The Mass Rapid Transit (MRT) Purple Line project is part of the Thai government’s energy- and transportation-related greenhouse gas reduction plan. The number of passengers estimated during the feasibility study period was used to calculate the greenhouse gas reduction effect of project implementation. Most of the estimated numbers exceed the actual number of passengers, resulting in errors in estimating greenhouse gas emissions. This study employed a direct demand ridership model (DDRM) to accurately predict MRT Purple Line ridership. The variables affecting the number of passengers were the population in the vicinity of stations, offices, and shopping malls, the number of bus lines that serve the area, and the length of the road. The DDRM accurately predicted the number of passengers within 10% of the observed change and, therefore, the project can help reduce greenhouse gas emissions by 1289 tCO₂ in 2023 and 2059 tCO₂ in 2030.

Scholars widely agree that modular technologies can significantly improve environmental sustainability compared to traditional building methods. There has been considerable debate about the viability of replacing traditional cast-in-place structures with modular construction projects. The primary purpose of this study is to determine the feasibility of using modular technology for construction projects in island areas. Thus, it is necessary to investigate the potential problems and suitable solutions associated with modular building project implementation. This study is accomplished through the use of qualitative and quantitative methods. It systematically examines desk research based on the wide academic literature and real case studies, collating secondary data from government files, news articles, professional blogs, and interviews. This research identifies several important barriers to the use of modular construction projects. Among the issues are the complexity of stakeholder engagement, limited practical skills and construction methodologies, and a scarcity of manufacturing capacity specialised for modular components. Fortunately, these unresolved challenges can be mitigated through fiscal incentives and governmental regulations, induction training programmes, efficient management strategies, and adaptive governance approaches. As a result, the findings support the feasibility of starting and advancing modular building initiatives in island areas. Project developers will likely be more willing to embrace and commit resources to initiate modular building projects. Additional studies can be undertaken to acquire the most recent first-hand data for detailed validation.

The use of geotechnologies combined with remote sensing has become increasingly essential and important for efficiently and economically understanding land use and land cover in specific regions. The objective of this study was to observe changes in agricultural activities, particularly agriculture/livestock farming, in the North Forest Zone of Pernambuco (Mata Norte), a political-administrative region where sugarcane cultivation has historically been the backbone of the local economy. The region’s sugarcane biomass also contributes to land use and land cover observations through remote sensing techniques applied to digital satellite images, such as those from Landsat-8, which was used in this study. This study was conducted through digital image processing, allowing the calculation of the Normalized Difference Vegetation Index (NDVI), the Soil-Adjusted Vegetation Index (SAVI), and the Leaf Area Index (LAI) to assess vegetation cover dynamics. The results revealed that sugarcane cultivation is the predominant agricultural and vegetation activity in Mata Norte. Livestock farming areas experienced a significant reduction over the observed decade, which, in turn, led to an increase in agricultural and forested areas. The most dynamic spatiotemporal behavior was observed in the expansion and reduction of livestock areas, a more significant change compared to sugarcane areas. Therefore, land use and land cover in this region are more closely tied to sugarcane cultivation than any other agricultural activity.

In this paper, we deal with one of the most urgent and relevant topics nowadays, i.e., water pollution. The problem is finding a valid candidate for the absorption and removal of different kinds of pollutants commonly found in water. There are already some indications about graphene oxide as a potential candidate. In the present work, we take a step forward to show how graphene nanoplatelets (rather than the oxide form of this material) are capable of decontaminating water. In this starting step, we use a specific substance as a model pollutant, i.e., acetonitrile, leaving for the future steps, to extend the analysis to additional types of pollutants. In addition to laboratory-produced graphene nanoplatelets, we already examined in the past; now we wish to consider also commercially available ones, so that the new results will not be bound to a laboratory (low technology readiness level) material, but will become interesting also from the industrial point of view, thanks to the scalability of the nanoplatelets production. For this aim, we compare the performance of two types of filters based on two classes of nanomaterials, i.e., those produced by microwave and ultrasound assisted exfoliation, already analyzed in our earlier works, with those commercially distributed by an Italian company, i.e., NANESA, http://www.nanesa.com/. The latter is an innovative SME involved in the production of graphene-based nanomaterials. We focus here in the graphene nanoplatelets, commercially available in industrial batches (GXNan grades). The present study leads to determine which filtering membrane, among the various types of commercial graphene considered, shows the greatest stability, and the lack of breakage of the membrane, concentrating on such accessory features, given that all types of graphene showed excellent adsorption properties.

This study introduces a novel Groundwater Flooding Risk Assessment (GFRA) model to evaluate risks associated with groundwater flooding (GF), a globally significant hazard often overshadowed by surface water flooding. GFRA utilizes a conditional probability function considering critical factors, including topography, ground slope, and land use-recharge to generate a risk assessment map. Additionally, the study evaluates the return period of GF events (GFRP) by fitting annual maxima of groundwater levels to probability distribution functions (PDFs). Approximately 57% of the pilot area falls within high and critical GF risk categories, encompassing residential and recreational areas. Urban sectors in the north and east, containing private buildings, public centers, and industrial structures, exhibit high risk, while developing areas and agricultural lands show low to moderate risk. This serves as an early warning for urban development policies. The Generalized Extreme Value (GEV) distribution effectively captures groundwater level fluctuations. According to the GFRP model, about 21% of the area, predominantly in the city’s northeast, has over 50% probability of GF exceedance (1 to 2-year return period). Urban outskirts show higher return values (> 10 years). The model’s predictions align with recorded flood events (90% correspondence). This approach offers valuable insights into GF threats for vulnerable locations and aids proactive planning and management to enhance urban resilience and sustainability.

Hospital waste containing antibiotics is toxic to the ecosystem. Ciprofloxacin is one of the essential, widely used antibiotics and is often detected in water bodies and soil. It is vital to treat these medical wastes, which urge new research towards waste management practices in hospital environments themselves. Ultimately minimizes its impact in the ecosystem and prevents the spread of antibiotic resistance. The present study highlights the decomposition of ciprofloxacin using nano-catalytic ZnO materials by reactive oxygen species (ROS) process. The most effective process to treat the residual antibiotics by the photocatalytic degradation mechanism is explored in this paper. The traditional co-precipitation method was used to prepare zinc oxide nanomaterials. The characterization methods, X-Ray diffraction analysis (XRD), Fourier Transform infrared spectroscopy (FTIR), Ulraviolet-Visible spectroscopy (UV-Vis), Scanning Electron microscopy (SEM) and X-Ray photoelectron spectroscopy (XPS) have done to improve the photocatalytic activity of ZnO materials. The mitigation of ciprofloxacin catalyzed by ZnO nano-photocatalyst was described by pseudo-first-order kinetics and chemical oxygen demand (COD) analysis. In addition, ZnO materials help to prevent bacterial species, S. aureus and E. coli, growth in the environment. This work provides some new insights towards ciprofloxacin degradation in efficient ways.