A Big Data Analytics Approach to Develop Industrial Symbioses in Large Cities
Author links open overlay panelSong Bina *,Yeo Zhiquana , Low Sze Choong Jonathana , Derek Koh Jieweia , Denis Kurleb , Felipe Cerdasb , Christoph Herrmannb
a Singapore Institute Of Manufacturing Technology, Singapore
b Sustainable Manufacturing and Life Cycle Engineering Research Group, Institue of Machine Tools and Production Technology (IWF), Technische Universitaet Braunschweig, Germany
Procedia CIRP -2015 - 29 -P P 450-455:
The 22nd CIRP conference on Life Cycle Engineering
Abstract
A big problem for industry and large cities is the increasing waste streams from households as well as industries and their impacts to the environment. Treatment of the waste is expensive, and cities face challenges on waste disposal sites. A sustainable solution would be to realize industrial symbioses. The typical approach is to design and develop industrial parks each of which is aimed to be an industrial symbiosis. This approach is proven by successful cases, but is constrained by land scarce cities as well as the limited types and scales of the companies that can be included in an industrial park. The paper proposes a big data analytics approach to realize industrial symbioses among the industries in a city's close proximity. The waste streams and resource requirements of existing companies are identified and matched with resources needs directly or indirectly through conversion processes. The viability, critical elements and technical challenges of the approach are discussed.
© 2015 The Authors. Published by Elsevier B.V. Peer-review under responsibility of the International Scientific Committee of the Conference “22nd CIRP conference on Life Cycle Engineering.
Keywords: Big data analytics; Industrial symbiosis; Waste management
1. Introduction
The world is becoming more urbanized along with the industrialization and economic growth. People are increasingly attracted to cities by higher paid jobs and quality of living. According to United Nations’ report [1], urban residences is projected to grow from 54% of the current 7 billion pollution to 66% of the estimated 9 billion people by the year 2050. This translates to about 2.2 billion more people to live in urban areas. Among these people, 500 million is projected to live in the top 600 cities in the world [2]. Coupled with the growth of cities in number and sizes is the challenge to tackle waste. Accordingly to World Bank [3], waste generated in world cities is expected to increase from about 1.3 billion tons per year at present to 2.2 billion tons by 2025. The amount of municipal solid waste per urban resident per day is projected to increase from 1.2 kg today to 1.42 kg by 2025. More than 50% of the waste comes from industrial, commercial, and institutions (ICI). During the period, the cost of solid waste management will increase from $205.4 billion to about $375.5 billion, and the cost increases will be more severe in low-income countries and lower-middle income countries.
The ever-increasing waste in cities posts challenges to the environment and waste treatment [4,5]. Particularly in developing countries, investment cost and environmental concerns hamper the growth of waste incineration. Land constraints limit the capacity of waste disposal. The increasing complexity of substances in the waste due to complexity in the use of materials in products and packaging make it more difficult to recycle. A sustainable waste management solution is needed to support urbanization and economic growth.
The behavior of our natural biological ecosystem, in which waste from one component of the system represents resources to another, is promising to provide the guidance for a sustainable waste solution. The pioneering work of Graedel and Allenby [6] looked into the biological ecosystem for ways to establish a sustainable industrial ecosystem. Industrial symbiosis, in the context of industrial ecosystem, is defined as a relationship within which at least two willing participants exchange materials, energy, or information in a mutually beneficial manner. The realization of such a relationship among many participants in a close geographical proximity would drastically reduce the waste.
Modern cities exist primarily due to economic forces that cause employment to be concentrated in space, and concentration of jobs leads to concentration of residences [17]. The high density and diversity of industries in large cities provides high opportunities for the evolution of many economically viable waste-to-resource relationships. These relationships can lead to industrial symbioses, which would theoretically pave the way towards zero waste from industrial, commercial, and institutions in a large city. In the process, waste streams are no longer a burden, but value-creation resources.
A primary challenge in achieving such a goal is to discover the required information of the sources, quantity, and quality of waste streams and resource requirements. In fact, an important factor in the success evolution of Kalundborg could be due to the small size of the town where people and companies know each other well. Such information sharing in a natural manner is impossible in large cities.
To overcome the information barrier for the evolution of industrial symbioses in large cities, we propose the big data approach. In this approach, digital enterprise information from the cyber space interacts with industrial specific resourcewaste models to provide the needed information for the identification and evaluation of viable industrial symbioses.
2. Industrial Symbiosis and Industrial Cases
2.1. Approaches on Industrial Symbiosis
A few approaches are well documented for the realization of an industrial symbiosis. One is the exemplified Kalundborg approach by which the industrial symbiosis was evolved gradually by market forces over a period of 25 years [7]. Another approach is by planning industrial parks in which the knowledge and principles developed from the Kalundborg and other successful cases in Europe and North America are applied [8]. The topics studied ranges from eco-industrial park design [9] to the selection of locations for eco-industrial parks [10]. A broader form of the approach is on industrial symbioses of industrial areas [11]. Studies have been carried out on sharing heating and cooling through synchronization of facilities management in North-Eastern Italy [12], the life cycle assessment based optimal configuration of industrial types and waste streams of the factories in the agro-chemical complex in the Lower Mississipi River Corridor involving 13 chemical and petrochemical industries [13], and sectorspecific eco-industrial networks [14]. Further efforts have been elucidated in the Australian minerals industry, primarily focusing on identifying and prioritizing synergy opportunities in Kwinana and Gladstone [18, 19].
Desrochers [15] argued that the attempts to foster ecoindustrial parks and eco-industrial networks are too narrow in their geographical scope. A flexible regulatory framework should be a better means to evolve industrial symbioses in cities. The study by Murakami et al. [16] on the relationship between government policies and recycling reinforces the strong influence of public policies on materials recycling among industries. However, the influence of policies is by distortion of market conditions through taxation and other financial means. Consequently, public policies can promote businesses’ willingness to recycle. Solutions are required to over come information and technical barriers [16]:
• The recycling is limited by the small volume and low cost of the waste, and
• Much of the waste arrives in a condition that does not permit its recycling.
Technical and economical solutions are related to the sufficient volume of a waste stream. Therefore, fundamental to the barriers is the limitations in diversity and scale of an industrial area, the lack of information on the overall waste streams and resource needs, or both.
2.2. Industrial Cases in Singapore
The above cases are well reflected by a number of successful and failed attempts of, eco-networks in Singapore, which led to the conceptualization of the proposed big data approach for industrial symbiosis.
Over the recent years, projects have been carried out to help companies to measure and manage their environmental performance and resource efficiency. In the process, knowledge on the companies and possible waste/by-product to resource matches was evolved. Due to the limitation of the number and types of companies involved, the evolved econetworks were simple and straightforward. However, these cases help prove the needs, waste reduction potentials, and economical value of industrial symbiosis if relevant and sufficient knowledge on a big number of business entities in a large city can be established. One successful and one failed case are presented below to illustrate the value and major issues in developing eco-networks.
Case 1: By-product to Biocomposite materials and products .
Company A is in a manufacturer of a range of food related products and services. Its operation covers flour milling, food manufacturing, food services to finished products and retail stores. In its effort to improve the company’s eco-efficiency, a study was carried out to understand the impact of its manufacturing activities on the environment and formulate appropriate strategies to reduce the negative effects. One of the strategies is found to be the conversion of by-products derived from the flour milling process into sustainable materials.
The by-products of the flour milling process consist of bran and pollard. Based on the past one-year production data, the company produced a total mass of by-products averaging to about 4,000 tons per month, or 48,000 tons annually. At the time of the study, the by-products were sold as low-value animal feed. Technical analysis of the by-products found that they could be used to formulate biocomposite materials, which effectively doubled the value of the by-products.
4. Conclusion Remarks
The projected expansion of large cities globally coupled with the increasing urban waste generation is a critical challenge. Industrial symbiosis is widely recognized as a desirable approach to not only minimize the waste, but also create value from the waste by using and conversion the waste into resources. Many successful cases have been reported in Europe and North America. These cases are either developed by some natural evolution, or by design. The increasing popularity of eco-industrial parks is a typical approach for the realization of industrial symbioses by design. Limitations in terms of the available land in large cities as well as the scale and diversity of companies in an eco-industrial park constrain the scale and effectiveness of the approach .
Learning from past work and the authors’ own experiences, a big data analytics approach is proposed. The aim is to realize industrial symbioses based on the existing establishments in a large city by leveraging on the big number and varieties of industrial/institutions.
A study has been carried out to understand the ways and feasibility to develop industrial symbioses by such an approach. As a result, a framework and the feasible methods to develop a solution system is conceptualized and analyzed.
The solution framework consists of three major elements: data discovery and repository to develop a big data base, econetwork detection, and eco-network evaluation and optimization. Four types of waste to resource scenarios are identified in the formation of possible eco-networks. Included are direct waste to resources, indirect waste to resources, by product to higher value resources, and waste to new materials. By this approach, many-to-one or many-to-many econetworks can be generated. Cost-benefit analysis, coupled with necessary environmental assessment, can be applied to evaluate and optimize the eco-networks to form commercially viable industrial symbioses. The study has shown that the proposed approach should be technically feasible.
Some critical challenges need to be addressed in the realization of the proposed solution. These include, but not limited to, the algorithms to discover the comprehensive data required for each entity, the specific details in the quality and technical properties of the waste streams, and the representation and information on required technologies for the processing of waste streams to resources. Further research is being carried out to develop solutions for the critical challenges.
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