江苏省太湖污染防治概述

太湖水源是整个太湖流域国民经济与社会发展的命脉，近年来太湖水质恶化已影响太湖流域的经济与社会发展，分析了太湖污染来源及污染状况探讨了太湖污染的发展原因，指出了太湖水污染防治的措施，如污染物总量控制，重点治理，综合防治等。     

生命周期评价在水泥企业清洁生产审核中的应用

利用生命周期评价工具对企业的生产过程进行全面分析与评价，做好企业清洁生产的审核工作具有重要理论研究价值和现实应用意义。运用生命周期评价方法对重庆小南海水泥厂普通硅酸盐水泥生产过程进行了初步评价，认识了普通硅酸盐水泥生产过程的环境协调性，为普通硅酸盐水泥进一步提高环境性能提供了理论依据。     

东亚三角涡虫监测水体重金属污染的可行性研究

随着现代工、农业的快速发展,水体重金属污染已成为全球性的环境问题。对水体重金属污染的现状、来源、危害以及监测方法进行了介绍,并探讨了生物监测技术的优越性。在前人的研究基础上,结合本实验室工作,提出利用东亚三角涡虫(Dugesiaojapoice)作为水体重金属污染监测指示生物的可行性,并对更为灵敏的生物标志物的策略和实验方案进行了展望。     

地表水环境监测进展与问题分析

地表水环境的质量监测对我国水环境保护工作具有非常重要的作用,同时对我国的经济发展有着深远的影响。随着我国经济的快速发展,我国水环境监测工作有了较大的发展,但是在仪器更新、分析能力等方面还存在一系列的问题,本文对地表水环境监测的进展进行了阐述,并分析了水环境监测中存在的问题。     

水资源环境承载能力监测预警平台设计探讨

建立水资源环境承载力监测预警平台与机制,是实现我国环境管理战略由以环境污染控制为目标导向,向以环境质量改善为目标导向彻底转变的重要支撑手段。以水资源环境承载力领域的相关研究进展为基础,提出水资源环境承载力监控预警平台的设计框架,平台设计的逻辑结构、核心功能以及相对应的水资源环境承载力评估技术,并对该平台建设的困难、问题及未来的发展趋势进行了分析,以期为水资源环境承载能力监测预警机制建设提供有益的参考。     

固相萃取-GC/MS法测定水中有机氯农药

建立了固相萃取-气相色谱／质谱联用测定水中痕量六六六、滴滴涕和环氧七氯的方法。采用C18固相萃取柱富集水样,二氯甲烷／丙酮混合溶剂洗脱,加入菲-d10作为内标,利用气相色谱／质谱联用仪选择离子监测模式检测,内标法定量,定性、定量准确,线性响应良好,干扰小,按采样1 L计算,方法检出限为4．26ng／L～19、2ng／L,RSD在0、4％-6、3％之间,平均加标回收率在77．7％～118％之间,实际样品测定结果表明方法能满足环境水体中痕量有机氯农药的监测要求。     

Integrating intraseasonal grassland dynamics in cross-scale distribution modeling to support waterbird recovery plans

Despite much discussion about the utility of remote sensing for effective conservation, the inclusion of these technologies in species recovery plans remains largely anecdotal. We developed a modeling approach for the integration of local, spatially measured ecosystem functional dynamics into a species distribution modeling (SDM) framework in which other ecologically relevant factors are modeled separately at broad scales. To illustrate the approach, we incorporated intraseasonal water-vegetation dynamics into a cross-scale SDM for the Common Snipe (Gallinago gallinago), which is highly dependent on water and vegetation dynamics. The Common Snipe is an Iberian grassland waterbird characteristic of European agricultural meadows and a member of one of the most threatened bird guilds. The intraseasonal dynamics of water content of vegetation were measured using the standard deviation of the normalized difference water index time series computed from bimonthly images of the Sentinel-2 satellite. The recovery plan for the Common Snipe in Galicia (northwestern Iberian Peninsula) provided an opportunity to apply our modeling framework. Model accuracy in predicting the species’ distribution at a regional scale (resulting from integration of downscaled climate projections with regional habitat–topographic suitability models) was very high (area under the curve [AUC] of 0.981 and Boyce's index of 0.971). Local water-vegetation dynamic models, based exclusively on Sentinel-2 imagery, were good predictors (AUC of 0.849 and Boyce's index of 0.976). The predictive power improved (AUC of 0.92 and Boyce's index of 0.98) when local model predictions were restricted to areas identified by the continental and regional models as priorities for conservation. Our models also performed well (AUC of 0.90 and Boyce's index of 0.93) when projected to updated water-vegetation conditions. Our modeling framework enabled incorporation of key ecosystem processes closely related to water and carbon cycles while accounting for other factors ecologically relevant to endangered grassland waterbirds across different scales, allowed identification of priority areas for conservation, and provided an opportunity for cost-effective recovery planning by monitoring management effectiveness from space.     

Structurally-consistent estimation of use and nonuse values for landscape-wide environmental change

We address the problem of estimating the use and nonuse value derived from a landscape-wide programme of environmental change. Working in the random utility framework, we develop a structural model that describes both demand for recreational trips to the landscape's quality-differentiated natural areas and preferences over different landscape-wide patterns of environmental quality elicited in a choice experiment. The structural coherence of the model ensures that the parameters of the preference function can be simultaneously estimated from the combination of revealed and stated preference data. We explore the properties of the model in a Monte Carlo experiment and then apply it to a study of preferences for changes in the ecological quality of rivers in northern England. This implementation reveals plausible estimates of the use and nonuse parameters of the model and provides insights into the distance decay in those two different forms of value.     

Extinction rate of discovered and undiscovered plants in Singapore

Extinction is a key issue in the assessment of global biodiversity. However, many extinction rate measures do not account for species that went extinct before they could be discovered. The highly developed island city–state of Singapore has one of the best-documented tropical floras in the world. This allowed us to estimate the total rate of floristic extinctions in Singapore since 1822 after accounting for sampling effort and crypto extinctions by collating herbaria records. Our database comprised 34,224 specimens from 2076 native species, of which 464 species (22%) were considered nationally extinct. We assumed that undiscovered species had the same annual per-species extinction rates as discovered species and that no undiscovered species remained extant. With classical and Bayesian algorithms, we estimated that 304 (95% confidence interval, 213–414) and 412 (95% credible interval, 313–534) additional species went extinct before they could be discovered, respectively; corresponding total extinction rate estimates were 32% and 35% (range 30–38%). We detected violations of our 2 assumptions that could cause our extinction estimates, particularly the absolute numbers, to be biased downward. Thus, our estimates should be treated as lower bounds. Our results illustrate the possible magnitudes of plant extirpations that can be expected in the tropics as development continues.     

2,4-dichlorophenoxyacetic acid (2,4-D) micropollutant herbicide removing from water using granular and powdered activated carbons: a comparison applied for water treatment and health safety

Abstract

Activated carbons are well-known porous materials as an effective adsorbent used for the removal of emerging contaminants, such as herbicides, which are increasingly present in water bodies. Most water treatment plants, specially in Brazil, are unable to completely remove such contaminants by the conventional process and advanced treatment using activated carbons is required. The aim of this paper was to verify the influence of the activated carbons granulometry and specific surface area on the 2,4-dichlorophenoxyacetic acid (2,4-D) herbicide removal efficiency using distilled-deionized water and filtered water collected from a conventional Water Treatment Plant. Commercial activated carbons samples used in this work were obtained from two different manufacturers. Activated carbons were analyzed by the specific surface area, pore size and volume distribution, nuclear magnetic resonance, infrared and x-ray spectroscopy, moisture, volatile matter and ash contents. Batch adsorption isotherms experiments were used and performed by Langmuir and Freundlich models. Granular and powdered activated carbons removed over 99% of 2,4-D in distilled water and near to 99% using filtered water. The activated carbons evaluated in this work presented high performance and played a key role in water treatment by removing 2,4-D herbicide, ensuring the protection of human health and the ecosystem.