Multivariate Statistical Methods Research Articles

Organizational ethics and position relationship moderators among knowledge workers: a regional study of Poland

ABSTRACT This research explores organizational ethics among knowledge workers using ICT4Ds in regional enterprises in Poland before, during, and after the COVID-19 pandemic. The study addresses the importance of understanding how ethics in organizations, particularly ethical optimism, corporate social responsibility, and top management action, have evolved across these periods. This topic is crucial as organizational ethics influence employee behavior and decision-making, particularly during crises. The research question focuses on how organizational ethics, influenced by gender and the pandemic, differ by position. Online surveys and random sampling were employed to collect data among knowledge workers (139 before, 134 during, and 98 after the pandemic). The study applied multivariate statistical methods, including variance analysis and causal moderation. Findings were that superiors rated organizational ethics higher than subordinates, and ethical optimism fluctuated, rising during the pandemic and dropping afterward. The study contributes to understanding the role of gender and crises as moderators in organizational ethics, benefiting managers and policymakers.

Editorial: Is There a Relationship/An Association Between ABO Blood Group System and Cardiac Conduction Disorders?

Abstract Introduction Data from the literature suggest a slight increase in cardiovascular risk for people with non-O blood types. The purpose of the study was to evaluate if there is an association between advanced cardiac conduction disorders and blood groups. Material and methods In this retrospective study, a group of patients with atrio-ventricular conduction disorders or sinus node disease, having an indication for permanent cardiostimulation, was analyzed and compared with a control group consisting of patients who underwent coronary angiography or elective peripheral angiography. The blood group was determined in all patients. Univariate and multivariate statistical methods were used. Results Six hundred forty patients, mean age 72±11y, 55.3% men, were included: 320 patients with advanced atrio-ventricular conduction disorders or sinus node dysfunction in the study group and 320 patients in the control group. Blood type A had the highest prevalence (46.8%), followed by blood types O (28.95%), B (16.74%) and AB (7.51%). In the group with heart rhythm disorders, patients with blood type A had an increased risk of atrio-ventricular block (OR 1.38, p= 0.02), but not with sinus node disease (OR 1.02, p= 0.98). Blood type O had a protective role both for atrio-ventricular block and for sinus node dysfunction (OR 0.65, p= 0.01). Conclusion Blood type A proved to be an independent predictor for atrio-ventricular conduction disorders in patients with severe heart rhythm disorders with indication for permanent cardiostimulation.

A new approach to assess post-mortem interval: A machine learning-assisted label-free ATR-FTIR analysis of human vitreous humor

A crucial issue in forensics is determining the post-mortem interval (PMI), the time between death and the finding of a body. Despite various methods already employed for its estimation, only approximate values are currently achievable. Vitreous humor (VH) is an avascular tissue between the lens and the retina, mainly composed by a collagen fibers network, hyaluronic acid, and hyalocytes. Recently, it has received interest in forensic medicine, being easy to collect and susceptible to low microbiological contamination and putrefaction. Based on this evidence and thanks to the ability of Attenuated Total Reflectance – Fourier Transform InfraRed (ATR–FTIR) spectroscopy to perform fast analyses on a minimal sample amount, in this study, a new analytical approach to reliably estimate PMI is proposed combining ATR-FTIR analysis of VH human samples with multivariate statistical procedures, such as Principal Component Analysis (PCA) and Partial Least Squares-Discriminant Analysis (PLS-DA), for discriminant classification. Regression procedures, including Partial Least Squares Regression (PLSR), were performed: extremely positive results were obtained, and the most discriminant spectral features were highlighted (peaks at 1665, 1630, 1585, 1400, 1220, 1200, 1120, 854, 835, and 740 cm−1) and associated to PMI classes (average accuracy over 80 %). Specific and reliable markers able to correlate the macromolecular composition of VH with the PMI were identified, revealing a post-mortem protein degradation and amino acids deamination (decrease of proteins and increase of free amino acids and NH3), an increase of lactate, which diffuses from the retina to the VH, and changes in the hyaluronic acid component.

Sediment evaluation indices point to cadmium and selenium contamination: A simultaneous analysis of potentially toxic elements in the water and sediment along the upper and middle Awash River, Ethiopia

This study presents a simultaneous analysis of potentially toxic elements (PTEs) in the water and sediment of the upper and middle Awash River for the first time. We used standard field and laboratory procedures, sediment assessment indices and guidelines, and multivariate statistical methods to analyze PTEs and assess their possible sources. Water and sediment samples were collected from nine sampling sites, and PTEs were analyzed using the Inductively Coupled Plasma Optical Emission Spectrometer. The PTEs concentrations arranged in descending order in water were Fe>Mn>B>Zn>Cr>Ni>Pb>Cu, ranging between 4.14 ± 2.093 mg L 1 and 0.074 ± 0.016 mg L 1. The level of PTEs in the sediment varied between 24,493.6 ± 16,640.3 mg kg-1 and 0.4 ± 0.2 mg kg-1 and follows the order: Fe>Mn>Cr>Zn>Pb>Ni>B>Se>Co>Cu>Cd>Hg>As. The river-mouth of the upper Awash had the highest concentrations of Mn, Ni, Cr, and Cu in water and Fe, Mn, Cr, Ni, Pb, Co, Se, Cu, Cd, and AS in the sediment. Contamination factor, enrichment factor, and geo-accumulation index showed a very high level of contamination of Se and Cd. The ecological risk index, Nemerow pollution index, and pollution load index also indicated a high ecological risk and pollution by PTEs in the river. The levels of Fe, Pb, Ni, Mn, B, and Cr in the water surpassed Ethiopian/WHO's drinking water guidelines, while the levels of Cd, Hg, and Cr in the sediment exceeded Canadian/Ontario's probable/severe effect levels. This study revealed the presence of ecological degradation at the downstream sites of the upper and middle Awash. The most likely sources of contaminants were identified as small-scale agricultural pollution, residential and commercial waste from towns like Addis Ababa, Merti, and Metehara, and the inflow of Lake Beseka. We recommend an integrated management plan for the Awash River to ensure sustainable use of the water, guarantee the well-being of wildlife, and reduce public health risks.

Structural characterization and screening of chemical markers of alkaloids in Aconiti lateralis radix Praeparata and its processed products by UHPLC/Q-TOF-MS/MS and GNPS combining multivariate statistical methods based on the clinic.

Aconiti Lateralis Radix Praeparata (AC) is a traditional Chinese medicine with a long history of use. However, the current research on the material basis of AC and its processed products is still not comprehensive, especially the changes in lipo-diterpenoid alkaloids (LDAs) that can be hydrolyzed into diester-diterpenoid alkaloids in AC before and after processing. This study aimed to provide material basis guidance for the clinical use of AC and its processed products by comprehensively analyzing the changes in substances between AC and its processed products. An ultra-high-performance liquid chromatography with quadrupole time-of-flight mass spectrometry (UHPLC/Q-TOF-MS/MS) approach was optimized to chemical profiling. The MS data were processed using molecular networking combined with the in-house library database to fast characterize the compounds. Multivariate statistical methods were adopted to determine the dissimilarities of components in AC and its processed products. A total of 310 compounds were tentatively identified from AC, including 109 potential new alkaloids, of which 98 were potential novel LPAs. A metabolomics approach was applied to find the characteristic marker components. As a result, 52 potential chemical markers were selected to distinguish the AC samples of different extraction methods and 42 potential chemical markers for differentiating between AC and its processed products were selected. The results indicate that UHPLC/Q-TOF-MS/MS and Global Natural Products Social Molecular Networking coupled with multivariate analysis strategies was a powerful tool to rapidly identify and screen the chemical markers of alkaloids between the AC samples and its processed products. These results also indicate that the toxicity of water extracts of AC and its processed products were decreased. This research not only guides the clinical safe use of AC and its processed products, but also extends the application of the molecular networking strategy in traditional herbal medicine.

Morphological variation of endemic Gymnocypris chilianensis (Cyprinidae) collected from three inland water systems in Qilian Mountains, China

To explore the morphological differences among different geographic populations of Gymnocypris chilianensis, 29 measurable traits and 13 landmarks on 191 individuals of 10 geographic populations were collected from three different inland water systems, i.e., Shiyang River, Heihe River, and Shule River, in Qilian Mountains, China. Multivariate statistical methods were used to compare morphological differences among the populations, such as principal component analysis, cluster analysis, discriminant analysis, and visual analysis of landmark data. The results showed that: (1) There were significant morphological differences between groups of G. chilianensis. The Shiyang River basin differs significantly from populations in the other two basins. (2) The inter-population differences were mainly reflected in the length of the trunk and tail, and the difference between trunk and caudal fin had the most obvious characteristics, proving the tail being the main direction of variation. This research provides an effective theoretical basis for the fine management and accurate protection of G. chilianensis germplasm resources.

GROUNDWATER POLLUTION SOURCE USING PRINCIPAL COMPONENT ANALYSIS IN GUELMA PLAIN, NORTHEAST ALGERIA

This study was conducted in the agricultural region of Guelma, located in northeastern Algeria, where groundwater is the main source of water for human consumption, agriculture, and industry. The objective was to characterize groundwater quality and identify potential pollution sources using multivariate statistical methods, including Principal Component Analysis (PCA), correlation matrix, and the Piper diagram. The analyses revealed strong correlations between certain ions, such as sodium and chloride, suggesting carbonate dissolution processes, such as calcite and dolomite, leading to increased water hardness. The Piper diagram allowed for the classification of water types based on the relative concentrations of major cations (Ca²⁺, Mg²⁺, Na⁺+K⁺) and anions (Cl⁻, SO₄²⁻, CO₃²⁻+HCO₃⁻), showing a predominance of mixed hydrochemical types influenced by both natural and anthropogenic processes.PCA then simplified the interpretation by identifying the most influential variables that could serve as key indicators for the continuous monitoring of water quality. Overall, the results indicate that groundwater chemistry in this region is strongly influenced by human activities and local geological conditions, highlighting the need for sustainable management and continuous monitoring to protect this vital resource.

Study on Sensory Quality and Flavor Characteristics of Jiangxiang Baijiu Produced by Different Fermentation Techniques

As a representative of traditional Chinese distilled liquor, the unique flavor of Sauce Flavor Baijiu is closely related to its brewing techniques. This study systematically explored the sensory quality and flavor characteristics of Sauce Flavor Baijiu produced by different fermentation techniques through sensory evaluation, gas chromatography analysis, and multivariate statistical methods. The results indicated that the techniques of Chuansha, Suisha, Kunsha, and their blends significantly influenced the concentration and proportion of flavor compounds in Baijiu, subsequently altering its aroma and taste. Specifically, Chuansha Baijiu exhibited weaker aroma and thinner taste; Suisha Baijiu presented certain complexity and a softer taste; while Kunsha Baijiu boasted a strong aroma and full-bodied taste. This study established a scientific quality evaluation system for Sauce Flavor Baijiu, providing theoretical foundations and technical support for the optimization of brewing techniques and improvement of Baijiu quality.

Analysis and discrimination of adhesive species using ATR-FTIR combined with Raman, and HS-GC-IMS together with multivariate statistical analysis

Identifying the species and origin of adhesives in criminal investigations aids in narrowing inquiry scope and supporting case detection. This study introduces two advanced combined analytical techniques for distinguishing adhesive species, including attenuated total reflectance-Fourier transform infrared spectroscopy (ATR-FTIR) combined with Raman spectroscopy, and headspace gas chromatography-ion mobility spectrometry (HS-GC-IMS) together with multivariate statistical analysis. ATR-FTIR categorized seven adhesives into three groups based on the base materials, with further differentiation achieved via Raman spectra. Analysis of volatile components identified 79 volatile organic compounds (VOCs), with esters being the most concentrated. The fingerprint profile clearly illustrated the characteristic fingerprint sequence and unique marker compounds of each adhesive, effectively enabling their differentiation. Multivariate statistical analysis methods, including principal component analysis (PCA), orthogonal partial least squares discriminant analysis (OPLS-DA), heatmap, and hierarchical cluster analysis (HCA), were utilized to visually interpret the classification of adhesives. This integrated analytical approach provides a comprehensive analysis of adhesive compositions, facilitating the diversification and precision of adhesive species identification, and broadening the scope for detecting and analyzing trace evidence in forensic science.

Cocoa bean metabolomics reveals polyphenols as potential markers relating to fine dark chocolate color shades.

This study aimed to evaluate the color and the discriminating compounds for two types of cocoa beans (black and brown beans) related to 70% dark chocolates of black and brown colors from a previous work of our group. Color analysis and untargeted high-resolution mass spectrometry-based metabolomic analysis were performed on eight beans of each type. Mass spectral data processing, univariate and multivariate statistical methods were conducted for classification of beans and selection of discriminant features. The results showed that the color difference already observed for black and brown chocolates preexists in the beans. Black and brown beans had 45 and 50 discriminant features, respectively, of which 16 and 41 were phenolic compounds. Most of them were also previously identified as discriminating compounds for black and brown chocolates. Black beans predominantly contained glycosylated flavanols, ranging from monomers to trimers, with dimers and trimers being A-type procyanidins, along with a phenolic acid (protocatechuic acid), and an O-glycosylated flavonol (quercetin-3-O-glucoside). In contrast, brown beans mostly contained non-glycosylated B-type procyanidins ranging from dimers to decamers, but also dimers and trimers of A-type procyanidins, and a glycosylated and sulfated flavanol ((epi) catechin hexoside-sulfate). These markers may be useful for quality control purposes and may contribute to the selection of beans that yield black or brown dark chocolates.

Mortality and Associated Risk Factors in Patients With Candida auris: Insights From a Tertiary Care Hospital in Bahrain.

Introduction Candida auris poses a significant healthcare challenge due to its high mortality rates, difficulties in identification, and resistance to antifungal treatment. This study aims to identify risk factors associated with 30-day mortality in patients with either invasive Candida auris infection or colonization. Methods We conducted a prospective study at Salmaniya Medical Complex, a tertiary care hospital in Bahrain, from September 2023 to February 2024. The study included 59 patients infected or colonized by Candida auris. Data were systematically collected from patient records, including demographics, clinical characteristics, and outcomes. Risk factors for 30-day mortality were analyzed using both univariate and multivariate statistical methods. Results Among the 59 patients studied, the mean age was 63.9 years, and the cohort was predominantly male (74.6%). Key findings include a high prevalence of multiple indwelling catheters (44.2%) and recent intubation (42.4%). Candida auris was most frequently isolated from the groin (33.9%) and urine (25.4%), with a notable presence in the axillary regions (23.7%). The mortality rate was 44.1%. Univariate and multivariate analyses revealed that age (≥65 years), multiple indwelling catheters, ICU admission for over 24 hours, and recent intubation were significant risk factors for mortality while chronic kidney disease did not retain its significance in the multivariate model. Conclusion The study underscores the critical need for focused infection control and strong antimicrobial stewardship to address the high mortality associated with Candida auris infections. Emphasizing the importance of early detection and a multidisciplinary approach, these strategies are essential for managing and mitigating the impact of Candida auris in healthcare settings.

Nomads of the Oghuz-Pecheneg Time of the Volga-Don Region According to Anthropology Data.

Introduction. The article presents the results of an anthropological study of the nomads of the Oghuz-Pecheneg period of the Volga-Don region, known from written and archaeological sources. Material and methods. To carry out the analysis, both published materials and new ones studied by the author were used. The craniological series included data on 55 skulls – 38 male and 17 female. The new material is represented by skulls obtained from excavations of cemeteries in the Volgograd region, for 23 skulls. The anthropological composition, intragroup structure, and ethnogenetic connections were determined by the methods of simple and multivariate statistics. Analysis and discussion. The arithmetic mean values of the male and female craniological series demonstrated a racially mixed Caucasoid-Mongoloid complex, components of which are determined in men by II and in women by both I and II principal components. In addition, in the male series I, the main component performs the function of size and demarcates the skulls with a massive and gracile structure of the brain and facial regions. The multiple discriminant analysis carried out in order to identify ethnogenetic connections showed the greatest similarity of a series of nomads of the Oghuz-Pecheneg period both with their predecessors, the population of the Khazar period, and with groups of Cuman and Golden Horde nomads. The Turkic origin of the study group demonstrates connections with the synchronous populations of Southern Siberia and Kazakhstan. Conclusions. The Oghuz-Pecheneg people exhibited a racially heterogeneous anthropological composition, combining Mongoloid and Caucasoid components. This is a direct consequence of their origin. Apparently, the nomads of the Volga-Don region of the studied time, after its development, could include in their composition the nomadic groups of the previous Khazar time and form the composition of both the urban and nomadic population of the Golden Horde.

Comprehensive investigation on the flavor difference in five types of tea from JMD (Camellia sinensis 'Jinmudan').

Jinmudan (JMD) is a high-aroma variety widely cultivated in China. The current study primarily focuses on the key volatile metabolites in JMD black and oolong teas,and investigates the impact of processing technologies on the aroma quality of JMD tea. However, few studies have explored the suitabilityof JMD for producing a certain type of tea or the characteristic quality differences among various JMD teas using multivariate statistical analysis methods. The principal volatile metabolites contributing to the floral quality of JMD tea are linalool, geraniol, indole and phenethyl alcohol. In JMD black tea (BT), the key volatile metabolites include methyl salicylate, geraniol, (E)-β-ocimene and phenethyl alcohol. In JMD oolong tea (OT), the key volatile metabolites include indole, linalyl valerate and phenethyl alcohol. In JMD yellow tea (YT), the key volatile metabolites include methyl salicylate, geraniol and terpinolene. In JMD white tea (WT), the key volatile metabolites include methyl salicylate, geraniol and terpinolene. In JMD green tea (GT), the key volatile metabolites include (E)-β-ocimene, indole and geraniol. Comparative analysis and KEGG pathway enrichment analysis revealed that flavonoid biosynthesis is the primary metabolic pathway responsible for the taste differences among various tea types. GT exhibited higher levels of phloretin, dihydromyricetin and galangin. The contents of vitexin, tricetin in YT were relatively higher. The contents of aromadendrin and naringenin in BT were higher, while OT contained higher levels of kaempferol. Additionally, WT showed higher contents of 3-O-acetylpinobanksin and 3,5,7-pinobanksin. This study explained the reasons for the quality differences of different JMD tea and provided a reliable theoretical basis for the adaptability of JMD tea. © 2024 Society of Chemical Industry.

The Combined Effects of the Thermal Environment and Air Quality at Recreation Places on the Physiology and Psychology of People in Urban Parks

Urban forests, crucial to urban ecosystems, are increasingly threatened by the challenges of urbanization, such as deteriorating thermal environments and declining air quality. Despite their recognized benefits to city dwellers’ quality of life, a systematic understanding of the impact of these environmental factors on public psychophysiological well-being in recreational sites is a notable gap in the literature. The objective of this research was to bridge this gap by examining the effects of the thermal environment and air quality in urban forests on the public’s perception, offering scientific evidence to inform environmental optimization and health management strategies for urban parks, essential for sustainable urban development and public health. Three urban parks in Fuzhou, Fujian Province, namely Fuzhou National Forest Park, Xihu Park, and Jinniushan Sports Park, were selected as research sites. Environmental monitoring and questionnaire surveys were conducted at 24 recreation places from October to December 2020, collecting temperature, humidity, and wind speed; the atmospheric composition includes PM2.5, PM10, negative oxygen ion, and psychophysiological data from the public. Multivariate statistical methods were employed to assess the environmental characteristics of different recreation places types and their impact on public health. The findings reveal that environmental factors explained 1.9% to 11.8% of the variation in physiological and psychological responses, mainly influenced by temperature, wind speed, and negative oxygen ions. Forests and waterfront recreation places significantly outperform canopy and open recreation places in promoting mental invigoration, stress relief, emotional tranquility, and attention restoration. Environmental monitoring results indicate that favorable meteorological conditions and good air quality are crucial for enhancing the service functions of recreation places. Notably, the positive correlation between a negative air ion concentration and psychological well-being provides a novel perspective on understanding the health benefits of urban forests. The thermal environment and air quality of urban recreation places exert a significant influence on the psychophysiological status of the public. Increasing green coverage, improving water body environments, and rationally planning recreation places layout are of great theoretical and practical significance for enhancing the environmental quality and service functions of urban forests.

Spatiotemporal distribution of cyanobacteria in relation to water chemistry of Sutlej River, Punjab (India).

In this investigation, the spatiotemporal distribution of cyanobacteria and their relationships with variations in water chemistry (physico-chemical parameters and heavy metal) of Sutlej River, Punjab (India) has been analyzed by employing multivariate statistical methods. Sutlej River exhibits a rich array of cyanobacterial diversity, comprising 28 species across 15 genera, distributed among 11 families and spanning 5 orders within the class Cyanophyceae. In terms of relative abundance, Microcystis aeruginosa (17.47%) was documented as the most abundant taxa followed by Microcystis robusta (16.55%), Merismopedia punctata (11.03%), Arthrospira fusiformis (6.67%) and Pseudanabaena galeata (3.68%). Significant variations were observed among sampling sites in most of the physico-chemical parameters. Principal Component Analysis delineated sampling sites into two discernible groups according to variations in water chemistry. River Pollution Index (RPI) showed that river water is under the unpolluted (RPI 1.5) to negligibly polluted category in the upstream sites, while moderately polluted (RPI 5.5) in the downstream sites. Heavy metal Pollution Index (HPI) revealed consistent heavy metal contamination at sites RWS7 and RWS8 across all seasons. Conversely, site RWS1 consistently exhibited lower HPI values throughout the three studied seasons. Further, Canonical Correspondence Analysis identified that pH, TDS, TA, NO3, Na, and NH4 are the key physicochemical parameters which affect the spatiotemporal distribution of cyanobacteria in the studied river system. Overall, this study will offer significant information for hydrologists, ecologists, and taxonomists to develop future holistic strategies for further monitoring of the Sutlej River and other similar habitats.

Identifying environmental impacts on planktonic algal proliferation and associated risks: a five-year observation study in Danjiangkou Reservoir, China

Understanding the risks of planktonic algal proliferation and its environmental causes is crucial for protecting water quality and controlling ecological risks. Reservoirs, due to the characteristics of slow flow rates and long hydraulic retention times, are more prone to eutrophication and algal proliferation. Chlorophyll-a (Chl-a) serves as an indicator of planktonic algal biomass. Exploring the intricate interactions and driving mechanisms between Chl-a and the water environment, and the potential risks of algal blooms, is crucial for ensuring the ecological safety of reservoirs and the health of water users. This study focused on the Danjiangkou Reservoir (DJKR), the core water source of the Middle Route of the South-to-North Water Diversion Project of China (MRSNWDPC). The multivariate statistical methods and structural equation modeling were used to explore the relationships between chlorophyll-a (Chl-a) contents and water quality factors and understand the driving mechanisms affecting Chl-a variations. The Copula function and Bayesian theory were combined to analyze the risk of changes in Chl-a concentrations at Taocha (TC) station, which is the core water source intake point of the MRSNWDPC. The results showed that the factors driving planktonic algal proliferation were spatially heterogeneous. The main factors affecting Chl-a concentrations in Dan Reservoir (DR) were water physicochemical factors (water temperature, dissolved oxygen, pH value, and turbidity) with a total contribution rate of 60.18%, whereas those in Han Reservoir (HR) were nutrient factors (total nitrogen, total phosphorus, and ammonia nitrogen) with a total contribution rate of 73.58%. In TC, the main factors were water physicochemical factors (turbidity, pH, and water temperature) and nutrient factors (total phosphorus) with total contribution rates of 39.76% and 45.78%, respectively. When Chl-a concentrations in other areas of the DJKR ranged from the minimum to the uppermost quartile, the probabilities that Chl-a concentrations at the TC station exceeded 3.4 μg/L (the benchmark value of Chl-a for lakes in the central-eastern lake area of China) owing to the influence of these areas were all less than 10%. Thus, the risk of planktonic algal proliferation at the MRSNWDPC intake point is low. This study developed an integrated framework to investigate spatiotemporal changes in algal proliferation and their driving factors in reservoirs, which can be used to support water quality management in mega hydro projects.

Comprehensive comparison of two colour varieties of Perillae folium by UHPLC-Q-TOF/MS analysis combining with feature-based molecular networking

Perillae Folium (PF), the leaf of Perilla frutescens (L.) Britt is extensively used as a culinary vegetable and medicinal herb in many countries. Purple PF (P. frutescens var. arguta) and green PF (P. frutescens var. frutescens) are two of the main varieties. In this study, UHPLC-Q-TOF/MS assisted with feature-based molecular networking (FBMN) was applied for chemical characterization. In total, 82 metabolites, mainly phenolic acid derivatives were identified from PF. With the help of FBMN, five organic acid glucosides together with three N-phenylpropenoyl-L-amino acids (NPAs) were identified in PF for the first time. Multivariate statistical methods were utilized for comprehensive comparison of purple and green PF profiles. 12 compounds with their relative contents varied significantly between purple and green PF were screened out. Overall, the present study offers valuable insights for chemical elucidation of PF which would be helpful for comprehensive utilization of PF resource.

Understanding the spatial patterns of atmospheric ammonia trends in South Asia

Ammonia (NH3) is the most abundant alkaline gas in the atmosphere, mainly emitted by agricultural activities. NH3 readily reacts with other atmospheric acidic pollutants, such as the oxidation products of sulfur dioxide (SO2) and nitrogen oxides (NOₓ), to create fine particulate matter, which has far-reaching effects on human health and ecosystems. Here, we investigated long-term atmospheric NH3 trends in South Asia (SA) using satellite observations from the Infrared Atmospheric Sounding Interferometer (IASI). We analyzed 15 years (2008–2022) of IASI-NH3 retrievals against climate, biophysical, and chemical variables using an ensemble of multivariate statistical methods to identify the major factors driving the observed patterns in the region. Trend analysis of IASI-NH3 data reveals a significant rise in atmospheric NH3 over 51 % of SA plains, but a downward trend over 31 % of the region. Spatial correlation analysis reveals that biophysical factors, representing cropland expansion and agriculture intensification, have the highest positive correlation over 56 % of SA plains experiencing positive NH3 trends. However, our results reveal that the chemical conversion of NH3 to ammonium compounds, driven by the positive trends in NOₓ and SO2 pollution, is driving the apparently declining trend of NH3 in the other regions. Our results provide important insights into the NH3 trends detected by satellite data and can better inform the policy design aimed at reducing NH3 emissions and improving air quality for developing regions of the world.

Assessment of water quality and identification of priority areas for intervention in Guanabara Bay basin, Rio de Janeiro, Brazil, using nonparametric and multivariate statistical methods.

The Guanabara Bay hydrographic region (GBHR) has served as a central hub for human settlement and resource utilization throughout Brazil's history. However, the region's high population density and intense industrial activity have come at a cost, leading to a significant decline in water quality. This work aimed to identify homogeneous regions in GBHR according to water quality parameters in dry and rainy periods. The following water quality monitoring variables were monitored at 49 gauge stations: total phosphorus (TP), nitrate (NO3-), dissolved oxygen (DO), hydrogenionic potential (pH), turbidity (Turb), thermotolerant coliforms (TCol), total dissolved solids (TDS), biochemical oxygen demand (BOD), water temperature (Tw), and air temperature (Ta). The statistical analysis consisted of determining principal components, cluster analysis, seasonal differences, and Spearman's correlation. The water quality parameter correlations were not expressively influenced by seasonality, but there are differences in the concentrations of these parameters in the dry and rainy periods. In the dry period, urban pressure on water quality is mainly due to fecal coliforms. The resulting clusters delimited areas under urban, agricultural, and forestry influence. Clusters located in areas with high demographic density showed high concentrations of TCol and TP, while clusters influenced by forestry and agriculture had better water quality. In the rainy season, clusters with urban influence showed problems with TCol and TP, in addition to some characteristics in each group, such as high TDS, NO3-, and BOD. Forested areas showed high DO, and clusters under agricultural influence had higher concentrations of TCol, BOD, and NO3- concerning forested regions. The troubling state of sanitation in GBHR occurs in metropolitan regions due to lack of a formal sanitation system.

CROSS-FACTOR MODELING OF ESG RISKS

The purpose of this study is to develop a cross-factor model for assessing ESG risks in the Republic of Kazakhstan.The research methodology involves using cross-factor modeling with standard multivariate statistical methods, including multiple regression analysis, to assess ESG risks in Kazakhstan from 2010 to 2020. The methodology incorporates environmental, economic, and social components into a model, calculating their respective sums and determining the integral ESG indicator (I) through normalization and weighted averaging. The final stage involves conducting regression analysis to determine the coefficients for each component, ensuring that the model accurately reflects the impact of these factors on the region's economic security.The orginality / value of the research: This model aims to evaluate the mutual and combined effects of various ESG factors on integral indicators, with the goal of understanding how these factors can lead to reputational or financial damage to companies. By defining and measuring three structural components— environmental, economic, and social—the study constructs a set of indicators for each component and employs multiple regression analysis to build a comprehensive model and determine the coefficients for an integral ESG indicator.Findings. To assess ESG risks in Kazakhstan, cross-factor analysis methods are recommended, enabling the determination and justification of each factor's numerical contribution to the integral indicator. Recent dynamics in implementing ESG principles in Kazakhstan's corporate practice are uneven, influenced by factors such as company publicity and sector-specific ESG risks. Regulatory changes, including updates to the Environmental and Entrepreneurial Codes and ESG reporting requirements, create incentives for corporations to adopt ESG principles, necessitating further regulatory improvements and increased business community awareness.