High density sensor network system for air quality studies at Heathrow airport
High density sensor network system for air quality studies at Heathrow airport
批准号:
NE/I007229/1
负责人:
Paul Williams
金额:
$6.59万
依托单位:
依托单位国家:
英国
项目类别:
Research Grant
财政年份:
2011
资助国家:
英国
项目状态:
已结题
起止时间:
2011 至 --
中文摘要
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英文摘要
Overview: The overall scientific objective is to demonstrate the potential of low cost sensor network systems for characterising air quality in the urban environment at an appropriate granularity in order to understand the factors which influence pollutant distributions on local scales. The ultimate aim is develop and demonstrate a sensor network system* methodology which, when appropriately deployed, can contribute to scientific, economic, public policy and regulatory issues, crossing climate change, human (health) responses, as well as air quality on local and regional scales. As well as demonstrating a generic capability, the intention of this application is to address a number of specific scientific and ultimately legislative issues relevant to London Heathrow Airport. We therefore propose to deploy a high-density air quality sensor network system in and around London Heathrow Airport for an extended period. This will use state of the art low cost sensors for selected gases and for size speciated aerosols, providing an unprecedented data-set for use in a range of activities and outcomes. Air Quality and Human Health: The World Health Organisation (WHO) reported in 2005 on the effects of air quality on human health and identified the relative contributions to mortality from different components of air pollution. The strongest correlations with health were found to be particulate matter (PM), followed by O3 and NO2; for example it was estimated that a reduction in the PM10 annual mean exposure to 20 ug m-3 would lead to a reduction of 22,000 attributable deaths per year in Europe. The report also identified a substantial reduction in the quality of life for millions of citizens with pre-existing respiratory and/or cardiovascular disease. However, the magnitudes of health impacts per incremental increase in pollutant levels vary between studies, in part due to imperfect knowledge of human exposure particularly within urban locations and complex, multi-source transport infrastructures. The problem lends itself to a high density, long term network of air quality monitoring to refine our understanding of the drivers of the health impacts, and better understand potential mitigation options. London Heathrow Airport: There is also a strong political aspect. In 2004 the DfT established technical panels of experts to strengthen and update the assessment of air quality around Heathrow Airport in response to the Airport Transport White Paper 'The Future of Air Transport'. This identified key planning issues with respect to compliance with air quality standards. Deployment of a Sensor Network at London Heathrow Airport: Miniaturised low cost measurement methodologies are now available for measurements of a range of chemical species and aerosols at concentrations observed in the urban environment, while infrastructures also exist for GPS (positioning) and GPRS (mobile phone data transfer). The proposed primary sensor network would consist of a series of ~60 sensor units combining NO, NO2, CO, O3, CO2, hydrocarbons, SO2, size speciated aerosols, temperature and RH, allowing deployment along the (14 km) perimeter of Heathrow airport at intervals of a few 100 m. Additional sites would be co-located with static AURN sites in neighbouring Boroughs, and on a campaign basis mobile sensors would be deployed. The project also aims to bring complex mathematical techniques to provide innovative ways of calibrating the sensor network, and sophisticated methods for storing and displaying the data obtained. State of the art computer modelling of pollution levels around Heathrow would also be undertaken, with the aim of producing a more refined tool for assessing the potential impacts, e.g. of airport expansion. The intention is that the sensor network would be developed during the first year of the project, deployed during the second year, with major data analysis during the third year.
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