Sustainable Earth Review
Volume:3 Issue: 4, Oct 2023

Benthic macroinvertebrates are commonly used for assessment of water quality. Usually, these insects in rivers are present, easily collected, not moving much and it is easy to detect kinship. Benthic macroinvertebrates can also show changes in water quality and as sensitive indicators of environmental change are used. Jajrud River originated from the Elburz Mountains in northern Tehran. A sampling of Jajrud River benthic macroinvertebrate organisms from a Surber sampler device with an area of 900 cm2 and mesh size of 250-micron was repeated three times at each station. Physicochemical parameters including Elevation, Depth, Flow Velocity (WatFlow), Water Temperature (WatTem), Turbidity, Total Suspended Solids (TSS), Electrical conductivity (EC), Fecal Coliform, Phosphate, Nitrate, Nitrite, Ammonium, Dissolved oxygen (DO), pH, Chemical Oxygen Demand (COD) Biochemical Oxygen Demand (BOD) were measured. Habitat parameters such as Epifaunal Substrate (EFAC), Embeddedness (Embed), Velocity and Depth Regimes (Vel), sediment deposition (Sedimen), Channel Flow Status (Channelf), Channel Alteration (Channelt), Frequency of Riffles (Freq), Bank Stability (Bankstu), Vegetative Protection (Veg) and Riparian Vegetative Zone Width (RipaVeg) were reviewed. Then according to bioassessment protocols and ratings based on a zero to 20, for relationship between physicochemical and habitat parameters with an abundance of benthos grouping and assessment of water quality, from CANOCO software and principal component analysis (PCA) was used. The results showed that the water quality in the downstream Jajrud is unfavorable and appropriate management measures should be taken to improve the river's water quality.

The concept of 15-minute city (FMC) represents an urban planning and policy paradigm that seeks to focus the attention on the neighborhood as a place rather than a spatial and functional planning unit. The main premise of this concept is that urban services and amenities should be accessible within 15 minutes of walking or cycling from the residence. The principles of urban planning that enable the realization of the FMC include planning in mixed-use neighborhood units, proximity-based planning, transportation planning, citizen participation in planning and innovation, and smart planning. This innovative approach provides important findings and recommendations to the principles of urban planning of FMC, along with the issues of proximity-based planning, using the land and urban form, urban governance, and citizen participation. The aim of this study was examining the concept, characteristics and theoretical literature as well as the emerging themes for urban planning and policy making in the FMC. The FMC and its principles can help achieve sustainable development in environmental, social, and economic dimensions. The greater accessibility, reduce vehicle dependency, improve air quality, equitable planning decision, better health and well-being are the advantages FMC. However, the FMC can be criticized for its physical determination, feasibility in areas with low population density, difficulty in implementation, financing, not taking into account the different geographical features of cities, the conditions of not paying attention to the needs of different social groups, biodiversity, energy efficiency, and culture and heritage.

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

Geological studies rely heavily on facies classification since it offers vital information for reservoir characterization and hydrocarbon exploitation. Because facies are inherently complex and heterogeneous, traditional approaches frequently struggle to categorize them effectively. Artificial Neural Networks (ANNs) have shown great promise in recent years for improving the efficiency and accuracy of facies classification. This review assesses ANN applications for facies classification in geological investigations critically and it begins by delineating the essential principles of facies classification and the constraints of traditional methodologies. Then ANNs' theoretical underpinnings and applicability to tasks involving the classification of facies was explored. The different architectures and configurations of ANNs used in geological research were also examined, as well as the benefits and difficulties of their use. The several ANNs architectures and configurations used in geological research are examined, as well as the benefits and difficulties of putting them into practice. In order to enhance the efficacy of ANNs in facies classification, the paper also addresses the integration of auxiliary data sources, such as well logs, seismic, and core data. Furthermore, the application of new developments in Deep Learning methods, including Recurrent Neural Networks (RNNs) and Convolutional Neural Networks (CNNs), to facies classification were discussed. To guarantee solid and trustworthy classification results, factors including feature selection, data preparation, and model assessment metrics were also taken into account. Lastly, the review highlights possible avenues for future research and breakthroughs in leveraging ANNs for enhanced facies classification, precision and effectiveness in geological studies.

The paper investigates the lift-to-drag coefficient ratio (CL/CD) efficiency of three airfoils, namely E387, RG15, and SD6060. The objective is to optimize the airfoils for maximum CL/CD efficiency and evaluate them using XFOIL software. The study focuses on these airfoils' performance at different Reynolds numbers (Re) from 500,000 to 1,000,000, with varying thickness-to-camber ratio percentages (t/c%). The results indicate that the E387-Opt airfoil improved the maximum CL/CD by 18.92% at Re 500,000, 23.77% at Re 600,000, 27.14% at Re 700,000, 32.44% at Re 800,000, 32.93% at Re 900,000, and 38.46% at Re 1,000,000. The RG15-Opt airfoil also demonstrated impressive performance, with a maximum CL/CD increase of 34.38% at Re 500,000, 36.75% at Re 600,000, 38.54% at Re 700,000, 41.58% at Re 800,000, 45.57% at Re 900,000, and 51.30% at Re 1,000,000. Finally, the SD6060-Opt airfoil showed even better results, with a maximum CL/CD increase of 37.07% at Re 500,000, 38.16% at Re 600,000, 42.44% at Re 700,000, 48.99% at Re 800,000, 53.10% at Re 900,000, and 56.91% at Re 1,000,000.

In recent decades, scientists have made extensive efforts to find an alternative material in concrete in order to stop the emission of gas CO2 in the cement production process. Geopolymers are materials with aluminosilicate properties that play the role of cement in concrete in the presence of water. Past research has proven that geopolymer concretes (GPC) do not have CO2 pollution due to the absence of cement in their mixing design, so they are environmentally and nature friendly. In this laboratory research, a mixed design of ordinary portland cement concrete (OPCC) containing Portland cement with a grade of 500 kg/m3 and a mixed design of GPC based on granulated blast furnace slag (GBFS)was made. In order to check the mechanical properties and durability, tests of compressive strength and weight loss of concrete were carried out under the temperature of 21 and 600 °C at the age of 90 days. Applying high heat to concrete samples caused a decrease in the compressive strength test results in OPCC and GPC by 42.31 and 14.9 percent, respectively, and in the weight loss test by 0.0067, respectively. And 0.0064 percent weight loss was obtained in OPCC and GPC. In the compressive strength test under 21 and 600 °C, GPC showed 11.41 and 64.35% superiority over OPCC. The results obtained from the scanning electron microscope imaging analysis of concrete were in harmony and overlapping with the results of other tests in this research.