中国虚拟水贸易的测算及影响因素研究

本文测算2005年、2007年与2010年3个年度中国虚拟水进出口贸易量,采用投入产出及IO-SDA等方法分解分析其变化的影响因素。研究结果显示部门间用水系数差距都非常大,直接用水系数最大的农业部门857.9 t/万元(3年平均值,下同),与直接用水系数最小的部门差距达600倍之多。完全用水系数最大的也为农业部门1 078.7 t/万元,与完全用水系数最小的部门亦达113倍。各部门的完全用水系数和直接用水系数也存在较大不同,有些部门完全用水系数和直接用水系数差距很大,如服装皮革羽绒及其制品业部门差距达115倍,食品制造及烟草加工业部门差距达618.5 t/万元;而有些部门差距非常小,如农业部门差距仅仅0.24倍,煤炭开采和洗选业部门差距仅为8.2 t/万元。虚拟水出口量和进口量分别从2005年的1 774.3亿t和1 378.7亿t增加到2010年的2 254.1亿t和1 836.5亿t,且出口量一直大于进口量。影响因素分解显示,在此期间,进出口规模的增加是虚拟水贸易量增加的主要影响因素,其中出口规模合计为103 698.8×10~6t,进口规模合计为80 401.2×10~6t。进出口贸易结构的影响在不同部门间存在较大的差异。真实用水系数和真实中间投入技术是虚拟水贸易变化的主要负向因素,其中真实用水系数对虚拟水出口与进口的影响分别为-36 793.2×10~6t和-34 668.3×10~6t,真实中间投入技术对虚拟水出口与进口的影响分别为-1 719.7×10~6t和-1 660.8×10~6t,表明在此期间用水效率和中间投入效率都得到了改善。另外,直接用水系数和中间投入技术分解出的结构效应都不明显,中间投入进口比率效应也不明显。     

中国工业CO_2排放的行业间传导网络及协同减排

工业是碳排放的主要部门,科学识别工业CO_2排放的行业间传导并揭示其联动结构对于跨行业协同减排具有重要的理论和现实意义。本文基于1991-2012年中国工业36个两位数行业数据,在VAR模型框架下,利用Granger因果检验方法对CO_2排放的行业间传导关系进行了识别,并从关系视角出发,借助社会网络分析方法(SNA)揭示工业CO_2排放行业间传导的整体和个体网络结构特征,研究发现:工业CO_2排放的行业间传导呈网络结构形态,网络密度在1-6期的滞后阶数下呈先升高后下降的趋势,并且在滞后2期达到最高;燃气生产和供应业、电力热力生产和供应业、服装业、造纸及纸制品业、木材加工业具有较高的度数中心度、中介中心度、接近中心度,在网络中处于核心位置,并发挥中介和桥梁作用;在CO_2排放的行业传导网络中,煤炭采选业、黑色金属矿采选业、有色金属矿采选业等10个行业属于经纪人板块,医药制造业、饮料制造业、化学纤维制造业等9个行业属于净受益板块,金属制品业、塑料制品业、农副食品加工业等11个行业属于双向溢出板块,烟草加工业、石油加工及炼焦业、燃气生产和供应业等6个行业属于净溢出板块。基于上述结论,本文提出了工业CO_2排放的跨行业协同减排思路。     

A soil sampling intercomparison exercise for the ALMERA network

Soil sampling and analysis for radionuclides after an accidental or routine release is a key factor for the dose calculation to members of the public, and for the establishment of possible countermeasures. The IAEA organized for selected laboratories of the ALMERA (Analytical Laboratories for the Measurement of Environmental Radioactivity) network a Soil Sampling Intercomparison Exercise (IAEA/SIE/01) with the objective of comparing soil sampling procedures used by different laboratories. The ALMERA network is a world-wide network of analytical laboratories located in IAEA member states capable of providing reliable and timely analysis of environmental samples in the event of an accidental or intentional release of radioactivity. Ten ALMERA laboratories were selected to participate in the sampling exercise. The soil sampling intercomparison exercise took place in November 2005 in an agricultural area qualified as a “reference site”, aimed at assessing the uncertainties associated with soil sampling in agricultural, semi-natural, urban and contaminated environments and suitable for performing sampling intercomparison. In this paper, the laboratories sampling performance were evaluated.     

Assessment of present and future risk to Italian forests and human health: Modelling and mapping

A review of ozone pollution in Italy shows levels largely above the thresholds established by EU regulation for vegetation and human health protection. The Italian air quality monitoring network appears quantitatively inadequate to cover all the territorial surface, because of scarcity and unequal distribution of monitoring sites. By applying the integrated assessment model RAINS-Italy to the year 2000, the whole of Italy exceeds the AOT40 critical level for forest, while Northern and central areas show strong potential of O₃ impact on human health with ∼11% of territory >10 O₃-induced premature deaths. Two scenarios for the year 2020, the Current Legislation and the Maximum Technical Feasible Reduction, show a reduction of AOT40Forest by 29% and 44%, SOMO35 by 31% and 47%, and O₃-induced premature deaths by 32% and 48%, compared to 2000. RAINS-Italy can be used to improve the map quality and cover areas not reached by the national monitoring network.     

River channel network design for drought and flood control: A case study of Xiaoqinghe River basin, Jinan City, China

Vulnerability of river channels to urbanization has been lessened by the extensive construction of artificial water control improvements. The challenge, however, is that traditional engineering practices on isolated parts of a river may disturb the hydrologic continuity and interrupt the natural state of ecosystems. Taking the Xiaoqinghe River basin as a whole, we developed a river channel network design to mitigate river risks while sustaining the river in a state as natural as possible. The river channel risk from drought during low-flow periods and flood during high-flow periods as well as the potential for water diversion were articulated in detail. On the basis of the above investigation, a network with “nodes” and “edges” could be designed to relieve drought hazard and flood risk respectively. Subsequently, the shortest path algorithm in the graph theory was applied to optimize the low-flow network by searching for the shortest path. The effectiveness assessment was then performed for the low-flow and high-flow networks, respectively. For the former, the network connectedness was evaluated by calculating the “gamma index of connectivity” and “alpha index of circuitry”; for the latter, the ratio of flood-control capacity to projected flood level was devised and calculated. Results show that the design boosted network connectivity and circuitry during the low-flow periods, indicating a more fluent flow pathway, and reduced the flood risk during the high-flow periods.     

人工神经网络方法在拟建小区域环境质量评价中的应用

人工神经网络的评价方法用于小区域环境质量评价中,根据本地区特点因地制宜地选择环境质量参数,代入模型中进行环境质量评价及预测,对用于环境质量评价的BP人工神经网络模型进行了改进,即对网络模型的训练样本进行了扩充,从而提高了模型的抗干扰能力和准确性.将改进了的BP人工神经网络模型应用于四川省资阳市沱江二桥拟建项目小区域的大气、地表水环境质量评价中, 对该市小区域大气、地表水环境质量状况进行评价,评价结果表明,BP人工神经网络模型用于环境质量评价是可行的,且评价结论客观,评价模型普遍适用.     

基于模糊神经网络的机动车驾驶教练员职业适宜性研究

提出应用模糊神经网络系统,建构教练员职业适宜性的3个要素(即心理素质、驾驶技能和知识的表达阐述能力)的学习样本,分析"三要素"的8项特征参数指标——场依存性、速度估计能力、交通安全意识、简单反应、选择反应、跟踪能力、行车注意力、表达阐述能力等,使用K-均值法对实验样本进行初始分类,形成标准学习样本,使用该样本对所构建系统进行训练和调试。利用经调试训练后的系统,依据所测教练员的心理、心理参数对其职业适宜性进行评价。试验表明:建立的教练员职业适宜性仿真模型能取得很好的评价效果。     

我国危险化学品安全监管网络整合研究

分析我国危险化学品安全监管网络的特征,指出安全监管网络中存在的法律法规、监管部门信息共享、合作协调机制等方面存在的突出问题,提出了我国危险化学品安全监管网络整合的主要对策,包括建立监管部门之间的常态合作协调机制、无缝隙化城市安全监管平台以及跨区域合作监管机制。危险化学品安全监管网络整合,对提高我国危险化学品监管水平具有重要意义。     

基于粗糙集-神经网络的矿山地质环境影响评价模型及应用

采用衡山白果地区石膏矿山的11个评价指标,综合运用粗糙集和神经网络理论,构建了基于粗糙集-神经网络(RS-ANN)的矿山地质环境影响评价模型,对RSES软件约简的数据和无约简的数据采用EasyNN-plus软件进行预测评价。神经网络模型的输入属性为8个,而粗糙集-神经网络模型的输入属性为6个,训练样本均为13个,预测样本均为4个,前者的平均预测精度为1.85%～24.86%,后者为1.23%～15.28%。研究发现,粗糙集在保留关键信息的前提下可有效地对数据表进行约简,约简后的神经网络预测结果与实际情况吻合,并比无约简时总体精度有较大幅度提高。     

人工神经网络在化学和环境科学中应用的若干问题

讨论了人工神经网络中最常用的多层前馈网络 ( BP网络 )及误差反向传播算法应用于化学和环境科学时要考虑的几个问题 :网络的输入与数据的归一化 ;隐含层数、隐含层节数和学习速率 ;训练集与监控集 ;网络误差 ;初始权重