Peanut Shell for Energy: Properties and Its Potential to Respect the Environment
Abstract
:1. Introduction
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- Reduce 20% of the emissions of greenhouse gases (GHG) that were recorded in 1990 (well above the Kyoto target of 8%).
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- Achieve that renewable sources constitute 20% of total energy consumption.
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- Improve energy efficiency by 20%.
2. Materials and Methods
2.1. Peanut Shells from Industrial Processing Samples for the Study
2.2. Quality Parameters for Peanut Shell
2.2.1. Physical Parameters
2.2.2. Chemical Parameters
Elemental Analysis
Immediate Analysis
2.2.3. Energy Parameters
3. Results and Discussion
3.1. Peanut Shell Quality Parameters
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- Stoves, usually of pellets or wood, that create a single room and usually act simultaneously as decorative elements.
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- Low power boilers for single-family homes or small buildings.
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- Boilers designed for a block or building of flats, which act as central heating.
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- Thermal power stations that heat several buildings or installations (district heating) or a group of houses.
3.2. Predictive Models for Estimating the HHV of Peanut Shell
3.3. Potential of Peanut Shell for Reducing CO2 Emissions
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- Efficiency improvement.
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- Limitation of inefficient coal-fired power stations.
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- Decrease in methane emissions from oil and gas.
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- Reform of fossil fuel subsidies.
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- Increase in renewable energies, without their use leading to a loss of competition with respect to other countries where there are no measures to reduce greenhouse gas emissions.
4. Conclusions
Author Contributions
Funding
Conflicts of Interest
References
- Nie, S.; Huang, Z.C.; Huang, G.H.; Yu, L.; Liu, J. Optimization of electric power systems with cost minimization and environmental-impact mitigation under multiple uncertainties. Appl. Energy 2018, 221, 249–267. [Google Scholar] [CrossRef]
- Zhang, S.; Ren, H.; Zhou, W.; Yu, Y.; Chen, C. Assessing air pollution abatement co-benefits of energy efficiency improvement in cement industry: A city level analysis. J. Clean. Prod. 2018, 185, 761–771. [Google Scholar] [CrossRef]
- Jung, J.; Koo, Y. Analyzing the Effects of Car Sharing Services on the Reduction of Greenhouse Gas (GHG) Emissions. Sustainability 2018, 10, 539. [Google Scholar] [CrossRef]
- Lee, S.; Kim, M.; Lee, J. Analyzing the Impact of Nuclear Power on CO2 Emissions. Sustainability 2017, 9, 1428. [Google Scholar] [CrossRef]
- Cho, S.; Na, S. The Reduction of CO2 Emissions by Application of High-Strength Reinforcing Bars to Three Different Structural Systems in South Korea. Sustainability 2017, 9, 1652. [Google Scholar]
- O’reilly, C.M.; Alin, S.R.; Plisnier, P.D.; Cohen, A.S.; McKee, B.A. Climate change decreases aquatic ecosystem productivity of Lake Tanganyika, Africa. Nature 2003, 424, 766. [Google Scholar] [CrossRef] [PubMed]
- Garrabou, J.; Coma, R.; Bensoussan, N.; Bally, M.; Chevaldonné, P.; Cigliano, M.; Diaz, D.; Harmelin, J.G.; Gambi, M.C.; Kersting, D.K.; et al. Mass mortality in Northwestern Mediterranean rocky benthic communities: Effects of the 2003 heat wave. Glob. Chang. Biol. 2009, 15, 1090–1103. [Google Scholar] [CrossRef]
- Wilby, R.L.; Dawson, C.W.; Barrow, E.M. SDSM—A decision support tool for the assessment of regional climate change impacts. Environ. Model. Softw. 2002, 17, 145–157. [Google Scholar] [CrossRef]
- Reckien, D.; Heidrich, O.; Church, J.; Pietrapertos, F.; De Gregorio-Hurtado, S.; D’Alonzo, V.; Foley, A.; Simoes, S.G.; Lorencová, E.K.; Orruk, H.; et al. How are cities planning to respond to climate change? assessment of local climate plans from 885 cities in the EU-28. J. Clean. Prod. 2018, 191, 207–219. [Google Scholar] [CrossRef]
- D’Agostino, D.; Parker, D. A framework for the cost-optimal design of nearly zero energy buildings (NZEBs) in representative climates across Europe. Energy 2018, 149, 814–829. [Google Scholar] [CrossRef]
- De la Cruz-Lovera, C.; Perea-Moreno, A.-J.; de la Cruz-Fernández, J.-L.; Alvarez-Bermejo, J.A.; Manzano-Agugliaro, F. Worldwide Research on Energy Efficiency and Sustainability in Public Buildings. Sustainability 2017, 9, 1294. [Google Scholar] [CrossRef]
- Yama, A.; Abe, N. Ex-post assessment of the Kyoto protocol—Quantification of CO2 mitigation impact in both annex B and non-annex B countries. Appl. Energy 2018, 220, 286–295. [Google Scholar] [CrossRef]
- Nava, C.R.; Meleo, L.; Cassetta, E.; Morelli, G. The impact of the EU-ETS on the aviation sector: Competitive effects of abatement efforts by airlines. Transp. Res. Part A Policy Pract. 2018, 113, 20–34. [Google Scholar] [CrossRef] [Green Version]
- Newbery, D.; Pollitt, M.G.; Ritz, R.A.; Strielkowski, W. Market design for a high-renewables European electricity system. Renew. Sustain. Energy Rev. 2018, 91, 695–707. [Google Scholar] [CrossRef]
- European Commission. EU Reference Scenario 2016 Energy, Transport and GHG Emissions—Trends to 2050 Main Results. 2016. Available online: https://ec.europa.eu/energy/sites/ener/files/documents/20160712_Summary_Ref_scenario_MAIN_RESULTS%20(2)-web.pdf (accessed on 20 July 2018).
- Gallo, C.; Faccilongo, N.; La Sala, P. Clustering analysis of environmental emissions: A study on Kyoto protocol’s impact on member countries. J. Clean. Prod. 2018, 172, 3685–3703. [Google Scholar] [CrossRef]
- Ali, Y. Carbon, water and land use accounting: Consumption vs production perspectives. Renew. Sustain. Energy Rev. 2017, 67, 921–934. [Google Scholar] [CrossRef]
- Perea-Moreno, M.-A.; Hernandez-Escobedo, Q.; Perea-Moreno, A.-J. Renewable Energy in Urban Areas: Worldwide Research Trends. Energies 2018, 11, 577. [Google Scholar] [CrossRef]
- Perea-Moreno, A.-J.; Perea-Moreno, M.-A.; Hernandez-Escobedo, Q.; Manzano-Agugliaro, F. Towards forest sustainability in mediterranean countries using biomass as fuel for heating. J. Clean. Prod. 2017, 156, 624–634. [Google Scholar] [CrossRef]
- Pleßmann, G.; Blechinger, P. Outlook on south-east European power system until 2050: Least-cost decarbonization pathway meeting EU mitigation targets. Energy 2017, 137, 1041–1053. [Google Scholar] [CrossRef]
- Perea-Moreno, A.-J.; Aguilera-Ureña, M.-J.; Manzano-Agugliaro, F. Fuel properties of avocado stone. Fuel 2016, 186, 358–364. [Google Scholar] [CrossRef]
- Filipe dos Santos Viana, H.; Martins Rodrigues, A.; Godina, R.; Carlos de Oliveira Matias, J.; Jorge Ribeiro Nunes, L. Evaluation of the Physical, Chemical and Thermal Properties of Portuguese Maritime Pine Biomass. Sustainability 2018, 10, 2877. [Google Scholar] [CrossRef]
- Agugliaro, F.M. Gasification of greenhouse residues for obtaining electrical energy in the south of Spain: Localization by GIS. Interciencia 2007, 32, 131–136. [Google Scholar]
- Casanova-Peláez, P.J.; Palomar-Carnicero, J.M.; Manzano-Agugliaro, F.; Cruz-Peragón, F. Olive cake improvement for bioenergy: The drying kinetics. Int. J. Green Energy 2015, 12, 559–569. [Google Scholar] [CrossRef]
- Perea-Moreno, A.J.; Juaidi, A.; Manzano-Agugliaro, F. Solar greenhouse dryer system for wood chips improvement as biofuel. J. Clean. Prod. 2016, 135, 1233–1241. [Google Scholar] [CrossRef]
- Manzano-Agugliaro, F.; Sanchez-Muros, M.J.; Barroso, F.G.; Martínez-Sánchez, A.; Rojo, S.; Pérez-Bañón, C. Insects for biodiesel production. Renew. Sustain. Energy Rev. 2012, 16, 3744–3753. [Google Scholar] [CrossRef]
- Al-Hamamre, Z.; Saidan, M.; Hararah, M.; Rawajfeh, K.; Alkhasawneh, H.E.; Al-Shannag, M. Wastes and biomass materials as sustainable-renewable energy resources for Jordan. Renew. Sustain. Energy Rev. 2017, 67, 295–314. [Google Scholar] [CrossRef]
- Yevich, R.; Logan, J.A. An assessment of biofuel use and burning of agricultural waste in the developing world. Glob. Biogeochem. Cycles 2003, 17. [Google Scholar] [CrossRef] [Green Version]
- Hammons, R.O.; Herman, D.; Stalker, H.T. Origin and early history of the peanut. In Peanuts; Elsevier: Amsterdam, The Netherlands, 2016; pp. 1–26. [Google Scholar]
- McArthur, W.C.; Grise, V.N.; Doty, H.O., Jr.; Hacklander, D.; US Peanut Industry; US Department of Agriculture; Economic Research Service. Agricultural Economics Report; EMS Publications: Washington, DC, USA, 1982; p. 493.
- Ramos, M.J.; Fernández, C.M.; Casas, A.; Rodríguez, L.; Pérez, Á. Influence of fatty acid composition of raw materials on biodiesel properties. Bioresour. Technol. 2009, 100, 261–268. [Google Scholar] [CrossRef] [PubMed]
- FAOSTAT. Agriculture Data. 2016. Available online: http://www.fao.org/faostat/en/#home (accessed on 13 May 2018).
- Olayinka, B.U.; Etejere, E.O. Growth analysis and yield of two varieties of groundnut (Arachis hypogaea L.) as influenced by different weed control methods. Indian J. Plant Physiol. 2015, 20, 130–136. [Google Scholar] [CrossRef] [PubMed]
- Zhao, X.; Chen, J.; Du, F. Potential use of peanut by-products in food processing: A review. J. Food Sci. Technol. 2012, 49, 521–529. [Google Scholar] [CrossRef] [PubMed]
- Rinaldi, A.; Schweiker, M.; Iannone, F. On uses of energy in buildings: Extracting influencing factors of occupant behaviour by means of a questionnaire survey. Energy Build. 2018, 168, 298–308. [Google Scholar] [CrossRef]
- Sebastián Nogués, F. Energía de la Biomasa; Prensas Universitarias de Zaragoza: Zaragoza, Spain, 2010; Volume I, p. 558. ISBN 978-84-92774-91-3. [Google Scholar]
- Mata-Sánchez, J.; Pérez-Jiménez, J.A.; Díaz-Villanueva, M.J.; Serrano, A.; Núñez-Sánchez, N.; López-Giménez, F.J. Statistical evaluation of quality parameters of olive stone to predict its heating value. Fuel 2013, 113, 750–756. [Google Scholar] [CrossRef]
- García, R.; Pizarro, C.; Lavín, A.G.; Bueno, J.L. Spanish biofuels heating value estimation. Part I: Ultimate analysis data. Fuel 2014, 117, 1130–1138. [Google Scholar] [CrossRef]
- García, R.; Pizarro, C.; Lavín, A.G.; Bueno, J.L. Biomass sources for thermal conversion. Techno-economical overview. Fuel 2017, 195, 182–189. [Google Scholar] [CrossRef]
- Arranz, J.I.; Miranda, M.T.; Montero, I.; Sepúlveda, F.J.; Rojas, C.V. Characterization and combustion behaviour of commercial and experimental wood pellets in south west Europe. Fuel 2015, 142, 199–207. [Google Scholar] [CrossRef]
- Gómez, N.; Rosas, J.G.; Cara, J.; Martínez, O.; Alburquerque, J.A.; Sánchez, M.E. Slow pyrolysis of relevant biomasses in the mediterranean basin. Part 1. Effect of temperature on process performance on a pilot scale. J. Clean. Prod. 2016, 120, 181–190. [Google Scholar] [CrossRef]
- González, J.F.; González-García, C.M.; Ramiro, A.; Gañán, J.; González, J.; Sabio, E.; Román, S.; Turegano, J. Use of almond residues for domestic heating: Study of the combustion parameters in a mural boiler. Fuel Process. Technol. 2005, 86, 1351–1368. [Google Scholar] [CrossRef]
- Abe, H.; Katayama, A.; Sah, B.P.; Toriu, T.; Samy, S.; Pheach, P.; Adams, M.A.; Grierson, P.F. Potential for rural electrification based on biomass gasification in Cambodia. Biomass Bioenergy 2007, 31, 656–664. [Google Scholar] [CrossRef]
- Singh, M.; Singh, R.; Gill, G. Estimating the correlation between the calorific value and elemental components of biomass using regrassion analysis. Int. J. Ind. Electron. Electr. Eng. 2015, 3, 18–23. [Google Scholar]
- Jenkins, B.M.; Ebeling, J.M. Correlations of physical and chemical properties of terrestrial biomass with conversion. In Symposium Papers-Energy from Biomass and Wastes; Inst of Gas Technology: Des Plaines, IL, USA, 1985; pp. 371–403. [Google Scholar]
- Sheng, C.; Azevedo, J.L.T. Estimating the higher heating value of biomass fuels from basic analysis data. Biomass Bioenergy 2005, 28, 499–507. [Google Scholar] [CrossRef]
- Yin, C.Y. Prediction of higher heating values of biomass from proximate and ultimate analyses. Fuel 2011, 90, 1128–1132. [Google Scholar] [CrossRef] [Green Version]
- Graboski, M.; Bain, R. Properties of biomass relevant to gasification. Surv. Biomass Gasif. 1979, 2, 21–65. [Google Scholar]
- Callejón-Ferre, A.J.; Velázquez-Martí, B.; López-Martínez, J.A.; Manzano-Agugliaro, F. Greenhouse crop residues: Energy potential and models for the prediction of their higher heating value. Renew. Sustain. Energy Rev. 2011, 15, 948–955. [Google Scholar] [CrossRef]
- Channiwala, S.A.; Parikh, P.P. A unified correlation for estimating HHV of solid, liquid and gaseous fuels. Fuel 2002, 81, 1051–1063. [Google Scholar] [CrossRef]
- Bridgwater, A.V.; Double, J.M.; Earp, D.M. Technical and Market Assessment of Biomass Gasification in the United Kingdom; ETSU Report; UKAEA: Harwell, UK, 1996. [Google Scholar]
- Tillman, D.A. Wood as an Energy Resource; Academic Press: New York, NY, USA, 1978; p. 266. ISBN 978-0-12-691260-9. [Google Scholar]
- Annamalai, K.; Sweeten, J.M.; Ramalingam, S.C. Estimation of gross heating values of biomass fuels. Trans. ASAE 1987, 30, 1205–1208. [Google Scholar] [CrossRef]
- Demirbaş, A.; Demirbaş, A.H. Estimating the calorific values of lignocellulosic fuels. Energy Explor. Exploit. 2004, 22, 135–143. [Google Scholar] [CrossRef]
- Jimennez, L.; Gonzales, F. Study of the physical and chemical properties of lignocellulosic residues with a view to the production of fuels. Fuel 1991, 70, 947–950. [Google Scholar] [CrossRef]
- Demirbaş, A. Calculation of higher heating values of biomass fuels. Fuel 1997, 76, 431–434. [Google Scholar] [CrossRef]
- Cordedo, T.; Marquez, F.; Rodriguez-Mirasol, J.; Rodriguez, J.J. Predicting heating values of lignocellulosics and carbonaceous materials from proximate analysis. Fuel 2001, 80, 1567–1571. [Google Scholar] [CrossRef]
- World Bank 2018. Available online: http://databank.worldbank.org/data/home.aspx (accessed on 1 August 2018).
Parameter | Unit | Standards | Measurement Equipment |
---|---|---|---|
Moisture | % | EN 14774-1 | Drying Oven Memmert UFE 700 |
Ash | % | EN 14775 | Muffle Furnace NABERTHERM LVT 15/11 |
Higher heating value | MJ/kg | EN 14918 | Calorimeter Parr 6300 |
Lower heating value | MJ/kg | EN 14918 | Calorimeter Parr 6300 |
Total carbon | % | EN 15104 | Analyzer LECO TruSpec CHN 620-100-400 |
Total hydrogen | % | EN 15104 | Analyzer LECO TruSpec CHN 620-100-400 |
Total nitrogen | % | EN 15104 | Analyzer LECO TruSpec CHN 620-100-400 |
Total sulphur | % | EN 15289 | Analyzer LECO TruSpec CHN 620-100-400 |
Total chlorine | mg/kg | EN 15289 | Titrator Mettler Toledo G20 |
Volatile matter | % | EN 15148 | Muffle Furnace NABERTHERM LVT 15/11 |
Fixed carbon | % | EN 15148 | Muffle Furnace NABERTHERM LVT 15/11 |
Parameter | Unit | Standard Value | Standard Deviation (SD) | Maximum Value | Minimum Value |
---|---|---|---|---|---|
Moisture ** | % | 5.79 | --- | 5.79 | 5.79 |
Ash content * | % | 4.26 | 0.15 | 4.41 | 4.11 |
HHV * | MJ/kg | 18.547 | 0.025 | 18.572 | 18.522 |
LHV * | MJ/kg | 17.111 | 0.011 | 17.122 | 17.100 |
Total carbon * | % | 46.42 | 0.007 | 46.427 | 46.413 |
Total hydrogen * | % | 6.61 | 0.016 | 6.626 | 6.594 |
Total nitrogen * | % | 0.50 | 0.012 | 0.512 | 0.488 |
Total sulphur * | % | 0.54 | 0.01 | 0.55 | 0.53 |
Total oxygen * | % | 41.77 | 2.453 | 44.223 | 39.317 |
Total chlorine * | % | 0.07 | 0.001 | 0.071 | 0.069 |
Volatile matter * | % | 84.90 | 1.09 | 85.99 | 83.81 |
Fixed carbon * | % | 13.40 |
Parameters | Unit | Avocado Stone [21] | Olive Stone [37,38,39] | Pine Pellets [39,40] | Peanut Shell | Almond Shell [39,41,42] |
---|---|---|---|---|---|---|
Moisture | % | 35.20 | 18.45 | 7.29 | 5.79 | 7.63 |
HHV | MJ/kg | 19.145 | 17.884 | 20.030 | 18.547 | 18.200 |
LHV | MJ/kg | 17.889 | 16.504 | 18.470 | 16.994 | 17.920 |
Ash content | % | 2.86 | 0.77 | 0.33 | 4.26 | 0.55 |
Total carbon | % | 48.01 | 46.55 | 47.70 | 46.42 | 49.27 |
Total hydrogen | % | 5.755 | 6.33 | 6.12 | 6.61 | 6.06 |
Total nitrogen | % | 0.447 | 1.810 | 1.274 | 0.50 | 0.120 |
Total sulphur | % | 0.104 | 0.110 | 0.004 | 0.54 | 0.050 |
Total oxygen | % | 42.80 | 45.20 | 52.30 | 41.77 | 44.49 |
Total chlorine | % | 0.024 | 0.060 | 0.000 | 0.07 | 0.01 |
% | 103.22 | 96.43 | 110.05 | 100 | 98.13 |
No. | Name of the Authors and Reference | Correlation Equation (MJ/kg) |
---|---|---|
(1) | Jenkins and Ebeling (1) [45] | HHV = −0.763 + 0.301 C + 0.525 H + 0.064 O |
(2) | Sheng and Azevedo (1) [46] | HHV = −1.3675 + 0.3137 C + 0.7009 H + 0.0318 O |
(3) | Yin [47] | HHV = 0.2949 C + 0.8250 H |
(4) | Graboski and Bain [48] | HHV = 0.328 C + 1.4306 H − 0.0237 N + 0.0929 S − (1 − Ash/100)·(40.11 H/C) + 0.3466 |
(5) | Callejón-Ferre et al. [49] | HHV = −3.440 + 0.517 (C + N) − 0.433 (H + N) |
(6) | Channiwala and Parikh [50] | HHV = 0.3491 C + 1.1783 H + 0.1005 S – 0.1034 O − 0.0151 N − 0.0211 Ash |
(7) | Sheng and Azevedo (2) [46] | HHV = 19.914 − 0.2324 Ash |
(8) | Brigwater et al. [51] | HHV = 0.341 C + 1.323 H + 0.068 S − 0.0153 Ash − 0.1194 (O − N) |
(9) | Tillman [52] | HHV = – 1.6701+0.4373 C |
(10) | Annamalai et al. [53] | HHV = 0.3516 C + 1.16225 H – 0.1109 O + 0.0628 N + 0.10465 S |
(11) | Demirbas (1) [54] | HHV = − 0.459+0.4084 C |
(12) | Callejón-Ferre et al. [49] | HHV = −3.147 + 0.468 C |
(13) | Jenkins and Ebeling (2) [45] | HHV = 1.209 + 0.379 C |
(14) | Jimenez and Gonzalez [55] | HHV = −10.81408 + 0.3133 (VM + FC) |
(15) | Demirbas (2) [56] | HHV = 0.312 FC + 0.1534 VM |
(16) | Cordero et al. [57] | HHV = 0.3543 FC + 0.1708 VM |
(17) | Jenkins and Ebeling (3) [45] | HHV = −0.049 + 0.332 C + 0.851 H − 0.036 O |
(18) | Jenkins and Ebeling (4) [45] | HHV = 3.210 + 0.3333 C |
(19) | Jenkins and Ebeling (5) [45] | HHV = 0.007 + 0.311 C+0.752H + 0.006 O |
(20) | Demirbas (3) [54] | HHV = 0.4182 (C + H) − 3.4085 |
Equation Number | Correlation Value (MJ/kg) | Difference | % Deviation |
---|---|---|---|
(1) | 19.353 | −0.806 | 4.345 |
(2) | 19.156 | −0.609 | 3.282 |
(3) | 19.143 | −0.596 | 3.211 |
(4) | 19.599 | −1.052 | 5.671 |
(5) | 17.739 | 0.808 | 4.356 |
(6) | 19.632 | −1.085 | 5.848 |
(7) | 18.924 | −0.377 | 2.033 |
(8) | 19.618 | −1.071 | −5.775 |
(9) | 18.629 | −0.082 | 0.444 |
(10) | 19.459 | −0.912 | 4.919 |
(11) | 18.499 | 0.048 | 0.259 |
(12) | 18.578 | −0.031 | 0.165 |
(13) | 18.802 | −0.255 | 1.376 |
(14) | 19.983 | −1.436 | 7.744 |
(15) | 17.204 | 1.343 | 7.239 |
(16) | 19.249 | −0.702 | 3.782 |
(17) | 19.484 | −0.937 | 5.051 |
(18) | 18.682 | −0.135 | 0.727 |
(19) | 19.665 | −1.118 | 6.028 |
(20) | 18.763 | −0.216 | 1.166 |
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Perea-Moreno, M.-A.; Manzano-Agugliaro, F.; Hernandez-Escobedo, Q.; Perea-Moreno, A.-J. Peanut Shell for Energy: Properties and Its Potential to Respect the Environment. Sustainability 2018, 10, 3254. https://doi.org/10.3390/su10093254
Perea-Moreno M-A, Manzano-Agugliaro F, Hernandez-Escobedo Q, Perea-Moreno A-J. Peanut Shell for Energy: Properties and Its Potential to Respect the Environment. Sustainability. 2018; 10(9):3254. https://doi.org/10.3390/su10093254
Chicago/Turabian StylePerea-Moreno, Miguel-Angel, Francisco Manzano-Agugliaro, Quetzalcoatl Hernandez-Escobedo, and Alberto-Jesus Perea-Moreno. 2018. "Peanut Shell for Energy: Properties and Its Potential to Respect the Environment" Sustainability 10, no. 9: 3254. https://doi.org/10.3390/su10093254
APA StylePerea-Moreno, M. -A., Manzano-Agugliaro, F., Hernandez-Escobedo, Q., & Perea-Moreno, A. -J. (2018). Peanut Shell for Energy: Properties and Its Potential to Respect the Environment. Sustainability, 10(9), 3254. https://doi.org/10.3390/su10093254