Source apportionment of circum-Arctic atmospheric black carbon from isotopes and modeling

Black carbon (BC) contributes to Arctic climate warming, yet source attributions are inaccurate due to lacking observational constraints and uncertainties in emission inventories. Year-round, isotope-constrained observations reveal strong seasonal variations in BC sources with a consistent and synchronous pattern at all Arctic sites. These sources were dominated by emissions from fossil fuel combustion in the winter and by biomass burning in the summer. The annual mean source of BC to the circum-Arctic was 39 ± 10% from biomass burning. Comparison of transport-model predictions with the observations showed good agreement for BC concentrations, with larger discrepancies for (fossil/biomass burning) sources. The accuracy of simulated BC concentration, but not of origin, points to misallocations of emissions in the emission inventories. The consistency in seasonal source contributions of BC throughout the Arctic provides strong justification for targeted emission reductions to limit the impact of BC on climate warming in the Arctic and beyond

Identifying Unique Neighborhood Characteristics to Guide Health Planning for Stroke and Heart Attack: Fuzzy Cluster and Discriminant Analyses Approaches

Socioeconomic, demographic, and geographic factors are known determinants of stroke and myocardial infarction (MI) risk. Clustering of these factors in neighborhoods needs to be taken into consideration during planning, prioritization and implementation of health programs intended to reduce disparities. Given the complex and multidimensional nature of these factors, multivariate methods are needed to identify neighborhood clusters of these determinants so as to better understand the unique neighborhood profiles. This information is critical for evidence-based health planning and service provision. Therefore, this study used a robust multivariate approach to classify neighborhoods and identify their socio-demographic characteristics so as to provide information for evidence-based neighborhood health planning for stroke and MI.The study was performed in East Tennessee Appalachia, an area with one of the highest stroke and MI risks in USA. Robust principal component analysis was performed on neighborhood (census tract) socioeconomic and demographic characteristics, obtained from the US Census, to reduce the dimensionality and influence of outliers in the data. Fuzzy cluster analysis was used to classify neighborhoods into Peer Neighborhoods (PNs) based on their socioeconomic and demographic characteristics. Nearest neighbor discriminant analysis and decision trees were used to validate PNs and determine the characteristics important for discrimination. Stroke and MI mortality risks were compared across PNs. Four distinct PNs were identified and their unique characteristics and potential health needs described. The highest risk of stroke and MI mortality tended to occur in less affluent PNs located in urban areas, while the suburban most affluent PNs had the lowest risk.Implementation of this multivariate strategy provides health planners useful information to better understand and effectively plan for the unique neighborhood health needs and is important in guiding resource allocation, service provision, and policy decisions to address neighborhood health disparities and improve population health

Neighborhood disparities in stroke and myocardial infarction mortality: a GIS and spatial scan statistics approach

<p>Abstract</p> <p>Background</p> <p>Stroke and myocardial infarction (MI) are serious public health burdens in the US. These burdens vary by geographic location with the highest mortality risks reported in the southeastern US. While these disparities have been investigated at state and county levels, little is known regarding disparities in risk at lower levels of geography, such as neighborhoods. Therefore, the objective of this study was to investigate spatial patterns of stroke and MI mortality risks in the East Tennessee Appalachian Region so as to identify neighborhoods with the highest risks.</p> <p>Methods</p> <p>Stroke and MI mortality data for the period 1999-2007, obtained free of charge upon request from the Tennessee Department of Health, were aggregated to the census tract (neighborhood) level. Mortality risks were age-standardized by the direct method. To adjust for spatial autocorrelation, population heterogeneity, and variance instability, standardized risks were smoothed using Spatial Empirical Bayesian technique. Spatial clusters of high risks were identified using spatial scan statistics, with a discrete Poisson model adjusted for age and using a 5% scanning window. Significance testing was performed using 999 Monte Carlo permutations. Logistic models were used to investigate neighborhood level socioeconomic and demographic predictors of the identified spatial clusters.</p> <p>Results</p> <p>There were 3,824 stroke deaths and 5,018 MI deaths. Neighborhoods with significantly high mortality risks were identified. Annual stroke mortality risks ranged from 0 to 182 per 100,000 population (median: 55.6), while annual MI mortality risks ranged from 0 to 243 per 100,000 population (median: 65.5). Stroke and MI mortality risks exceeded the state risks of 67.5 and 85.5 in 28% and 32% of the neighborhoods, respectively. Six and ten significant (p < 0.001) spatial clusters of high risk of stroke and MI mortality were identified, respectively. Neighborhoods belonging to high risk clusters of stroke and MI mortality tended to have high proportions of the population with low education attainment.</p> <p>Conclusions</p> <p>These methods for identifying disparities in mortality risks across neighborhoods are useful for identifying high risk communities and for guiding population health programs aimed at addressing health disparities and improving population health.</p

Research that Facilitates Praxis and Praxis Development

acceptedVersionPeer reviewe

Distinguishing between old and modern permafrost sources in the northeast Siberian land-shelf system with compound-specific δ2H analysis

Pleistocene ice complex permafrost deposits contain roughly a quarter of the organic carbon (OC) stored in permafrost (PF) terrain. When permafrost thaws, its OC is remobilized into the (aquatic) environment where it is available for degradation, transport or burial. Aquatic or coastal environments contain sedimentary reservoirs that can serve as archives of past climatic change. As permafrost thaw is increasing throughout the Arctic, these reservoirs are important locations to assess the fate of remobilized permafrost OC. We here present compound-specific deuterium (δ2H) analysis on leaf waxes as a tool to distinguish between OC released from thawing Pleistocene permafrost (ice complex deposits; ICD) and from thawing Holocene permafrost (from near-surface soils). Bulk geochemistry (%OC; δ13C; %total nitrogen, TN) was analyzed as well as the concentrations and δ2H signatures of long-chain n-alkanes (C21 to C33) and mid- to long-chain n-alkanoic acids (C16 to C30) extracted from both ICD-PF samples (n Combining double low line 9) and modern vegetation and O-horizon (topsoil-PF) samples (n Combining double low line 9) from across the northeast Siberian Arctic. Results show that these topsoil-PF samples have higher %OC, higher OC/TN values and more depleted δ13C-OC values than ICD-PF samples, suggesting that these former samples trace a fresher soil and/or vegetation source. Whereas the two investigated sources differ on the bulk geochemical level, they are, however, virtually indistinguishable when using leaf wax concentrations and ratios. However, on the molecular isotope level, leaf wax biomarker δ2H values are statistically different between topsoil PF and ICD PF. For example, the mean δ2H value of C29 n-alkane was -246±13‰ (mean±SD) for topsoil PF and -280±12‰ for ICD PF. With a dynamic isotopic range (difference between two sources) of 34 to 50‰; the isotopic fingerprints of individual, abundant, biomarker molecules from leaf waxes can thus serve as endmembers to distinguish between these two sources. We tested this molecular δ2H tracer along with another source-distinguishing approach, dual-carbon (δ13C-Δ14C) isotope composition of bulk OC, for a surface sediment transect in the Laptev Sea. Results show that general offshore patterns along the shelf-slope transect are similar, but the source apportionment between the approaches vary, which may highlight the advantages of either. This study indicates that the application of δ2H leaf wax values has potential to serve as a complementary quantitative measure of the source and differential fate of OC thawed out from different permafrost compartments