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301.
小清河沿岸地下水中有机污染物优先排序的研究 总被引:8,自引:1,他引:7
提出了对区域性有机污染物优先排序和风险分类的定量评价方法———密切值法。该方法以反映污染物的毒性、暴露水平和化学性质的6项参数为指标,对小清河沿岸地下水中的有机污染物进行了优先排序和风险分类。 相似文献
302.
Jørgen Brandt Annemarie Bastrup-birk Jesper H. Christensen Torben Mikkelsen Søren Thykier-Nielsen Zahari Zlatev 《Atmospheric environment (Oxford, England : 1994)》1998,32(24):105
A tracer model, the DREAM, which is based on a combination of a near-range Lagrangian model and a long-range Eulerian model, has been developed. The meteorological meso-scale model, MM5V1, is implemented as a meteorological driver for the tracer model. The model system is used for studying transport and dispersion of air pollutants caused by a single but strong source as, e.g. an accidental release from a nuclear power plant. The model system including the coupling of the Lagrangian model with the Eulerian model are described. Various simple and comprehensive parameterizations of the mixing height, the vertical dispersion, and different meterological input data have been implemented in the combined tracer model, and the model results have been validated against measurements from the ETEX-1 release. Several different statistical parameters have been used to estimate the differences between the parameterizations and meterological input data in order to find the best performing solution. 相似文献
303.
304.
6+ ), copper (Cu), lead (Pb), mercury (Hg), nickel (Ni), selenium (Se), zinc (Zn), and polychlorinated biphenyls (PCBs). Water-column,
bed-sediment, and fish-tissue (fillets) data collected by five government agencies comprised the ambient data set; effluent
data from five registered facilities comprised the compliance data set. The nonparametric Mann-Kendall trend test indicated
that 33% of temporal trends in all data were statistically significant (P < 0.05). Possible reasons for this were low sample sizes, and a high percentage of samples below the analytical detection
limit. Trends in compliance data were more distinct; most trace elements decreased significantly, probably due to improvements
in wastewater treatment. Seven trace elements (Cr, Cd, Cu, Pb, Hg, Ni, and Zn) had statistically significant decreases in
wastewater and portions of either or both ambient water and bed sediment. No trends were found in fish tissue. Inconsistency
in trends between ambient and compliance data were often found for individual constituents, making overall similarity between
the data sets difficult to determine. Logistical differences in monitoring programs, such as varying field and laboratory
methods among agencies, made it difficult to assess ambient temporal trends. 相似文献
305.
306.
综采工作面人员操作可靠性与割煤机运行方式的选择与分析 总被引:4,自引:2,他引:2
王卫军 《中国安全科学学报》1999,9(6):45-48
应用人机工程及可靠性理论,分析了连续作业时间和割煤机运行方式对综采工作面人员操作可靠性的影响,建立了割煤机运行方式的优化模型。根据模型所选择的割煤机运行方式,既能提高工作面产量,也能提高人员操作可靠性,有利于综采工作面高效安全生产 相似文献
307.
We assessed the occurrence of a common river bird, the Plumbeous Redstart Rhyacornis fuliginosus, along 180 independent streams in the Indian and Nepali Himalaya. We then compared the performance of multiple discrimant analysis (MDA), logistic regression (LR) and artificial neural networks (ANN) in predicting this species’ presence or absence from 32 variables describing stream altitude, slope, habitat structure, chemistry and invertebrate abundance. Using the entire data (=training set) and a threshold for accepting presence in ANN and LR set to P≥0.5, ANN correctly classified marginally more cases (88%) than either LR (83%) or MDA (84%). Model performance was assessed from two methods of data partitioning. In a ‘leave-one-out’ approach, LR correctly predicted more cases (82%) than MDA (73%) or ANN (69%). However, in a holdout procedure, all the methods performed similarly (73–75%). All methods predicted true absence (i.e. specificity in holdout: 81–85%) better than true presence (i.e. sensitivity: 57–60%). These effects reflect species’ prevalence (=frequency of occurrence), but are seldom considered in distribution modelling. Despite occurring at only 36% of the sites, Plumbeous Redstarts are one of the most common Himalayan river birds, and problems will be greater with less common species. Both LR and ANN require an arbitrary threshold probability (often P=0.5) at which to accept species presence from model prediction. Simulations involving varied prevalence revealed that LR was particularly sensitive to threshold effects. ROC plots (received operating characteristic) were therefore used to compare model performance on test data at a range of thresholds; LR always outperformed ANN. This case study supports the need to test species’ distribution models with independent data, and to use a range of criteria in assessing model performance. ANN do not yet have major advantages over conventional multivariate methods for assessing bird distributions. LR and MDA were both more efficient in the use of computer time than ANN, and also more straightforward in providing testable hypotheses about environmental effects on occurrence. However, LR was apparently subject to chance significant effects from explanatory variables, emphasising the well-known risks of models based purely on correlative data. 相似文献
308.
309.
Conservation decisions are invariably made with incomplete data on species’ distributions, habitats, and threats, but frameworks for allocating conservation investments rarely account for missing data. We examined how explicit consideration of missing data can boost return on investment in ecosystem restoration, focusing on the challenge of restoring aquatic ecosystem connectivity by removing dams and road crossings from rivers. A novel way of integrating the presence of unmapped barriers into a barrier optimization model was developed and applied to the U.S. state of Maine to maximize expected habitat gain for migratory fish. Failing to account for unmapped barriers during prioritization led to nearly 50% lower habitat gain than was anticipated using a conventional barrier optimization approach. Explicitly acknowledging that data are incomplete during project selection, however, boosted expected habitat gains by 20–273% on average, depending on the true number of unmapped barriers. Importantly, these gains occurred without additional data. Simply acknowledging that some barriers were unmapped, regardless of their precise number and location, improved conservation outcomes. Given incomplete data on ecosystems worldwide, our results demonstrate the value of accounting for data shortcomings during project selection. 相似文献
310.
不同模型对土壤污染物空间分布预测精度具有重要影响,针对现有方法不能较好模拟土壤污染物较强的空间变异特征以及缺乏对影响污染物空间分布的关键环境因子识别,本研究基于随机森林(RF)模型,通过融合多源环境要素,开展了某冶炼厂周边农田土壤砷含量空间分布预测研究,并与反距离加权(IDW)和逐步线性回归模型(STEPREG)相比较.结果表明,研究区农田土壤砷污染范围较广,污染严重区域主要分布在研究区南部,3种模型模拟的砷污染空间分布虽总体趋势相似,但局部区域差异明显,IDW和STEPREG模型不能很好地反映研究区土壤污染的强空间变异特征,RF模型模拟结果较好的表达局部高污染区域的细部变化.不同环境要素对农田土壤砷含量空间分布影响的重要性不同,研究区环境变量和地形变量是影响土壤砷含量空间分布的关键环境因子.交叉验证结果表明,RF模型相对IDW和STEPREG模型具有最小的均方根误差(RMSE)、平均绝对误差(MAE)、平均误差(ME)和最大的R2,RF模型的RMSE、MAE、ME较IDW模型分别降低了10.8%、5.5%和88.1%,较STEPREG模型分别降低了17.8%、18.4%和94.7%,表明采用RF模型对研究区农田土壤砷含量预测精度最高,取得了最优的预测效果.本研究结果能够为土壤重金属污染空间分布制图提供方法学参考. 相似文献