Search

Pregnant people are vulnerable to air pollution exposure, including risk of preterm birth, low birth weight, and stillbirth. Understanding the infiltration of outdoor wildfire smoke into a residential space is critical for the accurate assessment of wildfire smoke exposure and associated health effects in pregnant people. Relying on ambient measurements of wildfire smoke alone can result in exposure misclassification. In this study, we examine the role of physical housing characteristics in the relationship between smoke exposure and preterm birth. In particular, we examine the effect of home size, year of construction, cooling type, and renovation status, as effect modifiers in the relationship between smoke exposure during pregnancy and preterm birth from 2007 to 2015 in California. To do this, we combined data on home characteristics from the California Tax Assessor, birth outcomes from the California birth records database, and the number of smoke days for each pregnancy from the NOAA (National Oceanic and Atmospheric Administration) Hazard Mapping System (HMS). We estimated the association between smoke day exposures and odds of preterm birth using logistic regression models and stratified by air basin and housing characteristics. Our findings reveal that cooling type and renovation status are key factors modifying the smoke exposure-preterm birth relationship. Notably, we found elevated associations for people living in unrenovated homes, those using evaporative cooling systems, and those using central air conditioning units. While we observed elevated odds of preterm birth associated with increasing smoke day exposure for residents of large and new homes, this effect does not significantly differ across home size and age quartiles. This study highlights the need to further examine the relative roles of housing characteristics as well as factors not measured here including behavioral factors, time spent outdoors, window use, and occupational exposures in driving adverse birth outcomes related to wildfire smoke exposure. [Display omitted] • Smoke day exposure is linked to preterm birth (PTB) outcomes in California 2007–2015. • Higher PTB risk from smoke exposure was found in unrenovated homes. • Increased PTB risk was found in homes with evaporative cooling systems, and to a lesser extent, central AC. • Large and new homes showed higher PTB odds with smoke exposure, but not statistically significant. [ABSTRACT FROM AUTHOR]

Urban wind conditions and air quality have the potential to affect the majority of the world's population. Specifically, smoke from wildfires is increasingly posing risks to people living in cities as it is transported by the wind, making a more complete understanding of how atmospheric flow affects air quality in urban environments necessary. Computational fluid dynamics is used to investigate the flow and smoke dispersion characteristics in Montréal on July 17, 2023, between 16:00 and 22:00 UTC. This day exhibited moderate southwest winds carrying significant amounts of wildfire smoke into the city. Reynolds-averaged Navier-Stokes simulations using the standard k-ε and Shear Stress Transport k-ω turbulence models are compared against measurements of wind velocity and PM2.5 concentration from an anemometer, a Doppler lidar, and an air quality monitoring station. While the models are shown to accurately predict the urban boundary layer wind profile, only the k-ε model provides satisfactory predictions of wind speed in comparison with the anemometer, stressing the importance of accurately modeling dynamics on the building scale. The effect of the turbulent Schmidt number is investigated, for which the value of 0.6 most accurately reproduces the dispersion phenomena near the air quality monitoring station. Concentrations of the wildfire smoke are found to vary significantly across areas of the city, as some building morphologies are found to direct pollution to regions where it becomes trapped. Additional discussion of local wind and air quality characteristics is presented to better inform citizens of potential risks. • Effects of wildfire smoke dispersion in urban environment investigated. • Computational fluid dynamics model validated using Doppler lidar wind profiler. • Standard k-ε turbulence model outperforms Shear Stress Transport k-ω model for wind. • A turbulent Schmidt number of 0.6 most accurately captures urban pollutant dispersion. • Buildings significantly alter wind comfort and air quality. [ABSTRACT FROM AUTHOR]

Wildfire smoke exposure alters grape composition, potentially resulting in "smoke tainted" wines. This has been correlated with elevated levels of smoke-derived volatile phenols (VPs) in grapes and wines. This work sought to create a predictive tool that could correlate levels of VPs in smoke with concentrations in grapes and wines. Therefore, passive samplers and Cabernet Sauvignon grapes were intentionally exposed to various smoke intensities, and wines were made thereafter. As expected, concentrations of VPs in grapes and wines were positively associated with the intensity of smoke exposure. Interestingly, levels of guaiacol in the passive samplers had a strong positive correlation with concentrations in grapes (R2 = 0.9999) and wines (R2 = 0.9998). The passive samplers were able to accurately predict guaiacol levels in smoke exposed grapes and wines with percent errors ranging from 0.08 to 11.3 %. These results suggest the capability of passive samplers to act as a monitoring system in vineyards during smoke events. • Levels of free and bound volatile phenols were positively correlated with smoke intensity in grapes and wines. • Passive samplers were able to accurately predict the concentration of guaiacol in grapes and wines and 4-methylguaiacol and o- cresol in wines • Passive samplers have potential to predict smoke impact in a vineyard after exposure [ABSTRACT FROM AUTHOR]

Low-cost, do-it-yourself (DIY) portable air cleaners (PACs) are an accessible option for socioeconomically disadvantaged communities to reduce smoke exposure, but their real-world efficacy is largely untested. We conducted two pilot studies to quantify the impact of DIY and comparable lower-cost commercial PACs on indoor fine particle mass concentrations (PM 2.5) in a tribal community exposed to wildfire and wood stove smoke. We measured indoor and outdoor PM 2.5 , indoor carbon dioxide, main door activity, and PAC usage in homes on the Hoopa Valley Indian Reservation for wildfire (n = 8) and wood stove (n = 11) pilot studies. We monitored initial PM 2.5 , then sequentially provided a DIY PAC (box fan with a MERV 13 filter), a commercial PAC, and a real-time air quality display with participants' choice of either or both PACs. We quantified reductions in total indoor (PM 2.5-IN) and infiltrated (PM 2.5-INFILT) PM 2.5 using mixed linear models and determined the barriers and facilitators of PAC usage through interviews. In the wildfire study, DIY PAC use was associated with 7–11% reduction in PM 2.5-IN and PM 2.5-INFILT ; commercial PAC use was only associated with reduced PM 2.5-INFILT (18.3%). In the wood stove study, commercial PAC use was associated with roughly twice the reductions in PM 2.5-IN (20.0%) and PM 2.5-INFILT (10.0%) relative to DIY PAC use. Interviews identified cost and access to replacement filters as barriers to PAC use, demonstrating the need for lower cost PACs. All households preferred the commercial PAC due to the DIY PAC's higher noise level and cooling effect in winter; 75% of participants reported that they would use DIY PACs in a different room or during warmer weather and smoke events. While both pilot studies suggest PACs reduced PM 2.5 , future studies in smoke-impacted communities should reflect that DIY PAC efficacy depends on prior PAC ownership, ambient smoke conditions, and PAC intrusiveness (noise, size and appearance, cooling effects) affecting user behavior. • Use of do-it-yourself air cleaner was associated with an ∼10% indoor PM 2.5 reduction, similar to a small commercial air cleaner. • The commercial air cleaner reduced PM 2.5 infiltration ratio 1.5–2.3 times more than the do-it-yourself air cleaner. • Participants disliked using the do-it-yourself air cleaner due to its undesirable cooling effect in cold months and loudness. [ABSTRACT FROM AUTHOR]

Adverse weather events significantly impact the operations of urban transportation systems and change human travel behaviors. Over the decades, wildfires have emerged as a pressing concern due to their increased frequency and intensity, yet the relationship between wildfire smoke and public transportation usage remains largely unexplored. Leveraging high-resolution daily wildfire-driven PM 2.5 concentration estimates and station-level Metrorail ridership data in the Washington Metropolitan Area spanning 2012–2019, we examine the effects of wildfire smoke exposure on Metrorail usage. We find that wildfire smoke exposure results in a 0.8% increase in Metrorail ridership on weekdays and a more pronounced 3.7% rise on weekends. Additionally, we show a stronger response in Metrorail ridership to wildfire smoke during off-peak hours compared to peak hours, with the most substantial increase observed during the winter. Our heterogeneity analysis further suggests that a lack of vehicle ownership and higher reliance on walking and public transportation are key factors leading to increased Metrorail ridership. Collectively, these results highlight the need for proactive service adjustments and effective communication strategies to accommodate the potential shifts in human travel behaviors and Metrorail ridership on days exposed to wildfire smoke. [ABSTRACT FROM AUTHOR]

As wildfire activity continues to increase throughout much of the western US, questions remain about how to effectively communicate wildfire smoke risk to harder-to-reach groups, including rural populations. Standard public health strategies rely largely on risk assessment and communication informed by available air quality data. However, rural populations can be difficult to reach through traditional communication channels and air quality monitoring to inform messaging can be absent or scarce. As efforts increase to expand air quality monitoring into rural regions, there is a need to identify and affirm the most effective content and communication channels for motivating protective action. We used a mental models approach to identify wildfire smoke risk information needs and preferred communication channels in three rural counties in northern Nevada. Participants revealed a substantial knowledge base with opportunities for enhancement related to the range of potential physical and mental health impacts, vulnerable groups, and exposure mitigation strategies. Preferred communication channels were varied but almost exclusively local. The mental models approach also uncovered important barriers to exposure mitigation as well as potential areas of future research. Insights gained from this study will be used to inform targeted wildfire smoke risk communication for rural Nevada counties and may serve to motivate similar studies in other rural regions. Identifying similarities and differences in information needs and preferred communication channels can help inform understanding of how and why to tailor wildfire smoke risk communication. Any new messaging developed from such studies should be evaluated to ensure its effectiveness. [ABSTRACT FROM AUTHOR]

Utility-related ignitions have historically been correlated with catastrophic wildfire. First noted in Australia and Southern California, as climate-change related drought has increased catastrophic wildfires from utility ignitions now plague the western US. Regulatory changes now require California utilities to analyze and mitigate wildfire risk. This analysis reviews recent data and risk assessments from Pacific Gas and Electric Company (PG&E), Southern California Edison Company (SCE), and San Diego Gas and Electric Company (SDG&E), California's largest electrical utilities. While utilities have adopted data science methodology, covariates capturing extreme weather effects are missing and tools lack mechanisms to incorporate causal linkage between likelihood and consequence models. Consequently, risk models incorrectly prioritize risk drivers, such as vegetation, equipment, or external agents. Additionally, match-drop wildfire spread calculations fail to represent large fires due to limited run time. Risk models also fail to incorporate the health effects of wildfire smoke. Power shutoff is an effective mitigation during extreme weather events, but causes significant public harm. "Hardening" programs, especially undergrounding lines, are effective but their expense threatens public health for the poorest. Accurate balancing of wildfire risks, risk of power loss, and financial impacts on vulnerable populations, in conjunction with application of new technology is required to address the utility wildfire problem. • Electric utility risk models have biases overestimating and underestimating risk. • Utility risk models should include extreme wind as ignition and consequence driver. • De-energization is an effective mitigation tool but biases risk models. • Wildfire smoke health effects should be incorporated into risk models. • Utility undergrounding costs are high enough to potentially harm public health. [ABSTRACT FROM AUTHOR]

In recent years, the size and severity of wildfires in the Western United States have been increasing, and there is growing evidence that smoke from wildfires is associated with various negative health consequences. Integrating perceived knowledge and prior experience into the protection motivation theory (PMT), we surveyed a diverse sample (N = 529) in the Western United States to identify sociopsychological factors that explain wildfire smoke-related adaptive behavioral intentions. While people's intention to adapt to wildfire smoke was positively associated with perceived vulnerability and response efficacy, such intention was negatively associated with perceived self-efficacy and response cost. While prior wildfire experience was not associated with coping appraisal, perceived knowledge was positively associated with coping appraisal and intensified the positive association between perceived severity and behavioral intention. Our findings extend PMT approach in the context of wildfire smoke exposure to identify the antecedent role and moderating role of perceived knowledge and prior experience, while also offering implications for risk communication campaigns to encourage wildfire smoke adaptive behaviors among the public. [ABSTRACT FROM AUTHOR]

The wildfires in Fort McMurray of Alberta, Canada, injected large amounts of smoke aerosols in May 2016 and were identified as being one of Canada's major weather events of the year. This paper presents a synergistic remote sensing and in-situ measurement of the resultant smoke plume transport, optical properties, and its impacts on local air quality in New York City (NYC). Comparisons with the operational air quality model forecast (the NOAA National Air Quality Forecasting Capability, NAQFC) performance are presented. The aloft plume intrusions on May 9–13 and 25–29, 2016, and their mixing down into the planetary-boundary layer (PBL) were observed by a combined lidar, ceilometer and other measurement. A decrease in single-scattering albedo and absorption Angstrom exponent near one indicates that the plumes were absorbing aerosol dominated. Dramatic impacts of smoke transport on the ground air quality are demonstrated with a coincident increase of ground PM 2.5 (from 5- to 25–30 μg/m 3 ) in NYC urban and upwind rural area, enhancement of the PM 2.5 speciation (organic carbon, elemental carbon, potassium ion (K + )) and the ozone exceedance of NAAQS. Using the satellite and model product, we show regional spatial distribution of smoke, multiple transport paths and wildfire sources. Finally, with the lidar vertical profiling observations, we evaluate the model PBL-height (PBLH) and PM 2.5 during May 24th to 30th, 2016. The model PBLH shows consistent diurnal variation with the observed mixing layer height (MLH), but is clearly overestimated during the convective daytime hours. On the other hand, when estimating the MLH directly from the model PM 2.5 profile, better agreement with observation was indicated. This helps explain the good agreement between the model PM 2.5 and surface measurements except for the model overestimate during the morning of May 25 and 26, 2016. [ABSTRACT FROM AUTHOR]

Wildfire episodes pose a significant public health threat in the United States. Adverse health impacts associated with wildfires occur near the burn area as well as in places far downwind due to wildfire smoke exposures. Health effects associated with exposure to particulate matter arising from wildfires can range from mild eye and respiratory tract irritation to more serious outcomes such as asthma exacerbation, bronchitis, and decreased lung function. Real-time operational forecasts of wildfire smoke concentrations are available but they are not readily integrated with information on vulnerable populations necessary to identify at-risk communities during wildfire smoke episodes. Efforts are currently underway at the Centers for Disease Control and Prevention (CDC) to develop an online tool that utilizes short-term predictions and forecasts of smoke concentrations and integrates them with measures of population-level vulnerability for identifying at-risk populations to wildfire smoke hazards. The tool will be operationalized on a national scale, seeking input and assistance from several academic, federal, state, local, Tribal, and Territorial partners. The final product will then be incorporated into CDC's National Environmental Public Health Tracking Network ( http://ephtracking.cdc.gov ), providing users with access to a suite of mapping and display functionalities. A real-time vulnerability assessment tool incorporating standardized health and exposure datasets, and prevention guidelines related to wildfire smoke hazards is currently unavailable for public health practitioners and emergency responders. This tool could strengthen existing situational awareness competencies, and expedite future response and recovery efforts during wildfire episodes. [ABSTRACT FROM AUTHOR]

Pacific Northwest wildfires are expected to increase in frequency and scale, with more communities exposed to smoke. We explored the environmental justice context for wildfire smoke impact to young children in urban communities in the Pacific Northwest with a focus on Seattle, Washington. We found substantial evidence that young children are vulnerable during wildfire smoke events due to a residential building stock that was primarily built before meaningful energy codes were enacted, along with low air conditioning rates; both contribute to a high transfer of air pollutants indoors from the outdoor environment. While our results are limited to PM2.5, we suggest that preventing injustices at child care settings during wildfire smoke events depends primarily on access to real-time information, use of that information to reduce exposure, and the strategies used by policy actors to make these adaptation options available and affordable for vulnerable communities. To date, adaptation during wildfire smoke events relies on voluntary efforts which may not be effective public health remedies in general, and particularly for vulnerable communities. Licensed child care settings could provide feasible and just risk management options for urban communities in the Pacific Northwest. • We explored the environmental justice context for children and wildfire smoke. • Seattle's building stock and lack of air conditioning affect indoor health risk. • Preventing injustice depends on information access by childcare providers. • Licensed childcare provides risk management options for vulnerable populations. [ABSTRACT FROM AUTHOR]

This work is a contribution to the understanding of wildfire smoke emissions. It focuses on the characterization of aerosols emitted by the combustion of dead shrub leaves and twigs with different thickness (range of 0.75–20 mm). The experiments were carried out at bench scale with a cone calorimeter for the burning of Cistus monspeliensis leaves and twigs. Auto-ignition of the samples was obtained by heating their surface with a radiant heat flux of 50 kW/m 2 . The smoke and aerosols emitted before ignition during pre-heating were analysed separately from the smoke and aerosols emitted during the flaming phase. Heat release rate (HRR) was also measured and we observed two different behaviours depending on the diameter of the twigs. Fuel samples with diameter smaller than 4 mm exhibit a single peak HRR whereas two peaks were observed for the twigs with larger diameters. The smoke production rate (SPR) was also measured and it showed that smoke was mainly emitted during the pre-heating phase. We also obtained a strong correlation between HRR and SPR during the flaming phase but no smoke was emitted during the glowing phase. Emission factors of aerosols were calculated depending on these combustion phases (pre-ignition and flaming) and for the range of thickness of the samples. The observations of the aerosols were performed by scanning electron microscopy (SEM) and transmission electron microscopy (TEM). The chemical composition of organic carbon (OC) aerosols, emitted during the pre-ignition phase, were analysed using gas chromatography (GC) coupled with mass spectrometry (MS). Some carcinogenic compounds were identified. The sizes of OC and black carbon (BC) aerosols emitted were measured with an optical device. Most of the BC were PM 0.3 , which corresponds to the alveolar fraction of particles. [ABSTRACT FROM AUTHOR]

Wildfires are increasing in magnitude, frequency, and severity. Populations in the wildland-urban interface and in downwind communities are at increased risk of exposure to elevated concentrations of fine particulate matter (PM 2.5) and other harmful components of wildfire smoke. We conducted this analysis to evaluate the use of modeled predictions of wildfire smoke to create county-level measures of smoke exposure for public health research and surveillance. We evaluated four years (2015–2018) of grid-based North American Mesoscale (NAM)-derived PM 2.5 forecasts from the U.S. Forest Service BlueSky modeling framework with monitoring data from the Environmental Protection Agency Air Quality System (AQS), the Interagency Monitoring of Protected Visual Environments (IMPROVE), the Western Regional Climate Center (WRCC), and the Interagency Real Time Smoke Monitoring (AIRSIS) programs. To assess relationships between model-derived estimates and monitor-based observations, we assessed Spearman's correlations by spatial (i.e., county, level of urbanization, states in the western United States impacted by major wildfires, and climate regions) and temporal (i.e., month and wildfire activity periods) characteristics. We then generated county-level smoke estimates and examined spatial and temporal patterns in total and person-days of smoke exposure. Across all counties in the coterminous United States and for all days, the correlation between county-level model- and monitor-derived PM 2.5 estimates was 0.14 (p < 0.001). Correlations were stronger using data from temporary monitors and for areas and days impacted by high wildfire smoke, especially in the western United States. Correlations between county-level model- and monitor-derived estimates in non-metropolitan counties, and at higher concentrations ranged from 0.25 to 0.54 (p < 0.001). In general, public health practitioners and health researchers need to consider the pros and cons associated with modeled data products for conducting health analyses. Our results support the use of model-derived smoke estimates to identify communities impacted by heavy smoke events, especially during emergency response and for communities located near wildfire episodes. • Spatial and temporal gaps in monitoring network data may be reduced by using archived gridded model predictions. • Correlations between BlueSky- and monitor-derived estimates were stronger using data from temporary monitors. • Model-derived smoke estimates can be used to identify communities impacted by heavy smoke events or near wildfire episodes. [ABSTRACT FROM AUTHOR]

[Display omitted] • Wildfire PM 2.5 was associated with DNA methylation of many human genome loci. • Those loci were mapped to 47 genes related to many human diseases. • The genes were enriched in inflammatory regulation and platelet activation pathways. • DNA methylation signatures of wildfire and non-wildfire PM 2.5 were quite different. Wildfire-related fine particulate matter (PM 2.5) has many adverse health impacts, but its impacts on human epigenome are unknown. We aimed to evaluate the associations between long-term exposure to wildfire-related PM 2.5 and blood DNA methylation, and whether the associations differ from those with non-wildfire-related PM 2.5. We studied 479 Australian women comprising 132 twin pairs and 215 of their sisters. Blood-derived DNA methylation was measured using the HumanMethylation450 BeadChip array. Data on 3-year (year of blood collection and previous two years) average wildfire-related and non-wildfire-related PM 2.5 at 0.01°×0.01° spatial resolution were created by combining information from satellite observations, chemical transport models, and ground-based observations. Exposure data were linked to each participant's home address, assuming the address did not change during the exposure window. For DNA methylation of each cytosine-guanine dinucleotide (CpG), and for global DNA methylation represented by the average of all measured CpGs or CpGs in repetitive elements, we evaluated their associations with wildfire- or non-wildfire-related PM 2.5 using a within-sibship analysis controlling for factors shared between siblings and other important covariates. Differentially methylated regions (DMRs) were defined by comb-p and DMRcate. The 3-year average wildfire-related PM 2.5 (range: 0.3 to 7.6 µg/m3 , mean: 1.6 µg/m3) was negatively, but not significantly (p -values greater than 0.05) associated with all seven global DNA methylation measures. There were 26 CpGs and 33 DMRs associated with wildfire-related PM 2.5 (Bonferroni adjusted p -value < 0.05) mapped to 47 genes enriched for pathways related to inflammatory regulation and platelet activation. These genes have been related to many human diseases or phenotypes e.g., cancer, mental disorders, diabetes, obesity, asthma, blood pressure. These CpGs, DMRs and enriched pathways did not overlap with the 1 CpG and 7 DMRs associated with non-wildfire-related PM 2.5. Long-term exposure to wildfire-related PM 2.5 was associated with various blood DNA methylation signatures in Australian women, and these were distinct from those associated with non-wildfire-related PM 2.5. [ABSTRACT FROM AUTHOR]

On August 8, 2010, a severe derecho type thunderstorm in the Baltic Sea region coincided with smoke from wildfires in Russia. Remarkable smoke aerosol concentrations, with a maximum aerosol optical depth of more than 2 at 550 nm, were observed near the thunderstorm. The impact of the wildfire smoke on the thunderstorm through direct radiative effects was investigated using the Hirlam Aladin Research for Mesoscale Operational Numerical Weather Prediction in Euromed (HARMONIE) model. HARMONIE was successfully able to resolve the dynamics of the thunderstorm, and simulations that considered the influence of the smoke-related aerosols were compared to simulation without aerosols. As simulated by the HARMONIE model, the smoke reduced the shortwave radiation flux at the surface by as much as 300 W/m 2 and decreased the near-surface temperature by as much as 3 °C in the vicinity of the thunderstorm and respectively 100 W/m 2 and 1 °C in the thunderstorm region. Atmospheric instability decreased through the direct radiative effect of aerosols, and several dynamic features of the simulated thunderstorm appeared slightly weaker. [ABSTRACT FROM AUTHOR]

Abstract: We report high concentrations of black carbon aerosols (BC), present at two rural sites in New York during the last week in May 2010, that are linked to wildfire activity. At Mayville BC from wood smoke was recorded for a total of 20 h from three separate episodes, mean concentration was 1400 ng m−3. These three short events contributed 13% of the BC burden during the month of May. At Whiteface Mountain high concentrations of BC, carbon monoxide gas (CO), and fine particulate matter mass (PM2.5) are reported from a heavy smoke event that impacted the Adirondack region of the State on May 31, 2010. PM2.5 mass recorded at the Lodge site (600 m above mean sea level) was 150 μg m−3 at 8:30 am EST and the 24-h mean was almost twice the USEPA limits while CO concentration exceeded 1000 ppb and BC concentration reached 9600 ng m−3. The event was delayed several hours at the Summit site (1500 m above mean sea level) but at 5:45 pm BC concentration reached 1600 ng m−3 and CO was 317 ppbv. Detailed temporal profiles and correlations are presented. [Copyright &y& Elsevier]

[Display omitted] • Early life wildfire smoke exposure was associated with epigenetic changes in macaques. • Many of the DNA methylation changes occurred near nervous and immune system genes. • Genes involved in asthma, COPD, and IPF showed changes in DNA methylation. • Genomic locations with DNA methylation changes were enriched for bivalent markers. • FLOT2 showed reduced expression levels in exposed macaques. Wildfire smoke is responsible for around 20% of all particulate emissions in the U.S. and affects millions of people worldwide. Children are especially vulnerable, as ambient air pollution exposure during early childhood is associated with reduced lung function. Most studies, however, have focused on the short-term impacts of wildfire smoke exposures. We aimed to identify long-term baseline epigenetic changes associated with early-life exposure to wildfire smoke. We collected nasal epithelium samples for whole genome bisulfite sequencing (WGBS) from two groups of adult female rhesus macaques: one group born just before the 2008 California wildfire season and exposed to wildfire smoke during early-life (n = 8), and the other group born in 2009 with no wildfire smoke exposure during early-life (n = 14). RNA-sequencing was also performed on a subset of these samples. We identified 3370 d ifferentially m ethylated r egions (DMRs) (difference in methylation ≥ 5%, empirical p < 0.05) and 1 differentially expressed gene (FLOT2) (FDR < 0.05, fold of change ≥ 1.2). The DMRs were annotated to genes significantly enriched for synaptogenesis signaling, protein kinase A signaling, and a variety of immune processes, and some DMRs significantly correlated with gene expression differences. DMRs were also significantly enriched within regions of bivalent chromatin (top odds ratio = 1.46, q-value < 3 × 10-6) that often silence key developmental genes while keeping them poised for activation in pluripotent cells. These data suggest that early-life exposure to wildfire smoke leads to long-term changes in the methylome over genes impacting the nervous and immune systems. Follow-up studies will be required to test whether these changes influence transcription following an immune/respiratory challenge. [ABSTRACT FROM AUTHOR]

Abstract: As a part of the PM2.5 Technology Assessment and Characterization Study-New York (PMTACS-NY), concentrations of sulfate and 15 trace elements were determined in daily PM2.5 samples collected from July 2001 to September 2002 at a site in urban Queens, NY. The elements were Mg, Al, Ca, V, Cr, Mn, Fe, Co, Ni, Zn, As, Se, Cd, Sb, and Pb. Over the first 12 months these elemental concentrations were measured in both a water extract and in a total acid digestate so that the solubility of the aerosols bearing the above trace elements could be evaluated. This is important as elements with high solubility can be more readily bio-activated in the lungs and thus may be potentially more harmful to humans. An overview of the elemental composition of PM2.5 aerosols at the Queens, NY site over the 15-month period is presented. This includes a comparison of seasonal changes in aerosol composition and solubility at the sites along with an evaluation of the impacts on aerosol composition of the collapse of the World Trade Center Towers in Manhattan on 9/11/2001 and the smoke from Quebec wildfires in early July 2002. [Copyright &y& Elsevier]

Abstract: Special episodes of long-range transported particulate (PM) air pollution were investigated in a one-month field campaign at an urban background site in Helsinki, Finland. A total of nine size-segregated PM samplings of 3- or 4-day duration were made between August 23 and September 23, 2002. During this warm and unusually dry period there were two (labelled P2 and P5) sampling periods when the PM2.5 mass concentration increased remarkably. According to the hourly-measured PM data and backward air mass trajectories, P2 (Aug 23–26) represented a single, 64-h episode of long-range transported aerosol, whereas P5 (Sept 5–9) was a mixture of two 16- and 14-h episodes and usual seasonal air quality. The large chemical data set, based on analyses made by ion chromatography, inductively coupled plasma mass spectrometry, X-ray fluorescence analysis and smoke stain reflectometry, demonstrated that the PM2.5 mass concentrations of biomass signatures (i.e. levoglucosan, oxalate and potassium) and of some other compounds associated with biomass combustion (succinate and malonate) increased remarkably in P2. Crustal elements (Fe, Al, Ca and Si) and unidentified matter, presumably consisting to a large extent of organic material, were also increased in P2. The PM2.5 composition in P5 was different from that in P2, as the inorganic secondary aerosols (NO3 −, SO4 2−, NH4 +) and many metals reached their highest concentration in this period. The water-soluble fraction of potassium, lead and manganese increased in both P2 and P5. Mass size distributions (0.035–10 μm) showed that a large accumulation mode mainly caused the episodically increased PM2.5 concentrations. An interesting observation was that the episodes had no obvious impact on the Aitken mode. Finally, the strongly increased concentrations of biomass signatures in accumulation mode proved that the episode in P2 was due to long-range transported biomass combustion aerosol. [Copyright &y& Elsevier]

Americans spend most of their time indoors at home, but comprehensive characterization of in-home air pollution is limited by the cost and size of reference-quality monitors. We assembled small "Home Health Boxes" (HHBs) to measure indoor PM 2.5 , PM 10 , CO 2 , CO, NO 2 , and O 3 concentrations using filter samplers and low-cost sensors. Nine HHBs were collocated with reference monitors in the kitchen of an occupied home in Fort Collins, Colorado, USA for 168 h while wildfire smoke impacted local air quality. When HHB data were interpreted using gas sensor manufacturers' calibrations, HHBs and reference monitors (a) categorized the level of each gaseous pollutant similarly (as either low, elevated, or high relative to air quality standards) and (b) both indicated that gas cooking burners were the dominant source of CO and NO 2 pollution; however, HHB and reference O 3 data were not correlated. When HHB gas sensor data were interpreted using linear mixed calibration models derived via collocation with reference monitors, root-mean-square error decreased for CO 2 (from 408 to 58 ppm), CO (645 to 572 ppb), NO 2 (22 to 14 ppb), and O 3 (21 to 7 ppb); additionally, correlation between HHB and reference O 3 data improved (Pearson's r increased from 0.02 to 0.75). Mean 168-h PM 2.5 and PM 10 concentrations derived from nine filter samples were 19.4 μg m−3 (6.1% relative standard deviation [RSD]) and 40.1 μg m−3 (7.6% RSD). The 168-h PM 2.5 concentration was overestimated by PMS5003 sensors (median sensor/filter ratio = 1.7) and underestimated slightly by SPS30 sensors (median sensor/filter ratio = 0.91). [Display omitted] • We assembled a platform to sample/sense PM 2.5 , PM 10 , CO 2 , CO, NO 2 , and O 3 indoors. • Nine units were collocated with reference monitors in a home kitchen for one week. • We tested manufacturer and empirical linear calibrations for low-cost gas sensors. • Gas sensors correctly identified whether pollutants exceeded air quality guidelines. • Cooking with natural gas burners led to 1-h indoor NO 2 concentrations above 100 ppb. [ABSTRACT FROM AUTHOR]

By using ozonesonde measurements during July–August in 2016, 2019, and 2020 at Golmud and Qaidam, European Centre for Medium-Range Weather Forecasts (ECMWF) next-generation reanalysis ERA5 data, satellite-borne Moderate Resolution Imaging Spectrometer data products, and backward trajectory calculations from the chemical Lagrangian model of the stratosphere (CLaMS) model, this study analyzes vertical ozone distributions and explores the influence of deep stratospheric intrusions and wildfires on ozone variation in the northern Tibetan Plateau (TP) during the Asian summer monsoon period. Large ozone partial pressures were observed between 20 and 30 km, with a maximum of ~16 mPa at approximately 27 km latitude. The comparisons between the vertical ozone profiles with and without the occurrence of stratospheric intrusions showed that their relative ozone difference was up to 72.4% in the tropopause layer (15.8 km), and a secondary maximum of 66.7% existed in the middle troposphere (10.1 km). The stratospheric intrusions dried the atmosphere by 52.9% and enhanced the ozone columns by 26.1% below the upper troposphere and lower stratosphere. A case study of deep stratospheric intrusion exhibited the occurrence of large ozone partial pressure in the middle troposphere in detail, with an ozone peak of ~6 mPa at 10 km, which was caused by a tropopause fold associated with the westerly wind jet at the north flank of the Asian summer monsoon anticyclone. The stratospheric intrusion processes effectively transported the cold and dry air mass with high ozone in the stratosphere downward to the middle troposphere over the northern TP. This study also confirmed that by long-range transport processes, large wildfire smoke occurred around central and eastern Russia on 19–26 July 2016 greatly caused ozone pollution in the troposphere (6 km depth from the surface) over the northern TP. • Ozonesondes at Golmud in 2016, at Qaidam in 2019, and 2020 were analyzed. • A tropopause fold associated with the westerly wind jet caused an ozone peak of ~6 mPa at 10 km at Qaidam. • Wildfire smoke occurred around central Russia on 19–26 July 2016 caused ozone pollution in the troposphere -at Golmud. [ABSTRACT FROM AUTHOR]

• Prior studies of wildfire smoke have focused on acute cardiopulmonary health effects. • Novel analysis of wildfire season particulate matter and influenza occurrence months later. • Air pollution during wildfire seasons associated with influenza months later. • Air pollution during winter period not associated with influenza days later. Particularly in rural settings, there has been little research regarding the health impacts of fine particulate matter (PM 2.5) during the wildfire season smoke exposure period on respiratory diseases, such as influenza, and their associated outbreaks months later. We examined the delayed effects of PM 2.5 concentrations for the short-lag (1–4 weeks prior) and the long-lag (during the prior wildfire season months) on the following winter influenza season in Montana, a mountainous state in the western United States. We created gridded maps of surface PM 2.5 for the state of Montana from 2009 to 2018 using spatial regression models fit with station observations and Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol optical thickness data. We used a seasonal quasi-Poisson model with generalized estimating equations to estimate weekly, county-specific, influenza counts for Montana, associated with delayed PM 2.5 concentration periods (short-lag and long-lag effects), adjusted for temperature and seasonal trend. We did not detect an acute, short-lag PM 2.5 effect nor short-lag temperature effect on influenza in Montana. Higher daily average PM 2.5 concentrations during the wildfire season was positively associated with increased influenza in the following winter influenza season (expected 16% or 22% increase in influenza rate per 1 μg/m3 increase in average daily summer PM 2.5 based on two analyses, p = 0.04 or 0.008). This is one of the first observations of a relationship between PM 2.5 during wildfire season and influenza months later. [ABSTRACT FROM AUTHOR]