Population exposure to hazardous air quality due to the 2015 fires in Equatorial Asia

Effectiveness of respiratory face masks in reducing acute PM2.5 pollution exposure during peak pollution period in Delhi

The cities of North India, such as Delhi, face a significant public health threat from severe air pollution. Between October 2021 and January 2022, 79 % of Delhi's daily average PM2.5 (Particulate matter with an aerodynamic diameter ≤ 2.5 μm) values exceeded 100 μg/m3 (the permissible level being 60 μg/m3 as per Indian standards). In response to this acute exposure, using Respiratory Face Masks (RFMs) is a cost-effective solution to reduce immediate health risks while policymakers develop long-term emission control plans. Our research focuses on the health and economic benefits of using RFMs to prevent acute exposure to PM2.5 pollution in Delhi for different age groups. Our findings indicate that, among the fifty chosen RFMs, M50 has greatest potential to prevent short-term excess mortality (908 in age ranges 5-44), followed by M49 (745) and M48 (568). These RFMs resulted in estimated economic benefits of 500.6 (46 %), 411.1 (37 %), and 313.4 (29 %) million Indian Rupee (INR), respectively during October-January 2021-22. By wearing RFMs such as M50, M49, and M48 during episodes of bad air quality, it is estimated that 13 % of short-term excess mortality and associated costs could be saved if at least 30 % of Delhi residents followed an alert issued by an operational Air Quality Early Warning System (AQEWS) developed by the Ministry of Earth Sciences. Our research suggests that RFMs can notably decrease health and economic burdens amid peak PM2.5 pollution in post-monsoon and winter seasons until long-term emission reduction strategies are adopted. It is suggested that an advisory may be crafted in collaboration with statutory bodies and should be disseminated to assist the vulnerable population in using RFMs during winter. The analysis presented in this research is purely science based and outcomes of study are in no way to be construed as endorsement of product.

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

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

Prediction of air pollutant concentrations based on the long short-term memory neural network

In recent years, environmental problems caused by air pollutants have received increasing attention. Effective prediction of air pollutant concentrations is an important way to protect the public from harm. Recently, due to extreme climate and social development, the forest fire frequency has increased. During the biomass combustion process caused by forest fires, the content of particulate matter (PM) in the atmosphere increases significantly. However, most existing air pollutant concentration prediction methods do not consider the considerable impact of forest fires, and effective long-term prediction models have not been established to provide early warnings for harmful gases. Therefore, in this paper, we collected a daily air quality data set (aerodynamic diameter smaller than 2.5 µm, PM2.5) for Heilongjiang Province, China, from 2017 to 2023 and A novel Long Short-Term Memory (LSTM) model was proposed to effectively predict the situation of air pollutants. The model could automatically extract information of the effective time step from the historical data set and combine forest fire disturbance and climate data as auxiliary data to improve the model prediction ability. Moreover, we created artificial neural network (ANN) and permissive regression (support vector machine, SVR) models for comparative experiments. The results showed that the precision accuracy of the developed LSTM model is higher. Unlike the other models, the LSTM neural network model could effectively predict the concentration of air pollutants in long-term series. Regarding long-term observation missions (7 days), the proposed model performed well and stably, with R2 reaching over 88%.

Assessing local and transboundary fine particulate matter pollution and sectoral contributions in Southeast Asia during haze months of 2015-2019

While previous studies have investigated haze events over Southeast Asia (SEA), local and transboundary contributions of various emission sources to haze months over the entire SEA have yet to be assessed comprehensively and systematically. We utilized the Particle Source Apportionment Technique (PSAT) to quantify the spatial local, transboundary, and sectoral contributions to PM2.5 over SEA during the haze months of 2015-2019. Results show that local emission contributions accounted for 56.1 % ~ 94.2 % of PM2.5 in Indonesia, Philippines, Vietnam, and Thailand. Transboundary contributions (23.1 % ~ 57.6 %) from Indonesia notably influenced maritime SEA. Vietnam (15.6 % ~ 39.1 %) and super-regional (17.0 % ~ 34.3 %) contributions outside the SEA exerted remarkable impacts on mainland SEA. Among different sectors, fire emissions contributed the most to PM2.5 over maritime SEA (23.0 % ~ 68.6 %) during the studied haze months, whereas residential and other emissions were the main contributors to mainland SEA (27.2 % ~ 36.7 %). Regarding the source species, primary PM2.5 accounted for the majority of PM2.5. VOC and SO2 composed most of the secondary PM2.5 due to massive VOC emissions in the region and the priority reaction of NH3 with sulfuric acid (H2SO4) to form ammonium sulfate. Besides, the intensified haze months in Oct 2015 and Sep 2019 were characterized by more intensive fire emissions in the region and the climatic variability-induced meteorological effects that provided favorable condition for transboundary air pollution (56.9 % and 44.9 %, respectively, for maritime SEA, as well as 46.0 % and 37.7 %, respectively, for mainland SEA in the two studied haze months). The haze months can be attributed to the notable drought conditions amidst global climatic phenomena such as El Niño and positive Indian Ocean Dipole (IOD) in Oct 2015 and Sep 2019, respectively.

Effect of biomass burning on premature mortality associated with long-term exposure to PM2.5 in Equatorial Asia

The health burden from exposure to ambient fine particulates (PM_2.5) in Equatorial Asia is substantially affected by the peatland fires in Indonesia, but the long-term health effect of the fires on local inhabitants is unclear. In this study, PM_2.5-associated excess mortality in Equatorial Asia over the past 30 years (1990-2019) was estimated and then the health effect of biomass burning was identified. The PM_2.5-related death in Equatorial Asia almost tripled from 113 (95% confidence interval, 100-125) thousand in 1990 to 337 (300-373) thousand in 2019, with a rate of increase of 6.4 (6.2-6.9) thousand/yr. The intense biomass burning between 1990 and 2019 was estimated to have induced 317 (282-348) thousand excess deaths in the study regions, with excess deaths mainly occurring in the El Niño years, such as in 1997, 2006, 2015 and 2019. Although the remote sensing data and emission inventories both reveal that the effective control measures have reduced biomass burning intensity in Equatorial Asia (especially in Sumatra and Borneo), the corresponding health benefit has been offset by variations in demographic factors, i.e., population and age structure. Over the same period, fossil fuel emissions continued to increase rapidly. Thus, more stringent and ambitious policies are required to reduce the health burden from biomass burning and anthropogenic emissions simultaneously to maximize the health benefits from government measures and policies.

Can air pollution reduce technology transfer? Evidence from China's prefecture-level cities

Air pollution hinders technological innovation, but the causal effects of air pollution on technology transfer are overlooked. We use thermal inversion as an instrumental variable for addressing air pollution endogeneity. The empirical results show that a one-unit increase in air pollution reduces technology transfer strength by 4.5 %. However, air pollution has a strong asymmetry in two directions of technology transfer strength. We find that those cities with worse pollution have an intention to transfer their technologies to cities in other provinces. In the PLFC model, heterogeneity varying with GDP can be addressed to estimate the marginal effect between them. Findings suggest that the marginal effects of air pollution on technology transfer can be divided into two parts based on GDP levels. Within the thresholds (lngdp = 11), the effect of environmental regulations will keep increasing and keep stable beyond the thresholds. In addition, different effects on different cities are also discussed.

Decadal changes in premature mortality associated with exposure to outdoor PM2.5 in mainland Southeast Asia and the impacts of biomass burning and anthropogenic emissions

In mainland Southeast Asia (SEA), a rapid increase of fossil fuel consumption and massive particulate matter emissions from biomass burning (BB) are severely threatening the health of local inhabitants. In this study, surface PM2.5 data, satellite fire observations and emission inventories were integrated with the Global Exposure Mortality Model (GEMM) to estimate premature mortality attributable to PM2.5 exposure from 1990 through 2019 and to explore and quantify the health burden associated with BB and anthropogenic emissions in mainland SEA. BB in mainland SEA has remained intense over the past decades. Owing to a lack of effective control measures, emission inventory and satellite-observed data both showed that BB has markedly intensified in several regions, including northern Cambodia and northern Laos. The multiannual average (1997-2015) BB PM2.5 emission was 1.6 × 106 t/yr, which is much higher than that of anthropogenic (fossil fuel combustion) PM2.5 emission. GEMM results indicated that PM2.5-related premature mortality in mainland SEA more than doubled from 100 (95 % confidence interval [CI], 88-112) thousand in 1990 to 257 (95 % CI, 228-286) thousand in 2019. Decomposition analysis revealed that variations in population size and age structure also promoted this increase of PM2.5-related deaths. Given that mainland SEA is a rapidly developing region, it is expected that local public health will face increasing challenges due to population growth, population ageing, and increased anthropogenic emissions. Therefore, it is imperative for policymakers to consider these influential factors, set practical mitigation targets, and explore how to effectively and systematically combine BB with anthropogenic emission controls to maximize the health benefits.

Demystifying ecological connectivity for actionable spatial conservation planning

Connectivity underpins the persistence of life; it needs to inform biodiversity conservation decisions. Yet, when prioritising conservation areas and developing actions, connectivity is not being operationalised in spatial planning. The challenge is the translation of flows associated with connectivity into conservation objectives that lead to actions. Connectivity is nebulous, it can be abstract and mean different things to different people, making it difficult to include in conservation problems. Here, we show how connectivity can be included in mathematically defining conservation planning objectives. We provide a path forward for linking connectivity to high-level conservation goals, such as increasing species' persistence. We propose ways to design spatial management areas that gain biodiversity benefit from connectivity.

Estimation of hospital visits for respiratory diseases attributable to PM10 from vegetation fire smoke and health impacts of regulatory intervention in Upper Northern Thailand

The air quality in Upper Northern Thailand (UNT) deteriorates during seasonal vegetation fire events, causing adverse effects especially on respiratory health outcomes. This study aimed to quantitatively estimate respiratory morbidity from vegetation fire smoke exposure, and to assess the impact of a burning ban enforced in 2016 on morbidity burden in UNT. We computed daily population exposure to fire-originated PM10 and estimated its health burden during a 5-year period from 2014 to 2018 using daily fire-originated PM10 concentration and the concentration-response function for short-term exposure to PM10 from vegetation fire smoke and respiratory morbidity. In subgroups classified as children and older adults, the health burden of respiratory morbidity was estimated using specific effect coefficients from previous studies conducted in UNT. Finally, we compared the health burden of respiratory morbidity before and after burning ban enforcement. Approximately 130,000 hospital visits for respiratory diseases were estimated to be attributable to fire-originated PM10 in UNT from 2014 to 2018. This estimation accounted for 1.3% of total hospital visits for respiratory diseases during the 5-year period, and 20% of those during burning events. Age-specific estimates revealed a larger impact of PM10 in the older adult group. The number of hospital visits for respiratory diseases attributable to fire-originated PM10 decreased from 1.8% to 0.5% after the burning ban policy was implemented in the area. Our findings suggest that PM10 released from vegetation fires is a health burden in UNT. The prohibition of the burning using regulatory measure had a positive impact on respiratory morbidity in this area.

A scoping review on the health effects of smoke haze from vegetation and peatland fires in Southeast Asia: Issues with study approaches and interpretation

Smoke haze due to vegetation and peatland fires in Southeast Asia is a serious public health concern. Several approaches have been applied in previous studies; however, the concepts and interpretations of these approaches are poorly understood. In this scoping review, we addressed issues related to the application of epidemiology (EPI), health burden estimation (HBE), and health risk assessment (HRA) approaches, and discussed the interpretation of findings, and current research gaps. Most studies reported an air quality index exceeding the ‘unhealthy’ level, especially during smoke haze periods. Although smoke haze is a regional issue in Southeast Asia, studies on its related health effects have only been reported from several countries in the region. Each approach revealed increased health effects in a distinct manner: EPI studies reported excess mortality and morbidity during smoke haze compared to non-smoke haze periods; HBE studies estimated approximately 100,000 deaths attributable to smoke haze in the entire Southeast Asia considering all-cause mortality and all age groups, which ranged from 1,064–260,000 for specified mortality cause, age group, study area, and study period; HRA studies quantified potential lifetime cancer and non-cancer risks due to exposure to smoke-related chemicals. Currently, there is a lack of interconnection between these three approaches. The EPI approach requires extensive effort to investigate lifetime health effects, whereas the HRA approach needs to clarify the assumptions in exposure assessments to estimate lifetime health risks. The HBE approach allows the presentation of health impact in different scenarios, however, the risk functions used are derived from EPI studies from other regions. Two recent studies applied a combination of the EPI and HBE approaches to address uncertainty issues due to the selection of risk functions. In conclusion, all approaches revealed potential health risks due to smoke haze. Nonetheless, future studies should consider comparable exposure assessments to allow the integration of the three approaches.

The role of information in consumer preferences for sustainable certified palm oil products in Germany

Food products are often subject to information asymmetries, which are commonly supposed to be reduced by labels and certifications. However, as the number of labels increases, consumers tend to get confused, bored or impatient and stop using them to make product choices. This study uses data from a discrete choice experiment, conducted in Germany, to analyze consumers’ preferences and willingness-to-pay (WTP) for sustainability indicators on products that contain palm oil as an ingredient. Since information is crucial to the assessment and awareness of, or attendance to, labels on consumer products, this study assesses the effect of factual information on preferences as well as attribute-processing strategies. We use a hybrid latent variable model that allows us to jointly examine the response to the stated choice component and the responses to attribute processing questions, thus capturing attribute non-attendance (ANA) to specific labels while controlling for heterogenous preferences. Our results reveal that the attribute ‘organic’ receives the highest monetary valuation in the overall sample as well as in the information intervention, and the no-information intervention groups. The results also show that providing additional information tends to change consumers’ non-attendance patterns as well as WTP values. In particular, the information intervention tends to increase consumers’ WTP and decreases their ANA for sustainability-indicating attributes. The findings suggest that the attribute ‘organic’ has the potential to be ranked highest across the entire latent variable structure, making it the most promising attribute for promoting sustainable palm oil use across consumer groups.

The health impacts of Indonesian peatland fires

BACKGROUND

Indonesian peatlands have been drained for agricultural development for several decades. This development has made a major contribution to economic development. At the same time, peatland drainage is causing significant air pollution resulting from peatland fires. Peatland fires occur every year, even though their extent is much larger in dry (El Niño) years. We examine the health effects of long-term exposure to fine particles (PM_2.5) from all types of peatland fires (including the burning of above and below ground biomass) in Sumatra and Kalimantan, where most peatland fires in Indonesia take place.

METHODS

We derive PM_2.5 concentrations from satellite imagery calibrated and validated with Indonesian Government data on air pollution, and link increases in these concentrations to peatland fires, as observed in satellite imagery. Subsequently, we apply available epidemiological studies to relate PM_2.5 exposure to a range of health outcomes. The model utilizes the age distribution and disease prevalence of the impacted population.

RESULTS

We find that PM_2.5 air pollution from peatland fires, causes, on average, around 33,100 adults and 2900 infants to die prematurely each year from air pollution. In addition, peatland fires cause on average around 4390 additional hospitalizations related to respiratory diseases, 635,000 severe cases of asthma in children, and 8.9 million lost workdays. The majority of these impacts occur in Sumatra because of its much higher population density compared to Kalimantan. A main source of uncertainty is in the Concentration Response Functions (CRFs) that we use, with different CRFs leading to annual premature adult mortality ranging from 19,900 to 64,800 deaths. Currently, the population of both regions is relatively young. With aging of the population over time, vulnerabilities to air pollution and health effects from peatland fires will increase.

CONCLUSIONS

Peatland fire health impacts provide a further argument to combat fires in peatlands, and gradually transition to peatland management models that do not require drainage and are therefore not prone to fire risks.

Assessing Sumatran Peat Vulnerability to Fire under Various Condition of ENSO Phases Using Machine Learning Approaches

In recent decades, catastrophic wildfire episodes within the Sumatran peatland have contributed to a large amount of greenhouse gas emissions. The El-Nino Southern Oscillation (ENSO) modulates the occurrence of fires in Indonesia through prolonged hydrological drought. Thus, assessing peatland vulnerability to fires and understanding the underlying drivers are essential to developing adaptation and mitigation strategies for peatland. Here, we quantify the vulnerability of Sumatran peat to fires under various ENSO conditions (i.e., El-Nino, La-Nina, and Normal phases) using correlative modelling approaches. This study used climatic (i.e., annual precipitation, SPI, and KBDI), biophysical (i.e., below-ground biomass, elevation, slope, and NBR), and proxies to anthropogenic disturbance variables (i.e., access to road, access to forests, access to cities, human modification, and human population) to assess fire vulnerability within Sumatran peatlands. We created an ensemble model based on various machine learning approaches (i.e., random forest, support vector machine, maximum entropy, and boosted regression tree). We found that the ensemble model performed better compared to a single algorithm for depicting fire vulnerability within Sumatran peatlands. The NBR highly contributed to the vulnerability of peatland to fire in Sumatra in all ENSO phases, followed by the anthropogenic variables. We found that the high to very-high peat vulnerability to fire increases during El-Nino conditions with variations in its spatial patterns occurring under different ENSO phases. This study provides spatially explicit information to support the management of peat fires, which will be particularly useful for identifying peatland restoration priorities based on peatland vulnerability to fire maps. Our findings highlight Riau’s peatland as being the area most prone to fires area on Sumatra Island. Therefore, the groundwater level within this area should be intensively monitored to prevent peatland fires. In addition, conserving intact forests within peatland through the moratorium strategy and restoring the degraded peatland ecosystem through canal blocking is also crucial to coping with global climate change.

Tripling of western US particulate pollution from wildfires in a warming climate

SignificanceRecord-setting fires in the western United States over the last decade caused severe air pollution, loss of human life, and property damage. Enhanced drought and increased biomass in a warmer climate may fuel larger and more frequent wildfires in the coming decades. Applying an empirical statistical model to fires projected by Earth System Models including climate-ecosystem-socioeconomic interactions, we show that fine particulate pollution over the US Pacific Northwest could double to triple during late summer to fall by the late 21st century under intermediate- and low-mitigation scenarios. The historic fires and resulting pollution extremes of 2017-2020 could occur every 3 to 5 y under 21st-century climate change, posing challenges for air quality management and threatening public health.

First fossil-leaf floras from Brunei Darussalam show dipterocarp dominance in Borneo by the Pliocene

The Malay Archipelago is one of the most biodiverse regions on Earth, but it suffers high extinction risks due to severe anthropogenic pressures. Paleobotanical knowledge provides baselines for the conservation of living analogs and improved understanding of vegetation, biogeography, and paleoenvironments through time. The Malesian bioregion is well studied palynologically, but there have been very few investigations of Cenozoic paleobotany (plant macrofossils) in a century or more. We report the first paleobotanical survey of Brunei Darussalam, a sultanate on the north coast of Borneo that still preserves the majority of its extraordinarily diverse, old-growth tropical rainforests. We discovered abundant compression floras dominated by angiosperm leaves at two sites of probable Pliocene age: Berakas Beach, in the Liang Formation, and Kampong Lugu, in an undescribed stratigraphic unit. Both sites also yielded rich palynofloral assemblages from the macrofossil-bearing beds, indicating lowland fern-dominated swamp (Berakas Beach) and mangrove swamp (Kampong Lugu) depositional environments. Fern spores from at least nine families dominate both palynological assemblages, along with abundant fungal and freshwater algal remains, rare marine microplankton, at least four mangrove genera, and a diverse rainforest tree and liana contribution (at least 19 families) with scarce pollen of Dipterocarpaceae, today's dominant regional life form. Compressed leaves and rare reproductive material represent influx to the depocenters from the adjacent coastal rainforests. Although only about 40% of specimens preserve informative details, we can distinguish 23 leaf and two reproductive morphotypes among the two sites. Dipterocarps are by far the most abundant group in both compression assemblages, providing rare, localized evidence for dipterocarp-dominated lowland rainforests in the Malay Archipelago before the Pleistocene. The dipterocarp fossils include winged Shorea fruits, at least two species of plicate Dipterocarpus leaves, and very common Dryobalanops leaves. We attribute additional leaf taxa to Rhamnaceae (Ziziphus), Melastomataceae, and Araceae (Rhaphidophora), all rare or new fossil records for the region. The dipterocarp leaf dominance contrasts sharply with the family's <1% representation in the palynofloras from the same strata. This result directly demonstrates that dipterocarp pollen is prone to strong taphonomic filtering and underscores the importance of macrofossils for quantifying the timing of the dipterocarps' rise to dominance in the region. Our work shows that complex coastal rainforests dominated by dipterocarps, adjacent to swamps and mangroves and otherwise similar to modern ecosystems, have existed in Borneo for at least 4-5 million years. Our findings add historical impetus for the conservation of these gravely imperiled and extremely biodiverse ecosystems.

Association between satellite-based estimates of long-term PM2.5 exposure and cardiovascular disease: evidence from the Indonesian Family Life Survey

Exposure to particulate matter with a diameter < 2.5 µm (PM2.5) increases the risk of cardiovascular disease (CVD), which is the leading cause of both morbidity and mortality in Indonesia, accounting for one-third of all deaths. Indonesian authorities started to monitor PM2.5 levels in urban areas in 2015. However, there is still no study examining the association between long-term PM2.5 exposure and CVD in Indonesia. In this study, we combined PM2.5 data and health survey data. Long-term (2000-2007) exposure to PM2.5 was measured based on satellite-derived aerosol optical depth measurements (1 × 1 km2) that could be used to predict ground-level PM2.5 concentrations. Population data on residents of Sumatra Island were obtained from the fourth wave of the Indonesian Family Life Survey (IFLS). A cross-sectional study was performed with 2324 participants who were aged ≥ 40 years old, and a report of doctor-diagnosed CVD determined CVD status. We used logistic regression to analyze the association between PM2.5 and CVD prevalence, adjusting for multiple covariates. Of the sample, 52.1% were women, and 47.9% were men. The sample was divided into those aged 40-59 (adults) and those ≥ 60 (older adults). The CVD prevalence was 4.05% (n = 94), with a mean (standard deviation) PM2.5 concentration of 14.4 (6.4) µg/m3. In adjusted models, a 10-µg/m3 increase in annual average PM2.5 levels was associated with 29% higher odds of having CVD (odds ratio = 1.29; 95% confidence interval: 1.02, 1.47). In this population-based IFLS data, long-term exposure to PM2.5 is associated with a higher prevalence of CVD in Sumatera, Indonesia.

Effect of a vegetation fire event ban on hospital visits for respiratory diseases in Upper Northern Thailand

BACKGROUND

Upper Northern Thailand (UNT) has been episodically affected by air pollution from vegetation burning, which causes adverse respiratory health effects. However, no study has evaluated the effect of regulatory actions to prohibit vegetation burning on respiratory morbidity. We examined the effect of a burning ban enforced in May 2016 on hospital visits for respiratory diseases in UNT.

METHODS

This study used data from eight provinces in UNT. Analyses were conducted for January to April of 2014-2016 (before ban enforcement) and January to April of 2017-2018 (after ban enforcement). Particulate matter of 10 microns in diameter or smaller (PM10) concentrations, numbers of satellite fire hotspots and age-standardized rates of hospital visits for respiratory diseases before and after ban enforcement were compared. The effect of the ban on hospital visits for respiratory diseases was evaluated using an interrupted time-series analysis controlled for season-specific temporal trends, day of week, public holiday, temperature, relative humidity, number of hospitals and offset population, with gastrointestinal diseases as a negative control. A meta-analysis was performed to pool province-specific effect estimates.

RESULTS

The daily average PM10 concentration and the number of fire hotspots decreased after ban enforcement in all provinces in UNT, with percent changes ranging from 5.3 to 34.3% and 14.3 to 81.5%, respectively. The adjusted pooled effect estimates of hospital visits for respiratory diseases decreased by 9.1% (95% CI: 5.1, 12.9), whereas a null association was observed for gastrointestinal diseases.

CONCLUSION

The burning ban had a positive impact on both air pollution levels and rates of hospital visits for respiratory diseases in UNT.

Deciphering Multifactorial Correlations of COVID-19 Incidence and Mortality in the Brazilian Amazon Basin

Amazonas suffered greatly during the COVID-19 pandemic. The mortality and fatality rates soared and scarcity of oxygen and healthcare supplies led the health system and funerary services to collapse. Thus, we analyzed the trends of incidence, mortality, and lethality indicators of COVID-19 and the dynamics of their main determinants in the state of Amazonas from March 2020 to June 2021. This is a time-series ecological study. We calculated the lethality, mortality, and incidence rates with official and public data from the Health Department. We used the Prais-Winsten regression and trends were classified as stationary, increasing, or decreasing. The effective reproduction number (Rt) was also estimated. Differences were considered significant when p < 0.05. We extracted 396,772 cases of and 13,420 deaths from COVID-19; 66% of deaths were in people aged over 60; 57% were men. Cardiovascular diseases were the most common comorbidity (28.84%), followed by diabetes (25.35%). Rural areas reported 53% of the total cases and 31% of the total deaths. The impact of COVID-19 in the Amazon is not limited to the direct effects of the pandemic itself; it may present characteristics of a syndemic due to the interaction of COVID-19 with pre-existing illnesses, endemic diseases, and social vulnerabilities.

Impact of Malaysian palm oil on sustainable development goals: co-benefits and trade-offs across mitigation strategies

Palm oil (PO) is an important source of livelihood, but unsustainable practices and widespread consumption may threaten human and planetary health. We reviewed 234 articles and summarized evidence on the impact of PO on health, social and economic aspects, environment, and biodiversity in the Malaysian context, and discuss mitigation strategies based on the sustainable development goals (SDGs). The evidence on health impact of PO is equivocal, with knowledge gaps on whether moderate consumption elevates risk for chronic diseases, but the benefits of phytonutrients (SDG2) and sensory characteristics of PO seem offset by its high proportion of saturated fat (SDG3). While PO contributes to economic growth (SDG9, 12), poverty alleviation (SDG1, 8, 10), enhanced food security (SDG2), alternative energy (SDG9), and long-term employment opportunities (SDG1), human rights issues and inequities attributed to PO production persist (SDG8). Environmental impacts arise through large-scale expansion of monoculture plantations associated with increased greenhouse gas emissions (SDG13), especially from converted carbon-rich peat lands, which can cause forest fires and annual trans-boundary haze; changes in microclimate properties and soil nutrient content (SDG6, 13); increased sedimentation and change of hydrological properties of streams near slopes (SDG6); and increased human wildlife conflicts, increase of invasive species occurrence, and reduced biodiversity (SDG14, 15). Practices such as biological pest control, circular waste management, multi-cropping and certification may mitigate negative impacts on environmental SDGs, without hampering progress of socioeconomic SDGs. While strategies focusing on improving practices within and surrounding plantations offer co-benefits for socioeconomic, environment and biodiversity-related SDGs, several challenges in achieving scalable solutions must be addressed to ensure holistic sustainability of PO in Malaysia for various stakeholders.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s11625-021-01052-4.

Assessing costs of Indonesian fires and the benefits of restoring peatland

Deforestation and drainage has made Indonesian peatlands susceptible to burning. Large fires occur regularly, destroying agricultural crops and forest, emitting large amounts of CO₂ and air pollutants, resulting in adverse health effects. In order to reduce fire, the Indonesian government has committed to restore 2.49 Mha of degraded peatland, with an estimated cost of US$3.2-7 billion. Here we combine fire emissions and land cover data to estimate the 2015 fires, the largest in recent years, resulted in economic losses totalling US$28 billion, whilst the six largest fire events between 2004 and 2015 caused a total of US$93.9 billion in economic losses. We estimate that if restoration had already been completed, the area burned in 2015 would have been reduced by 6%, reducing CO₂ emissions by 18%, and PM_2.5 emissions by 24%, preventing 12,000 premature mortalities. Peatland restoration could have resulted in economic savings of US$8.4 billion for 2004-2015, making it a cost-effective strategy for reducing the impacts of peatland fires to the environment, climate and human health.

Impact of the 2019/2020 Australian Megafires on Air Quality and Health

The Australian 2019/2020 bushfires were unprecedented in their extent and intensity, causing a catastrophic loss of habitat, human and animal life across eastern-Australia. We use a regional air quality model to assess the impact of the bushfires on particulate matter with a diameter less than 2.5 μm (PM2.5) concentrations and the associated health impact from short-term population exposure to bushfire PM2.5. The mean population Air Quality Index (AQI) exposure between September and February in the fires and no fires simulations indicates an additional ∼437,000 people were exposed to "Poor" or worse AQI levels due to the fires. The AQ impact was concentrated in the cities of Sydney, Newcastle-Maitland, Canberra-Queanbeyan and Melbourne. Between October and February 171 (95% CI: 66-291) deaths were brought forward due to short-term exposure to bushfire PM2.5. The health burden was largest in New South Wales (NSW) (109 (95% CI: 41-176) deaths brought forward), Queensland (15 (95% CI: 5-24)), and Victoria (35 (95% CI: 13-56)). This represents 38%, 13% and 30% of the total deaths brought forward by short-term exposure to all PM2.5. At a city-level 65 (95% CI: 24-105), 23 (95% CI: 9-38) and 9 (95% CI: 4-14) deaths were brought forward from short-term exposure to bushfire PM2.5, accounting for 36%, 20%, and 64% of the total deaths brought forward from all PM2.5. Thus, the bushfires caused substantial AQ and health impacts across eastern-Australia. Climate change is projected to increase bushfire risk, therefore future fire management policies should consider this.

Air Pollution From Forest and Vegetation Fires in Southeast Asia Disproportionately Impacts the Poor

Forest and vegetation fires, used as tools for agriculture and deforestation, are a major source of air pollutants and can cause serious air quality issues in many parts of Asia. Actions to reduce fire may offer considerable, yet largely unrecognized, options for rapid improvements in air quality. In this study, we used a combination of regional and global air quality models and observations to examine the impact of forest and vegetation fires on air quality degradation and public health in Southeast Asia (including Mainland Southeast Asia and south-eastern China). We found that eliminating fire could substantially improve regional air quality across Southeast Asia by reducing the population exposure to fine particulate matter (PM2.5) concentrations by 7% and surface ozone concentrations by 5%. These reductions in PM2.5 exposures would yield a considerable public health benefit across the region; averting 59,000 (95% uncertainty interval (95UI): 55,200-62,900) premature deaths annually. Analysis of subnational infant mortality rate data and PM2.5 exposure suggested that PM2.5 from fires disproportionately impacts poorer populations across Southeast Asia. We identified two key regions in northern Laos and western Myanmar where particularly high levels of poverty coincide with exposure to relatively high levels of PM2.5 from fires. Our results show that reducing forest and vegetation fires should be a public health priority for the Southeast Asia region.

Large Air Quality and Public Health Impacts due to Amazonian Deforestation Fires in 2019

Air pollution from Amazon fires has adverse impacts on human health. The number of fires in the Amazon has increased in recent years, but whether this increase was driven by deforestation or climate has not been assessed. We analyzed relationships between fire, deforestation, and climate for the period 2003 to 2019 among selected states across the Brazilian Legal Amazon (BLA). A statistical model including deforestation, precipitation and temperature explained ∼80% of the variability in dry season fire count across states when totaled across the BLA, with positive relationships between fire count and deforestation. We estimate that the increase in deforestation since 2012 increased the dry season fire count in 2019 by 39%. Using a regional chemistry-climate model combined with exposure-response associations, we estimate this increase in fire resulted in 3,400 (95UI: 3,300-3,550) additional deaths in 2019 due to increased exposure to particulate air pollution. If deforestation in 2019 had increased to the maximum recorded during 2003-2019, the number of active fire counts would have increased by an additional factor of 2 resulting in 7,900 (95UI: 7,600-8,200) additional premature deaths. Our analysis demonstrates the strong benefits of reduced deforestation on air quality and public health across the Amazon.

Biomass burning-derived airborne particulate matter in Southeast Asia: A critical review

Smoke haze episodes, resulting from uncontrolled biomass burning (BB) including forest and peat fires, continue to occur in Southeast Asia (SEA), affecting air quality, atmospheric visibility, climate, ecosystems, hydrologic cycle and human health. The pollutant of major concern in smoke haze is airborne particulate matter (PM). A number of fundamental laboratory, field and modeling studies have been conducted in SEA from 2010 to 2020 to investigate potential environmental and health impacts of BB-induced PM. The goal of this review is to bring together the most recent developments in our understanding of various aspects of BB-derived PM based on 127 research articles published from 2010 to 2020, which have not been conveyed in previous reviews. Specifically, this paper discusses the physical, chemical, toxicological and radiative properties of BB-derived PM. It also provides insights into the environmental and health impacts of BB-derived PM, summarizes the approaches taken to do the source apportionment of PM during BB events and discusses the mitigation of exposure to BB-derived PM. Suggestions for future research priorities are outlined. Policies needed to prevent future BB events in the SEA region are highlighted.

Dust Transport from Inland Australia and Its Impact on Air Quality and Health on the Eastern Coast of Australia during the February 2019 Dust Storm

Dust storms originating from Central Australia and western New South Wales frequently cause high particle concentrations at many sites across New South Wales, both inland and along the coast. This study focussed on a dust storm event in February 2019 which affected air quality across the state as detected at many ambient monitoring stations in the Department of Planning, Industry and Environment (DPIE) air quality monitoring network. The WRF-Chem (Weather Research and Forecast Model—Chemistry) model is used to study the formation, dispersion and transport of dust across the state of New South Wales (NSW, Australia). Wildfires also happened in northern NSW at the same time of the dust storm in February 2019, and their emissions are taken into account in the WRF-Chem model by using Fire Inventory from NCAR (FINN) as emission input. The model performance is evaluated and is shown to predict fairly accurate the PM2.5 and PM10 concentration as compared to observation. The predicted PM2.5 concentration over New South Wales during 5 days from 11 to 15 February 2019 is then used to estimate the impact of the February 2019 dust storm event on three health endpoints, namely mortality, respiratory and cardiac disease hospitalisation rates. The results show that even though as the daily average of PM2.5 over some parts of the state, especially in western and north western NSW near the centre of the dust storm and wild fires, are very high (over 900 µg/m3), the population exposure is low due to the sparse population. Generally, the health impact is similar in order of magnitude to that caused by biomass burning events from wildfires or from hazardous reduction burnings (HRBs) near populous centres such as in Sydney in May 2016. One notable difference is the higher respiratory disease hospitalisation for this dust event (161) compared to the fire event (24).

Community-Based Measurements Reveal Unseen Differences during Air Pollution Episodes

Short-term exposure to fine particulate matter (PM_2.5) pollution is linked to numerous adverse health effects. Pollution episodes, such as wildfires, can lead to substantial increases in PM_2.5 levels. However, sparse regulatory measurements provide an incomplete understanding of pollution gradients. Here, we demonstrate an infrastructure that integrates community-based measurements from a network of low-cost PM_2.5 sensors with rigorous calibration and a Gaussian process model to understand neighborhood-scale PM_2.5 concentrations during three pollution episodes (July 4, 2018, fireworks; July 5 and 6, 2018, wildfire; Jan 3-7, 2019, persistent cold air pool, PCAP). The firework/wildfire events included 118 sensors in 84 locations, while the PCAP event included 218 sensors in 138 locations. The model results accurately predict reference measurements during the fireworks (n: 16, hourly root-mean-square error, RMSE, 12.3-21.5 μg/m³, n(normalized)RMSE: 14.9-24%), the wildfire (n: 46, RMSE: 2.6-4.0 μg/m³; nRMSE: 13.1-22.9%), and the PCAP (n: 96, RMSE: 4.9-5.7 μg/m³; nRMSE: 20.2-21.3%). They also revealed dramatic geospatial differences in PM_2.5 concentrations that are not apparent when only considering government measurements or viewing the US Environmental Protection Agency's AirNow visualizations. Complementing the PM_2.5 estimates and visualizations are highly resolved uncertainty maps. Together, these results illustrate the potential for low-cost sensor networks that combined with a data-fusion algorithm and appropriate calibration and training can dynamically and with improved accuracy estimate PM_2.5 concentrations during pollution episodes. These highly resolved uncertainty estimates can provide a much-needed strategy to communicate uncertainty to end users.

The Influence of South East Asia Forest Fires on Ambient Particulate Matter Concentrations in Singapore: An Ecological Study Using Random Forest and Vector Autoregressive Models

Haze, due to biomass burning, is a recurring problem in Southeast Asia (SEA). Exposure to atmospheric particulate matter (PM) remains an important public health concern. In this paper, we examined the long-term seasonality of PM_2.5 and PM₁₀ in Singapore. To study the association between forest fires in SEA and air quality in Singapore, we built two machine learning models, including the random forest (RF) model and the vector autoregressive (VAR) model, using a benchmark air quality dataset containing daily PM_2.5 and PM₁₀ from 2009 to 2018. Furthermore, we incorporated weather parameters as independent variables. We observed two annual peaks, one in the middle of the year and one at the end of the year for both PM_2.5 and PM₁₀. Singapore was more affected by fires from Kalimantan compared to fires from other SEA countries. VAR models performed better than RF with Mean Absolute Percentage Error (MAPE) values being 0.8% and 6.1% lower for PM_2.5 and PM_10, respectively. The situation in Singapore can be reasonably anticipated with predictive models that incorporate information on forest fires and weather variations. Public communication of anticipated air quality at the national level benefits those at higher risk of experiencing poorer health due to poorer air quality.

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” [C_e; 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 C_e 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.

The environmental impacts of palm oil in context

Delivering the Sustainable Development Goals (SDGs) requires balancing demands on land between agriculture (SDG 2) and biodiversity (SDG 15). The production of vegetable oils and, in particular, palm oil, illustrates these competing demands and trade-offs. Palm oil accounts for ~40% of the current global annual demand for vegetable oil as food, animal feed and fuel (210 Mt), but planted oil palm covers less than 5-5.5% of the total global oil crop area (approximately 425 Mha) due to oil palm's relatively high yields. Recent oil palm expansion in forested regions of Borneo, Sumatra and the Malay Peninsula, where >90% of global palm oil is produced, has led to substantial concern around oil palm's role in deforestation. Oil palm expansion's direct contribution to regional tropical deforestation varies widely, ranging from an estimated 3% in West Africa to 50% in Malaysian Borneo. Oil palm is also implicated in peatland draining and burning in Southeast Asia. Documented negative environmental impacts from such expansion include biodiversity declines, greenhouse gas emissions and air pollution. However, oil palm generally produces more oil per area than other oil crops, is often economically viable in sites unsuitable for most other crops and generates considerable wealth for at least some actors. Global demand for vegetable oils is projected to increase by 46% by 2050. Meeting this demand through additional expansion of oil palm versus other vegetable oil crops will lead to substantial differential effects on biodiversity, food security, climate change, land degradation and livelihoods. Our Review highlights that although substantial gaps remain in our understanding of the relationship between the environmental, socio-cultural and economic impacts of oil palm, and the scope, stringency and effectiveness of initiatives to address these, there has been little research into the impacts and trade-offs of other vegetable oil crops. Greater research attention needs to be given to investigating the impacts of palm oil production compared to alternatives for the trade-offs to be assessed at a global scale.

The environmental impacts of palm oil in context

Delivering the Sustainable Development Goals (SDGs) requires balancing demands on land between agriculture (SDG 2) and biodiversity (SDG 15). The production of vegetable oils and, in particular, palm oil, illustrates these competing demands and trade-offs. Palm oil accounts for ~40% of the current global annual demand for vegetable oil as food, animal feed and fuel (210 Mt), but planted oil palm covers less than 5-5.5% of the total global oil crop area (approximately 425 Mha) due to oil palm's relatively high yields. Recent oil palm expansion in forested regions of Borneo, Sumatra and the Malay Peninsula, where >90% of global palm oil is produced, has led to substantial concern around oil palm's role in deforestation. Oil palm expansion's direct contribution to regional tropical deforestation varies widely, ranging from an estimated 3% in West Africa to 50% in Malaysian Borneo. Oil palm is also implicated in peatland draining and burning in Southeast Asia. Documented negative environmental impacts from such expansion include biodiversity declines, greenhouse gas emissions and air pollution. However, oil palm generally produces more oil per area than other oil crops, is often economically viable in sites unsuitable for most other crops and generates considerable wealth for at least some actors. Global demand for vegetable oils is projected to increase by 46% by 2050. Meeting this demand through additional expansion of oil palm versus other vegetable oil crops will lead to substantial differential effects on biodiversity, food security, climate change, land degradation and livelihoods. Our Review highlights that although substantial gaps remain in our understanding of the relationship between the environmental, socio-cultural and economic impacts of oil palm, and the scope, stringency and effectiveness of initiatives to address these, there has been little research into the impacts and trade-offs of other vegetable oil crops. Greater research attention needs to be given to investigating the impacts of palm oil production compared to alternatives for the trade-offs to be assessed at a global scale.

Tropical peatlands and their conservation are important in the context of COVID-19 and potential future (zoonotic) disease pandemics

The COVID-19 pandemic has caused global disruption, with the emergence of this and other pandemics having been linked to habitat encroachment and/or wildlife exploitation. High impacts of COVID-19 are apparent in some countries with large tropical peatland areas, some of which are relatively poorly resourced to tackle disease pandemics. Despite this, no previous investigation has considered tropical peatlands in the context of emerging infectious diseases (EIDs). Here, we review: (i) the potential for future EIDs arising from tropical peatlands; (ii) potential threats to tropical peatland conservation and local communities from COVID-19; and (iii) potential steps to help mitigate these risks. We find that high biodiversity in tropical peat-swamp forests, including presence of many potential vertebrate and invertebrate vectors, combined, in places, with high levels of habitat disruption and wildlife harvesting represent suitable conditions for potential zoonotic EID (re-)emergence. Although impossible to predict precisely, we identify numerous potential threats to tropical peatland conservation and local communities from the COVID-19 pandemic. This includes impacts on public health, with the potential for haze pollution from peatland fires to increase COVID-19 susceptibility a noted concern; and on local economies, livelihoods and food security, where impacts will likely be greater in remote communities with limited/no medical facilities that depend heavily on external trade. Research, training, education, conservation and restoration activities are also being affected, particularly those involving physical groupings and international travel, some of which may result in increased habitat encroachment, wildlife harvesting or fire, and may therefore precipitate longer-term negative impacts, including those relating to disease pandemics. We conclude that sustainable management of tropical peatlands and their wildlife is important for mitigating impacts of the COVID-19 pandemic, and reducing the potential for future zoonotic EID emergence and severity, thus strengthening arguments for their conservation and restoration. To support this, we list seven specific recommendations relating to sustainable management of tropical peatlands in the context of COVID-19/disease pandemics, plus mitigating the current impacts of COVID-19 and reducing potential future zoonotic EID risk in these localities. Our discussion and many of the issues raised should also be relevant for non-tropical peatland areas and in relation to other (pandemic-related) sudden socio-economic shocks that may occur in future.

Improving rural health care reduces illegal logging and conserves carbon in a tropical forest

Tropical forest loss currently exceeds forest gain, leading to a net greenhouse gas emission that exacerbates global climate change. This has sparked scientific debate on how to achieve natural climate solutions. Central to this debate is whether sustainably managing forests and protected areas will deliver global climate mitigation benefits, while ensuring local peoples' health and well-being. Here, we evaluate the 10-y impact of a human-centered solution to achieve natural climate mitigation through reductions in illegal logging in rural Borneo: an intervention aimed at expanding health care access and use for communities living near a national park, with clinic discounts offsetting costs historically met through illegal logging. Conservation, education, and alternative livelihood programs were also offered. We hypothesized that this would lead to improved health and well-being, while also alleviating illegal logging activity within the protected forest. We estimated that 27.4 km2 of deforestation was averted in the national park over a decade (∼70% reduction in deforestation compared to a synthetic control, permuted P = 0.038). Concurrently, the intervention provided health care access to more than 28,400 unique patients, with clinic usage and patient visitation frequency highest in communities participating in the intervention. Finally, we observed a dose-response in forest change rate to intervention engagement (person-contacts with intervention activities) across communities bordering the park: The greatest logging reductions were adjacent to the most highly engaged villages. Results suggest that this community-derived solution simultaneously improved health care access for local and indigenous communities and sustainably conserved carbon stocks in a protected tropical forest.

Global Wildfire Outlook Forecast with Neural Networks

Wildfire occurrence and spread are affected by atmospheric and land-cover conditions, and therefore meteorological and land-cover parameters can be used in area burned prediction. We apply three forecast methods, a generalized linear model, regression trees, and neural networks (Levenberg–Marquardt backpropagation) to produce monthly wildfire predictions 1 year in advance. The models are trained using the Global Fire Emissions Database version 4 with small fires (GFEDv4s). Continuous 1-year monthly fire predictions from 2011 to 2015 are evaluated with GFEDs data for 10 major fire regions around the globe. The predictions by the neural network method are superior. The 1-year moving predictions have good prediction skills over these regions, especially over the tropics and the southern hemisphere. The temporal refined index of agreement (IOA) between predictions and GFEDv4s regional burned areas are 0.82, 0.82, 0.8, 0.75, and 0.56 for northern and southern Africa, South America, equatorial Asia and Australia, respectively. The spatial refined IOA for 5-year averaged monthly burned area range from 0.69 in low-fire months to 0.86 in high-fire months over South America, 0.3–0.93 over northern Africa, 0.69–0.93 over southern Africa, 0.47–0.85 over equatorial Asia, and 0.53–0.8 over Australia. For fire regions in the northern temperate and boreal regions, the temporal and spatial IOA between predictions and GFEDv4s data in fire seasons are 0.7–0.79 and 0.24–0.83, respectively. The predictions in high-fire months are better than low-fire months. This study illustrates the feasibility of global fire activity outlook forecasts using a neural network model and the method can be applied to quickly assess the potential effects of climate change on wildfires.

Ambient particulate matter and biomass burning: an ecological time series study of respiratory and cardiovascular hospital visits in northern Thailand

BACKGROUND

Exposure to particulate matter (PM) emitted from biomass burning is an increasing concern, particularly in Southeast Asia. It is not yet clear how the source of PM influences the risk of an adverse health outcome. The objective of this study was to quantify and compare health risks of PM from biomass burning and non-biomass burning sources in northern Thailand.

METHODS

We collected ambient air pollutant data (PM with a diameter of < 10 μm [PM10], PM2.5, Carbon Monoxide [CO], Ozone [O3], and Nitrogen Dioxide [NO2]) from ground-based monitors and daily outpatient hospital visits in Thailand during 2014-2017. Outpatient data included chronic lower respiratory disease (CLRD), ischaemic heart disease (IHD), and cerebrovascular disease (CBVD). We performed an ecological time series analysis to evaluate the association between daily air pollutants and outpatient visits. We used the 90th and 95th percentiles of PM10 concentrations to determine days of exposure to PM predominantly from biomass burning.

RESULTS

There was significant intra annual variation in PM10 levels, with the highest concentrations occurring during March, coinciding with peak biomass burning. Incidence Rate Ratios (IRRs) between daily PM10 and outpatient visits were elevated most on the same day as exposure for CLRD = 1.020 (95% CI: 1.012 to 1.028) and CBVD = 1.020 (95% CI: 1.004 to 1.035), with no association with IHD = 0.994 (95% CI: 0.974 to 1.014). Adjusting for CO tended to increase effect estimates. We did not find evidence of an exposure response relationship with levels of PM10 on days of biomass burning.

CONCLUSIONS

We found same-day exposures of PM10 to be associated with certain respiratory and cardiovascular outpatient visits. We advise implementing measures to reduce population exposures to PM wherever possible, and to improve understanding of health effects associated with burning specific types of biomass in areas where such large-scale activities occur.

Health consequences of thick forest fire smoke to healthy residents in Riau, Indonesia: a cross-sectional study

BACKGROUND Indonesia forest fire in 2015 emitted a huge amount of pollutants into the air. This study was aimed to assess the health consequences of forest fire smoke in healthy residents in Riau during forest fire disaster in 2015. METHODS This cross-sectional study was performed in healthy residents who lived in Pekanbaru, Riau Province, Sumatera, for at least 6 months during forest fire disaster in 2015, and data were taken in October 2015. Questionnaires consisting of respiratory and non-respiratory symptoms were collected. Lung function was assessed by spirometry (MIR II Spirolab™ spirometer, Medical International Research, Italy) and exhaled carbon monoxide (CO) was assessed using piCO+ Smokerlyzer®. Heart rate at rest and oxygen saturation in the room air were measured using Onyx 9591 Pulse Oximeter®. RESULTS A total of 89 subjects were mostly female (75.3%), housewife (37.7%), nonsmoker (86.5%) with mean age of 38.9 years old. The non-respiratory and respiratory symptoms were reported in 84.7% and 71.4% subjects, respectively. Lung function was impaired in 72.6% subjects, mostly with mild obstruction and mild restriction. Exhaled CO was highly detected over normal values (mean [standard deviation] = 32.6 [9.97] ppm) with predicted carboxyhemoglobin (COHb) of 5.74 (1.56). CONCLUSIONS Forest fire smoke exposure increased the respiratory and nonrespiratory symptoms among healthy individuals, which showed impairment in lung function, exhaled CO, and predicted COHb. Long term health effects on healthy individuals exposed to forest fire smoke warrant further evaluation.

Forest and Land Fires Are Mainly Associated with Deforestation in Riau Province, Indonesia

Indonesia has experienced extensive land-cover change and frequent vegetation and land fires in the past few decades. We combined a new land-cover dataset with satellite data on the timing and location of fires to make the first detailed assessment of the association of fire with specific land-cover transitions in Riau, Sumatra. During 1990 to 2017, secondary peat swamp forest declined in area from 40,000 to 10,000 km2 and plantations (including oil palm) increased from around 10,000 to 40,000 km2. The dominant land use transitions were secondary peat swamp forest converting directly to plantation, or first to shrub and then to plantation. During 2001–2017, we find that the frequency of fire is greatest in regions that change land-cover, with the greatest frequency in regions that transition from secondary peat swamp forest to shrub or plantation (0.15 km−2 yr−1). Areas that did not change land cover exhibit lower fire frequency, with shrub (0.06 km−2 yr−1) exhibiting a frequency of fire >60 times the frequency of fire in primary forest. Our analysis demonstrates that in Riau, fire is closely connected to land-cover change, and that the majority of fire is associated with the transition of secondary forest to shrub and plantation. Reducing the frequency of fire in Riau will require enhanced protection of secondary forests and restoration of shrub to natural forest.

Spatiotemporal analysis of ground and satellite-based aerosol for air quality assessment in the Southeast Asia region

Satellite observations for regional air quality assessment rely on comprehensive spatial coverage, and daily monitoring with reliable, cloud-free data quality. We investigated spatiotemporal variation and data quality of two global satellite Aerosol Optical Depth (AOD) products derived from MODIS and VIIRS imagery. AOD is considered an essential atmospheric parameter strongly related to ground Particulate Matter (PM) in Southeast Asia (SEA). We analyze seasonal variation, urban/rural area influence, and biomass burning effects on atmospheric pollution. Validation indicated a strong relationship between AERONET ground AOD and both MODIS AOD (R² = 0.81) and VIIRS AOD (R² = 0.68). The monthly variation of satellite AOD and AERONET AOD reflects two seasonal trends of air quality separately for mainland countries including Myanmar, Laos, Cambodia, Thailand, Vietnam, and Taiwan, Hong Kong, and for maritime countries consisting of Indonesia, Philippines, Malaysia, Brunei, Singapore, and Timor Leste. The mainland SEA has a pattern of monthly AOD variation in which AODs peak in March/April, decreasing during wet season from May-September, and increasing to the second peak in October. However, in maritime SEA, AOD concentration peaks in October. The three countries with the highest annual satellite AODs are Singapore, Hong Kong, and Vietnam. High urban population proportions in Singapore (40.7%) and Hong Kong (21.6%) were associated with high AOD concentrations as expected. AOD values in SEA urban areas were a factor of 1.4 higher than in rural areas, with respective averages of 0.477 and 0.336. The AOD values varied proportionately to the frequency of biomass burning in which both active fires and AOD peak in March/April and September/October. Peak AOD in September/October in some countries could be related to pollutant transport of Indonesia forest fires. This study analyzed satellite aerosol product quality in relation to AERONET in SEA countries and highlighted framework of air quality assessment over a large, complicated region.

Influence of biomass burning on local air pollution in mainland Southeast Asia from 2001 to 2016

In this study, various remote sensing data, modeling data and emission inventories were integrated to analyze the tempo-spatial distribution of biomass burning in mainland Southeast Asia and its effects on the local ambient air quality from 2001 to 2016. Land cover changes have been considered in dividing the biomass burning into four types: forest fires, shrubland fires, crop residue burning and other fires. The results show that the monthly average number of fire spots peaked at 34,512 in March and that the monthly variation followed a seasonal pattern, which was closely related to precipitation and farming activities. The four types of biomass burning fires presented different tempo-spatial distributions. Moreover, the monthly Aerosol Optical Depth (AOD), concentration of particulate matter with a diameter less than 2.5 μm (PM_2.5) and carbon monoxide (CO) total column also peaked in March with values of 0.62, 45 μg/m³ and 3.25 × 10¹⁸ molecules/cm², respectively. There are significant correlations between the monthly means of AOD (r = 0.74, P < 0.001), PM_2.5 concentration (r = 0.88, P < 0.001), and CO total column (r = 0.82, P < 0.001) and the number of fire spots in the fire season. We used Positive Matrix Factorization (PMF) model to resolve the sources of PM_2.5 into 3 factors. The result indicated that the largest contribution (48%) to annual average concentration of PM_2.5 was from Factor 1 (dominated by biomass burning), followed by 27% from Factor 3 (dominated by anthropogenic emission), and 25% from Factor 2 (long-range transport/local nature source). The annually anthropogenic emission of CO and PM_2.5 from 2001 to 2012 and the monthly emission from the Emission Database for Global Atmosphere Research (EDGAR) were consistent with PMF analysis and further prove that biomass burning is the dominant cause of the variation in the local air quality in mainland Southeast Asia.

Relationship Between Fire and Forest Cover Loss in Riau Province, Indonesia Between 2001 and 2012

Forest and peatland fires occur regularly across Indonesia, resulting in large greenhouse gas emissions and causing major air quality issues. Over the last few decades, Indonesia has also experienced extensive forest loss and conversion of natural forest to oil palm and timber plantations. Here we used data on fire hotspots and tree-cover loss, as well as information on the extent of peat land, protected areas, and concessions to explore spatial and temporal relationships among forest, forest loss, and fire frequency. We focus on the Riau Province in Central Sumatra, one of the most active regions of fire in Indonesia. We find strong relationships between forest loss and fire at the local scale. Regions with forest loss experienced six times as many fire hotspots compared to regions with no forest loss. Forest loss and maximum fire frequency occurred within the same year, or one year apart, in 70% of the 1 km2 cells experiencing both forest loss and fire. Frequency of fire was lower both before and after forest loss, suggesting that most fire is associated with the forest loss process. On peat soils, fire frequency was a factor 10 to 100 lower in protected areas and natural forest logging concessions compared to oil palm and wood fiber (timber) concessions. Efforts to reduce fire need to address the underlying role of land-use and land-cover change in the occurrence of fire. Increased support for protected areas and natural forest logging concessions and restoration of degraded peatlands may reduce future fire risk. During times of high fire risk, fire suppression resources should be targeted to regions that are experiencing recent forest loss, as these regions are most likely to experience fire.

Assessing the health impacts of peatland fires: a case study for Central Kalimantan, Indonesia

The conversion of Indonesian tropical peatlands has been associated with the recurring problems of peatland fires and smoke affecting humans and the environment. Yet, the local government and public in the affected areas have paid little attention to the impacts and costs of the poor air quality on human health. This study aims to analyse the long-term health impacts of the peat smoke exposure to the local populations. We applied the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model to determine the smoke dispersion and the associated PM_2.5 concentrations of the resulted plumes from the fire hotspots in the deep and shallow peatlands in Central Kalimantan, Indonesia, that occurred during a 5-year period (2011-2015). We subsequently quantified the long-term health impacts of PM_2.5 on the local people down to the village level based on the human health risk assessment approach. Our study shows that the average increase in the annual mean PM_2.5 concentration due to peatland fires in Central Kalimantan was 26 μg/m³ which is more than twice the recommended value of the World Health Organisation Air Quality Guidelines. This increase in PM_2.5 leads to increased occurrence of a range of air pollution-related diseases and premature mortality. The number of premature mortality cases can be estimated at 648 cases per year (26 mortality cases per 100,000 population) among others due to chronic respiratory, cardiovascular and lung cancer. Our results shed further light on the long-term health impacts of peatland fires in Indonesia and the importance of sustainable peatland management.

Integrated assessment of health risk and climate effects of black carbon in the Pearl River Delta region, China

BACKGROUND

Black carbon (BC) caused by incomplete combustion of fossil and bio-fuel has a dual effect on health and climate. There is a need for systematic approaches to evaluation of health outcomes and climate impacts relevant to BC exposure.

OBJECTIVES

We propose and illustrate for the first time, to our knowledge, an integrated analysis of a region-specific health model with climate change valuation module to quantify the health and climate consequences of BC exposure.

METHODS

Based on the data from regional air pollution monitoring stations from 2013 to 2014 in the Pearl River Delta region (PRD), China, we analyzed the carcinogenic and non-carcinogenic effects and the relative risk of cause-specific mortality due to BC exposure in three typical cities of the PRD (i.e. Guangzhou, Jiangmen and Huizhou). The radiative forcing (RF) and heating rate (HR) were calculated by the Fu-Liou-Gu (FLG) plane-parallel radiation model and the conversion of empirical formula. We further connected the health and climate impacts by calculating the excess mortalities attributed to climate warming due to BC.

RESULTS

Between 2013 and 2014, carcinogenic risks of adults and children due to BC exposure in the PRD were higher than the recommended limits (1 × 10^-6 to 1 × 10^-4), resulting in an excess of 4.82 cancer cases per 10,000 adults (4.82 × 10^-4) and an excess of 1.97 cancer cases per 10,000 children (1.97 × 10^-4). Non-carcinogenic risk caused by BC was not found. The relative risks of BC exposure on mortality were higher in winter and dry season. The atmospheric RFs of BC were 26.31 W m^-2, 26.41 W m^-2, and 22.45 W m^-2 for Guangzhou, Jiangmen and Huizhou, leading to a warming of the atmosphere in the PRD. The estimated annual excess mortalities of climate warming due to BC were 5052 (95% CI: 1983, 8139), 5121 (95% CI: 2010, 8249) and 4363 (95% CI: 1712, 7032) for Guangzhou, Jiangmen and Huizhou, respectively.

CONCLUSION

Our estimates suggest that current levels of BC exposure in the PRD region posed a considerable risk to human health and the climate. Reduction of BC emission could lead to substantial health and climate co-benefits.

Fires, Smoke Exposure, and Public Health: An Integrative Framework to Maximize Health Benefits From Peatland Restoration

Emissions of particulate matter from fires associated with land management practices in Indonesia contribute to regional air pollution and mortality. We assess the public health benefits in Indonesia, Malaysia, and Singapore from policies to reduce fires by integrating information on fire emissions, atmospheric transport patterns, and population exposure to fine particulate matter (PM2.5). We use adjoint sensitivities to relate fire emissions to PM2.5 for a range of meteorological conditions and find that a Business-As-Usual scenario of land use change leads, on average, to 36,000 excess deaths per year into the foreseeable future (the next several decades) across the region. These deaths are largely preventable with fire reduction strategies, such as blocking fires in peatlands, industrial concessions, or protected areas, which reduce the health burden by 66, 45, and 14%, respectively. The effectiveness of these different strategies in mitigating human health impacts depends on the location of fires relative to the population distribution. For example, protecting peatlands through eliminating all fires on such lands would prevent on average 24,000 excess deaths per year into the foreseeable future across the region because, in addition to storing large amounts of fuel, many peatlands are located directly upwind of densely populated areas. We also demonstrate how this framework can be used to prioritize restoration locations for the Indonesian Peatland Restoration Agency based on their ability to reduce pollution exposure and health burden. This scientific framework is publicly available through an online decision support tool that allows stakeholders to readily determine the public health benefits of different land management strategies.

Active Carbon Respiratory Masks as the Adsorbent of Toxic Gases in Ambient Air

The air quality that is increasingly carrying out pollution as a result of pollution by human activities is of concern to the world, both developed and developing countries. The impact of air pollution is unavoidable, especially for health. Several efforts have been made to suppress the occurrence of pollution starting from the control of sources, media, and protective efforts in human beings. Focusing on protective efforts, this study was carried out by designed respiratory masks capable of adsorbing toxic gases in ambient air by utilizing mask materials on the market with the addition of activated carbon; the study was carried out with an experimental approach. Testing distinguishes the ability of cotton, spunbond, meltblown, and activated carbon as a respiratory mask to absorb toxic gases such as COx, NOx, and SOx. Test statistics are using the ANOVA test with a confidence level of 95%, α = 5%. The results show that combining activated carbon, spunbond, and meltblown is more effective compared to respiratory masks made from spunbond and meltblown (surgical masks) in absorbing toxic gases.

Effects of air pollution on mitochondrial function, mitochondrial DNA methylation, and mitochondrial peptide expression

Mitochondrial DNA is sensitive to damage by exogenous reactive oxygen sources, including traffic-related air pollution (TRAP). Given the important role for mitochondria in human disease, we hypothesized that prenatal air pollution exposure may be associated with mitochondrial dysfunction and that mitochondrial-derived peptides (MDPs) might protect against these effects. In in vitro studies, 24-hour exposure to nanoparticulate matter (nPM) increased oxidation of mtDNA, decreased mitochondrial consumption rate (OCR), and decreased mtDNAcn in SH-SY5Y cells. Addition of MDPs rescued these effects to varying degrees. Liver tissue taken from C57Bl/6 males exposed for 10 weeks to nPM had lower OCR, lower mtDNAcn and higher MDP levels, similar to in vitro studies. In newborn cord blood, MDP levels were positively associated with prenatal TRAP exposures. Moreover, DNA methylation of two distinct regions of the D-Loop in the mitochondria genome was associated with levels of several MDPs. Our in vitro and in vivo data indicate that TRAP can directly affect mitochondrial respiratory function and mtDNAcn. Treatment of cells with MDPs can counteract TRAP induced-effects. Lastly, we present evidence that suggests MDPs may be regulated in part by mitochondrial DNA methylation in humans.

Thermal-Drones as a Safe and Reliable Method for Detecting Subterranean Peat Fires

Underground peat fires are a major hazard to health and livelihoods in Indonesia, and are a major contributor to carbon emissions globally. Being subterranean, these fires can be difficult to detect and track, especially during periods of thick haze and in areas with limited accessibility. Thermal infrared detectors mounted on drones present a potential solution to detecting and managing underground fires, as they allow large areas to be surveyed quickly from above and can detect the heat transferred to the surface above a fire. We present a pilot study in which we show that underground peat fires can indeed be detected in this way. We also show that a simple temperature thresholding algorithm can be used to automatically detect them. We investigate how different thermal cameras and drone flying strategies may be used to reliably detect underground fires and survey fire-prone areas. We conclude that thermal equipped drones are potentially a very powerful tool for surveying for fires and firefighting. However, more investigation is still needed into their use in real-life fire detection and firefighting scenarios.

The palm oil industry and noncommunicable diseases

Large-scale industries do not operate in isolation, but have tangible impacts on human and planetary health. An often overlooked actor in the fight against noncommunicable diseases is the palm oil industry. The dominance of palm oil in the food processing industry makes it the world's most widely produced vegetable oil. We applied the commercial determinants of health framework to analyse the palm oil industry. We highlight the industry's mutually profitable relationship with the processed food industry and its impact on human and planetary health, including detrimental cultivation practices that are linked to respiratory illnesses, deforestation, loss of biodiversity and pollution. This analysis illustrates many parallels to the contested nature of practices adopted by the alcohol and tobacco industries. The article concludes with suggested actions for researchers, policy-makers and the global health community to address and mitigate the negative impacts of the palm oil industry on human and planetary health.