Environmental monitoring of alcohol sulfates and alcohol ethoxysulfates in marine sediments

The study describes the environmental monitoring of anionic surfactants―alcohol sulfates (AS) and alcohol ethoxysulfates (AES)—in marine sediments. Concentration values were obtained after pressurised liquid extraction (PLE) and liquid chromatography–tandem mass spectrometry analysis (LC–MS/MS). Samples were collected from a range of wastewater discharge points along the coast of the provinces of Huelva, Málaga, Granada and Almería. Urban, agricultural and industrial wastewaters are discharged at the selected 38 sampling sites. Principal component analysis was carried out in order to evaluate the distribution and behaviour of these compounds in these coastal environments. Evaluation of the data revealed that the behaviour and sources of AS and AES in marine sediments are different, and that the distribution of AES depends on the length of the alkyl chain, while the number of ethoxylated units is not relevant. Additionally, the 38 sampling sites can be grouped into only two types of outfalls according to their AS distribution. The concentration of compounds in sediment samples ranged from 7.52 to 13.50 mg kg^?1 for AS, from 3.04 to 10.68 mg kg^?1 for AES–C₁₂E_x and from 3.83 to 11.56 mg kg^?1 for AES–C₁₄E_x.     

基于GIS的滑坡灾害风险空间预测

滑坡灾害风险评价是一个包含有滑坡危险性评价和承灾体易损性评价的体系,对滑坡危险性进行了空间预测与区划,并开展了区域承灾体易损性的区划与评价。结合风险评价的基本要求,进行了研究区滑坡灾害的风险区划,将其划分为极高、高、中、低与极低风险区。针对研究区经济发展水平及政府防灾力度,提出了适合研究区的可接受风险标准与管理对策。     

Using deep-belief networks to understand propensity for livelihood change in a rural coastal community to further conservation

Overharvesting of terrestrial and marine resources may be alleviated by encouraging an alternative configuration of livelihoods, particularly in rural communities in developing countries. Typical occupations in such areas include fishing and farming, and rural households often switch livelihood activities to suit climate and economic conditions. We used a machine-learning tool, deep-belief networks (DBN), and data from surveys of a rural Philippine coastal community to examine household desire to change livelihood. This desire is affected by a variety of factors, such as income, family needs, and feelings of work satisfaction, that are interrelated in complex ways. In farming households, livelihood changes often occur to diversify resources, increase income, and lessen economic risk. The DBN, given its multilayer perceptron structure, has a capacity to model nonlinear relationships among factors while providing an acceptable degree of accuracy. Relative to a set of 34 features (e.g., education, boat ownership, and work satisfaction), we examined the binary response variables desire to change work or not to change work. The best network had a test set accuracy of 97.5%. Among the features, 7 significantly affected desire to shift work: ethnicity, work satisfaction, number of persons in a household in ill health, number of fighting cocks owned, fishing engagement, buy-and-sell revenue, and educational level. A cross-correlation matrix of these 7 features indicated households less inclined to change work were those engaged in fishing and retail buying and selling. For fishing, provision of economic and other incentives should be considered to encourage changing from this occupation to allow recovery of fishery resources.     

Distribution and correlation of radon and uranium and associated hydrogeochemical processes in alluvial aquifers of northwest India

Environmental Science and Pollution Research - The spatial and vertical distributions of radon and uranium are evaluated in relation to the hydrogeology, geomorphology, and hydrochemistry of...