Showing papers by "Margaret Bell published in 2020"
TL;DR: In this article, an attempt has been made to investigate the exhaust and non-exhaust emissions emitted from selected roads in Delhi city, based on the vehicular density per hour and speed, three categories of roads have been considered in the present study.
Abstract: Introduction Personal exposure to elevated vehicle exhaust and non-exhaust emissions at urban roadside leads to carcinogenic health effects, respiratory illness and nervous system disorders. In this paper, an attempt has been made to investigate the exhaust and non-exhaust emissions emitted from selected roads in Delhi city. Methods Based on the vehicular density per hour and speed, three categories of roads have been considered in the present study: (a) low density road (≤1000 vehicles/hour, V ≥ 10 m/s); (b) medium density road (>1000 vehicles/hour but ≤ 2000 vehicles/hour, V ≥ 7.5 m/s 2000 vehicles/hour, V Results Results indicated real-world NO exhaust emissions of 0.5 g/m3 (2.03 g/km) on high-density roads and 0.23 g/m3 (0.67 g/km) on low and medium density roads. These values were significantly higher than the Bharat Standard (BS) IV (0.25 g/km). The silt load on the different types of roads indicated 3, 25 and 44 g/m2 -day dust deposition on, low, medium and high-density road, respectively. PM2.5 and PM10 emission rates were measured using US-EPA AP-42 methodology and were found to be least at low-density roads with values of 0.54 and 2.22 g/VKT (VKT -Vehicle Kilometer Travelled) respectively, and highest for high density roads with values of 12.40 and 51.25 g/VKT respectively. Conclusion The present study reveals that both tailpipe (exhaust) and resuspend able road dust (non-exhaust) emissions contributes significantly and deteriorates local air quality. Although there exists emission standards, but there are no enforced regulations for non-exhaust emissions (resuspension of road dust). Hence, there is need to regulate non-exhaust emissions on urban roads.
16 citations
TL;DR: If REDUCE provides evidence showing that access to internet and telephone support enables more patients to stop treatment without increasing depression, it will try to implement the intervention throughout the National Health Service.
Abstract: Around one in ten adults take antidepressants for depression in England, and their long-term use is increasing. Some need them to prevent relapse, but 30–50% could possibly stop them without relapsing and avoid adverse effects and complications of long-term use. However, stopping is not always easy due to withdrawal symptoms and a fear of relapse of depression. When general practitioners review patients on long-term antidepressants and recommend to those who are suitable to stop the medication, only 6–8% are able to stop. The Reviewing long-term antidepressant use by careful monitoring in everyday practice (REDUCE) research programme aims to identify safe and cost-effective ways of helping patients taking long-term antidepressants taper off treatment when appropriate. Design: REDUCE is a two-arm, 1:1 parallel group randomised controlled trial, with randomisation clustered by participating family practices. Setting: England and north Wales. Population: patients taking antidepressants for longer than 1 year for a first episode of depression or longer than 2 years for repeated episodes of depression who are no longer depressed and want to try to taper off their antidepressant use. Intervention: provision of ‘ADvisor’ internet programmes to general practitioners or nurse practitioners and to patients designed to support antidepressant withdrawal, plus three patient telephone calls from a psychological wellbeing practitioner. The control arm receives usual care. Blinding of patients, practitioners and researchers is not possible in an open pragmatic trial, but statistical and health economic data analysts will remain blind to allocation. Outcome measures: the primary outcome is self-reported nine-item Patient Health Questionnaire at 6 months for depressive symptoms. Secondary outcomes: depressive symptoms at other follow-up time points, anxiety, discontinuation of antidepressants, social functioning, wellbeing, enablement, quality of life, satisfaction, and use of health services for costs. Sample size: 402 patients (201 intervention and 201 controls) from 134 general practices recruited over 15–18 months, and followed-up at 3, 6, 9 and 12 months. A qualitative process evaluation will be conducted through interviews with 15–20 patients and 15–20 practitioners in each arm to explore why the interventions were effective or not, depending on the results. Helping patients reduce and stop antidepressants is often challenging for practitioners and time-consuming for very busy primary care practices. If REDUCE provides evidence showing that access to internet and telephone support enables more patients to stop treatment without increasing depression we will try to implement the intervention throughout the National Health Service, publishing practical guidance for professionals and advice for patients to follow, publicised through patient support groups. ISRCTN:12417565. Registered on 7 October 2019.
10 citations
TL;DR: The nMote was designed for airport noise and is considered along with the eMote suitable for monitoring traffic noise in urban areas, and demonstrates much potential to be incorporated into existing Intelligent Transport System technologies to measure, manage and control population exposure to traffic noise.
4 citations
TL;DR: In this article, the authors used a cross impact model to identify the uncertainties evident in transport infrastructure planning, focusing on the early decision making stages of the project lifecycle, and found that executive leadership and collaboration between Local Authorities were the most influential determinants for progress.
Abstract: This research devised and demonstrated a method to identify the uncertainties evident in transport infrastructure planning, focussing on the early decision making stages of the project lifecycle. The core of the method used a “Cross Impact” model, anchored in complexity theory to analyse expert opinions on the future for the project. Stakeholder interviews, based around an ideal scenario, were undertaken to elicit opinions about the proposed development, focusing on the decision making steps and environment en-route to the outcome. The interviews were then coded using qualitative data analysis techniques and the emerging variables analysed using the cross impact model. The findings from this case study were that executive leadership and collaboration between Local Authorities were the most influential determinants for progress, and that the prime causes of uncertainty were the extant economic and planning policies. Since the completion of this study, structural transport governance developments have occurred in the UK that have endorsed these findings. This paper focusses on coding of the stakeholder interviews and rationalising the variables which were either present in the scenario or introduced by the stakeholders.
3 citations