3
Data centre sites
Momentum - Air Quality Dispersion Modelling for Data Centre
Project Momentum involved the development of data centres – or mission critical facilities – in Didcot, Bracknell and Swindon. Since the back-up generators will be fuelled by diesel, we were appointed to carry out an air quality assessment to support our client's planning and environmental permit applications.
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Key details
Project name
Project Momentum
Client
Confidential
Location
Didcot, Swindon and Bracknell
Services provided
- Air quality assessment
Challenge
Each site had a series of 2.4 MW diesel generators that would operate together should an emergency occur and electricity supply to the data centre is interrupted. Whilst an emergency is unlikely, each back-up generator needs to be tested at regular intervals throughout the year and the generators emit potentially harmful pollutants into the air when tested or used in an emergency.
Each generator is expected to be tested for a few hours a year and so the impact on the long-term limit values and objectives were not a major concern. The main concern was the impact of the generators on the short-term air quality limit values and objectives both during testing and if there is an emergency. The challenge was modelling the effects of emissions from the generators without knowing what the weather conditions would be during the time of testing.
Solution
Assessing the impacts using the Atmospheric Dispersion Modelling System (ADMS), we ran the model assuming that the generators operate all year round to predict concentrations using meteorological data collected over 5 years and at a nearby weather station. We compared the model predictions with the short-term limit values and objectives for this highly conservative scenario. Where these were met, we were confident the air quality effects were not likely to be significant. This was the case for all pollutants except nitrogen dioxide.
As the short-term limit value and objective for nitrogen dioxide was not met for this highly conservative scenario, the next step required some complex statistical analysis. Having run the model in every hour of the year, we determined the probability of the operational hours coinciding with the meteorological conditions that give rise to the highest hourly concentrations. As the probability of this coincidence was low an exceedance was considered unlikely.
Project statistics
56
Back-up diesel generators
66
Designated ecological sites assessed for impact
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