Found 9854 publications. Showing page 346 of 395:
2022
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
2022
Herring gulls (Larus argentatus) are opportunistic feeders, resulting in contaminant exposure depending on area and habitat. We compared contaminant concentrations and dietary markers between two herring gull breeding colonies with different distances to extensive human activity and presumed contaminant exposure from the local marine diet. Furthermore, we investigated the integrity of DNA in white blood cells and sensitivity to oxidative stress. We analyzed blood from 15 herring gulls from each colony—the urban Oslofjord near the Norwegian capital Oslo in the temperate region and the remote Hornøya island in northern Norway, on the Barents Sea coast. Based on d13C and d34S, the dietary sources of urban gulls differed, with some individuals having a marine and others a more terrestrial dietary signal. All remote gulls had a marine dietary signal and higher relative trophic level than the urban marine feeding gulls. Concentrations (mean ± standard deviation [SD]) of most persistent organic pollutants, such as polychlorinated biphenyl ethers (PCBs) and perfluorooctane sulfonic acid (PFOS), were higher in urban marine (PCB153 17 ± 17 ng/g wet weight, PFOS 25 ± 21 ng/g wet wt) than urban terrestrial feeders (PCB153 3.7 ± 2.4 ng/g wet wt, PFOS 6.7 ± 10 ng/g wet wt). Despite feeding at a higher trophic level (d15N), the remote gulls (PCB153 17 ± 1221 ng/g wet wt, PFOS 19 ± 1421 ng/g wet wt) were similar to the urban marine feeders. Cyclic volatile methyl siloxanes were detected in only a few gulls, except for decamethylcyclopentasiloxane in the urban colony, which was found in 12 of 13 gulls. Only hexachlorobenzene was present in higher concentrations in the remote (2.6 ± 0.42 ng/g wet wt) compared with the urban colony (0.34 ± 0.33 ng/g wet wt). Baseline and induced DNA damage (doublestreak breaks) was higher in urban than in remote gulls for both terrestrial and marine feeders.
Pergamon Press
2022
An actionable annotation scoring framework for gas chromatography-high-resolution mass spectrometry
Omics-based technologies have enabled comprehensive characterization of our exposure to environmental chemicals (chemical exposome) as well as assessment of the corresponding biological responses at the molecular level (eg, metabolome, lipidome, proteome, and genome). By systematically measuring personal exposures and linking these stimuli to biological perturbations, researchers can determine specific chemical exposures of concern, identify mechanisms and biomarkers of toxicity, and design interventions to reduce exposures. However, further advancement of metabolomics and exposomics approaches is limited by a lack of standardization and approaches for assigning confidence to chemical annotations. While a wealth of chemical data is generated by gas chromatography high-resolution mass spectrometry (GC-HRMS), incorporating GC-HRMS data into an annotation framework and communicating confidence in these assignments is challenging. It is essential to be able to compare chemical data for exposomics studies across platforms to build upon prior knowledge and advance the technology. Here, we discuss the major pieces of evidence provided by common GC-HRMS workflows, including retention time and retention index, electron ionization, positive chemical ionization, electron capture negative ionization, and atmospheric pressure chemical ionization spectral matching, molecular ion, accurate mass, isotopic patterns, database occurrence, and occurrence in blanks. We then provide a qualitative framework for incorporating these various lines of evidence for communicating confidence in GC-HRMS data by adapting the Schymanski scoring schema developed for reporting confidence levels by liquid chromatography HRMS (LC-HRMS). Validation of our framework is presented using standards spiked in plasma, and confident annotations in outdoor and indoor air samples, showing a false-positive rate of 12% for suspect screening for chemical identifications assigned as Level 2 (when structurally similar isomers are not considered false positives). This framework is easily adaptable to various workflows and provides a concise means to communicate confidence in annotations. Further validation, refinements, and adoption of this framework will ideally lead to harmonization across the field, helping to improve the quality and interpretability of compound annotations obtained in GC-HRMS.
Oxford University Press
2022
Beregning av korrosjonsklasse fra miljøparametere i Fitjar. Lokasjon (59°56’11.5″N 5°19’58.4″Ø)
Korrosjonsklasse ble beregnet på lokasjon (59°56'11.5"N 5°19'58.4"Ø) i Fitjar, Vestland, Norge, fra årsgjennomsnitt for miljøparametere etter ISO 9223 og ISO 12944-2. Det ble funnet at korrosjonsklassen med høy sannsynlighet er C3 og at dette i hovedsak er bestemt av våt-tiden på omtrent 4500 timer/år, som gjennomsnitt i perioden 2007-2022. Dette er godt innenfor grensene for C3 når saltavsetningen er < 60 mg Cl-/m2døgn og SO2 konsentrasjonen i luft < 30 µg/m3. Disse betingelsene synes med stor sannsynlighet oppfylt på lokasjonen i Fitjar som årsgjennomsnitt i normalår.
NILU
2022
2022
Microplastics in Norwegian coastal areas, rivers, lakes and air (MIKRONOR1)
Norsk institutt for vannforskning
2022
Monitoring atmospheric composition and deposition in Norway
The Norwegian monitoring programme is set up to meet national and international obligations and needs for measurement data with a long-term commitment. The data are important for compliance monitoring as well as input for effect studies. The monitoring of atmospheric composition and deposition are organised under national programmes mainly funded by the Norwegian Environment Agency in addition to some direct support from the Ministry of Climate and Environment. NILU – Norwegian Institute for Air Research is responsible for the daily operation and reporting of the results from this monitoring. The monitoring aim to fulfil several inter-connected purposes and is divided in four main programmes: transboundary fluxes, contaminants, climate change and the ozone layer. In addition, regularly moss surveys are conducted to assess atmospheric deposition of pollutants such as heavy metals.
NILU
2022
The modified Target Diagram (MTD) was developed to evaluate the performance of low-cost sensors (LCS) for air quality monitoring in comparison with reference methods by reporting relative expanded uncertainty and its contributors. An MTD provides several pieces of information, including compliance with regulation, sources of error and how to diminish them, completeness and validity of LCS calibration etc. It allows the user to examine the effect of selecting different regression types and residual fitting on the LCS measurement uncertainty. The ordinary least squared regression with fitted residuals and dynamic between reference analyser uncertainty rather than constant ones yielded more realistic LCS measurement uncertainty compared to other options. The MTD is a fast visual tool to extract several pieces of information on evaluation of any candidate method against reference method.
Elsevier
2022
Screening Programme 2020, Part 1 and 2: Plastic Additives and REACH Compounds
I screening 2020 gjennomført av Norsk institutt for vannforskning (NIVA) og NILU-Norsk institutt for luftforskning i fellesskap ble det satt søkelys på forekomst og mulige miljøproblemer av 160 kjemikalier. Forbindelser som er valgt ut til Screening 2020 inkluderer tilsetningsstoffer til plast og nylig registrerte stoffer i REACH registeret.
Norsk institutt for vannforskning
2022
Mercury in air and soil on an urban-rural transect in East Africa
There are large knowledge gaps concerning concentrations, sources, emissions, and spatial trends of mercury (Hg) in the atmosphere in developing regions of the Southern Hemisphere, particularly in urban areas. Filling these gaps is a prerequisite for assessing the effectiveness of international regulation and for enabling a better understanding of the global transport of Hg in the environment. Here we use a passive sampling technique to study the spatial distribution of gaseous elemental Hg (Hg(0), GEM) and assess emission sources in and around Dar es Salaam, Tanzania's largest city. Included in the study were the city's main municipal waste dumpsite and an e-waste processing facility as potential sources of GEM. To complement the GEM data and for a better overview of the Hg contamination status of Dar es Salaam, soil samples were collected from the same locations where passive air samplers were deployed and analysed for total Hg. Overall, GEM concentrations ranged between <0.86 and 5.34 ng m−3, indicating significant local sources within the urban area. The municipal waste dumpsite and e-waste site had GEM concentrations elevated above the background, at 2.41 and 1.77 ng m−3, respectively. Hg concentrations in soil in the region (range 0.0067 to 0.098 mg kg−1) were low compared to those of other urban areas and were not correlated with atmospheric GEM concentrations. This study demonstrates that GEM is a significant environmental issue in the urban region of Dar es Salaam. Further studies from urban areas in the Global South are needed to better identify sources of GEM.
Royal Society of Chemistry (RSC)
2022
Potential environmental impact of bromoform from Asparagopsis farming in Australia
To mitigate the rumen enteric methane (CH4) produced by ruminant livestock, Asparagopsis taxiformis is proposed as an additive to ruminant feed. During the cultivation of Asparagopsis taxiformis in the sea or in terrestrially based systems, this macroalgae, like most seaweeds and phytoplankton, produces a large amount of bromoform (CHBr3), which contributes to ozone depletion once released into the atmosphere. In this study, we focus on the impact of CHBr3 on the stratospheric ozone layer resulting from potential emissions from proposed Asparagopsis cultivation in Australia. The impact is assessed by weighting the emissions of CHBr3 with its ozone depletion potential (ODP), which is traditionally defined for long-lived halocarbons but has also been applied to very short-lived substances (VSLSs). An annual yield of ∼3.5 × 104 Mg dry weight is required to meet the needs of 50 % of the beef feedlot and dairy cattle in Australia. Our study shows that the intensity and impact of CHBr3 emissions vary, depending on location and cultivation scenarios. Of the proposed locations, tropical farms near the Darwin region are associated with the largest CHBr3 ODP values. However, farming of Asparagopsis using either ocean or terrestrial cultivation systems at any of the proposed locations does not have the potential to significantly impact the ozone layer. Even if all Asparagopsis farming were performed in Darwin, the CHBr3 emitted into the atmosphere would amount to less than 0.02 % of the global ODP-weighted emissions. The impact of remaining farming scenarios is also relatively small even if the intended annual yield in Darwin is scaled by a factor of 30 to meet the global requirements, which will increase the global ODP-weighted emissions up to ∼0.5 %.
2022
Condensable primary organic aerosol (CPOA) emissions are a class of organic compounds that are vapour phase at stack conditions, but which can undergo both condensation and evaporation processes as the stack air is cooled and diluted upon discharge into ambient air. Emission factors may misrepresent, and even miss, the amount of particulate matter (PM) or gas that actually enters the atmosphere, depending on the emission measurement techniques used. In the current emission reporting to EMEP/CLRTAP there is no clear definition of whether condensable organics are included or not, and, if included, to what extent.
In this study, new residential combustion emission estimates have been made for the years 2005-2019 (called TNO Ref2_v2.1) in a consistent manner, with improved estimation of fuel consumption (in particular wood) and emission factors, as well as an updated split of fuel use over different appliances and technologies. For these two elements, data were taken primarily from the Eurostat fuel statistics and the IIASA GAINS model. Three scenarios have been defined: a “typical” case, which is our best estimate, an alternative “ideal” case which excludes the impact of “bad combustion”, and a “high EF” scenario in which higher emission factors are assumed than in the typical scenario. Total emissions in the typical scenario are around 40% higher than in the ideal case (in 2019), whereas resulting emissions in the “high EF” scenario are around 90% higher than in the typical scenario.
The Ref2_v2.1 inventory was used in a series of modelling studies which aimed to assess the importance of condensable organics for current air quality, for trends over time (2010–2019), and for source-receptor calculations.
Including condensables in a consistent way for all countries gave model results (concentrations, trends and bias) in better agreement with observations for OC and PM2.5 than when using the EMEP emissions which have condensables for some countries but not others. However, the model results were sensitive to the choice of Ref2_v2.1 scenario, and also to the assumptions concerning volatility of the CPOA emissions, and assumptions about extra intermediate-volatility volatile organic compounds (IVOC) associated with such emissions.
No single setup performed best for each site. There are many factors that can contribute to such mixed results (activity data, emissions factors, assumed combustion conditions, large and small scale spatial distributions issues in emissions, dispersion and CPOA/IVOC assumptions in the modelling), and much further work (and with other observational data-sets) will be needed to disentangle the reasons for model-measurement discrepancies, and to draw conclusions on how realistic the new emissions are.
Assumptions about volatility seem to be important for both the country-to-itself contribution, and for impacts of each country on others. In the few cases investigated so far, assuming inert CPOA provides results which generally lie within the range of the more complex VBS scenarios. Given the many uncertainties associated with the emissions and the modelling of POA and SOA, these results indicates that the inert CPOA assumptions provide a reasonable first approach for handling POA emissions, which can hopefully be improved once our understanding of the sources and processing of these compounds improves.
The new emission data-base, combined with increasing availability of measurements of organic and other components, should provide the best available basis for future improvements in both the emission inventories and model formulations. Much analysis and further tests remain, both with the other model setups, and ideally with alternative secondary organic aerosol schemes to get a better idea of the sensitivity of the results to the various assumptions concerning both emissions and atmospheric processing of POA.
Nordic Council of Ministers
2022
2022
Air pollution involves multiple health and economic challenges. Its accurate and low-cost monitoring is important for developing services dedicated to reduce the exposure of living beings to the pollution. Particulate matter (PM) measurement sensors belong to the key components that support operation of these systems. In this work, a modular, mobile Internet of Things sensor for PM measurements has been proposed. Due to a limited accuracy of the PM detector, the measurement data are refined using a two-stage procedure that involves elimination of the non-physical signal spikes followed by a non-linear correction of the responses using a multiplicative surrogate model. The correction layer is derived from the sparse and non-uniform calibration data, i.e., a combination of the measurements from the PM monitoring station and the sensor obtained in the same location over a specified (relatively short) interval. The device and the method have been both demonstrated based on the data obtained during three measurement campaigns. The proposed correction scheme improves the fidelity of PM measurements by around two orders of magnitude w.r.t. the responses for which the post-processing has not been considered. Performance of the proposed surrogate-assisted technique has been favorably compared against the benchmark approaches from the literature.
2022