Algae biodiesel life cycle assessment using current commercial data.

Autotrophic microalgae represent a potential feedstock for transportation fuels, but life cycle assessment (LCA) studies based on laboratory-scale or theoretical data have shown mixed results. We attempt to bridge the gap between laboratory-scale and larger scale biodiesel production by using cultivation and harvesting data from a commercial algae producer with ∼1000 m(2) production area (the base case), and compare that with a hypothetical scaled up facility of 101,000 m(2) (the future case). Extraction and separation data are from Solution Recovery Services, Inc. Conversion and combustion data are from the Greenhouse Gases, Regulated Emissions, and Energy Use in Transportation Model (GREET). The LCA boundaries are defined as "pond-to-wheels". Environmental impacts are quantified as NER (energy in/energy out), global warming potential, photochemical oxidation potential, water depletion, particulate matter, and total NOx and SOx. The functional unit is 1 MJ of energy produced in a passenger car. Results for the base case and the future case show an NER of 33.4 and 1.37, respectively and GWP of 2.9 and 0.18 kg CO2-equivalent, respectively. In comparison, petroleum diesel and soy diesel show an NER of 0.18 and 0.80, respectively and GWP of 0.12 and 0.025, respectively. A critical feature in this work is the low algal productivity (3 g/m(2)/day) reported by the commercial producer, relative to the much higher productivities (20-30 g/m(2)/day) reported by other sources. Notable results include a sensitivity analysis showing that algae with an oil yield of 0.75 kg oil/kg dry biomass in the future case can bring the NER down to 0.64, more comparable with petroleum diesel and soy biodiesel. An important assumption in this work is that all processes are fully co-located and that no transport of intermediate or final products from processing stage to stage is required.

Ammonia modeling for assessing potential toxicity to fish species in the Rio Grande, 1989-2002.

Increasing volumes of treated and untreated human sewage discharged into rivers around the world are likely to be leading to high aquatic concentrations of toxic, unionized ammonia (NH3), with negative impacts on species and ecosystems. Tools and approaches are needed for assessing the dynamics of NH3. This paper describes a modeling approach for first-order assessment of potential NH3 toxicity in urban rivers. In this study daily dissolved NH3 concentrations in the Rio Grande of central New Mexico, USA, at the city of Albuquerque's treated sewage outfall were modeled for 1989-2002. Data for ammonium (NH4+) concentrations in the sewage and data for discharge, temperature, and pH for both sewage effluent and the river were used. We used State of New Mexico acute and chronic NH3- N concentration values (0.30 and 0.05 mg/L NH3-N, respectively) and other reported standards as benchmarks for determining NH3 toxicity in the river and for assessing potential impact on population dynamics for fish species. A critical species of concern is the Rio Grande silvery minnow (Hybognathus amarus), an endangered species in the river near Albuquerque. Results show that NH3 concentrations matched or exceeded acute levels 13%, 3%, and 4% of the time in 1989, 1991, and 1992, respectively. Modeled NH3 concentrations matched or exceeded chronic values 97%, 74%, 78%, and 11% of the time in 1989, 1991, 1992, and 1997, respectively. Exceedences ranged from 0% to 1% in later years after enhancements to the wastewater treatment plant. Modeled NH3 concentrations may differ from actual concentrations because of NH3 and NH4+ loss terms and additive terms such as mixing processes, volatilization, nitrification, sorbtion, and NH4+ uptake. We conclude that NH3 toxicity must be considered seriously for its potential ecological impacts on the Rio Grande and as a mechanism contributing to the decline of the Rio Grande fish community in general and the Rio Grande silvery minnow specifically. Conclusions drawn for the Rio Grande suggest that NH3 concentrations may be high in rivers around the world where alkaline pH values are prevalent and sewage treatment capabilities are poorly developed or absent.

Nutrient and organic carbon trends and patterns in the upper Rio Grande, 1975-1999.

Nutrient patterns and trends were analyzed using USGS water quality data collected from 1975 to 1999 along the uppermost 600 km of the Rio Grande in Colorado and New Mexico. Data on discharge, pH, organic carbon (total), N-NH(4+)+organic N (total), NH4+ (dissolved), N-NO(2-)+N-NO3- (dissolved), phosphorus (total), and P-orthophosphate (dissolved) came from six USGS stations--Lobatos, Taos Junction, Otowi, San Felipe, Isleta and Bernardo--ranging from the Colorado-New Mexico border to about 80 km below Albuquerque, NM. Kendall's S and Seasonal Kendall's S' were used to measure trend, and ANOVA and Tukey's multiple comparison test were used to analyze spatial differences between stations. Temporal trend analyses show widespread decreases in N and P concentrations at most stations, likely due to improvements in sewage treatment and dilution from increasing discharge. N-NO(2-)+N-NO3- (dissolved) and total nitrate load increases at Isleta and Bernardo, likely due to improved nitrification in sewage treatment and to increasing human population. Spatial analyses show large increases for most parameters at Isleta. All parameters show decreases again at Bernardo, about 50 km downstream from Isleta, except for N-NO(2-)+N-NO3- (dissolved), which continues to increase. Urbanization in the Albuquerque area significantly impacts downstream river nutrient levels.

Assessing public perceptions of computer-based models.

Although there is a solid body of research on both collaborative decision-making and on processes using models, there is little research on general public attitudes about models and their use in making policy decisions. This project assessed opinions about computer models in general and attitudes about a specific model being used in water planning in the Middle Rio Grande Region of New Mexico, United States. More than 1000 individuals were surveyed about their perceptions of computer-based models in general. Additionally, more than 150 attendees at public meetings related to the Middle Rio Grande planning effort were surveyed about their perceptions of the specific Rio Grande-based model. The results reveal that the majority of respondents are confident in their ability to understand models and most believe that models are appropriate tools for education and for making policy decisions. Responses also reveal that trust in who develops a model is a key issue related to public support. Regarding the specific model highlighted in this project, the public revealed tremendous support for its usefulness as a public engagement tool as well as a tool to assist decision-makers in regional water planning. Although indicating broad support for models, the results do raise questions about the role of trust in using models in contentious decisions.