Xiaoli Liu

We developed a multicomponent, multiphase, fluid and heat flow model to describe hydrate formation in marine sediments; the one‐ and two‐dimensional model accounts for the dynamic effects of hydrate formation on salinity, temperature, pressure, and hydraulic properties. Free gas supplied from depth forms hydrate, depletes water, and elevates salinity until pore water is too saline for further hydrate formation: Salinity and hydrate concentration increase upward from the base of the regional hydrate stability zone (RHSZ) to the seafloor, and the base of the hydrate stability zone has significant topography. In fine‐grained sediments, hydrate formation leads to rapid permeability reduction and capillary sealing to free gas. This traps gas and causes gas pressure to build up until it exceeds the overburden stress and drives gas through the RHSZ. Gas chimneys couple the free gas zone to the seafloor through high‐salinity conduits that are maintained at the three‐phase boundary by gas flow. As a result, significant amounts of gaseous methane can bypass the RHSZ, which implies a significantly smaller hydrate reservoir than previously envisioned. Hydrate within gas chimneys lies at the three‐phase boundary, and thus small increases in temperature or decreases in pressure can immediately transport methane into the ocean. This type of hydrate deposit may be the most economical for producing energy because it has very high methane concentrations ( S h > 70%), located near the seafloor, which lie on the three‐phase boundary.

Log and core data document gas saturations as high as 90% in a coarse‐grained turbidite sequence beneath the gas hydrate stability zone (GHSZ) at south Hydrate Ridge, in the Cascadia accretionary complex. The geometry of this gas‐saturated bed is defined by a strong, negative‐polarity reflection in 3D seismic data. Because of the gas buoyancy, gas pressure equals or exceeds the overburden stress immediately beneath the GHSZ at the summit. We conclude that gas is focused into the coarse‐grained sequence from a large volume of the accretionary complex and is trapped until high gas pressure forces the gas to migrate through the GHSZ to seafloor vents. This focused flow provides methane to the GHSZ in excess of its proportion in gas hydrate, thus providing a mechanism to explain the observed coexistence of massive gas hydrate, saline pore water and free gas near the summit.

The significance of air pollution and the problems associated with it are fueling deployments of air quality monitoring stations worldwide. The most common approach for air quality monitoring is to rely on environmental monitoring stations, which unfortunately are very expensive both to acquire and to maintain. Hence, environmental monitoring stations are typically sparsely deployed, resulting in limited spatial resolution for measurements. Recently, low-cost air quality sensors have emerged as an alternative that can improve the granularity of monitoring. The use of low-cost air quality sensors, however, presents several challenges: They suffer from cross-sensitivities between different ambient pollutants; they can be affected by external factors, such as traffic, weather changes, and human behavior; and their accuracy degrades over time. Periodic re-calibration can improve the accuracy of low-cost sensors, particularly with machine-learning-based calibration, which has shown great promise due to its capability to calibrate sensors in-field. In this article, we survey the rapidly growing research landscape of low-cost sensor technologies for air quality monitoring and their calibration using machine learning techniques. We also identify open research challenges and present directions for future research.