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This study introduces a Sagnac Interferometer (SI) fiber sensor that integrates Polarization-Maintaining Fibers (PMFs) with a Tilted Fiber Bragg Grating (TFBG) for the dual-parameter measurement of strain and lateral pressure. By incorporating a 6° TFBG with PMFs into the SI sensor, its sensitivity is significantly enhanced, enabling advanced multi-parameter sensing capabilities. The sensor demonstrates a temperature sensitivity of −1.413 nm/°C and a lateral pressure sensitivity of −4.264 dB/kPa, as validated by repeated experiments. The results exhibit excellent repeatability and high precision, underscoring the sensor's potential for robust and accurate multi-parameter sensing applications. [ABSTRACT FROM AUTHOR]

Drawing on prior reports highlighting the redox mediator properties of powdered activated carbon (PAC), this study was designed to evaluate these properties to enhance the decolorization of azo dye by Klebsiella quasipneumoniae GT7. It was found that the presence of 0.5 % PAC in the medium increased the biodecolorization rate early in incubation. Chemical analysis revealed that dye conversion into aromatic amines occurred in microbial systems both with and without PAC. However, at initial dye concentrations (C id) of 2 mM or higher, some dye remained on the PAC surface and in the medium. In contrast, the PAC-free system achieved nearly 100 % biodecolorization at all initial dye concentrations. The negative impact of PAC on decolorization efficiency in microbial systems with high initial dye concentrations cannot be solely explained by its redox mediator function. This study used the amphoteric-Donnan model for PAC's electrical double layer (EDL) and Mitchell's chemiosmotic model for bacterial proton motive force (PMF) to explore this. It found that charge storage in PAC's EDL regulates electron transfer fluxes, and proton species enhance the proton motive force across the bacterial membrane. These observations improve the understanding of PAC's role in microbial decolorization and its potential future applications. [Display omitted] • Dye biodegradation occurs mainly on activated carbon's porous surface in the medium. • Activated carbon enhances biodecolorization at low initial dye concentrations. • At high initial dye levels, activated carbon reduces final biodecolorization yield. • Charge storage in carbon's electrical double layer controls electron transfer flux. • Proton storage on carbon boosts proton motive force across the bacterial membrane. [ABSTRACT FROM AUTHOR]

To evaluate the pollution sources and dynamics of the upper reaches of the Tarim River, 10 typical sampling points were selected, and 23 water quality parameters from 2020 to 2022 were analyzed using one-way analysis of variance, the comprehensive Water Quality Identification Index (WQI), and Principal Component Analysis (PCA). The pollution status, sources, and contribution rates of water quality were investigated using the Absolute Principal Component-Multiple Linear Regression Model (APCS-MLR) and Positive Matrix Factorization (PMF). The results indicated that the water quality parameters of dissolved oxygen (DO), chemical oxygen demand (CODMn), biochemical oxygen demand after 5 days (BOD5), total nitrogen (TN), total phosphorus (TP), fluoride ions (F−), and ammonia-nitrogen (NH3-N) in the upper reaches of the Tarim River exceed standards, with noticeable spatial variations observed for each parameter. The water quality evaluation grades in the upper reaches of Tarim River primarily indicate "moderate" and "good" levels, with DO, TN, NH3-N, and electrical conductivity (EC) being the key parameters influencing variations in water quality. The source analysis results from APCS-MLR and PMF yielded similar outcomes, identifying six potential pollution sources. Among these, soil weathering, livestock and poultry breeding, and agricultural activities exhibited higher contribution rates. Specifically, the contribution rates for these sources according to APCS-MLR were 44.11%, 19.63%, and 11.67%, respectively; while according to PMF they are 24.08%, 17.88%, and 27.54%, respectively. Furthermore, industrial pollution sources contributed at a rate of 6.01% according to APCS-MLR, while urban living sources contributed at a rate of 2.13%. However, based on PMF analysis, the contribution rates for industrial pollution sources increased significantly to 16.71%. Additionally, APCS-MLR identified natural sources as contributing at a rate of 16.45%, whereas PMF suggested that a combination of agricultural activities and natural sources contributed at a lower rate of only 9.52%. In conclusion, the water quality within the upper reaches of the Tarim River is predominantly satisfactory. Nonetheless, localized pollution, primarily attributable to human activities, presents a substantial challenge. These observations provide critical insights into improving and protecting the fragile water quality of the Tarim River. [ABSTRACT FROM AUTHOR]

Understanding the health risks of polycyclic aromatic hydrocarbons (PAHs) in dust from city parks and prioritizing sources for control are essential for public health and pollution management. The combination of Source-specific and Monte Carlo not only reduces management costs, but also improves the accuracy of assessments. To evaluate the sources of PAHs in urban park dust and the possible health risks caused by different sources, dust samples from 13 popular parks in Kaifeng City were analyzed for PAHs using gas chromatograph-mass spectrometer (GC-MS). The results showed that the surface dust PAH content in the study area ranged from 332.34 µg·kg−1 to 7823.03 µg·kg−1, with a mean value of 1756.59 µg·kg−1. Nemerow Composite Pollution Index in the study area ranged from 0.32 to 14.41, with a mean of 2.24, indicating that the overall pollution warrants attention. Four pollution sources were identified using the positive matrix factorization (PMF) model: transportation source, transportation-coal and biomass combustion source, coke oven emission source, and petroleum source, with contributions of 33.74%, 25.59%, 22.14%, and 18.54%, respectively. The Monte Carlo cancer risk simulation results indicated that park dust PAHs pose a potential cancer risk to all three populations (children, adult male and adult female). Additionally, the cancer risk for children was generally higher than that for adult males and females, with transportation sources being the main contributor to the carcinogenic risk. Lastly, sensitivity analyses results showed that the toxic equivalent concentration (CS) is the parameter contributing the most to carcinogenic risk, followed by Exposure duration (ED). [ABSTRACT FROM AUTHOR]

To establish and implement effective policies for controlling fine particle matters (PM2.5), which is associated with high-risk diseases, continuous research on identifying PM2.5 sources was conducted. This study utilized the positive matrix factorization (PMF) receptor model to estimate the sources and characteristics of PM2.5 between Baengnyeong Island (BNI) and the Seoul Metropolitan Area (SMA). We conducted PMF modeling and backward trajectory analysis using the data on PM2.5 and its components collected from 2020 to 2021 at the Air quality Research Centers (ARC). The PMF modeling identified nine pollution sources in both BNI and the SMA, including secondary sulfate, secondary nitrate, vehicles, biomass burning, dust, industry, sea salt particles, coal combustion, and oil combustion. Secondary particulate matter, vehicles, and biomass burning were found to be major contributors to PM2.5 concentrations in both regions. A backward trajectory analysis indicated that air masses, passing through BNI to the SMA, showed higher concentrations and contributions of ammonium nitrate, vehicles, and biomass burning in the SMA site compared to BNI site. These findings suggest that controlling nitrogen oxides (NOx) and ammonia emissions in the SMA, as well as monitoring the intermediate products that form aerosols, such as HNO3, are needed. [ABSTRACT FROM AUTHOR]

Outdoor PM2.5 samples were collected for 34 months in Pretoria, South Africa from 18 April 2017 to 28 February 2020. The average total PM2.5 concentration was 23.2 ± 17.3 µg.m3 (0.69–139 µg.m−3), with the highest mean recorded during winter and the lowest during summer (p < 0.05). The sources were determined by means of cross referencing the US EPA PMF 5.0 program and the NOAA HYsplit model. The sources of the total PM2.5 were mining (33%), resuspended dust (24%), industry (15%), general exhaust (12%), vehicular emissions (12%) and biomass burning (4%). Sources of air pollutants are both ubiquitous and seasonal. Highlights: In central Pretoria, the largest contributing sources of PM2.5 are resuspended dust matrix and mining from surrounding areas; A winter analysis was run where As, Se and Pb was included in the dataset, confirming biomass burning sources which were typically higher during the winter season; and Air quality management policies should address both ubiquitous and seasonal sources. [ABSTRACT FROM AUTHOR]

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Diagnosis of myeloid neoplasm is currently performed according to the presence of a predetermined set of clinical, morphological, and molecular diagnostic criteria agreed upon by a consensus of experts. Even strictly adhering to these criteria, it is possible to encounter patients who present features that are not easily ascribable to a single disease category. This is the case, e.g., of patients with de novo myeloid neoplasms with features intermediate between primary myelofibrosis (PMF) and chronic myelomonocytic leukemia (CMML). In this study, we retrospectively searched the pathological database of IRCCS Humanitas Research Hospital to identify cases of chronic myeloid neoplasm with monocytosis with a driver mutation of classic myeloproliferative neoplasms (MPN) and showing morphological MPN features. For each case, we assessed all epidemiological, clinical, histopathological, and molecular data. Then, we carried out a literature review, searching for cases with features similar to those of our patients. We retrieved a total of 13 cases presenting such criteria (9 from the literature review and 4 from our institution); in all of them, there was a coexistence of clinical, histopathological, and molecular myelodysplastic and myeloproliferative features. To date, according to current classifications (World Health Organization and International Consensus Classification), given the presence/absence of essential features for PMF or CMML, these patients should be formally diagnosed as myelodysplastic/myeloproliferative neoplasm unclassified/not otherwise specified (U/NOS). This review aims to summarize the features of these difficult cases and discuss their differential diagnosis and their classification according to the novel classifications and the existing literature on overlapping myeloid neoplasms. [ABSTRACT FROM AUTHOR]

This study assessed the presence of potentially toxic elements (PTEs) in China's northeastern black soil belt, an area with limited prior research. We collected 304 soil samples (0–20 cm) from Gonghe Town, Hailun City, and analyzed the PTE contamination degree using the single-factor pollution index and Nemerow pollution index. The results demonstrated that the mean concentrations of arsenic (As), cadmium (Cd), chromium (Cr), copper (Cu), mercury (Hg), nickel (Ni), lead (Pb), and zinc (Zn) were 11.16, 0.11, 65.29, 22.56, 0.03, 27.07, 26.09, and 66.01 mg/kg, respectively. Source apportionment was conducted via correlation analysis, principal component analysis, and positive matrix factorization, identifying four main sources: natural (33.2%), irrigation (29.5%), fuel (23.4%), and fertilizer (13.2%). The ecological risk index indicated a slight ecological risk, while the human health risk showed that non-carcinogenic risks were negligible and carcinogenic risks were acceptable. Our findings emphasize the need to prioritize controlling PTEs from fertilizer, particularly cadmium, and to a lesser extent, irrigation and fuel sources, focusing on As, Pband Hg. This research provides critical insights for policymakers aiming to manage PTE contamination in black soils. [ABSTRACT FROM AUTHOR]

Summary: Allogeneic stem cell transplantation (alloSCT) is the only curative treatment option for patients with high-risk myelofibrosis (MF). However, it is important to bear in mind that alloSCT in MF is associated with a nonrelapse mortality that should not be underestimated. Therefore, both exact disease risk categorization and thorough evaluation of the individual transplant-related risk are mandatory to identify those patients to whom alloSCT should be offered. This short review is intended to provide a concise overview on relevant aspects to be considered for patient selection, planning, and performing alloSCT. [ABSTRACT FROM AUTHOR]

Heavy metals (HMs) seriously harm soil environment and threaten crop quality and human health. The aim of the study was to investigate the characteristics, quantify the sources and assess the risks of HMs in soil of upper Bailang River Basin (UBRB). The results indicated that the soils in UBRB were at a non-polluted level and posed a low ecological risk to the environment as a whole. The main pollutants were Ni and Cr obtained by indices Pi and Igeo. Based on the consideration of toxicity, the fuzzy comprehensive evaluation model and Ei index revealed that Hg and Cd were dominating pollutants and ecological risk factors of soil in UBRB. The positive matrix factorization model ascertained five potential sources of soil HMs, namely, plastic processing, energy activities, parent material, transportation and agriculture mixed source and industrial manufacturing, with contribution rates of 17%, 7%, 15%, 29% and 32%, respectively. Natural source primarily determined the non-carcinogenic risk for all populations, accounting for about 43% of the total risk. Industrial manufacturing mainly determined the carcinogenic risk, accounting for about 45%. For adults, the risk was acceptable for most of the sample points. For children, potential non-carcinogenic risks were present in 13.19% of the sample sites, which were mainly located in the west, and unacceptable carcinogenic risks were present in 57.21% of the sample sites, which were mainly concentrated in the western and central parts. [ABSTRACT FROM AUTHOR]

Previous studies have investigated the major sources and health risks associated with atmospheric volatile organic compounds (VOCs). However, the spatial variability of the impact of their emission sources on health risks has rarely been studied. In this study, passive air sampling of VOCs was conducted at 24 sites in Ulsan, the largest industrial city in South Korea. Toluene exhibited the highest time-averaged concentration (6.37 µg/m3), followed by m,p,o-xylenes (4.69 µg/m3), ethyl acetate (3.26 µg/m3), and ethylbenzene (2.70 µg/m3). Higher concentrations of total (Σ59) VOCs and BTEX (benzene, toluene, ethylbenzene, and m,p,o-xylenes) were observed near industrial complexes. The mean cumulative (Σ11) cancer risk was 9.1E-6, with the highest contribution from benzene (4.7E-6), while the mean cumulative (Σ17) non-cancer risk was 2.6E-1, primarily driven by naphthalene (1.7E-1), suggesting the importance of carcinogenic VOCs. Five major sources were identified using the positive matrix factorization model, revealing the dominance of industrial activities. Both cancer and non-cancer risks were elevated in the petrochemical industrial complex, which is located close to densely populated areas. Consequently, prioritized management of VOC exposure to workers and residents is necessary for the petrochemical industrial complex and nearby residential areas. [ABSTRACT FROM AUTHOR]

Diagnosis of myeloid neoplasm is currently performed according to the presence of a predetermined set of clinical, morphological, and molecular diagnostic criteria agreed upon by a consensus of experts. Even strictly adhering to these criteria, it is possible to encounter patients who present features that are not easily ascribable to a single disease category. This is the case, e.g., of patients with de novo myeloid neoplasms with features intermediate between primary myelofibrosis (PMF) and chronic myelomonocytic leukemia (CMML). In this study, we retrospectively searched the pathological database of IRCCS Humanitas Research Hospital to identify cases of chronic myeloid neoplasm with monocytosis with a driver mutation of classic myeloproliferative neoplasms (MPN) and showing morphological MPN features. For each case, we assessed all epidemiological, clinical, histopathological, and molecular data. Then, we carried out a literature review, searching for cases with features similar to those of our patients. We retrieved a total of 13 cases presenting such criteria (9 from the literature review and 4 from our institution); in all of them, there was a coexistence of clinical, histopathological, and molecular myelodysplastic and myeloproliferative features. To date, according to current classifications (World Health Organization and International Consensus Classification), given the presence/absence of essential features for PMF or CMML, these patients should be formally diagnosed as myelodysplastic/myeloproliferative neoplasm unclassified/not otherwise specified (U/NOS). This review aims to summarize the features of these difficult cases and discuss their differential diagnosis and their classification according to the novel classifications and the existing literature on overlapping myeloid neoplasms.

Ambient particulate matter (PM10) and its chemical composition in polycyclic aromatic hydrocarbons (PAHs) were studied in areas of specific interest, between September 2015 and July 2016. The principal aim of this study was to assess the different PAH source profiles in each area, as well as their potential health risk. In particular, the studied areas were (a) the semiurban industrialized zone of the Municipality of Peloponnese (Meligalas, Messini) of Messinia prefecture, due to the intensive olive-productive activity in the extensive area, (b) the industrialized zone of Oinofyta in Voiotia prefecture, and (c) the urban/traffic center of Athens (Aristotelous). Intense spatial and seasonal variations in PAH levels were observed among the study areas collectively, but also for each one individually. During the winter period, the total PAHs average concentration was 11.45 and 9.84 ng/m3 at Meligalas–Skala (S1, S2 stations), 8.84 ng/m3 at Messini (S3 station), and 6.30 ng/m3 at the center of Athens (Aristotelous). During the summer campaign, the corresponding levels were 0.99, 1.20, and 0.70 ng/m3 (S1, S2, and S3 stations), and 5.84 ng/m3 (Aristotelous), respectively. The highest potential cancer risk of the PAHs mixture was estimated based on winter season measurements taken at the Municipality of Peloponnese. In order to determine PAH sources, two different source apportionment techniques were applied, i.e., diagnostic ratios (DRs) and the positive matrix factorization (PMF) model. [ABSTRACT FROM AUTHOR]

The continuous monitoring of PM2.5 (including 12 metal elements) was conducted in Jinan, a city with poor air quality in China, during the 13th Five-Year Plan (2016–2020). Positive matrix factorization (PMF) was used to identify emission sources of PM2.5-bound metals, and the health risks of the metals and their emission sources were assessed. During the study period, the concentration of most metals showed a decreasing trend (except Al and Be), and a significant seasonal difference was found: winter > fall > spring > summer. The PMF analysis showed that there were four main sources of PM2.5-bound metals, and their contributions to the total metals (TMs) were dust emissions (54.3%), coal combustion and industrial emissions (22.3%), vehicle emissions (19.3%), and domestic emissions (4.1%). The results of the health risk assessment indicated that the carcinogenic risk of metals (Cr and As) exceeded the acceptable level (1 × 10−6), which was of concern. Under the influence of emission reduction measures, the contribution of emission sources to health risks changes dynamically, and the emission sources that contribute more to health risks were coal combustion and industrial emissions, as well as vehicle emissions. In addition, our findings suggest that a series of emission reduction measures effectively reduced the health risk from emission sources of PM2.5-bound metals. [ABSTRACT FROM AUTHOR]

This source apportionment research was one of the first attempts to quantify the contributions of pollution sources to ambient particulate matter (PM2.5) in the urban area of Skopje. The sampling was conducted at two locations in the city of Skopje, with permanent, year-round coverage. The elemental composition of PM2.5 aerosols was analyzed with non-destructive energy dispersive X-ray fluorescence spectroscopy, water-soluble ions were analyzed photometrically, and black carbon was assessed with an optical transmissometer. Positive Matrix Factorization was used for data modelling, and the contribution of each source to total particulate mass (PM2.5) was calculated. Seven main pollution sources were identified for both sites including biomass burning, open fire burning, traffic, fuel/residual oil burning, industry, and soil/mineral dust. Biomass combustion continues to be the largest single source of ambient air pollution and, due to its particular temporal distribution, is most likely the primary cause of extreme wintertime pollution episodes. Despite being fully seasonal, biomass burning provides the greatest annual relative contribution, reaching 32% for the Novo Lisiche site and 33% for the Karposh site, and during the winter months, this source alone contributes beyond the annual PM2.5 limit levels. Traffic is the second most important source. The annual relative contribution of traffic to the total particle mass at the Novo Lisiche site was 23%, and at the Karposh site, it was 18%. Other notable sources include the combustion of fuel/residual oil, soil dust, and open fires burning. [ABSTRACT FROM AUTHOR]

Despite enhancements in pollution control measures in southwestern China, detailed assessments of PM2.5 dynamics following the implementation of the Clean Air Action remain limited. This study explores the PM2.5 concentrations and their chemical compositions during the winter haze period of 2017 across four major urban centers—Chengdu, Chongqing, Guiyang, and Kunming. Significant variability in mean PM2.5 concentrations was observed: Chengdu (71.8 μg m−3) and Chongqing (53.3 μg m−3) recorded the highest levels, substantially exceeding national air quality standards, while Guiyang and Kunming reported lower concentrations, suggestive of comparatively milder pollution. The analysis revealed that sulfate, nitrate, and ammonium (collectively referred to as SNA) constituted a substantial portion of the PM2.5 mass—47.2% in Chengdu, 62.2% in Chongqing, 59.9% in Guiyang, and 32.0% in Kunming—highlighting the critical role of secondary aerosol formation. The ratio of NO3−/SO42− and nitrogen oxidation ratio to sulfur oxidation ratio (NOR/SOR) indicate a significant transformation of NO2 under conditions of heavy pollution, with nitrate formation playing an increasingly central role in the haze dynamics, particularly in Chengdu and Chongqing. Utilizing PMF for source apportionment, in Chengdu, vehicle emissions were the predominant contributor, accounting for 33.1%. Chongqing showed a similar profile, with secondary aerosols constituting 36%, followed closely by vehicle emissions. In contrast, Guiyang's PM2.5 burden was heavily influenced by coal combustion, which contributed 46.3%, reflecting the city's strong industrial base. Kunming presented a more balanced source distribution. Back trajectory analysis further confirmed the regional transport of pollutants, illustrating the complex interplay between local and distant sources. These insights underscore the need for tailored, region-specific air quality management strategies in southwestern China, thereby enhancing our understanding of the multifaceted sources and dynamics of PM2.5 pollution amidst ongoing urban and industrial development. [ABSTRACT FROM AUTHOR]

With the rapid development of industrialization and urbanization, the issue of soil environmental pollution is becoming more and more prominent, especially concerning heavy metal contamination, which has garnered significant scholarly attention. The surface watershed formed by waterline is influenced by various factors such as topography, industrial emissions, and agricultural runoff, resulting in a complex process of migration and accumulation of heavy metal elements from multiple sources. In this study, the pollution characteristics and sources of heavy metal elements Hg, As, Pb, Ni, Cd, Cr, Cu and Zn in 165 surface soil samples from the Manghe River watershed in Jiyuan City were comprehensively analyzed using a variety of methods, including statistics, geostatistics, enriched factor analysis and the Positive Matrix Factorization Model (PMF). The results showed that the concentrations of Hg, Cd, As, Cu, Pb and Zn exceeded their corresponding background values with varying degrees of enrichment. Notably, the average contents of Cd, Hg and Pb were 26.70 times, 3.69 times and 4.49 times higher than those in Chinese soils on average, respectively, showing obvious enrichment characteristics. Moreover, there were distinct spatial distribution patterns for each heavy metal element; Ni and Cr exhibited similar trends mainly controlled by the parent material, while human activities significantly affect the other six elements forming high-value areas around mining and related industries. It is noteworthy that Cu, Hg and Zn were influenced by dominant wind direction in autumn and winter, forming sub-high-value zones in southern forested areas; meanwhile, Cu and Zn were also influenced by agricultural fertilizer application as well as surface runoff, leading to secondary high-value areas in the dryland areas. Further analysis revealed a significant positive correlation among these heavy metal elements, suggesting that they may share common sources. Through the PMF Model, four main factors were identified, with factor 2 (36.25%), factor 1 (23.00%), factor 3 (21.20%) and factor 4 (19.55%) ranked in descending order of contribution rate. The heavy metal pollution in the study area was attributed to anthropogenic activities and natural factors, accounting for 63.75% and 36.25%, respectively. Coal mining, chemical industry smelting, vehicle emissions and excessive use of agrochemicals were identified as the main sources of heavy metal pollution. These pollutants entered the soil through direct emissions, atmospheric deposition, transportation and agricultural activities, exerting a significant impact on the soil environment. Therefore, delving into the spatial distribution pattern of soil heavy metal pollution and precise analysis of its sources are of great importance for effective treatment and remediation of soil heavy metal pollution in small watersheds, maintaining healthy soil ecology and safeguarding human health. [ABSTRACT FROM AUTHOR]

This work presents the first comprehensive assessment of PM pollution sources in Dushanbe, Tajikistan. A total of 138 PM2.5 samples were collected during 2015–2016 and 2018–2019 and were analyzed through gravimetric, ED-XRF, and multi-wavelength absorption techniques. The results show that PM2.5 concentrations were substantially higher than the European annual limit value and WHO Air Quality Guidelines annual average value, with an average of 90.9 ± 68.5 μg m−3. The PMF application identified eight sources of pollution that influenced PM2.5 concentration levels in the area. Coal burning (21.3%) and biomass burning (22.3%) were the dominant sources during the winter, while vehicular traffic (7.7%) contributed more during the warm season. Power plant emissions (17.5%) showed enhanced contributions during the warm months, likely due to high energy demand. Cement industry emissions (6.9%) exhibited significant contribution during the cold period of 2018–2019, while soil dust (11.3%) and secondary sulphates (11.5%) displayed increased contribution during the warm and cold months, respectively. Finally, waste burning (1.5%) displayed the lowest contribution, with no significant temporal variation. Our results highlight the significant impact of anthropogenic activities, and especially the use of coal burning for energy production (both in power plants and for residential heating), and the significant contribution of biomass burning during both warm and cold seasons. [ABSTRACT FROM AUTHOR]

Between January 2017 and September 2018, ACT Health conducted a study on the predominant sources of airborne fine particulate matter pollution across the Canberra region. The goal was to gain better understanding of particulate composition, insight into local emission sources, and to establish a baseline of the existing pollution inventory (for future assessments of effects from changes in air quality policies). Fine particulate matter samples were collected on PTFE filters at two locations in Canberra, in the north (Belconnen) and south (Tuggeranong), respectively. The sample’s chemical composition was determined by the Australian Nuclear Science and Technology Organisation (ANSTO) in Sydney, using accelerator-based ion-beam analysis. Resulting data was then used in a receptor model to statistically identify the predominant sources and look at both spatial and seasonal variations thereof. The main particulate pollution sources in Canberra were found to be wood smoke, secondary sulfates, traffic, soil dust, and salt. Overall, wood smoke constitutes the largest air pollution factor exhibiting the strongest seasonal pattern, while both traffic and secondary aerosols are constantly present over time. These three factors account for almost 90% of Canberra’s pollution inventory. Out of the remaining sources, soil dust represents the larger portion especially during the warmer months, while a marginal amount of salt, mainly calcium chloride, was found to be present all year round. [ABSTRACT FROM AUTHOR]

Urban science plays a pivotal role in understanding the complex interactions between fireworks, air quality, and urban environments. Dense firework smoke worsens air quality and poses a health hazard to the public. In this study, we show a situation where extremely foggy meteorological conditions coincided with intense anthropogenic emissions, including fireworks, in an urban area. For the first time, the chemical composition and sources of non-refractory submicron aerosol (NR-PM1) in outdoor and indoor air were characterized in Vilnius (Lithuania) using an aerosol chemical speciation monitor (ACSM) and Positive Matrix Factorization for the period before the fireworks, on New Year's Eve, and after the fireworks in 2020/2021; thus, typical changes were assessed. Due to stagnant weather conditions and increased traffic, the highest concentrations of black carbon (BC) (13.8 μg/m3) were observed before the fireworks display. The contribution of organic (Org) fraction to the total NR-PM1 mass concentration, in the comparison of the values of a typical night and New Year's Eve (from 9 p.m. to 6 a.m.), increased from 43% to 70% and from 47% to 60% in outdoor and indoor air, respectively. Biomass-burning organic aerosol (BBOA, 48% (44%)) and hydrocarbon-like organic aerosol (HOA, 35% (21%)) dominated the organic fraction indoors and outdoors, respectively. HOA was likely linked to increased traffic during the event, while BBOA may have been related to domestic heating and fireworks. [ABSTRACT FROM AUTHOR]

This paper presents results from a comprehensive study of source apportionment of particulate matter (PM) of size PM2.5 and PM10 near a busy highway in Sharjah, United Arab Emirates. Source apportionment was carried out using US Environmental Protection Agency (EPA) Positive Matrix Factorization model. Furthermore, backward trajectory analysis and Potential Source Contribution Function were used to assess air mass transport pathways and identify potential source regions, respectively. The results revealed six major sources for PM2.5, including traffic, sea salt, fugitive dust, secondary aerosols, heavy oil combustion and mineral dust. For PM10, four major sources were identified, including secondary aerosols, traffic, sea salt and mineral dust. Traffic emissions were found to be significant contributors to both PM2.5 and PM10 pollution, along with natural sources like sea salt and mineral dust. Backward trajectory analysis indicated the influence of different wind regimes on air mass transport, with contributions from regions like Arabian Gulf, Arabian Sea, Oman and Iran. The Conditional Bivariate Probability Function analysis further explained the impact of local traffic emissions and other sources on PM pollution under varying wind conditions.

Apportioning pollution sources under compound pollution conditions is challenging in river pollution source analysis. The positive matrix factorization (PMF) model is widely used to analyze river pollution sources. However, the identification of pollutants in this model relies primarily on the subjective experience of the researchers, leading to ineffective identification of different contaminants from similar sources. In this study, we propose a comprehensive deviation index (CDI) to quantitatively identify pollution source types based on the PMF and observed source profiles. Taking the subtropical Xizhijiang River Basin as a case study, we quantitatively identified the pollution sources and their contributions to dissolved organic carbon (DOC), total nitrogen (TN), and total phosphorus (TP) using observed water quality and pollution sources data. The results showed that the eight major pollutants in the study region exhibited significant positive correlations, indicating the similarity of pollutant sources in the watershed. The PMF model identified three primary pollution sources with coefficients of determination for observed versus predicted concentrations ranging from 0.60 to 0.98. The CDI unveiled that the watershed's three pollution sources were farmland, rural, and wastewater treatment plants (WTPs). Farmland emerges as the predominant contributor to DOC (68.04 %), TC (63.29 %), and TDP (44.51 %). Rural notably contributes to NH3-N, PO43−, TDP, and TN, with percentages of 86.37 %, 57.65 %, 41.40 %, and 30.45 %, respectively. WTPs significantly contribute to NO2−, NO3−, and TN, accounting for 71.81 %, 57.39 %, and 37.26 %, respectively. Incorporating source fingerprints into the PMF model, the CDI can accurately identify pollution sources, improve the interpretability of source identification, and mitigate uncertainty in the multiple-source unknown receptor model. These findings have immediate and practical implications for river ecosystem management and pollution control, providing a more effective method for identifying and addressing pollution sources.

Abstract Background Floods, especially flash floods, are the major transporting agent for fluvial sediments, whose pollution is a global concern. As floods result in the dispersion of and exposure to these sediments, a profound understanding of sedimentary dynamics during flood events and the related pollutant dispersion is of relevance. However, the characteristics of extreme flood events concerning pollutant dynamics are insufficiently known so far. Results In a Central European catchment impacted by intense industrial activities and former mining, over the course of five years, we surveyed six high-discharge events, five of them approx. bankfull discharge and one major flash flood event, supplemented by sampling of bank sediments. Fluvial sediments were analyzed for elemental composition by X-Ray fluorescence and for grain size distribution of the fine faction by laser diffraction. By applying a local enrichment factor, trace metal(loid) signatures in these sample sets were compared. Furthermore, Positive Matrix Factorization was used to investigate the trace metal(loid)s’ sources. The sediments deposited by minor flooding had continual trace metal(loid) signatures. However, for the extreme event, significant divergencies arose and persisted for the following years: The enrichment of anthropogenically influenced elements increased, with a slowly decreasing trend in the subsequent two years. Naturally dominated metal(oid)s decrease in enrichment without indicating a return to original levels. In contrast, other elements were insensitive to the extreme event. Positive Matrix Factorization identified anthropogenic influences in elements originating from copper and lead processing and mining activities. Furthermore, bed sediments and a natural background factor were found to dominate the non-anthropogenically influenced metal(loid)s. Conclusions In between extreme events, winnowing processes slowly alter the elemental composition of bed sediments. The depletion of such sediments due to the flash flood proves catchment-wide flushing, which induces a natural resetting of the geochemical signals. This ability to renew is an integral part of resilience in fluvial systems. This mechanism is disturbed by industrial activities in floodplains. The exceptional flooding reaches infrastructure that is assumed to be safe and, therefore, unprotected. These additional sources can shift flood sediments’ trace metal(loid) signature, which has a long-lasting impact on the catchment sediments. However, the modifications depend on the flooding extent, possible emitters, and protection measures.

Abstract The contamination and quantification of soil potentially toxic elements (PTEs) contamination sources and the determination of driving factors are the premise of soil contamination control. In our study, 788 soil samples from the National Agricultural Park in Chengdu, Sichuan Province were used to evaluate the contamination degree of soil PTEs by pollution factors and pollution load index. The source identification of soil PTEs was performed using positive matrix decomposition (PMF), edge analysis (UNMIX) and absolute principal component score-multiple line regression (APCS-MLR). The geo-detector method (GDM) was used to analysis drivers of soil PTEs pollution sources to help interpret pollution sources derived from receptor models. Result shows that soil Cu, Pb, Zn, Cr, Ni, Cd, As and Hg average content were 35.2, 32.3, 108.9, 91.9, 37.1, 0.22, 9.76 and 0.15 mg/kg in this study area. Except for As, all are higher than the corresponding soil background values in Sichuan Province. The best performance of APCS-MLR was determined by comparison, and APCS-MLR was considered as the preferred receptor model for soil PTEs source distribution in the study area. ACPS-MLR results showed that 82.70% of Cu, 61.6% of Pb, 75.3% of Zn, 91.9% of Cr and 89.4% of Ni came from traffic-industrial emission sources, 60.9% of Hg came from domestic-transportation emission sources, 57.7% of Cd came from agricultural sources, and 89.5% of As came from natural sources. The GDM results showed that distance from first grade highway, population, land utilization and total potassium (TK) content were the main driving factors affecting these four sources, with q values of 0.064, 0.048, 0.069 and 0.058, respectively. The results can provide reference for reducing PTEs contamination in farmland soil.

This study aimed to assess spatiotemporal water quality variation and its suitability for irrigation and domestic purposes in Lah River using the irrigation water quality index (IWQI) and the weighted arithmetic water quality index (WAWQI). The IWQI analysis result showed that the sodium absorption ratio, residual sodium carbonate, potential salinity, Kelly index, magnesium ratio, sodium percentage, and permeability index were found to be 1.07 mEq/L, −0.43 mEq/L, 0.8 mEq/L, 0.78 mEq/L, 43.01%, 42.95%, and 63.46%, respectively. The IWQIs revealed that the water quality of the river was appropriate for agricultural use during the dry season. Furthermore, the calculated WAWQI of the river water ranged from 123.13 to 394.72 during the wet season, indicating the high pollution levels in the Lah River and incompatibility for drinking purposes. On the other hand, the principal component analysis identified two pollution sources during the wet season and three during the dry season. In addition, the positive matrix prioritization model predicted the pollution source's contribution quite well with a signal-to-noise ratio of >2 and a residual error between −3 and 3 for both seasons. This study suggests that water quality of Lah River is degrading periodically necessitating proper pollution management. HIGHLIGHTS In this study, water quality and its suitability were assessed using multivariate statistical techniques and receptor models conjunctively.; The middle segment of the Lah River is more polluted than the upstream and downstream sections necessitating coordinated intervention measures.; During the dry season, the Lah River is suitable for irrigation.; Integrated water quality index and multivariate statistical techniques can be used for preliminary pollution management in Lah River.;

Oxidative potential (OP) has been proposed as a possible integrated metric for particles smaller than 2.5 μm in diameter (PM2.5) to evaluate adverse health outcomes associated with particulate air pollution exposure. Here, we investigate how OP depends on sources and chemical composition and how OP varies by land use type and neighborhood socioeconomic position in the Los Angeles area. We measured OH formation (OPOH), dithiothreitol loss (OPDTT), black carbon, and 52 metals and elements for 54 total PM2.5 samples collected in September 2019 and February 2020. The Positive Matrix Factorization source apportionment model identified four sources contributing to volume-normalized OPOH: vehicular exhaust, brake and tire wear, soil and road dust, and mixed secondary and marine. Exhaust emissions contributed 42% of OPOH, followed by 21% from brake and tire wear. Similar results were observed for the OPDTT source apportionment. Furthermore, by linking measured PM2.5 and OP with census tract level socioeconomic and health outcome data provided by CalEnviroScreen, we found that the most disadvantaged neighborhoods were exposed to both the most toxic particles and the highest particle concentrations. OPOH exhibited the largest inverse social gradients, followed by OPDTT and PM2.5 mass. Finally, OPOH was the metric most strongly correlated with adverse health outcome indicators.

Background: Floods, especially flash floods, are the major transporting agent for fluvial sediments, whose pollution is a global concern. As floods result in the dispersion of and exposure to these sediments, a profound understanding of sedimentary dynamics during flood events and the related pollutant dispersion is of relevance. However, the characteristics of extreme flood events concerning pollutant dynamics are insufficiently known so far. Results: In a Central European catchment impacted by intense industrial activities and former mining, over the course of five years, we surveyed six high-discharge events, five of them approx. bankfull discharge and one major flash flood event, supplemented by sampling of bank sediments. Fluvial sediments were analyzed for elemental composition by X-Ray fluorescence and for grain size distribution of the fine faction by laser diffraction. By applying a local enrichment factor, trace metal(loid) signatures in these sample sets were compared. Furthermore, Positive Matrix Factorization was used to investigate the trace metal(loid)s' sources. The sediments deposited by minor flooding had continual trace metal(loid) signatures. However, for the extreme event, significant divergencies arose and persisted for the following years: The enrichment of anthropogenically influenced elements increased, with a slowly decreasing trend in the subsequent two years. Naturally dominated metal(oid)s decrease in enrichment without indicating a return to original levels. In contrast, other elements were insensitive to the extreme event. Positive Matrix Factorization identified anthropogenic influences in elements originating from copper and lead processing and mining activities. Furthermore, bed sediments and a natural background factor were found to dominate the non-anthropogenically influenced metal(loid)s. Conclusions: In between extreme events, winnowing processes slowly alter the elemental composition of bed sediments. The depletion of such sediments due to the flash flood proves catchment-wide flushing, which induces a natural resetting of the geochemical signals. This ability to renew is an integral part of resilience in fluvial systems. This mechanism is disturbed by industrial activities in floodplains. The exceptional flooding reaches infrastructure that is assumed to be safe and, therefore, unprotected. These additional sources can shift flood sediments' trace metal(loid) signature, which has a long-lasting impact on the catchment sediments. However, the modifications depend on the flooding extent, possible emitters, and protection measures. [ABSTRACT FROM AUTHOR]

Identifying the potential pollution sources of surface water pollutants is essential for the management and protection of regional water environments in drinking water source areas. In this study, absolute principal component score-multiple linear regression (APCS-MLR) and positive matrix factorization (PMF) models were applied to assess water quality and identify the potential pollution sources affecting the surface water quality of Xin'an River Basin. For this purpose, a 10-year (2011–2020) dataset of eight water quality indicators (including pH, EC, DO, COD, NH3-N, TN, TP, and FC) covering eight monitoring stations and 7248 monthly observations was used. The results indicated that Pukou section had the worst water quality among the eight monitoring stations, and TN was the most serious water quality index. Both the APCS-MLR and PMF models identified agricultural nonpoint source pollution, urban nonpoint source pollution and rural domestic pollution, and meteorological factors. The sum of these three sources was very close, accounting for 60% and 58%, respectively. The APCS-MLR results demonstrated that for EC, COD, and NH3-N, the major pollution sources were urban nonpoint sources and rural domestic pollution. The major contamination source of TN was agricultural nonpoint source pollution (30.4%). Meanwhile, the major pollution sources of pH, DO, TP, and FC were unidentified factors. The PMF model identified five potential sources, and pH and DO were affected by meteorological factors. NH3-N and TP were influenced mainly by agricultural nonpoint source pollution. Atmospheric deposition was the major pollution source (87.9%) of TN. FC was mostly derived from livestock and poultry breeding (88.3%). EC and COD were mostly affected by urban nonpoint sources and rural domestic pollution. Therefore, receptor models can help managers identify the major sources of pollution in watersheds, but the major factors affecting different pollutants need to be supplemented by other methods. [ABSTRACT FROM AUTHOR]

The contamination and quantification of soil potentially toxic elements (PTEs) contamination sources and the determination of driving factors are the premise of soil contamination control. In our study, 788 soil samples from the National Agricultural Park in Chengdu, Sichuan Province were used to evaluate the contamination degree of soil PTEs by pollution factors and pollution load index. The source identification of soil PTEs was performed using positive matrix decomposition (PMF), edge analysis (UNMIX) and absolute principal component score-multiple line regression (APCS-MLR). The geo-detector method (GDM) was used to analysis drivers of soil PTEs pollution sources to help interpret pollution sources derived from receptor models. Result shows that soil Cu, Pb, Zn, Cr, Ni, Cd, As and Hg average content were 35.2, 32.3, 108.9, 91.9, 37.1, 0.22, 9.76 and 0.15 mg/kg in this study area. Except for As, all are higher than the corresponding soil background values in Sichuan Province. The best performance of APCS-MLR was determined by comparison, and APCS-MLR was considered as the preferred receptor model for soil PTEs source distribution in the study area. ACPS-MLR results showed that 82.70% of Cu, 61.6% of Pb, 75.3% of Zn, 91.9% of Cr and 89.4% of Ni came from traffic-industrial emission sources, 60.9% of Hg came from domestic-transportation emission sources, 57.7% of Cd came from agricultural sources, and 89.5% of As came from natural sources. The GDM results showed that distance from first grade highway, population, land utilization and total potassium (TK) content were the main driving factors affecting these four sources, with q values of 0.064, 0.048, 0.069 and 0.058, respectively. The results can provide reference for reducing PTEs contamination in farmland soil. [ABSTRACT FROM AUTHOR]

Severe ozone (O3) pollution has been recorded in China in recent years. The key precursor, volatile organic compounds (VOCs), is still not well understood in Nanning, which is a less developed city compared to other megacities in China. In this study, a year-long measurement of VOCs was conducted from 1 October 2020 to 30 September 2021, to characterize the ambient variations and apportion the source contributions of VOCs. The daily-averaged concentration of VOCs was measured to be 26.4 ppb, ranging from 3.2 ppb to 136.2 ppb across the whole year. Alkanes and oxygenated VOCs (OVOCs) were major species, contributing 46.9% and 25.2% of total VOC concentrations, respectively. Propane, ethane, and ethanol were the most abundant in Nanning, which differed from the other significant species, such as toluene (3.7 ppb) in Guangzhou, ethylene (3.8 ppb) in Nanjing, and isopentane (5.5 ppb), in Chengdu. The positive matrix factorization (PMF) model resolved six source factors, including vehicular emission (contributing 33% of total VOCs), NG and LPG combustion (19%), fuel burning (17%), solvent use (16%), industry emission (10%), and biogenic emission (5%). This indicated that Nanning was less affected by industrial emission compared with other megacities of China, with industry contributing 12–50%. Ethylene, m/p-xylene, butane, propylene, and isoprene were key species determined by ozone formation potential (OFP) analysis, which should be priority-controlled. The variations in estimated OFP and observed O3 concentrations were significantly different, suggesting that VOC reactivity-based strategies as well as meteorological and NOx effects should be considered collectively in controlling O3 pollution. This study presents a year-long dataset of VOC measurements in Nanning, which gives valuable implications for VOC control in terms of key sources and reactive species and is also beneficial to the formulation of effective ozone control strategies in other less developed regions of China. [ABSTRACT FROM AUTHOR]

In order to identify the source and bioavailability of soil Cd in the alluvial geological high background area, 3799 topsoil samples and 140 root soil samples were collected from the Jiulong area on the south bank of Poyang Lake, Jiangxi Province. The results confidently indicate that the range of topsoil Cd content is 0.02~8.12 ppm, with an exceedance rate of 14.6%. It is noteworthy that exceedance points were mostly distributed in quaternary sediments. The geostatistical analysis clearly shows that the spatial distribution characteristic of topsoil Cd is higher in the north and lower in the south. The area with extremely high values (>90% quantile) is predominantly located in the tidal flat and low-lying areas of the mainstream of the Xinjiang River. The PCA analysis confirms that the main source of topsoil Cd is man-made activities related to industry and mining. Soil Cd is primarily derived from upstream industrial and mining discharge (58.5%), as revealed by the PMF model analysis. The active Cd content in root soil is 77 ppb, with higher levels observed in the north and lower levels in the south. These findings suggest a significant risk of Cd diffusion along the upstream stream and deposition in the low-lying parts of the north. It is worth noting that Cd's bioavailability and active forms in paddy fields are the highest, which can have a detrimental effect on food security. The correlation analysis suggests that genetic sources primarily control the bioavailability of soil Cd, followed by soil physicochemical properties such as SOC, Fe-Al oxides, and soil texture. Preventing source pollution and cutting off water system transmission are effective methods for preventing and controlling soil Cd pollution. These methods ensure the safety of cultivated land in the lakeside area of Poyang Lake Plain. [ABSTRACT FROM AUTHOR]

The aim of this study was to identify the sources of atmospheric pollutants in densely populated urban areas from a particle toxicity perspective. To this end, the Positive Matrix Factorization (PMF) model and vehicle flux analysis were used to identify the sources of atmospheric pollutants in an urban area based on the measured compounds and wind speed at the receptor site. Moreover, the toxicity of each emission source was compared with the dithiothreitol-oxidation potential normalized to 9,10-Phenanthrenequinone (QDTT-OP) analysis using the PMF source apportionment results. The study found that the dominant sources of atmospheric pollutants in the urban area examined were secondary product (43.7%), resuspended dust (25.4%), and vehicle emissions (14.4%). The vehicle flux analysis demonstrated that reducing the number of vehicles could directly reduce urban atmospheric pollutants. By comparing the time series of PMF source profiles with QDTT-OP, the QDTT-OP analysis showed an r2 value of 0.9, thus indicating a strong correlation with biomass burning as the most harmful source of PM2.5 based on emission sources. Overall, this study is expected to provide valuable guidance for managing atmospheric pollutants in densely populated urban areas, and the findings could serve as a helpful resource for improving urban air quality in the future. [ABSTRACT FROM AUTHOR]

Trace element pollution from anthropogenic sources is increasingly widespread. This pollution in terrestrial environments threatens agricultural crop production, while in aquatic environments, it threatens fish cultivation. The contamination of these crucial food sources raises significant concerns regarding food safety, security, and its potential adverse effects on human health. Coastal areas are particularly vulnerable to heavy metal pollution due to their proximity to industrial and urban centres, as well as their susceptibility to contamination from marine sources. In attempting to identify the sources of heavy metals (As, Cu, Cr, Cd, Fe, Hg, Mn, Ni, Pb, and Zn) and measure their contributions, we collected soil samples from thirty sites along the three coastal districts (Patuakhali, Barguna, and Bhola) in Bangladesh. Using atomic absorption spectroscopy, heavy metal concentrations in soil samples were measured and three receptor models (PMF, PCA-MLR, and UNMIX) were applied to detect their sources. Pairwise correlation analysis of metal concentrations in 30 sites across 3 coastal districts showed all possible patterns, including both significant and insignificant positive and negative relationships between different metals, except for As and Hg which did not display any significant relationships with other metals. The concentrations of Cu, Fe, Mn, Ni, and Zn exceed the US-EPA sediment quality standard. The applied PCA-MLR, PMF, and UNMIX models identified several sources of heavy metal contamination, including (i) mixed anthropogenic and natural activities: contribution of 59%, 37%, and 43%, and (ii) vehicle emissions: contribution of 23%, 26% and 29%. The recognized metal sources should be prioritised to avoid the discharge of poisonous pollutants from anthropogenic factors and any possible future exposure. This study's findings have implications for ongoing monitoring and management of heavy metal contamination in coastal environments to mitigate potential health and ecological impacts and can inform policy development and management strategies. [ABSTRACT FROM AUTHOR]

Heavy metals in dust have been found to be a significant threat to human health, but how dust sources and physicochemical properties influence the distribution of heavy metals has not been fully investigated. Fuzhou, a Chinese subtropical city, was chosen as a case in this study. We collected 51 dust samples from open spaces, in order to serve as an early warning system for heavy metals in urban dust, the risk level of heavy metal pollution was assessed, the physicochemical properties of dust were analyzed, and the sources of heavy metals were examined using a combination of positive matrix factorization (PMF) and backward trajectory model (MeteoInfo). The results showed that the average concentrations of heavy metals were Zn > Pb > Cr > Cu > Ni > As > Cd, with Cd having the highest ecological risk level. All heavy metals are positively correlated, the higher the organic matter and the larger the particle size, the higher the heavy metal concentration. The higher the water content, the higher the Ni and Cu content. The sources of heavy metals in dust are complex and include local anthropogenic sources: traffic, architectural paint, combustion, and mixed sources, as well as the impact of atmospheric motion on dust from northern cities in Fuzhou City and Zhejiang Province. Our study provides a valuable point of reference for early warning of urban heavy metal. Sources of heavy metals in open space and ways of entering the human body. [ABSTRACT FROM AUTHOR]

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Five atmospheric trace gases were measured in Dhaka, Bangladesh, using an automated direct sensing gas monitoring system. The average concentrations of CO, NO, NO2, TVOC, and O3 were 2603.6 ± 1216.4, 281.5 ± 158.0, 182.7 ± 69.4, 10,068.2 ± 5296.1 and 36.6 ± 23.6 µg/m3. The measured trace gas concentrations demonstrated significant seasonal and monthly fluctuations, with NO and CO concentrations being the highest in winter, O3 and TVOC concentrations being the highest during the monsoon season, and NO2 concentrations being the highest during the pre-monsoon season. Air mass trajectories and wind rose plots during the monsoon were compared to the winter. It showed that air masses from the southeast and south had an impact on the quantity of most of the trace gases whilst they traveled over the Bay of Bengal throughout the monsoon period. In contrast, air masses from the northwestern region, north, and the west had a bigger effect on the rising amount of trace gases across the Indo Gangetic Plain (IGP) during the winter season. NO2 (182.7 µg/m3) had the maximum concentration of the gases measured and crossed the World Health Organization’s (WHO) annual recommended value. The source characteristics of NOx, TVCO, and O3 gases were determined using the positive matrix factorization (PMF 5.0) model. The combustion of fossil fuels and aerosols were found to be the major sources of NOx and O3, with aerosol formation being the primary source of TVOC concentration. [ABSTRACT FROM AUTHOR]

Although music plays a critical role in human behaviour, few scholars have examined how it may impact the shopping behaviours of sport consumers. This study uses structural equation modelling to explore how consumers' perceived musical fit (PMF) influences their purchase intention (PIN), store evaluation (SEV) and brand attitude (BAT) in a sport retails setting. Additionally, the study aimed to investigate whether consumers' emotional states (EMS) mediate the relations between PMF and the three outcome variables being tested. The results demonstrate that PMF directly affected BAT and PIN, but this was not statistically significant with SEV. Furthermore, EMS fully mediated the relationship between PMF and SEV. However, it was found to partially mediate the relations between PMF and PIN, as well as between PMF and BAT. The implications of the findings, limitations and future research directions are also discussed. [ABSTRACT FROM AUTHOR]

In order to understand the pollution degree and source of potentially toxic elements (PTEs) in groundwater around the accident site and evaluate their harm to human health, 22 groundwater samples were collected around the accident well, and the contents of As, Cd, Cr, Cu, Hg, Ni, Pb, Zn, CH2Cl2 and C2H4Cl2 were determined. On the basis of water quality evaluation, the source apportionment method combining qualitative and quantitative analysis was used to determine the main sources of PTEs in the region, and the health risk assessment model was used to evaluate the health risk of PTEs to the human body. The results show that pH, TDS, Th and COD all exceed the standard to varying degrees, among which TH is the index with the largest number exceeding the standard. The quality of the groundwater environment in the study area is at a very poor level, and the F value is between 7.25 and 8.49. The exposure results model showed that there was no non-carcinogenic risk of PTEs in the study area, and the health risk of oral intake in the exposed population was greater than that of skin contact. Compared with adults, children were more vulnerable to the health risk stress of PTEs in groundwater. The total carcinogenic risk is higher than the total non-carcinogenic risk. As, Cd and Cr are the primary factors causing carcinogenic health risks in this area. Principal component analysis (PCA) was used to analyze the sources of PTEs in groundwater, and three principal components were extracted. It was preliminarily determined that PTE pollution was mainly related to agricultural sources, anthropogenic industrial sources and industrial sedimentation sources. The results of positive definite factor matrix analysis (PMF) were basically similar to those of PCA, but PMF further clarified the contribution rate of three pollution sources, among which agricultural sources contributed the most to the accumulation of PTEs. [ABSTRACT FROM AUTHOR]

Cyprus is a typical eastern Mediterranean country that suffers from local emissions, transported anthropogenic pollution, and dust storms all year round. Therefore, exposures to PM in ambient and residential micro-environments are of great public health concern. Our study collected indoor and outdoor PM2.5 and PM10 samples simultaneously in 22 houses in Nicosia, Cyprus, during warm seasons and cold seasons from February 2019 to May 2021. Samples were analyzed for mass and constituents' concentrations. To determine indoor and outdoor sources of PM in residential environments, we used the EPA positive matrix factorization (PMF) model to conduct source apportionment analyses for both indoor and outdoor PM2.5 and PM10 particles. Generally, six types of residential-level PM sources were resolved: biomass burning, traffic, local or regional secondary sulfate pollution, Ca-rich particles, sea salt, and soil dust. In the source apportionment of PM2.5, the main contribution to outdoor levels (33.1%) was associated with sulfate-rich transported pollution. The predominant contribution to indoor levels (48.0%) was attributed to secondary sulfate pollution as a mixture of local- and regional-scale pollutants. Biomass burning and traffic sources constituted the main outdoor sources of indoor PM2.5, while the Ca-rich particles were identified to almost originate from indoors. By contrast, the largest fraction (29.3%) of the ambient PM10 and a smaller proportion (10.2%) of indoor PM10 were attributed to Ca-rich particles. Indoor PM10 was associated mainly with outdoor sources, except for the soil dust which originated from indoor activities. [ABSTRACT FROM AUTHOR]

The emission sources of fine particulate matter (PM2.5) have not yet been fully identified in Ho Chi Minh City (HCMC), Vietnam, presenting difficulties to authorities in controlling air pollution efficiently. To address this issue, this study explores the source apportionment of PM2.5 by the positive matrix factorization (PMF) model and identifies potential regional sources through the weighted concentration-weighted trajectory (WCWT) model based on the field observation data of PM2.5 in HCMC. 24-h PM2.5 samples were collected in central HCMC for a year (September 2019–August 2020). Herein, inductively coupled plasma mass spectroscopy was used to analyze trace elements, in addition to identifying PM2.5 mass and other chemical species, such as water-soluble ions and carbonaceous species, reported in our former study. The PMF results showed that PM2.5 in HCMC was dominated by anthropogenic-rich sources comprising biomass burning, coal combustion, transportation, and crustal origins (36.4% of PM2.5 mass), followed by secondary ammonium sulfate (18.4%), sea salt (13.7%), road dust (9.6%), and coal and crude oil combustion (9.4%). WCWT results suggested that the geological sources of PM2.5 were mainly from local areas and scattered to the northeast/southwest of HCMC. In addition, the long-range transport of PM2.5 from surrounding countries was revealed during the assembly restriction and lockdown period in 2020. [ABSTRACT FROM AUTHOR]

Abstract The simultaneous detection of BCR::ABL1 and JAK2 V617F was rarely reported and their clonal relationship and dynamic clonal shift were not characterized. Here, we described a unique case with the initial presentation as JAK2 V617F+ primary myelofibrosis, followed by the emergence of BCR::ABL1+ chronic myeloid leukemia. The patient then developed BCR::ABL1+ B‐lymphoblastic leukemia. Treatment for B‐lymphoblastic leukemia prompted a regression to the state of primary myelofibrosis. In light of these observations, we proposed a clonal evolution model for this case.

Abstract The emission sources of fine particulate matter (PM2.5) have not yet been fully identified in Ho Chi Minh City (HCMC), Vietnam, presenting difficulties to authorities in controlling air pollution efficiently. To address this issue, this study explores the source apportionment of PM2.5 by the positive matrix factorization (PMF) model and identifies potential regional sources through the weighted concentration-weighted trajectory (WCWT) model based on the field observation data of PM2.5 in HCMC. 24-h PM2.5 samples were collected in central HCMC for a year (September 2019–August 2020). Herein, inductively coupled plasma mass spectroscopy was used to analyze trace elements, in addition to identifying PM2.5 mass and other chemical species, such as water-soluble ions and carbonaceous species, reported in our former study. The PMF results showed that PM2.5 in HCMC was dominated by anthropogenic-rich sources comprising biomass burning, coal combustion, transportation, and crustal origins (36.4% of PM2.5 mass), followed by secondary ammonium sulfate (18.4%), sea salt (13.7%), road dust (9.6%), and coal and crude oil combustion (9.4%). WCWT results suggested that the geological sources of PM2.5 were mainly from local areas and scattered to the northeast/southwest of HCMC. In addition, the long-range transport of PM2.5 from surrounding countries was revealed during the assembly restriction and lockdown period in 2020. Graphical Abstract

This study introduces a Sagnac Interferometer (SI) fiber sensor that integrates Polarization-Maintaining Fibers (PMFs) with a Tilted Fiber Bragg Grating (TFBG) for the dual-parameter measurement of strain and lateral pressure. By incorporating a 6° TFBG with PMFs into the SI sensor, its sensitivity is significantly enhanced, enabling advanced multi-parameter sensing capabilities. The sensor demonstrates a temperature sensitivity of −1.413 nm/°C and a lateral pressure sensitivity of −4.264 dB/kPa, as validated by repeated experiments. The results exhibit excellent repeatability and high precision, underscoring the sensor’s potential for robust and accurate multi-parameter sensing applications.

To evaluate the pollution sources and dynamics of the upper reaches of the Tarim River, 10 typical sampling points were selected, and 23 water quality parameters from 2020 to 2022 were analyzed using one-way analysis of variance, the comprehensive Water Quality Identification Index (WQI), and Principal Component Analysis (PCA). The pollution status, sources, and contribution rates of water quality were investigated using the Absolute Principal Component-Multiple Linear Regression Model (APCS-MLR) and Positive Matrix Factorization (PMF). The results indicated that the water quality parameters of dissolved oxygen (DO), chemical oxygen demand (CODMn), biochemical oxygen demand after 5 days (BOD5), total nitrogen (TN), total phosphorus (TP), fluoride ions (F−), and ammonia-nitrogen (NH3-N) in the upper reaches of the Tarim River exceed standards, with noticeable spatial variations observed for each parameter. The water quality evaluation grades in the upper reaches of Tarim River primarily indicate “moderate” and “good” levels, with DO, TN, NH3-N, and electrical conductivity (EC) being the key parameters influencing variations in water quality. The source analysis results from APCS-MLR and PMF yielded similar outcomes, identifying six potential pollution sources. Among these, soil weathering, livestock and poultry breeding, and agricultural activities exhibited higher contribution rates. Specifically, the contribution rates for these sources according to APCS-MLR were 44.11%, 19.63%, and 11.67%, respectively; while according to PMF they are 24.08%, 17.88%, and 27.54%, respectively. Furthermore, industrial pollution sources contributed at a rate of 6.01% according to APCS-MLR, while urban living sources contributed at a rate of 2.13%. However, based on PMF analysis, the contribution rates for industrial pollution sources increased significantly to 16.71%. Additionally, APCS-MLR identified natural sources as contributing at a rate of 16.45%, whereas PMF suggested that a combination of agricultural activities and natural sources contributed at a lower rate of only 9.52%. In conclusion, the water quality within the upper reaches of the Tarim River is predominantly satisfactory. Nonetheless, localized pollution, primarily attributable to human activities, presents a substantial challenge. These observations provide critical insights into improving and protecting the fragile water quality of the Tarim River.

To establish and implement effective policies for controlling fine particle matters (PM2.5), which is associated with high-risk diseases, continuous research on identifying PM2.5 sources was conducted. This study utilized the positive matrix factorization (PMF) receptor model to estimate the sources and characteristics of PM2.5 between Baengnyeong Island (BNI) and the Seoul Metropolitan Area (SMA). We conducted PMF modeling and backward trajectory analysis using the data on PM2.5 and its components collected from 2020 to 2021 at the Air quality Research Centers (ARC). The PMF modeling identified nine pollution sources in both BNI and the SMA, including secondary sulfate, secondary nitrate, vehicles, biomass burning, dust, industry, sea salt particles, coal combustion, and oil combustion. Secondary particulate matter, vehicles, and biomass burning were found to be major contributors to PM2.5 concentrations in both regions. A backward trajectory analysis indicated that air masses, passing through BNI to the SMA, showed higher concentrations and contributions of ammonium nitrate, vehicles, and biomass burning in the SMA site compared to BNI site. These findings suggest that controlling nitrogen oxides (NOx) and ammonia emissions in the SMA, as well as monitoring the intermediate products that form aerosols, such as HNO3, are needed.