Factors affecting the quantitative uncertainty of the estimated short-term intake. Part II—Practical examples

ABSTRACT

The effects of the spread of residue concentrations in the samples derived from the selected supervised trials and the number of trials were studied on the magnitude and uncertainty of the short-term dietary intakes calculated with the proposed new procedure (IESTI_p) and that one used currently by the FAO (Food and Agriculture Organization) and WHO (World Health Organization) Joint meeting on Pesticide Residues (JMPR) (IESTI_c). The residue data of 10 pesticides were obtained from supervised trials conducted on apples and pears. The methods described in Part I were used for the calculations of the uncertainty. The results indicate that the ratio of IESTI_P to IESTI_c (φ_IESTI) is directly proportional to the ratio of the estimated maximum residue level (MRL), recommended by the JMPR; to the highest residue (HR) observed in supervised trials, and it may have a wide range depending on the particular conditions. The φ_IESTI becomes greater with the increase of the difference between the mrl or maximum residue limit (MRL, established by the Codex Alimentarius Commission, CAC) and HR, and becomes smaller if the difference between the large portion (LP) and unit mass (U) decreases. The φ_IESTI ranged between 2 and 5.1 in the 16 cases examined indicating that the IESTI_p calculation method leads to higher intake estimates. The ratio of CV_IESTIp and CV_IESTIc ranged typically between 0.62 and 1.71. It rapidly increased up to 12 trials. For a larger number of trials, the ratio remained practically constant (1.69–1.71). The processing factor (PF) equally affects the MRL and HR values, therefore, it will not practically influence the φ_IESTI. The uncertainty of the estimated median residues depends on the spread and number of values in the residue datasets, which affects the uncertainty of the conversion factor (CF) and subsequently the uncertainty of the estimated IESTI_p. Residue values obtained from minimum nine independent trials are required for the correct calculation of the 95% confidence intervals of the calculated median residues. The uncertainty of the analytical results directly affects the median, HR values and indirectly the calculated mrl and the MRL derived from it. Therefore, it should also be considered for the calculation of the combined uncertainty of the conversion factors. For the correct interpretation of the results of dietary exposure calculations, the upper 95% confidence limit of the short-term intake should also be considered. However, it is not the current practice of regulatory agencies or JMPR.     

Lichen microalgae are sensitive to environmental concentrations of atrazine

The identification of new organisms for environmental toxicology bioassays is currently a priority, since these tools are strongly limited by the ecological relevance of taxa used to study global change. Lichens are sensitive bioindicators of air quality and their microalgae are an untapped source for new low-cost miniaturized bioassays with ecological importance. In order to increase the availability of a wider range of taxa for bioassays, the sensitivity of two symbiotic lichen microalgae, Asterochloris erici and Trebouxia sp. TR9, to atrazine was evaluated. To achieve this goal, axenic cultures of these phycobionts in suspension were exposed to a range of environmental concentrations of the herbicide atrazine, a common water pollutant. Optical density and chlorophyll autofluorescence were used as endpoints of ecotoxicity and ecophysiology on cell suspensions. Results show that lichen microalgae show high sensitivity to very low doses of atrazine, being higher in Asterochloris erici than in Trebouxia sp. TR9. We conclude that environmental concentrations of atrazine could modify population dynamics probably through a shift in reproduction strategies of these organisms. This seminal work is a breakthrough in the use of lichen microalgae in the assessment of micropollution effects on biodiversity.     

Malathion dermal permeability in relation to dermal load: Assessment by physiologically based pharmacokinetic modeling of in vivo human data

Estimates of dermal permeability (K_p), obtained by fitting an updated human PBPK model for malathion to previously reported data on excreted urinary metabolites after 29 volunteers were dermally exposed to measured values of [¹⁴C]malathion dermal load (L), were used to examine the empirical relationship between K_p and L. The PBPK model was adapted from previously reported human biokinetic and PBPK models for malathion, fit to previously reported urinary excretion data after oral [¹⁴C]malathion intake by volunteers, and then augmented to incorporate a standard K_p approach to modeling dermal-uptake kinetics. Good to excellent PBPK-model fits were obtained to all of 29 sets of cumulative urinary metabolite-excretion data (ave. [±1 SD] R² = 0.953 [±0.064]). Contrary to the assumption that K_p and L are independent typically applied for dermally administered liquids or solutions, the 29 PBPK-based estimates of K_p obtained for malathion exhibit a strong positive association with the 2/3rds power of L (log-log Pearson correlation = 0.925, p = ～0). Possible explanations of this observation involving physico-chemical characteristics and/or in vivo cutaneous effects of malathion are discussed. The PBPK model presented, and our observation that K_p estimates obtained by fitting this model to human experimental urinary-excretion data correlate well with L^2/3, allow more realistic assessments of absorbed and metabolized dose during or after a variety of scenarios involving actual or potential dermal or multi-route malathion exposures, including for pesticide workers or farmers who apply malathion to crops.     

Assessment of age-dependent radiation dose and toxicity risk due to intake of uranium through the ingestion of groundwater from Northern Rajasthan,India

Uranium traces were measured by laser fluorimeter in groundwater samples collected from four districts of Rajasthan state in India. The average values of uranium concentration in groundwater in Sri Ganganagar, Hanumangarh, Churu, and Sikar districts were determined to be: 57, 50, 40, and 21 µg L^?1, respectively. These recorded values were compared with the maximum contamination levels recommended for drinking water by various health and environmental protection agencies. The associated age-dependent radiation dose is estimated by taking the prescribed water intake values of different age groups. The average cancer mortality and morbidity risks are calculated to be 5.6 × 10^?5 and 8.8 × 10^?5 respectively, indicate that the probability of carcinogenic risks is negligible. About half (49%) of the analyzed samples showed hazard quotient > 1.0, indicating significant risk due to chemical toxicity of uranium.     

Beta-normal distribution in dose–response modeling and risk assessment for quantitative responses

To establish allowable daily intakes for humans from animal bioassay experiments, benchmark doses corresponding to low levels of risk have been proposed to replace the no-observed-adverse-effect level for non-cancer endpoints. When the experimental outcomes are quantal, each animal can be classified with or without the disease. The proportion of affected animals is observed as a function of dose and calculation of the benchmark dose is relatively simple. For quantitative responses, on the other hand, one method is to convert the continuous data to quantal data and proceed with benchmark dose estimation. Another method which has found more popularity (Crump, Risk Anal 15:79–89; 1995) is to fit an appropriate dose–response model to the continuous data, and directly estimate the risk and benchmark doses. The normal distribution has often been used in the past as a dose–response model. However, for non-symmetric data, the normal distribution can lead to erroneous results. Here, we propose the use of the class of beta-normal distribution and demonstrate its application in risk assessment for quantitative responses. The most important feature of this class of distributions is its generality, encompassing a wide range of distributional shapes including the normal distribution as a special case. The properties of the model are briefly discussed and risk estimates are derived based on the asymptotic properties of the maximum likelihood estimates. An example is used for illustration.

Indoor radon levels in Greek schools

Radon and gamma dose rate measurements were performed in 512 schools in 8 of the 13 regions of Greece. The distribution of radon concentration was well described by a lognormal distribution. Most (86%) of the radon concentrations were between 60 and 250 Bq m⁻³ with a most probable value of 135 Bq m⁻³. The arithmetic and geometric means of the radon concentration are 149 Bq m⁻³ and 126 Bq m⁻³ respectively. The maximum measured radon gas concentration was 958 Bq m⁻³. As expected, no correlation between radon gas concentration and indoor gamma dose rate was observed. However, if only mean values for each region are considered, a linear correlation between radon gas concentration and gamma dose rate is apparent. Despite the fact that the results of radon concentration in schools cannot be applied directly for the estimation of radon concentration in homes, the results of the present survey indicate that it is desirable to perform an extended survey of indoor radon in homes for at least one region in Northern Greece.     

Doses of external exposure in Jordan house due to gamma-emitting natural radionuclides in building materials

The use of building materials containing naturally occurring radionuclides as ⁴⁰K, ²³²Th, and ²³⁸U and their progeny results in external exposures of the residents of such buildings. In the present study, indoor dose rates for a typical Jordan concrete room are calculated using Monte Carlo method. Uniform chemical composition of the walls, floor and ceiling as well as uniform mass concentrations of the radionuclides in walls, floor and ceiling are assumed.Using activity concentrations of natural radionuclides typical for the Jordan houses and assuming them to be in secular equilibrium with their progeny, the maximum annual effective doses are estimated to be 0.16, 0.12 and 0.22 mSv a⁻¹ for ⁴⁰K, ²³²Th- and ²³⁸U-series, respectively. In a total, the maximum annual effective indoor dose due to external γ-radiation is 0.50 mSv a⁻¹. Additionally, organ dose coefficients are calculated for all organs considered in ICRP Publication 74. Breast, skin and eye lenses have the maximum equivalent dose rate values due to indoor exposures caused by the natural radionuclides, while equivalent dose rates for uterus, colon (LLI) and small intestine are found to be the smallest. More specifically, organ dose rates (nSv a⁻¹ per Bq kg⁻¹) vary from 0.044 to 0.060 for ⁴⁰K, from 0.44 to 0.60 for radionuclides from ²³⁸U-series and from 0.60 to 0.81 for radionuclides from ²³²Th-series.The obtained organ and effective dose conversion coefficients can be conveniently used in practical dose assessment tasks for the rooms of similar geometry and varying activity concentrations and local-specific occupancy factors.     

Radiological risk assessment and biosphere modelling for radioactive waste disposal in Switzerland

Long-term safety assessments for geological disposal of radioactive waste in Switzerland involve the demonstration that the annual radiation dose to humans due to the potential release of radionuclides from the waste repository into the biosphere will not exceed the regulatory limit of 0.1 mSv. Here, we describe the simple but robust approach used by Nagra (Swiss National Cooperative for the Disposal of Radioactive Waste) to quantify the dose to humans as a result to time-dependent release of radionuclides from the geosphere into the biosphere. The model calculates the concentrations of radionuclides in different terrestrial and aquatic compartments of the surface environment. The fluxes of water and solids within the environment are the drivers for the exchange of radionuclides between these compartments. The calculated radionuclide concentrations in the biosphere are then used to estimate the radiation doses to humans due to various exposure paths (e.g. ingestion of radionuclides via drinking water and food, inhalation of radionuclides, external irradiation from radionuclides in soils). In this paper we also discuss recent new achievements and planned future work.     

Long-term investigation of anthropogenic and naturally occurring radionuclides at reference sites in western Sweden

In case of an accidental release of radioactive substances into the environment, it is important to quickly and reliably estimate the radiation dose received by people in the affected area, and to determine the extent of the contamination. Measurements of the extent of the release and the subsequent contamination can be facilitated if there are predetermined reference sampling sites with known background radiation and inventory of radionuclides. Since 1996, 34 reference sites for soil sampling, field gamma, and intensimeter measurements have been established in western Sweden. Time series data for dose rates and radioisotope inventory have been collected at these sites, allowing for the investigation of changes in these parameters over time. The mass activity densities for the uranium and thorium series elements varied approximately between 10 and 50 Bq/kg and between 10 and 40 Bq/kg, respectively. The mass activity density of ⁴⁰K was approximately in the range 300–800 Bq/kg. The radiation exposure due to ¹³⁷Cs was rather small in this area. The dose rates calculated from in situ measurement data showed that the contribution to the total dose rate was almost entirely due to naturally occurring radionuclides. The measured dose rate was about twice as high as the calculated rate, even after subtracting the contribution from cosmic radiation. This may be explained by the fact that intensimeters generally are calibrated to measure the quantity ambient dose equivalent, which should not underestimate the effective dose.