Found 10009 publications. Showing page 5 of 401:
2025
Citizen-operated low-cost air quality sensors (LCSs) have expanded air quality monitoring through community engagement. However, still challenges related to lack of semantic standards, data quality, and interoperability hinder their integration into official air quality assessments, management, and research. Here, we introduce FILTER, a geospatially scalable framework designed to unify, correct, and enhance the reliability of crowd-sourced PM2.5 data across various LCS networks. FILTER assesses data quality through five steps: range check, constant value detection, outlier detection, spatial correlation, and spatial similarity. Using official data, we modeled PM2.5 spatial correlation and similarity (Euclidean distance) as functions of geographic distance as benchmarks for evaluating whether LCS measurements are sufficiently correlated/consistent with neighbors. Our study suggests a −10 to 10 Median Absolute Deviation threshold for outlier flagging (360 h). We find higher PM2.5 spatial correlation in DJF compared to JJA across Europe while lower PM2.5 similarity in DJF compared to JJA. We observe seasonal variability in the maximum possible distance between sensors and reference stations for in-situ (remote) PM2.5 data correction, with optimal thresholds of ∼11.5 km (DJF), ∼12.7 km (MAM), ∼20 km (JJA), and ∼17 km (SON). The values implicitly reflect the spatial representativeness of stations. ±15 km relaxation for each season remains feasible when data loss is a concern. We demonstrate and validate FILTER's effectiveness using European-scale data originating from the two community-based monitoring networks, sensor.community and PurpleAir with QC-ed/corrected output including 37,085 locations and 521,115,762 hourly timestamps. Results facilitate uptake and adoption of crowd-sourced LCS data in regulatory applications.
2025
2025
2025
2025
2025
2025
2025
2025
Metaller, PCB, PAH og dioksiner i mose i Sør-Varanger. Moseundersøkelser 2008, 2015 og 2020
I 2008 samlet Svanhovd Miljøsenter inn mose ved 11 lokaliteter i grenseområdene mot Russland som NILU analyserte for 11 metaller, PCB, PAH og dioksiner. Formålet var å undersøke om det var andre kilder til forurensning i grenseområdene enn gruvedrift og smelteverksindustri. Prøvetaking og analyse ble gjentatt av NILU i 2015 og 2020, men kun for 60 (2015) og 56 (2020) metaller. For spormetallene Ni, Cu, Co og As er det et klart mønster med forhøyede konsentrasjoner nedstrøms Nikel og Zapolyarnyj. Organiske miljøgifter viser lave konsentrasjoner.
NILU
2025
På oppdrag fra Alcoa Norway AS dept. Mosjøen har NILU utført målinger i omgivelses-luft rundt smelteverket i Mosjøen. Målingene ble utført med aktiv prøvetaking (fluor, SO2, metaller, PAH, PM10) og passiv prøvetaking (SO2, støvnedfall). Måleprosjektet ble utført i perioden 22. mai – 19. august 2024. Alle målte komponenter var godt under de individuelle grenseverdier, målsettingsverdier og luftkvalitetskriterier i måleperioden. Siden Mosjøen er mest utsatt for utslipp fra aluminiumsverket i sommermånedene, pga. hovedvindretning fra fjorden, over smelteverket mot byen, blir måleresultatene et øvre anslag for bidraget fra smelteverket til konsentrasjonene i Mosjøen over hele året.
NILU
2025
Methane emissions from the Nord Stream subsea pipeline leaks
The amount of methane released to the atmosphere from the Nord Stream subsea pipeline leaks remains uncertain, as reflected in a wide range of estimates1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18. A lack of information regarding the temporal variation in atmospheric emissions has made it challenging to reconcile pipeline volumetric (bottom-up) estimates1,2,3,4,5,6,7,8 with measurement-based (top-down) estimates8,9,10,11,12,13,14,15,16,17,18. Here we simulate pipeline rupture emission rates and integrate these with methane dissolution and sea-surface outgassing estimates9,10 to model the evolution of atmospheric emissions from the leaks. We verify our modelled atmospheric emissions by comparing them with top-down point-in-time emission-rate estimates and cumulative emission estimates derived from airborne11, satellite8,12,13,14 and tall tower data. We obtain consistency between our modelled atmospheric emissions and top-down estimates and find that 465 ± 20 thousand metric tons of methane were emitted to the atmosphere. Although, to our knowledge, this represents the largest recorded amount of methane released from a single transient event, it is equivalent to 0.1% of anthropogenic methane emissions for 2022. The impact of the leaks on the global atmospheric methane budget brings into focus the numerous other anthropogenic methane sources that require mitigation globally. Our analysis demonstrates that diverse, complementary measurement approaches are needed to quantify methane emissions in support of the Global Methane Pledge19.
2025