Search

Increasing the price of fossil fuels, unreliability of fossil fuels for a secure supply of demand in future and their relevant environmental concerns provide an attitude toward substituting renewable energies with fossil fuels for reaching sustainable development in societies. Biofuels as a type of renewable energies can be easily transferred between supply chain's centers and do not have limitation for transportation after their production. Among various types of biofuels, biodiesel, which can be mainly produced from the non-edible feedstocks, such as Jatropha Curcas L. (JCL), is preferred to other biofuels because biodiesel production from JCL which can be cultivated in marginal lands, improves three pillars of sustainability. Since biofuel supply chain's costs can mainly be affected by its feedstock location optimization, this paper used a common weight data envelopment analysis (CWDEA) method for location optimization of feedstock cultivation for a biodiesel supply chain by considering a comprehensive set of sustainability criteria for investigating locations. A case study of Iran is provided for assessing the model's application, and its results in ranking potential locations for JCL cultivation are validated by a numerical taxonomy (NT) approach. In fact, this paper not only specifies the optimum locations for the feedstock cultivation of a biofuel supply chain regarding to sustainability criteria, but also discuss the balanced socioeconomic development and environmental benefits which can be attained by JCL cultivation in marginal and mostly underdeveloped lands. Provided results imply that vast area of Iran's marginal lands has suitable climate for JCL cultivation and policy makers can address all aspect of sustainability simultaneously by investment on those specified lands as well as supplying countries' demand for biodiesel which will be produced from this feedstock. [ABSTRACT FROM AUTHOR]

In this study, an innovative woody biomass‐fueled hybrid tetrageneration system composed of a single‐effect lithium bromide‐water absorption refrigeration system, a reverse osmosis desalination system, two organic Rankine cycle for the production of cooling, heating, power, and freshwater in two distinct configurations (configurations A and B), compared and discussed using energy, exergy, economic, and exergoeconomic analyses. The poplar sawdust used as a local woody biomass fuel was a by‐product of the Iran Wood and Paper Industries Company, located in northern Iran. The results revealed that the highest heating production and lowest exergy destruction were related to configuration B. The overall cost of configuration A was higher than that of configuration B. A detailed sensitivity analysis was also developed to study the effect of various factors on the thermodynamic and economic performance of the proposed configurations. By increasing the turbine inlet temperature of ORC1 from 625 to 692 K, the total sum unit costs of product of the system in configurations A and B decreased by 20 and 23 $ GJ−1, respectively (about 21%). [ABSTRACT FROM AUTHOR]

Environmental problems, combined with a finite supply of fossil fuels, have made the use of renewable energy sources necessary. Biomass is a renewable source of energy that has played a very important role in energy production in recent years. Because there are a number of technologies that can be used to convert biomass into energy, it is important to select the best option. The fact that multiple options are available that need to be evaluated based on a set of decision-making criteria makes this a multicriteria decision-making problem. This paper takes the first step in proposing an evaluation framework and identifying the importance of the relevant decision-making criteria in biofuel production technology selection. To determine the importance of the selection criteria, experts were asked to respond to an online questionnaire based on the best–worst method. The results indicate that air pollution, land use change, and human expertise are the three most important criteria for selecting the best biofuel production technology in our case country, Iran. [ABSTRACT FROM AUTHOR]

Innovative and more sustainable methods of supplying energy needs in the world have led to a change in the dependency model for fossil fuels, including more integrated planning and adoption of new and motivating models regarding the use of renewable energy. Today, with the reduction of fossil fuel consumption in the world, the use of renewable energy has gained an important role in the global energy mix, but according to studies, the share of renewable energy in Iran’s energy mix is very small. Therefore, the present paper attempts to present all potentialities for obtaining clean energy in Iran by assessing the current state of renewable energies. The fact that, in the present time, the real value of energy carriers is not appreciated properly in Iran, on the one hand, and the lack of willingness to invest in these energies in the private sector, which may have been less protected, on the other hand, has caused the consumption level of fossil fuels to remain unchanged, which may have some disadvantages, such as environmental damage, in addition to their utilization. The authors of the paper are of the opinion that, on the one hand, by finding solutions for bank investment problems, easing restrictive laws, providing bank with guarantees by investors, as well as modifying parts of the guaranteed electricity purchase contract for accepting foreign banks to provide loans and obtain financing, and on the other hand, by facilitating the process of obtaining land permits and connecting to these power plants, Iran is not far from reaching a reasonable rank in the world. [ABSTRACT FROM AUTHOR]

Nowadays, the use of renewable energies, especially wind, solar, and biomass, is essential as an effective solution to address global environmental and economic challenges. Therefore, the current study examines the energyeconomic-environmental analysis of off-grid electricity generation systems using solar panels, wind turbines, and biomass generators in various weather conditions in Iran. Simulations over 25 years were conducted using HOMER v2.81 software, aiming to determine the potential of each region and find the lowest cost of electricity production per kWh. In the end, to identify the most suitable location, the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method was employed to rank different stations based on simulation output parameters and some other influential factors. Considering the evaluation of various parameters, the stations in Yazd, Marand, and Dezful achieved the best results, while the stations in Ramsar, Shahrekord, and Gonbad presented the least favorable outcomes. In Yazd, the wind turbine is an economic priority, and a 100 kW wind turbine is utilized in the optimal system. In Yazd, where the simultaneous use of renewable energies is most prominent, the lowest pollutant production occurred with a quantity of 1174 kg/year. Annual energy losses are highest in Jask station and lowest in Yazd. [ABSTRACT FROM AUTHOR]

Current study designed to assess the population characteristics of white threadsfish in northern Oman Sea (Iran) by sampling sea cucumbers at nine sites from March 2018 to March 2019. The sites included Aliabady, Ramin, Beries, Gurdium, Kachoo, Beries plane, Tis, Pasabandar and Pozm. 125 female and 121 male specimens were measured for total length and total weight, with mean ± standard deviation of 28 ± 4 (21 - 33) cm for males and 25 ± 6 (14 - 39) cm for females, and 421 ± 128 (191 - 770) g and 365 ± 231 (116 - 776) g, individually. Overall length and weight were not suggestively changed between the sexes (p > 0.05). Both sexes showed an allometric growth pattern between length and weight. The average estimated number of sea cucumber post Monsoon and per Monsoon was 1.85 million (1.22-2.48) and 1.73 million (1.97-1.49) in the eastern area of Sistan and Baluchestan province, respectively. The total biomass ranged from 601-372 tons, and the harvestable biomass in the two seasons was between 53-90 tons. Contrast worth of phosphate showed substantial differences among diverse stations (P<0.05), while further parameters did not show substantial differences between stations (P>0.05). Multi-layer artificial neural network analysis indicated that two parameters, phosphate and nitrate, had the greatest impact on sea cucumber biomass. To implement a maximum sustainable yield method for this fishery in Iran. [ABSTRACT FROM AUTHOR]

Field experiments were conducted in the cropping years 2012 and 2013 with four irrigation treatments, I1, I2, I3, and I4, respectively, corresponding to full irrigation, 20, 35, and 50% less than the crop water requirement in a semi-arid region of Iran. Data were used for calibration (2012) and validation (2013) of biomass (B), grain yield (GY), soil water content (SWC), canopy cover (CC), and evapotranspiration (ET) of canola by the AquaCrop model. Model coefficients were calibrated for I1 treatment in 2012, and the calibrated parameters were used for other treatments in both years. Based on the results, the NRMSE value for SWC ranged from 10 to 20%. Simulated and measured SWC for the four water treatments showed that AquaCrop has good accuracy. Overall, the results of the model in simulating SWC for both years were satisfactory. AquaCrop provided overestimation in the calibration phase of ET and underestimation in the ET validation phase. The results also showed that AquaCrop is overestimated in the simulation and prediction of CC and is less satisfactory under water stress. The model evaluation showed that AquaCrop can simulate B and GY with high accuracy. In general, AquaCrop was identified as a good tool for studying irrigation management, crop B and GY, CC, SWC, and other factors affecting the canola growth in the studied fields and climate. [ABSTRACT FROM AUTHOR]

Biogas is the gas produced by the anaerobic degradation of organic matter. In addition to the usual uses in burning, it has widespread applications as a raw material in some industries. The biomass of organic matter decomposition is a good fertilizer for agriculture. Unfortunately, despite such a large potential for reasons such as the cheapness of energy in Iran, the use of this benefical capacity has not been addressed so far. This paper investigates the potential of biogas production from poultry manure sources in Iran and demonstrates the examples of biogas plants in Iran. Also, the information about the capacity of biogas production has been investigated and reported in different provinces in Iran. The results consist of economic analysis as the cost of biogas production, and the environmental analysis as the environmental impact of the biogas production and carbon footprint. Kermanshah, Chaharmahalbakhtiari, Golestan, Bushehr and North Khorasan provinces have the highest capacity for biogas production from poultry manure. The highest cost savings by using the biogas are in Khorasan Razavi and Isfahan provinces and the lowest levels have been found in Ardebil and North Khorasan provinces. • Biogas production potential from poultry's manure resource in Iran is investigated. • Energy, Economics, Exergy, and environmental impacts analyses are performed. • Footprint analysis is performed for monitoring impacts on sustainability. • Share of poultry's manure in natural gas demand of each province is predicted. • Good results related to energy saving, costs, environmental issues are achieved. [ABSTRACT FROM AUTHOR]

Increasing environmental awareness accompanied by the recent fluctuations in the fossil fuels underline the need to focus more on the management of energy mix and turn the attention towards renewable energies (REs). Diffusion and commercialization of renewable energy technologies are of paramount importance, particularly for developing countries. However, there are serious challenges and barriers that can be discussed in different aspects. This paper presents an applied and novel framework to tackle the challenges of diffusing and commercializing biomass energy technologies (BET) in developing countries. As a good example, our study focuses on the commercialization of the BETs in Iran. For this purpose, we provide an overview of the importance of commercialization of BETs. Then, by analysis of the literature and best cases, we identify crucial elements for commercialization of the BETs. Conducted surveys and theme analysis have resulted in a framework with 8 major dimensions and a total of 73 diverse components. The dimensions are technical and infrastructural; R & D and technology transfer; investment; social, cultural and behavioral; promotion and distribution; marketing and market building; macroeconomics; and support policy. Findings suggest that 'investment' and 'technical and infrastructural' dimensions are the two major pillars of the framework for commercialization of the BETs for developing countries. [ABSTRACT FROM AUTHOR]

This experiment was conducted to study the effect of pluramin and iron and zinc nanofertilizers on rainfed chickpea in autumn sowing at farmer conditions. The field located next to synoptic weathering station-Varmahang in Kamyaran-Iran during 2015-2016 growing season. The experiment layout was split plots in a randomized complete block design with three replications. The main factor were three levels of pluramin amino acid application (0, 150 g/ha and 250 g/ha) and subplot were four levels of nano fertilizers application (control: distilled water, nano-iron, nano-zinc, and nanoiron + zinc). The results showed that characters as: number of secondary branches, number of pods, number of seeds per pod, 100 seed weight, grain yield, biomass, protein percent and protein yield were significantly affected by the application of pluramin. An application of pluramin significantly increased all traits with exception of protein percent. In this experiment, the application of micronutrients nano-fertilizers also showed significant differences on the number of primary and secondary branches, number of pods, 100 seed weight, grain yield, biomass and protein yield, as this characters were enhanced by nano-fertilizer. Finally, mutual effect of pluramin and nanofertilizers indicated that the most pod numbers, grain yield and biomass were achieved by 250 g pluramin and iron+zinc nano-fertilizers. [ABSTRACT FROM AUTHOR]

Abstract: Recent changes in sea level of the Caspian Sea and ecological impacts caused by the invasive ctenophore (Mnemiopsis leidyi) have altered the ecosystem. A consequence is the changes in the absolute and relative abundance of the commercially important anchovy kilka (Clupeonella engrauliformis) in Iranian waters. To adjust to this change more rigorous management of this fishery is required. This paper examines the maximum sustainable yield (MSY) and fishing intensity at MSY. The paper presents estimates of f MSY, yield-per-recruit and spawning biomass-per-recruit under various harvest strategies of F max, F 0.1 and F 40%. We propose a method for estimating acceptable biological catch (ABC) that accounts for large differences in the quality and quantity of information and available data. The MSY and f MSY were estimated 44,652mt (metric tons) and 18,609 vessel×nights (a unit of effort). The ABC was estimated at 2190mt in 2004. In 2005, however, the catch of anchovy kilka was about 4300, over twice the estimated ABC. In 2008 (from January to October) the catch declined to 220mt. The analyses indicate that overfishing, especially between 2005 and 2008, is the main reason of the collapse of anchovy kilka in the Caspian Sea. [Copyright &y& Elsevier]

In face of climate change and global scale biodiversity loss, assessing the relationship between biodiversity and forest ecosystem functioning is essential, but poorly investigated in temperate forests of Iran. We examined plant diversity aboveground biomass relationships in unmanaged, and forests managed with a single-stem selection system in the Hyrcanian forests ecoregion in Northern Iran. Also, the effect of single-stem selection system on soil nutrient and plant species diversity of tree layer was investigated. Linear models were used to analyze the effect of management and soil characteristics on aboveground biomass and tree layer attributes. Moreover, the relationships between aboveground biomass and plant species diversity metrics and soil characteristics were investigated using simple linear and multiple linear regression analysis by using regression analysis. We found that tree layer species richness and Shannon diversity were significantly higher in managed forests compared to unmanaged forests. While simple regression analysis revealed no effect of tree layer diversity and soil characteristics on aboveground biomass, multiple regression analysis showed that the main positive driver of aboveground biomass was soil nitrogen content (or its equivalent soil organic carbon). These findings indicate that from a biodiversity point of view, the single-stem selection system can be considered a sustainable forest management approach in Hyrcanian forests because it has positive effects on tree layer diversity. This is probably driven by increased habitat heterogeneity and light availability at forest floor through cuttings, while keeping cutting intensity at a level that is too low to significantly affect tree biomass. While the relationship between soil nitrogen and biomass was positive, we found no relationship between species diversity and biomass. Finally, assessment of relationship between biomass and plant species diversity and other underlying factors such as soil nutrients can be considered an important tool to conserve and manage ecosystem services. [ABSTRACT FROM AUTHOR]

Unmanned aerial vehicle (UAV)-based remote sensing has been widely considered recently in field scale crop yield estimation. In this research, the capability of 13 spectral indices in the form of 5 groups was studied under different irrigation water and N fertilizer managements in terms of corn biomass monitoring and estimation. Farm experiments were conducted at Urmia University, Iran. The research was done using a randomized complete block design at three levels of 60, 80, and 100% of irrigation water and nitrogen requirements during four replications. The aerial imagery operations were performed using a fixed-wing UAV equipped with a Sequoia sensor during three plant growth stages including stem elongation, flowering, and silking. The effect of different irrigation water and nitrogen levels on vegetation indices and crop biomass was examined using variance decomposition analysis. Then, the correlation of the vegetation indices with corn biomass was evaluated by fitting linear regression models. Based on the obtained results, the indices based on near infrared (NIR) and red-edge spectral bands showed a better performance. Thus, the MERIS terrestrial chlorophyll index (MTCI) indicated the highest accuracy at estimating corn biomass during the growing season with the R2 and RMSE values of 0.92 and 8.27 ton/ha, respectively. Finally, some Bayesian model averaging (BMA) models were proposed to estimate corn biomass based on the selected indices and different spectral bands. Results of the BMA models revealed that the accuracy of biomass estimation models could be improved using the capabilities and advantages of different vegetation indices. [ABSTRACT FROM AUTHOR]

Iran is located in a dry climate zone, and climate change has substantially reduced its precipitation and water resources. Reusing wastewaters from urban communities can meet some requirements for irrigation and fertilization of tree plantations in arid environments, leading to sustainable wastewater recycling, enhanced biomass production, and reduced land degradation. The objective of this study was to test the growth, biomass, nutrition, and heavy-metal accumulation of poplars [Populus nigra L. "62/154," P. alba L. "20/45," P. euramericana (Dode) Guinier "92/40"], and willow (Salix excelsa S.G. Gmel) in a pot experiment at four and eight months after planting when grown in soils irrigated with tap water (SITW) and wastewater (SIWW). After four months, SIWW treatment had no significant effect on growth, biomass, nor absorption of macronutrients. After eight months, SIWW treatment of poplars and willow significantly (p = 0.000) increased: (1) height, (2) leaf area, (3) root, stem, leaf, and total biomass, and (5) phytoextraction and phytoaccumulation of macro-/micro-nutrients and heavy metals in tree tissues, over trees receiving the SITW treatment. There were significant differences in growth, biomass, and accumulation of micronutrients and heavy metals in poplar versus willow tissues, with the highest biomass production and tissue-specific content of heavy metals in P. nigra trees, and the greatest total concentrations of heavy metals in P. alba and S. excelsa trees. In contrast, uptake of Fe, Cu, Ni, Cr and Pb were similar between poplar and willow, and phytoaccumulation of these elements was primarily in the roots. Leaf concentrations were highest for Zn and Mn. While P. nigra outperformed all other species overall, tolerance index (TI; defined as the tolerance to the heavy metals as calculated by the ratio of the biomass of SIWW trees relative to SITW trees) values exceeding 100% for all one-year-old poplar and willow trees demonstrated that they can be considered for planting in soil affected by urban wastewaters with similar contaminant profiles as in the current study. Since the species would differ in their growth, biomass, and phytoremediation responses to the nutrient and heavy metal concentrations of the wastewater over time, this research is important for the development of silvicultural prescriptions of these fast-growing trees that support effective wastewater reuse strategies throughout heterogeneous landscapes and across variable human community resources and needs. [ABSTRACT FROM AUTHOR]

Biomass as one of the renewable-energy sources is both sustainable and eco- friendly. Considering the approximately 30% of wastes for agricultural products in Iran as well as the importance of processing industry in reducing wastes, biomass such as pistachio is extremely noteworthy. According to the published statistics, the area under cultivation of pistachio in Iran is currently more than 300,000 ha. Kerman Province with an area of 200,000 ha provides 67% of total Iranian pistachio so that it is the most important area of pistachio cultivation around the world. On average, there are approximately 520,400 tons of pistachio wastes per year in Iran, which is mostly related to peeling of product. Studies indicate that the fermentation and pyrolysis processes of pistachio waste produce valuable fuel. In addition, the biological digestion process can be performed on freshly harvested pistachio wastes. This paper shows that there is a considerable potential for the use of agricultural residues, especially pistachio as fuel in Iran. It was found that the production of biogas from pistachio's soft shell, and pyrolysis of pistachio's hard shell are the most effective ways to dispose of wastes, fuel production, and optimum use of them. It can produce about 256,410, 121,255, and 123,898 tons of bio-oil, char, and gas fuel from pistachio wastes by pyrolysis, respectively. Furthermore, the amount of 103.5 million cubic meters of biogas can be achieved using anaerobic fermentation. The potential of 47.6 million liters ethanol production from total pistachio waste can be predicted. The use of pistachio wastes in addition to economic benefits for investors, will have positive environmental effects. [ABSTRACT FROM AUTHOR]

AquaCrop is one of the dynamic and user-friendly models for simulating different conditions governing plant growth in the field. But this model requires many input parameters such as plant information, soil, climate, groundwater, and management factors. In this research, to solve this problem and develop a model with fewer input data, artificial neural network (ANN), support vector regression (SVR), and combined support vector regression with firefly algorithm (SVR-FFA) were used. For this purpose, 440 scenarios were created in 2 farms located in Iran, and the values of yield and biomass obtained by the AquaCrop model were compared with intelligent models. Also, consumable seed and irrigation were considered as inputs of intelligent models. The 99WestW2 farm in Miandoab had a seed yield of 6.588 t/ha, and the WestW10 farm in Mahabad had a seed yield of 5.05 t/ha. The results of this research showed that for both 99WestW2 and WestW10 farms, the SVR-FFA3 model was able to have the lowest amount of error so that for the amount of grain yield, the error values ​​for the farms were 0.033 and 0.069 t/ha, respectively. The error value of biomass was obtained for farms as 0.057 and 0.066 t/ha respectively. After SVR-FFA model, SVR and ANN models also showed good performance due to proper accuracy and saving time. Finally, SVR-FFA, SVR, and ANN models were able to predict yield and biomass values in the shortest time and with the highest accuracy with only two inputs. [ABSTRACT FROM AUTHOR]

Improvement of grain yield is the ultimate goal for wheat breeding under water-limited environments. In the present study, a high-density linkage map was developed by using genotyping-by-sequencing (GBS) of a recombinant inbred line (RIL) population derived from the cross between Iranian landrace #49 and cultivar Yecora Rojo. The population was evaluated in three locations in Iran during two years under irrigated and water deficit conditions for the agronomic traits grain yield (GY), plant height (PH), spike number per square meter (SM), 1000 kernel weight (TKW), grain number per spike (GNS), spike length (SL), biomass (BIO) and harvest index (HI). A linkage map was constructed using 5831 SNPs assigned to 21 chromosomes, spanning 3642.14 cM of the hexaploid wheat genome with an average marker density of 0.62 (markers/cM). In total, 85 QTLs were identified on 19 chromosomes (all except 5D and 6D) explaining 6.06–19.25% of the traits phenotypic variance. We could identify 20 novel QTLs explaining 8.87–19.18% of phenotypic variance on chromosomes 1A, 1B, 1D, 2B, 3A, 3B, 6A, 6B and 7A. For 35 out of 85 mapped QTLs functionally annotated genes were identified which could be related to a potential role in drought stress. [ABSTRACT FROM AUTHOR]

Economic complexity, biomass energy consumption, and information communication technology (ICT) have diverse impacts on energy consumption and carbon dioxide (CO2) emissions. Nevertheless, analysis of these variable effects is not addressed in the previous literature; the antiqueness of this article is stuffing this gap. This study assessed the relationship between gross domestic product (GDP) per capita, biomass consumption, economic complexity index (ECI), ICT, and CO2 emissions in Iran in 1994–2018. The autoregressive distributed lag (ARDL) model and the quantile regression (QR) econometric technique were used to investigate the factors affecting CO2 emissions in the tails of the conditional distribution. The share of each influential factor was predicted through the variance decomposition analysis (VD) for the next 10 years. The empirical results showed a long-run relationship between the variables. So, the variables of biomass consumption, ECI, and ICT improve the quality of the environment in Iran by reducing CO2 emissions, and the per capita GDP variable increases CO2 emissions. Results suggest no evidence indicating the presence of environmental Kuznets curve (EKC); however, QR demonstrated the existence of EKCs in the lower quantiles of the conditional distribution. The ECI will have the most share to change the CO2 emissions in the future. The income threshold should be determined at the turning point of the EKC to increase economic development. Moreover, investing in increasing biomass consumption is vital. Policymakers also need to consider strict added value for the export of products. [ABSTRACT FROM AUTHOR]

Pistacia atlantica Desf. (Beneh) is an important woody species that has been facing significant challenges to its natural regeneration and reforestation in Iran. This study investigates the interaction of soil moisture and shade on growth, chemical contents, and morphological and physiological characteristics of Beneh saplings. One-year-old Beneh saplings were treated with varying amounts of soil moisture (20, 50, and 100% of field capacity) and shade (0, 30, and 50% of full sunlight) in a split-plot experiment of a randomized complete block design in semiarid conditions of the Alborz Research Station of the Research Institute of Forests and Rangelands (RIFR) in Iran. The results indicate that soil moisture significantly affects the water content of the leaf, total chlorophyll, proline content, activity of catalase enzyme, leaf dry biomass, leaflet area, and dry stem biomass in the leaf. Shade significantly affected total chlorophyll, catalase enzyme activity, specific leaflet area, relative water content of the leaf, proline content, dry root biomass, and leaflet area. The interaction of shade and soil moisture significantly affected seedling height, catalase enzyme activity, specific leaflet area, and nitrogen and potassium content of the leaf. Shade moderates the stress of drought on Beneh saplings, but shading of Beneh saplings is not recommended in conditions where there is no concern about soil moisture. These conclusions can be used to improve the production of Beneh saplings in nurseries. [ABSTRACT FROM AUTHOR]

Population growth and technological advancement mean that human activities now consume increasingly higher levels of energy. This causes major problems such as depletion of fossil fuel resources and environmental pollution. Energy managers and planners are therefore trying to develop options to meet these increasing demands for energy while maintaining low environmental impact. Application of advanced energy saving techniques and renewable energy resources and technologies present a good solution to these problems. Bio-energy is a widely available resource so it presents an attractive type of renewable energy. Biomass is abundant and easily accessible, making it a low cost resource with great flexibility in terms of potential application. This paper reports on biogas production from livestock manure and considers evaluations made for the different provinces in Iran. Data for calculations were sourced from available databases relating to Iranian cattle farms. This study reports on calculations made using statistical data on number of cows, amount of manure produced and volume of created biogas per kilogram of animal waste. The total amount of biogas production from livestock waste was calculated for each province using theoretical and experimental methods. Outcomes showed that production of biogas from livestock waste could potentially supply a proportion of the country׳s natural gas demand. The outcomes were tabulated and a GIS database was generated. Volumes of produced biogas from livestock manure were compared with those of natural gas consumption and outcomes were plotted on a classified map showing data for natural gas consumption and biogas energy. Outcomes revealed that the provinces of Sistan-Baluchestan and Ilam had the highest priority in production of biogas from livestock waste with annual gas consumption levels of 33.3% and 9% respectively. [ABSTRACT FROM AUTHOR]

Abstract: Biomass is the only renewable energy source which can deliver electricity, provide heating, cooling and fuel in form of solid, liquid and gas. Biomass supplies more than 11.5% of the world's primary energy and about 79.7% of the world's energy consumption. In 2012, about 194.8millionton of renewable energy was consumed in the world and about 0.1millionton was consumed in Iran. Biogas is produced by anaerobic fermentation. Global biogas capacity will reach 22,000MW by 2025. European biogas electricity production in 2006 was 17,272GWh per year, of which 7338GWh was by Germany alone. Biogas now represents 1.2% of the annual production of electricity and nearly 10% of renewable energy, with an installed power close to 1500MW. Global biogas installed capacity is expected to achieve moderate growth over the next 12 years, reaching 22.040MW by 2025 and making a compound annual growth rate (CAGR) of 7.2%, a recently published analysis by Global Information Inc (GII) showed. The world biogas market has grown considerably between 2001 and 2011, with installed capacity expanding to 8.377MW in 2011 from 2.388MW in 2001. This equals a CAGR of 13.4%. The potential of biomass sources in Iran is estimated to be 132millionton (oil equivalent) in the form of agricultural and forest wastes, livestock wastes, municipal wastes, sewage and industrial wastes. Taking into account the usual amount of biogas yield from agricultural wastes, animal wastes, municipal wastes and industrial and municipal wastewater and with good safety factor, biogas in Iran will generate about 16146.35millionm3 which is approximately 323petajoule (1015) of energy. This paper investigates the potential of biogas production from biomass sources in Iran and presents the energy carriers, examples of biogas production, applications and quantitative potential of different sources in Iran. [Copyright &y& Elsevier]

Despite the increasing interest in mangroves as one of the most carbon-rich ecosystems, arid mangroves are still poorly investigated. We aimed to improve the knowledge of biomass and soil carbon sequestration for an arid mangrove forest located at the Azini creek, Sirik, Hormozgan Province (Iran). We investigated the biomass and organic carbon stored in the above and belowground biomass for three different regions selected based on the composition of the principal species: (1) Avicennia marina, (2) mixed forest of A. marina and Rhizophora mucronata, and (3) R. mucronata. Topsoil organic carbon storage to 30 cm depth was also estimated for each analyzed area. Biomass carbon storage, considering both aboveground (AGB) and belowground biomass (BGB), was significantly different between the cover areas. Overall, the mean forest biomass (MFB) was 283.1 ± 89 Mg C ha−1 with a mean C stored in the biomass of 128.9 ± 59 Mg C ha−1. Although pure Rhizophora stand showed the lowest value of above and below tree carbon (AGC + BGC); 17.6 ± 1.9 Mg C ha−1), soil organic carbon stock in sites under Rhizophora spp. was significantly higher than in the site with pure stand of Avicennia spp. Overall, forest soil stored the highest proportion of Sirik mangrove ecosystem organic carbon (59%), with a mean value of 188.3 ± 27 Mg C ha−1. These results will contribute to broaden the knowledge and the dataset available, reducing the uncertainties related to estimates and modeling of carbon pools in arid mangrove ecosystem, which also represent an important climatic threshold of mangrove worldwide distribution. [ABSTRACT FROM AUTHOR]

Weeds that emerge along with or immediately after crop plants usually can reduce the yield of those crops. Two randomized complete block design experiments were conducted during 2006 and 2007 in Tabriz, Iran to determine the critical period of redroot pigweed control in the green bean hybrid “Cantander”. The treatments were weed-infested and weed-free plots at 2, 4, 6, 8, 10, and 14 weeks after bean emergence (WABE). The green bean biomass was affected by the early emergence of redroot pigweed, but it was not reduced when redroot pigweed emerged at 10 weeks after crop emergence, along with crop emergence, and grew with green bean until 4 WABE. The redroot pigweed biomass decreased by 2.7 g m−2 per day when weed emergence was delayed. Each 100 g m−2 of weed biomass that was produced resulted in a 1.4 kg ha−1 loss in the green bean yield. When redroot pigweed interference lasted for ≥4 weeks after green bean emergence, the green bean yield was reduced significantly. Weeds, which emerged 2 weeks after green bean and thereafter were controlled, did not decrease crop productivity significantly. The highest crop yield was obtained when the weed emerged at 14 WABE. The critical period of redroot pigweed control, considering a 10% yield loss, was between 19 and 55 days after green bean emergence. Thus, weed control practises should be begun no later than 3 WABE and should continue until at least 8 WABE in order to obtain the maximum green bean yield. [ABSTRACT FROM AUTHOR]

Background: Chronic obstructive pulmonary disease (COPD) is a progressive airflow limitation and decline in lung function. Although tobacco smoke is the leading risk factor for COPD, air contamination by wood-burning smoke is also of great concern. About half of the world's populations, especially in developing countries such as Iran, exploit this energy source for cooking and heating. It is remained unknown if COPD induced by wood smoke from baking bread (COPD-B) and COPD induced by tobacco smoke (COPD-S) have different symptoms and clinical presentations. To fill this gap, the present study was to describe such differences. Materials and Methods: This retrospective cohort study was performed in Afshar COPD clinics affiliated with the Shahid Sadoughi University of Medical Sciences, Yazd, Iran. The clinical records of 231 patients with the COPD diagnosis were reviewed. After considering inclusion and exclusion criteria, 91 patients (46 with COPD-B and 45 with COPD-S) underwent physical examination and para-clinical assessments (i.e., respiratory function tests, Chest X-ray, and quality of life test). Results: The COPD-B patients were mainly women at older age and had higher FEV1/FVC and FEF-75; however, they had fewer post-bronchodilator positive responses to FEV1 (suggesting a restriction pattern) and sputum production, compared to the COPD-S patients. Regarding the other parameters, there were no statistically significant differences between the two groups. Conclusion: This was the first study evaluating and revealing some differences in the clinical and paraclinical characteristics of the COPD-B patients (with prolonged exposure to wood smoke from bread baking; >100 hours per year, for at least 10 years) and COPD-S patients (>10 packs per year of exposure to tobacco smoke). [ABSTRACT FROM AUTHOR]

In this study, the comprehensive thermodynamic, exergoeconomic and environmental performance of two multigeneration systemsfuelled by biomass and solar energy is surveyed. The multigeneration system A utilizes municipal solid waste and solar energy to produce power, heating, cooling, fresh water, and hydrogen which is considered to be located in the north of Iran with a moderate climate. Whereas, the multigeneration system B consumes bagasse and solar energy to supply power, heating, cooling, liquefied natural gas, and freshwater which is assumed to be located in the south of Iran with a hot climate. The results of the study show thatsystem B provides better performance from a thermodynamic viewpoint with energy and exergy efficiencies of 82.45% and 15.75%. Moreover, according to the outputs of exergoeconomic modelling, system B presents better performance because of lower capital costs. Finally, environmental profit is attained by accomplishing system B because of avoiding 1.14 million tons of NOx and 0.31 million tons of CO2 depletion to the atmosphere per year. In the end, through conducting a parametric study, the effect of key parameters on the thermodynamic, economic, and environmental performances of two systems is discussed. [ABSTRACT FROM AUTHOR]

Sustainable development programs rely on implementing energy policies in different sectors of a society. As far as agriculture sector is concerned, this paper intends to evaluate the current energy consumption and the potential for renewable energy programs' deployment in regional scale. The candidate region is Iran's Caspian Sea coastline. The assessment is modeled by recent multi-criteria decision analysis approaches, i.e. Level Based Weight Assessment (LBWA) with Weighted Aggregated Sum Product Assessment (WASPAS). The proposed index was designed so as to cover conventional and non-conventional energy resources subjects simultaneously, for instance: (1) biomass production, and (2) natural gas and diesel fuel at state level. From methodology point of view, the traditional WASPAS method is enhanced by the integration of the Weighted Power Heronian (WPHA) and Weight Geometric Power Heronian (WGPHA) functions. Application of these functions enables the elimination of the influence of extreme and unreasonable arguments in initial decision-making matrix. In addition, the interrelations between attributes is considered in the proposed model, that is particualrely appropriate for decision making in dynamic systems. The model capability in decision making has been investigated by comprehensive sensitivity analysis that implies in Iran's Caspian Sea coastline, Mazandaran state ranks first, followed by Guilan and Golestan. The result is suitable for policy makers and regional managers to define proper plans and actions in sustainable development of Caspian Sea coastline based on both agriculture-based energy efficiency as well as bio-based energy potential. [ABSTRACT FROM AUTHOR]

This study investigates length-mass relationships for 17 families of freshwater macroinvertebrates collected in the Choghakhor Wetland (Central Iran). Body length, head width, distance between eyes and mass (dry weight and wet weight) were used to estimate biomass with linear, log-linear and exponential models. The results show better performance of the log-linear model (ANOVA, p = 0.03), as compared to the other two (ANOVA, p > 0.05). A cross-validation test demonstrated that all three models performed reasonably well, in terms of both statistics and the accuracy of prediction. However, for more than 60% of the relationships the p value for the log-linear model was greater than for the other two, suggesting that the accuracy of this model is in general superior. Body length was generally demonstrated to be a good indicator to estimate biomass. However, for some taxa, the measurement of sclerotized structures (i.e., the distance between the eyes and the head width) were also found to be suitable biomass indicators. The latter is beneficial for the estimation of biomass with individuals that have been kept for a long time under laboratory conditions and/or those that show damaged parts of their bodies. The present study provides the first set of length-mass relationships for macroinvertebrates in the Middle-East region, and its findings are expected to contribute to the estimation of biomass in aquatic environments that are affected by semi-arid conditions and different degrees of anthropogenic stress. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Agricultural Science & Technology is the property of Tarbiat Modares University Press and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

• A hybrid GIS-ZDEA method is proposed to determine suitable locations for Paulownia cultivation. • The feasibility and suitability maps for Paulownia cultivation are derived based on three categories of criteria. • The high degree of fluctuation in weather condition is modelled by Z-number. • The computational experiments demonstrate that the proposed model can improve the results by 8% Paulownia has emerged as a prospering biomass resource for the production of renewable energy. Many countries have decided to cultivate this tree in order to reduce air pollution and secure the increasing energy demand. In this paper, a hybrid approach, including geographical information system (GIS) and mathematical modeling is proposed to determine suitable locations for Paulownia cultivation. The feasibility and suitability maps for Paulownia cultivation have been derived based on three categories of criteria, including (1) Certain Non-Compensatory Criteria (CNCC) (2) Uncertain Compensatory Criteria (UCC), and (3) Certain Compensatory Criteria (CCC), and a four-stage algorithm is proposed. This algorithm sets out to (1) recognize Paulownia growth conditions (2) identify feasible regions considering CNCC (3) evaluate the efficiency of candidate locations by employing data envelopment analysis (DEA) with respect to UCC, and (4) display suitability map according to CCC. The high degree of fluctuation in weather conditions is an important factor that significantly influences the DEA results. Therefore, Z-number is adopted to represent the uncertainty of input data in DEA modeling. To validate the proposed approach, the obtained efficiencies from Z-number, fuzzy number, and crisp DEA models are compared to those obtained from the actual data of a five years period. The results indicate that about 160,000 km2 land area is suitable to cultivate Paulownia in Iran that shows great potential for renewable energy production in this country. On the other hand, the computational results demonstrate that applying Z-number decreases the error of the weather forecast by 8% so that land suitability assessment can be carried out more accurately. As a result, this reliable method can prevent agricultural productivity loss due to selecting inappropriate locations. [ABSTRACT FROM AUTHOR]

Background: Traditional field-based methods of measurement of biomass and carbon storage face difficulty in collecting time-consuming and expensive, suggests the use of remote sensing-based techniques. It estimates the economic value of the aboveground biomass (AGB) using satellite remote sensing across the Hyrcanian forests of Iran. Methods: The Landsat-8 OLI sensor data were combined with field-based allometric information of 186 circular sample plots. The AGB was calculated at the plot level using the collected data and specific volumetric mass for species in the studied area. It was followed by calculating the carbon storage using a 50% carbon coefficient and the photosynthesis equation at the forest parcel level. Model results using the random forest and support vector machines. The carbon sequestration value was calculated with USD 25.3 as a shadow value of carbon in 2014 and using the replacement cost approach. Results: The highest performances achieved by RF for biomass, carbon storage and the carbon storage value (Iranian Rials of 0.67% and 16%, respectively). The value was derived once at the plot level of 12.22 million IRR (370.43 USD) per ha. In addition, at the parcel level, which resulted in an estimated value of 12.87 million IRR (390.24 USD) per ha. [ABSTRACT FROM AUTHOR]

Plantations established in highly-pollutant industrial areas have a crucial role to absorb greenhouse gases, particularly CO2. A thorough monitoring of their aboveground biomass and carbon balance is essential to ensure their beneficial effects. This can be operationally supported by using a combination of field and multispectral stereo remote sensing data to provide surface height information with high resolution and wide coverage. We estimated the fresh and dry aboveground biomass and the carbon sequestration from pairs of Pléiades satellite imagery of 25-year-old monoculture plantations of Pinus eldarica Medw., Cupressus arizonica Greene, Morus alba L. and Robinia pseudoacacia L., around the Mobarakeh Steel Complex near the megacity Isfahan. This complex is the largest-scale of its kind in semi-arid Iran. Tree heights were derived from a Canopy height model (CHM) at plantation management unit level. Parsimonious regression models were developed, and the accuracy was assessed by the coefficient of determination, bias and root mean square errors (RMSEs) at plot level. This resulted in R2 of total biomass, dry biomass, carbon sequestration, tree height and tree count of 0.90, 0.90, 0.91, 0.89, and 0.88, respectively. Moreover, mixed bias (with lowest value of -0.12 m for tree height) and NRMSE% (with lowest value of 5.93% for tree carbon sequestration) values were obtained. The results demonstrated that pairs of stereo imageries can be effectively used for predicting forest biomass and carbon sequestration across semi-arid plantations, hence enabling a continuous monitoring of vegetation established around pollutant industrial areas. [ABSTRACT FROM AUTHOR]

Satellite remote sensing has greatly facilitated the assessment of aboveground biomass in rangelands. Soil-adjusted vegetation indices have been developed to provide better predictions of aboveground biomass, especially for dryland regions. Semi-arid rangelands often complicate a remote sensing based assessment of aboveground biomass due to bright reflecting soils combined with sparse vegetation cover. We aim at evaluating whether soil-adjusted vegetation indices perform better than standard, i.e. unadjusted, vegetation indices in predicting dry aboveground biomass of a saline and semi-arid rangeland in NE-Iran. 672 biomass plots of 2 × 2 m were gathered and aggregated into 13 sites. Generalized Linear Regression Models (GLM) were compared for six different vegetation indices, three standard and three soil-adjusted vegetation indices. Vegetation indices were calculated from the MODIS MCD43A4 product. Model comparison was done using Akaike Information Criterion (AICc), Akaike weights and pseudo R2. Model fits for dry biomass showed that transformed NDVI and NDVI fitted best with R2 = 0.47 and R2 = 0.33, respectively. The optimized soil-adjusted vegetation index (OSAVI) behaved similar to NDVI but less precise. The soil-adjusted vegetation index (SAVI), the modified soil-adjusted vegetation index (MSAVI2) and the enhanced vegetation index (EVI) performed worse than a null model. Hence, soil-adjusted indices based on the soil-line concept performed worse than a simple square root transformation of the NDVI. However, more studies that compare MODIS based vegetation indices for rangeland biomass estimation are required to support our findings. We suggest applying a similar model comparison approach as performed in this study instead of relying on single vegetation indices in order to find optimal relationships with aboveground biomass estimation in rangelands. [ABSTRACT FROM AUTHOR]

Biomass is an important parameter in studying a variety of energetic processes in food webs, community structure, and composition of aquatic organisms. Biomass determinations are based on direct weighing of animals, biovolume determination, and length-weight conversion. Although direct weighing of individual organisms is the most accurate methodology, its application is not very common due to its time consuming nature. Length-weight regressions are the most widely used approach for estimating benthic invertebrate biomass because they are less time consuming and more precise than other methods. In this research, length-weight relationships are evaluated for the most common benthic invertebrates found in an Iranian mountain river in the Southern Caspian Sea Basin by fitting the power function (linearized by logarithmic transformation) to data of wet and dry weights against body length of aquatic invertebrates at both family and order level. A general predictive equation was also obtained for all individuals measured in this study. Regressions obtained were significant at a P value of < 0.05 and explained a high proportion of variation of the dependent variable, as expressed by the correlation coefficient (r= 0.82-0.99). Regression equations obtained in this study for three major orders of aquatic invertebrates were also compared to those in previous studies from different geographical locations. Relationships developed in this study, can be useful for future assessments of benthic community structure and for understanding the importance of these invertebrates in the energy flux of the river. [ABSTRACT FROM AUTHOR]

Aims The accurate estimation of aboveground biomass in vegetation is critical for global carbon accounting. Regression models provide an easy estimation of aboveground biomass at large spatial and temporal scales. Yet, only few prediction models are available for aboveground biomass in rangelands, as compared with forests. In addition to the development of prediction models, we tested whether such prediction models vary with plant growth forms and life spans, and with the inclusion of site and/or quadrat-specific factors. Methods We collected dataset of aboveground biomass from destructive harvesting of 8088 individual plants belonging to 79 species in 735 quadrats across 35 sites in semi-steppe rangelands in Iran. A logarithmic transformation of the power-law model was used to develop simple prediction models for the easy estimation of aboveground biomass using plant coverage and vegetation density as predictors for the species-specific model, multispecies and plants of different growth forms and life spans. In addition, additive and multiplicative linear regression models were developed by using plant coverage and one categorical variable from the site and/or quadrat-specific factors. Important Findings The log-transformed power-law model based on plant coverage precisely predicted aboveground biomass across the whole dataset for either most of the species-specific model, multispecies or plants of the same growth forms (shrubs, forbs or graminoids) and life spans (annuals, biennials or perennials). The addition of vegetation density as a single or in a compound predictor variable had relatively poor performance compared with the model having plant coverage only. Although generalizing at the levels of plant group forms and/or life spans did not substantially enhance the model-fit and validation of the plant coverage-based multispecies model, the inclusion of plant growth forms or life spans as a categorical predictor variable had performed well. Generalized models in this study will greatly contribute to the accurate and easy prediction of aboveground biomass in the studied rangelands and will be also useful to rangeland practitioners and ecological modellers interested in the global relationship between biodiversity and aboveground biomass productivity across space and time in natural rangelands. [ABSTRACT FROM AUTHOR]

Developing alternative oilseed crops with acceptable seed yield and biomass production in low-yielding environments could be a part of sustainable agriculture management strategies. Field experiments were conducted in a semiarid region of Iran in 2013 and 2014 to determine the effects of N fertilizer rates and plant densities on growth, seed yield and quality of blessed thistle (Cnicus benedictus L.) under low yielding conditions. Randomized complete-block design with factorial arrangement of treatments was used in three replicates. Treatments consisted of four N rates (0, 50, 100, and 150 kg N ha-1) combined with five plant densities (5, 10, 15, 20, and 25 plants m-2). According to quadratic functions, the maximum seed yield (913 kg ha-1) was achieved with 122 kg N ha-1 and 16 plants m-2. Although the seed oil content decreased with increasing N rates, increased seed yield partially compensated for the reduction in oil content. Higher seed protein was obtained from low plant densities (5-10 plants m-2) and high N rates (100-150 kg N ha-1). Nitrogen harvest index (NHI) decreased by 30 to 40% as a result of increased plant density across all N rates. Plant density and N did not affect seed fatty acid profiles, even though N rate by year interaction affected the profile. Linoleic acid was the predominant fatty acid comprising 62.5 to 66.2% of the total fatty acids. The study demonstrates that blessed thistle could be a promising oil crop for cultivation in low yielding soils, although breeding work is needed to enhance its prospects as a viable oil crop. [ABSTRACT FROM AUTHOR]

Copyright of Arboriculture & Urban Forestry is the property of International Society of Arboriculture and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Indoor artificial streams were used to evaluate the short-term (24 day) influence of copper and zinc, individually and in combination, on the biomass and taxonomic composition of algal periphyton communities. The effects of Cu (50 μg l-1) and Zn (1 mg l-1) were assessed using measurements of biomass, ash-free dry mass (AFDM), chlorophyll-a concentration, taxonomic composition and biovolume. In artificial streams with Cu, Zn and Cu+Zn, there were significant (p < 0.05) reductions of chlorophyll-a concentrations, dry mass and AFDM, and also changes in the species diversity and relative abundances of periphyton species. In artificial streams containing both Cu and Zn the taxonomic composition shifted from a Cyanophyceaen dominated community to one consisting mainly of Chlorophyceae, whilst the relative contribution of Bacillariophyceae was not significantly altered. [ABSTRACT FROM AUTHOR]

(1)The dispersion, biomass and population structure of the semi-desert shrub Zygophyllum eurypterum were measured in a 1 ha sample of the Turan Biosphere Reserve of north-eastern Iran. (2)The density was 530 plants ha[sup-1] and bushes covered 13% of the surface area. Biomass was estimated to be approximately 2600 ha[sup-1]. (3) Few small individuals were found in the area; this might be due to intraspecific competition or to grazing by domestic and wild herbivores. (4) The regularity of dispersion of bushes supports the hypothesis of intra- specific competition as the primary limitation to the Zygophyllum population. [ABSTRACT FROM AUTHOR]

At the Paris Agreement in 2015, Iran pledged a 4% reduction in greenhouse gas emissions by 2030 and bio-fuels like wood pellet are an option. To estimate the volume of waste woody biomass the International Energy Agency model was employed and results show that a total opportunity of 754,840 m3 of woody by-products. An economic feasibility study of wood pellet production was performed by calculating the economic indices and analyzing their sensitivity using COMFAR III software for three scenarios in annual capacities of 48,000, 75,000 and 120,000 tons. The costs of wood pellet production for each plan are 104.29, 107.63, and 106.92 €/Mt, respectively. Acceptable IRR (45%–124%) and NPV (7–14 Million Euro) support the feasibility of wood pellet production in Iran. Standard VDI 2067 used to calculate specific cost of generating energy with wood pellet fuel against domestic water boilers using diesel and natural gas fuels. Results showed that the cost of generating energy is higher by wood pellet (43.5 €/Mwh, against gasoline, 25.9 €/Mw, and natural gas, 22.3 €/Mwh) due to the high initial investment in the wood pellet-fired boilers compared to established fossil fuels and the low price of diesel and natural gas in Iran. • There are 754,840 cubic meters of wood debris that can be used for producing wood pellet as a source of Bio-energy. • This study showed that the costs of wood pellet production in Iran were considered to be between 104.29 and 107.63 €/Mt. • Economic indicators are more sensitive to operating costs due to the high share of the cost of raw materials. • The low price of fossil fuels in Iran makes the wood pellet competition harder. [ABSTRACT FROM AUTHOR]

Abstract: In this work, biomass-derived energy has been highlighted and biomass has been divided into three main categories: agricultural residues, animal waste, and municipal solid waste. Energy is essential for the economic and social development and improved quality of life in Iran as in other countries. Much of the world''s energy requirement, however, is currently produced from fossil fuels that could not be sustained if technology were to remain stagnant and if overall quantities were to increase substantially. The process of controlling atmospheric emissions of greenhouse and other gases and substances should increasingly be based on efficiency in energy production, transmission, distribution and consumption in the country. The need for transition to sustainable energy resources has been recognized in Iran. To reduce and utilize the waste produced from these resources and be benefited from green fuels, an assessment was carried out to provide an overview on green energy potentials in Iran. The annual biomass potentials of Iran in terms of agricultural, animal and municipal wastes are 8.78×106, 7.7×106 and 3×106 tonnes, respectively. In addition, poplar planting and microalgae can play an important role in the future scenario of wood supply and energy recovery in Iran. [Copyright &y& Elsevier]