Arup Global Research Challenge: Novel technologies to understand relationships between green infrastructure and environmental quality in cities

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About half of the world's population lives in urban areas and ongoing migration into city has given rise to larger cities or even megacities. Rapid urbanization and more intensive human activities have led to adverse environmental changes that deplete or impair environmental/ecosystem services; ultimately compromising the sustainability of economic activity. Urban pollution can also impact the health of the natural environment. It has long been recognised that Green Infrastructure (GI), such as trees, grassland, waterbodies, can enhance the quality of city environments. GI can mitigate against some types of urban pollution as well as be affected by urban pollution. However, the interplays between GI and urban pollution and other measures of environmental quality are still poorly understood. By better understanding these relationships, it may be possible to better integrate GI into the design and operation of cities. New monitoring and modelling technologies, such as wireless sensing networks, drones and crowdsourcing, could provide a better understanding of the relationships between GI and the quality of city environments. The aim of the project is therefore to explore how new modelling and monitoring technologies could be used to better understand the potential impact of GI resources within cities on environmental quality. The project will initially involve a detailed review of what new technologies are available for monitoring environmental quality (e.g. ecology, noise, humidity, temperature, NOx, particulates, volatile organic compounds and ozone) in cities. A selection of these technologies will then be employed in a small-scale pilot experimental study to monitor the relationships between one or more types of green infrastructure and environmental quality in a site in York. This pilot study will provide an understanding of how these studies should be designed, how the data should be analysed as well as providing data at high temporal and spatial resolutions on the impacts of the GI.