A Systems Approach to Sustainable Technical Product Design

Many existing methods for sustainable technical product design focus on environmental efficiency while lacking a framework for a holistic, sustainable design approach that includes combined social, technical, economic, and environmental aspects in the whole product life cycle, and that provides guidance on a technical product development level. This research proposes a framework for sustainable technical product design in the case of skis. We developed a ski under the Grown brand, benchmarked according to social, environmental, economic, and technical targets, following an initial sustainability assessment, and delivered the first environmental life cycle assessment (ELCA) and the first social life cycle assessment (SLCA) of skis. The framework applies a virtual development process as a combination of ELCA to calculate the environmental footprint as carbon equivalents of all materials and processes and a technical computer‐aided design (CAD) and computer‐aided engineering (CAE) simulation and virtual optimization using parameter studies for the nearly prototype‐free development of the benchmarked skis. The feedback loops between life cycle assessment (LCA) and virtual simulation led to the elimination of highly energy intensive materials, to the pioneering use of basalt fibers in skis, to the optimization of the use of natural materials using protective coatings from natural resins, and to the optimization of the production process. From an environmental perspective, a minimum 32% reduction in carbon equivalent emissions of materials in relation to other comparably performing skis has been achieved, as well as a pioneering step forward toward transparent communication of the environmental performance by the individual, comparable, and first published ski carbon footprint per volume unit.     

Parameter optimization by using differential elimination: a general approach for introducing constraints into objective functions

Background

The investigation of network dynamics is a major issue in systems and synthetic biology. One of the essential steps in a dynamics investigation is the parameter estimation in the model that expresses biological phenomena. Indeed, various techniques for parameter optimization have been devised and implemented in both free and commercial software. While the computational time for parameter estimation has been greatly reduced, due to improvements in calculation algorithms and the advent of high performance computers, the accuracy of parameter estimation has not been addressed.

Results

We propose a new approach for parameter optimization by using differential elimination, to estimate kinetic parameter values with a high degree of accuracy. First, we utilize differential elimination, which is an algebraic approach for rewriting a system of differential equations into another equivalent system, to derive the constraints between kinetic parameters from differential equations. Second, we estimate the kinetic parameters introducing these constraints into an objective function, in addition to the error function of the square difference between the measured and estimated data, in the standard parameter optimization method. To evaluate the ability of our method, we performed a simulation study by using the objective function with and without the newly developed constraints: the parameters in two models of linear and non-linear equations, under the assumption that only one molecule in each model can be measured, were estimated by using a genetic algorithm (GA) and particle swarm optimization (PSO). As a result, the introduction of new constraints was dramatically effective: the GA and PSO with new constraints could successfully estimate the kinetic parameters in the simulated models, with a high degree of accuracy, while the conventional GA and PSO methods without them frequently failed.

Conclusions

The introduction of new constraints in an objective function by using differential elimination resulted in the drastic improvement of the estimation accuracy in parameter optimization methods. The performance of our approach was illustrated by simulations of the parameter optimization for two models of linear and non-linear equations, which included unmeasured molecules, by two types of optimization techniques. As a result, our method is a promising development in parameter optimization.

     

基于生态系统服务供需的景感尺度特征分析和应用

自然生态系统与人类感知的交互作用是景感生态学关注的焦点,与生态系统服务的供需紧密关联。生态系统、生态过程、生态系统服务以及人的需求均具有一定的时空尺度特征,因此,由这些过程产生的"景感"也具有时空尺度特征,并依赖于这个过程的尺度特征相互作用。梳理生态系统服务供需关系与景感营造规划的尺度特征,探索二者相互联系,进而提出基于景感生态学理论,通过景感营造实现生态系统服务供需平衡的多尺度实现路径。从空间维度,体现从"社区-城市-流域-区域"的多尺度景感规划框架,从应用维度,体现从生态系统服务需求探索-关键指标体系识别-多源谜码数据感知-景感营造与规划设计的具体流程。通过多尺度的联合景感营造,调整自然供给水平与人类不同尺度的生态系统服务需求以期达到平衡,从而实现人类生存环境福利与居民福祉提升的目标。在此基础上,结合雄安新区规划建设实例,从多尺度景感营造的角度为城市绿色生态建设与可持续发展提出优化建议。主要结论：（1）基于"社区-城市-流域-区域"的多尺度景感分析框架,将景感要素与生态系统服务供需思想融入城市规划,在不同尺度上趋善优化,对于实现可持续发展城市规划和管理具有重要指示意义;（2）雄安新区规划设计需更系统和细致地考虑人类感知需求,通过多尺度景感营造设计,共同实现雄安新区的可持续发展与人居环境提升。其中,在社区尺度,需重点关注社区植被配置和居民的休闲游憩;在新区尺度重点关注绿地系统网络构建;在大清河流域尺度重点关注河流健康与水文调节;在京津冀区域尺度需注重山体通风廊道与生态屏障的构建与优化。     

Base Station Placement Algorithm for Large-Scale LTE Heterogeneous Networks

Data traffic demands in cellular networks today are increasing at an exponential rate, giving rise to the development of heterogeneous networks (HetNets), in which small cells complement traditional macro cells by extending coverage to indoor areas. However, the deployment of small cells as parts of HetNets creates a key challenge for operators’ careful network planning. In particular, massive and unplanned deployment of base stations can cause high interference, resulting in highly degrading network performance. Although different mathematical modeling and optimization methods have been used to approach various problems related to this issue, most traditional network planning models are ill-equipped to deal with HetNet-specific characteristics due to their focus on classical cellular network designs. Furthermore, increased wireless data demands have driven mobile operators to roll out large-scale networks of small long term evolution (LTE) cells. Therefore, in this paper, we aim to derive an optimum network planning algorithm for large-scale LTE HetNets. Recently, attempts have been made to apply evolutionary algorithms (EAs) to the field of radio network planning, since they are characterized as global optimization methods. Yet, EA performance often deteriorates rapidly with the growth of search space dimensionality. To overcome this limitation when designing optimum network deployments for large-scale LTE HetNets, we attempt to decompose the problem and tackle its subcomponents individually. Particularly noting that some HetNet cells have strong correlations due to inter-cell interference, we propose a correlation grouping approach in which cells are grouped together according to their mutual interference. Both the simulation and analytical results indicate that the proposed solution outperforms the random-grouping based EA as well as an EA that detects interacting variables by monitoring the changes in the objective function algorithm in terms of system throughput performance.     

基于空间优先级的快速城市化地区绿色基础设施网络构建——以南京市浦口区为例

绿色基础设施是一个由自然区域和其他开放空间相互联系的网络。在城市空间极为有限的情况下,如何有效构建城市绿色基础设施网络并识别那些具关键性景观生态功能的网络要素显得极为重要。为了给城市绿色基础设施网络的建设和管理提供新的建模与分析理念,以快速城市化的南京市浦口区为例,采用MSPA方法并结合景观连通性指数,遴选出了对维持景观连通性贡献最大的生境斑块作为绿色基础设施网络的网络中心,进而采用最小路径方法构建了研究区潜在的绿色基础设施网络,并尝试利用空间句法分析,基于结构优化视角对绿色基础设施网络进行优先级的识别,从而使绿色基础设施网络的构建更科学。研究结果可为快速城市化地区绿色基础设施网络的构建提供一种研究思路与方法,对绿色基础设施网络要素的优先级评价也具有一定的借鉴意义。     

Assessing the social dimension in strategic network optimization for a sustainable development: The case of bioethanol production in the EU

The complexity of social indicators and their subjective and often qualitative nature render their inclusion into quantitative optimization models for network design and strategic decision-making challenging. The social dimension is thus often implemented only rudimentarily, thwarting a holistic sustainability assessment and neglecting many of the social issues addressed in the sustainable development goals (SDGs). This work presents a structured process for including a comprehensive set of social aspects by selecting applicable quantitative and regionalized social indicators. This approach is applied to the case of second-generation bioethanol production in the EU. Based on inter alia the Guidelines for Social Life Cycle Assessment of Products and Organizations, the Social Hotspots Database, state-of-the-art literature, as well as previous work, we compile 9 social objective functions and 25 functions for social hotspot identification. They are evaluated alongside 1 economic and 21 environmental LCA-based objective functions in a mixed-integer linear programming (MILP) model. Key results show that social optimization either leads to large, labor-intensive or regionally focused, indicator-driven networks. Injuries and fatalities in the feedstock sectors of Central and Eastern European countries is the primary social hotspot. On the level of the overarching SDGs, SDG13 is most congruent with other goals, while SDG7 is hindered by pursuing other goals. This study's approach is novel in strategic network design and the European bioeconomy, and, by operationalizing the social dimension, enables a more holistic life cycle sustainability assessment and the consideration of the SDGs. This article met the requirements for a gold-gold JIE data openness badge described at http://jie.click/badges .      

Introducing Templates for Sustainable Product Development

We have previously developed a method for sustainable product development (MSPD) based on backcasting from basic sustainability principles. The MSPD informs investigations of product‐related social and ecological sustainability aspects throughout a concurrent engineering product development process. We here introduce “templates” for sustainable product development (TSPDs) as a complement. The idea is to help product development teams to arrive faster and more easily at an overview of the major sustainability challenges and opportunities of a product category in the early development phases. The idea is also to inform creative communication between top management, stakeholders, and product developers. We present this approach through an evaluation case study, in which the TSPDs were used for a sustainability assessment of televisions (TVs) at the Matsushita Electric Group. We study whether the TSPD approach has the ability to (1) help shift focus from gradual improvements of a selection of aspects in relation to past environmental performance of a product category to a focus on the remaining gap to a sustainable situation, (2) facilitate consensus among organizational levels about major sustainability challenges and potential solutions for a product category, and (3) facilitate continued dialogue with external sustainability experts, identifying improvements that are relevant for strategic sustainable development. Our findings indicate that the TSPD approach captures overall sustainability aspects of the life cycle of product categories and that it has the above abilities.     

交通网络空间互动视角下生态足迹驱动机制

长江中游城市群是中部崛起战略的重要区域,同时依托长江黄金水道面临发展和保护的困境。交通网络空间互动视角下的生态足迹驱动机制研究对统筹长江中游城市群经济社会高质量发展和生态文明高水平建设以实现可持续发展具有重要意义。基于生态足迹模型测度了长江中游城市群县域尺度的可持续发展状况,并在STIRPAT模型框架下基于交通网络空间互动关系挖掘生态足迹的驱动机制和空间效应,为交通网络扩张背景下的跨区域生态治理与可持续发展提供参考。研究结果显示：(1)2010—2017年,长江中游城市群县域生态足迹均值有所下降;(2)道路交通网络和铁路交通网络规模均有所扩大,但连通性略有下降;(3)在基于交通网络构建的空间互动媒介下,城镇化率和人均GDP对生态足迹具有显著的促进作用,而第三产业增加值占比对生态足迹产生抑制影响,且生态足迹表现出积极的空间外溢效应。基于以上研究结果,建议在基于交通网络加强区域生态协同发展的同时,建设产业互促、资源互通、技术互享的区域联动可持续发展新格局。     

Improving the efficiency of evolutionary de novo peptide design: strategies for probing configuration and parameter settings

Evolutionary molecular design based on genetic algorithms (GAs) has been demonstrated to be a flexible and efficient optimization approach with potential for locating global optima. Its efficacy and efficiency are largely dependent on the operations and control parameters of the GAs. Accordingly, we have explored new operations and probed good parameter setting through simulations. The findings have been evaluated in a helical peptide design according to "Parameter setting by analogy" strategy; highly helical peptides have been successfully obtained with a population of only 16 peptides and 5 iterative cycles. The results indicate that new operations such as multi-step crossover-mutation are able to improve the explorative efficiency and to reduce the sensitivity to crossover and mutation rates (CR-MR). The efficiency of the peptide design has been furthermore improved by setting the GAs at the good CR-MR setting determined through simulation. These results suggest that probing the operations and parameter settings through simulation in combination with "Parameter setting by analogy" strategy provides an effective framework for improving the efficiency of the approach. Consequently, we conclude that this framework will be useful for contributing to practical peptide design, and gaining a better understanding of evolutionary molecular design.     

Assessment of the National Eco-Industrial Park Standard for Promoting Industrial Symbiosis in China

Eco-industrial park (EIP) projects have become more prevalent in China. In order to evaluate the performance of such innovative projects, the State Environmental Protection Administration (SEPA) has set up a new national standard for EIPs, the first of its kind globally. This article examines the applicability and feasibility of the indicator system established in the standard. It first presents the details of this new standard. Then benefits and challenges in the standard's application are analyzed. The analysis shows that the new indicators are eco-efficiency-oriented and do not address the essence of the EIP. In the future, there will be a need to revise this set of indicators by considering the principles of eco-industrial development and local realities in order to ensure that the indicators are indeed used to promote sustainable development of industrial parks.     

Import‐based Indicator for the Geopolitical Supply Risk of Raw Materials in Life Cycle Sustainability Assessments

There is a growing concern over the security and sustainable supply of raw material among businesses and governments of developed, material‐intensive countries. This has led to the development of a systematic analysis of risk incorporated with raw materials usage, often referred as criticality assessment. In principle, this concept is based on the material flow approach. The potential role of life cycle assessment (LCA) to integrate resource criticality through broadening its scope into the life cycle sustainability assessment (LCSA) framework has been discussed within the LCA communities for some time. In this article, we aim at answering the question of how to proceed toward integration of the geopolitical aspect of resource criticality into the LCSA framework. The article focuses on the assessment of the geopolitical supply risk of 14 resources imported to the seven major advanced economies and the five most relevant emerging countries. Unlike a few previous studies, we propose a new method of calculation for the geopolitical supply risk, which is differentiated by countries based on the import patterns instead of a global production distribution. Our results suggest that rare earth elements, tungsten, antimony, and beryllium generally pose high geopolitical supply risk. Results from the Monte Carlo simulation allow consideration of data uncertainties for result interpretation. Issues concerning the consideration of the full supply chain are exemplarily discussed for cobalt. Our research broadens the scope of LCA from only environmental performance to a resource supply‐risk assessment tool that includes accessibility owing to political instability and market concentration under the LCSA framework.     

Hybrid simulation and optimization approach for green intermodal transportation problem with travel time uncertainty

The increasing volumes of road transportation contribute to congestion on road, which leads to delays and other negative impacts on the reliability of transportation. Moreover, transportation is one of the main contributors to the growth of carbon dioxide equivalent emissions, where the impact of road transportation is significant. Therefore, governmental organizations and private commercial companies are looking for greener transportation solutions to eliminate the negative externalities of road transportation. In this paper, we present a novel solution framework to support the operational-level decisions for intermodal transportation networks using a combination of an optimization model and simulation. The simulation model includes stochastic elements in form of uncertain travel times, whereas the optimization model represents a deterministic and linear multi-commodity service network design formulation. The intermodal transportation plan can be optimized according to different objectives, including costs, time and \(CO_2e\) emissions. The proposed approach is successfully implemented to real-life scenarios where differences in transportation plans for alternative objectives are presented. The solutions for transportation networks with up to 250 services and 20 orders show that the approach is capable of delivering reliable solutions and identifying possible disruptions and alternatives for adapting the unreliable transportation plans.     

中国生态工业园区发展现状与展望

综述了中国生态工业园区的发展,主要内容包括:(1)中国工业园区的发展历程和面临的挑战;(2)中国生态工业园区的发展历程与发展模式;(3)3个角度分析中国生态工业园区建设取得的环境绩效,即基于生态工业示范园区验收及规划基准年绩效变化,基于数据包络分析法的生态工业示范园区环境绩效和基于环境绩效指数方法的生态工业园区环境绩效评价;(4)国内外关于生态工业园区的研究现状和热点;(5)中国生态工业园区发展和研究面临的难点及未来发展展望。面向中国工业园区绿色低碳循环发展需求,以期通过对生态工业园区发展的回顾和评述,为园区实践者和决策者及后续研究提供参考。     

Biological network design strategies: discovery through dynamic optimization

An important challenge in systems biology is the inherent complexity of biological network models, which complicates the task of relating network structure to function and of understanding the conceptual design principles by which a given network operates. Here we investigate an approach to analyze the relationship between a network structure and its function using the framework of optimization. A common feature found in a variety of biochemical networks involves the opposition of a pair of enzymatic chemical modification reactions such as phosphorylation-dephosphorylation or methylation-demethylation. The modification pair frequently adjusts biochemical properties of its target, such as activating and deactivating function. We applied optimization methodology to study a reversible modification network unit commonly found in signal transduction systems, and we explored the use of this methodology to discover design principles. The results demonstrate that different sets of rate constants used to parameterize the same network topology represent different compromises made in the resulting network operating characteristics. Moreover, the same topology can be used to encode different strategies for achieving performance goals. The ability to adopt multiple strategies may lead to significantly improved performance across a range of conditions through rate modulation or evolutionary processes. The optimization framework explored here is a practical approach to support the discovery of design principles in biological networks.     

国外旅游生态效率优化与管理

旅游生态效率概念采用定量化方法对旅游业经济、环境影响进行分析,成为旅游业可持续发展评价的重要工具。基于可持续理论的旅游生态效率优化管理方案不断涌现,相关利益主体应用较多的有环境管理系统、旅游生态标签、清洁生产理念、旅游生态效率中心、21世纪地方议程等。在旅游企业日常运营中积极推动生态效率优化管理,是贯彻绿色发展理念,提高目的地旅游经济、环境绩效的一种新思路。从可持续背景下旅游生态效率优化模型入手,系统化分析了国外旅游生态效率优化管理方案的内容与特征。其中,环境管理系统在目的地层面为旅游生态效率优化设计了一套评估管理流程,旅游生态标签为目的地生态效率水平提供了可视化标志符号,21世纪地方议程为旅游可持续发展提供一致性整合方案,清洁生产理念是一种基于生态效率优化的长期战略,旅游生态效率中心作为非营利性机构有利于中小企业获得较好的环境绩效表现。国外旅游生态效率优化管理方案特征明显、设计合理、管理科学,对我国目的地旅游生态效率优化提升具有重要的借鉴作用。     

农工共生型生态产业园的构建——以郑州经开区为例

生态产业园已成为我国循环经济建设和可持续发展的重要载体之一,但我国的生态产业园明显存在着产业结构趋同、区域特色不鲜明等问题。提出了农工共生型生态产业园的概念,这是一类以工业园区为核心,集园区周边各类型农业相关企业、合作组织、农民、乡镇及农田为一体的一种"社会-经济-自然"复合区域产业共生体系。农工共生型生态产业园可以实现核心园区与周边腹地的协同发展,可以提升区域整体的生态效率。给出了农工共生型生态产业园的发展模式、建设意义及设计原则。并以农业大省河南省中唯一的国家级经济技术开发区为研究案例,结合当地区域特色及资源优势,构建了由3条产品链及一条服务链所组成的农工共生型产业生态系统。农工共生型生态产业园是产业共生理论在区域层面的具体实现,是复合生态系统理论在产业园层次的创新性应用。     

国内外产业共生网络研究比较述评

产业共生网络是指基于物质及能量交换以及知识及基础设施共享而形成的在不同产业主体之间的合作共赢网络,是产业转型升级的重要保障。作为产业共生的运作方式,产业共生网络的研究国外从20世纪90年代开始从概念到实例就展开了一系列探讨,国内自2002年也开始在网络结构等方面开展相关研究。尤其在2008年以后,产业共生网络的研究方向不断拓宽,研究成果丰富多样。为明晰国内外产业共生网络研究的发展态势,促进产业共生网络理论体系的发展并使其得到有效应用。本文从共生网络内涵、结构、功能及评价、演化、管理调控等方面比较分析了国内外产业共生网络的研究进展,并对产业共生网络的发展前景做了展望。未来产业共生网络研究在不同尺度的比较及推演、数据信息平台的搭建以及产业共生网络演化模拟及管理调控的耦合等方面需重点关注。     

Strain design optimization using reinforcement learning

Engineered microbial cells present a sustainable alternative to fossil-based synthesis of chemicals and fuels. Cellular synthesis routes are readily assembled and introduced into microbial strains using state-of-the-art synthetic biology tools. However, the optimization of the strains required to reach industrially feasible production levels is far less efficient. It typically relies on trial-and-error leading into high uncertainty in total duration and cost. New techniques that can cope with the complexity and limited mechanistic knowledge of the cellular regulation are called for guiding the strain optimization.In this paper, we put forward a multi-agent reinforcement learning (MARL) approach that learns from experiments to tune the metabolic enzyme levels so that the production is improved. Our method is model-free and does not assume prior knowledge of the microbe’s metabolic network or its regulation. The multi-agent approach is well-suited to make use of parallel experiments such as multi-well plates commonly used for screening microbial strains.We demonstrate the method’s capabilities using the genome-scale kinetic model of Escherichia coli, k-ecoli457, as a surrogate for an in vivo cell behaviour in cultivation experiments. We investigate the method’s performance relevant for practical applicability in strain engineering i.e. the speed of convergence towards the optimum response, noise tolerance, and the statistical stability of the solutions found. We further evaluate the proposed MARL approach in improving L-tryptophan production by yeast Saccharomyces cerevisiae, using publicly available experimental data on the performance of a combinatorial strain library.Overall, our results show that multi-agent reinforcement learning is a promising approach for guiding the strain optimization beyond mechanistic knowledge, with the goal of faster and more reliably obtaining industrially attractive production levels.     

基于网络分析的城市生态空间结构优化——以常州市为例

经济社会的高速发展带来城市的快速扩张,造成城市生态空间的萎缩和生态功能的下降,城市生态安全受到严重威胁。系统研究城市生态空间结构,提出针对性保护和优化措施,对于城市的可持续发展具有重大意义。本研究以常州市为研究区,考虑城市生态空间的自然生态功能和社会服务功能两方面,构建基于自然生态的“源地-廊道”与基于人文生态的“供给-需求”两类生态网络,对于源地廊道生态网络,主要从节点重要性、网络连通性与稳定性进行定量分析,对于供给需求生态网络,主要从节点重要性、供需均衡与稳定性进行定量分析。结果表明: 常州市主城区源地廊道生态网络的连通性与稳定性水平不高,供给需求生态网络的稳定性水平一般且存在服务供给与需求的空间错位。从连通性与稳定性提升角度,提出新增12个源地节点与57条廊道的源地廊道生态网络优化方案;从供需均衡与稳定性提升角度,提出新增22个供给节点的供给需求生态网络优化方案。对比初始源地廊道生态网络,优化网络连通性水平提升10%,稳定性提升0.05;对比初始供给需求生态网络,优化网络的服务水平提升4%,网络稳定性提升0.10。最后,综合两类生态网络,分别针对现状保护斑块与新增节点两类对象,提出了保护与管理实施方案。     

Combined Ring–Mesh Optical Transport Networks

To date in Sonet and DWDM transport environments, we see two dominant principles for network survivability: ring and mesh. Although both are used, they are virtually always deployed and operated on geographically separate networks or regions, or applied on a ring-access and mesh-core principle. We describe a new approach for optimized design of ring and mesh network components in a single hybrid transport network. A key concept in design of these hybrids is the clipping of forcer spans in the mesh network design by strategically added rings. We present a formal optimization model and a heuristic to form sych hybrid designs with lower total cost than a pure-mesh design. These ideas on optical network architecture are especially relevant to industry practice with the advent of OXC systems with integrated add–drop multiplexer functionality and by the development of ultra long reach (ULR) optics. This integration of OXC-OADM functionality effectively removes any extra costs associated with transitions from a ring to mesh environment and ULR optics permit all-optical bypass of OXC nodes which enhances the cost-effectiveness of the hybrid architectures.