Spatial distribution and hydrogeochemical evaluations of groundwater and its suitability for drinking and irrigation purposes in kaligonj upazila of satkhira district of Bangladesh.

Groundwater is a significant water resource for drinking and irrigation in Satkhira district, Bangladesh. The depletion of groundwater resources and deterioration in its quality are the results of the confluence of factors such as industrialization, intensive irrigation, and rapid population growth. For this reason, this study focused on the evaluation of tubewell water of six unions of Kaligonj upazila in Satkhira district, which is situated in the coastal southwest part of Bangladesh. Major and trace elemental concentrations were assimilated into positive matrix factorization (PMF) to identify potential sources and their respective contributions. Principal component analysis (PCA) revealed that groundwater salinization and manmade activities were the primary causes of heavy metals in the coastal groundwater. Its average pH value was found to be 7.5, while Dissolved oxygen, Total dissolved solids, salinity, and conductivity, with values ranging from 1.18 to 7.38 mg/L, 0.5-4.88 g/L, 0.4-5%, and 0.95 to 8.56 mS/cm, respectively. The total hardness average value was 561.7 mg/L, classified into the very hard water categories, which is why 90% of the tubewell water samples were unfit for household purposes. All samples had an excessive level of arsenic present. The iron concentration of fifteen (15) samples crossed the standard limit according to WHO 2011 value. Around 63% of the samples were of the Na+-K+-Cl--SO42- type, and about 72% were sodium-potassium and alkali types. 98% of samples were covered in chloride and bicarbonate. The findings showed that 45.83% of the groundwater samples had negative Chloroalkaline index (CAIs), while 54.16% had positive. The permeability index (PI) was an average of 73%, and residual sodium carbonate (RSC) averaged 260.2 mg/L, and the findings clearly showed that 80% of the samples weren't appropriate for irrigation. According to the sodium adsorption ratio (SAR) value, 65% of the samples fell into the unsuitable category. These calculations indicated a high overall salinity hazard in the study area, which may be caused by the intrusion of sea water given that the study area is close to the coastal region. Findings compared to standards revealed that the majority of the samples were deemed unfit for drinking and irrigation purposes. Hence, additional attention must be paid to this area to ensure the availability of drinkable water and to preserve sustainable farming practices.

Detecting Spatial Patterns of Peatland Greenhouse Gas Sinks and Sources with Geospatial Environmental and Remote Sensing Data.

Peatlands play a key role in the circulation of the main greenhouse gases (GHG) - methane (CH4), carbon dioxide (CO2), and nitrous oxide (N2O). Therefore, detecting the spatial pattern of GHG sinks and sources in peatlands is pivotal for guiding effective climate change mitigation in the land use sector. While geospatial environmental data, which provide detailed spatial information on ecosystems and land use, offer valuable insights into GHG sinks and sources, the potential of directly using remote sensing data from satellites remains largely unexplored. We predicted the spatial distribution of three major GHGs (CH4, CO2, and N2O) sinks and sources across Finland. Utilizing 143 field measurements, we compared the predictive capacity of three different data sets with MaxEnt machine-learning modeling: (1) geospatial environmental data including climate, topography and habitat variables, (2) remote sensing data (Sentinel-1 and Sentinel-2), and (3) a combination of both. The combined dataset yielded the highest accuracy with an average test area under the receiver operating characteristic curve (AUC) of 0.845 and AUC stability of 0.928. A slightly lower accuracy was achieved using only geospatial environmental data (test AUC 0.810, stability AUC 0.924). In contrast, using only remote sensing data resulted in reduced predictive accuracy (test AUC 0.763, stability AUC 0.927). Our results suggest that (1) reliable estimates of GHG sinks and sources cannot be produced with remote sensing data only and (2) integrating multiple data sources is recommended to achieve accurate and realistic predictions of GHG spatial patterns.

Temporal trends and spatial clusters of high risk for maternal death due to COVID-19 pre and during COVID-19 vaccination in Brazil: a national population-based ecological study.

OBJECTIVE: This study comprehensively analyzed the temporal and spatial dynamics of COVID-19 cases and deaths within the obstetric population in Brazil, comparing the periods before and during mass COVID-19 vaccination. We explored the trends and geographical patterns of COVID-19 cases and maternal deaths over time. We also examined their correlation with the SARS-CoV-2 variant circulating and the social determinants of health. STUDY DESIGN: This is a nationwide population-based ecological study. METHODS: We obtained data on COVID-19 cases, deaths, socioeconomic status, and vulnerability information for Brazil's 5570 municipalities for both the pre-COVID-19 vaccination and COVID-19 vaccination periods. A Bayesian model was used to mitigate indicator fluctuations. The spatial correlation of maternal cases and fatalities with socioeconomic and vulnerability indicators was assessed using bivariate Moran. RESULTS: From March 2020 to June 2023, a total of 23,823 cases and 1991 maternal fatalities were recorded among pregnant and postpartum women. The temporal trends in maternal incidence and mortality rates fluctuated over the study period, largely influenced by widespread COVID-19 vaccination and the dominant SARS-CoV-2 variant. There was a significant reduction in maternal mortality due to COVID-19 following the introduction of vaccination. The geographical distribution of COVID-19 cases and maternal deaths exhibited marked heterogeneity in both periods, with distinct spatial clusters predominantly observed in the North, Northeast, and Central West regions. Municipalities with the highest Human Development Index reported the highest incidence rates, while those with the highest levels of social vulnerability exhibited elevated mortality and fatality rates. CONCLUSION: Despite the circulation of highly transmissible variants of concern, maternal mortality due to COVID-19 was significantly reduced following the mass vaccination. There was a heterogeneous distribution of cases and fatalities in both periods (before and during mass vaccination). Smaller municipalities and those grappling with social vulnerability issues experienced the highest rates of maternal mortality and fatalities.

[Spatial distribution pattern of local tumor progression analysis after microwave ablation of hepatocellular carcinoma based on three-dimensional magnetic resonance imaging].

Objective: To investigate the spatial distribution pattern of local tumor progression (LTP) for hepatocellular carcinoma (HCC) ≤5 cm after microwave ablation. Methods: A retrospective analysis was performed on 169 HCCs with matched MRI before and after ablation from December 2009 to December 2019. A tumor MRI was reconstructed using three-dimensional visualization technology. LTP was classified as contact or non-contact, early or late stage, according to whether LTP was in contact with the edge of the ablation zone and the occurrence time (24 months). The tumor-surrounded area was divided into eight quadrants by using the eight-quadrant map method. An analysis was conducted on the spatial correlation between the quadrant where the ablative margin (AM) safety boundary was located and the quadrant where different types of LTP occurred. The t-test, or rank-sum test, was used for the measurement data. 2-test for count data was used to compare the difference between the two groups. Results: The AM quadrant had a distribution of 54.4% LTP, 64.2% early LTP stage, and 69.1% contact LTP, suggesting this quadrant was much more concentrated than the other quadrants (P < 0.001). Additionally, the AM quadrant had only 15.2% of non-contact type LTP and 17.1% of late LTP, which was not significantly different from the average distribution probability of 12.5% (100/8%) among the eight quadrants (P = 0.667, 0.743). 46.6% of early contact type LTP was located at the ablation needle tip, 25.2% at the body, and 28.1% at the caudal, while the location distribution probabilities of non-early contact LTP were 34.8%, 31.8%, and 33.3%, respectively. Conclusion: LTP mostly occurs in areas where the ablation safety boundary is the shortest. However, non-contact LTP and late LTP stages exhibit the feature of uniform distribution. Thus, this type of LPT may result from an inadequate non-ablation safety boundary.

[Spatial Distribution Characteristics of PM2.5 and O3 in Beijing-Tianjin-Hebei Region Based on Time Series Decomposition].

Notably, clear spatial differences occur in the distribution of air pollution among cities in the Beijing-Tianjin-Hebei (BTH) Region. Clarifying the concentration distribution of PM2.5 and O3 at different time scales is helpful to formulate scientific and effective pollution prevention and control measures. Here, the concentrations of PM2.5 and O3 were decomposed using a seasonal-trend decomposition procedure based on the loess (STL) method; their long-term, seasonal, and short-term components were obtained; and their temporal and spatial distribution characteristics were studied. The results showed that the decrease in PM2.5 concentration in the BTH Region from 2017 to 2021 was higher than that of O3. There was a positive correlation between PM2.5 and O3 concentrations in spring and summer and a negative correlation in autumn and winter. The short-term component and seasonal component had the greatest contribution to PM2.5 and O3 concentrations, respectively. There were two principal components in the seasonal and short-term components of PM2.5 and the long-term and short-term components of O3, corresponding to the central and southern part of Hebei Province and the northern part of the BTH Region. Sub-regional distribution of PM2.5 and O3 in the BTH Region at different time scales were found. Compared with that in the original series, the long-term component could better reflect the evolution trend of PM2.5 and O3 concentrations, and the standard deviation (SD) of the seasonal component and short-term component could be used to measure the fluctuation in PM2.5 and O3 concentrations in various cities. The SD of the seasonal and short-term components of the PM2.5 concentration in every city in front of Taihang Mountain was higher, and the SD of the short-term component of the O3 concentration in Tangshan was the highest.

Spatial distribution and influencing factors of rural tourism: A case study of Henan Province.

Rural tourism is a powerful way to revitalize the countryside, and its spatial pattern is crucial for sustainable development. This paper analyzes the spatial distribution of rural tourism characteristic villages in Henan Province by taking 723 villages as the research object and using the nearest neighbor index, kernel density analysis, and spatial autocorrelation. It investigates the influencing factors utilizing the optimal parameters-based geographical detector (OPGD) model. The results show that, firstly, the overall spatial distribution of the rural tourism characteristic villages in Henan Province is characterized by aggregation and unbalanced distribution, and the overall spatial distribution density demonstrates the aggregation characteristics of "four cores and one belt". Secondly, the rural tourism characteristic villages can be divided into four primary categories, agricultural industry, rural culture, and featured villages and towns. The spatial distributions of the four main categories are all clustered. Thirdly, the primary factors affecting the differences in the spatial distribution of the rural tourism characteristic villages are the topographic features, economic development level, tourism market potential, traffic capacity, and relevant policies, among which the critical factor is the number of A-class scenic spots in the tourism market potential. To promote the optimisation of the spatial pattern of rural tourism, it is necessary to strengthen resource integration. Furthermore, it is important to conduct in-depth exploration of more factors in order to provide comprehensive guidance for the sustainable development of rural tourism.

Analyzing temporal and spatial forest carbon storage using Google Plus Code: a case study of Zijin Mountain National Forest Park, China.

BACKGROUND: It is always a challenging job to compare forest resources as there is not a standardized spatial unit with location information. Google Plus Code, the newest alphanumeric geocoding system, uses 20 specifically selected letters and numbers to assign a unique global ID to every cell at different levels of a hierarchical grid system which is established based on latitude and longitude. It can be used as a standardized, unique global geospatial unit to segment, locate, quantitate, evaluate, and compare natural resources with area, boundary, and location information embedded. RESULTS: For this proof-of-concept case study, forest inventory data from 1987, 2002, and 2019 for the Zijin Mountain National Forest Park in Jiangsu Province, China was analyzed based on Google Plus Code grid/cell. This enabled the quantification of carbon storage at each cell allowing for the comparison of estimated carbon storage at same or different locations over time. CONCLUSIONS: This methodology is used to quantify the impacts of changing forest conditions and forest management activities on carbon storage with high spatial accuracy through the 32-year study period. Furthermore, this technique could be used for providing technical support and validation of carbon credit quantification and management.

Study on the geographic distribution and influencing factors of Dai settlements in Yunnan based on geodetector.

The Dai people are primarily found in Yunnan Province, China, and have a long heritage there. The latest national census reports that Yunnan is home to 1,259,000 individuals of the Dai ethnic group. This study focuses on 3504 Dai settlements in Yunnan, identified through county records. Using the ArcGIS spatial analysis platform, we first evaluated their settlements' spatial distribution patterns using metrics like the nearest neighbor index and geographic concentration index. Then, we applied geodetector to investigate the underlying mechanisms of their distribution. The results reveal that: (1) Dai settlements in Yunnan Province generally have a cohesive spatial distribution; at the provincial level, however, there is an uneven distribution pattern, with many densely populated areas and a pattern of "two cores, one belt, one area, and two points"; (2) The Dai settlements predominantly occupy the third gradient of the vertical zonation, with Dai gathering settlements primarily found in the Lancang, Ayeyarwaddy, and Red River basins. Conversely, Dai mixed settlements are mainly situated in the Lancang, Red, and Nu River basins; (3) Analysis via geodetector indicates that ethnocultural factors are the most significant in determining the spatial distribution of the Dai settlements, followed by socio-economic and natural factors; (4) The distribution of settlements is significantly influenced by the proportion of the Dai population within these settlements. Dai gathering settlements are typically located on flat slopes with elevations ranging from 500 to 1000 m and slopes of 0°-5°. Meanwhile, Dai mixed settlements are found on gentle slopes with elevations of 1000-2000 m and slopes of 5°-15°. The study reveals that the location of Dai settlements is strongly influenced by environmental considerations and has a significant explanation from similar origins.

Distribution and spatial variation of volatile methylsiloxanes in surface water and wastewater from the Yangtze River Basin, China.

Volatile methylsiloxanes (VMSs) earned serious concerns due to their detection and toxicities after their release to the environments. They were also detected in rivers around the globe, but their distribution remained to be explored in larger rivers with longer length, higher water volume and wider watershed. In the present study, 8 cyclic VMSs (cVMSs) and 7 linear ones (lVMSs) were investigated in 42 water samples (27 surface water (including 7 drinking source water) and 15 wastewater) from the Yangtze River Basin, China. Results showed that VMSs were detected in all sampling sites. In surface water, the concentrations of total cVMSs ranged from 17.3 to 4.57 × 103 ng/L, while those of lVMSs ranged from 1.72 to 81.6 ng/L. In wastewater, the total concentrations of cVMSs and lVMSs showed ranges of 17.6-1.66 × 103 ng/L and 2.59-252 ng/L, respectively. Apparently, cVMSs showed significantly higher concentrations than lVMSs. The concentrations of cVMSs followed an order of lower > upper > middle reaches, while those of lVMSs did not show clear distribution patterns. Among cVMSs, those with less Si numbers were dominant, while those with more Si numbers were dominant in lVMSs. Notably, the VMSs were also detected in 7 surface waters that served as drinking source waters, which earned them further concerns. In addition, the VMSs in surface water showed positive correlation with those in wastewater, which led to necessity in management on industrial emissions in the future.

Modeling refined differences of cortical folding patterns via spatial, morphological, and temporal fusion representations.

The gyrus, a pivotal cortical folding pattern, is essential for integrating brain structure-function. This study focuses on 2-Hinge and 3-Hinge folds, characterized by the gyral convergence from various directions. Existing voxel-level studies may not adequately capture the precise spatial relationships within cortical folding patterns, especially when relying solely on local cortical characteristics due to their variable shapes and homogeneous frequency-specific features. To overcome these challenges, we introduced a novel model that combines spatial distribution, morphological structure, and functional magnetic resonance imaging data. We utilized spatio-morphological residual representations to enhance and extract subtle variations in cortical spatial distribution and morphological structure during blood oxygenation, integrating these with functional magnetic resonance imaging embeddings using self-attention for spatio-morphological-temporal representations. Testing these representations for identifying cortical folding patterns, including sulci, gyri, 2-Hinge, and 2-Hinge folds, and evaluating the impact of phenotypic data (e.g. stimulus) on recognition, our experimental results demonstrate the model's superior performance, revealing significant differences in cortical folding patterns under various stimulus. These differences are also evident in the characteristics of sulci and gyri folds between genders, with 3-Hinge showing more variations. Our findings indicate that our representations of cortical folding patterns could serve as biomarkers for understanding brain structure-function correlations.

Developing a novel strategy for fabricating matrix film to assess the distribution of potassium perfluorooctanic sulfonate by matrix-assisted laser desorption/ionization mass spectrometry imaging.

Matrix deposition plays a critical role in image quality of matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI). To improve the ionization efficiency and overcome the limitation of traditional matrix deposition methods in the face of difficult-to-sublimate or difficult-to-dissolve matrix, covalent organic frameworks (COFs) named COF-DhaTab was successfully synthesized and firstly used as matrix film. It was fabricated by imprinting of sieved COF-DhaTab powder on the surface of a double-sided adhesive tape. Outstanding reproducibility and uniformity of COF-DhaTab film were demonstrated by relative standard deviation (RSD) within 8.37% and 7.71% from dot-to-dot and plate-to-plate, respectively. With the introduction of double-sided adhesive tape, water contact angle (WCA) of COF-DhaTab film increased from 55° to 141°, resulting in significant suppression of analyte diffusion. Moreover, the intensity of potassium perfluorooctanic sulfonate (PFOS, C8F17SO3-, m/z 498.93) was 9.3 × 105, more than six hundred times higher than that using DHB matrix. This enhancement was attributed to the rough surface and multiple branches of the synthesized COF-DhaTab. To verify the ability of COF-DhaTab film as substrate, the spatial distribution of PFOS in zebrafish, rat liver and kidney tissues was explored. Superior imaging capability was displayed with high-spatial resolution and reliable location distribution. These results not only demonstrate the outstanding ability of COF-DhaTab as matrix for MALDI-MS and MALDI-MSI, but also provide a facile approach for fabrication of novel matrix films for MALDI-MSI.

[Analysis and Evaluation of Heavy Metal Pollution in Farmland Soil in China：A Meta-analysis].

In this study, a Meta-analysis was used to investigate the pollution status of eight farmland soil heavy metal elements (As, Cd, Cr, Cu, Hg, Ni, Pb, and Zn) in China. Meanwhile, their spatiotemporal changes and differences between different types of cultivated land were explored. The research data were chosen from 449 relevant literature data collected by CNKI and Web of Science from 2005 to 2021, and the Meta-analysis used a weighted method based on "sampling numbers", "study area", and "standard deviation". The results showed that the national average values of the eight heavy metal elements in Chinese farmland soil were ω(As)11.00 mg·kg-1, ω(Cd)0.350 2 mg·kg-1, ω(Cr)62.91 mg·kg-1, ω(Cu)28.87 mg·kg-1, ω(Hg)0.135 1 mg·kg-1, ω(Ni)28.91 mg·kg-1, ω(Pb)34.67 mg·kg-1,and ω(Zn)90.24 mg·kg-1. Compared with their background values, all elements except As accumulated to some extent, and Cd and Hg accumulated the most, exceeding their background values by 177.9% and 340.3%, respectively. The research results indicated that Cd and Hg were the main pollution elements in farmland soil in China, and their accumulation was mainly influenced by human activities. In terms of their temporal and spatial changes, the Yunnan-Guizhou Plateau and the eastern coast were the most concentrated areas of pollution cases, and the pollution center shifted from the middle reaches of the Yangtze River to the southwest over time. The accumulation of heavy metals in farmland soil was affected by crop planting types, and the accumulation of heavy metals in vegetable and paddy soil was significantly greater than that in other cultivated land types.

Sociodemographic factors impacting the spatial distribution of private dental clinics in major cities of Peoples Republic of China.

OBJECTIVES: Investigate the geographical distribution of private dental practices in major Chinese cities and analyze the variables influencing this distribution. METHODS: This study used Python to extract various types of Point of Interest (POI) data spanning from 2016 to 2022 from the AutoNavi map. A 1km*1km grid was constructed to establish the study sample. Additional spatial pattern data, including nighttime lighting, population, and air quality data, were integrated into this grid. Global Moran's I index was used to analyze the spatial autocorrelation. The spatial lag model was used to explore the influencing factors of private dental practice distribution. RESULTS: This study reveals a specific clustering pattern for private dental practices in major Chinese cities. The primary influencing factors include nighttime lights, population density, and housing prices, suggesting that dental practices are typically concentrated in highly developed regions with dense populations and high housing costs. Additionally, we discovered that patterns vary across different metropolises, with the most pronounced clustering patterns and substantial inequalities found in the most developed areas. CONCLUSIONS: This study establishes that factors such as regional development and population density positively correlate with private dental practice. Additionally, it reveals a strong mutual correlation in the clustering of dental practices, which does not show a substantial correlation with public resources. Finally, it suggests that the spatial heterogeneity pattern implies a rising necessity to tackle inequality issues within urban areas as economic development progresses.

Spatial distribution characteristics and pollution evaluation of soil heavy metals in Wulongdong National Forest Park.

To scrutinize the spatial distribution attributes of soil heavy metal content and discern its pollution status within the expanse of Wulongdong National Forest Park, a meticulous investigation is imperative. Three altitude gradients of 900, 1000, and 1069 m were selected on the shady and sunny slopes of Wulongdong National Forest Park, and a total of 300 soil sample points were collected. Soil samples were collected in layers, and the contents of seven soil heavy metal elements, Cr, Cd, Hg, Ni, Se, As, and Pb, were measured. With regard to the national soil element background values, the single factor index method, Nemerow index method, and pollution load index were employed to undertake a thorough assessment of soil heavy metal pollution. (1) The contents of heavy metal elements Cr, Se, As, and Pb in the 0-20 cm soil layer of Wulongdong National Forest Park are lower than the national soil element background value and the Henan soil element background value; the Cd and Hg contents exceed the national soil element background value. The value and Henan soil element background value are 2.2 times and 2.92 times the national soil element background value, and 2.75 times and 9.5 times the Henan soil element background value respectively; Ni content is lower than the Henan soil element background value, but higher than the national soil element background value. The background value is 1.03 times its content. The coefficients of variation of the contents of seven heavy metal elements are all greater than 50%, among which Hg shows extreme variation, and the remaining six are highly variable. (2) In the same soil layer, the Cr and As contents are lower on sunny slopes than on shady slopes, and the contents of Pb, Ni, and Hg are generally higher on sunny slopes than on shady slopes. On sunny slopes, the contents of As, Cd, and Hg decrease with increasing altitude, and the Se content increases with increasing altitude; while on shady slopes, the contents of Cr, Se, and As decrease with increasing altitude, and Pb and Hg content increase with the increase of altitude; the content of heavy metal element As increases with the deepening of the soil layer on shady slopes, and the Hg content decreases with the deepening of the soil layer on sunny slopes. The contents of other heavy metal elements have no obvious regularity among different slope directions, altitudes and soil layers. (3) The single factor index evaluation results show that in the 0 ~ 20c soil layer and on the sunny slope, Hg is heavily polluted, Cd is moderately polluted, Ni is lightly polluted, and Cr, Se, As, and Pb are all non-polluted; On the shady slope, Cd and Hg are moderately polluted, and the other five heavy metal elements are in a non-polluting state. (4) The Nemerow index method evaluation results show that in the 0 ~ 20 cm soil layer, the soil on sunny slopes is significantly more polluted by heavy metals than on shady slopes, and the main pollutants are Ni, Cd and Hg. (5) In the 0 ~ 20 cm soil layer of Wulongdong National Forest Park, the three heavy metal elements Ni, Cd and Hg have reached pollution levels, of which Ni is slightly polluted, Cd and Hg are moderately or above polluted; the sunny slope soil is slightly polluted. Heavy metal pollution, no heavy metal pollution on shady slopes.

Pollution characteristics, distribution and risk level of heavy metals in sediments of the Yangtze River estuary.

Pollution characteristics, distribution, risk and sources of 7 heavy metals in sediments of Yangtze River Estuary were investigated. Total concentration ranges of As, Cr, Cu, Cd, Pb, Zn and Ni were [0, 16.5], [1.48, 51.3], [2.66, 318], [0, 0.99], [35.6, 992], [8, 91.3] and [1.88, 108] mg/kg, respectively. Based on the potential ecological risk index and Geoaccumulation index, it was determined that Pb is the most polluted heavy metal. According to class I standard of "Marine sediment quality" of China, mean baseline levels multiples were Pb (8.34) > Cu (0.57) > Cr (0.37) > Zn (0.355) > Ni (0.352) > As (0.28) > Cd (0.00). The study also found the heavy metal content of Pb is the most serious, but most of the Pb content comes from the residual state, which has minimal impact on the environment. The East Nanhui Shoal was identified as the most polluted sub-area in terms of Pb pollution, followed by other specific locations. Considering the pollution level and transport costs, the study concluded that dredge soils of the Yangtze River Estuary Deepwater Channel are not suitable for the restoration of East Hengsha Shoal.

The Biodiversity of Blackflies (Diptera: Simuliidae) in Brazil: New Distribution Records and Updated Checklist.

Currently, according to the most recent Simuliidae World Inventory, there are 97 valid species of blackflies recorded in Brazil, some of which act as vectors for zoonoses such as human onchocerciasis and mansonellosis in the northern and central-western regions of the country. Meanwhile, other species can cause serious socioeconomic problems due to the nuisance of female bites. Therefore, accurate knowledge of their distribution is crucial for the development and implementation of successful preventive strategies. With this aim, this study reviewed and updated the geographical distribution of the blackfly fauna throughout the Brazilian states. The data were compiled from three main sources: geographic information of material deposited at the Simuliidae Collection of the Instituto Oswaldo Cruz (CSIOC-IOC), a comprehensive review of scientific literature, and online biodiversity databases. We present a total of 71 new distribution records of 38 different Simuliidae species for 24 Brazilian states. Neither of these sets of records has been included in the Simuliidae World Inventory. Consequently, an updated Brazilian Simuliidae checklist, comprising a total of 98 valid species, is presented, highlighting these new distribution records. We also discuss six dubious records for the country and the implications of this updated data for the Simuliidae species richness of Brazil, its states, and biomes. This information is essential for future studies in the taxonomy, systematics, and biogeography of this family in Brazil.

Distribution, sources and influencing factors of heavy metals in the Ledong Sea, South China Sea.

The Ledong Sea Area is located on the southwest side of Hainan Island. In recent years, with the development of industrialization and urbanization, the problem of heavy metals in marine sediments has gradually become a global problem, and research on this topic is of great significance for nearshore environmental protection and coastal management. This paper analysed the heavy metal content of 97 surface sediments in the Ledong Sea, indicating unpolluted to moderately polluted and low to moderate risk. Cu, Zn, Hg, Pb, Cr, and Cd are highly correlated, with similar origins, and originate from rivers carrying industrial wastewater, domestic sewage, and weathered material from the parent rocks, which are subsequently redistributed under the action of ocean dynamics. The distribution of Hg is mainly influenced by feed and biological metabolites during the farming process. As originates from rivers carrying large amounts of agricultural pesticide and fertilizer residues.

Potential risk assessment and occurrence characteristic of heavy metals based on artificial neural network model along the Yangtze River Estuary, China.

Pollution from heavy metals in estuaries poses potential risks to the aquatic environment and public health. The complexity of the estuarine water environment limits the accurate understanding of its pollution prediction. Field observations were conducted at seven sampling sites along the Yangtze River Estuary (YRE) during summer, autumn, and winter 2021 to analyze the concentrations of seven heavy metals (As, Cd, Cr, Pb, Cu, Ni, Zn) in water and surface sediments. The order of heavy metal concentrations in water samples from highest to lowest was Zn > As > Cu > Ni > Cr > Pb > Cd, while that in surface sediments samples was Zn > Cr > As > Ni > Pb > Cu > Cd. Human health risk assessment of the heavy metals in water samples indicated a chronic and carcinogenic risk associated with As. The risks of heavy metals in surface sediments were evaluated using the geo-accumulation index (Igeo) and potential ecological risk index (RI). Among the seven heavy metals, As and Cd were highly polluted, with Cd being the main contributor to potential ecological risks. Principal component analysis (PCA) was employed to identify the sources of the different heavy metals, revealing that As originated primarily from anthropogenic emissions, while Cd was primarily from atmospheric deposition. To further analyze the influence of water quality indicators on heavy metal pollution, an artificial neural network (ANN) model was utilized. A modified model was proposed, incorporating biochemical parameters to predict the level of heavy metal pollution, achieving an accuracy of 95.1%. This accuracy was 22.5% higher than that of the traditional model and particularly effective in predicting the maximum 20% of values. Results in this paper highlight the pollution of As and Cd along the YRE, and the proposed model provides valuable information for estimating heavy metal pollution in estuarine water environments, facilitating pollution prevention efforts.

Effects of a rainwater harvesting system on the soil water, heat and growth of apricot in rain-fed orchards on the Loess Plateau.

Rainwater is the main water source in arid and semiarid areas of the Loess Plateau, where rainfall is generally insufficient, ineffective and underutilized during the growing season. Thus, improving rainwater utilization efficiency is essential for sustainable agricultural development. A new system composed of rainwater harvesting, an infiltrator bucket with multiple holes and mulching (RHM), was designed to maintain soil moisture at a proper level in rain-fed orchards in arid and semiarid areas of the Loess Region of China. However, there is a lack of clarity on the effectiveness of RHM. In this study, changes in the soil environment and the growth and physiology of apricot trees were monitored via two treatments: (1) Rain-harvesting irrigation system (RHM) treatment and (2) traditional orchard treatment (CK) as a baseline. The results showed that (1) RHM could effectively improve soil water storage at depths of 0-45 cm and at a horizontal distance of 40 cm from the trunk. For the 1.4 mm light rain event, the soil water content increased by 6.3-12%, and for the two moderate rains, the soil water content increased by 12-25%. The change in the soil relative water content predicted by the LSTM model is consistent with the overall trend of the measured value and gradually decreases, and the prediction accuracy is high, with an error of 0.65. (2) The average soil temperatures at 5 cm, 20 cm and 40 cm under RHM were 17.0% (2.4 °C), 13.6% (1.9 °C) and 7.5% (1 °C) greater than those under CK, respectively. (3) Compared with the control treatment, RHM improved the growth and WUEL of apricot trees. The results highlighted the efficiency of the RHM system in enhancing the soil environment and regulating the growth and physiology of apricot trees, which has greater popularization value in arid and semiarid areas.

A framework for risk assessment of groundwater contamination integrating hydrochemical, hydrogeological, and electrical resistivity tomography method.

Groundwater contamination have been widely concerned. To reliably conduct risk assessment, it is essential to accurately delineate the contaminant distribution and hydrogeological condition. Electrical resistivity tomography (ERT) has become a powerful tool because of its high sensitivity to hydrochemical parameters, as well as its advantages of non-invasiveness, spatial continuity, and cost-effectiveness. However, it is still difficult to integrate hydrochemical, hydrogeological, and ERT datasets for risk assessment. In this study, we develop a general framework for risk assessment by sequentially jointing hydrochemical, hydrogeological, and ERT surveys, while establishing petrophysical relationships among these data. This framework can be used in groundwater-contaminated site and help to delineate the distribution of contaminants. In this study, it was applied to a nitrogen-contaminated site where field ERT survey and borehole information provided valuable measurement data for validating the consistency of contamination and hydrogeological condition. Risk assessment was conducted based on the refined results by the establishment of relationship between conductivity and contaminants concentration with R 2 > 0.84 . The contamination source was identified and the transport direction was predicted with the good agreement of R 2 = 0.965 between simulated and observed groundwater head, which can help to propose measures for anti-seepage and monitoring. This study thus enhances the reliability of risk assessment and prediction through a thought-provoking innovation in the realm of groundwater environmental assessment.