Landscape fire smoke enhances the association between fine particulate matter exposure and acute respiratory infection among children under 5 years of age: Findings of a case-crossover study for 48 low- and middle-income countries.

BACKGROUND: Fine particulate matter (PM2.5) produced by landscape fires is thought to be more toxic than that from non-fire sources. However, the effects of "fire-sourced" PM2.5 on acute respiratory infection (ARI) are unknown. METHODS: We combined Demographic and Health Survey (DHS) data from 48 countries with gridded global estimates of PM2.5 concentrations from 2003 to 2014. The proportions of fire-sourced PM2.5 were assessed by a chemical transport model using a variety of PM2.5 source data. We tested for associations between ARI and short-term exposure to fire- and "non-fire-sourced" PM2.5 using a bidirectional case-crossover analysis. The robustness and homogeneity of the associations were examined by sensitivity analyses. We also established a nonlinear exposure-response relationship between fire- and non-fire-sourced PM2.5 and ARI using a two-dimensional spline function. RESULTS: The study included 36,432 children under 5 years who reported ARI symptoms. Each 1 µg/m3 increment of fire-sourced PM2.5 was associated with a 3.2 % (95 % confidence interval [CI] 0.2, 6.2) increment in the risk of ARI. This effect was comparable to that of each ∼5 µg/m3 increment in PM2.5 from non-fire sources (3.1 %; 95 % CI 2.4, 3.7). The association between ARI and total PM2.5 concentration was significantly mediated by the proportion of fire-sourced particles. Nonlinear analysis showed that the risk of ARI was increased by both fire- and non-fire-sourced PM2.5, but especially by the former. CONCLUSIONS: PM2.5 produced by landscape fire was more strongly associated to ARI among children under 5 years than that from non-fire sources.

Systematic Mapping and Review of Landscape Fire Smoke (LFS) Exposure Impacts on Insects.

Landscape fire activity is changing in many regions because of climate change. Smoke emissions from landscape fires contain many harmful air pollutants, and beyond the potential hazard posed to human health, these also have ecological impacts. Insects play essential roles in most ecosystems worldwide, and some work suggests they may also be sensitive to smoke exposure. There is therefore a need for a comprehensive review of smoke impacts on insects. We systematically reviewed the scientific literature from 1930 to 2022 to synthesize the current state of knowledge of the impacts of smoke exposure from landscape fires on the development, behavior, and mortality of insects. We found: (1) 42 relevant studies that met our criteria, with 29% focused on the United States of America and 19% on Canada; (2) of these, 40 insect species were discussed, all of which were sensitive to smoke pollution; (3) most of the existing research focuses on how insect behavior responds to landscape fire smoke (LFS); (4) species react differently to smoke exposure, with for example some species being attracted to the smoke (e.g., some beetles) while others are repelled (e.g., some bees). This review consolidates the current state of knowledge on how smoke impacts insects and highlights areas that may need further investigation. This is particularly relevant since smoke impacts on insect communities will likely worsen in some areas due to increasing levels of biomass burning resulting from the joint pressures of climate change, land use change, and more intense land management involving fire.

Associations between exposure to landscape fire smoke and child mortality in low-income and middle-income countries: a matched case-control study.

BACKGROUND: The prevalence of landscape fires has increased, particularly in low-income and middle-income countries (LMICs). We aimed to assess the impact of exposure to landscape fire smoke (LFS) on the health of children. METHODS: We conducted a sibling-matched case-control study and selected 552 155 children (aged <18 years) from Demographic and Health Surveys in 55 LMICs from 2000 to 2014. Each deceased child was matched with their sibling(s). The exposure indicators were fire-sourced PM2·5 and dry-matter emissions. We associated these exposure indicators with child mortality using conditional regressions, and derived an exposure-response function using a non-linear model. Based on the association, we quantified the global burden of fire-attributable child deaths in LMICs from 2000 to 2014. FINDINGS: Each 1 µg/m3 increment of fire-sourced PM2·5 was associated with a 2·31% (95% CI 1·50-3·13) increased risk of child mortality. The association was robust to different models. The exposure-response function was superlinear and suggested per-unit exposure to larger fires was more toxic. Based on our non-linear exposure-response function, we estimated that between 2000 and 2014, the five countries with the largest number of child deaths associated with fire-sourced PM2·5 were Nigeria (164 000 [126 000 to 209 000] annual deaths), Democratic Republic of the Congo (126 000 [95% CI 114 000 to 139 000] annual deaths), India (65 900 [-22 200 to 147 000] annual deaths), Uganda (30 200 [24 500 to 36 300] annual deaths), and Indonesia (28 900 [19 100 to 38 400]). INTERPRETATION: Exposure to landscape fire smoke contributes substantially to the global burden of child mortality. FUNDING: National Natural Science Foundation of China, Ministry of Science and Technology of China, Peking University, UK National Institute for Health Research Health Protection Research Unit, Leverhulme Center for Wildfires, Environment and Society, and National Environment Research Council National Capability funding to National Centre for Earth Observation and Energy Foundation.

Sensors for Fire and Smoke Monitoring.

Mastery of fire is intimately linked to advances in human civilization, culture and technology [...].

Top-Down Estimation of Particulate Matter Emissions from Extreme Tropical Peatland Fires Using Geostationary Satellite Fire Radiative Power Observations.

Extreme fires in the peatlands of South East (SE) Asia are arguably the world's greatest biomass burning events, resulting in some of the worst ambient air pollution ever recorded (PM10 > 3000 µg·m-3). The worst of these fires coincide with El Niño related droughts, and include huge areas of smouldering combustion that can persist for months. However, areas of flaming surface vegetation combustion atop peat are also seen, and we show that the largest of these latter fires appear to be the most radiant and intensely smoke-emitting areas of combustion present in such extreme fire episodes. Fire emissions inventories and early warning of the air quality impacts of landscape fire are increasingly based on the fire radiative power (FRP) approach to fire emissions estimation, including for these SE Asia peatland fires. "Top-down" methods estimate total particulate matter emissions directly from FRP observations using so-called "smoke emission coefficients" [Ce; g·MJ-1], but currently no discrimination is made between fire types during such calculations. We show that for a subset of some of the most thermally radiant peatland fires seen during the 2015 El Niño, the most appropriate Ce is around a factor of three lower than currently assumed (~16.8 ± 1.6 g·MJ-1 vs. 52.4 g·MJ-1). Analysis indicates that this difference stems from these highly radiant fires containing areas of substantial flaming combustion, which changes the amount of particulate matter emitted per unit of observable fire radiative heat release in comparison to more smouldering dominated events. We also show that even a single one of these most radiant fires is responsible for almost 10% of the overall particulate matter released during the 2015 fire event, highlighting the importance of this fire type to overall emission totals. Discriminating these different fires types in ways demonstrated herein should thus ultimately improve the accuracy of SE Asian fire emissions estimates derived using the FRP approach, and the air quality modelling which they support.

Development of the User Requirements for the Canadian WildFireSat Satellite Mission.

In 2019 the Canadian Space Agency initiated development of a dedicated wildfire monitoring satellite (WildFireSat) mission. The intent of this mission is to support operational wildfire management, smoke and air quality forecasting, and wildfire carbon emissions reporting. In order to deliver the mission objectives, it was necessary to identify the technical and operational challenges which have prevented broad exploitation of Earth Observation (EO) in Canadian wildfire management and to address these challenges in the mission design. In this study we emphasize the first objective by documenting the results of wildfire management end-user engagement activities which were used to identify the key Fire Management Functionalities (FMFs) required for an Earth Observation wildfire monitoring system. These FMFs are then used to define the User Requirements for the Canadian Wildland Fire Monitoring System (CWFMS) which are refined here for the WildFireSat mission. The User Requirements are divided into Observational, Measurement, and Precision requirements and form the foundation for the design of the WildFireSat mission (currently in Phase-A, summer 2020).

Connecting Earth observation to high-throughput biodiversity data.

Understandably, given the fast pace of biodiversity loss, there is much interest in using Earth observation technology to track biodiversity, ecosystem functions and ecosystem services. However, because most biodiversity is invisible to Earth observation, indicators based on Earth observation could be misleading and reduce the effectiveness of nature conservation and even unintentionally decrease conservation effort. We describe an approach that combines automated recording devices, high-throughput DNA sequencing and modern ecological modelling to extract much more of the information available in Earth observation data. This approach is achievable now, offering efficient and near-real-time monitoring of management impacts on biodiversity and its functions and services.

An Overview of the Use of the SimSphere Soil Vegetation Atmosphere Transfer (SVAT) Model for the Study of Land-Atmosphere Interactions.

Soil Vegetation Atmosphere Transfer (SVAT) models consist of deterministic mathematical representations of the physical processes involved between the land surface and the atmosphere and of their interactions, at time-steps acceptable for the study of land surface processes. The present article provides a comprehensive and systematic review of one such SVAT model suitable for use in mesoscale or boundary layer studies, originally developed by [1]. This model, which has evolved significantly both architecturally and functionally since its foundation, has been widely applied in over thirty interdisciplinary science investigations, and it is currently used as a learning resource for students in a number of educational institutes globally. The present review is also regarded as very timely, since a variation of a method using this specific SVAT model along with satellite observations is currently being considered in a scheme being developed for the operational retrieval of soil surface moisture by the US National Polar-orbiting Operational Environmental Satellite System (NPOESS), in a series of satellites that are due to be launched from 2016 onwards.