Localisation and circularity in perishable food supply chains are essential for sustainability. Poor allocation of time-sensitive food leads to waste, higher transport emissions, and unnecessary long-distance sourcing. Algorithms used in digital trading platforms and allocation systems can help address these problems by improving how local supply is matched with demand under real operational constraints. This paper examines localisation and circularity in the UK apple supply chain. Apples are an informative case because they are perishable, consumed fresh as dessert fruit, used as inputs across multiple food industries, and generate valuable by-products. We present a weighted-sum mixed-integer linear programming formulation for supply-demand allocation. The model encodes a single global objective with explicit weights on four operational criteria: price matching, quantity alignment, freshness requirements, and geographic distance. These weights make priorities explicit and adjustable, enabling transparent balancing between economic and sustainability considerations. The framework also supports the circulation of unallocated supply across allocation cycles. Using a realistic apple supply-demand dataset, we evaluate allocation outcomes under different priority settings. Results indicate that allocation outcomes are strongly shaped by both priority settings and the structure of the underlying supply network characteristics.
Abstract This study presents a multi-agent reinforcement learning (MARL) framework for integrated real-time control (RTC) of urban drainage systems (UDSs), coordinating sewers, wastewater treatment plants (WWTPs), and receiving waters. Trained within a hydraulic–water quality simulation environment using QMIX, the framework enables facility-level decision-making and adaptive system coordination. Applied to Lu’an City, China, MARL achieved a 25.4% reduction in flooding and overflow volumes and an 18.0% decrease in river pollutants relative to benchmark strategies, while maintaining real-time control feasibility (6.35 s per 5-min interval). Under rainfall forecast and sensor noise uncertainty, MARL improved performance stability by 44.7–52.4%. Despite operational trade-offs, the framework supports integrated system optimization and consistent water quality improvements in urban settings.
Aminu Doguwa, Mohammed Abdul Azeem, Hilal Ahmad
et al.
Abstract Membrane distillation (MD) faces critical challenges at the industrial scale, including poor permeate flux and membrane fouling. To address these issues and efficiently treat highly saline water, this study presents a nature-inspired approach to fabricating a robust multilayer Janus membrane using a gecko-inspired adhesion mechanism. The proposed membrane was fabricated using a layer-by-layer co-deposition method, combining a surface-roughened PVDF flat-sheet membrane prepared via phase inversion with an electrosprayed hydrophobic PVDF-HFP interfacial layer modified with CuO nanoparticles and an electrospun hydrophilic PEI fiber bottom layer. The hydrophobic top layer exhibited a water contact angle of 131.5°, followed by a superhydrophobic interfacial layer and the bottom/support layer with a contact angle of 41.4°, enabling superior directional wettability. The Janus membrane achieved an impressive water gap membrane distillation (WGMD) flux of 37.16 kg m⁻² h⁻¹ with a high salt rejection rate of 99.99% over 24 h. Furthermore, the membrane demonstrated long-term stability and excellent resistance to fouling and delamination in harsh saline environments, maintaining performance over 60 h of continuous MD operation. This work highlights the potential of bio-inspired engineering in developing efficient and durable membranes, offering a promising pathway for advancing MD technology for industrial-scale desalination.
Philippe Malick Dione, Cheikh Faye, Ahmed Mohamed
et al.
Abstract Studying the pressing impacts of climate change on runoff is vital for the sustainable functioning of society and ecosystems. In Senegal, there is insufficient consideration given to the magnitude of the decrease in water resources caused by climate change and the potential impact of this decrease on both society and the environment. The objective of this study was to evaluate the hydrological effects of climate change in the Aga-Foua-Djilas basin by employing CWatM hydrological models inside the frameworks of ISIMIP and HMF-WA. Over the historical period (1981–2019) in the Aga-Foua-Djilas basin, the analysis of all hydrological parameters indicates positive trends, although not statistically significant (except for runoff). Over the future period, unlike temperatures and PET, which show an upward trend in all scenarios, precipitation and runoff show downward trends, which are more significant under SSP 585. For precipitation, Kendall’s Tau shows a downward trend of − 0.157 mm/yr, − 0.321 mm/yr, and − 0.472 mm/yr under SSP 126, SSP 370 and SSP 585, respectively. For runoff, the trends are negative and of the order of − 0.207 m3/s/yr, − 0.44 m3/s/yr, and − 0.565 m3/s/yr, respectively, under SSP 126, SSP 370 and SSP 585 with CwatM and − 0.248 m3/s/yr (SSP 126), − 0.389 m3/s/yr (SSP 245) and − 0.579 m3/s/yr (SSP585) with HMF-WA. Compared with the decrease in precipitation toward the end of the century, the decrease in runoff noted for the distant future (2081–2100) will be of the order of − 32.8% (SSP 126), − 80.8% (SSP 370) and − 94.6% (SSP 585) with CwatM and − 22.3% (SSP 126), − 19.6% (SSP 245) and − 50.9% (SSP 585) with HMF-WA. This study could help policymakers and stakeholders to develop adaptation strategies for the Aga-Foua-Djilas basin.
Mohammad Reza Goodarzi, Mohammad Javad Poorattar, Majid Vazirian
et al.
Abstract Reports demonstrate that floods are among the most prevalent and deadliest natural disasters affecting 520 million people annually. The present study seeks to evaluate flood forecasting using the weather research and forecasting (WRF) model and the Hydrologic Engineering Center-Hydrologic Modeling System (HEC-HMS) model. To this end, WRF and HEC-HMS were calibrated by comparing their results with the data observed at measuring stations. Then, the output rainfall data of the WRF model were implemented by the calibrated HEC-HMS model and were examined using the statistical indices, which were revealed to be 4.13, 3.42, and 2.67 for the flow volume and 6.2, 2.46, and 5.11 for the peak flow, suggesting the accurate performance of WRF model alongside HEC-HMS in the Talesh catchment.
God’swill Nathan Sambo, Adedapo Oluwasanu Adeola, Syahidah Akmal Muhammad
Abstract Carbonaceous adsorbents were synthesized from palm kernel shell and palm mesocarp fiber for the adsorption of phenanthrene (PHE) and the highly carcinogenic-benzo(a)pyrene (BaP). The structure and properties of the activated biochar were characterized using standardized analytical tools. The microscopic examinations carried out with SEM and BET results revealed mesoporous structures and interstitial spaces in the activated samples (AB-PKS and AB-PMS). Powder X-ray diffraction (PXRD) results showed that prepared sorbents are amorphous and that activation affected the amorphous cellulose on the surface of the microfibrils which led to a decrease in the intensity of some peaks. Fourier-transform infrared spectroscopy (FTIR) affirms the availability of surface moieties that may promote polycyclic aromatic hydrocarbon (PAH) removal or decontamination of aqueous media. The sorption isotherm and effect of pH on the adsorption of PHE and BaP onto the activated palm kernel shell (AB-PKS) and activated palm mesocarp fiber (AB-PMF) were investigated. The isotherm studies and error analysis (SSE and R 2 ) confirm that the Freundlich model best fits experimental results for AB-PMF; while, the Langmuir model best describes AB-PKS sorption of BaP and PHE, respectively. The optimal removal efficiency for PHE was between 84 and 100% while that of BaP was between 68 and 87% with maximum adsorption capacity (q max) of 19.38–21.98 mg/g and 1.24–13.26 mg/g, respectively. The optimum pH condition for removing PHE is less than 7 and above 7 for BaP. Therefore, the conversion of waste materials to useful sorbents, as well as preliminary adsorption test results obtained suggests a cleaner and cost-effective pathway for waste management and water treatment.
Abstract Despite the regulations and controls implemented worldwide by governments and institutions to ensure the availability and quality of water resources, many water sources remain susceptible to contamination. This contamination poses significant risks to human health and can lead to substantial economic losses. One of the challenges in this context is the presence of missing or incomplete data, which can arise from various factors such as the methodology used or the expertise of personnel involved in sample collection and analysis. The existence of such data gaps hampers the accurate analysis that can be conducted. To address this issue and estimate a water quality index from the available samples, it is crucial to handle missing information appropriately to avoid biased calculations. This study focuses on the application of machine learning methods for imputing missing data in water samples. Furthermore, it quantifies the performance of different models based on the distribution of the obtained data. By applying 10 distinct methods to a sample of water quality data, the most effective approaches, namely Bayesian Ridge, Gradient Boosting, Ridge, Support Vector Machine, and Theil-Sen regressors, were identified. The selection of these models was based on the evaluation of two estimation error metrics: average percent bias (PBIAS) and Kling-Gupta Efficiency statistic (KGEss). The respective metric values for the aforementioned methods are as follows: $$\langle \hbox {PBIAS}\rangle _{0.5}=14.665, 19.555, 14.300, 15.380, 15.920$$ ⟨ PBIAS ⟩ 0.5 = 14.665 , 19.555 , 14.300 , 15.380 , 15.920 and $$\langle \hbox {KGEss}\rangle _{0.5}=0.670, 0.585, 0.655, 0.620, 0.595$$ ⟨ KGEss ⟩ 0.5 = 0.670 , 0.585 , 0.655 , 0.620 , 0.595 . The results obtained from these models have been utilized to establish unbiased relationships among physical, chemical, and biological parameters based on the information retrieved through the applied imputation methods.
Water supply for domestic and industrial purposes, Environmental sciences
Muhammad Ary Murti, Andi Rudi Adhy Saputra, Ibnu Alinursafa
et al.
Abstract Water is the most basic need for humans and a source of livelihood for humans. Lack of human awareness to maintain water quality, causing water to become polluted, by both industrial and household waste, impacts on human health and material loss. Thus, it is important to create technology that can monitor water pollution automatically and quickly. This research aims to create a system which utilizes the Internet of Things (IoT) technology that can facilitate quality of water by measuring parameters such as pH and turbidity. The methodology of the system progresses by the usage of a controller which is ATmega328P-AU, pH sensor to measure acidity, turbidity sensor to measure turbidity level, LPWAN LoRa works like a communication of data transmission as well as cloud service, namely Antares, to store data that are sent via Android. Based on the outcomes, the proposed system has achieved a reliable accuracy with percentage error of 99.73% in pH sensor and 99.41% in the turbidity sensor. Also, 2.6 s is the average required time to deliver the results to the cloud service.
This work aims to advance sound event detection (SED) research by presenting a new large language model (LLM)-powered dataset namely wild domestic environment sound event detection (WildDESED). It is crafted as an extension to the original DESED dataset to reflect diverse acoustic variability and complex noises in home settings. We leveraged LLMs to generate eight different domestic scenarios based on target sound categories of the DESED dataset. Then we enriched the scenarios with a carefully tailored mixture of noises selected from AudioSet and ensured no overlap with target sound. We consider widely popular convolutional neural recurrent network to study WildDESED dataset, which depicts its challenging nature. We then apply curriculum learning by gradually increasing noise complexity to enhance the model's generalization capabilities across various noise levels. Our results with this approach show improvements within the noisy environment, validating the effectiveness on the WildDESED dataset promoting noise-robust SED advancements.
This research investigates a multi-product, multi-echelon, and multi-period vaccine supply chain network model under uncertainty and quality inspection errors. The objective function seeks optimizing the total cost of the supply chain. Moreover, the proposed model is formulated as a mixed integer linear programming problem under multiple sources of uncertain parameters including demand, inspection errors, vaccine waste generated in healthcare centers, and defective treatment rate of vaccine waste. To provide meaningful solutions that are robust against future fluctuation of parameters, the robust optimization approach is utilized to incorporate the decision maker risk attitude under different type of uncertainty sets. Namely, box, polyhedral and combination of interval polyhedral. The performance of the proposed model is demonstrated through an illustrative example. The results show the effect of different types of uncertainties on the overall objective function. Managerial insights and research implications in terms of vaccine supply chain is advised and future research directions are proposed.
What impact does import competition have on firms' production organizational choices? Existing literature has predominantly focused on the relationship between import competition and firms' global production networks, with less attention given to domestic. We first develop a Nash-bargaining model to guide our empirical analysis, then utilize tariff changes as an exogenous shock to test our theoretical hypotheses using a database of Chinese listed firms from 2000 to 2023. Our findings indicate that a decrease in downstream tariffs lead to an increase in vertical integration. In our mechanism tests, we discover that a reduction in upstream tariffs also enhances this effect. Moreover, the impact of tariff reductions on vertical integration is primarily observed in industries with high asset specificity, indicating that asset-specificity is a crucial mechanism. We further explore whether import competition encourages vertical integration for technological acquisition purpose, the effect is found only among high-tech firms, while it's absent in non-high-tech firms. Our research provides new perspectives and evidence on how firms optimize their production organization in the process of globalization.
La planeación y manejo de los recursos hidráulicos de un río y la elaboración de los planes ―de tipo no estructural― de mitigación de daños causados por sus inundaciones dependen de la relación que guarda el gasto máximo anual con su fecha de ocurrencia. Tales fechas, al acontecer durante el año, pueden ser tratadas como datos circulares, cuyos estadísticos de dirección media y dispersión, o índice de estacionalidad, definen los dos parámetros de ajuste de la distribución de von Mises (dvM), la cual permite la caracterización probabilística de las fechas de ocurrencia de las crecientes anuales; es decir, define su función de distribución de probabilidades. En este estudio se describe la dvM y su método de ajuste por máxima verosimilitud cuando los datos o fechas anuales son unimodales y abarcan todo el año. Cuando las fechas anuales se concentran en una porción del año, la dvM se ajusta con optimización numérica, vía el algoritmo de Rosenbrock. Por último, se describe cómo se representan, con una mezcla de tres dvM, las fechas de ocurrencia que son bimodales, cuyo ajuste, vía optimización numérica restringida, se realizó con el algoritmo Complex. Como un caso de aplicación, se procesaron las fechas de ocurrencia de 777 crecientes anuales registradas en 21 estaciones hidrométricas de la Región Hidrológica No. 10 (Sinaloa), México; se exponen con detalle siete aplicaciones típicas de los tres tipos de ajuste de la dvM. Las conclusiones ratifican a la dvM como modelo probabilístico de las fechas de ocurrencia de las crecientes anuales, sean unimodales o bimodales.
Hydraulic engineering, Water supply for domestic and industrial purposes
Abstract Rainwater harvesting reliability, the proportion of days annually when rainwater demand is fully met, is challenging to estimate from cross-sectional household surveys that underpin international monitoring. This study investigated the use of a modelling approach that integrates household surveys with gridded precipitation data to evaluate rainwater harvesting reliability, using two local-scale household surveys in rural Siaya County, Kenya as an illustrative case study. We interviewed 234 households, administering a standard questionnaire that also identified the source of household stored drinking water. Logistic mixed effects models estimated stored rainwater availability from household and climatological variables, with random effects accounting for unobserved heterogeneity. Household rainwater availability was significantly associated with seasonality, storage capacity, and access to alternative improved water sources. Most households (95.1%) that consumed rainwater faced insufficient supply of rainwater available for potable needs throughout the year, with intermittencies during the short rains for most households with alternative improved sources. Although not significant, stored rainwater lasts longer for households whose only improved water source was rainwater (301.8 ± 40.2 days) compared to those having multiple improved sources (144.4 ± 63.7 days). Such modelling analysis could enable rainwater harvesting reliability estimation, and thereby national/international monitoring and targeted follow-up fieldwork to support rainwater harvesting.
Water markets represent a policy tool that aims at finding efficient water allocations among competing users by promoting reallocations from low-value to high-value uses. In Canada, water markets have been discussed and implemented at the provincial level; however, at the national level a study about the economic benefits of its implementation is still lacking. This paper fills this void by implementing a water market in Canada and examine how water endowment shocks would affect the economy under the assumptions of general equilibrium theory. Our results show a water market would damp the economic loss in case of reductions in water endowment, but it also cuts back on the economic expansion that would follow from an increase on it. These results provide new insights on the subject and will provide a novel look and reinvigorate informed discussions on the use of water markets in Canada as a potential tool to cope with climate-induced water supply changes.
Marwan Mostafa, Daniela Vorwerk, Johannes Heise
et al.
In order to meet ever-stricter climate targets and achieve the eventual decarbonization of the energy supply of German industrial metropolises, the focus is on gradually phasing out nuclear power, then coal and gas combined with the increased use of renewable energy sources and employing hydrogen as a clean energy carrier. While complete electrification of the energy supply of households and the transportation sector may be the ultimate goal, a transitional phase is necessary as such massive as well as rapid expansion of the electrical distribution grid is infeasible. Additionally, German industries have expressed their plans to use hydrogen as their primary strategy in meeting carbon targets. This poses challenges to the existing electrical, gas, and heating distribution grids. It becomes necessary to integrate the planning and developing procedures for these grids to maximize efficiencies and guarantee security of supply during the transition. The aim of this paper is thus to highlight those challenges and present novel concepts for the integrated planning of the three grids as one multi-energy grid.
This paper introduces and formalizes the classical view on supply and demand, which, we argue, has an integrity independent and distinct from the neoclassical theory. Demand and supply, before the marginal revolution, are defined not by an unobservable criterion such as a utility function, but by an observable monetary variable, the reservation price: the buyer's (maximum) willingness to pay (WTP) value (a potential price) and the seller's (minimum) willingness to accept (WTA) value (a potential price) at the marketplace. Market demand and supply are the cumulative distribution of the buyers' and sellers' reservation prices, respectively. This WTP-WTA classical view of supply and demand formed the means whereby market participants were motivated in experimental economics although experimentalists (trained in neoclassical economics) were not cognizant of their link to the past. On this foundation was erected a vast literature on the rules of trading for a host of institutions, modern and ancient. This paper documents textually this reappraisal of classical economics and then formalizes it mathematically. A follow-up paper will articulate a theory of market price formation rooted in this classical view on supply and demand and in experimental findings on market behavior.
Aruna Randeniya, Mohanasundar Radhakrishnan, T. A. J. G. Sirisena
et al.
Abstract Water rationing contributes to inequalities in the water supply. Household storage tanks complicate the performance and the hydraulic modelling of these systems. Rationing is often not based on insights into system performance and fails to achieve equity and the operators struggle to explain the rationing tactics to the stakeholders. Understanding the behaviour of water networks rationed regularly is essential to resolve the supply inequalities. We present a contextual analytical framework for understanding and managing water rationing based on the duration of supply (cycle time), rationing fraction (duration of non-supply) and domestic storage to analyse the equity and performance in the water network. The framework was tested using a model of a distribution network in Kakkapalliya, Sri Lanka, under different rationing schemes. The results show that large household tanks create inequities, which can be reduced through a trade-off by increasing the cycle-time of the rationing with a minor reduction in performance. Very small or non-existent domestic storage also negatively impacts the performance and equity of stressed water networks. Resolution of supply inequalities can be achieved through the trade-off between equity and performance is possible through the operation of the water network and by the regulation of domestic storage in water rationing regimes.
Mohammad Hamid Hamdard, Ilkhom Soliev, Hafizullah Rasouli
et al.
The research focused on assessing groundwater quality in Jawharkel, Ghanikhel, Chak, Mandukhel, Dawrankhel, Noorkhel, Baba Qala, Sanikhel, Muhkumkhel, and Rasheeddan villages, and specifically intended to measure groundwater physical and chemical parameters in the mountainous areas of the Chak Karstic Sedimentary Basin in Chak District, Wardak Province, located in Afghanistan’s central part. The analyzed parameters included electric conductivity, pH, turbidity, odor, taste, color, hardness, as well as chloride (Cl2), nitrogen (N), fluoride (F), iron (Fe), arsenic (Ar), ammonia (NH3), and sulfide (SO4) content. All the analyzed chemical and physical parameters were found to be within acceptable limits. The results obtained were compared with the WHO drinking water quality standards. The study revealed that the values of physical parameters such as color, taste, odor and turbidity fell within the acceptable (recommended standard) limits; that the examined samples demonstrated no toxic elements and/or components; and that the analyzed chemical parameters were likewise within the permissible limits recommended by WHO and ANSA. Water quality in the target rural area proved to be better compared to the concerns of its residents and households, and that local water posed no threat to residents’ health and survival. The article emphasizes the importance of properly applying water quality indicators previously not adequately explored in the target area.
Sabqatullah Alipour, Mohammad Zaman Amini, Mohammad Daud Haidari
Due to declining water resources allocated to agriculture and rapid population growth, it is important to use water efficiently and increase crop water productivity (CWP). Deficit irrigation is considered an important strategy to achieve this goal. For this purpose, field experiments were conducted at the research farm of the Agriculture Faculty on Kabul University campus for two continuous years (2018-2019). The experiment consisted of four treatments, including full irrigation (ET100), 80% (ET80), 60% (ET60), and 40% (ET40) arranged in a randomized complete block design with three replications. Compared to ET100 and ET80, the ET60 and ET40 treatments significantly (P<0.05) reduced the duration of flowering and pod formation. The bean crop also showed best performance in plant height, number of leaves per plant, leaf area, leaf area index, number of pods per plant, number of seeds per pod, length of pod, 100-seed weight, and total grain yield in the ET100 and ET80 treatments. Moreover, significantly greater values of crop water productivity (CWP) and lower value of Ky were observed in ET80 compared to ET100, ET60 and ET40. Overall, the experiment results showed that regulated deficit irrigation can effectively increase water productivity. Supplying only 80% instead of full water requirement can result in a higher common bean CWP. This is of particular importance in water-scarce areas, where the water saved based on this practice can be used to irrigate additional acreage.