scholarly journals Hubs for Circularity: Geo-Based Industrial Clustering towards Urban Symbiosis in Europe

2021 ◽  
Vol 13 (24) ◽  
pp. 13906
Author(s):  
Francisco Mendez Alva ◽  
Rob De Boever ◽  
Greet Van Eetvelde
Keyword(s):  
Circular Economy ◽  
Spatial Clustering ◽  
Industrial Symbiosis ◽  
Process Industries ◽  
Industrial Facilities ◽  
Industrial Activities ◽  
Industrial Landscape ◽  
Dbscan Algorithm ◽  
Community Stakeholders ◽  
Lime Plaster

Since the Green Deal, ambitious climate and resource neutrality goals have been set in Europe. Here, process industries hold a unique position due to their energy and material transformation capabilities. They are encouraged to develop cross-sectorial hubs for achieving not only climate ambition, but also joining a circular economy through urban–industrial symbiosis with both business and community stakeholders. This research proposes a data-based approach to identify potential hub locations by means of cluster analysis. A total of three different algorithms are compared on a set of location and pollution data of European industrial facilities: K-means, hierarchical agglomerative and density-based spatial clustering. The DBSCAN algorithm gave the best indication of potential locations for hubs because of its capacity to tune the main parameters. It evidenced that predominately west European countries have a high potential for identifying hubs for circularity (H4Cs) due to their industrial density. In Eastern Europe, the industrial landscape is more scattered, suggesting that additional incentives might be needed to develop H4Cs. Furthermore, industrial activities such as the production of aluminium, cement, lime, plaster, or electricity are observed to have a relatively lower tendency to cluster compared with the petrochemical sector. Finally, further lines of research to identify and develop industrial H4Cs are suggested.

Reuse of CO2 in energy intensive process industries

2021 ◽  
Author(s):  
Siglinda Perathoner ◽  
Kevin M. Van Geem ◽  
Guy B. Marin ◽  
Gabriele Centi
Keyword(s):  
Carbon Cycle ◽  
Circular Economy ◽  
Process Industries ◽  
Iron And Steel ◽  
Energy Intensive Industries

Closing the carbon cycle and enabling a carbon circular economy in energy intensive industries (iron and steel, cement, refineries, petrochemistry and fertilizers) are topics of increasing interest to meet the...

scholarly journals A Modelling Framework for the Conceptual Design of Low-Emission Eco-Industrial Parks in the Circular Economy: A Case for Algae-Centered Business Consortia

Water ◽  
2020 ◽  
Vol 13 (1) ◽  
pp. 69
Author(s):  
Aldric S. Tumilar ◽  
Dia Milani ◽  
Zachary Cohn ◽  
Nick Florin ◽  
Ali Abbas
Keyword(s):  
Circular Economy ◽  
Carbon Capture ◽  
Fossil Fuel ◽  
Production Systems ◽  
Flow Analysis ◽  
Biofuel Production ◽  
Industrial Symbiosis ◽  
Modelling Framework ◽  
Low Emission ◽  
Energy Exchanges

This article describes a unique industrial symbiosis employing an algae cultivation unit (ACU) at the core of a novel eco-industrial park (EIP) integrating fossil-fuel fired power generation, carbon capture, biofuel production, aquaculture, and wastewater treatment. A new modelling framework capable of designing and evaluating materials and energy exchanges within an industrial eco-system is introduced. In this scalable model, an algorithm was developed to balance the material and energy exchanges and determine the optimal inputs and outputs based on the industrial symbiosis objectives and participating industries. Optimizing the functionality of the ACU not only achieved a substantial emission reduction, but also boosted aquaculture, biofuel, and other chemical productions. In a power-boosting scenario (PBS), by matching a 660 MW fossil fuel-fired power plant with an equivalent solar field in the presence of ACU, fish-producing aquaculture and biofuel industries, the net CO2 emissions were cut by 60% with the added benefit of producing 39 m3 biodiesel, 6.7 m3 bioethanol, 0.14 m3 methanol, and 19.55 tons of fish products annually. Significantly, this article shows the potential of this new flexible modelling framework for integrated materials and energy flow analysis. This integration is an important pathway for evaluating energy technology transitions towards future low-emission production systems, as required for a circular economy.

scholarly journals Utilizing Urban Geospatial Data to Understand Heritage Attractiveness in Amsterdam

2021 ◽  
Vol 10 (4) ◽  
pp. 198
Author(s):  
Sevim Sezi Karayazi ◽  
Gamze Dane ◽  
Bauke de Vries
Keyword(s):  
Geographically Weighted Regression ◽  
Spatial Clustering ◽  
Least Square ◽  
Geospatial Data ◽  
Evidence Based ◽  
Ordinary Least Square ◽  
Mass Tourism ◽  
Dbscan Algorithm ◽  
National Monuments ◽  
Combined Data

Touristic cities are home to historical landmarks and irreplaceable urban heritages. Although tourism brings financial advantages, mass tourism creates pressure on historical cities. Therefore, “attractiveness” is one of the key elements to explain tourism dynamics. User-contributed and geospatial data provide an evidence-based understanding of people’s responses to these places. In this article, the combination of multisource information about national monuments, supporting products (i.e., attractions, museums), and geospatial data are utilized to understand attractive heritage locations and the factors that make them attractive. We retrieved geotagged photographs from the Flickr API, then employed density-based spatial clustering of applications with noise (DBSCAN) algorithm to find clusters. Then combined the clusters with Amsterdam heritage data and processed the combined data with ordinary least square (OLS) and geographically weighted regression (GWR) to identify heritage attractiveness and relevance of supporting products in Amsterdam. The results show that understanding the attractiveness of heritages according to their types and supporting products in the surrounding built environment provides insights to increase unattractive heritages’ attractiveness. That may help diminish the burden of tourism in overly visited locations. The combination of less attractive heritage with strong influential supporting products could pave the way for more sustainable tourism in Amsterdam.

Energy conservation and circular economy in China's process industries

Energy ◽  
2010 ◽  
Vol 35 (11) ◽  
pp. 4273-4281 ◽  
Author(s):  
Huiquan Li ◽  
Weijun Bao ◽  
Caihong Xiu ◽  
Yi Zhang ◽  
Hongbin Xu
Keyword(s):  
Energy Conservation ◽  
Circular Economy ◽  
Process Industries

scholarly journals Object-Independent Grasping in Heavy Clutter

2020 ◽  
Vol 10 (3) ◽  
pp. 804 ◽  
Author(s):  
HyunJun Jo ◽  
Jae-Bok Song
Keyword(s):  
Spatial Clustering ◽  
Computational Time ◽  
Success Rates ◽  
Computational Costs ◽  
Difference Image ◽  
Cluttered Environment ◽  
Depth Difference ◽  
Dbscan Algorithm ◽  
Bin Picking ◽  
Object Region

When grasping objects in a cluttered environment, a key challenge is to find appropriate poses to grasp effectively. Accordingly, several grasping algorithms based on artificial neural networks have been developed recently. However, these methods require large amounts of data for learning and high computational costs. Therefore, we propose a depth difference image-based bin-picking (DBP) algorithm that does not use a neural network. DBP predicts the grasp pose from the object and its surroundings, which are obtained through depth filtering and clustering. The object region is estimated by the density-based spatial clustering of applications with noise (DBSCAN) algorithm, and a depth difference image (DDI) that represents the depth difference between adjacent areas is defined. To validate the performance of the DBP scheme, bin-picking experiments were conducted on 45 different objects, along with bin-picking experiments in heavy clutters. DBP exhibited success rates of 78.6% and 83.3%, respectively. In addition, DBP required a computational time of approximately 1.4 s for each attempt.

scholarly journals Towards Circular Economy Solutions for The Management of Rice Processing Residues to Bioenergy via Gasification

2019 ◽  
Vol 11 (22) ◽  
pp. 6433 ◽  
Author(s):  
Vaskalis ◽  
Skoulou ◽  
Stavropoulos ◽  
Zabaniotou
Keyword(s):  
Waste Management ◽  
Value Chain ◽  
Circular Economy ◽  
Economic Assessment ◽  
Stoichiometric Ratio ◽  
Industrial Symbiosis ◽  
Rice Husks ◽  
Experimental Proof ◽  
Custom Made ◽  
Rice Processing

A techno-economic assessment of two circular economy scenarios related to fluidized bed gasification-based systems for combined heat and power (CHP) generation, fueled with rice processing wastes, was conducted. In the first scenario, a gasification unit with 42,700 t/y rice husks capacity provided a waste management industrial symbiosis solution for five small rice-processing companies (SMEs), located at the same area. In the second scenario, a unit of 18,300 t/y rice husks capacity provided a waste management solution to only one rice processing company at the place of waste generation, as a custom-made solution. The first scenario of a cooperative industrial symbiosis approach is the most economically viable, with an annual revenue of 168 €/(t*y) of treated rice husks, a very good payout time (POT = 1.05), and return in investment (ROI = 0.72). The techno-economic assessment was based on experiments performed at a laboratory-scale gasification rig, and on technological configurations of the SMARt-CHP system, a decentralized bioenergy generation system developed at Aristotle University, Greece. The experimental proof of concept of rice husks gasification was studied at a temperature range of 700 to 900 °C, under an under-stoichiometric ratio of O2/N2 (10/90 v/v) as the gasification agent. Producer gas’s Lower Heating Value (LHV) maximized at 800 °C (10.9 MJ/Nm3), while the char’s Brunauer Emmet Teller (BET) surface reached a max of 146 m2/g at 900 °C. Recommendations were provided for a pretreatment of rice husks in order to minimize de-fluidization problems of the gasification system due to Si-rich ash. With the application of this model, simultaneous utilization and processing of waste flows from various rice value chain can be achieved towards improving environmental performance of the companies and producing energy and fertilizer by using waste as a fuel and resource with value.

scholarly journals Methodology for Extracting Potential Customized Bus Routes Based on Bus Smart Card Data

Energies ◽  
2018 ◽  
Vol 11 (9) ◽  
pp. 2224 ◽  
Author(s):  
Jing Li ◽  
Yongbo Lv ◽  
Jihui Ma ◽  
Qi Ouyang
Keyword(s):  
Smart Card ◽  
Traffic Congestion ◽  
Spatial Clustering ◽  
Extraction Process ◽  
Methodological Framework ◽  
Transit Service ◽  
Dbscan Algorithm ◽  
Smart Card Data ◽  
Division Process

To alleviate traffic congestion and traffic-related environmental pollution caused by the increasing numbers of private cars, public transport (PT) is highly recommended to travelers. However, there is an obvious contradiction between the diversification of travel demands and simplification of PT service. Customized bus (CB), as an innovative supplementary mode of PT service, aims to provide demand-responsive and direct transit service to travelers with similar travel demands. But how to obtain accurate travel demands? It is passive and limited to conducting online surveys, additionally inefficient and costly to investigate all the origin-destinations (ODs) aimlessly. This paper proposes a methodological framework of extracting potential CB routes from bus smart card data to provide references for CB planners to conduct purposeful and effective investigations. The framework consists of three processes: trip reconstruction, OD area division and CB route extraction. In the OD area division process, a novel two-step division model is built to divide bus stops into different areas. In the CB route extraction process, two spatial-temporal clustering procedures and one length constraint are implemented to cluster similar trips together. An improved density-based spatial clustering of application with noise (DBSCAN) algorithm is used to complete these procedures. In addition, a case study in Beijing is conducted to demonstrate the effectiveness of the proposed methodological framework and the resulting analysis provides useful references to CB planners in Beijing.

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