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Fant 9887 publikasjoner. Viser side 312 av 396:

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SEN4POL – Towards a Sentinel-based pollen information service

Schneider, Philipp; Hamer, Paul David; Vogt, Matthias; Trier, Øivind Due; Solberg, Rune; Skogesal, Hogne; Brobakk, Trond Einar; Ramfjord, Hallvard

2020

SEN4POL – Towards a Sentinel-based pollen information service

Schneider, Philipp; Hamer, Paul David; Vogt, Matthias; Trier, Øivind Due; Solberg, Rune; Skogesal, Hogne; Brobakk, Trond Einar; Ramfjord, Hallvard

2020

SEN4POL Phase-1: Final Scientific Report

Schneider, Philipp; Hamer, Paul David; Trier, Øivind Due; Solberg, Rune; Ramfjord, Hallvard; Brobakk, Trond Einar; Skogesal, Hogne

Norsk institutt for luftforskning

2019

SensEURCity: A multi-city air quality dataset collected for 2020/2021 using open low-cost sensor systems

Van Poppel, Martine; Schneider, Philipp; Peters, Jan; Yatkin, Sinan; Gerboles, Michel; Matheeussen, Christina; Bartonova, Alena; Davila, Silvije; Signorini, Marco; Vogt, Matthias; Dauge, Franck Rene; Skaar, Jøran Solnes; Haugen, Rolf

Low-cost air quality sensor systems can be deployed at high density, making them a significant candidate of complementary tools for improved air quality assessment. However, they still suffer from poor or unknown data quality. In this paper, we report on a unique dataset including the raw sensor data of quality-controlled sensor networks along with co-located reference data sets. Sensor data are collected using the AirSensEUR sensor system, including sensors to monitor NO, NO2, O3, CO, PM2.5, PM10, PM1, CO2 and meteorological parameters. In total, 85 sensor systems were deployed throughout a year in three European cities (Antwerp, Oslo and Zagreb), resulting in a dataset comprising different meteorological and ambient conditions. The main data collection included two co-location campaigns in different seasons at an Air Quality Monitoring Station (AQMS) in each city and a deployment at various locations in each city (also including locations at other AQMSs). The dataset consists of data files with sensor and reference data, and metadata files with description of locations, deployment dates and description of sensors and reference instruments.

Springer Nature

2023

Sensitivity analysis of ammonia emission reductions on exceedances of PM air quality standards. ETC/ACM Technical Paper, 2013/12

Beauchamp, M.; Bessagnet, B.; Meleux, F.; Colette, A.; Rouïl, L.; Guerreiro, C.; Tsyro, S.; de Leeuw, F.; Ruyssenaars, P.; Sauter, F.; Velders, G.

2014

Sensitivity of summer 2-m temperature to sea ice conditions.

Benestad, R. E.; Senan, R.; Balmaseda, M.; Ferranti, L.; Orsolini, Y.; Melsom, A.

2011

Sensitivity studies of Arctic ice clouds. NILU PP

Svendby, T.M.; Myhre, C.L.; Kahnert, M.

2006

Sentinel and Copernicus powered Arctic Wildfire Knowledge System “Arctic Peat-And Forest-fire Information System”

Stebel, Kerstin; Eckhardt, Sabine; Evangeliou, Nikolaos; Kaiser, Johannes; Schneider, Philipp; Sollum, Espen; Aun, Margit; George, Jan-Peter

2024

Sentinel-5P based NOx emissions from large combustion plants for comparison with and possibly QA/QC of E-PRTR emissions

Stebel, Kerstin; Schneider, Philipp; Hamer, Paul David; Tarrasón, Leonor; Weydahl, Torleif; Antognazza, Frederico

2022

Separation of ash and sulfur dioxide during the 2011 Grímsvötn eruption.

Moxnes, E.D.; Kristiansen, N.I.; Stohl, A.; Clarisse, L.; Durant, A.; Weber, K.; Vogel, A.

2014

Separation of volcanic ash and sulfur dioxide from the Eyjafjallajökull eruption, April-May 2010. NILU F

Thomas, H.E.; Prata, F.; Carn, S.A.; Clarisse, L.; Watson, M.I.

2010

SESS report 2018. The State of Environmental Science in Svalbard – an annual report.

Orr, Elisabeth; Hansen, Georg; Lappalainen, Hanna; Hübner, Christiane E.; Lihavainen, Heikki (eds.)

Svalbard Integrated Arctic Earth Observing System (SIOS)

2019

SEVIRI Aerosol Optical Depth Validation Using AERONET and Intercomparison with MODIS in Central and Eastern Europe

Ajtai, Nicolae; Mereuta, Alexandru; Stefanie, Horatiu; Radovici, Andrei; Botezan, Camelia; Zawadzka-Manko, Olga; Stachlewska, Iwona S.; Stebel, Kerstin; Zehner, Claus

This paper presents the validation results of Aerosol Optical Depth (AOD) retrieved from the Spinning Enhanced Visible Infrared Radiometer (SEVIRI) data using the near-real-time algorithm further developed in the frame of the Satellite-based Monitoring Initiative for Regional Air quality (SAMIRA) project. The SEVIRI AOD was compared against multiple data sources: six stations of the Aerosol Robotic Network (AERONET) in Romania and Poland, three stations of the Aerosol Research Network in Poland (Poland–AOD) and Moderate Resolution Imaging Spectroradiometer (MODIS) data overlapping Romania, Czech Republic and Poland. The correlation values between a four-month dataset (June–September 2014) from SEVIRI and the closest temporally available data for both ground-based and satellite products were identified. The comparison of the SEVIRI AOD with the AERONET AOD observations generally shows a good correlation (r = 0.48–0.83). The mean bias is 0.10–0.14 and the root mean square error RMSE is between 0.11 and 0.15 for all six stations cases. For the comparison with Poland–AOD correlation values are 0.55 to 0.71. The mean bias is 0.04–0.13 and RMSE is between 0.10 and 0.14. As for the intercomparison to MODIS AOD, correlations values were generally lower (r = 0.33–0.39). Biases of −0.06 to 0.24 and RMSE of 0.04 to 0.28 were in good agreement with the ground–stations retrievals. The validation of SEVIRI AOD with AERONET results in the best correlations followed by the Poland–AOD network and MODIS retrievals. The average uncertainty estimates are evaluated resulting in most of the AOD values falling above the expected error range. A revised uncertainty estimate is proposed by including the observed bias form the AERONET validation efforts.

MDPI

2021

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