Analyzing ecosystem service values (ESV) is crucial for achieving sustainable development. The main objective of this study was to assess the ecosystem services of the Cisadane watershed in Indonesia, with specific goals: (i) examining the spatiotemporal dynamics of ESV using multi-year land use and land cover (LULC) data from 2000 to 2021, (ii) exploring trade-offs and synergies among various ecosystem services, and (iii) investigating the sensitivity of ESV to changes in LULC. The results unveiled a significant decrease in forested areas (21.2%) and rice fields (10.2%), leading to a decline in ESV of $196.37 billion (33.17%) from 2010 to 2021. Throughout the period from 2000 to 2021, interactions between ESV were mainly synergistic. Projected from the baseline year (2021), the decline in ESV is expected to persist, ranging from $24.78 billion to $124.28 million by 2030 and from $45.78 billion to $124.28 million by 2050. The total estimated ecosystem values exhibited an inelastic response in terms of ecosystem value coefficients. The study also emphasizes an inelastic response in total estimated ESV coefficient concerning ecosystem value coefficients. These findings underscore the urgent need for targeted conservation efforts and sustainable land management practices to mitigate the further decline in ecosystem services and safeguard the long-term well-being of the Cisadane watershed and its inhabitants.

Monitoring marine biodiversity is a challenge in some vulnerable and difficult-to-access habitats, such as underwater caves. Underwater caves are a great focus of biodiversity, concentrating a large number of species in their environment. However, most of the sessile species that live on the rocky walls are very vulnerable, and they are often threatened by different pressures. The use of these spaces as a destination for recreational divers can cause different impacts on the benthic habitat. In this work, we propose a methodology based on video recordings of cave walls and image analysis with deep learning algorithms to estimate the spatial density of structuring species in a study area. We propose a combination of automatic frame overlap detection, estimation of the actual extent of surface cover, and semantic segmentation of the main 10 species of corals and sponges to obtain species density maps. These maps can be the data source for monitoring biodiversity over time. In this paper, we analyzed the performance of three different semantic segmentation algorithms and backbones for this task and found that the Mask R-CNN model with the Xception101 backbone achieves the best accuracy, with an average segmentation accuracy of 82%.

The use of saline water in agriculture is a viable alternative, considering the increased demand for fresh water. The objective of this study was to evaluate the growth and phytomass production of sugar beet under irrigation with water of different saline concentrations in a field experiment on the campus of the Federal University of Alagoas in Arapiraca. The treatments were five levels of electrical conductivity (1.0, 2.0, 3.0, 4.0 and 5.0 dS m^-1). The design was in randomized blocks, with four repetitions. The maximum yield of sugar beet at 27 days after the application of saline treatments was obtained with a salinity of 3.0 dS m^-1, for the variables plant height (PA), stem diameter (CD), root length (RC), aboveground dry phytomass (FSPA) and total dry phytomass (FST). At 42 days after the application of saline treatments, the variables aboveground fresh phytomass (FFPA), root fresh phytomass (FFR), total fresh phytomass (FFT), aboveground dry phytomass (FSPA) and total dry phytomass (FST) increased with increasing water salinity. Rain may have influenced the results obtained for the evaluations, performed at 42 days after the application of the saline treatments.

Natural water purification system especially constructed has been commonly employed in Taiwan and worldwide nowadays. This paper has reviewed several papers written by the author.

This paper aims to verify the possibility of utilising water-in-diesel emulsions (WiDE) as an alternative drop-in fuel for diesel engines. An 8% WiDE was produced to be tested in a four-stroke, indirect injection (IDI) diesel engine and compared to EN590 diesel fuel. An eddy current brake and an exhaust gas analyser were utilised to measure different engine parameters such as torque, fuel consumption, and emissions at different engine loads. The results show that the engine running on emulsified fuel leads to a reduction in torque and power, an increase in the specific fuel consumption, and slightly better thermal efficiency. The highest percentual increment of thermal efficiency for WiDE is obtained at 100% engine load, 5.68% higher compared to diesel. The emissions of nitric oxide (NO) and carbon dioxide (CO₂) are reduced, but carbon monoxide (CO) and hydrocarbons (HC) emissions are increased, compared to traditional diesel fuel. The most substantial decrease in NO and CO₂ levels was achieved at 75% engine load with 33.86% and 25.08% respectively, compared to diesel.

This study investigates the performance assessment of methanol and water as working fluid in a solar-powered vapour absorption refrigeration system. This research clarifies the system’s performance across a spectrum of operating conditions. Furthermore, the HAP software was utilized to determine and scrutinize the cooling load, facilitating a comparative analysis between software-based results and theoretical calculations. To empirically substantiate the findings, this research investigates methanol-water as a superior refrigerant compared to traditional ammonia- water and LiBr-water systems. Through experimental analysis and its comparison with previous research, the methanol-water refrigeration system demonstrated higher cooling efficiency and better environmental compatibility. The system’s performance was evaluated under varying conditions, showing that methanol-water has a 1% higher coefficient of performance (COP) compared to ammonia-water systems, proving its superior effectiveness in solar-powered applications. This empirical model acts as a pivotal tool for understanding the dynamic relationship between methanol concentration (40%, 50%, 60%) and system performance. The results show that temperature of the evaporator (5–15 ℃), condenser (30 ℃–50 ℃), and absorber (25 ℃–50 ℃) are constant, the coefficient of performance (COP) increases with increase in generator temperature. Furthermore, increasing the evaporator temperature while keeping constant temperatures for the generator (70 ℃–100 ℃), condenser, and absorber improves the COP. The resulting data provides profound insights into optimizing refrigerant concentrations for improved efficiency.