Spatial modelling of the probability of obtaining a detectable concentration of ammonia in Moreton Bay, Australia

Ammonia is an important water quality variable, which in excess, can be detrimental to waterways and their ecosystems. In the Ecosystem Health Monitoring Program in South-east Queensland ammonia is monitored monthly, however, often more than 50% of the ammonia observations in Moreton Bay are below detection limit, making it difficult to draw useful inferences. In this paper a clipped Gaussian random field is used to spatially model and map the probability of detectable concentration of ammonia. The methodology is applied to the Moreton Bay samples collected in February 2005. The results suggest that for this month the oceanic impacted areas have higher probability of detectable ammonia concentration than the areas closer to the main sources of anthropogenic inputs.     

The Role of Abatement Costs in GHG Permit Allocations: A Global Stabilization Scenario Analysis

Our objective is to propose permit allocation schemes that lead to a fair distribution of the net abatement cost among regions in a global greenhouse gas (GHG) stabilization scenario. We use a detailed technology-based energy model, World-MARKAL, to determine efficient abatement decisions, and to calculate the regional gross abatement costs (before permit allocation and trading). The net abatement costs are then calculated and used for different permit allocation schemes.     

Temporal and spatial variations of nutrients in the Ten Mile Creek of South Florida, USA and effects on phytoplankton biomass

Water quality throughout south Florida has been a major concern for many years. Nutrient enrichment in the Indian River Lagoon (IRL) is a major surface water issue and is suggested as a possible cause of symptoms of ecological degradation. In 2005-06, water samples were collected weekly from seven sites along Ten Mile Creek (TMC), which drains into the Indian River Lagoon, to investigate and analyze spatial and temporal fluctuations of nutrients nitrogen (N) and phosphorus (P). The objective of this study was to understand the relationships among chlorophyll a concentration, nutrient enrichment and hydrological parameters in the surface water body.High median concentrations of total P (TP, 0.272 mg L(-1)), PO4-P (0.122 mg L(-1)), and dissolved total P (DTP, 0.179 mg L(-1)); and total N (TN, 0.988 mg L(-1)), NO3(-)-N (0.104 mg L(-1)), NH4+-N (0.103 mg L(-1)), and total Kjeldahl N (TKN, 0.829 mg L(-1)), were measured in TMC. The concentrations of TP, PO4-P, DTP, TN, NO3(-)-N, NH4+-N, and TKN were higher in summer and fall than in winter and spring. However, chlorophyll a and pheophytin concentrations during this period in TMC varied in the range of 0.000-60.7 and 0.000-17.4 microg L(-1), with their median values of 3.54 and 3.02 microg L(-1), respectively. The greatest mean chlorophyll a (10.3 microg L(-1)) and pheophytin (5.71 microg L(-1)) concentrations occurred in spring, while the lowest chlorophyll a (1.49 microg L(-1)) and pheophytin (1.97 mug L(-1)) in fall. High concentrations of PO4-P (>0.16 mg L(-1)), DTP (>0.24 mg L(-1)), NO3(-)-N (>0.15 mg L(-1)), NH4+-N (>0.12 mg L(-1)), and TKN (>0.96 mg L(-1)), occurred in the upstream of TMC, while high concentrations of chlorophyll a (>6.8 mug L(-l)) and pheophytin (>3.9 microg L(-l)) were detected in the downstream of TMC. The highest chlorophyll a (11.8 mug L(-l)) and pheophytin (6.06 microg L(-l)) concentrations, however, were associated with static and open water conditions. Hydrological parameters (total dissolved solid, electrical conductivity, salinity, pH, and water temperature) were positively correlated with chlorophyll a and pheophytin concentrations (P < 0.01) and these factors overshadowed the relationships between N and P concentrations and chlorophyll a under field conditions. Principal component analysis and the ratios of DIN/DP and TN/TP in the water suggest that N is the limiting nutrient factor for phytoplankton growth in the TMC and elevated N relative to P is beneficial to the growth of phytoplankton, which is supported by laboratory culture experiments under controlled conditions.     

Magnesium hydroxide bulk and colloid-associated 152Eu in an alkaline environment: colloid characterisation and sorption properties in the presence and absence of carbonate

The distribution of 152Eu between magnesium hydroxide bulk, colloids and solution has been assessed under alkaline conditions, such as those in nuclear fuel storage ponds. The colloidal phase has been characterised by two complementary methods: coupled ultrafiltration-ICP-AES and scanning electron microscopy. The quantity and the size distribution of the colloidal phase is strongly ionic strength-dependent. A decrease of the quantity of colloids, in particular the larger size ranges, has been observed with increasing ionic strength. Small colloids (1 kDa-10 kDa fraction) are predominant at all ionic strengths. The morphology of colloids, observed by field-emission gun scanning electron microscopy, appears to change from hexagonal prismatic (characteristic to the mineral) to spherical (energetically more favourable) as size decreases. The distribution of 152Eu between the solid and liquid/colloidal phases has been investigated at carbonate concentrations ranging from 0 to 10(-2) M by coupled ultrafiltration and gamma-spectrometry. Mg(OH)2 bulk appears to be a very strong sorbent for 152Eu, since complete sorption onto the bulk happens for carbonate concentrations as high as 10(-3) M. Scavenging of 152Eu by Mg(OH)2 colloids is negligible in the presence of Mg(OH)2 bulk. The distribution of 152Eu between liquid and colloidal phases has been investigated in the absence of bulk at various carbonate concentrations. A significant uptake of 152Eu by the colloids in solution has been observed, which decreases with increasing carbonate concentration. 152Eu appears to be mainly associated to the smallest colloids (1 kDa-10 kDa fraction). There is a strong correlation between the sorption properties and the surface area of the colloids.     

Optimal Expansion Strategy for a Sewer System under Uncertainty

Because of fast urban sprawl, land use competition, and the gap in available funds and needed funds, municipal decision makers and planners are looking for more cost-effective and sustainable ways to improve their sewer infrastructure systems. The dominant approaches have turned to planning the sanitary sewer systems within a regional context, while the decentralized and on-site/cluster wastewater systems have not overcome the application barriers. But regionalization policy confers uncertainties and risks upon cities while planning for future events. Following the philosophy of smart growth, this paper presents several optimal expansion schemes for a fast-growing city in the US/Mexico borderlands—the city of Pharr in Texas under uncertainty. The waste stream generated in Pharr is divided into three distinct sewer sheds within the city limit, including south region, central region, and north region. The options available include routing the wastewater to a neighboring municipality (i.e., McAllen) for treatment and reuse, expanding the existing wastewater treatment plant (WWTP) in the south sewer shed, and constructing a new WWTP in the north sewer shed. Traditional deterministic least-cost optimization applied in the first stage can provide a cost-effective and technology-based decision without respect to associated uncertainties system wide. As the model is primarily driven by the fees charged for wastewater transfer, sensitivity analysis was emphasized by the inclusion of varying flat-rate fees for adjustable transfer schemes before contracting process that may support the assessment of fiscal benefits to all parties involved. Yet uncertainties might arise from wastewater generation, wastewater reuse, and cost increase in constructing and operating the new wastewater treatment plant simultaneously. When dealing with multiple sources of uncertainty, the grey mixed integer programming (GIP) model, formulated in the second stage, can further allow all sources of uncertainties to propagate throughout the optimization context, simultaneously leading to determine a wealth of optimal decisions within a reasonable range. Both models ran for three 5-year periods beginning in 2005 and ending in 2020. The dynamic outputs of this analysis reflect the systematic concerns about integrative uncertainties within this decision analysis, which enable decision makers and stakeholders to make all-inclusive decisions for sanitary sewer system expansion in an economically growing region.     

Modelling Tracer Dispersion from Landfills

Several wind tunnel experiments of tracer dispersion from reduced-scale landfill models are presented in this paper. Different experimental set-ups, hot-wire anemometry, particle image velocimetry and tracer concentration measurements were used for the characterisation of flow and dispersion phenomena nearby the models. The main aim of these experiments is to build an extensive experimental data set useful for model validation purposes. To demonstrate the potentiality of the experimental data set, a validation exercise on several mathematical models was performed by means of a statistical technique. The experiments highlighted an increase in pollutant ground level concentrations immediately downwind from the landfill because of induced turbulence and mean flow deflection. This phenomenon turns out to be predominant for the dispersion process. Tests with a different set-up showed an important dependence of the dispersion phenomena from the landfill height and highlighted how complex orographic conditions downwind of the landfill do not affect significantly the dispersion behaviour. Validation exercises were useful for model calibration, improving code reliability, as well as evaluating performances. The Van Ulden model proved to give the most encouraging results.     

A Model for Landscape Planning Under Complex Spatial Conditions

We present a new mathematical programming framework that is adaptable to a variety of spatially explicit landscape problems in environmental investment, conservation, and land-use planning, transport planning, and agriculture. As part of capturing spatial interdependencies, the framework considers decision variables at two levels, finely spaced grid cells and landholdings. We applied the framework to an environmental investment problem using objective functions representing biodiversity and carbon sequestration. We also tested the model to optimize the path of a road through part of the landscape. Using the Nambucca case study in eastern Australia, we applied a hybrid greedy randomised adaptive search procedure (GRASP) to find solutions to the model.     

Extension of the EUROS Integrated Air Quality Model to Fine Particulate Matter by Coupling to CACM/MADRID 2

The European Operational Smog (EUROS) integrated air quality modelling system has been extended to model fine particulate matter (PM). From an extended literature study, the Caltech Atmospheric Chemistry Mechanism and the Model of Aerosol Dynamics, Reaction, Ionisation and Dissolution were selected and recently coupled to EUROS. Currently, modelling of mass and chemical composition of aerosols in two size fractions (PM_2.5 and PM_10–2.5) is possible. The chemical composition is expressed in terms of seven components: ammonium, nitrate, sulphate, elementary carbon, primary inorganic compounds, primary organic compounds and secondary organic compounds. Calculated PM₁₀ concentrations and chemical composition are presented for two summer months of the year 2003 (1 July to 31 August).     

Development and Parameterization of a Rain- and Fire-driven Model for Exploring Elephant Effects in African Savannas

We describe the development and parameterization of a grid-based model of African savanna vegetation processes. The model was developed with the objective of exploring elephant effects on the diversity of savanna species and structure, and in this formulation concentrates on the relative cover of grass and woody plants, the vertical structure of the woody plant community, and the distribution of these over space. Grid cells are linked by seed dispersal and fire, and environmental variability is included in the form of stochastic rainfall and fire events. The model was parameterized from an extensive review of the African savanna literature; when available, parameter values varied widely. The most plausible set of parameters produced long-term coexistence between woody plants and grass, with the tree–grass balance being more sensitive to changes in parameters influencing demographic processes and drought incidence and response, while less sensitive to fire regime. There was considerable diversity in the woody structure of savanna systems within the range of uncertainty in tree growth rate parameters. Thus, given the paucity of height growth data regarding woody plant species in southern African savannas, managers of natural areas should be cognizant of different tree species growth and damage response attributes when considering whether to act on perceived elephant threats to vegetation.     

Multiscale satellite and spatial information and analysis framework in support of a large-area forest monitoring and inventory update

Many countries undertake a national forest inventory to enable statistically valid monitoring in support of national and international reporting of forest conditions and change. Canada’s National Forest Inventory (NFI) program is designed to operate on a 10-year remeasurement cycle, with an interim report produced at the 5-year mid-point. The NFI is a sample-based inventory, with approximately 18,850 2 ×2-km photo plots across the country, distributed on a 20×20-km grid of sample points; these photo plots are the primary data source for the NFI. Capacity to provide annual monitoring information is required to keep policy and decision makers apprised of current forest conditions. In this study, we implemented a multistage monitoring framework and used a Moderate Resolution Imaging Spectroradiometer (MODIS) change product to successfully identify 78% of the changes in forest cover area that were captured with a Landsat change detection approach. Of the NFI photo plots that were identified by both the Landsat and MODIS approaches as having changes in forest cover, the proportion of change area within the plots was similar (R ²?=?0.78). Approximately 70% of the Landsat-derived change events occupied less than 40% of a single MODIS pixel, and more than 90% of the change events of this size were successfully detected with the MODIS product. Finally, MODIS estimates of the proportion of forest cover change at the NFI photo plot level were comparable to change estimates for the ecoregions as a whole (R ²?=?0.95). High-temporal, low-spatial resolution imagery such as MODIS, in combination with other remotely sensed data sources, can provide information on disturbance events within a national forest inventory remeasurement cycle, thereby satisfying the interim information needs of policy and decision makers as well as the requirements of national and international reporting commitments.