Journal of Natural Environment
Year:2021 | Volume:74 | Issue:1|Papers Count:15

Understanding the habitat preference of riverine species is important in their management to protect their habitat. This study aimed to investigate the habitat preference of the Sefid river loach, Oxynemacheilus bergianus in Jajroud River by comparing its preference in autumn and winter. For this purpose, elevation, depth, water current velocity, river width, slope, average diameter of the bedrock, type of predominant bedrock cover, EC, TDS, pH, water temperature and beach vegetation were measured and investigated in autumn and winter. The preferred habitat of this species in autumn had lower elevation and depth, faster water current, medium rock bed, lower slope, higher temperature, medium EC and TDS and river bank with shrub-tree cover, but in winter the selected habitat changed to areas with higher elevation, depth and water current, and bed with medium-sized rocks, medium temperature, medium EC, less TDS and the river bank with tree cover i.e. the results showed that the preferred habitat of this species in winter changes to areas with greater depth, width, elevation and slope.

Nowadays, the compounds known as emerging pollution are increasing in the environment. Pharmaceutical compounds are one of the most important substances in this group. Due to the complexity of chemical structure of pharmaceutical compounds and their metabolites, removal of these is important. Removal of these compounds by conventional water and wastewater treatment methods is not possible. In the present research, the performance of a hybrid of synthesized zeolite and ZnO nanoparticles for photocatalytic degradation of acetaminophen-codeine from aqueous solutions was investigated. To remove acetaminophen-codeine from aqueous solution, ZnO-Zeolite under UV and solar radiations was used. Final concentration of drug was measured using by HPLC in λmax = 214 nm. The optimal conditions of pH, catalyst dosage, drug initial concentration and reaction time were determined, based on Response Surface Methodology (RSM). Reusability test was finally performed for this synthesized composite. The results indicated that maximum removal of acetaminophen under UV radiation (48W/m2) was related to 14 mg/L of initial concentration in the neutral pH and a catalyst concentration of 1.7 g/L after 167min and that under the solar radiation (1200W/m2) was related on 5.5 mg/L of initial concentration in the neutral pH and a catalyst concentration of 1.2 mg/L after 143min of reaction start. Optimal initial concentration for codeine remove was 7.5 mg/L in the neutral pH. The maximum removal under UV and solar radiations was related to 1.5 and 1 g/L of composite after 192 and 170 min for codeine photocatalytic degradation. Photocatalytic degradation using this synthesized composite under optimal conditions, is able to completely remove the drug compounds (>99%) under UV and solar radiation. The photocatalytic method of ZnO-Z to remove acetaminophen and codeine from aqueous solutions is recommended. Synthesized composite in this research is a suitable material with reusability. Its efficiency also is acceptable under sunlight.

People are looking for new spaces that they can discover, and keep distance from dull and repetitive spaces, to create a place that is compatible with today's complexity and specific desires. The purpose of this study is to model the complexity of landscape in urban parks using artificial neural network in order to predict the complexity of landscape in urban parks and determination of the effect of different landscape variables on it. The present study was carried out in ten parks with an area of more than 10 hectares in Tehran city (Saei, Mellat, Nahj al-Balagheh, Iran Zaman, Laleh, Abo Atash, Taleghani, Jamshidieh, Gheitarieh and Niavaran) and in four municipality districts (1, 2, 3, and 6). The purpose of this study was to evaluate the complexity of landscape in urban park using a combination of user-based approach and artificial neural network modeling using 17 objective elements of landscape. According to the results, the model with 17-14-1 structure (17 input variables, 14 neurons in hidden layer and one output variable) according to the highest value of coefficient of determination in the three categories of training, validation and test datasets equal with 0.93, 0.85, and 0.87 created the best optimization performance. Accordingly, hard surfaces ratio, the mean of trees diameter and buildings, with the coefficients of 0.21, 0.15, and 0.12, respectively, are the most influential factors on the complexity of landscape in Tehran city parks, respectively. The presented model in this study is known as a decision support system in engineering design of urban parks and enables prediction of the complexity of landscape according to the environmental variables. .

The tourism industry is one of the largest service industries and one of the most important economic activities in the world. There are many studies on this subject, most of which have studied the climatic and economic factors seperately. In this study, we want to examine the simultaneous effects of economic and climatic factors on tourism. In this regard, panel data was collected for 30 provinces of Iran during the years 2006 to 2018. These provinces were classified in seven regions and each region is individually examined. Given the cointegration analysis results, we were using panel data or DOLS or GMM procedures, for each region. In general, according to the results, in many provinces, climate variables have a significant effect on tourism along with economic variables. In fact, in all provinces where provincial value added has been significant, value added leads to an increase in the number of tourists in the long run. Results for climate variables show that with increasing temperature, the number of tourists in provinces of Khorasan Razavi, South Khorasan, Tehran, Semnan, Isfahan, Kerman, Markazi, Sistan and Baluchestan, Yazd, Qom, Bushehr, Hormozgan, Khuzestan provinces increases. The increase in raining in the autumn and winter seasons in the provinces of Mazandaran and Gilan are among the provinces with the highest number of tourists and Fars, Ilam, Lorestan, Kohkiloyehr and Boyer Ahmad provinces will have fewer tourists in these seasons.

Human-induced climate change has had worldwide impacts on coastal human and natural systems. Sea-level rise (SLR) due to climate change is one of the biggest challenges human civilization is facing in coastal regions today. Over the past 25 years of satellite altimetry, global sea level rose at an average rate of 3.3 mm/yr. (13 in. /century), but this rate is accelerating. Global mean sea-level rise (SLR) will continue during the 21st century, very likely at an increased rate. Climate related SLR has major adverse effects on coastal systems. Assessing the vulnerability of individual coastal areas to future inundation is essential in order to develop adaptive management strategies to cope with the future impacts of sea-level rise. In this vulnerability assessment, exposure of the 292 km coast of southern Iran (Jask County) along the sea of Oman has been studied. To identify areas that would be inundated by future sea-level rise we applied NOAA’s modified bathtub model, and used high estimates of projected global sea-level rise for all RCP scenarios for the year 2100 from the IPCC Fifth Assessment. The results of inundation mapping indicate that under RCP 2.5 scenario (with 0.55 m of SLR) about 299 sq. km. would be inundated. For RCP 4.5 and 6 (with 0.63 m of SLR), about 334 sq. km., and under extreme sea- level rise (RCP 8.5 and 0.82 m SLR) about 449 sq. km. will be inundated. In addition the results indicate although only 1% of the entire coastal area falls into the urban/built category, this includes the most populous city in the county, 2 strategic ports, as well as an airport and industrial zones. Assessing the socio-economic and ecological vulnerability of coastal areas subject to future sea-level rise can assist government officials, managers or decision makers in developing appropriate action plans to adapt to and mitigate sea-level rise impacts. This is particularly timely along the southern coast of Iran where development is in an early stage.

Nowadays, different societies are facing increasing population and extensive urbanization. Land use changes is one of the phenomena that is very important in the world and has significantly impact on the environment. The purpose of this research is investigating the effect of land use change on land surface temperature in the central zone of Sanandaj city. Using supervised classification method, maximum likelihood algorithm, the land use map was classified into five categories agriculture, bare, urban, vegetation, and water. The land surface temperature examined using Sebal algorithm in a period of 19 years. The obtained results from land use analysis in the study area revealed that urban, agriculture, vegetation and water areas show an increasing trend but bare lands show a decreasing trend from 2000 to 2019. Minimum land surface temperature arrived to 6.15 ºC and 5.26 ºC in 2000 and 2019, respectively. Also, maximum temperature increased from 49.22 ºC to 51.39 ºC in this 19 years period. The highest surface temperature in both mentioned years were obtained in bare lands. Vegetation and water areas have the lowest surface temperature in this period. Unlike Mediterranean and tropical cities which experience the urban heat island, Sanandaj city, with cold and semi-arid climate, experienced the urban cool island. Urban cool island is due to the surrounding urban areas with bare lands with high surface temperature.

Wetlands are valuable ecosystems that provide a variety of environmental services such as water storage and supply, erosion and flood control, and biodiversity conservation. Migratory birds including waterfowls and shorebirds are among wetland-dependent species whose survival depends on wetlands. Ecological conditions and water quality of a wetland depend on the characteristics of its surrounding environment, including the type and ratio of land use and land covers. Miangharan wetland is one of the valuable wetlands in Iran, located in the southwest of the country in Khuzestan province. The current study was conducted to monitor land cover changes in Miangharan wetland over a period of 30 years and to rank destructing factors of this wetland. Satellite images were utilized from the mid-winter of 1990, 2000, 2010 and 2018 and land use maps of different years were produced and analyzed. Five land use classes including urban area, agricultural area, wetland, rocky outcrop and forests were identified using supervised classification. Destruction factors were identified through field observation and reports. The analytic hierarchy process (AHP) was used to rank the destruction factors of the wetland. A questionnaire was designed and completed by 20 environmental experts in Khuzestan province and analyzed, using Expert Choice software. Result showed that the wetland area has been decreased up to 80% from 1990 to 2018 and agricultural and urban areas have increased by 40%. Based on the results, the highest calculated weights were related to three threatening factors including sewage inflow (0.35), agricultural activities near the wetland (0.16) and natural drought (0.15). A correct and accurate understanding of the process of changes in a wetland and its threatening factors, provide a basis for preventing and dealing with these factors, as well as the prevention and accurate implementation of wetland conservation plans.

This study was conducted to evaluate the concentrations of heavy metals including: copper, cobalt, chromium, cadmium and arsenic in sediments, water, roots of Phragmites in three areas of Kiaklayeh wetland that are affected by Mehr housing, agricultural and municipal wastewater. In order to measure heavy metals, ICP-OES was used. Qualitative indicators were also used to examine these pollutants more closely. The results showed that the accumulation of cobalt in the sediments which receivied agricultural and housing effluents is higher than the area of the wetland that is affected by the municipal landfill, but the concentration of chromium and cadmium in the sediments near the landfill is higher than the other two areas of the wetland. Is. Also, in the sediments under agricultural effluent, the amount of copper and arsenic was higher than the other two regions. Accumulation of cobalt and copper in the roots of Phragmites in the area affected by Mehr housing wastewater is higher than the agricultural area, but the amount of copper in the stem of Phragmites growing in the agricultural grounds is higher. EF higher than 1 was obtained for cadmium and cobalt in the area contaminated with Mehr housing effluent. The highest Igeo was related to cadmium and the highest anthropogenic contribution was obtained as well as the highest RI and MERMQ for the studied metals in the wastewater from agricultural area. The highest amount of PLI was obtained for the area contaminated with Mehr housing wastewater. together, it can be said that agronomic wastewater have the highest potential for ecological and biological hazards and also Mehr effluent has the the biggest amount of pollution for the wetland ecosystem. Arsenic agricultural wastewater and also arsenic and copper in Mehr housing wastewater, respectively , showed the highest TF to the roots of reeds.

Due to the increasing trend of Hyrcanian deforestation and Iran's significant proportion in CO2 emissions, the Reduction of Deforestation and Degradation (REDD) emission project was implemented in nine steps and two scenarios in Golestan province. In the baseline scenario it was assumed that the trend of past land use changes will continue. In this regard, land use changes were studied using Landsat images of 1984, 2008 and 2018. Transition potential modeling was performed by Multi-Layer Perceptron (MLP) neural network. Then future land use change was predicted under the baseline scenario over a period of 30 years (2018-2048) and CO2 emissions were estimated. In this regard, study area was divided into the project area and leakage belt based on the Multi Criteria Evaluation (MCE) derived forest suitability map. In the project scenario, some of deforestation activities were controlled. Due to the importance of the project success rate and leakage rate in CO2 emissions, the effectiveness of the project scenario was assessed by changing the leakage rate (10, 20, 30, 40 and 50%) and the project success rate (90, 80, 70, 60 and 50%). Based on the results in the best state (success and leakage rates of 90 and 10% respectively), the amount of CO2 emissions within the project area decreased from 573968.3 tons in 2018 year under the baseline scenario to 66265.5 tons in 2047 year. Evan in the worst state (success and leakage rate of 50% respectively), a decrease in emission was observed compared to the baseline scenario. If any management approach isn't implemented to conserve forests in Golestan province, the amount of CO2 emissions will increase to 662655.9 tons in the year 2047.

Today, noise pollution is considered as one of the major pollution of the urban and industrial environment that disrupts the ecological processes of the environment and ecosystem services, physical and mental health of humans and wildlife populations. In this research, the distribution of noise pollution in air and dtermination of noise intensity level in terrestrial habitats for indicator fanua in Khark Wildlife Refuge was done using SPreAD-GIS model. indicator fanua such as deer (Gazella subgutturosa), Whiskered Tern (Chalidonias hybridus), Bridled tern (Onychoprion anaethetus) and Hawksbill sea turtle (Eretmochelys imbricate), Green sea turtle (Chelonia mydas) were studied in this research. The results showed that the noise intensity level from noise sources in the region had no significant negative impact on the presence and distribution of studied species. In other words, the studied species have been adapted to the noise from sources of pollution. In addition, in the vicinity of the sources of noise pollution, there are security and protection conditions for the species to survive in the area without especial problems.

Ardakan Wastewater Treatment Plant with biological sludge treatment system of activated sludge and total nominal capacity of 23328 cubic meters per day and an area of 14 hectares, is responsible for wastewater treatment in the entire city of Ardakan, which can have significant effects on the environment and water resources. The purpose of this study is to investigate the effects of constructing a complete municipal wastewater collection network and implementing the complete phase of the treatment plant on quantity and quality groundwater resources in Ardakan using the MODFLOW numerical model. The conceptual model prepared using observatory wells, aqueducts, aqueducts, absorption wells, hydraulic conductivity, aquifer boundary layers and surface feeding. All layers were defined in different formats including polygon, linear and raster and point in ArcGIS and then inserted to GMS. The modeling results showed that the use of treated effluents to improve and compensate for the drop in water levels in groundwater resources in the Yazd-Ardakan plain can be very effective and prevent at least 23% reduction in groundwater levels. The RMSE values obtained from the model calibration in steady and unstable states were 0.41 and 0.42, respectively. The results showed that in the defined scenarios, in exchange for removing the municipal wastewater collection network from the hydrological cycle in general, we will encounter the largest drop in water level, which is equivalent to 35%, which from the management perspective for the underground aquifer in the direction Reducing the trend of water level drop in this scenario can be considered as the most inappropriate scenario. Also, from the point of view, the effect of the sewerage network on the water level, there is the least negative effect on the aquifer.

Nowadays, waste management has become a serious concern of society due to increasing population growth rate and waste production. Despite efforts have been made to reduce the landfilling rate in Iran, a large amount of waste is still disposed of in landfills. Leachate generation is a major problem of landfills and, if not managed properly, it can cause significant threat to surface water and groundwater near to the landfill. Therefore, it is necessary to design a proper collection system to remove the leachate from landfill efficiently. Knowing the rate of leachate generation with reasonable accuracy is the critical input to design a landfill leachate collection system. In this study, a water balance method was used to estimate the amount of leachate produced in the Halgheh Darreh landfill of Karaj. In this model, we have considered a wide range of parameters that contribute to leachate generation in a landfill including rainfall, annual heat index, runoff, potential and actual evapotranspiration, the rate of leachate recirculation, evaporation from the surface of recirculation ponds, the amount of water used in gas production and also the initial moisture content of waste at the gate of landfill. The leachate generation rate was calculated for each month. In order to validate the results of the model, the actual leachate production was measured in December, January, February, March, April, May, June, and July. The comparison of the model estimates against the actual values measured at the site indicated an acceptable accuracy with a correlation coefficient (R) and the coefficient of determination (R2) equal to 0.966 and 0.933, respectively. Also, the root-mean-square error (RMSE) and mean absolute value of error percentage (MAPA) were 1328.27 and 9.17%, respectively, showing a small difference between the actual values and predicted values by the model. Also, the sensitivity analysis of the input parameters showed that the most important factor influencing the leachate generation is the moisture content of the incoming waste. The model developed in this study was a simple model and, with limited modification, it can be applied in other landfills located in arid regions of Iran.

AbstractThe city of Yazd has located in central of Iran that experiences dust storms most of the year, and also has witnessed rapid industrial growth, especially in industries with high dust generation capacity (tiles, steel, etc.) during the last two decades. Therefore, predicting the concentration of particulate pollutants during dust storms and industrial pollution through the use of accurate warning systems is critical to maintaining the health of citizens. In this study, an Adaptive Neuro-Fuzzy Inference System (ANFIS), Support Vector Regression (SVR), and Artificial Neural Network (ANN) models were used at the same time to predict the concentration of PM10 for the next 24 hours and to introduce the most accurate method. For this purpose, were used PM10 data, meteorological parameters, and gas pollutant concentrations of Yazd city from 2015 to 2019 years. The results of this study showed that the ANFIS model with (R2 = 0.989) and accuracy of about 99% were better than other models, followed by the ANN model with (R2 = 0.978) and the SVR model with (R2 = 0.957) had the best accuracy, respectively. Finally, data analysis showed that at the operational scale, city managers can make appropriate and timely decisions based on high-precision predictive models, maintain public health before the start of the PM10 alert status.

The purpose of this study was to investigate the composition and biodiversity of herbaceous cover and regeneration in natural forest (dominated by hornbeam-iron tree), plantations (pure and mixed alder and maple) and degraded forest areas (without tree cover) in the Kelarabad of Chalus. A total of 16 large sample plots (20 × 20 m2) to record the vegetative characteristics of the trees and 144 small sample plots (1 × 1 m2) to record the number of regenerated woody species, type and percentage of herbaceous species. The variety of indices were used to compare biodiversity. The highest percentage of herbaceous species belonged to the Brachypodim pinnatum L., while in the degraded area the percentage of Rubus caesius L. was dominant. Among the understory herbaceous plants, hemicryptophytes and cryptophytes were the most abundant biological form. Also, according to the results, the highest percentage of regeneration species was related to the dominant tree species in each forest stands, and among regeneration species, Phanerophytes were the most abundant biological form. Investigation of biodiversity indices in both herbaceous and regeneration layers indicates the negative effects of forest degradation as well as the positive role of natural forest in the study area. As a general conclusion, the present study demonstrates the protective role of temperate broadleaf mixed forest stands for the richness and diversity of herbaceous plant species and the sustainable regeneration and conservation of understory communities.

In the present study, in order to model the environmental impacts using landscape metrics; Guilan province was divided into 183 impact unit, and the Land Degradation Model was applied. In the next step, using the measures of (Related circumscribing circle, Perimeter-area ratio, Shape index, Fractal dimension index & Contiguity index) which were calculated by Fragststs, five models were developed based on stepwise modeling approach. Following from that, Akaike information criterion was applied to determine the most appropriate model. The results of this study showed that 39.78% of Guilan province is located in sensitive and susceptible areas. The highest physiological density was observed in Siahkal county. Regression models indicated that the amount of environmental degradation can be predicted using the weighted average of measures related to the landscape structure metrics: rcc (r2 = 0.437, p ≤ 0.05), contig (r2 = 0.615, p ≤ 0.05), frac (r2 = 0.505, p ≤ 0.05), shp (r2 = 0.499, p ≤ 0.05) and (r2 = 0.672, p ≤ 0.05). The most appropriate model, which was determined by AIC, was the model for the Perimeter-area ratio, and it had a good model validation result. Our findings revealed that applying the landscape metrics would be able to use for assessing the environmental impacts. In turn, it would decrease the degree of subjectivity in the landscape degradation model, as well. On the other hand, the use of landscape metrics, which can be easily and quickly calculated through land use or land cover maps, will greatly eliminate the need for extensive field work. Accordingly, using land degradation model will be more easily implemented in a much shorter time and at a lower cost to evaluate the environmental impacts.