Estimating canopy closure density and above-ground tree biomass using partial least square methods in Chinese boreal forests

Boreal forests play an important role in global environment systems. Understanding boreal forest ecosystem structure and function requires accurate monitoring and estimating of forest canopy and biomass. We used partial least square regression （PLSR） models to relate forest parameters, i.e. canopy closure density and above ground tree biomass, to Landsat ETM＋ data. The established models were optimized according to the variable importance for projection （VIP） criterion and the bootstrap method, and their performance was compared using several statistical indices. All variables selected by the VIP criterion passed the bootstrap test （p〈0.05）. The simplified models without insignificant variables （VIP 〈1） performed as well as the full model but with less computation time. The relative root mean square error （RMSE%） was 29% for canopy closure density, and 58% for above ground tree biomass. We conclude that PLSR can be an effective method for estimating canopy closure density and above ground biomass.

Effect of Different Irrigation Methods on Dissolved Organic Carbon and Microbial Biomass Carbon in the Greenhouse Soil

The objective of this study was to investigate the contents and distribution of dissolved organic carbon （DOC） and microbial biomass carbon （MBC） at 0-100 cm soil depth under three irrigation treatments, viz., subsurface, drip and furrow irrigation in the greenhouse soil. The soil samples were collected at different depths （0-100 cm）, and the contents of soil total organic carbon （TOC）, DOC and MBC were analysed. The experiment was conducted for 10 yr, during which period the application of fertilizers and crop management practices were kept identical. The results showed that the contents of TOC, DOC and MBC were significantly affected by different irrigation regimes, decreased with the increase of soil depth. TOC at 0-10 and 80-100 cm soil depths followed the order of furrow irrigation 〉 subsurface irrigation 〉 drip irrigation, whereas at the depth of 10-80 cm followed the order of subsurface irrigation 〉 furrow irrigation 〉 drip irrigation. DOC and MBC contents at 0-100 cm soil depths followed the order of furrow irrigation 〉 drip irrigation 〉 subsurface irrigation, and drip irrigation 〉 furrow irrigation 〉 subsurface irrigation, respectively. The ratios of DOC and MBC to TOC accounted for 4.98-12.87% and 1.48-2.82%, respectively, which were the highest in the drip irrigation treatment, followed were in the furrow irrigation treatment, and the lowest in subsurface irrigation treatment. There were significant positive correlations among the contents of DOC, MBC and TOC in all irrigation treatments. The furrow irrigation facilitated the accumulation of TOC and DOC, while drip irrigation increased the MBC. The content of TOC and the ratios of DOC to TOC were the lowest in subsurface irrigation treatment.

Canopy cover or remotely sensed vegetation index,explanatory variables of above-ground biomass in an arid rangeland,Iran

Estimation of above-ground biomass is vital for understanding ecological processes. Since direct measurement of above-ground biomass is destructive, time consuming and labor intensive, canopy cover can be considered as a predictor if a significant correlation between the two variables exists. In this study, relationship between canopy cover and above-ground biomass was investigated by a general linear regression model. To do so, canopy cover and above-ground biomass were measured at 5 sub-life forms（defined as life forms grouped in the same height classes） using 380 quadrats, which is systematic-randomly laid out along a 10-km transect, during four sampling periods（May, June, August, and September） in an arid rangeland of Marjan, Iran. To reveal whether obtained canopy cover and above-ground biomass of different sampling periods can be lumped together or not, we applied a general linear model（GLM）. In this model, above-ground biomass was considered as a dependent or response variable, canopy cover as an independent covariate or predictor factor and sub-life forms as well as sampling periods as fixed factors. Moreover, we compared the estimated above-ground biomass derived from remotely sensed images of Landsat-8 using NDVI（normalized difference vegetation index）, after finding the best regression line between predictor（measured canopy cover in the field） and response variable（above-ground biomass） to test the robustness of the induced model. Results show that above-ground biomass（response variable） of all vegetative forms and periods can be accurately predicted by canopy cover（predictor）, although sub-life forms and sampling periods significantly affect the results. The best regression fit was found for short forbs in September and shrubs in May, June and August with R^2 values of 0.96, 0.93 and 0.91, respectively, whilst the least significant was found for short grasses in June, tall grasses in August and tall forbs in June with R^2 values of 0.71, 0.73 and 0.75, respectively. Even though the estimated above-ground biomass by NDVI is also convincing（R^2=0.57）, the canopy cover is a more reliable predictor of above-ground biomass due to the higher R^2 values（from 0.75 to 0.96）. We conclude that canopy cover can be regarded as a reliable predictor of above-ground biomass if sub-life forms and sampling periods（during growing season） are taken into account. Since,（1） plant canopy cover is not distinguishable by remotely sensed images at the sub-life form level, especially in sparse vegetation of arid and semi-arid regions, and（2） remotely sensed-based prediction of above-ground biomass shows a less significant relationship（R^2=0.57） than that of canopy cover（R^2 ranging from 0.75 to 0.96）, which suggests estimating of plant biomass by canopy cover instead of cut and weighting method is highly recommended. Furthermore, this fast, nondestructive and robust method that does not endanger rare species, gives a trustworthy prediction of above-ground biomass in arid rangelands.

Re-estimating the changes and ranges of forest biomass carbon in China during the past 40 years

Background: In recent decades the future of global forests has been a matter of increasing concern, particularly in relation to the threat of forest ecosystem responses under potential climate change. To the future predictions of these responses, the current forest biomass carbon storage(FCS) should first be clarified as much as possible,especially at national scales. However, few studies have introduced how to verify an FCS estimate by delimiting the reasonable ranges. This paper addresses an estimation of national FCS and its verification using two-step process to narrow the uncertainty. Our study focuses on a methodology for reducing the uncertainty resulted by converting from growing stock volume to above-and below-ground biomass(AB biomass), so as to eliminate the significant bias in national scale estimations.Methods: We recommend splitting the estimation into two parts, one part for stem and the other part for AB biomass to preclude possible significant bias. Our method estimates the stem biomass from volume and wood density(WD), and converts the AB biomass from stem biomass by using allometric relationships.Results: Based on the presented two-step process, the estimation of China’s FCS is performed as an example to explicate how to infer the ranges of national FCS. The experimental results demonstrate a national FCS estimation within the reasonable ranges(relative errors: + 4.46% and-4.44%), e.g., 5.6–6.1 PgC for China’s forest ecosystem at the beginning of the 2010 s. These ranges are less than 0.52 PgC for confirming each FCS estimate of different periods during the last 40 years. In addition, our results suggest the upper-limits by specifying a highly impractical value of WD(0.7 t·m-3) on the national scale. As a control reference, this value decides what estimate is impossible to achieve for the FCS estimates.Conclusions: Presented methodological analysis highlights the possibility to determine a range that the true value could be located in. The two-step process will help to verify national FCS and also to reduce uncertainty in related studies. While the true value of national FCS is immeasurable, our work should motivate future studies that explore new estimations to approach the true value by narrowing the uncertainty in FCS estimations on national and global scales.

基于光合法和生物量法分析塔里木沙漠公路防护林带碳汇估算差异性

【目的】研究基于光合法和生物量法分析塔里木沙漠公路防护林带碳汇估算差异性,为干旱荒漠区人工林管护和碳储量的评估提供科学依据。【方法】以新疆塔克拉玛干沙漠公路沿线人工防护林为研究对象,对比光合速率模型和生物量模型,估算防护林带3种主要建林植物各自光合速率及筛选最优生物量模型,进而估算其固碳能力及碳储量。【结果】3种植物在光合固碳模型中,单位叶面积固碳量差异显著,表现为梭梭>沙拐枣>柽柳;3种植物生物量最优模型均为幂函数,预测值与实测值回归决定系数在90%以上。光合固碳法估算得到的沙漠公路防护林带总固碳量为567431.68 t,生物量法估算的值为565083.75 t,2种方法估算得到的固碳量相当。【结论】3种植物固氮量差异显著(梭梭>沙拐枣>柽柳),模型效果精确可靠。

森林碳汇的碳资产价值评估方法

森林碳汇是实现碳中和的重要途径之一,如何评价其经济价值是重要的理论与现实问题。文章将碳资产价值理论引入森林碳汇领域,提出一种评估森林碳汇碳资产价值及分析其影响因素敏感性的方法,继而通过实例估计某森林碳汇项目碳资产价值的合理值,并对该项目碳资产价值的影响因素进行敏感性分析。研究表明:(1)森林碳汇具有较高的、可度量的碳资产价值;(2)碳资产理论能够为森林碳汇经济价值的评估和计量提供一种新的方法;(3)森林碳汇的经济价值主要取决于项目碳汇量和碳汇价格,与碳汇价格变动相比,项目碳汇量变动对森林碳汇碳资产价值具有更大的影响。

Heat Transfer within Direct Heating Integrated Moving Bed Torrefier by Method of Lines

This work deals with the determination of the temperature profile within a direct heating moving bed torrefier in order to determine its minimum column height. A thermal model based on eulerian-eulerian two-phase solid-gas theory was performed and solved with the method of lines. In addition, this study allows to investigate the effect of the biomass particle size on the minimum torrefier column height. This investigation was performed by changing, simultaneously, the diameter of particles and the minimum fluidization velocity of the bed. Then, the calculations were made for a counter-current torrefaction reactor of 30 cm in diameter and for 5 kg/h of the feed rate of raw sugarcane bagasse. Results show that the height of the reactor column must be at least 30 cm for that are 1 mm in diameter and 108 cm for particles that are 2 mm in diameter.

响应曲面法优化磁性生物质炭吸附水中汞离子特性研究

以玉米秸秆为原材料制备了生物质基炭,经共沉淀法成功制备了磁性生物质碳(Fe_(3)O_(4)@C)用于吸附水中的汞离子。采用控制变量法探究了4个单因素(溶液pH、温度、吸附剂投入量、吸附时间)对磁性生物质炭吸附Hg^(2+)效率的影响,发现pH值和投入量的影响程度较大,吸附时间次之,温度影响较小。借助上述实验结果,使用Design Expert软件,通过Box-Behnken设计汞吸附实验,成功构建了汞吸附效率与上述影响因素之间的回归模型;借助响应曲面法分析,精确确定了最佳的工艺条件。经平行实验验证,磁性生物质炭对水中Hg^(2+)的吸附效率可达到98.91%,经过吸附处理后的含汞废水达到可排放标准。

纤维素制备乙酰丙酸乙酯的研究进展

从纤维素原料入手,总结了合成乙酰丙酸乙酯的多种技术路线。通过技术路线优缺点对比,优选了纤维素直接醇解法,并探究了纤维素直接醇解法下乙酰丙酸乙酯形成的关键反应机理。以催化剂为切入点,指出了制备乙酰丙酸乙酯催化剂的研究进展,讨论了该领域研究存在的3个问题,特别强调了适用生物质种类的选择,展望了催化剂进一步研究的发展方向。

使用二类调查数据对森林碳储量评估及多因素预测

为及时且准确地估算森林碳储量,以湖南省怀化市靖州县排牙山国有林场为研究对象,使用森林资源二类调查数据,在分树种(组)及龄组的情况下,采用联合国政府间气候变化专门委员会(IPCC)材积源生物法估算了研究区林场碳储量、碳密度及其分布。运用空间代替时间法,筛选碳储量的影响因子并对其量化,验证多因素方法预测的准确性。结果表明:林场乔木林总碳储量为192 508.07 t,林分平均碳密度为34.46 t·hm^(-2)。在人工抚育的林分中通过用胸径、株数密度、树种组成多样性因素参数化的多因素方法对碳储量进行量化。其预测结果较精确,而在大面积天然林中使用该方法结果则存在一定误差。碳储量多因素预测模型可以在较大面积的人工林中进行碳储量预测。

生物质活性炭的制备与微结构特性调控研究进展

生物质是一种极具应用潜力的可再生资源,具有来源广泛、储量丰富和价格低廉等特点。以生物质为原料制备活性炭,是推进生物质材料资源化利用的重要途径。本文主要综述了以生物质为原料制备活性炭以及通过制备条件调控其比表面积、孔隙结构和表面性质等微结构特性的研究,重点阐述了生物质组成、炭化和活化条件(如炭化方式、活化剂种类、活化剂用量及反应停留时间等因素)对活性炭微结构特性的影响,并对常用活化剂(如水蒸气、CO_(2)、ZnCl_(2)、H_(3)PO_(4)、KOH等)对孔结构和表面性质的调控机理进行了详细探讨。最后对具有不同微结构特性活性炭的应用做了总结。

纤维素纳米晶的性质、制备及应用研究进展

纤维素是地球上含量最丰富的天然高分子聚合物,从生物质中提取物理结构和表面化学性质可控的纤维素纳米晶(CNC),是目前农业废弃物高值化和再利用的研究热点。本文综述了CNC的研究现状,概述了纳米纤维素的分类、理化特性,重点介绍了从生物质中提取CNC的方法,通过对CNC的几何尺寸和微观形貌进行对比分析,评价了酸解法、机械处理法、氧化法和酶解法等CNC制备方法的优缺点,以及系统地介绍了CNC在光电、生物医学、能源与环境、食品工业等领域的应用。最后,对当前CNC制备面临的挑战进行了总结并展望了其发展前景。

考虑电转氨和生物质废能转换的农村化工综合能源系统低碳调度方法

农村地区能源绿色转型发展是构建现代能源体系的重要组成部分,而引入化工类产业在促进乡村振兴的同时,也带来严重的污染问题。因此,研究农村化工生产脱碳及园区能源结构优化对实现“双碳”目标和农村现代化具有重要意义。该文提出一种考虑电转氨和生物质废能转换的农村化工园区综合能源系统低碳调度方法,通过利用富余可再生资源产生绿氨,考虑碳-氨耦合过程,将绿氨与碳捕集设备联合运行促进化工生产,同时利用生物质能替代燃煤发电,三者构建化工园区联合生产单元,进而降低园区碳排放及运行成本。首先,建立电转氨两阶段模型和生物质废能转换模型及其能流关系。其次,构建化工园区联合生产单元,分析其电、热、气以及碳能量耦合特性。再次,引入有机朗肯循环(organic Rankine cycle,ORC)余热发电和负荷侧综合需求响应,综合优化化工园区联合生产单元。最后,以化工园区运行总成本最低为目标,通过不同场景对比分析证明所提调度方法对化工园区有较好的改善作用,可为农村产业结构调整和能源转型提供理论支持。

浙江省竹林碳汇测算研究

采用生物量法测算浙江省竹林固碳量,运用能源活动二氧化碳排放测算法估算浙江省碳排放量,将二者进行对比分析竹林碳汇贡献。结果表明:1973—2021年浙江竹林固碳量从1820.64万t增长到3570.88万t,净增长量为1750.24万t,增长率高达96.13%,总体呈现增加的趋势,其中毛竹林为主要固碳林种;浙江省碳排放量呈现出稳定增长的趋势,增长率在2004—2021年有所下降;竹林固碳量与碳排放量呈现趋同的增长趋势,但竹林固碳量对于整体的碳排放量而言占比较小,固碳贡献小。为有效助力浙江省碳达峰、碳中和目标进程,提出应注重稳定竹林碳汇增量、切实巩固竹林碳汇发展,规范引导碳汇经营方案、合理提高竹林碳汇潜力,有效结合企业碳汇主体、科学管控企业排放数量,以此有效发挥竹林碳汇价值。

Determinants of Marketability for Organic Biomass Liquid Fertilizer from Human Waste in Da Nang City, Vietnam

Recently, 90 tons of human waste per day are collected from private residences, offices, and public facilities in Da Nang City. Meanwhile, farmers in this region have to allocate 10% - 20% of rice sales for purchasing chemical fertilizer. Therefore, it is essential to be adopted more inexpensive organic fertilizer. To deal with these problems, Japan International Cooperation Agency (JICA) has signed a contract with Da Nang city government about human waste treatment and production of organic biomass liquid fertilizer (OBLF) in 2015. The aims of this project are to promote the use of OBLF in farming and improve public awareness of environmental protection. 530 respondents were interviewed at Hoa Vang districts of Da Nang city, and data was analyzed by Contingent Valuation Method (CVM) under double bounded dichotomous choice approach. The results have revealed that 436 respondents (82%) agreed to use OBLF. The farmers’ WTP depends on factors including household income, experience in using organic fertilizer, awareness of environment and training of organic fertilizer in the past. The estimated price for OBLF was 94,856 VND (4.0 USD)/ton. The cost that farmers paid for OBLF was lower than that of current available chemical fertilizers in Da Nang city. This proves that marketability seems to be existed for OBLF product in Da Nang city. From these findings, the government should have policies to support and subsidize the farmers to encourage them to use OBLF in a large scale of cultivation. Furthermore, establishment of a market to consume the organic products harvested from cultivated areas using OBLF is also recommended.

适用于生物质直接耦合煤发电过程的温室气体核算方法优化

生物质与煤直接耦合燃烧发电作为降低火电行业碳排放的关键技术选择得到广泛关注,在双碳目标的推动下,准确量化生物质掺烧电力生产过程温室气体排放能有效提升发电行业碳排放数据的准确性与一致性,确保国内碳排放交易市场向更公平稳定的方向发展。介绍了国内外生物质耦合煤发电机组碳核算方法,提出生物质直接耦合发电机组温室气体核算边界、计算方法和核算参数的选取原则。结果表明:与现行核算法相比,基于生物质直接耦合煤发电的温室气体核算方法在核算边界、核算范围和计算方法上均有一定差异。对于核算边界,有必要新增燃料燃烧过程N_(2)O排放、新增设备资源带来的间接碳排放;针对常见生物质是否可视为零碳燃料进行评估,发现在各省份生物质的最佳经济运输半径内秸秆、城市垃圾、林类剩余物等常见生物质均达到温室气体减排要求,且合理运输范围(48 km)内均可视为零排放;在计算方法上,燃料消耗量建议根据碳排放量分层级选取测定方法,小比例掺烧时碳氧化率可直接选取缺省值99%,并且建议核算脱硫环节带来的碳排放,对循环流化床燃烧温度在1123 K以下的工况需要进行N_(2)O核算。

不同组分优先策略下的生物质三大素分离研究进展

木质纤维生物质结构组成复杂,导致原料利用率低、生产成本高。对生物质进行组分分离,是实现其全组分高效利用的前提。根据化学法分离生物质组分的特点,可将其归为3类:纤维素优先、木质素优先和半纤维素优先。本文介绍了3种优先策略的特点及其所包含的主要方法,重点综述了这些方法的最新进展,并对各方法的优劣势及组分分离效果进行了分析。最后,对未来生物质高效分离技术优化及生物精炼的研究重点提出了展望。

生物质基碳材料的制备及其在超级电容器中的研究进展

生物质基碳材料具有可再生性和灵活的微观结构可调性,作为高效、廉价的超级电容器电极材料受到越来越多的关注,但原生生物质衍生炭存在有低孔隙率、低比表面积和比电容不足等缺点。电极材料的比表面积、孔隙结构和导电性等都会影响超级电容器的储能性能,故如何制造具有高比电容、快速充放电且兼具一定柔性的电极材料成为了目前的研究重点。综述了超级电容器的类别、储能机理以及生物质基碳材料的制备方法和研究现状,分析了高质量负载电极的关键性能评价参数,并对其电化学性能影响因素进行了系统讨论,未来的发展趋势是将不同种类的储能器械集成复合型能源存储器械,以满足各领域需求。复合型的能源存储器械,大大提高了超级电容器的综合性能,因此研发高效、稳定的电能存储技术对于缓解能源短缺、减少环境污染和推动可持续发展具有重要的意义。

繁殖方式对杉木幼苗根系不同序级生物量、形态性状和碳氮含量的影响

[目的]探究繁殖方式对杉木幼苗根系不同序级生物量分配和生长的影响,分析不同繁殖方式培育的杉木幼苗在相似生长环境下的根系生长策略,为杉木幼苗个体根系生长发育研究提供科学依据。[方法]以种子萌发、组织培养和无性扦插等繁殖方式培育1年的杉木幼苗为研究对象,比较杉木幼苗根系不同序级生物量、形态性状和组织碳氮含量的差异,分析根系生物量与不同序级测定指标之间的内在关系,探究杉木幼苗因繁殖方式不同影响根系生长策略的差异性。[结果]1)不同繁殖方式培育的杉木幼苗根冠比差异达显著水平(P<0.05),表现为扦插苗>实生苗>组培苗。从同一序级生物量分配情况看,扦插苗1级根生物量[每株(0.68±0.13)g]分别是实生苗的4.31倍和组培苗的1.09倍;组培苗2~4级根生物量显著大于实生苗和扦插苗,分别为每株(1.19±0.21)g、(1.63±0.19)g和(1.82±0.27)g,组培苗和扦插苗根系不同序级生物量积累量更大。2)实生苗通过4级根生长促进1~2级根延伸,其4级根生物量、1~2级根比表面积显著大于组培苗和扦插苗(P<0.05);组培苗和扦插苗1级根平均直径和比根长显著大于实生苗,表现出通过直径增大和长度增加方式增强资源吸收效率的策略。3)实生苗、组培苗和扦插苗根系不同序级组织C和N含量存在差异,组培苗和扦插苗1~2级根N含量显著高于实生苗(P<0.05),3~4级根N含量显著低于实生苗;组培苗1~4级根C含量显著低于实生苗和扦插苗;组培苗和扦插苗1级根C/N显著小于实生苗。4)实生苗根系生物量与1级根上的组织N含量、2~3级根上的形态性状、4级根上的形态性状和组织C含量均具有显著关系(P<0.05);对于组培苗、扦插苗而言,根系生物量与1~2级根上的形态性状、3~4级根上的形态性状和组织C含量具有显著关系,体现出根系不同序级在形态构建与资源获取效率间存在的生态权衡关系。[结论]不同繁殖方式培育的杉木幼苗根系发育水平和生长策略存在明显差异,实生苗根系表现出探索寻觅土壤空间资源的生长策略;与之相比,组培苗和扦插苗根系形态构建特征和生长策略更具相似性,表现出增强对已占据空间资源吸收利用效率的生长策略。

2000—2030年多级流域尺度下重庆市林地景观格局碳储量变化

[目的]分析多级流域林地变化对碳储量变化的影响,预测未来多级流域碳储量变化趋势,为从流域角度的地区林地可持续发展以及碳中和政策实施提供一定的科学依据。[方法]以重庆市为研究区,运用PLUS模型、景观格局指数、生物量扩展因子法、灰色关联度等方法,分析2000—2030年多级流域尺度下重庆市林地与碳储量的时空动态变化,探究了自然情景发展下林地格局变化与碳储量的关联度。[结果](1)2000—2020年,林地面积增加3404.55 km~2,主要来自耕地转换;一级流域林地景观格局总体趋向于聚集化与规则化,破碎程度相对减少;二级流域内“区与群”的林地格局变化历史规律与未来趋势方面存在差异;(2)前20 a,林地碳储量呈现增加—减少趋势,总碳储量增加,其中一级流域洞庭湖水系碳储量增加最多,而二级流域碳储量增量高值区域由北向南移动;(3)预测2030年总碳储量增加,且与不规则指数具有较强关联度。[结论]不同流域尺度下,不同林地景观格局指数与碳储量的相关性存在差异,未来可以从流域角度出发制定有效措施,提高碳汇效益实现碳中和目标。