Geographic distribution and environmental characterization of livestock production systems in Eastern Africa

The central role played by livestock in the livelihoods of rural households in the developing world is seldom fully appreciated by policy makers, development agencies and donors. Knowledge gaps in the geographic distribution and environmental determinants of farming systems, especially if viewed through the livestock lens, compound this problem. We have produced a map of pastoral, agro-pastoral and mixed farming systems across Eastern Africa, by analysing datasets collected in the framework of livelihood analysis. Input data were gathered between 2000 and 2007 by various emergency and development agencies for Djibouti, Eritrea, Kenya, Somalia, Uganda and parts of Ethiopia and Sudan. A quantitative definition of the production systems is adopted, based on the ratio of livestock- to crop-derived income. The resulting livelihood-based map of livestock production systems was compared through correspondence analysis to an alternative livestock production systems map, produced independently from environmental data. Convergence between the two mapping approaches was evident. The geographic distribution of the livestock production systems was also modelled using multivariate analysis of remotely sensed and other geospatial datasets. Models show high statistical accuracy, and were thus used to fill the gaps in the observed distribution of livestock production systems. Finally, selected environmental factors underpinning the systems (agro-climatology, human and livestock populations and land cover) were analysed in detail, enabling the livestock production systems to be characterized in terms of them. The regional scope of the map, as well as its direct link with a vast amount of livelihood information, render it a valuable tool for a range of development and research applications, including those related to global change.     

Reply to Discussion1 - by George Ice,George Brown,John Gravelle,C. Rhett Jackson,Jeff Light,Timothy Link,Douglas Martin,Dale McGreer,and Arne Skaugset2 “Stream Temperature Relationships to Forest Harvest in Western Washington”3

Pollock, Michael M. and Timothy J. Beechie, 2010. Reply to Discussion –“Stream Temperature Relationships to Forest Harvest in Western Washington” by George Ice, George Brown, John Gravelle, C. Rhett Jackson, Jeff Light, Timothy Link, Douglas Martin, Dale McGreer, and Arne Skaugset. Journal of the American Water Resources Association (JAWRA) 46(4): 843-847. DOI: 10.1111/j.1752-1688.2010.00456.x     

Electricity from Fossil Fuels without CO2 Emissions: Assessing the Costs of Carbon Dioxide Capture and Sequestration in U.S. Electricity Markets

ABSTRACT

The decoupling of fossil-fueled electricity production from atmospheric CO₂ emissions via CO₂ capture and sequestration (CCS) is increasingly regarded as an important means of mitigating climate change at a reasonable cost. Engineering analyses of CO₂ mitigation typically compare the cost of electricity for a base generation technology to that for a similar plant with CO₂ capture and then compute the carbon emissions mitigated per unit of cost. It can be hard to interpret mitigation cost estimates from this plant-level approach when a consistent base technology cannot be identified. In addition, neither engineering analyses nor general equilibrium models can capture the economics of plant dispatch. A realistic assessment of the costs of carbon sequestration as an emissions abatement strategy in the electric sector therefore requires a systems-level analysis. We discuss various frameworks for computing mitigation costs and introduce a simplified model of electric sector planning. Results from a “bottom-up” engineering-economic analysis for a representative U.S. North American Electric Reliability Council (NERC) region illustrate how the penetration of CCS technologies and the dispatch of generating units vary with the price of carbon emissions and thereby determine the relationship between mitigation cost and emissions reduction.     

Magnetic ion exchange treatment of stabilized landfill leachate

Stabilized landfill leachate is characterized by a high concentration of non-biodegradable organic matter, which is similar in chemistry to dissolved organic matter (DOM) in the natural aquatic environment. Magnetic ion exchange (MIEX) resin treatment is well-studied in drinking water for removal of DOM from natural waters. There are fewer studies evaluating MIEX treatment of waste waters, and there is no previous work evaluating MIEX treatment of landfill leachate. This work systematically evaluated MIEX treatment of stabilized landfill leachate and evaluated the results in the context of previous studies of MIEX treatment of natural and waste waters. Five leachates from four landfills were evaluated as a function of MIEX resin dose, mixing time, and regeneration efficiency. MIEX resin removed DOM from landfill leachate, even in the presence of a reported high background concentration of inorganic ions. MIEX resin that was exhausted with leachate DOM was effectively regenerated with a concentrated NaCl solution, and regenerated MIEX resin performed similarly to virgin resin. For a majority of the leachates, the removal trend for MIEX resin was color > UV-absorbing substances > dissolved organic carbon ≈ COD > total nitrogen. Finally, MIEX resin removed a wider range of DOM from leachate than coagulation. The most important contribution of this work is that MIEX treatment of leachate followed very similar trends as MIEX treatment of natural waters, which will allow previous MIEX data to be used to estimate the treatment efficiency of other waste waters.     

Comparing universal kriging and land-use regression for predicting concentrations of gaseous oxides of nitrogen (NOx) for the Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air)

BACKGROUND: Epidemiological studies that assess the health effects of long-term exposure to ambient air pollution are used to inform public policy. These studies rely on exposure models that use data collected from pollution monitoring sites to predict exposures at subject locations. Land use regression (LUR) and universal kriging (UK) have been suggested as potential prediction methods. We evaluate these approaches on a dataset including measurements from three seasons in Los Angeles, CA. METHODS: The measurements of gaseous oxides of nitrogen (NOx) used in this study are from a "snapshot" sampling campaign that is part of the Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air). The measurements in Los Angeles were collected during three two-week periods in the summer, autumn, and winter, each with about 150 sites. The design included clusters of monitors on either side of busy roads to capture near-field gradients of traffic-related pollution. LUR and UK prediction models were created using geographic information system (GIS)-based covariates. Selection of covariates was based on 10-fold cross-validated (CV) R(2) and root mean square error (RMSE). Since UK requires specialized software, a computationally simpler two-step procedure was also employed to approximate fitting the UK model using readily available regression and GIS software. RESULTS: UK models consistently performed as well as or better than the analogous LUR models. The best CV R(2) values for season-specific UK models predicting log(NOx) were 0.75, 0.72, and 0.74 (CV RMSE 0.20, 0.17, and 0.15) for summer, autumn, and winter, respectively. The best CV R(2) values for season-specific LUR models predicting log(NOx) were 0.74, 0.60, and 0.67 (CV RMSE 0.20, 0.20, and 0.17). The two-stage approximation to UK also performed better than LUR and nearly as well as the full UK model with CV R(2) values 0.75, 0.70, and 0.70 (CV RMSE 0.20, 0.17, and 0.17) for summer, autumn, and winter, respectively. CONCLUSION: High quality LUR and UK prediction models for NOx in Los Angeles were developed for the three seasons based on data collected for MESA Air. In our study, UK consistently outperformed LUR. Similarly, the 2-step approach was more effective than the LUR models, with performance equal to or slightly worse than UK.     

The Role of Ownership in Environmental Performance: Evidence from Coalbed Methane Development

One way coalbed methane production differs from traditional oil and gas extraction is in the large quantities of produced water. This water must be disposed of for production to occur. Surface discharge has proven to be a low-cost alternative; regulations are in place to protect surface water quality. This paper investigates the effects of alternative ownership regimes on regulatory compliance. A unique dataset linking coalbed methane wells in Wyoming to water disposal permit violations is used to explore differences in environmental performance across severed and unified minerals. Empirical analysis of these data suggest that ownership does impact environmental compliance behavior. Most violations occur on split estate. Federal split estate wells have more severe violations, though not necessarily more of them. Federal unified wells performed best, with fewer and less serious violations. Wells on private land have more, though not necessarily more severe, violations. These results suggest some room for policy proposals accounting for alternative ownership regimes.     

SOIL MOISTURE SENSORS FOR CONTINUOUS MONITORING1

ABSTRACT: Certain physical and chemical properties of soil vary with soil water content. The relationship between these properties and water content is complex and involves both the pore structure and constituents of the soil solution. One of the most economical techniques to quantify soil water content involves the measurement of electrical resistance of a dielectric medium that is in equilibrium with the soil water content. The objective of this research was to test the reliability and accuracy of fiberglass soil-moisture electrical resistance sensors (ERS) as compared to gravimetric sampling and Time Domain Reflectometry (TDR). The response of the ERS was compared to gravimetric measurements at eight locations on the USDA-ABS Walnut Gulch Experimental Watershed. The comparisons with TDR sensors were made at three additional locations on the same watershed. The high soil rock content (≥45 percent) at seven locations resulted in consistent overestimation of soil water content by the ERS method. Where rock content was less than 10 percent, estimation of soil water was within 5 percent of the gravimetric soil water content. New methodology to calibrate the ERS sensors for rocky soils will need to be developed before soil water content values can be determined with these sensors.     

HYDROLOGIC BEHAVIOR OF VEGETATED ROOFS1

ABSTRACT: Control of stormwater runoff from impervious surfaces is an important national goal because of disruptions to downstream ecosystems, water users, and property owners caused by increased flows and degraded quality. One method for reducing stormwater is the use of vegetated (green) roofs, which efficiently detain and retain stormwater when compared to conventional (black) roofs. A paired green roof‐black roof test plot was constructed at the University of Georgia and monitored between November 2003 and November 2004 for the green roof's effectiveness in reducing stormwater flows. Stormwater mitigation performance was monitored for 31 precipitation events, which ranged in depth from 0.28 to 8.43 cm. Green roof precipitation retention decreased with precipitation depth; ranging from just under 90 percent for small storms (< 2.54 cm) to slightly less than 50 percent for larger storms (> 7.62 cm). Runoff from the green roof was delayed; average runoff lag times increased from 17.0 minutes for the black roof to 34.9 minutes for the green roof, an average increase of 17.9 minutes. Precipitation and runoff data were used to estimate the green roof curve number, CN = 86. This information can be used in hydrologic models for developing stormwater mitigation programs.