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利用EXCEL强大的数据处理功能,可以方便地对精密度—偏性分析质控数据进行处理,具有较高的推广价值。 相似文献
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Water quality indices (WQIs) have been developed to assess the suitability of water for a variety of uses. These indices reflect the status of water quality in lakes, streams, rivers, and reservoirs. The concept of WQIs is based on a comparison of the concentration of contaminants with the respective environmental standards. The number, frequency, and magnitude by which the environmental standards for specific variables are not met in a given time period are reflected in WQIs. Further, the water quality trend analysis predicts the behavior of the water quality parameters and overall water quality in the time domain. In this paper, the concept of WQI was applied to three selected watersheds of Atlantic region: the Mersey River, the Point Wolfe River, and the Dunk River sites. To have robust study, two different water quality indices are used: Canadian Water Quality Index (CWQI), and British Columbia Water Quality Index (BWQI). The complete study was conducted in two steps. The first step was to organize and process the data into a format compatible with WQI analysis. After processing the input data, the WQI was calculated. The second step outlined in the paper discusses detailed trend analysis using linear and quadratic models for all the three sites. As per the 25 years trend analysis, overall water quality for agriculture use observed an improving trend at all the three sites studied. Water quality for raw water used for drinking (prior to treatment) and aquatic uses has shown improving trend at Point Wolfe River. It is further observed that pH, SO4, and NO3 concentrations are improving at Dunk River, Mersey River, and Point Wolfe River sites. To ascertain the reliability and significance of the trend analysis, a detailed error analysis and parametric significance tests were also conducted It was observed that for most of the sites and water uses quadratic trend models were a better fit than the linear models. 相似文献
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Using improved neural network model to analyze RSP,NOx and NO2 levels in urban air in Mong Kok,Hong Kong 总被引:4,自引:0,他引:4
As the health impact of air pollutants existing in ambient addresses much attention in recent years, forecasting of airpollutant parameters becomes an important and popular topic inenvironmental science. Airborne pollution is a serious, and willbe a major problem in Hong Kong within the next few years. InHong Kong, Respirable Suspended Particulate (RSP) and NitrogenOxides NOx and NO2 are major air pollutants due to thedominant diesel fuel usage by public transportation and heavyvehicles. Hence, the investigation and prediction of the influence and the tendency of these pollutants are ofsignificance to public and the city image. The multi-layerperceptron (MLP) neural network is regarded as a reliable andcost-effective method to achieve such tasks. The works presentedhere involve developing an improved neural network model, whichcombines the principal component analysis (PCA) technique and theradial basis function (RBF) network, and forecasting thepollutant levels and tendencies based in the recorded data. Inthe study, the PCA is firstly used to reduce and orthogonalizethe original input variables (data), these treated variables arethen used as new input vectors in RBF neural network modelestablished for forecasting the pollutant tendencies. Comparingwith the general neural network models, the proposed modelpossesses simpler network architecture, faster training speed,and more satisfactory predicting performance. This improvedmodel is evaluated by using hourly time series of RSP, NOx and NO2 concentrations collected at Mong Kok Roadside Gaseous Monitory Station in Hong Kong during the year 2000. By comparing the predicted RSP, NOx and NO2 concentrationswith the actual data of these pollutants recorded at the monitorystation, the effectiveness of the proposed model has been proven.Therefore, in authors' opinion, the model presented in the paper is a potential tool in forecasting air quality parameters and hasadvantages over the traditional neural network methods. 相似文献
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Sulphate, Nitrogen and Base Cation Budgets at 21 Forested Catchments in Canada, the United States and Europe 总被引:1,自引:0,他引:1
Watmough SA Aherne J Alewell C Arp P Bailey S Clair T Dillon P Duchesne L Eimers C Fernandez I Foster N Larssen T Miller E Mitchell M Page S 《Environmental monitoring and assessment》2005,109(1-3):1-36
To assess the concern over declining base cation levels in forest soils caused by acid deposition, input-output budgets (1990s
average) for sulphate (SO4), inorganic nitrogen (NO3-N; NH4-N), calcium (Ca), magnesium (Mg) and potassium (K) were synthesised for 21 forested catchments from 17 regions in Canada,
the United States and Europe. Trend analysis was conducted on monthly ion concentrations in deposition and runoff when more
than 9 years of data were available (14 regions, 17 sites). Annual average SO4 deposition during the 1990s ranged between 7.3 and 28.4 kg ha−1 per year, and inorganic nitrogen (N) deposition was between 2.8 and 13.8 kg ha−1 per year, of which 41–67% was nitrate (NO3-N). Over the period of record, SO4 concentration in deposition decreased in 13/14 (13 out of 14 total) regions and SO4 in runoff decreased at 14/17 catchments. In contrast, NO3-N concentrations in deposition decreased in only 1/14 regions, while NH4-N concentration patterns varied; increasing at 3/14 regions and decreasing at 2/14 regions. Nitrate concentrations in runoff
decreased at 4/17 catchments and increased at only 1 site, whereas runoff levels of NH4-N increased at 5/17 catchments. Decreasing trends in deposition were also recorded for Ca, Mg, and K at many of the catchments
and on an equivalent basis, accounted for up to 131% (median 22%) of the decrease in acid anion deposition. Base cation concentrations
in streams generally declined over time, with significant decreases in Ca, Mg and K occurring at 8, 9 and 7 of 17 sites respectively,
which accounted for up to 133% (median 48%) of the decrease in acid anion concentration. Sulphate export exceeded input at
18/21 catchments, likely due to dry deposition and/or internal sources. The majority of N in deposition (31–100%; median 94%)
was retained in the catchments, although there was a tendency for greater NO3-N leaching at sites receiving higher (<7 kg ha-1 per year) bulk inorganic N deposition. Mass balance calculations show that export of Ca and Mg in runoff exceeds input at
all 21 catchments, but K export only exceeds input at 16/21 sites. Estimates of base cation weathering were available for
18 sites. When included in the mass balance calculation, Ca, Mg and K exports exceeded inputs at 14, 10 and 2 sites respectively.
Annual Ca and Mg losses represent appreciable proportions of the current exchangeable soil Ca and Mg pools, although losses
at some of the sites likely occur from weathering reactions beneath the rooting zone and there is considerable uncertainty
associated with mineral weathering estimates. Critical loads for sulphur (S) and N, using a critical base cation to aluminium
ratio of 10 in soil solution, are currently exceeded at 7 of the 18 sites with base cation weathering estimates. Despite reductions
in SO4 and H+ deposition, mass balance estimates indicate that acid deposition continues to acidify soils in many regions with losses of
Ca and Mg of primary concern.
The U.S. Government's right to retain a non-exclusive, royalty free licence in and to any copyright is acknowledged.
The Canadian Crown reserves the right to retain a non-exclusive, royalty free licence in and to any copyright. 相似文献
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汉江水质评价的化学计量学研究 总被引:4,自引:1,他引:4
运用因子分析法对汉江各主要水质断面进行水质因子分析及综合评价,通过各主因子的方差贡献及因子得分得出各水质因子的赋权值,从而对所取断面进行水质污染程度的综合评价、分析与排序。同时运用聚类分析法对汉江17个断面的水质污染相似性进行分析,给出分类处理结果。 相似文献
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