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91.
Model evaluation of the phytoextraction potential of heavy metal hyperaccumulators and non-hyperaccumulators 总被引:3,自引:0,他引:3
Hong-Ming Liang Jeng-Min Chiou 《Environmental pollution (Barking, Essex : 1987)》2009,157(6):1945-1952
Evaluation of the remediation ability of zinc/cadmium in hyper- and non-hyperaccumulator plant species through greenhouse studies is limited. To bridge the gap between greenhouse studies and field applications for phytoextraction, we used published data to examine the partitioning of heavy metals between plants and soil (defined as the bioconcentration factor). We compared the remediation ability of the Zn/Cd hyperaccumulators Thlaspi caerulescens and Arabidopsis halleri and the non-hyperaccumulators Nicotiana tabacum and Brassica juncea using a hierarchical linear model (HLM). A recursive algorithm was then used to evaluate how many harvest cycles were required to clean a contaminated site to meet Taiwan Environmental Protection Agency regulations. Despite the high bioconcentration factor of both hyperaccumulators, metal removal was still limited because of the plants' small biomass. Simulation with N. tabacum and the Cadmium model suggests further study and development of plants with high biomass and improved phytoextraction potential for use in environmental cleanup. 相似文献
92.
表面活性剂清洗处理重度石油污染土壤 总被引:5,自引:1,他引:4
为了优化表面活性剂清洗处理重度石油污染土壤的方法和具体洗脱条件参数,采集山东省东营市胜利油田污染土壤,研究了阴离子-非离子混合表面活性剂对该土壤中石油类污染物的去除效果。应用化学热洗原理,主要考查了表面活性剂配比、投加量、清洗温度及清洗助剂对去除效果的影响。实验得到的清洗处理最佳条件为:使用LAS与TX-100质量比为8∶2的组合表面活性剂,总表面活性剂浓度为3 g/L,助剂硅酸钠浓度为5 g/L,75℃条件下搅拌1 h。清洗后土壤含油量从20%下降到4.6%,去除率达到76.9%。废水回用实验表明,清洗处理的废水对土壤中石油烃类物质仍有一定的去除效果。废水回用比从30%到100%时,对土壤中石油烃的去除率都可达到55%以上。对废水进行二次回用时仍能去除18.8%的污染物。 相似文献
93.
Uncertainty plays an important role in water quality management problems. The major sources of uncertainty in a water quality management problem are the random nature of hydrologic variables and imprecision (fuzziness) associated with goals of the dischargers and pollution control agencies (PCA). Many Waste Load Allocation (WLA) problems are solved by considering these two sources of uncertainty. Apart from randomness and fuzziness, missing data in the time series of a hydrologic variable may result in additional uncertainty due to partial ignorance. These uncertainties render the input parameters as imprecise parameters in water quality decision making. In this paper an Imprecise Fuzzy Waste Load Allocation Model (IFWLAM) is developed for water quality management of a river system subject to uncertainty arising from partial ignorance. In a WLA problem, both randomness and imprecision can be addressed simultaneously by fuzzy risk of low water quality. A methodology is developed for the computation of imprecise fuzzy risk of low water quality, when the parameters are characterized by uncertainty due to partial ignorance. A Monte-Carlo simulation is performed to evaluate the imprecise fuzzy risk of low water quality by considering the input variables as imprecise. Fuzzy multiobjective optimization is used to formulate the multiobjective model. The model developed is based on a fuzzy multiobjective optimization problem with max–min as the operator. This usually does not result in a unique solution but gives multiple solutions. Two optimization models are developed to capture all the decision alternatives or multiple solutions. The objective of the two optimization models is to obtain a range of fractional removal levels for the dischargers, such that the resultant fuzzy risk will be within acceptable limits. Specification of a range for fractional removal levels enhances flexibility in decision making. The methodology is demonstrated with a case study of the Tunga–Bhadra river system in India. 相似文献
94.
95.
关于植物中氟化物测定结果的计算 总被引:1,自引:0,他引:1
针对植物中氟化物测定时由于绘制校准曲线的标准溶液体积与分析样品的定容体积不一样而引出的结果计算时的某些问题,提出了正确的计算方法和建议。 相似文献
96.
Because of fast urban sprawl, land use competition, and the gap in available funds and needed funds, municipal decision makers
and planners are looking for more cost-effective and sustainable ways to improve their sewer infrastructure systems. The dominant
approaches have turned to planning the sanitary sewer systems within a regional context, while the decentralized and on-site/cluster
wastewater systems have not overcome the application barriers. But regionalization policy confers uncertainties and risks
upon cities while planning for future events. Following the philosophy of smart growth, this paper presents several optimal
expansion schemes for a fast-growing city in the US/Mexico borderlands—the city of Pharr in Texas under uncertainty. The waste
stream generated in Pharr is divided into three distinct sewer sheds within the city limit, including south region, central
region, and north region. The options available include routing the wastewater to a neighboring municipality (i.e., McAllen)
for treatment and reuse, expanding the existing wastewater treatment plant (WWTP) in the south sewer shed, and constructing
a new WWTP in the north sewer shed. Traditional deterministic least-cost optimization applied in the first stage can provide
a cost-effective and technology-based decision without respect to associated uncertainties system wide. As the model is primarily
driven by the fees charged for wastewater transfer, sensitivity analysis was emphasized by the inclusion of varying flat-rate
fees for adjustable transfer schemes before contracting process that may support the assessment of fiscal benefits to all
parties involved. Yet uncertainties might arise from wastewater generation, wastewater reuse, and cost increase in constructing
and operating the new wastewater treatment plant simultaneously. When dealing with multiple sources of uncertainty, the grey
mixed integer programming (GIP) model, formulated in the second stage, can further allow all sources of uncertainties to propagate
throughout the optimization context, simultaneously leading to determine a wealth of optimal decisions within a reasonable
range. Both models ran for three 5-year periods beginning in 2005 and ending in 2020. The dynamic outputs of this analysis
reflect the systematic concerns about integrative uncertainties within this decision analysis, which enable decision makers
and stakeholders to make all-inclusive decisions for sanitary sewer system expansion in an economically growing region. 相似文献
97.
We propose a stochastic dynamic programming framework to model the management of a multi-stand forest under climate risk (strong
wind occurrence). The preferences of the forest-owner are specified by a non-expected utility in order to separately analyze
intertemporal substitution and risk aversion effects. A numerical method is developed to characterize the optimal forest management
policies and the optimal consumption-saving strategy. The stochastic dynamic programming framework is applied to a non-industrial
private forest-owner located in North-East of France. We show that the optimal decisions both depend upon risk and time preferences.
The authors would like to thank participants at the international conference on Economics of Sustainable Forest Management
in Toronto, at the PARIS 1 seminar on Environmental and Natural Resource Economics, at the 2004 Applied Microeconomics Conference
in Lille and at the 13th annual conference of the European Association of Environmental and Resource Economists at Budapest. 相似文献
98.
We present a new mathematical programming framework that is adaptable to a variety of spatially explicit landscape problems
in environmental investment, conservation, and land-use planning, transport planning, and agriculture. As part of capturing
spatial interdependencies, the framework considers decision variables at two levels, finely spaced grid cells and landholdings.
We applied the framework to an environmental investment problem using objective functions representing biodiversity and carbon
sequestration. We also tested the model to optimize the path of a road through part of the landscape. Using the Nambucca case
study in eastern Australia, we applied a hybrid greedy randomised adaptive search procedure (GRASP) to find solutions to the
model. 相似文献
99.
In this study, an interval-fuzzy two-stage chance-constrained integer programming (IFTCIP) method is developed for supporting
environmental management under uncertainty. The IFTCIP improves upon the existing interval, fuzzy, and two-stage programming
approaches by allowing uncertainties expressed as probability distributions, fuzzy sets, and discrete intervals to be directly
incorporated within a general mixed integer linear programming framework. It has advantages in uncertainty reflection, policy
investigation, risk assessment, and capacity-expansion analysis in comparison to the other optimization methods. Moreover,
it can help examine the risk of violating system constraints and the associated consequences. The developed method is applied
to the planning for facility expansion and waste-flow allocation within a municipal solid waste management system. Violations
of capacity constraints are allowed under a range of significance levels, which reflects tradeoffs between the system cost
and the constraint-violation risk. The results indicate that reasonable solutions for both binary and continuous variables
have been generated under different risk levels. They are useful for generating desired decision alternatives with minimized
system cost and constraint-violation risk under various environmental, economic, and system-reliability conditions. Generally,
willingness to take a higher risk of constraint violation will guarantee a lower system cost; a strong desire to acquire a
lower risk will run into a higher system cost. 相似文献
100.
Mixed-integer linear programs are proposed for siting development and conservation areas in watersheds, addressing economic
objectives (development perimeter and proximity) and ecological objectives. Links between watershed hydrology and ecology
need not be well defined. Parameters for the linear programs are obtained from linearization of the SWAT hydrologic model. 相似文献