Faculty of Biological and Environmental Sciences, University of Helsinki, Helsinki, Finland.
Helsinki Institute of Sustainability Science (HELSUS), University of Helsinki, Helsinki, Finland.
PLoS One. 2021 Dec 2;16(12):e0260009. doi: 10.1371/journal.pone.0260009. eCollection 2021.
Air pollution is one of the major environmental challenges cities worldwide face today. Planning healthy environments for all future populations, whilst considering the ongoing demand for urbanisation and provisions needed to combat climate change, remains a difficult task.
To combine artificial intelligence (AI), atmospheric and social sciences to provide urban planning solutions that optimise local air quality by applying novel methods and taking into consideration population structures and traffic flows.
We will use high-resolution spatial data and linked electronic population cohort for Helsinki Metropolitan Area (Finland) to model (a) population dynamics and urban inequality related to air pollution; (b) detailed aerosol dynamics, aerosol and gas-phase chemistry together with detailed flow characteristics; (c) high-resolution traffic flow addressing dynamical changes at the city environment, such as accidents, construction work and unexpected congestion. Finally, we will fuse the information resulting from these models into an optimal city planning model balancing air quality, comfort, accessibility and travelling efficiency.
空气污染是当今全球城市面临的主要环境挑战之一。在考虑到城市化的持续需求以及应对气候变化所需的措施的同时，为未来所有人口规划健康的环境仍然是一项艰巨的任务。
结合人工智能（AI）、大气科学和社会科学，提供城市规划解决方案，通过应用新方法并考虑人口结构和交通流量来优化当地空气质量。
我们将使用高分辨率空间数据和链接的电子人口队列来模拟（a）与空气污染相关的人口动态和城市不平等；（b）详细的气溶胶动力学、气溶胶和气相化学以及详细的流动特征；（c）解决城市环境中动态变化的高分辨率交通流量，例如事故、施工工作和意外拥堵。最后，我们将把这些模型产生的信息融合到一个平衡空气质量、舒适度、可达性和旅行效率的最优城市规划模型中。
