Greywater waste is a type of wastewater that comes from bathroom water, washing that enters the drainage system, and is supplemented with rainwater whose downstream flow enters the river. This research aims to enhance the effectiveness of greywater treatment by using a physical model comprising a treatment process, namely a cattious wetland filter. This study applied the vetigenetic wetland method with and without media. The observed research variables were wastewater discharge variations, wetland residence time at intervals of 2 days, 4 days and 7 days, and the number of vetinous root stems, as well as water quality parameters (Y) consisting of pH, odor, color, turbidity, total dissolved solids (TDS), nitrate (NO$_3$$^-$), nitrite (NO$_2$$^-$), fecal coliform, and iron (Fe). The data analysis was based on descriptive evaluation of water quality parameters under different operational conditions, including variations in hydraulic retention time, flow rate, and plant density. The study is expected to show that using a physical model of a media-filtration root wetland can improve wastewater quality, with the output meeting clean-water quality standards that will be used as input to the pond. The qualified water quality consists of pH (7.9), NO$_3$$^-$ 2.319 mg/L, NO$_2$$^-$ 0.0922 mg/L, Fe 0.0286 mg/L, and the unqualified water quality consists of: odor 0.77, color 10.6 true colour units (TCU), turbidity 5.44 nephelometric turbidity units (NTU), TDS 175 mg/L, fecal coliform 85 colony‑forming unit (CFU)/100ml. The output comprises five parameters that do not meet treated effluent quality standards and will be used as inputs to the pond; therefore, further research on phytoremediation is warranted. A constructed wetland using vetiver grass effectively cleans fishpond greywater and reduces pollutant levels. This means it could be used as an initial or final step in water treatment when reuse is limited. However, in this study, the treated water didn’t always meet all health standards. This suggests extra treatment steps are needed, along with more real-world testing to ensure safety.

Pulau Weh, with Sabang as its capital, is located at the westernmost tip of Indonesia. Beyond its significance for domestic and international tourism, the island hosts several national strategic projects. Currently, the landscape of Pulau Weh is dominated by non-urban areas (agriculture, forests, and open land), including critical conservation and protected forest zones. These areas provide essential Cultural Ecosystem Services (CES) that benefit the local island community. This study aims to analyze land-use changes and local community perceptions of CES values within the forest conservation areas of Pulau Weh, Aceh Province. The research aligns with the Sustainable Development Goals (SDGs), specifically Goals 1 (No Poverty), 11 (Sustainable Cities and Communities), and 13 (Climate Action). A mixed-methods approach was employed, integrating ArcGIS analysis to evaluate spatial functional changes and statistical analysis using Principal Component Analysis (PCA) via SPSS to measure public perception. The results indicate that the 2023 land-use composition comprises built-up areas (497.69 ha; 4.49%), woodlands (5,203 ha; 46.89%), agricultural land (3,111 ha; 28.04%), grasslands (2,071 ha; 18.67%), water bodies (157 ha; 1.41%), and bare land (55.76 ha; 0.50%). Based on community perceptions, the forest conservation areas in Sabang contribute significantly to CES values, including recreation, cultural heritage, aesthetics, education, social relations, health, spirituality, and ecological/tourism benefits. Notably, disaster mitigation was the only value perceived as non-significant by the community.

The increasing demand for electrical energy and the commitment to clean energy transition encourage the utilization of renewable energy at the community level through the development of solar photovoltaic (PV). This study aims to identify the potential of solar PV, design the generating system, and analyze the technical and economic feasibility of developing an energy-independent village based on microgrids in Kedungrong Hamlet, Yogyakarta Special Region. The study uses a descriptive quantitative approach with the research object being 53 houses’ rooftops identified as having the potential for installing rooftop solar power plants (PLTS). Primary data were obtained through field observations, inventory of roof area and household electricity needs, and technical documentation, while secondary data were obtained from Global Solar Atlas and relevant scientific literature. The analysis was carried out through identification of solar radiation potential, calculation of electricity consumption, design of solar panel capacity and its supporting components, and evaluation of economic feasibility based on initial investment and energy saving benefits. The results of the study indicate that the rooftops of 53 buildings in Kedungrong Hamlet have good potential to be developed as PLTS systems because they are supported by adequate solar radiation intensity throughout the year. Economic analysis shows that PV investments provide benefits in the form of electricity cost savings and have a viable long-term return on investment. The integration of rooftop PV through a microgrid system improves energy supply reliability, electricity distribution efficiency, and strengthens community energy security. This research produces an energy-independent village planning model based on the utilization of 53 rooftops as a source of renewable electricity generation that can be replicated in other rural areas with similar characteristics to support the achievement of the national energy mix and sustainable development.

Crude oil is a major energy resource; however, oil exploration and production activities may release petroleum hydrocarbons (PHCs), heavy metals, and other contaminants that can adversely affect groundwater quality. This study evaluates the quality of groundwater surrounding oil mining sites in Musi Banyuasin Regency, South Sumatra, Indonesia, using the Water Quality Index (WQI) method. Groundwater samples were collected from 36 sampling points, consisting of 30 study wells located near oil drilling areas and six control wells, with two control wells in each of the three sub-districts: Sanga Desa, Babat Toman, and Lawang Wetan. The analyzed parameters included pH, temperature, total dissolved solids (TDS), turbidity, color, and heavy metals, including copper (Cu), nickel (Ni), lead (Pb), and mercury (Hg). The physicochemical and heavy metal data were processed and analyzed using Python, and the WQI was calculated to determine the overall groundwater quality classification. The results indicated that all 30 study wells (100%) were classified as unfit for consumption, whereas all six control wells (100%) were classified as excellent based on the WQI classification. The primary contaminants contributing to poor groundwater quality were Ni, Pb, and Hg, which exceeded the applicable national groundwater quality standards at several sampling points. Elevated concentrations of TDS, turbidity, and color were also observed at several study wells. These findings demonstrate a substantial anthropogenic influence of oil exploration activities on groundwater quality in the study area. Continuous groundwater monitoring, improved pollution control, and appropriate environmental management by relevant authorities are therefore essential to minimize contamination and prevent further degradation of groundwater resources.

Rooftop photovoltaic (PV) systems are a practical option for Baghdad, but their performance depends on module technology, mounting strategy, row spacing, and near-shading. This study integrates SketchUp/Skelion and PVsyst to evaluate grid-connected rooftop PV systems on the College of Education building at Mustansiriyah University, Baghdad. Seventeen configurations were simulated using monocrystalline and heterojunction (HJT) modules, fixed, seasonal, and two-axis mounting strategies, portrait and landscape layouts, row spacings of 0, 0.5, and 1.0 m, and practical losses including soiling, aging, unavailability, and auxiliary consumption. The objective was to combine a realistic 3D rooftop model with PVsyst near-shading analysis and compare technical, economic, and environmental performance. HJT modules outperformed comparable monocrystalline cases under Baghdad's hot conditions because of their lower power temperature coefficient. The two-axis HJT case achieved the highest annual energy production (272,308 kWh/yr), while the seasonal HJT case achieved the highest performance ratio (85.22%). The fixed landscape HJT system provided a strong practical balance, producing 244,305 kWh/yr and 1,871 kWh/kWp/yr with a performance ratio of 85.19%. Under the stated 25-year economic assumptions, its discounted levelized cost of energy (LCOE) was 0.0291 USD/kWh, with a simple payback period (PBP) of 3.1 years. Increasing row spacing improves specific yield by reducing self-shading, but total rooftop output decreases because fewer rows fit on the roof. Over the 25-year study period, the simulated systems avoid approximately 1,840.6–4,043.8 tCO$_2$ relative to grid electricity. Overall, the fixed landscape HJT arrangement is a practical candidate for rooftop PV deployment in Baghdad and similar hot, dry urban environments.

Exposure to heavy metals during pregnancy poses significant risks to maternal and child health. This study aims to analyze trends in research on heavy metal exposure in pregnant women using bibliometric analysis and systematic review. A total of 125 publications from the Scopus database (1973–2023) were analyzed. The bibliometric analysis examined publication trends, geographical distribution, and researcher collaboration. A systematic review assessed statistical methods, focusing on advanced models like Bayesian Kernel Machine Regression (BKMR) and Weighted Quantile Sum (WQS) regression, as well as traditional methods like linear and logistic regression. The bibliometric analysis showed an increasing number of studies, with the United States leading in publications, followed by China and India. The systematic review found that advanced models such as BKMR and WQS regression are increasingly used to evaluate interactions between heavy metal mixtures and pregnancy outcomes. However, many studies still rely on traditional regression models, highlighting a gap in the adoption of more advanced techniques. The study highlights the particular analytical capabilities of advanced statistical models in examining complex interactions between heavy metal mixtures and pregnancy outcome in understanding complex interactions between heavy metal mixtures and pregnancy outcomes. It also points to the need for greater adoption of these methods to improve risk assessments and inform public health policies. In conclusion, advanced modeling techniques, particularly BKMR and WQS regression, are crucial for understanding the risks of heavy metal exposure during pregnancy and guiding public health interventions.