Spatial Distribution of the Annual Atmospheric Carbon Dioxide in the Contiguous USA and Their Controlling Factors

Environmental Modeling & Assessment - Analyzing the geographical distribution of carbon dioxide (CO2) is essential for understanding the influence and structural nature of area-specific...     

Ensemble Modeling of the Baltic Sea Ecosystem to Provide Scenarios for Management

We present a multi-model ensemble study for the Baltic Sea, and investigate the combined impact of changing climate, external nutrient supply, and fisheries on the marine ecosystem. The applied regional climate system model contains state-of-the-art component models for the atmosphere, sea ice, ocean, land surface, terrestrial and marine biogeochemistry, and marine food-web. Time-dependent scenario simulations for the period 1960–2100 are performed and uncertainties of future projections are estimated. In addition, reconstructions since 1850 are carried out to evaluate the models sensitivity to external stressors on long time scales. Information from scenario simulations are used to support decision-makers and stakeholders and to raise awareness of climate change, environmental problems, and possible abatement strategies among the general public using geovisualization. It is concluded that the study results are relevant for the Baltic Sea Action Plan of the Helsinki Commission.     

Modelling spatial patterns of correlations between concentrations of heavy metals in mosses and atmospheric deposition in 2010 across Europe

Background

This paper aims to investigate the correlations between the concentrations of nine heavy metals in moss and atmospheric deposition within ecological land classes covering Europe. Additionally, it is examined to what extent the statistical relations are affected by the land use around the moss sampling sites. Based on moss data collected in 2010/2011 throughout Europe and data on total atmospheric deposition modelled by two chemical transport models (EMEP MSC-E, LOTOS-EUROS), correlation coefficients between concentrations of heavy metals in moss and in modelled atmospheric deposition were specified for spatial subsamples defined by ecological land classes of Europe (ELCE) as a spatial reference system. Linear discriminant analysis (LDA) and logistic regression (LR) were then used to separate moss sampling sites regarding their contribution to the strength of correlation considering the areal percentage of urban, agricultural and forestry land use around the sampling location. After verification LDA models by LR, LDA models were used to transform spatial information on the land use to maps of potential correlation levels, applicable for future network planning in the European Moss Survey.

Results

Correlations between concentrations of heavy metals in moss and in modelled atmospheric deposition were found to be specific for elements and ELCE units. Land use around the sampling sites mainly influences the correlation level. Small radiuses around the sampling sites examined (5 km) are more relevant for Cd, Cu, Ni, and Zn, while the areal percentage of urban and agricultural land use within large radiuses (75–100 km) is more relevant for As, Cr, Hg, Pb, and V. Most valid LDA models pattern with error rates of <?40% were found for As, Cr, Cu, Hg, Pb, and V. Land use-dependent predictions of spatial patterns split up Europe into investigation areas revealing potentially high (=?above-average) or low (=?below-average) correlation coefficients.

Conclusions

LDA is an eligible method identifying and ranking boundary conditions of correlations between atmospheric deposition and respective concentrations of heavy metals in moss and related mapping considering the influence of the land use around moss sampling sites.

     

Using design effects from previous cluster surveys to guide sample size calculation in emergency settings

A good estimate of the design effect is critical for calculating the most efficient sample size for cluster surveys. We reviewed the design effects for seven nutrition and health outcomes from nine population-based cluster surveys conducted in emergency settings. Most of the design effects for outcomes in children, and one-half of the design effects for crude mortality, were below two. A reassessment of mortality data from Kosovo and Badghis, Afghanistan revealed that, given the same number of clusters, changing sample size had a relatively small impact on the precision of the estimate of mortality. We concluded that, in most surveys, assuming a design effect of 1.5 for acute malnutrition in children and two or less for crude mortality would produce a more efficient sample size. In addition, enhancing the sample size in cluster surveys without increasing the number of clusters may not result in substantial improvements in precision.     

Extremes of Temperature, Oxygen and Blooms in the Baltic Sea in a Changing Climate

In the future, the Baltic Sea ecosystem will be impacted both by climate change and by riverine and atmospheric nutrient inputs. Multi-model ensemble simulations comprising one IPCC scenario (A1B), two global climate models, two regional climate models, and three Baltic Sea ecosystem models were performed to elucidate the combined effect of climate change and changes in nutrient inputs. This study focuses on the occurrence of extreme events in the projected future climate. Results suggest that the number of days favoring cyanobacteria blooms could increase, anoxic events may become more frequent and last longer, and salinity may tend to decrease. Nutrient load reductions following the Baltic Sea Action Plan can reduce the deterioration of oxygen conditions.     

Modeling the Baltic Sea eutrophication in a decision support system

SANBALTS (Simple As Necessary Baltic Long-Term Large-Scale) is a model of the coupled nitrogen and phosphorus cycles. This model has been developed as an integral part of the decision support system Marine Research on Eutrophication's Nest with the overall aim to evaluate management options for reducing Baltic Sea eutrophication. Simulated nutrient and oxygen concentrations as well as transport flows and major biogeochemical fluxes can be analyzed in many different ways, including construction of detailed nutrient budgets and tracing the fate of nutrient inputs. The large amounts of data that exist for this sea makes it possible to validate model results with observations. Major biogeochemical properties of the Baltic Sea are discussed through an analyses of model sensitivity to external forcing and internal parameterizations. Model results emphasize two features that are especially important for ecosystem management: i) impacts of local measures would always be modified by the long-range transports from other regions and ii) the response to significant changes in loads would only be seen after several decades.     

Internal ecosystem feedbacks enhance nitrogen-fixing cyanobacteria blooms and complicate management in the Baltic Sea

Eutrophication of the Baltic Sea has potentially increased the frequency and magnitude of cyanobacteria blooms. Eutrophication leads to increased sedimentation of organic material, increasing the extent of anoxic bottoms and subsequently increasing the internal phosphorus loading. In addition, the hypoxic water volume displays a negative relationship with the total dissolved inorganic nitrogen pool, suggesting greater overall nitrogen removal with increased hypoxia. Enhanced internal loading of phosphorus and the removal of dissolved inorganic nitrogen leads to lower nitrogen to phosphorus ratios, which are one of the main factors promoting nitrogenfixing cyanobacteria blooms. Because cyanobacteria blooms in the open waters of the Baltic Sea seem to be strongly regulated by internal processes, the effects of external nutrient reductions are scale-dependent. During longer time scales, reductions in external phosphorus load may reduce cyanobacteria blooms; however, on shorter time scales the internal phosphorus loading can counteract external phosphorus reductions. The coupled processes inducing internal loading, nitrogen removal, and the prevalence of nitrogen-fixing cyanobacteria can qualitatively be described as a potentially self-sustaining "vicious circle." To effectively reduce cyanobacteria blooms and overall signs of eutrophication, reductions in both nitrogen and phosphorus external loads appear essential.     

Utilising of the oiled rolling mills scale in iron ore sintering process

Up to 5% of steel is lost with the scale at hot rolling operation. This waste contains 69-72% of iron in the form of oxides. However, its recycling is confronted with presence of up to 20% of oil and 10% of water. E.g. when the oiled scale is introduced as an additive to the iron ore sintering mixture, incomplete combustion of liberated oil at heating during sintering process creates problems for gas cleaning and may even lead to damage of the equipment. A possibility to improve combustion of the scale's oil at the sintering process by preparation of a mixture with peat was shown in the laboratory experiments. Industrial trials demonstrate possibility to increase the oil combustion degree at sintering 2.7 times as much. Consumption of the oiled scale was increased from zero to 12.8 kg (in a form of scale-peat blend) per ton of sinter, which allows for closing the loop of this waste at the integrated steelmaking factory.