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371.
为解决快速测量生化需氧量,生化需氧量智能生物检测仪对多种废水的实际测定表明,操作简单,测量周期为30min,精密度为±10%左右,特别适用于污水处理中控制分析及批量样品的分析测定。 相似文献
372.
现代应急管理是研究突发事件的现象及其发展规律的学科,集成多个学科的前沿理论、方法和技术,是当代中国应急管理发展需依托的知识体系及方法论。本文从现代应急管理的概念和理论出发,阐述了应急管理的功能体制与组织架构、风险分析策略与应急评价方法创新、新兴风险防范与应急管理机制设计、应急管理技术支撑与系统平台等核心问题。同时,从应急资源、应急产业、协作模式、应急文化4个方面对现代应急管理的应用与实践提出一些建议。研究表明:现代应急管理能够全面提高国家综合防灾减灾救灾能力。 相似文献
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Alexa N. Seal James E. Pratley Terry J. Haig Min An Hanwen Wu 《Agriculture, ecosystems & environment》2010,135(1-2):52-57
Herbicide resistance in annual ryegrass (ARG, Lolium rigidum) threatens the quality and yield of winter wheat crops in Australia, prompting research to discover novel natural plant compounds with herbicidal properties. Due to its novel nature and potentially interesting chemistry, the Australian native, Wollemi pine (Wollemia nobilis), was tested for its ability to suppress ARG growth and its feasibility for use in weed control strategies. The leaf extract of Wollemi pine significantly inhibited the growth of ARG and wild radish (Raphanus raphanistrum) in laboratory bioassays at concentrations above 1% extract. In soil trials, the 100% extract (100 g dried plant material/L) inhibited the dry weight of ARG by 25%. The addition of a wetting agent to the extract increased the suppression of ARG to 80% which was as phytotoxic as a 4-fold increase in the extract concentration (“400%” extract). Using bioassay-guided fractionation, the most phytotoxic fraction was identified and further analysed via GC/MS. Several compounds not previously identified in Wollemi pine leaf extracts have been identified, namely, 2-propylphenol, 3,4-dimethoxyphenol, 2-methoxybenzoic acid, vanillyl alcohol and isovanillic acid. These results suggest that Wollemi pine is an important potential source of compounds for the control of ARG and wild radish in winter crops. 相似文献
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中国生态环境问题及环境保护计划 总被引:4,自引:0,他引:4
本将中国面临的生态环境问题归纳为七大问题,即:土地流失、土地荒漠化、森林覆盖面积减少、草原退化、自然灾害加剧、空气污染和酸雨、水污染和缺水。以统计数据为依据,从7个方面展现了生态环境的现状和遭受破坏的程度。扼要说明了由灾害和污染所造成的经济损失。介绍了中国政府就治理污染、防止生态环境破坏的环境保护计划。 相似文献
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ABSTRACT This study presents a novel method for integrating the output of a microscopic emission modeling approach with a regional traffic assignment model in order to achieve an accurate greenhouse gas (GHG, in CO2-eq) emission estimate for transportation in large metropolitan regions. The CLustEr-based Validated Emission Recalculation (CLEVER) method makes use of instantaneous speed data and link-based traffic characteristics in order to refine on-road GHG inventories. The CLEVER approach first clusters road links based on aggregate traffic characteristics, then assigns representative emission factors (EFs), calibrated using the output of microscopic emission modeling. In this paper, cluster parameters including number and feature vector were calibrated with different sets of roads within the Greater Toronto Area (GTA), while assessing the spatial transferability of the algorithm. Using calibrated cluster sets, morning peak GHG emissions in the GTA were estimated to be 2,692 tons, which is lower than the estimate generated by a traditional, average speed approach (3,254 tons). Link-level comparison between CLEVER and the average speed approach demonstrates that GHG emissions for uncongested links were overestimated by the average speed model. In contrast, at intersections and ramps with more congested links and interrupted traffic flow, the average speed model underestimated GHG emissions. This proposed approach is able to capture variations in traffic conditions compared to the traditional average speed approach, without the need to conduct traffic simulation. Implications: A reliable traffic emissions estimate is necessary to evaluate transportation policies. Currently, accuracy and transferability are major limitations in modeling regional emissions. This paper develops a hybrid modeling approach (CLEVER) to bridge between computational efficiency and estimation accuracy. Using a k-means clustering algorithm with street-level traffic data, CLEVER generates representative emission factors for each cluster. The approach was validated against the baseline (output of a microscopic emission model), demonstrating transferability across different cities . 相似文献
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Abstract Reservoir water environment is a grey system. The grey clustering method is applied to assessing the reservoir water environment to establish a relatively complete model suitable for the reservoir eutrophication evaluation and appropriately evaluate the quality of reservoir water, providing evidence for reservoir management. According to China’s lakes and reservoir eutrophication criteria and the characteristics of China’s eutrophication, as well as certain evaluation indices, the degree of eutrophication is classified into six categories with the utilization of grey classified whitening weight function to represent the boundaries of classification, to determine the clustering weight and clustering coefficient of each index in grey classifications, and the classification of each clustering object. The comprehensive evaluation of reservoir eutrophication is established on such a foundation, with Sichuan Shengzhong Reservoir as the survey object and the analysis of the data attained by several typical monitoring points there in 2006. It is found that eutrophication of Tiebian Power Generation Station, Guoyuanchang and Dashiqiao Bridge is the heaviest, Tielusi and Qinggangya the second, and Lijiaba the least. The eutrophication of this reservoir is closely relevant to the irrational exploitation in its surrounding areas, especially to the aggravation of the non-point source pollution and the increase of net-culture fishing. Therefore, it is feasible to use grey clustering in environment quality evaluation, and the point lies in the correct division of grey whitening function 相似文献