Comparative life cycle analysis of municipal waste management systems: Kırklareli/Turkey case study

Environmental Science and Pollution Research - Waste-to-energy approaches are becoming increasingly important around the world, and municipal solid waste (MSW) as a renewable and sustainable energy...     

Removal efficiency of emerging micropollutants in biofilter wastewater treatment plants in tropical areas

Environmental Science and Pollution Research - We studied the removal of 61 emerging micropollutants, including illicit drugs, in a biofilter wastewater treatment plant located in the French Indies...     

Identification of structural breaks in the forest product markets: how sensitive are to changes in the Nordic region?

Forests play a fundamental role in the global carbon cycle and can be managed to mitigate greenhouse gas emissions and conserve or sequester carbon. Global policy and environmental changes can affect regional consumption of forest products, as well as inter-regional trade of forest goods and services. This study analyzes global and regional change impacts on the production, consumption and trade of forest products in two Nordic countries, Finland and Sweden. Annual data on removal and trade (1964–2012) for roundwood and sawnwood is used to identify structural breaks based on Chow tests. According to the analysis, the time period is divided into two periods: t1 (1964–1980) and t2 (1981–2012). In the first period, breaks occurred in 1975 and 1976 in the Finnish model and no break is found in the Swedish model. In the second period, we identify breaks in 1991 and 1992 for the Finnish model and in 2004, 2005 and 2006 for the Swedish model. Although our findings have broad empirical support, we do not identify any specific incident as a direct cause of the changes in the consumption and trade patterns of the two types of wood in these countries. The models and analysis presented here can serve as methodological tools for policymakers to better understand the effects of structural changes in the production of forest goods and services in the Nordic region and globally.     

Surface lipids of queen-laid eggs do not regulate queen production in a fission-performing ant

In animal societies, most collective and individual decision making depends on the presence of reproductive individuals. The efficient transmission of information among reproductive and non-reproductive individuals is therefore a determinant of colony organization. In social insects, the presence of a queen modulates multiple colonial activities. In many species, it negatively affects worker reproduction and the development of diploid larvae into future queens. The queen mostly signals her presence through pheromone emission, but the means by which these chemicals are distributed in the colony are still unclear. In several ant species, queen-laid eggs are the vehicle of the queen signal. The aim of this study was to investigate whether queen-laid eggs of the ant Aphaenogaster senilis possess queen-specific cuticular hydrocarbons and/or Dufour or poison gland compounds, and whether the presence of eggs inhibited larval development into queens. Our results show that the queen- and worker-laid eggs shared cuticular and Dufour hydrocarbons with the adults; however, their poison gland compounds were not similar. Queen-laid eggs had more dimethylalkanes and possessed a queen-specific mixture of cuticular hydrocarbons composed of 3,11?+?3,9?+?3,7-dimethylnonacosane, in higher proportions than did worker-laid eggs. Even though the queen-laid eggs were biochemically similar to the queen, their addition to experimentally queenless groups did not prevent the development of new queens. More studies are needed on the means by which queen ant pheromones are transmitted in the colony, and how these mechanisms correlates with life history traits.     

An environmental impact assessment of quantum dot photovoltaics (QDPV) from raw material acquisition through use

Some emerging technologies are expected to be pivotal for solving many of the environmental challenges faced today, especially those related to energy. However, many of these technologies may incur significant environmental impacts over their life cycle, while having environmental benefits during their use. This paper presents results of a Life Cycle Assessment (LCA) of a proposed type of nanophotovoltaic, quantum dot photovoltaic (QDPV) module. The LCA is confined to the stages of raw materials acquisition, manufacturing, and use. The impacts of QDPV are compared with other types of PV modules and energy sources - both renewable and nonrenewable. To provide a comprehensive comparative assessment, QDPV modules were compared with mature as well as emerging PV types for which data are available. Comparative assessment with other types of energy sources includes coal, oil, lignite, natural gas, diesel, nuclear, wind, and hydropower.QDPV modules may have the potential to overcome two current barriers of solar technology: low efficiencies and high manufacturing costs. If higher efficiencies are realized, QDPV modules could pave the way to large scale implementation of solar energy, helping nations move toward greater energy independence. On the other hand, candidate materials as quantum dots for solar cell applications are mostly compound semiconductors such as cadmium selenide, cadmium telluride, and lead sulfide which may be toxic and for which renewable options are limited. Toxic effects of these materials may be exacerbated by their nanoscale features.The LCA was carried out using the software SimaPro, and the Ecoinvent Life Cycle Inventory (LCI) database supplemented with available literature and patent information. Our results indicate that while QDPV modules have shorter Energy PayBack Time (EPBT), lower Global Warming Potential (GWP), SO_x and NO_x emissions than other types of PV modules, they have higher heavy metal emissions, underscoring the need for investigation of emerging technologies, especially nano-based ones, from a life cycle perspective. QDPV modules are better in all impact categories assessed than carbon-based energy sources but they have longer EPBT than wind and hydropower and higher GWP.     

Earthworm cast production as a new behavioural biomarker for toxicity testing

There is currently a lack of ecotoxicity tests adapted to earthworm species of higher ecological relevance and whose endpoints could be directly related to their ecological role in the soil. We propose a new and relatively simple ecotoxicity test based on the estimation of cast production (CP) by Lumbricus terrestris under laboratory conditions. CP was found to be linearly correlated to earthworm biomass and to be greatly influenced by soil water content. Azinphos-methyl had no effect on CP at all the concentrations tested. Significant decreases were observed at the normal application rate for other pesticides with (imidacloprid, carbaryl, methomyl) or without (ethyl-parathion and chlorpyrifos-ethyl) a clear concentration-effect response. For the highest concentration tested, reduction in CP varied between 35 and 67%. CP is straightforward and rapidly measured and ecologically meaningful. We thus believe it to be of great use as an endpoint in ecotoxicity testing.     

Robust optimization evaluation of reliance on locally produced foods

While local food production may be beneficial in terms of developing the local economy and reducing greenhouse gases from transportation, sustainability strategies focused on local food production may generate their own risks due to yield variability. We have developed a robust optimization (RO) model to determine the minimum amount of land (cropland and pasture) required to grow food items that would satisfy a local population’s (accounting for gender and age) calorie and nutrient needs. This model has been applied to Boone County, Missouri, which has a population of approximately 170,000. Boone County is 1790 km², with 16% of the land defined as cropland and 30% defined as pasture. The model includes 27 nutrients from 17 potential foods that could be produced: six fruits and vegetables, five grains and six animal-sourced foods. Yield estimates are based on the predominate methods of agriculture in the USA. We first run our model assuming no variability, using the midpoint yield estimates. Then, to quantify uncertainty in yield for different food types, we use historical yield data over 10 years to estimate this variability and run our RO model under these variability estimates. We compare the two model results to illustrate the impact of data uncertainty on meeting sustainable local food for communities. Solutions suggest that nutrition needs can be met for the Boone County population within the land area defined.     

Modeling kelp forest distribution and biomass along temperate rocky coastlines

We address the global deficit of data describing kelp forest distribution, relative covers and biomass by testing the ability of species distribution models to predict these attributes at locations where data are currently limited. We integrated biological ground truth data with high-resolution environmental datasets to develop generalized additive models that accurately predict the structure of Laminaria forests within the Bay of Morlaix (48°42′42″N, 3°55′40″W). Forest distribution and proportional covers were predicted using water depth, light availability, wave exposure and sediment dynamics. The biomass of individual kelp species was modeled by supplementing these same variables with measures of seafloor slope and benthic position. Biomass predictions for Laminaria digitata and Laminaria hyperborea contrast the physiological tolerances of these species to light and wave exposure gradients. As a direct management output, we produced high-resolution maps (25 m² grids) that closely match independent field data and provide vital information for marine spatial planning.     

Bioaccessibility of trace elements as affected by soil parameters in smelter-contaminated agricultural soils: a statistical modeling approach

An investigation was undertaken to identify the most significant soil parameters that can be used to predict Cd, Pb, and Zn bioaccessibility in smelter-contaminated agricultural soils. A robust model was established from an extended database of soils by using: (i) a training set of 280 samples to select the main soil parameters, to define the best population to be taken into account for the model elaboration, and to construct multivariate regression models, and (ii) a test set of 110 samples to validate the ability of the regression models. Total carbonate, organic matter, sand, P(2)O(5), free Fe-Mn oxide, and pseudototal Al and trace element (TE) contents appeared as the main variables governing TE bioaccessibility. The statistical modeling approach was reasonably successful, indicating that the main soil factors influencing the bioaccessibility of TEs were taken into account and the predictions could be applicable for further risk evaluation in the studied area.