Databases physical-chemical

The model contains a surface energy method for parameterizing winds and turbulence near the ground. Its chemical database library has physical properties (seven types, three temperature dependent) for 190 chemical compounds obtained from the DIPPR" database. Physical property data for any of the over 900 chemicals in DIPPR can be incorporated into the model, as needed. The model computes hazard zones and related health consequences. An option is provided to account for the accident frequency and chemical release probability from transportation of hazardous material containers. When coupled with preprocessed historical meteorology and population den.sitie.s, it provides quantitative risk estimates. The model is not capable of simulating dense-gas behavior. 

The CESARS database contains comprehensive environmental and health information on chemicals. It provides detailed descriptions of chemical toxicity to humans, mammals, aquatic and plant life, as well as data on physical chemical properties, and environmental fate and persistence. Each record consists of chemical identification information and provides descriptive data on up to 23 topic areas, ranging from chemical properties to toxicity to environmental transport and fate. Records are in English. Available online through CCINFOline from the Canadian Centre For Occupational Health and Safety (CCOHS) and Chemical Information System (CIS) on CD-ROM through CCIN-FOdisc. 

CleanGredients is an online database of cleaning product ingredients A one-stop-shop for green formulation . The database contains physical chemical data, MSDSs, technical datasheets, and environmental and human health hazard data on raw materials used to formulate cleaning products. 

Syracuse Research Corporation. Physical/Chemical Property Database (PHYSPROP), SRC Environmental Center, Syracuse, NY, 1994. 

In a study by Andersson et al. [30], the possibilities to use quantitative structure-activity relationship (QSAR) models to predict physical chemical and ecotoxico-logical properties of approximately 200 different plastic additives have been assessed. Physical chemical properties were predicted with the U.S. Environmental Protection Agency Estimation Program Interface (EPI) Suite, Version 3.20. Aquatic ecotoxicity data were calculated by QSAR models in the Toxicity Estimation Software Tool (T.E.S.T.), version 3.3, from U.S. Environmental Protection Agency, as described by Rahmberg et al. [31]. To evaluate the applicability of the QSAR-based characterization factors, they were compared to experiment-based characterization factors for the same substances taken from the USEtox organics database [32], This was done for 39 plastic additives for which experiment-based characterization factors were already available. 

A fourth recommendation is to expand LCIA databases with characterization factors on additives. Ideally this should be done on the basis of measured physical/ chemical and effect data but even interim characterization factors based on sound QSAR estimations are better than none. 

The process of risk evaluation for personnel working with dyes and textile chemicals has been discussed in detail [69]. The more extensive the database covering toxicological, physical, chemical and application properties of the product, the easier it is to assess the risks involved. 

Chemical Hazards Response Information System (CHRIS) Database on chemical and physical properties guides to compatibility of chemicals U.S. Coast Guard (USCG)... 

Studies on physical, chemical, and thermodynamic properties of ILs, high-quality data on reference systems, the creation of the comprehensive database, the review efforts, the theoretical modeling of physical-chemical properties, also, the development of acceptable thermodynamic models such as COSMO-RS (01), or mod. UNIFAC is a strategy that will help to make progress in the field of ILs. 

A database of chemical, mineralogical, and physical characteristics of North American fly ashes was assembled from the analysis of more than 178 samples of North American fly ash (McCarthy et al 1989). These fly ashes were derived from the combustion of five principal... 

McCarthy, G. J., Solem, J. K. et al. 1989. Database of chemical, mineralogical and physical properties of North American low-rank coal fly ash. In Ness, H. M. (ed) Proceedings of the 15th Biennial Low-Rank Fuels Symposium, DOE/METC-90/6109, 555-563. 

Another typical source of uncertainty in mixture assessment is the potential interaction between substances. Interactions may occur in the environment (e.g., precipitation after emission in water), during absorption, transportation, and transformation in the organism, or at the site of toxic action. Interactions can be either direct, for example, a chemical reaction between 2 or more mixture components, or indirect, for example, if 1 mixture component blocks an enzyme that metabolizes another mixture component (see Chapters 1 and 2). Direct interactions between mixture components are relatively easy to predict based on physical-chemical data, but prediction of indirect interactions is much more difficult because it requires detailed information about the processes involved in the toxic mechanisms of action. One of the main challenges in mixture risk assessment is the development of a method to predict mixture interactions. A first step toward such a method could be the setup of a database, which contains the results of mixture toxicity tests. Provided such a database would contain sufficient data, it could be used to predict the likelihood and magnitude of potential interaction effects, that is, deviations for CA and RA. This information could subsequently be used to decide whether application of an extra safety factor for potential interaction effects is warranted, and to determine the size of such a factor. The mixture toxicity database could also support the search for predictive parameters of interaction effects, for example, determine which modes of action are involved in typical interactions. 

Preparation and transfer of queries for CAS database searches and capture of hits image display Internet connection to STN. Internet address stnc.cas.org (134,243.5.32). STN provides on-line access to many databases with chemical, physical, thermodynamic, toxicological, pharmaceutical, biomedical, and patent data. 12th Collective Index of Chemical Abstracts on CD-ROM. PCs and Macintosh. 

On the other hand, samples in natural product libraries are usually mixtures of compounds extracted from even more complex mixtures found in living tissues or environments. Such samples are derived and not prepared, and therefore the concentrations of major constituents will not be uniform. Thus, generally, there will be no direct relationship between the physical compound and information held in a database of chemical characteristics. Natural product metabolites are frequently cited as being too... 

Based on the above notion, we began to collect the physical-chemical properties data of ionic liquids in 2003. The collection of data initially began in 2003. After one year, the first phase of the database was established in 2004. That part of the work was published in the Journal of Physical and Chemical Data. With the development of ionic liquids, its kind has greatly increased to approximately 1800 from previous about 600. Their various strucmres result in multiplicate properties. The aim of this handbook of ionic liquids extracted from a large number of scattered publications in the literature is to establish the properties relationships of ionic liquid-stmctures and provide clues to discovering the potentially over one million simple ionic liquids. 

The Canadian Environmental Protection Act, 1999 (CEPA 1999) requires the Ministers of the Environment and Health to categorize the substances on the Canadian Domestic Substances List (DSL). The DSL contains 23 000 substances that are subject to categorization (i.e., prioritization). Generally the data selection process involves a search of the scientific literature and databases for quality experimental data for persistence, bioaccumulation potential and inherent toxicity to humans and nonhuman species. If acceptable data are not found, QSARs or other models are used to estimate the persistence, bioaccumulation, and aquatic toxicity of substances based on structure and physical - chemical properties. 

---