Hormesis: considerations and implications for human health risk assessment

The concept of hormesis as a phenomenon is presented, in the context of its evolving definitions. Predominant types of hormetic effect and potential examples thereof are discussed, focusing on chemicals. The potential for hormesis to affect regulatory approaches and several basic processes used in formulating risk assessment parameters, such as study design, interpretation of dose-response information, and extrapolation of toxicity values, is examined. The potential ramifications for human health risk assessment and risk management are discussed.     

Application of GIS and modelling in health risk assessment for urban road mobility

Transport is an essential sector in modern societies. It connects economic sectors and industries. Next to its contribution to economic development and social interconnection, it also causes adverse impacts on the environment and results in health hazards. Transport is a major source of ground air pollution, especially in urban areas, and therefore contributes to the health problems, such as cardiovascular and respiratory diseases, cancer and physical injuries. This paper presents the results of a health risk assessment that quantifies the mortality and the diseases associated with particulate matter pollution resulting from urban road transport in Haiphong City, Vietnam. The focus is on the integration of modelling and geographic information system approaches in the exposure analysis to increase the accuracy of the assessment and to produce timely and consistent assessment results. The modelling was done to estimate traffic conditions and concentrations of particulate matters based on geo-referenced data. The study shows that health burdens due to particulate matter in Haiphong include 1,200 extra deaths for the situation in 2007. This figure can double by 2020 as the result of the fast economic development the city pursues. In addition, 51,000 extra hospital admissions and more than 850,000 restricted activity days are expected by 2020.     

Ecological risk assessment of pollutant chemicals: extinction risk based on population-level effects

The extinction probability is one of the most useful endpoints that are utilized in conservation biology. A parallel approach is advocated for the ecological risk assessment of chemical pollutants. The presented framework estimates extinction probability induced by pollutant chemicals in order to evaluate ecological hazards of pollution, and is applicable to any biological community (aquatic or terrestrial). The analytical framework, which is based on stochastic population dynamics theory, is briefly explained. The extinction risk estimation is feasible if ecotoxicological data concerning pollutant effects on population growth rate of organisms (the intrinsic rate of natural increase), and if environmental exposure concentration is provided. Tentative risk estimation was made for some agrochemicals and surfactants on zooplankton populations (Daphnia) as target organisms.     

Synthesis of branched para-nonylphenol isomers: occurrence and quantification in two commercial mixtures

Eight tertiary nonanols were synthesized via Grignard reaction and coupled by Friedel–Crafts alkylation with phenol to the corresponding nonylphenols. Six branched para-nonylphenols (NP) were obtained: 4-(3′-methyl-3′-octyl)phenol (33NP), 4-(2′-methyl-2′-octyl)phenol (22NP), 4-(2′,5′-dimethyl-2′-heptyl)phenol (252NP), 4-(2′,5′,5′-trimethyl-2′-hexyl)phenol (2552NP), 4-(2′,4′-dimethyl-2′-heptyl)phenol (242NP) and 4-(4′-ethyl-2′-methyl-2′-hexyl)phenol (4E22NP). Their structures were confirmed by GC–MS and NMR spectroscopy. These six isomers as well as the earlier synthesized 4-(3′,5′-dimethyl-3′-heptyl)phenol (353NP), 4-(3′,6′-dimethyl-3′-heptyl)phenol (363NP) and 4-(2′,6′-dimethyl-2′-heptyl)phenol (262NP) were compared with commercial NP mixtures purchased from Acros and Fluka by GC–MS (equipped with a 100 m polysiloxane column). The analyses revealed that all obtained isomers are occurring in different quantities in both commercial NP mixtures.     

Metals and emerging contaminants in groundwater and human health risk assessment

Environmental Science and Pollution Research - Groundwaters are normally consumed without previous treatment and therefore the monitoring of contaminants in order to guarantee its safety is...     

Human health and environmental risk assessment: the need for a more harmonised and integrated approach

Historically the procedures for human risk assessment and for risk assessment have developed separately with different terminologies and separate data bases. The identification that there are many common features and that sharing of certain types of data for risk assessment purposes would be beneficial is a driver towards a better integration of their procedures. Risk assessors are facing increasing challenges from governments, stimulated by public pressure for (i) human and environmental risk assessments of an ever growing number of products and processes, (ii) further restrictions of the use of animal tests and human studies on ethical grounds, (iii) the requirement to demonstrate that the assessments are independent, transparent and of high quality, (iv) reducing resources in particular a diminishing number of individuals with the scientific depth, breadth and independence act as risk assessors, (v) the need to incorporate new sciences continually and new discoveries into the risk assessment process. It is important for society that these challenges are met successfully. This requires changes in both risk assessment procedures and in the infrastructure needed to support them. Risk assessment is a science based process for establishing the likelihood of adverse effects to human health and to the environment from specific chemical, biological and physical agents. In the last few years there has been a renewed effort, by international bodies such as WHO, OECD and the EU, to achieve a more integrated and harmonised approach to risk assessment. Before examining the potential for a more integrated approach to risk assessment it is timely to consider the key factors which have led to the current position.     

Wastewater treatment and public health in Nunavut: a microbial risk assessment framework for the Canadian Arctic

Wastewater management in Canadian Arctic communities is influenced by several geographical factors including climate, remoteness, population size, and local food-harvesting practices. Most communities use trucked collection services and basic treatment systems, which are capable of only low-level pathogen removal. These systems are typically reliant solely on natural environmental processes for treatment and make use of existing lagoons, wetlands, and bays. They are operated in a manner such that partially treated wastewater still containing potentially hazardous microorganisms is released into the terrestrial and aquatic environment at random times. Northern communities rely heavily on their local surroundings as a source of food, drinking water, and recreation, thus creating the possibility of human exposure to wastewater effluent. Human exposure to microbial hazards present in municipal wastewater can lead to acute gastrointestinal illness or more severe disease. Although estimating the actual disease burdens associated with wastewater exposures in Arctic communities is challenging, waterborne- and sanitation-related illness is believed to be comparatively higher than in other parts of Canada. This review offers a conceptual framework and evaluation of current knowledge to enable the first microbial risk assessment of exposure scenarios associated with food-harvesting and recreational activities in Arctic communities, where simplified wastewater systems are being operated.     

Evaluation of heavy metal contaminants in prepared noodles: source allocation and health risk assessment

Environmental Science and Pollution Research - In recent years, special attention has been given to emission research that led to the deposition of toxicants from road traffic. Thus, it is...     

Ambient air concentrations of polychlorinated dibenzo-p-dioxins and dibenzofurans in Ohio: Sources and health risk assessment

PCDD and PCDF were measured in air samples collected in Ohio in 1987. No 2,3,7,8-TCDD was detected in any of the samples with a detection limits of less than 240 fg/m³. Using a chemical mass balance model applied to PCDD/PCDF congener group profiles, major potential sources of these compounds to the atmosphere in Ohio were determined to be municipal solid waste combustion, and sewage sludge combustion. Cancer risk calculations for inhalation of PCDD/PCDF in ambient air in Ohio are approximately 10–6. Given the current knowledge of the health effects of exposure to PCDD/PCDF in air, there is no appreciable risk to public health for the levels of these compounds found in ambient air in Ohio.     

Sediment dioxin levels as the basis for risk assessment and human health criteria

Methods for assessing human health risks and establishing water quality criteria under the Clean Water Act are based on the assumption that fish accumulation of dioxin is correlated with the dissolved phase of the dioxin in the water column by a water-to-fish predictive factor called a bioconcentration factor. However, dioxin does not remain dissolved in the water column to any significant degree, but sorbs to organic matter in the water column and sediment. Under Toxic Substances Control Act regulations, dioxin's hydrophobicity is recognised, and fish dioxin levels are predicted with a solids-to-fish factor. These two different predictive methods can result in extremely variable predictions of fish contaminant levels. A methodology for establishing criteria under the Clean Water Act, which considers fish uptake of sorbed hydrophobic compounds by way of ingestion of contaminated sediment, is offered as an alternative to the methods used today.     

Adsorptive removal of ibuprofen to binary and amine-functionalized UiO-66 in the aquatic environment: synergistic/antagonistic evaluation

Environmental Science and Pollution Research - The removal of ibuprofen (IBP) from the aqueous solution by metal–organic frameworks such as UiO-66, UiO-66-NH2, and a binary MOF...     

A new dose model for assessment of health risk due to contaminants in air

The problem of making quantitative assessments of the risks associated with human exposure to toxic contaminants in the environment is a pressing one. This study demonstrates the capability of a new computational technique involving the use of fuzzy logic and neural networks to produce realistic risk assessments. The systematic analysis of human exposure involves the use of measurements and models, the results of which are sometimes used in regulatory decisions or in the drafting of legislation. Because of limited scientific understanding, however, interpretation of models often involves substantial uncertainty. Extensive measurement programs can be very expensive. The high complexity and inherent heterogeneity of exposure analysis is still a major challenge. The approach to this challenge tested here is to use a new model incorporating sophisticated artificial intelligence algorithms. Exposure assessment often requires that a number of factors be evaluated, including exposure concentrations, intake rates, exposure times, and frequencies. These factors are incorporated into a system that can "learn" the relevant relationships based on a known data set. The results can then be applied to new data sets and thus be applied widely without the need for extensive measurements. In this analysis, an example is developed for human health risk through inhalation exposure to benzene from vehicular emissions in the cities of Auckland and Christchurch, New Zealand. Risk factors considered were inhaled contaminant concentration, age, body weight, and activity patterns of humans. Three major variables affecting the inhaled contaminant concentration were emissions (mainly from motor vehicles), meteorology (wind speed, temperature, and atmospheric stability), and site factors (hilly, flat, etc.). The results are preliminary and used principally to demonstrate the technique, but they are very encouraging.     

Comprehensive estimate of the theoretical maximum daily intake of pesticide residues for chronic dietary risk assessment in Argentina

A chronic dietary risk assessment for pesticide residues was conducted for four age groups of the Argentinian population following the procedure recommended by the WHO. The National Theoretical Maximum Daily Intake (NTMDI) for 308 pesticides was calculated for the first time, using the Maximum Residue Limits (MRLs) from several Argentinean regulations and food consumption data from a comprehensive National Nutrition and Health Survey. The risk was estimated by comparing the TMDI with the Acceptable Daily Intakes (ADI) identified by various sources. Furthermore, for each of the compounds with a TMDI >65% of the ADI, a probabilistic analysis was conducted to quantify the probability of exceeding the ADI. In this study 27, 22, 10, and 6 active ingredients (a.i.) were estimated to exceed the 100% of the ADI for the different population groups: 6–23 month-old children, 2–5 year-old children, pregnant women, and 10–49 year-old women, respectively. Some of these ADI-exceeding compounds (carbofuran, diazinon, dichlorvos, dimethoate, oxydemeton-methyl and methyl bromide) were found in all four of these groups. Milk, apples, potatoes, and tomatoes were the foods that contributed most to the intake of these pesticides. The study is of primary importance for the improvement of risk assessment, regulations, and monitoring activities.     

An atmospheric dispersion model for the environmental impact assessment of thermal power plants in Japan--a method for evaluating topographical effects

An atmospheric dispersion model was developed for the environmental impact assessment of thermal power plants in Japan, and a method for evaluating topographical effects using this model was proposed. The atmospheric dispersion model consists of an airflow model with a turbulence closure model based on the algebraic Reynolds stress model and a Lagrangian particle dispersion model (LPDM). The evaluation of the maximum concentration of air pollutants such as SO2, NOx, and suspended particulate matter is usually considered of primary importance for environmental impact assessment. Three indices were therefore estimated by the atmospheric dispersion model: the ratios (alpha and beta, respectively) of the maximum concentration and the distance of the point of the maximum concentration from the source over topography to the respective values over a flat plane, and the relative concentration distribution [gamma(x)] along the ground surface projection of the plume axis normalized by the maximum concentration over a flat plane. The atmospheric dispersion model was applied to the topography around a power plant with a maximum elevation of more than 1,000 m. The values of alpha and beta evaluated by the atmospheric dispersion model varied between 1 and 3 and between 1 and 0.4, respectively, depending on the topographical features. These results and the calculated distributions of y(x) were highly similar to the results of the wind tunnel experiment. Therefore, when the slope of a hill or mountain is similar to the topography considered in this study, it is possible to evaluate topographical effects on exhaust gas dispersion with reasonable accuracy using the atmospheric dispersion model as well as wind tunnel experiments.     

The current practice of health risk assessment: potential impact on standards for toxic air contaminants

Since the Bhopal incident, the public has placed pressure on regulatory agencies to set community exposure limits for the dozens of chemicals that may be released by manufacturing facilities. More or less objective limits can be established for the vast majority of these chemicals through the use of risk assessment. However, each step of the risk assessment process (i.e., hazard identification, dose-response assessment, exposure assessment, and risk characterization) contains a number of pitfalls that scientists need to avoid to ensure that valid limits are established. For example, in the hazard identification step there has been little discrimination among animal carcinogens with respect to mechanism of action or the epidemiology experience. In the dose-response portion, rarely is the range of "plausible" estimated risks presented. Physiologically based pharmacokinetic (PB-PK) models should be used to understand the difference between the tissue doses and the administered dose, as well as the difference in target tissue concentrations of the toxicant between rodents and humans. Biologically-based models like the Moolgavkar-Knudson-Venzon (MKV) should be developed and used, when appropriate. The exposure assessment step can be significantly improved by using more sensitive and specific sampling and analytical methods, more accurate exposure parameters, and computer models that can account for complex environmental factors. Whenever possible, model predictions of exposure and uptake should be validated by biological monitoring of exposed persons (urine, blood, adipose) or by field measurements of plants, soil, fish, air, or water. In each portion of an assessment, the weight of evidence approach should be used to identify the most defensible value. In the risk characterization, the best estimate of the potential risk as well as the highest plausible risk should be presented. Future assessments would be much improved if quantitative uncertainty analyses were conducted. Procedures are currently available for making future assessments. By correcting some of these shortcomings in how health risk assessments have been conducted, scientists and risk managers should be better able to identify scientifically appropriate ambient air standards and emission limits.     

Multiple exposure pathways and health risk assessment of selenium for children in a coal mining area

Environmental Science and Pollution Research - Selenium (Se) presents a dual role to human body, harmful or beneficial, depending on its concentration. The exposure to this element has been...     

Acute and chronic health risk assessment for inhalation and ingestion exposure in acrylic acid leak accidents

Environmental Science and Pollution Research - We established a hypothetical acrylic acid leak accident scenario, conducted a health risk assessment of local residents, and compared an actual...     

Comparison of the industrial source complex and AERMOD dispersion models: case study for human health risk assessment

Air quality models are typically used to predict the fate and transport of air emissions from industrial sources to comply with federal and state regulatory requirements and environmental standards, as well as to determine pollution control requirements. For many years, the U.S. Environmental Protection Agency (EPA) widely used the Industrial Source Complex (ISC) model because of its broad applicability to multiple source types. Recently, EPA adopted a new rule that replaces ISC with AERMOD, a state-of-the-practice air dispersion model, in many air quality impact assessments. This study compared the two models as well as their enhanced versions that incorporate the Plume Rise Model Enhancements (PRIME) algorithm. PRIME takes into account the effects of building downwash on plume dispersion. The comparison used actual point, area, and volume sources located on two separate facilities in conjunction with site-specific terrain and meteorological data. The modeled maximum total period average ground-level air concentrations were used to calculate potential health effects for human receptors. The results show that the switch from ISC to AERMOD and the incorporation of the PRIME algorithm tend to generate lower concentration estimates at the point of maximum ground-level concentration. However, the magnitude of difference varies from insignificant to significant depending on the types of the sources and the site-specific conditions. The differences in human health effects, predicted using results from the two models, mirror the concentrations predicted by the models.