جستجوی مقالات مرتبط با کلیدواژه "مصرف سوخت" در نشریات گروه "محیط زیست"

Air pollution is recognized as one of the fundamental challenges in the field of environmental engineering. This study examines the impact of vehicle tires on air pollution and explores methods to reduce it. A significant portion of the energy generated by the vehicle engine is lost through tire rolling resistance. Consequently, reducing tire rolling resistance leads to decreased fuel consumption and, consequently, reduced air pollution. Modifying the formulation of tire tread compounds can be an effective approach to reducing tire rolling resistance. One proposed method for modifying the formulation is the addition of nanoparticles as fillers. In this research, the impact of adding varying amounts of nanosilica to the tire tread compound formulation, which is the main factor contributing to vehicular energy dissipation, has been investigated. The results indicate that the addition of nanosilica increases tire rolling resistance. Furthermore, the influence of tire thickness on its lifespan and rolling resistance has been examined, demonstrating an increase in rolling resistance over time. Additionally, necessary changes in the production process conditions and their impact on the mechanical properties and performance of the produced materials have also been investigated. Rheological analysis reveals that the addition of nanosilica leads to increased viscosity. Moreover, the examination of mechanical properties shows an increase in the modulus values of both 100% and 300% materials with the addition of nanosilica.

The number of diesel engines is increasing every year due to high yield and fuel economy and low greenhouse gas emission. Especially biodiesel and ethanol have been considered as major alternative fuels as they are derived from renewable sources. These fuels are well oxygenated and therefore have a great potential to reduce emissions. Material and

The effect of engine load and speed and different percentages of diesel-biodiesel fuel blends on the performance characteristics of a diesel engine was investigated. Experiments were designed by response surface method (RSM), and optimal levels for independent variables were obtained to minimize or maximize response levels.

According to the results, brake torque increased with increasing biodiesel level in fuel blends. Among independent variables, engine load and speed had the greatest impact on engine torque. The maximum torque was obtained for the fuel blend D36B64. Specific fuel consumption increased with increasing biodiesel level in fuel blends in comparison with the diesel fuel. The least specific fuel consumption was obtained for pure diesel fuel. Discussion and

According to the results, the highest torque was 315.55 Nm for fuel (D36.12B63.88) and the lowest torque was 44 Nm for pure diesel fuel (D100B0). According to fuel consumption results, the lowest fuel consumption occurs at 2323 rpm and for pure diesel fuel (D100B0). Also, the highest specific fuel consumption occurs at 67% engine load and 2800 revolutions per minute for pure biodiesel fuel (D0B100) at 304 g / kW. The results of multi-objective optimization indicated that the highest performance characteristics occurred at full load (100%) and engine speed of 1984 rpm for the fuel blend D22B78 (with a desirability of 91%).

Considering the high transportation costs of sugar market (produced by sugar beet), the logistic management of its supply chain is of particular importance, which can reduce costs as well as air pollutants, and help with locating facilities, on-time delivery of services and customer satisfaction. Up until now, few studies have been conducted on the optimization of the distribution network of agricultural products in the supply chain, taking into account the economic and environmental impacts. Therefore, the present study aimed to optimize the sugar beet’s distribution network from production areas to refineries in Iran’s sugar supply chain and determine its economic and environmental impacts. In this study, in addition to comparing transport costs in the current and optimal distribution situation, changes in fuel consumption per shift in sugar beet’s distribution, reduced emissions due to the reform of the transportation network and its economic benefits in the country were also evaluated.

The present study was carried out using data obtained from Iran’s statistics center in 2014 for 10 provinces producing sugar beet’s sugar, including Western Azerbaijan, Kermanshah, Khuzestan, Fars, Yasuj, Lorestan, Semnan, Qazvin, Khorasan Razavi, and northern Khorasan and 24 demand centers. This study used a linear programming model to consider the simple transport model to analyze the data using GAMS software.

The implementation results of optimal transportation plan showed that the implementation of the proposed program decreased the costs of about 4.5 billion USD, equivalent to 3.84%. Also, the implementation results of the optimal transportation plan considering the environmental impacts indicated two million and 177 thousand liters reduction of gasoline and 5.7 billion rials increase in environmental benefits.

It can be concluded that implementing an optimal transportation plan may reduce transportation costs as well as environmental pollution. Therefore, implementation of an optimal plan resulted in the reduction of transportation costs and consequently, on the final price of sugar. Based on results, it is suggested that, during transportation planning in the sugar supply chain, the proposed model in this study should be used for sugar beet transport

Iran has access to open seas and plenty of sea transit around it has urged presence of merchant ships in the region. Fuel consumption has always been a matter of concern for ships. In this study, it is attempted to develop computer models for several container ship cargo configurations and discuss an optimum configuration at a constant speed front wind. The paper presents simulation results using ANSYS CFX commercial software for a Post-Panamax 9000 TEU container ship. The ship is modelled in a 1:4 scale, then using unstructured mesh the wind filed around it is solved. Drag force, drag coefficient, pressure contour and wind streamline velocity in ten different loading conditions are compared with each other. Finally, the optimized container configuration for loading on deck of the vessel is introduced. Findings: Simulation results demonstrate the influence of container configuration on wind load distribution. Also the numerical results are verified versus wind tunnel test data. Finally, the influence of container configurations on fuel consumption and reduction of pollutant emissions was calculated. Discussion and Conclusion: It is proposed to minimize empty spaces between the cargo containers and avoid unbalanced cargo distribution over deck in order to reduce the wind drag force and consequently reduce the fuel consumption and pollutant emissions. Also, it is suggested to make cargo distribution on the forward and aftward deck areas more streamlined.

Recently much attention has been paid to the development of alternative fuels in order to meet the emission standards and to reduce the dependency on fossil fuel. Especially biodiesel and ethanol have been considered as major alternative fuels as they are derived from renewable sources. These fuels are well oxygenated and therefore have a great potential to reduce emissions. This study is aimed at investigating the effect of operating factors of engine load and speed as well as blended levels of biodiesel and ethanol in diesel fuel on the specific fuel consumption of a DI diesel engine OM 314. The experiments were designed using a statistical tool known as response surface methodology (RSM).
Findings: The results depicted that specific fuel consumption increased with increasing percentage of bioethanol and biodiesel and the minimum of the specific fuel consumption (156 g/kWh) was accured at full load and engine rotational speed of 2453 rpm for pure diesel (B0E0D100)
Discussion and the maximum of specific fuel consumption was obtained with amount of 413 g/kWh at 20% engine load and rotational speed of 2800 rpm and for a fuel blend containing 0.4 l biodiesel, 0.4 l ethanol and 1l diesel (B22E22D56)

Despite the abundant renewable energy sources, the Iranian energy sector relies almost entirely on fossil fuel energy resources. Power sector is dominant source of CO2emissions and responsible for about 35% of total CO2 emissions in the country. Additionally, long-term electricity demand of Iran is expected to grow quickly, which in turn requires extensive investment to meet the growing demand over the next decades. On the other hand, increasing domestic fossil fuel consumption had been a serious challenge due to high costs of oil and gas. Current study pays particular attention to the possible penetration rates of renewable electricity technologies and their implications for fossil fuel consumption and CO2 emissions. The analysis is performed by using an energy supply optimization model. Different scenarios are defined to evaluate the impact of fossil fuel prices and carbon tax on utilization of renewable resources. Model for Energy Supply Strategy Alternatives and their GeneralEnvironmental Impacts (MESSAGE) is applied in this study as a mathematical programming tool. MESSAGE is a multi-objective optimization model used for energy system planning, energy policy analysis, and scenario development over medium to long-term periods. MESSAGE was originally developed at International Institute for Applied Systems Analysis (IIASA) and the International Atomic Energy Agency (IAEA) added a user-interface to facilitate its application. In this methodology, the performance of a special technology is compared with its alternatives on a life cycle basis to identify how much of the available technologies should be expanded to meet the future energy demands. Reference energy system for Iranian power sector: Reference energy system represents the structure of power system depicting energy chains, electricity generation technologies, resources required to meet electricity demand, and energy levels. At the resource level, natural gas, petroleum products, hydrogen, nuclear fuel, thermal coal and different renewable energy resources including hydropower, wind, solar, geothermal, and biomass can be mentioned. Conversion level consists of various conventional and advanced thermal power plants and different renewable electricity technologies for centralized power generation. In addition, some distributed generation (DG) technologies are also considered for on-site generation of electricity. Imports and exports of electricity are modeled at the transmission level. Data and Scenarios:The required data and the main assumptions for the Iranian power sector are presented in this section. Different scenarios are then defined to determine the appropriate technology options and to quantify the implications of renewables’ contribution to fuel consumption and CO2 emissions. The main assumptions of the different scenarios are as follows: Reference Scenario: This scenario refers to business-as-usual situation describing the development of power sector with constant fuel price level over the projected period. High fuel price scenario: we assume a rising trend for fossil fuel prices which are consistent with those developed by U.S. Energy Information Administration. Carbon tax scenario: Fuel price is assumed to be the same as high fuel price scenario and a rising trend for carbon tax is used in this scenario from 8 $/tonne carbon at the base year to 50 $/tonne at the end of the study period. Natural gas combined cycle power plant holds the largest contribution almost in all conditions over the period of study, as it may reduce the investment cost of electricity supply system and benefit from the higher energy efficiency. Hydropower is one of the leading power generation technologies of the future. The total amount of hydropower generation will increase continuously until the limit of its exploitation is reached. Operation of gas turbines will also be attractive due to the technical possibilities of plants in terms of adjusting power level to meet the peak load demand. However, in a longer term perspective, the maximum potential of generation from pumped-storage hydropower is fully exploited and the share of gas turbine may be reduced. A gradual change is seen in the power system structure over a short to medium-term period in the high fuel price scenario. Combined cycle power plants increases at a descending rate. In the long-term, the generation is characterized with the application of wind turbines and solar photovoltaic systems. Carbon price in carbon tax scenario accelerate the employment of renewable energies. The contribution of renewables to electricity generation in 2045 will reach to 10%, 20%, and 35% of total generation in the reference, high fuel price, and carbon tax scenarios, respectively.When there is no carbon tax, advanced coal power plants will be competitive, due to the assumed coal-to-gas fuel price ratio and their costs applied. The fuel consumption is slowed down in the alternative scenarios by deployment of renewable energies (24-42% reduction compared to the reference case in 2045). In the reference scenario, total emission reaches 217 million tonnes in 2045. In the alternative scenarios, between 38 to 93 million tonnes of carbon dioxide per year could be avoided compared with the reference case by 2045. This is as a result of renewable energy deployment. Total amount of CO2 emissions and carbon intensity are shown in Figure 1. This paper mainly focuses on the future development of electricity supply system in Iran. It also explores the prospects for development of renewable electricity technologies and their implications for fossil fuel consumption and CO2 emissions over the next three decades. Different scenarios are investigated to evaluate how renewable energy utilization can be affected by technology development, fossil fuel prices, and carbon tax. The assessment of new energy technologies are provided by using MESSAGE, a cost minimizing mixed-integer programming model. Results of the model reveal that renewable energy technologies will contribute to supply 10-35% of total electricity demand by 2045. The average CO2 emissions per unit of electricity generated can be reduced by 30-70%.