Effective water treatment for rural communities in Suriname : a comparison of point-of-use ceramic filters and centralized treatment with sand filters

For countless communities around the world, acquiring access to safe drinking water is a daily challenge which many organizations endeavor to meet. The villages in the interior of Suriname have been the focus of many improved drinking water projects as most communities are without year-round access. Unfortunately, as many as 75% of the systems in Suriname fail within several years of implementation. These communities, scattered along the rivers and throughout the jungle, lack many of the resources required to sustain a centralized water treatment system. However, the centralized system in the village of Bendekonde on the Upper Suriname River has been operational for over 10 years and is often touted by other communities. The Bendekonde system is praised even though the technology does not differ significantly from other failed systems. Many of the water systems that fail in the interior fail due to a lack of resources available to the community to maintain the system. Typically, the more complex a system becomes, so does the demand for additional resources. Alternatives to centralized systems include technologies such as point-of-use water filters, which can greatly reduce the necessity for outside resources. In particular, ceramic point-of-use water filters offer a technology that can be reasonably managed in a low resource setting such as that in the interior of Suriname. This report investigates the appropriateness and effectiveness of ceramic filters constructed with local Suriname clay and compares the treatment effectiveness to that of the Bendekonde system. Results of this study showed that functional filters could be produced from Surinamese clay and that they were more effective, in a controlled laboratory setting, than the field performance of the Bendekonde system for removing total coliform. However, the Bendekonde system was more successful at removing E. coli. In a life-cycle assessment, ceramic water filters manufactured in Suriname and used in homes for a lifespan of 2 years were shown to have lower cumulative energy demand, as well as lower global warming potential than a centralized system similar to that used in Bendekonde.

REMEDIATION OF TETRACYCLINE FROM WATER SOURCES USING VETIVER GRASS (Chrysopogon zizanioides L. Nash) AND TETRACYCLINE-TOLERANT ROOT-ASSOCIATED BACTERIA

Antibiotics are emerging contaminants worldwide. Due to insufficient policy regulations, public awareness, and the constant exposure of the environment to antibiotic sources has created a major environmental concern. Wastewater treatment plants (WWTP) are not equipped to filter-out these compounds before the discharge of the disinfected effluent into water sources (e.g., lakes and streams) and current available technologies are not equipped to remediate these compounds from environmental sources. Hence, the challenge remains to establish a biological system to remove these antibiotics from wastewater. An invitro hydroponic remediation system was developed using vetiver grass (Chrysopogon zizanioides L. Nash) to remediate tetracycline (TC) from water. Comparative metabolomics studies were conducted to investigate the metabolites/pathways associated with tetracycline metabolism in plants and TC-degrading bacteria. The results show that vetiver plants effectively uptake tetracycline from water sources. Vetiver root-associated bacteria recovered during the hydroponic remediation trial were highly tolerant to TC (as high as 600 ppm) and could use TC as a sole carbon and energy source. Growth conditions (pH, temperature, and oxygen requirement) for TC-tolerant bacteria were optimized for higher TC remediation capability from water sources. The plant (roots and shoots) and bacterial species were further characterized for the metabolites produced during the TC degradation process using GC-MS to identify the possible biochemical mechanism involved. Also, the plant root zone was screened for metabolites/enzymes that were secreted during antibiotic degradation and could potentially enhance the degradation process. The root zone was selected for this analysis because this region of the plant has shown a greater capacity for antibiotic degradation compared to the shoot zone. The role of antioxidant enzymes in TC degradation process revealed glutathione-S-transferase (GSTs) as an important group of enzymes in both plant and bacteria potentially involved in TC degradation process. Metabolomics results also suggest potential GST activity in the TC remediation/ transformation process used by plants. This information could be useful in gaining insights for the application of biological remediation systems for the mitigation of antibiotics from waste-water.

PROBABILISTIC MODELING OF RAINFALL INDUCED LANDSLIDE HAZARD ASSESSMENT IN SAN JUAN LA LAGUNA, SOLOLÁ, GUATEMALA

The municipality of San Juan La Laguna, Guatemala is home to approximately 5,200 people and located on the western side of the Lake Atitlán caldera. Steep slopes surround all but the eastern side of San Juan. The Lake Atitlán watershed is susceptible to many natural hazards, but most predictable are the landslides that can occur annually with each rainy season, especially during high-intensity events. Hurricane Stan hit Guatemala in October 2005; the resulting flooding and landslides devastated the Atitlán region. Locations of landslide and non-landslide points were obtained from field observations and orthophotos taken following Hurricane Stan. This study used data from multiple attributes, at every landslide and non-landslide point, and applied different multivariate analyses to optimize a model for landslides prediction during high-intensity precipitation events like Hurricane Stan. The attributes considered in this study are: geology, geomorphology, distance to faults and streams, land use, slope, aspect, curvature, plan curvature, profile curvature and topographic wetness index. The attributes were pre-evaluated for their ability to predict landslides using four different attribute evaluators, all available in the open source data mining software Weka: filtered subset, information gain, gain ratio and chi-squared. Three multivariate algorithms (decision tree J48, logistic regression and BayesNet) were optimized for landslide prediction using different attributes. The following statistical parameters were used to evaluate model accuracy: precision, recall, F measure and area under the receiver operating characteristic (ROC) curve. The algorithm BayesNet yielded the most accurate model and was used to build a probability map of landslide initiation points. The probability map developed in this study was also compared to the results of a bivariate landslide susceptibility analysis conducted for the watershed, encompassing Lake Atitlán and San Juan. Landslides from Tropical Storm Agatha 2010 were used to independently validate this study’s multivariate model and the bivariate model. The ultimate aim of this study is to share the methodology and results with municipal contacts from the author's time as a U.S. Peace Corps volunteer, to facilitate more effective future landslide hazard planning and mitigation.