Is ionizing radiation effective in removing pharmaceuticals from wastewater?

Environmental Science and Pollution Research - Wastewater and effluent discharges are the main causes of receiving water body pollution and important challenges in water quality management. Among...     

山东省农田土壤中拟除虫菊酯类农药污染特征与风险评价

在山东省范围内采集农田表层土壤样品91个,采用气相色谱法分析了7种拟除虫菊酯类农药(SPs)的含量和组成,分析了其分布特征,比较了大田土壤和大棚土壤中该类农药含量的差异,并评价了其生态风险.结果表明,7种拟除虫菊酯类农药总含量(∑_7SPs)范围在0.01—88.51μg·kg~(-1)之间,均值为5.65μg·kg~(-1).与国内其他地区农田土壤相比,山东省农田土壤中拟除虫菊酯含量处于中等偏低水平.山东省各地区的拟除虫菊酯含量存在差异,但组成相近,均是高效氯氟氰菊酯、联苯菊酯和氯氰菊酯的比例较高.部分地区大棚土壤中的含量高于大田土壤.风险评价结果表明,山东省农田土壤个别采样点中甲氰菊酯和高效氯氟氰菊酯具有生态风险,三分之一的采样点存在潜在生态风险,其余采样点不存在生态风险.     

The tree species matters: Biodiversity and ecosystem service implications of replacing Scots pine production stands with Norway spruce

Ambio - The choice of tree species used in production forests matters for biodiversity and ecosystem services. In Sweden, damage to young production forests by large browsing herbivores is helping...     

Correction to: Keeping pace with forestry: Multi-scale conservation in a changing production forest matrix

Ambio - In the original published article, the sentence “Nevertheless, semi-natural forest remnants continue to be harvested and fragmented (Svensson et al. 2018; Jonsson et al. 2019), and...     

磺胺类制药废水中苯系物的快速同步检测

磺胺类制药废水是一类难降解有机废水,其中含有苯磺酰胺、苯磺酸、苯酚等苯系物,对这些物质的快速检测十分必要,针对这3种物质建立了基于高效液相色谱的快速同步检测方法。采用C18柱为分离柱,比较了乙腈/水、甲醇/水和甲醇/缓冲盐3种流动相体系的分离效果,优化了230、240、250和260 nm 4种检测波长等条件。结果表明,V甲醇∶V磷酸二氢铵溶液(0.5%,p H=3.5)=50∶50作为流动相时,基线稳定,峰形较好,3种目标物在11 min内即可实现有效分离,且浓度为5～100 mg·L~(-1)时,3种目标物峰面积与质量浓度的线性关系良好(R20.999),检出限为15.0～29.4μg·L~(-1),相对偏差为0.05%～1.56%(n=5),该方法能同时检测苯磺酸、苯酚和苯磺酰胺,具有简便、灵敏、准确等优点,可为制药废水的快速检测和磺胺类药物降解机理的分析提供便利。     

基于复合治理理论的基层应急管理模式优化*

为弥补传统基层应急管理模式的短板，解决信息壁垒、协调困难、公众参与不足等问题。从复合性视角出发，阐述复合治理理论内涵，探讨复合治理与应急管理在主体、思维、过程、空间、目标上的契合性，并进一步分析基层应急管理的现实背景和困境，进而构建基于复合治理理论的基层应急管理模式，阐明模式基本结构和工作流程，最终提出理念树立、平台搭建、机制保障、队伍建设、制度安排、文化营造、技术支撑方面的优化路径。结果表明:复合治理理论的应用可以加强基层应急管理能力，促进多元主体协同共治。     

The impact of global change on economic values of water for Public Irrigation Schemes at the São Francisco River Basin in Brazil

Economic values of water for the main Public Irrigation Schemes in the sub-middle region of the São Francisco River Basin, in northeastern Brazil, are determined in this study using an integration of a global agro-economic land and water use (MAgPIE) with a local economic model (Positive Mathematical Programming). As in the latter, the water values depend on the crops grown, and as Brazilian agriculture is strongly influenced by the global market, we used a regionalized version of the global model adapted to the region in order to simulate the crop land use, which is in turn determined by changes in global demand, trade barriers, and climate. The allocation of sugarcane and fruit crops projected with climate change by the global model, showed an impact on the average yields and on the water costs in the main schemes resulting in changes in the water values locally. The economic values for all schemes in the baseline year were higher than the water prices established for agricultural use in the basin. In the future, these water values will be higher in all the schemes. The highest water values currently and in the future were identified in municipalities with a significant proportion of area growing irrigated sugarcane. Being aware of current water values of each user in a baseline year and in a projected future under global climate and socioeconomic changes, decision makers should improve water allocation policies at local scale, in order to avoid conflicts and unsustainable development in the future.     

Air Quality Modeling Using the PSO-SVM-Based Approach,MLP Neural Network,and M5 Model Tree in the Metropolitan Area of Oviedo (Northern Spain)

The main aim of this study was to construct several regression models of air quality using techniques based on the statistical learning, in the metropolitan area of Oviedo, in northern Spain. In this research, a hybrid particle swarm optimization-based evolutionary support vector regression is implemented to predict the air quality from the experimental dataset (specifically, nitrogen oxides, carbon monoxide, sulfur dioxide, ozone, and dust) collected from 2013 to 2015 in the metropolitan area of Oviedo. Furthermore, a multilayer perceptron network (MLP) and the M5 model tree were also fitted to the experimental dataset for comparison purposes. Finally, the predicted results show that the hybrid proposed model is more robust than the MLP and M5 model tree prediction methods in terms of statistical estimators and testing performances.     

Influence of community-based natural resource management strategies in the resilience of social-ecological systems

Different social-ecological systems around the world are managed under community-based natural resource management (CBNRM) strategies. This paper analyses how CBNRM strategies influence the resilience of social-ecological systems to the disturbances they face, drawing upon the experience of three Latin American cases (two in Mexico and one in Colombia). The cases differ in their CBNRM approach and in the time these governance systems have been in place. By using a mixed-method approach, we review the socio-ecological history and describe each CBNRM characteristics. We then assess their resilience to socioeconomic and environmental disturbances through a set of indicators. We found that CBNRM strategies influence positively and negatively resilience and that internal decisions might address important threats. On the positive side, the social-ecological systems with longer tradition of CBNRM and more local buy-in of commonly agreed objectives appear to be more resilient to environmental challenges. But, internal governance factors such as power imbalances, poor income distribution, and gender inequities linked to CBNRM undermine resilience and foster out migration. Finally, communities appear to have limited capacities to cope with external disturbances such as global drivers of change or national policies that negatively affect their social-ecological resilience.

     

Contamination of marine fauna by chlordecone in Guadeloupe: evidence of a seaward decreasing gradient

Chlordecone is an organochlorine pesticide, used in the Lesser Antilles from 1972 to 1993 to fight against a banana weevil. That molecule is very persistent in the natural environment and ends up in the sea with runoff waters. The objective of the present study is to evaluate the level of contamination in several trophic groups of marine animals according to their distance from the source of pollution. Samples of suspended matter, macroalgae, herbivorous fishes, detrivorous crustaceans, zooplanktivorous fishes, first- and second-order of carnivorous fishes, and piscivorous fishes have been collected in two sites, located downstream the contaminated sites (Goyave and Petit-Bourg), in three marine habitats (coastal mangroves, seagrass beds located 1.5 km from the shoreline, and coral reefs at 3 km offshore). Animals collected in mangroves were the most contaminated (mean concentrations 193 μg kg^?1 in Goyave and 213 μg kg^?1 in Petit-Bourg). Samples from seagrass beds presented intermediate concentrations of chlordecone (85 μg kg^?1 in Goyave and 107 μg kg^?1 in Petit-Bourg). Finally, samples from coral reefs were the less contaminated (71 μg kg^?1 in Goyave and 74 μg kg^?1 in Petit-Bourg). Reef samples, collected 3 km offshore, were two to three times less contaminated than those collected in mangroves.