Natural disasters are natural activities that can disrupt various aspects. Natural disasters cannot be avoided, but the impact of natural disasters can be minimized through mitigation. This can be known through event history to determine an area’s vulnerability to natural disasters. This research aims to determine regional natural disaster vulnerability by calculating the natural disaster index. The data used in this research refers to data from the 2021 PODES data collection, which contains the intensity of natural disasters and casualties according to the type of natural disaster in Indonesia in 2020. The method used for the calculation is the weighted index method. The results of this research produced 5 clusters based on the level of natural disaster vulnerability according to sub-district/village. The top five provinces in Indonesia that have the highest natural disaster-prone areas are Aceh, North Sumatra, West Java, East Java, and Central Sulawesi. Research shows that sub-districts/villages in Indonesia are known according to their level of vulnerability to natural disasters. These results can be used as a reference for the government to carry out mitigation so that accelerated development in the local area can continue.

The study was conducted within the Protected Area of the Tumauini Watershed Natural Park located in the municipality of Tumauini province of Isabela along the western part of the Northern Sierra Madre Natural Park. The protected areas in the Philippines cover 39% of the total forest cover. Protection and conservation of protected areas is significant due to the increasing habitat loss and biodiversity loss. The main objective of the study is to assess the tree diversity of the park using the modified belt-transect method adopted by the Department of Environment and Natural Resources (DENR). The transect line has a distance of 2 kilometers and a total of 9 stations. A Nested Quadrat was established along the transect line for tree identification. Results of the assessment show that the park has a species richness of 34 tree species in eight families and 26 genera. Species diversity indicates low (2.4) to very low (1.12) based on the Shannon-Weiner Diversity Index despite the high number of individuals found in the watershed area. The low diversity of the watershed is affected by the rampant anthropogenic activities and naturally-induced hazards occurring in the protected area. Shorea polysmerma is the most dominant and the most important species, with an Importance Value index of 38.78. Three species of trees were recorded as generalists in the area such as Calophyllum blancoi, Shorea palosapis, and Ficus sp.

Recently, Extended Producer Responsibility (EPR) schemes have been considered as potential policies for solid waste management and many countries have applied them. Researchers, authorities, and producers need a comprehensive and up-to-date understanding of EPR. Therefore, this literature review aims to review the current research status of EPR implementation on packaging, to highlight actual experiences conducting EPR, and to find research gaps. Results indicate that during the last 5 years, there has been an increase in the amount of research on EPR in packaging and that packaging waste recycling under this scheme is the most considered activity. Additionally, the primary metrics used to assess the efficacy of EPRs are recycling and reducing packaging waste. According to the lessons learned, applying EPR to packaging should take stakeholder engagement, policy design, transparency, and incentive strategy into account. Additionally, knowing the economic effectiveness problems small- and medium-sized packaging companies face, the effectiveness of EPR methods on various materials and geographical areas, and the efficacy of monitoring methods are the main areas that need to be researched.

Bioremediation is an important technique to remove heavy metals from wastewater. The current research aimed to use Azospirillum bacteria in removing cadmium ions from wastewater. The source of Azospirillum bacteria was the soil of Al-Mishkhab in Al-Najaf province, Iraq (rice fields), while the source of wastewater was taken from the Al-Rustamia wastewater treatment plant, in Baghdad in October 2020. All the experiments were carried out in Soil and Water Research Center, Ministry of Science and Technology. After collecting the soil, the microorganisms were isolated through the Immunomagnetic beads (IMB) process and were incubated on a certain synthesized medium. The concentration of cadmium ion was determined through the Absorption Spectrophotometer (AAS) technique. The Azospirillum colonies were identified and characterized as white colonies while the concentration of cadmium ion ranged from 0.03-1.6 mg/L and applying the microorganism on the wastewater will decrease the concentration up to 99.9% in a process called biosorption. Treatment time was also studied for 24, 48, 72, and 168 hours. The statistical analysis shows that increasing time will enhance the removal of cadmium. Cadmium is one of the heavy metals responsible for soil contamination; bacteria play a crucial role in bioremediation, demonstrating stability in decomposing various compounds and materials. Azospirillum is employed for soil decontamination purposes; increasing incubation time will enhance the removal of the trace element; also further investigate the effect of other factors such as temperature, pH, and the effect of using other microorganisms.

The objective of this research was to determine an environmental management model that integrates social, economic, geographic, and community aspects to promote the growth of social capital among residents in the periphery area of Banjarmasin City. The analysis was conducted with 150 respondents selected through purposive sampling based on specific criteria. A quantitative descriptive method was adopted, and the structural model analysis was conducted using SmartPLS 3.0 software. The structural model analysis consisted of (a) formulation of the structural model theory, (b) analysis of the outer model, (c) analysis of the inner model, and (d) hypothesis testing. The field data analysis and calculations using SmartPLS 3.0 software showed an R² value of 0.855. The value showed that the economic, social, geographic, and community indicators could indeed contribute to the development of social capital, including norms, culture, perceptions, and behaviors among residents in the periphery area. Approximately 85.5% of the variation could be explained, while the remaining 14.5% might be influenced by other factors. In terms of the development of social capital, environmental management model was shown by (1) economic, with a T-statistic value of 2.627 and a P-value of 0.009, (2) geographic, with a T-statistic value of 1.982 and a P-value of 0.048, (3) community, with a T-statistic value of 4.211 and a P-value of 0.000, and (4) social with a T-statistic value of 2.057 and a P-value of 0.040. Since the T-statistic values exceeded the T-table threshold of 1.96, and the P-values were less than the significance level of 0.05, it could be concluded that economic, geographic, community, and social, environmental management in the periphery area served as valuable indicators for fostering the sustainable development of social capital among residents of Banjarmasin City.

Plastic pollution is a global concern affecting water, soil, and air quality. Urgent action is needed to address this issue. This study aims to identify factors influencing the use of biodegradable plastic to reduce its negative impacts. Data were collected from 269 households-129 in Punggawan and 140 in Mojosongo, Surakarta, and analyzed using multiple regression analysis to study the determinants of WTP (Willingness to Pay) for biodegradable plastic with STATA software. The results show that the average WTP for biodegradable plastic is IDR 2,214. Most people in Surakarta are already environmentally conscious. Age, knowledge, occupation, interaction of sex and location, education, and marital status influence WTP for biodegradable plastic. It is hoped that the implications of the research will be used as a recommendation for government policies to reduce the amount of plastic waste generation, which is a danger to human beings and the environment.

The port is a place for ships as sea transportation to dock. The port, as a place of entry and exit for goods or passengers from various regions, places, and environments, encourages the potential for disease transmission to a new environment. Pathogens present in the environment can directly contact the human body through air, touch, and transmission through food around areas with high mobilization. Therefore, this study aims to look at the results of hygiene observations and laboratory testing related to food, drinking water, and air samples at Galala Port, Ambon City. This study used descriptive research with a cross-sectional research design. From all parameter examination results, several examination results do not meet the standards such as food microbiology examination results (E. coli bacteria > 3.6MPN/gr), sanitation (walls and floors are not watertight), the presence of mosquito larvae (seven Aedes albopictus mosquito larvae), drinking water microbiology (total Coliforms 64 CFU.100 mL-1), and clean water microbiology (E. coli > 250 CFU. 100 mL-1 and total Coliforms 8 CFU.100 mL-1). Therefore, it can be concluded that the inspection of restaurants carried out at Galala port, Ambon City, is not appropriate and does not meet the standards according to the Minister of Health Decree number 942 of 2003.

Water quality prediction plays an important role in environmental monitoring and ecosystem sustainability in the Amazon. Therefore, this review focuses on determining the advances in the scientific production of artificial intelligence in water quality prediction in the Amazon, as well as the limitations and perspectives compared to water quality indexes (WQI). In this sense, Boolean operators were applied, using the following terms: “artificial intelligence”, “machine learning”, “water quality,” and “Amazonia” The databases were Scopus, web of Science, Springer, and IEEE. In this study, 14 scientific articles published during the period 2000-2024 focused on Amazonian countries were evaluated. Although in the Amazon low scientific production was evidenced and is led by Brazil, the highest scientific growth was for 2021, and 93% belongs to the Scopus database, with a compound annual rate of 12.16%. The IA is characterized by using data from governmental institutions and is only limited to parameters such as Total Suspended Solids (TSS), Total Organic Carbon, Turbidity, and Chlorophyll, using satellite imaging techniques, and the most commonly used algorithm was the Clustering Algorithms. In this context, AI applications are still very low in Amazonian countries compared to other European countries. Its limitations are in the accuracy and the limited amount of physicochemical and microbiological data used for predictions. However, AI is a tool that will replace the water quality indexes used manually.

Vegetable waste, particularly cabbage waste (CW), is a valuable raw material for various applications, including bioenergy production, owing to its high lignocellulosic content. However, the potential of lignin in biomass conversion remains largely untapped. This study is significant as it aims to optimize the pretreatment of CW biomass using different chemical reagents and concentrations (sulphuric acid, acetic acid, sodium hydroxide, potassium hydroxide, and sodium chloride) at 12 and 24 h for 50, 75, and 100°C. In this study, a novel pretreatment approach was introduced with 2% NaCl at 50°C for 12 h for CW biomass. At this optimized condition, 2% NaCl led to 28% delignification for CW biomass. The study examined the impact of pretreatment efficacy on biomass characterization using SEM, XRD, and FTIR analytical techniques. Results showed that 2% NaCl pretreatment significantly improved digestibility, increased surface area and porosity, altered the crystallinity index, and confirmed delignification through shifts in peaks and intensity changes. Furthermore, reduced hemicellulose and reduced lignin were noted in comparison to untreated biomass. This reassures us of the effectiveness of the pretreatment method. This promising result underscores the feasibility, economics, sustainability, and environmental friendliness of this pretreatment method. The method not only offers a cost-effective solution but also aligns with the principles of sustainability and environmental protection, thereby reassuring the researchers about its potential for various industrial applications.

At a global level, energy production is predominantly based on the use of conventional resources such as oil, coal, and gasoline; this dependence has led to adverse effects such as climate change and detrimental impacts on human health; consequently, green hydrogen emerges as a renewable energy source. This work develops and analyses the parameters of a portable hybrid system to produce green hydrogen on a small scale in a more efficient way, allowing it to be placed in rural areas to be used as an ecological fuel source. The hybrid system is divided into two stages; for energy production, a microhydraulic system was developed based on an Archimedes screw turbine, which is made up of a mechanical and electrical design, where the electricity produced is stored in a continuous energy source, which supplies the electric current to the electrodes in the alkaline electrolysis process; where a reaction occurs in the water resource to produce green hydrogen and oxygen. It was demonstrated that the turbine, when presenting a greater wetted area and slope of fall, produces a higher electrical potential, while in the electrolysis process to produce green hydrogen and oxygen, it was determined that the appropriate electrolyte to use is potassium hydroxide at 20% because it has greater electrical conductivity unlike sodium chloride and sodium hydroxide; evidencing the most efficient parameters to implement the hybrid system in rural areas to replace the conventional fuel that is used in cooking food.