The present study presents the general methodology on optimal site selection and environmental impact minimization for Floating Photovoltaic Systems (FPVS) by using Multi Criteria Decision Making Methodology (MCDM) in proposing more resilient energy societies. Six lakes have been chosen as candidates for the comparison and discussion on the suitability scores on the example of Republic of Serbia. Two of them were excluded due to restrictions on protected areas after the site’s investigation and data collection process. The following steps were applied through the process: (i) determining the criteria sets that are essential for FPVS, (ii) collecting expert opinions for pairwise comparison, (iii) applying the Fuzzy Analytical Hierarchy Process (FAHP) and obtaining the results, (iv) environmental impact minimization recommendations. According to results, Global Horizontal Irradiance (GHI), which directly affects PV performance, has the highest importance value while water pollution due to materials is calculated as the least importance weight factor for FPVS. In addition to criteria comparison, candidate lakes were ranked among each other based on the suitability scores. As a result, Zlatar Lake achieved the highest suitability score while Perucac lake has the lowest suitability. The study gives the comprehensive and novelty framework in the selecting the suitable water bodies for FPVS development in Republic of Serbia, while the developed methodology is general and can be applied for other countries as well. The presented economical-environmental analysis for all selected locations of FPVS offer important insights in clean energy, emission and evaporation reduction and contributes to the UN’s sustainable development goals. The results obtained offer comprehensive recommendations for stakeholders and policy makers towards resilient societies and fulfillment of the de-carbonization goals by using renewables.
Land-system studies often emphasize structural land-cover change while overlooking functional shifts within socio-ecological systems. We address this gap by integrating spatial and socio-metabolic analyses to examine approximately 150 years of agricultural landscape change in Central Russia. Historical maps, satellite imagery, archival records, and contemporary surveys were used to reconstruct land-use change and agroecosystem energy flows. Arable land decreased by only 19
Public data access may improve urban environmental outcomes by expanding the information available to firms and the public. This study applies the double/debiased machine learning (DDML) framework to examine the effects of public data access platforms (PDAPs) on air pollutants and carbon emissions across Chinese cities. The results show that PDAPs significantly reduce both air pollution and carbon emissions, indicating a joint environmental benefit of public data access. Mechanism analyses suggest that these effects are associated with improvements in total factor energy efficiency, green innovation, as well as greater public environmental attention and participation. Heterogeneity analysis shows stronger pollution-reduction effects in cities with higher baseline pollution, while evidence related to market integration is concentrated in SO₂-related outcomes. Sectoral analyses further show that PDAPs reduce CO₂ emissions from industry, construction, transport, and waste. These findings highlight the role of public data infrastructure in supporting integrated air-quality and climate governance and provide policy implications for the design of public data access initiatives in urban environmental management. Public data access promotes joint reductions in air pollution and CO₂ emissions. DDML flexibly estimates the environmental effects of public data access platforms. Total factor energy efficiency, green innovation, and public environmental engagement are key channels.
This study investigates the ecological and chemical status of the Greenmoore ponds, Woodcote, UK, to identify factors driving biodiversity loss. A biodiversity assessment was conducted in situ using standardized dip-net sampling at 20 water/biota and 10 soil points across the upper and lower ponds, over two seasons (winter: January–February; summer: June–July), alongside analyses of water, leaf debris, and soil samples for microbiological, physicochemical, nutrient, and trace metal parameters. Pollutant speciation modelling (using PHREEQC), spatial mapping, and statistical analyses (using Spearman’s and Kendall’s correlation, and multivariate statistics) were employed to evaluate ecological integrity. The results revealed a substantial decline in biodiversity compared with historical surveys (Pond Action 2000), with total recorded organism abundance falling by approximately 52–60
Given the implication of household time allocation for its overall physical and economic well-being, this study examines how cooking time allocations influence households’ ability to afford cooking energy. It adds to the emerging discourse on the time use and energy poverty nexus, focusing on time spent on daily meal preparation and energy affordability. Descriptive analysis, multivariate logistic regression, and Lewbel Instrumental Variable estimation techniques are employed to analyse data from 1,184 households sampled across 51 of Ghana’s marine fishing communities. The descriptive results show that households devote an average of 3.36 hours to daily meal preparation, with half of all households (50.1
