In the fight against global warming, various options for reducing CO2 emissions are being implemented on campus. Furthermore, the management of campus sustainability at the Universitas Negeri Semarang (UNNES), Central Java, Indonesia, should be supported by accurate forecasts of electrical energy consumption. Therefore, this research aims to develop a predictive model to forecast the consumption of electrical energy in reducing CO2 emissions and to determine the factors triggering the increase. The prediction model is developed using Back Propagation Neural Network Artificial (BP-ANN) architecture. Furthermore, the data on the occupancy of lecturers and education staff as well as on students was obtained from the University's staffing and student affairs bureau. Climatic data such as temperature, humidity, wind speed, the duration of irradiation, and the average intensity of solar radiation were obtained per month from the Meteorology, Climatology, and Geophysics Agency of Semarang, Central Java for the 2013-2019 period as input data. The results of the empirical analysis showed an increase in electrical energy consumption from 2020 to 2025. In March, the consumption decreased but increased from April to June and decreased in July. It then increased until November and December, and it decreased every year. The results of CO2 emissions calculated by considering the emission factors from Indonesia's RUPTL-PLN in 2020-2025 showed an increase in electrical energy consumption and the ecological consequences affecting the campus area. Furthermore, the main factors causing the high consumption of electrical energy are the occupancy rate, lecturers, students, and campus employees, as well as local climate influences such as temperature, humidity, wind speed, duration of solar radiation, and intensity of solar radiation. Therefore, developing guidelines to reduce power consumption on campus should be a priority

Plankton and other microscopic colloids are tiny particles that are suspended in water and cause turbidity, which causes the water to seem murky or opaque. These particles are too unstable and light to settle or be naturally eliminated. These details contribute to water turbidity and pose some stability. During the process of purifying raw water, all water treatment Plants (WTPs) produce waste/residue known as water treatment sludge (WTS). The majority of the sludge’s chemical components include silica, alumina, ferric oxide, lime, and many heavy metals. The surface water treatment technique included coagulation, flocculation, sedimentation, and filtration to remove colloidal and suspended particles from raw water. The sludge obtained from the WTP located at Kekri (Rajasthan), India is being investigated for its physical and chemical properties. About 60% of the sand contained in the sludge is found in the 155-60 grain size range. Additionally, nutrient reduction of soil due to contamination and runoff can be minimized or rounded out by wastewater treatment or the removal of heavy metals from water solutions. To develop water-safe and appealing sludge management solutions, the efficiency of aluminum sulfate and poly aluminum chloride was assessed at different coagulant doses in the study. To make water safe and appealing for human consumption, numerous purification procedures are employed from a variety of sources. Sludge bricks are acceptable to high temperatures in the furnace and have better compressive strength than clay bricks.

Engaged for many years in a strategy to control climate change, Morocco is committed to leverage on sustainable development as a new development model and as a true project for society. This commitment resulted in implementing several reforms targeting the consolidation of a developed economy, improving social conditions, and accelerating positive environmental changes. The public administration developed the Administration Exemplarity Pact (AEP) as a concrete action to lead by example in implementing the National Strategy for Sustainable Development. Developed in accordance with the main stake of the National Strategy of Sustainable Development, its goal is to promote sustainable development governance in our country through several strategic focus areas. This document presents the experience of a Moroccan administration that has implemented the guidelines described in the AEP. The approach and results are detailed and could be used as an example for other Moroccan companies. The first step of the methodology consists of a diagnostic phase to establish the current situation. The second step is related to the strategy to define the approach’s main orientations and the action plan. These key steps allow us to identify areas of improvement and build a roadmap adapted to the current context and constraints. One of the best practices for this approach is to define the main orientations to act by positive contagion on the ecosystem. In conclusion, the AEP axes deployed in a dynamic improvement logic give convincing results. By acting with partners (subcontractors and suppliers), the Moroccan administration can act on the whole value chain and induce an essential change in the Moroccan economic fabric.

Environmental pollution is a serious concern nowadays with its disastrous impact on living organisms. In several types of pollution, Air pollution takes on a crucial role by directly affecting the respiratory system and causing fatal diseases in humans. Air pollution is a mixture of gaseous and particulate matter interweaved by different sources and emanating into the atmosphere. In particular, particle pollutants are critical in growing air pollution in India’s main cities. Forecasting the particulate matter could mitigate the complications caused by it. The employment of a model to predict future values based on previously observed values is known as time series forecasting. In this paper, the PM2.5 pollutant emission data recorded at the Kodungaiyur region of Chennai city were forecasted using three-time series models. The standard ARIMA model is compared with the deep learning-based LSTM model and Facebook’s developed Prophet algorithm. This comparison helps to identify an appropriate forecasting model for PM2.5 pollutant emission. The Root Mean Squared Error (RMSE) acquired from experimental findings is used to compare model performances.

Characterization and treatment of greywater are major environmental issues in most nations of the world. The research aims to characterize and evaluate recycling technologies using an analytical hierarchical process for Afe Babalola University Ado-Ekiti (ABUAD) community. A survey was conducted around ABUAD to determine the number of functioning boreholes and active water systems in the area, the total population of students was derived from the total head count of each room and student in each hostel, and a population projection for the next 3 years was conducted to determine the rate at which the student body will grow in terms of future water demands, and daily water volume and questionnaires were used to collect data. Before developing the small-scale model of the greywater filter system (consisting of activated carbon, shaft sand, pebbles, cotton fiber, and gravel), water grey samples were gathered from several ABUAD locations to evaluate the pollution level of each greywater source. A total of 88 students (43 males and 45 females) replied to the survey, revealing their high need for clean water and their dissatisfaction with the water supply in their respective hostels. The water quality tests conducted in the various locations of ABUAD reveal high levels of total dissolved solids (TDS) and turbidity, particularly in the girl’s hostels, and the water was discovered to be predominantly alkaline. After passing a sample of greywater through the small-scale greywater filtering device, it was determined to be effective, since it produced clear, reusable water and a greywater filtration system in ABUAD will yield favorable outcomes.

The review paper comprised the impact of geographical and environmental factors on polyploidy and vice versa. The review covers different effects of geographical factors, like spatial isolation, altitude, and local climate on polyploidy, and the behavior of polyploid(s) in abiotic factors, such as temperature and light with a few examples of northwest Himalayas. The paper concludes that polyploid plants behave differently in environmental conditions, as polyploids are more prominent in higher altitudes, colder environments, and nutrient-rich soil than diploid progenitors, but have a mixed distribution in different geographical conditions. Further, polyploidy is more common among perennials than annuals, while niche differentiation depends more on the local environment. The virtual case study results from North and North Western India have been shown with the help of ArcGIS online software. The scrutiny of spatial distribution on maps highlights the fact that polyploidy is still a complex research puzzle with interesting perspectives.

Goa is a coastal State located on the west coast of India, known for its pristine sandy beaches and environment. Ministry of Environment and Forest implemented Coastal Regulation Zone Notification in 1991 for monitoring the coastal zones for unplanned developmental activities but has been just for name-sake purposes (Mascarenhas 1999, Agarwal 2019). The regulation has been changed in recent years thereby making the coastal and the riverine ecosystem more vulnerable to human interference. In the name of development, various hap-hazardous, unplanned activities have taken place which is degrading the coastal and riverine environment, especially mangroves. This paper studies the vulnerability of mangroves to the changing regulations with respect to 1991 and the 2018 CRZ notifications considering the land use land cover changes in the regulated zones of Mandovi and Zuari rivers. Spatial analysis techniques and software such as Arc GIS 10.3, and ERDAS IMAGINE 2014 have been used for analysis and results. The findings from the study can be effectively implemented in monitoring the regulated zones and protecting mangroves efficiently.

Wind and temperature measurements at an oil refinery site located southeast of Baghdad city at two levels, 15 and 30 m, are presented. Three schemes are used to determine different stability classifications: Monin-Obukhov length, gradient, and bulk Richardson numbers. Meanwhile, vertical changes in air temperature and wind shear are also computed. There were lapse rate and inversion cases during the nights and days while favorable wind shear was dominant. The variation of stability in each scheme is large, covering the entire range of stability for a given class. The results of stability schemes are compared to each other. The results show that the schemes based on gradient and bulk Richardson numbers reasonably compare them.

The requirement for a renewable and environmentally gracious alternative resource of energy has grown in recent years as a result of increased knowledge of the negative impacts of petroleum-based fuels on the environment and the regular rise in crude oil prices. Biodiesel has been proven to be the ideal replacement for diesel because of its unique qualities, such as a huge decrease in greenhouse gas emissions, nonparticulate matter pollutants, non-sulfur emissions, less toxicity, and degradability. This article examines the pre-treatment stage, the physiological and chemical features of WCO, transesterification, esterification, and the manufacturing of biofuel from waste-cooked oil using several techniques and catalyst types. The elements that influence the stated process parameters are investigated, with a particular focus on the methanol to oil ratio (molar ratio), time of reaction, the temperature of the reaction, catalyst percentage, and yield of biodiesel. After the production of biodiesel, we can optimize the process parameters, for example, methanol to oil ratio, the temperature of the reaction, duration of reaction, and catalyst percentage, and also optimize the yield of biofuel generation with the CCD design of the Response surface methodology (RSM) algorithm using Design Expert software.

The availability of land for proper waste disposal is one of the most important and emerging potential challenges in most big cities. Although some attempts are being made to minimize and recover garbage, landfill disposal continues to be the dominant method of waste disposal. An improper landfill site can negatively impact the environment, the economy, and the environment. Thus, it should be carefully chosen, taking into consideration both rules and standards from other sources. To examine all aspects of this study, an integration of the “Geographic Information System (GIS)” and the “Analytic Hierarchy Process (AHP)” was incorporated for land-fill site selection. Various parameters were examined to make decisions about landfill site selection. These parameters included slope, elevation, soil texture, LULC, surface water, groundwater table, road network, historical areas, and residential areas. An analytic-hierarchy process was used to determine the relative importance of each parameter, and a final site suitability map was created. With an equal interval classification method, the final index model was categorized into four categories, which included “unsuitable”, “less suitable”, “moderately suitable” and “suitable”. As a result, 30.28% of the study area was less suitable, 28.49% was moderately suitable, 12.39% was suitable, and 28.84% of the study area was unsuitable for landfilling.