Vertical physicochemical parameter distributions and health risk assessment for trace metals in water columns in eastern Lake Tanganyika,Tanzania

The vertical distributions of trace metals and physicochemical parameters in water columns in Kigoma Bay and Kungwe Bay in eastern Lake Tanganyika, Tanzania, were studied. The Al, Ba, Ca, Co,K, Mg, Mn, Mo, Na, Sn, Sr, and V concentrations were low and varied very little with depth. The toxic heavy metal(As, Cr, Cu, Ni, Pb, and Zn) concentrations were relatively high in the surface water, and the Cu, Ni, Pb, and Zn concentrations decreased with depth. Principal component and cluster analyses indicated that the metals in the lake had three main sources. Al, Ba, Ca, Co, Cu, Cr, Mn, Sr, Sn, and V were found to be geogenic; As, Cr, Cu, Mo, Ni, Pb, Sn and Zn anthropogenic; and As, Ca, Co, Mg, and Na biogenic.Human health risk assessments were performed, and it was found that trace metals in the water at most of the sampling sites would cause no potential adverse ef fects or non-carcinogenic health risks through dermal contact or ingestion. However, trace metals in surface water in Kungwe Bay could have certain adverse ef fects on human health through the ingestion pathway(the total hazard quotient for ingestion(ΣHQi ng)was 1.75(a value 1 was de?ned as possibly indicating adverse ef fects). The Pb HQi ng for surface water in Kungwe Bay was 1.50 and contributed 80% of the ΣHQ_(ing_, implying that Pb pollution is a water quality and safety problem that needs to be carefully monitored and the potential sources identi?ed.     

Evaluation of Hydraulic Conductivity Estimates from Various Approaches with Groundwater Flow Models

Significant efforts have been expended for improved characterization of hydraulic conductivity (K) and specific storage (S_s) to better understand groundwater flow and contaminant transport processes. Conventional methods including grain size analyses (GSA), permeameter, slug, and pumping tests have been utilized extensively, while Direct Push-based Hydraulic Profiling Tool (HPT) surveys have been developed to obtain high-resolution K estimates. Moreover, inverse modeling approaches based on geology-based zonations, and highly parameterized Hydraulic Tomography (HT) have also been advanced to map spatial variations of K and S_s between and beyond boreholes. While different methods are available, it is unclear which one yields K estimates that are most useful for high resolution predictions of groundwater flow. Therefore, the main objective of this study is to evaluate various K estimates at a highly heterogeneous field site obtained with three categories of characterization techniques including: (1) conventional methods (GSA, permeameter, and slug tests); (2) HPT surveys; and (3) inverse modeling based on geology-based zonations and highly parameterized approaches. The performance of each approach is first qualitatively analyzed by comparing K estimates to site geology. Then, steady-state and transient groundwater flow models are employed to quantitatively assess various K estimates by simulating pumping tests not used for parameter estimation. Results reveal that inverse modeling approaches yield the best drawdown predictions under both steady and transient conditions. In contrast, conventional methods and HPT surveys yield biased predictions. Based on our research, it appears that inverse modeling and data fusion are necessary steps in predicting accurate groundwater flow behavior.     

Dynamical lifetime survey of geostationary transfer orbits

In this paper, we study the long-term dynamical evolution of highly elliptical orbits in the medium-Earth orbit region around the Earth. The real population consists primarily of Geosynchronous Transfer Orbits (GTOs), launched at specific inclinations, Molniya-type satellites and related debris. We performed a suite of long-term numerical integrations (up to 200 years) within a realistic dynamical model, aimed primarily at recording the dynamical lifetime of such orbits (defined as the time needed for atmospheric reentry) and understanding its dependence on initial conditions and other parameters, such as the area-to-mass ratio (A / m). Our results are presented in the form of 2-D lifetime maps, for different values of inclination, A / m, and drag coefficient. We find that the majority of small debris (\(>70\%\), depending on the inclination) can naturally reenter within 25–90 years, but these numbers are significantly less optimistic for large debris (e.g., upper stages), with the notable exception of those launched from high latitude (Baikonur). We estimate the reentry probability and mean dynamical lifetime for different classes of GTOs and we find that both quantities depend primarily and strongly on initial perigee altitude. Atmospheric drag and higher A / m values extend the reentry zones, especially at low inclinations. For high inclinations, this dependence is weakened, as the primary mechanisms leading to reentry are overlapping lunisolar resonances. This study forms part of the EC-funded (H2020) “ReDSHIFT” project.     

Particulate organic matter and ballast fluxes measured using time-series and settling velocity sediment traps in the northwestern Mediterranean Sea

Prompted by recent data analyses suggesting that the flux of particulate organic carbon sinking into deep waters is determined by fluxes of mineral ballasts, we undertook a study of the relationships among organic matter (OM), calcium carbonate, opal, lithogenic material, and excess aluminum fluxes as part of the MedFlux project. We measured fluxes of particulate components during Spring and Summer of 2003, and Spring of 2005, using a swimmer-excluding sediment trap design capable of measuring fluxes both in a time-series (TS) mode and in a configuration for obtaining particle settling velocity (SV) profiles. On the basis of these studies, we suggest that distinct OM–ballast associations observed in particles sinking at a depth of 200 m imply that the mechanistic basis of the organic matter–ballast association is set in the upper water column above the Twilight Zone, and that the importance of different ballast types follows the seasonal succession of phytoplankton. As in other studies, carbonate appears to enhance the flux of organic matter over opal. Particles must be at least half organic matter before their settling velocity is affected by ballast concentration. This lack of change in ballast composition with SV in particles with <40% OM content suggests that particle SV reaches a maximum because of the increasing importance of inertial drag. Relative amounts of OM and opal decrease with depth due to decomposition and dissolution; carbonates and lithogenic material contribute about the same amount to total mass, or increase slightly, throughout the water column. The high proportion of excess Al cannot be explained by its incorporation into diatom opal or reverse weathering, so Al is most likely adsorbed to particulate oxides. On shorter time scales, dust appears to increase particle flux through its role in aggregation rather than by nutrient inputs enhancing productivity. We suggest that the role of dust as a catalyst in particle formation may be a central mechanism in flux formation in this region, particularly when zooplankton fecal pellet production is low.     

The Effects of Quality Control on Decreasing Error Propagation in the LandScan USA Population Distribution Model: A Case Study of Philadelphia County

LandScan USA is a 90 m population distribution model that is used for a variety of applications, including emergency management. Models should have a measure of accuracy; however, the accuracy of population distribution models is difficult to determine due to the inclusion of multiple input datasets and the lack of quantifiable, observable (validated) data to confirm model output. Validated data enables quantification of: (1) overall model accuracy and (2) changes in model output at different levels of quality control. This article examines the effect of quality control for two national school datasets incorporated as input in LandScan USA for Philadelphia County, Pennsylvania; which had a local, validated school dataset available. The effect of each stage of quality control efforts utilized throughout the LandScan USA process were assessed to determine what level of quality control was required to have a statistically significant change of the model's population distribution. The typical level of quality control for LandScan USA resulted in 36% of schools being moved to the correct location and 20% of missing student enrollments were found, compared to 87% and 98% respectively for the validated dataset. The costs of increasing quality control resulted in a six-fold increase in labor time; however, the additional quality control did not produce statistically significant improvements in the LandScan USA model. Thus, typical quality control efforts for schools in LandScan USA produced a population distribution similar to the validated level of quality control, and can be applied with confidence for policy, planning, and emergency situations.