Application of geographical information system and agent-based modeling to estimate particle-gaseous pollutant emissions and transportation cost of woody biomass supply chain

2022 ◽  
Vol 309 ◽  
pp. 118482
Author(s):  
Seyed Mojib Zahraee ◽  
Nirajan Shiwakoti ◽  
Peter Stasinopoulos
2021 ◽  
Author(s):  
Angel Xin Yee Mah ◽  
Wai Shin Ho ◽  
Mimi H. Hassim ◽  
Haslenda Hashim ◽  
Zarina Ab Muis ◽  
...  

Abstract Hydrogen is a potential energy carrier for renewables that has a clean emission during the point of use. To implement hydrogen energy system in large-scale, a comprehensive hydrogen supply network should be built to supply the hydrogen with optimal infrastructure arrangement. Although the optimization of hydrogen supply chain has been extensively studied, the investigation of an integrated hydrogen-electricity supply chain is still lacking. Considering the interconvertibility of hydrogen and electricity, this study presents a spatial optimization framework that integrates geographical information system with mathematical modelling for the design and optimization of a photovoltaic-based hydrogen-electricity supply chain. The proposed framework allows the concurrent targeting of vehicle fuel and electricity demands as well as the identification of suitable locations for supply chain infrastructures. Case study results showed that the minimum cost of hydrogen-electricity supply chain is about 14.9 billion USD/y assuming two days of autonomy, and the cost of battery constitutes 43% of the total supply chain cost. When the days of autonomy is 8 and above, electricity storage in the form of hydrogen and reconversion through fuel cell is preferred.


2001 ◽  
Vol 14 (5-6) ◽  
pp. 233-242 ◽  
Author(s):  
Chao Tang ◽  
Li Da Xu ◽  
Shan Feng

2016 ◽  
Author(s):  
Annalisa Minelli ◽  
Cyril Tissot ◽  
Mathias Rouan ◽  
Matthieu Le Tixerant

This short paper presents an example of integration between open source Geographical Information System (GIS) and Agent Based Model (ABM) in order to better simulate fishing activities on Iroise Sea (Brittany, France). This work makes part of the SIMARIS project: a simulation prototype that integrate multi-source and multi-scale spatiotemporal constraints as forcing variable in order to assess the intensity and the variability of marine activities. A pre-processing step, executed in batch in GRASS GIS, aims to calculate data for initialization and simulation step, then the Agent Based simulation is launched (in batch) on GAMA platform. All these operations are scheduled in a Python script to perform pre-processing and simulation. The work presents an example of integration from a geographical point of view. The technical improvements are detailed and the potentials of such integrated solution are discussed.


2016 ◽  
Author(s):  
Annalisa Minelli ◽  
Cyril Tissot ◽  
Mathias Rouan ◽  
Matthieu Le Tixerant

This short paper presents an example of integration between open source Geographical Information System (GIS) and Agent Based Model (ABM) in order to better simulate fishing activities on Iroise Sea (Brittany, France). This work makes part of the SIMARIS project: a simulation prototype that integrate multi-source and multi-scale spatiotemporal constraints as forcing variable in order to assess the intensity and the variability of marine activities. A pre-processing step, executed in batch in GRASS GIS, aims to calculate data for initialization and simulation step, then the Agent Based simulation is launched (in batch) on GAMA platform. All these operations are scheduled in a Python script to perform pre-processing and simulation. The work presents an example of integration from a geographical point of view. The technical improvements are detailed and the potentials of such integrated solution are discussed.


2016 ◽  
Author(s):  
Annalisa Minelli ◽  
Cyril Tissot ◽  
Mathias Rouan ◽  
Matthieu Le Tixerant

This short paper presents an example of integration between open source Geographical Information System (GIS) and Agent Based Model (ABM) in order to better simulate fishing activities on Iroise Sea (Brittany, France). This work makes part of the SIMARIS project: a simulation prototype that integrate multi-source and multi-scale spatiotemporal constraints as forcing variable in order to assess the intensity and the variability of marine activities. A pre-processing step, executed in batch in GRASS GIS, aims to calculate data for initialization and simulation step, then the Agent Based simulation is launched (in batch) on GAMA platform. All these operations are scheduled in a Python script to perform pre-processing and simulation. The work presents an example of integration from a geographical point of view. The technical improvements are detailed and the potentials of such integrated solution are discussed.


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