Iranica Journal of Energy and Environment
Year:2025 | Volume:16 | Issue:4|Papers Count:15

Since photovoltaic (PV) panels are exposed to solar intensity long during the daytime, their temperature increases significantly, which reduces their electrical efficiencies. This crucial factor has led many studies to investigate various methods of cooling PV. The current study experimentally analyzes the effectiveness of a new passive method to reduce PVs’ temperature by using encapsulated phase change material (PCM) units placed on the PVs’ backsides. PCMs have high latent heat and absorb/release huge amounts of thermal energy through melting/solidification. Recent studies covered the PVs’ backside with PCM, while the current study used PCM capsules instead. This new strategy lets the PV exchange heat the ambient when PCM melt completely and improves cooling performance. An experimental setup was developed for this aim, and it was tested outdoors in Bam, Iran, in late April and early May 2024, considering two scenarios: PV with and without encapsulated PCM. The results proved that PCM units reduced the PV temperature between 3 oC and 9 oC. This temperature reduction caused the PV with PCM capsules to produce more electrical power by 17% compared to the conventional PV at noon. The higher the electrical power generated, the higher the efficiency can be achieved in the scenario with PCM units. The daily electrical efficiency of the PV with PCM units was 14.14% higher than the conventional PV. This study illustrates that using encapsulated PCM units as a passive method is a strong and affordable method to improve the PVs’ electrical efficiency.

This paper focuses on the design of a 200 kW photovoltaic (PV) system on the University of Mazandaran (UMZ) campus and the technical and practical challenges. In this regard, PVsyst software is used to optimize the panel layout to both reduce land use and maximize energy efficiency. The findings indicate that a tilt angle of 26 degrees and a row spacing of 4 meters, which decreases land area by 43% relative to a 7-meter spacing, results in just a 4.4% reduction in energy production. In a comparison of three layout designs including longitudinal rectangle, transverse rectangle and square, the transverse rectangular design with dimensions of 52 × 27.5 m offers the best performance with an annual efficiency of 256 MWh and a performance ratio of 0.817, which is ideal for rectangular plots. The Law on the Removal of Production Barriers and the Renewable Energy Agency (SATBA) authorize a 6.9 cents/kWh feed-in tariff, extending the payback time to four years. Technical, economic, and policy aspects of PV systems in limited urban areas are optimized.  It also suggests realistic solar solutions for corporations within spatial and climatic constraints. Key recommendations include promoting PV systems to save land and holding educational workshops to gain community support and address environmental concerns. This research provides a sustainable and replicable model for solar energy development that reduces dependence on fossil fuels and reduces carbon emissions. This is done by combining cost-benefit analysis, technical optimization and policy alignment.

This study examines the impact of balcony design on energy efficiency and daylight performance in residential buildings located in Tehran's hot and arid climate. Balconies function as semi-open shaded spaces during the warm season and transform into greenhouses with enclosures during the cold season, significantly influencing ventilation efficiency and thermal dynamics. To investigate these seasonal effects, simulations were conducted using Rhino 7 and Grasshopper3D, along with plugins such as Ladybug Tools, which incorporate Radiance for daylight analysis and EnergyPlus for energy modeling. A dataset comprising 1,636 balcony models with varying dimensions and window-to-wall ratios (WWR) was analyzed. The results indicate that well-designed balconies, optimized for depth, width, and orientation, can substantially reduce energy consumption while enhancing visual comfort. Optimal designs vary based on orientation: east-west elongated balconies maximize daylight access, square-shaped balconies improve versatility and energy efficiency, and north-south elongated balconies achieve the lowest energy consumption. Balconies shorter than 3 meters in length, approximately 1.5 meters in width, and with a WWR of around 20% effectively balance energy efficiency and natural lighting. These findings provide practical insights for sustainable balcony design, promoting reduced energy consumption and improved occupant comfort.

This paper presents the analysis of key operational performance indicators and some effective improvement strategies, carried out on four gas turbine generators of a power plant company, in Nigeria for a period of four years (2019-2022). The investigation used the NERC/IEEE Standard 762 generator performance indices amongst other calculated key performance indices in the evaluation of the collected data. The research methodology was done through collection of data using questionnaires, operational records and plant data sheets recorded by operators in the power station and data analysis using Excel and Python software, afterward, constructive optimization techniques were recommended for each operational factor. From the result obtained, the operational performance shows an average energy generation of approximately 389.71 GWh. The equipment availability factor averaged 54.08%, indicating moderate reliability. The energy availability factor was notably lower, averaging 11.99%, suggesting significant room for improvement. The capacity factor averaged 9.39%, while the plant use factor was relatively high at 80.59%, demonstrating efficient usage when operational. The load factor was low, with an average of 0.10, pointing to potential underutilization of capacity. The shortfall in performance levels of the plant is attributed to less plant availability due to overdue overhauling of some units resulting in frequent breakdowns/failures, obsolete technology, ageing plant equipment, instability of the national grid system, among others. The recommended strategic techniques are designed to address the specific challenges associated with each factor, thereby enhancing the overall operational performance of the power plant and other power generation companies for maximum productivity.

The global community is expected to face crises related to water, energy, food, and environment in the foreseeable future. Water, environment, food, and energy are crucial and interconnected factors for the present and future of humanity in achieving sustainable development. This study aimed to investigate the relationships between water, food, energy, and environmental resources and to examine the effect of environmental policies on the security of water, food, and energy resources in Sistan region. For this purpose, a system dynamics approach was employed for a 30-year period from 2006 to 2036. The model calibration results revealed that it would successfully simulate the overall trend of the data. Furthermore, the results showed that implementing environmental policies would reduce water resource security in all three scenarios compared to the base scenario. Specifically, with the restoration of the Hamoun Wetland (Scenario 1), water security would decrease from 4,156 million m3 in 2006 (base scenario) to -6,815.07 million m3 in 2036. That is a decrease of almost 160 percent. Similarly, in the depression restoration scenario of the Hamoun Wetland (Scenario 2) and the scenario of changing allocation priorities (Scenario 3), water resource security would decline. However, applying these scenarios would slightly increase food security compared to the base scenario. In Scenario 1, food security would rise from 2,271.76 tons in 2006 to 4,978.33 tons in 2036, while in Scenario 2, it would reach 4,977 tons, and in Scenario 3, it would reach 4,972.84 tons, showing an increase of 53% in all scenarios. According to the results, it is not feasible to allocate water from surface water resources to the wetland as it reduces water security. Therefore, protecting the Hamoun Wetland requires adopting an integrated approach and implementing a set of participatory policies.

This study analyzes a hybrid solar-wind energy system for a nearly zero-energy building (nZEB) in Shahinshahr, Iran, over 25 years, using HOMER V2.81 software. It highlights the system's significance as a sustainable energy solution. The scientific contribution lies in its sensitivity analysis for optimizing hybrid systems and renewable energy use. Real-world data informs the methodology, and scenarios are ranked via the TOPSIS method. Among six parameters, “Emissions (kg/year)” has the highest influence (normalized weight: 0.52), while “Renewable Fraction (%)” and “Losses (kWh/year)” have the least (weight: 0.31). Results indicate that the grid-connected solar system, supplying 46% of energy at a cost of $58,726, is most suitable, preventing 119 tons of CO2 annually. The hybrid solar-wind system ranks second, despite achieving the highest renewable electricity and pollution reduction. The grid-connected wind system ranks third, offering the lowest converter losses and highest surplus electricity. This work serves as a roadmap for optimizing renewable energy systems and advancing nZEBs.

Global warming (GW) has emerged as a critical environmental issue, significantly impacting urban areas and community life. It has led to rising ambient air temperatures, altered precipitation patterns, and introduced severe health risks to urban populations. Understanding the severe implications of this phenomenon on a city like Kermanshah, the present study employed a strategic planning process to explore optimal solutions that promote environmental ethics (EE) to combat GW. Utilizing a descriptive-analytical methodology, the research integrated insights from scholarly resources and expert opinions to initially identify the strengths, weaknesses, opportunities, and threats (SWOT) associated with EE in Kermanshah. Following this, the study employed the Analytic Hierarchy Process (AHP) for prioritizing and weighing these variables with the support of Expert Choice software for precise calculations. The findings revealed that the evaluation score for internal factors, comprising strengths and weaknesses, stood at 3.618, while external factors, encompassing opportunities and threats, scored 1.342. Based on these data points, the strategic positioning was determined to align with the competitive strategy (ST) framework. The application of a competitive strategy has emerged as a pivotal solution for addressing bioethical concerns related to environmental challenges in Kermanshah. Such a strategy holds the potential to mitigate the repercussions of GW effectively and serves as an exemplary model for other cities aiming to adopt similar initiatives. By embracing this framework, cities can move significantly closer to achieving sustainable development goals.

Buildings and their subsidiary industries account for a significant portion of world energy consumption and greenhouse gas emissions, making it essential to assess the impact of climate change on them. In this study, the impact of the RCP 2.6 and RCP 8.5 scenarios, as the potential scenarios of the Intergovernmental Panel on Climate Change, has been evaluated on energy consumption of a residential building. A detailed computer model was developed based on local climate data for a villa house to assess the changes in energy use under different climatic impacts. The scenarios are RCP 2.6 which represents the most optimistic scenario, assuming strong mitigation efforts, and RCP 8.5 which reflects the worst-case scenario with minimal climate action. The results showed that a 48% decrease in gas consumption and a 35% increase in electricity will be expected in 2100 according to the RCP 8.5 scenario. Meanwhile, in the RCP 2.6 scenario, gas consumption decreases by 28%, and electricity consumption will increase by only 15%. Iran is struggling with a severe energy deficit crisis exacerbated during the summer due to the government's failure to supply electricity. Providing a realistic estimation of climatic impacts on the energy consumption type and magnitude will help to develop better future strategies to solve this across the country.

The increasing concentration of greenhouse gases (GHGs), particularly methane (CH₄) and carbon dioxide (CO₂), significantly contributes to climate change, necessitating continuous and accurate monitoring. This study presents the design and implementation of a real-time greenhouse gas detection and measurement system using cost-effective sensors (MQ-4, MQ-135, DHT-11, and BMP-280) integrated with an Arduino Uno and ESP32 WiFi module. The system was deployed in selected locations across Abuja, Nigeria, and monitored CH₄ and CO₂ concentrations over a period of five months. Calibration of the sensors was performed using known gas standards, and data validation was conducted to account for environmental factors such as temperature and humidity. The results indicate significant variability in CO₂ (27 ppm to 1043 ppm) and CH₄ (313 ppb to 4762 ppb) concentrations, with notable spikes linked to potential emission events. Statistical analysis was employed to differentiate between natural fluctuations and external emissions. The system demonstrated high reliability in data transmission and sensor accuracy, making it a cost-effective alternative for continuous environmental monitoring. Future research will focus on improving sensor precision and expanding monitoring to diverse locations for a more comprehensive understanding of greenhouse gas trends.

Microplastics in sewage sludge represent a formidable obstacle to the use of biosolids in agricultural lands. Ultrasonic pretreatment is extensively utilized in sludge management to enhance biodegradability, reduce organic contaminants, and improve process efficiency through cavitation-induced physical and chemical effects. This research evaluates the effects of conventional ultrasonic sludge pretreatment—operating at a frequency of 20 kHz, a power level of 400 W, a temperature of 25°C, and 15 minutes—on sludge containing biodegradable polyethylene (PE) and non-biodegradable polyvinyl chloride (PVC) microplastics. Structural, morphological, and chemical analyses were conducted using Scanning Electron Microscopy (SEM) and Fourier Transform Infrared Spectroscopy (FTIR). The SEM results, obtained at magnifications of 60× (PE) and 100× (PVC) with scales of 500 µm and 300 µm, revealed no major physical modifications, such as cracks, fractures, or surface erosion, in either PE or PVC microplastics. Similarly, surface morphology remained largely unchanged across all examined resolutions, including 500 nm and 300 nm, suggesting their structural stability following treatment. Likewise, FTIR spectra demonstrated the chemical resilience of both polymers, as not major alterations were observed in their characteristic absorption peaks (e.g., 2920 and 2850 cm⁻¹ for PE, 1430 and 1250 cm⁻¹ for PVC). Overall, the findings indicate that conventional ultrasonic sludge pretreatment exerts negligible influence on the physical and chemical integrity of the studied microplastics, highlighting their resistance to ultrasonic cavitation and potential persistence in sewage sludge used for agricultural applications.

Today, the focus of governments, industries, and consumers has significantly shifted from traditional products to the development of eco-friendly alternatives. Green product development is becoming essential for the survival of manufacturing businesses in most markets. In addition, with growing environmental concern, companies are actively competing in green economic development. Therefore, this paper aims to estimate new green product development according to the dynamic capability theory. The current research is based on the paradigm of meta-positivism and utilizes a quantitative approach. Dynamic capability theory and structural equation modeling via M-plus software programs were used to analyze the statistical population consisting of CEOs and senior managers of 57 companies in Iranian dairy industry. The sample size was calculated using Cohen’s formula, and the questionnaire was provided to the sample members via email and social networks. The questionnaire’s reliability was confirmed using factor loadings, Cronbach’s alpha, and composite reliability. Also, its validity was evaluated using the AVE criterion. Researchers in this study were able to predict a high proportion of new green product development behavior using research variables. This shows that the exogenous variables used in the conceptual model were chosen correctly. The results underscore the negative impact of green technology turbulence and the positive effect of green product innovation, green entrepreneurial orientation, green transformational leadership, and green competitive advantage on new green product development. Additionally, the findings highlight the moderating effects of green dynamic capability in improving new green product development. The impact of exogenous research variables on new green product development has been investigated in previous studies. However, there is a lack of studies on the moderating role of green dynamic capability in this impact. This study aims to fill the empirical gap in the literature by demonstrating that business dynamic capability effectively guides green product innovation and supports a green entrepreneurship orientation, which improves the success of developing new green products. Furthermore, by utilizing various theories as basic concepts, this research provides valuable theoretical and practical contributions, concepts, and recommendations for managers of dairy industry companies. Finally, our sample is collected from companies active in dairy industry and is limited to Iran.

Semantic segmentation is a fundamental task in computer vision, requiring precise object delineation for applications such as autonomous driving and medical imaging. Traditional convolutional neural networks (CNNs) often struggle with capturing long-range dependencies and preserving fine spatial details. It is the study's goal to make segmentation more accurate by adding adaptive attention to the encoder and decoder stages of the U-Net-based architecture. The proposed network employs ResNet-50 as its backbone for efficient multi-level feature extraction. The encoder incorporates an Efficient Channel Attention Atrous Spatial Pyramid Pooling (ECA-ASPP) module to enhance its context representation. This module uses dilated convolutions and adaptive channel attention to improve the collection of features at different sizes. There is also a Point-wise Spatial Attention (PSA) module in the decoder that dynamically gathers global contextual information while keeping fine-grained spatial details. Extensive experiments on the Stanford Background Dataset demonstrate a consistent improvement across all segmentation categories. The best-performing model achieves a mean Intersection over Union (mIoU) of 78.65%, outperforming baseline approaches. Furthermore, evaluation on the Cityscapes dataset yields an mIoU of 80.46%, surpassing state-of-the-art methods such as DeepLabV3 and DANet. These results show that using adaptive attention during both the encoding and decoding steps works well, finding a good balance between accurate segmentation and fast computing. The proposed network demonstrates strong potential for real-world applications requiring precise segmentation.

This study develops a detailed numerical model for catalytic converters, incorporating a refined approach to reaction kinetics and mass transfer effects to improved prediction accuracy. Unlike previous models with simplified reaction mechanisms, this study integrates a multi-species reaction framework that better represents real-world catalytic behavior. The model is validated against experimental data, showing differences of 8.72%, 5.00%, and 12.6% for methane, CO, and NO conversion efficiencies, respectively, which are lower than those in other studies. The findings reveal that increasing volumetric flow rate reduces conversion efficiency and raises light-off temperature. For instance, when flow increases from 0.05 to 1 m³.s⁻¹ at 500 K, CO, methane, and NO efficiencies drop significantly, while their light-off temperatures rise by over 80 K. Conversely, increasing the converter length enhances efficiency and lowers light-off temperature, with over 40% improvement for CO and NO when length increases from 0.05 to 0.3 m at 550 K. Higher oxygen levels boost CO and methane efficiency but reduce NO efficiency. Increasing CO concentrations decreases CO and methane conversion but enhances NO reduction. These findings offer insights for optimizing catalytic converter design. The model serves as a valuable tool for automotive engineers developing efficient and eco-friendly emission control systems.

Grid-tied voltage source inverters, used to convert DC power generated by photovoltaic (PV) sources into AC power for injection into the grid, inherently generate voltage and current harmonics at the Point of Common Coupling (PCC). Although inductor-capacitor-inductor (LCL) filters effectively attenuate the harmonics generated by the inverter, they can also create resonance, potentially compromising the stability of grid-connected systems. Various methods, including active damping through filter capacitor current feedback, have been employed to mitigate these issues. Thorough feedforward control of grid voltage is considered an effective method for improving the quality of injected current in grid-connected inverters. In this paper, a novel control strategy for grid-connected solar array power conditioning systems is proposed, utilizing a weighted thorough feedforward scheme of grid voltage based on multiple resonant components. The proposed method significantly enhances the system's ability to suppress PCC voltage harmonics by incorporating a set of quasi-resonance sections into the feedforward path of the network voltage. With proper design of these quasi-resonance components, the phase delay created by digital control is resolved, PCC voltage harmonic attenuation is further enhanced, and the stable operation of the grid-tied solar array power conditioning system is improved under harmonic-polluted grid conditions.

The use of passive solar systems can be introduced as a solution and part of a general strategy in order to reduce building energy consumption and achieve zero energy buildings. In this research, the effect of using shading devices as a passive solar system, on cooling and heating loads is evaluated by Energy Plus software in four different Iranian cities; Tabriz, Tehran, Bandar Abbas, and Shiraz. Two main investigation parameters received their weighting results from Shannon's entropy and TOPSIS multi-criteria decision-making procedure. Research showed that using simulated shading devices creates positive effects on reducing annual energy consumption especially in hot climates due to high cooling demand. Therefore, the greatest effect of using shading devices has been recorded in Bandar Abbas city with a decrease of 23.17% due to its cooling demand, and the lowest effect in Tabriz city with a decrease of 9.17% due to its high heating demand, compared to the reference state. The 150 cm overhang demonstrates the best performance in terms of cooling saving in Tehran, Bandar Abbas, Shiraz and shows a 39.71%, 25.46% and 36.47% reduction, respectively. Shading devices also lead to an increase in heating where the screen shows the lowest increase with 0.76%, 0.91%, 2.66% and 1.48% in Tabriz, Tehran, Bandar Abbas and Shiraz. Finally, Shannon entropy weighting introduced cooling as the most important factor in the four-dimensional climate, and the TOPSIS options ranking also suggested an overhang of 150 cm for Tehran, Bandar Abbas, and Shiraz, and interior roller shade for Tabriz.