Uncertainty in life cycle costing for long-range infrastructure. Part II: guidance and suitability of applied methods to address uncertainty

Life cycle costing (LCC) is the state-of-the-art method to economically evaluate long-term projects over their life spans. However, uncertainty in long-range planning raises concerns about LCC results. In Part I of this series, we developed a holistic framework of the different types of uncertainty in infrastructure LCCs. We also collected methods to address these uncertainties. The aim of Part II is to evaluate the suitability of methods to cope with uncertainty in LCC. Part I addressed two research gaps. It presented a systematic collection of uncertainties and methods in LCC and, furthermore, provided a holistic categorization of both. However, Part I also raised new issues. First, a combined analysis of sources and methods is still outstanding. Such an investigation would reveal the suitability of different methods to address a certain type of uncertainty. Second, what has not been assessed so far is what types of uncertainty are insufficiently addressed in LCC. This would be a feature to improve accuracy of LCC results within LCC, by suggesting options to better cope with uncertainty. To address these research gaps, we conducted a systematic literature review. Part II analyzed the suitability of methods to address uncertainties. The suitability depends on data availability, type of data (tangible, intangible, random, non-random), screened hotspots, and tested modeling specifications. We identified types of uncertainties and methods that have been insufficiently addressed. The methods include probabilistic modeling such as design of experiment or subset simulation and evolutionary algorithm and Bayesian modeling such as the Bayesian latent Markov decision process. Subsequently, we evaluated learning potential from other life cycle assessment (LCA) and life cycle sustainability assessment (LCSA). This analysis revealed 28 possible applications that have not yet been used in LCC. Lastly, we developed best practices for LCC practitioners. This systematic review complements prior research on uncertainty in LCC for infrastructure, as laid out in Part I. Part II concludes that all relevant methods to address uncertainty are currently applied in LCC. Yet, the level of application is different. Moreover, not all methods are equally suited to address different categories of uncertainty. This review offers guidance on what to do for each source and type of uncertainty. It illustrates how methods can address both based on current practice in LCC, LCA, and LCSA. The findings of Part II encourage a dialog between practitioners of LCC, LCA, and LCSA to advance research and practice in uncertainty analysis.     

Life cycle considerations of the flue gas desulphurization system at a lignite-fired power plant in Thailand

Goal, Scope and Background  The Flue Gas Desulphurization (FGD) system has been installed at the biggest lignite-fired power generation plant in Thailand to reduce the large amount of SO₂ emission. In order to understand the costs and benefits, both in ecological and economic terms, the lignite-fired plant was studied both before and after the installation of the FGD system. The focus of this study is to consider not only the Life Cycle Assessment (LCA) outcome but also the Life Cycle Costing (LCC) factors. The results can provide valuable information when selecting appropriate technologies to minimize the negative impact that lignite-fired power plants have on the environment. Methods  The Life Cycle Assessment - Numerical Eco-load Total Standardization (LCA-NETS) system was used to evaluate the impact on the environment of both the lignite-fired plant and the FGD system. Life Cycle Costing (LCC) was used to provide a comparison between alternative before and after installation of FGD. LCC, a powerful analytical tool, examines the total cost, in net present value terms, of a FGD system over its entire service lifetime. Results and Discussion  The results of the study are shown in the eco-load values over the entire life cycle of the lignite-fired plant. Comparative models of the power plant, before and after the installation of the FGD system, are evaluated using the LCA-NETS system. The results indicate that the installation of the FGD system can reduce the acidification problem associated with lignite-fired plants by approximately 97%. The LCC estimation shows the major costs of the FGD system: capital investment, operating and maintenance, and miscellaneous costs. The LCC provides the decision-making information when considering the cost of the FGD system in terms of protecting the environment. Conclusion and Outlook  LCA is an important decision-making tool for environmental policies, especially with regard to the selection of pollution control equipment for lignite-fired plants. Green coal technologies and strategies to reduce the negative impact on the environment are essential to produce more environmentally-friendly power plants with a sustainable future.     

An integrated environmental and cost assessment method based on LCA and LCC for automobile interior and exterior trim design scheme optimization

Purpose

This paper provided an integrated method to evaluate environmental impact and life cycle cost (LCC) of various alternative design schemes in the early design and development stages of complex mechanical product; an optimization method of product design schemes based on life cycle assessment (LCA) and LCC is proposed as a supporting design tool to achieve optimal integration of environmental impact and cost of the design.

Methods

The applied research methods include product level deconstruction model, LCA/LCC integrated analysis model, and the product design scheme optimization method. In the life cycle environmental assessment, GaBi software and CML2001 evaluation method are used to evaluate product environmental impact. In terms of product design configuration scheme optimization, the TOPSIS method is used to optimize the design schemes generated. Taking the internal and external trim of automobile as an example, the specific implementation process of the method is illustrated.

Results and discussion

The case study indicates that, when comprehensively considering the environmental impact and cost, the composite indices of the optimal and worst schemes are 0.8667 and 0.3001, respectively; their costs are ¥164.87 and ¥179.68, respectively; and the eco points of environmental impact are 14.74 and 39.78, respectively. The cost of the two schemes are not much different, but the environmental impact of the optimal scheme is only 37.1% of the worst scheme’s; When cost is the only factor to be considered, the lowest cost design scheme is about 36.7% of the maximum scheme’s cost, and the environmental impact of the lowest cost design scheme is about 1.6 times of the maximum cost scheme’s. When environmental impact is the only factor to be considered, the least environmental impact of design scheme accounts about 31.7% of the largest; the cost of design scheme with the least environmental impact accounts for about 58.1% of the largest one’s. Integrating LCA and LCC, scientific suggestions can be provided from several perspectives.

Conclusions

By considering the environmental impact and LCC, this paper proposes a method of product design scheme optimization as a supporting design tool which could evaluate the design options of the product and identify the preferred option in the early stage of product design. It is helpful to realize the sustainability of the product. In order to improve the applicability of this method, the weighting factors of environmental impact and cost could be adjusted according to the requirements of energy saving and emission reduction of different enterprises.

     

基于多源数据的城市生境网络规划方法研究与实践

生态文明建设导向下的城镇发展建设,需要切实平衡人与自然的空间发展矛盾,应用多源数据分析和判断如何建设一个体系更健康、结构更合理、功能更完善的城市绿色空间体系,具有重要的规划探索和实践意义。选定目标鸟种,研究建立其潜在生境空间参数指标体系,运用多源数据分析潜在生境、廊道和踏脚石增设需求。构建以鸟类生境为代表的特定类型生境网络、指导城市绿色空间布局。随着多源数据获取成本的逐步降低和物种类群生境参数的逐步深化发展,该方法在研究城市生境网络构建和绿色空间布局上的作用还将进一步提升。     

Estimation of the leaf chlorophyll content using multiangular spectral reflectance factor

Chlorophyll is one of the primary pigments of plant leaves, and changes in its content can be used to characterize the physiological status of plants. Spectral indices have been devised and validated for estimating leaf chlorophyll content (LCC). However, most of the existing spectral indices do not consider the influence of angular reflection on the accuracy of the LCC estimation. In this study, the spectral reflectance factors of leaves from three plant species were measured from several observations in the principal plane. The relationship between the existing spectral indices and the LCC from different directions suggests that the directional reflection of a leaf surface impacts the accuracy of its LCC estimation. Subsequently, the ratio of reflectance differences, that is, the modified Datt index, was tested to reduce the directional reflection effect when predicting LCC. Our results indicated that the modified Datt index not only estimated LCC with high accuracy for all observation directions and plant species but also consistently predicted the LCC of each species in individual observation directions. Our method opens the possibility for optical detection of LCC using multiangular spectral reflection, which is convenient for plant science studies focused on the variation in LCC.     

基于多源数据空间分析的国家公园管控分区研究——以钱江源国家公园体制试点区为例

《关于建立以国家公园为主体的自然保护地体系的指导意见》提出国家公园实行管控分区的要求,以便实现国家公园最严格保护目标。然而,国家公园管控分区评价的指标尚不明确,以浙江钱江源国家公园体制试点区（以下简称"钱江源国家公园"）为研究对象,采用层次分析法从基础环境（包括高程、植被指数、交通道路影响和基本农田）、重点野生动植物分布（野生动植物、黑麂生境适宜性和白颈长尾雉生境适宜性）、自然资源保护基础（古田山国家级自然保护区、钱江源国家森林公园、钱江源风景名胜区和生态公益林）和生态现状（生态功能适宜性评价、自然资源承载力、三区三线和土地利用现状）等指标构建多源数据空间分析指标体系,利用空间叠加分析技术获取钱江源国家公园的管控分区结果,并与管控分区最终结果进行对比分析。结果表明：（1）基于多源数据的方法能有效地识别钱江源国家公园内生态保护价值较高区域;（2）多源数据空间分析结果与最终管控分区结果对比显示,其总体精度为78.07%（197.70 km²）,在核心保护区精度为83.55%（127.99 km²）,一般控制区精度为69.67%（69.71 km²）;（3）影响精度主要原因是新调入区域基础数据不足,以及通过定性分析解决管控分区破碎化等。研究认为基于多源空间数据分析技术能够客观、高效地划分国家公园管控分区,具有一定普适性,但仍需通过增加数据数量或优化算法提高精度。     

The pronghorn (Antilocapra americana): A review as a model for development of a “Species Management Plan” format,Part I

A format is suggested for a “Species Management Plan”; the model for this presentation is the pronghorn (Antilocapra americana). By using the Species Management Plan format, the captive maintenance of pronghorn is analyzed in relation to habitat and microhabitat needs, behavioral requirements, and nutritional needs. A strategy for captive maintenance of pronghorn in relatively wet climates is presented. It is suggested that development of a Species Management Plan is necessary before any new species is acquired for captive maintenance and reproduction.     

High resolution retrieval of leaf chlorophyll content over Himalayan pine forest using Visible/IR sensors mounted on UAV and radiative transfer model

Forests play an essential role towards net primary productivity, biological cycles and provide habitat to flora & fauna. To monitor key physiological activities in forest canopies such as photosynthesis, respiration, transpiration, spatially-explicit and precise information of the biochemical (biological) variables such as Leaf Chlorophyll Content (LCC) is required. While lookup-table (LUT)-based Radiative Transfer Model (RTM) inversion against optical remote sensing imagery is regarded as a physically sound and robust approach for retrieving biochemical and biophysical variables, regularization procedures are required to offset the problem of ill-posedness. To optimize the RTM inversion of LCC over a sub-tropical pine forest plantation, in the Western Himalaya, we investigated the role of: (1) cost functions (CFs), (2) added noise, and (3) multiple finest solutions in LUT inversion. Principal CFs were evaluated belonging to three categories: information measures, M-estimates, and minimal contrast approaches. The inversion approaches were applied to a LUT produced by the coupled leaf-canopy model known as PROSAIL RTM and tested in contrast field spectral data obtained from reflectance data derived from UAV (Unmanned Aerial Vehicle) images taken over the canopies of covered pine forests. The Bhattacharyya divergence, an information measure, outperformed all other CFs in LCC inversion, with R² of 0.94, RMSE of 6.20 μg/cm² and NRMSE of 12.27% during the validation. The optimized inversion strategy was subsequently applied to a UAV-acquired multispectral image at an 8.2 cm pixel resolution for detailed landscape forest LCC mapping. The associated residuals as provided by the LUT-based inversion provided insights in the spatial consistency of the LCC map.     

Mikrocomputer-unterstützte prozeßkontrolle in der fermentationstechnik

Nowadays computer control is an effective and well established tool in optimizing fermentation processes. Based on recent development in microelectronics, especially in the field of personal computers, cost effective applications of this technology are now possible, even on laboratory- and pilot scale. In this paper the application of a personal computer (CBM 3032), controlling various types of fermentations, is described. In more detail the availability of physiologically relevant sensors, especially the respiration and the dynamic calorimetry, are discussed. Finally some examples of practical realisations are presented.     

基于生命周期方法的生活垃圾资源化利用系统生态效率分析

我国生活垃圾产量大但处理能力不足,产生多种环境危害,对其资源化利用能够缓解环境压力并回收资源。为探讨生活垃圾资源化利用策略,综合生命周期评价与生命周期成本分析方法,建立生态效率模型。以天津市为例,分析和比较焚烧发电、卫生填埋-填埋气发电、与堆肥+卫生填埋3种典型生活垃圾资源化利用情景的生态效率。结果表明,堆肥+卫生填埋情景具有潜在最优生态效率;全球变暖对总环境影响贡献最大,而投资成本对经济影响贡献最大。考虑天津市生活垃圾管理现状,建议鼓励发展生活垃圾干湿组分分离及厨余垃圾堆肥的资源化利用策略。     

陆地植被水碳通量模型模拟与数据同化研究进展

精确估算水碳通量对陆地水碳循环研究意义重大,同时也极具挑战性。目前的估算精度有待进一步提高。传统的模型模拟和站点观测两种估算方法各有优势和不足,二者需结合进行研究。数据同化将观测融合到基于物理规律的模型中,尽可能得到模型状态变量和参数的最优估计,为模型和观测的结合提供了一条有效的途径。本文追踪陆地植被水碳通量过程模型与多源观测信息数据同化的研究进展;从植被水碳通量过程模型、数据同化算法、水碳通量模型数据同化3方面梳理了国内外相关研究进展,总结了研究中可能存在的问题:多源观测数据协同不足、同化策略相对简单、同化模型缺乏融合、同化尺度有待扩展;并从同化策略、模型选择、数据扩展、尺度效应、科学计算5个方面对今后的发展方向和趋势进行了分析和展望,以期为该领域研究者提供较全面的背景资料和信息,同时引发更多学者的关注。     

Life Cycle Cost Disclosure, Consumer Behavior, and Business Implications

Comprehensive assessments of final consumption have identified "housing" as a major contributor to total environmental impacts. Within this category, electrical-energy-using products are important. Do consumers opt for more energy-efficient household appliances if they are provided with life cycle cost (LCC)—that is, the sum of purchase price and operating cost estimated over the life span of the appliance? And what consequences does LCC disclosure have for business? Physical energy figures shown on appliance labels may be cognitively demanding for consumers, whereas monetary information promises to simplify the decision problem. Despite the rising interest in monetary cost disclosure, its effectiveness relative to physical cost disclosure has not been rigorously evaluated. This research approached the question of effectiveness with an online field experiment for washing machines. Customers of a commercially operating online shop were randomly assigned to two groups. The control group was provided with regular product price information; the treatment group received additional LCC information. A total of 2,065 clicks were recorded and analyzed with multiple regression that controlled for several product characteristics. The evidence suggests that LCC disclosure decreases the mean specific energy use of chosen washing machines by 0.8% ( p < 0.01) and their mean specific water use by 0.7% ( p < 0.05). As to business implications, LCC disclosure had no effect on the indicator of retail volume, which makes it unattractive for retailers to provide LCC on their own initiative.     

Plant Construction Cost in the Boreal Species Differing in Their Ecological Strategies

Construction cost (CC) of leaves was studied in 73 boreal plant species differing in ecological strategy. CC is the energy cost, expressed as glucose weight, of the plant weight unit formation. The perennial species that exhibited the stress-tolerant (S) type of strategy had the highest, whereas the annual plants of the ruderal type (R) of strategy had the lowest CC values, and the individual plant species from these two groups significantly differed in their CC indices. Plant species of diverse strategies were regularly distributed in the Grime's triangle, according to their CC values. The analysis of leaf chemical components has shown that high CC values in plants of the S-group correlated with a higher content of energy-expensive organic compounds, pigments, lignin, waxes, phenolics, etc. In contrast, in the plants that exhibited the r-strategy, the majority of photosynthetically assimilated carbon was utilized in the synthesis of functional substances, namely, proteins and carbohydrates. Our data showed the differential organization of plant metabolism in the plants exhibiting different types of ecological strategies. The CC values of leaf, together with other known characteristics, can be used for the identification of the types of ecological strategies and the assessment of the resistance of plant species and varieties to environmental stress.     

The Effect of Life Cycle Cost Information on Consumer Investment Decisions Regarding Eco-Innovation

Life cycle cost (LCC) computations are a well-established instrument for the evaluation of intertemporal choices in organizations, but they have not been widely adopted by private consumers yet. Consumer investment decisions for products and services with higher initial costs and lower operating costs are potentially subject to numerous cognitive biases, such as present-biased preferences or framing effects. This article suggests a classification for categorizing different cost profiles for eco-innovation and a conceptual model for the influence of LCC information on consumer decisions regarding eco-innovation. It derives hypotheses on the decision-making process for eco-innovation from a theoretical perspective. To verify the hypotheses, the publication reviews empirical studies evaluating the effects of LCC information on consumer investment decisions. It can be concluded that rather than finding ways to make customers pay more for environmentally sound products, the marketing challenge for eco-innovation should be reconceptualized as one of lowering customers' perceived initial cost and increasing awareness of LCC. Most existing studies report a positive effect of LCC information on the purchase likelihood of eco-innovations. Disclosing LCC information provides an important base for long-term thinking on the individual, corporate, and policy levels.     

The neural basis of financial risk taking

Investors systematically deviate from rationality when making financial decisions, yet the mechanisms responsible for these deviations have not been identified. Using event-related fMRI, we examined whether anticipatory neural activity would predict optimal and suboptimal choices in a financial decision-making task. We characterized two types of deviations from the optimal investment strategy of a rational risk-neutral agent as risk-seeking mistakes and risk-aversion mistakes. Nucleus accumbens activation preceded risky choices as well as risk-seeking mistakes, while anterior insula activation preceded riskless choices as well as risk-aversion mistakes. These findings suggest that distinct neural circuits linked to anticipatory affect promote different types of financial choices and indicate that excessive activation of these circuits may lead to investing mistakes. Thus, consideration of anticipatory neural mechanisms may add predictive power to the rational actor model of economic decision making.     

Informing Packaging Design Decisions at Toyota Motor Sales Using Life Cycle Assessment and Costing

Throughout their life cycle stages—material production, package manufacture, distribution, end-of-life management—packaging systems consume natural resources and energy, generate waste, and emit pollutants. Each of these stages also carries a financial cost. Motivated by a desire to decrease environmental burdens while reducing financial costs associated with the packaging of accessory and service parts, Toyota Motor Sales (TMS) partnered with the Donald Bren School of Environmental Science & Management to build a life cycle assessment and costing tool to support packaging design decisions. The resulting Environmental Packaging Impact Calculator (EPIC) provides comprehensive life cycle assessment (LCA) and life cycle costing (LCC). It allows packaging designers to identify environmentally and economically preferable packaging systems in daily decision-making. EPIC's parameterized process flow model allows users to assess many different packaging systems using a single model. Its input/output interface is designed for users without preexisting knowledge of LCA theory or practice and calculates results based on relatively few input data. The main motivation behind this environmental design tool is to provide relevant information to those individuals who are in the best position to reduce life cycle impacts and costs from TMS's packaging and distribution systems.     

A new method of long-term preventive cardioprotection using Lactobacillus

Potential long-term cardioprotection was investigated in an extensive experimental study. Lactobacillus cultivation components (LCC) were administered intravenously in anesthetized rats 1, 7, and 21 days before global ischemia (GI). GI was produced by full stop flow in isolated Langendorff-perfused hearts for 20 min and was followed by reperfusion. Control animals were injected with saline. LCC reduced reperfusion tachyarrhythmia significantly and improved functional recovery of the ischemized rat heart. These beneficial effects were associated with reduction of release of norepinephrine (NE) and prostacyclin at the first minute of reperfusion, activation of myocardial catalase, and overexpression of 70-kDa heat stress protein (HSP-70) at ischemia and reperfusion (P < 0.05). This cardioprotection was documented up to 21 days after a single injection of LCC. Thus Lactobacillus cultivation components are new nontoxic materials that produce marked long-term cardioprotection against ischemia-reperfusion damage. This effect is attributed to an activation of the cellular defense system, manifested by activation of the antioxidant pathway and by expression of protective proteins. NE is involved in this process, and the data also suggest a role for prostacyclin in this model of cardioprotection. The potential of LCC and related compounds working through similar mechanisms in the prevention and therapy of various ischemic heart syndromes should be explored.     

Quantification of lignin–carbohydrate linkages with high-resolution NMR spectroscopy

A quantitative approach to characterize lignin–carbohydrate complex (LCC) linkages using a combination of quantitative ¹³C NMR and HSQC 2D NMR techniques has been developed. Crude milled wood lignin (MWLc), LCC extracted from MWLc with acetic acid (LCC-AcOH) and cellulolytic enzyme lignin (CEL) preparations were isolated from loblolly pine (Pinus taeda) and white birch (Betula pendula) woods and characterized using this methodology on a routine 300 MHz NMR spectrometer and on a 950 MHz spectrometer equipped with a cryogenic probe. Structural variations in the pine and birch LCC preparations of different types (MWL, CEL and LCC-AcOH) were elucidated. The use of the high field NMR spectrometer equipped with the cryogenic probe resulted in a remarkable improvement in the resolution of the LCC signals and, therefore, is of primary importance for an accurate quantification of LCC linkages. The preparations investigated showed the presence of different amounts of benzyl ether, γ-ester and phenyl glycoside LCC bonds. Benzyl ester moieties were not detected. Pine LCC-AcOH and birch MWLc preparations were preferable for the analysis of phenyl glycoside and ester LCC linkages in pine and birch, correspondingly, whereas CEL preparations were the best to study benzyl ether LCC structures. The data obtained indicate that pinewood contains higher amounts of benzyl ether LCC linkages, but lower amounts of phenyl glycoside and γ-ester LCC moieties as compared to birch wood.     

Strategies and Decision-Support Tools for Optimizing Long-Term Groundwater Monitoring Plans—MAROS 2.0

Existing long-term groundwater monitoring programs can be optimized to increase their effectiveness/efficiency with the potential to generate considerable cost savings. The optimization can be achieved through an overall evaluation of conditions of the contaminant plume and the monitoring network, focused spatial and temporal sampling analyses, and automated and efficient management of data, analyses, and reporting. Version 2.0 of the Monitoring and Remediation Optimization System (MAROS) software, by integrating long-term monitoring analysis strategies and innovative optimization methods with a data management, processing, and reporting system, allows site managers to quickly and readily develop cost-effective long-term groundwater monitoring plans. The MAROS optimization strategy consists of a hierarchical combination of analysis methods essential to the decision-making process. Analyses are performed in three phases: 1) evaluating site information and historical monitoring data to obtain local concentration trends and an overview of the plume status; 2) developing optimal sampling plans for future monitoring at the site with innovative optimization methods; and 3) assessing the statistical sufficiency of the sampling plans to provide insights into the future performance of the monitoring program. Two case studies are presented to demonstrate the usefulness of the developed techniques and the rigor of the software.     

Strategies and Decision-Support Tools for Optimizing Long-Term Groundwater Monitoring Plans—MAROS 2.0

Existing long-term groundwater monitoring programs can be optimized to increase their effectiveness/efficiency with the potential to generate considerable cost savings. The optimization can be achieved through an overall evaluation of conditions of the contaminant plume and the monitoring network, focused spatial and temporal sampling analyses, and automated and efficient management of data, analyses, and reporting. Version 2.0 of the Monitoring and Remediation Optimization System (MAROS) software, by integrating long-term monitoring analysis strategies and innovative optimization methods with a data management, processing, and reporting system, allows site managers to quickly and readily develop cost-effective long-term groundwater monitoring plans. The MAROS optimization strategy consists of a hierarchical combination of analysis methods essential to the decision-making process. Analyses are performed in three phases: 1) evaluating site information and historical monitoring data to obtain local concentration trends and an overview of the plume status; 2) developing optimal sampling plans for future monitoring at the site with innovative optimization methods; and 3) assessing the statistical sufficiency of the sampling plans to provide insights into the future performance of the monitoring program. Two case studies are presented to demonstrate the usefulness of the developed techniques and the rigor of the software.