Water-Soluble Organic Components in Aerosols Associated with Savanna Fires in Southern Africa: Identification, Evolution, and Distribution

During the SAFARI 2000 field campaign, both smoke aerosols from savanna fires and haze aerosols in the boundary layer and in the free troposphere were collected from an aircraft in southern Africa. These aerosol samples were analyzed for their water-soluble chemical components, particularly the organic species. A novel technique, electrospray ionization-ion trap mass spectrometry, was used concurrently with an ion chromatography system to analyze for carbohydrate species. Seven carbohydrates, seven organic acids, five metallic elements, and three inorganic anions were identified and quantified. On the average, these 22 species comprised 36% and 27% of the total aerosol mass in haze and smoke aerosols, respectively. For the smoke aerosols, levoglucosan was the most abundant carbohydrate species, while gluconic acid was tentatively identified as the most abundant organic acid. The mass abundance and possible source of each class of identified species are discussed, along with their possible formation pathways. The combustion phase of a fire had an impact on the chemical composition of the emitted aerosols. Secondary formation of sulfate, nitrate, levoglucosan, and several organic acids occurred during the initial aging of smoke aerosols. It is likely that under certain conditions, some carbohydrate species in smoke aerosols, such as levoglucosan, were converted to organic acids during upward transport

Aerosol Properties and Chemical Apportionment of Aerosol Optical Depth at Locations off the U.S. East Coast in July and August 2001

Airborne in situ measurements of vertical profiles of the aerosol light scattering coefficient, light absorption coefficient, and single scattering albedo (ω0) are presented for locations off the East Coast of the United States in July–August 2001. The profiles were obtained in relatively clean air, dominated by airflows that had passed over Canada and the Atlantic Ocean. Comparisons of aerosol optical depths (AODs) at 550 nm derived from airborne in situ and sun-photometer measurements agree, on average, to within 0.034 ± 0.021. A frequency distribution of ω0 measured in the atmospheric boundary layer off the coast yields an average value of ω0 = 0.96 ± 0.03 at 550 nm. Values for the mass scattering efficiencies of sulfate and total carbon (organic and black carbon) derived from a multiple linear regression are 6.0 ± 1.0 m2 (g SO=4)−1 and 2.6 ± 0.9 m2 (g C)−1, respectively. Measurements of sulfate and total carbon mass concentrations are used to estimate the contributions of these two major components of the submicron aerosol to the AOD. Mean percentage contributions to the AOD from sulfate, total carbon, condensed water, and absorbing aerosols are 38% ± 8%, 26% ± 9%, 32% ± 9%, and 4% ± 2%, respectively. The sensitivity of the above results to the assumed values of the hygroscopic growth factors for the particles are examined and it is found that, although the AOD derived from the in situ measurements can vary by as much as 20%, the average value of ω0 is not changed significantly. The results are compared with those obtained in the same region in 1996 under more polluted conditions

A fire model with distinct crop, pasture, and non-agricultural burning: Use of new data and a model-fitting algorithm for FINAL.1

This study describes and evaluates the Fire Including Natural & Agricultural Lands model (FINAL) which, for the first time, explicitly simulates cropland and pasture management fires separately from non-agricultural fires. The non-agricultural fire module uses empirical relationships to simulate burned area in a quasi-mechanistic framework, similar to past fire modeling efforts, but with a novel optimization method that improves the fidelity of simulated fire patterns to new observational estimates of non-agricultural burning. The agricultural fire components are forced with estimates of cropland and pasture fire seasonality and frequency derived from observational land cover and satellite fire datasets. FINAL accurately simulates the amount, distribution, and seasonal timing of burned cropland and pasture over 2001–2009 (global totals: 0:434 x 10^6 and 2:02 x 10^6 km^2 yr-1 modeled, 0:454 x 10^6 and 2:04 x 10^6 km2 yr-1 observed), but carbon emissions for cropland and pasture fire are overestimated (global totals: 0.295 and 0.706 PgCyr-1 modeled, 0.194 and 0.538 PgCyr-1 observed). The non-agricultural fire module underestimates global burned area (1:91 x 10^6 km2 yr-1 modeled, 2:44 x 10^6 km^2 yr-1 observed) and carbon emissions (1.14 PgCyr-1 modeled, 1.84 PgCyr-1 observed). The spatial pattern of total burned area and carbon emissions is generally well reproduced across much of sub-Saharan Africa, Brazil, Central Asia, and Australia, whereas the boreal zone sees underestimates. FINAL represents an important step in the development of global fire models, and offers a strategy for fire models to consider human-driven fire regimes on cultivated lands. At the regional scale, simulations would benefit from refinements in the parameterizations and improved optimization datasets. We include an in-depth discussion of the lessons learned from using the Levenberg–Marquardt algorithm in an interactive optimization for a dynamic global vegetation model

Cytoplasmic p53 couples oncogene-driven glucose metabolism to apoptosis and is a therapeutic target in glioblastoma.

Cross-talk among oncogenic signaling and metabolic pathways may create opportunities for new therapeutic strategies in cancer. Here we show that although acute inhibition of EGFR-driven glucose metabolism induces only minimal cell death, it lowers the apoptotic threshold in a subset of patient-derived glioblastoma (GBM) cells. Mechanistic studies revealed that after attenuated glucose consumption, Bcl-xL blocks cytoplasmic p53 from triggering intrinsic apoptosis. Consequently, targeting of EGFR-driven glucose metabolism in combination with pharmacological stabilization of p53 with the brain-penetrant small molecule idasanutlin resulted in synthetic lethality in orthotopic glioblastoma xenograft models. Notably, neither the degree of EGFR-signaling inhibition nor genetic analysis of EGFR was sufficient to predict sensitivity to this therapeutic combination. However, detection of rapid inhibitory effects on [18F]fluorodeoxyglucose uptake, assessed through noninvasive positron emission tomography, was an effective predictive biomarker of response in vivo. Together, these studies identify a crucial link among oncogene signaling, glucose metabolism, and cytoplasmic p53, which may potentially be exploited for combination therapy in GBM and possibly other malignancies

A multi-ancestry genome-wide study incorporating gene-smoking interactions identifies multiple new loci for pulse pressure and mean arterial pressure

Elevated blood pressure (BP), a leading cause of global morbidity and mortality, is influenced by both genetic and lifestyle factors. Cigarette smoking is one such lifestyle factor. Across five ancestries, we performed a genome-wide gene-smoking interaction study of mean arterial pressure (MAP) and pulse pressure (PP) in 129 913 individuals in stage 1 and follow-up analysis in 480 178 additional individuals in stage 2. We report here 136 loci significantly associated with MAP and/or PP. Of these, 61 were previously published through main-effect analysis of BP traits, 37 were recently reported by us for systolic BP and/or diastolic BP through gene-smoking interaction analysis and 38 were newly identified (P <5 x 10(-8), false discovery rate <0.05). We also identified nine new signals near known loci. Of the 136 loci, 8 showed significant interaction with smoking status. They include CSMD1 previously reported for insulin resistance and BP in the spontaneously hypertensive rats. Many of the 38 new loci show biologic plausibility for a role in BP regulation. SLC26A7 encodes a chloride/bicarbonate exchanger expressed in the renal outer medullary collecting duct. AVPR1A is widely expressed, including in vascular smooth muscle cells, kidney, myocardium and brain. FHAD1 is a long non-coding RNA overexpressed in heart failure. TMEM51 was associated with contractile function in cardiomyocytes. CASP9 plays a central role in cardiomyocyte apoptosis. Identified only in African ancestry were 30 novel loci. Our findings highlight the value of multi-ancestry investigations, particularly in studies of interaction with lifestyle factors, where genomic and lifestyle differences may contribute to novel findings.Peer reviewe

A Global Analysis of Hunter-Gatherers, Broadcast Fire Use, and Lightning-Fire-Prone Landscapes

We examined the relationships between lightning-fire-prone environments, socioeconomic metrics, and documented use of broadcast fire by small-scale hunter-gatherer societies. Our approach seeks to re-assess human-fire dynamics in biomes that are susceptible to lightning-triggered fires. We quantify global lightning-fire-prone environments using mean monthly lightning and climatological flammability, and then compare how well those environments and socioeconomic variables (population density, mobility, and subsistence type) serve as predictors of observed broadcast fire use from the ethnographic data. We use a logistic model for all vegetated, forested, and unforested biomes. Our global analysis of human-fire-landscape interaction in three hundred and thirty-nine hunter-gatherer groups demonstrates that lightning-fire-prone environments strongly predict for hunter-gatherer fire use. While we do not maintain that lightning-fire-prone environments determine the use of fire by small societies, they certainly appear to invite its use. Our results further suggest that discounting or ignoring human agency contradicts empirical evidence that hunter-gatherers used fire even in locations where lightning could explain the presence of fire. Paleoecological research on fire and hypothesis testing using global fire modeling should consider insights from human ecology in the interpretation of data and results. More broadly, our results suggest that small-scale societies can provide insight into sustainable fire management in lightning-fire-prone landscapes

A fire model with distinct crop, pasture, and non-agricultural burning: use of new data and a model-fitting algorithm for FINAL.1

This study describes and evaluates the Fire Including Natural & Agricultural Lands model (FINAL) which, for the first time, explicitly simulates cropland and pasture management fires separately from non-agricultural fires. The non-agricultural fire module uses empirical relationships to simulate burned area in a quasi-mechanistic framework, similar to past fire modeling efforts, but with a novel optimization method that improves the fidelity of simulated fire patterns to new observational estimates of non-agricultural burning. The agricultural fire components are forced with estimates of cropland and pasture fire seasonality and frequency derived from observational land cover and satellite fire datasets. FINAL accurately simulates the amount, distribution, and seasonal timing of burned cropland and pasture over 2001–2009 (global totals: 0:434 x 10^6 and 2:02 x 10^6 km^2 yr-1 modeled, 0:454 x 10^6 and 2:04 x 10^6 km2 yr-1 observed), but carbon emissions for cropland and pasture fire are overestimated (global totals: 0.295 and 0.706 PgCyr-1 modeled, 0.194 and 0.538 PgCyr-1 observed). The non-agricultural fire module underestimates global burned area (1:91 x 10^6 km2 yr-1 modeled, 2:44 x 10^6 km^2 yr-1 observed) and carbon emissions (1.14 PgCyr-1 modeled, 1.84 PgCyr-1 observed). The spatial pattern of total burned area and carbon emissions is generally well reproduced across much of sub-Saharan Africa, Brazil, Central Asia, and Australia, whereas the boreal zone sees underestimates. FINAL represents an important step in the development of global fire models, and offers a strategy for fire models to consider human-driven fire regimes on cultivated lands. At the regional scale, simulations would benefit from refinements in the parameterizations and improved optimization datasets. We include an in-depth discussion of the lessons learned from using the Levenberg–Marquardt algorithm in an interactive optimization for a dynamic global vegetation model