General prevention and risk minimization in LCA A combined approach

Methods for life cycle assessment of products (LCA) are most often based on the general prevention principle, as opposed to the risk minimization principle. Here, the desirability and feasibility of a combined approach are discussed, along with the conditions for elaboration in the framework of LCA methodology, and the consequences for LCA practice. A combined approach provides a separate assessment of above and below threshold pollution, offering the possibility to combat above threshold impacts with priority. Spatial differentiation in fate, exposure, and effect modelling is identified to play a central role in the implementation. The collection of region-specific data turns out to be the most elaborate requirement for the implementation in both methodology and practice. A methodological framework for the construction of characterization factors is provided. Along with spatial differentiation of existing parameters, two newly introduced spatial parameters play a key role: the sensitivity factor and the threshold factor. The practicability of the proposed procedure is illustrated by an example of its application. Providing a reasonable data availability, the development of separate LCA characterization factors for the respective assessment of pollution levels above and below environmental threshold values seems to be a feasible task that may add to LCA credibility.     

Impacts of interannual climate variability on past and future forest composition

Numerous analyses of the possible impacts of future climatic changes on tree species composition have been published for both lowland and high-elevation forests. Most of these studies were based on the application of forest "gap" models, and the vast majority of them considered only changes in the average of climatic parameters over time. In this study, we use a unique data set on reconstructed past climatic variations to analyse forest dynamics simulated by the forest gap model ForClim. This analysis forms the basis for a systematic exploration of the ecological effects of changing means vs. changing variability of climate on central European forests. A reconstruction of historical climate covering the last 470 years in the Swiss lowlands (ClimIndex) is extrapolated to a transect across the alpine (cold) treeline and used to simulate the influence of climate variations on the time scale of decades on forest biomass and tree species composition at both sites. While the simulation at the low-elevation site shows little sensitivity to climate variations, the results from upper subalpine forests suggest that two major dieback events would have occurred at elevations above the current but below the climatic tree line, induced by clusters of exceptionally cold summers. The results are in agreement with available dendrochronological data and with documentary evidence on massive negative impacts on flora and fauna at high elevations during these periods. We conclude that ForClim is capable of capturing the effects on tree population dynamics of climate variability at these sites as reconstructed from the ClimIndex record. A factorial design is used to address the sensitivity of ForClim to changes of the long-term averages vs. changes of the variability of monthly temperature and precipitation data. To this end, the simulated tree species composition of near-natural forests is examined along a climate gradient in Europe. The results indicate that there are three types of forest response: (1) little sensitivity to both kinds of change, (2) strong sensitivity to changes in the means, but little sensitivity to changing variability, and (3) strong sensitivity to changing variability at least in parts of the examined climate space. Half of the cases investigated fall under the third category, suggesting that emphasis should be placed on also assessing the sensitivity of ecosystems to future changes in climate variability rather than on changes of average values alone. Electronic Publication     

Democracy at its Best? The Consensus Conference in a Cross-national Perspective

Over recent decades, public participation in technology assessment has spread internationally as an attempt to overcome or prevent societal conflicts over controversial technologies. One outcome of this new surge in public consultation initiatives has been the increased use of participatory consensus conferences in a number of countries. Existing evaluations of consensus conferences tend to focus on the modes of organization, as well as the outcomes, both procedural and substantial, of the conferences they examine. Such evaluations seem to rest on the assumption that this type of procedure has universally agreed goals and meanings, and that therefore consensus conferences can readily be interpreted and applied across national boundaries. This article challenges this approach to consensus conferences. The core of the article is a study of national differences in ideas about what constitutes legitimate goals for participatory arrangements. The study looks at three consensus conferences on GMOs, which took place in France, Norway, and Denmark. Drawing on this study, the article discusses the ways in which interpretations of the concept of participation; the value attributed to lay knowledge vs. technical expertise; as well as ideas about the role of the layperson, are all questions that prompt entirely different answers from country to country. Further, the article analyses these national differences within a theoretical framework of notions of democratic legitimacy.     

COMPARATIVE EVALUATION OF THREE URBAN RUNOFF MODELS1

ABSTRACT: Three urban runoff models, namely, the Road Research Laboratory Model (RRLM), the Storm Water Management Model (SWMM) and the University of Cincinnati Urban Runoff Model (UCURM), were examined by comparing the model simulated hydrographs with the hydrographs measured on several instrumented urban watersheds. This comparison was done for the hydrograph peak points as well as for the entire hydrographs using such statistical measures as the correlation coefficient, the special correlation coefficient and the integral square error. The results of the study indicated that, when applying the three selected non-calibrated models on small urban catchments, the SWM model performed marginally better than the RRL model and both these models were more accurate than the UCUR model. On larger watersheds, the comparisons between the SWM model and the other two models would be likely even more favourable for the SWM model, because it has the most advanced flow routing scheme among the studied models.     

Simulation modeling and resource management

Simulation models are becoming increasingly important as tools for synthesizing and applying information in almost all aspects of land management. They are particulary valuable for predicting and comparing outcomes of alternative decisions and assumptions. Models also permit managers to consider and integrate the potential influences of a large number of variables.     

ACCURACY OF IMPERVIOUS AREA VALUES ESTIMATED USING REMOTELY SENSED DATA1

ABSTRACT: Remote sensing offers an attractive alternative to conventional data collection employed in the estimation of certain hydrologic model parameters. In this investigation, the standard error of parameters estimated from Landsat data are examined. Relationships between the standard error and the size of the spatial-modeling units are developed that allow extending results to larger areas. Based upon the investigations conducted, a generalized model of the error relationships could not be developed.     

REDUCING THE COST OF CONTINUOUS HYDROLOGIC-HYDRAULIC SIMULATION1

ABSTRACT: The use of continuous hydrologic-hydraulic-water quality models is inhibited by their large computer run costs relative to cost incurred with discrete event models. The fixed recurrence interval transfer (FRIT) technique is a means of achieving substantial reductions in computer costs associated with continuous models while retaining their technical advantages. The FRIT technique is applicable where it is reasonable to assume that the recurrence interval of the response of a watershed to a causative meteorologic event is the same for both “before” and “after” conditions. Example applications of the FRIT technique to the hydrologic-hydraulic modeling of floodwater storage, land use changes, and channel modifications are presented to demonstrate the procedure, to suggest the expected accuracy, and to illustrate how computer run costs might be reduced by 99% or more. The FRIT technique is intended for preliminary assessment of the impact of alternative land use conditions and structural water control measures.     

THE EFFECT OF DATA INDEPENDENCE IN MODEL CALIBRATION AND MODEL TESTING1

ABSTRACT: With the increased use of models in hydrologic design, there is an immediate need for a comprehensive comparison of hydrologic models, especially those intended for use at ungaged locations (i.e., where measured data are either not available or inadequate for model calibration). But some past comparisons of hydrologic models have used the same data base for both calibration and testing of the different models or implied that the results of model calibration are indicative of the accuracy at ungaged locations. This practice was examined using both the regression equation approach to peak discharge estimation and a unit hydrograph model that was intended for use in urban areas. The results suggested that the lack of data independence in the calibration and testing of regression equations may lead to both biased results and misleading statements about prediction accuracy. Additionally, although split-sample testing is recognized as desirable, the split-samples should be selected using a systematic-random sampling scheme, rather than random sampling, because random sampling with small samples may lead to a testing sample that is not representative of the population. A systematic-random sampling technique should lead to more valid conclusions about model reliability. For models like a unit hydrograph model, which are more complex and for which calibration is a more involved process, data independence is not as critical because the data fitting error variation is not as dominant as the error variation due to the calibration process and the inability of the model structure to conform with data variability.     

OPTIMAL RESERVOIR MANAGEMENT AND CROP PLANNING UNDER DETERMINISTIC AND STOCHASTIC INFLOWS1

ABSTRACT: This study analyzes planning under deterministic and stochastic inflows for the Mayurakshi project in India. Models are developed to indicate the optimal storage of reservoir water, the transfer of water to the producing regions, and the spillage of water from the reservoir, if needed. A deterministic programming model was first formulated to represent the existing situation. A chance-constrained model then was constructed to evaluate potential violations of the deterministic model. Both models were quantified for the command area. Data were collected from surveys of the area and from government agencies. Both the deterministic and change-constrained models suggest a more intensive cropping program in the region. Both emphasize more dependence on rabi and less on kharif crops. The chance-constrained especially suggests use of more water in the rabi season. Important chances in cropping programs and labor use take place under the chance-constrained model.