Assessing environmental impacts of COVID-19 emergency public health measures in Oxford City.

评估牛津市 COVID-19 紧急公共卫生措施的环境影响。

• 批准号: NE/V010360/1
• 负责人: Suzanne Bartington
• 金额: $ 26.41万
• 依托单位: University of Birmingham
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2020
• 资助国家: 英国
• 起止时间: 2020 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=NE%2FV010360%2F1
• 关键词: Assessing; environmental; impacts; COVID; 19

Emergency public health measures were implemented across the UK in early 2020 to suppress COVID-19 transmission; with major implications for ambient air quality (AQ). Well publicised satellite data have indicated associated reductions in air pollutant (AP) concentrations with potential benefits for human health; however ground-based measurements suggest more complex trends in UK cities. These events present a unique natural experimental opportunity to better understand environmental consequences arising from these measures and to apply this learning to future AQ intervention scenarios.Our research focus is Oxford (population ~155,000). Oxford has significant AQ and health inequity challenges, with the equivalent of 1 in 20 early deaths attributed to AP exposure. The City and County Councils plan to introduce a Zero Emissions Zone and enhanced Low Emission Zone from 2021 and to achieve carbon neutral status by 2030. Oxford is also a focal point for existing research activity, including NIHR, Defra, Highways England and Research England funded studies supporting a broad range of environmental and transport monitoring capabilities and existing research infrastructure, which we plan to utilise and repurpose for this study.We plan a 18 month study to integrate longitudinal data arising from multiple observational inputs (e.g. AQ, noise, smart roadside sensors) to enable robust evaluation of the positive and negative impacts of introduction, maintenance and removal of COVID-19 measures in Oxford City. The data we assimilate will be used to generate a series of AQ control scenarios and predicted health benefits, thereby informing and redefining council-led AQ policy and climate strategy.

在2020年初，整个英国实施了紧急公共卫生措施，以抑制Covid-19的传播；对环境空气质量（AQ）产生了重大影响。广泛宣传的卫星数据表明，空气污染物（AP）浓度的降低，对人类健康的潜在益处；但是，基于地面的测量表明英国城市的趋势更加复杂。这些事件带来了独特的自然实验机会，可以更好地了解这些措施引起的环境后果，并将这些学习应用于未来的AQ干预场景。我们的研究重点是牛津（人口约155,000）。牛津面临巨大的AQ和健康不平等挑战，相当于20早期死亡中的1个归因于AP暴露。 The City and County Councils plan to introduce a Zero Emissions Zone and enhanced Low Emission Zone from 2021 and to achieve carbon neutral status by 2030. Oxford is also a focal point for existing research activity, including NIHR, Defra, Highways England and Research England funded studies supporting a broad range of environmental and transport monitoring capabilities and existing research infrastructure, which we plan to utilise and repurpose for this study.We plan a 18 month study整合由多个观察性输入（例如水溶液，噪声，智能路边传感器）引起的纵向数据，以便对牛津市的COVID-19措施的引入，维护和删除的正面和负面影响进行强有力的评估。我们同化的数据将用于生成一系列AQ控制方案并预测健康益处，从而为理事会主导的AQ政策和气候战略提供信息。

项目成果

The impact of COVID-19 public health restrictions on particulate matter pollution measured by a validated low-cost sensor network in Oxford, UK.

• DOI: 10.1016/j.buildenv.2023.110330
• 发表时间: 2023-06-01
• 期刊: BUILDING AND ENVIRONMENT
• 影响因子: 7.4
• 作者: Bush, Tony;Bartington, Suzanne;Pope, Francis D.;Singh, Ajit;Thomas, G. Neil;Stacey, Brian;Economides, George;Anderson, Ruth;Cole, Stuart;Abreu, Pedro;Leach, Felix C. P.
• 通讯作者: Leach, Felix C. P.

Air quality sensing technology: opportunities and challenges for local applications

空气质量传感技术：本地应用的机遇与挑战

• 发表时间: 2023
• 作者: Tony Bush

COVID-19 Impacts on Air Quality in Oxford City

COVID-19 对牛津市空气质量的影响

• 发表时间: 2022
• 作者: Suzanne Bartington

Machine Learning Techniques to Improve the Field Performance of Low-Cost Air Quality Sensors

机器学习技术可提高低成本空气质量传感器的现场性能

• DOI: 10.5194/amt-2021-282
• 发表时间: 2021
• 作者: Bush T

Impacts of COVID-19 Lockdown on Traffic Flow, Active Travel and Gaseous Pollutant Concentrations; Implications for Future Emissions Control Measures in Oxford, UK

COVID-19 封锁对交通流量、活跃出行和气体污染物浓度的影响；

• DOI: 10.3390/su142316182
• 发表时间: 2022
• 期刊: Sustainability
• 影响因子: 3.9
• 作者: Singh A