环境保护视角下的食物里程研究

随着全球环境问题日趋严峻,可持续发展越来越重要,食品与环境如何相互影响,食品生产和消费过程中的碳减排问题,日益受到人们的广泛关注。"食物里程"通过考察食品从生产到餐桌的距离,量化食品生产、运输、消费过程的碳排放,考察食品对环境的影响,该指标得到政府、食品加工厂、贸易商、消费者、环保主义者和学者普遍关注。本文从食物里程的内涵着手,系统阐述食物里程概念的形成与发展,介绍食物里程的两种计算方法,包括投入产出-生命周期法和供应链中的能源使用等,食物里程涉及到碳排放的三个公认的评估标准:1PAS 2050,联合国气候变化框架公约清洁发展机制,ISO/CD 14067。在此基础上,本文从食物里程的价值角度、消费者角度及国际贸易角度对国内外相关研究进行系统的归纳与总结,提出未来的研究方向主要在于合理界定食物里程的内涵,科学利用食物里程改变生产和消费方式,从而改善环境,防止食物里程成为新的国际贸易壁垒。     

产业结构变动对中国碳排放的影响

采用LMDI分解方法,对中国1996-2009年的碳排放进行分解,定量分析产业结构变动对碳排放变动的影响。在此基础上,依据对未来中国产业结构变动的预测,估算了2020年之前产业结构变动对中国碳减排的贡献。基本情况是,1996-2009年中国碳排放增长464 678万t,其中,经济总量效应531 337万t,产业结构效应49 887万t,能源消费强度效应-223 940万t,能源消费结构效应107 395万t,诸因素对碳排放增长的贡献度分别为114.3%,10.7%,-48.2%和23.1%。产业结构变动驱动了碳排放增长,尽管它不是最主要因素。进一步研究发现,高耗能产业上升或下降1个百分点所对应的CO2排放量增加或减少2.2-2.9亿t。依据对高耗能产业结构变动值的预测,到2020年,产业结构变动效应约为-5亿t,占期间碳排放增量的-15%。这表明,与此前产业结构变动导致碳排放量增加情形相反,未来产业结构变动将有助于减少碳排放。     

基于河流生态系统服务功能的皂市水利枢纽工程的生态补偿标准

生态补偿标准核算是生态补偿研究的核心问题之一。运用市场价值法、机会成本法、影子工程法、影子价格法、防护费用法等评估方法,以皂市水利枢纽工程为例,构建了5个生态补偿主体受益评估模型和8个生态补偿对象受损评估模型,从河流生态系统服务功能视角对皂市水利枢纽工程生态补偿标准进行了评估。结果表明：皂市水利枢纽工程建设的生态补偿标准为0676 0×108元/a,中央政府和地方政府、水电开发业主是主要的生态补偿主体,其承担的生态补偿额分别占总生态补偿额的6805%和2658%;移民和河流生态系统本身是主要的生态补偿对象,其获得的生态补偿额分别占总生态补偿额的7574%和1695%     

Lessons from the 2006 Louisiana health and population survey

The 2005 hurricane season caused extensive damage and induced a mass migration of approximately 1.1 million people from southern Louisiana in the United States. Current and accurate estimates of population size and demographics and an assessment of the critical needs for public services were required to guide recovery efforts. Since forecasts using pre-hurricane data may produce inaccurate estimates of the post-hurricane population, a household survey in 18 hurricane-affected parishes was conducted to provide timely and credible information on the size of these populations, their demographics and their condition. This paper describes the methods used, the challenges encountered, and the key factors for successful implementation. This post-disaster survey was unique because it identified the needs of the people in the affected parishes and quantified the number of people with these needs. Consequently, this survey established new population and health indicator baselines that otherwise would have not been available to guide the relief and recovery efforts in southern Louisiana.     

Evaluating water quality investments using cost utility analysis

This study borrows concepts from healthcare economics and uses cost utility analysis (CUA) to select an optimum portfolio of water quality enhancement projects in Perth, Western Australia. In CUA, costs are handled via standard discounted cash flow analysis, but the benefits, being intangible, are measured with a utility score. Our novel methodology combines CUA with a binary combinatorial optimisation solver, known as a 'knapsack algorithm', to identify the optimum portfolio of projects. We show how water quality projects can be selected to maximise an aggregate utility score while not exceeding a budget constraint. Our CUA model applies compromise programming (CP) to measure utility over multiple attributes in different units. CUA is shown to provide a transparent and analytically robust method to maximise benefits from water quality remediation investments under a constrained budget.     

AutoRAPID: A Model for Prompt Streamflow Estimation and Flood Inundation Mapping over Regional to Continental Extents

This article couples two existing models to quickly generate flow and flood‐inundation estimates at high resolutions over large spatial extents for use in emergency response situations. Input data are gridded runoff values from a climate model, which are used by the Routing Application for Parallel computatIon of Discharge (RAPID) model to simulate flow rates within a vector river network. Peak flows in each river reach are then supplied to the AutoRoute model, which produces raster flood inundation maps. The coupled tool (AutoRAPID) is tested for the June 2008 floods in the Midwest and the April‐June 2011 floods in the Mississippi Delta. RAPID was implemented from 2005 to 2014 for the entire Mississippi River Basin (1.2 million river reaches) in approximately 45 min. Discretizing a 230,000‐km² area in the Midwest and a 109,500‐km² area in the Mississippi Delta into thirty‐nine 1° by 1° tiles, AutoRoute simulated a high‐resolution (~10 m) flood inundation map in 20 min for each tile. The hydrographs simulated by RAPID are found to perform better in reaches without influences from unrepresented dams and without backwater effects. Flood inundation maps using the RAPID peak flows vary in accuracy with F‐statistic values between 38.1 and 90.9%. Better performance is observed in regions with more accurate peak flows from RAPID and moderate to high topographic relief.     

空气中超细颗粒物检测方法的研究进展

颗粒物的健康损害效应已得到广泛的关注。尤其近年来,国内外学者们针对PM2.5等大颗粒开展了大量的人群流行病学和毒理学研究,健康损害效应的因果关系得到基本确认。然而比PM2.5粒径更小但数量更多的超细颗粒物(UFPs),其暴露特征及对健康影响的贡献值尚不清楚,缺乏统一的检测方法及策略是影响其健康评估的关键因素。因此,本文根据国内外文献,综述了目前超细颗粒物的检测方法、仪器及策略,总结了超细颗粒物评价方法的影响因素及其存在的不足,为超细颗粒物检测方法的进一步研究提供建议和帮助。     

Developing green infrastructure ‘thinking’: devising and applying an interactive group-based methodology for practitioners

Recent years have witnessed a wave of interest in the concept of green infrastructure (GI) as a means of applying an ecosystem approach to spatial planning practice; however, more limited attention has been paid to decision-making processes or tools to enhance GI within spatial plans and guidance. We address this deficit by reporting on the development and application of an interactive group-based methodology to enhance GI ‘thinking’ and interdisciplinary collaboration, drawing on the literature on the sociology of interactions. Our findings suggest that a game-based approach to GI problem-solving was successful in breaking down professional barriers by creating an informal learning arena, providing an enabling opportunity for participants to solve problems in an iterative, non-linear style to develop principles for action with transferability to ongoing plan formation. This style of problem-solving was characterised by shifting norms and routines of interaction, leading to problem re-framing and a search for alternative solutions.     

Identifying Urban Features from LiDAR for a High‐Resolution Urban Hydrologic Model

Light Detection and Ranging (LiDAR), is relatively inexpensive, provides high spatial resolution sampling at great accuracy, and can be used to generate surface terrain and land cover datasets for urban areas. These datasets are used to develop high‐resolution hydrologic models necessary to resolve complex drainage networks in urban areas. This work develops a five‐step algorithm to generate indicator fields for tree canopies, buildings, and artificial structures using Geographic Resources Analysis Support System (GRASS‐GIS), and a common computing language, Matrix Laboratory. The 54 km² study area in Parker, Colorado consists of twenty‐four 1,500 × 1,500 m LiDAR subsets at 1 m resolution with varying degrees of urbanization. The algorithm correctly identifies 96% of the artificial structures within the study area; however, application success is dependent upon urban extent. Urban land use fractions below 0.2 experienced an increase in falsely identified building locations. ParFlow, a three‐dimensional, grid‐based hydrological model, uses these building and artificial structure indicator fields and digital elevation model for a hydrologic simulation. The simulation successfully develops the complex drainage network and simulates overland flow on the impervious surfaces (i.e., along the gutters and off rooftops) made possible through this spatial analysis process.