Ecological Monitoring for Assessing the State of the Nearshore and Open Waters of the Great Lakes

The Great Lakes Water Quality Agreement stipulates that the Governments of Canada and the United States are responsible for restoring and maintaining the chemical, physical and biological integrity of the waters of the Great Lakes Basin Ecosystem. Due to varying mandates and areas of expertise, monitoring to assess progress towards this objective is conducted by a multitude of Canadian and U.S. federal and provincial/state agencies, in cooperation with academia and regional authorities. This paper highlights selected long-term monitoring programs and discusses a number of documented ecological changes that indicate the present state of the open and nearshore waters of the Great Lakes.     

On-filter determination of collected wood dust by diffuse reflectance infrared Fourier-transform spectroscopy (DRIFTS)

A new analytical technique based on DRIFTS spectroscopy has been developed for the specific and sensitive determination of size-fractionated wood dust from 37 mm glass fiber filter samples collected with the Respicon sampler. A translational diffuse reflectance apparatus was modified to accept filter samples by incorporating a special filter holder in the sample stage and a clockwork motor to drive the translational stage during infrared scanning, thus providing an average analysis across the filter face. Filter samples were pre-treated with ethyl acetate to uniformly redeposit dust onto the filter and extract potential chemical interferences. Two absorbance maxima (1251 and 1291 cm(-1)), corresponding to the cellulose content of the wood, were suitable for quantitation of wood dust. Analysis of seven species of wood at 1291 cm(-1) showed an equivalent quantitative response for all species except maple. The response at 1251 cm(-1) was more variable across species but more sensitive for the softwoods. There was a statistically significant effect of particle size on the analytical response, so that analytical standards should be matched to the samples in terms of particle size distribution. Analytical limit of detection was approximately 0.08 mg of wood dust per sample with overall precision of about 6%. Comparison of DRIFTS and gravimetric analyses of 51 pure wood dust samples ranging from about 0.2 to 2 mg yielded a slope of 1.08 and r2 equal to 0.9. Other particulate contaminants common in the industrial wood processing industry showed little or no interference with the determination of wood dust by this method.     

SUWANNEE RIVER LONG RANGE STREAMFLOW FORECASTS BASED ON SEASONAL CLIMATE PREDICTORS1

ABSTRACT: A study of the influence of climate variability on streamflow in the southeastern United States is presented. Using a methodology previously applied to watersheds in Australia and the United States, a long range streamflow forecast (0 to 9 months in advance) is developed. Persistence (i.e., the previous season's streamflow) and climate predictors of the previous season are used to forecast the following season's (winter and spring) streamflow of the Suwannee River located in northern Florida. The winter and spring streamflow is historically the most likely to have severe flood events due to large scale cyclonic (frontal) storms. Results of the analysis indicated that a strong El Nino‐Southern Oscillation (ENSO) signal exists at various lead times to the winter and spring streamflow of the Suwannee River. These results are based on the high correlation values of two commonly used measurements of ENSO strength, the Multivariate ENSO Index (MEI) and Sea Surface Temperature Range 1. Using the relationships developed between climate and streamflow, a continuous exceedance probability forecast was developed for two Suwannee River stations. The forecast system provided an improved forecast for ENSO years. The ability to predict above normal (flood) or below normal (drought) years can provide communities the necessary lead time to protect life, property, sensitive wetlands, and endangered and threatened species.     

MULTIVARIATE ANALYSIS OF WATER QUALITY AND PHYSICAL CHARACTERISTICS OF SELECTED WATERSHEDS IN PUERTO RICO1

ABSTRACT: Multivariate analyses were used to develop equations that could predict certain water quality (WQ) conditions for unmonitored watersheds in Puerto Rico based on their physical characteristics. Long term WQ data were used to represent the WQ of 15 watersheds in Puerto Rico. A factor analysis (FA) was performed to reduce the number of chemical constituents. Cluster analysis (CA) was used to group watersheds with similar WQ characteristics. Finally, a discriminant analysis (DA) was performed to relate the WQ clusters to different physical parameters and generate predicting equations. The FA identified six factors (77 percent of variation explained): nutrients, dissolved ions, sodium and chloride, silicacious geology, red ox conditions, and discharge. From the FA, specific conductance, sodium, phosphorous, silica, and dissolved oxygen were selected to represent the WQ characteristics in the CA. The CA determined five groups of watersheds (forested, urban polluted, mixed urban/rural, forested plutonic, and limestone) with similar WQ properties. From the five WQ clusters, two categories can be observed: forested and urban watersheds. The DA found that changes in forest cover, percent of limestone, mean annual rainfall, and watershed shape factor were the most important physical features affecting the WQ of watersheds in Puerto Rico.     

DETERMINING WATERSHED SUB-AREAS WITH PRINCIPAL COMPONENT ANALYSIS1

ABSTRACT: Principal component analysis is used to incorporate the effects of several socioeconomic variables into an index of watershed socioeconomic change. The index is then used as a basis for delineating economic sub-areas within the Tennessee River basin.     

Biodegradation of Thermoplastic Polyurethanes from Vegetable Oils

Thermoplastic urethanes based on polyricinoleic acid soft segments and MDI/BD hard segments with varied soft segment concentration were prepared. Soft segment concentration was varied from, 40 to 70 wt%. Biodegradation was studied by respirometry. Segmented polyurethanes with soft segments based on polyricinoleic acid degrade relatively slow losing about 11% carbon after 30 days, but faster than corresponding petrochemical polyesterurethanes. Since biodegradation proceeds mainly through the soft segments, higher soft segment content polymers displayed slightly higher biodegradation. Polyurethanes with dispersed hard domains in the soft phase displayed slightly faster biodegradation than those with co-continuous morphology. Polyester diol degrades slower than castor oil but significantly faster than the polyurethanes with built in soft segments from the same diol. Castor oil biodegrades slower than soybean oil.     

Implementing second-best environmental policy under adverse selection

A key obstacle to practical application of mechanism design theory to regulation is the difficulty of obtaining consistent beliefs regarding information that theoretical models assume to be commonly held. This article presents a solution to this problem by developing an easily implemented empirical methodology with which the government can use available data to develop beliefs regarding the technology and distribution of types in a regulated sector characterized by hidden information. Results are used to calibrate a second-best land conservation mechanism and evaluate its cost relative to simpler alternatives.