactive protein, decreased among adult primary cooks in the intervention groups relative to the control group. We do not find detectable impacts for any of the anthropometry variables or self-reported health. CONCLUSIONS: Overall, we conclude that the REACCTING intervention did not substantially improve the health outcomes examined here, likely due to continued use of traditional stoves, lack of evidence of particulate matter emissions reductions from "improved" stoves, and mixed results for HAP exposure reductions. CLINICAL TRIAL REGISTRY: ClinicalTrials.gov (National Institutes of Health); Trial Registration Number: NCT04633135 ; Date of Registration: 11 November 2020 - Retrospectively registered. URL: https://clinicaltrials.gov/ct2/show/NCT04633135?term=NCT04633135&draw=2&rank=1.

Using Gas-Phase Air Quality Sensors to Disentangle Potential Sources in a Los Angeles Neighborhood.

In the late summer of 2016, our team deployed a network of low-cost air quality sensing systems in partnership with community-based organizations in a neighborhood in South Los Angeles, California. Residents of this community were concerned about possible emissions from local oil and gas activity, however in addition to these potential emissions, the neighborhood is also subject to a complex mixture of pollutants from other nearby sources including major highways. For this deployment, metal-oxide VOC sensors were quantified to provide methane (CH4) and total non-methane hydrocarbon (TNMHCs) concentration estimates. This data along with other sensor signals, meteorological data, and community member observations was used to examine the composition and possible origins of observed emissions. The sensor network displayed expected environmental trends and highlighted short-term elevations in CH4 and/or TNMHCs, which we were then able to investigate more closely. The results indicated that sources of both combusted and volatilized hydrocarbons were likely affecting air quality throughout the community, including near the site of the local oil and gas activity. This deployment may serve as a model for how multi-sensor systems deployed in networks can be leveraged to better understand sources in complex areas, potentially supporting future community-based air quality research.

Updated Emission Factors from Diffuse Combustion Sources in Sub-Saharan Africa and Their Effect on Regional Emission Estimates.

Diffuse emission sources outside of kitchen areas are poorly understood, and measurements of their emission factors (EFs) are sparse for regions of sub-Saharan Africa. Thirty-one in-field emission measurements were taken in northern Ghana from combustion sources common to rural regions worldwide. Sources sampled included commercial cooking, trash burning, kerosene lanterns, and diesel generators. EFs were calculated for carbon monoxide (CO), carbon dioxide (CO2), as well as carbonaceous particulate matter, specifically elemental carbon (EC) and organic carbon (OC). EC and OC emissions were measured from kerosene lighting events (EFEC = 25.1 g/kg-fuel SD = 25.7, EFOC = 9.5 g/kg-fuel SD = 10.0). OC emissions from trash burning events were large and highly variable (EFOC = 38.9 g/kg-fuel SD = 30.5). Combining our results with other recent in-field emission factors for rural Ghana, we explored updated emission estimates for Ghana using a region specific emissions inventory. Large differences are calculated for all updated source emissions, showing a 96% increase in OC and 78% decrease in EC compared to prior estimates for Ghana's emissions. Differences for carbon monoxide were small when averaged across all updated source types (-1%), though the household wood use and trash burning categories individually show large differences.

Using A Low-Cost Sensor Array and Machine Learning Techniques to Detect Complex Pollutant Mixtures and Identify Likely Sources.

An array of low-cost sensors was assembled and tested in a chamber environment wherein several pollutant mixtures were generated. The four classes of sources that were simulated were mobile emissions, biomass burning, natural gas emissions, and gasoline vapors. A two-step regression and classification method was developed and applied to the sensor data from this array. We first applied regression models to estimate the concentrations of several compounds and then classification models trained to use those estimates to identify the presence of each of those sources. The regression models that were used included forms of multiple linear regression, random forests, Gaussian process regression, and neural networks. The regression models with human-interpretable outputs were investigated to understand the utility of each sensor signal. The classification models that were trained included logistic regression, random forests, support vector machines, and neural networks. The best combination of models was determined by maximizing the F1 score on ten-fold cross-validation data. The highest F1 score, as calculated on testing data, was 0.72 and was produced by the combination of a multiple linear regression model utilizing the full array of sensors and a random forest classification model.

Prices, peers, and perceptions (P3): study protocol for improved biomass cookstove project in northern Ghana.

BACKGROUND: Despite their potential health and social benefits, adoption and use of improved cookstoves has been low throughout much of the world. Explanations for low adoption rates of these technologies include prices that are not affordable for the target populations, limited opportunities for households to learn about cookstoves through peers, and perceptions that these technologies are not appropriate for local cooking needs. The P3 project employs a novel experimental design to explore each of these factors and their interactive effects on cookstove demand, adoption, use and exposure outcomes. METHODS: The P3 study is being conducted in the Kassena-Nankana Districts of Northern Ghana. Leveraging an earlier improved cookstove study that was conducted in this area, the central design of the P3 biomass stove experiment involves offering stoves at randomly varying prices to peers and non-peers of households that had previously received stoves for free. Using household surveys, electronic stove use monitors, and low-cost, portable monitoring equipment, we measure how prices and peers' experience affect perceptions of stove quality, the decision to purchase a stove, use of improved and traditional stoves over time, and personal exposure to air pollutants from the stoves. DISCUSSION: The challenges that public health and development communities have faced in spreading adoption of potentially welfare-enhancing technologies, like improved cookstoves, have highlighted the need for interdisciplinary, multisectoral approaches. The design of the P3 project draws on economic theory, public health practice, engineering, and environmental sciences, to more fully grasp the drivers and barriers to expanding access to and uptake of cleaner stoves. Our partnership between academic institutions, in the US and Ghana, and a local environmental non-governmental organization creates unique opportunities to disseminate and scale up lessons learned. TRIAL REGISTRATION: ClinicalTrials.gov NCT03617952 7/31/18 (Retrospectively Registered).

Comparing Building and Neighborhood-Scale Variability of CO2 and O3 to Inform Deployment Considerations for Low-Cost Sensor System Use.

The increased use of low-cost air quality sensor systems, particularly by communities, calls for the further development of best-practices to ensure these systems collect usable data. One area identified as requiring more attention is that of deployment logistics, that is, how to select deployment sites and how to strategically place sensors at these sites. Given that sensors are often placed at homes and businesses, ideal placement is not always possible. Considerations such as convenience, access, aesthetics, and safety are also important. To explore this issue, we placed multiple sensor systems at an existing field site allowing us to examine both neighborhood-level and building-level variability during a concurrent period for CO2 (a primary pollutant) and O3 (a secondary pollutant). In line with previous studies, we found that local and transported emissions as well as thermal differences in sensor systems drive variability, particularly for high-time resolution data. While this level of variability is unlikely to affect data on larger averaging scales, this variability could impact analysis if the user is interested in high-time resolution or examining local sources. However, with thoughtful placement and thorough documentation, high-time resolution data at the neighborhood level has the potential to provide us with entirely new information on local air quality trends and emissions.

-NOD Mice Having a Lyn Tyrosine Kinase Mutation Exhibit Abnormal Neutrophil Chemotaxis.

Neutrophils from NOD (Non-Obese Diabetic) mice exhibited reduced migration speed, decreased frequency of directional changes, and loss of directionality during chemotaxis (compared to wild-type [WT] C57BL/6 mice). Additionally, F-actin of chemotaxing NOD neutrophils failed to orient toward the chemoattractant gradient and NOD neutrophil adhesion was impaired. A point mutation near the autophosphorylation site of Lyn in NOD mice was identified. Point mutations of G to A (G1412 in LynA and G1199 in LynB) cause a change of amino acid E393 (glutamic acid) to K (lysine) in LynA (E393 →K) (E372 of LynB), affecting fMLP-induced tyrosine phosphorylation. These data indicate that the Lyn mutation in NOD neutrophils is likely responsible for dysregulation of neutrophil adhesion and directed migration, implying the role of Lyn in modulating diabetic patient's susceptibility to bacterial and fungal infections. J. Cell. Physiol. 232: 1689-1695, 2017. © 2016 Wiley Periodicals, Inc.

Improving present day and future estimates of anthropogenic sectoral emissions and the resulting air quality impacts in Africa.

The African continent is undergoing immense social and economic change, particularly regarding population growth and urbanization, where the urban population in Africa is anticipated to increase by a factor of 3 over the next 40 years. To understand the potential health impacts from this demographical shift and design efficient emission mitigation strategies, we used improved Africa-specific emissions that account for inefficient combustion sources for a number of sectors such as transportation, household energy generation, waste burning, and home heating and cooking. When these underrepresented emissions sources are combined with the current estimates of emissions in Africa, ambient particulate matter concentrations from present-day anthropogenic activity contribute to 13 210 annual premature deaths, with the largest contributions (38%) coming from residential emissions. By scaling both the population and the emissions for projected national-scale levels of growth, the predicted health impact grows to approximately 78 986 annual premature deaths by 2030 with 45% now resulting from emissions related to energy combustion. In order to mitigate this resulting increase in premature deaths, three scenarios have been developed which reduce sector-specific future emissions based on prior targets for technological improvements and emission controls in transportation, energy production and residential activities. These targeted potential mitigation strategies can avoid up to 37% of the estimated annual premature deaths by 2030 with the largest opportunity being a reduction of 10 868 annual deaths from switching half of the energy generation in South Africa to renewable technologies.

New Emission Factors and Efficiencies from in-Field Measurements of Traditional and Improved Cookstoves and Their Potential Implications.

Household cooking using solid biomass fuels is a major global health and environmental concern. As part of the Research on Emissions Air quality Climate and Cooking Technologies in Northern Ghana study, we conducted 75 in-field uncontrolled cooking tests designed to assess emissions and efficiency of the Gyapa woodstove, Philips HD4012, threestone fire and coalpot (local charcoal stove). Emission factors (EFs) were calculated for carbon monoxide (CO), carbon dioxide (CO2), and particulate matter (PM). Moreover, modified combustion (MCE), heat transfer (HTE) and overall thermal efficiencies (OTE) were calculated across a variety of fuel, stove and meal type combinations. Mixed effect models suggest that compared to traditional stove/fuel combinations, the Philips burning wood or charcoal showed significant fuel and energy based EF differences for CO, but no significant PM changes with wood fuel. MCEs were significantly higher for Philips wood and charcoal-burning stoves compared to the threestone fire and coalpot. The Gyapa emitted significantly higher ratios of elemental to organic carbon. Fuel moisture, firepower and MCE fluctuation effects on stove performance were investigated with mixed findings. Results show agreement with other in-field findings and discrepancies with some lab-based findings, with important implications for estimated health and air quality impacts.

Quantifying Neighborhood-Scale Spatial Variations of Ozone at Open Space and Urban Sites in Boulder, Colorado Using Low-Cost Sensor Technology.

Recent advances in air pollution sensors have led to a new wave of low-cost measurement systems that can be deployed in dense networks to capture small-scale spatio-temporal variations in ozone, a pollutant known to cause negative human health impacts. This study deployed a network of seven low-cost ozone metal oxide sensor systems (UPods) in both an open space and an urban location in Boulder, Colorado during June and July of 2015, to quantify ozone variations on spatial scales ranging from 12 m between UPods to 6.7 km between open space and urban measurement sites with a measurement uncertainty of ~5 ppb. The results showed spatial variability of ozone at both deployment sites, with the largest differences between UPod measurements occurring during the afternoons. The peak median hourly difference between UPods was 6 ppb at 1:00 p.m. at the open space site, and 11 ppb at 4:00 p.m. at the urban site. Overall, the urban ozone measurements were higher than in the open space measurements. This study evaluates the effectiveness of using low-cost sensors to capture microscale spatial and temporal variation of ozone; additionally, it highlights the importance of field calibrations and measurement uncertainty quantification when deploying low-cost sensors.

Low-Cost Air Quality Monitoring Tools: From Research to Practice (A Workshop Summary).

In May 2017, a two-day workshop was held in Los Angeles (California, U.S.A.) to gather practitioners who work with low-cost sensors used to make air quality measurements. The community of practice included individuals from academia, industry, non-profit groups, community-based organizations, and regulatory agencies. The group gathered to share knowledge developed from a variety of pilot projects in hopes of advancing the collective knowledge about how best to use low-cost air quality sensors. Panel discussion topics included: (1) best practices for deployment and calibration of low-cost sensor systems, (2) data standardization efforts and database design, (3) advances in sensor calibration, data management, and data analysis and visualization, and (4) lessons learned from research/community partnerships to encourage purposeful use of sensors and create change/action. Panel discussions summarized knowledge advances and project successes while also highlighting the questions, unresolved issues, and technological limitations that still remain within the low-cost air quality sensor arena.

The short-term association of selected components of fine particulate matter and mortality in the Denver Aerosol Sources and Health (DASH) study.

BACKGROUND: Associations of short-term exposure to fine particulate matter (PM2.5) with daily mortality may be due to specific PM2.5 chemical components. Daily concentrations of PM2.5 components were measured over five years in Denver to investigate whether specific PM2.5 components are associated with daily mortality. METHODS: Daily counts of total and cause-specific deaths were obtained for the 5-county Denver metropolitan region from 2003 through 2007. Daily 24-hour concentrations of PM2.5, elemental carbon (EC), organic carbon (OC), sulfate and nitrate were measured at a central residential monitoring site. Using generalized additive models, we estimated relative risks (RRs) of daily death counts for daily PM2.5 and four PM2.5 component concentrations at single and distributed lags between the current and three previous days, while controlling for longer-term time trend and meteorology. RESULTS: RR of total non-accidental mortality for an inter-quartile increase of 4.55 µg/m(3) in PM2.5 distributed over 4 days was 1.012 (95 % confidence interval: 0.999, 1.025); RRs for EC and OC were larger (1.024 [1.005, 1.043] and 1.020 [1.000, 1.040] for 0.33 and 1.67 µg/m(3) increases, respectively) than those for sulfate and nitrate. We generally did not observe associations with cardiovascular and respiratory mortality except for associations with ischemic heart disease mortality at lags 3 and 0-3 depending on the component. In addition, there were associations with cancer mortality, particularly for EC and OC, possibly reflecting advanced deaths of a frail population. CONCLUSIONS: PM2.5 components possibly from combustion-related sources are more strongly associated with daily mortality than are secondary inorganic aerosols.

Research on Emissions, Air quality, Climate, and Cooking Technologies in Northern Ghana (REACCTING): study rationale and protocol.

BACKGROUND: Cooking over open fires using solid fuels is both common practice throughout much of the world and widely recognized to contribute to human health, environmental, and social problems. The public health burden of household air pollution includes an estimated four million premature deaths each year. To be effective and generate useful insight into potential solutions, cookstove intervention studies must select cooking technologies that are appropriate for local socioeconomic conditions and cooking culture, and include interdisciplinary measurement strategies along a continuum of outcomes. METHODS/DESIGN: REACCTING (Research on Emissions, Air quality, Climate, and Cooking Technologies in Northern Ghana) is an ongoing interdisciplinary randomized cookstove intervention study in the Kassena-Nankana District of Northern Ghana. The study tests two types of biomass burning stoves that have the potential to meet local cooking needs and represent different "rungs" in the cookstove technology ladder: a locally-made low-tech rocket stove and the imported, highly efficient Philips gasifier stove. Intervention households were randomized into four different groups, three of which received different combinations of two improved stoves, while the fourth group serves as a control for the duration of the study. Diverse measurements assess different points along the causal chain linking the intervention to final outcomes of interest. We assess stove use and cooking behavior, cooking emissions, household air pollution and personal exposure, health burden, and local to regional air quality. Integrated analysis and modeling will tackle a range of interdisciplinary science questions, including examining ambient exposures among the regional population, assessing how those exposures might change with different technologies and behaviors, and estimating the comparative impact of local behavior and technological changes versus regional climate variability and change on local air quality and health outcomes. DISCUSSION: REACCTING is well-poised to generate useful data on the impact of a cookstove intervention on a wide range of outcomes. By comparing different technologies side by side and employing an interdisciplinary approach to study this issue from multiple perspectives, this study may help to inform future efforts to improve health and quality of life for populations currently relying on open fires for their cooking needs.

Quantification Method for Electrolytic Sensors in Long-Term Monitoring of Ambient Air Quality.

Traditional air quality monitoring relies on point measurements from a small number of high-end devices. The recent growth in low-cost air sensing technology stands to revolutionize the way in which air quality data are collected and utilized. While several technologies have emerged in the field of low-cost monitoring, all suffer from similar challenges in data quality. One technology that shows particular promise is that of electrolytic (also known as amperometric) sensors. These sensors produce an electric current in response to target pollutants. This work addresses the development of practical models for understanding and quantifying the signal response of electrolytic sensors. Such models compensate for confounding effects on the sensor response, such as ambient temperature and humidity, and address other issues that affect the usability of low-cost sensors, such as sensor drift and inter-sensor variability.

Gas/particle partitioning of 2-methyltetrols and levoglucosan at an urban site in Denver.

In this study, a medium volume sampler incorporating quartz fiber filters (QFFs) and a polyurethane foam (PUF)/XAD/PUF sandwich (PXP) was used to collect 2-methyltetrols (isoprene tracer) and levoglucosan (biomass burning tracer) in gaseous and particle (PM2.5) phases. The measured gas/particle (G/P) partitioning coefficients (Kp,OMm) of 2-methyltetrols and levoglucosan were calculated and compared to their predicted G/P partitioning coefficients (Kp,OMt) based on an absorptive partitioning theory. The breakthrough experiments showed that gas-phase 2-methyltetrols and levoglucosan could be collected using the PXP or PUF adsorbent alone, with low breakthrough; however, the recoveries of levoglucosan in PXP samples were lower than 70% (average of 51.9­63.3%). The concentration ratios of 2-methyltetrols and levoglucosan in the gas phase to those in the particle phase were often close to or higher than unity in summer, indicating that these polar species are semi-volatile and their G/P partitioning should be considered when applying particle-phase data for source apportionment. The Kp,OMm values of 2-methyltetrols had small variability in summer Denver, which was ascribed to large variations in concentrations of particulate organic matter (5.14 ± 3.29 µg m­3) and small changes in ambient temperature (21.8 ± 4.05 °C). The regression between log Kp,OMm and log Kp,OMt suggested that the absorptive G/P partitioning theory could reasonably predict the measured G/P partitioning of levoglucosan in ambient samples.

Impact of gas/particle partitioning of semivolatile organic compounds on source apportionment with positive matrix factorization.

To quantify and minimize the influence of gas/particle (G/P) partitioning on receptor-based source apportionment using particle-phase semivolatile organic compound (SVOC) data, positive matrix factorization (PMF) coupled with a bootstrap technique was applied to three data sets mainly composed of "measured-total" (measured particle- + gas-phase), "particle-only" (measured particle-phase) and "predicted-total" (measured particle-phase + predicted gas-phase) SVOCs to apportion carbonaceous aerosols. Particle- (PM2.5) and gas-phase SVOCs were collected using quartz fiber filters followed by PUF/XAD-4/PUF adsorbents and measured using gas chromatography-mass spectrometry (GC-MS). Concentrations of gas-phase SVOCs were also predicted from their particle-phase concentrations using absorptive partitioning theory. Five factors were resolved for each data set, and the factor profiles were generally consistent across the three PMF solutions. Using a previous source apportionment study at the same receptor site, those five factors were linked to summertime biogenic emissions (odd n-alkane factor), unburned fossil fuels (light SVOC factor), road dust and/or cooking (n-alkane factor), motor vehicle emissions (PAH factor), and lubricating oil combustion (sterane factor). The "measured-total" solution was least influenced by G/P partitioning and used as reference. Two out of the five factors (odd n-alkane and PAH factors) exhibited consistent contributions for "particle-only" vs "measured-total" and "predicted-total" vs "measured-total" solutions. Factor contributions of light SVOC and n-alkane factors were more consistent for "predicted-total" vs "measured-total" than "particle-only" vs "measured-total" solutions. The remaining factor (sterane factor) underestimated the contribution by around 50% from both "particle-only" and "predicted-total" solutions. The results of this study confirm that when measured gas-phase SVOCs are not available, "predicted-total" SVOCs should be used to decrease the influence of G/P partitioning on receptor-based source apportionment.

VOC source apportionment: How monitoring characteristics influence positive matrix factorization (PMF) solutions.

Positive matrix factorization (PMF) can be used to develop more targeted air quality mitigation strategies by identifying major sources of a pollutant in an area. This technique is dependent, however, on the ability of PMF to resolve factors that accurately represent all sources of that pollutant in an area. We investigated how the accuracy of PMF solutions might be influenced by monitoring data characteristics, such as temporal resolution, monitoring location, and species composition, to better inform the use of PMF in VOC mitigation strategies. We applied PMF to five VOC monitoring programs collected within a four-year period in Colorado and found generally consistent factors, which we identified as oil extraction, processing, and evaporation; natural gas; vehicle exhaust; and liquid gasoline/short-lived oil and gas. The main determinant influencing whether or not a dataset resolved each of these sources was whether the dataset had a comprehensive list of VOC species covering key species of each source. Pollution spikes were not well-modeled in any of the solutions. Hyperlocal and volatile chemical product factors expected to be resolved in the industrialized, urban location were also missing, highlighting three limitations of PMF analysis. Wind direction dependence and diurnal trends aided in source identification, suggesting that high-time resolution data is important for developing actionable PMF results. Based on these findings, we recommend that air monitoring for PMF-informed VOC mitigation efforts include high temporal resolution and a comprehensive array of VOC species.

WindCline: Sloping wind tunnel for characterizing flame behavior under variable inclines and wind conditions.

Developing accurate computational models of wildfire dynamics is increasingly important due to the substantial and expanding negative impacts of wildfire events on human health, infrastructure, and the environment. Wildfire spread and emissions depend on a number of factors, including fuel type, environmental conditions (moisture, wind speed, etc.), and terrain/location. However, there currently exist only a few experimental facilities that enable testing of the interplay of these factors at length scales <1 m with carefully controlled and characterized boundary conditions and advanced diagnostics. Experiments performed at such facilities are required for informing and validating computational models. Here, we present the design and characterization of a tilting wind tunnel (the "WindCline") for studying wildfire dynamics. The WindCline is unique in that the entire tunnel platform is constructed to pivot around a central axis, which enables the sloping of the entire system without compromising the quality of the flow properties. In addition, this facility has a configurable design for the test section and diffuser to accommodate a suite of advanced diagnostics to aid in the characterization of (1) the parameters needed to establish boundary conditions and (2) flame properties and dynamics. The WindCline thus allows for the measurement and control of several critical wildfire variables and boundary conditions, especially at the small length scales important to the development of high-fidelity computational simulations (10-100 cm). Computational modeling frameworks developed and validated under these controlled conditions can expand understanding of fundamental combustion processes, promoting greater confidence when leveraging these processes in complex combustion environments.