On the Determination of Odor Thresholds in Air Pollution Control—An Experimental Field Study on Flue Gases from Sulfate Cellulose Plants

From the hygienic point of view, not only the health hazards caused by air pollutants but also the odor from emitted flue gases should be reduced to a minimum. An effective control of the risk of odor at ground level presupposes knowledge of the source concentration of the odoriferous gas as well as its odor threshold. This threshold has to be estimated empirically, as the flue gases often contain a complex mixture of different odoriferous substances, the odor thresholds of which are in most cases unknown. For this purpose a method has been developed for estimating the odor thresholds of flue gases emitted, from different industrial processes. The method, afield method, is based on an exposure procedure, a number of subjects compare different concentrations of the flue gas with samples of fresh air and decide at what concentration the flue gas is no longer noticeable. The gas samples used are neither compressed, nor absorbed or heated before the exposure test. The method has been used in two studies on gases from Swedish sulfate cellulose plants. In order to estimate the effect on the odor threshold of different deodorizing measures, gas samples were taken not only from the stack but also from different phases in the production process. The results and a brief discussion on the practical applications of the method are given.     

An Atmospheric Dispersion Model for the Environmental Impact Assessment of Thermal Power Plants in Japan—A Method for Evaluating Topographical Effects

Abstract

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, NO_x, 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 (α and β, 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 [γ(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 1000 m. The values of α and β 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 γ(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.     

An attempt to assess the relevance of flood events—biomarker response of rainbow trout exposed to resuspended natural sediments in an annular flume

There is a consensus within the scientific community that sediments act as a long-term sink for a variety of organic and inorganic pollutants, which, however, can re-enter the water column upon resuspension of deposited material under certain hydraulic conditions such as flood events. Within the implementation of the European Water Framework Directive, it is important to understand the potential short- and long-term impact of suspended particulate matter (SPM)-associated contaminants on aquatic organisms as well as the related uptake mechanisms for a sound risk assessment. To elucidate the effects of sediment-bound organic pollutants, such as polycyclic aromatic hydrocarbons (PAHs), rainbow trout (Oncorhynchus mykiss) were exposed to three resuspended natural sediments with different contamination levels. Physicochemical parameters including dissolved oxygen concentration, pH and temperature, total PAH concentration in sediments and SPM as well as different biomarkers of exposure in fish (7-ethoxyresorufin O-deethylase activity, biliary PAH metabolites, micronuclei, and lipid peroxidation) were measured following seven days of exposure within an annular flume, a device to assess erosion and deposition processes of cohesive sediment. Concentrations of PAHs in SPM remained constant and represented the different contamination levels in the un-suspended sediments. Significant differences in bile metabolite concentrations as well as in 7-ethoxyresorufin O-deethylase induction compared to control experiments (untreated animals and animals that were exposed in the annular flume without sediment) were observed for all exposure scenarios. The ratio between 1-hydroxypyrene in bile from fish exposed to the three different contamination levels was 1.0:3.6:10.7 and correlated well with (1) the ratio of pyrene concentrations in corresponding sediments which was 1.0:3.1:12.7 and (2) with the ratio of particle-bound pyrene in SPM which was 1.0:2.7:11.7. In contrast, hepatic lipid peroxidation and micronuclei formation represented the different contamination levels less conclusive. The results of this study clearly demonstrate that firmly bound PAH from aged sediments can become bioaccessible upon resuspension under flood-like conditions and are readily absorbed by aquatic organisms such as rainbow trout. Associated short-term effects were clearly documented and possible adverse long-term impacts due to genotoxicity are likely to follow.     

SimPhy: a simulation game to lessen the impact of phytosanitaries on health and the environment—the case of Merja Zerga in Morocco

Diffuse phytosanitary pollution is a complex phenomenon to manage. Reducing this type of pollution is one of today’s key socio-economic and environmental challenges. At the regional level, few approaches enable the actors concerned to implement agricultural management strategies to reduce the use and impact of phytosanitary products. Our research problem focused on the consequences of intensive agriculture and, in particular, how to evaluate the impact of phytosanitary products on human health and the environment. In this article, we present the SimPhy simulation game which places the actors from a given region directly into a situation in which they manage farms whilst under pressure to reduce phytosanitaries (quantity and toxicity). The application focused on the Merja Zerga catchment area in Morocco. The region is dominated by intensive agriculture which is located upstream from a Ramsar-classified wetland area. The SimPhy simulation game is based on a decision support system-type tool. It allows us to anticipate the impact of regulations on farming systems. It also enables us to analyse the consequences of the actors’ strategies on farm economies, human health and the quality of ecosystems. Initial results from the SimPhy simulation game enabled the technicians from Agricultural Development Center (CDA) themselves to learn about managing agricultural production systems in a dynamic and interactive fashion. With the simulation game, it was possible to learn about the farmer's ability to adapt to new regulatory constraints, and the involved consequences for toxicity risks for human health and the environment.     

Correction to: Study on habitat suitability of overwintering cranes based on landscape pattern change—a case study of typical lake wetlands in the middle and lower reaches of the Yangtze River

Environmental Science and Pollution Research - The correct corresponding Author of this paper is Bin Dong.     

An Air Quality Data Analysis System for Interrelating Effects,Standards, and Needed Source Reductions: Part 13— Applying the EPA Proposed Guidelines for Carcinogen Risk Assessment to a Set of Asbestos Lung Cancer Mortality Data

Abstract

The Clean Air Act Amendments of 1990 (CAAA-90) list 189 hazardous air pollutants (HAPs) for which “safe” ambient concentrations are to be determined. The primary purpose of this paper is to develop two mathematical models, lognormal and logarithmic, that effectively express excess lung cancer mortality as a function of asbestos concentration for an example set of data and also to suggest using these two models for additional HAPs. The secondary purpose of this paper is to calculate a “safe” asbestos concentration by first assuming a default linear extrapolation (to one excess death per million people, as specified for carcinogenic HAPs). The resulting “safe” concentration is an impossible-to-achieve 1/1000 of present background asbestos concentrations. A letter to the editor and a response in this Journal issue use additional asbestos data that suggest that the “safe” concentration should be about 730 times higher than first calculated here and that a default nonlinear extrapolation should be used instead, with the “safe” concentration proportional to the desired mortality level raised to the 0.39 power. These results suggest that the most important problem in setting a “safe” concentration for each carcinogenic HAP is to determine the correct nonlinear extrapolation to use for each HAP.     

An Empirical, Quantitative Approach to Predict the Reactivity of Some Substituted Aromatic Compounds Towards Reactive Radical Species (Cl2-·, Br2-·, ·NO2, SO3-·, SO4-·) in Aqueous Solution (3 pp)

The Hammett approach, applied to the reaction of various classes of aromatic compounds with the radicals Cl2-*, Br2-*, *NO2, SO3-*, and SO4-* yielded good predictive models, supported by high values of the correlation coefficient r2 in the case of phenols with Cl2-* and of phenolates with *NO2 and SO3-*. Lower but statistically significant correlation coefficients could be obtained for benzoates with Cl2-*, phenolates with Br2-*, and benzoates and anisoles with SO4-*.