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341.
受火约束钢梁在升温段和降温段行为的理论分析(Ⅱ) 总被引:1,自引:0,他引:1
通过约束钢梁抗火试验结果与笔者提出的理论方法结果的比较,验证了升温段理论分析方法的正确性。在降温段,采用本文方法所得结果与其他理论所得结果也很相近。采用笔者提出的理论方法对约束钢梁进行了参数分析,研究了约束钢梁的轴向约束刚度、转动约束刚度、荷载比、梁的高跨比、钢材屈服、荷载作用类型和截面温度分布等因素对受火约束钢梁在升温段和降温段的影响。研究表明,上述因素,尤其是梁的荷载比、轴向约束刚度和高跨比等对约束钢梁在火灾升温段的行为有很大影响;在降温段,由于梁的收缩受到约束,引起很大的轴向拉力,轴向力的大小除了与梁的荷载比、轴向约束刚度有关外,还与梁所经历的最高温度有关。 相似文献
342.
大型水母爆发对东海生态系统中上层能量平衡的影响 总被引:8,自引:0,他引:8
通过建立东海生态系统ECOPATH模型,并将大型水母作为一个独立的功能组,从能量平衡的角度探讨近年来东海大型水母爆发对生态系统的影响,并在此基础上提出抑制大型水母爆发加剧的控制机制的假说。模型分析结果表明:大型水母对中上层生物资源普遍具有显著不利影响;在大型水母、浮游动物和鲳鱼等小型中上层鱼类之间可能存在一个由大型水母爆发引发的生态系统中上层能量反馈循环;大型水母爆发初期将破坏生态系统中上层能量平衡;浮游动物生物量的波动可能是抑制大型水母爆发加剧的自然控制机制之一。 相似文献
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344.
Identification of the leakage of hazardous gases plays an important role in the environment protection, human health and safety of industry production. However, lots of current optimization algorithms, such as particle swarm optimization (PSO) and Grey Wolf Optimizer (GWO), suffer from poor global optimization capability and estimation accuracy. In this work, a hybrid differential evolutionary and GWO (DE-GWO) algorithm is proposed. Tested by simulation cases and Prairie Grass emission experimental data, DE-GWO shows higher estimation accuracy than GWO. Compared with the other four optimization algorithms, DE-GWO exhibits finer robust stability under different population sizes, fewer iterations, as well as higher estimation accuracy with fewer search agents. Importantly, simulation results demonstrate that DE-GWO is more suitable to apply in the scene with a small number of sensors. Therefore, the proposed in this paper outperforms other optimization algorithms for the gas emission inverse problem. DE-GWO can provide reliable estimation towards gas emission identification and positioning, which shows huge potential as the data analysis module of real-time monitoring and early warning system. 相似文献
345.
Jiajia Liu Shangwen Xia Di Zeng Cong Liu Yingjun Li Wenjing Yang Bao Yang Jian Zhang Ferry Slik David B. Lindenmayer 《Conservation biology》2022,36(4):e13907
Extremely old trees have important roles in providing insights about historical climatic events and supporting cultural values, yet there has been limited work on their global distribution and conservation. We extracted information on 197,855 tree cores from 4854 sites and combined it with other tree age (e.g., the OLDLIST) data from a further 156 sites to determine the age of the world's oldest trees and quantify the factors influencing their global distribution. We found that extremely old trees >1000 years were rare. Among 30 individual trees that exceeded 2000 years old, 27 occurred in high mountains. We modeled maximum tree age with climatic, soil topographic, and anthropogenic variables, and our regression models demonstrated that elevation, human population density, soil carbon content, and mean annual temperature were key determinants of the distribution of the world's oldest trees. Specifically, our model predicted that many of the oldest trees will occur in high-elevation, cold, and arid mountains with limited human disturbance. This pattern was markedly different from that of the tallest trees, which were more likely to occur in relatively more mesic and productive locations. Global warming and expansion of human activities may induce rapid population declines of extremely old trees. New strategies, including targeted establishment of conservation reserves in remote regions, especially those in western parts of China and the United States, are required to protect these trees. 相似文献