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Accurate wind power forecasting is one of the most important operations within the economic dispatch problem to increase the performance of power and energy systems. Accordingly, this study proposes a cyber-resilient hybrid approach based on the Federated Learning and Convolutional Neural Network (CNN) procedure for short-term wind power generation forecasting in different regions of Iran. Generalizability, data independence, forecasting for regions where no training data is available, and preserving the security and privacy of data are prominent features of the proposed method. The federated network was designed with an architecture of 9 clients to perform the training process and extract the salient features from the data associated with each region in each client via the CNN technique. Then, the generalized global supermodel is produced based on the extracted features in each client to forecast the wind power in new and unknown regions such as Mahshahr, Bojnord, and Lootak that had no training data available and had no effect on global supermodel generation. Various scenarios were developed to test the robustness of the suggested methodology. In the first scenario, wind power forecasting is performed based on the suggested technique. In this scenario, the accuracy of the generalized supermodel to forecast wind power generation in each of the Mahshahr, Bojnord, and Lootak regions is 84%, 85%, and 74%, respectively. The second scenario models the scaling attack by changing the wind speed parameters to evaluate the performance of forecasting models against the data integrity attack. In this scenario, an evaluation of the forecast results based on various performance metrics is conducted highlighting the accuracy reduction of the forecast model, due to the damage caused by cyber-attacks on the input data. In the third scenario, the detection of cyber-attack is done based on the image processing-based technique. The presented results emphasize the accurate performance and high generalizability of the cyber-resilient global supermodel in forecasting wind power in various regions of Iran.

Humic-like substances (HULIS) account for a major redox-active fraction of biomass burning organic aerosols (BBOA). During atmospheric transport, fresh acidic BB-HULIS in droplets and humid aerosols are subject to neutralization and pH-modified aging process. In this study, solutions containing HULIS isolated from wood smoldering emissions were first adjusted with NaOH and NH3 to pH values in the range of 3.6-9.0 and then aged under oxic dark conditions. Evolution of HULIS oxidative potential (OP) and total peroxide content (equivalent H2O2 concentration, H2O2eq) were measured together with the changes in solution absorbance and chemical composition. Notable immediate responses such as peroxide generation, HULIS autoxidation, and an increase in OP and light absorption were observed under alkaline conditions. Initial H2O2eq, OP, and absorption increased exponentially with pH, regardless of the alkaline species added. Dark aging further oxidized the HULIS and led to pH-dependent toxic and chemical changes, exhibiting an alkaline-facilitated initial increase followed by a decrease of OP and H2O2eq. Although highly correlated with HULIS OP, the contributions of H2O2eq to OP are minor but increased both with solution pH and dark aging time. Alkalinity-assisted autoxidation of phenolic compounds and quinoids with concomitant formation of H2O2 and other alkalinity-favored peroxide oxidation reactions are proposed here for explaining the observed HULIS OP and chemical changes in the dark. Our findings suggest that alkaline neutralization of fresh BB-HULIS represents a previously overlooked peroxide source and pathway for modifying aerosol redox-activity and composition. Additionally, these findings imply that the lung fluid neutral environment can modify the OP and peroxide content of inhaled BB-HULIS. The results also suggest that common separation protocols of HULIS using base extraction methods should be treated with caution when evaluating and comparing their composition, absorption, and relative toxicity.

La presente investigación se centra en el marco del desarrollo local, considerando las particularidades de un territorio inmerso en grandes complejidades y contradicciones sociales que, incluso, han sido generadoras de violencia por más de 60 años. El propósito se centró en realizar un análisis macro de las condiciones para el desarrollo glocal sostenible, a través de un estudio con enfoque cualitativo y cuantitativo, que permitió contrastar las visiones institucionales y comunitarias sobre la gobernanza actual, la implementación de los objetivos de desarrollo sostenible y la articulación con la implementación del proceso de paz, en el municipio de Santander de Quilichao, departamento del Cauca Colombia. Del mismo modo, se realizó un análisis micro para identificar nuevas aportaciones a la gobernanza glocal sostenible, soportado en la propuesta teórica que emergió en el desarrollo de esta investigación que hemos llamado Aproximación a la Nueva Gobernanza para el Desarrollo Glocal Sostenible. The research focuses on the framework of local development, considering the particularities of a territory immersed in great complexities and social contradictions that have generated violence for more than 60 years. A macro analysis of the conditions for sustainable glocal development and a micro analysis to identify new contributions to sustainable glocal governance was carried out, through a study with a qualitative and quantitative approach, which allowed to contrast the institutional and community visions on current governance, the implementation of the Sustainable Development Goals and the articulation with the implementation of the peace process, in Santander de Quilichao Cauca Colombia. One of the main conclusions is that it is necessary to strengthen citizen participation, civic and formal education, especially among youth, as future leaders and managers of sustainable glocal governance processes, in pursuit of the common good and social well-being. Programa de Doctorat en Desenvolupament Local i Cooperació Internacional

Anaerobic nitrogen removal technologies offer advantages in terms of energy and cost savings over conventional nitrification-denitrification systems. A mathematical model was constructed to evaluate the influence of process operation on the coexistence of nitrite dependent anaerobic methane oxidizing bacteria (n-damo) and anaerobic ammonium oxidizing bacteria (anammox) in a single granule. The nitrite and methane affinity constants of n-damo bacteria were measured experimentally. The biomass yield of n-damo bacteria was derived from experimental data and a thermodynamic state analysis. Through simulations, it was found that the possible survival of n-damo besides anammox bacteria was sensitive to the nitrite/ammonium influent ratio. If ammonium was supplied in excess, n-damo bacteria were outcompeted. At low biomass concentration, n-damo bacteria lost the competition against anammox bacteria. When the biomass loading closely matched the biomass concentration needed for full nutrient removal, strong substrate competition occurred resulting in oscillating removal rates. The simulation results further reveal that smaller granules enabled higher simultaneous ammonium and methane removal efficiencies. The implementation of simultaneous anaerobic methane and ammonium removal will decrease greenhouse gas emissions, but an economic analysis showed that adding anaerobic methane removal to a partial nitritation/anammox process may increase the aeration costs with over 20%. Finally, some considerations were given regarding the practical implementation of the process.

Accurate estimation of sensible and latent heat fluxes as well as soil moisture from remotely sensed satellite images poses a great challenge. Yet, it is critical to face this challenge since the estimation of spatial and temporal distributions of these parameters over large areas is impossible using only ground measurements. A major difficulty for the calibration and validation of operational remote sensing methods such as SEBAL, METRIC, and ALEXI is the ground measurement of sensible heat fluxes at a scale similar to the spatial resolution of the remote sensing image. While the spatial length scale of remote sensing images covers a range from 30 m (LandSat) to 1000 m (MODIS) direct methods to measure sensible heat fluxes such as eddy covariance (EC) only provide point measurements at a scale that may be considerably smaller than the estimate obtained from a remote sensing method. The Large Aperture scintillometer (LAS) flux footprint area is larger (up to 5000 m long) and its spatial extent better constraint than that of EC systems. Therefore, scintillometers offer the unique possibility of measuring the vertical flux of sensible heat averaged over areas comparable with several pixels of a satellite image (up to about 40 Landsat thermal pixels or about 5 MODIS thermal pixels). The objective of this paper is to present our experiences with an existing network of seven scintillometers in New Mexico and a planned network of three scintillometers in the humid tropics of Panama and Colombia.

AbstractAlthough our observing capabilities of solar‐induced chlorophyll fluorescence (SIF) have been growing rapidly, the quality and consistency of SIF datasets are still in an active stage of research and development. As a result, there are considerable inconsistencies among diverse SIF datasets at all scales and the widespread applications of them have led to contradictory findings. The present review is the second of the two companion reviews, and data oriented. It aims to (1) synthesize the variety, scale, and uncertainty of existing SIF datasets, (2) synthesize the diverse applications in the sector of ecology, agriculture, hydrology, climate, and socioeconomics, and (3) clarify how such data inconsistency superimposed with the theoretical complexities laid out in (Sun et al., 2023) may impact process interpretation of various applications and contribute to inconsistent findings. We emphasize that accurate interpretation of the functional relationships between SIF and other ecological indicators is contingent upon complete understanding of SIF data quality and uncertainty. Biases and uncertainties in SIF observations can significantly confound interpretation of their relationships and how such relationships respond to environmental variations. Built upon our syntheses, we summarize existing gaps and uncertainties in current SIF observations. Further, we offer our perspectives on innovations needed to help improve informing ecosystem structure, function, and service under climate change, including enhancing in‐situ SIF observing capability especially in “data desert” regions, improving cross‐instrument data standardization and network coordination, and advancing applications by fully harnessing theory and data.

Even when water scarcity and quality issues are not severe in the European Union (EU) countries, the impacts of climate change and external pressures vary across EU nations, leading to different outcomes. Achieving sustainability requires prioritizing the efficient management of water resources and sanitation services. To this end, conducting studies to identify countries needing appropriate measures is essential. This research focuses on evaluating and analysing the situation of water resources and sanitation systems in the European Union, with two specific objectives in mind. The first objective is to compare disparities between Member States (MSs) in a particular year and track their progress over two periods of five and ten years concerning variables related to water resources and sanitation services. By examining these disparities, the study aims to identify which countries have made significant improvements and which require more attention and resources to enhance their water management and sanitation systems. The second objective is to identify the countries best positioned to achieve certain Sustainable Development Goals (SDG 6, SDG 1, SDG 2, SDG 8, SDG 10, SDG 11, SDG 12). The results indicate that the countries best positioned in terms of meeting the SDGs and achieving sustainability in water and sanitation are Luxembourg, the Netherlands, Finland, Sweden, Denmark and Germany. However, in contrast, Romania, Lithuania, and Slovakia face greater challenges, particularly in sanitation. Factors such as economic level and climate change, which impact southern countries more severely (Greece, Spain, Cyprus) where water scarcity is more acute, contribute to these difficulties. Additionally, the lack of information on wastewater management hinders decision-making and the proper management of these wastes. This study analyses the progress and current status of water and sanitation indicators from an environmental perspective for the first time. It introduces variables to assess sustainability in EU countries that are not listed as indicators on the United Nations website, aiming to evaluate compliance with the SDGs.