Multi-elements atmospheric deposition study in Albania

For the first time, the moss biomonitoring technique and inductively coupled plasma–atomic emission spectrometric (ICP-AES) analytical technique were applied to study multi-element atmospheric deposition in Albania. Moss samples (Hypnum cupressiforme) were collected during the summer of 2011 and September–October 2010 from 62 sites, evenly distributed over the country. Sampling was performed in accordance with the LRTAP Convention–ICP Vegetation protocol and sampling strategy of the European Programme on Biomonitoring of Heavy Metal Atmospheric Deposition. ICP-AES analysis made it possible to determine concentrations of 19 elements including key toxic metals such as Pb, Cd, As, and Cu. Cluster and factor analysis with varimax rotation was applied to distinguish elements mainly of anthropogenic origin from those predominantly originating from natural sources. Geographical distribution maps of the elements over the sampled territory were constructed using GIS technology. The median values of the elements in moss samples of Albania were high for Al, Cr, Ni, Fe, and V and low for Cd, Cu, and Zn compared to other European countries, but generally were of a similar level as some of the neighboring countries such as Bulgaria, Croatia, Kosovo, Macedonia, and Romania. This study was conducted in the framework of ICP Vegetation in order to provide a reliable assessment of air quality throughout Albania and to produce information needed for better identification of contamination sources and improving the potential for assessing environmental and health risks in Albania, associated with toxic metals.     

Resilience: A New Consideration for Environmental Remediation in an Era of Climate Change

There has been a growing movement within the environmental industry to develop more sustainable approaches in environmental remediation. These have generally included carbon footprint analysis, life cycle assessment, and best management practices to reduce the overall net environmental, social, and economic impacts of investigation and remediation activities. One of the foundational reasons net environmental impacts are currently evaluated is to identify and, subsequently, reduce contributions to climate change, primarily greenhouse gas emissions. While this trend toward sustainability and reduction in impact to the global environment is both important and admirable, the approach to remediation design and long‐term planning now needs to evolve further to better incorporate climate resilience into sustainable remediation design and implementation: designing remediation solutions that account for the projected impacts of climate change, as well as have the capacity to adapt to changing conditions. As a global population, we are now beyond the point of being able to prevent climate change and instead need to plan for adapting to it. In remediation, the effects of climate change create both risks and opportunities which should be considered during remedial design and long‐term planning. Responsible parties may see the push for—and management of—these considerations through their internal corporate risk management. The authors of this paper propose a simple framework for climate adaptation and resilience evaluations and plan development for remediation projects. ©2015 Wiley Periodicals, Inc.     

Permutation/randomization-based inference for environmental data

Quantitative inference from environmental contaminant data is almost exclusively from within the classic Neyman/Pearson (N/P) hypothesis-testing model, by which the mean serves as the fundamental quantitative measure, but which is constrained by random sampling and the assumption of normality in the data. Permutation/randomization-based inference originally forwarded by R. A. Fisher derives probability directly from the proportion of the occurrences of interest and is not dependent upon the distribution of data or random sampling. Foundationally, the underlying logic and the interpretation of the significance of the two models vary, but inference using either model can often be successfully applied. However, data examples from airborne environmental fungi (mold), asbestos in settled dust, and 1,2,3,4-tetrachlorobenzene (TeCB) in soil demonstrate potentially misleading inference using traditional N/P hypothesis testing based upon means/variance compared to permutation/randomization inference using differences in frequency of detection (Δf _d). Bootstrapping and permutation testing, which are extensions of permutation/randomization, confirm calculated p values via Δf _d and should be utilized to verify the appropriateness of a given data analysis by either model.     

Arctic marine mammal population status,sea ice habitat loss,and conservation recommendations for the 21st century

Arctic marine mammals (AMMs) are icons of climate change, largely because of their close association with sea ice. However, neither a circumpolar assessment of AMM status nor a standardized metric of sea ice habitat change is available. We summarized available data on abundance and trend for each AMM species and recognized subpopulation. We also examined species diversity, the extent of human use, and temporal trends in sea ice habitat for 12 regions of the Arctic by calculating the dates of spring sea ice retreat and fall sea ice advance from satellite data (1979–2013). Estimates of AMM abundance varied greatly in quality, and few studies were long enough for trend analysis. Of the AMM subpopulations, 78% (61 of 78) are legally harvested for subsistence purposes. Changes in sea ice phenology have been profound. In all regions except the Bering Sea, the duration of the summer (i.e., reduced ice) period increased by 5–10 weeks and by >20 weeks in the Barents Sea between 1979 and 2013. In light of generally poor data, the importance of human use, and forecasted environmental changes in the 21st century, we recommend the following for effective AMM conservation: maintain and improve comanagement by local, federal, and international partners; recognize spatial and temporal variability in AMM subpopulation response to climate change; implement monitoring programs with clear goals; mitigate cumulative impacts of increased human activity; and recognize the limits of current protected species legislation.     

The return of the giants: ecological effects of an increasing elephant population

Northern Botswana and adjacent areas, have the world's largest population of African elephant (Loxodonta africana). However, a 100 years ago elephants were rare following excessive hunting. Simultaneously, ungulate populations were severely reduced by decease. The ecological effects of the reduction in large herbivores must have been substantial, but are little known. Today, however, ecosystem changes following the increase in elephant numbers cause considerable concern in Botswana. This was the background for the "BONIC" project, investigating the interactions between the increasing elephant population and other ecosystem components and processes. Results confirm that the ecosystem is changing following the increase in elephant and ungulate populations, and, presumably, developing towards a situation resembling that before the reduction of large herbivores. We see no ecological reasons to artificially change elephant numbers. There are, however, economic and social reasons to control elephants, and their range in northern Botswana may have to be artificially restricted.     

Sampling frequency guidance for ambient air toxics monitoring

The U.S. Environmental Protection Agency (EPA) is in the process of designing a national network to monitor hazardous air pollutants (HAPs), also known as air toxics. The purposes of the expanded monitoring are to (1) characterize ambient concentrations in representative areas; (2) provide data to support and evaluate dispersion and receptor models; and (3) establish trends and evaluate the effectiveness of HAP emission reduction strategies. Existing air toxics data, in the form of an archive compiled by EPA's Office of Air Quality Planning and Standards (OAQPS), are used in this paper to examine the relationship between estimated annual average (AA) HAP concentrations and their associated variability. The goal is to assess the accuracy, or bias and precision, with which the AA can be estimated as a function of ambient concentration levels and sampling frequency. The results suggest that, for several air toxics, a sampling schedule of 1 in 3 days (1:3) or 1:6 days maybe appropriate for meeting some of the general objectives of the national network, with the more intense sampling rate being recommended for areas expected to exhibit relatively high ambient levels.     

Effects of engine speed and accessory load on idling emissions from heavy-duty diesel truck engines

A nontrivial portion of heavy-duty vehicle emissions of NOx and particulate matter (PM) occurs during idling. Regulators and the environmental community are interested in curtailing truck idling emissions, but current emissions models do not characterize them accurately, and little quantitative data exist to evaluate the relative effectiveness of various policies. The objectives of this study were to quantify the effect of accessory loading and engine speed on idling emissions from a properly functioning, modern, heavy-duty diesel truck and to compare these results with data from earlier model year vehicles. It was found that emissions during idling varied greatly as a function of engine model year, engine speed, and accessory load conditions. For the 1999 model year Class 8 truck tested, raising the engine speed from 600 to 1050 rpm and turning on the air conditioning resulted in a 2.5-fold increase in NOx emissions in grams per hour, a 2-fold increase in CO2 emissions, and a 5-fold increase in CO emissions while idling. On a grams per gallon fuel basis, NOx emissions while idling were approximately twice as high as those at 55 mph. The CO2 emissions at the two conditions were closer. The NOx emissions from the 1999 truck while idling with air conditioning running were slightly more than those of two 1990 model year trucks under equivalent conditions, and the hydrocarbon (HC) and CO emissions were significantly lower. It was found that the NOx emissions used in the California Air Resources Board's (CARB) EMFAC2000 and the U.S. Environmental Protection Agency's (EPA) MOBILE5b emissions inventory models were lower than those measured in all of the idling conditions tested on the 1999 truck.     

Herbicide safeners: uses,limitations, metabolism,and mechanisms of action

Several methods were examined to minimize crops injury caused by herbicides. Thus increase their selectivity. A selective herbicide is one that controls weeds at rates that do not injure the crop. Herbicides are selective in a particular crop within certain limits imposed by the herbicide, the plant, the application rate, the method and time of application, and environment conditions. Herbicide safeners are compounds of diverse chemical families. They are applied with herbicides to protect crops against their injury. Using chemical safeners offer practical, efficient and simple method of improving herbicide selectivity. This method has been applied successfully in cereal crops such as maize, rice and sorghum, against pre-emergence thiocarbamate and chloroacetanilide herbicides. Some reports indicate promising results for the development of safeners for post-emergence herbicides in broadleaved crops. Various hypotheses were proposed explaining mechanisms of action of herbicide safeners: interference with uptake and translocation of the herbicide, alteration in herbicide metabolism, and competition at site of action of the herbicide. Even though progress was made in the development of herbicide safeners and in understanding their mechanisms of action, more research is needed to elucidate clearly how these chemicals act and why their activity is restricted to particular crops and herbicides.     

Design unbiased estimation in line intersect sampling using segmented transects

In many applications of line intersect sampling, transects consist of multiple, connected segments in a prescribed configuration. The relationship between the transect configuration and the selection probability of a population element is illustrated and a consistent sampling protocol, applicable to populations composed of arbitrarily shaped elements, is proposed. It is shown that this protocol obviates the arbitrary practice of treating multiple intersections of a single particle as independent probabilistic events and preserves the design-unbiasedness of Kaisers (1983, Biometrics 39, 965–976) conditional and unconditional estimators, suitably generalized to segmented transect designs. The relative efficiency and utility of segmented transect designs are also discussed from a fixed population perspective.