Found 2229 publications. Showing page 19 of 223:
Monitoring of the atmospheric ozone layer and natural ultraviolet radiation. Annual report 2021.
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 2021 was characterized by low total ozone values in June and July, whereas “normal” ozone values were measured during winter and spring.
NILU
2022
Tiltaksutredning for lokal luftkvalitet i Levanger. Del 1: Kartlegging.
Tiltaksutredningen for lokal luftkvalitet i Levanger, del 1 Kartlegging, skal gjøre rede for forurensningssituasjonen og mulige tiltak for å redusere nivået av luftforurensning innenfor kravene i forurensningsforskriften. Tiltaksutredningen omfatter en kartlegging med utslipps- og spredningsberegninger for alle relevante kilder til PM10 og PM2,5 i 2017 og 2019. I tillegg er det utført målinger av disse komponentene gjennom hele 2021 ved en målestasjon (Kirkegata) i Levanger sentrum. Basert på resultatene fra kartleggingen, er det foreslått en handlingsplan med fire hovedpunkter som kan bidra til å redusere forurensningsnivåene i Levanger.
NILU
2022
Content and migration of chemical additives from plastic products
NILU has, on behalf of the Norwegian Environment Agency, performed chemical analyses of a selection of additives in plastic products. The goal was to identify content and migration of the chemical additives in and from the products to air and surfaces of the products at room temperature. The plastic products covered extension cord, sockets, flooring, wall papers, upholstery, PC-mouse and PCs. Targeted chemicals were organophosphorous flame retardants (OPFRs), brominated flame retardants (BFRs) including TBBPA, and chlorinated substances. TPHP (triphenyl phosphate) was detected in most sample types, but the highest concentrations were found for TBEP (tris(2-butoxyethyl)phosphate. The highest number of compounds were detected in the PC-mouses and high levels were also found in the surface wipes on PC-mouses. None of the targeted compounds were detected in the air samples.
NILU
2022
FAIRMODE Guidance Document on Modelling Quality Objectives and Benchmarking. Version 3.3.
The development of the procedure for air quality model benchmarking in the context of the Air Quality Directive 2008/50/EC (AQD) has been an on-going activity in the context of the FAIRMODE community, chaired by the JRC. A central part of the studies was the definition of proper modelling quality indicators and criteria to be fulfilled in order to allow sufficient level of quality for a given model application under the AQD. The focus initially on applications related to air quality assessment has gradually been expanded to other applications, such as forecasting and planning. The main purpose of this Guidance Document is to explain and summarise the current concepts of the modelling quality objective methodology, elaborated in various papers and documents in the FAIRMODE community, addressing model applications for air quality assessment and forecast. Other goals of the Document are linked to presentation and explanation of templates for harmonised reporting of modelling results. Giving an overview of still open issues in the implementation of the presented methodology, the document aims at triggering further research and discussions. A core set of statistical indicators is defined using pairs of measurement-modelled data. The core set is the basis for the definition of a modelling quality indicator (MQI) and additional modelling performance indicators (MPI), which take into account the measurement uncertainty. The MQI describes the discrepancy between measurements and modelling results (linked to RMSE), normalised by measurement uncertainty and a scaling factor. The modelling quality objective (MQO) requires MQI to be less than or equal to 1. With an arbitrary selection of the scaling factor of 2, the fulfilment of the MQO means that the allowed deviation between modelled and measured concentrations is twice the measurement uncertainty. Expressions for the MQI calculation based on time series and yearly data are introduced. MPI refer to aspects of correlation, bias and standard deviation, applied to both the spatial and temporal dimensions. Similarly to the MQO for the MQI, modelling performance criteria (MPC) are defined for the MPI; they are necessary, but not sufficient criteria to determine whether the MQO is fulfilled. The MQO is required to be fulfilled at 90% of the stations, a criterion which is implicitly taken into account in the derivation of the MQI. The associated modelling uncertainty is formulated, showing that in case of MQO fulfilment the modelling uncertainty must not exceed 1.75 times the measurement one (with the scaling factor fixed to 2). A reporting template is presented and explained for hourly and yearly average data. In both cases there is a diagram and a table with summary statistics. In a separate section open issues are discussed and an overview of related publications and tools is provided. Finally, a chapter on modelling quality objectives for forecast models is introduced. In Annex 1, we discuss the measurement uncertainty which is expressed in terms of concentration and its associated uncertainty. The methodology for estimating the measurement uncertainty is overviewed and the parameters for its calculation for PM, NO2 and O3 are provided. An expression for the associated modelling uncertainty is also given. This aim of this document is to support modelling groups, local, regional and national authorities in their modelling application, in the context of air quality policy.
Publications Office for the European Union
2022
Information on the origin of pollution is an essential element of air quality management that helps identifying measures to control air pollution. In this document, we review the most widely used source-apportionment (SA) methods for air quality management. The focus is on particulate matter but examples are provided for NO2 as well. Using simple theoretical examples, we explain the differences between these methods and the circumstances where they give different results and thus possibly different conclusions for air quality management. These differences are a consequence of the assumptions that underpin each methodology and determine/limit their range of applicability. We show that ignoring these underlying assumptions is a risk for efficient/successful air quality management when the methods are used outside their scope or range of applicability.
Publications Office for the European Union
2022
Best practices for local and regional air quality management. Version 1.
FAIRMODE is the Forum for Air Quality Modeling created for exchanging experience and results from air quality modeling in the context of the Air Quality Directives (AQD) and for promoting the use of modeling for air quality assessment and management. FAIRMODE is organized in different activities and task, called cross-cutting tasks, to which representative of Member States and experts participate. Among the different activities, one is devoted to Air Quality management practices, called cross-cutting task 5 (CT5). This report is indeed based on the last activities of the FAIRMODE Cross Cutting Task 5 (CT5), focusing, in particular, on elaborating recommendations to support local, regional and national authorities in the use of modelling for the development of air quality plans, defining on how to quantify emission changes associated to a set of measures, and quantifying their impacts in terms of concentration (using an ‘impact pathway approach’ from ‘abatement measure’ to ‘emissions’ to ‘concentrations’). This is done on one side taking advantage of the results already produced by previous FAIRMODE working groups and in coordination with existing activities under other FAIRMODE CTs. On the other side, examples of best practice policies are presented, focusing on Low emission zones: with an example on Antwerp and Copenhagen, Measures on non-exhaust traffic to reduce PM, with an application on Stockholm. How to reduce ozone concentrations, with a focus on local to global contributions. How to build an air quality plan in an integrated way, with an application on Italy. How to evaluate the socio-economic impact of measures, focusing on a case study on UK. The results show how different pollutants should be tackled differently, the importance of integration among different sectoral plans (on emissions, greenhouse gases mitigation, …) and also how other dimensions of the problem (i.e. social aspects) should be considered when building air quality plans.
Publications Office for the European Union
2022
Revidert tiltaksutredning for lokal luftkvalitet i Bergen
Tiltaksutredningen for lokal luftkvalitet i Bergen med handlings- og beredskapsplan skal bidra til at forurensningsnivået holder seg innenfor kravene i forurensningsforskriften. Tiltaksutredningen omfatter en kartlegging av luftkvaliteten i Bergen kommune ved trafikkberegninger og utslipps- og spredningsberegninger for PM10, PM2,5 og NO 2 for Dagens situasjon 2019 og Referansesituasjonen 2030 med eksisterende og eventuelle nye tiltak. Utredningen vurderer effekten som tiltakene har for å overholde krav, men ser også på muligheten for ytterligere reduksjon i henhold til anbefalingene til helsemyndighetene. Basert på resultatene fra beregningene og i samarbeid med oppdragsgiver og referansegruppen, er det foreslått en revidert handlings- og beredskapsplan som skal behandles politisk.
NILU
2022
Beregning av luftkvalitet ved Bjørnheimveien 26
NILU har blitt engasjert av Prem Partners II A/S for å vurdere utbredelse av luftsoner for dagens situasjon og en framtidig situasjon med foreslått boligblokk i Bjørnheimveien 26. Det er anvendt en Gaussisk spredningsmodell for linjekilder (Hiway-2). Når det tas hensyn til at E6 går på bru ved det aktuelle området, viser beregningene et vesentlig lavere konsentrasjonsnivå og dermed mindre utbredelse av rød og gul luftsone på bakkenivå. Videre viser beregningene at skjermingseffekten for eksisterende bebyggelse av en ny bygning er marginal. Dersom de samme forutsetningene om høyde av veg og høyde av terreng legges til grunn, viser beregningene god overenstemmelse med eksisterende luftsonekart.
NILU
2021
This report presents a review of data assimilation methods applicable to air quality. In the introduction, we first describe a brief history of data assimilation method development in the context of numerical weather prediction (NWP), and then we highlight key differences when applying data assimilation methods to air quality prediction from NWP applications. Based on these differences, we outline a set of key requirements for data assimilation when applied to air quality. Following this, we review the available data assimilation algorithms and attempt to identify suitable data assimilation methods that could be applied with air quality models. This review and its findings form the basis of the developments to be carried out in the Urban Data Assimilation Systems project.
NILU
2021