An integrated multivariate statistical approach for the evaluation of spatial variations in groundwater quality near an unlined landfill

Environmental Science and Pollution Research - Groundwater is a major resource for water supply in Canada, and 43 of 68 Saskatchewan municipalities rely on groundwater or combined groundwater and...     

Simultaneous determination of parathion and p-nitrophenol in vegetable tissues by derivative spectrophotometry

A first derivative spectrophotometric method has been developedfor the determination of parathion and p-nitrophenol in vegetabletissues. Ethanol was used as solvent for extracting the compoundsfrom the tissues and subsequently the samples were evaluated against a vegetable tissue blank, directly by derivative spectrophotometry. The simultaneous determination of these compounds can be carried out using the zero-crossing approach for parathion at 253.0 nm and for p-nitrophenol at 273.1 nm. In the samples each analyte was determined in the presence of one another in the ranges between 4.9 to 3883.5 g g^-1 forparathion and 4.9 to 3285.3 g g^-1 for p-nitrophenol.The detection limits (3) were found to be 1.5 and 1.4 g g^-1 for parathion and p-nitrophenol, respectively. The relative standard deviations were in all instances less than1.8%. The proposed method was applied to the determination ofthe analytes in spiked leafs of corn. The results show a goodrecovery and they are in agreement with those obtained bypolarography.     

Leaf arrangement

The striking universality of the occurrence of Fibonacci numbers in phyllotaxis is analyzed. Geometric investigation shows that Fibonacci patterns are intimately related to the golden divergence angle along the genetic spiral. A simple argument is presented to make this angle plausible by considering inhibitory action in primary pattern formation. The various types of leaf arrangement are related to the spatial and temporal range of the inhibitory influences.     

TEMPORAL CHANGES IN THE YADKIN RIVER FLOW VERSUS SUSPENDED SEDIMENT CONCENTRATION RELATIONSHIP1

ABSTRACT: Dynamic linear models (DLM) and seasonal trend decomposition (STL) using local regression, or LOESS, were used to analyze the 50‐year time series of suspended sediment concentrations for the Yadkin River, measured at the U.S. Geological Survey station at Yadkin College, North Carolina. A DLM with constant trend, seasonality, and a log₁₀ streamflow regressor provided the best model to predict monthly mean log₁₀ suspended sediment concentrations, based on the forecast log likelihood. Using DLM, there was evidence (odds approximately 69:1) that the log₁₀ streamflow versus log₁₀ suspended sediment concentration relationship has changed, with an approximate 20 percent increase in the log₁₀ streamflow coefficient over the period 1981 to 1996. However, sediment concentrations in the Yadkin River have decreased during the decade of the 1990s, which has been accompanied by a concomitant increase in streamflow variability. Although STL has been shown to be a versatile trend analysis technique, DLM is shown to be more suitable for discovery and inference of structural changes (trends) in the model coefficient describing the relationship between flow and sediment concentration.     

Attribution of Carbon Dioxide Fluxes to Crop Types in a Heterogeneous Agricultural Landscape of Argentina

The increasing proportion of agricultural lands worldwide makes it necessary to intensify the research concerning the carbon exchange at agricultural sites. In order to determine the Net Ecosystem Exchange (NEE) in an agricultural landscape in the province of Buenos Aires, Argentina, we carried out eddy covariance measurements with a flux tower, which was placed between two agricultural fields. Therefore, the measured CO₂ flux represents the accumulated flux from both areas, i.e., from different crop types. We here present an analysis method which attributes the flux to the two crop types. For this analysis, we applied the Hsieh footprint model to identify the contributing source area to the flux measurement. We then applied a multiple regression analysis to calculate the NEE in the growing season 2011/2012 for each field separately. The pronounced differences in the time courses of the CO₂ fluxes in the two fields can be explained by the different sowing times and different growth stages of both cultivations. The time courses furthermore show that the CO₂ uptake of the plants was strongly affected by the drought which lasted from December 2011 to January 2012. For the growth cycle of maize (216 days), the NEE was ?240 g C m^?2 and for the growth cycle of soybean (154 days) ?231 g C m^?2. In order to obtain the NEE of a complete agricultural cycle (from harvest to harvest), we also considered the NEE of autumn and winter 2011. Uncertainties of the spatially partitioned NEE are quantified and discussed.     

Alternative carbon dioxide modelling approaches accounting for high residual gases in LandGEM

High Canadian waste disposal rates necessitate landfill gas monitoring and accurate forecasting. CO₂ estimates in LandGEM version 3.02 currently rest on the assumptions that CO₂ is a function of CH₄, where the two gases make up nearly 100% of landfill gas content, leading to overestimated CO₂ collection estimates. A total of 25 cases (five formulas, five approaches) compared annual CO₂ collection at four western Canadian landfills. Despite common use in literature, the 1:1 ratio of CH₄ to CO₂ was not recommended to forecast landfill gas collection in cold climates. The existing modelling approach significantly overestimated CO₂ production in three of four sites, resulting in the highest residual sum of squares. Optimization resulted in the most accurate results for all formulas and approaches, which had the greatest reduction in residual sums of squares (RSS) over the default approach (60.1 to 97.7%). The 1.4 Ratio approach for L _o:L _o-CO2 yielded the second most accurate results for CO₂ flow (mean RSS reduction of 50.2% for all sites and subsection models). The annual k-modified LandGEM calculated k’s via two empirical formulas (based on precipitation) and yielded the lowest accuracy in 12 of 20 approaches. Unlike other studies, strong relationships between optimized annual k’s and precipitation were not observed.