气候变化和人类活动对武江流域年径流及最大日流量影响的定量分析

针对气候变化与人类活动对流域年径流及最大日流量变化影响的定量识别问题,以华南湿润区武江流域为例,分别采用HIMS（Hydro-Informatic Modeling System）模型和敏感性系数法,从日和年尺度定量模拟和评估气候变化与人类活动对流域年最大日流量和径流变化的影响过程及贡献率。结果表明：HIMS模型在武江流域适用性良好,日尺度模型率定期和验证期的纳西效率系数分别为0.85和0.77,水量平衡误差绝对值分别为3.1%和3.3%;两种方法均表明气候变化是引起流域年径流量增加的主要因素,人类活动导致了流域径流量的减少,但贡献率较小。气候变化与人类活动导致了流域年最大日流量的增加,气候变化对年最大日流量增加的贡献率为94%,而人类活动的贡献率则为6%。相较于年均径流量,气候变化对年最大日流量的影响更为显著。     

约束条件下中国循环经济发展中的生态效率——基于优化的超效率SBM-Malmquist-Tobit模型

以中国30个省份、直辖市、自治区的年度面板数据为研究对象,重点将生态资源存量和环境污染造成的经济浪费两项指标纳入新的生态效率评价体系,运用优化的引入非期望产出的超效率SBM模型测算生态效率,再运用Malmquist指数考察全要素生产率（TFP）与生态效率的动态变动关系,最后运用Tobit回归分析探索生态效率主要影响因素的方向、强度和变化趋势,以此度量和展现循环经济发展的整体情况.结果显示：生态效率呈现由东到西、由沿海到内陆逐渐收敛的格局,东部沿海地区和中部、西部内陆地区间,循环经济发展水平存在显著的阶梯式区域失衡;生态效率的集群效应明显,辐射效应不足,不同地区或同一地区的不同省份间,循环经济发展水平同样参差不齐;经济发展引发的生态赤字问题逐步缓解,但在短时间内经济和生态的矛盾依旧存在,西北地区尤为突显;第三产业比重、技术进步、市场开放对生态效率的提升具有积极作用且趋于强化;政府规制、人口密度对生态效率的提升也具有积极作用但趋于减弱;第二产业比重、能源结构对生态效率的改善存在负面影响亦趋于强化.     

考虑边界条件不确定性的地下水污染风险分析

为分析边界条件不确定性对地下水污染质运移数值模拟模型输出结果的影响,运用Monte Carlo方法对一算例进行阐明,并从污染风险预报方面对模拟结果进行分析.为减少重复调用模拟模型产生的大量计算负荷,将边界条件（第一类边界条件-水头值）作为随机变量,建立地下水污染质运移数值模拟模型的Kriging替代模型,在保证较高精度的同时,实现了Monte Carlo模拟.结果表明：边界条件的不确定性,对地下水污染质运移数值模拟模型预报的结果有很大影响,考虑与未考虑边界条件不确定性得到的研究区污染羽分布差别较大.对地下水污染质运移数值模拟模型的Monte Carlo模拟结果进行统计与分析,可以评估研究区观测井1,2,3污染物浓度预报结果的可靠程度,并且可以预报出研究区观测井1,2,3遭受不同程度污染的风险.     

Relationship between physicochemical properties and dewaterability of hydrothermal sludge derived from different source

Sewage sludge (SS) and deinking sludge (DS) were used to comparatively study the hydrothermal dewatering of sludge with different components. For a better overview, an insight into the relationship between physicochemical properties and dewaterability of hydrothermal sludge was provided. Results found that not all kinds of sludge were suitably conditioned by hydrothermal treatment (HT) in term of the elevation of dewaterability. Higher hydrothermal temperature tended to enhance the dewaterability of SS rather than DS, which was supported by the variation of their physicochemical properties (including water distribution, bonding energy, extracellular polymeric substance (EPS), particles size, acid functional groups and zeta potential in this study). In addition, the changes in surface morphology suggested that the reverse effect of HT on sludge dewaterability was mainly due to their dewatering behavior. For SS, the destruction of EPS structure leaded to the release of bound water, thereby strengthening sludge dewatering. Conversely, “Bridging effect” generated by lignocellulose in DS was beneficial for sludge dewatering; however, the increasing hydrothermal temperature degraded part of lignocellulose and weakened “bridging effect”, finally resulting in worse dewaterability of DS.     

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.     

A modular approach to Integrated Assessment modeling

In this paper, we present a new approach to model coupling that probably forms the methodological basis of a new generation of Integrated Assessment models. This approach respects the knowledge and expertise that is embodied in existing models and encourages their gradual evolution. Modularity is the guiding principle. Our approach is distinguished by the way modules are coupled which is based on an interplay of a job control module, a numerical coupling module, and a couple of stand-alone functional modules. The numerical coupling module - the core component - serves to treat the feedbacks between the functional modules. A first implemented example that couples an economic and a climate module by means of a two-phase meta-optimization is presented here. The algorithm and mathematical structure behind are discussed as well as important features such as convergence behavior and reliability.     

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.     

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.     

Modeling of non-point source pollution in a Mediterranean drainage basin

SWAT ver. 2000 was used to predict hydrographs, and sediment, nitrate and total phosphorus loadings from a 1349 km² mountainous/agricultural watershed in Northern Greece. The model was calibrated and verified using continuous meteorological data from eight stations within the drainage area, and runoff, sediment and nutrient concentrations measured at nine stations located within the main tributaries of the watershed, for the time period from May 1st, 1998 to January 31st, 2000. Model validation methodology and resulting input parameters appropriate for Mediterranean drainage basins are presented. Predicted by the model hydrographs, sedimentographs and pollutographs are plotted against observed values and show good agreement. Model performance is evaluated using the root mean square error computation and scattergrams of predicted versus observed data. The validated model is also used to test the effectiveness of three alternative cropping scenarios in reducing nutrient loadings from the agricultural part of the watershed. The study showed that this model, if properly validated, can be used effectively in testing management scenarios in Mediterranean drainage basins.