Characterisation of unresolved complex mixtures of hydrocarbons by degradative methods

Merged with duplicate record (10026.1/698) on 03.01.2017 by CS (TIS)This is a digitised version of a thesis that was deposited in the University Library. If you are the author please contact PEARL Admin ([email protected]) to discuss options.Unresolved Complex Mixtures (UCMs) of hydrocarbons are found in crude and refined oils and in water, sediments and biota polluted with oils. The concentrations of UCMs in oils are significant (e. g. >65% of the aliphatic hydrocarbons in fresh Kuwait crude) and it is perhaps surprising that virtually nothing is known about UCM composition. The present study sought to redress this paucity of information in three main ways: First, following two recent studies of aliphatic UCMs, an investigation of the composition of the "aromatic" UCM of Venezuelan Tia Juana Pesado crude oil was made by spectroscopic (IR, NMR, MS) and oxidative (CrO3, Ru04) methods. These showed that the UCM was, in fact, highly aliphatic. The major compounds identified were alkyl substituted naphthenoaromatics with one and two aromatic rings. Chemical oxidation indicated that the alkyl branched side chains extended to at least twenty three carbon atoms. Second, an investigation into the origins of UCMs was made. The products of hydrous pyrolysis of man-made (polythene) and biogenic (cutan) polymers under conditions proposed previously to simulate catagenesis, included, in the hydrocarbons, high proportions of UCMs (50% - >70%). Hydrous pyrolysis of polythene produced a mixture of saturated (56%) and olefinic (44%) hydrocarbons, whilst pyrolysis of cutan produced hydrocarbon (aliphatic and aromatic; 30-75%) and nonhydrocarbon (70-25%) fractions, both with >60% unresolved components. Oxidative characterisation of these UCMs produced mainly n-acids with somewhat similar results to those found when oil UCMs were oxidised. However, the laboratory generated UCMs are not perfect oil UCM models since some oil UCM oxidation products were not observed in the laboratory models. Finally, an attempt was made to release the geochemical information contained within UCMs. Replicate oxidations of milligram quantities of oil UCMs followed by quantitative GCMS characterisation and multivariate statistical analysis of the resolved oxidation products gave reproducible distributions with >80% similarity. Application of this method to two oil spill incidents where the source oil was known (Milford Haven and the Humber Estuary) gave good correlations between sediment and source. In contrast analysis of Mersey Estuary sediments contaminated with heavy asphaltic oil and of Sullom Voe sediments contaminated with UCMs failed to show any correlation between the sediments and the source oils. However, subsequent re-analysis of the data excluding the major UCM oxidation products (n-carboxylic acids) produced better correlations which indicated that the greatest correlation potential for these UCMs was contained within the minor oxidation products. A similar study of UCMs from two oil seeps from the Siljan Ring region of Sweden failed to show any correlation with potential source rocks, in agreement with biomarker data. This study has extended present knowledge of UCM composition and suggested a mechanism for UCM formation. Furthermore, quantitative and statistical analysis of UCM oxidation products has been shown to be useful for oil identification. There is still much to be learned about UCMs and the subject should provide a fruitful area for further research. Some possible approaches are suggested. Parts of this work have been published [Revill et al. (1991), Organic Geochemistry: Advances and Applications in Energy and the Natural Environment, Manchester University Pressthe Natural Environment Research Counci

Constraining the carbon budgets of croplands with Earth observation data

Cropland management practices have traditionally focused on maximising the production of food, feed and fibre. However, croplands also provide valuable regulating ecosystem services, including carbon (C) storage in soil and biomass. Consequently, management impacts the extents to which croplands act as sources or sinks of atmospheric carbon dioxide (CO2). And so, reliable information on cropland ecosystem C fluxes and yields are essential for policy-makers concerned with climate change mitigation and food security. Eddy-covariance (EC) flux towers can provide observations of net ecosystem exchanges (NEE) of CO2 within croplands, however the tower sites are temporally and spatially sparse. Process-based crop models simulate the key biophysical mechanisms within cropland ecosystems, including the management impacts, crop cultivar, soil and climate on crop C dynamics. The models are therefore a powerful tool for diagnosing and forecasting C fluxes and yield. However, crop model spatial upscaling is often limited by input data (including meteorological drivers and management), parameter uncertainty and model complexity. Earth observation (EO) sensors can provide regular estimates of crop condition over large extents. Therefore, EO data can be used within data assimilation (DA) schemes to parameterise and constrain models. Research presented in this thesis explores the key challenges associated with crop model upscaling. First, fine-scale (20-50 m) EO-derived data, from optical and radar sensors, is assimilated into the Soil-Plant-Atmosphere crop (SPAc) model. Assimilating all EO data enhanced the simulation of daily C exchanges at multiple European crop sites. However, the individually assimilation of radar EO data (as opposed to combined with optical data) resulted in larger improvements in the C fluxes simulation. Second, the impacts of reduced model complexity and driver resolution on crop photosynthesis estimates are investigated. The simplified Aggregated Canopy Model (ACM) – estimating daily photosynthesis using coarse-scale (daily) drivers – was calibrated using the detailed SPAc model, which simulates leaf to canopy processes at half-hourly time-steps. The calibrated ACM photosynthesis had a high agreement with SPAc and local EC estimates. Third, a model-data fusion framework was evaluated for multi-annual and regional-scale estimation of UK wheat yields. Aggregated model yield estimates were negatively biased when compared to official statistics. Coarse-scale (1 km) EO data was also used to constrain the model simulation of canopy development, which was successful in reducing the biases in the yield estimates. And fourth, EO spatial and temporal resolution requirements for crop growth monitoring at UK field-scales was investigated. Errors due to spatial resolution are quantified by sampling aggregated fine scale EO data on a per-field basis; whereas temporal resolution error analysis involved re-sampling model estimates to mimic the observational frequencies of current EO sensors and likely cloud cover. A minimum EO spatial resolution of around 165 m is required to resolve the field-scale detail. Monitoring crop growth using EO sensors with a 26-day temporal resolution results in a mean error of 5%; however, accounting for likely cloud cover increases this error to 63%

Setting research priorities in Global Health : appraising the value of evidence generation activities to support decision-making in health care

The allocation of scarce resources among competing health care priorities is a key objective in all jurisdictions, whether in low- and middle-income countries (LMICs) or high-income countries. This involves allocating resources to ensure access to health care programmes, which can deliver improvements in health, but also to managing innovation in the development of new technologies, and investing in evidence generation activities to improve health for future generations. The allocation of health care resources among competing priorities requires an assessment of the expected health effects and costs of investing resources in the different activities and the opportunity costs of these expenditures, as well as an assessment of the uncertainty in health effects and costs. Uncertainty can lead to unintended adverse health consequences, e.g., when expected benefits of an activity are not realised when implemented in practice, or resources committed by an activity are transferred away from other health improving activities. The consequences of uncertainty can be reduced by investing in evidence generation activities that improve the information available to support future resource allocation decisions. An analytic framework is developed to assess the value of evidence generation activities to support international research funders, who have the responsibility for allocating funds among competing research priorities in Global Health. Within the framework, the costs and health benefits of evidence generation activities are assessed using the same principles as those employed when evaluating the cost-effectiveness of investments in service provision. Metrics of value, founded on an understanding of the health opportunity costs imposed by research expenditure, are used to quantify the scale of the potential global net health impact across all beneficiary populations (in net disability-adjusted life years averted), or the equivalent health care system resources required to deliver this net health impact, and research costs and their potential health opportunity costs. The framework can be applied to answer key questions such as: whether investment in research activities is worthwhile; which research activities should be prioritised; what type of research activity is necessary and what is the most appropriate design of the research; what are the opportunity costs associated with evidence generation; what is the optimal timing of research; and whether evidence generation activities should be prioritised over investments in service provision or new technology development. An illustrative example is used to demonstrate the application of the framework for informing research priorities in Global Health

Insights for the partitioning of ecosystem evaporation and transpiration in short‐statured croplands

Reducing water losses in agriculture needs a solid understanding of when evaporation (E) losses occur and how much water is used through crop transpiration (T). Partitioning ecosystem T is however challenging, and even more so when it comes to short-statured crops, where many standard methods lead to inaccurate measurements. In this study, we combined biometeorological measurements with a Soil-Plant-Atmosphere Crop (SPA-Crop) model to estimate T and E at a Swiss cropland over two crop seasons with winter cereals. We compared our results with two data-driven approaches: The Transpiration Estimation Algorithm (TEA) and the underlying Water Use Efficiency (uWUE). Despite large differences in the productivity of both years, the T to evapotranspiration (ET) ratio had relatively similar seasonal and diurnal dynamics, and averaged to 0.72 and 0.73. Our measurements combined with a SPA-Crop model provided T estimates similar to the TEA method, while the uWUE method produced systematically lower T even when the soil and leaves were dry. T was strongly related to the leaf area index, but additionally varied due to climatic conditions. The most important climatic drivers controlling T were found to be the photosynthetic photon flux density (R2 = 0.84 and 0.87), and vapor pressure deficit (R2 = 0.86 and 0.70). Our results suggest that site-specific studies can help establish T/ET ratios, as well as identify dominant climatic drivers, which could then be used to partition T from reliable ET measurements. Moreover, our results suggest that the TEA method is a suitable tool for ET partitioning in short-statured croplands

The effects of temporary exclusion of activity due to wind farm construction on a lobster (Homarus gammarus) fishery suggests a potential management approach

Offshore wind farms form an important part of many countries strategy for responding to the threat of climate change but their development can conflict with other offshore activities. Static gear fisheries targeting sedentary benthic species are particularly affected by spatial management that involves exclusion of fishers. Here we investigate the ecological effect of a short-term closure of a European lobster (Homarus gammarus (L.)) fishing ground, facilitated by the development of the Westermost Rough offshore wind farm located on the north-east coast of the United Kingdom. We also investigate the effects on the population when the site is reopened on completion of the construction. We find that temporary closure offers some respite for adult animals and leads to increases in abundance and size of the target species in that area. Reopening of the site to fishing exploitation saw a decrease in catch rates and size structure, this did not reach levels below that of the surrounding area. Opening the site to exploitation also allows the fishery to recuperate some of the economic loss during the closure. We suggest that our results may indicate that temporary closures of selected areas may be beneficial and offer a management option for lobster fisheries

Contribution of floodplain wetland pools to the ecological functioning of the Fitzroy River Estuary

Coastal wetlands function as links between terrestrial and marine ecosystems throughout the world. They have vibrant and diverse flora and fauna, and are crucial habitats for fish and invertebrates, often providing critical nursery grounds and are major contributors of nutrients to coastal systems. However, our present understanding of tropical and subtropical estuarine floodplain wetlands is limited, particularly in tropical and subtropical areas. This lack of understanding, together with their extensive ecological importance and their value to so many user groups, makes detailed understanding of estuarine floodplain wetlands an important research priority. The delta of the Fitzroy River, in Central Queensland, has extensive wetlands clustered around its large estuary system. Except during flooding, the aquatic environment of the wetlands is restricted to a number of semi-permanent pools of varying types and sizes, which are recognised as important nursery habitats for marine fish, such as barramundi. Unfortunately, the way these habitats provide for juvenile fish, and how juvenile fish interact with other animals and plants associated with the pools (as prey or predators) is unknown. Similarly, there is no knowledge of how aquatic animals are influenced by the type of pool environment (eg. marine or freshwater influenced), or how the compositions and fates of pool inhabitants are influenced by the degree and regularity of connection to other habitats. Thus the current project aims to extend, broaden and refine our understanding by investigating the in luence of connectivity on faunal dynamics and food webs of Fitzroy Estuarine Floodplain Wetland Pools. The current study was conducted during a drought period, with no substantial wet season flows during the project. This has two consequences: (1) the study is limited to wetland pools, with little ability to generalise the results to the whole wetland, and (2) the results of the study are not necessarily representative of the situation during wet years