SELECTED CHALLENGES IN RUNOFF GENERATION RESEARCH IN FORESTS FROM THE HILLSLOPE TO HEADWATER DRAINAGE BASIN SCALE1

ABSTRACT: When faced with practical forest land management issues such as the impacts of logging or forest conversion to other land uses, planners ideally require a comprehensive understanding of within drainage basin hydrological processes to determine the most vulnerable areas to increased storm runoff and erosion. Land managers in particular need to know the source areas and magnitude of inputs to the storm hydrograph, in terms of water quantity, sediment and solute transport; and the routing of such hydrographs from headwater to larger drainage basins. The latter includes an overall assessment at various scales of the impacts of forest disturbance and conversion on the water balance. This paper will focus on runoff generation in terms of identifying the various pathways and source areas. Such aspects will be linked with the need for a more comprehensive effort towards the field testing of so-called ‘physically based’ models of runoff generation. Some of the controversial issues arising from the difficulties in reconciling results from hydrochemical investigations with complementary hydrometric studies will be highlighted. Subsequently, attention will be given to topographic-wetness models, which have promising applications in forestland management. In addition, alternative simple models for application at the catchment scale will be assessed. The latter is in recognition that at smaller scales, heterogeneity both in time and space of soil hydraulic properties demand a greater number of parameters in modelling. Such considerations can even prove an obstacle in terms of the confident application of ‘physically based’ models.     

城市生活垃圾填埋产沼的模拟实验

通过城市生活垃圾的填埋降解模拟实验，研究了不同温度、不同垃圾成份对垃圾降解及填埋气产生过程的影响。实验结果表明：增加温度及在填埋垃圾中添加污泥，可加快填埋垃圾的降解与填埋气的产生，实验期间累计产气量分别比对照组提高2．04和3．4倍；以厨余垃圾为主的样品垃圾，其产气过程的显著特征是产气速率衰减较快，这与国外文献报道有较大差异。对我国城市生活垃圾，填埋封场后产气量的快速衰减，是填埋气利用规划设计应该考虑的问题。     

构建限制性条件下微生物群体生长模型时的问题

Logistic生长模型在表征营养限制性生长条件下微生物群体生长时,遇到了种种困难．该模型未能明确给出微生物群体生长的“延迟期”和“代时”两个重要生长动力学参数,也忽视了方程中参数“r”应为平均生长速率,且不具有内禀生长率性质等诸多生物学特点．采用E．coli ATCC31343,37℃液体摇瓶培养下获得的实验数据,证实了Logistic模型存在的上述局限性．通过对E．coli以葡萄糖和山梨醇共作碳源时,表现出的“二峰生长”曲线与用Logistic方程拟合结果的比较,表明适合度分析（goodness—fit test）不能作为模型是否适合的唯一判据．并对构建微生物群体生长模型的策略进行了讨论．图5参31     

控制燃油锅炉运行中NOx 生成的技术研究

分析燃油锅炉运行中NOx产生的机理，探讨影响其生成的因素，研究抑制其生成和排放的燃烧技术：低氧燃烧、掺水燃烧、空气分级燃烧和废气循环燃烧等。结合实验研究结果，重点分析空气分级燃烧和废气循环燃烧对油燃烧中燃料氮转化和氮氧化物生成的影响，并介绍一种新型低氮氧化物排放的燃油技术——预蒸发燃烧技术。     

不同栽植代数杉木林凋落物特性的比较

在全国杉木中心产区福建建瓯 ,选择不同栽植代数、不同发育阶段的杉木人工林 ,进行凋落物特性的比较研究 .结果表明 :不同栽植代数杉木林凋落物年产量有显著差异 ,表现出随栽植代数增加而减少的趋势 .不同栽植代数杉木林的凋落物组成、凋落动态及其分解速率差异不明显 .但杉木刚掉落凋落物与地面凋落物的分解状况存在明显差异 ,刚掉落凋落物的分解速率明显低于地面凋落物 ,而且刚掉落杉木凋落物的周转期高于地面凋落物 ,因此在杉木林地上随意选取凋落物样品进行凋落物分解试验 ,不能反映整个林分凋落物的分解状况 .图 2表 5参 2 4     

濮阳市VOCs污染特征及其臭氧生成潜势分析

以京津冀及周边"2+26"城市之一濮阳为例,对环境空气VOCs的污染特征及其臭氧生成潜势进行分析。研究表明:濮阳市的臭氧生成对VOCs浓度比较敏感,VOCs各组分的平均浓度表现为含氧有机物烷烃芳香烃烯烃炔烃,乙烯和丙酮是浓度水平最高的2种物质,对VOCs浓度贡献分别为11. 3%和10. 5%; VOCs各组分的臭氧生成潜势量表现为含氧有机物芳香烃烯烃烷烃炔烃。OFP排名前三位的是乙醛、乙烯和甲苯,其对臭氧生成的贡献量超过了总量的三分之一;制定关键物质选取原则,筛选出濮阳市VOCs的关键种类; VOCs及其关键种类与气温和风向存在一定的相关关系;濮阳市VOCs关键种类的污染主要来源于化石燃料燃烧、石油化工生产和溶剂涂料挥发等工业生产和机动车尾气排放等。     

北京城市塑料垃圾年产量的模拟预测及其影响因素分析

揭示城市塑料垃圾年产量及影响因素、预测其发展趋势对于城市生活垃圾收集系统的优化、处理技术的合理选择和降低环境影响具有重要意义.本研究基于1989年以来北京塑料垃圾占比、城市生活垃圾产量数据和社会经济数据,利用赤池信息量准则（AIC）和灰关联度法研究了北京城市塑料垃圾占比的年变化趋势和城市塑料垃圾年产量的主要影响因素.通过多元线性回归模型（MLR）、灰色系统模型GM（1,1）和BP神经网络模型对北京城市塑料垃圾年产量进行了模拟预测.结果表明,北京城市塑料垃圾占比由1989年的1.88%,增加到2012年的14.87%.基于AIC准则预测2013—2050年北京城市塑料垃圾占比增长趋势较平缓、稳定在14%~19%之间.2000—2012年北京市城市塑料垃圾年产量由40.2×10⁴ t增加到121.1×10⁴ t,年增长15.5%.人均可支配收入是影响北京城市塑料垃圾年产量的最大社会经济因素,而常住人口的影响较低.BP神经网络是模拟预测北京城市塑料垃圾产量的最佳模型,其模拟预测结果表明：2013年后北京市塑料垃圾年产量随时间呈不规则的非线性增长趋势,到2025、2035、2050年北京城市塑料垃圾产量将分别达到335、488和859×10⁴ t,将对北京城市生活垃圾处理处置与防控管理带来巨大挑战.     

基于离散模型的落叶资源利用方案评价

结合社会调查,对落叶资源利用的几种方案进行评估分析,运用离散模型分析得到影响资源利用方案的各因素的比重,找到最优的落叶资源利用方案。以武汉市为例,分析表明将落叶进行生物质发电能有效利用落叶资源且资源利用率高,能为我国环保事业做出贡献。     

The role of automated feedback in training and retaining biological recorders for citizen science

The rapid rise of citizen science, with lay people forming often extensive biodiversity sensor networks, is seen as a solution to the mismatch between data demand and supply while simultaneously engaging citizens with environmental topics. However, citizen science recording schemes require careful consideration of how to motivate, train, and retain volunteers. We evaluated a novel computing science framework that allowed for the automated generation of feedback to citizen scientists using natural language generation (NLG) technology. We worked with a photo‐based citizen science program in which users also volunteer species identification aided by an online key. Feedback is provided after photo (and identification) submission and is aimed to improve volunteer species identification skills and to enhance volunteer experience and retention. To assess the utility of NLG feedback, we conducted two experiments with novices to assess short‐term (single session) and longer‐term (5 sessions in 2 months) learning, respectively. Participants identified a specimen in a series of photos. One group received only the correct answer after each identification, and the other group received the correct answer and NLG feedback explaining reasons for misidentification and highlighting key features that facilitate correct identification. We then developed an identification training tool with NLG feedback as part of the citizen science program BeeWatch and analyzed learning by users. Finally, we implemented NLG feedback in the live program and evaluated this by randomly allocating all BeeWatch users to treatment groups that received different types of feedback upon identification submission. After 6 months separate surveys were sent out to assess whether views on the citizen science program and its feedback differed among the groups. Identification accuracy and retention of novices were higher for those who received automated feedback than for those who received only confirmation of the correct identification without explanation. The value of NLG feedback in the live program, captured through questionnaires and evaluation of the online photo‐based training tool, likewise showed that the automated generation of informative feedback fostered learning and volunteer engagement and thus paves the way for productive and long‐lived citizen science projects.     

绿色导向下的光伏产业环境污染控制进展研究

光伏发电技术具有环保和节约能源的特点,在光伏组件废弃后和太阳能电池的原料生产环节,会产生一定程度的环境污染.对太阳能电池废弃物进行资源化回收处理,积极研发新型电池和新材料,可以有效控制污染.目前对光伏废弃物进行资源化的方法主要有:热解法,无机酸溶解法,有机溶剂溶解法,化学蚀刻等;薄膜型光伏电池和聚合物光伏新材料的研究也取得了相应进展,拥有较好的发展前景.