Enhanced, multi criteria based site selection to measure mobile source toxic air pollutants

A multi-criteria-based site selection process that was developed for the Las Vegas near-road study is used to select the most appropriate near-road measurement sites in the Detroit area. The study measures particulate matter with aerodynamic diameters ?2.5 μm and mobile source air toxic compounds, and to document the rationale for selecting or rejecting specific sites. An application of this multi-criteria decision analysis may be the recent US Environmental Protection Agency rule requiring the siting of NO₂ monitors within 50 m of major roads as well as siting for the measurement of community-wide NO₂ concentrations.     

发展中国家机动化讨论

以中国、印度等为代表的广大发展中国家已进入快速机动化阶段.以此为背景,首先分析了发展中国家机动化发展的新现实,包括:提高了出行机动性,带来了大量的社会经济成本,增加了能源消耗,加剧了环境污染,同时面临发展资金不足、管理经验缺乏及资源分配不公等带来的社会问题.然后指出依靠交通运输技术的跨越式发展,未必能解决上述一系列问题...     

Estimating the agglomeration benefits of transport investments: some tests for stability

The case for including agglomeration benefits within transport appraisal rests on an assumed causality between access to economic mass and productivity. Such causality is justified by the theory of agglomeration, but is difficult to establish empirically because estimates may be subject to sources of bias from endogeneity and confounding. The paper shows that conventional panel methods used to address these problems are unreliable due to the highly persistent nature of accessibility measures. Adopting an alternative approach, by applying semiparametric techniques to restricted sub-samples of the data, we find considerable nonlinearity in the relationship between accessibility and productivity with no positive effect to be discerned over broad ranges of the data. A key conclusion is that we are unable to distinguish the role of accessibility from other potential explanations for productivity increases. For transport appraisal, this implies that the use of conventional point elasticity estimates could be highly misleading.     

Random covariance heterogeneity in discrete choice models

In this paper, we extend the standard discrete choice modelling framework by allowing for random variations in the substitution patterns between alternatives across respondents, leading to increased model flexibility. The paper shows how such a Mixed Covariance model can be specified either with purely random variation or with a mixture of random and deterministic variation. Additionally, the model can be based on an underlying GEV or ECL structure. Finally, the model can be specified as a continuous mixture or as a discrete mixture. An application on Stated Preference data for the choice of departure time and travel mode shows that important gains in model performance can be obtained by allowing for random covariance heterogeneity. Furthermore, the approach leads to significant differences in the implied willingness to pay measures, and the substitution patterns between alternatives.