Alternative amendment for soluble phosphorus removal from poultry litter

Background, aim, and scope  

Alum (aluminum sulfate) is the currently preferred chemical amendment for phosphorus (P) treatment in poultry litter (PL). Aluminum-based drinking-water treatment residuals (Al-WTRs) are the waste by-product of the drinking-water treatment process and have been effectively used to remove P from aqueous solutions, but their effectiveness in PL water extracts has not been studied in detail. Elevated cost associated with alum could be minimized by using the equally effective WTRs to remove soluble P from PL, and they can be obtained at a minimal cost from drinking-water treatment plants.     

Chitosan-polypropylene imine dendrimer hybrid: a new ecological biomordant for cochineal dyeing of wool

The classical use of synthetic dyes is causing issues of environmental pollution and heath risk. As a consequence natural dyes are gaining interest, but the use of natural dyes still includes toxic reagents such as metals as mordants and acids to enhance color and yield. Therefore, we designed a new chitosan-polypropylene imine dendrimer hybrid at 0–2000 mg/L to treat wool before dyeing with cochineal. We compared dye exhaustion, color depth, color characteristics, and color fastness of the new process with dyed pristine and metal mordanted wool. Results show that wool pretreatment improved dye exhaustion from 48 to 88 %, shifted saturation point toward lower dye concentration from 3000 to 1000 mg/L, and improved color depth from 13.68 for pristine wool and 15.17 for metal mordanted wool to 23.89 for the new process.     

International Environmental Agreements: Design of Optimal Transfers Under Heterogeneity

International environmental agreements (IEAs) can coordinate abatement of transboundary pollutants. This paper investigates how heterogeneous countries facing a stock pollutant might structure such an agreement. In particular, we examine how an IEA might be implemented with a set of monetary transfers. The focus is on transfers that are time invariant, linear in emissions, and consistent with budget balance. There is a range of such schemes that would induce efficient emissions. We provide a simple and intuitive characterization of these penalties and describe how specific proposals might be chosen in order to facilitate compliance and implementation. Our proposals are illustrated with a simple example. We show that heterogeneity reduces the scope for penalty schemes to jointly satisfy desirable properties.     

Analytical survey of arsenic in geothermal waters from sites in Kyushu,Japan, and a method for removing arsenic using magnetite

The objective of this study was to survey the cation and anion contents of geothermal waters to gather fundamental information on geographical variations. Sixteen sites in hot spring areas on the island of Kyushu in Japan were studied. The study focused on the arsenic content of the samples. Very high arsenic concentrations (more than 0.1 mg/l) were detected in most of the geothermal waters sampled. High contents of boron and fluoride (more than 1.0 mg/l) were also detected in some samples. Arsenic removal was performed on a laboratory scale using columns packed with a magnetite-type adsorbent. The reduction of arsenic contamination to a concentration of less than 0.01 mg/l could be achieved in the early stages of adsorption (bed volume = 200).     

Modeling a spatially restricted distribution in the Neotropics: How the size of calibration area affects the performance of five presence-only methods

We here examine species distribution models for a Neotropical anuran restricted to ombrophilous areas in the Brazilian Atlantic Forest hotspot. We extend the known occurrence for the treefrog Hypsiboas bischoffi (Anura: Hylidae) through GPS field surveys and use five modeling methods (BIOCLIM, DOMAIN, OM-GARP, SVM, and MAXENT) and selected bioclimatic and topographic variables to model the species distribution. Models were first trained using two calibration areas: the Brazilian Atlantic Forest (BAF) and the whole of South America (SA). All modeling methods showed good levels of predictive power and accuracy with mean AUC ranging from 0.77 (BIOCLIM/BAF) to 0.99 (MAXENT/SA). MAXENT and SVM were the most accurate presence-only methods among those tested here. All but the SVM models calibrated with SA predicted larger distribution areas when compared to models calibrated in BAF. OM-GARP dramatically overpredicted the species distribution for the model calibrated in SA, with a predicted area around 10⁶ km² larger than predicted by other SDMs. With increased calibration area (and environmental space), OM-GARP predictions followed changes in the environmental space associated with the increased calibration area, while MAXENT models were more consistent across calibration areas. MAXENT was the only method that retrieved consistent predictions across calibration areas, while allowing for some overprediction, a result that may be relevant for modeling the distribution of other spatially restricted organisms.     

Environmental analysis of a construction and demolition waste recycling plant in Portugal – Part I: Energy consumption and CO2 emissions

This work is a part of a wider study involving the economic and environmental implications of managing construction and demolition waste (CDW), focused on the operation of a large scale CDW recycling plant. This plant, to be operated in the Lisbon Metropolitan Area (including the Setúbal peninsula), is analysed for a 60 year period, using primary energy consumption and CO₂eq emission impact factors as environmental impact performance indicators.Simplified estimation methods are used to calculate industrial equipment incorporated, and the operation and transport related impacts. Material recycling – sorted materials sent to other industries, to act as input – is taken into account by discounting the impacts related to industrial processes no longer needed.This first part focuses on calculating the selected impact factors for a base case scenario (with a 350 tonnes/h installed capacity), while a sensitivity analysis is provided in part two. Overall, a 60 year global primary energy consumption of 71.4 thousand toe (tonne of oil equivalent) and a total CO₂eq emission of 135.4 thousand tonnes are expected. Under this operating regime, around 563 thousand toe and 1465 thousand tonnes CO₂eq could be prevented by replacing raw materials in several construction materials industries (e.g.: ferrous and non-ferrous metals, plastics, paper and cardboard).     

The Role of Disaggregation of Asset Values in Flood Loss Estimation: A Comparison of Different Modeling Approaches at the Mulde River,Germany

In loss estimation there is a spatial mismatch of hazard data that are commonly modeled on an explicit raster level and exposure data that are often available only for aggregated administrative units. Usually disaggregation methods that use ancillary information to distribute lumped exposure data in a finer spatial resolution help to bridge this gap. However, the actual influence of different mapping techniques and ancillary data on the final loss estimation has not been analyzed yet. In this paper three methods are applied to disaggregate residential building assets using two kinds of land use/land cover (LULC) data. The resulting disaggregated assets are validated and compared using census data of the residential building number on the community and constituency level. In addition, the disaggregated assets are taken to estimate residential building losses due to the flood in August 2002 in 21 municipalities on the River Mulde in Saxony, Germany. Losses are calculated with the help of four loss models. In general, disaggregation helps to decrease the error variance within the loss estimation. It must, however, be stated that the application of sophisticated disaggregation methods does not lead to significant improvements compared to the straightforward binary method. Therefore more effort should instead be put into the provision of high-resolution LULC data. Finally, the remaining uncertainties in loss estimation are high and demand further improvements in all modeling aspects.