Fant 10351 publikasjoner. Viser side 356 av 415:
2023
This paper examines the creation of fine resolution maps at 100 m x 100 m resolution using statistical downscaling for the area of Prague, as a case study. This Czech city was selected due to the fine resolution proxy data available for this city. The reference downscaling methodology used is the linear regression and the interpolation of its residuals by the area-to-point kriging. Next to this, several other methods of statistical downscaling have been also executed. The results of different downscaling methods have been compared mutually and against the data from the monitoring stations of Prague, separately for urban background and traffic areas.
The downscaled maps in 100 m x 100 m resolution have been constructed for the area of Prague for three pollutants, namely for NO2, PM10 and PM2.5. Several methods of the statistical downscaling have been compared mutually and against the data from the monitoring stations. In general, the best results are given by the linear regression and the interpolation of its residuals, either by the area-to-point kriging or the bilinear interpolation. In the maps, one can see overall realistic spatial patterns, the main roads in Prague are visible through higher air pollution levels. This is distinct especially for NO2, while for PM10 and PM2.5 the differences between road increments and urban background are smaller as would be expected. The results of the case study for Prague have proven the usefulness of the statistical downscaling for the air quality mapping, especially for NO2. In addition, the population exposure estimates based on the downscaled mapping results have been also calculated.
ETC/HE
2023
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2023
2023
2023
Accurate Lightweight Calibration Methods for Mobile Low-Cost Particulate Matter Sensors
Monitoring air pollution is a critical step towards improving public health, particularly when it comes to identifying the primary air pollutants that can have an impact on human health. Among these pollutants, particulate matter (PM) with a diameter of up to 2.5 μm (or PM2.5) is of particular concern, making it important to continuously and accurately monitor pollution related to PM. The emergence of mobile low-cost PM sensors has made it possible to monitor PM levels continuously in a greater number of locations. However, the accuracy of mobile low-cost PM sensors is often questionable as it depends on geographical factors such as local atmospheric conditions. <p>This paper presents new calibration methods for mobile low-cost PM sensors that can correct inaccurate measurements from the sensors in real-time. Our new methods leverage Neural Architecture Search (NAS) to improve the accuracy and efficiency of calibration models for mobile low-cost PM sensors. The experimental evaluation shows that the new methods reduce accuracy error by more than 26% compared with the state-of-the-art methods. Moreover, the new methods are lightweight, taking less than 2.5 ms to correct each PM measurement on Intel Neural Compute Stick 2, an AI-accelerator for edge devices deployed in air pollution monitoring platforms.
2023
In order to measure progress towards the aims outlined by the United Nations (UN) 2030 Agenda, data are needed for the different indicators that are linked to each UN Sustainable Development Goal (SDG). Where statistical or scientific data are not sufficient or available, alternative data sources, such as data from citizen science (CS) activities, could be used.
Statistics Norway, together with the Norwegian Association of Local and Regional Authorities, have developed a taxonomy for classifying indicators that are intended to measure the SDGs. The purpose of this taxonomy is to sort, evaluate, and compare different SDG indicators and to assess their usefulness by identifying their central properties and characteristics. This is done by organizing central characteristics under the three dimensions of Goal, Perspective, and Quality. The taxonomy is designed in a way that can help users to find the right indicators across sectors to measure progress towards the SDGs depending on their own context and strategic priorities. The Norwegian taxonomy also offers new opportunities for the re-use of data collected through CS activities. This paper presents the taxonomy and demonstrates how it can be applied for an indicator based on a CS data set, and we also suggest further use of CS data.
2023
As wild-caught fish become scarce, feed ingredients for farming fish, such as salmon, are increasingly sourced from agricultural plants that depend on mineral fertilizers. Since these fish are naturally carnivorous, they have difficulty digesting the phosphorus in plant-based feed. So additional phosphorus supplements are added to the feed, resulting in a disproportionate increase in mineral phosphorus use and emission. Aquatic food production is increasingly relying on agriculture and mineral phosphorus resources. The feed surplus and the excreta are seldom collected and recycled, leading to a massive loss of nutrients to water bodies and the seafloor, resulting in local risk for eutrophication. Norway currently produces more than half of the world’s Atlantic salmon, and it is set to increase production from currently 1.5 to 5 Mt. in 2050. This has large implications for feed supply and emissions globally. There is a lack of studies that analyze the phosphorus system in aquatic food production at a sufficient spatial and temporal granularity to effectively inform interventions for a more circular use of phosphorus. Here, we present a multi-scale phosphorus flow analysis at monthly resolution ranging between 2005 and 2021 for aquatic food production in Norway and quantitatively discuss the effectiveness of alternative strategies for improving resource efficiency. The results indicate that P emissions from aquaculture have nearly doubled in the period between 2005 and 2021. The P use efficiency (PUE) in Norwegian aquaculture was 19% in 2021. The addition of phytase to the feed could improve the PUE by 8% by reducing P supplements and emissions by 7 kt/y. The use of Integrated Multi-Trophic Aquaculture close to fish farming sites could absorb emissions by 4 kt/y by creating new marine food products. Sludge collection systems could reduce P emissions by 4 to 11 kt/y, depending on the technology. Using the sludge in local agriculture would exacerbate the current P accumulation in soils close to the coastline, given that the animal density in this region is already high. Hence, a large and sophisticated processing infrastructure will be needed to create transportable, high-quality secondary fertilizers for effective sludge recycling in regions with a P deficit.
2023
Skogens helsetilstand i Norge. Resultater fra skogskadeovervåkingen i 2022
Skogens helsetilstand påvirkes i stor grad av klima og værforhold, enten direkte ved tørke, frost og vind, eller indirekte ved at klimaet påvirker omfanget av soppsykdommer og insektangrep. Klimaendringene og den forventede økningen i klimarelaterte skogskader gir store utfordringer for forvaltningen av framtidas skogressurser. Det samme gjør invaderende skadegjørere, både allerede etablerte arter og nye som kan komme til Norge i nær framtid. I denne rapporten presenteres resultater fra skogskadeovervåkingen i Norge i 2022 og trender over tid for følgende temaer:
(i) Landsrepresentativ skogovervåking;
(ii) Intensiv skogovervåking;
(iii) Overvåking av bjørkemålere i Troms og Finnmark;
(iv) Barkbilleovervåkingen;
(v) Furuvednematode;
(vi) Askeskuddsyke;
(vii) Andre spesielle skogskader i 2022.
NIBIO
2023
2023
2023
Utslipp og spredning av støv fra LKAB i Narvik
Denne rapporten presenterer spredningsberegninger som estimerer LKAB sitt bidrag til forurensningssituasjonen i Narvik. Spredningsberegningene er basert på et anslag for det samlede støvutslippet fra både punktkilder og diffuse kilder via målt støvavsetning rundt anlegget. Spredningsberegningene som er utført med partikkelmodellen Flexpart-WRF, viser ingen overskridelse av grenseverdiene for PM10 eller PM2,5 utenfor LKABs industriområde.
NILU
2023
Genotoxic effects of occupational exposure to glass fibres - A human biomonitoring study.
As part of a large human biomonitoring study, we conducted occupational monitoring in a glass fibre factory in Slovakia. Shopfloor workers (n = 80), with a matched group of administrators in the same factory (n = 36), were monitored for exposure to glass fibres and to polycyclic aromatic hydrocarbons (PAHs). The impact of occupational exposure on chromosomal aberrations, DNA damage and DNA repair, immunomodulatory markers, and the role of nutritional and lifestyle factors, as well as the effect of polymorphisms in metabolic and DNA repair genes on genetic stability, were investigated.
The (enzyme-modified) comet assay was employed to measure DNA strand breaks (SBs) and apurinic sites, oxidised and alkylated bases. Antioxidant status was estimated by resistance to H2O2-induced DNA damage. Base excision repair capacity was measured with an in vitro assay (based on the comet assay).
Exposure of workers to fibres was low, but still was associated with higher levels of SBs, and SBs plus oxidised bases, and higher sensitivity to H2O2. Multivariate analysis showed that exposure increased the risk of high levels of SBs by 20%. DNA damage was influenced by antioxidant enzymes catalase and glutathione S-transferase (measured in blood). DNA repair capacity was inversely correlated with DNA damage and positively with antioxidant status. An inverse correlation was found between DNA base oxidation and the percentage of eosinophils (involved in the inflammatory response) in peripheral blood of both exposed and reference groups. Genotypes of XRCC1 variants rs3213245 and rs25487 significantly decreased the risk of high levels of base oxidation, to 0.50 (p = 0.001) and 0.59 (p = 0.001), respectively.
Increases in DNA damage owing to glass fibre exposure were significant but modest, and no increases were seen in chromosome aberrations or micronuclei. However, it is of concern that even low levels of exposure to these fibres can cause significant genetic damage.
2023
Deployment and Evaluation of a Network of Open Low-Cost Air Quality Sensor Systems
Low-cost air quality sensors have the potential to complement the regulatory network of air quality monitoring stations, with respect to increased spatial density of observations, however, their data quality continues to be of concern. Here we report on our experience with a small network of open low-cost sensor systems for air quality, which was deployed in the region of Stavanger, Norway, under Nordic winter conditions. The network consisted of AirSensEUR sensor systems, equipped with sensors for, among others, nitrogen dioxide and fine particulate matter. The systems were co-located at an air quality monitoring station, for a period of approximately six weeks. A subset of the systems was subsequently deployed at various roadside locations for half a year, and finally co-located at the same air quality monitoring station again, for a post-deployment evaluation. For fine particulate matter, the co-location results indicate a good inter-unit consistency, but poor average out-of-the-box performance (R2 = 0.25, RMSE = 9.6 μ
g m−3). While Köhler correction did not significantly improve the accuracy in our study, filtering for high relative humidity conditions improved the results (R2 = 0.63, RMSE = 7.09 μg m−3). For nitrogen dioxide, the inter-unit consistency was found to be excellent, and calibration models were developed which showed good performance during the testing period (on average R2 = 0.98, RMSE = 5.73 μg m−3), however, due to the short training period, the calibration models are likely not able to capture the full annual variability in environmental conditions. A post-deployment co-location showed, respectively, a slight and significant decrease in inter-sensor consistency for fine particulate matter and nitrogen dioxide. We further demonstrate, how observations from even such a small network can be exploited by assimilation in a high-resolution air quality model, thus adding value to both the observations and the model, and ultimately providing a more comprehensive perspective of air quality than is possible from either of the two input datasets alone. Our study provides valuable insights on the operation and performance of an open sensor system for air quality, particularly under challenging Nordic environmental conditions.
2023