Considering its biological situation, each country has a specific carrying capacities to absorb pollutants. Increased production, population, and direct and indirect fossil energy consumption have increased emissions such as carbon dioxide, resulting in destructive effects on the environment such as imbalanced greenhouse gases, global warming, climate changes, and endangering of humans’ and other creatures’ lives. The extent and dimension of the mentioned effects can vary depending on the consumption modus and technique practiced by households and industries. Ecological carbon footprint is a criterion to measure the humans’ impact on carbon emissions. In an attempt to measure the carbon footprint of households, this research seeks to answer the following questions: How much is the carbon footprint of urban and rural household deciles? What deciles create higher carbon footprints? What is the share of households in the country’s total carbon footprint? How big is the carbon footprint per capita in each decile? For this purpose, the Social Accounting Matrix of the year 2011 is used. The empirical results indicate that in 2011, the total net direct and indirect carbon footprint in Iran was 517 million tons, in which the household consumption accounts for 64% and the remaining 36% belongs to the government’s final consumption, export and others. Moreover, carbon footprint of urban households is more than the rural ones and it is elevated in higher income deciles. Carbon footprint of the tenth urban decile is 11 times greater than the first one. For rural deciles, this ratio is 9. Furthermore, carbon footprint of the tenth urban decile is 4 times greater than that of the tenth rural one. An Iranian’s household carbon footprint per capita was found to be about 4429 kg in 2012. Carbon foot print per capita in the first urban decile, the tenth urban decile, first rural decile, and the tenth rural decile is 1,124, 17,134, 965 and 9,803 kg, respectively. The results indicate that people with higher incomes have a greater carbon footprint.

In recent decades, releasing more carbon emissions resulting from energy consumption, more damaging effects on the environment is set up.Some of the Industries and manufacturing sectors share some sectors more than others, and from one country to another countries may vary. Some countries have started the carbon war by transfer of polluting industries to other countries. However, each country according to its biological status has a capacity to absorb pollutants. If carbon footprint is higher than the absorb capacity potential harmful effects on the environment is entered. In this paper, economic sectors carbon footprint trade balance by using Social Accounting Matrix 1390 is studied. Results indicate that in 1390, the negative trade balance of the country's carbon footprint is 4.5 tonnes. That is only 8-thousandth of the total economic sectors's carbon footprint. Sector of oil, natural gas distribution, manufacture of chemicals and chemical products, transport have a highest positive carbon footprint trade balance and food products, manufacture of motor vehicles, trailers and semi-trailers, manufacture of basic metals have the most negative The carbon trade balance.

The present research introduces a pseudo comprehensive carbon footprint model for simple cycle and combined cycle power plants based on Life Cycle Assessment frameworks for sustainable planning in Iran. For this purpose, parameters which their effects are considered distinguishable have been investigated. The mentioned parameters include: plant type, fuel type, fuel transmission type, own consumption of the plant, degradation, site ambient condition, transmission and distribution losses. Investigating power plant operational phase and transmission and distribution effect on carbon footprint assessment of power plant is the specific feature of the proposed model. Afterward, a sensitivity analysis is performed under different cases covering all the possible choices for investigated parameters. The results show that carbon footprint of fossil fuel (simple and combined cycle) varies remarkably due to the parameters affecting the carbon footprint. Results of sensitivity analyses show that by controlling the effective parameters carbon footprint of power plants can be reduced by 142%.

In this study a pseudo comprehensive carbon footprint model for fossil fuel power plants is presented. Parameters which their effects are considered in this study include: plant type, fuel type, fuel transmission type, internal consumption of the plant, degradation, site ambient condition, transmission and distribution losses. Investigating internal consumption, degradation and site ambient condition effect on carbon footprint assessment of fossil fuel power plant is the specific feature of the proposed model. To evaluate the model, a sensitivity analysis is performed under different scenarios covering all possible choices for investigated parameters. The results show that carbon footprint of fossil fuel electrical energy that is produced, transmitted and distributed, varies from 321 g CO2 eq/kWh to 980 g CO2 equivalent /kWh. Carbon footprint of combined cycle with natural gas as main fuel is the minimum carbon footprint. Other factors can also cause indicative variation. Fuel type causes a variation of 28%. Ambient condition may change the result up to 13%. Transmission makes the carbon footprint larger by 4%. Internal consumption and degradation influence the result by 2 and 2.5%, respectively. Therefore, to minimize the carbon footprint of fossil fuel electricity, it is recommended to construct natural gas ignited combined cycles in low lands where the temperature is low and relative humidity is high. And the internal consumption is as least as possible and the maintenance and overhaul is as regular as possible.

The increasing emission of greenhouse gases as the most crucial factor in global warming has made this a global concern in recent years. One concept proposed to better understand the amount of greenhouse gas emissions is the carbon footprint. Carbon footprint is the amount of greenhouse gases produced by a particular product or activity in its simplest definition. Since the power generation industry is one of the most highly emitting sectors, the study of carbon footprint has also become significant. This is primarily because fossil fuels are still the number one energy source for electricity generation, and even coal-fired power plants, which have the highest greenhouse gas emissions, will be the number one source in the coming years. They will still have a high share. Therefore, in the present study, while examining the concept of carbon footprint and its calculation method in the electricity industry, in a case study of South Khorasan province, the carbon footprint from steam and combined cycle gas and diesel power plants has been compared with Tabas coal-fired power plant. The obtained results show that the site's elevation according to the air density can have up to 10% impact the carbon footprint of the combined cycle power plant, and sites with low height should be chosen as much as possible. Also, the carbon footprint of the coal-burning power plant with a value of 968 grams per kilowatt hour is far higher than other fossil power plants with a value of 579 grams per kilowatt hour.

The construction industry, the leading cause of global greenhouse gas emissions, is responsible for at least 37 percent of global emissions. In Iran, greenhouse emissions in the construction sector between 1990 and 2020 have increased from 0.73 to 1.44 tons of carbon dioxide equivalent per person per year. The purpose of the current study is to investigate the direct and indirect carbon footprints for one square meter of the residential building built-area. The system boundary is “gate to gate,” and its functional unit is “one square meter of the residential building built-area.” Data selection was carried out using the checklist and literature review methods. The carbon footprint assessment was conducted using the IPCC 2013 model and the ReCiPe method. Concrete is the most substantial contributor to carbon footprint among all building materials. The results show that the total, direct, and indirect carbon footprint for one square meter of the residential building built-area is 445, 436, and 9 kgCO2e/m2, respectively. The building’s “excavation, foundation, and framing” phase mainly contribute to the indirect carbon footprint among building construction phases. The carbon footprint for each square meter of the residential building construction is related to different factors, such as total building area, type of buildings, material transportation distance, and type of building materials used.

The main purpose of this research is to investigate and compare the effect of ecological and carbon footprints on multidimensional poverty in Iran's economy. In this study, three models have been specified and estimated using the available data of 2018-2018 and the ARDL approach. In all three models, the dependent variable of multidimensional poverty is defined as a combination index of life expectancy index and human development index, so that in the first model, the effect of the ecological footprint, in the second model, the effect of the carbon footprint, in the third model, the effect of both and other factors affecting multidimensional poverty have been included. According to the estimation results of the first model and the second model in the short and long term, ecological and carbon footprints have a negative and significant effect on poverty. The results of the estimation of the third model in the short term show that the ecological footprint has a positive effect and the carbon footprint has a negative and significant effect on poverty. On the other hand, the long-term estimation results of the third model show that the ecological footprint has a positive and significant effect on poverty, while the carbon footprint has a negative effect on the multidimensional poverty index. Other findings indicate that in the first and second models, in the short and long term, the index of fiscal policy and inflation has a positive effect and the index of monetary policy has a negative and significant effect on poverty. The results of the estimation of the third model in the short term show that the fiscal policy index has a negative effect and its lag has a positive and significant effect on poverty. The effect of this variable in the long term is negative and of course not significant. Also, in the short and long term, monetary policy has a negative effect and inflation in the long term has a positive and significant effect on multidimensional poverty in Iran's economy.

Building and their related activities are important sources of the environmental pollutants, regarding the fact that during the process of building and materials manufacturing a considerable amount of carbon is produced and disposed to the atmosphere. Virtual carbon footprint related to this industry is not confined to the process of building and manufacturing, it actually includes the operation time and dismantling too. In this study, the per capita energy consumption and the carbon footprint of three buildings in Mazandaran province during one year of operation have been estimated and compared with each other. So, a house, two-story, and five-story apartments with the same structure in Babolsar have been modeled in Design-Builder, and energy consumption and carbon footprint during one year of operation have been assessed comparatively. The results of modeling indicate that along the one-year operation of the house, two-story and five-story apartments, 8490, 4878, and 4881kg carbon (kg per occupant) have been produced and released into the atmosphere. Furthermore, the per capita, energy consumption of the house has been estimated more than those of apartments significantly, and this fact illustrates a vast difference between the detrimental effects of houses and those of apartments during operation time on the environment.

This study addresses the substantial contribution of mobile sources in commuting to greenhouse gas (GHG) emissions in megacities and underscores strategies for carbon footprint emission reduction. Field interviews and questionnaires facilitate data collection, enabling the classification of the studied vehicle fleet based on various parameters. The scenarios aim to minimize GHGs from the commute, utilizing the International Vehicle Emission (IVE) model to establish a primary carbon footprint emission inventory for commuting in Karaj. The base scenario reveals that commuting in Karaj produces 1579423 grams of CO2e, with CO2, N2O, and CH4 emissions at 1389039 grams, 43.74 grams, and 6385.38 grams, respectively. Three carbon footprint reduction scenarios, involving removing diesel vehicles, adopting natural gas-fueled vehicles, and replacing Euro 4 and 5 with older vehicles, demonstrate that the removal of diesel vehicles (S1) and adopting natural gas-fueled vehicles, and replacing Euro 4 and 5 with older vehicles (S3) are the most effective strategies, achieving a 99% efficiency rate in reducing CO2e. This study highlights the substantial impact of curbing carbon emissions from GHGs. S1 and S3 show significant reductions in carbon footprint emissions, emphasizing the crucial role of strategic planning and greenhouse gas minimization in controlling emissions from commuting. These findings underscore the critical importance of reducing carbon footprints and commuting to effectively mitigate GHGs in congested urban areas.

This study explored the impact of label location on consumers' visual attention to environmentally friendly products. Specifically, it investigated the effect of the distance of the carbon footprint label from the center of the packaging on consumers' visual attention. The research employed an experimental laboratory approach, utilizing eye-tracking technology to gather data on participants' visual attention. The study included 120 students and graduates from universities in Tehran Province. The findings revealed that the location of the carbon footprint label significantly influenced consumers' visual attention. Regression analysis demonstrated a direct relationship between the distance of the label from the package center and the time to first stabilization, while an inverse relationship was observed with the total duration of stabilization, fixation number, visit duration, and number of visits. These results highlighted the importance of strategically placing labels, such as carbon footprint labels, to enhance their effectiveness in capturing consumers' visual attention and influencing purchasing decisions. The findings have implications for product and packaging designers, as well as organizations focused on environmental and consumer health.