Found 9990 publications. Showing page 15 of 400:
2024
2024
Fine particulate matter (PM2.5) is a key air quality indicator due to its adverse health impacts. Accurate PM2.5 assessment requires high-resolution (e.g., atleast 1 km) daily data, yet current methods face challenges in balancing accuracy, coverage, and resolution. Chemical transport models such as those from the Copernicus Atmosphere Monitoring Service (CAMS) offer continuous data but their relatively coarse resolution can introduce uncertainties. Here we present a synergistic Machine Learning (ML)-based approach called S-MESH (Satellite and ML-based Estimation of Surface air quality at High resolution) for estimating daily surface PM2.5 over Europe at 1 km spatial resolution and demonstrate its performance for the years 2021 and 2022. The approach enhances and downscales the CAMS regional ensemble 24 h PM2.5 forecast by training a stacked XGBoost model against station observations, effectively integrating satellite-derived data and modeled meteorological variables. Overall, against station observations, S-MESH (mean absolute error (MAE) of 3.54 μg/m3) shows higher accuracy than the CAMS forecast (MAE of 4.18 μg/m3) and is approaching the accuracy of the CAMS regional interim reanalysis (MAE of 3.21 μg/m3), while exhibiting a significantly reduced mean bias (MB of −0.3 μg/m3 vs. −1.5 μg/m3 for the reanalysis). At the same time, S-MESH requires substantially less computational resources and processing time. At concentrations >20 μg/m3, S-MESH outperforms the reanalysis (MB of −7.3 μg/m3 and -10.3 μg/m3 respectively), and reliably captures high pollution events in both space and time. In the eastern study area, where the reanalysis often underestimates, S-MESH better captures high levels of PM2.5 mostly from residential heating. S-MESH effectively tracks day-to-day variability, with a temporal relative absolute error of 5% (reanalysis 10%). Exhibiting good performance at high pollution events coupled with its high spatial resolution and rapid estimation speed, S-MESH can be highly relevant for air quality assessments where both resolution and timeliness are critical.
2024
Environmental pollutants in the terrestrial and urban environment 2023
Samples from the urban terrestrial environment in the Oslo area were analysed for metals and a large number of organic environmental pollutants. The selected samples that were analysed were soil, earthworm, fieldfare egg, brown rat liver, roe deer liver, vegetation, honeybee, and Spanish slug. Biomagnification potential was estimated based on detected data for relevant predator-prey pairs.
NILU
2024
2024
We analyzed long-term measurements of organic carbon, elemental carbon, and source-specific organic tracers from 2017 to 2020 to constrain carbonaceous aerosol sources in the rapidly changing Arctic. Additionally, we used absorption photometer (Aethalometer) measurements to constrain equivalent black carbon (eBC) from biomass burning and fossil fuel combustion, using positive matrix factorization (PMF).
Our analysis shows that organic tracers are essential for understanding Arctic carbonaceous aerosol sources. Throughout 2017 to 2020, levoglucosan exhibited bimodal seasonality, reflecting emissions from residential wood combustion (RWC) in the heating season (November to May) and from wildfires (WFs) in the non-heating season (June to October), demonstrating a pronounced interannual variability in the influence of WF. Biogenic secondary organic aerosol (BSOA) species (2-methyltetrols) from isoprene oxidation was only present in the non-heating season, peaking in July to August. Warm air masses from Siberia led to a substantial increase in 2-methyltetrols in 2019 and 2020 compared to 2017 to 2018. This highlights the need to investigate the contribution of local sources vs. long-range atmospheric transport (LRT), considering the temperature sensitivity of biogenic volatile organic compound emissions from Arctic vegetation. Tracers of primary biological aerosol particles (PBAPs), including various sugars and sugar alcohols, showed elevated levels in the non-heating season, although with different seasonal trends, whereas cellulose had no apparent seasonality. Most PBAP tracers and 2-methyltetrols peaked during influence of WF emissions, highlighting the importance of measuring a range of source-specific tracers to understand sources and dynamics of carbonaceous aerosol. The seasonality of carbonaceous aerosol was strongly influenced by LRT episodes, as background levels are extremely low. In the non-heating season, the organic aerosol peak was as influenced by LRT, as was elemental carbon during the Arctic haze period.
Source apportionment of carbonaceous aerosol by Latin hypercube sampling showed mixed contributions from RWC (46 %), fossil fuel (FF) sources (27 %), and BSOA (25 %) in the heating season. In contrast, the non-heating season was dominated by BSOA (56 %), with lower contributions from WF (26 %) and FF sources (15 %).
Source apportionment of eBC by PMF showed that FF combustion dominated eBC (70±2.7 %), whereas RWC (22±2.7 %) was more abundant than WF (8.0±2.9 %). Modeled BC concentrations from FLEXPART (FLEXible PARTicle dispersion model) attributed an almost equal share to FF sources (51±3.1 %) and to biomass burning. Both FLEXPART and the PMF analysis concluded that RWC is a more important source of (e)BC than WF. However, with a modeled RWC contribution of 30±4.1 % and WF of 19±2.8 %, FLEXPART suggests relatively higher contributions to eBC from these sources. Notably, the BB fraction of EC was twice as high as that of eBC, reflecting methodological differences between source apportionment by LHS and PMF. However, important conclusions drawn are unaffected, as both methods indicate the presence of RWC- and WF-sourced BC at Zeppelin, with a higher relative BB contribution during the non-heating season.
In summary, organic aerosol (281±106 ng m−3) constitutes a significant fraction of Arctic PM10, although surpassed by sea salt aerosol (682±46.9 ng m−3), mineral dust (613±368 ng m−3), and typically non-sea-salt sulfate SO (314±62.6 ng m−3), originating mainly from anthropogenic sources in winter and from natural sources in summer.
2024
2024
2024
Monitoring of the atmospheric ozone layer and natural ultraviolet radiation. Annual Report 2023
This report summarizes the results from the Norwegian monitoring programme on stratospheric ozone and UV radiation measurements. The ozone layer has been measured at three locations since 1979: In Oslo/Kjeller, Tromsø/Andøya and Ny-Ålesund. The UV measurements started in 1995. The results show that there was a significant decrease in stratospheric ozone above Norway between 1979 and 1997. After that, the ozone layer stabilized at a level ~2% below pre-1980 level. The year 2023 was characterized by low ozone values in winter, high spring values, and annual average total ozone values slightly below the long-term mean.
NILU
2024
There are sparse opportunities for direct measurement of upper stratospheric winds, yet improving their representation in subseasonal-to-seasonal prediction models can have significant benefits. There is solid evidence from previous research that global atmospheric infrasound waves are sensitive to stratospheric dynamics. However, there is a lack of results providing a direct mapping between infrasound recordings and polar-cap upper stratospheric winds. The global International Monitoring System (IMS), which monitors compliance with the Comprehensive Nuclear-Test-Ban Treaty, includes ground-based stations that can be used to characterize the infrasound soundscape continuously. In this study, multi-station IMS infrasound data were utilized along with a machine-learning supported stochastic model, Delay-SDE-net, to demonstrate how a near-real-time estimate of the polar-cap averaged zonal wind at 1-hPa pressure level can be found from infrasound data. The infrasound was filtered to a temporal low-frequency regime dominated by microbaroms, which are ambient-noise infrasonic waves continuously radiated into the atmosphere from nonlinear interaction between counter-propagating ocean surface waves. Delay-SDE-net was trained on 5 years (2014–2018) of infrasound data from three stations and the ERA5 reanalysis 1-hPa polar-cap averaged zonal wind. Using infrasound in 2019–2020 for validation, we demonstrate a prediction of the polar-cap averaged zonal wind, with an error standard deviation of around 12 m·s compared with ERA5. These findings highlight the potential of using infrasound data for near-real-time measurements of upper stratospheric dynamics. A long-term goal is to improve high-top atmospheric model accuracy, which can have significant implications for weather and climate prediction.
2024
2024
A machine learning algorithm combined with measurements obtained by a NILU-UV irradiance meter enables the determination of total ozone column (TOC) amount and cloud optical depth (COD). In the New York City area, a NILU-UV instrument on the rooftop of a Stevens Institute of Technology building (40.74° N, −74.03° E) has been used to collect data for several years. Inspired by a previous study [Opt. Express 22, 19595 (2014)], this research presents an updated neural-network-based method for TOC and COD retrievals. This method provides reliable results under heavy cloud conditions, and a convenient algorithm for the simultaneous retrieval of TOC and COD values. The TOC values are presented for 2014–2023, and both were compared with results obtained using the look-up table (LUT) method and measurements by the Ozone Monitoring Instrument (OMI), deployed on NASA’s AURA satellite. COD results are also provided.
2024
Whereas inhalation exposure to organic contaminants can negatively impact human health, knowledge of their spatial variability in the ambient atmosphere remains limited. We analyzed the extracts of passive air samplers deployed at 119 unique sites in Southern Canada between 2019 and 2022 for 353 organic vapors. Hierarchical clustering of the obtained data set revealed four archetypes of spatial concentration variability in the outdoor atmosphere, which are indicative of common sources and similar atmospheric dispersion behavior. “Point Source” signatures are characterized by elevated concentration in the vicinity of major release locations. A “Population” signature applies to compounds whose air concentrations are highly correlated with population density, and is associated with emissions from consumer products. The “Water Source” signature applies to substances with elevated levels in the vicinity of water bodies from which they evaporate. Another group of compounds displays a “Uniform” signature, indicative of a lack of major sources within the study area. We illustrate how such a data set, and the derived spatial patterns, can be applied to support the identification of sources, the quantification of atmospheric emissions, the modeling of air quality, and the investigation of potential inequities in inhalation exposure.
2024
Monitoring of greenhouse gases and aerosols at Svalbard and Birkenes in 2023. Annual report
This annual report for 2023 summarizes the activities and results of the greenhouse gas monitoring at the Zeppelin Observatory, situated on Svalbard, during the period 2001-2023, and the greenhouse gas monitoring and aerosol observations from Birkenes for 2009-2023.
NILU
2024
2024