CDM Projects under the Kyoto Protocol: A Methodology for Sustainability Assessment – Experiences from South Africa and Uruguay

Under the Clean Development Mechanism (CDM) of the Kyoto Protocol, industrialised countries may finance greenhouse gases mitigation projects in developing countries. The Kyoto Protocol explicitly requires that the CDM shall assist developing countries to achieve sustainable development. However, a clear definition of sustainability for CDM projects is still debatable. MATA-CDM (Multi-Attributive Assessment of CDM Projects) is an approach that facilitates a quantitative assessment of potential projects regarding their contribution to sustainable development. This paper presents applications of MATA-CDM in two different countries. In South Africa, the application was done mainly for academic and demonstrative purposes, whereas in Uruguay it was implemented together with the responsible Designated National Authority (DNA). The work in both countries included the selection of sustainability criteria and measurable indicators. Experts weighted the criteria using personal interviews and a multi-stakeholder workshop. This method was applied to three potential CDM projects in South Africa and one in Uruguay. Results show that under the conditions of this study, the MATA-CDM approach yet fails to yield a perfect quantitative overall sustainability assessment of CDM projects but that several findings could be useful to further develop the approach with the aim to translate the vague term sustainable development to a mainstream project level. Valuable experience was in particular collected with different stakeholder processes to perform criteria weighting.     

一种更加安全的密码技术——量子密码

信息安全技术备受世人关注,由于现有的加密方法存在着很多弊端,人们将目光转向了量子密码。根据量子力学中的海森堡不确定性原理,任何窃听者都无法窃听量子密码通信中的信息而不被发现,笔者正是从量子不确定性基本原理出发来研究量子密码技术的,结合量子密码协议在通信网络中的应用来探讨了在量子通信过程中量子密钥生成、分发的详尽过程及量子密钥的分发协议在通信中应该遵循的原则,介绍了当前实验研究的进展,分析了量子密码研究存在的问题,并针对这些问题提出了一些建设性意见,最后对量子密码的发展前景和方向进行展望。     

无线传感网络在安全生产中的应用

本文详细介绍了无线传感器网络在安全生产中的应用结构、无线传感器节点的构成以及无线传感网络的数据模型,探讨了无线传感器网络在危险场所日常监测及应急救援场合应用的技术问题,分析了无线传感网络在实际应用中的关键技术。     

重大事故的应急救援预案编制技术

重大应急预案编制是安全生产的一项重要基础工作 ,对于提高应急救援能力 ,控制事故与灾害的恶化 ,保障人民安全具有重大意义。笔者从应急预案编制的技术层面上 ,论述了应急预案的基本框架和应急预案体系 ;认为该体系可以由 6个一级和 2 0个二级的核心要素构成。其中 ,应急策划是制定应急预案的技术基础 ,包括风险评价、资源分析和法律法规要求 3个二级要素 ;应急准备包括机构与职责、应急设备设施与物质、应急人员培训、预案演练、公众教育和互助协议 6个二级要素 ;应急响应是应急预案中核心的内容 ,包括现场指挥与控制等 1 1个二级要素。所提出的应急救援预案文件体系 ,建议一般按照四级文件形式的设想 ,应急预案的目标是提高整体应急能力 ;建议把应急预案的具体编制过程划分为 6个基本的步骤 ,对于预案编制与实施应实现持续改进的机制     

北京铁路局降雨量远程实时监测系统的研究与开发——系统结构及硬件

为北京铁路局各级防洪指挥部门在汛期能够实时掌握所辖铁路范围内的降雨量情况 ,实现主动防洪 ,并做好铁路抗洪抢险准备工作 ,确保汛期铁路行车安全 ,研究开发了北京铁路局“降雨量远程实时监测系统”。笔者介绍了系统的功能结构 ,重点分析了用于降雨量数据采集、传输的单片机雨量计、工业数据传输硬件设备技术 ,数据通讯协议以及网络通讯技术     

重大工业隐患的地域监控体系研究

系统地分析了重大工业危险源与事故隐患 ;研究了地域监控、预警、应急预案的体系建设以及隐患监控的新技术应用基础 ;提出了职业安全卫生监控体系中的工业危险源和隐患监控。笔者认为 :应该分为过程安全监控和安全目标监控两个层次     

2,3,7,8,-四氯苯噁英对NIH小鼠早期妊娠和生殖激素的影响

用不同剂量的2,3,7,8 四氯苯二英(2,3,7,8 tetrachlorodibenzopdioxin,TCDD)对小鼠胚胎附植数量和生长发育情况进行剂量反应评估,分析TCDD对假孕小鼠子宫蜕膜生长状况的影响以及比较胚胎种植前后染毒效果.所有样本采集血液,测定母体血清雌二醇和孕酮的浓度变化.结果表明,50和100ng·(kg·d)-1TCDD处理的孕鼠,胚胎附植数量明显减少(P<0 05),着床后胚胎出现发育迟缓,质量减轻(P<0 05);同等剂量TCDD处理的假孕小鼠,子宫蜕膜生长受到了极显著的抑制(P<0 01);种植前后染毒效果比较发现种植前期染毒的小鼠胚胎对TCDD更为敏感.母体血清雌二醇浓度随剂量和染毒时段有不同程度的升高,而孕酮浓度则极显著下降(P<0 01).由此表明低剂量TCDD可能通过对生殖激素的干扰,强烈影响NIH小鼠妊娠早期生殖生理状态和着床后胚胎的发育.实验同时证明小鼠也可作为早期妊娠毒物研究的供试动物,用以筛选动物和人类早期妊娠的有害化合物.     

大气细颗粒物中有机碳和元素碳监测方法对比

在线精确测量大气细颗粒物中有机碳(OC)和元素碳(EC)是研究碳质气溶胶形成和来源解析的重要科学基础.在线测定仪器选取不同的升温程序可能导致OC和EC观测数据差异,造成对研究结果的误判.对比分析在线OC/EC分析仪最常使用的RT-Quartz(R法)、NIOSH 5040(N法)和Fast-TC(F法)这3种温度协议下获得的OC和EC实际观测结果,结合北京空气污染程度,讨论了3种分析程序观测结果的异同.结果表明,3种分析程序对TC(TC=OC+EC)、OC和EC的测量均无显著性差异,但存在一定偏差.对TC的测量,R法比N法低5%,比F法高1%;对OC的测量,R法比N法低9%,比F法高1%;对EC的测量,R法比N法高20%,比F法低11%,其中R法温度协议在不同空气质量下对TC、OC和EC测量的变异系数均小于N法和F法.使用R法的在线分析与小流量PM2.5石英膜采样-离线分析所测定的TC、OC和EC结果的线性拟合斜率分别为1.21、1.14和1.35,R2TC、R2OC和R2EC分别为0.99、0.99和0.98;R法测定的EC浓度显著低于多角度吸收光度计(MAAP)测定的BC浓度.当BC8μg·m-3时,EC/BC为0.39,而当BC8μg·m-3,EC/BC为0.88.EC与BC变化趋势相近,但浓度值存在系统误差.     

Evaluating weather effects on interannual variation in net ecosystem productivity of a coastal temperate forest landscape: A model intercomparison

Forest productivity is strongly affected by seasonal weather patterns and by natural or anthropogenic disturbances. However weather effects on forest productivity are not currently represented in inventory-based models such as CBM-CFS3 used in national forest C accounting programs. To evaluate different approaches to modelling these effects, a model intercomparison was conducted among CBM-CFS3 and four process models (ecosys, CN-CLASS, Can-IBIS and 3PG) over a 2500 ha landscape in the Oyster River (OR) area of British Columbia, Canada. The process models used local weather data to simulate net primary productivity (NPP), net ecosystem productivity (NEP) and net biome productivity (NBP) from 1920 to 2005. Other inputs used by the process and inventory models were generated from soil, land cover and disturbance records. During a period of intense disturbance from 1928 to 1943, simulated NBP diverged considerably among the models. This divergence was attributed to differences among models in the sizes of detrital and humus C stocks in different soil layers to which a uniform set of soil C transformation coefficients was applied during disturbances. After the disturbance period, divergence in modelled NBP among models was much smaller, and attributed mainly to differences in simulated NPP caused by different approaches to modelling weather effects on productivity. In spite of these differences, age-detrended variation in annual NPP and NEP of closed canopy forest stands was negatively correlated with mean daily maximum air temperature during July-September (T_amax) in all process models (R² = 0.4-0.6), indicating that these correlations were robust. The negative correlation between T_amax and NEP was attributed to different processes in different models, which were tested by comparing CO₂ fluxes from these models with those measured by eddy covariance (EC) under contrasting air temperatures (T_a). The general agreement in sensitivity of annual NPP to T_amax among the process models led to the development of a generalized algorithm for weather effects on NPP of coastal temperate coniferous forests for use in inventory-based models such as CBM-CFS3: NPP′ = NPP − 57.1 (T_amax − 18.6), where NPP and NPP′ are the current and temperature-adjusted annual NPP estimates from the inventory-based model, 18.6 is the long-term mean daily maximum air temperature during July-September, and T_amax is the mean value for the current year. Our analysis indicated that the sensitivity of NPP to T_amax was nonlinear, so that this algorithm should not be extrapolated beyond the conditions of this study. However the process-based methodology to estimate weather effects on NPP and NEP developed in this study is widely applicable to other forest types and may be adopted for other inventory based forest carbon cycle models.