Specific growth and mortality rates of juvenile rainbow trout (Salmo gairdneri) were determined for 50 days at seven constant temperatures between 8 and 22 °C and six diel temperature fluctuations (sine curve of amplitude ±3.8 deg C about mean temperatures from 12 to 22 °C). For constant temperature treatments the maximum specific growth rate of trout fed excess rations was 5.12%/day at 17.2 °C. An average specific mortality rate of 0.35%/day was observed at the optimum temperature and lower. At temperatures in excess of the growth optimum, mortality rates were significantly higher during the first 20 days of this experiment than the last 30 days. The highest constant temperature at which specific growth and mortality rates became equal (initial biomass remained constant over 40 days) was 23 °C. The upper incipient lethal temperature was 25.6 °C for trout acclimated to 16 °C. A yield model was developed to describe the effects of temperature on the living biomass over time and to facilitate comparison of treatment responses. When yield was plotted against mean temperature, the curve of response to fluctuating temperatures was shifted horizontally an average 1.5 deg C towards colder temperatures than the curve of response to constant temperature treatments. This response pattern to fluctuating treatments indicates that rainbow trout do not respond to mean temperature, but they acclimate to some value between the mean and maximum daily temperatures. These data are discussed in relation to establishment of criteria for summer maximum temperatures for fish. Key words: constant temperature, fluctuating temperature, specific growth rate, specific mortality rate, yield, lethal temperature, zero net biomass, rainbow trout, thermal criteria

An estimation of the human lung cancer “unit risk” from diesel engine particulate emissions has been made using a comparative potency approach. This approach involves evaluating the tumorigenic and mutagenic potencies of the particulates from four diesel and one gasoline engine in relation to other combustion and pyrolysis products (coke oven, roofing tar, and cigarette smoke) that cause lung cancer in humans. The unit cancer risk is predicated on the linear nonthreshold extrapolation model and is the individual lifetime excess lung cancer risk from continuous exposure to 1 μg carcinogen per m3 inhaled air. The human lung cancer unit risks obtained from the epidemiologic data for coke oven workers, roofing tar applicators, and cigarette smokers were, respectively, 9.3 × 10−4, 3.6 × 10−4, and 2.2 × 10−6 per μg particulate organics per m3 air. The comparative potencies of these three materials and the diesel and gasoline engine exhaust particulates (as organic extracts) were evaluated by in vivo tumorigenicity bioassays involving skin initiation and skin carcinogenicity in SENCAR mice and by the in vitro bioassays that proved suitable for this analysis: Ames Salmonella microsome bioassay, L5178Y mouse lymphoma cell mutagenesis bioassay, and sister chromatid exchange bioassay in Chinese hamster ovary cells. The relative potencies of the coke oven, roofing tar, and cigarette smoke emissions, as determined by the mouse skin initiation assay, were within a factor of 2 of those determined using the epidemiologic data. The relative potencies, from the in vitro bioassays as compared to the human data, were similar for coke oven and roofing tar, but for the cigarette smoke condensate the in vitro tests predicted a higher relative potency. The mouse skin initiation bioassay was used to determine the unit lung cancer risk for the most potent of the diesel emissions. Based on comparisons with coke oven, roofing tar, and cigarette smoke, the unit cancer risk averaged 4.4 × 10−4. The unit lung cancer risks for the other, less potent motor‐vehicle emissions were determined from their comparative potencies relative to the most potent diesel using three in vitro bioassays. There was a high correlation between the in vitro and in vivo bioassays in their responses to the engine exhaust particulate extracts. The unit lung cancer risk per μg particulates per m3 for the automotive diesel and gasoline exhaust particulates ranged from 0.20 × 10−4 to 0.60 × 10−4; that for the heavy‐duty diesel engine was 0.02 × 10−4. These unit risks provide the basis for a future assessment of human lung cancer risks when combined with human population exposure to automotive emissions.

A two-stage dose response model is proposed for use in cancer risk assessment. The model assumes that transformation probabilities and cellular dynamics are exposure- and time-dependent.

Although procedures for assessing the carcinogenic risks associated with exposure to individual chemicals are relatively well developed, risk assessment methods for mixtures of chemicals are still in the developmental stage. In this paper, we examine the difficulties in assessing the risks of exposure to complex mixtures, with special reference to the potential for synergistic effects among the components of the mixture. Statistical models for describing the joint action of multiple exposures are reviewed, and their implications for low-dose risk assessment are examined. The potential use of pharmacokinetic models to describe the metabolism of mixtures is also considered. Application of these results in regulating mixtures of carcinogenic substances is illustrated using examples involving multiple contaminants in drinking water and polycyclic aromatic hydrocarbons produced from combustion sources.

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