Guidelines for assessing the environmental impact of public mass transportation projects. Notebook 2: social impacts. Final report.

Transportation Department, Office of Environment and Safety, Washington, D.C.

Guidelines for assessing the environmental impact of public mass transportation projects. Notebook 4: physical impacts. Final report.

Transportation Department, Office of Environment and Safety, Washington, D.C.

Guidelines for assessing the environmental impact of public mass transportation projects. Notebook 5: environmental assessment reference book. Final report.

Transportation Department, Office of Environment and Safety, Washington, D.C.

Guidelines for assessing the environmental impact of public mass transportation projects. Notebook 3: economic impacts. Final report.

Transportation Department, Office of Environment and Safety, Washington, D.C.

The camera; or, Art of drawing in water colours : with instructions for sketching form nature : comprising the whole process of water-coloured drawing, familiarly exmplified in drawing, shadowing, and tinting a complete landscape ... and directions for compounding and using colours, sepia, Indian ink, bister, &c.

Mode of access: Internet.

The environmental control of reproduction in the female dace, Leuciscus leuciscus

An investigation was made into the nature and control of the annual reproductive cycle of the dace, Leuciscus leuciscus. It includes 1) a study of the natural reproductive cycle, 2) the use of Carp Pituitary Extract (CPE) to induce final maturation and ovulation in captive fish, 3) the effect of artificial light treatments on ovarian development and 4) the measurement of serum melatonin levels under different photoperiod regimes. Ovarian development was monitored by endocrinological data, notably serum cycles of 17-oestradiol (E2), testosterone (T), and calcium (as an index of vitellogenin), oocyte diameter, the gonadosomatic index and histological studies of the ovary. Under natural conditions, ovarian development can broadly be divided into 4 stages: 1) oogenesis which occurs immediately after spawning; 2) a primary growth phase (previtellogenic growth) prevalent between spawning and June; 3) a secondary growth phase (yolk vesicle plus vitellogenic growth) occurring between June and December and 4) final maturation and ovulation which occurs in mid-March. During the annual ovarian cycle, the sex steroids E2 and T showed two clear elevations. The first occurred initially in April followed by a rise in serum calcium levels. This subsequently initiated the appearance of yolk granules in the oocytes in June. The second rise occurred in September and levels were maintained until December, after which there was a decline in serum E2 levels. It is proposed that in the dace, high serum E2 levels between September and December were required to maintain vitellogenin production and therefore its uptake into the developing oocytes which occurred during this time, albeit at a slower rate than in the summer months. After December, prior to final maturation, whereas serum E2 and calcium levels declined, serum T levels remained elevated. In captivity, final maturation beyond the germinal vesicle migration stage failed to occur suggesting that the stimuli required for these events were absent. However ovulation could be induced by a single injection of CPE, which induced ovulation between 6 and 14 hours after treatment. Endocrine events associated with the artificial induction of spawning included a rise in serum levels of E2, T and the maturation inducing steroid 1720-dihydroxy progesterone. Photoperiodic manipulation demonstrated that whereas short or increasing daylengths were stimulatory to ovarian development, long days delayed development. Changes from long to short and constant short daylengths early in the reproductive cycle advanced maturation (up to 5 months), suggesting that the stimulus for ovarian development and maturation was a short day. However, experiments conducted later in the reproductive cycle demonstrated that only a simulated ambient photoperiod could induce final maturation. It is proposed therefore that under natural conditions the environmental stimulus for ovarian development and final maturation are short and increasing daylengths respectively. Further support that photoperiod is the dominant timing cue in this species was provided by the pattern of serum melatonin levels. Under different photoperiod treatments, serum melatonin, which is believed to be the chemical transducer of photoperiodic information (similar to other photoperiodic species) was elevated for the duration of the dark phase, indicating that the dace at least has the ability to `measure' changes in daylength.

The mathematical modelling of the environmental performance of buildings as an aid in the design process

This thesis is a theoretical study of the accuracy and usability of models that attempt to represent the environmental control system of buildings in order to improve environmental design. These models have evolved from crude representations of a building and its environment through to an accurate representation of the dynamic characteristics of the environmental stimuli on buildings. Each generation of models has had its own particular influence on built form. This thesis analyses the theory, structure and data of such models in terms of their accuracy of simulation and therefore their validity in influencing built form. The models are also analysed in terms of their compatability with the design process and hence their ability to aid designers. The conclusions are that such models are unlikely to improve environmental performance since: a the models can only be applied to a limited number of building types, b they can only be applied to a restricted number of the characteristics of a design, c they can only be employed after many major environmental decisions have been made, d the data used in models is inadequate and unrepresentative, e models do not account for occupant interaction in environmental control. It is argued that further improvements in the accuracy of simulation of environmental control will not significantly improve environmental design. This is based on the premise that strategic environmental decisions are made at the conceptual stages of design whereas models influence the detailed stages of design. It is hypothesised that if models are to improve environmental design it must be through the analysis of building typologies which provides a method of feedback between models and the conceptual stages of design. Field studies are presented to describe a method by which typologies can be analysed and a theoretical framework is described which provides a basis for further research into the implications of the morphology of buildings on environmental design.

Modifying the yield factor based on more efficient use of fertilizer — The environmental impacts of intensive and extensive agricultural practices

The aim of this article is to draw attention to calculations on the environmental effects of agriculture and to the definition of marginal agricultural yield. When calculating the environmental impacts of agricultural activities, the real environmental load generated by agriculture is not revealed properly through ecological footprint indicators, as the type of agricultural farming (thus the nature of the pollution it creates) is not incorporated in the calculation. It is commonly known that extensive farming uses relatively small amounts of labor and capital. It produces a lower yield per unit of land and thus requires more land than intensive farming practices to produce similar yields, so it has a larger crop and grazing footprint. However, intensive farms, to achieve higher yields, apply fertilizers, insecticides, herbicides, etc., and cultivation and harvesting are often mechanized. In this study, the focus is on highlighting the differences in the environmental impacts of extensive and intensive farming practices through a statistical analysis of the factors determining agricultural yield. A marginal function is constructed for the relation between chemical fertilizer use and yield per unit fertilizer input. Furthermore, a proposal is presented for how calculation of the yield factor could possibly be improved. The yield factor used in the calculation of biocapacity is not the marginal yield for a given area, but is calculated from the real and actual yields, and this way biocapacity and the ecological footprint for cropland are equivalent. Calculations for cropland biocapacity do not show the area needed for sustainable production, but rather the actual land area used for agricultural production. The proposal the authors present is a modification of the yield factor and also the changed biocapacity is calculated. The results of statistical analyses reveal the need for a clarification of the methodology for calculating marginal yield, which could clearly contribute to assessing the real environmental impacts of agriculture.

Modifying the yield factor based on more efficient use of fertilizer — The environmental impacts of intensive and extensive agricultural practices

The aim of this article is to draw attention to calculations on the environmental effects of agriculture and to the definition of marginal agricultural yield. When calculating the environmental impacts of agricultural activities, the real environmental load generated by agriculture is not revealed properly through ecological footprint indicators, as the type of agricultural farming (thus the nature of the pollution it creates) is not incorporated in the calculation. It is commonly known that extensive farming uses relatively small amounts of labor and capital. It produces a lower yield per unit of land and thus requires more land than intensive farming practices to produce similar yields, so it has a larger crop and grazing footprint. However, intensive farms, to achieve higher yields, apply fertilizers, insecticides, herbicides, etc., and cultivation and harvesting are often mechanized. In this study, the focus is on highlighting the differences in the environmental impacts of extensive and intensive farming practices through a statistical analysis of the factors determining agricultural yield. A marginal function is constructed for the relation between chemical fertilizer use and yield per unit fertilizer input. Furthermore, a proposal is presented for how calculation of the yield factor could possibly be improved. The yield factor used in the calculation of biocapacity is not the marginal yield for a given area, but is calculated from the real and actual yields, and this way biocapacity and the ecological footprint for cropland are equivalent. Calculations for cropland biocapacity do not show the area needed for sustainable production, but rather the actual land area used for agricultural production. The proposal the authors present is a modification of the yield factor and also the changed biocapacity is calculated. The results of statistical analyses reveal the need for a clarification of the methodology for calculating marginal yield, which could clearly contribute to assessing the real environmental impacts of agriculture.

Exploring the Justificational Status of Assertions Made About Nursing’s Collective Beliefs

Nursing publications frequently reference groups (e.g. the group nurses). The nature and capabilities of group agents or collective subjects, and the relationship between nursing as a group and nurses as individuals is, however, rarely made explicit in these publications. Following Alvin Goldman, questions pertaining to groups can be classified as metaphysical or epistemic. Metaphysical questions take two forms. First, we might ask about the ontological status of group agents. For example, to what extent, if at all, do group agents exist and act independently of their constituent members? Second, we can ask whether group agents have psychological states or properties that can, for example, be formulated as propositional attitudes and, if they can, in what ways are group attitudes correlated with or tied to those of individual group members? In this presentation, having recognised the potential reality of group ontological and psychological being, I examine an under researched element of social epistemology. Specifically, the potential of non-individualist reliabilism (social process reliabilism) to justify doxastic group beliefs (i.e. statements such as “nurses believe that”) are considered. It is suggested that this issue has concrete implications for how we think about nursing.

Exploring the potential role of allostatic load biomarkers in risk assessment of patients presenting with depressive symptoms

Background: Depression is a major health problem worldwide and the majority of patients presenting with depressive symptoms are managed in primary care. Current approaches for assessing depressive symptoms in primary care are not accurate in predicting future clinical outcomes, which may potentially lead to over or under treatment. The Allostatic Load (AL) theory suggests that by measuring multi-system biomarker levels as a proxy of measuring multi-system physiological dysregulation, it is possible to identify individuals at risk of having adverse health outcomes at a prodromal stage. Allostatic Index (AI) score, calculated by applying statistical formulations to different multi-system biomarkers, have been associated with depressive symptoms. Aims and Objectives: To test the hypothesis, that a combination of allostatic load (AL) biomarkers will form a predictive algorithm in defining clinically meaningful outcomes in a population of patients presenting with depressive symptoms. The key objectives were: 1. To explore the relationship between various allostatic load biomarkers and prevalence of depressive symptoms in patients, especially in patients diagnosed with three common cardiometabolic diseases (Coronary Heart Disease (CHD), Diabetes and Stroke). 2 To explore whether allostatic load biomarkers predict clinical outcomes in patients with depressive symptoms, especially in patients with three common cardiometabolic diseases (CHD, Diabetes and Stroke). 3 To develop a predictive tool to identify individuals with depressive symptoms at highest risk of adverse clinical outcomes. Methods: Datasets used: ‘DepChron’ was a dataset of 35,537 patients with existing cardiometabolic disease collected as a part of routine clinical practice. ‘Psobid’ was a research data source containing health related information from 666 participants recruited from the general population. The clinical outcomes for 3 both datasets were studied using electronic data linkage to hospital and mortality health records, undertaken by Information Services Division, Scotland. Cross-sectional associations between allostatic load biomarkers calculated at baseline, with clinical severity of depression assessed by a symptom score, were assessed using logistic and linear regression models in both datasets. Cox’s proportional hazards survival analysis models were used to assess the relationship of allostatic load biomarkers at baseline and the risk of adverse physical health outcomes at follow-up, in patients with depressive symptoms. The possibility of interaction between depressive symptoms and allostatic load biomarkers in risk prediction of adverse clinical outcomes was studied using the analysis of variance (ANOVA) test. Finally, the value of constructing a risk scoring scale using patient demographics and allostatic load biomarkers for predicting adverse outcomes in depressed patients was investigated using clinical risk prediction modelling and Area Under Curve (AUC) statistics. Key Results: Literature Review Findings. The literature review showed that twelve blood based peripheral biomarkers were statistically significant in predicting six different clinical outcomes in participants with depressive symptoms. Outcomes related to both mental health (depressive symptoms) and physical health were statistically associated with pre-treatment levels of peripheral biomarkers; however only two studies investigated outcomes related to physical health. Cross-sectional Analysis Findings: In DepChron, dysregulation of individual allostatic biomarkers (mainly cardiometabolic) were found to have a non-linear association with increased probability of co-morbid depressive symptoms (as assessed by Hospital Anxiety and Depression Score HADS-D≥8). A composite AI score constructed using five biomarkers did not lead to any improvement in the observed strength of the association. In Psobid, BMI was found to have a significant cross-sectional association with the probability of depressive symptoms (assessed by General Health Questionnaire GHQ-28≥5). BMI, triglycerides, highly sensitive C - reactive 4 protein (CRP) and High Density Lipoprotein-HDL cholesterol were found to have a significant cross-sectional relationship with the continuous measure of GHQ-28. A composite AI score constructed using 12 biomarkers did not show a significant association with depressive symptoms among Psobid participants. Longitudinal Analysis Findings: In DepChron, three clinical outcomes were studied over four years: all-cause death, all-cause hospital admissions and composite major adverse cardiovascular outcome-MACE (cardiovascular death or admission due to MI/stroke/HF). Presence of depressive symptoms and composite AI score calculated using mainly peripheral cardiometabolic biomarkers was found to have a significant association with all three clinical outcomes over the following four years in DepChron patients. There was no evidence of an interaction between AI score and presence of depressive symptoms in risk prediction of any of the three clinical outcomes. There was a statistically significant interaction noted between SBP and depressive symptoms in risk prediction of major adverse cardiovascular outcome, and also between HbA1c and depressive symptoms in risk prediction of all-cause mortality for patients with diabetes. In Psobid, depressive symptoms (assessed by GHQ-28≥5) did not have a statistically significant association with any of the four outcomes under study at seven years: all cause death, all cause hospital admission, MACE and incidence of new cancer. A composite AI score at baseline had a significant association with the risk of MACE at seven years, after adjusting for confounders. A continuous measure of IL-6 observed at baseline had a significant association with the risk of three clinical outcomes- all-cause mortality, all-cause hospital admissions and major adverse cardiovascular event. Raised total cholesterol at baseline was associated with lower risk of all-cause death at seven years while raised waist hip ratio- WHR at baseline was associated with higher risk of MACE at seven years among Psobid participants. There was no significant interaction between depressive symptoms and peripheral biomarkers (individual or combined) in risk prediction of any of the four clinical outcomes under consideration. Risk Scoring System Development: In the DepChron cohort, a scoring system was constructed based on eight baseline demographic and clinical variables to predict the risk of MACE over four years. The AUC value for the risk scoring system was modest at 56.7% (95% CI 55.6 to 57.5%). In Psobid, it was not possible to perform this analysis due to the low event rate observed for the clinical outcomes. Conclusion: Individual peripheral biomarkers were found to have a cross-sectional association with depressive symptoms both in patients with cardiometabolic disease and middle-aged participants recruited from the general population. AI score calculated with different statistical formulations was of no greater benefit in predicting concurrent depressive symptoms or clinical outcomes at follow-up, over and above its individual constituent biomarkers, in either patient cohort. SBP had a significant interaction with depressive symptoms in predicting cardiovascular events in patients with cardiometabolic disease; HbA1c had a significant interaction with depressive symptoms in predicting all-cause mortality in patients with diabetes. Peripheral biomarkers may have a role in predicting clinical outcomes in patients with depressive symptoms, especially for those with existing cardiometabolic disease, and this merits further investigation.

Strategies for lowering the environmental impact of different electrochemical energy storage system

The continuous growth of global population brings an exponential increase on energy consumption and greenhouse gas emission in the atmosphere contributing to the increase of the planet temperature. Therefore, it is mandatory to adopt renewable energy production systems like photovoltaic or wind power: unfortunately, the main limit of these technologies is the natural intermittence of the energy sources that limits their applicability. The key enabling technology for a widespread usage of clean power sources are electrochemical energy storage systems, most commonly known as batteries. Batteries will enable the storage of energy during overproduction period and the release during low production period stabilizing the power outcome, allowing the connection to the main grid and increasing the applicability of renewable energy sources. Despite the high number of benefits that the widespread use of batteries will bring, starting from the reduction of CO2 emitted in the atmosphere, it is necessary also to take care of the environmental impact of processes and materials used for the production of electrochemical storage systems. In addition, there are many different battery systems, with different chemistries and designs that require specific strategies. Nowadays, the most part of the materials and chemicals used for battery production are toxic for humans and the environment. For this reason, this Ph.D. thesis addresses the challenging scope of lowering the environmental impact of manufacturing processes of different electrochemical energy storage systems using natural derived or low carbon footprint materials while increasing the performances with respect to commercial devices. The activities carried out during my Ph.D. cover a high number of different electrochemical storage systems involving a wide range of electrochemical processes from capacitive to faradic. New materials, different production processes and new battery design, all in view of sustainability and low environmental impact, increased the innovative and challenging aspects of this work.

Long-term Prospects For The Environmental Profile Of Advanced Sugar Cane Ethanol.

This work assessed the environmental impacts of the production and use of 1 MJ of hydrous ethanol (E100) in Brazil in prospective scenarios (2020-2030), considering the deployment of technologies currently under development and better agricultural practices. The life cycle assessment technique was employed using the CML method for the life cycle impact assessment and the Monte Carlo method for the uncertainty analysis. Abiotic depletion, global warming, human toxicity, ecotoxicity, photochemical oxidation, acidification, and eutrophication were the environmental impacts categories analyzed. Results indicate that the proposed improvements (especially no-til farming-scenarios s2 and s4) would lead to environmental benefits in prospective scenarios compared to the current ethanol production (scenario s0). Combined first and second generation ethanol production (scenarios s3 and s4) would require less agricultural land but would not perform better than the projected first generation ethanol, although the uncertainties are relatively high. The best use of 1 ha of sugar cane was also assessed, considering the displacement of the conventional products by ethanol and electricity. No-til practices combined with the production of first generation ethanol and electricity (scenario s2) would lead to the largest mitigation effects for global warming and abiotic depletion. For the remaining categories, emissions would not be mitigated with the utilization of the sugar cane products. However, this conclusion is sensitive to the displaced electricity sources.

Exploring the emission intensities of ICP OES aided by chemometrics in the geographical discrimination of mineral waters

A rapid method for classification of mineral waters is proposed. The discrimination power was evaluated by a novel combination of chemometric data analysis and qualitative multi-elemental fingerprints of mineral water samples acquired from different regions of the Brazilian territory. The classification of mineral waters was assessed using only the wavelength emission intensities obtained by inductively coupled plasma optical emission spectrometry (ICP OES), monitoring different lines of Al, B, Ba, Ca, Cl, Cu, Co, Cr, Fe, K, Mg, Mn, Na, Ni, P, Pb, S, Sb, Si, Sr, Ti, V, and Zn, and Be, Dy, Gd, In, La, Sc and Y as internal standards. Data acquisition was done under robust (RC) and non-robust (NRC) conditions. Also, the combination of signal intensities of two or more emission lines for each element were evaluated instead of the individual lines. The performance of two classification-k-nearest neighbor (kNN) and soft independent modeling of class analogy (SIMCA)-and preprocessing algorithms, autoscaling and Pareto scaling, were evaluated for the ability to differentiate between the various samples in each approach tested (combination of robust or non-robust conditions with use of individual lines or sum of the intensities of emission lines). It was shown that qualitative ICP OES fingerprinting in combination with multivariate analysis is a promising analytical tool that has potential to become a recognized procedure for rapid authenticity and adulteration testing of mineral water samples or other material whose physicochemical properties (or origin) are directly related to mineral content.