Synthesis of optimal and near-optimal biochar-based Carbon Management Networks with P-graph

The application of biochar to soil is a potentially significant way to achieve negative net emissions. Photosynthesis fixes carbon from the atmosphere during plant growth; subsequently, pyrolysis stabilizes the carbon in biomass into recalcitrant form, which results in long-term storage when the carbonized product is put in soil. However, effective planning of such Biochar-based Carbon Management Networks is needed to ensure that benefits are maximized, and that adverse consequences are mitigated. The objective of this work is to develop a P-graph methodology for planning Biochar-based Carbon Management Networks, where pyrolysis plants act as sources, while the agricultural lands that receive the biochar act as sinks. Two problem variants are considered. In the first case study, the allocation of biochar is constrained by the presence of contaminants that exist naturally in the biomass or are formed during pyrolysis, such that only 72.5% of the available biochar is applied to soil. In the second case study, the distribution of biochar is limited both by the ultimate soil carbon limit, as well as annual application rates at each site; 88.9% of the available biochar is used in the optimal solution. The P-graph framework also generates near-optimal network topologies, which present alternative solutions that can be useful for the large-scale implementation of Biochar-based Carbon Management Networks.

[1]  Ferenc Friedler,et al.  Synthesis of processing systems taking into account reliability , 2018 .

[2]  Guiyao Zhou,et al.  Effects of biochar application on soil greenhouse gas fluxes: a meta‐analysis , 2017 .

[3]  János Abonyi,et al.  Reliability - Redundancy allocation in process graphs , 2018 .

[4]  Raymond R. Tan,et al.  Fuzzy P-graph for optimal synthesis of cogeneration and trigeneration systems , 2018, Energy.

[5]  Jiří Jaromír Klemeš,et al.  Process network design and optimisation using P-graph: The success, the challenges and potential roadmap , 2017 .

[6]  Dominic C.Y. Foo,et al.  P-graph and Monte Carlo simulation approach to planning carbon management networks , 2017, Comput. Chem. Eng..

[7]  L. T. Fan,et al.  Combinatorially Accelerated Branch-and-Bound Method for Solving the MIP Model of Process Network Synthesis , 1996 .

[8]  J. Amonette,et al.  Sustainable biochar to mitigate global climate change , 2010, Nature communications.

[9]  Raymond R. Tan,et al.  Problem-based learning of process systems engineering and process integration concepts with metacognitive strategies: The case of P-graphs for polygeneration systems , 2017 .

[10]  Mark A. Kramer,et al.  Autoassociative neural networks , 1992 .

[11]  Raymond R. Tan,et al.  Pinch analysis approach to optimal planning of biochar-based carbon management networks , 2017, 2017 6th International Symposium on Advanced Control of Industrial Processes (AdCONIP).

[12]  Botond Bertók,et al.  Synthesis and Analysis of Process Networks by Joint Application of P-graphs and Petri Nets , 2017, Petri Nets.

[13]  Igor Bulatov,et al.  Sustainability in the Process Industry: Integration and Optimization , 2010 .

[14]  L. T. Fan,et al.  Graph-theoretic approach to process synthesis: Polynomial algorithm for maximal structure generation , 1993 .

[15]  Jiří Jaromír Klemeš,et al.  New directions in the implementation of Pinch Methodology (PM) , 2018, Renewable and Sustainable Energy Reviews.

[18]  Raymond R. Tan,et al.  A multi-period source–sink mixed integer linear programming model for biochar-based carbon sequestration systems , 2016 .

[19]  J. Váchal,et al.  Biochar pricing hampers biochar farming , 2016, Clean Technologies and Environmental Policy.

[20]  Duncan McLaren,et al.  A comparative global assessment of potential negative emissions technologies , 2012 .

[21]  Raymond R. Tan,et al.  Towards generalized process networks: prospective new research frontiers for the p-graph framework , 2018 .

[22]  Brent A. Gloy,et al.  Life cycle assessment of biochar systems: estimating the energetic, economic, and climate change potential. , 2010, Environmental science & technology.

[23]  Raymond R. Tan,et al.  Implementation of P-graph modules in undergraduate chemical engineering degree programs: experiences in Malaysia and the Philippines , 2016 .

[24]  R. Naidu,et al.  Agronomic and remedial benefits and risks of applying biochar to soil: Current knowledge and future research directions. , 2016, Environment international.

[25]  Pete Smith,et al.  The potential for implementation of Negative Emission Technologies in Scotland , 2018, International Journal of Greenhouse Gas Control.

[26]  O. Mašek,et al.  Pyrolysis biochar systems, balance between bioenergy and carbon sequestration , 2015 .

[27]  J. Amonette,et al.  Role of Biochar in Mitigation of Climate Change , 2010 .

[28]  Ferenc Friedler,et al.  Combinatorial algorithms for process synthesis , 1992 .

[29]  J. Klemeš,et al.  Enabling low-carbon emissions for sustainable development in Asia and beyond , 2018 .

[30]  J. Gyenis,et al.  Computerized generation of technological structures , 1979 .

[31]  B. A. Belmonte,et al.  Biochar systems in the water-energy-food nexus: the emerging role of process systems engineering , 2017 .

[32]  André Bardow,et al.  The optimum is not enough: A near-optimal solution paradigm for energy systems synthesis , 2015 .

[33]  Raymond R. Tan,et al.  Bi-objective optimization of biochar-based carbon management networks , 2018, Journal of Cleaner Production.

[34]  Ferenc Friedler,et al.  Design and engineering of sustainable process systems and supply chains by the P‐graph framework , 2018 .

[35]  B. A. Belmonte,et al.  A two-stage optimization model for the synthesis of biochar-based carbon management networks , 2017 .

[36]  Raymond R. Tan,et al.  Process Integration and Climate Change: From Carbon Emissions Pinch Analysis to Carbon Management Networks , 2018 .

[37]  Heriberto Cabezas,et al.  Energy consumption optimization of a manufacturing plant by the application of the p-graph framework , 2018 .

[38]  Ferenc Friedler,et al.  Process synthesis involving multi-period operations by the P-graph framework , 2015, Comput. Chem. Eng..

[39]  S. Ogle,et al.  Climate-smart soils , 2016, Nature.

[40]  Division on Earth,et al.  Negative Emissions Technologies and Reliable Sequestration , 2019 .

[41]  L. T. Fan,et al.  Graph-theoretic approach to process synthesis: axioms and theorems , 1992 .

[42]  J. J. Klemeš,et al.  Spreading the Message: P-graph Enhancements: Implementations and Applications , 2015 .

[43]  Botond Bertók,et al.  Process graph approach for two-stage decision making: Transportation contracts , 2019, Comput. Chem. Eng..

[44]  Gareth Johnson,et al.  Negative emissions technologies and carbon capture and storage to achieve the Paris Agreement commitments , 2018, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[45]  Rodrigo Navia,et al.  Environmental hotspots in the life cycle of a biochar-soil system , 2017 .

[46]  Pete Smith Soil carbon sequestration and biochar as negative emission technologies , 2016, Global change biology.

[47]  Raymond R. Tan,et al.  P-graph approach to planning human resource expansion for universities in transition , 2018 .

[48]  Hon Loong Lam,et al.  Extended P-graph applications in supply chain and Process Network Synthesis , 2013 .

[49]  Jiří Jaromír Klemeš,et al.  Recent developments in Process Integration , 2013 .

[50]  J. Klemeš,et al.  Pre- and Post-Treatment Assessment for the Anaerobic Digestion of Lignocellulosic Waste: P-graph , 2018 .

[51]  Jiří Jaromír Klemeš,et al.  A review on the global warming potential of cleaner composting and mitigation strategies , 2017 .

[52]  Nilay Shah,et al.  High-level techno-economic assessment of negative emissions technologies , 2012 .

[53]  Ignacio E. Grossmann,et al.  Search for reaction pathways with P-graphs and reaction blocks: methanation of carbon dioxide with hydrogen , 2018, Journal of Mathematical Chemistry.