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Analysis of the Differences Between Pollution Levels into a New and an Old District of a Big City Using Dispersion Simulations at Microscale

  • Gianni Tinarelli
  • Lorenzo Mauri
  • Cristina Pozzi
  • Alessandro Nanni
  • Andrea Ciaramella
  • Valentina Puglisi
  • Tommaso Truppi
  • Giuseppe Carlino
Conference paper
Part of the Springer Proceedings in Complexity book series (SPCOM)

Abstract

The new residential district ‘CityLife’ is under construction inside the city of Milan, northern Italy, replacing the old structure of the trade fair. It consists of relatively insulated blocks, surrounded by many gardens and commercial buildings and no car traffic at the surface. The objective of this study is to simulate and compare the pollution level inside this new area with a more common residential district located not so far away. High resolution simulations have been performed inside two domains – having linear dimension of approximately 1 km – using a microscale modeling system, taking directly into account the effects of buildings and street canyons to the atmospheric mean flow and turbulence. Emissions coming from car traffic (around the new district and inside the old one), underground traffic (emerging from ground-level openings in the new district) and heating systems (during winter) have been taken into account. Background values have been estimated from local measurements using a box model and added to the simulated concentration fields in order to produce a complete view of the local pollution levels. Both average levels of pollution at district scale and local behaviours into sub-zones of the two domains where similar activities are supposed to take place are compared showing the potential benefits inside the new district both in absolute terms and in percentage, setting in evidence which portion of the pollution can be reduced by local interventions.

Keywords

Trade Fair Heat Pump Street Canyon Concentration Field Local Emission 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgments

The authors thanks CityLife S.p.A., for their support in supplying the data necessary for the realization of the work.

References

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Gianni Tinarelli
    • 1
  • Lorenzo Mauri
    • 1
  • Cristina Pozzi
    • 1
  • Alessandro Nanni
    • 1
  • Andrea Ciaramella
    • 2
  • Valentina Puglisi
    • 2
  • Tommaso Truppi
    • 2
  • Giuseppe Carlino
    • 3
  1. 1.ArianetMilanoItaly
  2. 2.Built Environment and Construction Engineering A.B.C. DepartmentPolitecnico di MilanoMilanoItaly
  3. 3.SimulariaTorinoItaly

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