Nasibe Rezvantalab; Afshin Soltani; Ebrahim Zeinali; Salman Dastan; Alireza Foroughnia
Introduction: Inputs such as chemical fertilizers, fossil fuels, electricity, seed, and machinery consume energy in soybean production. This energy consumption is expected to cause Greenhouse Gases Emissions (GHG). Increasing the concentration of these gases in the atmosphere could lead to Global Warming. ...
Introduction: Inputs such as chemical fertilizers, fossil fuels, electricity, seed, and machinery consume energy in soybean production. This energy consumption is expected to cause Greenhouse Gases Emissions (GHG). Increasing the concentration of these gases in the atmosphere could lead to Global Warming. The purpose of this study was to investigate the energy consumption and GHG in soybean production in Golestan Province, Iran. Material and methods: In this study, 140 farmers were selected to investigate the soybean production systems in Golestan Province in northeastern Iran. The data of consumed energy (machines, seeds, fertilizers, fuel, pesticides, human labor, and electricity) were collected by a questionnaire. Then fuel, input and output energy, energy indices, and global warming potential (kg eq-CO2/ha) were calculated by related coefficients. Results and discussion: Based on results, fuel and energy requirements for soybean production were estimated 210.83±0.09 L/ha and 19036.08±2.53 MJ/ha, respectively. Also, GHG emissions were calculated 2306.85±3.17 kg eq-CO2/ha. Fossil fuel and electricity consumption had the highest energy consumption and GHG emissions values, respectively, so that 62% of the total energy consumption and 75% of the total GHG emission belonged to electricity and fossil fuel consumption, respectively. Energy output derived from soybean was 42124.95±0.73 MJ/ha. The output-input ratio was estimated 2.21±0.01. Net energy gain was raised by increasing the seed yield and decreasing the input consumption such as electricity, fossil fuel, and N-fertilizer. Energy productivity was calculated 0.147±0.01 Kg/MJ. On average, 2306.85±3.17 kg eq-CO2/ha greenhouse gases were released into the atmosphere for soybean seed production. Conclusion: Focusing on optimal consumption of fossil fuels and decreasing the electricity consumption in irrigation is essential for reducing the energy consumption and greenhouse gas emissions for soybean production in Golestan Province, Iran.
Mohammad Hosein Torabi; Afshin Soltani; Salman Dastan; Hosein Ajam Norouzi
Volume 16, Issue 4 , January 2019, , Pages 187-212
Introduction: Environmental assessment of the life cycle of crops in production systems is an accepted method for achieving agricultural sustainability. Moreover, the agricultural sector has a significant contribution to greenhouse gas emissions and global warming. Hence, improving agricultural operations ...
Introduction: Environmental assessment of the life cycle of crops in production systems is an accepted method for achieving agricultural sustainability. Moreover, the agricultural sector has a significant contribution to greenhouse gas emissions and global warming. Hence, improving agricultural operations is an appropriate way to mitigate the effects of climate change. Therefore, the aim of this research was the environmental assessment of different scenarios of the production of improved rice cultivars. Material and methods: After preliminary evaluation and consultation with rice specialists, 100 paddy fields were selected for semi-mechanized planting method and 100 paddy fields for traditional planting method in Sari region from 2015 to 2016. After recording the data, each planting method was converted into four planting systems based on agronomic management and input consumption, which formed a total of eight scenarios. Four scenarios of the semi-mechanized method were systems of low-input (SL), conservation (SCI), conventional (SCII) and high-input (SH). Four scenarios of the traditional method were systems of low-input (TL), conservation (TCI), conventional (TCII) and high-input (TH). Results and discussion: The results indicated that the average paddy yield in eight scenarios was 6418 kg.ha-1. The average input energy in eight scenarios was 28138.93 MJ.ha-1, which contained 45.44% renewable (biologic) energy and 54.56% non-renewable (industrial) energy. The highest input energy was observed in scenarios IV and VIII, which was related to the SH in both planting methods. The average output energy in eight scenarios was equal to 197076 MJ.ha-1. The highest output energy was obtained in scenarios III, IV, VII and VIII. The average energy productivity in the eight scenarios was equal to 0.23 kg.MJ-1 that the least amount was obtained in both planting methods and the other scenarios were on the same level. The average CO2 emissions in all eight scenarios were 1120.37 kg CO2.eq ha-1, which had the highest share related to seed, fuel, and machinery. In terms of global warming potential per unit area, scenario VIII was ranked first and scenario IV ranked second. The highest global warming potential per grain weight and GWP per input energy were achieved in scenarios I and V. The highest heavy metal emission into water and soil was observed in the SH and SCII, respectively. The highest net primary productivity (NPP) in production scenarios was related to SCII and SH, which was higher in the semi-mechanized method than the traditional method. In both planting methods, the most relative carbon inputs (Ri) were obtained in scenarios of the SH (I and V). With regard to input-output carbon and net carbon in eight scenarios, the average sustainability index was 4.66. The highest sustainability index was observed in scenario II (5.05), which was related to the conservation system. The scenarios V, I, III and VI were next ranked in terms of the sustainability index. In fact, the correct management of the paddy field in the SCI has led to a reduction in emissions of environmental pollutants. Conclusion: According to the findings, SL and SCI were closer to sustainable development indicators in both methods. Furthermore, the economic efficiency of rice production was more important to farmers than environmental sustainability and energy efficiency. Hence, using the findings of this research can be very effective in increasing environmental sustainability and reducing the environmental impacts of chemical inputs and achieving agricultural sustainability.
Salman Dastan; Afshin Soltani; Ghorban Noormohamadi; Hamid Madani; Reza Yadi
Volume 14, Issue 1 , April 2016, , Pages 19-28
Optimal management approaches can be adopted in order to increase crop productivity and lower the carbon footprint of grain products. The objective of this study was to estimate the carbon (C) footprint and global warming potential of rice production systems. In this experiment, rice production systems ...
Optimal management approaches can be adopted in order to increase crop productivity and lower the carbon footprint of grain products. The objective of this study was to estimate the carbon (C) footprint and global warming potential of rice production systems. In this experiment, rice production systems (including SRI, improved and conventional) were studied. All activities, field operations and data in production methods and at different input rates were monitored and recorded during 2012. Results showed that average GWP across production systems was equal to 2803.25 kg CO2-eq ha-1. The highest and least GWP were observed in the SRI and conventional systems, respectively. GWP per unit energy input was the least and most in SRI and conventional systems, respectively. Also, the SRI and conventional systems had the maximum and minimum GWP per unit energy output, respectively. SRI and conventional system had the greatest and least GWP per unit energy output, respectively. Therefore, the optimal management approach found in SRI resulted in a reduction in GHGs, GWP and the carbon footprint.