Selection Bias in Value of Travel Time Savings

In this paper we investigate the value of travel time savings. Estimation of this is in most cases based on samples using a specific mode. We use a mixed logit model to estimate the VTTS together with an auxiliary probit equation to capture the fact that the sample is non random. The results show that the probit equation in some cases gives extra information that can be used to improve the VTTS estimates from the mixed logit model. Hence this opens a way to investigate the possible selection bias in standard estimations of VTTS

Analyser af GPS‐data fra ”Test en elbil” og TU data

Artiklen undersøger data fra ”Test en elbil”‐projektet. Husstandes kørsel i deres konventionelle bil og den lånte elbil sammenlignes. Derudover inddrages data fra transportvaneundersøgelsen (TU) for at sammenligne kørselsmønstrene med danskernes daglige kørsel. Resultaterne bekræfter en række gængse formodning, f.eks. at elbiler benyttes til kortere ture, samt at motorveje undgås med elbiler. Derudover viser resultaterne, at kun 12,1 % af turkæderne fra TU ikke kan klares med elbiler. Resultatet bestyrker, at elbilerne har et potentiale til dagligdags transport for mange danskere, såfremt der tilbydes passende opladningsmuligheder eller andre transportmuligheder for at dække de få turkæder, som ikke kan klares med elbiler

Bilvalg under påvirkning af en skattereform og stigende brændstofpriser

Artiklen undersøger, hvordan bilpriser, brændstofpriser og udviklingen i bilkarakteristika påvirker individers bilvalg. For at sammenholde effekterne opstilles en diskret valgmodel, som beskriver danskernes bilvalg ved køb af en ny bil i årene 2005-2008. Modellen anvendes til at undersøge effekten af 2007-reformen, som ændrede registreringsafgiften, og sammenholde reformens effekter med tilsvarende effekter fra stigende brændstofpriser og den teknologiske udvikling i bilernes karakteristika. Resultaterne viser, at de ændringer i nybilssalget, som fandt sted fra 2007 til 2008, kan skyldes flere faktorer bl.a. reformen, stigende benzinpriser og den teknologiske udvikling. Desuden viser resultaterne, at den teknologiske udvikling har haft en langt større effekt end reformen på valget af biltype

239 + 240Pu from “contaminant” to soil erosion tracer: Where do we stand?

As soil erosion is the major threat to one of the most essential resources of humankind, methods to quantify soil redistribution are crucial for agro-environmental assessment as well as for optimisation of soil conservation practices. The use of fallout radionuclides (FRN) as soil redistribution tracers is, next to modelling, currently the most promising approach for assessing soil erosion. This review aims to evaluate the suitability of Plutonium (Pu) in general and the 239+240Pu isotopes in particular as soil redistribution tracers. It provides information on its origin, distribution and behaviour in soils and in the environment. Analytical methods, their recent advances as well as limitations, are discussed. To establish the current state of knowledge and to deepen our understanding, particular attention is given to the main existing achievements and findings based on using 239+240Pu as soil erosion tracer in agroecosystems. We further discuss similarities and differences to other more mature FRN techniques such as the 137Cs based approach which has been until now the most widely used method. We conclude that 239+240Pu has the potential to become the next generation of soil redistribution tracer compared to the more mature FRN techniques mostly due to (i) its long half-life guaranteeing its long-term availability in the environment, (ii) its analytical advantage in terms of measurement precision and measurement time and (iii) its greater homogeneity at reference sites due to its main origin from past atmospheric nuclear weapon tests. In identifying some key future research opportunities and needs, we hope to refine the efficiency of this promising agro-environmental tracer for effective soil redistribution studies under future climate and land use change

Tracing sediment sources in an agriculture and livestock catchment of Argentina through the use of geochemical fingerprints

A mixing modelling approach (CSSIAR v2.00), using Energy Dispersive X Ray Fluorescence (EDXRF) and Total Organic Carbon (TOC) data as fingerprints for sediment sources and sinks, was applied for identifying critical hot spots of erosion in a typical Argentinian agro-ecosystem. The selected study site is the Estancia Grande catchment, covering 1235 hectares, which is located 23 km north east of San Luis (in the centre of Argentina). The studied catchment, which is characterized by highly erodible Haplic Kastanozem soils, is currently being used for agriculture (crop rotation), and livestock (free grazing and feedlots), and some fields are used for growing nut trees (walnuts and almonds) (Figure 1). Further fallow land is found in between the agriculture land and in the upper part of the catchment.Fil: Torres Astorga, Romina Vanesa. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Luis. Instituto de Matemática Aplicada de San Luis "Prof. Ezio Marchi". Universidad Nacional de San Luis. Facultad de Ciencias Físico, Matemáticas y Naturales. Instituto de Matemática Aplicada de San Luis "Prof. Ezio Marchi"; ArgentinaFil: Velasco, Ricardo Hugo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Luis. Instituto de Matemática Aplicada de San Luis "Prof. Ezio Marchi". Universidad Nacional de San Luis. Facultad de Ciencias Físico, Matemáticas y Naturales. Instituto de Matemática Aplicada de San Luis "Prof. Ezio Marchi"; ArgentinaFil: Resch, C.. Organismo Internacional de Energía Atómica ; AustriaFil: Gruber, R.. Organismo Internacional de Energía Atómica ; AustriaFil: Padilla, R.. Organismo Internacional de Energía Atómica ; AustriaFil: Dercon, G.. Organismo Internacional de Energía Atómica ; AustriaFil: Mabit, L.. Organismo Internacional de Energía Atómica ; Austri

Methodological perspectives on the application of compound-specific stable isotope fingerprinting for sediment source apportionment

Compound-specific stable isotope (CSSI) fingerprinting of sediment sources is a recently introduced tool to overcome some limitations of conventional approaches for sediment source apportionment. The technique uses the C-13 CSSI signature of plant-derived fatty acids (delta C-13-fatty acids) associated with soil minerals as a tracer. This paper provides methodological perspectives to advance the use of CSSI fingerprinting in combination with stable isotope mixing models (SIMMs) to apportion the relative contributions of different sediment sources (i.e. land uses) to sediments. CSSI fingerprinting allows quantitative estimation of the relative contribution of sediment sources within a catchment at a spatio-temporal resolution, taking into account the following approaches. First, application of CSSI fingerprinting techniques to complex catchments presents particular challenges and calls for well-designed sampling strategies and data handling. Hereby, it is essential to balance the effort required for representative sample collection and analyses against the need to accurately quantify the variability within the system. Second, robustness of the CSSI approach depends on the specificity and conservativeness of the delta C-13-FA fingerprint. Therefore, saturated long-chain (> 20 carbon atoms) FAs, which are biosynthesised exclusively by higher plants and are more stable than the more commonly used short-chain FAs, should be used. Third, given that FA concentrations can vary largely between sources, concentration-dependent SIMMs that are also able to incorporate delta C-13-FA variability should be standard operation procedures to correctly assess the contribution of sediment sources via SIMMs. This paper reflects on the use of delta C-13-FAs in erosion studies and provides recommendations for its application. We strongly advise the use of saturated long-chain (> 20 carbon atoms) FAs as tracers and concentration-dependent Bayesian SIMMs. We anticipate progress in CSSI sediment fingerprinting from two current developments: (i) development of hierarchical Bayesian SIMMs to better address catchment complexity and (ii) incorporation of dual isotope approaches (delta C-13- and delta H-2-FA) to improve estimates of sediment sources

Practical solutions for sampling alternatives in large-scale models

Many large-scale real-world transport applications have choice sets that are so large as to make model estimation and application computationally impractical. The ability to estimate models on subsets of the alternatives is thus of great appeal, and correction approaches have existed since the late 1970s for the simple multinomial logit (MNL) model. However, many of these models in practice rely on nested logit specifications, for example, in the context of the joint choice of mode and destination. Recent research has put forward solutions for such generalized extreme value (GEV) structures, but these structures remain difficult to apply in practice. This paper puts forward a simplification of the GEV method for use in computationally efficient implementations of nested logit. The good performance of this approach is illustrated with simulated data, and additional insights into sampling error are also provided with different sampling strategies for MNL

The impact of catchment source group classification on the accuracy of sediment fingerprinting outputs

The objective classification of sediment source groups is at present an under-investigated aspect of source tracing studies, which has the potential to statistically improve discrimination between sediment sources and reduce uncertainty. This paper investigates this potential using three different source group classification schemes. The first classification scheme was simple surface and subsurface groupings (Scheme 1). The tracer signatures were then used in a two-step cluster analysis to identify the sediment source groupings naturally defined by the tracer signatures (Scheme 2). The cluster source groups were then modified by splitting each one into a surface and subsurface component to suit catchment management goals (Scheme 3). The schemes were tested using artificial mixtures of sediment source samples. Controlled corruptions were made to some of the mixtures to mimic the potential causes of tracer non-conservatism present when using tracers in natural fluvial environments. It was determined how accurately the known proportions of sediment sources in the mixtures were identified after unmixing modelling using the three classification schemes. The cluster analysis derived source groups (2) significantly increased tracer variability ratios (inter-/ intra-source group variability) (up to 2122%, median 194%) compared to the surface and subsurface groupings (1). As a result, the composition of the artificial mixtures was identified an average of 9.8% more accurately on the 0e100% contribution scale. It was found that the cluster groups could be reclassified into a surface and subsurface component (3) with no significant increase in composite uncertainty(a 0.1% increase over Scheme 2). The far smaller effects of simulated tracer non-conservatism for the cluster analysis based schemes (2 and 3) was primarily attributed to the increased inter-group variability producing a far larger sediment source signal that the non-conservatism noise (1). Modified cluster analysis based classification methods have the potential to reduce composite uncertainty significantly in future source tracing studies