| Literature DB >> 30455288 |
Elizabeth B Wiggins1, Claudia I Czimczik2, Guaciara M Santos2, Yang Chen2, Xiaomei Xu2, Sandra R Holden2, James T Randerson1, Charles F Harvey3,4, Fuu Ming Kai3, Liya E Yu5,6.
Abstract
In response to a strong El Niño, fires in Indonesia during September and October 2015 released a large amount of carbon dioxide and created a massive regional smoke cloud that severely degraded air quality in many urban centers across Southeast Asia. Although several lines of evidence indicate that peat burning was a dominant contributor to emissions in the region, El Niño-induced drought is also known to increase deforestation fires and agricultural waste burning in plantations. As a result, uncertainties remain with respect to partitioning emissions among different ecosystem and fire types. Here we measured the radiocarbon content (14C) of carbonaceous aerosol samples collected in Singapore from September 2014 through October 2015, with the aim of identifying the age and origin of fire-emitted fine particulate matter (particulate matter with an aerodynamic diameter less than or equal to 2.5 μm). The Δ14C of fire-emitted aerosol was -76 ± 51‰, corresponding to a carbon pool of combusted organic matter with a mean turnover time of 800 ± 420 y. Our observations indicated that smoke plumes reaching Singapore originated primarily from peat burning (∼85%), and not from deforestation fires or waste burning. Atmospheric transport modeling confirmed that fires in Sumatra and Borneo were dominant contributors to elevated PM2.5 in Singapore during the fire season. The mean age of the carbonaceous aerosol, which predates the Industrial Revolution, highlights the importance of improving peatland fire management during future El Niño events for meeting climate mitigation and air quality commitments.Entities:
Keywords: global carbon cycle; human health; isotope; land cover change; tropical peatlands
Year: 2018 PMID: 30455288 PMCID: PMC6298069 DOI: 10.1073/pnas.1806003115
Source DB: PubMed Journal: Proc Natl Acad Sci U S A ISSN: 0027-8424 Impact factor: 11.205
Fig. 1.Location (A) and timing (B) of satellite-detected active fires during the 2015 September–October fire season across the Maritime Continent. The satellite detections of active fires were from the Moderate Resolution Imaging Spectroradiometer MCD14ML product that combines fire detections from NASA’s Aqua and Terra satellites. The units of A are number of fire detections per 0.1° grid cell. The month with the maximum number of fire detections in each grid cell is shown in B.
Fig. 2.Time series of aerosol composition and fire activity during the 2014 and 2015 fire seasons. (A) TC concentration of aerosol samples collected in Singapore during 2014 and 2015. Samples collected during the 2014 fire season are shown in brown, those collected during a low-fire urban background interval during the first half of 2015 are shown in blue, and those collected during the 2015 fire season are shown in red. (B) The radiocarbon content [Δ14C; with units of per mil (‰)] of the carbonaceous aerosol shown in A. (C) The number of satellite active fire detections on the islands of Borneo (dark red) and Sumatra (red). (D) PM2.5 estimates from the GEOS-Chem atmospheric model with all sources (full; red line) and a model simulation in which fire emissions were excluded (no fire; blue line). Daily average PM2.5 observations collected from a site at the National University of Singapore are shown in D with black circles.
Fig. 3.(A) A Keeling plot showing radiocarbon content (Δ14C) vs. the reciprocal of aerosol TC concentration (1/TC). A best-fit line derived from a model II regression, taking into account uncertainty in both Δ14C and concentration, is shown in black for all of the fire season data from 2014 and 2015. The y intercept for this regression is −76 ± 51‰ and represents the isotopic composition of the fire-emitted aerosol. Brown and red lines denote the best-fit lines for the 2014 and 2015 fire seasons, respectively. B shows the Δ14C of atmospheric CO2 (blue line) and model estimates of agricultural waste burning emissions (light green line) and deforestation (dark green line). A source with a turnover time of 800 ± 420 y (black line) was required to match the observed Δ14C of the fire-emitted aerosols (black circle). The error bar on the fire-emitted aerosol in B denotes 1 SD and was derived from the All Fires regression line shown in A.
Fig. 4.(A) Histogram of the radiocarbon content (Δ14C) of fire-derived carbonaceous aerosols, using a mass balance approach using all of the aerosol observations from 2014 and 2015. (B) Histogram of Δ14C value of the 2014–2015 atmosphere, using a Monte-Carlo approach with a mean of 25 ± 3‰. (C) Histogram of Δ14C values of agricultural waste burning, using a Monte-Carlo approach with a mean of 55 ± 21‰, corresponding to a carbon pool with a turnover time of 7.5 ± 4 y. (D) Histogram of Δ14C values of deforestation related fires, using a Monte-Carlo approach with a mean of 114 ± 26‰ corresponding to a carbon pool with a turnover time of 55 ± 28 y. The vertical black line and gray shaded area represents the mean and SD of the fire-derived carbonaceous aerosol derived from the Keeling plot approach.