Back-trajectories Show Export of Airborne Fungal Spores (Ganoderma sp.) From Forests to Agricultural and Urban Areas in England

We propose here the hypothesis that all of United Kingdom (UK) is likely to be affected by Ganoderma sp. spores, an important plant pathogen. We suggest that the main sources of this pathogen, which acts as a bioaerosol, are the widely scattered woodlands in the country, although remote sources must not be neglected. The hypothesis is based on related studies on bioaerosols and supported by new observations from a non-forest site and model calculations to support our hypothesis. Hourly concentrations of Ganoderma sp. spores were measured from 2006 to 2010 using a 7-day volumetric spore trap at the city of Worcester. The concentrations peak during the night and early in the morning. This suggests that the main spore sources are located a few hours away with respect to air masses transport and reach urban areas thanks to air masses transport. The back-trajectory analysis was applied to determine the location of Ganoderma sp. spore sources. The analysis of back-trajectories demonstrated that 78% of the air masses reached Worcester from a 180° arc direction from the East to West. Three episodes were selected for detailed investigation and they revealed that during the episodes air masses always passed main UK woodlands before the arrival in Worcester, independently of their origin, but the long distance transport under certain conditions might be possible. Our studies suggest that the sources of UK Ganoderma sp. spores are mainly to be found in UK. Hence our studies suggest that research and mitigation strategies in UK should give their main attention to national sources, without neglecting the contribution from long distance transport.

Improvement in the Accuracy of Back Trajectories Using WRF to Identify Pollen Sources in Southern Iberian Peninsula

Airborne pollen transport at micro-, meso-gamma and meso-beta scales must be studied by atmospheric models, having special relevance in complex terrain. In these cases, the accuracy of these models is mainly determined by the spatial resolution of the underlying meteorological dataset. This work examines how meteorological datasets determine the results obtained from atmospheric transport models used to describe pollen transport in the atmosphere. We investigate the effect of the spatial resolution when computing backward trajectories with the HYSPLIT model. We have used meteorological datasets from the WRF model with 27, 9 and 3 km resolutions and from the GDAS files with 1 ° resolution. This work allows characterizing atmospheric transport of Olea pollen in a region with complex flows. The results show that the complex terrain affects the trajectories and this effect varies with the different meteorological datasets. Overall, the change from GDAS to WRF-ARW inputs improves the analyses with the HYSPLIT model, thereby increasing the understanding the pollen episode. The results indicate that a spatial resolution of at least 9 km is needed to simulate atmospheric flows that are considerable affected by the relief of the landscape. The results suggest that the appropriate meteorological files should be considered when atmospheric models are used to characterize the atmospheric transport of pollen on micro-, meso-gamma and meso-beta scales. Furthermore, at these scales, the results are believed to be generally applicable for related areas such as the description of atmospheric transport of radionuclides or in the definition of nuclear-radioactivity emergency preparedness.

Detecting a shallow surface layer in Barkley Sound from Lagrangian drifter trajectories

Senior thesis written for Oceanography 444

Improving energy efficiency in the road freight transport sector: the application of a vehicle approach

Several approaches can be used to analyse performance, energy consumption and CO2 emissions in freight transport. In this paper we define and apply a vehicle-oriented, bottom up survey approach, the so called ‘vehicle approach’, in contrast to a ‘supply chain approach’. The main objective of the approach is to assess the impacts of various freight transport operations on efficiency and energy use. We apply the approach, comparing official statistics on freight transport and energy efficiency in Britain and France. Results on freight intensity, vehicle utilisation, fuel use, fuel efficiency and CO2 intensity are compared for the two countries. The results indicate comparable levels of operational and fuel efficiency in road freight transport operations in the two countries. Issues that can be addressed with the vehicle approach include: the impacts of technology innovations and logistics decisions implemented in freight companies, and the quantification of the effect of policy measures on fuel use at the national level.

Using official data sources to analyse the light goods vehicle fleet and operations in Britain

Report produced as part of the Green Logistics project (EPSRC and Department for Transport funded). Light goods vehicles play a key role in providing goods and services to businesses and other organisations in Britain. In order to better understand the relationship between costs and benefits of LGV operations it is necessary to gain a more detailed appreciation of the roles that these vehicles are fulfilling. This report aims to provide a better understanding of this sector by examining LGV fleet and operations in terms of their characteristics, utilisation and efficiency and purpose. Important potential external impacts of LGVs are also considered.

Internalising the external costs of light goods vehicle transport in Britain

Report produced as part of the Green Logistics project (EPSRC and Department for Transport funded). To what extent do the taxes paid by the light goods vehicles (LGVs) users in Britain cover their allocated infrastructural, environmental and congestion costs? This report is a continuation of a study on the internalisation of the external costs of heavy goods vehicle activity. Research undertaken jointly by the Transport Studies Group at University of Westminster and Logistics Research Centre at Heriot-Watt University has attempted to answer this question using official government transport statistics and monetary valuations for the external costs.

Internalising the external costs of light and heavy goods vehicle transport in London

Report produced as part of the Green Logistics project (EPSRC and Department for Transport funded). This report provides estimates of the total external costs of LGV and HGV operations in London. In 2006, total LGV and HGV activity imposed external costs of approximately £1.75-£1.8 billion using low, medium and high emission cost values. About 27 per cent of these costs were internalised by duties and taxes paid by LGV operators, compared with 26% in the case of HGVs. If congestion costs are excluded, taxes and duties paid by LGV operators are estimated to be 155% of LGVs' allocated infrastructural and environmental costs, compared with 85% in the case of HGVs. When using the medium emission cost values, LGVs accounted for 56% of these external costs in London and HGVs for 44%.

Internalising the external costs of light goods vehicle transport in Britain

To what extent do the taxes paid by the light goods vehicles (LGVs) users in Britain cover their allocated infrastructural, environmental and congestion costs? This report is a continuation of a study on the internalisation of the external costs of heavy goods vehicle activity. Research undertaken jointly by the Transport Studies Group at University of Westminster and Logistics Research Centre at Heriot-Watt University has attempted to answer this question using official government transport statistics and monetary valuations for the external costs.

Sex-specific disruption of murine midbrain astrocytic and dopaminergic developmental trajectories following antenatal GC treatment

The mammalian midbrain dopaminergic systems arising in the substantia nigra pars compacta (SNc) and ventral tegmental area (VTA) are critical for coping behaviours and are implicated in neuropsychiatric disorders where early life challenges comprise significant risk factors. Here, we aimed to advance our hypothesis that glucocorticoids (GCs), recognised key players in neurobiological programming, target development within these systems, with a novel focus on the astrocytic population. Mice received antenatal GC treatment (AGT) by including the synthetic GC, dexamethasone, in the mothers' drinking water on gestational days 16-19; controls received normal drinking water. Analyses of regional shapes and volumes of the adult SNc and VTA demonstrated that AGT induced long-term, dose-dependent, structural changes that were accompanied by profound effects on astrocytes (doubling/tripling of numbers and/or density). Additionally, AGT induced long-term changes in the population size and distribution of SNc/VTA dopaminergic neurons, confirming and extending our previous observations made in rats. Furthermore, glial/neuronal structural remodelling was sexually dimorphic and depended on the AGT dose and sub-region of the SNc/VTA. Investigations within the neonatal brain revealed that these long-term organisational effects of AGT depend, at least in part, on targeting perinatal processes that determine astrocyte density and programmed cell death in dopaminergic neurons. Collectively, our characterisation of enduring, AGT-induced, sex-specific cytoarchitectural disturbances suggests novel mechanistic links for the strong association between early environmental challenge (inappropriate exposure to excess GCs) and vulnerability to developing aberrant behaviours in later life, with translational implications for dopamine-associated disorders (such as schizophrenia, ADHD, autism, depression), which typically show a sex bias

Statistical classification of road pavements using near field vehicle rolling noise measurements

Low noise surfaces have been increasingly considered as a viable and cost-effective alternative to acoustical barriers. However, road planners and administrators frequently lack information on the correlation between the type of road surface and the resulting noise emission profile. To address this problem, a method to identify and classify different types of road pavements was developed, whereby near field road noise is analyzed using statistical learning methods. The vehicle rolling sound signal near the tires and close to the road surface was acquired by two microphones in a special arrangement which implements the Close-Proximity method. A set of features, characterizing the properties of the road pavement, was extracted from the corresponding sound profiles. A feature selection method was used to automatically select those that are most relevant in predicting the type of pavement, while reducing the computational cost. A set of different types of road pavement segments were tested and the performance of the classifier was evaluated. Results of pavement classification performed during a road journey are presented on a map, together with geographical data. This procedure leads to a considerable improvement in the quality of road pavement noise data, thereby increasing the accuracy of road traffic noise prediction models.

Data mining techniques contributions to support electrical vehicle demand response

The introduction of Electric Vehicles (EVs) together with the implementation of smart grids will raise new challenges to power system operators. This paper proposes a demand response program for electric vehicle users which provides the network operator with another useful resource that consists in reducing vehicles charging necessities. This demand response program enables vehicle users to get some profit by agreeing to reduce their travel necessities and minimum battery level requirements on a given period. To support network operator actions, the amount of demand response usage can be estimated using data mining techniques applied to a database containing a large set of operation scenarios. The paper includes a case study based on simulated operation scenarios that consider different operation conditions, e.g. available renewable generation, and considering a diversity of distributed resources and electric vehicles with vehicle-to-grid capacity and demand response capacity in a 33 bus distribution network.