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Development of Methods, Models, and Datasets for Science-Based Air Pollution Decision-Making

Development of Methods, Models, and Datasets for Science-Based Air Pollution Decision-Making
开发基于科学的空气污染决策方法、模型和数据集
批准号:
RGPIN-2016-06181
负责人:
Hakami, Amir
金额:
$1.97万
依托单位:
依托单位国家:
加拿大
项目类别:
Discovery Grants Program - Individual
财政年份:
2018
资助国家:
加拿大
项目状态:
已结题
起止时间:
2018-01-01 至 2019-12-31

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中文摘要
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英文摘要
Worldwide, an estimated 3.4 million deaths per year occur because of exposure to outdoor air pollution. The magnitude of this health burden highlights the severity of air pollution as a risk factor for illness and premature death globally and to Canadians. Due to the complex nature of air pollution, there is a need to better understand and more effectively manage air quality based on the best available science.******Our research program will provide estimates of the health and agricultural benefits (or price tags) of reducing air pollutant emissions across Canada. Such data will be made publically available in an open-access database to strengthen the basis for scientific research and communications. We will investigate how the health benefits of reducing emissions change going into the future, as pollution regulations become stricter. Recent scientific research indicates that efforts to reduce emissions today, not only bring immediate health benefits to Canadians, but are also a compounding investment in the health of future generations. We will examine public health benefits with a forward-looking lens and in the context of a dynamic world with a warming climate. Climate change is another pressing issue facing society, and efforts to reduce greenhouse gas emissions (such as CO2) often carry ancillary benefits to the environment and human health beyond their climate impacts. Our research will address the interplay between climate and air quality, with a focus on policies aimed at reducing CO2 emissions from fossil fuel sources that in turn reduce emissions of air pollutants.******While the above components focus on long-term exposure to air pollution, short-term changes in air quality are also of importance to the health of Canadians. Air quality in Canada is forecasted daily and communicated to the public by means of the Air Quality Health Index. We propose to develop a system to forecast and communicate air pollution sensitivities – how changes in emitting activities (such as driving or electricity generation) impact air pollution on a particular day. This framework will educate and engage the public on their role in proactively reducing air pollution and aims to increase the sense of social responsibility in the Canadian public. Our proposal recognizes the uncertainties in estimating health and environmental impacts of emitters. Our research program will quantify these uncertainties in order to communicate measures of confidence in scientific data, and to environmental managers and the general public.
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Development of Methods, Models, and Datasets for Science-Based Air Pollution Decision-Making
  • 批准号:
    RGPIN-2016-06181
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $1.97万
  • 财政年份:
    2021
  • 负责人:
    Hakami, Amir
  • 依托单位:
Development of Methods, Models, and Datasets for Science-Based Air Pollution Decision-Making
  • 批准号:
    RGPIN-2016-06181
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $1.97万
  • 财政年份:
    2020
  • 负责人:
    Hakami, Amir
  • 依托单位:
Development of Methods, Models, and Datasets for Science-Based Air Pollution Decision-Making
  • 批准号:
    RGPIN-2016-06181
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $1.97万
  • 财政年份:
    2019
  • 负责人:
    Hakami, Amir
  • 依托单位:
Development of Methods, Models, and Datasets for Science-Based Air Pollution Decision-Making
  • 批准号:
    RGPIN-2016-06181
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $1.97万
  • 财政年份:
    2017
  • 负责人:
    Hakami, Amir
  • 依托单位:
国内基金
海外基金
Computational Methods for Analyzing Toponome Data