铝合金的实验室盐雾试验腐蚀行为图像特征提取

目的提取铝合金材料在盐雾箱试验中可以表征腐蚀程度的表面形貌图像特征量。方法首先,对采集于表面化学清洗过的试样原始图像进行图像增强等预处理,突出腐蚀部位;其次,基于数字图像处理的分形和小波分解方法提取出分形维数和小波能量特征值。结果与以质量损失量为基础的腐蚀深度特征值进行相关性对比,基于图像分析的特征提取法的准确度和精度比较高。结论该方法可以应用于对试样的腐蚀程度进行定性和定量分析,判断并预测试样的腐蚀速度。     

Cumulative impact assessment in environmental planning: A coastal wetland watershed example

Several theoretical, analytical, and institutional difficulties have impeded the development and application of the assessment of cumulative environmental impacts. Watershed development on coastal wetlands offers an ideal context for evaluating the land disturbance target approach to cumulative impact assessment. A model land use planning system involving a time series approach was developed for Elkhorn Slough in California. The approach included four major components: evaluation of erosion susceptibility, measurement of land disturbance, establishment of a land disturbance target, and a comparison of existing and target land disturbance values. Further research is needed to test the transferability of the approach in a wide range of coastal watersheds and to verify the applicability of the methods to other cumulative impact problems.     

青铜峡铝厂氟污染对广武乡玉米影响的调查分析

监测了青铜峡铝厂东南方向４．５ｋｍ的广武乡玉米叶，得知含氟量为４３．９４－１６６．１ｍｇ／ｋｇ，对照样品树新林场玉米叶的含氟均值为１３．１５ｍｇ／ｋｇ，广武乡的玉米受到了严重的氟污染，农作物减产严重。     

From proposal to decision: Suggestions for tightening up the “NEPA process”

Although the process of documenting compliance with NEPA (the National Environmental Policy Act) requires no drastic revisions, it can be managed more rigorously. Suggestions for revision can be grouped under five major steps: 1) getting a complete proposal from the applicant; 2) getting the decision-making process onto the right decision-making path; 3) modifying the applicant's proposal 4) going down a shorter path through the EA/FONSI (environmental assessment and finding of no significant impact) or through categorical exclusion review; and 5) going down the longer path through the EIS. Step 2 is perhaps the most critical, because there a decision must be made whether to write an EA/FONSI or an EIS, on the basis of whether the proposal would “significantly affect … the … environment.” In the past, this decision has not always been made promptly or rigorously. Accordingly, we suggest that the agency responsible for NEPA compliance should develop a system (a “black box”), consisting of a core group of specialists working with an interdisciplinary team, using sophisticated techniques for modeling impacts and directing both their research and their writing according to the concept of significance. By determining more efficiently and reliably whether the impacts of a proposal would be significant, such an approach would improve management of the total process.     

关于中小城市生活垃圾的处理与回收利用的探讨

对城市生活垃圾的分类回收、处理进行了探讨，对完善城市基础设施建设，改善投资环境将起到重要作用。     

Economic development and environmental protection: an ecological economics perspective

This paper argues on both theoretical and empirical grounds that, beyond a certain point, there is an unavoidable conflictbetween economic development (generally taken to mean 'materialeconomic growth') and environmental protection. Think for a moment of natural forests, grasslands, marine estuaries, salt marshes, and coral reefs; and of arable soils, aquifers, mineraldeposits, petroleum, and coal. These are all forms of 'natural capital' that represent highly-ordered self-producing ecosystemsor rich accumulations of energy/matter with high use potential (low entropy). Now contemplate despoiled landscapes, eroding farmlands, depleted fisheries, anthropogenic greenhouse gases,acid rain, poisonous mine tailings and toxic synthetic compounds.These all represent disordered systems or degraded forms of energy and matter with little use potential (high entropy). The main thing connecting these two states is human economic activity. Ecological economics interprets the environment-economyrelationship in terms of the second law of thermodynamics. The second law sees economic activity as a dissipative process. Fromthis perspective, the production of economic goods andservices invariably requires the consumption of available energy and matter. To grow and develop, the economynecessarily 'feeds' on sources of high-quality energy/matter first produced by nature. This tends to disorder and homogenizethe ecosphere, The ascendance of humankind has consistently been accompanied by an accelerating rate of ecological degradation, particularly biodiversity loss, the simplificationof natural systems and pollution. In short, contemporary political rhetoric to the contrary, the prevailing growth-oriented global development paradigm is fundamentally incompatible with long-term ecological and social sustainability. Unsustainability is not a technical nor economic problem as usually conceived, but rather a state of systemic incompatibilitybetween a economy that is a fully-contained, growing, dependent sub-system of a non-growing ecosphere. Potential solutions fly inthe face of contemporary development trends and cultural values.     

Using improved neural network model to analyze RSP,NOx and NO2 levels in urban air in Mong Kok,Hong Kong

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 NO_x 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, NO_x and NO₂ concentrations collected at Mong Kok Roadside Gaseous Monitory Station in Hong Kong during the year 2000. By comparing the predicted RSP, NO_x 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.     

Application of the benthic index of biotic integrity to environmental monitoring in Chesapeake Bay

The Chesapeake Bay benthic index of biotic integrity (B-IBI) was developed to assess benthic community health and environmental quality in Chesapeake Bay. The B-IBI provides Chesapeake Bay monitoring programs with a uniform tool with which to characterize bay-wide benthic community condition and assess the health of the Bay. A probability-based design permits unbiased annual estimates of areal degradation within the Chesapeake Bay and its tributaries with quantifiable precision. However, of greatest interest to managers is the identification of problem areas most in need of restoration. Here we apply the B-IBI to benthic data collected in the Bay since 1994 to assess benthic community degradation by Chesapeake Bay Program segment and water depth. We used a new B-IBI classification system that improves the reliability of the estimates of degradation. Estimates were produced for 67 Chesapeake Bay Program segments. Greatest degradation was found in areas that are known to experience hypoxia or show toxic contamination, such as the mesohaline portion of the Potomac River, the Patapsco River, and the Maryland mainstem. Logistic regression models revealed increased probability of degraded benthos with depth for the lower Potomac River, Patapsco River, Nanticoke River, lower York River, and the Maryland mainstem. Our assessment of degradation by segment and water depth provided greater resolution of relative condition than previously available, and helped define the extent of degradation in Chesapeake Bay.     

Selecting Socio-Economic Metrics for Watershed Management

The selection of social and economic metrics to document baseline conditions and analyze the dynamic relationships between ecosystems and human communities are important decisions for scientists, managers, and watershed citizens. A large variety of social and economic data is available but these have limited use without theoretical frameworks. In this paper, several frameworks for reviewing social-ecosystem relations are offered, namely social sanctions, sense of place, civic structure, and cultural differences. Underlying all of these frameworks are attitudes, beliefs, values, and norms that affect which questions are asked and which indicators are chosen. Much work and significant challenges remain in developing a standard set of spatially based socio-economic metrics for watershed management.     

Aerosol Scavenging: Model Application and Sensitivity Analysis in the Indian Context

Sulfate aerosols have been found to bethe major contributors to precipitation acidity. Thus,in view of the long-term ecological repercussions theyhave on aquatic ecosystems and their acidity-potential,the present analysis focuses on a case study applicationof the layer-averaged aerosol-scavenging model (Okita et al., 1996) for predicting values of the wet scavengingcoefficient and sulfate concentrations in precipitationsamples on the basis of the information available forsome selected Indian cities. Through sensitivityanalysis (Pandey et al., 1997) the scavengingcoefficient has been found to be very strongly dependenton precipitation intensity. Comparison of modelpredictions has been done with the measured values forDelhi, Mumbai, Calcutta and Chennai in India.