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1

Immediate energy-saving responses of EU households to the 2022 Russian invasion of Ukraine: a cluster analysis

Buchholtz Sonia

Economics and Environment

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2026

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No. 1

art. no. 953

EN

This article examines the immediate energy-saving strategies declared by EU households in response to the 2022 Russian invasion of Ukraine, which exposed the Union’s reliance on Russian fossil fuels. Drawing on data from Flash Eurobarometer 506 (April 2022), the study applies principal component analysis and k-means clustering to identify coherent behavioural patterns. Three segments are distinguished: engaged (broad action takers), selective (focused on low-cost behavioural changes), and unwilling (low or no declared engagement). While most respondents expressed a willingness to act, only a minority reported strategies that spanned both behavioural and investment domains. Cross-country variation was more pronounced than socio-demographic differences, highlighting the role of national context, geopolitical awareness, and perceived urgency. The findings contribute to the understanding of household behaviour under acute external shocks and demonstrate the value of strategy-based segmentation. Policy implications include designing targeted interventions aligned with behavioural patterns, rather than relying solely on socio-demographic profiling.

PL

Artykuł analizuje natychmiastowe strategie oszczędzania energii deklarowane przez gospodarstwa domowe w Unii Europejskiej w odpowiedzi na inwazję Rosji na Ukrainę w 2022 roku, która uwidoczniła zależność UE od rosyjskich paliw kopalnych. Na podstawie danych z badania Flash Eurobarometr 506 (kwiecień 2022) zastosowano analizę głównych składowych (PCA) oraz grupowanie metodą k-średnich w celu identyfikacji spójnych wzorców zachowań. Wyróżniono trzy segmenty: zaangażowanych (podejmujących szeroki zakres działań), selektywnych (koncentrujących się na niskokosztowych zmianach zachowań) oraz niezaangażowanych (brak lub niska deklarowana aktywność). Choć większość respondentów wyraziła gotowość do działania, tylko mniejszość zadeklarowała strategie obejmujące zarówno zachowania, jak i inwestycje. Zróżnicowanie między krajami okazało się wyraźniejsze niż różnice demograficzne, co podkreśla znaczenie kontekstu narodowego, świadomości geopolitycznej i poczucia pilności. Wyniki przyczyniają się do lepszego zrozumienia reakcji gospodarstw domowych na kry-zysy zewnętrzne i wskazują na potrzebę projektowania polityk dostosowanych do typów zachowań, a nie jedynie profili demograficznych.

2

The critical factors for successfully applying lean tools in the Egyptian construction sector

Shaqour Eman, Alshafei Islam A., AbuKarki Hanan, Almashhour Rashwan T. N.

Budownictwo i Architektura

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2026

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Vol. 25, no. 1

art. no 26004

EN

Lean construction has gained global recognition for improving efficiency, yet its adoption in Egypt remains hindered by numerous barriers. This study empirically investigates the key factors influencing the successful implementation and adoption of lean construction practices in Egypt. Using a data-driven methodology, the research identifies the five most critical CSFs are: awareness of lean philosophy, elimination of design errors, effective management of the production chain, strong collaborative relationships, and a robust work plan with comprehensive risk planning. An extensive review of previous research was conducted to identify Critical Success Factors (CSFs), resulting in a list of 27 factors included in a survey. A questionnaire was distributed to 162 practitioners involved in construction projects to evaluate the significance of these CSFs in the Egyptian context. Various statistical analyses were performed using IBM SPSS Statistics, including validity and reliability tests, descriptive statistics for ranking the CSFs, and principal component analysis (PCA) to identify the primary drivers of lean construction success. Beyond demonstrating established CSFs, the findings underscore their contextual relevance in a developing economy, offering practical guidance for industry stakeholders and extending theoretical insights into lean implementation across construction environments.

3

Integrated meteorological and hydrological drought assessment using a GIS-PCA framework in a humid tropical catchment of the Western Ghats, India

Sharannya T. M., Ashna K. A. Mary, Naveena K.

Acta Geophysica

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2026

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vol. 74, no. 3

art. no. 153, s. 1--21

EN

Drought is a critical natural hazard that poses significant challenges across various sectors, particularly in regions with high population density and water dependency. Despite their slow onset, droughts are difficult to manage due to their uncertain duration, intensity, and spatial extent. This study presents a comprehensive analysis of drought events over a 20-year period (2002-2022) in the Bharathapuzha River Basin (BRB), a humid tropical catchment in Kerala, India. Both meteorological and hydrological droughts were assessed using the Standardized Precipitation Index (SPI) and the Streamflow Drought Index (SDI), respectively, across multiple timescales (1-, 3-, 6-, and 12-month). The study integrates SPI and SDI using Principal Component Analysis (PCA) to derive a Composite Drought Index (CDI) for assessing overall drought severity. The CDI effectively captures the compounded impacts of precipitation deficits and streamflow reductions. Results reveal a strong relationship between SPI and SDI, particularly at the 12-month timescale, highlighting the potential of the composite approach for comprehensive drought assessment. The 2016-2017 drought emerged as the most severe during the study period, corroborated by records from the Kerala State Disaster Management Authority (KSDMA). While validated against historical drought records, the CDI showed good agreement, indicating its potential utility for drought assessment. Spatial mapping of drought severity revealed significant intra-basin variability, emphasizing the need for region-specific mitigation strategies. The study recommends adaptive measures such as rainwater harvesting, recharge well construction, and catchment reforestation to build long-term resilience. These insights are essential for informed water resource planning and drought-risk reduction in the BRB and similar humid tropical regions.

4

Singular value versus eigenvalue decomposition efficiency in computing principal components for dimensionality reduction of large datasets

Romanuke Vadim

Scientific Journal of Gdynia Maritime University

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2025

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nr 134

56--70

EN

Principal component analysis, being one of the best techniques for dimensionality reduction, is implemented by using one of the two high-accuracy algorithms: the singular value decomposition (SVD) and eigenvalue decomposition (EVD). The EVD is generally faster than the SVD, except for datasets with fewer observations or when the observation has fewer features. Apart from cases of shallower datasets consisting of just a few hundred double-precision observations, the EVD speeds up computing principal components by at least 4.5%, whereas the average speedup in 45% widely varies from 12% to 92%. The speedup on non-shallower single-precision datasets is roughly similar, but it nonetheless makes no sense due to EVD poor accuracy while operating on numeric data with single precision. The EVD is efficient if the dataset consists of no fewer than a few hundred observations (objects) having at least three double-precision features.

5

Assessing the Interdependence between Air Pollutant Emissions and Energy Consumption in the Context of Energy Independence

Bălănică Dragomir Carmelia Mariana, Crețu Mirela, Coadă Marian Tiberiu, Ceoromila Alina Mihaela, Șerban Cecilia

Inżynieria Mineralna

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2025

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Vol. 3, no. 2

art. no. 43

EN

There is extensive agreement between energy resources and strategy analysts in Romania and the accelerating energy demand is the principal contributing factor to anthropic air pollution emissions. Energy is indispensable to entire economic sectors, despite that, the expanding consideration given to changes in the global climate and sustainable economic growth has reiterated the scientific interest in the connection between pollution and economic development, especially in the current period when energy independence is extremely important. This paper analyzes the long-term and the connection between air pollution emissions, primary energy resources, final energy consumption in industry and the economic value of the production of environmental goods and services over the period 2008–2023. The data sets used in this article are based on statistical research by the National Institute of Statistics, in compliance with the provisions imposed by Community legislation. From the total analysis of energy sources, a decrease can be observed from 48,166 thousand tons of oil equivalent in 2008 to 40,578 thousand tons of oil equivalent in 2023, which required a series of investments in alternative sources to compensate for this decrease. The production and supply of electricity and heat, gas, hot water and air conditioning generated approximately 42,772 thousand tons (Gg) CO2 in 2008 compared to 17,865.65 thousand tons (Gg) CO2 in 2023 and also during this period PM10 varied from 15,241.94 Tons (Mg) to 22,091.25 Tons (Mg). At the national level, the degree of energy independence for energy products as a whole was around 72.2%.

6

Impact of climate variability and soil physicochemical parameters on phytobiodiversity on four wetland sites in Taza province (Morocco)

Hazyoun Zineb, Lyazidi Aziza, Rouai Saber, Echchgadda Ghizlane, El Haouari Mohammed, Assem Najat

Ecological Engineering & Environmental Technology

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2025

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Vol. 26, iss. 10

356--370

EN

Understanding how ecological factors influence plant communities is essential for biodiversity conservation, especially in regions experiencing climatic and anthropogenic pressures. In this context, the present study explores the floristic diversity of four wetland sites in Taza province (Morocco): Oued M’Soun, Ras-El-Ma, Oued Elbared, and Lac Tameda. These sites, representative of the region’s ecological variability, offer a valuable opportunity to assess the relationship between environmental conditions and plant distribution. Floristic surveys were conducted in March 2024 using 10 m² plots, complemented by physico-chemical soil analyses (granulometry and pH), satellite-derived vegetation indices, notably the normalized difference vegetation index (NDVI), and statistical analyses including principal component analysis (PCA) and hierarchical classification. The NDVI was employed to assess vegetation vigor and spatial distribution patterns at each station, providing a quantitative complement to field observations. The results reveal significant differences among the stations in terms of precipitation, temperature, soil type, pH, and NDVI values, all of which shape the composition and health of local vegetation. A high level of plant diversity was observed, with dominant families including Asteraceae, Lamiaceae, and Rosaceae. Some species, such as Scolymus hispanicus and Carduus pycnocephalus, were present at all four sites, highlighting their ecological adaptability, whereas others, like Juniperus thurifera and Nerium oleander, were restricted to specific habitats. The PCA and classification analyses distinguished three floristically distinct groups of stations, structured according to environmental gradients, including vegetation vigor inferred from NDVI. These findings underscore the uniqueness of Taza’s flora within semi-arid Mediterranean ecosystems and emphasize the need for conservation strategies adapted to the pressures threatening these natural habitats.

7

Assessing biodiversity across bioclimatic zones in northeastern Algeria using pollen rain analysis

Boughediri Soumaia, Benslama Mohamed, Boughediri Khaoula, Boubehziz Sana

Ecological Engineering & Environmental Technology

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2025

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Vol. 26, iss. 7

126--138

EN

This study aims to explore the potential of pollen rain analysis as a method for assessing plant diversity across three bioclimatic zones in northeastern Algeria. The primary objective is to investigate how climate, vegetation structure, and biodiversity are interrelated, particularly how airborne pollen can be used to reveal the composition of plant communities and to evaluate the influence of climatic factors such as humidity and aridity, along with human activities. The research was carried out in three distinct bioclimatic regions of northeastern Algeria, each characterized by unique environmental conditions. The humid zone, located in the Edough Mountains near Annaba, features high rainfall and supports dense, diverse forest vegetation. The sub-humid zone, situated near Souk Ahras, represents a moderately moist forest environment with a mix of plant species. In contrast, the semi-arid zone, found south of Souk Ahras, is defined by low rainfall, higher temperatures, and sparse vegetation adapted to arid conditions. Pollen samples were collected from six strategically selected sites using pollen traps. After collection, the samples were examined under a microscope for identification and counting of pollen grains, allowing for the assessment of plant taxa diversity and relative abundance. Principal component analysis (PCA) was then used to identify patterns and relationships among pollen taxa, vegetation types, and environmental variables, with particular attention to indicator species that reflect specific climatic conditions and anthropogenic influence. The analysis revealed notable differences in pollen composition across the three bioclimatic zones, each exhibiting a distinct vegetation profile. Dominant tree and understory species varied between the regions. The PCA results demonstrated strong correlations between pollen assemblages, climatic gradients, and human impacts on vegetation distribution and structure. These findings underscore the reliability of pollen rain analysis as a valuable tool for monitoring plant biodiversity. By integrating climatic and environmental factors, the study highlights the effectiveness of airborne pollen analysis in enhancing our understanding of plant distribution, ecosystem dynamics, and the impacts of environmental change on biodiversity.

8

Analiza porównawcza wydajności architektury głębokiego uczenia się w klasyfikacji obrazów podwodnych

Mehrunnisa, Juszka Dawid, Zhang Yi, Leszczuk Mikołaj

Przegląd Telekomunikacyjny + Wiadomości Telekomunikacyjne

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2024

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nr 4

187--190

PL

W tym badaniu oceniamy wydajność modeli VGG-16, EfficientNetB0 i SimCLR w klasyfikacji 5000 podwodnych zdjęć. Zbiór danych podzielono na 75 procent do celów szkoleniowych i 25 procent do testów, przy czym ręczne etykietowanie zapewniało dokładne odwzorowanie podstaw. Zastosowaliśmy grupowanie K-średnich do segmentacji zbioru danych na podstawie podobieństwa oraz PCA w celu zmniejszenia wymiarowości przy jednoczesnym zachowaniu struktury semantycznej. Zróżnicowany zbiór danych zwiększa zdolność modeli do uogólniania w różnych warunkach. Oceniliśmy grupowanie i klasyfikacje za pomocą wyniku sylwetki, wskaźnika Daviesa-Bouldina i wskaźnika Calinskiego-Harabasza. Wyniki ujawniają mocne i słabe strony każdego modelu, dostarczając informacji na temat przyszłych ulepszeń w analizie obrazów podwodnych.

EN

In this study, we assess the performance of the VGG-16, EfficientNetB0, and SimCLR models in classifying 5,000 underwater images. The dataset was split into 75 perceent for training and 25 percent for testing, with manual labeling ensuring accurate ground truth. We used K-means clustering to segment the dataset based on similarity, and PCA to reduce dimensionality while maintaining the semantic structure. The diverse dataset boosts the models’ ability to generalize across various conditions. We evaluated clustering and classification using the silhouette score, Davies-Bouldin index, and Calinski-Harabasz index. The results reveal each model’s strengths and weaknesses, providing insights for future improvments in underwater image analysis.

9

Digital Transformation in the Context of Sustainable Development of European Countries

Kolupaieva Irina, Sheiko Iryna, Polozova Tetiana

Problemy Ekorozwoju

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2024

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Vol. 19, no. 1

89--103

EN

The country’s sustainable development is focused on improving the quality of life at the global level, ensuring equal access to education and public goods, and caring for the environment and biodiversity, as well as responsible consumption and production. Digital technologies are among the main drivers of sustainable development. It is very important to develop government strategy and choose correct measures aimed at ensuring sustainable development of the countries in terms of the digitalization processes. The purpose of the research is to investigate the nature of the correlation between indicators of digital development and sustainable development of the European countries, as well as to identify policy directions and measures regarding their digital and sustainable progress. Methods of the research are principal component analysis, geometric aggregation, and cluster analysis. The positive correlation within the digital and sustainable development is observed. Most indicators of digital and sustainable development positively correlate with each other. Based on PCA, it was found that indicators of sustainable development have a stronger intercorrelation than those of digital development. Based on the construction of integral indicators of digital and sustainable development, a cluster analysis was conducted. The main digital tools that contribute to the achievement of each of the 17 goals of sustainable development were determined. The results of the analysis provide a suitable basis for comparing the digital and sustainable development of individual countries and offer opportunities to identify tools and strategy directions for policymakers.

PL

Zrównoważony rozwój koncentruje się na poprawie jakości życia na poziomie globalnym, zapewnieniu równego dostępu do edukacji i dóbr publicznych oraz dbałości o środowisko i różnorodność biologiczną, a także odpowiedzialną konsumpcję i produkcję. Technologie cyfrowe należą do głównych czynników zrównoważonego rozwoju. Bardzo ważne jest opracowanie strategii rządu i wybór właściwych działań mających na celu zapewnienie zrównoważonego rozwoju krajów w zakresie procesów cyfryzacji. Celem artykułu jest zbadanie charakteru korelacji pomiędzy wskaźnikami rozwoju cyfrowego i zrównoważonego rozwoju krajów w Europie, a także identyfikacja kierunków i mierników polityki w zakresie ich postępu cyfrowego i zrównoważonego. Metody badawcze to analiza głównych składowych, agregacja geometryczna i analiza skupień. Obserwuje się pozytywną korelację w zakresie rozwoju cyfrowego i zrównoważonego. Większość wskaźników rozwoju cyfrowego i zrównoważonego jest ze sobą pozytywnie skorelowana. Na podstawie PCA stwierdzono, że wskaźniki rozwoju zrównoważonego wykazują silniejszą korelację niż wskaźniki rozwoju cyfrowego. W oparciu o konstrukcję integralnych wskaźników rozwoju cyfrowego i zrównoważonego przeprowadzono analizę skupień. Określono główne narzędzia cyfrowe, które przyczyniają się do osiągnięcia każdego z 17 Celów zrównoważonego rozwoju. Wyniki analizy stanowią odpowiednią podstawę do porównania rozwoju cyfrowego i zrównoważonego poszczególnych krajów oraz dają możliwości identyfikacji narzędzi i kierunków strategii dla decydentów.

10

Zastosowanie metod statystycznych do określenia związków pomiędzy minerałami a pierwiastkami jako wprowadzenie do analizy chemostratygraficznej

Przelaskowska Anna, Zagórska Urszula

Nafta-Gaz

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2024

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R. 80, nr 4

191--201

PL

Chemostratygrafia to technika korelacji oparta na danych geochemii nieorganicznej. Polega na dobraniu odpowiednich wskaźników korelacyjnych (pierwiastków / stosunków pierwiastków) pozwalających na wyodrębnienie charakterystycznych poziomów chemostratygraficznych w profilu otworu. Dla prawidłowego doboru wskaźników chemostratygraficznych niezbędne jest ustalenie związków między minerałami a pierwiastkami, ponieważ wiele pierwiastków może wchodzić w skład różnych minerałów. Celem pracy było zastosowanie analizy statystycznej do scharakteryzowania związków między minerałami a pierwiastkami dla próbek piaskowców czerwonego spągowca. W pracy wykorzystano takie metody jak: analiza korelacyjna oparta na interpretacji macierzy korelacji (CC) i wykresach korelacyjnych oraz analiza głównych składowych (PCA). PCA służy do redukcji liczby zmiennych opisujących zjawiska oraz do odkrycia prawidłowości między zmiennymi. Uzyskane wyniki pozwoliły na wyróżnienie kilku grup pierwiastków wzajemnie ze sobą powiązanych, kumulujących się w podobnych minerałach. Wyodrębniono szereg grup związanych z różnymi minerałami, między innymi z minerałami ciężkimi, minerałami ilastymi i dodatkami z płuczki. Pierwiastki ziem rzadkich (REE) rozdzieliły się na dwie grupy: lekkie ziemie rzadkie (LREE) i ciężkie ziemie rzadkie (HREE), co świadczy o tym, że mogą być związane z nieco innymi asocjacjami minerałów ciężkich. Analiza korelacyjna potwierdziła wnioski uzyskane na podstawie analizy PCA, jak również pozwoliła na uszczegółowienie niektórych zależności. Podsumowując, w ramach pracy scharakteryzowano związki pomiędzy pierwiastkami a minerałami w profilu otworu Pł 3. Zaprezentowano właściwy sposób analizy danych geochemicznych, który jest podstawą budowania podziału chemostratygraficznego.

EN

Chemostratigraphy is a correlation technique based on inorganic geochemistry data. It involves the selection of appropriate correlation indices (elements/element ratios) that allow to determine characteristic chemozones in the borehole profile. Determination of element-mineral links is necessary for the correct selection of chemostratigraphic indices, as many elements can be part of different minerals. The purpose of this study was to apply statistical analysis to characterize the relationships between minerals and elements for Rotliegend sandstone samples. The following methods were used in the study: correlation analysis based on interpretation of correlation matrix (CC), correlation plots and principal component analysis (PCA). Principal component analysis (PCA) is used to reduce the number of variables describing phenomena and to discover regularities between them. The results made it possible to distinguish several groups of elements related to each other, accumulating in similar minerals. A number of groups associated with various minerals were distinguished, including, among others, heavy minerals, clay minerals and mud additives. Rare earth elements (REEs) separated into two groups: light rare earths (LREE) and heavy rare earths (HREE), indicating that they may be associated with slightly different heavy mineral associations. The correlation analysis confirmed the conclusions obtained from the PCA analysis and allowed for a more detailed analysis of some relationships. In conclusion, the paper characterizes the relationships between elements and minerals in the profile of the Pł 3 borehole. The correct method of analysing geochemical data, which is the basis for building a chemostratigraphic division, was presented.

11

Assessment of heavy metal pollution in groundwater using a multivariate analysis approach

Sbai Khalid, Tahri Latifa, Hafiane Fatima Zahra, Halima Oumaima Iben, Fekhaoui Mohammed

Journal of Water and Land Development

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2024

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no. 61

175--182

EN

The current study aims to assess underground water pollution using an integrated approach that combines statistical methods such as principal component analysis (PCA) and water quality diagrams (Piper diagram, Schoeller-Berkalov diagram). A total of twenty water samples were collected from the Tiflet region in the Sebou basin and analysed for various physicochemical parameters, including temperature, pH, and heavy metal concentrations (Cu2+, Zn2+, Fe2+ and Pb2+). The average concentrations of Pb2+, Zn2+, Cu2+, and Fe2+ in the water samples were found to be 41.9, 14.8, 20.1, and 8.1 mg∙dm-3, respectively. These concentrations indicate a significant presence of heavy metals in the groundwater samples. Therefore, it can be concluded that the groundwater in this area is heavily polluted with heavy metals and other pollutants. This finding raises concerns regarding the use of this water for irrigation and agricultural activities in the region. This suggests that these four components play a crucial role in determining the overall water quality. The distribution patterns of the metals Pb2+, Zn2+, Cu2+, and Fe2+ in the well water within the study area are of particular environmental concern. It is recommended to establish a monitoring network to ensure the sustainable management of water resources in order to address this issue effectively.

12

Accumulation of Macronutrients and Trace Elements in Leaves and Stems of Reynoutria japonica and Reynoutria sachalinensis

Parzych Agnieszka Edyta, Sobisz Zbigniew

Journal of Ecological Engineering

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2024

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Vol. 25, nr 11

306--316

EN

Knotweeds, Reynoutria japonica (RJ) and R. sachalinensis (RS) are invasive species that strongly interfere with the soil environment and disrupt the biogeochemical cycles of many chemical elements. This paper analyses the content of C, N, P, K, Na, Mg, Ca, Al, Fe, Mn, Zn, Ni, Cu, Cd, Cr and Pb in the above-ground biomass of RJ and RS and in the soil (0–15 cm) in order to assess the accumulation properties of knotweed. Studies conducted in northern Poland showed statistically significant (p<0.05) differences in the content of Na in the soil of the studied knotweed. The elemental composition of the leaves and stems showed a good supply of macronutrients and increased concentrations of some trace elements. The leaves of RJ and RS were shown to be good bioaccumulators of N, K, Na, Mg, Ca, P, Mn, Zn, Ni, Cu and Cd, and the stems of N, K, Na, Ca, Ni, Cd, Cr and Pb. Based on the values of bioconcentration factors (BCF), the similarity between the studied knotweeds concerning Mn, Cu and Cr in the leaf/soil relation and Al, Fe, Cu, Cd, Cr and Pb in the stem/soil relation was demonstrated. The highest mobility from stems to leaves expressed by the translocation factor (TF) was exhibited by Mn and Mg, and the lowest by Cr. Despite the low content in the soil, RJ and RS leaves and stems accumulated significant amounts of trace elements, which indicates their phytoextractive properties.

13

Impact of agriculture on soil and water quality in the north-east of Algeria: Boumaiza Plain

Majour Habiba, Sedrati Nassima, Halimi Fahima, Attoui Badra

Geomatics, Landmanagement and Landscape

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2024

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no. 4

7--21

EN

The Boumaiza Plain is situated in the northeast of Algeria and encompasses a vast area of the ElKebir West watershed, which has a significant water potential. The intensification of agricultural activities in this region has led to a notable increase in the use of phytosanitary products, which may impact the physico-chemical quality of groundwater and soil. A sampling campaign was conducted in 2022 to assess the impact of agriculture. To achieve this aim, we analysed 12 points, comprising 7 wells and 5 boreholes, as well as the grain size and physicochemical characteristics of 12 soil samples. The methodology employed for processing the analysis results is based on multivariate statistical methods. The results of the analyses revealed pollution of agricultural origin. This is substantiated by the observation of relatively high levels of nutrients, including NO2, NO3, as well as potassium which exceed 5 mg/l in water and 40.76 mg/l for soil analyses. Principal component analysis (PCA) was also applied, while the opposition of physicochemical elements to nitrites, nitrites, chlorides, sulfates, ammonium, and potassium variables highlights another mechanism involved in water mineralization, which is governed by the inputs of surface water fromagricultural areas and the intrusion of rich in organic matter waste from domesticated animals.

PL

Równina Boumaiza znajduje się w północno-wschodniej Algierii i obejmuje rozległy obszar zlewni El-Kebir West, który ma znaczny potencjał wodny. Intensyfikacja działalności rolniczej w tym regionie doprowadziła do znacznego wzrostu stosowania produktów fitosanitarnych, co może mieć wpływ na jakość fizykochemiczną wód gruntowych i gleby. W 2022 r. przeprowadzono kampanię pobierania próbek w celu oceny wpływu rolnictwa. Aby osiągnąć ten cel, przeanalizowaliśmy 12 punktów, obejmujących 7 studni i 5 otworów wiertniczych, a także wielkość ziarna i właściwości fizykochemiczne 12 próbek gleby. Metodologia zastosowana do przetwarzania wyników analizy opiera się na wielowymiarowych metodach statystycznych. Wyniki analiz ujawniły zanieczyszczenie pochodzenia rolniczego. Potwierdza to obserwacja stosunkowo wysokich poziomów składników odżywczych, w tym NO 2 , NO 3 , a także potasu, które przekraczają 5 mg/l w wodzie i 40,76 mg/l w analizach gleby. Zastosowano również analizę głównych składowych (PCA), natomiast kontrast pierwiastków fizykochemicznych ze zmiennymi azotynami, azotynami, chlorkami, siarczanami, amoniakiem i potasem wskazuje na inny mechanizm zaangażowany w mineralizację wody, który jest regulowany przez dopływ wód powierzchniowych z obszarów rolniczych i wnikanie bogatych w materię organiczną odpadów pochodzących od zwierząt domowych.

14

The Classification of Land Quality Index Using Minimum Data Set – Study in a Tropical Agroecosystem of East Java

Mas’udi Fauzan, Mandala Marga, Indarto Indarto

Ecological Engineering & Environmental Technology

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2024

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Vol. 25, iss. 10

282--296

EN

This study aimed to identify the factors influencing land quality in a tropical agroecosystem of Jember Regency, East Java, Indonesia, using a minimum data set approach. A principal component analysis (PCA) approach was employed to derive a minimum data set from various land parameters, including soil texture, bulk density, soil depth, pH, CEC, SOC, available P, available K, drainage, slope, surface rock, irrigation infrastructure, erosion hazard, flood hazard, annual temperature, and climate type. Data from 105 sampling locations were analysed to calculate the land quality index (LQI). The study found that six parameters significantly represent land quality: SOC (30.4%), effective soil depth (19.8%), available P (17.0%), available K (13.0%), erosion hazard (10.7%), and pH (8.9%). Long-term use of organic fertiliser can enhance land quality and prevent degradation. The study was limited to the Jember Regency and may not apply directly to other regions without adaptation. The findings can guide sustainable agricultural practices and land management in tropical regions, particularly in areas facing similar climatic and soil conditions. This study provides a quantitative assessment of land quality using a minimum data set in a tropical agroecosystem, filling a gap in the literature and offering a model for other regions to adopt.

15

Study of the Physico-Chemical Parameters of Surface Water Resources in the Oued Ansegmir Watershed Area (Morocco)

Rahoui Hassan, Kessou Hind Ait, Bejjaji Zohra, Chakiri Said

Ecological Engineering & Environmental Technology

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2024

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Vol. 25, iss. 11

179--189

EN

This study aims to analyze the physico-chemical parameters of 11 water samples to establish a qualitative description of water resources and assess their suitability for agricultural irrigation in the Oued Ansegmir (OAW) catchment area (1060 km2). The study involved the collection and analysis of water samples, focusing on cations and anions. Hydrogeochemical classification diagrams, including trilinear Piper and Scholler-Berkaloff diagrams, were modeled using Diagrammes software. A multivariate statistical method, principal component analysis (PCA), was employed to evaluate the physico-chemical parameters. The water quality index (WQI) was calculated for all samples to provide a comprehensive assessment of water quality. The Schöeller Berkaloff diagram indicated the presence of a sodium chloride facies (S1, S4) and a calcium bicarbonate facies for the remaining samples. The Piper diagram revealed a potassium sulphate-chloride facies and a calcium and magnesium bicarbonate facies. PCA identified two main factors: salinity and ion concentration (PC1), and the distinction between geochemical influences and potential human impacts (PC2). The WQI results showed that 36.4% of the water samples were of good quality, while 63.6% were of poor quality. To the best of our knowledge, this is the first study that examined water quality of OAW for agricultural purposes. Our results clearly indicate the suitability of OAW water resources for agricultural irrigation, while providing essential and relevant information for agricultural practices along Oued Ansegmir.

16

Relationships Among Global Climate Indices, Rainfall Patterns, and Crop Productivity in the Southern Part of Java, Indonesia

Nugroho Bayu Dwi Apri, Arif Chusnul, Suryandika Fadila, Annisa Hertiyana Nur, Wijayanti Syintianuri Intan

Ecological Engineering & Environmental Technology

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2024

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Vol. 25, iss. 10

87--95

EN

In tropical countries, especially Indonesia, even though there is a notable correlation between rainfall pattern and indices of global climate, limited proof exists regarding the impact on crop productivity. Global climate indices are one of the indicators to identify the occurrence of climate change, but there is little research on climate change in Indonesia. In this research, the relationships among indices of global climate are represented by the southern oscillation index (SOI) and the sea surface temperature (SST) such as Nino. West, the Indian Ocean Basin-Wide (IOBW), and Nino 3, then the pattern of rainfall distribution and crop productivity during 10 years from 2012 to 2022 in the southern part of Java. The southern part of Java which is represented by Gunung Kidul District is a rain-fed area, and its location is in hilly topography so rainfall will be an important factor in this area, not only for daily life but also for agricultural sector purposes. The purpose of the study was to discover the relationship between global climate indices, rainfall distribution pattern and crop productivity in the Southern Part of Java, Indonesia. Rainfall distribution pattern for 10 years was calculated and displayed with spatial method, then principal component analysis (PCA) was used to analyse SST, and correlation analyses were used, along with wet and dry seasons as well as crop productivity. The results showed that from 2012 to 2022, high rainfall and correlation with global climate indices occurred in the southern and western part of Gunung Kidul district, and correlation among rainfall patterns and crop productivity showed significant correlations in some sub-districts. This result also showed that the relationships among global climate indices and rainfall distribution pattern can be influenced the agricultural productivity in the rainfed areas.

17

Physicochemical properties of water in the Nida valley, Poland

Phan Cong Ngoc, Strużyński Andrzej, Kowalik Tomasz

Archives of Environmental Protection

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2024

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Vol. 50, no. 2

42--54

EN

The investigation of Nida Valley water aimed to assess fluctuations in physicochemical properties. In this study, environmental monitoring method was utilized to evaluate the changes in physicochemical properties of water. Over a 24-month period, from June 2021 to May 2023, a total of 228 water samples were collected from 10 sampling sites, with a monthly sampling frequency. Statistical analyses were utilized including the Shapiro–Wilk test (α = 0.05), Kruskal–Wallis test and Wilcoxon (Mann–Whitney) rank sum test (α = 0.05), Pearson correlation analysis (α = 0.001) and principal component analysis (PCA). Statistical analyses revealed significant differences between months in GW samples for for temperature, dissolved oxygen, pH, total nitrogen, total phosphorus, chloride, manganese, and zinc in GW samples and for T and DO in SW samples. Pearson correlation coefficient analysis (α = 0.001) identified strong positive correlations within the SW dataset. Similarly, significant positive correlations were observed among the GW dataset. Noteworthy positive correlations were also detected between the GW and SW datasets. Principal component analysis (PCA) revealed a substantial dissimilarity between GW2 samples compared to others, characterized by elevated manganese, iron, and Sulfate content. Two distinct groups emerged: Group 1 included samples at GW1, GW2, GW3, GW5, and SW2, while Group 2 comprised all other samples. This study demonstrated the stability in the physicochemical properties of SW and underscore a discernible correlation between the hydrochemical compositions of both SW and GW in the riparian area. Outstanding characteristics in hydrochemical component of sample waters have been indicated.

18

A multivariate approach to pebble morphometry : a case study of Witów section (southern Poland)

Mol Szymon, Ninard Krzysztof, Kuźma Agata, Deryk Anastasila, Łapcik Piotr

Annales Societatis Geologorum Poloniae

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2024

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Vol. 94, No. 3

273--286

EN

Gravel-dominated Neogene – Early Pleistocene braided river deposits of the Witów Series occur in the Carpathian Foredeep, about 20 km north of the front of the Polish Outer Carpathians, between the Szreniawa and Vistula rivers. For the first time, these deposits were subjected to numerical analyses, based on the morphometry and mass of almost 1,500 pebbles sampled at 10 cm intervals along the 4.4-m-high section in the Witów Quarry. In contrast to the traditional approach to pebble morphometry, multivariate statistics was utilised. This enables the examination of various aspects of the dataset holistically and simultaneously. A multivariate method, called principal component analysis (PCA), is widely used in the life sciences, but the employment of PCA for pebble morphometry has not yet been described. Here, PCA was applied to reveal the interrelations between pebble size, mass, lithological composition and stratigraphic height. Most notably, some differences in the distribution of morphometric features between different pebble lithotypes are displayed. Even though the morphometric features and petrological composition of pebbles remain similar in the section as a whole, overall upward-decreasing trends of stream-bed velocity proxies were recognized with the aid of PCA results and were validated, using standard bivariate correlation methods. This approach to the multivariate analysis of large quantitative and qualitative datasets should be considered as a possible part of the integrated sedimentological research of coarsegrained deposits. The consistency between results among the multiple indicators studied reduces the uncertainty of the sedimentological interpretations, presented in this work.

19

Registration, modal decomposition and analysis of human left ventricles

Stankiewicz Witold

Vibrations in Physical Systems

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2023

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Vol. 34, nr 2

art. no. 2023224

EN

Cardiovascular diseases, especially myocardial infarction and heart failure, are among the most common causes of death. Proper, timely diagnosis can be a key factor in reducing the mortality of these diseases. In the present paper, statistical data analysis of left ventricle of human heart is presented. Raster DICOM images are processed, segmented and registered, in order to mark the left ventricle on medical images, and then to obtain its geometrical 3D models of constant topology. Registered, geometrical data, obtained for whole cardiac cycle of patients with healthy hearts, hypertrophy and heart failure, is then decomposed using Principal Component Analysis. The obtained modes represent the movement of the ventricle during one heart cycle. The proposed approach allows neglecting unimportant, noisy signal and enables the interpretation of the heart cycle. It is shown that modal decomposition might be used to distinguish the hearts with heart failure and the group containing healthy hearts and the ones with hypertrophy. Being a non-invasive method, this approach enables the diagnosis of various hearts, including prenatal ones.

20

Odtwarzanie położenia wału dla prędkości zerowej w napędzie z PMSM z użyciem analizy głównych składowych

Urbański Konrad, Janiszewski Dariusz

Przegląd Elektrotechniczny

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2023

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R. 99, nr 5

237--242

PL

W pracy przedstawiono sposób odtwarzania położenia wału silnika synchronicznego z magnesami trwałymi z wykorzystaniem dodatkowego prądu wysokiej częstotliwości. Uzyskany hodograf tego prądu przetwarzany jest z użyciem analizy głównych składowych. Rezultatem przetwarzania jest informacja o poziomie dopasowania do poszczególnych wzorców. Wzorzec o najlepszym dopasowaniu określa odtworzone położenie wału maszyny. Badania zostały przeprowadzone z użyciem danych pomiarowych laboratoryjnego układu napędowego z PMSM.

EN

This paper presents a method of estimating the shaft position of a permanent magnet synchronous motor using an additional high-frequency current. The resulting hodograph of this current is processed using principal component analysis. The result of the processing is information about the level of fit to individual patterns. The pattern with the best match determines the estimated shaft position. The research was carried out using measurement data of a laboratory drive with a PMSM.