Sharing and preparing: cross-institutional,food security-based knowledge in Canada

This study proposes a framework for the collection and management of knowledge related to food security in Canada. This paper has several goals. First, the paper summarizes the current state of food security knowledge in Canada. Second, the paper presents data from an experiment where food security issues were discussed by stakeholders at two fora, the first of which was held in western Canada and the second held in eastern Canada. Finally, based on the notes taken during and feedback received after the fora, this paper suggests a framework for organizing and managing the multiple perspectives and complex types of knowledge about food security and sustainable development from a Canadian context. Two fora were held in Canada where food security issues were presented and discussed by multiple stakeholders. Most provinces in Canada were represented in at least one of the two sessions. Sessions were designed to be informative and interactive; agenda were designed to take advantage of the needs and experiences of multiple stakeholders in both western and eastern regions of Canada. To develop the framework, the sessions were also designed to assess the types of issues and knowledge about food security in Canada. Evidence presented from this experiment supports arguments that food security work must be approached in a collaborative manner, no matter the approach or discipline. Data from fora held in western and eastern regions of Canada indicate a number of specific ways in which those along the food continuum have the desire to share knowledge and enter into partnerships to work toward secure and sustainable food systems. Data also indicate how academia and institutions of higher learning might play a key role in sharing food security-based knowledge. The data from this study suggest that academia could play a leadership role in collecting and sharing information about food security-based knowledge from all disciplinary approaches that could help collaborative in addressing the complexity of food security challenges. The framework developed in this paper could provide the guide for organizing knowledge about food security and sustainable development. The framework could be used as a map to guide understanding about the different ways in which food security can be approached and understood; this could help reduce tensions among partners in projects where a wide variety of experiences are attempting to work collaboratively. The two food security fora brought together stakeholders with specialized knowledge about food security in a Canadian context. The analysis of data arising from the fora permitted unique insights to arise about the nature of knowledge by region. The data in this study also allowed us to build a framework for food security knowledge from these regional knowledge bases. This paper suggests that academia actively take a leadership role and openly share knowledge about food security. Open sharing of knowledge will help collaborates in dealing with complex food security issues understand in-depth other approaches; this sharing may help to make explicit the tensions that arise during collaborative work.     

中国碳排放的区域差异及其与经济增长的关联分析

采用政府间气候变化专门委员会(IPCC)的碳排放测算方法,计算了除香港、澳门、台湾和西藏外中国30个省(市、自治区)1995-2010年的碳排放量,并选取碳排放总量、碳排放强度和人均碳排放量3个指标,运用多指标面板数据聚类法,将各省份划分为高、中和低碳排放区域:高碳排放区域包括河北、山西、内蒙古、辽宁、山东和宁夏,低碳排放区域包括北京、浙江、安徽、福建、江西、湖北、湖南、广东、广西、海南、重庆、四川、云南、陕西和青海,中碳排放区域包括天津、吉林、黑龙江、上海、江苏、河南、贵州、甘肃和新疆.分别对3类地区的人均碳排放量和人均GDP进行协整检验和回归分析,结果显示人均碳排放量和人均GDP存在长期协整关系且符合环境库兹涅茨曲线,高、中和低碳排放区域的理论曲线拐点分别为人均GDP 41 046、50 219和47 049元.今后一段时期内我国碳排放总量还将继续增长,但GDP的增长速度大于碳排放量的增长速度,碳排放强度会继续下降.     

氯胺消毒管网“三氮”与总氯变化的预测模型

为探讨氯胺消毒供水管网的水质问题,建立了一种试验规模的氯胺消毒供水管网水质模拟系统。基于质量守恒原理和双Monod方程建立了该系统的硝化与氯胺衰减动力学耦合模型,并通过试验对该模型进行了验证。模型中的部分参数采用非线性多项式回归方法进行估计。应用该模型确定了活性氨氧化菌(AOB)和亚硝酸盐氧化菌(NOB)的数量。该模型对管网模拟系统内氨氮、硝酸盐氮与总氯的预测值与实测值基本一致,但对亚硝酸盐氮的预测值与实测值存在较大偏差。     

驾驶行为模型的研究进展

驾驶员行为模型的研究对于预测和干预驾驶员的风险行为、设计相关的道路安全设施与车内设备,以及制定交通法律法规等具有重要的意义。为了解和掌握学术界关于驾驶行为模型的研究进展,搜集、筛选和归纳了1960—2010年被SCI数据库索引的相关文章,将驾驶行为模型分类为描述性模型、信息处理模型、动机模型、计划行为理论(TPB)和躯体标识假设,并对每种模型进行评述和总结,理清这些模型间的内在联系。研究发现,现有各模型只是从某个角度研究驾驶员行为的部分特征,而不能解释驾驶员的全部行为。今后应不断完善和整合各类模型,并借鉴心理学、生理学和行为科学等相关领域的理论、知识,使驾驶行为模型变得更为实用、有效。     

中国城市化水平省际差异的成因探析

1990～2000年中国城市化水平的省际差异已从原来的北高南低态势转变为目前东高西低的格局。这是由各地区不同的自然环境背景、人口分布与增长、经济发展水平,以及国家区域发展政策等因素的综合影响而形成的。对中国各省区1990年和2000年城市化水平与自然、人口、经济发展、工业化水平等四类12个指标的因子分析表明,区域城市化水平不仅与工业化水平或经济发展水平呈正相关,与人口密度、农业经济呈负相关,而且受工业化水平或经济发展水平的影响更为强烈。并且,随着社会经济发展和工业化推进,工业化因子对城市化的拉动效应在减弱,而综合经济发展对城市化的拉动效应在显著增强。     

长江干流地区区域发展与国家工业化

江河流域是人类文明的摇篮。作为四大文明古国之一,江河流域、特别是长江流域（干流）资源的开发对中国的持续发展至关重要。在农耕时期,受气候条件变化的影响,自盛唐中期以后（公元640年）长江流域（干流）就开始取代黄河流域成为国家最重要的人口集聚和社会生产场所。进入工业化进程以来,由于优越的地理位置和良好的人文素质,长江流域（干流）再次承担起推动国家现代经济发展主力引擎的职责,尽管这一发展经受过国家区域发展政策的不同影响。随着国家人地关系演进状态和社会经济整体发展环境的变化,21世纪长江流域（干流）在国家现代化进程中将承担起较以往更为重大的责任,其中以重化工制造业的发展最为重要。然而,要切实完成国家工业化和现代化所赋予的历史使命,长江流域（干流）地区未来的发展应首先处理好自身的发展环境问题,诸如上游地区土壤侵蚀、沿岸城市空气污染、地区能源供应短缺、城乡用地冲突等等。而所有这些问题的解决都依赖于一系列科学的区域发展政策。     

火灾烟气毒性的定量评价方法评述

火灾烟气毒性定量评价是毒理学研究的一个新兴领域.烟气毒性与建筑材料、燃烧条件、烟气毒物在建筑物内的传播规律及暴露时间有关,这些都是传统毒理学评价方法难以解决的问题.烟气毒性定量评价的目的是通过建立数学模型,以最少的动物试验,从宏观上更加定量化、系统化地评价和预测火灾烟气毒性.本文介绍了国外火灾烟气毒性定量评价的标准、烟气定量评价的数学模型,评述了这些模型的适用范围和优缺点,分析了火灾烟气毒性定量评价的发展方向.     

Numerical and field investigation of enhanced in situ denitrification in a shallow-zone well-to-well recirculation system

This study investigated efficiency of in situ enhanced biological denitrification of nitrate-contaminated groundwater which employs a well-to-well circulation in a shallow zone where oxygen might give an adverse affect on the denitrification processes. The numerical model developed for the efficiency test included sequential aerobic and nitrate-based respiration, multi-Monod kinetics of reactive components, growth and decay of biomass, and denitrification inhibition associated with the presence of oxygen. Moreover, reaction kinetics for production of toxic intermediates such as nitrite and nitrous oxide were also included in the model. The developed model was applied to the analysis of enhanced in situ denitrification using an injection/extraction well pair. To evaluate the relative remediation effectiveness, comparisons were made between a continuous fumarate injection test (CFIT) system and a pulsed fumarate injection test (PFIT) system, where both systems had the same total fumarate mass injected into the aquifer. The PFIT system was preferable to the CFIT system because of the high possibility of occurrence of clogging in the latter case at the injection well, with no other significant advantages found in either the CFIT or the PFIT system. Accordingly, this developed numerical model is useful to predict and evaluate an in situ bioremediation by denitrification in aquifers.     

Instream and offstream environmental conditions and stream biotic integrity: Importance of scale and site similarities for learning and prediction

Two different methods to predict biotic integrity were tested and compared in the present paper. The first one tries to predict the fish indices of biotic integrity (IBI) at the state or regional scale based on the most similar observations to a specific target site of interest using the simple to implement k-nearest neighbors (or kNN) method. Two different distance functions were considered to find the k-nearest neighbors: the Euclidean and the Mahalanobis. The second method was applied on the same datasets and consisted of a step-wise multiple regression. The two modeling approaches yielded similar results but kNN proved to be more time-efficient and very fast computationally for the given dataset sizes, which allowed applying a leave-one-out cross validation.In an attempt to reveal the importance of scale in the prediction of IBI, regression models were constructed at the state (or regional) scale and at the more refined cluster of sampling sites scale. Clusters of sites were extracted using Kohonen's self-organizing maps (SOM) followed by k-means clustering of the SOM neurons. Cluster-level regression models, constructed after site patterning, performed better in IBI prediction than global regression models constructed without any previous site patterning. The importance of identifying groups of sites with similar environmental characteristics affecting the IBI was revealed. The combined use of site patterning and regression modeling for IBI prediction also helped identifying important variables acting at the local scale which remain latent at the global scale.