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.     

Prediction of Leachate Level in Kimpo Metropolitan Landfill Site by Total Water Balance

Kimpo metropolitan landfill has received various kinds of wastessince January 1992. The leachate level was measured to be 10.3 m in May 1995 and the level increased to 12.2 m in August 1996. Therefore, to prove the reason for the increasing leachate level, we calibrated hydraulic conductivity of each waste andintermediate layer using the HELP (Hydrologic Evaluation ofLandfill Performance) model. The leachate generation data measured from February 1993 to October 1995 was used in the model calibration. As a result of a model calibration, we obtained anaverage infiltration ratio and used this in analysis of the total water balance to predict elevation of leachate level. Main causes of the elevation of the leachate level were the high water content of the waste and the degradation of the leachate-drainage system caused by the subsidence of a naturalbarrier layer.     

Nitrogen isotope ratios in pine bark as an indicator of N emissions from anthropogenic sources

The article describes the use of Scots pine bark to identifynitrogen sources in eastern Germany, as well as background areas in Russia and Bulgaria, by using natural isotope ratios of total nitrogen (N_t) and individual N compoundssuch as ammonium (NH₄ ⁺), nitrate (NO₃ ^-)and amid nitrogen (amide-N). The samples collected were analysed using an elemental analyser in connection with a gas isotope mass spectrometer (EA-IRMS). Natural ¹⁵N abundances in pine bark from impact areas suggest that the ammonium accumulated on the surface of the bark is releasedfrom livestock management. Bark of Scots pines growing near agricultural land had highly depleted ¹⁵N_t values (between –8 and –12), while bark from background areas (unpolluted areas) displayed slightly negative ¹⁵N_t values (mean ¹⁵N_t = –3.8). It is assumed that part of the N adsorbed on the bark surface is mainly derived from ammonia(mean ¹⁵N_t = –40.3) escaping from livestock housing and during the application of manure. This assumption is confirmed by experiments under controlled conditions in which manure samples were spread on soil. In addition, temporal and spatial variations of ¹⁵N_t abundances in pine bark from various locations in eastern Germany as wellas pine stands in Nature Park Dübener Heath are discussed.     

博斯腾湖水质矿化度模型及预测研究

根据博斯腾湖１９８５～１９９５年水质监测数据和出入湖水量等水文数据观测值，采用水质扩散模型和盐量平衡关系推导出博斯腾湖大湖区（简称博湖）水质矿化度模型，并预测了几种情况下博湖水质矿化度及近几年变化趋势，分析了影响博湖水质矿化度的主要因素，为博湖的近期和远期环境保护规划、环境管理等提供科学依据．     

哈密地区环境中^220Rn子体α潜能浓度所致居民剂量估算

用ＳｔｒａｎｄｅｎＥ．推荐的测量方法对哈密地区环境空气中２２０Ｒｎ子体α潜能浓度测量结果表明，室内、外平均值分别为５６．１和１０．２（×１０－７Ｊ·ｍ－３）。室内外２２０Ｒｎ／２２２Ｒｎ子体α潜能浓度比值分别为０．８４和０３２。２２０Ｒｎ子体所致居民有效剂量当量为２２８μＳｖ·ａ－１（集体有效剂量当量为０．９×０２ｍａｎ·Ｓｖ）。