OrangerV1, PascalFrancis, Curation, bibRecord, 000976

Optimization of energy required and greenhouse gas emissions analysis for orange producers using data envelopment analysis approach

Identifieur interne : 000976 ( PascalFrancis/Curation ); précédent : 000975; suivant : 000977

Optimization of energy required and greenhouse gas emissions analysis for orange producers using data envelopment analysis approach

Auteurs : Ashkan Nabavi-Pelesaraei [Iran] ; Reza Abdi [Iran] ; Shahin Rafiee [Iran] ; HASSAN GHASEMI MOBTAKER [Iran]

Source :

Journal of cleaner production [ 0959-6526 ] ; 2014.

RBID : Pascal:14-0091907

Descripteurs français

Pascal (Inist)
- Optimisation, Energie, Emission gaz, Analyse enveloppement donnée, Rendement énergétique, Verger, Méthode non paramétrique, Protection environnement, Développement durable, Citrus sinensis, Gaz effet serre, Iran, Prévention pollution, Efficacité énergétique.
Wicri :
- geographic : Iran.
- topic : Rendement énergétique, Verger, Développement durable.

English descriptors

KwdEn :
- Citrus sinensis, Data envelopment analysis, Energetic efficiency, Energy, Energy efficiency, Environmental protection, Gas emission, Greenhouse gas, Iran, Non parametric method, Optimization, Orchard, Pollution prevention, Sustainable development.

Abstract

Data envelopment analysis is a non-parametric method for multi-criteria decision and performance measurement. This approach has two models including constant returns to scale and variable returns to scale model. The main objective of this study was to analyze the efficiency of orchardists, discriminate efficient orchardists from inefficient ones and identify wasteful uses of energy using Data envelopment analysis for orange production in Guilan province of Iran. Also, another purpose of this paper was to determine greenhouse gas emissions for efficient and inefficient orange producers. This method was used based on single output of orange yield and seven energy inputs including human labor, machinery, diesel fuel, chemical fertilizers, farmyard manure, chemical and electricity. The technical, pure technical, scale and cross efficiencies were calculated for orange orchardists using CCR and BCC models. The results indicated that out of the total number of orchardists the share of efficient and inefficient units were 73.3% and 26.7% based on BCC model, respectively. Also, the results revealed the average of technical, pure technical and scale efficiencies of orchardists were 0.894, 0.965 and 0.922, respectively. Energy saving for target ratio was calculated about 13% for orange production in Guilan province of Iran. The energy use efficiency, energy productivity and net energy were improved by 14.7%, 14.4% and 15.4% using optimization of energy. The results illustrated the difference of greenhouse gas emissions between efficient and inefficient units. It was calculated about 19.6%. Also, the electricity has the highest difference of greenhouse gas emissions between efficient and inefficient orchardists for orange production. Generally, the application of data envelopment analysis method can improve energy efficiency and GHG emissions in orange production, significantly.

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A08	`01`	`1`	`ENG`	`@1 Optimization of energy required and greenhouse gas emissions analysis for orange producers using data envelopment analysis approach`
A11	`01`	`1`		`@1 NABAVI-PELESARAEI (Ashkan)`
A11	`02`	`1`		`@1 ABDI (Reza)`
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A11	`04`	`1`		`@1 HASSAN GHASEMI MOBTAKER`
A14	`01`			`@1 Department of Agricultural Machinery Engineering, Faculty of Agriculture, University of Tabriz @2 Tabriz @3 IRN @Z 1 aut. @Z 2 aut. @Z 4 aut.`
A14	`02`			`@1 Department of Agricultural Machinery Engineering, Faculty of Agricultural Engineering and Technology, University of Tehran @2 Karaj @3 IRN @Z 3 aut.`
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C01	`01`		`ENG`	@0 Data envelopment analysis is a non-parametric method for multi-criteria decision and performance measurement. This approach has two models including constant returns to scale and variable returns to scale model. The main objective of this study was to analyze the efficiency of orchardists, discriminate efficient orchardists from inefficient ones and identify wasteful uses of energy using Data envelopment analysis for orange production in Guilan province of Iran. Also, another purpose of this paper was to determine greenhouse gas emissions for efficient and inefficient orange producers. This method was used based on single output of orange yield and seven energy inputs including human labor, machinery, diesel fuel, chemical fertilizers, farmyard manure, chemical and electricity. The technical, pure technical, scale and cross efficiencies were calculated for orange orchardists using CCR and BCC models. The results indicated that out of the total number of orchardists the share of efficient and inefficient units were 73.3% and 26.7% based on BCC model, respectively. Also, the results revealed the average of technical, pure technical and scale efficiencies of orchardists were 0.894, 0.965 and 0.922, respectively. Energy saving for target ratio was calculated about 13% for orange production in Guilan province of Iran. The energy use efficiency, energy productivity and net energy were improved by 14.7%, 14.4% and 15.4% using optimization of energy. The results illustrated the difference of greenhouse gas emissions between efficient and inefficient units. It was calculated about 19.6%. Also, the electricity has the highest difference of greenhouse gas emissions between efficient and inefficient orchardists for orange production. Generally, the application of data envelopment analysis method can improve energy efficiency and GHG emissions in orange production, significantly.
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N21				`@1 125`

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<term>Environmental protection</term>
<term>Gas emission</term>
<term>Greenhouse gas</term>
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<front><div type="abstract" xml:lang="en">Data envelopment analysis is a non-parametric method for multi-criteria decision and performance measurement. This approach has two models including constant returns to scale and variable returns to scale model. The main objective of this study was to analyze the efficiency of orchardists, discriminate efficient orchardists from inefficient ones and identify wasteful uses of energy using Data envelopment analysis for orange production in Guilan province of Iran. Also, another purpose of this paper was to determine greenhouse gas emissions for efficient and inefficient orange producers. This method was used based on single output of orange yield and seven energy inputs including human labor, machinery, diesel fuel, chemical fertilizers, farmyard manure, chemical and electricity. The technical, pure technical, scale and cross efficiencies were calculated for orange orchardists using CCR and BCC models. The results indicated that out of the total number of orchardists the share of efficient and inefficient units were 73.3% and 26.7% based on BCC model, respectively. Also, the results revealed the average of technical, pure technical and scale efficiencies of orchardists were 0.894, 0.965 and 0.922, respectively. Energy saving for target ratio was calculated about 13% for orange production in Guilan province of Iran. The energy use efficiency, energy productivity and net energy were improved by 14.7%, 14.4% and 15.4% using optimization of energy. The results illustrated the difference of greenhouse gas emissions between efficient and inefficient units. It was calculated about 19.6%. Also, the electricity has the highest difference of greenhouse gas emissions between efficient and inefficient orchardists for orange production. Generally, the application of data envelopment analysis method can improve energy efficiency and GHG emissions in orange production, significantly.</div>
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<fC01 i1="01" l="ENG"><s0>Data envelopment analysis is a non-parametric method for multi-criteria decision and performance measurement. This approach has two models including constant returns to scale and variable returns to scale model. The main objective of this study was to analyze the efficiency of orchardists, discriminate efficient orchardists from inefficient ones and identify wasteful uses of energy using Data envelopment analysis for orange production in Guilan province of Iran. Also, another purpose of this paper was to determine greenhouse gas emissions for efficient and inefficient orange producers. This method was used based on single output of orange yield and seven energy inputs including human labor, machinery, diesel fuel, chemical fertilizers, farmyard manure, chemical and electricity. The technical, pure technical, scale and cross efficiencies were calculated for orange orchardists using CCR and BCC models. The results indicated that out of the total number of orchardists the share of efficient and inefficient units were 73.3% and 26.7% based on BCC model, respectively. Also, the results revealed the average of technical, pure technical and scale efficiencies of orchardists were 0.894, 0.965 and 0.922, respectively. Energy saving for target ratio was calculated about 13% for orange production in Guilan province of Iran. The energy use efficiency, energy productivity and net energy were improved by 14.7%, 14.4% and 15.4% using optimization of energy. The results illustrated the difference of greenhouse gas emissions between efficient and inefficient units. It was calculated about 19.6%. Also, the electricity has the highest difference of greenhouse gas emissions between efficient and inefficient orchardists for orange production. Generally, the application of data envelopment analysis method can improve energy efficiency and GHG emissions in orange production, significantly.</s0>
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<s5>03</s5>
</fC03>
<fC03 i1="03" i2="X" l="SPA"><s0>Emisión gas</s0>
<s5>03</s5>
</fC03>
<fC03 i1="04" i2="X" l="FRE"><s0>Analyse enveloppement donnée</s0>
<s5>04</s5>
</fC03>
<fC03 i1="04" i2="X" l="ENG"><s0>Data envelopment analysis</s0>
<s5>04</s5>
</fC03>
<fC03 i1="04" i2="X" l="SPA"><s0>Análisis envolvimiento datos</s0>
<s5>04</s5>
</fC03>
<fC03 i1="05" i2="X" l="FRE"><s0>Rendement énergétique</s0>
<s5>05</s5>
</fC03>
<fC03 i1="05" i2="X" l="ENG"><s0>Energetic efficiency</s0>
<s5>05</s5>
</fC03>
<fC03 i1="05" i2="X" l="SPA"><s0>Rendimiento energético</s0>
<s5>05</s5>
</fC03>
<fC03 i1="06" i2="X" l="FRE"><s0>Verger</s0>
<s5>06</s5>
</fC03>
<fC03 i1="06" i2="X" l="ENG"><s0>Orchard</s0>
<s5>06</s5>
</fC03>
<fC03 i1="06" i2="X" l="SPA"><s0>Huerto</s0>
<s5>06</s5>
</fC03>
<fC03 i1="07" i2="X" l="FRE"><s0>Méthode non paramétrique</s0>
<s5>07</s5>
</fC03>
<fC03 i1="07" i2="X" l="ENG"><s0>Non parametric method</s0>
<s5>07</s5>
</fC03>
<fC03 i1="07" i2="X" l="SPA"><s0>Método no paramétrico</s0>
<s5>07</s5>
</fC03>
<fC03 i1="08" i2="X" l="FRE"><s0>Protection environnement</s0>
<s5>08</s5>
</fC03>
<fC03 i1="08" i2="X" l="ENG"><s0>Environmental protection</s0>
<s5>08</s5>
</fC03>
<fC03 i1="08" i2="X" l="SPA"><s0>Protección medio ambiente</s0>
<s5>08</s5>
</fC03>
<fC03 i1="09" i2="X" l="FRE"><s0>Développement durable</s0>
<s5>09</s5>
</fC03>
<fC03 i1="09" i2="X" l="ENG"><s0>Sustainable development</s0>
<s5>09</s5>
</fC03>
<fC03 i1="09" i2="X" l="SPA"><s0>Desarrollo sostenible</s0>
<s5>09</s5>
</fC03>
<fC03 i1="10" i2="X" l="FRE"><s0>Citrus sinensis</s0>
<s2>NS</s2>
<s5>10</s5>
</fC03>
<fC03 i1="10" i2="X" l="ENG"><s0>Citrus sinensis</s0>
<s2>NS</s2>
<s5>10</s5>
</fC03>
<fC03 i1="10" i2="X" l="SPA"><s0>Citrus sinensis</s0>
<s2>NS</s2>
<s5>10</s5>
</fC03>
<fC03 i1="11" i2="X" l="FRE"><s0>Gaz effet serre</s0>
<s5>15</s5>
</fC03>
<fC03 i1="11" i2="X" l="ENG"><s0>Greenhouse gas</s0>
<s5>15</s5>
</fC03>
<fC03 i1="11" i2="X" l="SPA"><s0>Gas efecto invernadero</s0>
<s5>15</s5>
</fC03>
<fC03 i1="12" i2="X" l="FRE"><s0>Iran</s0>
<s2>NG</s2>
<s5>20</s5>
</fC03>
<fC03 i1="12" i2="X" l="ENG"><s0>Iran</s0>
<s2>NG</s2>
<s5>20</s5>
</fC03>
<fC03 i1="12" i2="X" l="SPA"><s0>Iran</s0>
<s2>NG</s2>
<s5>20</s5>
</fC03>
<fC03 i1="13" i2="X" l="FRE"><s0>Prévention pollution</s0>
<s5>28</s5>
</fC03>
<fC03 i1="13" i2="X" l="ENG"><s0>Pollution prevention</s0>
<s5>28</s5>
</fC03>
<fC03 i1="13" i2="X" l="SPA"><s0>Prevención polución</s0>
<s5>28</s5>
</fC03>
<fC03 i1="14" i2="X" l="FRE"><s0>Efficacité énergétique</s0>
<s4>CD</s4>
<s5>96</s5>
</fC03>
<fC03 i1="14" i2="X" l="ENG"><s0>Energy efficiency</s0>
<s4>CD</s4>
<s5>96</s5>
</fC03>
<fC03 i1="14" i2="X" l="SPA"><s0>Eficiencia energética</s0>
<s4>CD</s4>
<s5>96</s5>
</fC03>
<fC07 i1="01" i2="X" l="FRE"><s0>Rutaceae</s0>
<s2>NS</s2>
</fC07>
<fC07 i1="01" i2="X" l="ENG"><s0>Rutaceae</s0>
<s2>NS</s2>
</fC07>
<fC07 i1="01" i2="X" l="SPA"><s0>Rutaceae</s0>
<s2>NS</s2>
</fC07>
<fC07 i1="02" i2="X" l="FRE"><s0>Dicotyledones</s0>
<s2>NS</s2>
</fC07>
<fC07 i1="02" i2="X" l="ENG"><s0>Dicotyledones</s0>
<s2>NS</s2>
</fC07>
<fC07 i1="02" i2="X" l="SPA"><s0>Dicotyledones</s0>
<s2>NS</s2>
</fC07>
<fC07 i1="03" i2="X" l="FRE"><s0>Angiospermae</s0>
<s2>NS</s2>
</fC07>
<fC07 i1="03" i2="X" l="ENG"><s0>Angiospermae</s0>
<s2>NS</s2>
</fC07>
<fC07 i1="03" i2="X" l="SPA"><s0>Angiospermae</s0>
<s2>NS</s2>
</fC07>
<fC07 i1="04" i2="X" l="FRE"><s0>Spermatophyta</s0>
<s2>NS</s2>
</fC07>
<fC07 i1="04" i2="X" l="ENG"><s0>Spermatophyta</s0>
<s2>NS</s2>
</fC07>
<fC07 i1="04" i2="X" l="SPA"><s0>Spermatophyta</s0>
<s2>NS</s2>
</fC07>
<fC07 i1="05" i2="X" l="FRE"><s0>Asie</s0>
<s2>NG</s2>
</fC07>
<fC07 i1="05" i2="X" l="ENG"><s0>Asia</s0>
<s2>NG</s2>
</fC07>
<fC07 i1="05" i2="X" l="SPA"><s0>Asia</s0>
<s2>NG</s2>
</fC07>
<fC07 i1="06" i2="X" l="FRE"><s0>Agrume</s0>
<s5>31</s5>
</fC07>
<fC07 i1="06" i2="X" l="ENG"><s0>Citrus fruit</s0>
<s5>31</s5>
</fC07>
<fC07 i1="06" i2="X" l="SPA"><s0>Agrios</s0>
<s5>31</s5>
</fC07>
<fC07 i1="07" i2="X" l="FRE"><s0>Moyen Orient</s0>
<s2>NG</s2>
<s5>59</s5>
</fC07>
<fC07 i1="07" i2="X" l="ENG"><s0>Middle east</s0>
<s2>NG</s2>
<s5>59</s5>
</fC07>
<fC07 i1="07" i2="X" l="SPA"><s0>Oriente Medio</s0>
<s2>NG</s2>
<s5>59</s5>
</fC07>
<fN21><s1>125</s1>
</fN21>
</pA>
</standard>
</inist>
</record>

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Optimization of energy required and greenhouse gas emissions analysis for orange producers using data envelopment analysis approach

Optimization of energy required and greenhouse gas emissions analysis for orange producers using data envelopment analysis approach

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