Determination of specific gravity of municipal solid waste

This investigation was conducted to evaluate experimental determination of specific gravity (G_s) of municipal solid waste (MSW). Water pycnometry, typically used for testing soils was adapted for testing MSW using a large flask with 2000 mL capacity and specimens with 100–350 g masses. Tests were conducted on manufactured waste samples prepared using US waste constituent components; fresh wastes obtained prior and subsequent to compaction at an MSW landfill; and wastes obtained from various depths at the same landfill. Factors that influence specific gravity were investigated including waste particle size, compaction, and combined decomposition and stress history. The measured average specific gravities were 1.377 and 1.530 for as-prepared/uncompacted and compacted manufactured wastes, respectively; 1.072 and 1.258 for uncompacted and compacted fresh wastes, respectively; and 2.201 for old wastes. The average organic content and degree of decomposition were 77.2% and 0%, respectively for fresh wastes and 22.8% and 88.3%, respectively for old wastes. The G_s increased with decreasing particle size, compaction, and increasing waste age. For fresh wastes, reductions in particle size and compaction caused occluded intraparticle pores to be exposed and waste particles to be deformed resulting in increases in specific gravity. For old wastes, the high G_s resulted from loss of biodegradable components that have low G_s as well as potential access to previously occluded pores and deformation of particles due to both degradation processes and applied mechanical stresses. The G_s was correlated to the degree of decomposition with a linear relationship. Unlike soils, the G_s for MSW was not unique, but varied in a landfill environment due both to physical/mechanical processes and biochemical processes. Specific gravity testing is recommended to be conducted not only using representative waste composition, but also using representative compaction, stress, and degradation states.     

Why does the United States lack a global warming policy? The corporate inner circle versus public interest sector elites

Why has the United States not adopted global warming policies? Because the inner circle of the corporate elite has opposed these policies despite some corporate support for cap-and-trade and other policies. Pro- and anti-positions taken by think tanks that have led the policy debate in the post-Kyoto period are analyzed in order to demonstrate this. The corporate and upper class social ties of the directors of these pro- and anti-think tanks are examined, revealing a corporate elite split between the inner circle opposing these policies, and a ‘public interest sector’ of corporate law and media corporations along with top executives from higher education and other nonprofits that is supportive of policies addressing global warming. To enable adoption of major global warming policies, the corporate inner circle will need to become supportive and forge a class-wide corporate consensus on the need to address global warming.     

Value chain for next-generation biofuels: resilience and sustainability of the product life cycle

Multiple factors including climate change, price uncertainties, and geopolitical instability have prompted many industries to investigate the feasibility of replacing traditional petroleum-based fuels with biofuel alternatives. However, to make this transition successful, these new biofuels must be environmentally sustainable and the necessary support infrastructure must be in place to make the production, distribution, and storage of these biofuels technologically feasible and cost effective. Developing a value chain, spanning from feedstock production to distribution to end users, requires garnering buy-in from multiple stakeholders by demonstrating environmental, economic, and social benefits and incentives. Two critical factors are the environmental benefits achieved from the use of the biofuel technology and the degree of resilience of the value chain to emergent conditions to ensure steady supply to consumers. Moreover, different biofuel pathways have different costs, benefits, and risks which must be compared. In this paper, we describe how environmental sustainability can be modeled using life cycle assessment (LCA) and how the resilience of value chain initiatives can be modeled using a scenario-based decision model. We then describe how sustainability and resilience assessments can be integrated in an iterative, anticipatory LCA framework. These assessments can be used as the basis for a business case for various investments, as well as a means for promoting responsible innovations, with the aviation industry used as a case study.     

How Good? Ethical Criteria for a ‘Good Life’ for Farm Animals

The Farm Animal Welfare Council’s concept of a Good Life gives an idea of an animal’s quality of life that is over and above that of a mere life worth living. The concept needs explanation and clarification, in order to be meaningful, particularly for consumers who purchase farm animal produce. The concept could allow assurance schemes to apply the label to assessments of both the potential of each method of production, conceptualised in ways expected to enhance consumers’ engagement such as ‘naturalness’ and ‘freedom’; and the concept of a life worth living as a safeguard threshold below which no animal’s actual welfare should fall, based on each animal’s overall affective states. This may provide a framework for development of the Good Life concept, within scientific and sociological fields, in order to allow reliable and influential use by assessors, consumers and retailers.     

A Comprehensive Python Toolkit for Accessing High‐Throughput Computing to Support Large Hydrologic Modeling Tasks

The National Flood Interoperability Experiment (NFIE) was an undertaking that initiated a transformation in national hydrologic forecasting by providing streamflow forecasts at high spatial resolution over the whole country. This type of large‐scale, high‐resolution hydrologic modeling requires flexible and scalable tools to handle the resulting computational loads. While high‐throughput computing (HTC) and cloud computing provide an ideal resource for large‐scale modeling because they are cost‐effective and highly scalable, nevertheless, using these tools requires specialized training that is not always common for hydrologists and engineers. In an effort to facilitate the use of HTC resources the National Science Foundation (NSF) funded project, CI‐WATER, has developed a set of Python tools that can automate the tasks of provisioning and configuring an HTC environment in the cloud, and creating and submitting jobs to that environment. These tools are packaged into two Python libraries: CondorPy and TethysCluster. Together these libraries provide a comprehensive toolkit for accessing HTC to support hydrologic modeling. Two use cases are described to demonstrate the use of the toolkit, including a web app that was used to support the NFIE national‐scale modeling.     

Phytoremediation of a Petroleum‐Hydrocarbon Contaminated Shallow Aquifer in Elizabeth City,North Carolina,USA

A former bulk fuel terminal in North Carolina is a groundwater phytoremediation demonstration site where 3,250 hybrid poplars, willows, and pine trees were planted from 2006 to 2008 over approximately 579,000 L of residual gasoline, diesel, and jet fuel. Since 2011, the groundwater altitude is lower in the area with trees than outside the planted area. Soil‐gas analyses showed a 95 percent mass loss for total petroleum hydrocarbons (TPH) and a 99 percent mass loss for benzene, toluene, ethylbenzene, and xylenes (BTEX). BTEX and methyl tert‐butyl ether concentrations have decreased in groundwater. Interpolations of free‐phase, fuel product gauging data show reduced thicknesses across the site and pooling of fuel product where poplar biomass is greatest. Isolated clusters of tree mortalities have persisted in areas with high TPH and BTEX mass. Toxicity assays showed impaired water use for willows and poplars exposed to the site's fuel product, but Populus survival was higher than the willows or pines on‐site, even in a noncontaminated control area. All four Populus clones survived well at the site. © 2014 Wiley Periodicals, Inc.*     

Potential Impact of Climate Change on Hurricane Flooding Inundation,Population Affected and Property Damages in Corpus Christi1

Frey, Ashley E., Francisco Olivera, Jennifer L. Irish, Lauren M. Dunkin, James M. Kaihatu, Celso M. Ferreira, and Billy L. Edge, 2010. Potential Impact of Climate Change on Hurricane Flooding Inundation, Population Affected and Property Damages in Corpus Christi. Journal of the American Water Resources Association (JAWRA) 1–11. DOI: 10.1111/j.1752-1688.2010.00475.x Abstract: The effect of climate change on storm-surge flooding and the implications for population and structural damages on the city of Corpus Christi, Texas, was investigated. The study considered the influence of sea level rise and hurricane intensification, both influenced by climate change. Combinations of future carbon dioxide equivalent emission rates and carbon dioxide doubling sensitivities, based on findings of the Intergovernmental Panel on Climate Change, were considered to define future climate scenarios. A suite of physically based numerical models for hurricane winds and the resulting waves, surge, and morphological change at the coast were used to determine flooded areas, population affected, and property damages for Hurricanes Bret, Beulah, and a version of Carla shifted south from its original track, under present and predicted future climate conditions. A comparison of the economic damages for current climate conditions and for the 2080s climate scenario shows that, for Carla (shifted), there will be an increase in the range of $270-1,100 million; for Beulah, of $100-390 million; and, for Bret, of $30-280 million. A similar analysis was also conducted for 2030s predicted climate scenarios. Overall, the comparison of the results for the different climate conditions indicates what the destructive consequences of climate change could be, even within the somewhat short time frame of 80 years considered here.     

Development of the Metropolitan Water Availability Index (MWAI) and short-term assessment with multi-scale remote sensing technologies

Global climate change will influence environmental conditions including temperature, surface radiation, soil moisture, and sea level, and it will also significantly impact regional-scale hydrologic processes such as evapotranspiration (ET), precipitation, runoff, and snowmelt. The quantity and quality of water available for drinking and other domestic usage is also likely to be affected by changes in these processes. Consequently, it is necessary to assess and reflect upon the challenges ahead for water infrastructure and the general public in metropolitan regions. One approach to the problem is to use index-based assessment, forecasting and planning. The drought indices previously developed were not developed for domestic water supplies, and thus are insufficient for the purpose of such an assessment. This paper aims to propose and develop a “Metropolitan Water Availability Index (MWAI)” to assess the status of both the quantity and quality of available potable water sources diverted from the hydrologic cycle in a metropolitan region. In this approach, the accessible water may be expressed as volume per month or week (i.e., m³/month or m³/week) relative to a prescribed historical record, and such a trend analysis may result in final MWAI values ranging from ?1 to +1 for regional water management decision making. The MWAI computation uses data and information from both historical point measurements and spatial remote-sensing based monitoring. Variables such as precipitation, river discharge, and water quality changes at drinking water plant intakes at specific locations are past “point” measurements in MWAI calculations. On the other hand, remote sensing provides information on both spatial and temporal distributions of key variables. Examples of remote-sensing images and sensor network technologies are in-situ sensor networks, ground-based radar, air-borne aircraft, and even space-borne satellites. A case study in Tampa Bay, Florida is described to demonstrate the short-term assessment of the MWAI concept at a practical level. It is anticipated that such a forecasting methodology may be extended for middle-term and long-term water supply assessment.     

Sampling animal association networks with the gambit of the group

Ecologists increasingly use network theory to examine animal association patterns. The gambit of the group (GoG) is a simple and useful assumption for accumulating the data necessary for a network analysis. The gambit of the group implies that each animal in a group is associating with every other individual in that group. Sampling is an important issue for networks in wild populations collected assuming GoG. Due to time, effort, and resource constraints and the difficulty of tracking animals, sampled data are usually a subset of the actual network. Ecologists often use association indexes to calculate the frequency of associations between individuals. These indexes are often transformed by applying a filter to produce a binary network. We explore GoG sampling using model networks. We examine assortment at the level of the group by a single dichotomous trait, along with many other network measures, to examine the effect of different sampling regimes, and choice of filter on the accuracy and precision with which measures are estimated. We find strong support for the use of weighted, rather than filtered, network measures and show that different filters have different effects depending on the nature of the sampling. We make several practical recommendations for ecologists planning GoG sampling.