How green is my river? A new paradigm of eutrophication in rivers

Although the process of eutrophication is reasonably well understood in lakes, there is currently no conceptual understanding of how eutrophication develops in rivers. This issue is addressed here. A review of the main processes controlling the development of eutrophication in lakes has been carried out as a precursor to considering the effect in rivers. The importance of hydraulic flushing in controlling algal growth suggests that short-retention-time rivers will show different effects compared to long retention-time, impounded rivers. The latter are likely to operate like lakes, moving from macrophyte domination to phytoplankton domination whereas the former move to benthic and filamentous algal domination. Subsequently, a conceptual model of the development of eutrophic conditions in short-retention-time rivers is developed. Although there is general agreement in the literature that an increase in nutrients, particularly phosphorus, is a pre-requisite for the eutrophic conditions to develop, there is little evidence in short-retention-time rivers that the plant (macro and micro) biomass is limited by nutrients and a good case can be made that the interaction of hydraulic drag with light limitation is the main controlling factor. The light limitation is brought about by the development of epiphytic algal films on the macrophyte leaves. The implications of this conceptual model are discussed and a series of observable effects are predicted, which should result if the model is correct.     

Comparison of cytopathogenicity, immunofluorescence and In situ DNA hybridization as methods for the detection of adenoviruses

Three different methods were compared for their efficiency at detection of adenoviruses. The samples examined for viral analysis consisted of concentrates prepared from raw sewage, chosen as providing a representation of the spectrum of viruses being intestinally shed from a large population at any given time. When using one single cell line, HEp-2, the overall numbers of adenoviruses detected using cytopathogenicity and immunofluorescence were roughly equal. In situ hybridization was approx. 40% more sensitive than either of these other methods as determined by average virus titers for the different samples, and also proved to be better by means of a nonparametric comparison. The 293 cell line was approx. 5 times more sensitive for detecting adenoviruses by cytopathogenicity as compared with the HEp-2 cell line, but proved unsuitable in our hands for quantitatively detecting indigenous adenoviruses by immunofluorescence. The relative number of indigenous adenoviruses present in the sewage concentrates we examined was, on average, 94-fold greater than that of enteroviruses. Assay of enteroviruses was performed by plaque assay in the BGM cell line.     

Distribution and bioavailability of copper in farm effluent

Effluent and sludge samples from a number of dairy and piggery units in the North Island of New Zealand were collected and analysed for free ionic-copper (Cu(2+)) and organically-complexed Cu. The bioavailability of sludge-Cu was examined using microbial respiration and plant growth experiments. Microbial respiration was measured at various levels of Cu (0-1000 mg kg(-1)), added as copper sulfate (CuSO(4)) and sludge-Cu, using a Gilson differential respirometer. A glass house experiment was conducted to examine the transformation of Cu in soils and its subsequent uptake by ryegrass pasture. Three Cu sources were used that included fast-release CuSO(4), slow-release copper oxide (CuO) and Cu-enriched sludge. The pasture samples were analysed for Cu concentration. The transformation of Cu in the soil was monitored by analysing the soil samples for various fractions of Cu. The effluent and sludge samples collected from farms which regularly used Cu to treat lameness in dairy cattle and as a growth promoter in swine contained higher concentration of Cu. The total Cu concentration ranged from approximately 0.1 to 1.55 mg l(-1) and from 0.5 to 10.5 mg l(-1) in the piggery and diary effluent, respectively. The corresponding values for the sludge samples were 3.0-526 and 25-105 mg kg(-1). Most of the Cu in both the effluent and solid sludge material was organically complexed. The respiration measurements indicated that sludge-Cu was less toxic to soil microbial activity than CuSO(4). The results from the glass house experiment indicated that increasing the level of Cu applied through fertilisers and sludge increased Cu concentration in plants. At the same rate of application, plants took up less Cu from sludge and CuO than from CuSO(4). There was, however, a greater translocation of Cu from root to shoot at the highest rate of Cu through sludge application. The Cu fractionation study indicated that there was greater accumulation of organic bound Cu in the sludge-treated soil than the fertiliser-treated soil.     

The potential for oestrogenic effects of pesticides in headwater streams in the UK

Twenty-six pesticidal compounds and samples of stormwater from two different agricultural catchments were screened for oestrogenic activity using an in vitro recombinant yeast-based assay. Only six fungicides showed an oestrogenic response with low comparative biological activity of 5000 to 2.5 million times less potent than 17beta-estradiol (E2), a natural steroidal oestrogen. Concentrations of biological activity expressed as E(2) equivalents for the headwater stream stormwater samples ranged from <0.01 to 0.11 ng E2/l. These values are at least one order of magnitude below levels that have been documented to produce oestrogenic effects in fish and are therefore considered to represent a low risk to associated headwater stream communities. The potential sources of the oestrogenic activity measured in the headwater streams are discussed.     

Housing need assessments in San Francisco,Vancouver, and Melbourne: normative science or neoliberal alchemy?

Abstract

Governments in much of the Global North have responded to dramatic increases in house prices and rents by setting supply-side targets for new housing in regional and local plans, based on calculations of need. We apply social constructionism to assess widely divergent needs assessments underlying housing strategies in San Francisco, US; Vancouver, Canada; and Melbourne, Australia. In San Francisco, authorities use an approach required by the state government that ignores overcrowding and other ‘invisible’ criteria. In Vancouver, authorities have taken an ambitious approach that goes beyond a minimum quantum of affordable housing to discuss limits to market production. In Melbourne, the state government has chosen to ignore its own commissioned needs assessment to de-prioritize concerns around affordable housing shortages. We conclude by recommending that planners apply greater rigor in housing needs assessments, that can inform public debates around more equitable housing policy.     

Demand Profiling for Dynamic Traffic Assignment by Integrating Departure Time Choice and Trip Distribution

One challenge in dynamic traffic assignment (DTA) modeling is estimating the finely disaggregated trip matrix required by such models. In previous work, an exogenous time distribution profile for trip departure rates is applied uniformly across all origin‐destination (O‐D) pairs. This article develops an endogenous departure time choice model based on an arrival time penalty function incorporated into trip distribution, which results in distinct demand profiles by O‐D pair. This yields a simultaneous departure time and trip choice making use of the time‐varying travel times in DTA. The required input is arrival time preferences, which can be disaggregated by O‐D pair and may be easier to collect through surveys than the demand profile. This model is integrated into the four‐step planning process with feedback, creating an extension of previous frameworks which aggregate over time. Empirical results from a network representing Austin, Texas indicate variation in departure time choice appropriate to the arrival time penalties and travel times. Our model also appears to converge faster to a dynamic trip table prediction than a time‐aggregated coupling of DTA and planning, potentially reducing the substantial computation time of combined planning models that solve DTA as a subproblem of a feedback process.     

Economic comparison of current electricity generating technologies and advanced nuclear options

This analysis compares the cost of various electric grid scenarios at the national level over a one-year period. Scenarios include high renewable, zero nuclear, zero carbon, and deployment of advanced nuclear. Additionally, several carbon tax scenarios are explored in the model to further assess the cost generation if the current nuclear fleet retired. The cheapest scenarios were those that involved less reliance on conventional nuclear reactors and more molten salt reactors, renewables, or natural gas.     

Piecewise empirical model (PEM) of resistive memory for pulsed analog and neuromorphic applications

With the end of Dennard scaling and the ever-increasing need for more efficient, faster computation, resistive switching devices (ReRAM), often referred to as memristors, are a promising candidate for next generation computer hardware. These devices show particular promise for use in an analog neuromorphic computing accelerator as they can be tuned to multiple states and be updated like the weights in neuromorphic algorithms. Modeling a ReRAM-based neuromorphic computing accelerator requires a compact model capable of correctly simulating the small weight update behavior associated with neuromorphic training. These small updates have a nonlinear dependence on the initial state, which has a significant impact on neural network training. Consequently, we propose the piecewise empirical model (PEM), an empirically derived general purpose compact model that can accurately capture the nonlinearity of an arbitrary two-terminal device to match pulse measurements important for neuromorphic computing applications. By defining the state of the device to be proportional to its current, the model parameters can be extracted from a series of voltages pulses that mimic the behavior of a device in an analog neuromorphic computing accelerator. This allows for a general, accurate, and intuitive compact circuit model that is applicable to different resistance-switching device technologies. In this work, we explain the details of the model, implement the model in the circuit simulator Xyce, and give an example of its usage to model a specific \(\hbox {Ta}/\hbox {TaO}_{\mathrm{x}}\) device.     

Microstructure-Based Estimation of Strength and Ductility Distributions for $$\alpha +\beta $$ Titanium Alloys

Titanium alloys are processed to develop a wide range of microstructure configurations and therefore material properties. While these properties are typically measured experimentally, a framework for property prediction could greatly enhance alloy design and manufacturing. Here a microstructure-sensitive framework is presented for the prediction of strength and ductility as well as estimates of the bounds in variability for these properties. The framework explicitly considers distributions of microstructure via new approaches for instantiation of structure in synthetic samples. The parametric evaluation strategy, including the finite element simulation package FEpX, is used to create and test virtual polycrystalline samples to evaluate the variability bounds of mechanical properties in Ti-6Al-4V. Critical parameters for the property evaluation framework are provided by measurements of single crystal properties and advanced characterization of microstructure and slip system strengths in 2D and 3D. Property distributions for yield strength and ductility are presented, along with the validation and verification steps undertaken. Comparisons between strain localization and slip activity in virtual samples and in experimental grain-scale strain measurements are also discussed.

     

Safety risk perception in construction companies in the Pacific Northwest of the USA

Unsafe worker actions contribute greatly to the frequency and severity of construction injuries. Recently, contractors have expressed concern with the high rate of injuries that occur when workers violate company safety policies. To enhance knowledge associated with this topic the following four objectives were targeted: (1) quantifying the current level of safety risk as perceived by construction workers; (2) quantifying the risk tolerance of workers and managers; (3) comparing the risk perceptions and tolerance of workers with managers; and (4) identifying factors that may affect one’s risk tolerance. Fifty‐one risk perceptions were gathered through interviews with managers and workers of nine different construction firms in the Pacific Northwest region of the United States. The results indicate that the level of current perceived risk is approximately five times higher than the tolerable risk value, workers are most dissatisfied with the frequency of high severity injuries, and there is a statistically significant difference in the risk tolerance between workers and managers. The findings presented can be used by project managers to increase awareness of risk tolerances, current areas where workers feel improvement is most needed, and for goal setting.