Canopy leaf area index (LAI) is an important structural parameter of the vegetation controlling pollutant uptake by terrestrial ecosystems. This paper presents a computationally efficient algorithm for retrieval of vegetation LAI and canopy clumping factor from satellite data using observed Simple Ratios (SR) of near-infrared to red reflectance. The method employs numerical inversion of a physics-based analytical canopy radiative transfer model that simulates the bi-directional reflectance distribution function (BRDF). The algorithm is independent of ecosystem type. The method is applied to 1-km resolution AVHRR satellite images to retrieve a geo-referenced data set of monthly LAI values for the conterminous USA. Satellite-based LAI estimates are compared against independent ground LAI measurements over a range of ecosystem types. Verification results suggest that the new algorithm represents a viable approach to LAI retrieval at continental scale, and can facilitate spatially explicit studies of regional pollutant deposition and trace gas exchange. The paper presents a physics-based algorithm for retrieval of vegetation LAI and canopy-clumping factor from satellite data to assist research of pollutant deposition and trace-gas exchange. The method is employed to derive a monthly LAI dataset for the conterminous USA and verified at a continental scale.

An integrative passive sampler consisting of a C18 Empore® disk receiving phase saturated with n-octanol and fitted with low-density polyethylene diffusion membrane was calibrated for the measurement of time-weighted average concentrations of hydrophobic micropollutants, including polyaromatic hydrocarbons and organochlorine pesticides, in water. The effect of temperature and water turbulence on kinetic and thermodynamic parameters characterising the exchange of analytes between the sampler and water was studied in a flow-through system under controlled conditions. It was found that the absorption of test analytes from water to the sampler is related to their desorption to water. This allows for the in situ calibration of the uptake of pollutants using offload kinetics of performance reference compounds. The sampling kinetics are dependent on temperature, and for most of the tested analytes also on the flow velocity. Sampler–water partition coefficients did not significantly change with temperature.

Sedimentation basins and sediment traps are established methodologies for reducing sediment and other pollutants exiting small watersheds such as urban areas and construction sites. However, estimating the trap efficiency or designing a basin or trap to provide a pre-determined trap efficiency, is difficult, especially for dynamic conditions of water and sediment inflow. A conceptual dynamic model, called SedTrap, was developed that can be used to assess the varying removal efficiencies as a storm is routed through different sized basins or traps. The model uses the STELLA® modeling software from Iseesystems, Inc. to build a dynamic model to route both water and sediment through the system. Settling velocities are determined for a range of sediment sizes and temperatures using the Rubey-Watson law and compared to the more traditional Stokes' law. The variation of efficiencies with time and by sediment size as the basin fills with sediment is also addressed. The results for the example used show a decrease in trap efficiencies with decreasing particle size, which leads to an increase in percent fine material of total sediment load at the outlet of the basin. This “fining” of the material coupled with the higher surface area per mass of the fine particles has implications for changes in the upstream-downstream concentrations of adsorbed contaminants.

Sulfate (SO₄ ²-), nitrate (NO₃ -) and ammonium (NH₄ ⁺) concentrations in precipitation as measured at NADP sites within the Ohio River Valley of the Midwestern USA between 1985 and 2002 are quantified and temporal trends attributed to changes/ variations in (i) the precipitation regime, (ii) emission patterns and (iii) air mass trajectories. The results indicate that mean SO₄ ²- concentrations in precipitation declined by 37-43% between 1985 and 2002, while NO₃ - concentrations decreased by 1-32%, and NH₄ ⁺ concentrations exhibited declining concentrations at some sites and increasing concentrations at others. The change in SO₄ ²- concentrations is in broad agreement with estimated reductions in sulfur dioxide emissions. Changes in NO₃ - concentrations appear to be less closely related to variations in emissions of oxides of nitrogen and exhibit a stronger dependence on weekly precipitation volume. Up to one quarter of the variability in log-transformed weekly NO₃ - concentrations in precipitation is explicable by variations in precipitation volume. Trends in annual average log-transformed SO₄ ²- concentrations exhibit only a relatively small influence of variability in weekly precipitation amount but at each of the sites considered the variance explanation of annual average log-transformed SO₄ ²- by sampling year was increased by removing the influence of precipitation volume. Annual mean log-transformed ion concentrations detrended for precipitation volume (by week) and emission changes (by year) exhibit positive correlations at all sites, indicating that the residual variability of SO₄ ²-, NO₃ - and NH₄ ⁺ may have a common source which is postulated to be linked to synoptic scale variability and air mass trajectories.