(NRDAs). SIMAP calculates effects as well as fates, but only the fates component is discussed here. OilMap is a widely used relative of SIMAP that considers only near-surface fates, but does provide a choice of process algorithms. As indicated in Table 4-6, three of the four models consider only surface waters. SIMAP is apparently the only widely available model that considers the entire water column. In addition it tracks four oil components separately:

  • monoaromatics: aromatics with molecular weights (MW) less than 100 g/mole;

  • polynuclear aromatic hydrocarbons (PAH): volatile aromatics with MW between 100 and 200 grams/mole;

  • non-aromatic volatiles (<200 g/mole MW); and

  • a residual fraction that is neither volatile nor soluble (>200 g/mole MW).

A comparison between SIMAP and the Conceptual Model of Figure 4-1 shows that SIMAP accounts for all the processes, although obviously each process submodel is often far less than ideal. The simplest model in Table 4-6 is the OSRA model, although it is more complex than can be described in a table. A multiple-step process is actually involved. The first step is to run the basic OSRA model in a Monte Carlo fashion to establish contact probability and time-to-impact contour maps. The second step is to look at weathering and dispersion of some specific spill scenarios impacting critical resources. The first step gives the probability that the spill will hit that resource along with the time to impact. Weathering for these specific scenarios is calculated using NOAA’s ADIOS2, described in part in Table 4-6.

Composite models compare reasonably well with observations. ASCE (1996) briefly compares hindcast results from several two-dimensional models with data from two actual spills (simulations for three historical spills are given, but observations are included for just two of the three). The focus is on time periods on the order of one week after a sudden surface point source spill, with observations consisting of time series locations of major patches of oil. (Comparisons are only for surface oil. No modeling was attempted for overwashed oil.) In general, the ASCE (1996) study concluded that the models evaluated did well, but also noted several major limitations should be kept in mind:

  • The comparisons are largely qualitative, and no mass-balance comparisons are possible because of the lack of comprehensive field observations.

  • The models are run in “hindcast” mode, i.e., after the fact. Actual wind and especially current measurements are minimal; thus the current and wind inputs into the model are modified so that the modeled slicks track the observed one as closely as possible.

  • If the models are run in a “forecast” mode in which future winds and currents must be estimated, then model forecasts will often deviate substantially from observations.

The cases considered by ASCE (1996) are quite limited in the context of the greater problem of “Oil in the Sea.” For example, these cases did not consider subsurface releases, continuous point sources, non-point source releases, or long-term (greater than one week) fates (for more details see ASCE [1996]). French (1998) provided some comparisons between fates and effects calculated from SIMAP, as observed during the North Cape oil spill. Comparisons were generally good.

FATE OF OIL INPUT

Table 4-7 is a summary of the fate processes that affect petroleum hydrocarbons from the seven major input categories. Each input is ranked using a scale of high, medium, and low that indicates the relative importance of each fate process. Table 4-7 was developed by consensus of the committee and is based on many assumptions. It is intended to provide only a general idea of the relative importance of the fates processes. Clearly one of the biggest problems in developing a table such as this is that the importance of a particular fate process will depend on the details of the event. The committee has tried to account for this to a limited extent in the case of accidental spills by including subcategories for various oil types. With these caveats in mind, an explanation of each of the fates is as follows.

Evaporation-volatilization is ranked according to the relative volume of the release that would be lost by net transport from the sea surface to the atmosphere. For example, gasoline would have “high” evaporation whereas a heavy crude would be “low.” Evaporation has been ranked “high” for two-stroke engine inputs, which consist largely of unburned gasoline. Emulsification rankings are driven largely by the oil type whereby gasoline, which has no emulsification potential, would have a low ranking, while a medium, fresh-crude could have a high ranking, although this depends on the specific crude composition.

Dissolution rankings consider the total water-soluble fraction, the rate of dissolution, and the rate of volatilization from the water, reflecting the relative potential of releases to impact water-column resources.

Oxidation rankings reflect the relative rate and extent of oil removal by microbial and photooxidative degradation for those oils that have moderate persistence in the marine environment. Thus, releases of crude oils are ranked “medium” because microbial degradation is a significant weathering process for the intermediate-weight hydrocarbon components in crude oil, whereas releases of heavy, weathered oils are ranked “low” because they are recalcitrant to microbial and photodegradation. In contrast, light oils such as gasoline and light distillates are mostly lost by evaporation-volatilization (Figure 4-2) and not to oxidation, and are ranked as not relevant.

Horizontal transport is a combination of spreading, advection, and horizontal dispersion, and the rankings are



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