Reassessment of the Ocean-To-Atmosphere Flux of Carbon Monoxide

Carbon monoxide (CO) in the surface sea waters is produced predominantly by photochemical processes, oxidized by micro-organisms and outgassed to the atmosphere. to assess carbon monoxide flux from the oceans to the atmosphere, the photochemical production and microbial oxidation of carbon monoxide in the oceanic mixed-layer was investigated during several oeanographic cruises and in the laboratory. the photoproduction rate of carbon monoxide was found to be well correlated to the concentration of dissolved organic carbon (DOC) in coastal and open ocean surface waters. Taking a global average carbon monoxide production rate of 10 ± 2 nmole litre^-1 (mg DOC hr)^-1 in the surface open ocean water, and 25 ± 7 nmole litre^-1 (mg DOC hr)^-1 in coastal sea water, at cloud-free summer solar noon, the photochemical production of carbon monoxide in the global oceans is estimated to be at a rate of 1200 ± 200 Tg CO y^-1. the microbial carbon monoxide turnover time in the mixed-layer was observed to range from hours in a coastal estuary to 16 days in the Pacific along 1057deg; W in dark incubations. Natural sunlight can largely inhibit the microbial consumption of carbon monoxide in surface water. On a global scale, microbial consumption is responsible for the loss of less than 10% of photochemical produced carbon monoxide in the surface ocean. Field measurements have shown that the net transport of carbon monoxide from the euphotic zone to the underlying deeper ocean water is limited and that the overall life time in surface sea waters is less than 3-4 hours. When combined, these field measurements with the photoproduction and microbial consumption rates obtained, we estimate the oceanic flux to the atmosphere is about 1000 ± 200 Tg CO y^-1, which represents the largest single source of atmospheric carbon monoxide.     

A Modeling System to Assess Land Cover Land Use Change Effects on SAV Habitat in the Mobile Bay Estuary

Estuarine ecosystems are largely influenced by watersheds directly connected to them. In the Mobile Bay, Alabama watersheds we examined the effect of land cover and land use (LCLU) changes on discharge rate, water properties, and submerged aquatic vegetation, including freshwater macrophytes and seagrasses, throughout the estuary. LCLU scenarios from 1948, 1992, 2001, and 2030 were used to influence watershed and hydrodynamic models and evaluate the impact of LCLU change on shallow aquatic ecosystems. Overall, our modeling results found that LCLU changes increased freshwater flows into Mobile Bay altering temperature, salinity, and total suspended sediments (TSS). Increased urban land uses coupled with decreased agricultural/pasture lands reduced TSS in the water column. However, increased urbanization or agricultural/pasture land coupled with decreased forest land resulted in higher TSS concentrations. Higher sediment loads were usually strongly correlated with higher TSS levels, except in areas where a large extent of wetlands retained sediment discharged during rainfall events. The modeling results indicated improved water clarity in the shallow aquatic regions of Mississippi Sound and degraded water clarity in the Wolf Bay estuary. This integrated modeling approach will provide new knowledge and tools for coastal resource managers to manage shallow aquatic habitats that provide critical ecosystem services.     

Variable Irrigation District Action in Water Trading

Irrigation districts (IDs) in the American west are highly diverse in their economic attributes and local water scarcity circumstances. This diversity may affect reallocative action via water transactions as scarcity rises. The institutional background defining and constraining IDs is described here. For a Texas study region the progress of permanent water right transfers involving IDs is documented and examined. An econometric analysis of multiple decades of ID water transfer activities in the Lower Rio Grande Valley finds that IDs with larger initial water right holdings and higher populations in nearby cities are more likely to participate in agricultural‐to‐municipal water transfer activities. The findings suggest that consolidation of smaller water right holding IDs may be an avenue for quickening the pace of reallocation, especially in more populated areas.     

Methane and nitrous oxide emissions from a subtropical coastal embayment (Moreton Bay, Australia)

Surface water methane (CH₄) and nitrous oxide (N₂O) concentrations and fluxes were investigated in two subtropical coastal embayments (Bramble Bay and Deception Bay, which are part of the greater Moreton Bay, Australia). Measurements were done at 23 stations in seven campaigns covering different seasons during 2010-2012. Water-air fluxes were estimated using the Thin Boundary Layer approach with a combination of wind and currents-based models for the estimation of the gas transfer velocities. The two bays were strong sources of both CH₄ and N₂O with no significant differences in the degree of saturation of both gases between them during all measurement campaigns. Both CH₄ and N₂O concentrations had strong temporal but minimal spatial variability in both bays. During the seven seasons, CH₄ varied between 500% and 4000% saturation while N₂O varied between 128 and 255% in the two bays. Average seasonal CH₄ fluxes for the two bays varied between 0.5 ± 0.2 and 6.0 ± 1.5 mg CH₄/(m²·day) while N₂O varied between 0.4 ± 0.1 and 1.6 ± 0.6 mg N₂O/(m²·day). Weighted emissions (t CO₂-e) were 63%-90% N₂O dominated implying that a reduction in N₂O inputs and/or nitrogen availability in the bays may significantly reduce the bays' greenhouse gas (GHG) budget. Emissions data for tropical and subtropical systems is still scarce. This work found subtropical bays to be significant aquatic sources of both CH₄ and N₂O and puts the estimated fluxes into the global context with measurements done from other climatic regions.     

Identifying fecal sources in a selected catchment reach using multiple source-tracking tools

Given known limitations of current microbial source-tracking (MST) tools, emphasis on small, simple study areas may enhance interpretations of fecal contamination sources in streams. In this study, three MST tools-Escherichia coli repetitive element polymerase chain reaction (rep-PCR), coliphage typing, and Bacteroidales 16S rDNA host-associated markers-were evaluated in a selected reach of Plum Creek in south-central Nebraska. Water-quality samples were collected from six sites. One reach was selected for MST evaluation based on observed patterns of E. coli contamination. Despite high E. coli concentrations, coliphages were detected only once among water samples, precluding their use as a MST tool in this setting. Rep-PCR classification of E. coli isolates from both water and sediment samples supported the hypothesis that cattle and wildlife were dominant sources of fecal contamination, with minor contributions by horses and humans. Conversely, neither ruminant nor human sources were detected by Bacteroidales markers in most water samples. In bed sediment, ruminant- and human-associated Bacteroidales markers were detected throughout the interval from 0 to 0.3 m, with detections independent of E. coli concentrations in the sediment. Although results by E. coli-based and Bacteroidales-based MST methods led to similar interpretations, detection of Bacteroidales markers in sediment more commonly than in water indicates that different tools to track fecal contamination (in this case, tools based on Bacteroidales DNA and E. coli isolates) may have varying relevance to the more specific goal of tracking the sources of E. coli in watersheds. This is the first report of simultaneous, toolbox approach application of a library-based and marker-based MST analyses to flowing surface water.     

The Annual Average: An Alternative to the Second Highest Value as a Measure of Air Quality

It is common practice to use the second highest value both in determining compliance with the once-per-year air quality standards (AQS) and as a measure of air quality in pollutant trend studies and rollback calculations. A study of the variation in the second highest 8 hr carbon monoxide concentration observed at the CAMP stations 1962-72 is presented. It is shown that, for a given annual average, the second highest value can differ by a factor of 2 due to random variation. The annual average is linearly related to the observed average of the second highest value and is shown to be a good predictor of the percent of time the carbon monoxide AQS is exceeded. It is concluded that the annual average, which is less variable and not as greatly influenced by erroneous measurements, is the preferred measure of air quality for trend studies and air quality projections.     

Application of non-linear automatic optimization techniques for calibration of HSPF.

Development of TMDLs (total maximum daily loads) is often facilitated by using the software system BASINS (Better Assessment Science Integrating point and Nonpoint Sources). One of the key elements of BASINS is the watershed model HSPF (Hydrological Simulation Program Fortran) developed by USEPA. Calibration of HSPF is a very tedious and time consuming task, more than 100 parameters are involved in the calibration process. In the current research, three non-linear automatic optimization techniques are applied and compared, as well an efficient way to calibrate HSPF is suggested. Parameter optimization using local and global optimization techniques for the watershed model is discussed. Approaches to automatic calibration of HSPF using the nonlinear parameter estimator PEST (Parameter Estimation Tool) with its Gauss-Marquardt-Levenberg (GML) method, Random multiple Search Method (RSM), and Shuffled Complex Evolution method developed at the University of Arizona (SCE-UA) are presented. Sensitivity analysis was conducted and the most and the least sensitive parameters were identified. It was noted that sensitivity depends on number of adjustable parameters. As more parameters were optimized simultaneously--a wider range of parameter values can maintain the model in the calibrated state. Impact of GML, RSM, and SCE-UA variables on ability to find the global minimum of the objective function (OF) was studied and the best variables are suggested. All three methods proved to be more efficient than manual HSPF calibration. Optimization results obtained by these methods are very similar, although in most cases RSM outperforms GML and SCE-UA outperforms RSM. GML is a very fast method, it can perform as well as SCE-UA when the variables are properly adjusted, initial guess is good and insensitive parameters are eliminated from the optimization process. SCE-UA is very robust and convenient to use. Logical definition of key variables in most cases leads to the global minimum.