Simulated Trading for Maryland's Nitrogen Loadings in the Chesapeake Bay

We investigate nutrient trading for point and non-point sources for the Bay Restoration Fund in Maryland. We demonstrate how to use the proceeds from the tax revenue to mimic a market by trading high-cost upgrades of sewage treatment plants for low-cost winter cover crops. Under an optimistic assumption about costs for non-point sources and naïve assumptions about the lag from planting cover crops to changes in nitrogen load, we calculate that 100 percent of abatement could be achieved at 56 percent of total costs, while in a pessimistic scenario, 100 percent of abatement could be could be achieved at 83 percent of total costs.Chesapeake Bay, cover crops, nitrogen abatement, nutrient trading, sewage treatment plants, trading ratios, water pollution, Environmental Economics and Policy,

Nutrient Trading, the Flush Tax, and Maryland's Nitrogen Emissions to the Chesapeake Bay

We investigate nutrient trading for point and non-point sources for the Bay Restoration Fund in Maryland. We demonstrate how to use the proceeds from the tax revenue to mimic trading high-cost upgrades of sewage treatment plants for low-cost winter cover crops. Under an optimistic assumption about costs for non-point sources, we calculate that abatement could be increased by more than 50%, while in a pessimistic scenario, abatement could be increased by 2%. We also explore the role of uncertainty in determining the appropriate trading ratio between point and non-point sources of pollution, showing that the higher uncertainty associated with non-point sources should induce a lower trading ratio.Chesapeake Bay, cover crops, nitrogen abatement, nutrient trading, sewage treatment plants, trading ratios, water pollution, Environmental Economics and Policy,

Predicted land use changes in agricultural areas of WA and resulting impact on the extent of dryland salinity

An assessment of current and possible future land use in Western Australia was undertaken as part of the National Land and Water Resources Audit. This data was used to assess the impact of land use change on the future extent of salinity. It was found that in some areas there is real capacity for changing land use to impact on recharge to the watertable

Using aircraft measurements to determine the refractive index of Saharan dust during the DODO Experiments

Much uncertainty in the value of the imaginary part of the refractive index of mineral dust contributes to uncertainty in the radiative effect of mineral dust in the atmosphere. A synthesis of optical, chemical and physical in-situ aircraft measurements from the DODO experiments during February and August 2006 are used to calculate the refractive index mineral dust encountered over West Africa. Radiative transfer modeling and measurements of broadband shortwave irradiance at a range of altitudes are used to test and validate these calculations for a specific dust event on 23 August 2006 over Mauritania. Two techniques are used to determine the refractive index: firstly a method combining measurements of scattering, absorption, size distributions and Mie code simulations, and secondly a method using composition measured on filter samples to apportion the content of internally mixed quartz, calcite and iron oxide-clay aggregates, where the iron oxide is represented by either hematite or goethite and clay by either illite or kaolinite. The imaginary part of the refractive index at 550 nm (ni550) is found to range between 0.0001 i to 0.0046 i, and where filter samples are available, agreement between methods is found depending on mineral combination assumed. The refractive indices are also found to agree well with AERONET data where comparisons are possible. ni550 is found to vary with dust source, which is investigated with the NAME model for each case. The relationship between both size distribution and ni550 on the accumulation mode single scattering albedo at 550 nm (ω0550) are examined and size distribution is found to have no correlation to ω0550, while ni550 shows a strong linear relationship with ω0550. Radiative transfer modeling was performed with different models (Mie-derived refractive indices, but also filter sampling composition assuming both internal and external mixing). Our calculations indicate that Mie-derived values of ni550 and the externally mixed dust where the iron oxide-clay aggregate corresponds to the goethite-kaolinite combination result in the best agreement with irradiance measurements. The radiative effect of the dust is found to be very sensitive to the mineral combination (and hence refractive index) assumed, and to whether the dust is assumed to be internally or externally mixed

Extent and impacts of dryland salinity

The extent and impact of dryland salinity in Western Australia was based on analysis of groundwater depth and trend and the risk of shallow watertables is derived from these two attributes. As dryland salinity is caused by shallow watertables, the risk of salinity is inferred from the risk of shallow watertables

Observations on groundwater recharge in the Westdale catchment

A study of the role of groundwater carriers and barriers in controlling salinity was carried out in the Westdale Catchment by Lewis and McConnell (in preparation). Although that study was primarily concerned with groundwater flow and discharge processes, the data collected also provided rudimentary information on the timing of groundwater recharge events and their distribution across the landscape

Bayesian multiscale deconvolution applied to gamma-ray spectroscopy

A common task in gamma-ray astronomy is to extract spectral information, such as model constraints and incident photon spectrum estimates, given the measured energy deposited in a detector and the detector response. This is the classic problem of spectral “deconvolution” or spectral inversion. The methods of forward folding (i.e., parameter fitting) and maximum entropy “deconvolution” (i.e., estimating independent input photon rates for each individual energy bin) have been used successfully for gamma-ray solar flares (e.g., Rank, 1997; Share and Murphy, 1995). These methods have worked well under certain conditions but there are situations were they don’t apply. These are: 1) when no reasonable model (e.g., fewer parameters than data bins) is yet known, for forward folding; 2) when one expects a mixture of broad and narrow features (e.g., solar flares), for the maximum entropy method; and 3) low count rates and low signal-to-noise, for both. Low count rates are a problem because these methods (as they have been implemented) assume Gaussian statistics but Poisson are applicable. Background subtraction techniques often lead to negative count rates. For Poisson data the Maximum Likelihood Estimator (MLE) with a Poisson likelihood is appropriate. Without a regularization term, trying to estimate the “true” individual input photon rates per bin can be an ill-posed problem, even without including both broad and narrow features in the spectrum (i.e., amultiscale approach). One way to implement this regularization is through the use of a suitable Bayesian prior. Nowak and Kolaczyk (1999) have developed a fast, robust, technique using a Bayesian multiscale framework that addresses these problems with added algorithmic advantages. We outline this new approach and demonstrate its use with time resolved solar flare gamma-ray spectroscopy