Choosing a Food Future: Differentiating Among Alternative Food Options

This article examines the diversity of food networks that fit within the alternative food system of the United States. While farmers’ markets, community supported agriculture schemes, and corporate organic food markets all fit within the alternative food system, they differ greatly in the conventions and beliefs that they represent. The alternative food system has divided into two movements: corporate, weak alternative food networks; and local, strong alternative food networks. The weak corporate version focuses on protecting the environment; however, it neglects issues concerning labor standards, animal welfare, rural communities, small-scale farmers, and human health. Local, strong alternative food networks not only assure environmental protection, but they also address the issues that weak alternatives neglect. Using three case studies from the Washington, D.C. metro area, the author explains that strong alternative food networks are better suited to create social and political change because they challenge the foundations of the conventional food system: standardized and generic products, price-based competition, consolidated power, and global scale. To affect true social and political change in the United States, the author recommends supporting strong alternative food networks by creating the requisite cultural and political space for them to succeed.     

边坡变形时序非线性判定及混沌预测研究

以探讨边坡变形性质及混沌预测可行性为目的,基于混沌理论利用相空间重构技术对其变形时间序列进行混沌特征判定,试验显示变形系统具有混沌特性,可用混沌相关理论进行研究;基于混沌相空间重构技术,笔者构建了多种混沌预测模型进行混沌预计研究,分析各类模型的工程实际应用效果;针对单次监测时序预测精度较低的问题,提出累加时序预测方案,训练结果显示,短期预测精度变形累计值基本控制在5%以内,高程值预测相对误差均低于1%,预测精度较高,可以用于工程实际。     

Scenario-visualization for the assessment of perceived green space qualities at the urban-rural fringe

The provision of green space is increasingly being perceived as an important factor for quality of life. However, green spaces often face high developmental pressure. The main objective of this study is to investigate a prospective approach to green space planning by combining three-dimensional (3D) visualization of green space scenarios and survey techniques to facilitate improved participation of the public. Aside from the ‘Status quo’, scenarios ‘Agriculture’, ‘Recreation’, ‘Nature conservation’ and ‘Wind turbines’ are visualized in three dimensions. In order to test responses, a survey was conducted both in print format and on the Internet. Overall, 49 different visualizations that belong to one of the scenarios were available in the survey and were rated according to the perceived esthetic, recreational and ecological values.The highest rated scenes include vegetation elements such as meadows with orchards, single trees, shrubs or forest. The least attractive scenes are those where buildings are highly dominant or where there are no vegetation elements.Based on the ratings for the individual images and on the corresponding scenarios, our study shows that there is high potential for improving the existing landscape. All suggested changes are either rated about equal to or considerably higher than the status quo, with the scenario ‘Nature conservation’ receiving the highest scores.     

The importance of differentiating urban and rural phenomena in examining the unequal distribution of locally desirable land

Previous research addressing the unequal distribution of locally desirable land (LDL) has mainly ignored their associated environments (i.e., rural or urban). However, this study proposed a new framework that treats rural and urban regions separately. In rural areas, the LDLs included all public lands. In urbanized areas, the LDLs were defined as green open spaces. Potential inequities in the distribution of LDL were assessed with respect to socioeconomic characteristics of residents in the State of Georgia. Using US Census Bureau Data (2000), Census Block Groups (CBGs) adjacent to LDLs were compared to CBGs outside of LDLs on four socioeconomic variables (per capita income, occupation, education, and race) in urban, suburban and rural environments. Results showed that CBGs adjacent to LDLs were composed of statistically significant upper-class communities containing fewer blue-collar workers, more whites, and higher income and higher educated people in rural, suburban and urban areas.     

Thoughts concerning the economic valuation of landscapes

The incorporation of economic thinking into the valuation of landscapes is still relatively new. It is an approach that yields valuable new insights and can help with prioritizing the use of scarce resources to improve and/or preserve landscapes. This paper explores and discusses the uses and limitations of economic valuation of landscapes from market failure, policy process, and theoretical and philosophical perspectives.     

山水林田湖草生命共同体的科学认知、路径及制度体系保障

山水林田湖草生命共同体是对人与自然和谐统一关系的新认知,是生态文明理论的重要组成部分。以建立一个山水林田湖草生命共同体的研究范式为目的,系统剖析了山水林田湖草生命共同体理论与应用在基础探索、快速发展和多元繁荣三个阶段的研究重点与特征;再次审视了山水林田湖草生命共同体的内涵、阐明了概念新认知、基本特征、人与生命共同体关系;最后提出面向山水林田湖草生命共同体的“问题—目标—时空策略—目的”的实施路径,及构建以自然资源监测监管体系、自然资源资产产权体系、国土空间规划体系、国土空间用途管制体系、国土空间生态修复体系、法律法规体系等为主的制度体系,进而提升其科学性和实用性,为构建国土空间治理体系及治理能力现代化提供决策支撑。     

不同天气型下武汉城市圈PM2.5污染及大气层结特征分析

利用2015—2019年PM_2.5和气象要素观测资料、NCEP和ERA5再分析资料,分析不同天气型下武汉城市圈PM_2.5区域污染时空分布、天气尺度环流和大气层结特征.结果表明,城市圈污染以武汉为中心,多为轻度-中度污染,西部重于东部.造成武汉城市圈区域污染增长的天气形势包括4类,分别为冷高压底前部型、高压后部型、均压场型和低压倒槽型.4类污染天气型均有较低的混合层高度和地表通风系数,且边界层存在弱下沉运动和逆温,抑制污染垂直扩散.但气象要素影响PM_2.5污染的机理各异：冷高压底前部型主要为大气压梯度引导偏北大风带来污染物远程输送,边界层冷平流导致低温、锋面逆温和浅薄高湿层(65%～80%),强输入性污染配合吸湿性累积增长造成严重污染,逆温厚度对PM_2.5增幅作用明显;低压倒槽型东南风输入污染弱,但高温、低压引起气流辐合导致本地污染汇积,边界层暖平流带来平流逆温和深厚湿层(1000～750 hPa),逆温层底高偏低、厚度偏厚,促进污染物在近地面吸湿增长;高压后部和均压场型均为浅薄湿层(1000～975...     

核化危害源项反演技术现状及研究展望

源项反演对缓解和遏制核化危害源、精准预测核化危害时空传输和扩散情况、辅助作战行动和保障决策等具有十分重要的意义.本文从源项反演应用平台和源项反演关键算法(包括欧拉方法、拉格朗日方法、深度学习等)两个方面,对国内外核化危害源项反演技术的现状和二者间的差距进行了总结与分析.研究指出,利用深度学习提高反演精度和速率、从单污染...     

顶空固相微萃取-气相色谱法测定水中氯苯类化合物

采用顶空固相微萃取（HS －SPME）技术萃取水中6种氯苯类化合物,全面分析对目标物萃取效率的影响因素,并确定萃取试验的最佳条件。用顶空固相微萃取联合气相色谱法（HS －SPME －GC）测定水中6种氯苯类化合物,方法在0.500 ng／L～2.00×10^5 ng／L范围内线性良好,检出限为0.05 ng／L ～2000 ng／L,空白样品加标回收率为69.8％～121％, RSD为4.8％～18.3％。用该方法测定实际水样,平行双样的相对偏差低于20％。     

基于Landsat 8遥感数据的天津市地表温度反演

以Landsat 8遥感数据为数据源,进行天津市地表温度反演研究。首先采用单通道算法反演地表温度,并利用均值标准差法进行温度分级。然后建立不同温度等级面积比例的估算模型。再通过随机样点,从不同温度等级和土地覆盖类型2个角度,分别建立并比较不同类样点的地表温度与各指数的拟合模型。结果表明:次高温区域面积比例与人口密度、人均GDP都具有较高的决定系数;地表温度与NDVI、BAEM的二元线性回归决定系数高于地表温度与单一指数的决定系数;将样点分类后,低温点与MNDBI的决定系数高于其他温度等级样点,水域和植被样点与各种指数的决定系数高于其他地物类型样点。