Environmental Chemicals Data and

Environmental Chemicals Data and Information Network (ECDIN) Environmental Fate (ENVIROFATE) Environmental Eate Databases... 

The data base CICLOPS (Computer interrogation of a Comprehensive List of Organic Pollutants) at December 1983 contained information on about 3.600 organic compounds with over 22.000 individual records. In order to make CICLOPS more easily accessible to participating laboratories and other establishments with legitimate interests, its conversion and loading as a subset of the environmental matrices files of the ECDIN (Environmental Chemicals Data and Information Network of the European Communities) data base has been investigated. 

CAS = Chemical Abstracts Service ECDIN = Environmental Chemicals Data and Infonnation Network HSDB = Hazardous Substances Data Bank PHYSPROP = Physical Properties Database (contains ChemS, arailable online at hUp /esc.syrres.com/ChemS3/deteulthtm)... 

POSTER SESSION ECDIN, ENVIRONMENTAL CHEMICALS DATA AND INFORMATION NETWORK... 

Environmental Chemicals Data and Information Network (ECDIN) (19). This is an Internet accessible factual data bank based in Europe containing a wide variety of environmental and CH S information. Much of the information is similar to that found on MSDSs, but unlike those extensive references are given. Additional information is available that is not found on MSDSs. Two categories that are useful in developing supplementary lecture material include Analytical Methods for Detection and Chemical Processes used for production. 

Databank) and ECDIN (Environmental Chemicals Data and Information Network) (see Chemical Safety Information Databases). HSDS gives extensive information about 4500 dangerous substances on practically all information types mentioned in Section 3. ECDIN is still available online and on CD-ROM. It comprises data on approximate 100000 chemicals, but the given datasets on each substance are often not completely filled with actual data. For some time ECDIN has also been available on the Internet free of charge. ... 

There is also a growing number of specialized databases available on specific topics such as CEC Replacement, effluents and pesticides, environmental chemical data, etc. These are usually on CD-ROM or floppy disk (3). 

Of course, in developing these models, it is necessary to test them extensively against experimental data to ensure that their predictions are the result of appropriately simulating the chemical and physical processes involved, and not to a fortuitous cancellation of errors. For example, the chemical submodels are tested against environmental chamber data, and the final model results against ambient air measurements. 

Tier 2 PRA process involved developing environmental exposure data and chronic toxicity data distributions for individual POPs. The mean concentrations of POPs in local marine water measured at various locations were used as exposure data in the construction of the exposure distribution. The chronic toxicity data distribution was established based on published international acute toxicity data (LC50, EC50) on a variety of aquatic organisms tested in many jurisdictions, drawn primarily from the USEPA ECOTOX database (2002) (available at http //www.epa.gov/ ecotox). If the upper 5th centile of the measured chemical exposure data distribution did not exceed the lower 5th centile of its estimated chronic toxicity distribution, the potential ecological risk posed by the chemical was judged to be tolerable (Hall and Giddings, 2000). 

Environmental projects revolve around environmental data collection, analytical chemistry data for toxic pollutants in particular. Chemical data enable us to conclude, whether hazardous conditions exist at a site and whether such conditions create a risk to human health and the environment. We gather environmental chemical data by collecting samples of soil, water, and other environmental media at the right time and at the right place and by analyzing them for chemical pollutants. In other words, in the core of every environmental project lies an environmental sample. 

As we already know, an environmental sample is a fragile living matter that can be severely damaged at every step of its existence. Due to the inherent nature of environmental media and a host of potential errors associated with sampling, analysis, and data management, the collection of environmental chemical data is not an exact science. In fact, all environmental chemical data are only the estimates of the true condition that these data represent. In order to make these estimates more accurate, we must examine the sources of errors and take measures to control them. 

Planning is the most critical phase of the data collection process as it creates a foundation for the success of the implementation and assessment phases. Two major tasks of the planning phase, as shown in Figure 2.1, are Task 1—Data Quality Objectives Development and Task 2—Sampling and Analysis Plan Preparation. The SAP summarizes the project objectives and requirements for environmental chemical data collection. 

The EPA first introduced the DQO process in 1986 (EPA, 1986) and finalized it in 2000 (EPA, 2000a). The purpose of the DQO process is to provide a planning tool for determining the type, quality, and quantity of data collected in support of the EPA s decisions. Although developed specifically for projects under the EPA s oversight, the DQO process, being a systematic planning tool, is applicable to any projects that require environmental chemical data collection. 

Comparability of environmental chemical data encompasses the concepts of precision, accuracy, and representativeness. Because accuracy and precision depend on the analytical procedure and representativeness depends on the sampling procedure, comparability is greatly affected by the sampling and analysis procedures used in data collection. For the data sets to be comparable, the samples must be collected and handled in a similar manner and the measurements must be obtained under the exact same analytical conditions. The observance of standard field and laboratory protocols and procedures, the use of EPA-approved or standard analytical methods and accepted QA/QC practices assure data comparability. 

In environmental chemical data collection, the purpose of field implementation is to collect representative samples for the production of valid and relevant data. To be representative, the samples must have all of the following attributes ... 

The second half of the implementation phase of the environmental chemical data collection process consists of Task 4—Laboratory Analysis and Task 5—Laboratory QA/QC. Arising from a foundation of project planning and following field sampling implementation as shown in Figure 4.1, these tasks transform the collected samples into chemical data. 

Statistical tests of environmental chemical data enable us to compare two sets of data to each other or to compare a set to an action level and make decisions based on these comparisons with a chosen level of confidence. Statistical tests are usually based on the assumptions that the measurements are normally distributed on a Gaussian curve and defined by the standard deviation o, as shown in Figure 1, and that the errors of measurements are random and independent (each given error affects a measurement but does not affect others). 

Student s t-test is frequently used in statistical evaluations of environmental chemical data. It establishes a relationship between the mean (x) of normally distributed sample measurements, their sample standard deviation (,v), and the population mean (p). Confidence intervals may be calculated based on Student s t-test (Equation 10). The upper limit of the confidence interval is compared to the action level to determine whether the sampled medium contains a hazardous concentration of a pollutant. If the upper confidence limit is below the action level, the medium is not hazardous otherwise the opposite conclusion is reached. 

A Real Time X-Ray Inspection System is introduced to replace Film X-Ray. The main objective is to reduce the consumption of film and to reduce the environmental pollution due to lead intensifying screens and chemicals. Other benefits are the reduction of space to storage X-ray data and the shorter inspection time, which gives a faster feed back to production. 

In 1986, David Weininger created the SMILES Simplified Molecular Input Line Entry System) notation at the US Environmental Research Laboratory, USEPA, Duluth, MN, for chemical data processing. The chemical structure information is highly compressed and simplified in this notation. The flexible, easy to learn language describes chemical structures as a line notation [20, 21]. The SMILES language has found widespread distribution as a universal chemical nomenclature... 

---