Analysis of energy consumption and end-use application of rapeseed in an agricultural production system in Izeh-Khuzestan

The biodiesel (B100) production starting from the plantation, crushing mill and biodiesel plant can generate high amount of Greenhouse Gas (GHG) emission which is harmful to the global environment. To reduce the GHG emission, an efficient managing strategy of the entire production process must be introduced. This paper presents a case study of the GHG emission analysis in Trang, Krabi and Chumporn province in 2013. The entire year data of each activity such as amount of energy, fertilizer and herbicides used, main product, residues produced in oil palm plantation, milling and biodiesel plant were analyzed and calculated by the basis of Gate to Gate. The result shows that the production process in the plantation generates the GHG emission of-0.54 ton CO2-eq /ton FFB while the GHG emitted from the crushing mill is at-2.89 ton CO2-eq /ton RPO and from the biodiesel plant is at-2.30 kg CO2-eq /liter B100.These calculated values show that the biodiesel production can alleviate the greenhouse effect. If the bio solid residues are used as a mixture for fertilizer and the wastewater is used to produce the biogas to generate electricity, the GHG emission can then be reduced.

PDF HTML阅读 XML下载 导出引用 引用提醒 基于生命周期评价的上海市水稻生产的碳足迹 DOI: 10.5846/stxb201304240794 作者: 作者单位: 上海市农业科学院,上海市农业科学院,上海市农业科学院,上海市农业科学院,江西农业大学 作者简介: 通讯作者: 中图分类号: 基金项目: 国家科技部支撑计划后世博专项资助项目（2010BAK69B18）；上海市科委崇明科技攻关专项资助项目（10DZ1960101） Life cycle assessment of carbon footprint for rice production in Shanghai Author: Affiliation: Shanghai Academy of Agricultural Sciences,Seed management station of Shanghai,,,Jiangxi Agricultural University Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:碳足迹是指由企业、组织或个人引起的碳排放的集合。参照PAS2050规范并结合生命周期评价方法对上海市水稻生产进行了碳足迹评估。结果表明：（1）目前上海市水稻生产的碳排放为11.8114 t CO2e/hm2，折合每吨水稻生产周期的碳足迹为1.2321 t CO2e；（2）稻田温室气体排放是水稻生产最主要的碳排放源，每吨水稻生产的总排放量为0.9507 t CO2e，占水稻生产全部碳排放的77.1%，其中甲烷（CH4）又是最主要的温室气体，对稻田温室气体碳排放的贡献率高达96.6%；（3）化学肥料的施用是第二大碳排放源，每吨水稻生产的总排放量为0.2044 t CO2e，占水稻生产总碳排放的16.5%，其中N最高，排放量为0.1159 t CO2e。因此，上海低碳水稻生产的关键在降低稻田甲烷的排放，另外可通过提高氮肥利用效率，减少氮肥施用等方法减少种植过程中碳排放。 Abstract:Global climate change has become an urgent issue of concern. Climate change will increasingly threaten our food production, security and even the survival of the human race. It also has a serious impact on natural ecosystems and the socioeconomic system. With the increasing scale and improvement in mechanization levels, the economic linkage between agricultural production and reduction of Greenhouse Gas (GHG) emissions is even closer in the agricultural production system. Therefore, the development of a low-carbon agricultural model is one of the long-term strategies for low-carbon economic growth throughout the country.This research of carbon footprint is introduced to measure the GHG emission over the rice production cycle. The carbon footprint can be defined as the total carbon emissions caused by an organization, event, product or person. At present, carbon footprints are used to measure GHG emissions in products, services, organizations, cities and countries and offer the decision basis for the formulation of GHG emission reduction schemes.Agricultural ecological systems, every year, also produce a lot of GHG emissions. The whole process of prenatal, intrapartum and postpartum agricultural production are closely related to energy consumption and GHG emission. In the process, all the agricultural inputs, such as chemical fertilizers, pesticides, seeds, cultivation, plant protection, agricultural machinery, irrigation and harvest also produce greenhouse gas emissions.The whole cultivation of rice involves methane (CH4) emission. This study shows that rice cultivation is one of the biggest sources of GHG emissions in crop cultivation. Rice paddies emit a large amount of methane in their water logged mode. Different irrigation modes have a great influence on the emission of GHG. Straw return is another factor that promotes GHG emissions. Soil organic content increases with the return of straw, with an increase in the soil methanogen activity, leading to increased methane emissions.The current carbon footprint research is the first time it has been used to measure the carbon emissions involved in rice production. The carbon footprint for rice production in Shanghai was assessed by the PAS2050 paradigm and life cycle assessment. The study area, located in Changjiang Farm, which belongs to the Guangming Group in Chongming County Shanghai City atlatitude 121°32'22' E, longitude31°40'23' N. Chongming County, in the Yangtze River Estuary, is a typical sub tropical monsoon climate with mild climate, abundant rainfall, annual average temperatures of 15.3 ℃, and annual precipitation of 1245 mm. It is the major grain production base for Shanghai city with winter wheat and summer rice forming their main planting patterns, which are typical for the middle and lower reaches of the Yangtze River rice-wheat rotation cropping pattern.The entire carbon emission of rice production in Shanghai was 11.8114 t CO2e (CO2-equivalents)/hm2, corresponding to a 1.2321 t CO2e/t rice grain yield. GHG emissions from paddy fields were the major source, which emitted 0.9507 t CO2e/t rice and accounted for 77.1% of total carbon emissions during rice production. Moreover, CH4 was the largest source for GHG emissions with a contribution rate of 96.6%.Chemical fertilizers were the second largest emission source in rice production. Chemical fertilizers emitted 0.2044 t CO2e for each ton of rice production, contributing 16.5% of total carbon emissions in rice production. N fertilizer was the biggest emission source, which released 0.1159 t CO2e/t rice.This research investigates the GHG emissions over the whole process of the Shanghai rice production cycle and reveals the energy consumption and GHG emissions in rice production. Thus, a rice carbon footprint is calculated by assessing the GHG emissions in Shanghai rice production. The results are beneficial for producing reduction plans of reducing GHG emissions in Shanghai rice production. Furthermore, the results will supply both practicable and theoretical foundations for drafting carbon footprint formulations in other industrial areas. 参考文献 相似文献 引证文献

Reasonable test, diagnosis, and analysis are meaningful for building energy efficiency retrofit and management. Energy consumption and greenhouse gas emission of a large-scale commercial building are described in this article. Basic information about energy consumption equipment is included in the investigation. Further diagnoses about the operational state of air-conditioning water systems, and ducted systems were implemented. Energy consumption decreased 200 kWh/m2 per year from 2007 to 2009 after energy-saving reconstruction in 2006. Next, a carbon audit was carried out; this comprised CO2 emission statistics associated with the energy use and categorization and structural analysis (categorization refers to energy categorization and structural analysis means the composition and its proportion relationship of all kinds of primary energy and secondary energy in energy production or consumption). Greenhouse gas emissions could be less than 150 kg/m2 per year from 2007 to 2009. An analysis of the correlation between CO2 emissions, building gross domestic product, and energy efficiency is also presented. This article makes an analysis on the energy utilization and energy-saving reconstruction of a public commercial building in Shanghai and then makes an analysis of carbon audit about greenhouse gas emissions related to energy utilization (it analyzes the status of building’s energy utilization and greenhouse gas emissions), to have a more comprehensive understanding on the internal relationship between energy consumption and its greenhouse gas emissions and provide researchful reference data for the development with reduction strategies of greenhouse gas emission in future building.

Aluminum production is a major energy consumer and important source of greenhouse gas (GHG) emissions globally. Estimation of the energy consumption and GHG emissions caused by aluminum production in China has attracted widespread attention because China produces more than half of the global aluminum. This paper conducted life cycle (LC) energy consumption and GHG emissions analysis of primary and recycled aluminum in China for the year 2020, considering the provincial differences on both the scale of self-generated electricity consumed in primary aluminum production and the generation source of grid electricity. Potentials for energy saving and GHG emissions reductions were also investigated. The results indicate that there are 157,207 MJ of primary fossil energy (PE) consumption and 15,947 kg CO2-eq of GHG emissions per ton of primary aluminum ingot production in China, with the LC GHG emissions as high as 1.5–3.5 times that of developed economies. The LC PE consumption and GHG emissions of recycled aluminum are very low, only 7.5% and 5.3% that of primary aluminum, respectively. Provincial-level results indicate that the LC PE and GHG emissions intensities of primary aluminum in the main production areas are generally higher while those of recycled aluminum are lower in the main production areas. LC PE consumption and GHG emissions can be significantly reduced by decreasing electricity consumption, self-generated electricity management, low-carbon grid electricity development, and industrial relocation. Based on this study, policy suggestions for China’s aluminum industry are proposed. Recycled aluminum industry development, restriction of self-generated electricity, low-carbon electricity utilization, and industrial relocation should be promoted as they are highly helpful for reducing the LC PE consumption and GHG emissions of the aluminum industry. In addition, it is recommended that the central government considers the differences among provinces when designing and implementing policies.

Decisions can be taken to increase energy efficiency and to mitigate the emissions to the environment by examining the energy audit and greenhouse gas (GHG) emissions footprint of crop production in different ways and in different regions, with comparable principles. In this study, energy consumption and energy indices of tomatoes production in four regions of Iran including East Azerbaijan province (open field), the provinces of Kermanshah, Tehran and Isfahan (greenhouse) were compared using related articles data. Chemical fertilizers and irrigation water in tomato production in open field and diesel fuel and chemical fertilizers in the tomato production in greenhouses system was greatest energy consumer in Iran. Energy consumption of irrigation water for tomato production in open field was markedly higher than the production in the greenhouse. In this study, the inputs of diesel fuel, chemical fertilizers, chemicals, plastics, and electricity used in the production of tomatoes, which contribute to the GHG emission footprint, were calculated via coefficients related to GHG emission. The highest and lowest greenhouse gas emissions in greenhouse tomato production in Tehran province and East Azerbaijan province farms were determined to be 13661.37 kgCO2eq ha-1 and 1274.02 kgCO2eq ha-1, respectively. Overall, tomato production in open field leads to lower greenhouse gas emissions and energy consumption per unit area, but according to more energy output in cultivation of tomato in greenhouse, energy efficiency of tomato production in greenhouse was higher.

PROSPECTS AND EFFICIENCY OF BIODIESEL PRODUCTION IN UKRAINE FROM OILSEED CROPS

High population growth and providing the food for this population have increased the amount of energy consumption in agricultural production systems. One of the most important issues for high energy consumption in recent century is the global warming where greenhouse gas (GHG) emission plays an important role. This study evaluated the energy balance between the input and output and the amount of GHG emission per unit area of wheat production in Iran. The total energy input and output were calculated as 31.5 and 44.6 GJ ha−1, respectively, where the highest energy consumer was chemical fertilizer with share of 64% of total energy. Total GHG emission was 1118.94 kgCO2eq ha−1 in which chemical fertilizer and diesel fuel had the highest contributions. The results of regression analysis indicated that use of 10 MJ in forms of direct, indirect, renewable, and nonrenewable energy leads to 3.0, 0.4, 2.8, and 0.6 kg ha−1 growth in wheat yield, respectively. The results of farm size analysis indicated that very large farms have better energy ratio and less GHG emission in comparison with other farm size levels due to better management. The results of this study indicated a list of choices which are available to reduce energy use and GHG emission in wheat production.

Rice is the second-most produced cereal worldwide and actively contributes to greenhouse gas (GHG) emissions, particularly methane, especially under deepwater production. Assessments of energy efficiency (EE) and GHG emissions can indicate the sustainability level of agrosystems and support decisions related to the reduction of production costs and environmental pollution. This study aimed to assess both EE and GHG emissions in organic and conventional rice production in the Southern region of Brazil. For this study, eight rice fields were evaluated. Energy inputs and outputs were calculated by multiplying the production input amounts by their respective calorific values or energy coefficients at each stage of production. EE was determined using the ratio between the total energy output and the total energy consumed during the production process. GHG emissions were estimated using the principles of the lifecycle assessment methodology in addition to the Intergovernmental Panel on Climate Change (IPCC) recommendations. Each 1.0 MJ consumed during the production of organic and conventional rice produced renewable energy averages of 10.5 MJ and 7.90 MJ, respectively, as grains. The primary energy expenses for organic rice were represented by seeds, fuel, tractors, and agricultural machinery and implements, and those for conventional rice were seeds, fuel, and fertilizers. Each kilogram of organic and conventional rice produced accounted for the emission of 0.21 and 0.32 kg of CO2eq, respectively, during the production cycles and delivery to the warehouse, with seeds, fuel, and fertilizers being the main sources of CO2eq emissions to the atmosphere.

Anaerobic treatment of palm oil mill effluents: potential contribution to net energy yield and reduction of greenhouse gas emissions from biodiesel production

There are significant research and knowledge gaps on how greenhouse vegetable production can be optimised and the energy consumption can be minimised. In this study, we conducted the analysis of crop production and energy consumption together with the greenhouse climate and local weather records for a capsicum crop in a national high-tech greenhouse facility at Western Sydney University, Australia. The analysis of energy consumption over the production cycle indicates that daily energy consumption varies, due to the seasonal nature of temperature and the need for maintaining desirable temperatures at different growth stages of the capsicum crop. Results also suggest that the system for maintaining temperature using for cooling and heating works within acceptable level of operations. The theoretical and practical implications of this research include the importance of assessing the impact of production cycle on overall performance, and complexities around setting optimum crop production cycles subject to the changing environment. It is concluded that protected crop production provides desired and quality products at estimated times and costs, but further analysis is required for making protected crop production can be adopted by growers in the region, under sustainable conditions of all aspect of resource sustainability. Future research will focus on developing a simulated process model to provide recommendations on appropriate greenhouse practices and crop management in order to effectively manage energy consumption in the protected cropping environment.

Due to limited oil reserves, the rising world fuel prices and environmental problems caused by the use of fossil fuels increase the tendency to use alternative fuels such as biodiesel and bioethanol. In this study, the evaluation of energy and exergy flow from seed planting to final production of biodiesel from rapeseed oil was carried out. Biodiesel production from rapeseed was made in three main phases: farm, oil extraction, and industrial biodiesel production. Initially, the input and output variables for rapeseed production were collected through questionnaires from 30 rapeseed farms in Khuzestan province, Iran. Thus, the amount of energy input and output to the field for rapeseed was estimated to be 12826.98 and 22195 MJ/ha, respectively. The highest energy consumption is related to chemical fertilizers with 65 % share of other inputs. Input and output exergy rates were obtained as 3933.494 and 22603.39 MJ/ha, respectively, and the highest exergy consumption related to diesel fuel with 58 % share of other inputs. At the biodiesel production stage, the input energy and output energy were 156.95 MJ and 41.88 MJ, respectively, and the highest amount of electricity consumed was 91.02 MJ. The total amount of exergy in the production of biodiesel and the output exergy was 48.412 MJ and 64.568 MJ, respectively. In this study, the effects of alcohol-to-oil molar ratio, ultrasound power (W), catalyst concentration (w/w %), and the reaction time (min) on methyl ester yield using response surface methodology based on Box Behnken experimental design in the Design Expert software were investigated. Finally, gas emissions were studied at the planting and biodiesel production stages, and the resultsshowed that the highest greenhouse gas emissions at the planting stage were related to chemical fertilizers and alcohol production.

Assessing the energy cycle and greenhouse gas (GHG) emissions of wheat production in small Egyptian farms is essential to improve wheat productivity to meet population growth and achieve sustainable development. This study aims to compare wheat production in terms of energy use and GHG emissions for different scenarios in the Delta of Egypt and to use Data Envelopment Analysis (DEA) to optimize the wheat production system. Three common scenarios of the wheat production system (S-I, S-II, and S-III) from old lands with one scenario (S-IV) from newly reclaimed land were included in the study. Data were collected from small farmers through a face-to-face questionnaire and interviews in 2022–2023. The results showed that the third scenario (S-III) in the old lands had the lowest input energy consumption (42,555 MJ ha−1) and the highest output energy (160,418 MJ ha−1), with an energy use efficiency of 3.770. In comparison, the input and output energy for the newly reclaimed scenario (S-IV) were 37,575 and 130,581 MJ ha−1, respectively, with an energy use efficiency of 3.475. S-III was an optimum scenario due to its high energy indicators, such as energy productivity of 0.173 kg MJ−1. The total GHG emissions of S-III were the lowest in old lands with a value of 1432.9 kg CO2-eq ha−1, while S-IV had 1290.2 kg CO2-eq ha−1. The highest GHG emissions input was diesel fuel for machinery and irrigation, followed by manure, chemical fertilizers, and agricultural machinery use. Using mechanization in most farming operations for S-III and S-IV led to decreased losses of agricultural inputs with increasing outputs (yield and straw). Therefore, using them in wheat farming practices is recommended to increase the wheat farming system’s energy efficiency and GHG emissions.

Emission intensities in EU countriesʼ food production systems and their market resilience during the 2020 global economic turmoil

PDF HTML阅读 XML下载 导出引用 引用提醒 中国主要农作物种植农药施用温室气体排放估算 DOI: 10.5846/stxb201405271084 作者: 作者单位: 中国科学院生态环境研究中心,中国科学院生态环境研究中心,中国科学院生态环境研究中心 作者简介: 通讯作者: 中图分类号: 基金项目: 国家自然科学基金青年基金项目(71003092);科技部973专题(2010CB833504-2);中国科学院战略性先导科技专项子课题(XDA05050602,XDA05060102) Estimate of greenhouse gases emission from pesticides usage in China's major crops Author: Affiliation: Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences,Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences,Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:过去30年来我国农作物的播种面积并未产生太大变化,但病虫害的发生和防治次数却不断增加。根据6种中国主要农作物的病虫害发生情况,收集了相应的农药用量及其制造的温室气体排放量数据,估算了中国主要农作物在种植过程中,因对病虫害使用杀虫剂和杀菌剂而产生的温室气体排放量现状。结果表明,我国主要农作物小麦、水稻、玉米、马铃薯、油菜和棉花的每公顷病虫害防治时使用农药所产生的温室气体排放量分别是9.19(1.86-23.24)、20.54(2.03-50.95)、10.38(3.45-19.32)、5.91(2.15-18.34)、10.84(8.10-13.62)、19.51(5.11-49.01)kg CE hm-2 a-1,即水稻和棉花最高;但论单产农药温室气体排放量,则油菜和棉花远高于其余4种粮食作物。每年小麦、水稻、玉米、马铃薯、油菜和棉花的病虫害防治使用农药所产生的总温室气体排放量分别是220.8(44.7-558.4)、606.7(60.0-1505.1)、336.4(112.0-606.3)、30.9(11.2-96.0)、79.5(59.4-99.8)、96.4(25.2-242.2)Gg CE,总计1.37(0.31-3.13)Tg CE。将以上6种作物的病虫害防治情况外推到全国农作物,则我国一年因为农作物病虫害防治而产生的温室气体排放量为2.13(0.48-4.85)Tg CE。另外由于缺乏草害面次数据而没有包括除草剂本分,所以以上数字仍是低估。病虫害防治由于作物本身、防治对象、防治方法以及药剂用量的固有差异,导致农作物病虫害防治的温室气体排放量计算结果存在着较大的不确定性,目前基于自下而上农户调查的估算方法无法克服这些问题,更精确的估算需要自上而下的企业级调查数据。 Abstract:Over the past 30 years, China's total area sown with crops did not change significantly. Meanwhile, the occurrences of crop pests and diseases as well as the control (treatment) areas have increased drastically. China has become the world's largest pesticide manufacturer and consumer since 2005 and the up-trend is expected to continue. Correspondingly, the greenhouse gases (GHGs) emission resulting from pesticide usage may also increase fast and become an important part of indirect GHGs emission in agriculture. However, domestic GHGs emission parameters from pesticide usage were rarely reported in analysis of China's agricultural life-cycle, which leads to considerable uncertainty in studies related to agricultural indirect GHGs emission. In this study, GHGs emission from pesticides manufacture was estimated by summing up the global warming potential of GHGs emitted from four processes including manufacture of active ingredients, formulation of emulsifiable oils/wettable powders/granules, packaging, and transport. According to the occurrence of pests and diseases in six major crops (wheat, rice, maize, potato, oilseed rape, and cotton) in China, the amount of current GHGs emissions induced by usage of insecticides and fungicides specific for these crops was assessed based on the integration of available information on the use of relevant pesticides and GHGs emissions from their manufacturing. Our estimation indicated that the GHGs emission pertaining to pests and diseases control was the highest for rice and cotton (20.54 [2.03-50.95] and 19.51 [5.11-49.01], respectively) followed by oilseed rape (10.84 [8.10-13.62]), maize (10.38 [3.45-19.32]), wheat (9.19 [1.86-23.24]), and potato (5.91 [2.15-18.34] kg carbon equivalent [CE] per hectare each year). Different crop pests and diseases contributed differently to crop's GHGs emission from pesticides usage: for maize and cotton, pests were the main contributors (especially maize borer, maize earworm, and cotton plant-bug); for oilseed rape and potato, diseases were the main contributors (especially potato late blight and rape sclerotinia rot); and for wheat and rice, pests and diseases both contributed equally to the total emission (especially wheat aphid, wheat midge, wheat red spider, wheat powdery mildew, wheat scab, rice plant hopper, rice leaf roller, rice striped stem borer, rice blast, and rice sheath blight). Meanwhile, as to the pesticide GHGs emission per unit yield, all four grain crops contributed far less than cotton and oilseed rape. Correspondingly, the overall emission due to the insect pests and diseases control measures for each of the analyzed crops in China was: 220.8 (44.7-558.4), 606.7 (60.0-1505.1), 336.4 (112.0-606.3), 30.9 (11.2-96.0), 79.5 (59.4-99.8), and 96.4 (25.2-242.2) Gg CE/a for wheat, rice, maize, potato, oilseed rape, and cotton, respectively, with a total amount of 1.37 (0.31-3.13) Tg CE/a. It should be noted that these results are underestimation of China's actual pesticide GHGs emission since the herbicides were not considered because of the unavailability of weed treatment data. Owing to the variation in the characteristics of crop pests and diseases control measures (including various conditions of crops, pests, and diseases, wide range of pesticide and fungicide choices and their legal dosage), non-negligible uncertainties still exist in our current bottom-up estimates based on farmer surveys. More accurate estimation requires implementation of top-down methods and data based on enterprise-level surveys. 参考文献 相似文献 引证文献

Introduction: Golestan province is one of Northern provinces in Iran. The area under cultivation of agricultural products in this province is 724.697 hectares, of which about 694.618 hectares are used for farm products (AJMDC, 2011). Cotton as one of oilseed is a potential feedstock for biodiesel production (Ahmad et al., 2011). In the study of energy consumption and greenhouse gas emissions for cotton production in Alborz province, results showed that the total energy input was 31.237 MJ ha-1. Energy efficiency and energy productivity were 1.85 and 0.11, respectively, and greenhouse gas emissions of cotton production in Alborz province were 1195.25 kg CO2eq ha-1 (Pishgar-Komleh et al., 2012). Another study on energy analysis, greenhouse gas emissions and economic analysis of agricultural production was performed in Northern Iran (AghaAlikhani et al., 2013; Royan et al., 2012; Pishgar-Komleh et al., 2011; Mohammadi et al., 2010; Taheri-Garavand et al., 2010). The aims of this study were to determine the energy flow, greenhouse gas emissions and economic analysis of cotton production in the Golestan province and also to determine the effect of energy inputs on cotton yield. Materials and methods: This research was conducted during 2011-2012 in three areas including Gorgan, Aq’qala and Gonbad in the Golestan province. The primary data were collected from the rice producers through a field survey with the help of a structured questionnaire. The number of subjects were studied by the Cochran formula (Snedecor and Cochran, 1980). Accordingly, 43 cotton producers were determined. In this study, eight energy inputs including seed, labor, machinery, diesel fuel, chemical fertilizers, chemicals, water for irrigation and farmyard manure for cotton production system were considered as independent variables. The outputs of the system including lint and seed were considered as dependent variable. Energy indices including energy efficiency, energy productivity, specific energy and net energy were calculated. In this study, the effect of energy inputs on yield was estimated using the Cobb-Douglas function. In order to determine the sensitivity of energy inputs in the production of cotton in the Golestan province, the marginal physical productivity method was applied. Greenhouse gas emissions, inputs of agricultural machinery, fuel, chemical fertilizers, chemicals and farmyard manure in cotton production in the Golestan province were calculated by the coefficients of each of these inputs. For economic evaluation of cotton production in the Golestan province, the variable costs, fixed and total production per unit area were considered. Economic indices of total production value, gross income, net income, economic productivity and benefit to cost ratio were estimated. Data analysis was performed using JMP8 software. Results and Discussion: Cotton yield in the Golestan province was about 2650 kg ha-1. Average cotton yield in the Alborz province was reported to be 3430 kg ha-1 (Pishgar-Komleh et al., 2012). In this study, diesel fuel had the highest energy consumer among other inputs like the other studies that have been done on energy crop production in Iran. Labor energy input with energy consumption of 2413 MJ ha-1, is known to be the fourth high-energy input in cotton production in the Golestan province. However, in many studies in Iran, this input was accounted to be less than one percent of the energy consumption in the production of agricultural products (Saeedi et al., 2013; Khoshnevisan et al., 2013; Mobtaker et al., 2012; Mobtaker et al., 2010). Chemical energy input with 1036 MJ ha-1, was allocated as 3.6% of energy consumption in the cotton production in the region. Seed energy input was the lowest energy among the other inputs in cotton production in the Golestan province. The results revealed that the total energy inputs for cotton production in the Golestan province was 28.898 MJ ha-1. The average energy efficiency for cotton production in the Golestan province was obtained to be 1.58. Energy productivity for cotton production in the Golestan province was calculated to be 0.092. From the results of Cobb-Douglas function to determine the relationship between energy input and yield of cotton in Golestan province, the effects of human labor, diesel fuel, water for irrigation, chemical fertilizers and farmyard manure inputs on the yield were positive, and the effects of agriculture machinery and chemicals inputs on cotton yield were negative. Greenhouse gas emission from diesel fuel input hadthe highest value of 646.23 kg CO2eq ha-1 with a 45.2 percent share. Farmyard manure with 23.5 percent of greenhouse emissions was identified as the second largest input in greenhouse gas emissions in cotton production. Variable costs, fixed and total cotton production in the Golestan province were calculated to be 3042429, 851880 and 3894309 Toman ha-1, respectively. Benefit to cost ratio for the cotton production in the Golestan province was calculated as 1.16. Conclusions: The results of this study showed that the energy efficiency for cotton production in the Golestan province was less than the energy efficiency for cotton production in the Alborz province, Hatay province of Turkey, and canola, soybean and sunflower production in the Golestan province. Also, the energy efficiency of cotton production was less than that of cotton production in Antalya Turkey and canola in the Mazandaran province. The highest share of energy consumption and greenhouse gas emissions belonged to diesel fuel with the share of 45.6 and 45.2 percent, respectively. However, this input accounted for 2.7 percent of variable costs.