Geographic information systems (GIS) based model of dairy manure transportation and application with environmental quality consideration

Survey information was used to develop a minimum cost spatial dairy manure transportation model where environmental quality and crop nutrient requirements were treated as constraints. The GIS model incorporated land use types, exact locations of dairy farms and farmlands, road networks, and distances from each dairy farm to receiving farmlands to identify dairy manure transportation routes that minimized costs relative to environmental and other constraints. Our analyses indicated that the characteristics of dairy manure, its bulk and relatively low primary N, P₂O₅ and K₂O nutrient levels limit the distribution areas or distances between the farms and the land over which the manure can be economically spread. Physical properties of the land limit the quantities of nutrients that can be applied because of excess nutrient buildup in soil and potential to harm nearby waterbodies and downstream people and places. Longer distances between dairy and farmland favor the use of commercial fertilizers due to the high cost of manure transportation. At $0.08 per ton per km transportation cost, the optimal cut-off distances for dairy manure application is 30 km for N and 15 km each for P₂O₅ and K₂O consistent rules. An analysis of dairy manure application to different crop types suggest that, on average, 1 ha of land requires 61 tons of dairy manure to meet the recommended N, P₂O₅ and K₂O needs.     

Water Resource Management in Botswana: Balancing Sustainability and Economic Development*

Botswana is a rapidly developing country in southern Africa. Over the last three decades, diamond mining and tourism have provided double-digit rates of economic growth. Yet most of Botswana’s land is in the Kalahari desert where the climate is subject to sustained periods of severe drought. In this environment, water resources are the most crucial of all environmental resources. Water use directly affects economic development because water utilization impacts all the major national economic sectors. A sustainable water use resource management plan must stretch several decades into the future to assure the availability of adequate supplies of water to future generations while not compromising the ability of the current generation to reasonable rates of economic development. Yet thinking about sustainability is present in Botswana water policy mostly only in rhetoric. A series of cultural traditions and political constraints, coupled with bureaucratic managerial weaknesses, serve to maintain a system of water allocation that is unsustainable in the long run and inefficient in the short-term. Unless sustainable water use patterns are adopted, the results for the short-term, as well as the long-term, will be devastating. Drawing on data obtained through a series of interviews with government officials, leaders of non-governmental organizations (NGOs), and water resource researchers, this paper explores water policy in Botswana within the larger context of sustainable natural resource management practice and the pressures of economic development. This research was partially funded under U.S. Department of State, College and University Affiliations Grant # ASCS-1095.     

Analysis of a Fisheries Model for Harvest of Hawksbill Sea Turtles (Eretmochelys imbricata)

The hawksbill sea turtle ( Eretmochelys imbricata ) is valued for its mottled shell, called bekko in Japan. Populations of hawksbills have declined worldwide, and currently there is a ban on all international trade of hawksbill shell and products (Convention on International Trade of Endangered Species of Wild Fauna and Flora). In 1992 the Bekko Association of Japan introduced a fisheries model for hawksbill sea turtles in Cuba. The model estimated a sustainable yield of 5500 turtles from Cuban feeding grounds. We examined the model to determine whether this level of harvest was reasonable. Little biological information is available for hawksbills, so the model contained a number of simplifying assumptions, and several of its parameters were unsupported by data. The population was assumed to be at equilibrium, with a constant number of recruits (1-year-old turtles) and constant annual survival and growth rates. We analyzed the model to see how population size and sustainable yield results were affected by changes in various model parameters, and we found that the model was most sensitive to annual survival probability, which was assumed to be a constant 90% per year for all turtles greater than 1 year old. When we entered growth curves generated by mark-recapture data from other hawksbill populations, the model predicted a wide range of population sizes and sustainable yields. We determined that the assumptions of the current model make it unreliable for predicting sustainable yield of hawksbills, and that much research is needed to produce a more accurate model for management of this endangered species.     

On the extraction of an exhaustible resource by a monopoly

Hotelling's r-percent rule does not hold for monopoly extractors of durable exhaustible resources. An example with a nondurable resource in which the rule also fails to hold is presented. An economy with a fixed average propensity to save is modelled. The monopoly extractor recognizes that resource extraction, by affecting output and hence capital accumulation, affects future demand. The firm exploits this effect by causing the marginal profitability of extraction to grow faster or slower than the rate of interest, depending upon initial conditions. Conditions are developed under which the growth rate will be less than the interest rate.     

Predicting runoff and associated nitrogen losses from turfgrass using the Root Zone Water Quality Model (RZWQM)

Nitrogen fertilizers are used to maintain optimum turfgrass quality, but off-site movement of this primary nutrient can affect water quality. We conducted a 4-yr study (1998-2001) designed to measure nitrate N runoff from turfgrass, gathering data to be used in the model. The process-based Root Zone Water Quality Model (RZWQM) was used to predict nitrate associated with runoff from turfgrass. The measurements were made on 12 sloped (5%), 25-m2 plots of 'Tifway' bermudagrass [Cynodon dactylon (L.) Pers.], managed as golf course fair-ways and exposed to natural and simulated rainfall. Surface runoff volume and nitrate N loads were monitored after applying simulated rainfall at an average intensity of 27.4 mm h(-1). The irrigation occurred (25 or 50 mm) 4 through 168 h after treatment with various rates of N fertilizers for 1998-2001. RZWQM adequately simulated water runoff volumes (<19%; nonsignificant, paired t test) in the first three (normal or wet) years, but overpredicted (70%) in the fourth, dry year. RZWQM overpredicted nitrate N loads by a factor of 1.3 for the first three years (nonsignificant), and by a factor of almost 6 for the fourth year (highly significant). These overpredictions occurred when the runoff volumes and N loads were very small. The research has shown that refinements to RZWQM are needed for turfgrass management applications.     

Perfluorinated chemicals in selected residents of the American continent

Perfluorinated chemicals (PFCs) are used in multiple consumer products. Perfluorooctane sulfonic acid (PFOS) and perfluorooctanoic acid (PFOA), the most widely studied PFCs, may be potential developmental, reproductive, and systemic toxicants. Although PFCs seem to be ubiquitous contaminants found both in humans and animals, geographic differences may exist in human exposure patterns to PFCs. We measured 11 PFCs in 23 pooled serum samples collected in the United States from 1990 through 2002, and in serum samples collected in 2003 from 44 residents from Trujillo, Peru. PFOS and PFOA were detected in all the pooled samples; perfluorohexane sulfonic acid (PFHxS) was detected in 21. Median concentrations were 31.1 micrograms per liter (mug/l, PFOS), 11.6 microg/l (PFOA), and 2 microg/l (PFHxS). The 90th percentile concentrations of PFCs in the 44 Peruvian residents were 0.7 microg/l (PFOS), 0.1 microg/l (PFOA), and <0.3 microg/l (PFHxS). The frequencies of detection were 20% (PFOS), 25% (PFOA), and 9% (PFHxS). The frequent detection of selected PFCs in the pooled samples from the United States and the lack of clear concentration trends based on a year of collection suggest a sustained widespread exposure to these compounds among US residents, at least since the 1990s. By contrast, the much lower frequency of detection and concentration ranges of PFCs in Peru suggest a lower exposure of Peruvians to PFCs compared with North Americans. Genetic variability, diet, lifestyle, or a combination of all these may contribute to the different patterns of human exposure to PFCs in the United States and Peru.     

Characterizing perfluorooctanoate in ambient air near the fence line of a manufacturing facility: comparing modeled and monitored values

In order to improve our understanding of the nature, measurement and prediction of salts of perfluorooctanoic acid (PFOA) in air, two studies were performed along the fence line of a fluoropolymer manufacturing facility. First, a six-event, 24-hr monitoring series was performed around the fence line using the OSHA versatile sampler (OVS) system. Perfluorooctanoate concentrations were determined as perfluorooctanoic acid (PFOA) via liquid chromatography and mass spectrometry. Those data indicated that the majority of the PFOA was present as a particulate. No vapor-phase PFOA was detected above a detection limit of approximately 0.07 microg/m3. A follow-up study using a high-volume cascade impactor verified the range of concentrations observed in the OVS data. Both studies aligned with the major transport direction and range of concentrations predicted by an air dispersion model, demonstrating that model predictions agreed with monitoring results. Results from both monitoring methods and predictions from air dispersion modeling showed the primary direction of transport for PFOA was in the prevailing wind direction. The PFOA concentration measured at the site fence over the 10-week sampling period ranged from 0.12 to 0.9 microg/m3. Modeled predictions for the same time period ranged from 0.12 to 3.84 microg/m3. Less than 6% of the particles were larger than 4 microm in size, while almost 60% of the particles were below 0.3 microm. These studies are believed to be the first published ambient air data for PFOA in the environment surrounding a manufacturing facility.     

Quality assured measurements of animal building emissions: gas concentrations

Comprehensive field studies were initiated in 2002 to measure emissions of ammonia (NH3), hydrogen sulfide (H2S), carbon dioxide (CO2), methane (CH4), nonmethane hydrocarbons (NMHC), particulate matter <10 microm in diameter, and total suspended particulate from swine and poultry production buildings in the United States. This paper focuses on the quasicontinuous gas concentration measurement at multiple locations among paired barns in seven states. Documented principles, used in air pollution monitoring at industrial sources, were applied in developing quality assurance (QA) project plans for these studies. Air was sampled from multiple locations with each gas analyzed with one high quality commercial gas analyzer that was located in an environmentally controlled on-farm instrument shelter. A nominal 4 L/min gas sampling system was designed and constructed with Teflon wetted surfaces, bypass pumping, and sample line flow and pressure sensors. Three-way solenoids were used to automatically switch between multiple gas sampling lines with > or =10 min sampling intervals. Inside and outside gas sampling probes were between 10 and 115 m away from the analyzers. Analyzers used chemiluminescence, fluorescence, photoacoustic infrared, and photoionization detectors for NH3, H2S, CO2, CH4, and NMHC, respectively. Data were collected using personal computer-based data acquisition hardware and software. This paper discusses the methodology of gas concentration measurements and the unique challenges that livestock barns pose for achieving desired accuracy and precision, data representativeness, comparability and completeness, and instrument calibration and maintenance.