BACKGROUND: Soil-transmitted helminth (STH) is a group of helminths that are considered to be neglected tropical diseases (NTDs) and, globally, affect more than 1.5 to 2.6 million people yearly. Depending on the species, they can be acquired by ingesting embryonated eggs from contaminated matter or by skin penetration. Most species of STH are found in the tropics, such as the Philippines. Despite the Mass Drug Administration (MDA), the cases of STH infection continue to rise in the country. Surveys from the Research Institute of Tropical Medicine (RITM) indicate that a high prevalence of STH (Ascaris lumbricoides, Trichuris trichiura, and Necator americanus) was primarily observed in the provinces of the country, such as in Camarines Sur.
OBJECTIVE: To correlate remote sensing covariates such as Normalized Difference Vegetation Index (NDVI) and Normalized Difference Built-up Index (NDBI) - to STH-infected cases of the 37 municipalities of Camarines Sur.
METHODS: The available public health record of STH cases from 2015 to 2019 were calculated using the Quantum Geographic Information System (QGIS)and correlated using Pearson Correlation Coefficient.
RESULTS: The results showed that infection was higher in children than adults, and A. lumbricoides caused 60% of infection. No correlation of indices with infection cases during 2015 and 2017 was observed; however, 2019 showed a moderate strength (p = 0.037) in correlation.
CONCLUSIONS: This indicates that infection relied not mainly on vegetation and urbanization but on additional environmental factors and non-environmental variables.

Plastic pollution has emerged as a significant environmental challenge worldwide, posing serious threats to ecosystems and human health. This study seeks to explore the interplay among circularity, sustainability, and the release of microplastics within the freshwater ecosystems situated along the western Black Sea coast- Düzce, Türkiye. Employing a multidisciplinary approach that integrates environmental science, economics, and policy analysis, the research examines the current state of plastic pollution in the region, considering diverse land uses and socio-economic lifestyles. Conducted over four different seasons, the current study identifies the prevailing types of microplastics in the region. Fibers dominate, comprising 86.7% in each season, followed by film and fragments at 7.7% and 7.0%, respectively. Notably, polyethylene (PE) and polypropylene (PP) emerges as the primary polymer types. The distribution of polymer types varies across different land uses within the region, emphasizing the influential role of land use in shaping the abundance polymer composition. The comprehensive assessment of pollution, as reflected in the overall pollution load index (PLI) of the Melen River indicating a concerning level of pollution (PLI>1). Finally, the study unveiled the relationship between socio-economic activities as well as the seasonal precipitation patterns, and microplastic contamination in the region. This underscored the importance of site-specific mitigation measures on reducing the amount of microplastics. Lastly, incorporating sustainable practices within the circular economy framework fosters a harmonious balance between economic development and environmental protection in Türkiye.

Noise pollution is an unintentional consequence of mining activities, needing rigorous assessment, monitoring, and mitigation techniques to reduce its impact on local residents and ecosystems. The study specifically examines the noise pollution from rare earth mining activities in the Neendakara-Kayamkulam (NK) coastal belt, Kollam, Kerala, India, a region rich in ilmenite, rutile, sillimanite, zircon, and monazite. Despite the known environmental and health impacts of noise pollution, there is limited specific data on its magnitude and sources in this region, as well as a lack of effective mitigation strategies tailored to rare earth mining operations. Studies have indicated that mining operations, such as the movement of heavy mineral sands, considerably elevate noise levels, which have an effect on the environment\'s quality and public health. This study seeks to fill the gap by geospatial mapping and assessing the noise levels and recommend measures to effectively mitigate noise pollution. Systematic noise measurements were conducted at 48 suitable locations within the NK coastal belt, including residential, commercial, industrial, coastal, and silence zones. The noise levels vary from 49.1 dB(A) near a religious place to 82.4 dB(A) near the local industry. The study employs geospatial noise mapping and land cover superimposition to implement class-specific mitigation measures for noise pollution in a coastal vicinity mixed land use area, including natural and vegetative barriers, operational scheduling, zoning, and land use planning.

In general, land use and layout of streets can have a significant impact on the behavior of drivers and pedestrians. In particular, streetscape has often been overlooked that recognizing the role of streetscape on street accident in urban areas is important. The aim of this research is to investigate the influence of streetscape and land use on urban accidents that occurred in Mashhad between the years 2017 and 2021. To achieve this objective, the study focused on analyzing accidents in three different urban zones. It also considered the land use types adjacent to both closed and open streets, including residential, commercial, and mixed land uses. The research employed various surveys to gather the necessary data and insights related to the targeted areas. Statistics on accident in three zones show that among the mentioned land uses, commercial areas have experienced the highest number of accidents, with their share being approximately three times that of accidents in residential areas. Additionally, 75 % of all accidents took place in areas with open streetscape, whereas accidents in areas with enclosed view accounted for one third of the number of accidents in open streetscape areas. In this research, analysis and modeling were conducted using machine learning algorithms implemented in the Python programming language. Several models were employed, and the best models were selected based on their performance and accuracy, which include Random Forest Regression (RFR), Multilayer Neural Network Perceptron Regression (MLP) and Extreme Boost Gradient Regression (XGBoost). The accuracy of the machine learning models which successfully predicted future outcomes was as follows: Random Forest Regression (RFR) achieved 85 % accuracy, Extreme Boost Gradient Regression (XGBoost) achieved 81 % accuracy, and finally, Neural Network Multilayer Perceptron Regression (MLP) achieved 75 % accuracy.

Rural areas are the main source of ecosystem services in arid and semi-arid areas, and ecosystem services are the background conditions for rural revitalization. In this study, the spatial pattern of key ecosystem services in the countryside was assessed, and the trade-offs and synergistic relationships among ecosystem services were investigated, using the Tacheng-Emin Basin in China as the study area. Finally, the types of ecological function zoning and development strategies for the countryside are proposed. The results showed that: (1) the area of ecological land was large, and the average land use intensity was 2.48, which belonged to the medium intensity. (2) The mean values of the six ecosystem services are all in the middle and lower classes, and the spatial distribution of the five ecosystem services is similar, except for food production. (3) Except for grain production, the other five ecosystem services showed positive feedback to elevation. The other five ecosystem services are synergistic, and there are trade-offs between grain production and other ecosystem services. In the nonlinear interaction mechanism of ecosystem services, the fluctuation constraint occupies the largest proportion. (4) At smaller spatial scales, there are more types of ecosystem service clusters. Combining the results of the study, the villages in the study area can be categorized into five types. This study formulates five priority levels of rural ecological revitalization and proposes different development recommendations for the sustainable development of each type of village. This study is helpful for the fine management of land resources and the revitalization of rural ecology and provides a reference for the sustainable development of ecosystem services in arid and semi-arid areas.

Despite concerted efforts in emission control, air pollution control remains challenging. Urban planning has emerged as a crucial strategy for mitigating PM2.5 pollution. What remains unclear is the impact of urban form and their interactions with seasonal changes. In this study, base on the air quality monitoring stations in the Yangtze River Delta urban agglomeration, the relationship between urban spatial indicators (building morphology and land use) and PM2.5 concentrations was investigated using full subset regression and variance partitioning analysis, and seasonal differences were further analysed. Our findings reveal that PM2.5 pollution exhibits different sensitivities to spatial scales, with higher sensitivity to the local microclimate formed by the three-dimensional structure of buildings at the local scale, while land use exerts greater influence at larger scales. Specifically, land use indicators contributed sustantially more to the PM2.5 prediction model as buffer zone expand (from an average of 2.41% at 100 m range to 47.30% at 5000 m range), whereas building morphology indicators display an inverse trend (from an average of 13.84% at 100 m range to 1.88% at 5000 m range). These results enderscore the importance of considering building morphology in local-scale urban planning, where the increasing building height can significantly enhance the disperion of PM2.5 pollution. Conversely, large-scale urban planning should prioritize the mixed use of green spaces and construction lands to mitigate PM2.5 pollution. Moreover, the significant seasonal differences in the ralationship between urban spatical indicatiors and PM2.5 pollution were observed. Particularly moteworthy is the heightened association between forest, water indicators and PM2.5 concentrations in summer, indicating the urban forests may facilitate the formation of volatile compunds, exacerbating the PM2.5 pollution. Our study provides a theoretical basis for addressing scale-related challenges in urban spatial planning, thereby forstering the sustainable development of cities.

Land use types have a significant impact on river ecosystems. The Yiluo River is the largest tributary below Xiaolangdi Reservoir in the middle reaches of the Yellow River, and is one of the important water conservation areas in the Yellow River Basin. Studying the ecological status of the Yiluo River under varied land use types in this basin is crucial for both ecological protection and the high-quality development of the Yellow River Basin. This study investigated the impacts of land use types on the macroinvertebrate community and functional structure in the Yiluo River Basin and introduced the concept of the land use health index (LUI). During the survey period, a total of 11,894 macroinvertebrates were collected, and 143 species were identified, belonging to 4 phyla, 7 orders, 22 families, and 75 families. The results showed that LUI had the most significant impact on macroinvertebrate community structure, with substrate type, dry plant weight, total phosphorus, turbidity, and attached algae biomass also playing significant roles in affecting macroinvertebrate communities. The species richness, the Shannon-Wiener index, and the Margalef richness index exhibited a nonlinear positive correlation with LUI of the sampling site, increasing as LUI enhancing and eventually reaching a plateau. Functional richness showed a linear and positive correlation with LUI, increasing with its enhancement, while functional evenness and functional divergence exhibited a nonlinear correlation with LUI. Functional evenness initially increased and then decreased with the enhancement of LUI, while functional divergence decreased with LUI enhancement. This study can provide a scientific reference for river ecological management under various land use scenarios.The Yiluo River is the largest tributary below Xiaolangdi Reservoir in the middle reaches of the Yellow River, and is one of the important water conservation areas in the Yellow River Basin. Studying the ecological status of the Yiluo River under varied land use types in this basin is crucial for both ecological protection and the high-quality development of the Yellow River Basin. This study investigated the impacts of land use types on the macroinvertebrate community and functional structure in the Yiluo River Basin and introduced the concept of the land use health index (LUI). During the survey period, a total of 11,894 macroinvertebrates were collected, and 143 species were identified, belonging to 4 phyla, 7 orders, 22 families, and 75 families. The results showed that LUI had the most significant impact on macroinvertebrate community structure, with substrate type, dry plant weight, total phosphorus, turbidity, and attached algae biomass also playing significant roles in affecting macroinvertebrate communities. The species richness, the Shannon-Wiener index, and the Margalef richness index exhibited a nonlinear positive correlation with LUI of the sampling site, increasing as LUI enhancing and eventually reaching a plateau. Functional richness showed a linear and positive correlation with LUI, increasing with its enhancement, while functional evenness and functional divergence exhibited a nonlinear correlation with LUI. Functional evenness initially increased and then decreased with the enhancement of LUI, while functional divergence decreased with LUI enhancement. This study can provide a scientific reference for river ecological management under various land use scenarios.

Revealing the spatiotemporal evolution characteristics and key driving processes behind the habitat quality is of great significance for the scientific management of production, living, and ecological spaces in resource-based cities, as well as for the efficient allocation of resources. Focusing on the largest coal-mining subsidence area in Jiangsu Province of China, this study examines the spatiotemporal evolution of land use intensity, morphology, and functionality across different time periods. It evaluates the habitat quality characteristics of the Pan\'an Lake area by utilizing the InVEST model, spatial autocorrelation, and hotspot analysis techniques. Subsequently, by employing the GTWR model, it quantifies the influence of key factors, unveiling the spatially varying characteristics of their impact on habitat quality. The findings reveal a notable surge in construction activity within the Pan\'an Lake area, indicative of pronounced human intervention. Concurrently, habitat degradation intensifies, alongside an expanding spatial heterogeneity in degradation levels. The worst habitat quality occurs during the periods of coal mining and large-scale urban construction. The escalation in land use intensity emerges as the primary catalyst for habitat quality decline in the Pan\'an Lake area, with other factors exhibiting spatial variability in their effects and intensities across different stages.

Identifying diets beneficial for both human and planetary health has become increasingly important. However, to date, there is limited research on sustainable diets for children and adolescents, a vulnerable population group with specific nutritional needs.
We aimed to identify 1) the main determinants; 2) age and time trends of greenhouse gas emissions (GHGE), land use (LU), and water use (WU) of diets of children and adolescents; and 3) analyze the associations of dietary GHGE, LU, and WU with nutrient adequacy.
A total of 5510 3-d-weighted dietary records (n = 856; 6-17 y; 48% ♀) of the DONALD (DOrtmund Nutritional and Anthropometric Longitudinally Designed) study between 2000 and 2021 were analyzed. Values of GHGE (kgCO2eq), LU (m2 × year), and WU (L) determined by life cycle assessment were assigned to all recorded foods. For nutrient adequacy, the mean adequacy ratio (MAR = ∑(nutrient intake / recommended intake) / number of nutrients) was used. Data were analyzed using polynomial mixed-effects regression models.
The main contributors to GHGE and LU were meat products (GHGE: 25.6%; LU: 32.8%), dairy products (22.2%; 17.7%), and sweets and pastries (14.0%; 14.3%); to WU, nonalcoholic beverages (24.3%), meat products (18.9%), and vegetables and fruits (17.7%). GHGE, LU, and WU per 1000 kcal increased with age (P < 0.01). GHGE and LU per 1000 kcal increased between 2000 and 2010 and decreased after that in females (P < 0.01) and males (GHGE only: P = 0.02). No significant time trend was found for WU (P > 0.05). A higher MAR was directly associated with GHGE/1000 kcal (MAR: β: 0.011, 95% CI: 0.008, 0.013, P < 0.0001), LU/1000 kcal (MAR: β: 0.009, 95%CI: 0.005, 0.013, P < 0.0001), and WU/1000 kcal (MAR: β: 0.429, 95% CI: 0.325, 0.533, P < 0.0001).
Our findings underscore the further need and the capacity for change toward more environmentally sustainable diets. Yet, the tradeoff between environmental sustainability and nutrient adequacy in the diets of children and adolescents requires specific attention to dietary composition.

Many studies have characterised resistomes in river microbial communities. However, few have compared resistomes in parallel rural catchments that have few point-source inputs of antimicrobial genes (ARGs) and organisms (i.e., AMR) - catchments where one can contrast more nebulous drivers of AMR in rural rivers. Here, we used quantitative microbial profiling (QMP) to compare resistomes and microbiomes in two rural river catchments in Northern England, the Coquet and Eden in Northumberland and Cumbria, respectively, with different hydrological and geographical conditions. The Eden has higher flow rates, higher annual surface runoff, and longer periods of soil saturation, whereas the Coquet is drier and has lower flowrates. QMP analysis showed the Eden contained significantly more abundant microbes associated with soil sources, animal faeces, and wastewater than the Coquet, which had microbiomes like less polluted rivers (Wilcoxon test, p < 0.01). The Eden also had greater ARG abundances and resistome diversity (Kruskal Wallis, p < 0.05), and higher levels of potentially clinically relevant ARGs. The Eden catchment had greater and flashier runoff and more extensive agricultural land use in its middle reach, which explains higher levels of AMR in the river. Hydrological and geographic factors drive AMR in rural rivers, which must be considered in environmental monitoring programmes.