| 11011. |
- Mohammadi, Ali, 1983-, et al.
(författare)
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Biochar use for climate-change mitigation in rice cropping systems
- 2016
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Ingår i: Journal of Cleaner Production. - : Elsevier. - 0959-6526 .- 1879-1786. ; 116, s. 61-70
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Tidskriftsartikel (refereegranskat)abstract
- This study estimated the climate change effects of alternative rice production systems in North Vietnam with different residue management options, using Life Cycle Assessment (LCA). The traditional practice of open burning of residues (System A) was compared with the alternative of converting residues to biochar, which was returned to the same land area from which the residues were obtained (System B). Pyrolytic cook-stoves and drum ovens were assumed to be used by households to produce biochar, and the cook-stoves produced heat energy for cooking. The annual rate of biochar applied was determined by the amount of biochar produced from the straw and husk available. We assumed that agronomic effects of biochar increased with each annual biochar application until reaching maximum benefits at 18 Mg ha I, which takes eight years to be produced in pyrolytic cook-stoves and drum ovens. The largest contributor to the carbon footprint of rice at the mill gate, was CH4 emissions from soil, in both systems. Biochar addition reduced the carbon footprint of spring rice and summer rice by 26% and 14% respectively, compared with System A, in the first year of application. These values substantially increased to 49% and 38% after eight years of biochar addition. The climate effect of System B was most sensitive to the assumed suppression of soil CH4 emissions due to biochar application. (C) 2015 Elsevier Ltd. All rights reserved.
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| 11012. |
- Mohammadi, Ali, 1983-
(författare)
-
Carbon sequestration potential of Miscanthus application as biofuel source in Sweden
- 2022
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Konferensbidrag (refereegranskat)abstract
- Sweden aims to achieve net zero GHG emissions by 2045. To do this, one strategy could be increasing the biomass contribution in energy sector as approximately 75% of total greenhouse gas (GHG) emissions are related to energy consumption. Therefore, it is beneficial to explore efficient ways to upgrade biomass materials into high value-added bioenergy. This study considers the potential of Miscanthus cultivation and its application as biofuel materials in Sweden in terms of carbon sequestration and contribution in climate impact mitigation. Miscanthus, as an energy crop with relatively low maintenance requirements and a high dry matter yield and energy content, can play a major role in the sustainable development of biofuels. Using Miscanthus for energy, results in avoiding fossil fuel combustion and the corresponding GHG emissions. The results of this assessment demonstrated that the Miscanthus cultivation contributes in soil organic carbon sequestration by over one tonne carbon ha−1 yr−1 which results in mitigating a significant amount of soil CO2 fluxes. Therefore, the adaption of Miscanthus biomass, would directly contribute in UN Goal 7, affordable and clean energy, and Goal 13, climate action due to a significant reduction in GHG emissions. The integration of Miscanthus plant into the landscape may stimulate the economy of rural areas in the country and offer more profit than afforestation and reforestation on abandoned and marginal croplands.
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| 11013. |
- Mohammadi, Ali, 1983-, et al.
(författare)
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Eco-Efficiency Analysis to Improve Environmental Performance of Wheat Production
- 2022
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Ingår i: Agriculture. - : MDPI. - 2077-0472. ; 12:7, s. 1-16
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Tidskriftsartikel (refereegranskat)abstract
- Though increasing food supply in order to meet the rising demand for nutrition is a global social imperative, reducing the dependence on imports of essential food commodities is both an economic and a geo-political imperative for national governments. However, in light of the Sustainable Development Goals, although Zero Hunger (SDG2) and Good Health and Well-Being (SDG3) can be ensured within a country when the inhabitants are well-nourished and staple food items remain affordable to one and all, oftentimes, there are trade-offs in the process, with the environmental dimensions—SDGs 13 (Climate action), 14 (Life below water) and 15 (Life on Land). In this paper, using a combination of Environmental-Life Cycle Assessment (E-LCA) and Data Envelopment Analysis (DEA), the authors have evaluated the eco-efficiency of 169 wheat cultivation systems in the Golestan province in the north of Iran. Benchmarking performance based on the best-performing wheat farms and optimizing (decreasing essentially) the consumption of resources, will enable an average reduction of between 10% and 16% in global warming, acidification, eutrophication, and non-renewable energy usage of the wheat cultivation systems in the case study region. The authors recommend the use of this combination not only for wheat cultivation in other regions of the world, but also for other agricultural systems.
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| 11014. |
- Mohammadi, Ali, 1983-, et al.
(författare)
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Energy use efficiency and greenhouse gas emissions of farming systems in north Iran
- 2014
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Ingår i: Renewable & sustainable energy reviews. - : Pergamon Press. - 1364-0321 .- 1879-0690. ; 30, s. 724-733
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Forskningsöversikt (refereegranskat)abstract
- Efficient use of energy resources in crop production is an important goal in sustainable agriculture. This study compares the energy flow in farming systems across farm size with their corresponding greenhouse gas (GHG) emissions - presented in terms of carbon dioxide equivalent (CO2 eq.) - in the north of Iran. To reach this aim, primary data were collected by survey with farmers whose main activity was major crops production in the region that included wheat, barley, canola, soybean, paddy and corn silage. The results showed that total energy input for corn silage (52.1 GJ ha(-1)) is greater than other systems. The results also revealed that yield and output energy of crops were not significantly affected by field size, whereas energy use efficiency of systems increased significantly as field size increased. Study shows that the cultivation of paddy emits the highest CO2 eq. emission (6094 kg CO2 eq. ha(-1)) among crops, in which around 60% is contributed by methane (CH4). The efficient use of fertilizers, optimized pumping facilities for irrigation, stopping of crop residue burning in the field and use them for energy supply could be among the options to improve energy use efficiency and mitigate GHG emissions. (C) 2013 Elsevier Ltd. All rights reserved.
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| 11015. |
- Mohammadi, Ali, 1983-, et al.
(författare)
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The Technical Challenges of the Gasification Technologies Currently in Use and Ways of Optimizing Them : A Review
- 2022
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Ingår i: Energy Recovery. - : INTECH. - 9781803556093
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Bokkapitel (refereegranskat)abstract
- Since the world is gradually drifting toward sustainable development, renewable energy technologies are gaining traction and gasification technology is one of many renewable energy technologies that have gained popularity in recent times. The gasification technology is one of three main (combustion and pyrolysis) thermochemical conversion pathways that can be used to recover energy from biomass materials. Although the gasification technology has been in existence for centuries, it has not been exploited to its full potential mainly because the fundamental principles underpinning its operation are still vague, particularly with regard to feedstock flexibility and the type of gasification system. Furthermore, due to the many types of gasification systems, the mechanisms involved in their feedstock conversion processes are still under debate and require further research to clearly establish the optimum conditions of performance of each type of gasifier. Therefore, this chapter presents an overview of the gasification technology and discusses the different types of gasification systems that are commonly used today for the recovery of energy. The limitations of each type of gasifier in relation to performance and feedstock conversion are also discussed, including research priority areas that will allow for system optimization in terms of efficiency.
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| 11016. |
- Mohammadi, Babak, et al.
(författare)
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Improving glacio-hydrological model calibration and model performance in cold regions using satellite snow cover data
- 2024
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Ingår i: Applied water science. - 2190-5487. ; 14:3
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Tidskriftsartikel (refereegranskat)abstract
- Hydrological modeling realism is a central research question in hydrological studies. However, it is still a common practice to calibrate hydrological models using streamflow as a single hydrological variable, which can lead to large parameter uncertainty in hydrological simulations. To address this issue, this study employed a multi-variable calibration framework to reduce parameter uncertainty in a glacierized catchment. The current study employed multi-variable calibration using three different calibration schemes to calibrate a glacio-hydrological model (namely the FLEXG) in northern Sweden. The schemes included using only gauged streamflow data (scheme 1), using satellite snow cover area (SCA) derived from MODIS data (scheme 2), and using both gauged streamflow data and satellite SCA data as references for calibration (scheme 3) of the FLEXG model. This study integrated the objective functions of satellite-derived SCA and gauged streamflow into one criterion for the FLEXG model calibration using a weight-based approach. Our results showed that calibrating the FLEXG model based on solely satellite SCA data (from MODIS) produced an accurate simulation of SCA but poor simulation of streamflow. In contrast, calibrating the FLEXG model based on the measured streamflow data resulted in minimum error for streamflow simulation but high error for SCA simulation. The promising results were achieved for glacio-hydrological simulation with acceptable accuracy for simulation of both streamflow and SCA, when both streamflow and SCA data were used for calibration of FLEXG. Therefore, multi-variable calibration in a glacierized basin could provide more realistic hydrological modeling in terms of multiple glacio-hydrological variables.
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| 11017. |
- Mohammadi, Babak, et al.
(författare)
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The superiority of the Adjusted Normalized Difference Snow Index (ANDSI) for mapping glaciers using Sentinel-2 multispectral satellite imagery
- 2023
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Ingår i: GIScience and Remote Sensing. - 1548-1603. ; 60:1
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Tidskriftsartikel (refereegranskat)abstract
- Accurate monitoring of glaciers’ extents and their dynamics is essential for improving our understanding of the impacts of climate and environmental changes in cold regions. The satellite-based Normalized Difference Snow Index (NDSI) has been widely used for mapping snow cover and glaciers around the globe. However, mapping glaciers in snow-covered areas using existing indices remains a challenging task due to their incapabilities in separating snow, glaciers, and water. This study aimed to evaluate a new satellite-based index and apply machine learning algorithms to improve the accuracy of mapping glaciers. A new index based on satellite data from Sentinel-2 was tested, which we call the Adjusted Normalized Difference Snow Index (ANDSI). ANDSI (besides NDSI) was used with five different machine learning algorithms, namely Artificial Neural Network, C5.0 Decision Tree Algorithm, Naive Bayes classifier, Support Vector Machine, and Extreme Gradient Boosting, to map glaciers, and their performance was evaluated against ground reference data. Four glacierized regions in different countries (Canada, China, Sweden, and Switzerland-Italy) were selected as study sites to evaluate the performance of the proposed ANDSI. Results showed that the proposed ANDSI outperformed the original NDSI, and the C5.0 classifier showed the best overall accuracy and Kappa among the selected five machine learning classifiers in the majority of cases. The original NDSI yielded results with an average overall accuracy of (around) 91% and the proposed ANDSI with (around) 95% for glacier mapping across all models and study regions. This study demonstrates that the proposed ANDSI serves as a superior and improved method for accurately mapping glaciers in cold regions.
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| 11018. |
- Mohammadi, Saeed, 1989-, et al.
(författare)
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A Machine Learning Approach for Prosumer Management in Intraday Electricity Markets
- 2022
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Ingår i: 2022 IEEE Workshop on Complexity in Engineering, COMPENG 2022. - : Institute of Electrical and Electronics Engineers (IEEE).
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Konferensbidrag (refereegranskat)abstract
- Prosumer operators are dealing with extensive challenges to participate in short-term electricity markets while taking uncertainties into account. Challenges such as variation in demand, solar energy, wind power, and electricity prices as well as faster response time in intraday electricity markets. Machine learning approaches could resolve these challenges due to their ability to continuous learning of complex relations and providing a real-time response. Such approaches are applicable with presence of the high performance computing and big data. To tackle these challenges, a Markov decision process is proposed and solved with a reinforcement learning algorithm with proper observations and actions employing tabular Q-learning. Trained agent converges to a policy which is similar to the global optimal solution. It increases the prosumer's profit by 13.39% compared to the well-known stochastic optimization approach.
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| 11019. |
- Mohammadi, Saeed, 1989-, et al.
(författare)
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Econometric Modeling of Intraday Electricity Market Price with Inadequate Historical Data
- 2022
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Ingår i: 2022 IEEE Workshop on Complexity in Engineering, COMPENG 2022. - : Institute of Electrical and Electronics Engineers (IEEE).
-
Konferensbidrag (refereegranskat)abstract
- The intraday (ID) electricity market has received an increasing attention in the recent EU electricity-market discussions. This is partly because the uncertainty in the underlying power system is growing and the ID market provides an adjustment platform to deal with such uncertainties. Hence, market participants need a proper ID market price model to optimally adjust their positions by trading in the market. Inadequate historical data for ID market price makes it more challenging to model. This paper proposes long short-term memory, deep convolutional generative adversarial networks, and No-U-Turn sampler algorithms to model ID market prices. Our proposed econometric ID market price models are applied to the Nordic ID price data and their promising performance are illustrated.
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| 11020. |
- Mohiti Ardakani, Maryam, 1989, et al.
(författare)
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A Decentralized Transactive-Based Model for Reactive Power Ancillary Service Provision by Local Energy Communities
- 2023
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Ingår i: 2023 IEEE Belgrade PowerTech, PowerTech 2023.
-
Konferensbidrag (refereegranskat)abstract
- Local Energy Communities (LECs) have been introduced to facilitate the high penetration of distributed energy resources into distribution systems (DSs), which can also be valuable sources of ancillary services for Distribution System Operators (DSOs). The aim of this paper is to investigate if and how LECs can contribute to the reactive power management of DSs. To this end, a transactive-based model is proposed to manage the reactive power of LECs in a decentralized way. In the proposed model, DSO sends transactive signals to LECs and incentivizes them to inject/absorb reactive power aiming at controlling the voltage profile of DS. Accordingly, the reactive power management and thus voltage control is performed without any direct interferences of the DSO in the resource scheduling of LECs. The proposed model is applied to the DS of Chalmers campus to demonstrate its performance in reactive power management and voltage control.
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