Journal of Environmental Resources Research
Volume:10 Issue: 1, Winter-Spring 2022

The goal of this study was to analyze the environmental behavior of elementary school students in green schools using Ajzen theory of planned behavior (TPB). This quantitative study was conducted through a cross-sectional descriptive survey using a questionnaire developed by the researcher. The study had a statistical population of 229 elementary students. One hundred students were selected as the sample based on the table by Krejcie and Morgan. The collected data were analyzed using SPSS and AMOS software through Path Diagram Analysis. The findings indicated that attitude, subjective norms, and perceived behavioral control (self-efficiency) had positive and significant association with intention. However, there was no significant relationship between intention and frequency of environmental behavior. The findings in this model suggest that other undiscovered factors may be involved in environmental behavior. Modifying the three components of attitude, subjective norms, and perceived behavioral control will therefore lead to the development and enhancement of intention for environmental behaviors. Other effective factors on environmental behavior, however, should be explored in further studies to minimize environmental damage and modify the course of environmental damage.

Ecotourism is a popular aspect of tourism that gives economic value to biodiversity and allows tourists to gain knowledge about the importance of environmental conservation. The rapid and imbalanced growth of the tourism industry and the prioritization of economic benefits in the areas around Tehran have disturbed the ecosystem and led to increasing pressure on the environment. Hence, ecological potential evaluation is recommended as a practical solution. The current study aims to evaluate the ecological potential of the Kan watershed for ecotourism development using the Analytical Hierarchy Process (AHP) and Geographic Information Systems (GIS). The case study is located between the Tehran in the south, Darakeh watershed in the east, Jajrud watershed in the north, and Karaj river watershed in the west. In the first step, the effective criteria were selected based on literature review and expert interviews. Then, the criteria were weighted and prioritized using AHP. Afterwards, Fuzzy logic and Weighted Linear Combination (WLC) methods in GIS were used to zonate intensive and extensive ecotourism development. The results showed that 1.3% (273 ha) and 11.3% (2327 ha) of the Kan watershed is very suitable for intensive and extensive ecotourism development, respectively. Also 2.3% (475 ha) and 14.1% (2903 ha) of the region falls in the category suitable for intensive and extensive ecotourism development. Suitable areas for intensive ecotourism are mostly located in the southeastern part of Sulqan rural district, Keshar-e Sofla, and Keshar-e Olya villages. Potential zones of extensive ecotourism are located throughout the watershed along riparian areas and in valley floors.

Urmia Lake has experienced a critical environmental condition in recent years. This paper discusses changes in various hydrological measures in the Urmia Lake Basin (ULB) and its tributaries. The Mann-Kendall test with Trend-Free Pre-Whitening )TFPW( approach was used to estimate the trend in annual time series (1978-2011) of average and peak values of discharge recorded in 65 and 55 stations of ULB, respectively. Accordingly, the Cumulative Sum (CUSUM) control chart test was used for change detection analysis and T-statistic to compare the discharge in two periods (before and after 1995 as the year in which the Urmia Lake water level started to decline). The results revealed that 55 stations (~86%) had a descending trend in recorded average values of discharge data. In 38 stations (~59%), this diminishing trend was significant at 95% confidence level. The trend of peak data recorded in 42 out of 55 stations was declining. This falling trend was significant at 95% confidence level in seven stations. The average value of T-statistic for all stations (2.8) represented a significant difference between discharge values in two periods at most of the studied stations. The CUSUM results indicated that in more than 50% of the stations, which recorded discharge series of 11 rivers, the existing jump was significant at 95% of confidence level. The trend of 0-1 m3 /s interval was ascending, but the trend of other discharge ranges (more than 1 m3 /s) was descending. The results of this study also revealed that the amount of peak and discharge volume entering the lake in 1998-2011 decreased in comparison with 1978-1997.

Water crisis and pollution increase have encouraged researchers to rehabilitate wastewater as an alternative water source. Wastewater treatment plants (WWTPs) implementation with high environmental and economic compatibility can be achieved using life cycle assessment (LCA). In this regard, the current review compared three well-known WWTPs including anaerobic/anoxic/aerobic (A2O), membrane bioreactor-reverse osmosis (MBR-RO), and integrated fixed-film activated sludge membrane bioreactor (IFAS-MBR) systems from an environmental perspective. The largest environmental impacts of the IFAS-MBR and MBR-RO were associated with climate change (27.5-95.13%) and human health (67.57- 92%), while the midpoint and endpoint impacts of A2O were attributed to freshwater eutrophication (31.62%), marine ecotoxicity (29.94%), and resources (60.18%). The maximum and minimum energy consumption were observed in the A2O and MBR-RO configurations, respectively. The obtained results revealed that fossil fuels utilization remarkably influenced greenhouse gas (GHG) emission, specifically CO2. The sensitivity analysis also elucidated that electricity is the main indicator, which affected climate change (3.09-8%) and ozone depletion (18.97%) categories. Therefore, the results of the present study can be utilized as a guideline for further investigations in the LCA of various WWTPs.

Agricultural sector has a key role in poverty reduction and improving food security. One of the important challenges in the agriculture sector is to feed the increasing global population. Agriculture has both significant positive and negative impacts on environment and is a significant contributor to pollution which in turn restricts expansion of the agriculture production. Climate change has also attracted attentions in agricultural-environmental interactions. Bayesian networks are relatively well recognized and employed in different types of environmental modeling efforts. In this study a Bayesian network model was designed to investigate the relationship between agro-economic-environmental indicators and Environmental Performance Index (EPI) in the EU countries compared to Middle East (ME) countries that face many challenges for sustainable development. Scarcity of water, population growth and degradation of natural ecosystems are a few of these challenges. In this study, we showed the relationships between influential variables on EPI based on expert interview and available data. The results indicated land productivity was directly affected by organic agriculture area. It is found that with expansion of the organic and conservation agriculture area, productivity can be increased in EU Countries. Our findings also showed that with decreasing N2O and CH4 emissions, EPI in EU countries increased but it decreased in ME countries. Therefore, EU countries have been able to improve the EPI and achieve sustainable development objectives due to improved agricultural practices and optimum applications of pesticides and fertilizer. However, ME countries did not achieve such status. Modeling of agroenvironmental indicators can help policymakers to evaluate the changes of agro-ecosystem and apply them even at international scales.

There are a wide range of equipments and machinery in the steel ingot industry, and most of them, are a source of noise pollution. The purpose of this study is to determine the main sources of noise, the daily exposure of labors and to investigate the noise-induced hearing loss (NIHL) prevalence in Anzali Steel Ingot factory. After a walk-through survey of existing units and the factory work schedule, 21 sampling points were selected in the process, office and service units of the factory. The field measurements were conducted at specific hours of two different work-shift days using a portable sound pressure level (SPL) meter. Noise map of the factory revealed that in almost 68% of job groups in the factory, daily-averaged noise level is greater than the occupational exposure limit (OEL). Also, the daily-averaged exposure of workers in all process units was more than the limits. Workers in furnace installation, electricity and facility units experienced the highest exposure with a daily exposure of more than 100 dB(A). A significant correlation was observed between the daily exposure level and NIHL (p-value=0.022) at α=0.05 significance level. The NIHL in the process units increased between 1.25 and 7.5 dB(A), annually. The maximum increase was observed at units whose workers' noise exposure was within 5 dB(A) of the exposure limits, due to not using personal protective equipment (PPE). The daily exposure of the workers, who spend at least 25 % of daily working time in the furnace installation area, was above 100 dB(A), despite regular wearing of earplugs. Due to the ineffectiveness of the exposure time reduction, the best solution for these workers is to increase the noise reduction coefficient of the chamber's walls in the furnace installation unit, installing barriers in the furnace installation open area and increasing the number of chambers. In other process units, full inspection of the regular wearing of the PPE over a period of time is recommended. Thereafter the hearing loss of workers should be checked again and in case of inefficiency, changing the workplace of workers in different process units is recommended to reduce the exposure.

This research ranked wheat-producing provinces of Iran based on crossefficiency and eco-efficiency. Eco-efficiency measured by cross-efficiency in which greenhouse gas (GHG) emissions were regarded as an undesirable output. Data required for the research on the amount of input consumption, yield, and revenue were derived from the databases of the Ministry of Agriculture Jahad for 2018 and were analyzed using the MATLAB and MS-Excel software packages. The ranking of irrigated wheat-producing provinces based on cross-efficiency showed that Lorestan was in the first rank. Based on eco-efficiency the ranks of 19 provinces were changed by one to five levels. Ardabil, Isfahan, Fars, and Mazandaran downgraded the most. Cross-efficiency based on revenue revealed that Kohgiluyeh and Boyer-Ahmad, attained the first ranks. Based on the results of crossefficiency of rainfed wheat-producing regions, South Khorasan, Kohgiluyeh and Boyer-Ahmad, and Zanjan consume inputs more optimally. In general, it was revealed that the provinces with higher cultivated areas and production did not have higher efficiency. It appears that in comparison with other provinces, production inputs are not used in these regions optimally. Given the status of these provinces in cultivated areas and production, any plan to increase production requires to seriously consider the optimal use of resources as well as the environmental effects.

Rain simulation is a method widely used in detecting hydrological and erosional processes. Most portable samples are inconvenient and challenging to transport, have high water consumption and energy demand. The objective of this study was to design and test a rainfall simulator characterized by the following innovative features: 1) Easily transported and assembled in the field, thereby allowing the necessary experimental replicates, and 2) Applicability on different slopes. The first calibration step was related to the spatial distribution of rainfall, the stability of the rainfall intensity, and the reproducibility of the rainfall intensities over time (among successive experiments). Next, the drop size distribution (DSD) and the related rainfall characteristics (median volumetric drop diameter D50 and mean kinetic energy per unit area and unit depth) were evaluated by the flour pellet method. A fluorescent tracer method was used to measure the velocity of falling drops. According to the findings, the Christiansen uniformity coefficient (Cu) of the developed rainfall simulator varies from 77-87% for rainfall intensities of 35-75 mmh-1 . The best rainfall distribution was achieved for rainfall intensities of 55 and 75 mmh-1 , with rain droplet sizes ranging from 0.6 to 3.8 mm. The raindrop velocity was also measured by photo-shooting and revealed a velocity rate of 2.7-5.7 ms-1 . The system allows rainfall simulation on the fields and under laboratory conditions. Moreover, using the simulator, erosion, runoff, and sediment production under natural and intact soil conditions can also be examined with the highest possible accuracy.

Ambient sound levels have risen dramatically over recent decades due to sound-generating human activities, so-called anthropogenic sound, in marine and freshwater habitats. In accordance with the World Health Organization (WHO), anthropogenic sound is recognized as a significant global pollutant. Anthropogenic sounds can vary in terms of temporal, spatial and structural patterns. Aquatic animals may use sounds to communicate with individual conspecifics, detect prey and avoid predators in their natural habitats. The Caspian Sea is a brackish-water habitat and the largest lake in the world. There is a diversity of aquatic animals that inhabit the Caspian Sea. However, to our knowledge, soundscapes and the potential effect of anthropogenic sound pollution on aquatic animals of the Caspian Sea has not been investigated. In this paper, we argue that we need to prioritize acoustic studies to understand the soundscape and bioacoustics criteria of the Caspian Sea, and assess the potential impacts of acoustic stimuli on aquatic animals at the individual and community level.

Because of the quantitative and qualitative problems of Daily Suspended Sediment Load (SSL) data with direct measurement, it is important to use methods for predicting it in watersheds. In this research, two methods consisting of the artificial neural network (ANN) and Genetic Expression Programming (GEP) were used to predict SSL. The studied area was a watershed in north of Iran. Input data included instantaneous flow discharge (Q), average daily flow discharge (Qi), average daily precipitation (Pi) and the output was SSL. A clustering method was used to homogenize data for the self-organizing map (SOM) method and then, all data were divided into three groups including 70, 15 and 15% for training, validating and testing, respectively. Also, the gamma test method was used to determine the best combination of input variables. In all combinations of inputs to the ANN and GEP models, the ANN model with tangent sigmoid activation function and input variables combination including Q, Qi, Qi-2, Qi-3, Pi, Pi-2, Pi-3 was the best for estimating SSL in the area with a root mean square error of 1995.3 (ton day -1 ) and the Nash-Sutcliff efficiency of 0.96. In general, the results of this study showed that intelligent models are capable of accurately estimating the SSL value. Also, using SOM preprocessing techniques and gamma tests increased the generalization power of the models. We also found that choosing the most influential variables and their best combination increased the modeling power and accuracy of SSL estimation, respectively.

In recent years, the issue of heavy metal contaminated soils is one of the biggest environmental problems. The Environmental Protection Agency (EPA) identifies Nickel and Lead as two of the most important environmental pollutants. The phytoremediation of metal-contaminated soils is a low cost method for soil remediation. This study was conducted to investigate the status of soil contamination in Gachsaran oil refinery using the pollution coefficients, the degree of contamination (DC), and the modified degree of contamination (MCD) indices. In order to evaluate the efficacy of alfalfa for phytoremediation of the Lead and Nickel from the oil-contaminated soil, transfer coefficients, bio concentration, and bioaccumulation factors were used. Four areas ranging from 0 to 500 meters, 500-1000 meters, 1000-1500 meters, and 1500-2000 meters were selected from the polluted site. Then, five soil samples were collected from each area. The inductively coupled plasma‐optical emission spectroscopy (ICP-OES) was used to determine heavy metals. The analysis of the environmental indicators of the studied area showed a significant degree of contamination for Nickel and Lead. Due to the higher biostatic and bioaccumulation factors of Nickel (0.3 and 0.31, respectively) compared to those of Lead (0.09 and 0.11, respectively), alfalfa plant showed greater ability in refining Nickel contaminant both in aerial and root organs. Conclusion IN sum, the findings indicated higher ability of alfalfa plant in the phytoremediation of Nickel than Lead in oil-contaminated soil. Finally, the alfalfa is suggested for purifying other contaminants.

Biodiversity conservation and ecosystem services provision are of the main ecosystem management objectives. Despite the enormous importance of cultural services, they are often ignored in ecosystem management plans due to the difficulty in quantifying. This study was done to investigate the impact of exclosure on cultural services in semi-arid shrublands. Flowering plants were considered as a proxy for cultural services. The canopy cover and the number of plant species inside and outside the exclosure were recorded in two vegetation types Artemisia aucheri and Artemisia aucheriZygophyllum eurypterum. The results showed that exclosure significantly increased diversity, abundance and richness of plant species. The exclosure also significantly increased the diversity, richness and abundance of flowering species in both vegetation types. A positive relationship was found between diversity indices and flowering species diversity. The results also showed that perennial forbs had a greater role in providing cultural services. It can be concluded that exclosure can promote both plant species diversity and cultural services in semi-arid shrublands.