Significant Spatial Variation Research Articles

Spatial Variations in Seamless Predictability of Subseasonal Precipitation Over Asian Summer Monsoon Region in S2S Models

AbstractThis study assesses the seamless predictability of subseasonal precipitation over the Asian summer monsoon (ASM) region. The prediction skill of 12 models from the subseasonal‐to‐seasonal (S2S) hindcast database varies considerably, suggesting a large uncertainty in the prediction of ASM precipitation. However, all models show that ASM precipitation is better predicted over ocean than over land, and less reliable in subtropical areas than in tropical areas. The results reveal significant spatial variations in the prediction skill and predictability of ASM precipitation. This study investigates the factors controlling these spatial variations by analyzing the area‐averaged precipitation predictability in three different subregions: the maritime continent (MC), the Indian summer monsoon (ISM) subregion, and the East ASM (EASM) subregion. Precipitation is best predicted over the MC, followed by the ISM and EASM. The distinct disparities in prediction skill among subregions are mainly controlled by differences in potential predictability; that is, the intrinsic limits of predictability among subregions. The high potential predictability of the MC is attributable to small noise due to a strong correlation with the El Niño–Southern Oscillation, whereas the low potential predictability of the EASM is attributable to its small signal. Meanwhile, the comparable signal and noise related to the intraseasonal oscillation in the ISM precipitation, limits the predictability of this subregion. Finally, the evaluation of the ASM precipitation ensemble forecasts in the S2S models demonstrates that the ensemble systems are underdispersive in the three subregions in most S2S models.

Spatial analysis of malaria hotspots in Dilla sub-watershed: Western Ethiopia.

This study aimed to examine the spatial variations in malaria hotspots along Dilla sub-watershed in western Ethiopia based on environmental factors for the prevalence; and compare the risk level along with districts and their respective kebele. The purpose was to identify the extent of the community's exposure to the risk of malaria due to their geographical and biophysical situations, and the results contribute to proactive interventions to halt the impacts. The descriptive survey design was used in this study. Ethiopia Central Statistical Agency based meteorological data, digital elevation model, and soil and hydrological data were integrated with other primary data such as the observations of the study area for ground truthing. The spatial analysis tools and software were used for watershed delineation, generating malaria risk map for all variables, reclassification of factors, weighted overlay analysis, and generation of risk maps. The findings of the study reveal that the significant spatial variations in magnitudes of malaria risk have persisted in the watershed due to discrepancy in their geographical and biophysical situations. Accordingly, significant areas in most of the districts in the watershed are characterized by high and moderate in malaria risks. In general, out of the total area of the watershed which accounts 2773 km2, about 54.8% (1522km2) identified as high and moderate malaria risk area. These areas are explicitly identified and mapped along with the districts and kebele in the watershed to make the result suitable for planning proactive interventions and other decision making. The research output may help the government and humanitarian organizations to prioritize the interventions based on identified spatial situations in severity of malaria risks. The study was aimed only for hotspot analysis which may not provide inclusive account for community's vulnerability to malaria. Thus, the findings in this study needs to be integrated with the socio-economic and other relevant data for better malaria management in the area. Therefore, future research should comprehend the analysis of vulnerability to the impacts of malaria through integrating the level of exposure to the risk, for instance identified in this study, with factors of sensitivity and adaptation capacity of the local community.

Spatial distribution and determinants of stunting, wasting and underweight in children under-five in Ethiopia

BackgroundThe burden of malnutrition in children under five remains an important child health issue where significant regional variations are observed in Ethiopia. The main aim of the current study was to explore the spatial distribution of stunting, wasting, and underweight in children under five in Ethiopia.MethodsThe secondary data from EDHS, 2016, was employed, and a total of 7960 under-five children were included in the analysis. The general spatial analysis was performed to explore the spatial distribution of malnutrition among under-five within and between the regions of Ethiopia. The Spatial Lag and Spatial Error models were used to examine the spatial dependence between stunting, wasting, and being underweight. The Geographically weighted regression analysis was performed to estimate the types and strength of relationships between malnutrition and associated determinant factors across the regions and within the clusters or Zones of each region.ResultsAmong the under-five children included in the study, 36.6% were stunted, 12.2% were wasted and 25.2% were underweight. The Global Moran Index's value indicates (Stunting, I = 0.3135, p-value < 0.00001, Wasting, I = 0.1948, p-value < 0.0001 and Underweight, I = 0.5291, p-value < 0.0001) that there was a significant spatial variation of malnutrition across the regions and Zones of Ethiopia. The significant source of spatial variation of malnutrition in children under five was associated with the mother's education level, drinking water facility, toilet facilities, number of children under-five in the household, household’s wealth index, breastfeeding duration of the child, child size at birth, Body Mass Index of Mothers (BMI), region, and place of residence.ConclusionsThe spatial association and spatial patterns of stunting, wasting, and being underweight were clustered within and between the regions of Ethiopia. The hotspot areas of stunting, wasting, and being underweight were detected in the regions where there were poor health facilities and limited socioeconomic indicators.

Estimation of the Manning’s n coefficient in multi-constituent tidal models by assimilating satellite observations with the adjoint data assimilation

The bottom friction is critical for the dissipation of the global tidal energy. The bottom friction coefficient is traditionally determined using the Manning’s n formulation in tidal models. The Manning’s n coefficient in the Manning’s n formulation is vital for the accurate simulation and prediction of the tide in coastal shallow waters, but it cannot be directly measured and contains large amounts of uncertainties. Based on a two-dimensional multi-constituent tidal model with the adjoint data assimilation, the estimation of the Manning’s n coefficient is investigated by assimilating satellite observations in the Bohai, Yellow and East China Seas with the simulation of four principal tidal constituents M2, S2, K1 and O1. In the twin experiments, the Manning’s n coefficient is assumed to be constant, and it is estimated by assimilating the synthetic observations at the spatial locations of the satellite tracks. Regardless the inclusion of artificial random observational errors associated with synthetic observations, the model performance is improved as evaluated by the independent synthetic observations. The prescribed ‘real’ Manning’s n coefficient is reasonably estimated, indicating that the adjoint data assimilation is an effective method to estimate the Manning’s n coefficient in multi-constituent tidal models. In the practical experiments, the errors between the independent observations at the tidal gauge stations and the corresponding simulated results of the four principal tidal constituents are substantially decreased under both scenarios of the constant and spatially-temporally varying Manning’s n coefficient estimated by assimilating the satellite observations with the adjoint data assimilation. In addition, the estimated spatial and temporal variation trend is robust and not affected by the model settings. The spatially-temporally varying Manning’s n coefficient is negatively correlated with the current speed and shows significant spatial variation in the shallow water areas. This study demonstrates that the Manning’s n coefficient can be reasonably estimated by the adjoint data assimilation, which allows significant improvement in accurate simulation of the ocean tide.

Quantitative analysis and risk assessment to full-size microplastics pollution in the coastal marine waters of Hong Kong

Given the potential risk to the ecosystem, attention has increased in recent decades to the contamination of the aquatic environment by microplastics (MPs). Due to the limitations of conventional analysis methods of MPs, little is known about the size distribution and abundance of a full-size MPs from 1 μm to 5 mm. The present study quantified MPs with size ranges of 50 μm – 5 mm and 1–50 μm in the coastal marine waters from twelve locations in Hong Kong using fluorescence microscopy and flow cytometry respectively, during the end of wet (September 2021) and dry (March 2022) seasons. The average abundance of MPs with size ranges of 50 μm – 5 mm and 1–50 μm from twelve sampling locations marine surface waters were found ranging from 27 to 104 particles L−1 and 43,675–387,901 particles L−1 in the wet season respectively, and 13–36 particles L−1 and 23,178–338,604 particles L−1 in the dry season respectively. Significant temporal and spatial variations of small MPs abundance might be observed at the sampling locations, which were contributed by the influences of the estuary of Pearl River, sewage discharge points, land structure, and other anthropogenic activities. Based on the MPs abundance information, ecological risk assessment was conducted and revealed that the small MPs (< 10 μm) in coastal marine surface waters may pose potential health risks to aquatic organisms. Additional risk assessments are needed in order to determine whether or not the MPs exposure would cause health risks to the public.

Genomic selection for genotype performance and environmental stability in Coffea canephora.

Coffee is one of the most important beverages and trade products in the world. Among the multiple research initiatives focused on coffee sustainability, plant breeding provides the best means to increase phenotypic performance and release cultivars that could meet market demands. Since coffee is well adapted to a diversity of tropical environments, an important question for those confronting the problem of evaluating phenotypic performance is the relevance of genotype-by-environment interaction. As a perennial crop with a long juvenile phase, coffee is subjected to significant temporal and spatial variations. Such facts not only hinder the selection of promising materials but also cause a majority of complaints among growers. In this study, we hypothesized that trait stability in coffee is genetically controlled and therefore is predictable using molecular information. To test it, we used genome-based methods to predict stability metrics computed with the primary goal of selecting coffee genotypes that combine high phenotypic performance and stability for target environments. Using 2 populations of Coffea canephora, evaluated across multiple years and locations, our contribution is 3-fold: (1) first, we demonstrated that the number of harvest evaluations may be reduced leading to accelerated implementation of molecular breeding; (2) we showed that stability metrics are predictable; and finally, (3) both stable and high-performance genotypes can be simultaneously predicted and selected. While this research was carried out on representative environments for coffee production with substantial crossover in genotypic ranking, we anticipate that genomic prediction can be an efficient tool to select coffee genotypes that combine high performance and stability across years and the target locations here evaluated.

Fate and Spatial–Temporal Variation of 23 Elements at 7 Wastewater Treatment Plants in Southeast City of China

Rapid urbanization has caused an increase in the discharge of inorganic elements into the environment; however, the knowledge about the fate and annual variations of multiple elements in wastewater treatment plants (WWTPs) is limited. To understand the distribution and change of those elements, we collected and analyzed wastewater and sludge samples from seven WWTPs in a southeast city of China. Results revealed the elemental concentration ranging from 0.06 μg·L−1 (Tl) to 221.90 μg·L−1 (Mn) in the influent, below the detection limit (Er), to 206.40 μg·L−1 (Mn) in the effluent, and 0.58 mg·kg−1 (Tl) to 309.30 mg·kg−1 (Zn) in the sludge. The removal analysis revealed that rare earth elements (REEs) were removed well from the wastewater with removal efficiencies ranging from 88.03% (Tm) to 97.37% (Sm), while heavy metals were poor, with removal efficiencies ranging from 10.71% (Mn) to 89.17% (Pb). The elemental flux analysis highlighted that activated sludge served as a major temporary storage site for 23 elements, while excess sludge acted as the major sink for REEs. Significant spatial variations were detected among different WWTPs. On the contrary, the temporal variations were insignificant based on the monitoring data from 2010 to 2020, indicating the satisfactory implementation of current environmental regulations.

Spatial distribution of airborne bacterial communities in caged poultry houses

ABSTRACT Microbial aerosols in intensive broiler houses whose species and concentrations are closely related to human health are ubiquitous. Based on 16S rRNA gene sequencing, the aim of this study was to investigate the spatial distribution and diversity of bacterial aerosols in the air of broiler houses. Significant spatial variations in airborne bacterial concentrations were observed inside the poultry farmhouse. The results indicated that bacteria in the air samples could be grouped into a total of 1,674 OTUs. Alpha diversity analysis showed that the diversity of the microbial community at the entry of the broiler house was higher than that at the middle or the rear (p < 0.01). The Sankey diagram illustrated species dynamic changes in Proteobacteria, Firmicutes, and Actinobacteria among the different locations. From the aspect of LEfSe (LDA Effect Size) analysis, we discovered that the abundance of Planctomycetes was significantly higher in the entry than in the rear and middle. This study shows the spatial distribution of the entire bacterial community in intensive broiler houses, which offers a new perspective for studying airborne total bacteria in those environments. Implications: The bacteria contained in air aerosols from poultry houses are closely connected to animal health and production. This study aimed to investigate the spatial distribution and diversity of bacterial aerosols in the air of broiler houses. The results observed that bacterial aerosol concentrations in the examined broilers house varied greatly at different positions, and a significantly higher exposure to bacterial aerosol was observed at the middle than at the other positions (p < 0.05). The alpha diversity analysis showed that the diversity of the microbial community at the entry of the broiler house was higher than that at the middle or the rear (P<0.01). Sankey diagram illustrated species dynamic changes of Proteobacteria, Firmicutes and Actinobacteria among the different locations. The microbial communities in genus level in the samples of entry and rear were closer, while the species diversity of middle and rear samples in chicken house was highly similar (P>0.05). Altogether, results revealed that the effects of spatial factors on the diversity and abundance of bacteria in the air of closed-cage broiler houses, which poses a potential threat to the health of animals and workers in those environments.

Quality of Water from Hand-Dug Wells in Nembe Town, Bayelsa State, Nigeria

This study examined the quality of water supply from hand-dug wells in Nembe town, Bayelsa State using sample survey design. Data was obtained from primary sources. To assess if the quality of groundwater supplied in Nembe town is safe for domestic and drinking purposes, the physico-chemical and microbial status of the groundwater were studied. Nembe town was stratified into ten neighbourhoods and a total of ten (10) hand dug well water samples was randomly collected from each of the sampled ten neighbourhoods and analyzed for twenty-one (21) paramaters in the month of November 2019. These samples were sent to the laboratory for physico-chemical and microbial analysis. The results of the study revealed that physico-chemical paramaters such as Total Dissolved Solids (TDS), Total Suspended Solids(TSS), Sulphate (So4-2), Bicarbonate (HCo3-), Calcium (Ca), Sodium (Na), Manganese (Mn), Electrical Conductivity (EC), Iron (Fe), Chloride (CL), Nitrate (NO), Salinity, Total Alkalinity (TA) and Magnesium (Mg) are all within the permissible level of WHO and NESREA drinking water standards. Groundwater in the area have turbidity and potassium levels higher than the WHO and NESREA maximum permissible limits for drinking water standard. All the sampled hand dug wells have pH value within the permissible limit of drinking water except one which had pH value of 6.48 and considered too acidic for human consumption. Based on hardness, 70% of the groundwater samples are slightly hard water to hard water in nature. The result of the microbial analysis showed the presence of total coliforms, Total bacteria counts and fungi in all the hand dug wells. The ANOVA statistical tool was employed in testing the stated hypothesis and the results show that there is no significant spatial variation in the physico-chemical properties of water in the study area and that there is a significant spatial variation in the microbial properties of water in the study area. The result of the study was conclusive evidence that all the hand dug wells studied are not safe for domestic purpose especially for drinking as they were affected by some physico-chemical and biological parameters. Hence the affected wells call for periodic monitoring and treatment to improve the quality of the water.

Atmospheric benzo[a]pyrene in the Yangtze River Delta, China: pollution level and lung cancer risk in 2016 and future predictions.

The Yangtze River Delta (YRD) has undergone widespread polycyclic aromatic hydrocarbon (PAH) pollution. In this study, we simulated the spatial distribution of atmospheric benzo[a]pyrene (BaP, the most carcinogenic PAH) in the YRD in 2016 and 2030 under different emission scenarios using a 3-D atmospheric transport model and evaluated the lung cancer risks posed by BaP during the study years. The purpose of this study is to suggest targeted policy recommendations for policy-makers to mitigate BaP pollution through numerical simulation. Our results showed that the average BaP concentration in the YRD was 0.30ng/m3 in 2016; however, a significant spatial variation was observed, with the highest BaP concentration in Shanghai (0.59ng/m3). The population-weighted incremental lifetime lung cancer risk (PILCR) was 6.67 × 10-6 in 2016, whereas it ranged from 2.70 × 10-6 to 1.05 × 10-5 in 2030 under the five emission scenarios. A higher future population density in the YRD region could increase lung cancer risk. In all scenarios, Shanghai had the highest number of lung cancer cases (range: 208-476). The results suggest that BaP pollution could be effectively improved through the synergistic effect of reducing activity levels and improving technology. Finally, we provide specific suggested pollution control strategies (e.g., accelerating the use of clean energy in rural areas) for atmospheric BaP in the YRD.

Spatio-temporal variations of activity of nitrate-driven anaerobic oxidation of methane and community structure of Candidatus Methanoperedens-like archaea in sediment of Wuxijiang river

Nitrate-driven anaerobic oxidation of methane (AOM), catalyzing by Candidatus Methanoperedens-like archaea, is a new addition in the global CH4 cycle. This AOM process acts as a novel pathway for CH4 emission reduction in freshwater aquatic ecosystems; however, its quantitative importance and regulatory factors in riverine ecosystems are nearly unknown. Here, we examined the spatio-temporal changes of the communities of Methanoperedens-like archaea and nitrate-driven AOM activity in sediment of Wuxijiang River, a mountainous river in China. These archaeal community composition varied significantly among reaches (upper, middle, and lower reaches) and between seasons (winter and summer), but their mcrA gene diversity showed no significant spatial or temporal variations. The copy numbers of Methanoperedens-like archaeal mcrA genes were 1.32 × 105–2.47 × 107 copies g−1 (dry weight), and the activity of nitrate-driven AOM was 0.25–1.73 nmol CH4 g−1 (dry weight) d−1, which could potentially reduce 10.3% of CH4 emissions from rivers. Significant spatio-temporal variations of mcrA gene abundance and nitrate-driven AOM activity were found. Both the gene abundance and activity increased significantly from upper to lower reaches in both seasons, and were significantly higher in sediment collected in summer than in winter. In addition, the variations of Methanoperedens-like archaeal communities and nitrate-driven AOM activity were largely impacted by the sediment temperature, NH4+ and organic carbon contents. Taken together, both time and space scales need to be considered for better evaluating the quantitative importance of nitrate-driven AOM in reducing CH4 emissions from riverine ecosystems.

Juvenile fish communities in coastal soft-bottom and shallow water habitats at the Tolo Harbour and Channel in Hong Kong, South China

Coastal soft-bottom and shallow water habitats are often key nursery grounds for marine fishes, which are important not only in supporting a rich biodiversity, but also of social-economic importance in terms of ecosystem services and fishery resources provided by these habitats. Tolo Harbour and Channel (the Tolo Area) at north-eastern Hong Kong in South China has been previously recognised as a nursery ground of marine fish species, including those that are commercially important. However, marine biodiversity and fisheries resources in this area have been jeopardized by various anthropogenic threats such as coastal development and pollution. This study aimed at providing up-to-date ecological information of juvenile marine fishes in the Tolo Area, and identifying locations with a high conservation priority. A three-year study, using beach and purse seining, was carried out to assess the current status of the juvenile fish community in coastal soft-bottom and shallow water habitats throughout the Tolo Area. A total of 171 species/taxa were recorded, including the IUCN-red-listed vulnerable species of seahorse Hippocampus kuda. Juvenile individuals were found in 155 of the recorded species/taxa. Juvenile fishes were dominated by small and/or fast-growing species. Significant spatial and seasonal variations in juvenile fish assemblages were recorded in the Tolo Area. Diel differences in juvenile fish assemblages were also recorded in sites where additional night-time surveys were conducted. Species richness was generally higher in outer Tolo Harbour and inner Tolo Channel, and priority should be given to the coastal soft-bottom and shallow water habitats in these areas to protect the species diversity and fishery resources. The results of this systematic study provide an ecological baseline of juvenile fishes in the Tolo Area for future monitoring and conservation of the marine fish communities.

Individual and community-level determinants and spatial distribution of prenatal HIV test uptake in Ethiopia: Spatial and multilevel analysis.

Human immunodeficiency virus (HIV) testing and counseling services are routine prenatal care services for the prevention of mother-to-child transmission of HIV. Although the prevalence of HIV infection is high among women, evidence suggests that the uptake of HIV testing during prenatal services in Ethiopia is scarce. Therefore, the aim of this study was to investigate individual- and community-level determinants and the spatial distribution of prenatal HIV test uptake in Ethiopia based on the 2016 Ethiopian Demographic and Health Survey. Data were accessed from the 2016 Ethiopian Demographic and Health Survey. A total weighted sample of 4,152 women aged 15-49 years who gave birth in the 2 years preceding the survey were included in the analysis. The Bernoulli model was fitted using SaTScan V.9.6 to identify cold-spot areas and ArcGIS V.10.7 to explore the spatial distribution of prenatal HIV test uptake. Stata version 14 software was used to extract, clean, and analyze the data. A multilevel logistic regression model was used to identify the individual- and community-level determinants of prenatal HIV test uptake. An adjusted odds ratio (AOR) with a corresponding 95% confidence interval (CI) was used to declare significant determinants of prenatal HIV test uptake. The prevalence of HIV test uptake was 34.66% (95% CI: 33.23, 36.13%). The spatial analysis revealed that the distribution of prenatal HIV test uptake was significantly varied across the country. In the multilevel analysis, the following individual and community-level determinants were significantly associated with prenatal HIV test uptake: women who attained primary education (AOR = 1.47, 95% CI: 1.15, 1.87) and secondary and higher education (AOR = 2.03, 95% CI: 1.32, 3.11); women from middle (AOR = 1.46; 95% CI: 1.11, 1.91) and rich household wealth status (AOR = 1.81; 95% CI: 1.36, 2.41); those who had health facility visits in the last 12 months (AOR = 2.17; 95% CI: 1.77, 2.66); women who had higher (AOR = 2,07; 95% CI: 1.66, 2.59) and comprehensive HIV-related knowledge (AOR = 2.90; 95% CI: 2.09, 4.04); women who had moderate (AOR = 1.61; 95% CI: 1.27, 2.04), lower (AOR = 1.52; 95% CI: 1.15, 1.99), and no stigma attitudes (AOR = 2.67; 95% CI: 1.43, 4.99); those who had awareness of MTCT (AOR = 1.83; 95% CI: 1.50, 2.24); those from rural areas (AOR = 0.31; 95% CI: 0.16, 0.61); high community level of education for women (AOR =1.61; 95% CI: 1.04, 2.52); and those living in large central (AOR = 0.37; 95% CI: 0.15, 0.91) and small peripheral areas (AOR = 0.22; 95% CI: 0.08, 0.60). In Ethiopia, prenatal HIV test uptake had significant spatial variations across the country. Both individual- and community-level determinants were found to be associated with prenatal HIV test uptake in Ethiopia. Hence, the impact of these determinants should be recognized while developing strategies in "cold spot" areas of prenatal HIV test uptake to enhance prenatal HIV test uptake in Ethiopia.

Effect of soil anisotropy and variability on the stability of undrained soil slope

Soil is a naturally heterogeneous material and can show significant spatial variation in strength and other properties. For silty and clayey soils, these variations are often more pronounced. Despite such variation, many past studies considered these soils as homogeneous and only considered a single set of soil parameters. This may lead to underestimation of the failure potential of geo-structure such as natural slopes, water retaining dams, retaining walls, etc. A finite element method considering soil variability should be an ideal tool to investigate the behaviour of these soils. This study adopted a 2D random finite element method to evaluate the effect of such variability on slope stability. The spatial variability was implemented by using the coefficient of variation (COV) and the spatial correlation length (θ) for cohesion. It was found that the soil slope with higher COV would have a higher chance of failure, whereas the soil slope with less COV might not show any failure. In addition, the soil with a higher θ, in general, show less potential of failure. In the literature, most studies considered an isotropic condition for the soil, i.e., θ in x and y directions are the same θx = θy, which is not realistic. Therefore, the soil anisotropy (i.e., θx ≠ θy) was considered carefully in this study. It was found that the probability of failure for anisotropic soil might be significantly higher than the isotropic soil.

Spatial and temporal variation of economic resilience and its drivers: Evidence from Chinese cities

Based on panel data of 282 cities in China from 2005 to 2019, this paper constructs an economic resilience evaluation index system in three dimensions and applies the entropy value method to measure it. The two-stage nested Thiel index, kernel density estimation and geographic detector methods are also used to explore the characteristics of their spatial and temporal divergence and their driving factors. We find that the economic resilience of Chinese cities has increased rapidly over the sample period, but with significant spatial variation, with the intra-provincial variation being the main source of the overall variation. Without considering the spatial conditions, the economic resilience of cities has a strong stability. In the case of spatial conditions, spatial factors have a significant impact on cities with low economic resilience, but not on cities with high economic resilience. Differences in technological innovation capabilities are a key driver of spatial divergence in the economic resilience of Chinese cities. The interaction of any two factors enhances their respective effects on the spatial differentiation of economic resilience in Chinese cities. Based on the above findings, cities should actively explore targeted and differentiated ways to improve economic resilience based on their comparative advantages, accelerate the construction of a collaborative improvement mechanism for urban economic resilience, and support the collaborative improvement of urban economic resilience in China. Our findings provide a useful reference for promoting the concerted improvement of economic resilience in Chinese cities.

The scattering of seismic waves from saturated river valley with water layer: Modelled by indirect boundary element method

River valley topography will cause local amplification effect and significant spatial variation effect of ground motion. In this paper, an indirect boundary element method (IBEM) is proposed to solve seismic wave scattering in sedimentary valleys. A ``water layer - soft sedimentary layer - poroelastic halfspace'' model is established, and the effects of water layer, soil parameters of sedimentary layer and terrain on incident P and SV waves are discussed in detail. The numerical results demonstrate that the scattering characteristics are closely related to the depth of water layer, porosity, the location of observation points, et al. The surface displacement amplitude decreases with increasing water layer thickness, with a maximum reduction of 16.2%. Moreover, the peak ground acceleration (PGA) is significantly larger and the seismic response is stronger when the observation point is located outside the valley compared to the observation point inside the valley. The influence of porosity on Fourier spectrum and response spectrum curve is mainly reflected in the peak value and predominant frequency. The research results can provide a theoretical basis for the seismic fortification of the structures around the saturated sedimentary valley.

Geochemical characteristics and water quality assessment in the Mt. Changbai volcanic field, Northeastern China

The chemistry of groundwater is an important determinant of water quality, which is vital to human health and the ecosystem. It is estimated that 10% of the worldwide population lives in the vicinity of an active volcano; in these regions, the quality of the water could greatly affect crop yield and soil fertility. The Mt. Changbai volcanic field (CVF), located on the border between China and North Korea, is the most well-preserved typical forest ecosystem in eastern Asia, providing various ecological services to human beings. Many types of water bodies, including hot springs, cold springs, and surface water bodies (e.g. rivers and pools) are distributed in the volcanic field. In this study, the geochemical characteristics of these water types, the quality of the water for irrigation purposes, as well as the water quality-related natural mechanism of the water chemistry in the CVF were systematically studied. The results indicate that the hydrochemical characteristics of the water samples in the CVF show the obvious difference between the volcanic cone and the peripheral areas. Significant spatial variation in the water quality was found in the CVF, where water in the peripheral areas was found to be of better water quality than that in the volcanic cone. The hot spring water in the CVF is not only unsuitable for drinking, but also unsuitable for irrigation. Water-rock interactions, ion exchange, and the addition of magmatic volatiles as well as atmospheric and anthropogenic sources are the main source and controlling factors of ions in the water in the CVF. The results of this study can be used as a reference for the sustainable management of groundwater resources in dormant volcanoes.

Coronal Abundances in an Active Region: Evolution and Underlying Chromospheric and Transition Region Properties

The element abundances in the solar corona and solar wind are often different from those of the solar photosphere, typically with a relative enrichment of elements with low first ionization potential (FIP effect). Here, we study the spatial distribution and temporal evolution of the coronal chemical composition in an active region (AR) over about 10 days, using Hinode/EIS spectra, and we also analyze coordinated IRIS observations of the chromospheric and transition region emission to investigate any evidence of the footprints of the FIP effect in the lower atmosphere. To derive the coronal abundances, we use a spectral inversion method recently developed for the MUSE investigation. We find that, in the studied active region (AR 12738), the coronal FIP bias, as diagnosed by the Si/S abundance ratio, presents significant spatial variations, with its highest values (∼2.5–3.5) in the outflow regions at the boundary of the AR, but typically modest temporal variability. Some moss regions and some regions around the AR sunspot show enhanced FIP bias (∼2–2.5) with respect to the AR core, which has only a small FIP bias of ∼1.5. The FIP bias appears most variable in these moss regions. The IRIS observations reveal that the chromospheric turbulence, as derived from IRIS2 inversions of the Mg ii spectra, is enhanced in the outflow regions characterized by the high FIP bias, providing significant new constraints to both models aimed at explaining the formation of AR outflows and models of chemical fractionation.

Modeling spatial variations in co-axial melt pool monitoring signals in laser powder bed fusion

The transition of additive manufacturing from rapid prototyping to large-scale manufacturing is being impeded by the limited repeatability of part quality within and across independent builds. The property variations are a result of process fluctuations, which can be random or systemic, like the location of the part on the build plate. In-situ sensors are employed to measure these process variations to monitor and control the part properties. A priori estimates of the systemic variations in the in-situ signals can enhance the efficiency of such techniques. In this work, custom builds for IN718, along with multiphysics simulations, are employed to probe systemic trends in the signals from the co-axial melt pool monitoring system on laser powder bed fusion based GE Concept Laser M2. Significant spatial variations are observed in the in-situ melt pool area, and intensity signals, and the subsequent analysis suggests that the interplay of the angled laser beam and the shield gas flow is likely a major source of the spatial trends. Machine learning is employed to develop data-driven surrogate models that make accurate predictions for this systemic variation in the melt pool area and intensity, generalizing across independent builds with significantly diverse print parameters. These models are anticipated to inform control algorithms and tune optimal print parameters with the objective of enhancing the repeatability of the part quality for laser powder bed fusion.

A spatial analysis of TB cases and abnormal X-rays detected through active case-finding in Karachi, Pakistan

Tuberculosis (TB) is the leading cause of avoidable deaths from an infectious disease globally and a large of number of people who develop TB each year remain undiagnosed. Active case-finding has been recommended by the World Health Organization to bridge the case-detection gap for TB in high burden countries. However, concerns remain regarding their yield and cost-effectiveness. Data from mobile chest X-ray (CXR) supported active case-finding community camps conducted in Karachi, Pakistan from July 2018 to March 2020 was retrospectively analyzed. Frequency analysis was carried out at the camp-level and outcomes of interest for the spatial analyses were mycobacterium TB positivity (MTB+) and X-ray abnormality rates. The Global Moran’s I statistic was used to test for spatial autocorrelation for MTB+ and abnormal X-rays within Union Councils (UCs) in Karachi. A total of 1161 (78.1%) camps yielded no MTB+ cases, 246 (16.5%) camps yielded 1 MTB+, 52 (3.5%) camps yielded 2 MTB+ and 27 (1.8%) yielded 3 or more MTB+. A total of 79 (5.3%) camps accounted for 193 (44.0%) of MTB+ cases detected. Statistically significant clustering for MTB positivity (Global Moran’s I: 0.09) and abnormal chest X-rays (Global Moran’s I: 0.36) rates was identified within UCs in Karachi. Clustering of UCs with high MTB positivity were identified in Karachi West district. Statistically significant spatial variation was identified in yield of bacteriologically positive TB cases and in abnormal CXR through active case-finding in Karachi. Cost-effectiveness of active case-finding programs can be improved by identifying and focusing interventions in hotspots and avoiding locations with no known TB cases reported through routine surveillance.