Water Coverage Research Articles

Unmasking MRSA antibiotic resistance: the impact of environment, pollution, and healthcare quality—a nationwide exploration in China: a comprehensive analysis spanning 2014 to 2021 in mainland China

BackgroundThe rise of antibiotic resistance has become a critical global health concern, resulting in numerous fatalities annually. Among resistant pathogens, methicillin-resistant Staphylococcusaureus (MRSA) poses a particularly severe and expanding threat. However, there is a lack of comprehensive studies on the prevalence, patterns, and contributing factors of MRSA resistance within mainland China.MethodsIn this study, the data of MRSA antimicrobial resistance in 31 provinces from 2014 to 2021 were obtained from the China Antimicrobial Resistance Surveillance System (CARSS). Environment and medical care data were obtained either from the National Bureau of Statistics (NBS) database or the National Ministry of Ecology and Environment (NMEE). Multiple linear regression and restricted cubic spline (RCS) was used to explore the potential influencing factors of MRSA antibiotic resistance rate (AMR).ResultsSignificant positive associations were identified between MRSA AMR and various factors, including cadmium pollution, soybean and poultry production, and oil consumption. Conversely, an inverse J-shaped relationship was observed between tap water coverage and MRSA resistance. Other noteworthy correlations included the effects of corn and pork production, as well as antibiotic use intensity. Our predictive model explained 52.7% of the variability in MRSA AMR, demonstrating strong predictive capability.ConclusionsThis study highlights the significant role of environmental, agricultural, and healthcare factors in influencing MRSA AMR in China. The findings emphasize the need for integrated strategies addressing regional environmental and healthcare quality in combating antibiotic resistance. Extending this research globally could enhance understanding of MRSA resistance dynamics on a broader scale.Graphical

Far-Ultraviolet Plexciton Formation in Water-Covered Indium Clusters.

In this work, we study the plexciton in the far-ultraviolet region formed between indium nanoclusters and water molecules. The indium clusters are fabricated on graphene under ultrahigh vacuum conditions and show a strong localized surface plasmon polariton (LSP) absorption band at 6-7 eV. Adsorption of water molecules onto the clusters at 115 K induces a band splitting larger than 1 eV, indicating a strong coupling between the LSP and water 4a1 ← 1b1 transition. The spectral evolution as a function of the water coverage is revealed, enabling the determination of the decay length of the plexciton collective effect to be ∼8 nm.

Mapping of water spread dynamics of a tropical Ramsar wetland of India for conservation and management.

Wetlands are dynamic ecosystems vital for sustaining ecological health and development at regional and global scales. Geospatial tools have emerged as essential for managing wetland ecosystems. This study assessed the spatiotemporal dynamics of water spread in the Point Calimere Wetland, a coastal Ramsar site located along the Bay of Bengal, India, from 1984 to 2023. The analysis based on Global Surface Water Explorer (GSWE) and Normalized Difference Water Index (NDWI) derived from Landsat 5, 7, and 8 data revealed that 21% of the total wetland area showed an increasing trend. In comparison, 5.7% of the area showed a decreasing trend of surface water coverage, largely driven by erosion and climatic variability. The mean water spread increased from 119.47 km2 (2000-2003) to 160.88 km2 (2020-2023), with notable seasonal fluctuations. Among all seasons, the monsoon with the highest surge (41.1%) in water dynamics reported the largest water spread in 2020-2023 (221.87 km2). A moderate positive and negative relationship was noted between rainfall and water spread (r = 0.35) and temperature and water spread (r = - 0.43). A marked increase in habitat patches and edge density between 2000-2003 and 2020-2023 indicates the wetland's vulnerability to changing climatic conditions and the critical role of seawater intrusion, shoreline changes, and tidal forces in shaping its hydrological dynamics. The data presented on the historical water dynamics in this study is invaluable for the conservation planning and management of wetlands to support the associated coastal biodiversity and livelihood of the dependent communities.

Soybean Water Monitoring and Water Demand Prediction in Arid Region Based on UAV Multispectral Data

Soil moisture content is a key factor influencing plant growth and agricultural productivity, directly impacting water uptake, nutrient absorption, and stress resistance. This study proposes a rapid, low-cost, non-destructive method for dynamically monitoring soil moisture at depths of 0–200 cm throughout the crop growth period under dryland conditions, with validation in soybean cultivation. During critical soybean growth stages, UAV multispectral data of the canopy were collected, and ground measurements were conducted for three GPS-referenced 50 cm × 50 cm plots to obtain canopy leaf water content, coverage, and soil volumetric moisture at 20 cm intervals. Ten vegetation indices were constructed from multispectral data to explore statistical relationships between vegetation indices, surface soil moisture, canopy leaf water content, and deeper soil moisture. Predictive models were developed and evaluated. Results showed that the NDVI-based nonlinear regression model achieved the best performance for leaf water content (R2 = 0.725), and a significant correlation was found between canopy leaf water content and 0–20 cm soil moisture (R2 = 0.705), enabling predictions of deeper soil moisture. Surface soil models accurately estimated 0–200 cm soil moisture distribution (R2 = 0.9995). Daily water dynamics simulations provided robust support for precision irrigation management. This study demonstrates that UAV multispectral remote sensing combined with ground sampling is a valuable tool for soybean water management, supporting precision agriculture and sustainable water resource utilization.

Numerical Study on Fire Suppression by Water Mist in Aircraft Cargo Compartments: Effects of Spray Pattern, Droplet Size, and Nozzle Layout

Aircraft cargo compartment fires are one of the main threats to the safety of civil aircraft. In this study, a series of numerical simulations on the fire suppression performance of water mist in cargo compartments was carried out to examine the effects of the spray pattern, droplet size, and nozzle layout. The fire dynamics simulator (FDS) code was used to construct a fire suppression scenario in a full-scale aircraft cargo compartment. The results show that the extinguishment time of a corner fire was longer compared with center and sidewall fires due to the relatively larger distance from the nozzle and, therefore, a lower effective number of droplets reaching the flame area. Solid and hollow spray patterns showed significant differences in the spray coverage area. For a fixed flow rate, the hollow spray showed better fire suppression performance than solid spray. When the droplet size varied from 50 to 400 µm, the fire extinguishment time first increased and then decreased, corresponding to the dominant mechanism of the smothering effect of small droplets and the cooling effect of large droplets. In addition, the nozzle layout affected the water coverage on the ground of the cargo compartment. With an increase in nozzle number, the water mist flux was more evenly distributed and the fire extinguishment effect also increased.

MONITORAMENTO DE RECURSOS HIDRÍCOS POR ALTIMETRIA ESPACIAL

Although most of the space missions discussed here have not been primarily dedicated to hydrology, 31 years of spatial altimetry have provided complementary data that can be used to create hydrological products for watersheds, such as time series water levels, estimates of river flows, longitudinal riverbed altitude profiles, minimum and maximum elevations, or leveling of stations in situ. The raw data still suffer from uncertainties of several decimeters. Today, altimetry techniques are evolving rapidly. One direction is the change of the radar band, from Ku to Ka. Another change is the replacement of the current LR Mode with SAR or Interferometry modes. Both evolutions tend to drastically decrease the imaged range, reducing both the contamination of the echo by the environment of the water body, and improving the vertical accuracy. Finally, as of 2015, the research missions were replaced by operational ones, making the longevity of the sampling sites more certain. All the aforementioned technical evolutions have been grouped together in the SWOT mission, a Ka-band interferometric altimeter, the first satellite mission actually dedicated to providing full coverage of continental waters, launched in December 2022.

Hydrological dynamics and its impact on wetland ecological functions in the Sanjiang Plain, China

The hydrological environment of wetlands is vital for ensuring the stable development of their ecological functions. However, previous sample-scale studies have failed to capture the spatial heterogeneity of the hydrology-function relationship. The objective of this study is to elucidate the hydrological driving mechanisms responsible for the formation of and changes in the spatial patterns of wetland functions at different spatial and time scales. This study established a multi-dimensional hydrological element and wetland function index system through space technology and multi-source remote sensing images and proposed a multi-scale hydrology-function relationship analysis framework to reveal the relationships between hydrological elements and wetland function spatial patterns at different spatial and temporal scales. The final results demonstrated that, at different spatial and time scales, increasing water coverage contributes greatly to the improvement of habitat, soil conservation, and water supply functions, and increasing the flooding frequency and connectivity structure are more effective at improving the water purification function. At the grid scale, the proportion of grids with medium or strong correlations ranges from 26.63 % to 51.19 %, whereas with respect to temporal correlations, the proportion of grids with medium or strong correlations ranges from 50.67 % to 92.76 %, indicating a pronounced scale effect and spatial heterogeneity of the hydrology-function relationship. The opposite relationships between hydrological elements and functions in some grids (with proportions ranging from 9.89 % to 37.38 %) may result from geographical, environmental constraints, which disrupt the normal correlation between hydrological elements and wetland functions. This study contributes to a deep understanding of the hydrological driving mechanism of wetland functional patterns and provides guidance for wetland protection and restoration planning and hydrological condition regulation by developing specific strategies for improving ecological function.

(Invited) Treated Perfluorosulfonic Acid Ionomer Layer with Dual Oxygen Transport Pathways for PEMFC Cathode Catalyst Layer

A hydrophobic treatment was developed to reduce the liquid water saturation level and increase its removal rate from the cathode catalyst layer (CL) of a PEM fuel cell with the expected outcome to be higher performance in the transport-controlled region. However, test results show improvement (> 200% increase in peak power)[1] in both kinetic and transport-controlled regions. Further investigation by mathematical modeling and neutron reflectometry shows the treatment affects the CL in two ways. First, the ionomer/gas phase interface in the pores of the CL becomes more hydrophobic. This facilitates less liquid water coverage of the ionomer layer surface and faster water drainage from the CL that results in better performance at high current densities, which is as expected. Second, it affects the microstructures of the ionomer phase and causes it to separate into two regions, a larger more hydrophobic (or less hydrophilic) region with fewer sulfonic acid groups and therefore lower water hydration levels and a smaller less hydrophobic (or more hydrophilic) region with more ionic groups with higher hydration levels. The more hydrophobic region, which facilitates faster liquid water removal from its interface with the gas pores and direct access to the oxygen gas at higher current densities, provides a higher oxygen solubility pathway to the catalyst active sites in CL at both low and high current densities leading to higher fuel cell performance over the whole polarization curve. See image. The ratio of these two regions can be controlled by the treatment process. This presentation will discuss the hydrophobic treatment process and the major findings of this study.References Regis P. Dowd, Yuanchao Li, Trung Van Nguyen, “Controlling the Ionic Polymer/Gas Interface Property of a PEM Fuel Cell Catalyst Layer During Membrane Electrode Assembly Fabrication,” Appl. Electrochem., 50 (10) 993-1006 (2020).Yuanchao Li and Trung Van Nguyen, “A One-Dimensional Model of the Cathode Catalyst Layer of a PEM Fuel cell Hydrophobically Treated for Water Management,” J. Electrochemical Society, 169 114505 (2022). Figure 1

SuperWater: Predicting Water Molecule Positions on Protein Structures by Generative AI.

Water molecules play a significant role in maintaining protein structural stability and facilitating molecular interactions. Accurate prediction of water molecule positions around protein structures is essential for understanding their biological roles and has significant implications for protein engineering and drug discovery. Here, we introduce SuperWater, a novel generative AI framework that integrates a score-based diffusion model with equivariant graph neural networks to predict water molecule placements around proteins with high accuracy. SuperWater surpasses existing methods, delivering state-of-the-art performance in both crystal water coverage and prediction precision, achieving water localization within 0.3 ± 0.06 Å of experimentally validated positions. We demonstrate the capabilities of SuperWater through case studies involving protein hydration, protein-ligand binding, and protein-protein binding sites. This framework can be adapted for various applications, including structural biology, binding site prediction, multi-body docking, and water-mediated drug design.

Surface temperature change amplifies social inequality in heat exposure? Evidence from Shanghai, China

Heat-related environmental justice has gained increasing attention, with many studies focusing on social inequalities in exposure to extreme surface temperatures. However, changes in land surface temperature (LST) also contribute to residents’ thermal discomfort, underscoring the need to explore inequalities in exposure to these changes. This study addresses this gap by analyzing spatial and social disparities in exposure to both LST changes and summer LST in Shanghai. We employed a boosted regression tree model to quantify LST changes, offering better predictive performance than traditional linear regression, and used geographically weighted regression with data from China's sixth population census to assess the city-wide and local scale inequality differences in exposure to LST changes and summer LST. Our findings reveal that 57.83 % of Shanghai's subdistricts experienced above-average LST changes and summer LST. Specific groups—males (22.17 %), children (22.61 %), the elderly (13.04 %), and residents in older housing (60.87 %)—were disproportionately exposed to local-scale LST changes. In contrast, those employed in agriculture, forestry, and fisheries faced consistently lower exposure. Furthermore, exposure to LST changes was 3.47 % higher among the elderly and 28.26 % higher for residents in older housing compared to exposure based on summer LST alone. To mitigate these inequalities, we recommend increasing water coverage and green roofs, enhancing green infrastructure in aging neighborhoods, and providing financial subsidies for outdoor workers. These findings emphasize the importance of addressing social inequalities in exposure to temperature changes to enhance urban resilience and promote sustainable urban planning in the face of climate change.

FUSING SATELLITE DATA TO MONITOR SEA LEVEL CHANGES: A DEM-BASED NEAREST NEIGHBOR APPROACH

High spatial and temporal resolution satellite imagery is essential for monitoring rapid environmental changes at finer scales. However, no single satellite currently provides images with both high spatial and temporal resolution. To overcome this limitation, spatiotemporal image fusion algorithms have been developed to generate images with improved spatial and temporal detail. Water level monitoring is also crucial for managing natural hazards like floods and tsunamis, but remote sensing satellites face challenges in continuous monitoring due to either low spatial or temporal resolution. For instance, while Landsat 8, with a spatial resolution of 30 meters, has been used for water level detection, it cannot capture fast-changing events because of its low temporal resolution. Conversely, the Advanced Himawari Imager (AHI) 8 offers observations every 10 minutes but has a coarse spatial resolution, limiting its ability to map sea level changes accurately. This study focuses on integrating Landsat and AHI imagery to monitor local and dynamic sea level changes. The process involves calibrating images from the study area to surface reflectance and co-registering them. The Normalized Difference Water Index (NDWI) is calculated from both Landsat and Himawari-8 images, serving as input for image fusion. In the previous study, the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) is used for image fusion. In this study we use the application of Spatial Temporal Adaptive Algorithm for Mapping Reflectance Change (STAARCH) for the image fusion step. Since traditional methods are influenced by land cover changes, this study proposes a method called DEM-based Nearest Neighbor to select appropriate land cover maps for image fusion. Evaluation results demonstrate that this approach can produce accurate water coverage maps with both high spatial and temporal resolution.

Effects of droplet dynamical behavior in flow channel of proton exchange membrane fuel cell under vibration conditions on cell performance

Proton exchange membrane fuel cells are subjected to severe vibration in aerospace applications. Understanding the droplet transport characteristics in the flow channelunder vibration conditions is essential for improving cell performance. However, the underlying patterns and mechanisms of the vibration effects on cell performance and its internal water transport remain unclear, and there is a lack of improvement methods for drainage under vibration conditions. This study experimentally investigates the effect of vibration on cell performance. Experimental results indicate that vibration predominantly affects cell performance through its modulation of water transport. Therefore, the droplet dynamic behavior in the flow channel is further studied using the volume of fluid method. The results indicate that vibrations can enhance the average performance of the fuel cells, with the largest increase of 8.30 %. This is attributed to vibrations promoting the detachment of droplets from the gas diffusion layer surface and reducing the water coverage ratio on said surface. Under conditions of low gas velocity, high surface hydrophobicity, and large droplet size, droplets exhibited oscillatory and jumping behavior in the flow channel due to vibration, resulting in the largest 53.5 % increase in peak water coverage ratio on the gas diffusion layer surface compared to no-vibration conditions. Furthermore, enhancing the hydrophobicity of the gas diffusion layer and the hydrophilicity of the channel walls promotes droplet detachment and discharge compared to no-vibration, as well as contributing to the improvement of vibration effects on the drainage process.

Strain Effects on the Adsorption of Water on Cerium Dioxide Surfaces and Nanoparticles: A Modeling Outlook.

Nanocrystalline ceria exhibits significant redox activity and oxygen storage capacity. Any factor affecting its morphology can tune such activities. Strain is a promising method for controlling particle morphology, whether as core@shell structures, supported nanoparticles, or nanograins in nanocrystalline ceria. A key challenge is to define routes of controlling strain to enhance the expression of more active morphologies and to maintain their shape during the lifespan of the particle. Here, we demonstrate a computational route to gain insights into the strain effects on particle morphology. We use density functional theory to predict surface composition and particle morphology of strained ceria surfaces, as a function of environmental conditions of temperature and partial pressure of water. We find that adsorbed molecular water is not sufficient to shift stability and as such under all compressive and tensile strains studied, the most stable particle is of octahedral shape, similarly to the unstrained case. When dissociative water is involved at the surfaces of the particle, then the most stable particle morphology changes under high water coverage and tensile strain to cuboidal or truncated cuboidal shapes. This shift in shape is due to strain effects that affect the strength of water adsorption.

Dust aerosol from the Aralkum Desert influences the radiation budget and atmospheric dynamics of Central Asia

Abstract. The Aralkum is a new desert created by the desiccation of the Aral Sea and is an efficient source of dust aerosol which perturbs the regional Central Asian radiation balance. COSMO–MUSCAT model simulations are used to quantify the direct radiative effects (DREs) of Aralkum dust, and investigate the associated perturbations to the atmospheric environment. Considering scenarios of “Past” (end of 20th century) and “Present” (beginning of 21st century) defined by differences in surface water coverage, it is found that in the Present scenario the simulated yearly mean net surface DRE across the Aralkum is −1.34 W m−2 with a standard deviation (±) of 6.19 W m−2, of which −0.15 ± 1.19 W m−2 comes from dust emitted by the Aralkum. In the atmosphere the yearly mean DRE is −0.62 ± 2.91 W m−2, of which −0.05 ± 0.51 W m−2 is from Aralkum dust: on the yearly timescale, Aralkum dust is cooling both at the surface and in the atmosphere, due to its optically scattering properties. The daytime surface cooling effect (solar zenith angle ≲ 70–80°) outweighs the nighttime heating effect and the atmospheric daytime (solar zenith angle ≲ 60–70°) heating and nighttime cooling effects. Instantaneous Aralkum dust DREs contribute up to −116 W m−2 of surface cooling and +54 W m−2 of atmospheric heating. Aralkum dust perturbs the surface pressure in the vicinity of the Aralkum by up to +0.76 Pa on the monthly timescale, implying a strengthening of the Siberian High in winter and a weakening of the Central Asian heat low in summer. These results highlight the impacts of anthropogenic lakebed dust on regional atmospheric environments.

Forecasting malaria dynamics based on causal relations between control interventions, climatic factors, and disease incidence in western Kenya.

Malaria remains one of the deadliest diseases worldwide, especially among young children in sub-Saharan Africa. Predictive models are necessary for effective planning and resource allocation; however, statistical models suffer from association pitfalls. In this study, we used empirical dynamic modelling (EDM) to investigate causal links between climatic factors and intervention coverage with malaria for short-term forecasting. Based on data spanning the period from 2008 to 2022, we used convergent cross-mapping (CCM) to identify suitable lags for climatic drivers and investigate their effects, interaction strength, and suitability ranges on malaria incidence. Monthly malaria cases were collected at St. Elizabeth Lwak Mission Hospital. Intervention coverage and population movement data were obtained from household surveys in Asembo, western Kenya. Daytime land surface temperature (LSTD), rainfall, relative humidity (RH), wind speed, solar radiation, crop cover, and surface water coverage were extracted from remote sensing sources. Short-term forecasting of malaria incidence was performed using state-space reconstruction. We observed causal links between climatic drivers, bed net use, and malaria incidence. LSTD lagged over the previous month; rainfall and RH lagged over the previous two months; and wind speed in the current month had the highest predictive skills. Increases in LSTD, wind speed, and bed net use negatively affected incidence, while increases in rainfall and humidity had positive effects. Interaction strengths were more pronounced at temperature, rainfall, RH, wind speed, and bed net coverage ranges of 30-35°C, 30-120 mm, 67-80%, 0.5-0.7 m/s, and above 90%, respectively. Temperature and rainfall exceeding 35°C and 180 mm, respectively, had a greater negative effect. We also observed good short-term predictive performance using the multivariable forecasting model (Pearson correlation coefficient = 0.85, root mean square error = 0.15). Our findings demonstrate the utility of CCM in establishing causal linkages between malaria incidence and both climatic and non-climatic drivers. By identifying these causal links and suitability ranges, we provide valuable information for modelling the impact of future climate scenarios.

Potentials of Green Hydrogen Production in P2G Systems Based on FPV Installations Deployed on Pit Lakes in Former Mining Sites by 2050 in Poland

Green hydrogen production is expected to play a major role in the context of the shift towards sustainable energy stipulated in the Fit for 55 package. Green hydrogen and its derivatives have the capacity to act as effective energy storage vectors, while fuel cell-powered vehicles will foster net-zero emission mobility. This study evaluates the potential of green hydrogen production in Power-to-Gas (P2G) systems operated in former mining sites where sand and gravel aggregate has been extracted from lakes and rivers under wet conditions (below the water table). The potential of hydrogen production was assessed for the selected administrative unit in Poland, the West Pomerania province. Attention is given to the legal and organisational aspects of operating mining companies to identify the sites suitable for the installation of floating photovoltaic facilities by 2050. The method relies on the use of GIS tools, which utilise geospatial data to identify potential sites for investments. Basing on the geospatial model and considering technical and organisational constraints, the schedule was developed, showing the potential availability of the site over time. Knowing the surface area of the water reservoir, the installed power of the floating photovoltaic plant, and the production capacity of the power generation facility and electrolysers, the capacity of hydrogen production in the P2G system can be evaluated. It appears that by 2050 it should be feasible to produce green fuel in the P2G system to support a fleet of city buses for two of the largest urban agglomerations in the West Pomerania province. Simulations revealed that with a water coverage ratio increase and the planned growth of green hydrogen generation, it should be feasible to produce fuel for net-zero emission urban mobility systems to power 200 buses by 2030, 550 buses by 2040, and 900 buses by 2050 (for the bus models Maxi (40 seats) and Mega (60 seats)). The results of the research can significantly contribute to the development of projects focused on the production of green hydrogen in a decentralised system. The disclosure of potential and available locations over time can be compared with competitive solutions in terms of spatial planning, environmental and societal impact, and the economics of the undertaking.

Microhabitat coverage influences avian species composition more than habitat heterogeneity in Hong Kong urban parks

The relationship between habitat heterogeneity and diversity can underpin design of urban spaces for biodiversity conservation. The area-heterogeneity trade-off hypothesis predicts that higher habitat heterogeneity should result in an increase in species richness but only up to a point, beyond which habitat micro-fragmentation leads to decreases in species diversity. However, the strength of area-heterogeneity trade-offs at small spatial scales is not well studied. We studied the relationship between avian diversity and habitat heterogeneity in 16 small urban parks across Hong Kong during the winter dry season across 2016 and 2017 (ten repeated surveys in total for each park). Habitat heterogeneity was assessed by measuring the evenness of microhabitat coverage of seven habitats as well as vertical canopy cover. In total, 12,973 individuals of 73 bird species were recorded in the study. Habitat heterogeneity had a small but negligible effect on total bird species richness or abundance. However, water coverage was positively related to total, intermediately rare and habitat specialist bird species richness, and shrub coverage was positively related to total and common bird species richness. These results demonstrate that environmental heterogeneity had little effect on avian species richness in urban green spaces at small spatial scales. We also found that microhabitat coverage can affect avian diversity and abundance, and these effects are specific to certain groups of bird species. When managing urban green spaces for biodiversity conservation in densely urbanized cities, a decrease in management disturbance (e.g. tree topping or pesticide application) will likely benefit avian species. Together with the fact that some locally uncommon species were observed throughout the study, capacity exists for environmental enhancement of these small urban parks to contribute to local avian conservation.

Carbon emission from the Lower Ob River floodplain during spring flood

Carbon emission from Arctic rivers constitutes a positive feedback between the climate warming and C cycle. However, in case of rivers with extensive floodplains, the impacts of temporary water bodies and secondary channels on CO2 exchange with atmosphere, compared to the main stem and tributaries, remain strongly understudied. In order to quantify the relative role of various water bodies of the Arctic river basin in the C cycle, the hydrochemical variables and greenhouse gases GHG concentrations and fluxes were measured within the floodplain of the largest Arctic River, Ob, in its low reaches located in the permafrost zone. These included the main stem, secondary channels, tributaries and floodplain lakes sampled over a 900 km north-south transect (25,736 km2 of the main stem and adjacent floodplain area; 7893 km2 water surface) during peak of spring flood (May 2023). In addition to main stem and tributaries, providing less than a half of overall C flux, floodplain lakes and secondary channels acted as important factor of C emission from the floodplain water surfaces. Multi-parametric statistical treatment of the data suggested two main processes of C emission from the Ob River floodplain waters: terrestrial organic matter-rich flooded wetlands (fens) provided elevated pCO2, whereas the sites of possible groundwater discharge in the secondary channels decreased the CO2 fluxes due to more alkaline environments, rich in labile metals and anionic elements.Based on available high-resolution Landsat-8 images, which matched the period of field work, it was found that the total water coverage of the floodplain during spring 2023 was 30 % of overall territory, compared to 18 % during the baseflow. Based on chamber-measured CO2 fluxes (1.56 ± 0.47 g C-CO2 m−2 d−1), overall CO2 emissions during 2 months of the spring flood from the entire Lower Ob River floodplain water surfaces including the main stem amounted to 0.73 ± 0.25 Tg C. Diffuse CH4 flux represented <1 % of total C flux. The main stem of the Ob River accounted for 34 % and 18 % of CO2 and CH4 emissions, respectively, whereas the floodplain lakes provided 59 % and 50 % of CO2 and CH4 emission, respectively. Considering that the low reaches of the Ob River represent >70 % of total river basin floodplain, and that during some years, the entire floodplain can be covered by water, emissions from the river – if assessed solely from summer (July–August) measurements – can be at least 3 times underestimated. It is therefore important to account for extended water surface during high water levels on Arctic rivers when assessing global riverine C emissions.

Implication of Urban Domestic Water Distribution on Human Health in Machakos Central Ward, Machakos County

The world's water resources are running out, and this situation is made worse by how quickly people are populating new areas, particularly in developing nations. This has highlighted the critical requirement for prepared action to manage water resources for sustainable development efficiently. Increasing water demands due to climate change, global pressures from urbanization, the already-existing unsustainable variables, and challenges of water supply systems in urban centres pose a challenge in managing water resource effectively. The purpose of the study was to investigate the implication of urban domestic water supply on human health in Machakos Central Ward, Machakos County. Using a Survey Research Design (SRD) both primary and secondary data was collected by use of questionnaires, face-to-face interviews, photography, use of GIS, authors’ observation, and the review of relevant literature in order to (1) document household water supply, (2) determine water quality for the identified categories of households and domestic water supply systems, and (3) Determine how the distribution and coverage of domestic water in a household or home affects the prevalence of water-borne illnesses. The target population was 8,331 households, from which a sample size of 381 respondents was selected. These included households, water vendors and key informants from the Machakos Water and Sewerage Company. Questionnaires (for households and vendors), interview schedules (for water officers and chiefs) and observation schedules were used as instruments for data collection. Data was analysed using Microsoft Excel and Statistical Package for Social Sciences (SPSS) software. The results revealed that the major factors attributed to lower accessibility are shortage of water, high cost of piped water connection, poor coordination, and participation of stakeholders, repairing of old and broken pipes. As a result, nearly half of the dwellers prefer to use alternative sources, exposing them to the risks of water-born diseases

Disparities in access to water, sanitation, and hygiene (WASH) services and the status of SDG-6 implementation across districts and states in India

IntroductionAccess to affordable and improved Water, Sanitation, and Hygiene (WASH) facilities is essential for people's daily lives, and it is the primary goal of Sustainable Development Goal 6 (SDG-6). However, achieving this goal is a significant challenge for many countries, including India. The aim of this study is to assess the progress made towards achieving SDG-6 targets in Indian districts, states, and Union Territories (UTs) and to identify clusters by measuring spatial inequality of WASH coverage in India. Aim and objectiveThe primary objective of this study is to measure the progress made towards achieving the SDG-6 targets for WASH facilities in Indian districts, states, and UTs. To fulfill this objective, the study used the household data of the National Family Health Survey-5 (NFHS-5) conducted from 2019 to 21. Data and methodsThe study used the household data of NFHS-5, which is a nationally representative survey that provides information on household and individual-level characteristics related to health and nutrition. The study identified the variables associated with WASH and created a composite index to measure WASH coverage separately and combined. The study used Gini coefficient to show WASH inequality, and Moran's statistics were used to show spatial dependency. ResultThe study found that the inequality of improved water coverage sources in Indian districts was high. Western and northeastern districts need to catch up in terms of achieving the SDG-6 targets. The value of the Gini coefficient (0.29) indicates that inequality in sanitation coverage is also high. All states have reached close to SDG-6 achievement in hygiene indicators. Goa, Sikkim, Andaman & Nicobar Islands, and Lakshadweep are close to the overall WASH coverage achievements of SDG-6. However, Jharkhand, Orissa, Tripura, Assam, and Rajasthan are behind in meeting the goal of SDG-6. ConclusionThe study suggests that more government initiatives and investments are needed to increase the availability, accessibility, and affordability of WASH facilities to improve WASH conditions in western and northeastern Indian districts. The localization or bottom-up approach by giving responsibility to rural and urban local bodies can also help enforce the achievement of SDG-6. The findings of this study can be used to guide policymakers in developing targeted interventions to improve WASH conditions and reduce inequality in India.