New Tropical Peatland Gas and Particulate Emissions Factors Indicate 2015 Indonesian Fires Released Far More Particulate Matter (but Less Methane) than Current Inventories Imply

Deforestation and draining of the peatlands in equatorial SE Asia has greatly increased their flammability, and in September-October 2015 a strong El Niño-related drought led to further drying and to widespread burning across parts of Indonesia, primarily on Kalimantan and Sumatra. These fires resulted in some of the worst sustained outdoor air pollution ever recorded, with atmospheric particulate matter (PM) concentrations exceeding those considered "extremely hazardous to health" by up to an order of magnitude. Here we report unique in situ air quality data and tropical peatland fire emissions factors (EFs) for key carbonaceous trace gases (CO2, CH4 and CO) and PM2.5 and black carbon (BC) particulates, based on measurements conducted on Kalimantan at the height of the 2015 fires, both at locations of "pure" sub-surface peat burning and spreading vegetation fires atop burning peat. PM2.5 are the most significant smoke constituent in terms of human health impacts, and we find in situ PM2.5 emissions factors for pure peat burning to be 17.8 to 22.3 g·kg-1, and for spreading vegetation fires atop burning peat 44 to 61 g·kg-1, both far higher than past laboratory burning of tropical peat has suggested. The latter are some of the highest PM2.5 emissions factors measured worldwide. Using our peatland CO2, CH4 and CO emissions factors (1779 ± 55 g·kg-1, 238 ± 36 g·kg-1, and 7.8 ± 2.3 g·kg-1 respectively) alongside in situ measured peat carbon content (610 ± 47 g-C·kg-1) we provide a new 358 Tg (± 30%) fuel consumption estimate for the 2015 Indonesian fires, which is less than that provided by the GFEDv4.1s and GFASv1.2 global fire emissions inventories by 23% and 34% respectively, and which due to our lower EFCH4 produces far less (~3×) methane. However, our mean in situ derived EFPM2.5 for these extreme tropical peatland fires (28 ± 6 g·kg-1) is far higher than current emissions inventories assume, resulting in our total PM2.5 emissions estimate (9.1 ± 3.5 Tg) being many times higher than GFEDv4.1s, GFASv1.2 and FINNv2, despite our lower fuel consumption. We find that two thirds of the emitted PM2.5 come from Kalimantan, one third from Sumatra, and 95% from burning peatlands. Using new geostationary fire radiative power (FRP) data we map the fire emissions' spatio-temporal variations in far greater detail than ever before (hourly, 0.05°), identifying a tropical peatland fire diurnal cycle twice as wide as in neighboring non-peat areas and peaking much later in the day. Our data show that a combination of greatly elevated PM2.5 emissions factors, large areas of simultaneous, long-duration burning, and very high peat fuel consumption per unit area made these Sept to Oct tropical peatland fires the greatest wildfire source of particulate matter globally in 2015, furthering evidence for a regional atmospheric pollution impact whose particulate matter component in particular led to millions of citizens being exposed to extremely poor levels of air quality for substantial periods. © 2018 by the authors

Denial of long-term issues with agriculture on tropical peatlands will have devastating consequences

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Fire activity in Borneo driven by industrial land conversion and drought during El Niño periods, 1982–2010

Tropical rainforests, naturally resistant to fire when intact, are increasingly vulnerable to burning due to ongoing forest perturbation and, possibly, climatic changes. Industrial-scale forest degradation and conversion are increasing fire occurrence, and interactions with climate anomalies such as El Niño induced droughts can magnify the extent and severity of fire activity. The influences of these factors on fire frequency in tropical forests has not been widely studied at large spatio-temporal scales at which feedbacks between fire reoccurrence and forest degradation may develop. Linkages between fire activity, industrial land use, and El Niño rainfall deficits are acute in Borneo, where the greatest tropical fire events in recorded history have apparently occurred in recent decades. Here we investigate how fire frequency in Borneo has been influenced by industrial-scale agricultural development and logging during El Niño periods by integrating long-term satellite observations between 1982 and 2010 – a period encompassing the onset, development, and consolidation of its Borneo's industrial forestry and agricultural operations as well as the full diversity of El Niño events. We record changes in fire frequency over this period by deriving the longest and most comprehensive spatio-temporal record of fire activity across Borneo using AVHRR Global Area Coverage (GAC) satellite data. Monthly fire frequency was derived from these data and modelled at 0.04° resolution via a random-forest model, which explained 56% of the monthly variation as a function of oil palm and timber plantation extent and proximity, logging intensity and proximity, human settlement, climate, forest and peatland condition, and time, observed using Landsat and similar satellite data. Oil-palm extent increased fire frequency until covering 20% of a grid cell, signalling the significant influence of early stages of plantation establishment. Heighted fire frequency was particularly acute within 10 km of oil palm, where both expanding plantation and smallholder agriculture are believed to be contributing factors. Fire frequency increased abruptly and dramatically when rainfall fell below 200 mm month−1, especially as landscape perturbation increased (indicated by vegetation index data). Logging intensity had a negligible influence on fire frequency, including on peatlands, suggesting a more complex response of logged forest to burning than appreciated. Over time, the epicentres of high-frequency fires expanded from East Kalimantan (1980's) to Central and West Kalimantan (1990's), coincidentally but apparently slightly preceding oil-palm expansion, and high-frequency fires then waned in East Kalimantan and occurred only in Central and West Kalimantan (2000's). After accounting for land-cover changes and climate, our model under-estimates observed fire frequency during ca. 1990–2002 and over-estimates it thereafter, suggesting that a multi-decadal shift to industrial forest conversion and forest landscapes may have diminished the propensity for high-frequency fires in much of this globally significant tropical region since ca. 2000. (Résumé d'auteur

2019 burned area map for Indonesia using Sentinel-2 data

The dataset '2019_burnedarea_indonesia' contains an Indonesia-wide map of burned areas for 2019 derived based on an analysis of time-series Sentinel-2 imagery at spatial resolution: 20 m x 20 m. The reference dataset 'Reference_dataset' contains 1298 randomly-distributed reference sites used to validate the burned area dataset (SENTINEL) and two other burned area products: 1) the 2019 Landsat-8 Official estimate from the Indonesian Ministry of Environment and Forestry, and 2) the 2019 MODIS burned area product (MCD64A1). Each reference site includes attribute ‘REFERENCE’ to describe the values obtained by visual interpretation: either ‘NO’ unburned or ‘YES’ burned. Each reference point has three attributes: ‘C_SENTINEL’, ‘C_OFFICIAL’ and ‘C_MCD64A1’ to describe the values of the classification of each burned area product: either ‘NO’ unburned or ‘YES’ burned. Finally, each reference point has three additional attributes: ‘SENTINEL’, ‘OFFICIAL’, and MCD64A1’ to describe which burned area product this reference point validates. The values are either 0: not validate or 1: validate

Refined burned-area mapping protocol using Sentinel-2 data increases estimate of 2019 Indonesian burning

Many nations are challenged by landscape fires. A confident knowledge of the area and distribution of burning is crucial to monitor these fires and to assess how they might best be reduced. Given the differences that arise using different detection approaches, and the uncertainties surrounding burned-area estimates, their relative merits require evaluation. Here we propose, illustrate, and examine one promising approach for Indonesia where recurring forest and peatland fires have become an international crisis. Drawing on Sentinel-2 satellite time-series analysis, we present and validate new 2019 burned-area estimates for Indonesia. The corresponding burned-area map is available at https://doi.org/10.5281/zenodo.4551243 (Gaveau et al., 2021a). We show that >3.11 million hectares (Mha) burned in 2019. This burned-area extent is double the Landsat-derived official estimate of 1.64 Mha from the Indonesian Ministry of Environment and Forestry and 50 % more that the MODIS MCD64A1 burned-area estimate of 2.03 Mha. Though we observed proportionally less peatland burning (31 % vs. 39 % and 40 % for the official and MCD64A1 products, respectively), in absolute terms we still observed a greater area of peatland affected (0.96 Mha) than the official estimate (0.64 Mha). This new burned-area dataset has greater reliability than these alternatives, attaining a user accuracy of 97.9 % (CI: 97.1 %–98.8 %) compared to 95.1 % (CI: 93.5 %–96.7 %) and 76 % (CI: 73.3 %–78.7 %), respectively. It omits fewer burned areas, particularly smaller- (<100 ha) to intermediate-sized (100–1000 ha) burns, attaining a producer accuracy of 75.6 % (CI: 68.3 %–83.0 %) compared to 49.5 % (CI: 42.5 %–56.6 %) and 53.1 % (CI: 45.8 %–60.5 %), respectively. The frequency–area distribution of the Sentinel-2 burn scars follows the apparent fractal-like power law or Pareto pattern often reported in other fire studies, suggesting good detection over several magnitudes of scale. Our relatively accurate estimates have important implications for carbon-emission calculations from forest and peatland fires in Indonesia

Remaining natural vegetation in the global biodiversity hotspots

The biodiversity hotspots are 35 biogeographical regions that have both exceptional endemism and extreme threats to their vegetation integrity, and as such are global conservation priorities. Nonetheless, prior estimates of natural intact vegetation (NIV) in the hotspots are generally imprecise, indirect, coarse, and/or dated. Using moderate- and high-resolution satellite imagery as well as maps of roads, settlements, and fires, we estimate the current extent of NIV for the hotspots. Our analysis indicates that hotspots retain 14.9% of their total area as NIV (∼3,546,975 km2). Most hotspots have much less NIV than previously estimated, with half now having ≤10% NIV by area, a threshold beneath which mean NIV patch area declines precipitously below 1000 ha. Hotspots with the greatest previous NIV estimates suffered the greatest apparent losses. The paucity of NIV is most pronounced in biomes dominated by dry forests, open woodlands, and grasslands, reflecting their historic affinities with agriculture, such that NIV tends to concentrate in select biomes. Low and declining levels of NIV in the hotspots underscore the need for an urgent focus of limited conservation resources on these biologically crucial regions

Forest loss in Indonesian New Guinea: trends, drivers, and outlook

International audienceThe rich forests of Indonesian New Guinea are threatened. We used satellite data to examine annual forest loss, road development and plantation expansion from 2001 to 2019, then developed a model to predict future deforestation in this understudied region. In 2019, 34.29 million hectares (Mha), or 83% of Indonesian New Guinea, supported old-growth forest. Over nineteen years, two percent (0.75 Mha) were cleared: 45% (0.34 Mha) converted to industrial plantations, roads, mine tailings, or other uses near cities; 55% (0.41 Mha) cleared by transient processes including selective natural timber extraction, inland water bodies-related processes, fires, and shifting agriculture. Industrial plantations expanded by 0.23 Mha, with the majority (0.21 Mha; 28% of forest loss) replacing forests and reaching 0.28 Mha in 2019 (97% oil palm; 3% pulpwood). The Trans-Papua Highway, a 4,000 km national investment project, increased by 1,554 km. Positive correlations between highway and plantations expansion indicate these are linked processes. Plantations and roads grew rapidly after 2011, peaked in 2015/16, and declined thereafter. Indonesian government allocated 2.62 Mha of land for the development of industrial plantations (90% oil palm 10% pulpwood) of which 74% (1.95 Mha) remained forest in 2019. A spatial model predicts that an additional 4.5 Mha of forest could be cleared by 2036 if Indonesian New Guinea follows similar relationships to Indonesian Borneo. We highlight the opportunities for policy reform and the importance of working with indigenous communities, local leaders, and provincial government to protect the biological and cultural richness still embodied in this remarkable region