In the natural environment, living organisms are constantly exposed to multiple chemicals. However, in the current framework of chemical management, biological effects are examined in laboratory toxicity tests with individual chemical substances. Therefore, several models such as concentration addition and independent action have been proposed and studied to estimate the combined effects caused by the exposure of multiple chemicals based on the toxicity of individual chemicals. The general applicability of these models is uncertain and there is currently no universal method to accurately predict combined effects of multiple substances. In other words, the model is poor at estimating the biological impacts when an organism is co-exposed with two or more chemicals since synergistic or antagonistic effects complicate the results. Although there is still much work to be done in understanding combined effects, this review highlights common misconceptions in research and introduce the experimental designs for evaluating combined effects.

Recent development of theoretical models for mixture effect of chemicals is reviewed in terms of the toxic unit summation, the component-based approach and the mixture-based approach. The component-based approach, which is based on the absence of interaction effects among components in a mixture, has two reference models, the independent action model and the concentration addition model. The latter model is regarded as the most efficient mixture model when implementing it into the regulatory framework, because it assumes that component chemicals have similar mode of action and then the adverse effects are cumulative among components, whereby producing more protecting estimates for mixture effects. By extending the concept of component addition, the generalized concentration addition approach is proposed as one of the least data-demanding models of the mixture-based approach.

This paper describes the method and application of cumulative ecological risk assessment of multiple pesticides. Species sensitivity distribution (SSD) is a statistical distribution of difference in sensitivity to the toxicant among species. By utilizing SSD to compute the “potentially affected fraction of species” (PAF), a metric for assessing the impact on biodiversity, and applying mixture toxicity models, it is possible to calculate the cumulative risk posed by multiple pesticides. The paper also details the development a risk assessment tool based on Microsoft Excel, NIAES-CERAP, to facilitate the calculation process. In addition, the validation of risk assessment using laboratory toxicity testing and field ecological surveys was introduced, as well as the application of NIAES-CERAP in constructing a national ecological risk map in Japan and evaluating the effectiveness of eco-friendly agriculture.

In the evaluation of soil contamination, the need for comprehensive hazard assessment by applying ecotoxicity tests has been recognized. The evaluation method of soil contamination by the terrestrial plant growth test was outlined. The terrestrial biotic ligand model used to predict the toxicity to the soil ecosystem was introduced in this manuscript, in addition to the introduction of soil contamination by conventional instrumental analysis. By combining a model that predicts the behavior of contaminants such as heavy metals in soil layers and groundwater with a model that can express combined toxicity caused by heavy metal mixture, it is expected that it will be possible to predict the state of the environment and the hazards to the ecosystem.

Metals are ubiquitous, and environment is a cocktail of them. There has long been concern that even if the toxicity of individual metals is low, a risk by the sum of all toxic effect by the individual metals cannot be neglected. A very large number of studies for the toxic effect of metal mixtures have been conducted. Not only in metal mixture, but also in chemical mixture in general, the first task to understand the mixture effect is to test that the mixture effect can be predicted by Loewe’s additivity. The test is made by toxicity test with concentration of two and more chemicals satisfying a prediction model by Loewe. The toxicities of individual metals are well predicted by the Biotic Ligand Model (BLM). A brief description of the model is presented in this article at first. The model is then extended for the prediction of the toxicity of metal mixture. By analyzing the extended model, it is revealed that the standard concentration setting satisfying the Loewe’s additivity is not suitable to detect the additivity. The result implies that we do not know enough about the toxic effect of metal mixtures because almost all concentrations in the previous tests were set to satisfy Loewe’s additivity.

Due to the recent increase in the number of low production volume chemicals and the need for mixture effects have become proposed by many researchers. The history and recent trend of mixture studies in the environmental toxicology is extensively reviewed for both component-based and whole mixture approaches. The challenges/perspectives in the implementation of mixture assessment/management into the current chemical regulation in Japan are also discussed.

Whole effluent toxicity (WET) tests have been used in the effluent management system in several foreign countries to evaluate the aggregate toxic effect of a mixture of pollutants in the effluents. Moreover, toxicity identification evaluations (TIEs) were developed to identify causative toxicants in the effluents. This paper explains the details and considerations of the TIE methods, with case studies being conducted as a WET pilot survey by the Ministry of the Environment, Japan. The correlation approach using toxic units based on an additive model is used to confirm the toxicants, but it is necessary to consider the matrix effect of the effluent and the synergic or offset effect among the toxicants. In the pilot survey, modified TIE procedures were developed to approximately categorize candidate toxicants by classes, metals, salinity, residual chlorine, ammonia, or nonpolar organic chemicals. Compared with the metal case study that identified and confirmed nickel as a toxicant in the metal plating factory, the identification of organic toxicants using the TIE methods still has a limitation because of the presence of thousands of organic chemicals, including unknown chemicals produced unintentionally, in the industrial effluents. Effect-directed analysis (EDA) is a focused method for identifying candidate organic toxicants using sample fractionation and comprehensive chemical analysis. This paper also introduces the differences between TIE and EDA and the technical issues of EDA.

A method for evaluating the combined effects of chemicals is the whole-mixture approach, which evaluates a water sample containing a mixture of several chemicals. In this approach, chemical analysis is important to identify the cause of toxicity. However, among the numerous chemicals present in wastewater and river water, it is difficult to identify the toxic chemicals using conventional chemical analysis methods. Therefore, a comprehensive analytical method capable of detecting many chemicals is required. This study focused on target screening methods for organic contaminants, especially in chemical analysis; introduced a gas chromatograph-mass spectrometer (GC-MS) database that could identify nearly 1000 organic compounds; and developed a rapid screening method. Furthermore, the combined effects on water samples using the target screening methods and biological response tests were evaluated.

Today, effluents from municipal wastewater treatment plants are utilized as an alternative water source in some cities of US, Asia, Europe, and Africa. However, wastewater effluents are also recognized as a source of numerous chemicals such as pharmaceuticals, personal care products, antibiotics, and pesticides. In addition, the wastewater effluent matrix is assumed to be more chemically complicated than pure pharmaceutical mixtures since it contains not only anthropogenic micropollutants but also soluble microbial products (SMP), metabolites/transformation products produced during treatment processes, and natural organic matters (NOM) derived from tap water. This review first overviews the complexity of wastewater as a chemical mixture system, and then, introduce previous findings on the biological impacts of wastewater samples, particularly those revealed by the application of toxicogenomic tools to the environmental and mixture samples. Finally, recent challenges to characterize the major origin of effluent-derived toxicity were presented. This review highlights the importance of prioritizing the pollutants for efficient control and monitoring of water quality under the limited human and financial resources.

Pharmaceuticals are produced and used with physiological effects on human and wildlife, and active pharmaceutical ingredients and their metabolites are discharged into the environment. In the environment, active pharmaceutical ingredients, with expected physiological effects, may coexist along with various substances and their environmental reaction products. Even if the concentrations of these substances individually do not cause load, there is a concern that their combined action may affect wildlife and indirectly human health. In particular, some active pharmaceutical ingredients have a common mechanism of action and a common site of action, and it is possible that combined actions may be existed. There are active pharmaceutical ingredients with a common structure involved in the mechanism of action and site of action, that can be used for group classification. In this paper, although the number of reports is limited, the outlines of combined actions of active pharmaceutical ingredients have been reviewed. The mechanism of combined actions is mainly able to be explained by additive actions, but there are also results that are thought to be synergistic actions, competitive antagonistic actions, and intermediate types of actions. It is necessary to understand the interaction among active pharmaceutical ingredients and to control to minimize the burden on human health and the environment.