Fant 835 publikasjoner. Viser side 2 av 35:
Do cytotoxicity and cell death cause false positive results in the in vitro comet assay?
The comet assay is used to measure DNA damage induced by chemical and physical agents. High concentrations of test agents may cause cytotoxicity or cell death, which may give rise to false positive results in the comet assay. Systematic studies on genotoxins and cytotoxins (i.e. non-genotoxic poisons) have attempted to establish a threshold of cytotoxicity or cell death by which DNA damage results measured by the comet assay could be regarded as a false positive result. Thresholds of cytotoxicity/cell death range from 20% to 50% in various publications. Curiously, a survey of the latest literature on comet assay results from cell culture studies suggests that one-third of publications did not assess cytotoxicity or cell death. We recommend that it should be mandatory to include results from at least one type of assay on cytotoxicity, cell death or cell proliferation in publications on comet assay results. A combination of cytotoxicity (or cell death) and proliferation (or colony forming efficiency assay) is preferable in actively proliferating cells because it covers more mechanisms of action. Applying a general threshold of cytotoxicity/cell death to all types of agents may not be applicable; however, 25% compared to the concurrent negative control seems to be a good starting value to avoid false positive comet assay results. Further research is needed to establish a threshold value to distinguish between true and potentially false positive genotoxic effects detected by the comet assay.
2022
Fungus-farming termites cultivate a Termitomyces fungus monoculture in enclosed gardens (combs) free of other fungi, except during colony declines, where Pseudoxylaria spp. stowaway fungi appear and take over combs. Here, we determined Volatile Organic Compounds (VOCs) of healthy Macrotermes bellicosus nests in nature and VOC changes associated with comb decay during Pseudoxylaria takeover. We identified 443 VOCs and unique volatilomes across samples and nest volatilomes that were mainly composed of fungus comb VOCs with termite contributions. Few comb VOCs were linked to chemical changes during decay, but longipinocarvone and longiverbenone were only emitted during comb decay. These terpenes may be involved in Termitomyces defence against antagonistic fungi or in fungus-termite signalling of comb state. Both comb and Pseudoxylaria biomass volatilomes contained many VOCs with antimicrobial activity that may serve in maintaining healthy Termitomyces monocultures or aid in the antagonistic takeover by Pseudoxylaria during colony decline. We further observed a series of oxylipins with known functions in the regulation of fungus germination, growth, and secondary metabolite production. Our volatilome map of the fungus-farming termite symbiosis provides new insights into the chemistry regulating complex interactions and serves as a valuable guide for future work on the roles of VOCs in symbioses.
2025
Atmospheric methane grew very rapidly in 2014 (12.7 ± 0.5 ppb/year), 2015 (10.1 ± 0.7 ppb/year), 2016 (7.0 ± 0.7 ppb/year), and 2017 (7.7 ± 0.7 ppb/year), at rates not observed since the 1980s. The increase in the methane burden began in 2007, with the mean global mole fraction in remote surface background air rising from about 1,775 ppb in 2006 to 1,850 ppb in 2017. Simultaneously the 13C/12C isotopic ratio (expressed as δ13CCH4) has shifted, has shifted, now trending negative for more than a decade. The causes of methane's recent mole fraction increase are therefore either a change in the relative proportions (and totals) of emissions from biogenic and thermogenic and pyrogenic sources, especially in the tropics and subtropics, or a decline in the atmospheric sink of methane, or both. Unfortunately, with limited measurement data sets, it is not currently possible to be more definitive. The climate warming impact of the observed methane increase over the past decade, if continued at >5 ppb/year in the coming decades, is sufficient to challenge the Paris Agreement, which requires sharp cuts in the atmospheric methane burden. However, anthropogenic methane emissions are relatively very large and thus offer attractive targets for rapid reduction, which are essential if the Paris Agreement aims are to be attained.
PLAIN LANGUAGE SUMMARY: The rise in atmospheric methane (CH4), which began in 2007, accelerated in the past 4 years. The growth has been worldwide, especially in the tropics and northern midlatitudes. With the rise has come a shift in the carbon isotope ratio of the methane. The causes of the rise are not fully understood, and may include increased emissions and perhaps a decline in the destruction of methane in the air. Methane's increase since 2007 was not expected in future greenhouse gas scenarios compliant with the targets of the Paris Agreement, and if the increase continues at the same rates it may become very difficult to meet the Paris goals. There is now urgent need to reduce methane emissions, especially from the fossil fuel industry.
2019
The effect of the 2018 extreme meteorological conditions in Europe on methane (CH4) emissions is examined using estimates from four atmospheric inversions calculated for the period 2005–2018. For most of Europe, we find no anomaly in 2018 compared to the 2005–2018 mean. However, we find a positive anomaly for the Netherlands in April, which coincided with positive temperature and soil moisture anomalies suggesting an increase in biogenic sources. We also find a negative anomaly for the Netherlands for September–October, which coincided with a negative anomaly in soil moisture, suggesting a decrease in soil sources. In addition, we find a positive anomaly for Serbia in spring, summer and autumn, which coincided with increases in temperature and soil moisture, again suggestive of changes in biogenic sources, and the annual emission for 2018 was 33 ± 38% higher than the 2005–2017 mean. These results indicate that CH4 emissions from areas where the natural source is thought to be relatively small can still vary due to meteorological conditions. At the European scale though, the degree of variability over 2005–2018 was small, and there was negligible impact on the annual CH4 emissions in 2018 despite the extreme meteorological conditions.
This article is part of a discussion meeting issue ‘Rising methane: is warming feeding warming? (part 2)’.
2021
2025
A combination of local (i.e. firefighting training facilities) and remote sources (i.e., long-range transport) are assumed to be responsible for the occurrence of per- and polyfluoroalkyl substances (PFASs) in Svalbard (Norwegian Arctic). However, no systematic elucidation of local PFASs sources have been conducted yet. Therefore, a survey was performed aiming at identifying local PFASs pollution sources on the island of Spitsbergen (Svalbard, Norway). Soil, fresh water (lake, draining rivers), sea water, melt-water run-off, surface snow and coastal sediment samples were collected from Longyearbyen (Norwegian mining town), Ny-Ålesund (research facility) and the Lake Linnévatnet area (background site) during several campaigns (2014-2016) and analysed for 14 individual target PFASs. For background site (Linnévatnet area, sampling during April to June 2015), ∑PFAS levels ranged from 0.4 – 4 ng/L in surface lake water (n = 20). PFAS in melt water from the contributing glaciers showed similar concentrations (~4 ng/L, n = 2). The short chain perfluorobutanoate (PFBA) was predominant in lake water (60-80% of the ∑PFASs), meltwater (20-30 %) and run-off water (40 %). Long range transport is assumed to be the major PFAS source. In Longyearbyen, 5 water samples (i.e. 2 seawater, 3 run-off) were collected near the local firefighting training site (FFTS) in November 2014 and June 2015, respectively. The highest PFAS levels were found in FFTS melt water run-off (118 ng/L). PFOS was the most abundant compound in the FFTS meltwater run-off (53 – 58 % PFASs). At the research station Ny-Ålesund, sea water (n = 6), soil (n = 9) and fresh water (n = 10) were collected in June 2016. Low ∑PFAS concentrations were determined for sea water (5 - 6 ng/L), whereas high ∑PFAS concentrations were found in run-off water (113 – 119 ng/L) and soil (211 – 800 ng/g dry weight (dw)) collected close to the local FFTS. In addition, high ∑PFAS levels (127 ng/L) were also found in fresh water from lake Solvatnet close to former sewage treatment facility. Overall, at both FFTS affected sites (soil, water), PFOS was the most abundant compound (60 – 69% of ∑PFASs). FFTS and landfill locations were identified as major PFASs sources for Svalbard settlements.
2018
Aerosol particles are a complex component of the atmospheric system which influence climate directly by interacting with solar radiation, and indirectly by contributing to cloud formation. The variety of their sources, as well as the multiple transformations they may undergo during their transport (including wet and dry deposition), result in significant spatial and temporal variability of their properties. Documenting this variability is essential to provide a proper representation of aerosols and cloud condensation nuclei (CCN) in climate models. Using measurements conducted in 2016 or 2017 at 62 ground-based stations around the world, this study provides the most up-to-date picture of the spatial distribution of particle number concentration (Ntot) and number size distribution (PNSD, from 39 sites). A sensitivity study was first performed to assess the impact of data availability on Ntot's annual and seasonal statistics, as well as on the analysis of its diel cycle. Thresholds of 50 % and 60 % were set at the seasonal and annual scale, respectively, for the study of the corresponding statistics, and a slightly higher coverage (75 %) was required to document the diel cycle.
Although some observations are common to a majority of sites, the variety of environments characterizing these stations made it possible to highlight contrasting findings, which, among other factors, seem to be significantly related to the level of anthropogenic influence. The concentrations measured at polar sites are the lowest (∼ 102 cm−3) and show a clear seasonality, which is also visible in the shape of the PNSD, while diel cycles are in general less evident, due notably to the absence of a regular day–night cycle in some seasons. In contrast, the concentrations characteristic of urban environments are the highest (∼ 103–104 cm−3) and do not show pronounced seasonal variations, whereas diel cycles tend to be very regular over the year at these stations. The remaining sites, including mountain and non-urban continental and coastal stations, do not exhibit as obvious common behaviour as polar and urban sites and display, on average, intermediate Ntot (∼ 102–103 cm−3). Particle concentrations measured at mountain sites, however, are generally lower compared to nearby lowland sites, and tend to exhibit somewhat more pronounced seasonal variations as a likely result of the strong impact of the atmospheric boundary layer (ABL) influence in connection with the topography of the sites. ABL dynamics also likely contribute to the diel cycle of Ntot observed at these stations. Based on available PNSD measurements, CCN-sized particles (considered here as either >50 nm or >100 nm) can represent from a few percent to almost all of Ntot, corresponding to seasonal medians on the order of ∼ 10 to 1000 cm−3, with seasonal patterns and a hierarchy of the site types broadly similar to those observed for Ntot.
Overall, this work illustrates the importance of in situ measurements, in particular for the study of aerosol physical properties, and thus strongly supports the development of a broad global network of near surface observatories to increase and homogenize the spatial coverage of the measurements, and guarantee as well data availability and quality. The results of this study also provide a valuable, freely available and easy to use support for model comparison and validation, with the ultimate goal of contributing to improvement of the representation of aerosol–cloud interactions in models, and, therefore, of the evaluation of the impact of aerosol particles on climate.
2021
Knowledge of the spatial distribution of the fluxes of greenhouse gases (GHGs) and their temporal variability as well as flux attribution to natural and anthropogenic processes is essential to monitoring the progress in mitigating anthropogenic emissions under the Paris Agreement and to inform its global stocktake. This study provides a consolidated synthesis of CH4 and N2O emissions using bottom-up (BU) and top-down (TD) approaches for the European Union and UK (EU27 + UK) and updates earlier syntheses (Petrescu et al., 2020, 2021). The work integrates updated emission inventory data, process-based model results, data-driven sector model results and inverse modeling estimates, and it extends the previous period of 1990–2017 to 2019. BU and TD products are compared with European national greenhouse gas inventories (NGHGIs) reported by parties under the United Nations Framework Convention on Climate Change (UNFCCC) in 2021. Uncertainties in NGHGIs, as reported to the UNFCCC by the EU and its member states, are also included in the synthesis. Variations in estimates produced with other methods, such as atmospheric inversion models (TD) or spatially disaggregated inventory datasets (BU), arise from diverse sources including within-model uncertainty related to parameterization as well as structural differences between models. By comparing NGHGIs with other approaches, the activities included are a key source of bias between estimates, e.g., anthropogenic and natural fluxes, which in atmospheric inversions are sensitive to the prior geospatial distribution of emissions. ...
2023
Mapping Plastic and Plastic Additive Cycles in Coastal Countries: A Norwegian Case Study
The growing environmental consequences caused by plastic pollution highlight the need for a better understanding of plastic polymer cycles and their associated additives. We present a novel, comprehensive top-down method using inflow-driven dynamic probabilistic material flow analysis (DPMFA) to map the plastic cycle in coastal countries. For the first time, we covered the progressive leaching of microplastics to the environment during the use phase of products and modeled the presence of 232 plastic additives. We applied this methodology to Norway and proposed initial release pathways to different environmental compartments. 758 kt of plastics distributed among 13 different polymers was introduced to the Norwegian economy in 2020, 4.4 Mt was present in in-use stocks, and 632 kt was wasted, of which 15.2 kt (2.4%) was released to the environment with a similar share of macro- and microplastics and 4.8 kt ended up in the ocean. Our study shows tire wear rubber as a highly pollutive microplastic source, while most macroplastics originated from consumer packaging with LDPE, PP, and PET as dominant polymers. Additionally, 75 kt of plastic additives was potentially released to the environment alongside these polymers. We emphasize that upstream measures, such as consumption reduction and changes in product design, would result in the most positive impact for limiting plastic pollution.
2024
The 2018 drought was one of the worst European droughts of the twenty-first century in terms of its severity, extent and duration. The effects of the drought could be seen in a reduction in harvest yields in parts of Europe, as well as an unprecedented browning of vegetation in summer. Here, we quantify the effect of the drought on net ecosystem exchange (NEE) using five independent regional atmospheric inversion frameworks. Using a network of atmospheric CO2 mole fraction observations, we estimate NEE with at least monthly and 0.5° × 0.5° resolution for 2009–2018. We find that the annual NEE in 2018 was likely more positive (less CO2 uptake) in the temperate region of Europe by 0.09 ± 0.06 Pg C yr−1 (mean ± s.d.) compared to the mean of the last 10 years of −0.08 ± 0.17 Pg C yr−1, making the region close to carbon neutral in 2018. Similarly, we find a positive annual NEE anomaly for the northern region of Europe of 0.02 ± 0.02 Pg C yr−1 compared the 10-year mean of −0.04 ± 0.05 Pg C yr−1. In both regions, this was largely owing to a reduction in the summer CO2 uptake. The positive NEE anomalies coincided spatially and temporally with negative anomalies in soil water. These anomalies were exceptional for the 10-year period of our study.
This article is part of the theme issue ‘Impacts of the 2018 severe drought and heatwave in Europe: from site to continental scale’.
2020
Changes in black carbon emissions over Europe due to COVID-19 lockdowns
Following the emergence of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) responsible for COVID-19 in December 2019 in Wuhan (China) and its spread to the rest of the world, the World Health Organization declared a global pandemic in March 2020. Without effective treatment in the initial pandemic phase, social distancing and mandatory quarantines were introduced as the only available preventative measure. In contrast to the detrimental societal impacts, air quality improved in all countries in which strict lockdowns were applied, due to lower pollutant emissions. Here we investigate the effects of the COVID-19 lockdowns in Europe on ambient black carbon (BC), which affects climate and damages health, using in situ observations from 17 European stations in a Bayesian inversion framework. BC emissions declined by 23 kt in Europe (20 % in Italy, 40 % in Germany, 34 % in Spain, 22 % in France) during lockdowns compared to the same period in the previous 5 years, which is partially attributed to COVID-19 measures. BC temporal variation in the countries enduring the most drastic restrictions showed the most distinct lockdown impacts. Increased particle light absorption in the beginning of the lockdown, confirmed by assimilated satellite and remote sensing data, suggests residential combustion was the dominant BC source. Accordingly, in central and Eastern Europe, which experienced lower than average temperatures, BC was elevated compared to the previous 5 years. Nevertheless, an average decrease of 11 % was seen for the whole of Europe compared to the start of the lockdown period, with the highest peaks in France (42 %), Germany (21 %), UK (13 %), Spain (11 %) and Italy (8 %). Such a decrease was not seen in the previous years, which also confirms the impact of COVID-19 on the European emissions of BC.
2021
Sudden Stratospheric Warmings (SSW) affect the chemistry and dynamics of the middle atmosphere. Major warmings occur roughly every second winter in the Northern Hemisphere (NH), but has only been observed once in the Southern Hemisphere (SH), during the Antarctic winter of 2002. Observations by the Global Ozone Monitoring by Occultation of Stars (GOMOS, an instrument on board Envisat) during this rare event, show a 40% increase of ozone in the nighttime secondary ozone layer at subpolar latitudes compared to non-SSW years. This study investigates the cause of the mesospheric nighttime ozone increase, using the National Center for Atmospheric Research (NCAR) Whole Atmosphere Community Climate Model with specified dynamics (SD-WACCM). The 2002 SH winter was characterized by several reductions of the strength of the polar night jet in the upper stratosphere before the jet reversed completely, marking the onset of the major SSW. At the time of these wind reductions, corresponding episodic increases can be seen in the modelled nighttime secondary ozone layer. This ozone increase is attributed largely to enhanced upwelling and the associated cooling of the altitude region in conjunction with the wind reversal. This is in correspondence to similar studies of SSW induced ozone enhancements in NH. But unlike its NH counterpart, the SH secondary ozone layer appeared to be impacted less by episodic variations in atomic hydrogen. Seasonally decreasing atomic hydrogen plays however a larger role in SH compared to NH.
2018
Individual variability in contaminants and physiological status in a resident Arctic seabird species
2019
Interactions between the atmosphere, cryosphere, and ecosystems at northern high latitudes
The Nordic Centre of Excellence CRAICC (Cryosphere–Atmosphere Interactions in a Changing Arctic Climate), funded by NordForsk in the years 2011–2016, is the largest joint Nordic research and innovation initiative to date, aiming to strengthen research and innovation regarding climate change issues in the Nordic region. CRAICC gathered more than 100 scientists from all Nordic countries in a virtual centre with the objectives of identifying and quantifying the major processes controlling Arctic warming and related feedback mechanisms, outlining strategies to mitigate Arctic warming, and developing Nordic Earth system modelling with a focus on short-lived climate forcers (SLCFs), including natural and anthropogenic aerosols.
The outcome of CRAICC is reflected in more than 150 peer-reviewed scientific publications, most of which are in the CRAICC special issue of the journal Atmospheric Chemistry and Physics. This paper presents an overview of the main scientific topics investigated in the centre and provides the reader with a state-of-the-art comprehensive summary of what has been achieved in CRAICC with links to the particular publications for further detail. Faced with a vast amount of scientific discovery, we do not claim to completely summarize the results from CRAICC within this paper, but rather concentrate here on the main results which are related to feedback loops in climate change–cryosphere interactions that affect Arctic amplification.
2019
Per- and polyfluoroalkyl substances (PFAS) have gained significant global attention due to their extensive industrial use and harmful effects on various organisms. Among these, perfluoroalkyl acids (PFAAs) are well-studied, but their diverse precursors remain challenging to monitor. The Total Oxidizable Precursor (TOP) assay offers a powerful approach to converting these precursors into detectable PFAAs. In this study, the TOP assay was applied to samples from the East Asian-Australian Flyway, a critical migratory route for millions of shorebirds. Samples included shellfish from China's coastal mudflats, key stopover sites for these birds, and blood and liver samples from shorebirds overwintering in Australia. The results showed a substantial increase in perfluorocarboxylic acids (PFCAs) across all sample types following the TOP assay, with the most significant increases in shorebird livers (Sum PFCAs increased by 18,156 %). Intriguingly, the assay also revealed unexpected increases in perfluorosulfonic acids (PFSAs), suggesting the presence of unidentified precursors. These findings highlight the need for further research into these unknown precursors, their sources, and their ecological impacts on shorebirds, other wildlife, and potential human exposure. This study also provides crucial insights into the TOP assay’s strengths and limitations in studying PFAS precursor dynamics in biological matrices.
2025
A number of studies have shown that assimilation of satellite derived soil moisture using the ensemble Kalman Filter (EnKF) can improve soil moisture estimates, particularly for the surface zone. However, the EnKF is computationally expensive since an ensemble of model integrations have to be propagated forward in time. Here, assimilating satellite soil moisture data from the Soil Moisture Active Passive (SMAP) mission, we compare the EnKF with the computationally cheaper ensemble Optimal Interpolation (EnOI) method over the contiguous United States (CONUS). The background error–covariance in the EnOI is sampled in two ways: (i) by using the stochastic spread from an ensemble open-loop run, and (ii) sampling from the model spinup climatology. Our results indicate that the EnKF is only marginally superior to one version of the EnOI. Furthermore, the assimilation of SMAP data using the EnKF and EnOI is found to improve the surface zone correlation with in situ observations at a 95% significance level. The EnKF assimilation of SMAP data is also found to improve root-zone correlation with independent in situ data at the same significance level; however this improvement is dependent on which in situ network we are validating against. We evaluate how the quality of the atmospheric forcing affects the analysis results by prescribing the land surface data assimilation system with either observation corrected or model derived precipitation. Surface zone correlation skill increases for the analysis using both the corrected and model derived precipitation, but only the latter shows an improvement at the 95% significance level. The study also suggests that assimilation of satellite derived surface soil moisture using the EnOI can correct random errors in the atmospheric forcing and give an analysed surface soil moisture close to that of an open-loop run using observation derived precipitation. Importantly, this shows that estimates of soil moisture could be improved using a combination of assimilating SMAP using the computationally cheap EnOI while using model derived precipitation as forcing. Finally, we assimilate three different Level-2 satellite derived soil moisture products from the European Space Agency Climate Change Initiative (ESA CCI), SMAP and SMOS (Soil Moisture and Ocean Salinity) using the EnOI, and then compare the relative performance of the three resulting analyses against in situ soil moisture observations. In this comparison, we find that all three analyses offer improvements over an open-loop run when comparing to in situ observations. The assimilation of SMAP data is found to perform marginally better than the assimilation of SMOS data, while assimilation of the ESA CCI data shows the smallest improvement of the three analysis products.
2019
2020
2018
2019
An Infrastructural Analysis of a Crowdsourcing Tool for Environmental Research
In this paper, we adopt information infrastructure design principles and concepts from the theory of critical mass to analyze and evaluate the socio-technical conditions that hindered the successful bootstrapping processes of a crowdsourcing tool for environmental research. The crowdsourcing tool was designed to improve the estimation of emissions from burning wood for residential heating in urban areas in Norway by collecting geolocation data on wood consumption and stove types. Our analysis identifies three groups of users, namely scientists, wood consumers (end users), and key stakeholders, that the IT capability of the tool needs to support. At this stage, we determined that the tool was more useful to the scientists than the other two groups, which was attributed to its low uptake. We uncovered various underlying issues through further analysis of means by which the tool becomes useful to key stakeholders. One particular issue concerned the tension between existing data collection practices, which are based on statistical methods, and the nature of crowdsourcing, which is based on the principle of open call with no sampling techniques. From our analysis, we concluded that developing crowdsourcing tools for research requires increasing the tool’s benefits for key stakeholders by addressing these underlying issues. Inferring from the theory of critical mass for collective action, we recommend that developers of crowdsourcing tools include a function that allows users to view the contributions of other users.
2018
While feathers have been successfully validated for monitoring of internal concentrations of heavy metals and legacy persistent organic pollutants (POPs), less is known about their suitability for monitoring ofemerging con- taminants (ECs). Our study presents a broad investigation ofboth legacy POPs and ECs in non-destructivematri- ces from a bird of prey. Plasma and feathers were sampled in 2015 and 2016 from 70 whitetailed eagle (Haliaeetus albicilla) nestlings from two archipelagos in Norway. Preen oil was also sampled in 2016. Samples were analysed for POPs (polychlorinated biphenyls (PCBs), polybrominated diphenyl ethers (PBDEs) and organochlorinated pesticides (OCPs)) and ECs (per- and polyfluoroalkyl substances (PFASs), dechlorane plus (DPs), phosphate and novel brominated flame retardants (PFRs and NBFRs)). A total of nine PCBs, three OCPs, one PBDE and one PFAS were detected in over 50% of the plasma and feather samples within each sampling year and location. Significant and positive correlationswere found between plasma, feathers and preen oil concentrations of legacy POPs and confirm the findings ofprevious research on the usefulness of these matrices for non-destructive mon- itoring. In contrast, the suitability of feathers for ECs seems to be limited. Detection frequencies (DF) of PFASs were higher in plasma (mean DF: 78%) than in feathers (mean DF: 38%). Only perfluoroundecanoic acid could be quantified in over 50% ofboth plasma and feather samples, yet their correlation was poor and not significant. The detection frequencies of PFRs, NBFRs and DPs were very low in plasma (mean DF: 1–13%), compared to feathers (meanDF: 10–57%). Thismay suggest external atmospheric deposition, rapid internal biotransformation or excretion of these compounds. Accordingly, we suggest prioritising plasma for PFASs analyses, while the sources of PFRs, NBFRs and DPs in feathers and plasma need further investigation.
2018
Methane at Svalbard and over the European Arctic Ocean
Methane (CH<sub>4</sub>) is a powerful greenhouse gas. Its atmospheric mixing ratios have been increasing since 2005. Therefore, quantification of CH<sub>4</sub> sources is essential for effective climate change mitigation. Here we report observations of the CH<sub>4</sub> mixing ratios measured at the Zeppelin Observatory (Svalbard) in the Arctic and aboard the research vessel (RV) Helmer Hanssen over the Arctic Ocean from June 2014 to December 2016, as well as the long-term CH<sub>4</sub> trend measured at the Zeppelin Observatory from 2001 to 2017. We investigated areas over the European Arctic Ocean to identify possible hotspot regions emitting CH<sub>4</sub> from the ocean to the atmosphere, and used state-of-the-art modelling (FLEXPART) combined with updated emission inventories to identify CH<sub>4</sub> sources. Furthermore, we collected air samples in the region as well as samples of gas hydrates, obtained from the sea floor, which we analysed using a new technique whereby hydrate gases are sampled directly into evacuated canisters. Using this new methodology, we evaluated the suitability of ethane and isotopic signatures (δ<sup>13</sup>C in CH<sub>4</sub>) as tracers for ocean-to-atmosphere CH<sub>4</sub> emission. We found that the average methane / light hydrocarbon (ethane and propane) ratio is an order of magnitude higher for the same sediment samples using our new methodology compared to previously reported values, 2379.95 vs. 460.06, respectively. Meanwhile, we show that the mean atmospheric CH<sub>4</sub> mixing ratio in the Arctic increased by 5.9±0.38 parts per billion by volume (ppb) per year (yr<sup>−1</sup>) from 2001 to 2017 and ∼8 pbb yr<sup>−1</sup> since 2008, similar to the global trend of ∼ 7–8 ppb yr<sup>−1</sup>. Most large excursions from the baseline CH<sub>4</sub> mixing ratio over the European Arctic Ocean are due to long-range transport from land-based sources, lending confidence to the present inventories for high-latitude CH<sub>4</sub> emissions. However, we also identify a potential hotspot region with ocean–atmosphere CH<sub>4</sub> flux north of Svalbard (80.4∘ N, 12.8∘ E) of up to 26 nmol m<sup>−2</sup>s<sup>−1</sup> from a large mixing ratio increase at the location of 30 ppb. Since this flux is consistent with previous constraints (both spatially and temporally), there is no evidence that the area of interest north of Svalbard is unique in the context of the wider Arctic. Rather, because the meteorology at the time of the observation was unique in the context of the measurement time series, we obtained over the short course of the episode measurements highly sensitive to emissions over an active seep site, without sensitivity to land-based emissions.
2018
A Lagrangian particle dispersion model, the FLEXible PARTicle dispersion chemical transport model (FLEXPART CTM), is used to simulate global three-dimensional fields of trace gas abundance. These fields are constrained with surface observation data through nudging, a data assimilation method, which relaxes model fields to observed values. Such fields are of interest to a variety of applications, such as inverse modelling, satellite retrievals, radiative forcing models and estimating global growth rates of greenhouse gases. Here, we apply this method to methane using 6 million model particles filling the global model domain. For each particle, methane mass tendencies due to emissions (based on several inventories) and loss by reaction with OH, Cl and O(1D), as well as observation data nudging were calculated. Model particles were transported by mean, turbulent and convective transport driven by 1∘×1∘ ERA-Interim meteorology. Nudging is applied at 79 surface stations, which are mostly included in the World Data Centre for Greenhouse Gases (WDCGG) database or the Japan–Russia Siberian Tall Tower Inland Observation Network (JR-STATION) in Siberia. For simulations of 1 year (2013), we perform a sensitivity analysis to show how nudging settings affect modelled concentration fields. These are evaluated with a set of independent surface observations and with vertical profiles in North America from the National Oceanic and Atmospheric Administration (NOAA) Earth System Research Laboratory (ESRL), and in Siberia from the Airborne Extensive Regional Observations in SIBeria (YAK-AEROSIB) and the National Institute for Environmental Studies (NIES). FLEXPART CTM results are also compared to simulations from the global Eulerian chemistry Transport Model version 5 (TM5) based on optimized fluxes. Results show that nudging strongly improves modelled methane near the surface, not only at the nudging locations but also at independent stations. Mean bias at all surface locations could be reduced from over 20 to less than 5 ppb through nudging. Near the surface, FLEXPART CTM, including nudging, appears better able to capture methane molar mixing ratios than TM5 with optimized fluxes, based on a larger bias of over 13 ppb in TM5 simulations. The vertical profiles indicate that nudging affects model methane at high altitudes, yet leads to little improvement in the model results there. Averaged from 19 aircraft profile locations in North America and Siberia, root mean square error (RMSE) changes only from 16.3 to 15.7 ppb through nudging, while the mean absolute bias increases from 5.3 to 8.2 ppb. The performance for vertical profiles is thereby similar to TM5 simulations based on TM5 optimized fluxes where we found a bias of 5 ppb and RMSE of 15.9 ppb. With this rather simple model setup, we thus provide three-dimensional methane fields suitable for use as boundary conditions in regional inverse modelling as a priori information for satellite retrievals and for more accurate estimation of mean mixing ratios and growth rates. The method is also applicable to other long-lived trace gases.
2018
Source Quantification of South Asian Black Carbon Aerosols with Isotopes and Modeling
Black carbon (BC) aerosols perturb climate and impoverish air quality/human health—affecting ∼1.5 billion people in South Asia. However, the lack of source-diagnostic observations of BC is hindering the evaluation of uncertain bottom-up emission inventories (EIs) and thereby also models/policies. Here, we present dual-isotope-based (Δ14C/δ13C) fingerprinting of wintertime BC at two receptor sites of the continental outflow. Our results show a remarkable similarity in contributions of biomass and fossil combustion, both from the site capturing the highly populated highly polluted Indo-Gangetic Plain footprint (IGP; Δ14C-fbiomass = 50 ± 3%) and the second site in the N. Indian Ocean representing a wider South Asian footprint (52 ± 6%). Yet, both sites reflect distinct δ13C-fingerprints, indicating a distinguishable contribution of C4-biomass burning from peninsular India (PI). Tailored-model-predicted season-averaged BC concentrations (700 ± 440 ng m–3) match observations (740 ± 250 ng m–3), however, unveiling a systematically increasing model-observation bias (+19% to −53%) through winter. Inclusion of BC from open burning alone does not reconcile predictions (fbiomass = 44 ± 8%) with observations. Direct source-segregated comparison reveals regional offsets in anthropogenic emission fluxes in EIs, overestimated fossil-BC in the IGP, and underestimated biomass-BC in PI, which contributes to the model-observation bias. This ground-truthing pinpoints uncertainties in BC emission sources, which benefit both climate/air-quality modeling and mitigation policies in South Asia.
2020