A primary requirement for understanding and predicting the behavior of complex systems is the ability to observe them. Observation contributes to understanding of processes and, therefore, the predictive power of physically based models but also provides calibration data vital for more empirical models. The heterogeneity in composition and large size of environmental systems makes their behavior complex, whilst the same factors make its representative observation difficult. Gas in the subsurface is a typical example of an environmental system, the predictability of which has been limited by insufficient observation. Traditionally due to the technology available these systems have been monitored using discrete measurements from which gas concentrations and migration potential are inferred. Unsurprisingly considering the nature of these systems this method of data collection frequently records highly variable regimes. Without understanding these variations large uncertainty on the data exists which propagates through to a conservative risk assessment based on the unquantified ‘worst’ concentration/flux observed during monitoring. Variations in soil gas concentrations are related to environmental parameters such as atmospheric pressure, subsurface pressure, temperature and water table. The recent development of technology which enables continuous soil gas monitoring that also records these parameters not only allows the variability in concentrations to be quantified and accounted for but also allows these relationships to be identified. Only after these relationships are identified is it possible to predict how gas/vapor regimes will change in the future. Using data collected from sites with varying wastes, contaminations, geologies and hydrologies the benefits of continuous data will be illustrated and novel techniques for risk assessment including concentration duration curves will be introduced. This will demonstrate that the availability of new monitoring methodology will play a part in repositioning both the legislative requirements and the cost-benefits of a more proactive approach.