A predictive model for estimating the indoor oxygen level and assessing Oxygen Deficiency Hazard (ODH)

• We develop a new predictive model to estimate indoor oxygen level and assess ODH.
• We evaluate ODH caused by voluntary and accidental releases of inert gases that displace the indoor air and the oxygen.
• The outputs of the model are the concentration by volume and the partial pressure of oxygen in time.
• The model fills some weaknesses and gaps of the predictive models available in the literature.
• The outputs of the model are comparable to the results of some case studies available in the literature.

In some working environments there may be Oxygen Deficiency Hazard (ODH) when workers are exposed to a low indoor oxygen level. This hazard can be assessed applying a predictive model. In the literature, there are sixteen models estimating the oxygen content subsequent to releases of inert gases. These models present several weaknesses, such as the rarity of consideration of accidental releases, of Heating, Ventilation, Air Conditioning, and Refrigeration (HVAC-R) systems reliability, and of the existence of both forced and natural ventilation. For overcoming these weaknesses, we propose a new predictive model for assessing ODH caused by voluntary or accidental releases of inert gases. Our model is based on the balances of mass of air and of moles of oxygen. Our model fills some gaps identified in the literature models (e.g. the estimation of natural ventilation, infiltration, and exfiltration), and allows the identification of those parameters responsible for ODH. In order to evaluate our model, we have performed several simulation tests. We have obtained that our results are comparable to the outputs of some case studies available in the literature, and we have analysed the effects of some new aspects of the model. The model represents a helpful tool to implement in any working environment where ODH has to be assessed.