Using Spatial Pattern to Quantify Relationship Between Samples, Surroundings, and Populations

The need for accurate carbon budgeting, climate change modelling, and sustainable resource management has lead to an increase in the number of large area forest monitoring programs. Large area forest monitoring programs often utilize field and remotely sensed data sources. Sampling, via field or photo plots, enables the collection of data with the desired level of categorical detail in a timely and efficient manner. When sampling, the aim is to collect representative detailed data enabling the statistical reporting upon the characteristics of larger areas. As a consequence, approaches for investigating how well sample data represent larger areas (i.e., the sample neighbourhood and the population) are desired. Presented in this communication is a quantitative approach for assessing the nature of sampled areas in relation to surrounding areas and the overall population of interest. Classified Landsat data is converted to forest/non-forest categories to provide a consistent and uniform data set over a 130,000 km² study region in central British Columbia, Canada. From this larger study area 322 2 × 2 km photo plots on a 20 × 20 km systematic grid are populated with composition and configuration information for comparison to non-sampled areas. Results indicate that typically, within the study area, the spatial pattern of forest within a photo plot is representative of the forest patterns found within primary and secondary neighbourhoods and over the entire population of the study. These methods have implications for understanding the nature of data used in monitoring programs worldwide. The ability to audit photo and field plot information promotes an increased understanding of the results developed from sampling and provides tools identifying locations of possible bias.     

Seasonal and Inter-Annual Variations in Methyl Mercury Concentrations in Zooplankton from Boreal Lakes Impacted by Deforestation or Natural Forest Fires

We compared the effects of natural and anthropogenic watershed disturbances on methyl mercury (MeHg) concentration in bulk zooplankton from boreal Shield lakes. MeHg in zooplankton was monitored for three years in nine lakes impacted by deforestation, in nine lakes impacted by wildfire, and in twenty lakes with undisturbed catchments. Lakes were sampled during spring, mid- and late summer. MeHg in zooplankton showed a seasonal trend: concentrations were the lowest in spring, then peaked in mid-summer and decreased in late summer. Over the three study years, MeHg concentrations observed in mid-summer in zooplankton from forest harvested lakes were significantly higher than in reference and fire-impacted lakes, whereas differences between these two groups of lakes were not significant. The pattern of distribution of MeHg in zooplankton during the different seasons paralleled that of dissolved organic carbon (DOC), which is known as a vector of Hg from watershed soils to lake water. Besides DOC, MeHg in zooplankton also showed a positive significant correlation with epilimnetic temperature and sulfate concentrations. An inter-annual decreasing trend in MeHg was observed in zooplankton from reference and fire-impacted lakes. In forest harvested lakes, however, MeHg concentrations remained higher and nearly constant over three years following the impact. Overall these results indicate that the MeHg pulse observed in zooplankton following deforestation by harvesting is relatively long-lived, and may have repercussions to the accumulation of MeHg along the food chain. Therefore, potential effects of deforestation on the Hg contamination of fish should be taken into account in forest management practices.     

Chemical composition of water conditioned by crowdedMoina macrocopa (Crustacea: Cladocera)

The chemical composition of water conditioned by colonies ofMoina macrocopa and involved in the regulation of their life cycle was analyzed in comparison with water samples from natural water bodies. Dechlorinated tap water was used as the control medium. The results showed that metabolism of crustaceans leads to an increase in the concentrations of phosphorus and nitrogen in all forms, the appearance of protein and carbohydrate fractions, and changes in the composition of lipid fractions in the water conditioned by their colonies. The contents of all organic components are very low, which makes their identification difficult. Concentrations of substances identified in the conditioned water do not exceed those occurring in nature.     

Evaluating the impact of uncertainty and variability on the value chain optimization of a forest biomass power plant using Monte Carlo Simulation

Mathematical programming models have been used to optimize the design and management of forest bioenergy supply chains. A deterministic mathematical model is beneficial for making optimum decisions; however, its applicability to real-world problems may be limited because it does not capture all the complexities, including uncertainties in the parameters, in the supply chain. In this paper, a combination of Monte Carlo Simulation and optimization model is used to evaluate the impact of uncertainty in biomass quality, availability and cost, and electricity prices on the supply chain of a forest biomass power plant. The optimization model is a deterministic mixed integer non-linear model with monthly time steps over a 1-year planning horizon. Variability in biomass quality, i.e. moisture content (MC) and higher heating value (HHV), based on the historical data of a real case study is studied in detail and fitted probability distributions are used in the model, while for electricity prices different scenarios are considered. The results show that the impact of variability in the MC on profit is higher than that of uncertainty in HHV. It is observed that the annual profit ranges between $13.3 million and $17.9 million in the presence of all possible uncertainties while its average is $15.5 million. Uncertainty in biomass availability and cost and electricity price results in the risks of having annual profit of less than $14 million and low monthly storage levels.     

复合链式结构下中国林业碳库系统测度模型构建

温室气体上升导致的全球气候变暖问题不容忽视,增加森林碳汇和木质林产品碳储是缓解温室效应的有效途径。根据森林碳汇功能与林产品碳储功能的关联理论与模型,推导和改进包括森林子碳库、土壤子碳库及木质林产品子碳库在内的林业碳库核算模型及方法,以实现目标碳从森林碳库向木质林产品碳库的过渡与转移。基于气候变化背景下森林-林产品产业链的发展现状,构建包括森林子碳库和林产品子碳库的复合一体化林业碳库模型,使之为中国林业碳库的计量与评价提供判据。首先,对包含森林子碳库和木质林产品子碳库在内的世界林业碳库的发展现状进行探讨,归纳和比较国内外主流的关联林业碳库评估方法模型,从而对中国林业碳库模型的构建提供理论背景支持和逻辑方法支撑。其次,分析现有中国林业碳库评估存在的优势和弊端,找出适合中国林业特点的国家碳库创新评估路径,运用政府间气候变化专门委员会指定的生产法的思路,通过分析目标碳在林产品产业链生产、加工等过程中的流入和支出,提出创新中国林业碳库的模型构想并对其系统内涵进行分析。最后,赋予中国林业碳库系统模型数学表达,分析其数理结构并进行逻辑演绎,在森林子碳库和木质林产品子碳库两个复合链式体系下构建中国林业碳库系统测度模型(ForestProducts Carbon Model/FPCM)。     

不同政策对农户农药施用行为的影响

农户不规范的施药行为是引发农产品质量安全风险最直接的原因,为规范农户的施药行为,政府颁布并实施了多种政策,但大多收效甚微。农户不规范的施药行为主要表现在过量使用高毒农药、施用过程中不按规定操作以及农药残留物的处理问题上,如何针对农户不同的施药行为制定相应的政策,以达到有效规范农户施药行为的效果,这是本文研究的主要目的。文章基于全国986个农户的调查数据,运用有序logistic模型,分别回归了不同政策对农户过量施用农药的行为、不遵守施药间隔期的行为以及在施药过程中不阅读标签说明的行为的影响程度,结果表明:强令禁止高毒农药、对违反农产品安全生产进行处罚以及对收购的农产品进行检测等命令控制政策对农户是否过量施用农药的行为具有较强的规范效应,但对农户在施药过程中是否阅读标签说明的规范效果不佳;农药施用技术培训、农产品安全生产宣传教育等宣传培训的政策能有效规范农户在施药前阅读标签说明,但对农户是否过量施用农药的影响不大;以市场为基础的激励政策对农户过量施用农药、阅读标签说明以及遵守间隔期均有显著的规范效果。由此提出,政府在实施命令控制政策的同时,应加强农产品安全知识的宣传力度,定期为农户提供农药施用技术培训;由于以市场为基础的激励政策能有效弥补命令控制政策的监管漏洞,从而更有效的规范农户的施药行为,因此要建立激励惩罚机制,对使用生物农药、施用有机肥等具有正外部性的投入行为进行补贴,对使用高污染、高毒农药的行为进行征税,充分发挥市场为基础的监管政策的有效性。     

REDD+ benefit sharing under models tested by pilot projects in Tanzania: Inputs towards developing national benefit-sharing mechanism models

This paper presents results of the assessment on benefit sharing and payment mechanisms tested by six non-governmental organizations (NGOs)-piloted Reducing Emissions from Deforestation and Forest Degradation (REDD+) initiatives in Tanzania. Results from the assessment indicate that models applied by most of the REDD+ pilot projects have provided most of decisions for the distribution of benefits to the communities through village general assemblies. Based on requirements of the tested models, national benefit-sharing mechanism models are proposed. Major attributes to be considered in the development of national benefit-sharing models should include: (i) ensuring that the existing government structure is not excluded to ensure sustainability; (ii) village general assembly is involved in determining the distribution of the benefits accrued; and (iii) transparency in handling the carbon finance is ensured. Models that are proposed for the national REDD+ benefit sharing apply to two forest management systems, namely Joint Forest Management (JFM) and Community Based Forest Management (CBFM). The paper recommends testing of the two proposed models to determine whether they could be useful in sharing benefits resulting from REDD+ in Tanzania.     

微波辐射对生物质热解过程的影响

自行设计加工了微波热重实验装置,研究了在微波辐射下菜籽粕热解过程特征及其产物产出规律.在此基础上,对比分析了菜籽粕微波热解与电热热解产物产出率之间的差异.结果发现,在菜籽粕微波热解过程中,半纤维素的反应区间为180 ～ 370℃,其转化率可以达到87.0％;纤维素的热解反应区间为370 ～ 550℃,其热解转化率32.8％.表明在微波作用下,纤维素的热稳定性远高于半纤维素.在菜籽粕的微波热解过程中,冷凝液的产生主要集中在100 ～400℃的温度范围内,热解得到的生物质油类主要是菜籽粕的半纤维素热解生成的.不凝气的产生主要集中在300 ～ 600℃的温度范围内,并且主要为纤维素与木质素的热解反应产生的.与电热方式相比,菜籽粕的微波热解升温速率较快,菜籽粕微波热解生物质炭的产出率较高,冷凝液产出率相对较低.     

中型污水处理厂中药物和个人护理品的分布与去除

为了解15种药物及个人护理用品(PPCPs)在中小型污水处理厂中的分布及其去除效果,采用液相色谱-串联质谱(LC-MS/MS)技术对3座A2/O工艺的污水处理厂水样进行分析研究。结果显示,除普萘洛尔、吉非罗平和吲哚美辛在3座中小型污水处理厂各个工艺单元中均未被检出外,其余12种目标化合物的检出频率在90%~100%之间。进水水样中PPCPs的平均检出浓度为2 285.4 ng/L,其中咖啡因(CF)的平均检出浓度最高为973.3 ng/L,酮洛芬(KP)的平均检出浓度次之为844.7 ng/L,两者之和占进水水样中PPCPs平均含量的79.5%,表明污水处理厂的主要污染物为CF和KP。3座污水处理厂对CF的去除效果最为显著,平均去除率为95.3%,对15种PPCPs总去除效率在39.3%~82.8%之间。     

盐效萃取法从电子产品清洗废液中回收异丙醇

用盐效萃取法从电子产品清洗废液中回收片丙醇,考察了碳酸钾水溶液与该清洗废液的质量比对脱水率的影响,测定了异丙醇-水-碳酸钾体系存40℃时的液液相平衡数据,用Pitzer理论和NRTL方程对液液相平衡数据进行了理论计算。结果表明：当质量分数为60．00％的碳酸钾水溶液与该废液的质晕比为2．00时,脱水率高达90．00％;将有机相进行精馏可得到质量分数为99．50％的异丙醇;计算值与实测值接近,水相和有机相的绝对平均偏差分别为0．62％和0．46％。