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Equipment renewal and replacement strategy as well as smart capital investment is a vital focus in engineering asset management, particularly for water utilities aiming to improve asset reliability, water quality, service continuity and affordability. This study presents a novel decision support model that integrates whole-life costing principles across all asset lifecycle phases—from capital delivery and daily operations to long-term maintenance. The proposed model uniquely combines asset degradation and failure patterns, operating and maintenance costs, and the impact of technological advancements to provide a holistic and comprehensive asset management decision-making tool. These dimensions are jointly analysed using a hybrid approach that combines optimisation with stochastic dynamic programming, allowing for the determination of optimal asset renewal and replacement timing. The model’s performance was validated using historical data from eight critical wastewater pump stations within a township’s sewerage network. This was performed by comparing the model’s cost-saving results to those achieved by the water utility’s current strategy. Results revealed that the proposed model achieved an average cost saving of 12%, demonstrating its effectiveness in supporting sustainable and cost-efficient asset renewal decisions. Full article

Anthropogenic climate change threatens production of essential natural resources, such as food, fiber, fresh water, and provisioning of ecosystem services such as carbon sequestration, increasing the risk of societal collapse. The Human and Nature Dynamics (HANDY) model simulates the effect of resource overexploitation on societal collapse but lacks representation of feedbacks between climate change and resource regeneration in ecological systems. We extend the HANDY model by integrating models of climate change and ecological function to examine the risk of societal collapse. We conducted a sensitivity analysis of our expanded model by systematically varying key parameters to examine the range of plausible socio-ecological conditions and evaluate model uncertainty. We find that lowered greenhouse gas emissions and resilient ecosystems can delay societal collapse by up to approximately 500 years, but that any scenario with greater than net-zero greenhouse gas emissions ultimately leads to societal collapse driven by climate-induced loss of ecosystem function. Reductions in greenhouse gas emissions are the most effective intervention to delay or prevent societal collapse, followed by the conservation and management of resilient ecological systems to sequester atmospheric carbon. Full article

Microplastic pollution in the Chesapeake Bay is of critical concern as estuaries serve as habitats and nurseries for diverse aquatic organisms and offer vital ecological services. However, quantitative analysis of microplastics, especially those smaller than 300 µm, in the natural aquatic environment is very challenging due to a lack of efficient sampling methods. This study takes a novel approach to quantify the abundance, size distribution, and morphological characteristics of microplastics, as small as 20 µm, in the surface waters of the Chesapeake Bay. Water samples (10 L) were collected monthly from July 2023 to October 2023 at four locations along the Chesapeake Bay. The samples were digested with a 10% potassium hydroxide solution and subjected to density separation using sodium chloride (ρ = 1.2 g/cc). Microplastic particles were examined using a Shimadzu AIM–9000 FTIR microscope for enumeration and chemical identification. Overall, the mean microplastic concentration observed was 766.16 ± 302.59 MP/L, significantly higher than previously estimated in the Chesapeake Bay. Microplastic abundance exhibited a significant (p = 0.02) spatial variation across the four sampling locations. Most abundant were particles less than 100 µm (60.65%), followed by particles between 100 µm and 300 µm (23.19%), and particles exceeding 300 µm (16.16%). Morphological analysis identified fragments as the dominant shape (86.02%), followed by fibers (11.87%), and beads (2.10%). This study underscores the importance of standard and efficient sampling methods in microplastics research. By sampling microplastics as small as 20 µm, this research demonstrated that the abundance of microplastics in the Chesapeake Bay is significantly higher than previously estimated and dominated by smaller–sized particles. These small microplastics are more likely to enter the food web where human exposure may occur. Therefore, microplastic pollution in the Chesapeake Bay ecosystem has the potential to impose environmental and public health risks. Full article

Land use change significantly affects regional carbon emissions and ecosystem service value (ESV). Under China’s Dual Carbon Goals, this study takes Beijing-Tianjin-Hebei, experiencing rapid land use change, as the study area and counties as the study unit. This study employs a combination of methods, including carbon emission coefficients, equivalent-factor methods, bivariate spatial autocorrelation, and a multinomial logit model. These were used to explore the spatial relationship between land use carbon emissions and ESV, and to identify their key driving factors. These insights are essential for promoting sustainable regional development. Results indicate the following: (1) Total land use carbon emissions increased from 2000 to 2015, then declined until 2020; emissions were high in municipal centers; carbon sinks were in northwestern ecological zones. Construction land was the primary contributor. (2) ESV declined from 2000 to 2010 but increased from 2010 to 2020, driven by forest land and water bodies. High-ESV clusters appeared in northwestern and eastern coastal zones. (3) A significant negative spatial correlation was found between carbon emissions and ESV, with dominant Low-High clustering in the north and Low-Low clustering in central and southern regions. Over time, clustering dispersed, suggesting improved spatial balance. (4) Population density and cultivated land reclamation rate were core drivers of carbon–ESV clustering patterns, while average precipitation, average temperature, NDVI, and per capita GDP showed varied effects. To promote low-carbon and ecological development, this study puts forward several policy recommendations. These include implementing differentiated land use governance and enhancing regional compensation mechanisms. In addition, optimizing demographic and industrial structures is essential to reduce emissions and improve ESV across the study area. Full article

Driven by the Rural Revitalization Strategy, China has substantially increased its investment in rural infrastructure. Nevertheless, widespread issues such as underutilization and inadequate management persist. Recognizing rural infrastructure as a complex and interdependent system, this study applies complex network analysis to evaluate data from 98 counties, treating each county as an analytical unit and various infrastructure types as network nodes. A rural infrastructure interdependency network is constructed to examine the interdependencies among infrastructure and the overarching structural characteristics of the system. The analysis demonstrates that the rural infrastructure network exhibits pronounced modularity, with three distinct functional clusters: (1) electricity–water–broadband internet, (2) public service infrastructure, and (3) housing–environmental governance infrastructure. Furthermore, by employing a network dismantling approach that simulates facility management failures through the progressive removal of nodes, this study identifies paved roads and electricity supply stability as critical nodes within the rural infrastructure network. The failure of these infrastructures triggers systemic fragmentation and functional collapse, indicating their pivotal role in maintaining overall network integrity. These findings offer theoretical support for the optimization of infrastructure maintenance strategies, with the ultimate goal of enhancing the overall resilience and sustainable development capacity of rural infrastructure systems. Full article

Ultra-long pool structures used in mine water treatment projects are typical large-volume concrete structures that are highly susceptible to cracking due to the combined effects of cement hydration heat, seasonal temperature variations, and internal water pressure. Such cracking can compromise the durability and long-term service performance of the structure. In this study, distributed fiber optic sensing and finite element analysis were conducted to observe the response of ultra-long pool structures under thermal–load effects. System comparison shows that the average error between the monitored peak thermal strain values and the corresponding simulated values is within 9%. Parametric analysis using the validated simulation model indicates that the hydration protocol with temperatures of 15 °C (casting), 55 °C (peak), and 15 °C (stable), a temperature drop of −20 °C, and loading conditions in sub-pools 3+6 and sub-pools 1+3+5 are the most unfavorable scenarios for inducing tensile stress. When a temperature drop of −20 °C is combined with loading conditions in sub-pools 3+6 or sub-pools 1+3+5, the tensile stress in the pool structure increases by 30% compared to the stress induced by loading alone. This indicates that during the service life of the pool structure, extreme temperature variations combined with mechanical loading may result in localized cracking. This study provides a comprehensive understanding of ultra-long pool behavior during construction and service phases, supporting effective maintenance and long-term durability. Full article

Optimizing the spatial pattern of water conservation services (WCSs) is essential for enhancing regional water retention and promoting sustainable water resource management. The Saihanba region, a critical ecological barrier in northern China, has experienced severe degradation due to historical over-logging, leading to weakened WCS functions. This study used remote sensing techniques to interpret land use/land cover change (LULC) and combined it with meteorological and basic ecological data to assess changes in WCS capacity in the Saihanba region, China, under multiple 2035 scenarios using CA-Markov and Bayesian network models. The Bayesian belief network identified priority areas for spatial optimization. Results showed the following: (1) The spatial distribution patterns of WCSs showed a strong dependence on land-use types, with both forest and grassland areas demonstrating superior water conservation capacity compared to other land cover categories; (2) although total WCS capacity varied across scenarios, spatial distribution remained consistent—high-value zones were mainly in the south and central-east, while lower values occurred in the west; and (3) WCS areas were categorized into key optimization, ecological protection, and general management zones. Notably, the Sandaohekou Forest Farm and the western Qiancengban Forest Farm emerged as critical areas requiring urgent optimization. These findings offer practical guidance for spatial planning, ecological protection, and water resource governance, supporting long-term WCS sustainability in the region. The study also contributes to cleaner production strategies by aligning ecosystem service management with sustainable development goals. Full article

This study aims to enhance the aquatic eco-functional zoning by incorporating the spatial variability of hydrological processes during the zoning process. We propose a method for watershed eco-functional zoning based on distributed hydrological modeling. Using the Jinjiang Basin in Southeast China as a case study, we applied the Soil Water and Assessment Tool (SWAT) model to delineate the basic zoning units and simulate their hydrological processes. We integrated natural environmental indicators—specifically topography, vegetation, meteorology, and hydrology—with land use as a measure of human activity, while accounting for their spatial variability. This approach enabled us to conduct both first-level and second-level eco-functional zoning of the watershed. The results indicated that (1) the Jinjiang Basin can be categorized into three main groups consisting of six first-level aquatic ecological zones, which reflect the spatial variability of terrestrial natural environmental factors and their influence on aquatic ecosystems; (2) building on this categorization, the first-level aquatic ecological regions were further divided into five categories comprising 18 second-level aquatic ecological functional zones, emphasizing the impact of human activities on aquatic ecosystems and their associated first-level ecological service functions; and (3) the application of hydrological simulation techniques allows for a comprehensive assessment of the spatial variability of hydrological processes, thereby enhancing the validity of the ecological function zoning results and providing robust technical support for watershed ecological function zoning. Full article

Kiwifruit (Actinidia deliciosa) is a globally important crop presenting challenges for ensuring cross-pollination. This study aimed to (1) record the entomological fauna visiting flowers; (2) evaluate the visitation frequency of pollinators; and (3) test the use of lavender extract to enhance cross-pollination by honeybees and assess the impacts on fruit quality. Nine species of floral visitors were recorded as pollinators, although the most frequent were the exotic honeybee (Apis mellifera) and the native bees Bombus pauloensis and Xylocopa augusti. Honeybees increased their visitation to flowers when the attractant was used, improving pollination service and fruit quality compared to the control-bagged treatment, resulting in fruits that were 20 g heavier (115.4 g vs. 95.6 g, 95% CI). Similarly, the number of seeds per fruit and the fruit shape index (FSI) increased in treatments exposed to bee visitation when compared to the bagged control. However, differences in bee visitation among treatments suggested a non-linear relationship between bee activity and fruit quality. Nevertheless, achieving high-quality fruit standards across treatments could be explained by the extended floral lifespan, which allowed for a high number of visits and ensured pollination. Finally, we did not observe any bias in honeybee visitation by applying sugar syrup combined with the attractant. Hence, to increase honeybees’ visits to flowers, we recommend applying the scent directly in a water solution. Full article

Clarifying the trade-offs and synergies between land use and ecosystem services in major water source river basins is enhancing regional land resource distribution and safeguarding water-related ecological environments. The Danjiangkou Reservoir Basin—the water source area of the South-to-North Water Diversion Project—land use change characteristics from 2012 to 2022 were focused on in this study. Five categories of ecosystem services, represented by six land use-related indicators, were selected for analysis. The InVEST model was utilized to conduct a quantitative assessment of their spatial and temporal variations. This study investigates the spatial variations of ecosystem services, analyzes their trade-offs and synergies, and explores the impacts of land use changes on the supply and interactions of these services. The findings reveal that cultivated land was served as the dominant source of land use conversion. Specifically, the largest areas of cultivated land conversion were to forest land (240.91 km²), followed by water bodies (144.65 km²) and construction land (38.43 km²). The selected ecosystem services exhibited distinct temporal and spatial variation: water yield, total carbon storage, and habitat quality showed upward trends, whereas total nitrogen output, total phosphorus output, and soil erosion demonstrated declining trends. Overall, the synergy and trade-off relationships among the six ecosystem service indicators weakened; however, the degree of improvement in trade-offs exceeded the decline in synergies. The integration of land use change, ecosystem service functions, and trade-off/synergy relationships into a unified analytical framework facilitates a robust theoretical foundation for basin-scale ecological management. This approach offers a scientific foundation for spatial optimization, ecological redline delineation, and resource allocation within the basin. Full article

The Internet of Things (IoT) has become an integral part of today’s smart and digitally connected world. IoT devices and technologies now connect almost every aspect of daily life, generating, storing, and analysing vast amounts of data. One important use of IoT is in utility management, where essential services such as water are supplied through IoT-enabled infrastructure to ensure fair, efficient, and sustainable delivery. The large volumes of data produced by water distribution networks must be safeguarded against manipulation, theft, and other malicious activities. Incidents such as the Queensland user data breach (2020–21), the Oldsmar water treatment plant attack (2021), and the Texas water system overflow (2024) show that attacks on water treatment plants, distribution networks, and supply infrastructure are common in Australia and worldwide, often due to inadequate security measures and limited technical resources. Lightweight cryptographic algorithms are particularly valuable in this context, as they are well-suited for resource-constrained hardware commonly used in IoT systems. This study focuses on the in-house developed ChaosFortress lightweight cryptographic algorithm, comparing its performance with other widely used lightweight cryptographic algorithms. The evaluation and comparative testing used an Arduino and a LoRa-based transmitter/receiver pair, along with the NIST Statistical Test Suite (STS). These tests assessed the performance of ChaosFortress against popular lightweight cryptographic algorithms, including ACORN, Ascon, ChaChaPoly, Speck, tinyAES, and tinyECC. ChaosFortress was equal in performance to the other algorithms in overall memory management but outperformed five of the six in execution speed. ChaosFortress achieved the quickest transmission time and topped the NIST STS results, highlighting its strong suitability for IoT applications. Full article

Forest litter plays a critical role in regulating the water balance of forest ecosystems, particularly in semi-arid regions where hydrological stability is under pressure due to climate change. This study investigates the maximum water holding capacity (MWHC) of litter layers across three ecologically distinct regions in Türkiye—Kastamonu, Kütahya, and Muğla—to evaluate how structural and physicochemical characteristics influence the maximum water holding capacity (MWHC) of litter layers. Litter samples classified into humus, fermenting debris, and needles were analyzed for MWHC, pH, electrical conductivity (EC), and total dissolved solids (TDSs). The results revealed that both the type of litter and regional ecological conditions significantly affect MWHC, with humus layers and moist environments exhibiting the highest water holding capacity. Additionally, MWHC showed moderate positive correlations with EC and TDS, highlighting the importance of chemical composition in water dynamics. The findings underscore that forest litter should be regarded as a dynamic and functional hydrological component, not merely residual biomass. This perspective is vital for sustainable watershed planning and adaptive forest management. The study supports the development of integrated management strategies aligned with the United Nations Sustainable Development Goals (SDGs), particularly SDG 6 (Clean Water and Sanitation), SDG 13 (Climate Action), and SDG 15 (Life on Land). Full article

Clarifying the spatiotemporal relationship between urban ecosystem services and changes in landscape patterns is essential, as it has significant implications for balancing ecological protection with socio-economic development. However, existing studies have largely focused on the one-sided impact of landscape patterns on either the supply or demand of ESs, with limited investigation into how changes in these patterns affect the growth rates of both supply and demand. The central urban area, characterized by complex urban functions, intricate land use structures, and diverse environmental challenges, further complicates this relationship; yet, the spatiotemporal differentiation patterns of ecosystem services’ supply–demand dynamics in such regions, along with the underlying influencing mechanisms, remain insufficiently explored. To address this gap, the present study uses Shenyang’s central urban area, China as a case study, integrating multiple data sources to quantify the spatiotemporal variations in landscape pattern indices and five ecosystem services: water retention, flood regulation, air purification, carbon sequestration, and habitat quality. The XGBoost model is employed to construct non-linear relationships between landscape pattern indices and the supply–demand ratios of these services. Using SHAP values and LOWESS analysis, this study evaluates both the magnitude and direction of each landscape pattern index’s influence on the ecological supply–demand ratio. The findings outlined above indicate that: there are distinct disparities in the spatiotemporal distribution of landscape pattern indices at the patch type level. Additionally, the changing trends in the supply, demand, and supply–demand ratios of ecosystem services show spatiotemporal differentiation. Overall, the ecosystem services in the study area are developing negatively. Further, the impact of landscape pattern characteristics on ecosystem services is non-linear. Each index has a unique effect, and there are notable threshold intervals. This study provides a novel analytical approach for understanding the intricate relationship between landscape patterns and ESs, offering a scientific foundation and practical guidance for urban ecological protection, restoration initiatives, and territorial spatial planning. Full article

Smallholder farmers play a pivotal role in food production and rural development in South Africa. However, their productivity is often constrained by reliance on rainfed agriculture and the underutilisation of innovative technologies such as irrigation systems. This study assessed the impact of innovative irrigation system (IIS) use on crop yield among smallholder crop farmers (SCFs) in Mbombela Local Municipality. Focusing on vegetables and agronomic crop producers. Primary data was collected from 308 SCFs using a structured questionnaire through descriptive and cross-sectional survey design. A Probit regression model was used to estimate the probability of using an IIS, while Propensity Score Matching (PSM) estimated the average treatment effect on the treated (ATT) in terms of yield. The results reveal that age group (p = 0.080), main source of off-farm income (p = 0.042), and high input costs (p = 0.006) significantly determined IIS use. Impact analysis confirms that users of IISs achieved higher yields than non-users. The study concludes that innovative irrigation technologies can significantly improve smallholder productivity. It recommends that policymakers and government bodies prioritise scaling up access to IIS, introduce subsidies or low-interest financing schemes to alleviate the IIS usage costs, and strengthen extension services to provide targeted training on irrigation scheduling, system maintenance, and water-use efficiency. Full article