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Gas flaring, the disposal of gas through stacks in an open-air flame, is a common feature in the processing of crude oil, especially in oil-rich regions of the world. The rates of emission of pollutants from gas flaring depend on a number of factors including, but not limited to, fuel composition and quantity, stack geometry, flame/combustion characteristics, and prevailing meteorological conditions. In this work, new estimated emission factors (EFs) for carbon-containing pollutants (excluding PAH) are derived for a specified subset of flame condition. The air pollution dispersion model, ADMS5, is used to simulate the dispersion of pollutants from gas-flaring stacks in the Niger delta. Fuel composition and flare size play significant role in the dispersion pattern and ground-level concentrations of pollutants. To assess the significance of gas-flaring to atmospheric aerosol loading, AERONET aerosol signals are clustered using trajectory analysis to identify dominant aerosol sources at the Ilorin site (4.34o E, 8.32o N) in West Africa. From 7-day back-trajectory calculations over a 10-year period calculated using the UK Universities Global Atmospheric Modelling Programme (UGAMP) trajectory model, which is driven by analyses from the European Centre for Medium-Range Weather Forecasts (ECMWF), dominant sources are identified, using literature classifications: desert dust, biomass burning, and urban-industrial. Using a combination of synoptic trajectories and aerosol optical properties, a fourth source is distinguished: that due to gas flaring. An estimation of the relative impact of these different aerosol sources on the overall radiative forcing at the Ilorin AERONET site was the carried out.

A street canyon is a typical urban configuration with surrounding buildings along the street, where emissions from vehicles are normally released. Buildings are the artificial obstacles to the urban atmospheric flow and give rise to limited ventilation, especially for deep street canyons. This study implements a large-eddy simulation (LES) coupled with a reduced chemical scheme (the LES-chemistry model) to investigate the processing, dispersion and transport of reactive pollutants in a deep street canyon. Spatial variation of reactive pollutants are significant due to the existence of unsteady multiple vortices and pollutant concentrations exhibit significant contrasts within each vortex. In practical applications of using one-box model, the hypothesis of a well-mixed deep street canyon is shown to be inappropriate. A simplified two-box model (vertically segregated) is developed and evaluated against the LES-chemistry model to represent key photochemical processes with timescales similar to and smaller than the turbulent mixing timescale. The two-box model provides the capability of efficiently running a series of emission scenarios under a set of meteorological conditions. In addition, a box model with grid-averaged emissions of street canyons is compared with a two-box model considering each street canyon independently (horizontally segregated) to evaluate uncertainties when grid-averaged emissions are adopted in a grid-based urban air quality model. This study could potentially support traffic management, urban planning strategies and personal exposure assessment.

Air pollution is not only a major risk to the environment, but also a major environmental risk to the health of the population in developed and developing countries. The health impact of both short-term and long-term exposure to air pollution has been the focus of much research in the past few decades, which has investigated the relationship between specific air pollutants, such as carbon monoxide (CO), nitrogen dioxide (NO_2), particulate matter (PM_2.5 and PM_10), and sulphur dioxide (SO_2), to cardiovascular and respiratory diseases. The health impact of short-term exposure is conducted through time series studies, whereas long-term exposure is investigated through cohort studies. Cohort studies are considered the gold-standard research design since inference is made at the individual level and can directly assess cause and effect. However, cohort studies are costly and require a long follow-up period meaning they take a long time to conduct. To counteract these limitations, spatial ecological studies are used instead, which make use of routinely available disease data and air pollutant concentrations at a small areal level, such as census tracts or postcodes. This is to ensure the population under study is relatively homogeneous within the areal unit in terms of socio-demographic characteristics, and thus complements inference from a cohort study. These studies quantify the health impact of exposure to air pollution by relating geographical contrasts between air pollutant concentrations and disease risk across the chosen spatial resolution. The disease data are counts of the numbers of disease cases occurring in each areal unit, and Poisson log-linear models are used to assess the pollutant-health relationship. Other covariate information, such as socio-economic deprivation, is also included to help explain the spatial pattern in disease risk. However, the residual disease risk after the covariate effects have been accounted for tends to contain spatial autocorrelation, which has to be modelled in order to make sound inferences. Residual spatial autocorrelation is typically modelled by a set of random effects that utilise a neighbourhood matrix in order to induce spatial autocorrelation into the model. There are a number of specifications to model this, but this thesis makes use of the Leroux specification due to its flexibility in being able to model both strong and weak spatial autocorrelation. An important issue with using a spatial ecological study design is the estimation of spatially representative pollutant concentrations that are available in each areal unit. Studies can typically use measured data from fixed-location monitors that are spatially sparse and do not provide a pollutant concentration for each areal unit; or they make use of modelled concentrations available at a fine grid square resolution, which are known to contain biases and no measure of uncertainty. There have been numerous statistical approaches to combine both sets of information in order to estimate accurate and spatially representative concentrations. This thesis will develop previous methodology that utilises extra data sources in order to improve the prediction performance of the model for use in a Scottish context. The overarching aim of this thesis is to investigate the cardio-respiratory health effects of long-term exposure to air pollution in West Central Scotland, UK. As the majority of air pollution in this region results from vehicle emissions, nitrogen dioxide (NO_2), a traffic-related gaseous pollutant, will be used to measure air pollution. Models investigating its health effect will incorporate predicted measures of NO_2 developed in this thesis. The sensitivity of the pollutant-health effect to the choice of NO_2 concentrations, indicator of deprivation, and choice of spatial model will be investigated. Changing these factors has been shown to modify estimated pollutant-health effects.\\ Findings in this thesis demonstrated that improvements in the accuracy of fine scale spatial prediction of NO_2 concentrations can be made by utilising extra sources of data in addition to the commonly-used monitoring stations. In addition, the estimated pollutant-health effect is not robust to the choice of the aforementioned factors and the choice of these factors can have a major impact on the resulting pollutant-health effects. This justified the combination of all statistical models into a single effect size, which estimated a small, but positive effect of NO_2 concentrations on cardio-respiratory ill health. However, the estimated NO_2-health relationship was not substantial, possibly due to the NO_2 concentrations in West Central Scotland being too low. Greater variation in the exposure would be needed to observe substantial health impacts.

The long-term adverse effects on health associated with air pollution exposure can be estimated using either cohort or spatio-temporal ecological designs. In a cohort study, the health status of a cohort of people are assessed periodically over a number of years, and then related to estimated ambient pollution concentrations in the cities in which they live. However, such cohort studies are expensive and time consuming to implement, due to the long-term follow up required for the cohort. Therefore, spatio-temporal ecological studies are also being used to estimate the long-term health effects of air pollution as they are easy to implement due to the routine availability of the required data. Spatio-temporal ecological studies estimate the health impact of air pollution by utilising geographical and temporal contrasts in air pollution and disease risk across $n$ contiguous small-areas, such as census tracts or electoral wards, for multiple time periods. The disease data are counts of the numbers of disease cases occurring in each areal unit and time period, and thus Poisson log-linear models are typically used for the analysis. The linear predictor includes pollutant concentrations and known confounders such as socio-economic deprivation. However, as the disease data typically contain residual spatial or spatio-temporal autocorrelation after the covariate effects have been accounted for, these known covariates are augmented by a set of random effects. One key problem in these studies is estimating spatially representative pollution concentrations in each areal which are typically estimated by applying Kriging to data from a sparse monitoring network, or by computing averages over modelled concentrations (grid level) from an atmospheric dispersion model. The aim of this thesis is to investigate the health effects of long-term exposure to Nitrogen Dioxide (NO2) and Particular matter (PM10) in mainland Scotland, UK. In order to have an initial impression about the air pollution health effects in mainland Scotland, chapter 3 presents a standard epidemiological study using a benchmark method. The remaining main chapters (4, 5, 6) cover the main methodological focus in this thesis which has been threefold: (i) how to better estimate pollution by developing a multivariate spatio-temporal fusion model that relates monitored and modelled pollution data over space, time and pollutant; (ii) how to simultaneously estimate the joint effects of multiple pollutants; and (iii) how to allow for the uncertainty in the estimated pollution concentrations when estimating their health effects. Specifically, chapters 4 and 5 are developed to achieve (i), while chapter 6 focuses on (ii) and (iii). In chapter 4, I propose an integrated model for estimating the long-term health effects of NO2, that fuses modelled and measured pollution data to provide improved predictions of areal level pollution concentrations and hence health effects. The air pollution fusion model proposed is a Bayesian space-time linear regression model for relating the measured concentrations to the modelled concentrations for a single pollutant, whilst allowing for additional covariate information such as site type (e.g. roadside, rural, etc) and temperature. However, it is known that some pollutants might be correlated because they may be generated by common processes or be driven by similar factors such as meteorology. The correlation between pollutants can help to predict one pollutant by borrowing strength from the others. Therefore, in chapter 5, I propose a multi-pollutant model which is a multivariate spatio-temporal fusion model that extends the single pollutant model in chapter 4, which relates monitored and modelled pollution data over space, time and pollutant to predict pollution across mainland Scotland. Considering that we are exposed to multiple pollutants simultaneously because the air we breathe contains a complex mixture of particle and gas phase pollutants, the health effects of exposure to multiple pollutants have been investigated in chapter 6. Therefore, this is a natural extension to the single pollutant health effects in chapter 4. Given NO2 and PM10 are highly correlated (multicollinearity issue) in my data, I first propose a temporally-varying linear model to regress one pollutant (e.g. NO2) against another (e.g. PM10) and then use the residuals in the disease model as well as PM10, thus investigating the health effects of exposure to both pollutants simultaneously. Another issue considered in chapter 6 is to allow for the uncertainty in the estimated pollution concentrations when estimating their health effects. There are in total four approaches being developed to adjust the exposure uncertainty. Finally, chapter 7 summarises the work contained within this thesis and discusses the implications for future research.

No description available.

Biodegradation is a commonly used approach for the removal of organic contaminants from soil, relying on naturally present microorganisms that utilise the pollutants as an energy source. Often these sites are co-contaminated with heavy metals and the aim of the current research was to investigate how this affects the biodegradation of 16 US EPA priority polycyclic aromatic hydrocarbons (PAHs), both in terms of removal rates and the overall functioning of the soil microbial community. Soil samples were obtained from a Greenfield site in Newcastle upon Tyne. The soil had a high organic content (11.0 %) and also contained elevated lead concentrations as a result of past atmospheric deposition from adjacent industrial activities. PAHs were applied to the soil using a coal tar source dissolved in acetone, giving a total PAH concentration in the spiked soil of 2166 mg kg-1. Individual PAH concentrations ranged from 1.44 mg kg-1 (acenaphthylene) to 325 mg kg-1 (benzo[b]fluoranthene); the benzo[a]pyrene concentration was 255 mg kg-1. The effect of heavy metal co-contaminants on the biodegradation was investigated using separate amendments of cadmium and lead to give respective total concentrations ranging from 133 to 620 mg kg-1 and 340 to 817 mg kg-1. Mercury amendment was used to give an abiotic control. The study was carried out over 40 weeks. For all treatments, the degradation of PAHs was observed to be biphasic. A novel kinetic model was developed to explain this dependence. In the absence of metal amendment, it was found that PAHs comprising two and three benzene rings generally degrade at a faster rate than four- five and six-membered rings. In the presence of metal amendments, overall % biodegradation after 40 weeks is relatively unaffected for two to four-ring PAHs but shows significant impairment for five and six-ring PAHs. Nevertheless, degradation rates generally decrease with increasing metal concentration, as do soil respiration rate, Shannon Diversity Index, and microbial biomass content. Lead appears to exert the greatest inhibitory effect. The novelty of this study arises from the integrated approach to investigating the effect of metal co-contaminants on the biodegradation of all 16 US EPA priority PAHs together with parameters relating to the functioning and diversity of the soil microbial community.

Microplastic pollution has been identified as an ever increasing proportion of marine litter. Despite an increase in microplastic awareness over the last decade, it represents an as yet unquantified threat to the marine environment. The relatively few studies that monitor its distribution and impact have illustrated a range of worrying effects on marine habitats and communities. The Clyde Sea Area (CSA) is subject to many sources of terrestrial and maritime plastic input. The use of plastics in recreational and commercial vessels throughout the CSA is believed to result in large levels of microplastic fibres, which have previously been seen to be ingested by a range of marine organisms. In a study of the breakdown of commonly used polymers in benthic environments, it was found that ropes of 10 mm diameter in sub-tidal conditions release between 0.086 and 0.422g of microfibers per meter per month in the early stages of degradation. This rate would be expected to increase over subsequent months, releasing substantial amounts of fibres into the CSA environment. In addition to the presence of numerous sources of microplastics, the CSA is relatively enclosed, and may accumulate high levels of debris as a result. Monthly sampling of the water and sediment in the CSA revealed contamination similar to that observed in other near-shore environments. Thus, it is expected that the potential threat to organisms in other areas will be similar to that observed in the CSA. One organism known to take up microplastics is the Norway lobster, Nephrops norvegicus, the target of the main fishery in the CSA. In this work we examined the levels of microplastic in the gut of N. norvegicus from the Scottish waters. Examination of individuals from the CSA revealed both a high occurrence and high accumulation of microplastic. This was found to be much greater than in N. norvegicus sampled from more remote Scottish waters. As a result, N. norvegicus from the CSA are most likely to suffer from the negative impacts associated with microplastic ingestion than those in offshore or in areas of low anthropogenic activity. In order to determine the potential impacts of microplastic ingestion on N. norvegicus, we first examined the mechanism by which N. norvegicus retain and egest microplastic. The position of microplastic aggregations in the foregut indicates that the gastric mill is the main obstacle to microplastic egestion. Inducing moult in microplastic-fed individuals demonstrated that expulsion of the gut lining during ecdysis enables N. norvegicus to reduce their plastic load, limiting plastic aggregation to the length of a single moult-cycle. In an 8 month controlled-feeding experiment retained plastic was seen to have a range of impacts on N. norvegicus. Feeding rate and body mass was seen to decrease in plastic loaded N. norvegicus, and a reduction was observed in a number of indicators of nutritional state. The results presented in this thesis have a number of implications to the CSA and wider marine environment. The similarity in the level of microplastic observed in the CSA to that of other studies of inshore waters indicates the potential for high microplastic uptake by crustaceans in those areas. The high variability in observed microplastic abundance suggests that small-scale monitoring is unsuitable for monitoring marine microplastic debris, and that use of an indicator species may provide a more reliable method of monitoring that is not subject to small-scale heterogeneity in distribution. The seasonal retention of microplastic by N. norvegicus indicates that crustaceans may provide a suitable indicator of local contamination. However, in the CSA, the high level of fibre aggregation and observed impacts of prolonged retention indicate that microplastic may be causing further pressure on an already exploited resource, reducing the stability of the valuable N. norvegicus population.

Water and environmental resources which provide opportunities for households are threatened by human activities that leads to pollution. The research objectives were to understand the contribution water makes to the livelihoods of urban and peri-urban households; the factors influencing perceptions, attitudes and behaviour in relation to surface water and environmental quality, and measures for promoting community participation in water and environmental management. Ten communities were selected in Accra and its surrounding communities to reflect different levels of infrastructure provision for the study. Four focus group discussions were held in each community, with a mixed group, men, women, and young adults. Issues which emerged were investigated further in a structured household questionnaire survey involving 443 respondents. Key informant interviews were held with the most important government and non government regulatory, research and service provision departments and organizations in water, sanitation, and the environment sectors. Water samples from some of the selected communities were analyzed in the laboratory to compare with respondents’ perceptions. Among the households surveyed, 59.14% were engaged in a water dependent occupation which contributed over 80% of household income in some cases. The study also found that perceptions of water and environment are influenced by the existing social and cultural setting. There were common concepts which helped groups to interpret and make meaning from their environment. The prospects for successful water and environmental interventions can be enhanced through an understanding of this local knowledge and perceptions. There was no clear relationship between attitudes and environmental behaviour or between attitudes and socioeconomic status. Actual behaviour was influenced by ability to pay for services, their availability and the influence of shared community norms. Although citizen participation in water and environmental management decision making is very limited at present, community collective action holds good prospects for future interventions in water and environmental management.

Mitigating maritime pollution linked to the oil and gas sector is increasingly seen as a priority issue in national and international contexts alike. A key policy tool that has been used to address this issue is Environmental Impact Assessment (EIA). It has become the primary means by which potentially adverse environmental impacts can be assessed and mitigated, and in theory, provides a variety of mechanisms for stakeholder engagement in the policy process. However, the governance of EIA in developing countries is embryonic, emergent, and in parts contradictory. This thesis reviews and evaluates EIA procedures as they relate to the Nigerian Maritime Oil and Gas Sector (NMOGS), relying, in particular, on Matland’s work on ambiguity and conflict in policy implementation. I argue that Matland’s scholarship affords valuable new insights into EIA implementation processes, particularly in terms of understanding the complex interactions among policy, business and civil society actors both within and beyond implementing agencies. Thus, the thesis’s broader contribution is to consider how the complex institutional mosaic sorrounding EIA might be conceptualised and understood theoretically by drawing on the rich literature on policy implementation. The empirical analysis utilises semi-structured face-to-face interviews with fifty-six respondents in key government implementing agencies, academia, and civil society. This is supplemented by secondary data on national level environmental policies, as well as surveys of EIA reports of multinational and national oil company projects in two Nigerian states. The thesis has demonstrated that the institutional context of NMOGS is characterised by high levels of interagency conflict and policy ambiguity. A key cause of the ambiguity is that two EIA systems operate in parallel at the national scale, thus making it difficult for the country to achieve its stated aim of attaining sustainable development in the domestic oil and gas sector. I have also found ample evidence of conflict over the roles, responsibilities and duties of Government actors across the whole spectrum of EIA implementation activities.