Project 1: Greenspace to build resilience to climate change impacts on health: The good, the bad, and the future

项目摘要-组件：项目1 城市绿地被认为是提高气候变化韧性的有效工具，通过提供 有利于环境、社会和公共健康。然而，绿地的意外后果有 已经观察到火灾风险增加、过敏原和病媒以及传染病的动物宿主。至 有效地将城市绿地纳入城市规划和设计，对于规划者和 让设计师了解城市绿地发展对公共健康的更广泛影响和权衡 结果。绿地的特定组成和形态可能会产生不同的环境和 健康结果，但这些探索很少，在实践中严重缺乏细微差别的方法 城市规划。为了解决这一知识鸿沟，我们提议的研究旨在研究城市绿地如何 设计可以提高气候变化的适应能力和公共健康。研究的目标是：(1)评价 基于案例研究的不同组成和形态的城市绿地公共健康权衡 在亚利桑那州凤凰城的一个大城市，与高温有关的疾病和蚊子传播的疾病风险；(2)发展健康 可用于预测拟议的城市绿地设计对健康影响的影响评估工具 和规划；以及(3)通过绿地设计活动将科学研究和社区参与联系起来，以 共同创造知识，并在绿地设计的影响中引发偏好和优先事项。要实现 为了实现这些目标，我们将整合气候/天气、与高温相关的疾病、蚊子数量和社会-- 亚利桑那州凤凰城和图森大都会地区城市绿地人口统计 来自集成数据可视化核心。我们将使用条件空间自回归模型(Car)。 为了分析城市绿地(例如，类型、组成和形态)与热之间的关系- 与此相关的疾病和蚊子数量。我们将开发一个健康影响评估工具，基于 基于菲尼克斯都市圈数据训练的机器学习模型及其现场验证 在图森大都市区内进行的收藏。该工具将用于评估性能 当前城市绿地和未来城市绿地发展的不同设计场景， 评估不同水平的耐热能力，潜在的与气候变化相关的健康影响，并确定 绿地分配不均加剧了不平等。最后，我们将开发一个平台，用于 社区成员通过对其环境的观察和参与来共同产生知识 决策者和社区成员制定绿地规划的优先事项。

PROJECT ABSTRACT – Component: Project 1 Urban greenspaces are recognized as an effective tool for increasing climate change resilience by providing environmental, social, and public health benefits. However, unintended consequences of greenspaces have been observed, such as increased fire risks, allergens and vectors and animal hosts of infectious diseases. To effectively incorporate urban greenspaces into urban planning and design, it is critical for planners and designers to understand the broader impacts and trade-offs of urban greenspace development on public health outcomes. Specific compositions and morphologies of greenspaces may generate different environmental and health outcomes but these are poorly explored and nuanced approaches are critically lacking in the practice of urban planning. To address this knowledge gap, our proposed study aims to examine how urban greenspace designs can increase climate change resilience and public health. The study objectives are to: (1) evaluate the public health trade-offs of urban greenspaces with varying composition and morphology using a case study of heat-related illness and mosquito-borne disease risk in a large urban city, Phoenix, AZ; (2) develop a health effects assessment tool that can be used to predict the health impacts of proposed urban greenspace designs and plans; and (3) link scientific research and community engagement through greenspace design activities to co-produce knowledge, and elicit preferences and priorities in the impacts of greenspace design. To achieve these goals, we will integrate data on climate/weather, heat-related illnesses, mosquito abundance, and socio- demographics on urban greenspaces in Phoenix and Tucson metropolitan areas in Arizona with assistance from the Integrated Data Visualization Core. We will use the conditional spatial autoregression models (CAR) to analyze the associations between urban greenspaces (e.g., types, composition, and morphology) and heat- related illnesses and mosquito abundance. We will develop a health effects assessment tool based on a machine learning model trained with data from Phoenix metropolitan area and validated based on field collections conducted within the Tucson metropolitan area. This tool will be used to evaluate the performance of current urban greenspaces and different design scenarios of future urban greenspace development, to estimate varying levels of heat resilience, potential climate change-related health effects, and to identify inequities exacerbated by inequitable distribution of greenspace. Finally, we will develop a platform for community members to co-produce knowledge through observations of their environment and engage decision-makers and community members to develop priorities for greenspace planning.