Managing Air for Green Inner Cities

The challenge articulated in this proposal is: how to develop cities with no air pollution and no heat-island effect by 2050?

It is difficult to predict with precision the future of cities, but there will be significant adaptations and changes by 2050, due to advances in technology, changing populations, social expectations and climate change. A roadmap is needed to ensure that decisions taken as the city evolves lead towards a sustainable future. Approximately half of the energy use, carbon dioxide emissions and exposure to air pollution in cities is due to either buildings or transportation, and this total energy use is increasing. Air pollution is projected to be the leading global cause of mortality by 2050. Therefore the question posed here in terms of air quality and temperature rise is important in its own right. However, these quantities together also provide, perhaps uniquely, specific measurable physical properties that cover an entire city and provide a metric for assessing the sustainability of system-wide decisions.

Traditional approaches to urban environmental control rely on energy-consuming and carbon/toxics-producing heating, ventilation and air conditioning (HVAC) systems. These traditional approaches produce an unsustainable cycle of increasing energy use with associated emissions of carbon dioxide and pollutants leading to rising temperatures implying, in turn, greater use of HVAC. Breaking this vicious cycle requires a completely different engineered solution, one that couples with natural systems and does not depend solely on mechanical systems. This project will develop a facility consisting of an integrated suite of models and an associated management and decision support system that together allow the city design and its operation to manage the air so that it becomes its own HVAC system, with clean, cool air providing low-energy solutions for health and comfort. This will be achieved by using natural ventilation in buildings to reduce demand for energy and ensuring air pollutants are diluted below levels that cause adverse health effects, coupled with increased albedo to reduce the heat island effect plus green (parks) and blue (water) spaces to provide both cooling and filtration of pollutants.

We have brought together a trans-disciplinary research team to construct this facility. It will be comprised of three components: (i) a fully resolved air quality model that interacts with sensor data and provides detailed calculations of the air flow, pollutant and temperature distributions in complex city geometries and is fully coupled to naturally ventilated buildings, and green and blue spaces; (ii) reduced order models that allow rapid calculations for real time analysis and emergency response; and (iii) a cost-benefit model to assess the economic, social and environmental viability of options and decision.

The scientific air quality component is a fully-resolved computational model that couples external and internal flows in naturally ventilated buildings at the building, block and borough scales. It will be supported and validated by field measurements at selected sites and by wind tunnel and salt-bath laboratory studies. The reduced order models will be developed from the computational model and from laboratory process studies, and will be capable of producing gross features such as mean pollutant concentrations and temperatures. They will be used to provide capabilities for scoping studies, and real-time and emergency response. The cost-benefit model will provide the link between the scientific and engineering models and implementation advice. It will include modules for the built environment, public spaces and transportation, and provide estimates of the life-cycle costs and benefits of the various scenarios at the individual building, city block and borough scales. Eventually, it is envisaged that this will also include social and health effects.

The impact of this work will occur over a range of length and time scales and be relevant to many different groups.

In the short term the outcomes will provide new information, understanding and capabilities to manage urban airflow. The management and decision support system will allow policy makers and communities to assess a wide range of options to improve air quality and reduce emissions of pollutants, heat and greenhouse gases. They will be able to quantify the benefits of incorporating the natural environment in the form of green and blue spaces in the urban environment. The capabilities within the modelling suite will allow these considerations to be made from the scale of an individual building up to the whole city. It will be possible to use the system for short-term decisions, such as re-directing cyclists away from polluted areas and for emergency response.

In the medium term we expect to see developments in new sensor technology, analysis and visualisation of environmental data, and improved methodologies for sampling strategies that can be deployed in cities in the UK and around the world, to the benefit of UK industry, and lead to improved environmental conditions for the inhabitants of those cities. The proposed integrated modelling and sensor data approach is the ONLY satisfactory way to exploit the vast quantities of data available from smart cities and in this way react promptly to changes in both pollution (accidental, traffic-induced or terror release) and weather conditions (e.g. temperature).

In the longer term the impact, through improved urban and building design and management, will lead to reduced pollution levels and a reduced city heat-island, with consequent improvements in public health and resilience to the impacts of climate change. This should lead to significant reductions in mortality rates and improved productivity through decreases in morbidity, with large positive economic benefits to the UK and elsewhere. These reductions will also lead to less damage to crops and other plants and help enhance ecosystem services generally.

Thus the proposed work will be of broad interest to all those people, organisations and communities concerned with pollution and heat in the built environment, mitigation of release of hazardous materials, health risk assessment and human health impact (e.g. architects, London government, the Home Office, Homeland Security, etc.) as well as those interested in next generation atmospheric/ocean modelling (e.g. Met Office).

Substantial benefits will be gained from the improved understanding of the variability of urban dispersion patterns and feedbacks through the development and modelling process. This has significant implications for other monitoring and modelling initiatives, as well as for the understanding of previously collected observational data sets and how best to collect new data sets.

The rapid reduced order modelling capability provides the possibility of replacing extensively used Gaussian plume models with associated major improvements in confidence/accuracy and attendant health/finance benefits. It also helps, along with adaptive, focussed numerical resolution, to bridge the gap between the scales - promising highly accurate sub-grid scale models which would have major impacts on computational physics, e.g. turbulent flows.

While our goal of a city with zero heat island and pollution levels is probably not strictly attainable, it is critically important that it remains the target as a 'holy grail', as something to be strived for and to provide a beacon for decisions. It then provides the motivation to remove sources of pollution, to design efficient buildings, and to promote low-consumption life styles. It ensures that the natural environment is valued and cherished, and that urban living is compatible with diversity and thriving ecosystems within the city boundary. This would be a truly wonderful legacy and the largest impact of all.