In Situ solidification—A case study at a former manufactured gas plant in Macon,Georgia

In situ solidification (ISS) is a reliable, EPA‐recognized technology for the treatment of industrial and waste sites. ISS was employed at a former manufactured gas plant (MGP) site in Macon, Georgia, for the treatment of approximately 33,000 cubic yards of coal tar residues in the saturated zone soil. The site is regulated by the Georgia Environmental Protection Division (EPD) under the Hazardous Site Rehabilitation Act (HSRA) and is located approximately four blocks from downtown Macon. This article will review the technical and regulatory basis for the successful use of this technology, provide an overview of the treatability and pilot testing used to develop the design and implementation of the treatment process, and present the results of the application of ISS to an MGP site. The results of groundwater monitoring, pre and postremediation, will also be discussed. © 2004 Wiley Periodicals, Inc.     

A data integration framework to support Triad projects

Cost‐effective and efficient site remediation and scientifically defensible decisions require site characterizations that are representative of site conditions. The Triad conceptual site model (CSM) is at the center of a continually improving site characterization process that begins during systematic planning and ends after the last data are developed. To gain the full benefit and greatest cost‐effectiveness, the process of CSM refinement should be performed in real time. Thus, the use of collaborative data is critical for evolving and maturing the CSM. In the field, through the use of all available data that are of known quality, a skilled and experienced field team can collect sufficient site information to mature the CSM in a timely manner. To facilitate the planning and execution of such a process, an easily understandable framework is needed to structure data quality that supports scientifically defensible decisions and efficient projects. This article explores such a framework. © 2004 Wiley Periodicals, Inc.     

Water quality monitoring—Some practical sampling frequency considerations

Water quality monitoring involves sampling a population, water quality, that is changing over time. Sample statistics (e.g., sample mean) computed from data collected by a monitoring network can be affected by three general factors: (1) random changes due to storms, rainfall, etc.; (2) seasonal changes in temperature, rainfall, etc.; and (3) serial correlation or duplication in information from sample to sample. (Closely spaced samples will tend to give similar information).In general, these effects have been noted, but their specific effects on water quality monitoring network design have not been well defined quantitatively. The purpose of this paper is to examine these effects with a specific data set and draw conclusions relative to sampling frequency determinations in network design.The design criterion adopted for this study of effects due to the above factors is the width of confidence intervals about annual sample geometric means of water quality variables. The data base for the study consisted of a daily record of 5 water quality variables at 9 monitoring stations in Illinois for a period of 1 year.Three general regions of frequencies were identified: (1) greater than approximately 30 samples per year where serial correlation plays a dominant role; (2) between approximately 10 and 30 samples per year where the effects of seasonal variation and serial correlation tended to cancel each other out; and (3) less than approximately 10 samples per year where seasonal variation plays a dominant role. In region 2, either seasonal variation and serial correlation should both be considered or both ignored. To consider only seasonal variation introduces more error than ignoring it. These results are network averages (over variables and stations) from one network, thus results for individual variables may deviate considerably from the average and from those for other networks.Financial support for this study was provided, in part, by the U.S. Environmental Protection Agency, grant number R805759-01-0.     

Does bird species diversity vary among forest types? A local-scale test in Southern Chile

Birds are the most diverse vertebrate group in Chile, characterized by low species turnover at the country-size scale (high alpha but low beta diversities), resembling an island biota. We tested whether this low differentiation is valid at a local scale, among six forest habitat types. We detected 25 bird species; avifauna composition was significantly different among habitat types, with five species accounting for 60 % of the dissimilarity. We found a higher level of bird assemblage differentiation across habitats at the local scale than has been found at the country-size scale. Such differentiation might be attributed to structural differences among habitats.     

Urinary arsenic levels influenced by abandoned mine tailings in the Southernmost Baja California Peninsula,Mexico

Gold has been mined at San Antonio-El Triunfo, (Baja California Sur, Mexico) since the 18th century. This area has approximately 5,700 inhabitants living in the San Juan de Los Planes and El Carrizal hydrographic basins, close to more than 100 abandoned mining sites containing tailings contaminated with potentially toxic elements such as arsenic. To evaluate the arsenic exposure of humans living in the surrounding areas, urinary arsenic species, such as inorganic arsenic (iAs) and the metabolites mono-methylated (MMA) and di-methylated arsenic acids (DMA), were evaluated in 275 residents (18–84 years of age). Arsenic species in urine were analyzed by hydride generation-cryotrapping-atomic absorption spectrometry, which excludes the non-toxic forms of arsenic such as those found in seafood. Urinary samples contained a total arsenic concentration (sum of arsenical species) which ranged from 1.3 to 398.7 ng mL^?1, indicating 33 % of the inhabitants exceeded the biological exposition index (BEI = 35 ng mL^?1), the permissible limit for occupational exposure. The mean relative urinary arsenic species were 9, 11 and 80 % for iAs, MMA and DMA, respectively, in the Los Planes basin, and 17, 10 and 73 %, respectively, in the El Carrizal basin. These data indicated that environmental intervention is required to address potential health issues in this area.     

A comparison of pretreatment methods for bioethanol production from lignocellulosic materials

Lignocellulosic materials, which consist mainly of cellulose, hemicellulose and lignin, are among the most promising renewable feedstocks for the production of energy and chemicals. Bioethanol is a major biofuel that can be produced from lignocellulosic materials. Its production typically involves a hydrolysis-fermentation route, which has three main steps: pretreatment to get fermentable sugars, fermentation to produce bioethanol, and a separation process to obtain highly concentrated bioethanol. The pretreatment step has been recognized as a technological bottleneck for the cost-effective development of bioprocesses from lignocellulosic materials. In this work we analyze the potential of several pretreatment methods for bioethanol production from lignocellulosic materials. Simulations based on stoichiometric relations and yield data were conducted to evaluate the energy requirements of each pretreatment method. Other parameters were also considered such as the cost of chemicals, consumption of water, and constraints on the composition of inhibitors. Performance benchmarks were identifies using targeting techniques and these benchmarks were used to assess the actual performance of the alternatives. The combination of the evaluated parameters with target production values obtained from reported yields served as the basis for identifying the most promising pretreatment options and for defining areas of opportunities. This approach uses limited information, but it provides reliable results in order to reduce the number of pretreatment alternatives. The target production usage gives an estimation of the global process efficiency without the completed flowsheet defined.     

Incidence of organochlorine pesticide and PCB residues in an aquatic ecosystem of river duero in castile and Leon (Spain)

The occurrence of organochlorine pesticides and polychlorinated biphenyls (PCBs) in an aquatic ecosystem of River Duero was checked by means of a bioindicator organism: the grey heron (Ardea cinerea). Analyses of water, sediments, fish fat tissues and heron viscera revealed a marked bioaccumulation of organochlorine compounds, particularly hexa‐ and heptachlorinated biphenyls of industrial origin, which may account for the gradual decline in the number of individuals that make up the heron colonies studied.     

Potential health impacts of heavy-metal exposure at the Tar Creek Superfund site,Ottawa County,Oklahoma

The potential impact of exposure to heavy metals and health problems was evaluated at the Tar Creek Superfund site, Ottawa County, Oklahoma, USA. Observed versus expected mortality was calculated for selected conditions in the County and exposed cities. Excess mortality was found for stroke and heart disease when comparing the exposed County to the state but not when comparing the exposed cities to the nonexposed rest of the County. However, sample sizes in the exposed area were small, population emigration has been ongoing, and geographic coding of mortality data was incomplete. In an exposed community, 62.5% of children under the age of 6 years had blood lead levels exceeding 10 μg/dl. The relationships between heavy-metal exposure and children’s health and chronic disease in adults are suggestive that a more thorough investigation might be warranted. A number of possible environmental and health studies are suggested, including those focusing on possible central nervous system impacts. Unfortunately, the exposed population is dispersing. One lesson learned at this site is that health studies need to be conducted as soon as possible after an environmental problem is identified to both study the impact of the most acute exposures and to maximize study sample size—including those exposed to higher doses—and minimize the loss of individuals to follow-up.