A cost-benefit analysis of WildFireSat, a wildfire monitoring satellite mission for Canada.

In anticipation of growing wildfire management challenges, the Canadian government is investing in WildFireSat, an Earth observation satellite mission designed to collect data in support of Canadian wildfire management. Although costs of the mission can be reasonably estimated, the benefits of such an investment are unknown. Here we forecast the possible benefits of WildFireSat via an avoided cost approach. We consider five socio-economic components: suppression costs (fixed and variable), timber losses, property, asset and infrastructure losses, evacuation costs, and smoke related health costs. Using a Monte Carlo analysis, we evaluated a range of possible changes to these components based on expert opinions. The resulting Net Present Value (NPV) estimates depend on the presumed impact of using WildFireSat decision support data products, with pessimistic and conservative assumptions generating mission costs that typically exceed potential benefits by 1.16 to 1.59 times, while more optimistic assumptions generate benefits in excess of costs by 8.72 to 10.48 times. The analysis here excludes some possibly significant market and non-market impacts expected from WildFireSat due to data limitations; accounting for these additional impacts would likely generate positive NPVs under even cautious impact assumptions.

Integrating meteorological and geospatial data for forest fire risk assessment.

Understanding the factors that cause fire is crucial for minimizing the fire risk. In this research, a comprehensive approach was adopted to recognize factors influencing forest fires. Golestan National Park (GNP) was considered as a representative area with a humid climate in this study. Initially, using the Multi-Criteria Evaluation Method, a fire risk map was created by analyzing natural and human factors, and vulnerable areas were identified. Then, the relationship between key elements such as meteorological conditions, Land Surface Temperature (LST), and precipitation, with the occurrence of fire in different years was investigated. CHIRPS and Landsat data were utilized to assess LST changes and precipitation. 23-year changes in fire occurrence areas in GNP were acquired using MODIS products. The results of the data analysis showed that the highest number of fires occurred in forest areas, and in the fire risk prediction map, the extremely high-risk class is completely consistent with the ground truth data. The assigned weights, derived from expert opinions, highlight the substantial significance of elevation, and distance from roads and settlements. Additionally, the effectiveness of the model in providing reliable forecasts for fire risks in GNP is highlighted by the ROC curve with an AUC value of 0.83. Forest fires within GNP exhibit a distinct seasonality, predominantly occurring from July to December. During the warmer months, by coinciding with summer excursions, human activities may contribute to the ignition of fires. In 2013 and 2014, rising fire incidents correlated with elevated temperatures, hinting at a potential connection. GNP fires showed an upward trend with higher monthly LST and a downward trend with increased annual precipitation. The results showed that there is a relationship between LST, precipitation, and the occurrence of fire in GNP. Approximately 176.15 ha of GNP's forest areas have been destroyed by fires over the last two decades. This research demonstrated that there is a dynamic interaction between environmental conditions and fire incidents. By considering these factors, managers and environmental planners can develop effective strategies for managing and preventing forest fire risks.

Evidence of increasing wildfire damage with decreasing property price in Southern California fires.

Across the Western United States, human development into the wildland urban interface (WUI) is contributing to increasing wildfire damage. Given that natural disasters often cause greater harm within socio-economically vulnerable groups, research is needed to explore the potential for disproportionate impacts associated with wildfire. Using Zillow Transaction and Assessment Database (ZTRAX), hereafter "Zillow", real estate data, we explored whether lower-priced structures were more likely to be damaged during the most destructive, recent wildfires in Southern California. Within fire perimeters occurring from 2000-2019, we matched property price data to burned and unburned structures. To be included in the final dataset, fire perimeters had to surround at least 25 burned and 25 unburned structures and have been sold at most seven years before the fire; five fires fit these criteria. We found evidence to support our hypothesis that lower-priced properties were more likely to be damaged, however, the likelihood of damage and the influence of property value significantly varied across individual fire perimeters. When considering fires individually, properties within two 2003 fires-the Cedar and Grand Prix-Old Fires-had statistically significantly decreasing burn damage with increasing property value. Occurring in 2007 and later, the other three fires (Witch-Poomacha, Thomas, and Woolsey) showed no significant relationship between price and damage. Consistent with other studies, topographic position, slope, elevation, and vegetation were also significantly associated with the likelihood of a structure being damaged during the wildfire. Driving time to the nearest fire station and previously identified fire hazard were also significant. Our results suggest that further studies on the extent and reason for disproportionate impacts of wildfire are needed. In the meantime, decision makers should consider allocating wildfire risk mitigation resources-such as fire-fighting and wildfire structural preparedness resources-to more socioeconomically vulnerable neighborhoods.

Forest fire susceptibility assessment under small sample scenario: A semi-supervised learning approach using transductive support vector machine.

Forest fires threaten global ecosystems, socio-economic structures, and public safety. Accurately assessing forest fire susceptibility is critical for effective environmental management. Supervised learning methods dominate this assessment, relying on a substantial dataset of forest fire occurrences for model training. However, obtaining precise forest fire location data remains challenging. To address this issue, semi-supervised learning emerges as a viable solution, leveraging both a limited set of collected samples and unlabeled data containing environmental factors for training. Our study employed the transductive support vector machine (TSVM), a key semi-supervised learning method, to assess forest fire susceptibility in scenarios with limited samples. We conducted a comparative analysis, evaluating its performance against widely used supervised learning methods. The assessment area for forest fire susceptibility lies in Dayu County, Jiangxi Province, China, renowned for its vast forest cover and frequent fire incidents. We analyzed and generated maps depicting forest fire susceptibility, evaluating prediction accuracies for both supervised and semi-supervised learning methods across various small sample scenarios (e.g., 4, 8, 12, 16, 20, 24, 28, and 32 samples). Our findings indicate that TSVM exhibits superior prediction accuracy compared to supervised learning with limited samples, yielding more plausible forest fire susceptibility maps. For instance, at sample sizes of 4, 16, and 28, TSVM achieves prediction accuracies of approximately 0.8037, 0.9257, and 0.9583, respectively. In contrast, random forests, the top performers in supervised learning, demonstrate accuracies of approximately 0.7424, 0.8916, and 0.9431, respectively, for the same small sample sizes. Additionally, we discussed three key aspects: TSVM parameter configuration, the impact of unlabeled sample size, and performance within typical sample sizes. Our findings support semi-supervised learning as a promising approach compared to supervised learning for forest fire susceptibility assessment and mapping, particularly in scenarios with small sample sizes.

Assessment of exposures to firefighters from wildfires in heavily contaminated areas of the Chornobyl Exclusion Zone.

The aim of this study was to assess the exposures received by firefighters engaged in extinguishing the large-scale wildfires in the most contaminated areas of the Ukrainian part of the Chornobyl Exclusion Zone in 2016 and 2020. The assessments are based on measurements of radionuclide airborne concentrations in the breathing zones of workers and at the aerosol sampling stations of the automated radiation monitoring system operated by SSE Ecocenter. During the wildfires, the radionuclide airborne concentrations increased by orders of magnitude compared to the background levels, reaching maximum values in the firefighting area of 1.20 ± 0.01 Bq m-3 for 90Sr, 0.18 ± 0.01 Bq m-3 for 137Cs, (1.8 ± 0.3) ∙10-4 Bq m-3 for 238Pu, (4.5 ± 0.7) ∙10-4 Bq m-3 for 239-240Pu, and (8.0 ± 1.3) ∙10-3 Bq m-3 for 241Pu. The internal effective doses to firefighters due to inhaled radionuclides did not exceed 2 µSv h-1 and were 3-5 times lower compared to the external dose of gamma radiation. Thus, the time of firefighting in the ChEZ will be limited by the external dose.

[Fire resistance of 15 main economic tree species in Liangshan Prefecture, Sichuan, China.] / 凉山州15ç§ä¸»è¦ç»æµŽæ ‘ç§çš„é˜²ç«æ€§èƒ½.

Liangshan Prefecture is one of the three major forest areas in Sichuan Province and one of the three major disaster areas of forest fire. We measured the physicochemical properties and combustion performances of different organs (leaves and branches) of 15 main economic tree species in Liangshan, and analyzed the bioecology characteristics, silviculture characteristics and value characteristics of different tree species. We investigated the fire resistance of different tree species to screen out fire-resistant species suitable for economic forest development in Liangshan Prefecture, and improve the biological fire prevention ability. The seven physicochemical properties and combustion performances indices of 15 tree species showed significant differences. Except for crude ash and lignin, the weights of moisture content, caloric value, ignition point, crude fat, and crude fibre of leaves were higher than those of branches. Crude fibre index of leaves (9.6%) and the crude ash index of branches (9.9%) were the highest weight indices of the two organs, respectively. Based on the fire resistance, we divided all the species into three classes, i.e., class Ⅰ (excellent fire-resistance trees) Juglans regia and Morus alba; class Ⅱ (better fire-resistant trees) Sapium sebiferum, Mangifera indica, Phyllanthus emblica, Eriobotrya japonica, Ligustrum lucidum, Castanea mollissima, and Punica granatum; class Ⅲ (poor fire-resistant trees) Pinus armandii, Illicium simonsii, Morella rubra, Sapindus mukorossi, Olea europaea and Camellia oleifera. J. regia and M. alba had fireproof solid performance and could be used as the preferred species for fireproof economic forest in Liangshan region. It was suggested that to use class Ⅰ to Ⅱ fire-resistant tree species built the main fireproof isolated forest belt, and pay attention to fire prevention after planting class Ⅲ tree species in a large area.

Assessing the 2023 Canadian wildfire smoke impact in Northeastern US: Air quality, exposure and environmental justice.

The Canadian wildfires in June 2023 significantly impacted the northeastern United States, particularly in terms of worsened air pollution and environmental justice concerns. While advancements have been made in low-cost sensor deployments and satellite observations of atmospheric composition, integrating dynamic human mobility with wildfire PM2.5 exposure to fully understand the environmental justice implications remains underinvestigated. This study aims to enhance the accuracy of estimating ground-level fine particulate matter (PM2.5) concentrations by fusing chemical transport model outputs with empirical observations, estimating exposures using human mobility data, and evaluating the impact of environmental justice. Employing a novel data fusion technique, the study combines the Weather Research and Forecasting model with Chemistry (WRF-Chem) outputs and surface PM2.5 measurements, providing a more accurate estimation of PM2.5 distribution. The study addresses the gap in traditional exposure assessments by incorporating human mobility data and further investigates the spatial correlation of PM2.5 levels with various environmental and demographic factors from the US Environmental Protection Agency (EPA) Environmental Justice Screening and Mapping Tool (EJScreen). Results reveal that despite reduced mobility during high PM2.5 levels from wildfire smoke, exposure for both residents and individuals on the move remains high. Regions already burdened with high environmental pollution levels face amplified PM2.5 effects from wildfire smoke. Furthermore, we observed mixed correlations between PM2.5 concentrations and various demographic and socioeconomic factors, indicating complex exposure patterns across communities. Urban areas, in particular, experience persistent high exposure, while significant correlations in rural areas with EJScreen factors highlight the unique vulnerabilities of these populations to smoke exposure. These results advocate for a comprehensive approach to environmental health that leverages advanced models, integrates human mobility data, and addresses socio-demographic disparities, contributing to the development of equitable strategies against the growing threat of wildfires.

The City of Penticton's comprehensive approach to wildfire risk reduction.

From 2017 to 2023, British Columbians experienced four record-breaking wildfire seasons, resulting in reduced air quality, mass evacuations and the destruction of homes, properties and livelihoods. Wildfire risk reduction is vital to breaking the sequence of disaster that has befallen such communities as Kelowna, BC in 2003, Ft. McMurray, AB in 2016, and Lytton, BC in 2021. As the City of Penticton ('the City') is located in a wildfire-prone environment, its Fire Department, FireSmart Team and Emergency Program have worked closely together to facilitate a proactive and comprehensive approach towards reducing the impacts of wildfire on Penticton's neighbourhoods, businesses and residents through a variety of wildfire mitigation initiatives. This paper discusses the City's efforts to achieve a holistic wildfire risk management plan through alignment with the seven disciplines of FireSmart and the four pillars of emergency management, namely: the use of education; land use planning and development considerations; vegetation management; emergency planning; and cross training and interagency cooperation. The paper describes the challenges the City has faced, as well its successes, and provides recommendations to help other local authorities reduce the risk of wildfire in their communities.

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.

Multiple social and environmental factors affect wildland fire response of full or less-than-full suppression.

Wildland fire incident commanders make wildfire response decisions within an increasingly complex socio-environmental context. Threats to human safety and property, along with public pressures and agency cultures, often lead commanders to emphasize full suppression. However, commanders may use less-than-full suppression to enhance responder safety, reduce firefighting costs, and encourage beneficial effects of fire. This study asks: what management, socioeconomic, environmental, and fire behavior characteristics are associated with full suppression and the less-than-full suppression methods of point-zone protection, confinement/containment, and maintain/monitor? We analyzed incident report data from 374 wildfires in the United States northern Rocky Mountains between 2008 and 2013. Regression models showed that full suppression was most strongly associated with higher housing density and earlier dates in the calendar year, along with non-federal land jurisdiction, regional and national incident management teams, human-caused ignitions, low fire-growth potential, and greater fire size. Interviews with commanders provided decision-making context for these regression results. Future efforts to encourage less-than-full suppression should address the complex management context, in addition to the biophysical context, of fire response.

High-Efficiency Particulate Air Filters for Preventing Wildfire-related Asthma Complications: A Cost-Effectiveness Study.

Rationale: Air pollution caused by wildfire smoke is linked to adverse health outcomes, especially for people living with asthma. Objectives: To evaluate whether government rebates for high-efficiency particulate air (HEPA) filters, which reduce concentrations of smoke particles indoors, are cost effective in managing asthma and preventing exacerbations in British Columbia (BC), Canada. Methods: We used a Markov model to analyze health states for asthma control, exacerbation severity, and death over a retrospective time horizon of 5 years (2018-2022). Concentrations of wildfire smoke-derived particulate matter with an aerodynamic diameter ⩽2.5 µm (PM2.5) from the Canadian Optimized Statistical Smoke Exposure Model and relevant literature informed the model. The base-case analysis assumed continuous use of a HEPA filter. Costs and quality-adjusted life-years (QALYs) resulting from varying rebates were computed for each Health Service Delivery Area (HSDA). Measurements and Main Results: In the base-case analysis, HEPA filter use resulted in increased costs of $83.34 (SE, $1.03) and increased QALYs of 0.0011 (SE, 0.0001) per person. The average incremental cost-effectiveness ratio among BC HSDAs was $74,652/QALY (SE, $3,517), with incremental cost-effectiveness ratios ranging from $40,509 to $89,206 per QALY in HSDAs. Across the province, the intervention was projected to prevent 4,418 exacerbations requiring systemic corticosteroids, 643 emergency department visits, and 425 hospitalizations during the 5-year time horizon. A full rebate was cost effective in 1 of the 16 HSDAs across BC. The probability of cost-effectiveness ranged from 0.1% to 74.8% across HSDAs. A $100 rebate was cost effective in most HSDAs. Conclusions: The cost-effectiveness of HEPA filters in managing wildfire smoke-related asthma issues in BC varies by region. Government rebates up to two-thirds of the filter cost are generally cost effective, with a full rebate being cost effective only in Kootenay Boundary.

Increasing multi-hazard climate risk and financial and health impacts on northern homeowners.

Currently, more than half of the world's human population lives in urban areas, which are increasingly affected by climate hazards. Little is known about how multi-hazard environments affect people, especially those living in urban areas in northern latitudes. This study surveyed homeowners in Anchorage and Fairbanks, USA, Alaska's largest urban centers, to measure individual risk perceptions, mitigation response, and damages related to wildfire, surface ice hazards, and permafrost thaw. Up to one third of residents reported being affected by all three hazards, with surface ice hazards being the most widely distributed, related to an estimated $25 million in annual damages. Behavioral risk response, policy recommendations for rapidly changing urban environments, and the challenges to local governments in mitigation efforts are discussed.

Bridging scales for landscape-level wildfire adaptation: A case study of the Kittitas Fire Adapted Communities Coalition.

Federal-level strategies or guidance for addressing wildfire risk encourage adaptation activities that span progressively larger scales, often focusing on landscape-level action that necessitates coordination between decision-makers and socially diverse communities. Collaborative organizations are increasingly explored as one approach for coordinating local efforts that address wildfire risk and adaptation, offering a platform for scaling and adjusting federal and state guidance that align with the needs of local landscapes. We conducted semi-structured interviews with members and supporters of the Kittitas Fire Adapted Communities Coalition (KFACC) and later facilitated two workshops at the behest of the organization. The goal of our interviews and workshops were to better understand how organizations such as KFACC emerge, function, and evolve in complex social and ecological landscapes, with a focus on their role in addressing landscape-level wildfire adaptation. We use an existing theoretical analogy of fire adaptation that crosses institutional and physical scales to help conceive of lessons from in-depth analysis of KFACC functioning. We found that KFACC originated from a need to establish a shared local mission for fire adaptation and a recognition that federal and state initiatives surrounding wildfire management needed further contextualization to be effective among diverse local social conditions. Later organizational foci included identifying key audiences for targeted adaptation efforts, including the identification of key messages and communities where specific mitigation actions might be needed. KFACC members were effective in strategically advocating for fire adaptation resources and policies at broader scales that might increase adaptation within Kittitas County, including caveats to local planning efforts designed for wildfire risk reduction. Likewise, the organization had begun to focus on tailoring mitigation efforts to different communities in the landscape as an effective means of catalyzing sustained, realistic fire adaptation actions. We suggest that organizations like KFACC are well-positioned to act as "board hoppers" who can integrate community-based needs into wildfire management, but caution that the functioning and 'niche' of such organizations may require strategic development or regular reflection on organizational goals.

School and childcare facility air quality decision-makers' perspectives on using low-cost sensors for wildfire smoke response.

BACKGROUND: During wildfire smoke episodes, school and childcare facility staff and those who support them rely upon air quality data to inform activity decisions. Where ambient regulatory monitor data is sparse, low-cost sensors can help inform local outdoor activity decisions, and provide indoor air quality data. However, there is no established protocol for air quality decision-makers to use sensor data for schools and childcare facilities. To develop practical, effective toolkits to guide the use of sensors in school and childcare settings, it is essential to understand the perspectives of the potential end-users of such toolkit materials. METHODS: We conducted 15 semi-structured interviews with school, childcare, local health jurisdiction, air quality, and school district personnel regarding sensor use for wildfire smoke response. Interviews included sharing PM2.5 data collected at schools during wildfire smoke. Interviews were transcribed and transcripts were coded using a codebook developed both a priori and amended as additional themes emerged. RESULTS: Three major themes were identified by organizing complementary codes together: (1) Low-cost sensors are useful despite data quality limitations, (2) Low-cost sensor data can inform decision-making to protect children in school and childcare settings, and (3) There are feasibility and public perception-related barriers to using low-cost sensors. CONCLUSIONS: Interview responses provided practical implications for toolkit development, including demonstrating a need for toolkits that allow a variety of sensor preferences. In addition, participants expected to have a wide range of available time for monitoring, budget for sensors, and decision-making types. Finally, interview responses revealed a need for toolkits to address sensor uses outside of activity decisions, especially assessment of ventilation and filtration.

Trends and patterns of polycyclic aromatic hydrocarbons (PAHs) in forest fire-affected soils and water mediums with implications on human health risk assessment.

Forest fires are extreme natural/artificial events releasing polycyclic aromatic hydrocarbons (PAHs), which are carcinogenic. Most of the released PAHs are trapped in burnt ash, a part of which is transported and settle on different mediums like soil and water. After strong rainfall events, PAHs enter into surface water bodies through surface runoff, thereby deteriorating water quality. Changes in PAHs levels during the post-fire duration and human health risks due to PAHs released from forest fires need attention. This study aim to explain the trends and patterns of PAHs and health risks due to exposure to soil and water contaminated with PAHs. Forest fires release a higher percentage of low molecular weight PAHs (LMW PAHs) than high molecular weight PAHs (HMW PAHs). Ash and burnt soils contain a higher percentage of LMW PAHs since biomass burning releases huge amounts of LMW PAHs. Whereas, sediments contain a higher percentage of HMW PAHs since most of the LMW PAHs are already degraded. HMW PAHs were causing higher risk to humans (both cancer and non-cancer) due to their higher oxidation potential. Exposure to water contaminated by PAHs resulted in higher health risks for both BaP equivalent and a mixture of PAHs. Exposure to sediment produced the highest health risk due to a higher percentage of HMW PAHs, followed by surface water, burnt soil, ash, and unburnt soil. Cancer and non-cancer risk due to dermal exposure was more elevated than oral exposure. The mixture of PAHs in sediment produced a higher average dermal risk for children (2.21E+00 for cancer and 7.69E+03 for non-cancer risk) and oral cancer risk for adults (7.11E-03). However, exposure to BaP equivalent in sediment produced higher oral non-cancer risk (7.01E+02) for children. Thus, effective PAHs monitoring is required in both soil and surface water mediums for ensuring proper treatment in water supply systems.

Asthma and landscape fire smoke: A Thoracic Society of Australia and New Zealand position statement.

Landscape fires are increasing in frequency and severity globally. In Australia, extreme bushfires cause a large and increasing health and socioeconomic burden for communities and governments. People with asthma are particularly vulnerable to the effects of landscape fire smoke (LFS) exposure. Here, we present a position statement from the Thoracic Society of Australia and New Zealand. Within this statement we provide a review of the impact of LFS on adults and children with asthma, highlighting the greater impact of LFS on vulnerable groups, particularly older people, pregnant women and Aboriginal and Torres Strait Islander peoples. We also highlight the development of asthma on the background of risk factors (smoking, occupation and atopy). Within this document we present advice for asthma management, smoke mitigation strategies and access to air quality information, that should be implemented during periods of LFS. We promote clinician awareness, and the implementation of public health messaging and preparation, especially for people with asthma.

Global population exposure to landscape fire air pollution from 2000 to 2019.

Wildfires are thought to be increasing in severity and frequency as a result of climate change1-5. Air pollution from landscape fires can negatively affect human health4-6, but human exposure to landscape fire-sourced (LFS) air pollution has not been well characterized at the global scale7-23. Here, we estimate global daily LFS outdoor fine particulate matter (PM2.5) and surface ozone concentrations at 0.25° × 0.25° resolution during the period 2000-2019 with the help of machine learning and chemical transport models. We found that overall population-weighted average LFS PM2.5 and ozone concentrations were 2.5 µg m-3 (6.1% of all-source PM2.5) and 3.2 µg m-3 (3.6% of all-source ozone), respectively, in 2010-2019, with a slight increase for PM2.5, but not for ozone, compared with 2000-2009. Central Africa, Southeast Asia, South America and Siberia experienced the highest LFS PM2.5 and ozone concentrations. The concentrations of LFS PM2.5 and ozone were about four times higher in low-income countries than in high-income countries. During the period 2010-2019, 2.18 billion people were exposed to at least 1 day of substantial LFS air pollution per year, with each person in the world having, on average, 9.9 days of exposure per year. These two metrics increased by 6.8% and 2.1%, respectively, compared with 2000-2009. Overall, we find that the global population is increasingly exposed to LFS air pollution, with socioeconomic disparities.