Experimental Investigation of Surfactant-Enhanced Dissolution of Residual NAPL in Saturated Soil

Nonaqueous phase liquid (NAPL) is a long-term source of ground water contamination as the pollutant slowly partitions into the air and water phases. The objective of this work was to study the efficacy of aqueous surfactant solution to enhance the dissolution of a residual NAPL below the capillary fringe, hence reducing the time needed for aquifer restoration. An analytical technique was developed to measure the concentration of NAPL in a nonionic surfactant. Soil column experiments simulated conditions in the saturated soil where a NAPL may become trapped as a discontinuous immobile phase. Experimental results indicate that dissolution was a rate-limited process, approaching equilibrium concentrations after 24 hours. The relative permeability of the aqueous phase initially decreased as surfactant was injected, but increased over time as the saturation of residual NAPL was reduced through mass transfer into the surfactant-enhanced aqueous phase. These findings suggest that enhancing the aqueous phase with a nonionic surfactant may significantly enhance the in situ recovery or residual NAPL.     

Monsoon-driven biogeochemical processes in the Arabian Sea

Although it is nominally a tropical locale, the semiannual wind reversals associated with the Monsoon system of the Arabian Sea result annually in two distinct periods of elevated biological activity. While in both cases monsoonal forcing drives surface layer nutrient enrichment that supports increased rates of primary productivity, fundamentally different entrainment mechanisms are operating in summer (Southwest) and winter (Northeast) Monsoons. Moreover, the intervening intermonsoon periods, during which the region relaxes toward oligotrophic conditions more typical of tropical environments, provide a stark contrast to the dynamic biogeochemical activity of the monsoons. The resulting spatial and temporal variability is great and provides a significant challenge for ship-based surveys attempting to characterize the physical and biogeochemical environments of the region. This was especially true for expeditions in the pre-satellite era.Here, we present an overview of the dynamical response to seasonal monsoonal forcing and the characteristics of the physical environment that fundamentally drive regional biogeochemical variability. We then review past observations of the biological distributions that provided our initial insights into the pelagic system of the Arabian Sea. These evolved through the 1980s as additional methodologies, in particular the first synoptic ocean color distributions gathered by the Coastal Zone Color Scanner, became available. Through analyses of these observations and the first large-scale physical–biogeochemical modeling attempts, a pre-JGOFS understanding of the Arabian Sea emerged. During the 1990s, the in situ and remotely sensed observational databases were significantly extended by regional JGOFS activities and the onset of Sea-viewing Wide Field-of-View Sensor ocean color measurements. Analyses of these new data and coupled physical–biogeochemical models have already advanced our understanding and have led to either an amplification or revision of the pre-JGOFS paradigms. Our understanding of this complex and variable ocean region is still evolving. Nonetheless, we have a much better understanding of time–space variability of biogeochemical properties in the Arabian Sea and much deeper insights about the physical and biological factors that drive them, as well as a number of challenging new directions to pursue.     

Climate Forcing and Salinity Variability in Chesapeake Bay,USA

Salinity is a critical factor in understanding and predicting physical and biogeochemical processes in the coastal ocean where it varies considerably in time and space. In this paper, we introduce a Chesapeake Bay community implementation of the Regional Ocean Modeling System (ChesROMS) and use it to investigate the interannual variability of salinity in Chesapeake Bay. The ChesROMS implementation was evaluated by quantitatively comparing the model solutions with the observed variations in the Bay for a 15-year period (1991 to 2005). Temperature fields were most consistently well predicted, with a correlation of 0.99 and a root mean square error (RMSE) of 1.5°C for the period, with modeled salinity following closely with a correlation of 0.94 and RMSE of 2.5. Variability of salinity anomalies from climatology based on modeled salinity was examined using empirical orthogonal function analysis, which indicates the salinity distribution in the Bay is principally driven by river forcing. Wind forcing and tidal mixing were also important factors in determining the salinity stratification in the water column, especially during low flow conditions. The fairly strong correlation between river discharge anomaly in this region and the Pacific Decadal Oscillation suggests that the long-term salinity variability in the Bay is affected by large-scale climate patterns. The detailed analyses of the role and importance of different forcing, including river runoff, atmospheric fluxes, and open ocean boundary conditions, are discussed in the context of the observed and modeled interannual variability.