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Top-down approaches, such as atmospheric inversions, are a promising tool for evaluating emission estimates based on activity-data. In particular, there is a need to examine carbon budgets at subnational scales (e.g. state/province), since this is where the climate mitigation policies occur. In this study, the subnational scale anthropogenic CO2 emissions are estimated using a high-resolution global CO2 inverse model. The approach is distinctive with the use of continuous atmospheric measurements from regional/urban networks along with background monitoring data for the period 2015–2019 in global inversion. The measurements from several urban areas of the U.S., Europe and Japan, together with recent high-resolution emission inventories and data-driven flux datasets were utilized to estimate the fossil emissions across the urban areas of the world. By jointly optimizing fossil fuel and natural fluxes, the model is able to contribute additional information to the evaluation of province–scale emissions, provided that sufficient regional network observations are available. The fossil CO2 emission estimates over the U.S. states such as Indiana, Massachusetts, Connecticut, New York, Virginia and Maryland were found to have a reasonable agreement with the Environmental Protection Agency (EPA) inventory, and the model corrects the emissions substantially towards the EPA estimates for California and Indiana. The emission estimates over the United Kingdom, France and Germany are comparable with the regional inventory TNO–CAMS. We evaluated model estimates using independent aircraft observations, while comparison with the CarbonTracker model fluxes confirms ability to represent the biospheric fluxes. This study highlights the potential of the newly developed inverse modeling system to utilize the atmospheric data collected from the regional networks and other observation platforms for further enhancing the ability to perform top-down carbon budget assessment at subnational scales and support the monitoring and mitigation of greenhouse gas emissions.
2023
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2023
2023
2023
Spatial distribution of Dechlorane Plus and dechlorane related compounds in European background air
The highly chlorinated chemical Dechlorane Plus (DP) was introduced as a replacement flame retardant for Mirex, which is banned through the Stockholm Convention (SC) for its toxicity (T), environmental persistence (P), potential for bioaccumulation (B) and long-range environmental transport potential (LRETP). Currently, Dechlorane Plus is under consideration for listing under the Stockholm Convention and by the European Chemical Agency as it is suspected to also have potential for P, B, T and LRET. Knowledge of atmospheric concentrations of chemicals in background regions is vital to understand their persistence and long-range atmospheric transport but such knowledge is still limited for Dechlorane Plus. Also, knowledge on environmental occurrence of the less described Dechlorane Related Compounds (DRCs), with similar properties and uses as Dechlorane Plus, is limited. Hence, the main objective of this study was to carry out a spatial mapping of atmospheric concentrations of Dechlorane Plus and Dechlorane Related Compounds at background sites in Europe. Polyurethane foam passive air samplers were deployed at 99 sites across 33 European countries for 3 months in summer 2016 and analyzed for dechloranes. The study showed that syn- and anti-DP are present across the European continent...
Frontiers Media S.A.
2023
Procellariiform seabirds like northern fulmars (Fulmarus glacialis) are prone to ingest and accumulate floating plastic pieces. In the North Sea region, there is a long tradition to use beached fulmars as biomonitors for marine plastic pollution. Monitoring data revealed consistently lower plastic burdens in adult fulmars compared to younger age classes. Those findings were hypothesized to partly result from parental transfer of plastic to chicks. However, no prior study has examined this mechanism in fulmars by comparing plastic burdens in fledglings and older fulmars shortly after the chick-rearing period. Therefore, we investigated plastic ingestion in 39 fulmars from Kongsfjorden (Svalbard), including 21 fledglings and 18 older fulmars (adults/older immatures). We found that fledglings (50–60 days old) had significantly more plastic than older fulmars. While plastic was found in all fledglings, two older fulmars contained no and several older individuals barely any plastic. These findings supported that fulmar chicks from Svalbard get fed high quantities of plastic by their parents. Adverse effects of plastic on fulmars were indicated by one fragment that perforated the stomach and possibly one thread perforating the intestine. Negative correlations between plastic mass and body fat in fledglings and older fulmars were not significant.
2023
2023
2023
Hazard and exposure assessment of do-it-yourself products forimpregnation
A large number of do-it-yourself impregnation products are marketed to Danish consumers. The products are typically used for re-impregnation of consumer products (e.g. footware and outdoor clothing) immediately after the products have been purchased or when the water and/or dirt-repellent effect begins to diminish.
The Danish Environmental Protection Agency has chosen to make a survey of the market, where 110 do-it-yourself impregnation products were identified within ten different application categories. Out of these products, 14 were included in initial chemical content analyzes, as well as hazard and exposure analyzes. The main components in the majority of the products were saturated hydrocarbons, but some of the products also contained oxygen-containing solvents (e.g. alcohols, ethers, esters or ketones). The potential hazard of 12 of the 14 selected impregnation spray products was performed by measuring acute respiratory toxicity. Of the 12 products tested, 10 inhibited the function of the lung surfactant and may therefore potentially be harmful by inhalation.
On the basis of this study, it could not be demonstrated that the products with PFAS resulted in an inhibition of the lung surfactant at lower doses as compared to products without PFAS; in fact, the lowest inhibitory doses were seen for impregnating agents based on siloxanes/silicones. The results show that the hazardous properties of an impregnation product cannot be determined solely on the basis of the ingredients, and it is therefore necessary to examine the ability of the individual products to inhibit the lung surfactant in connection with a hazard assessment.
Danish Environmental Protection Agency
2023
Impact of 2020 COVID-19 lockdowns on particulate air pollution across Europe
To fight against the first wave of coronavirus disease 2019 (COVID-19) in 2020, lockdown measures were implemented in most European countries. These lockdowns had well-documented effects on human mobility. We assessed the impact of the lockdown implementation and relaxation on air pollution by comparing daily particulate matter (PM), nitrogen dioxide (NO2) and ozone (O3) concentrations, as well as particle number size distributions (PNSDs) and particle light absorption coefficient in situ measurement data, with values that would have been expected if no COVID-19 epidemic had occurred at 28 sites across Europe for the period 17 February–31 May 2020. Expected PM, NO2 and O3 concentrations were calculated from the 2020 Copernicus Atmosphere Monitoring Service (CAMS) ensemble forecasts, combined with 2019 CAMS ensemble forecasts and measurement data. On average, lockdown implementations did not lead to a decrease in PM2.5 mass concentrations at urban sites, while relaxations resulted in a +26 ± 21 % rebound. The impacts of lockdown implementation and relaxation on NO2 concentrations were more consistent (−29 ± 17 and +31 ± 30 %, respectively). The implementation of the lockdown measures also induced statistically significant increases in O3 concentrations at half of all sites (+13 % on average). An enhanced oxidising capacity of the atmosphere could have boosted the production of secondary aerosol at those places. By comparison with 2017–2019 measurement data, a significant change in the relative contributions of wood and fossil fuel burning to the concentration of black carbon during the lockdown was detected at 7 out of 14 sites. The contribution of particles smaller than 70 nm to the total number of particles significantly also changed at most of the urban sites, with a mean decrease of −7 ± 5 % coinciding with the lockdown implementation. Our study shows that the response of PM2.5 and PM10 mass concentrations to lockdown measures was not systematic at various sites across Europe for multiple reasons, the relationship between road traffic intensity and particulate air pollution being more complex than expected.
2023
An increasing number of organisms from the polar regions are reported contaminated by plastic. Rarely a non-killing sampling method is used. In this study we wanted to assess plastic levels using stomach flushing and evaluate the method suitability for further research and monitoring. The stomach of 22 fulmars from Bjørnøya, Svalbard, were flushed with water in the field. On return to the laboratory, the regurgitated content was digested using potassium hydroxide. The extracted plastics were visually characterised and analysed with spectroscopy. Only three birds had plastics in their stomach, totaling 36 particles, most of them microplastics (< 5 mm). The plastic burdens are much lower than previously reported in Svalbard. The stomach flushing is assumed not to allow the collection of the gizzard content. This is a major limitation as most of the plastics accumulate in the fulmar's gizzard. However, the method is still useful for studies investigating plastic ingestion dynamics, allowing to sample the same individuals over time.
Elsevier
2023
Forskere har kartlagt hvor i verden landbruk fortrenger biologisk mangfold
Norges forskningsråd
2023
Decreasing trends of ammonia emissions over Europe seen from remote sensing and inverse modelling
Ammonia (NH3), a significant precursor of particulate matter, affects not only biodiversity, ecosystems, and soil acidification but also climate and human health. In addition, its concentrations are constantly rising due to increasing feeding needs and the large use of fertilization and animal farming. Despite the significance of ammonia, its emissions are associated with large uncertainties, while its atmospheric abundance is difficult to measure. Nowadays, satellite products can effectively measure ammonia with low uncertainty and a global coverage. Here, we use satellite observations of column ammonia in combination with an inversion algorithm to derive ammonia emissions with a high resolution over Europe for the period 2013–2020. Ammonia emissions peak in northern Europe due to agricultural application and livestock management, in western Europe (industrial activity), and over Spain (pig farming). Emissions have decreased by −26 % since 2013 (from 5431 Gg in 2013 to 3994 Gg in 2020), showing that the abatement strategies adopted by the European Union have been very efficient. The slight increase (+4.4 %) in 2015 is also reproduced here and is attributed to some European countries exceeding annual emission targets. Ammonia emissions are low in winter (286 Gg) and peak in summer (563 Gg) and are dominated by the temperature-dependent volatilization of ammonia from the soil. The largest emission decreases were observed in central and eastern Europe (−38 %) and in western Europe (−37 %), while smaller decreases were recorded in northern (−17 %) and southern Europe (−7.6 %). When complemented with ground observations, modelled concentrations using the posterior emissions showed improved statistics, also following the observed seasonal trends. The posterior emissions presented here also agree well with respective estimates reported in the literature and inferred from bottom-up and top-down methodologies. These results indicate that satellite measurements combined with inverse algorithms constitute a robust tool for emission estimates and can infer the evolution of ammonia emissions over large timescales.
2023
PM2.5 Retrieval Using Aerosol Optical Depth, Meteorological Variables, and Artificial Intelligence
Particulate matter (PM) is one of the major air pollutants that has adverse impacts on human health. The aim of this study is to present an alternative approach for retrieving fine PM (particles with an aerodynamic diameter less than 2.5 μm, PM2.5) using artificial intelligence. Ground-based instruments, including a hand-held Microtops II sun photometer (for aerosol optical depth), a PurpleAir sensor (for PM2.5), and Rotronic sensors (for temperature and relative humidity), are used for the machine learning algorithm training. The retrieved PM2.5 reveals an adequate performance with an error of 0.08 μg m−3 and a Pearson correlation coefficient of 0.84.
2023
The AirGAM 2022r1 air quality trend and prediction model
This paper presents the AirGAM 2022r1 model – an air quality trend and prediction model developed at the Norwegian Institute for Air Research (NILU) in cooperation with the European Environment Agency (EEA) over 2017–2021. AirGAM is based on nonlinear regression GAMs – generalised additive models – capable of estimating trends in daily measured pollutant concentrations at air quality monitoring stations, discounting for the effects of trends and time variations in corresponding meteorological data. The model has been developed primarily for the compounds NO2, O3, PM10, and PM2.5. Meteorological input data consist of temperature, wind speed and direction, planetary boundary layer height, relative and absolute humidity, cloud cover, and precipitation over the period considered. The exact set of meteorological variables used in the model depends on the compound selected for analysis. In addition to meteorological variables introduced in the model as covariates, i.e. explanatory variables for the concentration levels, the model also incorporates time variables such as the day of the week, day of the year, and overall time, which is related to the model's trend term. The trend analysis is performed at each station separately. Thus, the model only considers the temporal features of concentrations and meteorology at a station, rather than any spatial correlations or dependencies between stations. AirGAM is implemented using the R language for statistical computing and, in particular, the GAM package mgcv. In the model, meteorological and time covariates are represented and estimated as smooth nonlinear functions of the corresponding variables. Thus, the trend term is defined and estimated as a smooth nonlinear function of time over the period selected for analysis. Once fitted to training data, the model may be used as a prediction tool capable of predicting air pollutant concentrations for new sets of meteorological and time data which are not in the training set – e.g. for cross-validation or forecasting purposes. The model does not explicitly use emissions or background concentrations – these are sought to be implicitly represented through the estimated nonlinear relations between meteorology, time, and concentrations. In addition to meteorology-adjusted trends, the program also produces unadjusted trends – i.e. trends based on the same regression set-up but only including the time covariates. Both types of trends can be output in the same run, making it possible to compare them. Ideally, the meteorology-adjusted trend will show the trend in concentration mainly due to changes in emissions or physicochemical processes not induced by changes in meteorology. AirGAM has been developed and tested primarily in trend studies based on measurement data hosted by the EEA, including the AirBase data (before 2013) and the Air Quality e-Reporting (AQER) data from 2013 and onwards. Still, the model is general and could be applied in other regions with other input data. The EEA data provide daily or hourly surface measurements at individual monitoring stations in Europe. For input meteorological data, we extract time series from the gridded meteorological re-analysis (ERA5) provided by the European Centre for Medium-Range Weather Forecasts (ECMWF) for each monitoring station. The paper presents results with the model for all AirBase/AQER stations in Europe from the latest EEA trend study for 2005–2019.
2023
The report provides the annual update of the European air quality concentration maps and population exposure estimates for human health related indicators of pollutants PM10 (annual average, 90.4 percentile of daily means), PM2.5 (annual average), ozone (93.2 percentile of maximum daily 8-hour means, SOMO35, SOMO10), NO2 (annual average) and benzo(a)pyrene (annual average), and vegetation related ozone indicators (AOT40 for vegetation and for forests) for the year 2020. The report contains also Phytotoxic ozone dose (POD) for wheat, potato and tomato maps and NOx annual average map for 2020. The benzo(a)pyrene map is presented for the first time in this regular mapping report. The trends in exposure estimates in the period 2005–2020 are summarized. The analysis for 2020 is based on the interpolation of the annual statistics of the 2020 observational data reported by the EEA member and cooperating countries and other voluntary reporting countries and stored in the Air Quality e-reporting database, complemented, when needed, with measurements from additional sources. The mapping method is the Regression – Interpolation – Merging Mapping (RIMM). It combines monitoring data, chemical transport model results and other supplementary data using linear regression model followed by kriging of its residuals (residual kriging). The paper presents the mapping results and gives an uncertainty analysis of the interpolated maps. It also presents concentration change in 2020 in comparison to the five-year average 2015-2019 using the difference maps.
ETC/HE
2023