Evaluation of flow dependent external costs in freight logistics networks

In this paper we face a distribution problem arising in a freight logistics context. More precisely, we are involved with the containerized flow originating from maritime terminals and going to inland destinations using the road transportation network. The goal is the minimization of the total shipping costs, given by the travelled distance, vehicles and external cost components. In particular, we consider accidental and polluting costs as external negative costs. Note that the proposed externality costs depend on the amount of flow through the selected arcs in the route and their capacity; therefore, a novel stepwise function is proposed and analyzed. A deep analysis is performed for evaluating the impact of environmental externalities on the choice of the route in terms of costs and distances depending on the density of the traffic. Results of an extensive computational experimentation performed with randomly generated instances of different size and capacity values of the arcs are reported. A real case instance related to the logistics network connecting the main ports of the Liguria County (Italy) to the main inland destinations is finally proposed and analyzed

Implementation of the Polluter-Pays Principle (PPP) in local transport policy

Previous research has highlighted significant socio-environmental inequalities in the UK and elsewhere. A city's greatest polluters typically reside in affluent suburban communities located along the cities periphery, whilst those creating the least emissions reside in central locations, and most likely experience the largest associated health burdens. Using the culturally diverse city of Leicester as a study case, and building on Mitchell & Dorling's (2003) localised form of the Polluter Pays Principle, we investigate this environmental injustice. A pattern detection analysis of localised intra-urban interactions was achieved by a 'Local Indicators of Spatial Association' (LISA) modelling approach of high resolution census data, Driver Vehicle Licensing Agency (DVLA) records, road transport emission maps and geocoded hospital admissions records provided by the NHS Leicester City Primary Care Trust. Pearson's R statistics identified an inverse correlation between mobile polluters and communities characterised as either socially (-0.78) or environmentally burdened (-0.34), confirming the existence of environmental inequalities. Whilst some inner-city communities moderately contribute towards their environmental burden, these contributions were substantially outweighed by those made by external communities, whom appear to avoid the social, environment and physical cost of their actions. In contrast to their more affluent counterparts, residents of less affluent areas tend to use 'greener' and more active transport options, although any associated health benefits appear largely offset by increased periods of environmental exposure. Strong signs of spatial structuring within the modelling framework, suggest there may be a need to tailor travel schemes to local populaces. For example, in affluent areas where less environmentally friendly transport options tend to be adopted, options based on local carpool schemes may be more amenable than those based on enhanced public services

The effect of socio-environmental mechanisms on deteriorating respiratory health across urban communities during childhood

Spatial modelling techniques incorporating the social and physical structures of urban environments, previously establish a ‘triple jeopardy’ of social, respiratory health and environmental inequalities as operating within the multicultural UK City of Leicester (Jephcote & Chen, 2012). Expanding upon our initial findings, we aim to explore whether spatial relationships exist between relatively minor and severe respiratory conditions, and if so, then to what extent socio-environmental mechanisms play in the decline of children's respiratory health. Pearson's Correlation tests identified a high global level of correlation between children's acute upper and lower respiratory tract infections (URTI, LRTI), with Local Moran's I spatial autocorrelation tests identifying elevated hospitalisation rates across inner-city locales (p <0.05). Optimally weighted Geographically Weighted Regression models exploring the spatial distribution of children's URTI and LRTI respiratory hospitalisation incidents, expressed the extent to which individual socio-environmental mechanisms impeded health. Bivariate correlation statistics identified significant spatial trends between modelled URTI and LRTI admissions, with deprivation and TPM10 emissions detrimentally influencing respiratory health across inner-city communities (p <0.05). In contrast, lifestyle choices such as those seen by Indian residents, appeared to mitigate the onset of such conditions. Our findings suggest that exposure to detrimental socio-environmental factors may initiate URTI episodes, with prolonging recovery times likely occurring from sustained exposures. If a sufficient level of recovery is not reached in time for the cold season, then the child may become host to a viral infection exacerbating previous respiratory complaints. The findings of this investigation appear to confirm the existence of a link between certain socio-environmental influences and cases of ‘Catarrhal Child Syndrome’