ALBERT

Beschreibung: Differential exposure to multiple environmental burdens and benefits and their distribution across a population with varying vulnerability can contribute heavily to health inequalities. Particularly relevant are areas with high cumulative burdens and high social vulnerability termed as “hotspots”. This paper develops an index-based approach to assess these multiple burdens and benefits in combination with vulnerability factors at detailed intra-urban level. The method is applied to the city of Dortmund, Germany. Using non-spatial and spatial methods we assessed inequalities and identified “hotspot” areas in the city. We found modest inequalities burdening higher vulnerable groups in Dortmund (CI = −0.020 at p 〈 0.05). At the detailed intra-urban level, however, inequalities showed strong geographical patterns. Large numbers of “hotspots” exist in the northern part of the city compared to the southern part. A holistic assessment, particularly at a detailed local level, considering both environmental burdens and benefits and their distribution across the population with the different vulnerability, is essential to inform environmental justice debates and to mobilize local stakeholders. Locating “hotspot” areas at this detailed spatial level can serve as a basis to develop interventions that target vulnerable groups to ensure a health conducive equal environment.

Beschreibung: The goal of the study was to assess the quality of life (QOL) and depression and provide further insights into the relationship between QOL and depression among community-dwelling elderly Chinese people. Baseline data were collected from 1168 older adults (aged ≥ 60) in a large, prospective cohort study on measurement and evaluation of health-promoting and health-protecting behaviors intervention on chronic disease in different community-dwelling age groups. QOL was assessed using the 26-item, World Health Organization Quality of Life, brief version (WHOQOL-BREF) and depression was assessed using the 30-item Geriatric Depression Scale (GDS). The mean WHOQOL-BREF score for all dimensions was approximately 60, with the highest mean value (61.92) observed for social relationships, followed by environment, physical health, and psychological health domains. In this cohort, 26.1% of elderly urban adults met GDS criteria for depression. There were negative correlations between physical health (Odds Ratio (OR) = 0.928, 95% Confidence Interval (CI): 0.910–0.946), psychological health (OR = 0.906, 95% CI: 0.879–0.934), environment (OR = 0.966, 95% CI: 0.944–0.989) and depression among elderly people. Those with depression were older, less educated, had a lower monthly income, and were more likely to report insomnia. All WHOQOL-BREF domains, with the exception of the social domain were negatively correlated with depression.

Beschreibung: Background: Measuring mercury in newborn bloodspots to determine fetal exposures is a novel methodology with many advantages. Questions remain, however, about its reliability as an estimate of newborn exposure to mercury. Methods: We studied mercury concentrations in paired bloodspots and cord blood from a convenience sample of 48 Minnesota women and infants. Results: The limit of detection for bloodspots was higher than for cord blood (0.7 and 0.3 μg/L in bloodspots and cord blood, respectively) with the result that mercury was detected in only 38% of newborn bloodspots compared to 62% of cord blood samples. The geometric mean mercury concentration in cord blood was 0.6 μg/L. Mercury concentrations were almost uniformly lower in bloodspots than in cord blood (mean ratio (±SD) = 0.85 ± 0.4), their mean value was significantly less than that for the cord blood (p = 0.02), and the two methods were highly correlated (r = 0.82). Conclusion: These preliminary findings indicate that newborn bloodspot mercury measurements have utility; however, until bloodspot analyses are more sensitive, they are likely to underestimate in utero exposure.

Beschreibung: Materials based on biodegradable polyesters, such as poly(butylene terephthalate) (PBT) or poly(butylene terephthalate-co-poly(alkylene glycol) terephthalate) (PBTAT), have potential application as pro-regenerative scaffolds for bone tissue engineering. Herein, the preparation of films composed of PBT or PBTAT and an engineered spider silk protein, (eADF4(C16)), that displays multiple carboxylic acid moieties capable of binding calcium ions and facilitating their biomineralization with calcium carbonate or calcium phosphate is reported. Human mesenchymal stem cells cultured on films mineralized with calcium phosphate show enhanced levels of alkaline phosphatase activity suggesting that such composites have potential use for bone tissue engineering.

Beschreibung: Bioleaching is the mobilization of metal cations from insoluble ores by microorganisms. Biofilms can enhance this process. Since Sulfobacillus often appears in leaching heaps or reactors, this genus has aroused attention. In this study, biofilm formation and subsequent pyrite dissolution by the Gram-positive, moderately thermophilic acidophile Sulfobacillus thermosulfidooxidans were investigated. Five strategies, including adjusting initial pH, supplementing an extra energy source or ferric ions, as well as exchanging exhausted medium with fresh medium, were tested for enhancement of its biofilm formation. The results show that regularly exchanging exhausted medium leads to a continuous biofilm development on pyrite. By this way, multiply layered biofilms were observed on pyrite slices, while only monolayer biofilms were visible on pyrite grains. In addition, biofilms were proven to be responsible for pyrite leaching in the early stages.

Beschreibung: The objective of this study was to assess the performance of the simulated start of the photosynthetically active season by a large-scale biosphere model in boreal forests in Finland with remote sensing observations. The start of season for two forest types, evergreen needle- and deciduous broad-leaf, was obtained for the period 2003–2011 from regional JSBACH (Jena Scheme for Biosphere–Atmosphere Hamburg) runs, driven with climate variables from a regional climate model. The satellite-derived start of season was determined from daily Moderate Resolution Imaging Spectrometer (MODIS) time series of Fractional Snow Cover and the Normalized Difference Water Index by applying methods that were targeted to the two forest types. The accuracy of the satellite-derived start of season in deciduous forest was assessed with bud break observations of birch and a root mean square error of seven days was obtained. The evaluation of JSBACH modelled start of season dates with satellite observations revealed high spatial correspondence. The bias was less than five days for both forest types but showed regional differences that need further consideration. The agreement with satellite observations was slightly better for the evergreen than for the deciduous forest. Nonetheless, comparison with gross primary production (GPP) determined from CO2 flux measurements at two eddy covariance sites in evergreen forest revealed that the JSBACH-simulated GPP was higher in early spring and led to too-early simulated start of season dates. Photosynthetic activity recovers differently in evergreen and deciduous forests. While for the deciduous forest calibration of phenology alone could improve the performance of JSBACH, for the evergreen forest, changes such as seasonality of temperature response, would need to be introduced to the photosynthetic capacity to improve the temporal development of gross primary production.

Beschreibung: An innovative remote sensing approach that combines land-use change and water quality information is proposed in order to investigate if Artisanal and Small-scale Gold Mining (ASGM) area extension is associated with water siltation in the Tapajós River Basin (Brazil), containing the largest small-scale gold mining district in the world. Taking advantage of a 40-year period of the multi-satellite imagery archive, the objective of this paper is to build a normalized time-series in order to evaluate the influence of temporal mining expansion on the water siltation data (TSS, Total Suspended Solids concentration) derived from previous research. The methodological approach was set to deliver a full characterization of the ASGM expansion from its initial stages in the early 1970s to the present. First, based on IRS/LISSIII images acquired in 2012, the historical Landsat image database (1973–2001) was corrected for radiometric and atmospheric effects using dark vegetation as reference to create a normalized time-series. Next, a complete update of the mining areas distribution in 2012 derived from the TerraClass Project (an official land-use classification for the Brazilian Amazon) was conducted having IRS/LISSIII as the base map with the support of auxiliary data and vector editing. Once the ASGM in 2012 was quantified (261.7 km2) and validated with photos, a reverse classification of ASGM in 2001 (171.7 km2), 1993 (166.3 km2), 1984 (47.5 km2), and 1973 (15.4 km2) with the use of Landsat archives was applied. This procedure relies on the assumption that ASGM changes in the land cover are severe and remain detectable from satellite sensors for decades. The mining expansion area over time was then combined with the (TSS) data retrieved from the same atmospherically corrected satellite imagery based on the literature. In terms of gold mining expansion and water siltation effects, four main periods of ASGM activities were identified in the study area: (i) 1958–1977, first occurrence of mining activities and low water impacts; (ii) 1978–1993, introduction of low-budget mechanization associated with very high gold prices resulting in large mining area expansion and high water siltation levels; (iii) 1994–2003, general recession of ASGM activities and exhaustion of easy-access gold deposits, resulting in decreased TSS; (iv) 2004 to present, intensification of ASGM encouraged by high gold prices, resulting in an increase of TSS.

Beschreibung: Current earth observation models do not take into account the influence of water salinity on the evaporation rate, even though the salinity influences the evaporation rate by affecting the density and latent heat of vaporization. In this paper, we adapt the SEBS (Surface Energy Balance System) model for large water bodies and add the effect of water salinity to the evaporation rate. Firstly, SEBS is modified for fresh-water whereby new parameterizations of the water heat flux and sensible heat flux are suggested. This is achieved by adapting the roughness heights for momentum and heat transfer. Secondly, a salinity correction factor is integrated into the adapted model. Eddy covariance measurements over Lake IJsselmeer (The Netherlands) are carried out and used to estimate the roughness heights for momentum (~0.0002 m) and heat transfer (~0.0001 m). Application of these values over the Victoria and Tana lakes (freshwater) in Africa showed that the calculated latent heat fluxes agree well with the measurements. The root mean-square of relative-errors (rRMSE) is about 4.1% for Lake Victoria and 4.7%, for Lake Tana. Verification with ECMWF data showed that the salinity reduced the evaporation at varying levels by up to 27% in the Great Salt Lake and by 1% for open ocean. Our results show the importance of salinity to the evaporation rate and the suitability of the adapted-SEBS model (AquaSEBS) for fresh and saline waters.

Beschreibung: Area-based analyses of airborne laser scanning (ALS) data are an established approach to obtain wall-to-wall predictions of forest characteristics for vast areas. The analyses of sparse data in particular are based on the height value distributions, which do not produce optimal information on the horizontal forest structure. We evaluated the complementary potential of features quantifying the textural variation of ALS-based canopy height models (CHMs) for both supervised (linear regression) and unsupervised (k-Means clustering) analyses. Based on a comprehensive literature review, we identified a total of four texture analysis methods that produced rotation-invariant features of different order and scale. The CHMs and the textural features were derived from practical sparse-density, leaf-off ALS data originally acquired for ground elevation modeling. The features were extracted from a circular window of 254 m2 and related with boreal forest characteristics observed from altogether 155 field sample plots. Features based on gray-level histograms, distribution of forest patches, and gray-level co-occurrence matrices were related with plot volume, basal area, and mean diameter with coefficients of determination (R2) of up to 0.63–0.70, whereas features that measured the uniformity of local binary patterns of the CHMs performed poorer. Overall, the textural features compared favorably with benchmark features based on the point data, indicating that the textural features contain additional information useful for the prediction of forest characteristics. Due to the developed processing routines for raster data, the CHM features may potentially be extracted with a lower computational burden, which promotes their use for applications such as pre-stratification or guiding the field plot sampling based solely on ALS data.

Beschreibung: Presence of speech and motion artifacts has been shown to impact the performance of wearable sensor systems used for automatic detection of food intake. This work presents a novel wearable device which can detect food intake even when the user is physically active and/or talking. The device consists of a piezoelectric strain sensor placed on the temporalis muscle, an accelerometer, and a data acquisition module connected to the temple of eyeglasses. Data from 10 participants was collected while they performed activities including quiet sitting, talking, eating while sitting, eating while walking, and walking. Piezoelectric strain sensor and accelerometer signals were divided into non-overlapping epochs of 3 s; four features were computed for each signal. To differentiate between eating and not eating, as well as between sedentary postures and physical activity, two multiclass classification approaches are presented. The first approach used a single classifier with sensor fusion and the second approach used two-stage classification. The best results were achieved when two separate linear support vector machine (SVM) classifiers were trained for food intake and activity detection, and their results were combined using a decision tree (two-stage classification) to determine the final class. This approach resulted in an average F1-score of 99.85% and area under the curve (AUC) of 0.99 for multiclass classification. With its ability to differentiate between food intake and activity level, this device may potentially be used for tracking both energy intake and energy expenditure.