Generator categories

The following chart lists the differences in regulatory requirements for the three generator categories. 

Along with the specific training required for your generator category, there is some crossover between EPA and DOT training requirements. Generators who ship hazardous waste off-site must comply with both EPA and DOT regulations for hazardous materials (hazmat). Hazardous waste is considered a subset of hazmat. 

It is important to note that if you do not comply with all the regulations for your generator category, for instance, if you mistakenly assume a nonexempt waste is exempt, you do not keep your containers closed, or you exceed your accumulation time limits, EPA can now cite you under the very strict regulations for treatment, storage, and disposal facilities (TSDFs). TSDF requirements include permitting, waste treatment, and financial assurances — to name just a few. 

To resolve the problems associated with structured and unstructured grids, these fundamentally different approaches may be combined to generate mesh types which partially posses the properties of both categories. This gives rise to block-structured , overset and hybrid mesh types which under certain conditions may lead to more efficient simulations than the either class of purely structured or unstructured grids. Detailed discussions related to the properties of these classes of computational grid.s can be found in specialized textbooks (e.g, see Liseikin, 1999) and only brief definitions are given here. 

This category corresponds to the construction of the carbocyclic ring by 2 + 4 cycloaddition with pyrrole-2,3-quinodimethane intermediates. Such reactions can be particularly useful in the synthesis of 5,6-disubstituted indoles. Although there are a few cases where a pyrrolequinodimethane intermediate is generated, the most useful procedures involve more stable surrogates. Both 1,5-di-hydropyrano[3,4-b]pyrrol-5(lf/)-ones[l] and l,6-dihyropyrano[4,3-b]pyrrol-6-(in)-ones[2] can serve as pyrrole-2,3-quinodimethane equivalents. The adducts undergo elimination of CO2. 

Petroleum refining, also called petroleum processing, is the recovery and/or generation of usable or salable fractions and products from cmde oil, either by distillation or by chemical reaction of the cmde oil constituents under the effects of heat and pressure. Synthetic cmde oil, produced from tar sand (oil sand) bitumen, and heavier oils are also used as feedstocks in some refineries. Heavy oil conversion (1), as practiced in many refineries, does not fall into the category of synthetic fuels (syncmde) production. In terms of Hquid fuels from coal and other carbonaceous feedstocks, such as oil shale (qv), the concept of a synthetic fuels industry has diminished over the past several years as being uneconomical in light of current petroleum prices. 

Treatment of Major Depression. Dmgs commonly used for the treatment of depressive disorders can be classified heuristicaHy iato two main categories first-generation antidepressants with the tricycHc antidepressants (TCAs) and the irreversible, nonselective monoamine—oxidase (MAO) inhibitors, and second-generation antidepressants with the atypical antidepressants, the reversible inhibitors of monoamine—oxidase A (RIMAs), and the selective serotonin reuptake inhibitors (SSRIs). Table 4 fists the available antidepressants. 

Emerging technologies for the commercial manufacture of chloric acid fall into three categories (/) generation of high purity chloric acid by thermal decomposition of pure solutions of hypochlorous acid [7790-92-3], HCIO (5). 

The second category of coal Hquefaction iavolves those processes which first generate synthesis gas, a mixture of CO and by steam gasification of coal... 

In addition to these faciUties for supply of data in an expHcit form for direct use by the system, there also are options designed for the calculation of the parameters used by the system s point generation routines. Two obvious categories of this type can be identified and are included at the top left of Figure 5. The first of these appHes to the correlation of raw data and is most commonly appHed to the estimation of binary interaction parameters. 

The second category differs from those discussed above in that it relates, in the main, to those situations for which no data or only characterizing data exist. In such cases, this small set of characterizing data or, in its absence, stmcture data are used to estimate a set of parameters of the type requited by point generation routines. One notable specific example of this type of facihty is the creation of data sets for petroleum boiling fractions from information on average boiling point and density. 

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