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Found 9989 publications. Showing page 18 of 400:

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Year  
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Monitoring aerosol optical depth during the Arctic night: Instrument development and first results

Mazzola, Mauro; Stone, Robert S.; Kouremeti, Natalia; Vitale, Vito; Gröbner, Julian; Stebel, Kerstin; Hansen, Georg Heinrich; Stone, Thomas C.; Ritter, Christoph; Pulimeno, Simone

Moon-photometric measurements were made at two locations in the Arctic during winter nights using two different modified Sun photometers; a Carter Scott SP02 and a Precision Filter Radiometer (PFR) developed at PMOD/WRC. Values of aerosol optical depth (AOD) were derived from spectral irradiance measurements made at four wavelengths for each of the devices. The SP02 was located near Barrow, Alaska and recorded data from November 2012 to March 2013, spanning five lunar cycles, while the PFR was deployed to Ny-Ålesund, Svalbard each winter from February 2014 to February 2019 for a total of 56 measurement periods. A methodology was developed to process the raw data, involving calibration of the instruments and normalizing measured spectral irradiance values in accordance with site-specific determinations of the extraterrestrial atmospheric irradiance (ETI) as Moon phase cycled. Uncertainties of the derived AOD values were also evaluated and found to be in the range, 0.006–0.030, depending on wavelength and which device was evaluated.
The magnitudes of AOD determined for the two sites were in general agreement with those reported in the literature for sunlit periods just before and after the dark periods of Arctic night. Those for the PFR were also compared with data obtained using star photometers and a Cimel CE318-T, recently deployed to Ny-Ålesund, showing that Moon photometry is viable as a means to monitor AOD during the Arctic night. Such data are valuable for more complete assessments of the role aerosols play in modulating climate, the validation of AOD derived using various remote sensing techniques, and applications related to climate modeling.

2024

Potential sources and transport of atmospheric microplastics in the North Atlantic Ocean

Evangeliou, Nikolaos; Gossmann, Isabel; Herzke, Dorte; Held, Andreas; Schulz, Janina; Nikiforov, Vladimir; Eckhardt, Sabine; Gerdts, Gunnar; Wurl, Oliver; Scholz-Böttcher, Barbara

2024

Estimation of spatio-temporal source of microplastics using Bayesian Neural networks

Brožová, Antonie; Šmídl, Václav; Tichý, Ondřej; Evangeliou, Nikolaos

2024

Features Inspired PM2.5 Prediction: A Belfast City Case Study

Naz, Fareena; Fahim, Muhammad; Cheema, Adnan Ahmad; Nguyen, Trung Viet; Cao, Tuan-Vu; Duong, Trung Q.

2024

Forecasting transport of biomass burning emissions for the ARCSIX 2024 campaign

Evangeliou, Nikolaos; Eckhardt, Sabine; Zwaaftink, Christine Groot; Sollum, Espen; Stebel, Kerstin

2024

Telomere analysis of PFAS using GC-Orbitrap: SPE sampling in air and evaluation of chromatographic columns

Cerasa, Marina; Balducci, Catia; Mosca, Silvia; Perilli, Mattia; Moneta, Benedetta Giannelli; Nikiforov, Vladimir; Manni, Andrea; Guerriero, Ettore

2024

Advancing Air Quality Awareness and Action: Insights from the SOCIO-BEE Project on Community-Based Monitoring

Hassani, Amirhossein; Kyfonidis, Charalampos; Mansilla, Diego Casado; Salamalikis, Vasileios; Kotzagianni, Maria; Roussos, Anargyros; Castell, Nuria; Udina, Sergi; Morresi, Nicole; Casccia, Sara; Revel, Gian Marco; Angelis, Georgios-Fotios; Emvoliadis, Alexandros; Theodorou, Traianos-Ioannis; Karanassos, Dimitrios; Kopsacheilis, Evangelos; Drosou, Anastasios; Tzovaras, Dimitrios; Lopez, Carlos; Lisbona, Daniel

2024

AI-driven spatiotemporal quantification and prediction of soil salinity at European scale using the LUCAS database

Zarif, Mohammad Aziz; Hassani, Amirhossein; Panagos, Panos; Lebron, Inma; Robinson, David A.; Shokri, Nima

2024

AI-driven insights into soil health and soil degradation in Europe in the face of climate and anthropogenic challenges

Afshar, Mehdi H.; Hassani, Amirhossein; Aminzadeh, Milad; borrelli, Pasquale; Panagos, Panos; Robinson, David A.; Shokri, Nima

2024

Skogbrann herjer i Chile: – Hjerteskjærende å se

Kaiser, Johannes (interview subject); Tangen, Eivind (journalist)

2024

Assessing regional CO2 emissions by global high-resolution inverse model constrained by surface and satellite observations

Nayagam, Lorna Raja; Maksyutov, Shamil; Oda, Tomohiro; Achari, Rajesh Janardanan; Yoshida, Yukio; Kaiser, Johannes; Matsunaga, Tsuneo

2024

Toward Standardization of a Lung New Approach Model for Toxicity Testing of Nanomaterials

Elje, Elisabeth; Camassa, Laura Maria Azzurra; Shaposhnikov, Sergey; Anmarkrud, Kristine Haugen; Skare, Øivind; Nilsen, Asbjørn Magne; Zienolddiny, Shanbeh; Rundén-Pran, Elise

This study represents an attempt toward the standardization of pulmonary NAMs and the development of a novel approach for toxicity testing of nanomaterials. Laboratory comparisons are challenging yet essential for identifying existing limitations and proposing potential solutions. Lung cells cultivated and exposed at the air-liquid interface (ALI) more accurately represent the physiology of human lungs and pulmonary exposure scenarios than submerged cell and exposure models. A triculture cell model system was used, consisting of human A549 lung epithelial cells and differentiated THP-1 macrophages on the apical side, with EA.hy926 endothelial cells on the basolateral side. The cells were exposed to silver nanoparticles NM-300K for 24 h. The model used here showed to be applicable for assessing the hazards of nanomaterials and chemicals, albeit with some limitations. Cellular viability was measured using the alamarBlue assay, DNA damage was assessed with the enzyme-modified comet assay, and the expression of 40 genes related to cell viability, inflammation, and DNA damage response was evaluated through RT2 gene expression profiling. Despite harmonized protocols used in the two independent laboratories, however, some methodological challenges could affect the results, including sensitivity and reproducibility of the model.

2024

Forurensning

Heimstad, Eldbjørg Sofie

2024

The CE-RISE Project

Hernandez, Miguel Las Heras

2024

Enhancement of Highly Active Ice Nucleating Particles Linked to Surface Warming in Svalbard

Tobo, Yutaka; Adachi, Kouji; Kawai, Kei; Matsui, Hitoshi; Ohata, Sho; Oshima, Naga; Kondo, Yutaka; Hermansen, Ove; Inoue, Jun; Uchida, Masaki; Koike, Makoto

2024

Design of multi-luminescent silica-based nanoparticles for the detection of liquid organic compounds

Delic, Asmira; Lindgren, Mikael; Psarrou, Maria; Economopoulos, Solon; Mariussen, Espen; Krivokapic, Alexander; Torsæter, Ole; Omran, Mohamed; Einarsrud, Mari-Ann

Tracer testing in reservoir formations is utilised to determine residual oil saturation as part of optimum hydrocarbon production. Here, we present a novel detection method of liquid organic compounds by monodisperse SiO2 nanoparticles (NPs) containing two luminophores, a EuIII:EDTA complex and a newly synthesised fluorophore based on the organic boron-dipyrromethene (BODIPY)-moiety. The particles exhibited stable EuIII PL emission intensity with a long lifetime in aqueous dispersion. The fluorescence of the BODIPY was also preserved in the aqueous environment. The ratiometric PL detection technique was demonstrated by using toluene and 1-octanol as model compounds of crude oil. The optimal synthesis conditions were found to give NPs with a diameter of ~100 nm, which is suitable for transport through porous oil reservoir structures. The cytotoxicity of the NPs was confirmed to be very low for human lung cell and fish cell lines. These findings demonstrate the potential of the NPs to replace the hazardous chemicals used to estimate the residual oil saturation. Moreover, the ratiometric PL detection technique is anticipated to be of benefit in other fields, such as biotechnology, medical diagnostics, and environmental monitoring, where a reliable and safe detection of a liquid organic phase is needed.

2024

Monitoring of environmental contaminants in freshwater food webs (MILFERSK), 2023

Økelsrud, Asle; Grung, Merete; Bæk, Kine; Rundberget, Thomas; Øxnevad, Sigurd; Enge, Ellen Katrin; Hanssen, Linda; Johansen, Ingar

This report presents data from the third year of a 5-year period of the MILFERSK program. In 2023 the monitoring program reports on the sampling and analyses of the pelagic food chain in Lake Mjøsa, with the following sample types: zooplankton, Mysis, E. smelt, vendace, and brown trout, in addition to brown trout from Lake Femunden. A total of 205 single compounds/isomers were determined, and frequent detections were found of specific PFAS, PBDEs, Hg and siloxanes through the food chain with biomagnifying properties. Some contaminants, such as octocrylene is found in higher concentrations in the lower trophic levels. A slight downwards trend is observed from 2014 – 2023 for PFOS in Lake Mjøsa. We also observe a lower length adjusted mercury concentration for brown trout in Lake Mjøsa for the period 2014 to 2023, compared to the 9 years prior (2006 – 2014).

Norsk institutt for vannforskning (NIVA)

2024

Integrating Low-cost Sensor Systems and Networks to Enhance Air Quality Applications

Amegah, Kofi; Basart, Sara; Diez, Sebastiàn; Rosales, Colleen Marciel F.; Zimmerman, Naomi; Archer, Jan-Michael; Barreto, África; Bi, Jianzhao; Biggs, Russ; Castell, Nuria; deSouza, Priyanka; Dye, Tim; Fujita, Ryo; Giordano, Michael R.; Gonzalez, Marisa E.; Hasenkopf, Christa; Hassani, Amirhossein; Hodoli, Collins Gameli; Hofman, Jelle; Huneeus, Nicolás Jorge; Jayaratne, Rohan; Kroll, Jesse H.; Labrador, Lorenzo; Legri, Radouane; Levy, Robert C.; Marques, Tomas; Martins, Leila Droprinchinski; McMahon, Ethan; Mead, Mohammed Iqbal; Molina, Luisa T.; Montgomery, Anastasia; Morawska, Lidia; Ning, Zhi; Peltier, Richard; Popoola, Olalekan; Rojas, Néstor; Retama, Armando; Schneider, Philipp; Shairsing, Kerolyn; Strużewska, Joanna; Tang, Beiming; Poppel, Martine Van; Westervelt, Daniel M.; Zhang, Yang; Zheng, Mei

Low-cost air quality sensor systems (LCS) are emerging technologies for policy-relevant air quality analysis, including pollution levels, source identification, and forecasting. This report discusses LCS use in networks and alongside other data sources for comprehensive air quality applications, complementing other WMO publications on LCS operating principles, calibration, performance assessment, and data communication.

The LCS’s utility lies in their ability to provide new insights into air quality that existing data sources may not offer. While LCS data must be verified, their integration with other data sources can enhance understanding and management of air quality. In areas without reference-grade monitors, LCS can identify factors affecting local air quality and guide future monitoring efforts. Combining LCS data with satellite and other air quality systems can improve data reliability and establish corroborating evidence for observed trends. LCS can extend the spatial coverage of existing monitoring networks, offering localized insights and supporting effective air quality management policies. Co-locating LCS with reference-grade monitors helps quantify measurement uncertainties and apply LCS data appropriately for forecasting, source impact analysis, and community engagement.

World Meteorological Organization

2024

Long-term meteorology-adjusted and unadjusted trends of PM2.5 using the AirGAM model over Delhi, 2007–2022

Chetna, NN; Dhaka, Surendra K.; Walker, Sam-Erik; Rawat, Vikas; Singh, Narendra

This study investigates the impact of meteorological variations on the long-term patterns of PM2.5 in Delhi from 2007 to 2022 using the AirGAM 2022r1 model. Generalized Additive Modeling was employed to analyze meteorology-adjusted (removing the influence of inter-annual variations in meteorology) and unadjusted trends (trends without considering meteorology) while addressing auto-correlation. PM2.5 levels showed a modest decline of 14 μg m−3 unadjusted and 18 μg m−3 meteorology-adjusted over the study period. Meteorological conditions and time factors significantly influenced trends. Temperature, wind speed, wind direction, humidity, boundary layer height, medium-height cloud cover, precipitation, and time variables including day-of-week, day-of-year, and overall time, were used as GAM model inputs. The model accounted for 55% of PM2.5 variability (adjusted R-squared = 0.55). Day-of-week and medium-height cloud cover were non-significant, while other covariates were significant (p

2024

Forskere advarer mot giftstoffer som hoper seg opp i miljøet

Heimstad, Eldbjørg Sofie; Herzke, Dorte (interview subjects); Aukrust, Øyvind (journalist)

2024

Cost-Efficient measurement platform and machine-learning-based sensor calibration for precise NO2 pollution monitoring

Pietrenko-Dabrowska, Anna; Koziel, Slawomir; Wojcikowski, Marek; Pankiewicz, Bogdan; Rydosz, Artur; Cao, Tuan-Vu; Wojtkiewicz, Krystian

2024

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