Oil-smoke generator for use at elevated pressures.
Smoke generator control and performance for flow visualization applications
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Smoke generator control and performance for flow visualization applications
We are in the early stages of work on EPA task to investigate the effects of fires on air quality in North America, led by Jennifer Logan of Harvard University. JPL's contribution to this study is to find thousands of smoke plumes in satellite images of North America, and derive statistics about their geographic distribution, extent, orientation, and injection height.
The AeroCom BB (Biomass Burning) Experiment AOD (Aerosol Optical Depth) motivation: We have a substantial set of satellite wildfire plume AOD snapshots and injection heights to help calibrate model/inventory performance; We are 1) adding more fire source-strength cases 2) using MISR to improve the AOD constrains and 3) adding 2008 global injection heights; We selected GFED3-daily due to good overall source strength performance, but any inventory can be tested; Joint effort to test multiple, global models, to draw robust BB injection height and emission strength conclusions. We provide satellite-based injection height and smoke plume AOD climatologies.
The Fire Energetics and Emissions Research (FEER) group's new coefficient of emission global gridded product at 1x1 resolution that directly relates fire readiative energy (FRE) to smoke aerosol release, FEERv1.0 Ce, made its public debut in August 2013. Since then, steps have been taken to generate corresponding maps and totals of total particulate matter (PM) emissions using different sources of FRE, and subsequently to simulate the resulting PM(sub 2.5) in the WRF-Chem 3.5 model using emission rates from FEERv1.0 as well as other standard biomass burning emission inventories. An flowchart of the FEER algorithm to calculate Ce is outlined here along with a display of the resulting emissions of total PM globally and also regionally. The modeling results from the WRF-Chem3.5 simulations are also shown.
The Aerosol Single scattering albedo and Height Estimation (ASHE) algorithm was first introduced in Jeong and Hsu (2008) to provide aerosol layer height and single scattering albedo (SSA) for biomass burning smoke aerosols. By using multiple satellite sensors synergistically, ASHE can provide the height information over much broader areas than lidar observations alone. The complete ASHE algorithm uses aerosol data from MODIS or VIIRS, OMI or OMPS, and CALIOP. A simplified algorithm also exists that does not require CALIOP data as long as the SSA of the aerosol layer is provided by another source. Several updates have recently been made: inclusion of dust layers in the retrieval process, better determination of the input aerosol layer height from CALIOP, improvement in aerosol optical depth (AOD) for nonspherical dust, development of quality assurance (QA) procedure, etc.
Fires and the aerosols that they emit impact air quality, health, and climate, but the abundance and properties of carbonaceous aerosol (both black carbon and organic carbon) from biomass burning (BB) remain uncertain and poorly constrained. We aim to explore the uncertainties associated with fire emissions and their air quality and radiative impacts from underlying dry matter consumed and emissions factors. To investigate this, we compare model simulations from a global chemical transport model, GEOS-Chem, driven by a variety of fire emission inventories with surface and airborne observations of black carbon (BC) and organic aerosol (OA) concentrations and satellite-derived aerosol optical depth (AOD). We focus on two fire-detection-based and/or burned-area-based (FD-BA) inventories using burned area and active fire counts, respectively, i.e., the Global Fire Emissions Database version 4 (GFED4s) with small fires and the Fire INventory from NCAR version 1.5 (FINN1.5), and two fire radiative power (FRP)-based approaches, i.e., the Quick Fire Emission Dataset version 2.4 (QFED2.4) and the Global Fire Assimilation System version 1.2 (GFAS1.2). We show that, across the inventories, emissions of BB aerosol (BBA) differ by a factor of 4 to 7 over North America and that dry matter differences, not emissions factors, drive this spread. We find that simulations driven by QFED2.4 generally overestimate BC and, to a lesser extent, OA concentrations observations from two fire-influenced aircraft campaigns in North America (ARCTAS and DC3) and from the Interagency Monitoring of Protected Visual Environments (IMPROVE) network, while simulations driven by FINN1.5 substantially underestimate concentrations. The GFED4s and GFAS1.2-driven simulations provide the best agreement with OA and BC mass concentrations at the surface (IMPROVE), BC observed aloft (DC3 and ARCTAS), and AOD observed by MODIS over North America. We also show that a sensitivity simulation including an enhanced source of secondary organic aerosol (SOA) from fires, based on the NOAA Fire Lab 2016 experiments, produces substantial additional OA; however, the spread in the primary emissions estimates implies that this magnitude of SOA can be neither confirmed nor ruled out when comparing the simulations against the observations explored here. Given the substantial uncertainty in fire emissions, as represented by these four emission inventories, we find a sizeable range in 2012 annual BBA PM2.5 population-weighted exposure over Canada and the contiguous US (0.5 to 1.6 µg/cu. m). We also show that the range in the estimated global direct radiative effect of carbonaceous aerosol from fires (−0.11 to −0.048 W/sq. m) is large and comparable to the direct radiative forcing of OA (−0.09 W/sq. m) estimated in the Fifth Assessment Report (AR5) of the Intergovernmental Panel on Climate Change (IPCC). Our analysis suggests that fire emissions uncertainty challenges our ability to accurately characterize the impact of smoke on air quality and climate.
Background Wildfire events are increasing in frequency and intensity, and aging individuals demonstrate heightened biological susceptibility to air pollution exposures including increased risk of neurological sequelae. Declining ovarian hormones levels that occur with aging in females along with associated systemic physiological and inflammatory changes may contribute to increased cerebral vulnerability to air pollution, representing a potential but underexplored mechanism. Menopause and the menopausal transition represent a period of profound physiological change that affects cardiovascular, neurological, and immune health. Methods We tested whether peri-menopausal–like hormonal status amplifies hippocampal responses to acute wood smoke (WS) using an ovary-intact, 4-vinylcyclohexene diepoxide (VCD) model of moderate accelerated ovarian failure (AOF) in female C57BL/6 mice. Animals were exposed to HEPA-filtered air (FA) or WS for 4 h/day over 2 consecutive days (∼0.5 mg/m³). Exposure characterization confirmed a complex mixture of combustion products with significant levels of both trace metals and gas release during WS exposure. Results Spatial transcriptomics (10x Visium; n = 4 sections/group) with automated cell-type annotation identified astrocytes, GABAergic and glutamatergic neurons, oligodendrocytes, revealed cell type-specific transcriptional alterations following WS exposure. Distinct transcriptional patterns were observed across all identified neuronal and glial cell populations. Conclusion Together, these findings define a cell-type specific transcriptomic framework describing how WS exposure and ovarian hormone decline interact to influence hippocampal responses and identify potential cellular pathways relevant to hippocampal vulnerability.
Biomass burning emits a wide range of carbonaceous particles into the atmosphere and has negative impacts on human health and the Earth’s radiative balance. Nonvolatile spherical organic aerosol particles, commonly known as tar balls, represent one of the most abundant particles in aged biomass burning smoke. However, the detailed molecular-level composition of ambient tar balls is largely unknown but critical to access their environmental impacts. Ambient aerosol samples collected during a wildfire event, which were ~90% tar balls by number fraction, were analyzed using ultrahigh resolution Orbitrap Elite mass spectrometry with four complementary ionization modes. Our results show the molecular composition of tar balls to be complex, composed of over 10,000 molecular formulas. Model estimated saturation mass concentrations and relative humidity dependent glass transition temperatures were consistent with low volatility and solid morphology as expected for tar balls. Room-temperature evaporation kinetics showed that these particles were composed of ~90% non-volatile species. The molecular complexity detected here signifies a continuum of carbonaceous species, ranging from C3 to C45 with continuous ranges of oxygenation and hydrogen saturation for each Cn. Approximately 24% of molecular formulas were estimated the be highly aromatic, which could indicate chemical compounds with negative health effects, and which may contribute to visible light absorption. The carbon continuum observed here has significant implications for the molecular characterization of atmospheric organic matter. The level of complexity detected here should not be ignored in future studies and we demonstrate that multiple analytical methods may be required to suitably interpret this complexity on a molecular level.
Biomass burning (BB) events are occurring globally with increasing frequency, and their emissions are having more impacts on human health and climate. Large ash particles are recognized as a BB product with major influences on soil and water environments. However, fine-ash particles, which have diameters smaller than several microns and characteristic morphologies and compositions (mainly Ca and Mg carbonates), have not yet been explicitly considered as a major BB aerosol component either in field observations or climate models. This study measured BB aerosol samples using transmission electron microscopy (TEM) and ion chromatography during the Fire Influence on Regional to Global Environments and Air Quality (FIREX-AQ) campaign. We show that significant amounts of fine ash-bearing particles are transported >100 km from their fire sources. Our environmental chamber experiments suggest that they can act as cloud condensation and ice nuclei. We also found considerable amounts of fine ash-bearing particles in the TEM samples collected during previous campaigns (Biomass Burning Observation Project and Megacity Initiative: Local and Global Research Observations). These ash particles are commonly mixed with organic matter and make up ~8% and 5% of BB smoke by number and mass, respectively, in samples collected during the FIREX-AQ campaign. The measured ash-mass concentrations are approximately five times and six times greater than those of BB black carbon and potassium, respectively, scaling to an estimated global emission of 11.6 Tg yr -1 with a range of 8.8–16.3 Tg yr -1 . Better characterization and constraints on these fine ash-bearing particles will improve BB aerosol measurements and strengthen assessments of BB impacts on human health and climate.
Abstract Black carbon (BC) is estimated to have the second largest anthropogenic radiative forcing in earth‐systems models (ESMs), but there is significant uncertainty in its impact due to complex mixing with organics. Laboratory‐generated particles show that co‐mixed non‐absorbing material enhances absorption by BC by a factor of 2–3.5 as predicted by optical models. However, weak or no enhancements are often reported for field studies. The cause of lower‐than‐expected absorption is not well understood and implies a lower radiative impact of BC compared to how many ESMs currently treat aerosols. By analyzing BC aerosol particle‐by‐particle we reconcile observed and expected absorption for ambient smoke plumes varying in geographic origin, fuel types, burn conditions, atmospheric age and transport. Although particle‐by‐particle tracking is computationally prohibitive for sophisticated ESMs we show that realistic BC absorption is reliably estimated by bulk properties of the plume providing a suitable parameterization to constrain black carbon radiative forcing.
Low clouds play a key role in the Earth-atmosphere energy balance and influence agricultural production and solar-power generation. Smoke aloft has been found to enhance marine stratocumulus through aerosol-cloud interactions, but its role in regions with strong human activities and complex monsoon circulation remains unclear. Here we show that biomass burning aerosols aloft strongly increase the low cloud coverage over both land and ocean in subtropical southeastern Asia. The degree of this enhancement and its spatial extent are comparable to that in the Southeast Atlantic, even though the total biomass burning emissions in Southeast Asia are only one-fifth of those in Southern Africa. We find that a synergetic effect of aerosol-cloud-boundary layer interaction with the monsoon is the main reason for the strong semi-direct effect and enhanced low cloud formation in southeastern Asia.
Growing evidence indicates that thirdhand smoke (THS) exposure induces many adverse health effects. However, it is unclear how THS exposure affects behavior and how host genetic background modulates phenotypic changes. Here we used the Collaborative Cross (CC) mouse population-based model to assess behavioral alterations immediately after THS exposure from 4 to 9 weeks of age. We first measured anxiety-like behavior in six strains using light/dark box combined with a custom multivariate mouse tracking system. We developed an anxiety risk scoring system based on anxiety-related traits and then evaluated the THS impact on them. THS exposure significantly decreased anxiety risk in CC019 ( P = 0.002) and CC051 ( P = 0.009), but increased anxiety risk in CC036 ( P < 0.001), while the other three strains did not show significant changes in anxiety-related traits. Such differences were driven by female mice for the six measures of anxiety-like behavior. Memory potential was measured in the same cohort of mice using the passive avoidance assay. Both THS-exposed male and female CC019 mice displayed significant memory loss compared to controls while no significant changes were found in the other five strains. This study provides strong evidence that THS exposure leads to strain-dependent changes in anxiety-like behavior and memory, suggesting that host genetic variations play a critical role in individual susceptibility to THS-induced effects.
Laser desorption ionisation, coupled with ultrahigh-resolution mass spectrometry, provides an apt reflection of the physical properties of tar balls in wildfire smoke.
This framework was developed to ingest images/video images to train and test artificial neural network structures for image-based detection of fire and smoke. The code includes data preprocessing, model development, and testing. The framework is designed to work with RGB video imagery.
Residential wood heating lacks real-time particulate matter (PM) monitoring technologies capable of measuring emissions directly from flue gases. This study evaluates the performance of the Octoring, an opacity-based smoke sensor developed to monitor wood heater emissions and provide feedback for improved combustion. The device was tested on catalytic and non-catalytic cordwood heaters and a pellet heater during startup, high-burn, and low-burn phases. Performance was assessed against reference particle instruments and gravimetric measurements using concordance, correlation, and agreement analyses. Results show that temperature-dependent drift is the primary limitation affecting sensor accuracy, with systematic drift observed across ambient and combustion conditions. Agreement with reference instruments ranged from poor to good depending on operating conditions, with the strongest performance observed during pellet heater high-burn operation. These findings establish a performance baseline for opacity-based sensing technologies and identify key areas for further development before practical deployment in residential wood combustion monitoring systems.
Smoking history correlates of selected physiological, biochemical, and anthropometric measures
Wind velocity profiles measured by smoke trail method at Wallops Island, Va., in 1963 and 1964
Wind velocity profiles by smoke trail method for eastern test range