Assessment of temporal data for hospital admissions for asthma patients in comparison with ambient nitrogen dioxide levels in Guernsey, Channel Islands

There are some significant parallels between the environment in the island of Guernsey and that of coastal and island environments in Scotland. Although Guernsey enjoys milder temperatures in the summer months, the winter season experiences stormy weather fronts from the Atlantic and heavy rainfall.This research examines the temporal variation in nitrogen dioxide (NO2) levels in Guernsey and the hospital admissions of pre-existing asthmatics. Whilst air quality in Guernsey is generally good, the levels of NO2 exceed Scottish standards in several locations.The evidence indicates that people suffering from asthma have exacerbation of their symptoms if exposed to elevated levels of NO2, although this research has never been carried out in Guernsey before.For the first time in Guernsey, this research has examined NO2 levels in correlation with asthma patient admissions to hospital. The data showed a temporal correlation between NO2 levels and the number of hospital admissions. Statistical analysis of the data shows a direct correlation for both these variables.The relationships established should aid our understanding and serve as a base for directing future studies in this research area of improving health outcomes for asthmatics, and the respiratory health of the wider population

Optimizing Multi Modal Transportation Networks for Sustainable Urban Freight Delivery, Case Study Southwest Nigeria

Urban freight transportation enables economic productivity but contributes to congestion, emissions, and safety issues degrading livability. This paper investigates optimizing urban freight in Lagos, Nigeria using a multivariate regression model analyzing survey data on delivery costs across varying vehicles, routes, distances and frequencies. The model had low explanatory power, indicating complex contextual interactions impact costs. Spatial network analysis and logistics simulation are proposed to further evaluate infrastructure, vehicle technology, routing, coordination and policies holistically. Transitioning to electric vehicles, leveraging real-time traffic data, freight consolidation and policy incentives can balance efficiency, sustainability and equity in urban freight systems

Simple traffic measures significantly reduce the exposure of primary school children to NO₂

According to Public Health England (PHE, 2019) air quality is the largest environmental health risk in the UK; long-term exposure to air pollution claims some 28-36,000 premature deaths each year. It shortens lives and contributes to chronic illness. Health can be affected both by short-term, high-pollution episodes and by long-term exposure to lower levels of pollution. Environmental Health Officers (EHOs) are directly involved in managing and monitoring local air quality, but often direct action is only taken when there are exceedances of statutory limits and standards. A previous publication, REHIS Journal Autumn 2018, makes the case that long term exposure to lower than limit levels of air pollution can have significant health impacts in later life and that the developing lungs of children are at risk. PHE goes on to state that ‘effective communication of health messages about air pollution and appropriate action can save lives and improve quality of life for many’ (PHE, 2019)

Life cycle costing methodology for sustainable commerical office buildings

The need for a more authoritative approach to investment decision-making and cost control has been a requirement of office spending for many years now. The commercial offices find itself in an increasingly demanding position to allocate its budgets as wisely and prudently as possible. The significant percentage of total spending on buildings demands a more accurate and adaptable method of achieving quality of service within the constraints on the budgets. By adoption of life cycle costing techniques with risk management, practitioners have the ability to make accurate forecasts of likely future running costs. This thesis presents a novel framework (Artificial Neural Networks and probabilistic simulations) for modelling of operating and maintenance historical costs as well as economic performance measures of LCC. The methodology consisted of eight steps and presented a novel approach to modelling the LCC of operating and maintenance costs of two sustainable commercial office buildings. Finally, a set of performance measurement indicators were utilised to draw inference from these results. Therefore, the contribution that this research aimed to achieve was to develop a dynamic LCC framework for sustainable commercial office buildings, and by means of two existing buildings, demonstrate how assumption modelling can be utilised within a probabilistic environment. In this research, the key themes of risk assessment, probabilistic assumption modelling and stochastic assessment of LCC has been addressed. Significant improvements in existing LCC models have been achieved in this research in an attempt to make the LCC model more accurate and meaningful to estate managers and high-level capital investment decision makers A new approach to modelling historical costs and forecasting these costs in sustainable commercial office buildings is presented based upon a combination of ANN methods and stochastic modelling of the annual forecasted data. These models provide a far more accurate representation of long-term building costs as the inherent risk associated with the forecasts is easily quantifiable and the forecasts are based on a sounder approach to forecasting than what was previously used in the commercial sector. A novel framework for modelling the facilities management costs in two sustainable commercial office buildings is also presented. This is not only useful for modelling the LCC of existing commercial office buildings as presented here, but has wider implications for modelling LCC in competing option modelling in commercial office buildings. The processes of assumption modelling presented in this work can be modified easily to represent other types of commercial office buildings. Discussions with policy makers in the real estate industry revealed that concerns were held over how these building costs can be modelled given that available historical data represents wide spending and are not cost specific to commercial office buildings. Similarly, a pilot and main survey questionnaire was aimed at ascertaining current level of LCC application in sustainable construction; ranking drivers and barriers of sustainable commercial office buildings and determining the applications and limitations of LCC. The survey result showed that respondents strongly agreed that key performance indicators and economic performance measures need to be incorporated into LCC and that it is important to consider the initial, operating and maintenance costs of building when conducting LCC analysis, respondents disagreed that the current LCC techniques are suitable for calculating the whole costs of buildings but agreed that there is a low accuracy of historical cost data

Is Opportunistic Investing Rewarding? – A Study of United Kingdom Unlisted Funds

This study primarily investigates the impact of extreme financial leverage on UK unlisted property fund performance over a 11 year period, 2004 to 2014; accordingly the research problem is addressed applying a panel auto regression to an extended sample provided by the IPD Property Fund Vision Handbook covering funds information over a complete property cycle from 2004 to 2014. The results provide strong evidence in support of the traditional theory of capital structure asserting that financial leverage is a significant determinant of firm performance. A significant positive relationship is found between Leverage and performance of core and value added funds over the cycle but interestingly a significant negative association is seen for opportunistic funds as they underperformed through the cycle. Consequently, it is concluded that fund value may be enhanced by debt finance but must be kept at minimal levels, as an optimal debt finance level seems to exist considering the behaviour of Opportunistic funds over the investigated period. Key to the deduction is that irrespective of investment style (gearing intensity) through the cycle, performance persistence seems to sum the success or failure of UK unlisted property funds as lagged return showed a significant positive relationship in all regression results. Therefore the question of whether an unlisted fund persists in performance becomes even more decisive in determining how investors should select funds and develop investment strategies. Keywords: Performance, Leverage, Value added, Opportunistic, Unlisted fund

Road deposited sediment:implications for the performance of filter drains servicing strategic trunk roads

This study investigates the contribution of road deposited sediment (RDS) to clogging and the operational lifecycle of Highway Filter Drains (HFDs). RDS samples were collected from 9 Scottish trunk roads and fractionated into grain size classes to determine their particle size distributions (PSD). Results show that RDS PSDs, and the percentage of each grain size fraction, are highly variable. However, despite being collected from different trunk roads, PSD trends are similar, with individual RDS particles ranging in size from <63 μm to >10,000 μm. Medium sand, coarse sand, fine gravel and medium gravel make up 84.1% of the total particle mass concentration, with particles >1,000 μm mostly mineral or asphalt. The study also reveals that the dynamic nature of a trunk road catchment dictates that grading envelopes are essentially instantaneous values. These findings indicate that large particles from the road surface, contribute to clogging and have the potential to reduce the operational lifecycle of HFDs. The study also demonstrated that assuming a single RDS PSD profile for filter drain asset management purposes is unlikely to be representative of a trunk road catchment profile

Identifying Diseased Areas using a Geospatially Developed Human African Trypanosomiasis Vector Habitat Classification Scheme

Human African Trypanosomiasis (HAT) is a vector-borne disease transmitted by the bite of the tsetse fly that results in high human morbidity and mortality.  There is no HAT vaccine, but biological control of the vector has been successful in reducing HAT incidence. However, in recent years the disease has re-emerged and spread. Due to insufficient knowledge of HAT endemic foci, the disease management remains challenging. Information is vital to effective disease management, but the level of underreporting of disease, most especially HAT in Nigeria, impedes progress. The information gap, such as comprehensive digital spatial epidemiological information/data, could be reduced with geo-referenced studies, lacking in some previous work.  To achieve effective deployment of control strategies, accurate knowledge of the spatial distribution of the disease is vital. The current study is based in Nigeria, and looks at part of Delta State, in which HAT has been identified.  The study utilizes a previously geospatially developed HAT vector habitat classification scheme, to explore the dynamics of HAT propagation. The goal was to map the direction and magnitude of HAT and identify HAT vulnerable/risk areas. This helped identify ‘HAT priority intervention areas’. The study highlights the significance of geospatial techniques where epidemiological data are limited, for improving understanding of HAT.   The study findings suggested HAT propagation in the study area was multidirectional, and that this may have been influenced by landscape characteristics.  The study also suggested that the study area could be regarded as highly hazardous and that the human population residing in the area could be said to be at moderate risk of HAT. The method employed in this study will facilitate efficient decision making, planning for resource allocation as well as support active HAT surveillance. Keywords: Propagation, geospatially, multidirectional, disease

Assessment and Management of Human African Trypanosomiasis Propagation using Geospatial Techniques

Human African Trypanosomiasis (HAT) is a chronic and acute vector-borne disease. The propagation of the disease has been linked to environmental factors, and understanding the vector’s habitat is vital to its control. The available medications for HAT are dated, lethal and expensive, but biological control of the vector has been successful in some endemic foci. Nevertheless, recently the disease has re-emerged and spread and its management remains demanding. To manage and control the disease effectively, precise, up-to-date and comprehensive knowledge of its spatial characteristics is essential. This study is based in HAT endemic foci of Delta State, Nigeria. The study applied a geospatially developed HAT vector habitat classification scheme to assess the vulnerability level of settlements affected by HAT.  In addition, factors influencing HAT propagation and land cover suitability for HAT Vector within HAT vector Habitat Zones were investigated and assessed in a geographic information system environment.  The aim was to present HAT endemic countries with strategy for mapping and deriving precise, timely and life saving data/information from HAT vector habitat.  The study emphasizes the importance of geospatial techniques where there are dearths of epidemiological data, for improving perceptive of HAT.  The study findings suggested propagation of HAT resulted from suitability of water bodies, shrub and less-dense forest for the HAT vector, and continued exposure of human populations to these land cover classes. Overlapping of HAT vector habitat zones within built-up areas was also a cause. This novel approach can also be used in other part of Nigeria as well as adapted to investigate other diseases. Keywords:  Trypanosomiasis, Geospatial, Propagation, Epidemiological, HA

Development of a Classification Scheme for Managing Human African Trypanosomiasis using Geospatial Techniques

Distinctive environ-climatic variables have been associated with Trypanosoma brucei gambiense spatial characteristics, signifying the importance of physical landscape in HAT propagation/risk. Nevertheless, techniques projected to classify human African trypanosomiasis (HAT) vector habitats tend to be generalised, time wasting and costly.  Despite control efforts, HAT has become resurgent in some locations. No model to acquire detailed and comprehensive HAT spatial or epidemiological data exists for the study area, meaning many of those most in need, especially those  residing in remotest parts of the region, may not be benefitting from good health care due to lack of information about them. This paper proposes a geospatial technique to explore vector habitat mapping. The goal was to develop a surveillance methodology that will facilitate quick and efficient management of HAT.  Supervised classification and fuzzy logic were integrated to classify land cover and ancillary datasets into HAT vector habitat. The importance of criteria and how they were prioritised were determined by the judgments of experts, the impact of the criteria on HAT propagation and previous studies. Spatial distribution/habitat characteristics play an important role in HAT propagation. Therefore, locations which have all or most of these criteria present are vital for HAT propagation. This study helped distinguish HAT vector habitat into different zones (breed, feed and rest), the classification scheme is expected to offer effective decision support to all stakeholders. Keywords: Geospatial, Remote Sensing, Geographic Information Systems, Fuzzy, Vecto