A simplified logistics model for integrating BIMAT and IBSAL to estimate harvest costs, energy input and emissions

2019 ◽  
pp. 8.1-8.8
Author(s):  
Shahab Sokhansanj ◽  
Mahmood Ebadian ◽  
Lawrence Townley-Smith ◽  
David Lee

The Agriculture and Agri-Food’s Biomass Inventory Mapping and Analysis Tool (BIMAT) provides internet-based GIS functionality to query and visualize biomass inventory data in Canada. The Integrated Biomass Supply Analysis and Logistics (IBSAL) model is a modularized simulation of biomass supply chain. In this study, IBSAL modules are assembled to simulate harvesting of straw, stover, and switchgrass yields. The operations in this study started from combining for grain crop residues and ended in stacking bales on the field side. The equation C=aR^b Y^c was fitted to the simulated data to estimate constants a, b, and c for cost in $/dry tonne, energy input in MJ/dry tonne, and carbon emissions in kg CO2/dry tonne. Variable R is the fraction of above ground biomass removed during harvest and Y is the yield defined as biomass above ground (dry tonne/ha). These functions are supplied to the BIMAT portal and developed specific values for costs, energy input, and emissions on the map. The farm gate cost cost for the stacked bales ranged from $20 per dry tonne for high yielding regions of southwest Edmonton and Ontario to $27 per dry tonne for the eastern Ottawa region, and $31 per dry tonne for low yielding regions of central Saskatchewan. The costs are validated with published custom rates. It is recommended that the next step is to integrate IBSAL and BIMAT codes so the logistics values are generated and shown automatically on the map.

Energies ◽  
2019 ◽  
Vol 12 (15) ◽  
pp. 3020 ◽  
Author(s):  
Efthymios Rodias ◽  
Remigio Berruto ◽  
Dionysis Bochtis ◽  
Alessandro Sopegno ◽  
Patrizia Busato

Various sources of biomass contribute significantly in energy production globally given a series of constraints in its primary production. Green biomass sources (such as perennial grasses), yellow biomass sources (such as crop residues), and woody biomass sources (such as willow) represent the three pillars in biomass production by crops. In this paper, we conducted a comprehensive review on research studies targeted to advancements at biomass supply-chain management in connection to these three types of biomass sources. A framework that classifies the works in problem-based and methodology-based approaches was followed. Results show the use of modern technological means and tools in current management-related problems. From the review, it is evident that the presented up-to-date trends on biomass supply-chain management and the potential for future advanced approach applications play a crucial role on business and sustainability efficiency of biomass supply chain.


2016 ◽  
Vol 83 ◽  
pp. 1-11 ◽  
Author(s):  
Annelies De Meyer ◽  
Monique Snoeck ◽  
Dirk Cattrysse ◽  
Jos Van Orshoven

2021 ◽  
Vol 148 ◽  
pp. 106054
Author(s):  
Lina Martinez-Valencia ◽  
Dane Camenzind ◽  
Mark Wigmosta ◽  
Manuel Garcia-Perez ◽  
Michael Wolcott

2011 ◽  
Vol 150 (5) ◽  
pp. 584-594 ◽  
Author(s):  
V. A. PAPPA ◽  
R. M. REES ◽  
R. L. WALKER ◽  
J. A. BADDELEY ◽  
C. A. WATSON

SUMMARYIntercropping systems that include legumes can provide symbiotically fixed nitrogen (N) and potentially increase yield through improved resource use efficiency. The aims of the present study were: (a) to evaluate the effects of different legumes (species and varieties) and barley on grain yield, dry matter production and N uptake of the intercrop treatments compared with the associated cereal sole crop; (b) to assess the effects on the yields of the next grain crop and (c) to determine the accumulation of N in shoots of the crops in a low-input rotation. An experiment was established near Edinburgh, UK, consisting of 12 hydrologically isolated plots. Treatments were a spring barley (Hordeum vulgare cvar Westminster) sole crop and intercrops of barley/white clover (Trifolium repens cvar Alice) and barley/pea (Pisum sativum cvar Zero4 or cvar Nitouche) in 2006. All the plots were sown with spring oats (Avena sativa cvar Firth) in 2007 and perennial ryegrass in 2008. No fertilizers, herbicides or pesticides were used at any stage of the experiment. Above-ground biomass (barley, clover, pea, oat and ryegrass) and grain yields (barley, pea and oat) were measured at key stages during the growing seasons of 2006, 2007 and 2008; land equivalent ratio (LER) was measured only in 2006. At harvest, the total above-ground biomass of barley intercropped with clover (4·56 t biomass/ha) and barley intercropped with pea cvar Zero4 (4·49 t biomass/ha) were significantly different from the barley sole crop (3·05 t biomass/ha; P<0·05). The grain yield of the barley (2006) intercropped with clover (3·36 t grain/ha) was significantly greater than that in the other treatments (P<0·01). The accumulation of N in barley was low in 2006, but significantly higher (P<0·05) in the oat grown the following year on the same plots. The present study demonstrates for the first time that intercrops can affect the grain yield and N uptake of the following crop (spring oats) in a rotation. Differences were also linked to the contrasting legume species and cultivars present in the previous year's intercrop. Legume choice is essential to optimize the plant productivity in intercropping designs. Cultivars chosen for intercropping purposes must take into account the effects upon the growth of the partner crop/s as well as to the following crop, including environmental factors.


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