Laypeople's perceptions of health and safety risks have been widely studied, but only a few studies have addressed perceptions of ecological hazards. We assembled a list of 39 attributes of ecological hazards from the literatures on comparative risk assessment, ecological health, environmental conservation and management, environmental psychology, and risk perception. In Study 1, 125 laypeople evaluated 83 hazards on subsets of this attribute set. Factor analysis of attribute ratings (averaged over participants) revealed six oblique factors: ecological impacts, human impacts, human benefits, aesthetic impacts, scientific understanding, and controllability. These factors predicted mean judgments of overall riskiness, ecological riskiness, acceptability, and regulatory strictness. In Study 2, 30 laypeople each evaluated 34 hazards on 17 attributes and 3 dependent variables. Aggregate-level factor analysis of these data replicated the appropriate portion of the factor solution and yielded similar regression results. Parallel analyses at the individual-participant level yielded factors that explained less variance in judgments of overall riskiness, ecological riskiness, and acceptability. However, the decrease in explanatory power was much less than is often reported for disaggregate-level analyses of psychometric data. This discrepancy illustrates the importance of distinguishing between the level of analysis (aggregate versus disaggregate) and the focus of analysis (distinctions among hazards versus distinctions among participants). In a hybrid analysis, aggregate-level factor scores predicted individual participants' riskiness judgments reasonably well. Psychometric studies such as these provide a sound empirical basis for selecting attributes of ecological hazards for use in comparative risk assessment.
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http://dx.doi.org/10.1111/j.1539-6924.2005.00599.x | DOI Listing |
J Hazard Mater
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State Key Laboratory for Biology of Plant Disease and Insect Pests, Institute of Plant Protection, Chinese Academy of Agricultural Sciences, Beijing 100193, China. Electronic address:
The transgenerational impacts of pesticide mixture on Daphnia magna (D. magna) following long-term exposure, particularly regarding transcriptomic effects, remain poorly understood. We analyzed 470 irrigation water samples from various Chinese provinces.
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Jiangsu Key Laboratory of E-waste Recycling, School of Resources and Environmental Engineering, Jiangsu University of Technology, Changzhou 213001, PR China. Electronic address:
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Key Laboratory of Subsurface Hydrology and Ecological Effect in Arid Area of Ministry of Education, Chang'an University, No. 126 Yanta Road, Xi'an, Shaanxi 710054, China; School of Water and Environment, Chang'an University, No.126 Yanta Road, Xi'an, Shaanxi 710054, China; Key Laboratory of Eco-hydrology and Water Security in Arid and Semi-arid Regions of Ministry of Water Resources, Chang'an University, No. 126 Yanta Road, Xi'an 710054, Shaanxi, China E-mail:
Fluoride and nitrogen contamination is a global concern and has been a serious problem in agricultural areas. This study aims to identify the source of fluoride and nitrogen in the groundwater and assess groundwater quality and human health risks in the Guanzhong Plain, northwest China. The results showed that the concentrations were 0.
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Department of Food Technology and Nutrition, School of Agriculture, Lovely Professional University, Phagwara, 144411, India.
The fabricating of extremely effective, economical, ecologically safe, and reusable nanoparticle (NP) catalysts for the removal of water pollution is urgently needed. This study, spectroscopically optimizes the process parameters for the biogenic synthesis of AgNP catalysts using Cledrdendrum infortunatum leaf extract. The optimization of several synthesis parameters was systematically studied using UV-Vis spectroscopy to identify the ideal conditions for AgNPs formation.
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State Key Laboratory of Hydraulics and Mountain River Engineering, College of Water Resource and Hydropower, Sichuan University, Chengdu, 610065, China.
Addressing the need to harmonize environment conservation and sustainable economic development within the Yellow River Basin (YRB) requires a profound comprehension of the spatiotemporal dynamics of urban ecosystem resilience. This study developed an index system utilizing the resistance-adaptability-recovery framework to measure these dynamics. By applying the advanced multi-attribute boundary area comparison method and a spatial autocorrelation model, we investigated the spatiotemporal variations and spatial correlation patterns of urban ecological resilience across the YRB.
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