Global Journal of Environmental Science and Management
Volume:10 Issue: 1, Winter 2024

Rapid urbanization negatively affects the hydrologic cycle and makes cities vulnerable to disastrous flash floods. It can additionally cause erosion and water pollution in natural ecosystems. Global climate changes have exacerbated such issues, further upsetting hydrologic patterns. Therefore, many regions have considered the rain garden as green infrastructure, which can help mitigate urban runoff. However, design guidelines and the means of assessing rain garden cost effectiveness in the Global South are limited. Furthermore, as many countries in the Global South experience a tropical climate, design guidelines developed in the temperate Global North may not be directly transferable. The need for more information on design and cost effectiveness can make designers and decision makers hesitate to implement such a new strategy. The main objective of the present study is to create a design approach and simultaneously specify the cost of the infiltration rate of the rain garden in urban areas.

This study focuses on the ability of rain garden design to determine accurately the cost of materials used for construction. Sand and gravel are used in different sand ratios in the filter media layer, namely 1:1, 1:2, 1:3, and 1:4. The storage layer uses gravel only and has only one design. The aim is to determine the change in infiltration rate with an increase in the amount of sand. Knowing the amount of sand can determine the cost per infiltration rate.

The results showed that the most efficient design was a rain garden with a soil:sand ratio of 1:4, which increased the infiltration rate per cost by 2.00 millimeters per hour per United States Dollar per square meter. The lowest efficiency option was a soil:sand ratio of 1:1, which increased the infiltration rate per cost by 1.33 millimeters per hour per United States Dollar per square meter.

This study will serve as a guide for designers to design a rain garden area according to the needs of the area, having determined the construction cost per infiltration rate. However, spatial requirements, construction costs, and social factors may influence future decisions on rain garden design and must be studied further.

To improve photocatalytic degradation perfomance, photocatalyst particles with a larger surface area preferred. The effectiveness of titanium dioxide as a photocatalyst depends on the synthesis method used. The method affect the particle size, crystallinity and phase composition of the produced catalyst. This study aims to develop a green synthesis process of nano- titanium dioxide photocatalysts for the advanced treatment of palm oil mill effluent.

The green synthesis of titanium dioxide nanoparticles used de Man-Rogosa-Sharpe broth media containing Lactobacillus bulgaricus culture and titanium oxyhydroxide metal oxide. The factors investigated were the molarity of titanium oxyhydroxide (0.025 molar; 0.035 molar and 0.045 molar) and temperature (40; 50 and 60 degrees Celsius). The synthesized photocatalyst was characterized using a particle size analyzer to determine the particle size. The produced photocatalyst with a nanoparticle size range of 1-100 nanometer was further characterized using scanning electron microscopy-energy dispersive X-ray and X-ray diffraction. The photocatalyst was tested for advanced treatment of palm oil mill secondary effluent. The factors investigated in this test included the irradiation time and titanium dioxide photocatalyst dosage. The treatment performance was evaluated in terms of effluent quality and pollutant elimination efficiency.

Nano titanium dioxide photocatalysts have been synthesized through titanium oxyhydroxide metal oxide biologically using Lactobacillus bulgaricus. The synthesis process at a temperature of 60 degrees Celsius and a 0.025 molar metal oxide solution produced a titanium dioxide photocatalyst with a size of 33.28 nanometer. The content of titanium and oxygen constituents in the photocatalyst was confirmed to be 39.06 percent and 47.95 percent respectively, with 67.6 percent titanium dioxide crystallinity in a theta degree of 25.4. This indicates that the green synthesis has produced an anatase diffraction nano titanium dioxide photocatalyst. Testing the titanium dioxide photocatalyst to treat palm oil mill secondary effluent yielded in elimination efficiency of 16.16-27.27 percent for chemical oxygen demand and 11.05-21.95 percent for biological oxygen demand. Phenol, which is toxic and difficult to degrade biologically, could eliminated significantly (up to 81.12 percent) using a photocatalyst dose of 1 gram per liter at a time irradiation of 2.5 hour.

The biological synthesis of nano titanium dioxide photocatalysts is affected by temperatures and metal oxide concentrations. The photocatalytic process for advanced treatment of palm oil mill secondary effluent shows that this synthesis process effectively eliminates phenols. Some compounds such as lignin, amino acids, and pectin are not significantly mineralized using this process.

Industrial wastewater usually contains metal ions which are hazardous to human and aquatic organisms. Nowadays, the application of inexpensive biomaterials in adsorptive removal of metal ions, such as plant biomass, has been widely considered. In this study, the efficiency of Eucalyptus globulus fruit biomass for biological adsorption of cadmium ions from aquatic environments has been evaluated.

After drying, the collected biosorbent was ground and powdered. The dried biomass, after screening with particle size of less than 45 micrometers, was used in all experiments. The effects of operating factors, such as biosorbent to cadmium ratio, pH value of the solution and residence time of biomass and metal, on the amount of analyte adsorption were evaluated by response surface methodology. The optimum conditions for maximum metal uptake by Eucalyptus globulus fruit biomass were also evaluated using the Box-Behnken Design model. Kinetic studies were statistically described to investigate the metal adsorption process.

Validation experiments showed the accuracy of the model proposed for determining the optimum conditions for the cadmium biosorption process. Based on the experimental data, the values of coefficient of determination, adjusted coefficient and predicted coefficient used in the model were determined as 0.9948, 0.9855 and 0.9245, respectively. Using the model, the maximum cadmium ion adsorption by biomass was obtained at 93.65 percent, biosorbent-to-metal ratio of 9:1, pH value of 6, and contact time of 80 minutes.

In the present study, the Eucalyptus globulus fruit biomass, under optimal operating conditions, proved to be an efficient sorbent for cadmium uptake from aqueous environments. The results from the experimental data of the adsorption studies were consistent with pseudo-second-order kinetics (maximum capacity of 128.2 milligram per gram), indicating that the chemical adsorption of cadmium on the used biomass occurring in monolayers.

To address the potential harm caused by the intensive use of pesticides in pest control in agriculture, there is a need for accurate and efficient methods to detect and monitor pesticide residues. Therefore, this study aimed to develop a biosensor that can detect organophosphate pesticides highly toxic to humans and the environment. 

Biosensor organophosphate pesticides using a single film containing acetylcholinesterase/choline oxidase have been designed using silver-based plasmonic nanoparticles as a colorimetric indicator. In the presence of acetylcholinesterase, acetylcholine is hydrolyzed to choline and acetic acid, then choline oxidase catalyzes the oxidation of choline to hydrogen peroxide and betaine. Hydrogen peroxide reacts with the silver nanoparticles, and the discoloration of the brown solution occurs due to the oxidation of silver+.

As a biosensor indicator, silver nanoparticles were extremely accurate, sensitive, and stable over a long period of storage. Transmission Electron Microscope images confirmed the reduction in size of nanoparticles from 16.82 ± 4.36 to 9.63 ± 2.29 nanometers. The analyte profenofos, one of the organophosphate pesticides, inhibits the activity of acetylcholinesterase, thereby reducing the concentration decrease of silver nanoparticles by releasing less hydrogen peroxide. Optimum conditions for biosensors were achieved with a potential of Hydrogen of 7, buffer, and acetylcholinesterase concentrations of 7 and 70 millimolar, respectively, with an incubation time of 5 minutes. Biosensor response showed a linear range at profenofos concentrations of 0.05-2.00 milligrams per liter, with limits of detection and quantization of 0.04 and 0.13 milligrams/liter, respectively. Biosensor also has excellent sensitivity, reproducibility, and stability, with a Relative Standard Deviation of 2.5 percent and a stable response of up to 4 months. Subsequently, using a biosensor in the chilli as a sample resulted in a profonefos level of 0.04 milligrams per liter, making it safe for consumption.   

Biosensor measurement outcome aligned with the gas chromatography-mass spectrometry result, which is the accepted standard method for detecting profenofos. Additionally, the proposed biosensor offers several advantages such as ease of use, fast, low-cost, and on-site analysis. Hence, this method is suitable for monitoring and controlling pesticide residues, particularly organophosphate, in agricultural products and the environment.

Soil is an essential abiotic component serving as a habitat for numerous organisms, including cellulolytic bacteria commonly found in mangrove ecosystems. This bacteria could produce active enzymes needed to improve environmental quality by accelerating the organic matter decomposition. The unique mangrove environment may contain new types of cellulolytic bacteria with new characteristics. Despite several mangrove areas being explored as sources of cellulolytic bacteria, there is currently unexplored data on its diversity in Aceh Province, Indonesia. Accordingly, it is necessary to analyze the molecular biological approach, namely the 16 svedberg ribosomal ribonucleic acid gene, to identify the diversity of cellulolytic bacteria and analyze the phylogenetic relationships between them.

Bacteria isolates were collected from mangrove soil at six research locations with three replications. A purposive sampling method was applied to determine the research location. Isolates from soil samples were streaked and purified in carboxymethyl cellulose as selective media for cellulolytic bacteria. Molecular identification adopted 16 svedberg ribosomal ribonucleic acid gene sequencing, and the sequencing data were matched with GenBank data. Phylogenetic analysis and genetic distance between species were evaluated using molecular evolutionary genetics analysis.

Thirteen isolates were sequenced, and nine species of cellulolytic bacteria dominated by the Bacillus genus were identified. These species exhibited an identity value of 97.77-100 percent when compared to data from GenBank, and B. velezensis was found to have a close relationship with B. amyloliquefaciens at a value of 0.002 percent. Interestingly, the non-rehabilitated mangrove areas had more bacterial species than the rehabilitated ones. Two Bacillus genus had different nucleotide bases, proving they were distinct species.

Nine cellulolytic bacteria species were identified; the two closely interspecies genetic distance related were B. velezensis and B. amyloliquefaciens, whereas the farthest were Bacillus sp1. and Bacillus sp2. Small genetic distances of interspecies indicate a close relationship between species. In comparing the two sampling sites, the non-rehabilitated mangrove contains higher bacterial cellulolytic species than the rehabilitated and Bacillus-dominated site. The findings provide valuable insights into the diversity of cellulolytic bacteria in mangrove ecosystems. The abundance of bacterial species could serve as sources of cellulase enzymes with different characteristics, essential in an environmental aquatic management.

Developing countries'' governments face challenges in municipal solid waste collection, such as rapidly increased volume of waste, physical and social obstacles to collection routes, or funding shortages. The lack of practical evaluation of the waste collection performance is considered a gap in improving the waste collection system in these countries. This study aims to assess the efficiency of current municipal solid waste collection by analyzing operational data that can help enhance the collection.

The geographical information system and the geographical position system data of all active trucks were collected for 14 consecutive days using the digital map. Data on waste volume collected by trucks, waste volume at collection points, and operational time of trucks throughout a working day were collected by survey. The operational efficiency indicators, including the deadhead rate, waste collected per distance unit, stopping time rate, and costs, are estimated to evaluate the effectiveness of municipal solid waste collection services.

The results indicate that solid waste collection efficiency of 1.67 tons/kilometers is low for high-density population areas. The deadheading rate of approximately 20 percent shows that the collection route operated by drivers is meandering and inefficient. Although using small trucks (6–7 tons) for transporting waste to landfills over a long distance is inefficient, small vehicles are used more than large ones. Ineffective utilization of transfer stations could lead to high idle time, accounting for approximately 37.6 percent of a collection trip. The regulated estimating method for transportation costs is not comprehensively developed, which may cause mistakes in choosing collection vehicles for operation and transfer station usage.

The research findings assess the performance and identify ineffective factors that require improvement of waste collection, aiming to enhance the solid waste management system. Waste collection routes of Hoan Kiem district must be designed using empirical data. The distance-based coefficients should be developed for all collection vehicles with different loading capacities to better estimate collection and transportation costs in Hanoi, helping decision-makers utilize the current transfer station more effectively and appropriately in choosing collection vehicles for operation.

The condition of the watershed area, particularly the Tabunio Watershed, is one with priority treatment due to the condition of the land where it is located, which qualifies for the “very high recovery” category with a critical land area of 19,109.89 hectare. Moreover, the diminishing water absorption also results in flooding during the rainy season and drought in the dry season. Environmental damage in the Tabunio Watershed is exacerbated by the existence of traditional gold mining and has become a concern for many parties. With this in mind, the perceived increase in natural disasters, such as floods, landslides, and droughts from year to year requires an evaluation of land degradation in the Tabunio Watershed.

The objective of this study was to monitor and simulate the spatial and temporal aspects of land degradation in the Tabunio Watershed. It was suggested that a complete land degradation index be developed to capture the spatial and temporal aspects of land degradation between the years 2005 and 2020. This index integrates land use land cover, vegetation coverage, soil erosion, and soil moisture content.

The proposed comprehensive land degradation index in this study demonstrated that (a) the land degradation index, which successfully monitored the spatio-temporal aspect of land degradation (kappa coefficient > 0.73 and overall accuracy > 86 percent), is regarded as having high accuracy. (b) In comparison to the individual indices, the land degradation index is capable of revealing land degradation in a more comprehensive manner. (c) land degradation index is readily transferable and applicable to other study areas due to the fact that all of its land degradation indices can be quickly extracted from remotely sensed imagery. (d) land degradation index can be used in a wide variety of contexts, which also accounts for the provision of quantitative predictions with regard to the possibility of land degradation. (e) The rate of land degradation will generally increase from 2005 to 2020, with 2010 being the most extreme year.

The proposed comprehensive land degradation index method is capable of describing the spatial and temporal aspect of land degradation from 2005 to 2020 in the watershed area. Moreover, the proposed approach shows that the level of land degradation from 2005 to 2020 normally increases, recording the extreme years as the 2010s. In addition, in most years, the amount of land degradation was moderate, only few of which had severe or extreme degradation. As a consequence of this, some land degradation management measures ought to be created in advance, guaranteeing the protection of this vital region, which is a source of freshwater. The study provides a substantial understanding of the effect of land degradation on sustainable environment management and development in the watershed.

The innovativeness of this study lies in achieving a comprehensive understanding of the seasonal variations and oceanic characteristics of the Bay of Bengal by addressing the complex interplay of large-scale ocean-atmosphere dynamics. The study aimed to understand the upper ocean characteristics of the Bay of Bengal by analyzing the surface variables such as salinity and temperature using a high-resolution model simulation. To accomplish this, advanced high-resolution numerical simulations were employed, utilizing the coastal and regional ocean community model. This model was crucial for investigating and analyzing the circulation features throughout the entire Bay of Bengal, contributing knowledge and insights about the coastal and regional oceanographic community.

To investigate the temporal variability of the upper ocean in the Bay of Bengal, climatological simulations were performed over eight years using the coastal and regional ocean community model. Including a three-year spin-up phase facilitated the adjustment of the model to initial conditions and the attainment of equilibrium, ensuring its fidelity to real-world conditions. The follow-up analyses and comparisons were performed five years after the spin-up phase. The primary objective of this study was to examine the temporal evolution of the kinetic energy throughout the eight-year simulation. The volume-averaged kinetic energy was computed, revealing a gradual increase throughout the simulation, with particularly pronounced enhancements observed during the monsoon period. A Taylor diagram was used for predicting the model with the other data sets.

The analysis is performed above the surface and sub-surface oceanic layers with prominent dynamics. The temperature and salinity for the surface and sub-surface layers were validated and analyzed for their seasonal variations. The simulations were validated against the existing satellite, reanalysis, and in situ data.

The innovativeness of this study lies in its successful demonstration of the seasonal variability of temperature and salinity in the Bay of Bengal. Through extensive validations, it establishes the model to accurately simulate the climatological surface features of the Bay of Bengal. This study highlights the effectiveness of numerical models when combined with observations, and the data were reanalyzed, showcasing their utility as valuable tools for studying oceanic conditions. The utilization of a Taylor diagram further supports the validation and excellent performance of the model compared to other available datasets. During the simulation, there is a high correlation (0.96) between the evolution of the salinity and temperature values obtained from the model and the corresponding data from the World Ocean Atlas. This indicates a strong agreement between the model-based simulations and the assimilated data, as supported by the notable correlation values of 0.96 for salinity and temperature. These findings reinforce the existing knowledge regarding the influential role of monsoon winds in shaping the circulation patterns within the Bay of Bengal. Overall, this study contributes to advancing our understanding of the ocean dynamics of the region and underscores the importance of considering seasonal variations for comprehensive oceanographic research, coastal management, climate modeling, and future studies in the Bay of Bengal.

Land-based aquaculture operations, at present,  are intensively conducted to meet the ever-growing demand for food consumption. Floating net cages are one of the traditional methods commonly used by Indonesian fishermen for river fish farming. Increased human activities along the Musi River and coastline have resulted in pollution and waste in the river waters and fluctuating water quality. Yet, floating net cage owners still manually assess the water quality. This study aims to develop an early warning system for water quality and create a decision-making program as a reference for fishermen to relocate floating net cages when the river water quality deteriorates.

The device was tested at 39 locations within a radius of approximately 3400 meters, and the distance between locations varied between 55 and 334 meters. The river was divided into three sections: the river coast, the middle section, and the other river coast. Water quality sensors were placed at a depth of 0–20 centimeters from the surface of the Musi River, with measurement durations at each location ranging from 1 to 40 minutes. Direct measurements of the Musi River's water quality were obtained by monitoring the water quality using an internet-based computer application. A decision-making Python program utilizing fuzzy logic was then executed to evaluate the suitability of the river water quality for fish cultivation. The program's input variables comprise water temperature, potential of hydrogen, and dissolved oxygen sensor data. Meanwhile, the program output recommends floating net cage owners to either "Stay in position" or "Move." Water quality warnings that exceed the upper and lower threshold limits are displayed using light-emitting diode indicators and a buzzer.

Overall, the water quality values of the Musi River at the test locations generally indicated stable and suitable conditions for river fish cultivation. The average water quality values were 29.20 degrees Celsius for temperature, 3.98 milligrams per liter for dissolved oxygen, and a potential of hydrogen of 6.42. From all the data obtained during the decision-making program, 36 locations suggested that the floating net cages should "Stay in position." Meanwhile, the three remaining locations were recommended to "Move" as they exhibited poor water quality, with potential of hydrogen values below 6. Field observations indicated that these locations were situated near residential areas, factories/industries, and tributaries, which are highly susceptible to waste and pollution. The output of the decision-making program correlated with the issued warnings by the water quality warning indicators when the pH value exceeded the lower threshold limit.

The fuzzy logic method implemented in the Python program for decision-making regarding the relocation of floating net cages in river fish farming revealed the fluctuating water quality conditions of the Musi River within a specific time duration. These conditions correlated with the proximity of the water bodies to pollution sources such as residential areas, factories, and tributaries. The program's output classified the status of the floating net cages into two conditions: "Stay in position" or "Move." The decision-making application to relocate floating net cages for fish farming in rivers provides a solution for fishermen as the resulting program decisions give the same indication as the reading value of the water quality sensor.

Cadmium contamination in rice grains with a maximum concentration 19 times the national food standard at sites downstream of zinc mines in Thailand has been reported since 2005. These cultivated rice grains are consumed by local residents and have increased the risk of renal dysfunction in residents. Decreasing negative health effects by reducing cadmium accumulation in rice should be considered. Since the soil characteristics affecting the toxicity and accumulation of cadmium in rice cultivated in cadmium-contaminated soils have never been reported, this study was conducted to investigate the soil characteristics affecting the plant availability and mobility of cadmium in paddy soils and the impacts of these soil characteristics on rice seed germination and accumulation in rice.

The study area is the Mae Tao Subdistrict, Mae Sot District, Tak Province, located downstream of abandoned zinc mines in northwestern Thailand. A total of 36 paddy fields that were reported to produce rice grain with cadmium contents exceeding the national standard for cadmium in rice (0.4 milligrams per kilogram) were randomly selected for composite soil sample collection. The physicochemical characteristics of the soils, including soil texture, redox potential, cation exchange capacity, potential of hydrogen, organic matter, total cadmium concentration, and chemical speciation and concentration of plant-available cadmium, were analyzed. The toxicity of cadmium to rice and the cadmium accumulation ability in rice were assessed through the germination of Khao Dok Mali 105, a popular rice variety for cultivation and consumption in the study area.

Total cadmium concentrations of 0.20 to 89.87 milligrams/kilogram were found in the soils, with 64 percent of all samples containing values greater than the national background value in agricultural soils. Up to 74.2 percent and 99.5 percent of total cadmium was found in the forms of mobile- and plant-available cadmium, respectively. Plant-available cadmium caused significant reductions in the number of seeds germinated and root length. Cadmium toxicity to rice was positively affected by the concentrations of exchangeable, plant-available and total cadmium. The concentrations of plant-available, exchangeable, carbonate-bound, and total cadmium strongly affected the accumulation of cadmium in germinated roots. Cluster analysis showed that plant-available cadmium was the main factor responsible for high cadmium accumulation in rice.

Based on the overall analyses of soil characteristics affecting the mobility and plant availability of cadmium in soils and its toxicity and accumulation in germinated rice, the immobilization of plant-available cadmium in soils by adding organic matter-rich amendments to soils is recommended. In addition, oxidizing soil conditions should be maintained during rice cultivation to reduce the phytoavailability of cadmium in soils.

Isotoma longiflora L is commonly used as a medicinal plant by the local community in Indonesia, and its geographical position determines its bioactive compounds and hence its efficacy. Ethanol extracts of Isotoma longiflora leaves from various locations in Aceh Province were analyzed using a simple infrared spectroscopy technique combined with chemometrics to determine the effect of geographical location and conditions by classification and authentication.

Isotoma longiflora leaf samples were collected from Aceh Besar (a geothermal manifestation of Ie Suum), Banda Aceh, Aceh Jaya, Bireun, and Central Aceh. Principal component analysis was used to categorize the ethanol extract of Isotoma longiflora leaves, and a linear discriminant analysis was used for authentication.

The principal component analysis score plot indicated 89 percent of total data variance and that the samples formed three distinct groups: group I consisting of Aceh Tengah and Bener Meriah samples; group II of Aceh Besar and Banda Aceh samples; and group III of Aceh Selatan, Aceh Barat Daya, Aceh Jaya, and Bireun. A linear discriminant analysis was then used to validate these results, and the linear discriminant analysis model derived from the cross-validation predicted the origin of Isotoma longiflora samples with 100 percent accuracy rate.

The Isotoma longiflora leaf extracts were successfully classified using Fourier-transform infrared spectroscopy data processed through chemometric calculations (namely, principal component analysis). Based on the cross-validation using linear discriminant analysis showed that the prediction model had a 100 percent accuracy. The present study thus revealed the effect of geographical location on the composition of bioactive compounds in Isotoma longiflora, suggesting the potential of chemometric techniques for quality control and assurance in traditional medicine.

The decreasing availability of fossil fuels requires the adoption of renewable energy sources that facilitate the mitigation of greenhouse gas emissions. Meeting Indonesia’s goal of achieving a 23 percent mixed energy composition by 2025 through co-firing demands a substantial increase in the availability of renewable energy sources. Bamboo is a valuable biomass resource because of its fast growth rate and potential for energy production. Innovative processes like torrefaction are necessary to improve the quality of biomass due to its challenging low density and hydrophilic properties. The objective of this study is to evaluate the characteristics of torrefied bamboo pellets made from Gigantochloa pseudoarundinacea by using a fixed counter-flow multi-baffle reactor. This study aims to investigate the properties and viability of torrefied G. pseudoarundinacea pellets for solid fuel applications to fill existing knowledge gaps about this technology’s potential.

A fixed counter-flow multi-baffle reactor was used to torrefy G. pseudoarundinacea bamboo pellets. The baffles in the reactor column held the pellets, while hot gas flowed through them. Torrefaction was conducted at 280 degrees Celsius with a 3–5 minutes resident time, and the gas flow rate was 4.25 cubic meters per minute. Torrefied pellets at the column bottom were counted as the first cycle. Three cycles of torrefaction were used, and each cycle was evaluated. The second and third cycles used torrefied pellets from the first and second cycles. The physical, chemical, and bioenergetic properties of the pellets before and after torrefaction were evaluated.

The bamboo pellets’ physical, chemical, and thermal properties changed significantly after torrefaction. Torrefaction at 285 degrees Celsius produced 78.5 percent of the production yield, according to thermogravimetric and derivative thermogravimetric analyses. Lightness, red/green, and yellow/blue chromaticity decreased, indicating darker, better solid fuel pellets. Torrefaction in the third cycle reduced moisture content by 99.8 percent. The lower moisture content reduced fungal growth, and improvinged biomass transport and storage. Torrefaction also raised the bamboo pellets’ calorific value and physical and mechanical properties. The highest calorific value of 21.62 megajoules per kilogram was obtained after the third cycle of torrefaction, and it was 16.6 percent higher than that of raw pellets. Torrefaction improved pellet grindability and combustion by decreasing density and compressive strength. Torrefaction increased ash, volatile matter, and fixed carbon. The ultimate analysis showed increased carbon and reduced nitrogen, hydrogen, and oxygen, improving solid fuel quality, energy density, and combustion emissions. According to a Fourier-transform infrared analysis, torrefaction caused extractive and hemicellulose degradation and lignin increase. The chemical analysis showed that temperature and residence time degraded hemicellulose and increased lignin in the torrefied pellets.

The torrefaction process using a fixed counter-flow multi-baffle reactor demonstrated the enhanced properties of G. pseudoarundinacea bamboo pellets for their application as solid fuel. The study’s findings contribute to the comprehension of torrefaction and the enhancement of conditions for producing superior biomass products. These findings have implications for exploring the potential applications of torrefaction in diverse industries and energy sectors.

Iron, an essential micronutrient, significantly contributes to growth, immune health, and cognitive development in human health. Inadequate dietary iron intake leads to iron deficiency anemia, affecting nearly 1.6 billion people, especially pregnant women and preschool children. Biofortification and fortification of iron in wheat is an acceptable and cost-effective strategy to alleviate iron deficiencies. This study aims to address iron deficiencies through the strategy of fortification and biofortification of wheat varieties. The study places specific emphasis on the proximate composition and iron/mineral content of different wheat varieties. To achieve these objectives, different spectrometric methods were employed to analyze the wheat samples.

Proximate and mineral quantification were carried out following standard Association of Official Analytical Chemists methods using ultraviolet-visible spectrophotometry, atomic absorption spectrometry, inductive coupled plasma-mass spectroscopy, and prediction was carried out using near-infrared spectra combined with chemometrics.

The samples had moisture content (1.1 - 4.5 percent), protein (18.0 - 22.6 percent), fat (0.3 - 0.6 percent), gluten (6.3 - 10.3 percent), fiber (0.3 - 1.4 percent), alcoholic acidity (0.04 - 0.08 percent), ash (0.9 - 1.7 percent), and carbohydrate (71.1 - 75.2 percent). Iron was determined and compared by spectrophotometric methods. Iron concentration ranged from (0.7 to 6.3 milligrams/100 grams) in ultraviolet-visible analysis, (0.7 to 6.74 milligrams/100 grams) in atomic absorption spectrometry, and (0.81 to 6.8 milligrams/100 grams) in inductive coupled plasma-mass spectroscopy. The obtained results were compared with the standard "Food Composition and Food Safety Standard Authority of India" and predicted using near-infrared spectra combined with chemometrics.

The work aims to investigate the nutritional content of various wheat varieties, particularly focusing on iron content, which could potentially have implications for improving dietary strategies and addressing nutritional deficiencies. The biofortified varieties (HI-8663 and HI-1605) were found to have high iron content when compared to normal wheat. The acquired results bridge the intricate relationship between plant-based diets, micronutrient deficiencies, providing valuable insights into combating iron deficiencies in public health with the potential achievement of improved nutritional understanding, optimized wheat selection, advanced analytical techniques, education, awareness, and iron deficiency mitigation.

Microplastics are plastic fragments measuring less than 5 millimeters which are formed from degraded plastic materials and have the potential to pollute the environment. Due to their widespread presence in the marine environment, microplastics have become a significant global threat. The presence of microplastics is often considered as causing pollution in various environments, especially aquatic ecosystems such as rivers and oceans. Microplastics contamination can even be found in consumed salt, thus raising concerns about its impact on human health. However, information on the presence of microplastics in salt is still very limited. This study aims to determine the abundance and characteristics of microplastics as contaminants in salt and assess the human exposure to microplastics in Indonesia.

A total of 21 samples of salt products were taken from various brands available in Padang City and Jambi City, Indonesia for analysis. Microplastics extraction was carried out by removing the organic materials contained in the salt samples using 30 percent hydrogen peroxide and then filtering them with a 0.45 micrometer pore filter. A stereomicroscope was used to detect the abundance, shape, size, and color of microplastics, while the Attenuated Total Reflection-Fourier Transform Infrared Spectroscopy was utilized to identify the polymer type of the microplastics. Furthermore, human exposure to microplastics can be predicted by calculating the estimated dietary intake and taking into account the daily salt intake.

Microplastics were detected in significant amounts (p<0.05) in all salt samples, ranging from 33 to 313 particles/kilogram. The types of microplastics most commonly found in the samples were fragments (67.49 percent), fibers (23.82 percent), films (6.08 percent), and pellets (2.61 percent). The types of polymer identified include polyethylene, polypropylene, polyethylene terephthalate, and polyester. The dominant microplastics were 100-300 micrometers in size (47.3 percent) and black in color (52.88 percent). It is estimated that adults in Indonesia will be exposed to 60.225-571.225 microplastics/year if they consume 5 grams of salt/day or 120.45-1142.45 microplastics/year if they consume 10 grams of salt/day.

Of the 21 salt samples analyzed, all were detected to contain microplastics. Inadequate and unhygienic salt production and contaminated seawater used as raw material contribute to microplastics contamination of salt, thus posing a risk to human health. By calculating of daily salt intake of the Indonesian population, it is possible to estimate their daily and annual exposure to microplastics. The results of this study contain useful information for the efforts to prevent microplastics contamination by relevant stakeholders and the provision of education and socialization about the proper salt production process in accordance with food safety standards as to reduce or even eliminate microplastics in salt. In addition, this study can provide valuable data on human exposure to microplastics in salt products that can assist policymakers in making standard references for microplastics.

Leachate recirculation has become a global practice for anaerobic digestion of municipal solid waste. Implementation of artificial neural networks for modeling and prediction of this process still remains challenging. Additionally, there has been a lack of research regarding the generalization capacity of neural networks using the data from other studies. This study aimed to enhance methane production rates and decrease biostabilization time in municipal solid waste treatment. It addressed the research gap in applying and generalizing neural networks to predict biogas production based on laboratory-measured parameters.

Two distinct systems were utilized for leachate treatment. System 1 involved collecting the leachate delivered by a new municipal solid waste reactor and transferring it to a recirculation tank. System 2 consisted of passing the fresh municipal solid waste leachate through a degraded municipal solid waste and then returning the obtained liquid back to the waste reactor. The experimental data were employed to develop an artificial neural network to predict methane content and cumulative biogas production. The model was trained and optimized using the experimental data. The effectiveness and generalizability of the optimal neural network were evaluated by using it for the unseen data from other studies, ensuring its ability to make accurate predictions beyond the training dataset.

The results demonstrated that in System 1, ammonium and chemical oxygen demand concentrations in the leachate progressively increased to high levels. In System 2, the average removal efficiencies for chemical oxygen demand and ammonium were found to be 85 percent and 34 percent respectively. The methane yield in biogas reached 59 liters per kilogram of dry weight, with a corresponding methane fraction of 63 percent. The neural network model showed an excellent performance, with validation performances of 0.716 and 0.634. The overall performance of the dataset resulted in correlation coefficients of 0.9991 and 0.9975. Finally, high correlation coefficients of 0.88 and 0.82 were achieved by incorporating the test data from other studies.

Leachate recirculation enhanced the reduction of chemical oxygen demand and the production of methane in bioreactors. Ammonium concentrations initially increased and later decreased due to waste adsorption and bacterial assimilation. The artificial neural network applied for predicting the cumulative methane production from municipal solid waste displayed a robust generalizability when tested on the data from other studies. The neural network was not significantly affected by changes in waste chemical properties, laboratory conditions, and recirculation rate. However, it showed a significant sensitivity to variation of waste mechanical properties.

Land use and land cover changes are affected by massive construction, urban expansion, and exploitative agricultural management. These pressures threaten the potential of aboveground carbon storage in Rancakalong District, West Java, Indonesia. In that massive construction and agricultural expansion are ongoing, it is critical to detect the potential changes in carbon stocks in the region. This study evaluated the impact of land use and land cover changes on aboveground carbon stock potential in Rancakalong District, West Java, Indonesia, by incorporating several ground-based carbon inventories into geographic information systems and remote sensing approaches. The spatiotemporal dynamics of the aboveground carbon stocks were assessed using Integrated Valuation of Ecosystem Services and Tradeoffs models.

Aboveground carbon stocks were estimated using the integrated approach of field inventory and geographic information systems. Land use and land cover changes were assessed from remotely sensed imagery data recorded in 2009 and 2021 using the maximum likelihood classification method in the geographic information as a collection of layers and other elements in a map 10.6 package. Tree height and diameter were collected within the purposively distributed plots with a size of 30 × 30 square meters. Vegetation biomass was assessed using an allometric equation, and aboveground carbon stock data were extrapolated to the landscape scale using a linear regression model of measured carbon stocks and the Normalized Difference Vegetation Index derived from recent satellite imagery.

Vegetated areas were predominant in 2009 and 2021. Vegetation covered 51 percent of the total area in 2009, increasing to 57 percent in 2021. Regarding agricultural area, mixed gardens and drylands decreased between 2009 and 2021. Meanwhile, paddy fields were the only agricultural land use to increase between 2009 and 2021. The bare land and built-up expansion related to the observed land clearing for the Cisumdawu Highway mainly came from the conversion of mixed gardens, paddy fields, and drylands. The results show that the land use and land cover changes in Rancakalong District have caused a reduction in aboveground carbon stocks by 11,096 tons between 2009 and 2021. The highest reduction in aboveground carbon stocks occurred in mixed gardens, while a slight increase in aboveground carbon stocks occurred in forests, shrubs, and paddy fields. The results highlight the contribution of mixed gardens to carbon storage as they are visually similar to forests in the structure and composition of vegetation.

Land use and land cover changes directly affected the aboveground carbon stock potential in Rancakalong District, indicated by an 11,096-ton reduction in the stocks. This shortage of carbon stock potential was mainly attributed to the massive reduction in mixed garden areas between 2009 and 2021 by 12 percent, which caused a significant decrease in aboveground carbon stocks. The application of the Integrated Valuation of Ecosystem Services and Tradeoffs model is efficient in analyzing the effect of land use and land cover change on aboveground carbon stock dynamics and can be widely used in environmental engineering studies involving remote sensing approaches.

 Plant growth is improved by arbuscular mycorrhizal fungi, although they have not been researched for slope stability. These fungal inoculations and bamboo interventions may promote root development toward the slip plane. Thstudy looks at how tree roots react to planting in bamboo tubes and the fungal consortium.

 In a screen house, the development of three fast-growing native Indonesian woody plants, Paraserianthes falcataria, Acacia mangium, and Gmelina arborea, was observed. These plants were planted in bamboo tubes filled with soil donated by Jati Radio and Citatah. The tubes were arranged on an inclined plane with a 20° slope. Arbuscular mycorrhizal fungi were introduced in three dosages, with control plots without mycorrhiza and bamboo.

 The findings demonstrated that bamboo may drive root development toward the slip plane. On Jati Radio and Citatah soils, the best arbuscular mycorrhizal fungus inoculation results were observed in G. arborea with a treatment dosage of M3 or 30 g. In both sites, neither therapy showed a meaningful change.

 G. arborea has the maximum phosphorus absorption (80%) and biomass weight (660 grams) with M3 dosage in Citatah and 71 percent with 330 g at the same dose in Jati Radio, which is associated with the ideal amount of arbuscular mycorrhizal fungus inoculation. As a result, this species is the best choice for using biotechnological solutions to stabilize slopes in landslide-prone locations. When bamboo is combined with arbuscular mycorrhizal fungi, root development may be directed and accelerated for the purpose of bridging landslide slip planes.

As a producer within the ecological food chain, phytoplankton provides the base energy and oxygen to the environment through photosynthesis and higher tropic levels. These benefits can be applied in five consecutive nature-by-nature oxidation ponds for the treatment of community wastewater coming through a high density polyethylene pipeline from the Phetchaburi Municipality located at the King’s Royally Initiated Laem Phak Bia Environmental Research and Development Project, Ban Laem District, Phetchaburi Province (Universal Transverse Mercator 47P 1442725 North 617774 East). This study focuses on the vertical distribution of the phytoplankton Cylindrospermopsis sp. and its relationship with nitrogen compounds in oxidation ponds.

Samples were collected from a community wastewater treatment system at various depths (30, 60, 90, 120, and 150 centimeters) below the water surface in April 2019 between 11:00 and 13:00 hours and analyzed for their chemical and physical properties. The analysis revealed a vertical relationship between Cylindrospermopsis sp. and wastewater. In the density of phytoplankton which were collected by measuring 20 liters of water and filtered using a 36-micron plankton net, calculated and counted under a high magnification microscope, as the species are classified according the taxonomy.

The results of the wastewater quality were as follows: the content of suspended solids was 65–81 milligram per liter, water temperature was 31.8–33.2°C, potential of hydrogen was 8.7–9.2, total nitrogen content was 4.0–5.3 milligram per liter, ammonium content was 0.03–0.06 milligram per liter, nitrate content was 0.09–0.12 milligram per liter, total phosphorus content was 0.9–1.3 milligram per liter, and phosphate content was 0.4–0.5 milligram per liter. In the density of phytoplankton, a significant correlation was observed between the population of Cylindrospermopsis sp. and water depth (R2 = 0.9324). The number of populations at the depths of 30, 60, 90, 120, and 150 centimeters were 3.2 × 107, 1.6 × 107, 1.1 × 107, 5.5 × 107, and 1.1 × 108 cells per cubic meter, respectively.

The different densities of Cylindrospermopsis sp. found at different depths throughout the treatment pond are related to the nitrogen dynamics of the water body. The results of this study revealed that organic nitrogen, including ammonium, was assimilated and converted to inorganic nutrients, which promoted the growth of other phytoplankton species. The correlation between Cylindrospermopsis sp. and total nitrogen and ammonium showed significance at R2 = 0.7268 and 0.797, respectively, with a confidence level of 0.05. Therefore, to ensure treatment effectiveness, the depth of wastewater treatment ponds should be considered during their construction because phytoplankton regulation plays an important role to maintain the overall treatment efficiency.

Flooding is the most frequent hydrological disaster which greatly impacts humans and the environment. Lombok, a small tropical island, experiences severe flooding almost yearly. Flood susceptibility mapping is important to determine the priority watershed in implementing flood mitigation action, including improving the spatial planning in watershed management. Several methods of determining flood susceptibility require the support of long data series and a variety of monitoring equipment in the field where not every region has the resource capacity. Compared to other methods that require the support of long data series and a large number of evenly distributed monitoring equipment, the geomorphometric parameters and land use/cover in a watershed are closely related to the hydrological responses and are potentially applicable in flood susceptibility mapping. This research aimed to classify the watershed flood susceptibility on a small island based on the geomorphometric characteristics and land use/land cover of the watershed.

This study was carried out on Lombok Island, located in southern Indonesia, representing a small island in the tropical region. Watershed classification was carried out using 24 geomorphometric variables and land use/land cover, representing aspects of the river network, geometry, texture, and watershed relief. The principal component analysis approach was carried out to determine the most significant variable, and the weight of each variable was determined using the weighted sum approach method. Then, compound values were calculated based on the weighted values and preliminary ranking to indicate the flood susceptibility levels, which were divided into five classes.

The analysis found that the variables most related to flood events are the total number of rivers, relief ratio, elongation ratio, river density, stream frequency, and dry agricultural land use. These most related geomorphometrics indicate that the watersheds with higher flood susceptibility have low rock permeability, relatively low infiltration capacity, and relatively high surface runoff, thus triggering flooding. The flood susceptibility mapping classified 16 watersheds as having very high flood susceptibility. This research shows that analysis of the geomorphometric characteristics and land use/land cover can be relied upon to determine the flood susceptibility level, which is useful in spatial planning and flood disaster mitigation.

Geomorphometric characteristics and land use/land cover can be used to determine a watershed's hydrological characteristics or behaviour. Based on the geomorphometric characteristics of the watersheds on Lombok Island, some identifying variables that are highly related to flood processes were obtained. Based on these characteristics, watersheds with high and very high flood susceptibility levels have low rock permeability, relatively low potential infiltration capacity, and relatively high surface runoff potential. Flooding still occurs despite good forest cover because the geomorphometric characteristics of the watershed also play a major role in flood events.

Zeolite has been recognized as a potential adsorbent for heavy metals in water. The form of zeolite that is generally available in powder has challenged the use of zeolite in the environment. Embedding powder zeolite in a nonwoven sheet, known as a zeolite-embedded sheet can be an alternative to solve that. Another challenge is that information and models of zeolite-embedded sheet removal efficiency are still limited. The novelty of this study is, first, the development of a zeolite-embedded sheet to remove heavy metals from water, and second, the use of the random forest method to model the heavy metal removal efficiency of a zeolite-embedded sheet in water.

The heavy metals studied were copper, lead and zinc, considering that those are common heavy metals found in water. For developing the zeolite-embedded sheet, the methods include fabrication of the zeolite-embedded sheet using a heating procedure and heavy metals adsorption treatment using the zeolite-embedded sheet. The machine learning analysis to model the heavy metal removal efficiency using zeolite-embedded sheet was performed using the random forest method. The random forest models were then validated using the root mean square error, mean square of residuals, percentage variable explained and graphs depicting out-of-bag error of a random forest.

The results show the heavy metal removal efficiency was 5.51-95.6 percent, 42.71-98.92 percent and 13.39-95.97 percent for copper, lead and zinc, respectively. Heavy metals were reduced to 50 percent at metal concentrations of 10.355 milligram per liter for copper, 171.615 milligram per liter for lead and 4.755 milligram per liter for zinc. Based on the random forest models, the important variables affecting copper removal efficiency using zeolite-embedded sheet were its contents in water, followed by water temperature and potential of hydrogen. Conversely, lead and zinc removal efficiency was influenced mostly by potential of hydrogen. The random forest model also confirms that the high efficiency of heavy metals removal (>60 percent) will be achieved at water potential of hydrogen ranges of 4.94–5.61 and temperatures equal to 29.1 degrees Celsius.

In general, a zeolite-embedded sheet can adsorb diluted heavy metals from water because there are percentages of adsorbed heavy metals. The random forest model is very useful to provide information and determine the threshold of heavy metal contents, water potential of hydrogen and temperature to optimize the heavy metal removal efficiency using a zeolite-embedded sheet and reducing pollutants in the environment.

Climate change has a greater influence on agriculture through local climate variability than global climate patterns. The impact of climate change on agricultural productivity and shifts in crop patterns varies significantly across regions. Its impact is closely tied to the technical abilities of farmers in managing their cocoa farming businesses. Technical skills encompass the proficiency of farmers in adopting adaptive cocoa cultivation techniques for planting, maintaining cocoa plants, as well as handling harvest and postharvest processes. The technical capability is interconnected with factors such as crop dependency on rainfall patterns, availability of infrastructure for quality inputs, soil degradation and fertility, nutrient levels, limited farmers’ resources, and technology penetration. Given the significant impact of climate change on cocoa farmers, it becomes crucial to enhance their adaptive capacity to address these challenges. Therefore, this study aimed to analyze the relationship between the characteristics of farmers and their adaptive capacity in responding to the impact of climate change.

Data were collected from 960 populations from two regencies, 4 districts, and 8 villages using the stratified sampling technique through interviews with 282 respondents. The sample size was determined using the Slovin formula through in-depth interviews with five key informants. The data collected were descriptively and statistically analyzed using the Excel program, which involved generating frequency distribution tables. Furthermore, the Mann-Whitney test, utilizing Statistical Product and Service Solution version 24, was employed to conduct a comparative analysis.

This result showed that the characteristics of farmers in the two areas were relatively the same in terms of age, non-formal education, number of family dependents, and perceptions of the climate. In terms of age, most farmers fell within the mature group of 36-48 years, with an average age of 44.63, considering in low category. The low productive age of farmers (44.63), along with their non-formal education, including training in climate field schools and integrated pest management field schools, as well as the number of dependents and their perceptions of climate change, emerged as significant parameters impacting farmers'''' decision-making processes. These factors also influenced their ability to cope, adapt, and seek new approaches to manage and mitigate the effects of climate change on their farming operations.

The relationship between farmers’ characteristics and adaptive capacity showed that the larger the land owned by farmers, the higher the managerial adaptability of farmers with lower technical ability.

This study aimed to investigate endogenous variables namely, economic development and deforestation, in North Sumatra, and examine their determinants. Both variables are substantial in a country community welfare with harmonized environmental sustainability as a legacy for future generations.

In this quantitative study, secondary data in the form of time series data from 1991 to 2020 with a total of 30 years were analyzed. The novelty of this study is its aim to combine deforestation variables and their determinants in a research model related to economic development. In this study, the determinants of economic development used were education, health, mineral resources and forest resource, whereas those of deforestation, were  forest resource,  institutional factors, population density, and economic development.

The data analysis revealed that the economic development in North Sumatra was significantly influenced by education, health, and mineral resources, excluding forest resources. Simultaneously, the determinants influenced economic development by 74.15 percent. Education contributed 27 percent, health 71 percent, mineral resources 12 percent and forest resources 29 percent to economic development. Forest resources and institutions had a significant influence on deforestation in North Sumatra, whereas population density and economic development did not have a significant effect. Simultaneously, the determinants influenced deforestation by 77.24 percent. Partial, forest resources and institutions were identified and significant effect but population density does not significantly affect it. Forest resources contributed 14 percent to deforestation, institutional factors 72 persent, population density 3 percent and economic development 57 percent.

The findings of this study, indicated that education and health have a major effect on economic development whereas forest resources do not however, forest resources significantly affect deforestation. This means that an increasing environmental damage  removes forest cover. Thus, it is recommended that the government increase human resource in terms of education and health, which are  essential in prioritizing human resource development as a fundamental factor. It is also important to set the limit to long-term natural resource exploitation, consider environmental damages, and improve institutional quality. The government needs to explore alternative sources that are more sustainable and environmentally friendly, such as ecotourism, and renewable energy. Renewable energy can be a reliable source of energy that will help reduce reliance on fossil fuels while also minimizing environmental impacts.

Tridax procumbens L. is a plant that grows abundantly in the Ie-Seu'um geothermal area in Aceh Province, Indonesia. The objective of this study is to determine metabolite compounds from Tridax procumbens plants in a geothermal area using qualitative and quantitative analyses. In addition, the contents of six heavy metals in plants and their toxicology were assessed using an in silico approach.

The ethanolic extract of Tridax procumbens was analyzed qualitatively using reagents to determine the contents of secondary metabolites such as flavonoids, alkaloids, tannins, steroids, triterpenoids, and saponins. In addition, quantitative analysis was conducted using gas chromatography–mass spectroscopy to obtain the chromatograms and mass spectra of the metabolite compounds of the ethanolic extract of Tridax procumbens, which were used in computational toxicology analysis using a simplified molecular input system in a predictor server. Atomic absorption spectrometry was conducted to confirm the contents of six heavy metals harmful to medicinal plants.

The results showed that Tridax procumbens from the Ie-Seu'um geothermal area, Aceh, has secondary metabolites such as flavonoids, saponins, steroids, and tannins, with phytol from diterpenoid group having the highest content (32.72 percent). Toxicological analysis showed that the compounds in the ethanolic extract of Tridax procumbens were nontoxic or inactive in five toxicity parameters. The other results of the heavy metal analysis showed the dominance of chromium among the other six metals tested (copper, not detected; cadmium, 0.91 ± 0.03 milligram per kilogram; zinc, 3.50 ± 0.03 milligram per kilogram; iron, 4.65 ± 0.02 milligram per kilogram; lead, 6.42 ± 0.05 milligram per kilogram; and chromium, 13.81 ± 0.07 milligram per kilogram.

This study highlights the unique secondary metabolite composition of Tridax procumbens under such extreme conditions and underscores the potential implications of heavy metal accumulation in plants in geothermal areas.

This study provides a comprehensive exploration of the utilization of scrap tires in geotechnical engineering, focusing on their applications, mechanical behavior, environmental impact, and potential challenges. The utilization of waste tires in engineering applications is of paramount importance, offering a sustainable solution to the escalating challenge of waste tire management. The accumulation of discarded tires poses significant environmental and economic concerns globally, with traditional disposal methods often leading to environmental degradation, fire hazards, and increased land use. By harnessing the inherent properties of scrap tires, such as their durability and energy-absorbing characteristics, geotechnical engineering presents a promising path for repurposing these materials. This review examines how integrating scrap tires into geotechnical projects, such as retaining walls, slopes, and drainage systems, can offer sustainable alternatives while addressing environmental concerns. The paper extensively analyzes the mechanical behavior of sand-rubber mixtures through laboratory investigations. Factors including rubber proportions, aspect ratios, and interaction mechanisms are dissected to understand their influence on shear strength, deformation behavior, and modulus properties. These insights pave the way for optimizing the performance of sand-rubber mixtures in engineering applications. Additionally, the article delves into modeling approaches that simulate the intricate behavior of these mixtures, facilitating better design and analysis. The economic feasibility of incorporating scrap tires is investigated, emphasizing the cost-effectiveness achieved through reduced material costs and enhanced infrastructure durability. The environmental benefits of diverting rubber waste from landfills are discussed, highlighting the alignment with sustainability goals and regulations. Despite the advantages, engineering challenges associated with rubber particles' behavior are acknowledged, and potential solutions are explored. Through a comprehensive synthesis of research findings and practical implications, this review aims to provide a deep understanding of the potential of scrap tires in geotechnical engineering. It concludes by advocating for further research and innovation to harness the full potential of scrap tires, ultimately contributing to a more sustainable and resilient built environment.

Deforestation threatens 120.5 million hectares of forest, and it occurs at a rate of 115 thousand hectares per year.  Economic needs and livelihoods encourage people to cut and farm forest areas. Deforestation is considered to be a random and unstructured process that does not involve indigenous people.  This research found that indigenous people and various other parties are continuously involved in forest land encroachment. Social networks have facilitated indigenous people and encroachers (buyers of forest land). This research aims to identify the actors involved in forest encroachment and the social network structure in the deforestation process in the production forest of Dharmasraya, Indonesia.

This study employs an ethnographic case study approach to understanding the drivers of deforestation in the Production Forest Management Unit of Dharmasraya.  The Production Forest Management Unit of Dharmasraya covers an area of 33,550 hectares. In customary law, the production forest is owned by four indigenous communities from the Nagari (villages): Bonjol, Abai Siat Nagari Sikabau, and Sungai Dareh. In this research, the data were collected through interviews that asked the respondent to report on those with whom she/he shared particular relations.  Primary data were collected using in-depth interviews employing the snowball sampling method. The data collection used interview guides relating to the actors involved in forest sales and the deforestation process.  Key informant interviews involving 34 key informants were conducted with traditional leaders, representatives of a lineage unit (Ninik Mamak) and adat functionaries (Datuak customary authorities), Wali Nagari (village chiefs), local institutional leaders, the government, companies, and those holding concessions. The secondary data were collected from relevant agencies in the research area.  The data were analyzed using descriptive–qualitative tools. 

Three parties are interested in forest production, namely, the local indigenous people, the companies, and the government and each parties claims the production forest because each party sees itself as being the most eligible for forest ownership; this causes an overlap of forest management and ownership among the actors. The indigenous people have become the most powerful party in the ownership of the production forest. The claims of ownership of forests as customary forests have caused the traditional authorities to sell forests massively. The land sale price varies according to the position of the forest and its distance from villages, the topography, and the access. Ulayat (forest) land is considered cheap, ranging between USD 300 and USD 1,300 per hectare, including the Alas hak.  The Alas hak is a signed letter showing that the forest land or communal land has been sold to someone else. There are three models of ulayat forest land selling: selling by the customary authorities, selling through a broker, and selling by local people. The research has identified 40 actors involved in production forest management in Dharmasraya.  Eight actors were not involved in deforestation or ulayat forest selling. Ten actors were involved in deforestation and ulayat forest selling indirectly, and 22 actors were directly involved in deforestation through forest selling.

Deforestation occurred because the indigenous people sold forest land massively. The sale of the land claimed as ulayat forest is not restricted; anyone interested in opening a plantation in a forest area can buy the land from the customary authorities. Hence, deforestation has occurred as part of a systematic process involving critical figures in the community. Ulayat forest land sales involved government officers, such as high-ranking police officers and army personnel, and entrepreneurs, officials, civil servants, and other parties who supposedly understand forestry law. The study also confirmed that the economic factors driving deforestation are facilitated by the social networks between indigenous people and the people holding power. The findings of this study contradict the general fact that indigenous people can manage forests sustainably.