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

Seasons of smoke and fire: preparing health systems for improved performance before, during, and after wildfires

Increased frequency, intensity, and duration of wildfires are intensifying exposure to direct and smoke-related hazards in many areas, leading to evacuation and smoke-related effects on health and health systems that can affect regions extending over thousands of kilometres. Effective preparation and response are currently hampered by inadequate training, continued siloing of disciplines, insufficient finance, and inadequate coordination between health systems and governance at municipal, regional, national, and international levels. This Review highlights the key health and health systems considerations before, during, and after wildfires, and outlines how a health system should respond to optimise population health outcomes now and into the future. The focus is on the implications of wildfires for air quality, mental health, and emergency management, with elements of international policy and finance also addressed. We discuss commonalities of existing climate-resilient health care and disaster management frameworks and integrate them into an approach that addresses issues of financing, leadership and governance, health workforce, health information systems, infrastructure, supply chain, technologies, community interaction and health-care delivery, before, during, and after a wildfire season. This Review is a practical briefing for leaders and health professionals facing severe wildfire seasons and a call to break down silos and join with other disciplines to proactively plan for and fund innovation and coordination in service of a healthier future.

Respiratory Diseases Associated With Wildfire Exposure in Outdoor Workers

Wildfires, including forest fires, bushfires, and landscape fires, have become increasingly prevalent, fueled by climate change and environmental factors and posing significant challenges to both ecosystems and public health. This review article examines the relationship between wildfires and respiratory diseases in outdoor workers, with a main focus on airway disease. In addition to the expected effects of direct thermal respiratory injuries and possible carbon monoxide poisoning, there are associations between wildfires and upper and lower respiratory effects, including infections as well as exacerbations of asthma and chronic obstructive pulmonary disease. A few studies have also shown an increased risk of new-onset asthma among wildfire firefighters. Outdoor workers are likely to have greater exposure to wildfire smoke with associated increased risks of adverse effects. As wildfires become increasingly prevalent globally, it is crucial to understand the various dimensions of this association. Furthermore, this review addresses preventive measures and potential interventions to alleviate the airway burden on individuals during and after work with wildfires events.

A mouse model of wildfire smoke-induced health effects: sex differences in acute and sustained effects of inhalation exposures

Due to climate change, wildfires have increased in intensity and duration. While wildfires threaten lives directly, the smoke has more far-reaching adverse health impacts. During an extreme 2017 wildfire event, residents of Seeley Lake, Montana were exposed to unusually high levels of wood smoke (WS) causing sustained effects on lung function (decreased FEV1/FVC). Objective: The present study utilized an animal model of WS exposure to research cellular and molecular mechanisms of the resulting health effects. Methods: Mice were exposed to inhaled WS utilizing locally harvested wood to recapitulate community exposures. WS was generated at a rate resulting in a 5 mg/m3 PM2.5 exposure for five days. Results: This exposure resulted in a similar 0.28 mg/m2 particle deposition (lung surface area) in mice that was calculated for human exposure. As with the community observations, there was a significant effect on lung function, increased resistance, and decreased compliance, that was more pronounced in males at an extended (2 months) timepoint and males were more affected than females: ex vivo assays illustrated changes to alveolar macrophage functions (increased TNFα secretion and decreased efferocytosis). Female mice had significantly elevated IL-33 levels in lungs, however, pretreatment of male mice with IL-33 resulted in an abrogation of the observed WS effects, suggesting a dose-dependent role of IL-33. Additionally, there were greater immunotoxic effects in male mice. Discussion: These findings replicated the outcomes in humans and suggest that IL-33 is involved in a mechanism of the adverse effects of WS exposures that inform on potential sex differences.

Climate Change, Landscape Fires, and Human Health: A Global Perspective

Landscape fires are an integral component of the Earth system and a feature of prehistoric, subsistence, and industrial economies. Specific spatiotemporal patterns of landscape fire occur in different locations around the world, shaped by the interactions between environmental and human drivers of fire activity. Seven distinct types of landscape fire emerge from these interactions: remote area fires, wildfire disasters, savanna fires, Indigenous burning, prescribed burning, agricultural burning, and deforestation fires. All can have substantial impacts on human health and well-being directly and indirectly through (a) exposure to heat flux (e.g., injuries and destructive impacts), (b) emissions (e.g., smoke-related health impacts), and (c) altered ecosystem functioning (e.g., biodiversity, amenity, water quality, and climate impacts). Minimizing the adverse effects of landscape fires on population health requires understanding how human and environmental influences on fire impacts can be modified through interventions targeted at individual, community, and regional levels.

Seasonal extreme temperatures and short-term fine particulate matter increases pediatric respiratory healthcare encounters in a sparsely populated region of the intermountain western United States

BACKGROUND

Western Montana, USA, experiences complex air pollution patterns with predominant exposure sources from summer wildfire smoke and winter wood smoke. In addition, climate change related temperatures events are becoming more extreme and expected to contribute to increases in hospital admissions for a range of health outcomes. Evaluating while accounting for these exposures (air pollution and temperature) that often occur simultaneously and may act synergistically on health is becoming more important.

METHODS

We explored short-term exposure to air pollution on children's respiratory health outcomes and how extreme temperature or seasonal period modify the risk of air pollution-associated healthcare events. The main outcome measure included individual-based address located respiratory-related healthcare visits for three categories: asthma, lower respiratory tract infections (LRTI), and upper respiratory tract infections (URTI) across western Montana for ages 0-17 from 2017-2020. We used a time-stratified, case-crossover analysis with distributed lag models to identify sensitive exposure windows of fine particulate matter (PM2.5) lagged from 0 (same-day) to 14 prior-days modified by temperature or season.

RESULTS

For asthma, increases of 1 µg/m3 in PM2.5 exposure 7-13 days prior a healthcare visit date was associated with increased odds that were magnified during median to colder temperatures and winter periods. For LRTIs, 1 µg/m3 increases during 12 days of cumulative PM2.5 with peak exposure periods between 6-12 days before healthcare visit date was associated with elevated LRTI events, also heightened in median to colder temperatures but no seasonal effect was observed. For URTIs, 1 unit increases during 13 days of cumulative PM2.5 with peak exposure periods between 4-10 days prior event date was associated with greater risk for URTIs visits that were intensified during median to hotter temperatures and spring to summer periods.

CONCLUSIONS

Delayed, short-term exposure increases of PM2.5 were associated with elevated odds of all three pediatric respiratory healthcare visit categories in a sparsely population area of the inter-Rocky Mountains, USA. PM2.5 in colder temperatures tended to increase instances of asthma and LRTIs, while PM2.5 during hotter periods increased URTIs.

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.

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.

Causal effect of air pollution and meteorology on the COVID-19 pandemic: A convergent cross mapping approach

Environmental factors have been suspected to influence the propagation and lethality of COVID-19 in the global population. However, most of the studies have been limited to correlation analyses and did not use specific methods to address the dynamic of the causal relationship between the virus and its external drivers. This work focuses on inferring and understanding the causal effect of critical air pollutants and meteorological parameters on COVID-19 by using an Empirical Dynamic Modeling approach called Convergent Cross Mapping. This technique allowed us to identify the time-delayed causation and the sign of interactions. Considering its remarkable urban environment and mortality rate during the pandemic, Quito, Ecuador, was chosen as a case study. Our results show that both urban air pollution and meteorology have a causal impact on COVID-19. Even if the strength and the sign of the causality vary over time, a general trend can be drawn. NO2, SO2, CO and PM2.5 have a positive causation for COVID-19 infections (ρ > 0.35 and ∂ > 9.1). Contrary to current knowledge, this study shows a rapid effect of pollution on COVID-19 cases (1 < lag days <24) and a negative impact of O3 on COVID-19-related deaths (ρ = 0.53 and ∂ = -0.3). Regarding the meteorology, temperature (ρ = 0.24 and ∂ = -0.4) and wind speed (ρ = 0.34 and ∂ = -3.9) tend to mitigate the epidemiological consequences of SARS-CoV-2, whereas relative humidity seems to increase the excess deaths (ρ = 0.4 and ∂ = 0.05). A causal network is proposed to synthesize the interactions between the studied variables and to provide a simple model to support the management of coronavirus outbreaks.

Archetypal analysis of COVID-19 in Montana, USA, March 13, 2020 to April 26, 2022

Infectious disease data can often involve complex spatial patterns intermixed with temporal trends. Archetypal Analysis is a method to mine complex spatio-temporal data, and can be used to discover the dynamics of spatial patterns. The application of Archetypal Analysis to epidemiological data is relatively new, and here we present one of the first applications on COVID-19 data from March 13, 2020 to April 26, 2022, for the counties of Montana, USA. We present three views of the data set decomposed with Archetypal Analysis. First, we evaluate the entire 56 county data set. Second, we use a mutual information calculation to remove counties whose dynamics are mainly independent from the other counties, reducing the set to 17 counties. Finally, we analyze the top ten counties in terms of population size to focus on the dynamics in the large cities in the state. For each data set, we analyze four significant disease outbreaks across Montana. Archetypal Analysis uncovers distinct spatial patterns for each outbreak and demonstrates that each has a unique trajectory across the state.

Exogenous Chemicals Impact Virus Receptor Gene Transcription: Insights from Deep Learning

Despite the fact that coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has been disrupting human life and health worldwide since the outbreak in late 2019, the impact of exogenous substance exposure on the viral infection remains unclear. It is well-known that, during viral infection, organism receptors play a significant role in mediating the entry of viruses to enter host cells. A major receptor of SARS-CoV-2 is the angiotensin-converting enzyme 2 (ACE2). This study proposes a deep learning model based on the graph convolutional network (GCN) that enables, for the first time, the prediction of exogenous substances that affect the transcriptional expression of the ACE2 gene. It outperforms other machine learning models, achieving an area under receiver operating characteristic curve (AUROC) of 0.712 and 0.703 on the validation and internal test set, respectively. In addition, quantitative polymerase chain reaction (qPCR) experiments provided additional supporting evidence for indoor air pollutants identified by the GCN model. More broadly, the proposed methodology can be applied to predict the effect of environmental chemicals on the gene transcription of other virus receptors as well. In contrast to typical deep learning models that are of black box nature, we further highlight the interpretability of the proposed GCN model and how it facilitates deeper understanding of gene change at the structural level.

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.

Seasonal extreme temperatures and short-term fine particulate matter increases child respiratory hospitalizations in a sparsely populated region of the intermountain western United States

Background

Western Montana, USA, experiences complex air pollution patterns with predominant exposure sources from summer wildfire smoke and winter wood smoke. In addition, climate change related temperatures events are becoming more extreme and expected to contribute to increases in hospital admissions for a range of health outcomes. Few studies have evaluated these exposures (air pollution and temperature) that often occur simultaneously and may act synergistically on health.

Methods

We explored short-term exposure to air pollution on childhood respiratory health outcomes and how extreme temperature or seasonal period modify the risk of air pollution-associated hospitalizations. The main outcome measure included all respiratory-related hospital admissions for three categories: asthma, lower respiratory tract infections (LRTI), and upper respiratory tract infections (URTI) across western Montana for all individuals aged 0-17 from 2017-2020. We used a time-stratified, case-crossover analysis and distributed lag models to identify sensitive exposure windows of fine particulate matter (PM2.5) lagged from 0 (same-day) to 15 prior-days modified by temperature or season.

Results

Short-term exposure increases of 1 μg/m3 in PM2.5 were associated with elevated odds of all three respiratory hospital admission categories. PM2.5 was associated with the largest increased odds of hospitalizations for asthma at lag 7-13 days [1.87(1.17-2.97)], for LRTI at lag 6-12 days [2.18(1.20-3.97)], and for URTI at a cumulative lag of 13 days [1.29(1.07-1.57)]. The impact of PM2.5 varied by temperature and season for each respiratory outcome scenario. For asthma, PM2.5 was associated most strongly during colder temperatures [3.11(1.40-6.89)] and the winter season [3.26(1.07-9.95)]. Also in colder temperatures, PM2.5 was associated with increased odds of LRTI hospitalization [2.61(1.15-5.94)], but no seasonal effect was observed. Finally, 13 days of cumulative PM2.5 prior to admissions date was associated with the greatest increased odds of URTI hospitalization during summer days [3.35(1.85-6.04)] and hotter temperatures [1.71(1.31-2.22)].

Conclusions

Children's respiratory-related hospital admissions were associated with short-term exposure to PM2.5. PM2.5 associations with asthma and LRTI hospitalizations were strongest during cold periods, whereas associations with URTI were largest during hot periods.

Classification

environmental public health, fine particulate matter air pollution, respiratory infections.

Continent-based systematic review of the short-term health impacts of wildfire emissions

This review systematically gathers and provides an analysis of pollutants levels emitted from wildfire (WF) and their impact on short-term health effects of affected populations. The available literature was searched according to Population, Exposure, Comparator, Outcome, and Study design (PECOS) database defined by the World Health Organization (WHO) and a meta-analysis was conducted whenever possible. Data obtained through PECOS characterized information from the USA, Europe, Australia, and some Asian countries; South American countries were seldom characterized, and no data were available for Africa and Russia. Extremely high levels of pollutants, mostly of fine fraction of particulate matter (PM) and ozone, were associated with intense WF emissions in North America, Oceania, and Asia and reported to exceed several-fold the WHO guidelines. Adverse health outcomes include emergency department visits and hospital admissions for cardiorespiratory diseases as well as mortality. Despite the heterogeneity among exposure and health assessment methods, all-cause mortality, and specific-cause mortality were significantly associated with WF emissions in most of the reports. Globally, a significant association was found for all-cause respiratory outcomes including asthma, but mixed results were noted for cardiovascular-related effects. For the latter, estimates were only significant several days after WF emissions, suggesting a more delayed impact on the heart. Different research gaps are presented, including the need for the application of standardized protocols for assessment of both exposure and adverse health risks. Mitigation actions also need to be strengthened, including dedicated efforts to communicate with the affected populations, to engage them for adoption of protective behaviors and measures.

Risk of systemic fungal infections after exposure to wildfires: a population-based, retrospective study in California

BACKGROUND

Large-scale wildfires in California, USA, are increasing in both size and frequency, with substantial health consequences. The capacity for wildfire smoke to displace microbes and cause clinically significant fungal infections is poorly understood. We aimed to determine whether exposure to wildfire smoke was associated with an increased risk of hospital admissions for systemic fungal infections.

METHODS

In this population-based, retrospective study, we used hospital administrative data from 22 hospitals in California, USA, to analyse the association between wildfire smoke exposure and monthly hospital admissions for aspergillosis and coccidioidomycosis. We included hospitals that were members of the Vizient Clinical Data Base or Resource Manager during the study and excluded those that did not have complete reporting into Vizient during the study period. Smoke exposure was estimated using satellite-imaged smoke plumes in the hospital county. Incident rate ratios were calculated for all infection types 1 month and 3 months after smoke exposure.

FINDINGS

Between Oct 1, 2014, and May 31, 2018, there were a median of 1638 annual admissions per hospital in the study sample. Individual patient demographics were not collected. We did not observe an association between smoke exposure and rate of hospital admission for aspergillosis. However, hospital admission for coccidioidomycosis increased by 20% (95% CI 5-38) in the month following any smoke exposure. Hospital admission increased by 2% (0-4) for every day that there had been smoke exposure in the previous month, after adjustment for temperature and temporal trend. Similar results were obtained with smoke exposure data from the 3 months before admission.

INTERPRETATION

In the months following wildfire smoke exposure, California hospitals saw increased coccidioidomycosis infections. Given the projected increase in California wildfires and their expansion in endemic territories of soil-dwelling fungi, the ability for wildfire smoke to carry microbes and cause human disease warrants further research.

FUNDING

None.

Long-term impacts of non-occupational wildfire exposure on human health: A systematic review

The intensity and frequency of wildfires is increasing globally. The systematic review of the current evidence on long-term impacts of non-occupational wildfire exposure on human health has not been performed yet. To provide a systematic review and identify potential knowledge gaps in the current evidence of long-term impacts of non-occupational exposure to wildfire smoke and/or wildfire impacts on human health. We conducted a systematic search of the literature via MEDLINE, Embase and Scopus from the database inception to July 05, 2022. References from the included studies and relevant reviews were also considered. The Newcastle-Ottawa Scale (NOS) and a validated quality assessment framework were used to evaluate the quality of observational studies. Study results were synthesized descriptively. A total of 36 studies were included in our systematic review. Most studies were from developed countries (11 in Australia, 9 in Canada, 7 in the United States). Studies predominantly focused on mental health (21 studies, 58.33%), while evidence on long-term impacts of wildfire exposure on health outcomes other than mental health is limited. Current evidence indicated that long-term impacts of non-occupational wildfire exposure were associated with mortality (COVID-19 mortality, cardiovascular disease mortality and acute myocardial disease mortality), morbidity (mainly respiratory diseases), mental health disorders (mainly posttraumatic stress disorder), shorter height of children, reduced lung function and poorer general health status. However, no significant associations were observed for long-term impacts of wildfire exposure on child mortality and respiratory hospitalizations. The population-based high-quality evidence with quantitative analysis on this topic is still limited. Future well-designed studies considering extensive wildfire smoke air pollutants (e.g., particulate matter, ozone, nitrogen oxides) and estimating risk coefficient values for extensive health outcomes (e.g., mortality, morbidity) are warranted to fill current knowledge gaps.

The impact of fire-specific PM2.5 calibration on health effect analyses

The quantification of PM_2.5 concentrations solely stemming from both wildfire and prescribed burns (hereafter referred to as 'fire') is viable using the Community Multiscale Air Quality (CMAQ), although CMAQ outputs are subject to biases and uncertainties. To reduce the biases in CMAQ-based outputs, we propose a two-stage calibration strategy that improves the accuracy of CMAQ-based fire PM_2.5 estimates. First, we calibrated CMAQ-based non-fire PM_2.5 to ground PM_2.5 observations retrieved during non-fire days using an ensemble-based model. We estimated fire PM_2.5 concentrations in the second stage by multiplying the calibrated non-fire PM_2.5 obtained from the first stage by location- and time-specific conversion ratios. In a case study, we estimated fire PM_2.5 during the Washington 2016 fire season using the proposed calibration approach. The calibrated PM_2.5 better agreed with ground PM_2.5 observations with a 10-fold cross-validated (CV) R² of 0.79 compared to CMAQ-based PM_2.5 estimates with R² of 0.12. In the health effect analysis, we found significant associations between calibrated fire PM_2.5 and cardio-respiratory hospitalizations across the fire season: relative risk (RR) for cardiovascular disease = 1.074, 95% confidence interval (CI) = 1.021-1.130 in October; RR = 1.191, 95% CI = 1.099-1.291 in November; RR for respiratory disease = 1.078, 95% CI = 1.005-1.157 in October; RR = 1.153, 95% CI = 1.045-1.272 in November. However, the results were inconsistent when non-calibrated PM_2.5 was used in the analysis. We found that calibration affected health effect assessments in the present study, but further research is needed to confirm our findings.

The overlooked formation of environmentally persistent free radicals on particulate matter collected from biomass burning under light irradiation

BACKGROUND

The illumination process may be an important contributor to environmentally persistent free radicals (EPFRs) in atmospheric particles, but the ability of light to generate EPFRs in combustion products remains unclear.

OBJECTIVE

This paper studies the characteristics and formation mechanism of EPFRs in combustion particles after photoexcitation.

METHOD

The secondary photochemical processes and the generation and decay capability of EPFRs in size-resolved (<10 µm) biomass combustion particles were analysed by electron paramagnetic resonance (EPR) spectroscopy.

RESULT

Our results indicated that secondary EPFRs can be generated after illumination and the produced EPFRs have a lifetime of approximately 1 day. The content of secondary EPFRs after light exposure increased by 20 %-30 % compared to that of the original EPFRs. Through the analysis of components of different polarities, it was found that non-extractable substances were the main contributors to secondary EPFRs (75 %), followed by extractable organics. This study showed that metal species and quinones are important precursors for the formation of secondary EPFRs from non-extractable and extractable PM components, respectively. We found that O₂ molecules are an important factor for the formation of secondary EPFRs from organic substances without oxygen functional groups.

CONCLUSIONS

This study presents information about the effects of light and O₂ on the generation of EPFRs, and the unstable nature of secondary EPFRs has important implications for assessing the health risks of atmospheric particles.

Did unprecedented air pollution levels cause spike in Delhi's COVID cases during second wave?

The onset of the second wave of COVID-19 devastated many countries worldwide. Compared with the first wave, the second wave was more aggressive regarding infections and deaths. Numerous studies were conducted on the association of air pollutants and meteorological parameters during the first wave of COVID-19. However, little is known about their associations during the severe second wave of COVID-19. The present study is based on the air quality in Delhi during the second wave. Pollutant concentrations decreased during the lockdown period compared to pre-lockdown period (PM_2.5: 67 µg m^-3 (lockdown) versus 81 µg m^-3 (pre-lockdown); PM₁₀: 171 µg m^-3 versus 235 µg m^-3; CO: 0.9 mg m^-3 versus 1.1 mg m^-3) except ozone which increased during the lockdown period (57 µg m^-3 versus 39 µg m^-3). The variation in pollutant concentrations revealed that PM_2.5, PM₁₀ and CO were higher during the pre-COVID-19 period, followed by the second wave lockdown and the lowest in the first wave lockdown. These variations are corroborated by the spatiotemporal variability of the pollutants mapped using ArcGIS. During the lockdown period, the pollutants and meteorological variables explained 85% and 52% variability in COVID-19 confirmed cases and deaths (determined by General Linear Model). The results suggests that air pollution combined with meteorology acted as a driving force for the phenomenal growth of COVID-19 during the second wave. In addition to developing new drugs and vaccines, governments should focus on prediction models to better understand the effect of air pollution levels on COVID-19 cases. Policy and decision-makers can use the results from this study to implement the necessary guidelines for reducing air pollution. Also, the information presented here can help the public make informed decisions to improve the environment and human health significantly.

Association Between Air Pollution, Climate Change, and COVID-19 Pandemic: A Review of the Recent Scientific Evidence

Background: Recent studies indicated the possible relationship between climate change, environmental pollution, and Coronavirus Disease 2019 (COVID-19) pandemic. This study reviewed the effects of air pollution, climate parameters, and lockdown on the number of cases and deaths related to COVID-19. Methods: The present review was performed to determine the effects of weather and air pollution on the number of cases and deaths related to COVID-19 during the lockdown. Articles were collected by searching the existing online databases, such as PubMed, Science Direct, and Google Scholar, with no limitations on publication dates. Afterwards, this review focused on outdoor air pollution, including PM2.5, PM10, NO2, SO2, and O3, and weather conditions affecting severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)/COVID-19. Results: Most reviewed investigations in the present study showed that exposure to air pollutants, particularly PM2.5 and NO2, is positively related to COVID-19 patients and mortality. Moreover, these studies showed that air pollution could be essential in transmitting COVID-19. Local meteorology plays a vital role in coronavirus spread and mortality. Temperature and humidity variables are negatively correlated with virus transmission. The evidence demonstrated that air pollution could lead to COVID-19 transmission. These results support decision-makers in curbing potential new outbreaks. Conclusions: Overall, in environmental perspective-based COVID-19 studies, efforts should be accelerated regarding effective policies for reducing human emissions, bringing about air pollution and weather change. Therefore, using clean and renewable energy sources will increase public health and environmental quality by improving global air quality.

Interactions between climate and COVID-19

In this Personal View, we explain the ways that climatic risks affect the transmission, perception, response, and lived experience of COVID-19. First, temperature, wind, and humidity influence the transmission of COVID-19 in ways not fully understood, although non-climatic factors appear more important than climatic factors in explaining disease transmission. Second, climatic extremes coinciding with COVID-19 have affected disease exposure, increased susceptibility of people to COVID-19, compromised emergency responses, and reduced health system resilience to multiple stresses. Third, long-term climate change and prepandemic vulnerabilities have increased COVID-19 risk for some populations (eg, marginalised communities). The ways climate and COVID-19 interact vary considerably between and within populations and regions, and are affected by dynamic and complex interactions with underlying socioeconomic, political, demographic, and cultural conditions. These conditions can lead to vulnerability, resilience, transformation, or collapse of health systems, communities, and livelihoods throughout varying timescales. It is important that COVID-19 response and recovery measures consider climatic risks, particularly in locations that are susceptible to climate extremes, through integrated planning that includes public health, disaster preparedness, emergency management, sustainable development, and humanitarian response.

Daily 1 km terrain resolving maps of surface fine particulate matter for the western United States 2003-2021

We developed daily maps of surface fine particulate matter (PM2.5) for the western United States. We used geographically weighted regression fit to air quality station observations with Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol optical depth (AOD) data, and meteorological data to produce daily 1-kilometer resolution PM2.5 concentration estimates from 2003-2020. To account for impacts of stagnant air and inversions, we included estimates of inversion strength based on meteorological conditions, and inversion potential based on human activities and local topography. Model accuracy based on cross-validation was R2 = 0.66. AOD data improve the model in summer and fall during periods of high wildfire activity while the stagnation terms capture the spatial and temporal dynamics of PM2.5 in mountain valleys, particularly during winter. These data can be used to explore exposure and health outcome impacts of PM2.5 across spatiotemporal domains particularly in the intermountain western United States where measurements from monitoring station data are sparse. Furthermore, these data may facilitate analyses of inversion impacts and local topography on exposure and health outcome studies.

Impact of Wildfire Smoke Exposure on Health in Korea

PURPOSE

The characteristic topography and climate often affect the occurrence of large-scale wildfires in the Eastern Gangwon-do region of Korea. However, there are no studies on the health effects of these wildfires in Korea. This study aimed to analyze the differences in medical use between a wildfire-affected area and an adjacent non-affected area before and after a wildfire in 2019 in Gangwon-do, Korea.

MATERIALS AND METHODS

We used medical usage data from the Korean National Health Insurance Corporation. Rates of medical use were determined for citizens of a wildfire-affected area in the Eastern Yeongdong region and a non-affected area in the Western Yeongseo region. Logistic regression analysis was performed considering an increase in medical use per individual as a dependent variable; age, sex, income, smoking, drinking, and exercise were included as confounding variables.

RESULTS

The odds ratio for medical use in Yeongdong region increased significantly after 3 days, 3 months, and 1 year after a fire occurred, compared with Yeongseo region.

CONCLUSION

The results of this study confirmed that the use of medical care increased for residents of a wildfire-affected area, compared with those of an adjacent non-affected area. This is the first study on the relationship between wildfires and inpatient medical use in Korea.

Association between air pollution and COVID-19 disease severity via Bayesian multinomial logistic regression with partially missing outcomes

Recent ecological analyses suggest air pollution exposure may increase susceptibility to and severity of coronavirus disease 2019 (COVID-19). Individual-level studies are needed to clarify the relationship between air pollution exposure and COVID-19 outcomes. We conduct an individual-level analysis of long-term exposure to air pollution and weather on peak COVID-19 severity. We develop a Bayesian multinomial logistic regression model with a multiple imputation approach to impute partially missing health outcomes. Our approach is based on the stick-breaking representation of the multinomial distribution, which offers computational advantages, but presents challenges in interpreting regression coefficients. We propose a novel inferential approach to address these challenges. In a simulation study, we demonstrate our method's ability to impute missing outcome data and improve estimation of regression coefficients compared to a complete case analysis. In our analysis of 55,273 COVID-19 cases in Denver, Colorado, increased annual exposure to fine particulate matter in the year prior to the pandemic was associated with increased risk of severe COVID-19 outcomes. We also found COVID-19 disease severity to be associated with interactions between exposures. Our individual-level analysis fills a gap in the literature and helps to elucidate the association between long-term exposure to air pollution and COVID-19 outcomes.

Examining the status of forest fire emission in 2020 and its connection to COVID-19 incidents in West Coast regions of the United States

Forest fires impact on soil, water, and biota resources. The current forest fires in the West Coast of the United States (US) profoundly impacted the atmosphere and air quality across the ecosystems and have caused severe environmental and public health burdens. Forest fire led emissions could significantly exacerbate the air pollution level and, therefore, would play a critical role if the same occurs together with any epidemic and pandemic health crisis. Limited research is done so far to examine its impact in connection to the current pandemic. As of October 21, nearly 8.2 million acres of forest area were burned, with more than 25 casualties reported so far. In-situ air pollution data were utilized to examine the effects of the 2020 forest fire on atmosphere and coronavirus (COVID-19) casualties. The spatial-temporal concentrations of particulate matter (PM_2.5 and PM₁₀) and Nitrogen Dioxide (NO₂) were collected from August 1 to October 30 for 2020 (the fire year) and 2019 (the reference year). Both spatial (Multiscale Geographically Weighted Regression) and non-spatial (Negative Binomial Regression) analyses were performed to assess the adverse effects of fire emission on human health. The in-situ data-led measurements showed that the maximum increases in PM_2.5, PM₁₀, and NO₂ concentrations (μg/m³) were clustered in the West Coastal fire-prone states during August 1 - October 30, 2020. The average concentration (μg/m³) of particulate matter (PM_2.5 and PM₁₀) and NO₂ was increased in all the fire states severely affected by forest fires. The average PM_2.5 concentrations (μg/m³) over the period were recorded as 7.9, 6.3, 5.5, and 5.2 for California, Colorado, Oregon, and Washington in 2019, increasing up to 24.9, 13.4, 25.0, and 17.0 in 2020. Both spatial and non-spatial regression models exhibited a statistically significant association between fire emission and COVID-19 incidents. Such association has been demonstrated robust and stable by a total of 30 models developed for analyzing the spatial non-stationary and local association. More in-depth research is needed to better understand the complex relationship between forest fire emission and human health.

Effects of short-term ambient particulate matter exposure on the risk of severe COVID-19

OBJECTIVES

Previous studies have suggested a relationship between outdoor air pollution and the risk of coronavirus disease 2019 (COVID-19). However, there is a lack of data related to the severity of disease, especially in China. This study aimed to explore the association between short-term exposure to outdoor particulate matter (PM) and the risk of severe COVID-19.

METHODS

We recruited patients diagnosed with COVID-19 during a recent large-scale outbreak in eastern China caused by the Delta variant. We collected data on meteorological factors and ambient air pollution during the same time period and in the same region where the cases occurred and applied a generalized additive model (GAM) to analyze the effects of short-term ambient PM exposure on the risk of severe COVID-19.

RESULTS

A total of 476 adult patients with confirmed COVID-19 were recruited, of which 42 (8.82%) had severe disease. With a unit increase in PM₁₀, the risk of severe COVID-19 increased by 81.70% (95% confidence interval [CI]: 35.45, 143.76) at a lag of 0-7 days, 86.04% (95% CI: 38.71, 149.53) at a lag of 0-14 days, 76.26% (95% CI: 33.68, 132.42) at a lag of 0-21 days, and 72.15% (95% CI: 21.02, 144.88) at a lag of 0-28 days. The associations remained significant at lags of 0-7 days, 0-14 days, and 0-28 days in the multipollutant models. With a unit increase in PM_2.5, the risk of severe COVID-19 increased by 299.08% (95% CI: 92.94, 725.46) at a lag of 0-7 days, 289.23% (95% CI: 85.62, 716.20) at a lag of 0-14 days, 234.34% (95% CI: 63.81, 582.40) at a lag of 0-21 days, and 204.04% (95% CI: 39.28, 563.71) at a lag of 0-28 days. The associations were still significant at lags of 0-7 days, 0-14 days, and 0-28 days in the multipollutant models.

CONCLUSIONS

Our results indicated that short-term exposure to outdoor PM was positively related to the risk of severe COVID-19, and that reducing air pollution may contribute to the control of COVID-19.

Cows as canaries: The effects of ambient air pollution exposure on milk production and somatic cell count in dairy cows

Exposure to air pollution, including criteria pollutants such as fine particulate matter (PM_2.5) and ozone (O₃), has been associated with morbidity and mortality in mammals. As a genetically homogenous population that is closely monitored for health, dairy cattle present a unique opportunity to assess the association between changes in air pollution and mammalian health. Milk yield decreases in the summer if temperature and humidity, measured by the Temperature Humidity Index (THI). As O₃ levels increase with warmer temperatures, and summer PM_2.5 may increase with wildfire smoke, dairy cows may serve as a useful sentinel species to evaluate subacute markers of inflammation and metabolic output and ambient pollution. Over two years, we assessed summertime O₃ and PM_2.5 concentrations from local US EPA air quality monitors into an auto-regressive mixed model of the association between THI and daily milk production data and bulk tank somatic cell count (SCC). In unadjusted models, a 10 unit increase THI was associated with 28,700 cells/mL (95% CI: 17,700, 39,690) increase in SCC. After controlling for ambient air pollutants, THI was associated with a 14,500 SCC increase (95% CI: 3,400, 25,680), a 48% decrease in effect compared to the crude model. Further, in fully adjusted models, PM_2.5 was associated with a 105,500 cells/mL (95% CI: 90,030, 121,050) increase in SCC. Similar results were found for milk production. Results were amplified when high PM_2.5 days (95th percentile of observed values) associated with wildfire smoke were removed from the analyses. Our results support the hypothesis that PM_2.5 confounds the relationships between THI and milk yield and somatic cell count. The results of this study can be used to inform strategies for intervention to mitigate these impacts at the dairy level and potentially contribute to a model where production animals can act as air quality sentinels.

Climate change and global health: A call to more research and more action

There is increasing understanding, globally, that climate change and increased pollution will have a profound and mostly harmful effect on human health. This review brings together international experts to describe both the direct (such as heat waves) and indirect (such as vector-borne disease incidence) health impacts of climate change. These impacts vary depending on vulnerability (i.e., existing diseases) and the international, economic, political, and environmental context. This unique review also expands on these issues to address a third category of potential longer-term impacts on global health: famine, population dislocation, and environmental justice and education. This scholarly resource explores these issues fully, linking them to global health in urban and rural settings in developed and developing countries. The review finishes with a practical discussion of action that health professionals around the world in our field can yet take.

Understanding the distribution and drivers of PM2.5 concentrations in the Yangtze River Delta from 2015 to 2020 using Random Forest Regression

Understanding the drivers of PM_2.5 is critical for the establishment of PM_2.5 prediction models and the prevention and control of regional air pollution. In this study, the Yangtze River Delta is taken as the research object. Spatial cluster and outlier method was used to analyze the temporal and spatial distribution and variation of surface PM_2.5 in the Yangtze River Delta from 2015 to 2020, and Random Forest was utilized to analyze the drivers of PM_2.5 in this area. The results indicated that (1) based on the spatial cluster distribution of PM_2.5, the northwest and north of Yangtze River Delta region were mostly highly concentrated and surrounded by high concentrations of PM_2.5, while lowly concentrated and surrounded by low concentrations areas were distributed in the southern; (2) the relationship between PM_2.5 concentrations and drivers in the Yangtze River Delta was modeled well and the explanatory rate of drivers to PM_2.5 were more than 0.9; (3) temperature, precipitation, and wind speed were the main driving forces of PM_2.5 emission in the Yangtze River Delta. It should be noted that the repercussion of wildfire on PM_2.5 was gradually prominent. When formulating air pollution control measures, the local government normally considers the impact of weather and traffic conditions. In order to reduce PM_2.5 pollution caused by biomass combustion, the influence of wildfire should also be taken into account, especially in the fire season. Meanwhile, high leaf area was conducive to improving air quality, and the increasing green area will help reduce air pollutants.

Inherent heterogeneity of influenza A virus stability following aerosolization

Efficient human-to-human transmission represents a necessary adaptation for a zoonotic influenza A virus (IAV) to cause a pandemic. As such, many emerging IAVs are characterized for transmissibility phenotypes in mammalian models, with an emphasis on elucidating viral determinants of transmission and the role host immune responses contribute to mammalian adaptation. Investigations of virus infectivity and stability in aerosols concurrent with transmission assessments have increased in recent years, enhancing our understanding of this dynamic process. Here, we employ a diverse panel of 17 human and zoonotic IAVs, inclusive of seasonally circulating H1N1 and H3N2 viruses, and avian and swine viruses associated with human infection, to evaluate differences in spray factor (a value that assesses efficiency of the aerosolization process), stability, and infectivity following aerosolization. While most seasonal influenza viruses did not exhibit substantial variability within these parameters, there was more heterogeneity among zoonotic influenza viruses, which possess a diverse range of transmission phenotypes. Aging of aerosols at different relative humidities identified strain-specific levels of stability with different profiles identified between zoonotic H3, H5, and H7 subtype viruses associated with human infection. As studies continue to elucidate the complex components governing virus transmissibility, notably aerosol matrices and environmental parameters, considering the relative role of subtype- and strain-specific factors to modulate these parameters will improve our understanding of the pandemic potential of zoonotic influenza A viruses. Importance Transmission of respiratory pathogens through the air can facilitate the rapid and expansive spread of infection and disease through a susceptible population. While seasonal influenza viruses are quite capable of airborne spread, there is a lack of knowledge regarding how well influenza viruses remain viable after aerosolization, and if influenza viruses capable of jumping species barriers to cause human infection differ in this property from seasonal strains. We evaluated a diverse panel of influenza viruses associated with human infection (originating from human, avian, and swine reservoirs) for their ability to remain viable after aerosolization in the laboratory under a range of conditions. We found greater diversity among avian and swine-origin viruses compared with seasonal influenza viruses; strain-specific stability was also noted. Although influenza virus stability in aerosols is an underreported property, if molecular markers associated with enhanced stability are identified, we will be able to quickly recognize emerging strains of influenza that present the greatest pandemic threat.

COVID-19 and Air Pollution: A Spatial Analysis of Particulate Matter Concentration and Pandemic-Associated Mortality in the US

In 2019, a novel coronavirus, SARS-CoV-2, was first reported in Wuhan, China. The virus causes the disease commonly known as COVID-19, and, since its emergence, it has infected over 252 million individuals globally and taken the lives of over 5 million in the same time span. Primary research on SARS-CoV-2 and COVID-19 focused on understanding the biomolecular composition of the virus. This research has led to the development of multiple vaccines with great efficacy and antiviral treatments for the disease. The development of biomedical interventions has been crucial to combating this pandemic; additionally, environmental confounding variables that could have exacerbated the pandemic need further assessment. In this research study, we conducted a spatial analysis of particulate matter (PM) concentration and its association with COVID-19 mortality in the United States. Results of this study demonstrate a significant positive correlation between PM concentration levels and COVID-19 mortality; however, this does not necessarily imply a causal relationship. These results are consistent with similar studies in Italy and China, where significant COVID-19 cases and corresponding deaths were exhibited. Furthermore, maps of the data demonstrate clustering of COVID-19 mortality which suggest further investigation into the social determinants of health impacting the pandemic.

Assessing the impact of air pollution and climate seasonality on COVID-19 multiwaves in Madrid, Spain

While the COVID-19 pandemic is still in progress, being under the fifth COVID-19 wave in Madrid, over more than one year, Spain experienced a four wave pattern. The transmission of SARS-CoV-2 pathogens in Madrid metropolitan region was investigated from an urban context associated with seasonal variability of climate and air pollution drivers. Based on descriptive statistics and regression methods of in-situ and geospatial daily time series data, this study provides a comparative analysis between COVID-19 waves incidence and mortality cases in Madrid under different air quality and climate conditions. During analyzed period 1 January 2020-1 July 2021, for each of the four COVID-19 waves in Madrid were recorded anomalous anticyclonic synoptic meteorological patterns in the mid-troposphere and favorable stability conditions for COVID-19 disease fast spreading. As airborne microbial temporal pattern is most affected by seasonal changes, this paper found: 1) a significant negative correlation of air temperature, Planetary Boundary Layer height, and surface solar irradiance with daily new COVID-19 incidence and deaths; 2) a similar mutual seasonality with climate variables of the first and the fourth COVID-waves from spring seasons of 2020 and 2021 years. Such information may help the health decision makers and public plan for the future.

Exposure to PM2.5 and PM10 and COVID-19 Infection Rates and Mortality: a one-year observational study in Poland

Background

Atmospheric contamination, especially particulate matter (PM), can be associated viral infections connected with respiratory failure. Literature data indicates that intensity of SARS-CoV-2 infections worldwide can be associated with PM pollution levels.

Objectives

The aim of the study was to examine the relationship between atmospheric contamination, measured as PM2.5 and PM10 levels, and the number of COVID-19 cases and related deaths in Poland in a one-year observation study.

Methods

Number and geographical distribution of COVID-19 incidents and related deaths, as well as PM2.5 and PM10 exposure levels in Poland were obtained from publicly accessible databases. Average monthly values of these parameters for individual provinces were calculated. Multiple regression analysis was performed for the period between March 2020 and February 2021, taking into account average monthly exposure to PM2.5 and PM10, monthly COVID-19 incidence and mortality rates per 100,000 inhabitants and the population density across Polish provinces.

Results

Only December 2020 the number of new infections was significantly related to the three analyzed factors: PM2.5, population density and the number of laboratory COVID-19 tests (R² = 0.882). For COVID-19 mortality, a model with all three significant factors: PM10, population density and number of tests was obtained as significant only in November 2020 (R² = 0.468).

Conclusion

The distribution of COVID-19 incidents across Poland was independent from annual levels of particulate matter concentration in provinces. Exposure to PM2.5 and PM10 was associated with COVID-19 incidence and mortality in different provinces only in certain months. Other cofactors such as population density and the number of performed COVID-19 tests also corresponded with both COVID-19-related infections and deaths only in certain months. Particulate matter should not be treated as the sole determinant of the spread and severity of the COVID-19 pandemic but its importance in the incidence of infectious diseases should not be forgotten.

Impact of exposure to smoke from biomass burning in the Amazon rain forest on human health

This review study aimed to determine the relationship between exposure to smoke from biomass burning in the Amazon rain forest and its implications on human health in that region in Brazil. A nonsystematic review was carried out by searching PubMed, Google Scholar, SciELO, and EMBASE databases for articles published between 2005 and 2021, either in Portuguese or in English, using the search terms "biomass burning" OR "Amazon" OR "burned" AND "human health." The review showed that the negative health effects of exposure to smoke from biomass burning in the Amazon have been poorly studied in that region. There is an urgent need to identify effective public health interventions that can help improve the behavior of vulnerable populations exposed to smoke from biomass burning, reducing morbidity and mortality related to that exposure.

Physical and Mental Health Effects of Bushfire and Smoke in the Australian Capital Territory 2019-20

The 2019-20 bushfire season in south-eastern Australia was one of the most severe in recorded history. Bushfire smoke-related air pollution reached hazardous levels in major metropolitan areas, including the Australian Capital Territory (ACT), for prolonged periods of time. Bushfire smoke directly challenges human health through effects on respiratory and cardiac function, but can also indirectly affect health, wellbeing and quality of life. Few studies have examined the specific health effects of bushfire smoke, separate from direct effects of fire, and looked beyond physical health symptoms to consider effects on mental health and lifestyle in Australian communities. This paper describes an assessment of the health impacts of this prolonged exposure to hazardous levels of bushfire smoke in the ACT and surrounding area during the 2019-20 bushfire season. An online survey captured information on demographics, health (physical and mental health, sleep) and medical advice seeking from 2,084 adult participants (40% male, median age 45 years). Almost all participants (97%) experienced at least one physical health symptom that they attributed to smoke, most commonly eye or throat irritation, and cough. Over half of responders self-reported symptoms of anxiety and/or feeling depressed and approximately half reported poorer sleep. Women reported all symptoms more frequently than men. Participants with existing medical conditions or poorer self-rated health, parents and those directly affected by fire (in either the current or previous fire seasons) also experienced poorer physical, mental health and/or sleep symptoms. Approximately 17% of people sought advice from a medical health practitioner, most commonly a general practitioner, to manage their symptoms. This study demonstrated that prolonged exposure to bushfire smoke can have substantial effects on health. Holistic approaches to understanding, preventing and mitigating the effects of smoke, not just on physical health but on mental health, and the intersection of these, is important. Improved public health messaging is needed to address uncertainty about how individuals can protect their and their families health for future events. This should be informed by identifying subgroups of the population, such as those with existing health conditions, parents, or those directly exposed to fire who may be at a greater risk.

Protecting Children from Wildfire Smoke

The impacts of wildfires on the health of children are becoming a more urgent matter as wildfires become more frequent, intense and affecting, not only forested areas, but also urban locations. It is important that medical professionals be prepared to provide information to patients and families on how to minimize the adverse health effects on children of wildfire smoke and ash from wildfires.

Exploring the linkage between seasonality of environmental factors and COVID-19 waves in Madrid, Spain

Like several countries, Spain experienced a multi wave pattern of COVID-19 pandemic over more than one year period, between spring 2020 and spring 2021. The transmission of SARS-CoV-2 pandemics is a multi-factorial process involving among other factors outdoor environmental variables and viral inactivation.This study aims to quantify the impact of climate and air pollution factors seasonality on incidence and severity of COVID-19 disease waves in Madrid metropolitan region in Spain. We employed descriptive statistics and Spearman rank correlation tests for analysis of daily in-situ and geospatial time-series of air quality and climate data to investigate the associations with COVID-19 incidence and lethality in Madrid under different synoptic meteorological patterns. During the analyzed period (1 January 2020-28 February 2021), with one month before each of three COVID-19 waves were recorded anomalous anticyclonic circulations in the mid-troposphere, with positive anomalies of geopotential heights at 500 mb and favorable stability conditions for SARS-CoV-2 fast diffusion. In addition, the results reveal that air temperature, Planetary Boundary Layer height, ground level ozone have a significant negative relationship with daily new COVID-19 confirmed cases and deaths. The findings of this study provide useful information to the public health authorities and policymakers for optimizing interventions during pandemics.

Long-Term Exposure to PM2.5, Facemask Mandates, Stay Home Orders and COVID-19 Incidence in the United States

Long-term PM_2.5 exposure might predispose populations to SARS-CoV-2 infection and intervention policies might interrupt SARS-CoV-2 transmission and reduce the risk of COVID-19. We conducted an ecologic study across the United States, using county-level COVID-19 incidence up to 12 September 2020, to represent the first two surges in the U.S., annual average of PM_2.5 between 2000 and 2016 and state-level facemask mandates and stay home orders. We fit negative binomial models to assess COVID-19 incidence in association with PM_2.5 and policies. Stratified analyses by facemask policy and stay home policy were also performed. Each 1-µg/m³ increase in annual average concentration of PM_2.5 exposure was associated with 7.56% (95% CI: 3.76%, 11.49%) increase in COVID-19 risk. Facemask mandates and stay home policies were inversely associated with COVID-19 with adjusted RRs of 0.8466 (95% CI: 0.7598, 0.9432) and 0.9193 (95% CI: 0.8021, 1.0537), respectively. The associations between PM_2.5 and COVID-19 were consistent among counties with or without preventive policies. Our study added evidence that long-term PM_2.5 exposure increased the risk of COVID-19 during each surge and cumulatively as of 12 September 2020, in the United States. Although both state-level implementation of facemask mandates and stay home orders were effective in preventing the spread of COVID-19, no clear effect modification was observed regarding long-term exposure to PM_2.5 on the risk of COVID-19.

Travelling to polluted cities: a systematic review on the harm of air pollution on international travellers' health

RATIONALE FOR REVIEW

In 2019, approximately, 1.4 billion people travelled internationally. Many individuals travel to megacities where air pollution concentrations can vary significantly. Short-term exposure to air pollutants can cause morbidity and mortality related to cardiovascular and respiratory disease, with the literature clearly reporting a strong association between short-term exposure to particulate matter ≤2.5 μm and ozone with adverse health outcomes in resident populations. However, limited research has been conducted on the health impacts of short-term exposure to air pollution in individuals who travel internationally. The objective of this systematic review was to review the evidence for the respiratory and cardiovascular health impacts from exposure to air pollution during international travel to polluted cities in adults aged ≥18 years old.

KEY FINDINGS

We searched PubMed, Scopus and EMBASE for studies related to air pollution and the health impacts on international travellers. Of the initially identified 115 articles that fit the search criteria, 6 articles were selected for the final review. All six studies found indications of adverse health impacts of air pollution exposure on international travellers, with most of the changes being reversible upon return to their home country/city. However, none of these studies contained large populations nor investigated vulnerable populations, such as children, elderly or those with pre-existing conditions.

CONCLUSIONS

More research is warranted to clearly understand the impacts of air pollution related changes on travellers' health, especially on vulnerable groups who may be at higher risk of adverse impacts during travel to polluted cities.

Spatiotemporal variability of COVID-19 pandemic in relation to air pollution, climate and socioeconomic factors in Pakistan

Information on the spatiotemporal variability of respirable suspended particulate pollutant matter concentrations, especially of particles having size of 2.5 μm and climate are the important factors in relation to emerging COVID-19 cases around the world. This study aims at examining the association between COVID-19 cases, air pollution, climatic and socioeconomic factors using geospatial techniques in three provincial capital cities and the federal capital city of Pakistan. A series of relevant data was acquired from 3 out of 4 provinces of Pakistan (Punjab, Sindh, Khyber Pakhtunkhwa (KPK) including the daily numbers of COVID-19 cases, PM2.5 concentration (μgm-3), a climatic factors including temperature (°F), wind speed (m/s), humidity (%), dew point (%), and pressure (Hg) from June 1 2020, to July 31 2020. Further, the possible relationships between population density and COVID-19 cases was determined. The generalized linear model (GLM) was employed to quantify the effect of PM2.5, temperature, dew point, humidity, wind speed, and pressure range on the daily COVID-19 cases. The grey relational analysis (GRA) was also implemented to examine the changes in COVID-19 cases with PM2.5 concentrations for the provincial city Lahore. About 1,92, 819 COVID-19 cases were reported in Punjab, Sindh, KPK, and Islamabad during the study period. Results indicated a significant relationship between COVID-19 cases and PM2.5 and climatic factors at p < 0.05 except for Lahore in case of humidity (r = 0.175). However, mixed correlations existed across Lahore, Karachi, Peshawar, and Islamabad. The R2 value indicates a moderate relationship between COVID-19 and population density. Findings of this study, although are preliminary, offers the first line of evidence for epidemiologists and may assist the local community to expedient for the growth of effective COVID-19 infection and health risk management guidelines. This remains to be seen.

Health Impact Assessment of the 2020 Washington State Wildfire Smoke Episode: Excess Health Burden Attributable to Increased PM2.5 Exposures and Potential Exposure Reductions

Major wildfires starting in the summer of 2020 along the west coast of the United States made PM2.5 concentrations in this region rank among the highest in the world. Washington was impacted both by active wildfires in the state and aged wood smoke transported from fires in Oregon and California. This study aims to estimate the magnitude and disproportionate spatial impacts of increased PM2.5 concentrations attributable to these wildfires on population health. Daily PM2.5 concentrations for each county before and during the 2020 Washington wildfire episode (September 7-19) were obtained from regulatory air monitors. Utilizing previously established concentration-response function (CRF) of PM2.5 (CRF of total PM2.5) and odds ratio (OR) of wildfire smoke days (OR of wildfire smoke days) for mortality, we estimated excess mortality attributable to the increased PM2.5 concentrations in Washington. On average, daily PM2.5 concentrations increased 97.1 μg/m3 during the wildfire smoke episode. With CRF of total PM2.5, the 13-day exposure to wildfire smoke was estimated to lead to 92.2 (95% CI: 0.0, 178.7) more all-cause mortality cases; with OR of wildfire smoke days, 38.4 (95% CI: 0.0, 93.3) increased all-cause mortality cases and 15.1 (95% CI: 0.0, 27.9) increased respiratory mortality cases were attributable to the wildfire smoke episode. The potential impact of avoiding elevated PM2.5 exposures during wildfire events significantly reduced the mortality burden. Because wildfire smoke episodes are likely to impact the Pacific Northwest in future years, continued preparedness and mitigations to reduce exposures to wildfire smoke are necessary to avoid excess health burden.

Association of environmental and meteorological factors on the spread of COVID-19 in Victoria, Mexico, and air quality during the lockdown

This study aims to analyze the correlation between environmental factors and confirmed cases of COVID-19 pandemic in Victoria, Mexico. The analysis is performed at the micro-level, filtering only confirmed cases of COVID-19 that are located near air quality monitoring stations, within an approximate coverage of 2.5 km, in order to identify a possible specific association between PM_2.5, PM₁₀, carbon monoxide (CO), relative humidity, temperature, absolute humidity, and total confirmed cases of COVID-19. The results evidenced that the cases of COVID-19 were very strongly associated with CO concentration. Our results also suggested that particulate matter pollution (PM_2.5 and PM₁₀) exposure have a significant correlation for confirmed cases of COVID-19. Furthermore, we studied the changes in air quality during the COVID-19 outbreak by comparing the average concentration of the four weeks before lockdown (February 16 to March 14, 2020) and the following twelve weeks during the partial lockdown (March 15 to June 06, 2020), revealing a very significant decrease of pollutants.

Wildfire Smoke Is Associated With an Increased Risk of Cardiorespiratory Emergency Department Visits in Alaska

Alaskan wildfires have major ecological, social, and economic consequences, but associated health impacts remain unexplored. We estimated cardiorespiratory morbidity associated with wildfire smoke (WFS) fine particulate matter with a diameter less than 2.5 μm (PM2.5) in three major population centers (Anchorage, Fairbanks, and the Matanuska-Susitna Valley) during the 2015-2019 wildfire seasons. To estimate WFS PM2.5, we utilized data from ground-based monitors and satellite-based smoke plume estimates. We implemented time-stratified case-crossover analyses with single and distributed lag models to estimate the effect of WFS PM2.5 on cardiorespiratory emergency department (ED) visits. On the day of exposure to WFS PM2.5, there was an increased odds of asthma-related ED visits among 15-65 year olds (OR = 1.12, 95% CI = 1.08, 1.16), people >65 years (OR = 1.15, 95% CI = 1.01, 1.31), among Alaska Native people (OR = 1.16, 95% CI = 1.09, 1.23), and in Anchorage (OR = 1.10, 95% CI = 1.05, 1.15) and Fairbanks (OR = 1.12, 95% CI = 1.07, 1.17). There was an increased risk of heart failure related ED visits for Alaska Native people (Lag Day 5 OR = 1.13, 95% CI = 1.02, 1.25). We found evidence that rural populations may delay seeking care. As the frequency and magnitude of Alaskan wildfires continue to increase due to climate change, understanding the health impacts will be imperative. A nuanced understanding of the effects of WFS on specific demographic and geographic groups facilitates data-driven public health interventions and fire management protocols that address these adverse health effects.

Wildland firefighter exposure to smoke and COVID-19: A new risk on the fire line

Throughout the United States, wildland firefighters respond to wildfires, performing arduous work in remote locations. Wildfire incidents can be an ideal environment for the transmission of infectious diseases, particularly for wildland firefighters who congregate in work and living settings. In this review, we examine how exposure to wildfire smoke can contribute to an increased likelihood of SARS-CoV-2 infection and severity of coronavirus disease (COVID-19). Human exposure to particulate matter (PM), a component of wildfire smoke, has been associated with oxidative stress and inflammatory responses; increasing the likelihood for adverse respiratory symptomology and pathology. In multiple epidemiological studies, wildfire smoke exposure has been associated with acute lower respiratory infections, such as bronchitis and pneumonia. Co-occurrence of SARS-CoV-2 infection and wildfire smoke inhalation may present an increased risk for COVID-19 illness in wildland firefighters due to PM based transport of SARS CoV-2 virus and up-regulation of angiotensin-converting enzyme II (ACE-2) (i.e. ACE-2 functions as a trans-membrane receptor, allowing the SARS-CoV-2 virus to gain entry into the epithelial cell). Wildfire smoke exposure may also increase risk for more severe COVID-19 illness such as cytokine release syndrome, hypotension, and acute respiratory distress syndrome (ARDS). Current infection control measures, including social distancing, wearing cloth masks, frequent cleaning and disinfecting of surfaces, frequent hand washing, and daily screening for COVID-19 symptoms are very important measures to reduce infections and severe health outcomes. Exposure to wildfire smoke may introduce additive or even multiplicative risk for SARS-CoV-2 infection and severity of disease in wildland firefighters. Thus, additional mitigative measures may be needed to prevent the co-occurrence of wildfire smoke exposure and SARS-CoV-2 infection.

Impacts of nationwide lockdown due to COVID-19 outbreak on air quality in Bangladesh: a spatiotemporal analysis

In Bangladesh, a nationwide lockdown was imposed on 26 March 2020, due to the COVID-19 pandemic. Due to restricted emissions, it was hypothesized that the air quality has been improved during lockdown throughout the country. The study is intended to assess the impact of nationwide lockdown measures on air quality in Bangladesh. We analyzed satellite data for four different air pollutants (NO₂, SO₂, CO, and O₃) to assess the changes in the atmospheric concentrations of pollutants in major cities as well as across the country. In this study, the concentrations of NO₂, SO₂, CO, and O₃ from 1 February to 30 May of the year 2019 and 2020 were analyzed. The average SO₂ and NO₂ concentrations were decreased by 43 and 40%, respectively, while tropospheric O₃ were found to be increased with a maximum of > 7%. Among the major cities, Dhaka, Gazipur, Chattogram, and Narayanganj were found to be more influenced by the restricted emissions. In Dhaka, NO₂ and SO₂ concentrations were decreased approximately by 69 and 67%, respectively. Our analysis reveals that NO₂ concentrations are highly correlated with the regional COVID-19 cases (r = 0.74). The study concludes that the lockdown measures significantly reduced air pollution because of reduced vehicular and industrial emissions in Bangladesh.

How Do Brazilian Fires Affect Air Pollution and Public Health?

Fires burning across the Amazon in the summer of 2019 attracted global attention for the widespread destruction of natural ecosystems and regional smoke production. Using a combination of satellite fire observations and atmospheric modeling, Nawaz and Henze (2020, https://doi.org.10.1029/2020GH000268) provide new evidence for the widespread regional public health consequences attributed to these fires. They find that approximately 10% of premature deaths in Brazil due to fine particulate matter (PM2.5) are attributable to smoke pollution and highlight how fire locations play a critical role in determining downwind health impacts.

The Effects of Air Pollution on COVID-19 Infection and Mortality-A Review on Recent Evidence

The outbreak of COVID-19 has created a serious public health concern worldwide. Although, most of the regions around the globe have been affected by COVID-19 infections; some regions are more badly affected in terms of infections and fatality rates than others. The exact reasons for such variations are not clear yet. This review discussed the possible effects of air pollution on COVID-19 infections and mortality based on some recent evidence. The findings of most studies reviewed here demonstrate that both short-term and long-term exposure to air pollution especially PM2.5 and nitrogen dioxide (NO2) may contribute significantly to higher rates of COVID-19 infections and mortalities with a lesser extent also PM10. A significant correlation has been found between air pollution and COVID-19 infections and mortality in some countries in the world. The available data also indicate that exposure to air pollution may influence COVID-19 transmission. Moreover, exposure to air pollution may increase vulnerability and have harmful effects on the prognosis of patients affected by COVID-19 infections. Further research should be conducted considering some potential confounders such as age and pre-existing medical conditions along with exposure to NO2, PM2.5 and other air pollutants to confirm their detrimental effects on mortalities from COVID-19.