The role of respondents’ comfort for variance in stated choice surveys: evidence from a SCUBA diving case

Preference elicitation among outdoor recreational users is subject to measurement errors that depend, in part, on survey planning. This study uses data from a choice experiment survey on recreational SCUBA diving to investigate whether self-reported information on respondents’ comfort when they complete surveys correlates with the error variance in stated choice models of their responses. Comfort-related variables are included in the scale functions of the scaled multinomial logit models. The hypothesis was that higher comfort reduces error variance in answers, as revealed by a higher scale parameter and vice versa. Information on, e.g., sleep and time since eating (higher comfort) correlated with scale heterogeneity, and produced lower error variance when controlled for in the model. That respondents’ comfort may influence choice behavior suggests that knowledge of the respondents’ activity patterns could be used to plan the timing of interviews to decrease error variance in choices and, hence, generate better information.     

Observations and Modeling of Stream Plunging in an Urban Lake1

Owens, Emmet M., Steven W. Effler, Anthony R. Prestigiacomo, David A. Matthews, and Susan M. O’Donnell, 2012. Observations and Modeling of Stream Plunging in an Urban Lake. Journal of the American Water Resources Association (JAWRA) 48(4): 707‐721. DOI: 10.1111/j.1752‐1688.2012.00646.x Abstract: The plunging behavior of two tributaries in Onondaga Lake, New York, is quantified based on a program of monitoring, process studies, and modeling. The dynamics of buoyancy of the tributaries are resolved with hourly measurements of temperature (T), specific conductance (SC), and turbidity (Tn) at the mouths, and observations every 6 h in the lake. Negative buoyancy of the tributaries is found to diminish and change rapidly during runoff events compared to dry periods. In‐lake patterns of the transport of plunging inflow are resolved for dry weather conditions using a dye tracer, and following a runoff event through measurements of T, SC, and Tn. The hydrodynamic/transport model ELCOM (Estuary Lake and Coastal Ocean Model) is demonstrated to perform well in simulating these patterns. Analyses conducted with the model establish the importance of diurnal effects and in‐lake mixing mediated by wind, the need for temporally detailed measurements during runoff events, and modifications of the plunging behavior of the urban tributary as it passes through a harbor. The model provides critical information to support rehabilitation programs for the lake by quantifying the transport of the two largest tributaries, particularly the distribution of the loads between the upper waters and stratified layers. The model predicts that 10% of the urban tributary load enters the upper waters of the lake within 24 h for a dry weather period; this portion increases to 30% for a runoff event.     

Noise annoyance from industrial and road traffic combined noises: A survey and a total annoyance model comparison

The literature on noise annoyance emphasizes that acoustical factors cannot totally explain the annoyance felt by a population exposed to community noises, and that some non-acoustical factors have an effect on annoyance. This research paper deals with the annoyance caused by combined noises coming from road traffic and an industrial site. This type of combination has been very little studied to date. An in situ study was conducted in an area of a French town exposed to these two noise sources. To investigate the annoyance caused by these combined noises, the work involved both a mapping of the industrial and road traffic noises present in the survey area and a questionnaire designed to evaluate the noise annoyance experienced by residents and to identify the factors that probably influence noise annoyance. The results highlight the link between the noise levels measured and the annoyance felt by the respondents. They also show that certain non-acoustical factors have an impact on annoyance felt. Indeed, the results highlight a positive correlation between fear of industrial sites and the annoyance expressed. They also show correlations between some items to evaluate noise sensitivity and the annoyance expressed. No significant correlation has been found between annoyance and the other non-acoustical factors such as age, sex and length of residence. Finally, several total annoyance models were tested for this noise combination. Two of them, namely the strongest component model and a proposed perceptual version of the mixed model, were able to better predict total annoyance than the other tested models.     

Regional-scale application of the decision support system MOIRA-PLUS: an example of assessment of the radiological impact of the Chernobyl accident on the fresh water ecosystem in Italy

The present work illustrates the customisation and application of the decision support system MOIRA-PLUS (a MOdel-based computerised system for management support to Identify optimal remedial strategies for Restoring radionuclide contaminated Aquatic ecosystems and drainage areas) to the fresh water environment in Italy. MOIRA-PLUS is aimed at evaluating the behaviour of radiocaesium and radiostrontium in fresh water ecosystems and at assessing the appropriateness of suitable strategies for the management of contaminated water bodies by the application of multi-attribute analysis techniques. MOIRA-PLUS can be applied to complex networks of lakes, rivers and tributaries and can be straightforwardly customised utilising data and information from readily accessible sources such as official websites provided by scientific or government organisations. The present work shows an application of the decision system to 10 lakes and 18 rivers in Italy contaminated with ¹³⁷Cs of Chernobyl origin. Site-specific values of some aggregated transfer parameters were estimated for the most important Italian lakes. Although high values of fish and water consumptions were hypothesised, very low doses to public from the fresh water pathway following the accident were calculated.     

Development of models for predicting toxicity from sediment chemistry by partial least squares-discriminant analysis and counter-propagation artificial neural networks

There is strong interest in developing tools to link chemical concentrations of contaminants to the potential for observing sediment toxicity that can be used in initial screening-level sediment quality assessments. This paper presents new approaches for predicting toxicity in sediments, based on 10-day survival tests with marine amphipods, from sediment chemistry, by means of the application of Partial Least Squares-Discriminant Analysis (PLS-DA) and Counter-propagation Artificial Neural Networks (CP-ANNs) to large historical databases of chemical and toxicity data. The exploration of the internal structure of the developed models revealed inherent limitations of predicting toxicity from common chemical analyses of bulk contaminant concentrations. However, the results obtained in the validation of these models combined relevant values of non-error classification rate, sensitivity and specificity of, respectively, 76, 87 and 73% with PLS-DA and 92, 75 and 97% with CP-ANNs, outperforming the results reported for previous approaches.     

Linking desorption kinetics to phenanthrene biodegradation in soil

The desorption of polycyclic aromatic hydrocarbons (PAHs) often exhibits a biphasic profile similar to that observed for biodegradation whereby an initial rapid phase of degradation or desorption is followed by a phase of much slower transformation or release. Most investigations to-date have utilised a polymeric sorbent, such as Tenax, to characterise desorption, which is methodologically unsuitable for the analysis of soil. In this study, desorption kinetics of ¹⁴C-phenanthrene were measured by consecutive extraction using aqueous solutions of hydroxypropyl-β-cyclodextrin (HPCD). The data indicate that the fraction extracted after 24 h generally approximated the linearly sorbed, rapidly desorbing fraction (F_rap), calculated using a three-compartment model. A good linear correlation between phenanthrene mineralised and F_rap was observed (r² = 0.89; gradient = 0.85; intercept = 8.20). Hence HPCD extraction (24 h) and first-order three-compartment modelling appear to provide an operationally straightforward tool for estimating mass-transfer limited biodegradation in soil.     

Review on Quantitative Research Methods of Regional Sustainable Development in China

Since the 1990s, with the in-depth study and understanding of sustainable development, quantitative study of regional sustainable development (RSD) was increasingly hot in China. Based on quantitative study of RSD from Core Periodical in China National Knowledge Infrastructure (1992–2008), statistical analysis on the annual distribution, periodicals distribution and changes of the distribution were made. And from perspectives of social–economic, ecological, systematic and emerging methods, the course, probl...     

Relevance of Hydro-Climatic Change Projection and Monitoring for Assessment of Water Cycle Changes in the Arctic

Rapid changes to the Arctic hydrological cycle challenge both our process understanding and our ability to find appropriate adaptation strategies. We have investigated the relevance and accuracy development of climate change projections for assessment of water cycle changes in major Arctic drainage basins. Results show relatively good agreement of climate model projections with observed temperature changes, but high model inaccuracy relative to available observation data for precipitation changes. Direct observations further show systematically larger (smaller) runoff than precipitation increases (decreases). This result is partly attributable to uncertainties and systematic bias in precipitation observations, but still indicates that some of the observed increase in Arctic river runoff is due to water storage changes, for example melting permafrost and/or groundwater storage changes, within the drainage basins. Such causes of runoff change affect sea level, in addition to ocean salinity, and inland water resources, ecosystems, and infrastructure. Process-based hydrological modeling and observations, which can resolve changes in evapotranspiration, and groundwater and permafrost storage at and below river basin scales, are needed in order to accurately interpret and translate climate-driven precipitation changes to changes in freshwater cycling and runoff. In contrast to this need, our results show that the density of Arctic runoff monitoring has become increasingly biased and less relevant by decreasing most and being lowest in river basins with the largest expected climatic changes.     

Using advanced surface complexation models for modelling soil chemistry under forests: Solling forest, Germany

Various dynamic soil chemistry models have been developed to gain insight into impacts of atmospheric deposition of sulphur, nitrogen and other elements on soil and soil solution chemistry. Sorption parameters for anions and cations are generally calibrated for each site, which hampers extrapolation in space and time. On the other hand, recently developed surface complexation models (SCMs) have been successful in predicting ion sorption for static systems using generic parameter sets. This study reports the inclusion of an assemblage of these SCMs in the dynamic soil chemistry model SMARTml and applies this model to a spruce forest site in Solling Germany. Parameters for SCMs were taken from generic datasets and not calibrated. Nevertheless, modelling results for major elements matched observations well. Further, trace metals were included in the model, also using the existing framework of SCMs. The model predicted sorption for most trace elements well.