Wildfire smoke impacts on indoor air quality assessed using crowdsourced data in California

Mitigating wildfire smoke inside homes: Evidence from Oregon, September 2020

The smoke produced by wildfires can travel great distances and lead to respiratory and/or cardiovascular health impacts through inhalation. Individuals can reduce exposure by implementing smoke mitigation measures in their homes and beyond. In this article, we examine household level survey data (n = 543) on wildfire smoke mitigation in response to the September 2020 wildfires that occurred in the state of Oregon (and beyond). The air quality was hazardous for about 10 days in many affected regions. This study assessed the implementation of six commonly referenced approaches to reducing exposure to smoke: staying indoors; keeping doors and windows closed, turning on HVAC; using air purifiers; replacing air filters, and wearing face masks. We found high levels of implementation of staying indoors and keeping doors and windows closed; however, statistical analysis of socioeconomic demographics suggests that respondents vary in the implementation of the other measures. Income, number of exposure days, and access to information on smoke mitigation were positively associated with the implementation. Given the importance of information access for implementation for three of the measures, we also present data on how different age groups prefer to be contacted about air quality and smoke mitigation. For example, participants above 65 years of age prefer local TV as opposed to social media, whereas text messages were favored by all age groups. These survey results will help to inform the design of campaigns to engage community members differentially and potentially affect best communication practices and other assistance/preparation for smoke mitigation across demographics.

Impact of Wildfires on Cardiovascular Health

Wildfire smoke (WFS) is a mixture of respirable particulate matter, environmental gases, and other hazardous pollutants that originate from the unplanned burning of arid vegetation during wildfires. The increasing size and frequency of recent wildfires has escalated public and occupational health concerns regarding WFS inhalation, by either individuals living nearby and downstream an active fire or wildland firefighters and other workers that face unavoidable exposure because of their profession. In this review, we first synthesize current evidence from environmental, controlled, and interventional human exposure studies, to highlight positive associations between WFS inhalation and cardiovascular morbidity and mortality. Motivated by these findings, we discuss preventative measures and suggest interventions to mitigate the cardiovascular impact of wildfires. We then review animal and cell exposure studies to call attention on the pathophysiological processes that support the deterioration of cardiovascular tissues and organs in response to WFS inhalation. Acknowledging the challenges of integrating evidence across independent sources, we contextualize laboratory-scale exposure approaches according to the biological processes that they model and offer suggestions for ensuring relevance to the human condition. Noting that wildfires are significant contributors to ambient air pollution, we compare the biological responses triggered by WFS to those of other harmful pollutants. We also review evidence for how WFS inhalation may trigger mechanisms that have been proposed as mediators of adverse cardiovascular effects upon exposure to air pollution. We finally conclude by highlighting research areas that demand further consideration. Overall, we aspire for this work to serve as a catalyst for regulatory initiatives to mitigate the adverse cardiovascular effects of WFS inhalation in the community and alleviate the occupational risk in wildland firefighters.

Spatial Heterogeneity of the Respiratory Health Impacts of Wildfire Smoke PM2.5 in California

Wildfire smoke fine particles (PM2.5) are a growing public health threat as wildfire events become more common and intense under climate change, especially in the Western United States. Studies assessing the association between wildfire PM2.5 exposure and health typically summarize the effects over the study area. However, health responses to wildfire PM2.5 may vary spatially. We evaluated spatially-varying respiratory acute care utilization risks associated with short-term exposure to wildfire PM2.5 and explored community characteristics possibly driving spatial heterogeneity. Using ensemble-modeled daily wildfire PM2.5, we defined a wildfire smoke day to have wildfire-specific PM2.5 concentration ≥15 μg/m3. We included daily respiratory emergency department visits and unplanned hospitalizations in 1,396 California ZIP Code Tabulation Areas (ZCTAs) and 15 census-derived community characteristics. Employing a case-crossover design and conditional logistic regression, we observed increased odds of respiratory acute care utilization on wildfire smoke days at the state level (odds ratio [OR] = 1.06, 95% confidence interval [CI]: 1.05, 1.07). Across air basins, ORs ranged from 0.88 to 1.57, with the highest effect estimate in San Diego. A within-community matching design and spatial Bayesian hierarchical model also revealed spatial heterogeneity in ZCTA-level rate differences. For example, communities with a higher percentage of Black or Pacific Islander residents had stronger wildfire PM2.5-outcome relationships, while more air conditioning and tree canopy attenuated associations. We found an important heterogeneity in wildfire smoke-related health impacts across air basins, counties, and ZCTAs, and we identified characteristics of vulnerable communities, providing evidence to guide policy development and resource allocation.

California Case Study of Wildfires and Prescribed Burns: PM2.5 Emissions, Concentrations, and Implications for Human Health

Wildfires are a significant threat to human health, in part through degraded air quality. Prescribed burning can reduce wildfire severity but can also lead to an increase in air pollution. The complexities of fires and atmospheric processes lead to uncertainties when predicting the air quality impacts of fire and make it difficult to fully assess the costs and benefits of an expansion of prescribed fire. By modeling differences in emissions, surface conditions, and meteorology between wildfire and prescribed burns, we present a novel comparison of the air quality impacts of these fire types under specific scenarios. One wildfire and two prescribed burn scenarios were considered, with one prescribed burn scenario optimized for potential smoke exposure. We found that PM2.5 emissions were reduced by 52%, from 0.27 to 0.14 Tg, when fires burned under prescribed burn conditions, considerably reducing PM2.5 concentrations. Excess short-term mortality from PM2.5 exposure was 40 deaths for fires under wildfire conditions and 39 and 15 deaths for fires under the default and optimized prescribed burn scenarios, respectively. Our findings suggest prescribed burns, particularly when planned during conditions that minimize smoke exposure, could be a net benefit for the impacts of wildfires on air quality and health.

Data Linkages for Wildfire Exposures and Human Health Studies: A Scoping Review

Wildfires are increasing in frequency and intensity, with significant consequences that impact human health. A scoping review was conducted to: (a) understand wildfire-related health effects, (b) identify and describe environmental exposure and health outcome data sources used to research the impacts of wildfire exposures on health, and (c) identify gaps and opportunities to leverage exposure and health data to advance research. A literature search was conducted in PubMed and a sample of 83 articles met inclusion criteria. A majority of studies focused on respiratory and cardiovascular outcomes. Hospital administrative data was the most common health data source, followed by government data sources and health surveys. Wildfire smoke, specifically fine particulate matter (PM2.5), was the most common exposure measure and was predominantly estimated from monitoring networks and satellite data. Health data were not available in real-time, and they lacked spatial and temporal coverage to study health outcomes with longer latency periods. Exposure data were often available in real-time and provided better temporal and spatial coverage but did not capture the complex mixture of hazardous wildfire smoke pollutants nor exposures associated with non-air pathways such as soil, household dust, food, and water. This scoping review of the specific health and exposure data sources used to underpin these studies provides a framework for the research community to understand: (a) the use and value of various environmental and health data sources, and (b) the opportunities for improving data collection, integration, and accessibility to help inform our understanding of wildfires and other environmental exposures.

Experimental and Modeled Assessment of Interventions to Reduce PM2.5 in a Residence during a Wildfire Event

Increasingly large and frequent wildfires affect air quality even indoors by emitting and dispersing fine/ultrafine particulate matter known to pose health risks to residents. With this health threat, we are working to help the building science community develop simplified tools that may be used to estimate impacts to large numbers of homes based on high-level housing characteristics. In addition to reviewing literature sources, we performed an experiment to evaluate interventions to mitigate degraded indoor air quality. We instrumented one residence for one week during an extreme wildfire event in the Pacific Northwest. Outdoor ambient concentrations of PM2.5 reached historic levels, sustained at over 200 μg/m3 for multiple days. Outdoor and indoor PM2.5 were monitored, and data regarding building characteristics, infiltration, and mechanical system operation were gathered to be consistent with the type of information commonly known for residential energy models. Two conditions were studied: a high-capture minimum efficiency rated value (MERV 13) filter integrated into a central forced air (CFA) system, and a CFA with MERV 13 filtration operating with a portable air cleaner (PAC). With intermittent CFA operation and no PAC, indoor corrected concentrations of PM2.5 reached 280 μg/m3, and indoor/outdoor (I/O) ratios reached a mean of 0.55. The measured I/O ratio was reduced to a mean of 0.22 when both intermittent CFA and the PAC were in operation. Data gathered from the test home were used in a modeling exercise to assess expected I/O ratios from both interventions. The mean modeled I/O ratio for the CFA with an MERV 13 filter was 0.48, and 0.28 when the PAC was added. The model overpredicted the MERV 13 performance and underpredicted the CFA with an MERV 13 filter plus a PAC, though both conditions were predicted within 0.15 standard deviation. The results illustrate the ways that models can be used to estimate indoor PM2.5 concentrations in residences during extreme wildfire smoke events.

Measuring long-term exposure to wildfire PM2.5 in California: Time-varying inequities in environmental burden

Wildfires have become more frequent and intense due to climate change and outdoor wildfire fine particulate matter (PM2.5) concentrations differ from relatively smoothly varying total PM2.5. Thus, we introduced a conceptual model for computing long-term wildfire PM2.5 and assessed disproportionate exposures among marginalized communities. We used monitoring data and statistical techniques to characterize annual wildfire PM2.5 exposure based on intermittent and extreme daily wildfire PM2.5 concentrations in California census tracts (2006 to 2020). Metrics included: 1) weeks with wildfire PM2.5 < 5 μg/m3; 2) days with non-zero wildfire PM2.5; 3) mean wildfire PM2.5 during peak exposure week; 4) smoke waves (≥2 consecutive days with <15 μg/m3 wildfire PM2.5); and 5) mean annual wildfire PM2.5 concentration. We classified tracts by their racial/ethnic composition and CalEnviroScreen (CES) score, an environmental and social vulnerability composite measure. We examined associations of CES and racial/ethnic composition with the wildfire PM2.5 metrics using mixed-effects models. Averaged 2006 to 2020, we detected little difference in exposure by CES score or racial/ethnic composition, except for non-Hispanic American Indian and Alaska Native populations, where a 1-SD increase was associated with higher exposure for 4/5 metrics. CES or racial/ethnic × year interaction term models revealed exposure disparities in some years. Compared to their California-wide representation, the exposed populations of non-Hispanic American Indian and Alaska Native (1.68×, 95% CI: 1.01 to 2.81), white (1.13×, 95% CI: 0.99 to 1.32), and multiracial (1.06×, 95% CI: 0.97 to 1.23) people were over-represented from 2006 to 2020. In conclusion, during our study period in California, we detected disproportionate long-term wildfire PM2.5 exposure for several racial/ethnic groups.

Clearing the Air: Understanding the Impact of Wildfire Smoke on Asthma and COPD

Wildfires are a global natural phenomenon. In North America, wildfires have not only become more frequent, but also more severe and longer in duration, a trend ascribed to climate change combined with large fuel stores left from modern fire suppression. The intensification of wildfire activity has significant implications for planetary health and public health, as exposure to fine particulate matter (PM2.5) in wildfire smoke is linked to adverse health effects. This review focuses on respiratory morbidity from wildfire smoke exposure. Inhalation of wildfire PM2.5 causes lung injury via oxidative stress, local and systemic inflammation, airway epithelium compromise, and increased vulnerability to infection. Wildfire PM2.5 exposure results in exacerbations of pre-existing asthma and chronic obstructive pulmonary disease, with an escalation in healthcare utilization, including emergency department visits and hospitalizations. Wildfire smoke exposure may be associated with asthma onset, long-term impairment of lung function, and increased all-cause mortality. Children, older adults, occupationally-exposed groups, and possibly women are the most at risk from wildfire smoke. Future research is needed to clarify best practices for risk mitigation and wildfire management.

Polycyclic Aromatic Hydrocarbons (PAHs) in Wildfire Smoke Accumulate on Indoor Materials and Create Postsmoke Event Exposure Pathways

Wildfire smoke contains PAHs that, after infiltrating indoors, accumulate on indoor materials through particle deposition and partitioning from air. We report the magnitude and persistence of select surface associated PAHs on three common indoor materials: glass, cotton, and mechanical air filter media. Materials were loaded with PAHs through both spiking with standards and exposure to a wildfire smoke proxy. Loaded materials were aged indoors over ∼4 months to determine PAH persistence. For materials spiked with standards, total PAH decay rates were 0.010 ± 0.002, 0.025 ± 0.005, and 0.051 ± 0.009 day-1, for mechanical air filter media, glass, and cotton, respectively. PAH decay on smoke-exposed samples is consistent with that predicated by decay constants from spiked materials. Decay curves of smoke loaded samples show that PAH surface concentrations are elevated above background for ∼40 days after the smoke clears. Cleaning processes efficiently remove PAHs, with reductions of 71% and 62% after cleaning smoke-exposed glass with ethanol and a commercial cleaner, respectively. Laundering smoke-exposed cotton in a washing machine and heated drying removed 48% of PAHs. An exposure assessment indicates that both inhalation and dermal PAH exposure pathways may be relevant following wildfire smoke events.

Impact of agricultural activity on PM2.5 and its compositions in elementary schools near corn and rice farms

Agricultural activity is an important source of particulate matter <2.5 μm in size (PM2.5) in rural areas. In Taiwan, many elementary schools are surrounded by farms, and studies investigating the impact of agricultural activity on air quality in schools are required. We collected PM2.5 samples from the classrooms of elementary schools near corn and rice farms during the crop cultivation stages and analyzed their concentrations and compositions to investigate whether agricultural activity affects the schools' air quality. We found that the average ratio of PM2.5/PM10 (<10 μm in particle size) was <0.6 in the school near the corn farm, and that the indoor PM2.5/PM10 ratio was significantly associated (r = 0.93, p < 0.05) with the outdoor ratio. Moreover, the potassium (K) concentration in the school near the corn farm (189.2 ± 119 ng/m3) was higher than that near the rice farm (140.9 ± 116.0 ng/m3). There were higher concentrations of K and crustal elements, and a greater crustal elements/heavy metals ratio, in the school near the corn farm during the sowing and soil covering stages than during other cultivation stages. Positive matrix factorization (PMF) results indicate that agricultural activity was a predominant contributor of PM2.5 in the schools near corn and rice farms, however, PM2.5 from industrial and traffic emissions also affected schools' air quality. In summary, agricultural activity influenced the air quality of schools, especially near the corn farm. Governments should develop air quality management policies to reduce the risk of children suffering exposure to high particle concentrations in these schools and further suggest that the impact of industrial and traffic emissions on air quality also requires attention.

Assessing residential PM2.5 concentrations and infiltration factors with high spatiotemporal resolution using crowdsourced sensors

Building conditions, outdoor climate, and human behavior influence residential concentrations of fine particulate matter (PM2.5). To study PM2.5 spatiotemporal variability in residences, we acquired paired indoor and outdoor PM2.5 measurements at 3,977 residences across the United States totaling >10,000 monitor-years of time-resolved data (10-min resolution) from the PurpleAir network. Time-series analysis and statistical modeling apportioned residential PM2.5 concentrations to outdoor sources (median residential contribution = 52% of total, coefficient of variation = 69%), episodic indoor emission events such as cooking (28%, CV = 210%) and persistent indoor sources (20%, CV = 112%). Residences in the temperate marine climate zone experienced higher infiltration factors, consistent with expectations for more time with open windows in milder climates. Likewise, for all climate zones, infiltration factors were highest in summer and lowest in winter, decreasing by approximately half in most climate zones. Large outdoor-indoor temperature differences were associated with lower infiltration factors, suggesting particle losses from active filtration occurred during heating and cooling. Absolute contributions from both outdoor and indoor sources increased during wildfire events. Infiltration factors decreased during periods of high outdoor PM2.5, such as during wildfires, reducing potential exposures from outdoor-origin particles but increasing potential exposures to indoor-origin particles. Time-of-day analysis reveals that episodic emission events are most frequent during mealtimes as well as on holidays (Thanksgiving and Christmas), indicating that cooking-related activities are a strong episodic emission source of indoor PM2.5 in monitored residences.

Identification and Parametrization of Key Factors Affecting Levoglucosan Emission During Solid Fuel Burning

Levoglucosan (LG) is a pyrolysis product of cellulose and hemicellulose at low combustion temperatures. However, LG release cannot be determined only by considering the contents of cellulose and hemicellulose exclusively due to the complexity of combustion processes and the physical-chemical properties of the fuel. This study detected the emission factors (EFs) of LG from 22 different solid fuel samples (including coal and biomass) by considering 18 different fuel properties and five combustion parameters. The average LGEFs during solid fuel burning varied in a range of 0.03-136 mg kg-1, with a magnitude difference of 1-4 orders. While the variations in cellulose (59.5-368 mg g-1) and hemicellulose (73.5-165 mg g-1) contents of fuel samples were only one- to 6-fold. A short combustion duration (<150 min) and a medium combustion temperature (200-400 °C) influenced by volatile and ash contents are crucial for the generation and accumulation of LG. A random forest coupled with the Akaike information criterion stepwise regression model successfully explained 96% of the total LG emission variation using three variables (ash content, cellulose content, and modified combustion efficiency). The ash content promoted coke formation and LG chain cracking by increasing the pyrolysis temperature and is considered the most important factor. The alkali metal in ash can reduce the energy barrier of intramolecular ring contraction reactions and inhibit the dehydration reactions, which led to additional heat being utilized by the competitive pathways of LG formation. This study provided a method to address the parametrization and release mechanisms of combustion source emissions.

China's public health initiatives for climate change adaptation

China's health gains over the past decades face potential reversals if climate change adaptation is not prioritized. China's temperature rise surpasses the global average due to urban heat islands and ecological changes, and demands urgent actions to safeguard public health. Effective adaptation need to consider China's urbanization trends, underlying non-communicable diseases, an aging population, and future pandemic threats. Climate change adaptation initiatives and strategies include urban green space, healthy indoor environments, spatial planning for cities, advance location-specific early warning systems for extreme weather events, and a holistic approach for linking carbon neutrality to health co-benefits. Innovation and technology uptake is a crucial opportunity. China's successful climate adaptation can foster international collaboration regionally and beyond.

Ventilation in a Residential Building Brings Outdoor NOx Indoors with Limited Implications for VOC Oxidation from NO3 Radicals

Energy-efficient residential building standards require the use of mechanical ventilation systems that replace indoor air with outdoor air. Transient outdoor pollution events can be transported indoors via the mechanical ventilation system and other outdoor air entry pathways and impact indoor air chemistry. In the spring of 2022, we observed elevated levels of NOx (NO + NO2) that originated outdoors, entering the National Institute of Standards and Technology (NIST) Net-Zero Energy Residential Test Facility through the mechanical ventilation system. Using measurements of NOx, ozone (O3), and volatile organic compounds (VOCs), we modeled the effect of the outdoor-to-indoor ventilation of NOx pollution on the production of nitrate radical (NO3), a potentially important indoor oxidant. We evaluated how VOC oxidation chemistry was affected by NO3 during NOx pollution events compared to background conditions. We found that nitric oxide (NO) pollution introduced indoors titrated O3 and inhibited the modeled production of NO3. NO ventilated indoors also likely ceased most gas-phase VOC oxidation chemistry during plume events. Only through the artificial introduction of O3 to the ventilation duct during a NOx pollution event (i.e., when O3 and NO2 concentrations were high relative to typical conditions) were we able to measure NO3-initiated VOC oxidation products, indicating that NO3 was impacting VOC oxidation chemistry.

Fine particulate matter infiltration at Western Montana residences during wildfire season

BACKGROUND/AIMS

Wildfire air pollution is a growing public health concern as wildfires increase in size, intensity, and duration in the United States. The public is often encouraged to stay indoors during wildfire smoke events to reduce exposure. However, there is limited information on how much wildfire smoke infiltrates indoors at residences and what household/behavioral characteristics contribute to higher infiltration. We assessed fine particulate matter (PM2.5) infiltration into Western Montana residences during wildfire season.

METHODS

We measured continuous outdoor and indoor PM2.5 concentrations from July-October 2022 at 20 residences in Western Montana during wildfire season using low-cost PM2.5 sensors. We used paired outdoor/indoor PM2.5 data from each household to calculate infiltration efficiency (Finf; range 0-1; higher values indicate more outdoor PM2.5 infiltration to the indoor environment) using previously validated methods. Analyses were conducted for all households combined and for various household subgroups.

RESULTS

Median (25th percentile, 75th percentile) daily outdoor PM2.5 at the households was 3.7 μg/m3 (2.1, 7.1) during the entire study period and 29.0 μg/m3 (19.0, 49.4) during a 2-week period in September impacted by wildfire smoke. Median daily indoor PM2.5 at the households was 2.5 μg/m3 (1.3, 5.5) overall and 10.4 μg/m3 (5.6, 21.0) during the wildfire period. Overall Finf was 0.34 (95 % Confidence Interval [95%CI]: 0.33, 0.35) with lower values during the wildfire period (0.32; 95%CI: 0.28, 0.36) versus non-wildfire period (0.39; 95%CI: 0.37, 0.42). Indoor PM2.5 concentrations and Finf varied substantially across household subgroups such as household income, age of the home, presence of air conditioning units, and use of portable air cleaners.

CONCLUSIONS

Indoor PM2.5 was substantially higher during wildfire-impacted periods versus the rest of the study. Indoor PM2.5 and Finf were highly variable across households. Our results highlight potentially modifiable behaviors and characteristics that can be used in targeted intervention strategies.

The persistence of smoke VOCs indoors: Partitioning, surface cleaning, and air cleaning in a smoke-contaminated house

Wildfires are increasing in frequency, raising concerns that smoke can permeate indoor environments and expose people to chemical air contaminants. To study smoke transformations in indoor environments and evaluate mitigation strategies, we added smoke to a test house. Many volatile organic compounds (VOCs) persisted days following the smoke injection, providing a longer-term exposure pathway for humans. Two time scales control smoke VOC partitioning: a faster one (1.0 to 5.2 hours) that describes the time to reach equilibrium between adsorption and desorption processes and a slower one (4.8 to 21.2 hours) that describes the time for indoor ventilation to overtake adsorption-desorption equilibria in controlling the air concentration. These rates imply that vapor pressure controls partitioning behavior and that house ventilation plays a minor role in removing smoke VOCs. However, surface cleaning activities (vacuuming, mopping, and dusting) physically removed surface reservoirs and thus reduced indoor smoke VOC concentrations more effectively than portable air cleaners and more persistently than window opening.

Laboratory Comparison of Low-Cost Particulate Matter Sensors to Measure Transient Events of Pollution-Part B-Particle Number Concentrations

Low-cost Particulate Matter (PM) sensors offer an excellent opportunity to improve our knowledge about this type of pollution. Their size and cost, which support multi-node network deployment, along with their temporal resolution, enable them to report fine spatio-temporal resolution for a given area. These sensors have known issues across performance metrics. Generally, the literature focuses on the PM mass concentration reported by these sensors, but some models of sensors also report Particle Number Concentrations (PNCs) segregated into different PM size ranges. In this study, eight units each of Alphasense OPC-R1, Plantower PMS5003 and Sensirion SPS30 have been exposed, under controlled conditions, to short-lived peaks of PM generated using two different combustion sources of PM, exposing the sensors' to different particle size distributions to quantify and better understand the low-cost sensors performance across a range of relevant environmental ranges. The PNCs reported by the sensors were analysed to characterise sensor-reported particle size distribution, to determine whether sensor-reported PNCs can follow the transient variations of PM observed by the reference instruments and to determine the relative impact of different variables on the performances of the sensors. This study shows that the Alphasense OPC-R1 reported at least five size ranges independently from each other, that the Sensirion SPS30 reported two size ranges independently from each other and that all the size ranges reported by the Plantower PMS5003 were not independent of each other. It demonstrates that all sensors tested here could track the fine temporal variation of PNCs, that the Alphasense OPC-R1 could closely follow the variations of size distribution between the two sources of PM, and it shows that particle size distribution and composition are more impactful on sensor measurements than relative humidity.

Data-Driven Placement of PM2.5 Air Quality Sensors in the United States: An Approach to Target Urban Environmental Injustice

In the United States, citizens and policymakers heavily rely upon Environmental Protection Agency mandated regulatory networks to monitor air pollution; increasingly they also depend on low-cost sensor networks to supplement spatial gaps in regulatory monitor networks coverage. Although these regulatory and low-cost networks in tandem provide enhanced spatiotemporal coverage in urban areas, low-cost sensors are located often in higher income, predominantly White areas. Such disparity in coverage may exacerbate existing inequalities and impact the ability of different communities to respond to the threat of air pollution. Here we present a study using cost-constrained multiresolution dynamic mode decomposition (mrDMDcc) to identify the optimal and equitable placement of fine particulate matter (PM2.5) sensors in four U.S. cities with histories of racial or income segregation: St. Louis, Houston, Boston, and Buffalo. This novel approach incorporates the variation of PM2.5 on timescales ranging from 1 day to over a decade to capture air pollution variability. We also introduce a cost function into the sensor placement optimization that represents the balance between our objectives of capturing PM2.5 extremes and increasing pollution monitoring in low-income and nonwhite areas. We find that the mrDMDcc algorithm places a greater number of sensors in historically low-income and nonwhite neighborhoods with known environmental pollution problems compared to networks using PM2.5 information alone. Our work provides a roadmap for the creation of equitable sensor networks in U.S. cities and offers a guide for democratizing air pollution data through increasing spatial coverage of low-cost sensors in less privileged communities.

Characterizing the effects of structural fires on fine particulate matter with a dense sensing network

Short-term increases in air pollution levels are linked to large adverse effects on health and productivity. However, existing regulatory monitoring systems lack the spatial or temporal resolution needed to capture localized events. This study uses a dense network of over 100 sensors, deployed across the city of Chicago, Illinois, to capture the spread of smoke from short-term structural fire events. Examining all large structural fires that occurred in the city over a year (N = 21), we characterize differences in PM[Formula: see text] concentrations downwind versus upwind of the fires. On average, we observed increases of up to 10.7 [Formula: see text]g/m[Formula: see text] (95% CI 5.7-15.7) for sensors within 2 km and up to 7.7 [Formula: see text]g/m[Formula: see text] (95% CI 3.4-12.0) for sensors 2-5 km downwind of fires. Statistically significant elevated concentrations were evident as far as 5 km downwind of the location of the fire and persisted over approximately 2 h on average. This work shows how low-cost sensors can provide insight on local and short-term pollution events, enabling regulators to provide timely warnings to vulnerable populations.

Short-Term total and wildfire fine particulate matter exposure and work loss in California

BACKGROUND

Few studies investigated the impact of particulate matter (PM2.5) on some symptom exacerbations that are not perceived as severe enough to search for medical assistance. We aimed to study the association of short-term daily total PM2.5 exposure with work loss due to sickness among adults living in California.

METHODS

We included 44,544 adult respondents in the workforce from 2015 to 2018 California Health Interview Survey data. Daily total PM2.5 concentrations were linked to respondents' home addresses from continuous spatial surfaces of PM2.5 generated by a geostatistical surfacing algorithm. We estimated the effect of a 2-week average of daily total PM2.5 exposure on work loss using logistic regression models.

RESULTS

About 1.69% (weighted percentage) of adult respondents reported work loss in the week before the survey interview. The odds ratio of work loss was 1.45 (odds ratio [OR] = 1.45, 95% confidence interval [CI]: 1.03, 2.03) when a 2-week average of daily total PM2.5 exposure was higher than 12 µg/m3. The OR for work loss was 1.05 (95% CI: 0.98, 1.13) for each 2.56ug/m3 increase in the 2-week average of daily total PM2.5 exposure, and became stronger among those who were highly exposed to wildfire smoke (OR = 1.06, 95% CI: 1.00, 1.13), compared to those with lower wildfire smoke exposure (OR = 1.04, 95% CI: 0.79, 1.39).

CONCLUSIONS

Our findings suggest that short-term ambient PM2.5 exposure is positively associated with work loss due to sickness and the association was stronger among those with higher wildfire smoke exposure. It also indicated that the current federal and state PM2.5 standards (annual average of 12 µg/m3) could be further strengthened to protect the health of the citizens of California.

Health Research in the Wake of Disasters: Challenges and Opportunities for Sensor Science

BACKGROUND

Disaster events adversely affect the health of millions of individuals each year. They create exposure to physical, chemical, biological, and psychosocial hazards while simultaneously exploiting community and individual-level vulnerabilities that allow such exposures to exert harm. Since 2013, the National Institute of Environmental Health Sciences (NIEHS) has led the development of the Disaster Research Response (DR2) program and infrastructure; however, research exploring the nature and effects of disasters on human health is lacking. One reason for this research gap is the challenge of developing and deploying cost-effective sensors for exposure assessment during disaster events.

OBJECTIVES

The objective of this commentary is to synergize the consensus findings and recommendations from a panel of experts on sensor science in support of DR2.

METHODS

The NIEHS convened the workshop, "Getting Smart about Sensors for Disaster Response Research" on 28 and 29 July 2021 to discuss current gaps and recommendations for moving the field forward. The workshop invited full discussion from multiple viewpoints, with the goal of identifying recommendations and opportunities for further development of this area of research. The panel of experts included leaders in engineering, epidemiology, social and physical sciences, and community engagement, many of whom had firsthand experience with DR2.

DISCUSSION

The primary finding of this workshop is that exposure science in support of DR2 is severely lacking. We highlight unique barriers to DR2, such as the need for time-sensitive exposure data, the chaos and logistical challenges that ensue from a disaster event, and the lack of a robust market for sensor technologies in support of environmental health science. We highlight a need for sensor technologies that are more scalable, reliable, and versatile than those currently available to the research community. We also recommend that the environmental health community renew efforts in support of DR2 facilitation, collaboration, and preparedness. https://doi.org/10.1289/EHP12270.

Quantifying the premature mortality and economic loss from wildfire-induced PM2.5 in the contiguous U.S

Emissions from wildfires worsen air quality and can adversely impact human health. This study utilized the fire inventory from NCAR (FINN) as wildfire emissions, and performed air quality modeling of April-October 2012, 2013, and 2014 using the U.S. Environmental Protection Agency CMAQ model under two cases: with and without wildfire emissions. This study then assessed the health impacts and economic values attributable to PM_2.5 from fires. Results indicated that wildfires could lead annually to 4000 cases of premature mortality in the U.S., corresponding to $36 billion losses. Regions with high concentrations of fire-induced PM_2.5 were in the west (e.g., Idaho, Montana, and northern California) and Southeast (e.g., Alabama, Georgia). Metropolitan areas located near fire sources, exhibited large health burdens, such as Los Angeles (119 premature deaths, corresponding to $1.07 billion), Atlanta (76, $0.69 billion), and Houston (65, $0.58 billion). Regions in the downwind of western fires, although experiencing relatively low values of fire-induced PM_2.5, showed notable health burdens due to their large population, such as metropolitan areas of New York (86, $0.78 billion), Chicago (60, $0.54 billion), and Pittsburgh (32, $0.29 billion). Results suggest that impacts from wildfires are substantial, and to mitigate these impacts, better forest management and more resilient infrastructure would be needed.

The application of portable air cleaners in spaces occupied by vulnerable people during wildfire events

In this study, PM2.5 concentrations were collected and documented during wildfire smoke impacted days using PurpleAir PA-II sensors at three different locations in a community located in the northwestern United States. Each location was comprised of three co-located sensors with one sensor positioned outdoors, one sensor indoors, and one sensor indoors with an air cleaner in the room. The relationship between both indoor and outdoor PM2.5 concentrations provided evidence on the effectiveness of sheltering indoors from wildfire smoke events with and without an air purification system.

The impact of wildfires on air pollution and health across land use categories in Brazil over a 16-year period

Forest fires cause many environmental impacts, including air pollution. Brazil is a very fire-prone region where few studies have investigated the impact of wildfires on air quality and health. We proposed to test two hypotheses in this study: i) the wildfires in Brazil have increased the levels of air pollution and posed a health hazard in 2003-2018, and ii) the magnitude of this phenomenon depends on the type of land use and land cover (e.g., forest area, agricultural area, etc.). Satellite and ensemble models derived data were used as input in our analyses. Wildfire events were retrieved from Fire Information for Resource Management System (FIRMS), provided by NASA; air pollution data from the Copernicus Atmosphere Monitoring Service (CAMS); meteorological variables from the ERA-Interim model; and land use/cover data were derived from pixel-based classification of Landsat satellite images by MapBiomas. We used a framework that infers the "wildfire penalty" by accounting for differences in linear pollutant annual trends (β) between two models to test these hypotheses. The first model was adjusted for Wildfire-related Land Use activities (WLU), considered as an adjusted model. In the second model, defined as an unadjusted model, we removed the wildfire variable (WLU). Both models were controlled by meteorological variables. We used a generalized additive approach to fit these two models. To estimate mortality associated with wildfire penalties, we applied health impact function. Our findings suggest that wildfire events between 2003 and 2018 have increased the levels of air pollution and posed a significant health hazard in Brazil, supporting our first hypothesis. For example, in the Pampa biome, we estimated an annual wildfire penalty of 0.005 μg/m³ (95%CI: 0.001; 0.009) on PM_2.5. Our results also confirm the second hypothesis. We observed that the greatest impact of wildfires on PM_2.5 concentrations occurred in soybean areas in the Amazon biome. During the 16 years of the study period, wildfires originating from soybean areas in the Amazon biome were associated with a total penalty of 0.64 μg/m³ (95%CI: 0.32; 0.96) on PM_2.5, causing an estimated 3872 (95%CI: 2560; 5168) excess deaths. Sugarcane crops were also a driver of deforestation-related wildfires in Brazil, mainly in Cerrado and Atlantic Forest biomes. Our findings suggest that between 2003 and 2018, fires originating from sugarcane crops were associated with a total penalty of 0.134 μg/m³ (95%CI: 0.037; 0.232) on PM_2.5 in Atlantic Forest biome, resulting in an estimated 7600 (95%CI: 4400; 10,800) excess deaths during the study period, and 0.096 μg/m³ (95%CI: 0.048; 0.144) on PM_2.5 in Cerrado biome, resulting in an estimated 1632 (95%CI: 1152; 2112) excess deaths during the study period. Considering that the wildfire penalties observed during our study period may continue to be a challenge in the future, this study should be of interest to policymakers to prepare future strategies related to forest protection, land use management, agricultural activities, environmental health, climate change, and sources of air pollution.

Air pollution and COPD: GOLD 2023 committee report

Exposure to air pollution is a major contributor to the pathogenesis of COPD worldwide. Indeed, most recent estimates suggest that 50% of the total attributable risk of COPD may be related to air pollution. In response, the Global Initiative for Chronic Obstructive Lung Disease (GOLD) Scientific Committee performed a comprehensive review on this topic, qualitatively synthesised the evidence to date and proffered recommendations to mitigate the risk. The review found that both gaseous and particulate components of air pollution are likely contributors to COPD. There are no absolutely safe levels of ambient air pollution and the relationship between air pollution levels and respiratory events is supra-linear. Wildfires and extreme weather events such as heat waves, which are becoming more common owing to climate change, are major threats to COPD patients and acutely increase their risk of morbidity and mortality. Exposure to air pollution also impairs lung growth in children and as such may lead to developmental COPD. GOLD recommends strong public health policies around the world to reduce ambient air pollution and for implementation of public warning systems and advisories, including where possible the use of personalised apps, to alert patients when ambient air pollution levels exceed acceptable minimal thresholds. When household particulate content exceeds acceptable thresholds, patients should consider using air cleaners and filters where feasible. Air pollution is a major health threat to patients living with COPD and actions are urgently required to reduce the morbidity and mortality related to poor air quality around the world.

Spatial Variation of PM2.5 Indoors and Outdoors: Results from 261 Regulatory Monitors Compared to 14,000 Low-Cost Monitors in Three Western States over 4.7 Years

Spatial variation of indoor and outdoor PM_2.5 within three states for a five-year period is studied using regulatory and low-cost PurpleAir monitors. Most of these data were collected in an earlier study (Wallace et al., 2022 Indoor Air 32:13105) investigating the relative contribution of indoor-generated and outdoor-infiltrated particles to indoor exposures. About 260 regulatory monitors and ~10,000 outdoor and ~4000 indoor PurpleAir monitors are included. Daily mean PM_2.5 concentrations, correlations, and coefficients of divergence (COD) are calculated for pairs of monitors at distances ranging from 0 (collocated) to 200 km. We use a transparent and reproducible open algorithm that avoids the use of the proprietary algorithms provided by the manufacturer of the sensors in PurpleAir PA-I and PA-II monitors. The algorithm is available on the PurpleAir API website under the name "PM_2.5_alt". This algorithm is validated using several hundred pairs of regulatory and PurpleAir monitors separated by up to 0.5 km. The PM_2.5 spatial variation outdoors is homogeneous with high correlations to at least 10 km, as shown by the COD index under 0.2. There is also a steady improvement in outdoor PM_2.5 concentrations with increasing distance from the regulatory monitors. The spatial variation of indoor PM_2.5 is not homogeneous even at distances < 100 m. There is good agreement between PurpleAir outdoor monitors located <100 m apart and collocated Federal Equivalent Methods (FEM).

Adaptation Resources and Responses to Wildfire Smoke and Other Forms of Air Pollution in Low-Income Urban Settings: A Mixed-Methods Study

Little is known about how low-income residents of urban communities engage their knowledge, attitudes, behaviors, and resources to mitigate the health impacts of wildfire smoke and other forms of air pollution. We interviewed 40 adults in Los Angeles, California, to explore their threat assessments of days of poor air quality, adaptation resources and behaviors, and the impacts of air pollution and wildfire smoke on physical and mental health. Participants resided in census tracts that were disproportionately burdened by air pollution and socioeconomic vulnerability. All participants reported experiencing days of poor air quality due primarily to wildfire smoke. Sixty percent received advanced warnings of days of poor air quality or routinely monitored air quality via cell phone apps or news broadcasts. Adaptation behaviors included remaining indoors, circulating indoor air, and wearing face masks when outdoors. Most (82.5%) of the participants reported some physical or mental health problem or symptom during days of poor air quality, but several indicated that symptom severity was mitigated by their adaptive behaviors. Although low-income residents perceive themselves to be at risk for the physical and mental health impacts of air pollution, they have also adapted to that risk with limited resources.

Quantifying Exposure to Wildfire Smoke Among Schoolchildren in California, 2006 to 2021

This cross-sectional study quantifies exposure to wildfire particulate matter less than 2.5 μm among schoolchildren in California.

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.

Temporal trends in ambient fine particulate matter and the impacts of COVID-19 on this pollutant in Grenada, West Indies

Most Caribbean islands do not have air pollution surveillance programs. Those who live in these countries are exposed to ambient air pollution from a variety of sources including motor vehicles, ocean-going vessels, and Saharan dust. We conducted an air sampling exposure study in Grenada to describe daily changes in fine particulate matter (PM_2.5) pollution, and during Saharan dust episodes. Further, we assessed the impacts of COVID-19 public health interventions on PM_2.5 concentrations in 2020. Four fixed-site PurpleAir monitors were installed throughout Grenada, and one on the neighboring island of Carriacou. PM_2.5 was measured between January 6 and December 31, 2020. We classified each of these days based on whether COVID-19 public health mitigation measures were in place or not. Descriptive analyses were performed to characterize fluctuations in PM_2.5, and we assessed the impacts of public health restrictions on PM_2.5 using multivariate regression. The mean daily PM_2.5 concentration in 2020 was 4.4 μg/m³. During the study period, the minimum daily PM_2.5 concentration was 0.7 μg/m³, and the maximum was 20.4 μg/m³. Daily mean PM_2.5 concentrations more than doubled on Saharan dust days (8.5 vs 3.6 μg/m³; p < 0.05). The daily mean PM_2.5 concentrations were estimated to be 1.2 μg/m³ lower when COVID-19 restrictions were in effect. Ambient PM_2.5 concentrations in Grenada are relatively low compared to other countries; however, Saharan dust episodes represent an important source of exposure. Low-cost sensors provide an opportunity to increase surveillance of air pollution in the Caribbean, however their value could be enhanced with the development of correction algorithms that more closely approximate values from reference-grade monitors.Implications: This study describes daily fluctuations in ambient PM_2.5 concentrations in Grenada in 2020. Overall, concentrations of PM_2.5 were low; however, we found that Saharan dust events cause daily exceedances in PM_2.5 above the current 24-hr limits of the World Health Organization. Moreover, the constructed models suggest that public health interventions to reduce the spread of COVID-19 reduced PM_2.5 concentrations by 27%.

Long-Term Indoor-Outdoor PM2.5 Measurements Using PurpleAir Sensors: An Improved Method of Calculating Indoor-Generated and Outdoor-Infiltrated Contributions to Potential Indoor Exposure

Low-cost monitors make it possible now for the first time to collect long-term (months to years) measurements of potential indoor exposure to fine particles. Indoor exposure is due to two sources: particles infiltrating from outdoors and those generated by indoor activities. Calculating the relative contribution of each source requires identifying an infiltration factor. We develop a method of identifying periods when the infiltration factor is not constant and searching for periods when it is relatively constant. From an initial regression of indoor on outdoor particle concentrations, a Forbidden Zone can be defined with an upper boundary below which no observations should appear. If many observations appear in the Forbidden Zone, they falsify the assumption of a single constant infiltration factor. This is a useful quality assurance feature, since investigators may then search for subsets of the data in which few observations appear in the Forbidden Zone. The usefulness of this approach is illustrated using examples drawn from the PurpleAir network of optical particle monitors. An improved algorithm is applied with reduced bias, improved precision, and a lower limit of detection than either of the two proprietary algorithms offered by the manufacturer of the sensors used in PurpleAir monitors.

Environmental justice analysis of wildfire-related PM2.5 exposure using low-cost sensors in California

The increasing number and severity of wildfires is negatively impacting air quality for millions of California residents each year. Community exposure to PM_2.5 in two main population centers (San Francisco Bay area and Los Angeles County area) was assessed using the low-cost PurpleAir sensor network for the record-setting 2020 California wildfire season. Estimated PM_2.5 concentrations in each study area were compared to census tract-level environmental justice vulnerability indicators, including environmental, health, and demographic data. Higher PM_2.5 concentrations were positively correlated with poverty, cardiovascular emergency department visits, and housing inequities. Sensors within 30 km of actively burning wildfires showed statistically significant increases in indoor (~800 %) and outdoor (~540 %) PM_2.5 during the fires. Results indicate that wildfire emissions may exacerbate existing health disparities as well as the burden of pollution in disadvantaged communities, suggesting a need to improve monitoring and adaptive capacity among vulnerable populations.

Reaction of HOCl with Wood Smoke Aerosol: Impacts on Indoor Air Quality and Outdoor Reactive Chlorine

High loadings of biomass burning (BB) aerosol particles from wildfire or residential heating sources can be present in both outdoor and indoor environments, where they deposit onto surfaces such as walls and furniture. These pollutants can interact with oxidants in both the aerosol and deposited forms. Hypochlorous acid (HOCl), a strong oxidant emitted during cleaning with chlorine-cleaning agents such as bleach, can attain mixing ratios of hundreds of ppbv indoors; moreover, lower mixing ratios are naturally present outdoors. Here, we report the heterogeneous reactivity of HOCl with wood smoke aerosol particles. After exposure to gas-phase HOCl, the particle chlorine content increased reaching chlorine-to-organic mass ratios of 0.07 with the chlorine covalently bound as organochlorine species, many of which are aromatic. Investigating individual potential BB components, we observed that unsaturated species such as coniferaldehyde and furfural react efficiently with HOCl. These observations indicate that organochlorine pollutants will form indoors when bleach cleaning a wildfire impacted space. The chlorine component of particles internally mixed with BB material and chloride initially increased, upon HOCl exposure, indicating that active chlorine recycling in the outdoor environment will be suppressed in the presence of BB emissions.

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.

Lung Effects of Household Air Pollution

Biomass fuel smoke, secondhand smoke, and oxides of nitrogen are common causes of household air pollution (HAP). Almost 2.4 billion people worldwide use solid fuels for cooking and heating, mostly in low- and middle-income countries. Wood combustion for household heating is also common in many areas of high-income countries, and minorities are particularly vulnerable. HAP in low- and middle-income countries is associated with asthma, acute respiratory tract infections in adults and children, chronic obstructive pulmonary disease, lung cancer, tuberculosis, and respiratory mortality. Although wood smoke exposure levels in high-income countries are typically lower than in lower-income countries, it is similarly associated with accelerated lung function decline, higher prevalence of airflow obstruction and chronic bronchitis, and higher all-cause and respiratory cause-specific mortality. Household air cleaners with high-efficiency particle filters have mixed effects on asthma and chronic obstructive pulmonary disease outcomes. Biomass fuel interventions in low-income countries include adding chimneys to cookstoves, improving biomass fuel combustion stoves, and switching fuel to liquid petroleum gas. Still, the impact on health outcomes is inconsistent. In high-income countries, strategies for reducing biomass fuel-related HAP are centered on community-level woodstove changeout programs, although the results are again inconsistent. In addition, initiatives to encourage home smoking bans have mixed success in households with children. Environmental solutions to reduce HAP have varying success in reducing pollutants and health problems. Improved understanding of indoor air quality factors and actions that prevent degradation or improve polluted indoor air may lead to enhanced environmental health policies, but health outcomes must be rigorously examined.

Modeling fine-grained spatio-temporal pollution maps with low-cost sensors

The use of air quality monitoring networks to inform urban policies is critical especially where urban populations are exposed to unprecedented levels of air pollution. High costs, however, limit city governments' ability to deploy reference grade air quality monitors at scale; for instance, only 33 reference grade monitors are available for the entire territory of Delhi, India, spanning 1500 sq km with 15 million residents. In this paper, we describe a high-precision spatio-temporal prediction model that can be used to derive fine-grained pollution maps. We utilize two years of data from a low-cost monitoring network of 28 custom-designed low-cost portable air quality sensors covering a dense region of Delhi. The model uses a combination of message-passing recurrent neural networks combined with conventional spatio-temporal geostatistics models to achieve high predictive accuracy in the face of high data variability and intermittent data availability from low-cost sensors (due to sensor faults, network, and power issues). Using data from reference grade monitors for validation, our spatio-temporal pollution model can make predictions within 1-hour time-windows at 9.4, 10.5, and 9.6% Mean Absolute Percentage Error (MAPE) over our low-cost monitors, reference grade monitors, and the combined monitoring network respectively. These accurate fine-grained pollution sensing maps provide a way forward to build citizen-driven low-cost monitoring systems that detect hazardous urban air quality at fine-grained granularities.

Exposures and behavioural responses to wildfire smoke

Pollution from wildfires constitutes a growing source of poor air quality globally. To protect health, governments largely rely on citizens to limit their own wildfire smoke exposures, but the effectiveness of this strategy is hard to observe. Using data from private pollution sensors, cell phones, social media posts and internet search activity, we find that during large wildfire smoke events, individuals in wealthy locations increasingly search for information about air quality and health protection, stay at home more and are unhappier. Residents of lower-income neighbourhoods exhibit similar patterns in searches for air quality information but not for health protection, spend less time at home and have more muted sentiment responses. During smoke events, indoor particulate matter (PM2.5) concentrations often remain 3-4× above health-based guidelines and vary by 20× between neighbouring households. Our results suggest that policy reliance on self-protection to mitigate smoke health risks will have modest and unequal benefits.

Smoke and the eyes: A review of the harmful effects of wildfire smoke and air pollution on the ocular surface

Wildfires are occurring worldwide with greater frequency and intensity. Wildfires, as well as other sources of air pollution including environmental tobacco smoke, household biomass combustion, agricultural burning, and vehicular emissions, release large amounts of toxic substances into the atmosphere. The ocular surface is constantly exposed to the ambient air and is hence vulnerable to damage from air pollutants. This review describes the detrimental effects of wildfire smoke and air pollution on the ocular surface and resultant signs and symptoms. The latest relevant evidence is synthesised and critically evaluated. A mechanism for the pathophysiology of ocular surface damage will be proposed considering the existing literature on respiratory effects of air pollution. Current strategies to reduce human exposure to air pollutants are discussed and specific possible approaches to protect the ocular surface and manage air pollution induced ocular surface damage are suggested. Further avenues of research are suggested to understand how acute and chronic air pollution exposure affects the ocular surface including the short and long-term implications.

Indoor contribution to PM2 .5 exposure using all PurpleAir sites in Washington, Oregon, and California

Low-cost monitors have made it possible for the first time to measure indoor PM_2.5 concentrations over extended periods of time (months to years). Coupled with concurrent outdoor measurements, these indoor measurements can be divided into particles entering the building from outdoors and particles generated from indoor activities. Indoor-generated particles are not normally considered in epidemiological studies, but they can have health effects (e.g., passive smoking and high-temperature cooking). We employed The Random Component Superposition (RCS) regression model to estimate infiltration factors for up to 790 000 matched indoor and outdoor sites. The median infiltration factors for subgroups in the 3-state region ranged between 0.22 and 0.24, with an interquartile range (IQR) of 0.13-0.40. These infiltration factors allowed calculation of both the indoor-generated and outdoor-infiltrated PM_2.5 . Indoor-generated particles contributed, on average, 46%-52% of total indoor PM_2.5 concentrations. However, the site-specific fractional contribution of these indoor sources to total indoor PM_2.5 ranged from near-zero to nearly 100%. The influence of indoor-generated particles on potential exposures varied widely relative to outdoor concentrations. The greatest influence of indoor-generated particles occurred at low-to-moderate daily mean outdoor PM_2.5 levels around 6 μg/m³ and was negligible at outdoor concentrations >20 μg/m³ . Epidemiological studies incorporating only estimated exposures due to the particles of ambient origin may benefit from the newly available knowledge of long-term indoor-generated particle concentrations.

As California burns: the psychology of wildfire- and wildfire smoke-related migration intentions

Climate change impacts and rapid development in the wildland-urban interface are increasing population exposure and vulnerability to the harmful effects of wildfire and wildfire smoke. The direct and indirect effects of these hazards may impact future mobility decisions among populations at risk. To better understand how perceptions and personal experience inform wildfire- and smoke-associated migration intentions, we surveyed a representative sample of 1108 California residents following the 2020 wildfire season. We assessed the associations between threat appraisal, coping appraisal, personal experience, migration intentions, the impact of wildfire and smoke on migration intentions and place satisfaction, and the potential likelihood of future migration. Results indicate that roughly a third of our sample intended to move in the next 5 years, nearly a quarter of whom reported that wildfire and smoke impacted their migration decision at least a moderate amount. Prior negative outcomes (e.g., evacuating, losing property) were associated with intentions to migrate. Perceived susceptibility and prior negative outcomes were associated with a greater impact of wildfire and smoke on migration intentions. For those intending to remain in place, prior negative outcomes were associated with a greater impact of wildfire and smoke on place satisfaction, which was in turn associated with a greater reported likelihood of future migration. Our findings suggest that perceptions of and experiences with wildfire and smoke may impact individual mobility decisions. These insights may be leveraged to inform risk communications and outreach campaigns to encourage wildfire and smoke risk mitigation behaviors and to improve climate migration modeling.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s11111-022-00409-w.

Field measurements of indoor and community air quality in rural Beijing before, during, and after the COVID-19 lockdown

The coronavirus (COVID-19) lockdown in China is thought to have reduced air pollution emissions due to reduced human mobility and economic activities. Few studies have assessed the impacts of COVID-19 on community and indoor air quality in environments with diverse socioeconomic and household energy use patterns. The main goal of this study was to evaluate whether indoor and community air pollution differed before, during, and after the COVID-19 lockdown in homes with different energy use patterns. Using calibrated real-time PM_2.5 sensors, we measured indoor and community air quality in 147 homes from 30 villages in Beijing over 4 months including periods before, during, and after the COVID-19 lockdown. Community pollution was higher during the lockdown (61 ± 47 μg/m³ ) compared with before (45 ± 35 μg/m³ , p < 0.001) and after (47 ± 37 μg/m³ , p < 0.001) the lockdown. However, we did not observe significantly increased indoor PM_2.5 during the COVID-19 lockdown. Indoor-generated PM_2.5 in homes using clean energy for heating without smokers was the lowest compared with those using solid fuel with/without smokers, implying air pollutant emissions are reduced in homes using clean energy. Indoor air quality may not have been impacted by the COVID-19 lockdown in rural settings in China and appeared to be more impacted by the household energy choice and indoor smoking than the COVID-19 lockdown. As clean energy transitions occurred in rural households in northern China, our work highlights the importance of understanding multiple possible indoor sources to interpret the impacts of interventions, intended or otherwise.

Integrating Multiscale Geospatial Environmental Data into Large Population Health Studies: Challenges and Opportunities

Quantifying the exposome is key to understanding how the environment impacts human health and disease. However, accurately, and cost-effectively quantifying exposure in large population health studies remains a major challenge. Geospatial technologies offer one mechanism to integrate high-dimensional environmental data into epidemiology studies, but can present several challenges. In June 2021, the National Institute of Environmental Health Sciences (NIEHS) held a workshop bringing together experts in exposure science, geospatial technologies, data science and population health to address the need for integrating multiscale geospatial environmental data into large population health studies. The primary objectives of the workshop were to highlight recent applications of geospatial technologies to examine the relationships between environmental exposures and health outcomes; identify research gaps and discuss future directions for exposure modeling, data integration and data analysis strategies; and facilitate communications and collaborations across geospatial and population health experts. This commentary provides a high-level overview of the scientific topics covered by the workshop and themes that emerged as areas for future work, including reducing measurement errors and uncertainty in exposure estimates, and improving data accessibility, data interoperability, and computational approaches for more effective multiscale and multi-source data integration, along with potential solutions.

Wildfire Impact on Indoor and Outdoor PAH Air Quality

Air quality impacts from wildfires are poorly understood, particularly indoors. As frequencies increase, it is important to optimize methodologies to understand and reduce chemical exposures from wildfires. Public health recommendations use air quality estimates from outdoor stationary air monitors, discounting indoor air conditions, and do not consider chemicals in the vapor phase, known to elicit adverse effects. We investigated vapor-phase polycyclic aromatic hydrocarbons (PAHs) in indoor and outdoor air before, during, and after wildfires using a community-engaged research approach. Paired passive air samplers were deployed at 15 locations across four states. Twelve unique PAHs were detected only in outdoor air during wildfires, highlighting a PAH exposure mixture for future study. Heavy-molecular-weight (HMW) outdoor PAH concentrations and average Air Quality Index (AQI) values were positively correlated (p < 0.001). Indoor PAH concentrations were higher in 77% of samples across all sampling events. Even during wildfires, 58% of sampled locations still had higher indoor PAH air concentrations. When AQI values exceeded 140 (unhealthy for sensitive groups), outdoor PAH concentrations became similar to or higher than indoors. Cancer and noncancer inhalation risk estimates from vapor-phase PAHs were higher indoors than outdoors, regardless of the wildfire impact. Consideration of indoor air quality and vapor-phase PAHs could inform public health recommendations regarding wildfires.

Leveraging Citizen Science and Low-Cost Sensors to Characterize Air Pollution Exposure of Disadvantaged Communities in Southern California

Assessing exposure to fine particulate matter (PM_2.5) across disadvantaged communities is understudied, and the air monitoring network is inadequate. We leveraged emerging low-cost sensors (PurpleAir) and engaged community residents to develop a community-based monitoring program across disadvantaged communities (high proportions of low-income and minority populations) in Southern California. We recruited 22 households from 8 communities to measure residential outdoor PM_2.5 concentrations from June 2021 to December 2021. We identified the spatial and temporal patterns of PM_2.5 measurements as well as the relationship between the total PM_2.5 measurements and diesel PM emissions. We found that communities with a higher percentage of Hispanic and African American population and higher rates of unemployment, poverty, and housing burden were exposed to higher PM_2.5 concentrations. The average PM_2.5 concentrations in winter (25.8 µg/m³) were much higher compared with the summer concentrations (12.4 µg/m³). We also identified valuable hour-of-day and day-of-week patterns among disadvantaged communities. Our results suggest that the built environment can be targeted to reduce the exposure disparity. Integrating low-cost sensors into a citizen-science-based air monitoring program has promising applications to resolve monitoring disparity and capture “hotspots” to inform emission control and urban planning policies, thus improving exposure assessment and promoting environmental justice.

Indoor Air Quality Considerations for Laboratory Animals in Wildfire-Impacted Regions-A Pilot Study

Wildfire events are increasing across the globe. The smoke generated as a result of this changing fire landscape is potentially more toxic than air pollution from other ambient sources, according to recent studies. This is especially concerning for populations of humans or animals that live downwind of areas that burn frequently, given that ambient exposure to wildfire smoke cannot be easily eliminated. We hypothesized that a significant indoor air pollution risk existed for laboratory animal facilities located proximal to fire-prone areas. Here, we measured real time continuous outdoor and indoor air quality for 28 days at a laboratory animal facility located in the Rocky Mountain region. We demonstrated that during a wildfire event, the indoor air quality of this animal facility is influenced by ambient smoke events. The daily average indoor fine particulate matter value in an animal room exceeded the Environmental Protection Agency's ambient annual standard 14% of the time and exceeded the World Health Organization's ambient annual guideline 71% of the time. We further show that specialized cage filtration systems are capable of mitigating air pollution penetrance and could improve an animal's microenvironment. The potential effects for laboratory animal physiology that occur in response to the exposure levels and durations measured in this study remain to be determined; yet, even acute wildfire exposure events have been previously correlated with significant differences in gene regulatory and metabolic processes in vivo. We believe these findings warrant consideration for indoor laboratory animal facility air quality monitoring and development of smoke exposure prevention and response protocols, especially among facilities located downwind of fire-prone landscapes.

Calibration of PurpleAir PA-I and PA-II Monitors Using Daily Mean PM2.5 Concentrations Measured in California, Washington, and Oregon from 2017 to 2021

Large quantities of real-time particle data are becoming available from low-cost particle monitors. However, it is crucial to determine the quality of these measurements. The largest network of monitors in the United States is maintained by the PurpleAir company, which offers two monitors: PA-I and PA-II. PA-I monitors have a single sensor (PMS1003) and PA-II monitors employ two independent PMS5003 sensors. We determine a new calibration factor for the PA-I monitor and revise a previously published calibration algorithm for PA-II monitors (ALT-CF3). From the PurpleAir API site, we downloaded 83 million hourly average PM_2.5 values in the PurpleAir database from Washington, Oregon, and California between 1 January 2017 and 8 September 2021. Daily outdoor PM_2.5 means from 194 PA-II monitors were compared to daily means from 47 nearby Federal regulatory sites using gravimetric Federal Reference Methods (FRM). We find a revised calibration factor of 3.4 for the PA-II monitors. For the PA-I monitors, we determined a new calibration factor (also 3.4) by comparing 26 outdoor PA-I sites to 117 nearby outdoor PA-II sites. These results show that PurpleAir PM_2.5 measurements can agree well with regulatory monitors when an optimum calibration factor is found.

Outdoor and indoor fine particulate matter at skilled nursing facilities in the western United States during wildfire and non-wildfire seasons

Wildfire activity is increasing in parts of the world where extreme drought and warming temperatures contribute to fireprone conditions, including the western United States. The elderly are among the most vulnerable, and those in long-term care with preexisting conditions have added risk for adverse health outcomes from wildfire smoke exposure. In this study, we report continuous co-located indoor and outdoor fine particulate matter (PM_2.5 ) measurements at four skilled nursing facilities in the western United States. Throughout the year 2020, over 8000 h of data were collected, which amounted to approximately 300 days of indoor and outdoor sampling at each facility. The highest indoor 24 h average PM_2.5 recorded at each facility was 43.6 µg/m³ , 103.2 µg/m³ , 35.4 µg/m³ , and 202.5 µg/m³ , and these peaks occurred during the wildfire season. The indoor-to-outdoor PM_2.5 ratio and calculated infiltration efficiencies indicated high variation in the impact of wildfire events on Indoor Air Quality between the four facilities. Notably, infiltration efficiency ranged from 0.22 to 0.76 across the four facilities. We propose that this variability is evidence that PM_2.5 infiltration may be impacted by modifiable building characteristics and human behavioral factors, and this should be addressed in future studies.

Intercomparison of PurpleAir Sensor Performance over Three Years Indoors and Outdoors at a Home: Bias, Precision, and Limit of Detection Using an Improved Algorithm for Calculating PM2.5

Low-cost particle sensors are now used worldwide to monitor outdoor air quality. However, they have only been in wide use for a few years. Are they reliable? Does their performance deteriorate over time? Are the algorithms for calculating PM_2.5 concentrations provided by the sensor manufacturers accurate? We investigate these questions using continuous measurements of four PurpleAir monitors (8 sensors) under normal conditions inside and outside a home for 1.5–3 years. A recently developed algorithm (called ALT-CF3) is compared to the two existing algorithms (CF1 and CF_ATM) provided by the Plantower manufacturer of the PMS 5003 sensors used in PurpleAir PA-II monitors. Results. The Plantower CF1 algorithm lost 25–50% of all indoor data due in part to the practice of assigning zero to all concentrations below a threshold. None of these data were lost using the ALT-CF3 algorithm. Approximately 92% of all data showed precision better than 20% using the ALT-CF3 algorithm, but only approximately 45–75% of data achieved that level using the Plantower CF1 algorithm. The limits of detection (LODs) using the ALT-CF3 algorithm were mostly under 1 µg/m³, compared to approximately 3–10 µg/m³ using the Plantower CF1 algorithm. The percentage of observations exceeding the LOD was 53–92% for the ALT-CF3 algorithm, but only 16–44% for the Plantower CF1 algorithm. At the low indoor PM_2.5 concentrations found in many homes, the Plantower algorithms appear poorly suited.

2021 Climate and Health Review - Uncharted Territory: Extreme Weather Events and Morbidity

Extreme weather events (EWEs) affected health in every world region during 2021, placing the planet in "uncharted territory." Portraying the human impacts of EWEs is part of a health frame that suggests public knowledge of these risks will spur support for needed policy change. The health frame has gained traction since the Paris COP21 (United Nations Climate Change Conference) and arguably helped to achieve modest progress at the Glasgow COP26. However, reporting rarely covers the full picture of health impacts from EWEs, instead focusing on cost of damages, mortality, and displacement. This review summarizes data for 30 major EWEs of 2021 and, based on the epidemiological literature, discusses morbidity-related exposures for four hazards that marked the year: wildfire smoke; extreme cold and power outages; extreme, precipitation-related flooding; and drought. A very large likely burden of morbidity was found, with particularly widespread exposure to risk of respiratory outcomes (including interactions with COVID-19) and mental illnesses. There is need for a well-disseminated global annual report on EWE morbidity, including affected population estimates and evolving science. In this way, the public health frame may be harnessed to bolster evidence for the broader and promising frame of "urgency and agency" for climate change action.