Found 819 publications. Showing page 17 of 35:
This study investigates the impact of meteorological variations on the long-term patterns of PM2.5 in Delhi from 2007 to 2022 using the AirGAM 2022r1 model. Generalized Additive Modeling was employed to analyze meteorology-adjusted (removing the influence of inter-annual variations in meteorology) and unadjusted trends (trends without considering meteorology) while addressing auto-correlation. PM2.5 levels showed a modest decline of 14 μg m−3 unadjusted and 18 μg m−3 meteorology-adjusted over the study period. Meteorological conditions and time factors significantly influenced trends. Temperature, wind speed, wind direction, humidity, boundary layer height, medium-height cloud cover, precipitation, and time variables including day-of-week, day-of-year, and overall time, were used as GAM model inputs. The model accounted for 55% of PM2.5 variability (adjusted R-squared = 0.55). Day-of-week and medium-height cloud cover were non-significant, while other covariates were significant (p
2024
2024
Data fusion for enhancing urban air quality modeling using large-scale citizen science data
Rapid urbanization has led to many environmental issues, including poor air quality. With urbanization set to continue, there is an urgent need to mitigate air pollution and minimize its adverse health impacts. This study aims to advance urban air quality management by integrating a dispersion model output with large-scale citizen science data, collected over a 4-week period by 642 participants in Cork City, Ireland. The dispersion model enabled the identification of major sources of NO2 air pollution while also addressing gaps in regulatory monitoring efforts. Integrating the diffusion tube data with the dispersion model output, we developed a data fusion model that captured localized fluctuations in air quality, with increases of up to 22μg/m3 observed at major road intersections. The data fusion model provided a more accurate representation of NO2 concentrations, with estimates within 1.3μg/m3 of the regulatory monitoring measurement at an urban traffic location, an improvement of 11.7μg/m3 from the priori dispersion model. This enhanced accuracy enabled a more precise assessment of the population exposure to air pollution. The data fusion model showed a higher population exposure to NO2 compared to the dispersion model, providing valuable insights that can inform environmental health policies aimed at safeguarding public health.
2024
Two-Stage Feature Engineering to Predict Air Pollutants in Urban Areas
Air pollution is a global challenge to human health and the ecological environment. Identifying the relationship among pollutants, their fundamental sources and detrimental effects on health and mental well-being is critical in order to implement appropriate countermeasures. The way forward to address this issue and assess air quality is through accurate air pollution prediction. Such prediction can subsequently assist governing bodies in making prompt, evidence-based decisions and prevent further harm to our urban environment, public health, and climate, all of which co-benefit our economy. In this study, the main objective is to explore the strength of features and proposed a two stage feature engineering approach, which fuses the advantage of influential factors along with the decomposition approach and generates an optimum feature combination for five major pollutants including Nitrogen Dioxide (NO 2 ), Ozone (O 3 ), Sulphur Dioxide (SO 2 ), and Particulate Matter (PM2.5, and PM10). The experiments are conducted using a dataset from 2015 to 2020 which is publicly available and is collected from Belfast-based air quality monitoring stations in Northern Ireland, UK. In stage-1, using the dataset new features such as trigonometric and statistical features are created to capture their dependency on the target pollutant and generated correlation-inspired best feature combinations to improve forecasting model performance. This is further enhanced in stage-2 by an optimum feature combination which is an integration of stage-1 and Variational Mode Decomposition (VMD) based features. This study employed a simplified Long Short Term Memory (LSTM) neural network and proposed a single-step forecasting model to predict multivariate time series data. Three performance indicators are used to evaluate the effectiveness of forecasting model: (a) root mean square error (RMSE), (b) mean absolute error (MAE), and (c) R-squared (R 2 ). The results demonstrate the effectiveness of proposed approach with 13% improvement in performance (in terms of R 2 ) and the lowest error scores for both RMSE and MAE.
2024
The Integrated Carbon Observation System in Europe
Since 1750, land use change and fossil fuel combustion has led to a 46 % increase in the atmospheric carbon dioxide (CO2) concentrations, causing global warming with substantial societal consequences. The Paris Agreement aims to limiting global temperature increases to well below 2°C above pre-industrial levels. Increasing levels of CO2 and other greenhouse gases (GHGs), such as methane (CH4) and nitrous oxide (N2O), in the atmosphere are the primary cause of climate change. Approximately half of the carbon emissions to the atmosphere is sequestered by ocean and land sinks, leading to ocean acidification but also slowing the rate of global warming. However, there are significant uncertainties in the future global warming scenarios due to uncertainties in the size, nature and stability of these sinks. Quantifying and monitoring the size and timing of natural sinks and the impact of climate change on ecosystems are important information to guide policy-makers’ decisions and strategies on reductions in emissions. Continuous, long-term observations are required to quantify GHG emissions, sinks, and their impacts on Earth systems. The Integrated Carbon Observation System (ICOS) was designed as the European in situ observation and information system to support science and society in their efforts to mitigate climate change. It provides standardized and open data currently from over 140 measurement stations across 12 European countries. The stations observe GHG concentrations in the atmosphere and carbon and GHG fluxes between the atmosphere, land surface and the oceans. This article describes how ICOS fulfills its mission to harmonize these observations, ensure the related long-term financial commitments, provide easy access to well-documented and reproducible high-quality data and related protocols and tools for scientific studies, and deliver information and GHG-related products to stakeholders in society and policy.
2021
2025
Within the framework of the AeroCom (Aerosol Comparisons between Observations and Models) initiative, the state-of-the-art modelling of aerosol optical properties is assessed from 14 global models participating in the phase III control experiment (AP3). The models are similar to CMIP6/AerChemMIP Earth System Models (ESMs) and provide a robust multi-model ensemble. Inter-model spread of aerosol species lifetimes and emissions appears to be similar to that of mass extinction coefficients (MECs), suggesting that aerosol optical depth (AOD) uncertainties are associated with a broad spectrum of parameterised aerosol processes.
Total AOD is approximately the same as in AeroCom phase I (AP1) simulations. However, we find a 50 % decrease in the optical depth (OD) of black carbon (BC), attributable to a combination of decreased emissions and lifetimes. Relative contributions from sea salt (SS) and dust (DU) have shifted from being approximately equal in AP1 to SS contributing about 2∕3 of the natural AOD in AP3. This shift is linked with a decrease in DU mass burden, a lower DU MEC, and a slight decrease in DU lifetime, suggesting coarser DU particle sizes in AP3 compared to AP1.
Relative to observations, the AP3 ensemble median and most of the participating models underestimate all aerosol optical properties investigated, that is, total AOD as well as fine and coarse AOD (AODf, AODc), Ångström exponent (AE), dry surface scattering (SCdry), and absorption (ACdry) coefficients. Compared to AERONET, the models underestimate total AOD by ca. 21 % ± 20 % (as inferred from the ensemble median and interquartile range). Against satellite data, the ensemble AOD biases range from −37 % (MODIS-Terra) to −16 % (MERGED-FMI, a multi-satellite AOD product), which we explain by differences between individual satellites and AERONET measurements themselves. Correlation coefficients (R) between model and observation AOD records are generally high (R>0.75), suggesting that the models are capable of capturing spatio-temporal variations in AOD. We find a much larger underestimate in coarse AODc (∼ −45 % ± 25 %) than in fine AODf (∼ −15 % ± 25 %) with slightly increased inter-model spread compared to total AOD. These results indicate problems in the modelling of DU and SS. The AODc bias is likely due to missing DU over continental land masses (particularly over the United States, SE Asia, and S. America), while marine AERONET sites and the AATSR SU satellite data suggest more moderate oceanic biases in AODc.
Column AEs are underestimated by about 10 % ± 16 %. For situations in which measurements show AE > 2, models underestimate AERONET AE by ca. 35 %. In contrast, all models (but one) exhibit large overestimates in AE when coarse aerosol dominates (bias ca. +140 % if observed AE < 0.5). Simulated AE does not span the observed AE variability. These results indicate that models overestimate particle size (or underestimate the fine-mode fraction) for fine-dominated aerosol and underestimate size (or overestimate the fine-mode fraction) for coarse-dominated aerosol. This must have implications for lifetime, water uptake, scattering enhancement, and the aerosol radiative effect, which we can not quantify at this moment.
Comparison against Global Atmosphere Watch (GAW) in situ data results in mean bias and inter-model variations of −35 % ± 25 % and −20 % ± 18 % for SCdry and ACdry, respectively. The larger underestimate of SCdry than ACdry suggests the models will simulate an aerosol single scattering albedo that is too low. The larger underestimate of SCdry than ambient air AOD is consistent with recent findings that models overestimate scattering enhancement due to hygroscopic growth. The broadly consistent negative bias in AOD and surface scattering suggests an underestimate of aerosol radiative effects in current global aerosol models.
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2021
Populations of killer whale (Orcinus orca) contain some of the most polluted animals on Earth. Yet, the knowledge on effects of chemical pollutants is limited in this species. Cell cultures and in vitro exposure experiments are pertinent tools to study effects of pollutants in free-ranging marine mammals. To investigate transcriptional responses to pollutants in killer whale cells, we collected skin biopsies of killer whales from the Northern Norwegian fjords and successfully established primary fibroblast cell cultures from the dermis of 4 out of 5 of them. Cells from the individual with the highest cell yield were exposed to three different concentrations of a mixture of persistent organic pollutants (POPs) that reflects the composition of the 10 most abundant POPs found in Norwegian killer whales (p,p’-DDE, trans-nonachlor, PCB52, 99, 101, 118, 138, 153, 180, 187). Transcriptional responses of 13 selected target genes were studied using digital droplet PCR, and whole transcriptome responses were investigated utilizing RNA sequencing. Among the target genes analysed, CYP1A1 was significantly downregulated in the cells exposed to medium (11.6 µM) and high (116 µM) concentrations of the pollutant mixture, while seven genes involved in endocrine functions showed a non-significant tendency to be upregulated at the highest exposure concentration. Bioinformatic analyses of RNA-seq data indicated that 13 and 43 genes were differentially expressed in the cells exposed to low and high concentrations of the mixture, respectively, in comparison to solvent control. Subsequent pathway and functional analyses of the differentially expressed genes indicated that the enriched pathways were mainly related to lipid metabolism, myogenesis and glucocorticoid receptor regulation. The current study results support previous correlative studies and provide cause-effect relationships, which is highly relevant for chemical and environmental management.
2023
SuperDARN Radar Wind Observations of Eastward-Propagating Planetary Waves
An array of SuperDARN meteor radars at northern high latitudes was used to investigate the sources and characteristics of eastward-propagating planetary waves (EPWs) at 95 km, with a focus on wintertime. The nine radars provided the daily mean meridional winds and their anomalies over 180 degrees of longitude, and these anomalies were separated into eastward and westward waves using a fast Fourier transform (FFT) method to extract the planetary wave components of zonal wavenumbers 1 and 2. Years when a sudden stratospheric warming event with an elevated stratopause (ES-SSW) occurred during the winter were contrasted with years without such events and composited through superposed epoch analysis. The results show that EPWs are a ubiquitous—and unexpected—feature of meridional wind variability near 95 km. Present even in non-ES-SSW years, they display a regular annual cycle peaking in January or February, depending on the zonal wavenumber. In years when an ES-SSW occurred, the EPWs were highly variable but enhanced before and after the onset.
2024
Acquired drug resistance and metastasis in breast cancer (BC) are coupled with epigenetic deregulation of gene expression. Epigenetic drugs, aiming to reverse these aberrant transcriptional patterns and sensitize cancer cells to other therapies, provide a new treatment strategy for drug-resistant tumors. Here we investigated the ability of DNA methyltransferase (DNMT) inhibitor decitabine (DAC) to increase the sensitivity of BC cells to anthracycline antibiotic doxorubicin (DOX). Three cell lines representing different molecular BC subtypes, JIMT-1, MDA-MB-231 and T-47D, were used to evaluate the synergy of sequential DAC + DOX treatment in vitro. The cytotoxicity, genotoxicity, apoptosis, and migration capacity were tested in 2D and 3D cultures. Moreover, genome-wide DNA methylation and transcriptomic analyses were employed to understand the differences underlying DAC responsiveness. The ability of DAC to sensitize trastuzumab-resistant HER2-positive JIMT-1 cells to DOX was examined in vivo in an orthotopic xenograft mouse model. DAC and DOX synergistic effect was identified in all tested cell lines, with JIMT-1 cells being most sensitive to DAC. Based on the whole-genome data, we assume that the aggressive behavior of JIMT-1 cells can be related to the enrichment of epithelial-to-mesenchymal transition and stemness-associated pathways in this cell line. The four-week DAC + DOX sequential administration significantly reduced the tumor growth, DNMT1 expression, and global DNA methylation in xenograft tissues. The efficacy of combination therapy was comparable to effect of pegylated liposomal DOX, used exclusively for the treatment of metastatic BC. This work demonstrates the potential of epigenetic drugs to modulate cancer cells' sensitivity to other forms of anticancer therapy.
2022
A satellite-based estimate of combustion aerosol cloud microphysical effects over the Arctic Ocean
Climate predictions for the rapidly changing Arctic are highly uncertain, largely due to a poor understanding of the processes driving cloud properties. In particular, cloud fraction (CF) and cloud phase (CP) have major impacts on energy budgets, but are poorly represented in most models, often because of uncertainties in aerosol–cloud interactions. Here, we use over 10 million satellite observations coupled with aerosol transport model simulations to quantify large-scale microphysical effects of aerosols on CF and CP over the Arctic Ocean during polar night, when direct and semi-direct aerosol effects are minimal. Combustion aerosols over sea ice are associated with very large (∼ 10Wm−2) differences in longwave cloud radiative effects at the sea ice surface. However, co-varying meteorological changes on factors such as CF likely explain the majority of this signal. For example, combustion aerosols explain at most 40% of the CF differences between the full dataset and the clean-condition subset, compared to between 57% and 91% of the differences that can be predicted by co-varying meteorology. After normalizing for meteorological regime, aerosol microphysical effects have small but significant impacts on CF, CP, and precipitation frequency on an Arctic-wide scale. These effects indicate that dominant aerosol–cloud microphysical mechanisms are related to the relative fraction of liquid-containing clouds, with implications for a warming Arctic.
2018
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.
2022
2018
Zurich statement on future actions on per-and polyfluoroalkyl substances (PFASs)
Per- and polyfluoroalkyl substances (PFASs) are man-made chemicals that contain at least one perfluoroalkyl moiety, –CnF2n–. To date, over 4,000 unique PFASs have been used in technical applications and consumer products, and some of them have been detected globally in human and wildlife biomonitoring studies. Because of their extraordinary persistence, human and environmental exposure to PFASs will be a long-term source of concern. Some PFASs such as perfluorooctanoic acid (PFOA) and perfluorooctanesulfonic acid (PFOS) have been investigated extensively and thus regulated, but for many other PFASs, knowledge about their current uses and hazards is still very limited or missing entirely. To address this problem and prepare an action plan for the assessment and management of PFASs in the coming years, a group of more than 50 international scientists and regulators held a two-day workshop in November, 2017. The group identified both the respective needs of and common goals shared by the scientific and the policy communities, made recommendations for cooperative actions, and outlined how the science–policy interface regarding PFASs can be strengthened using new approaches for assessing and managing highly persistent chemicals such as PFASs.
2018
Northern Fulmars (Fulmarus glacialis) are a pelagic seabird species distributed at northern and polar latitudes. They are often used as an indicator of plastic pollution in the North Sea region, but data are lacking from higher latitudes, especially when it comes to chicks. Here, we investigated amounts of ingested plastic and their characteristics in fulmar chicks from the Faroe Islands. Plastic particles (≥1 mm) in chicks of two age classes were searched using a digestion method with KOH. In addition, to evaluate if additive tissue burden reflects plastic ingestion, we measured liver tissue concentrations of two pollutant classes associated with plastic materials: polybrominated diphenyl ethers (PBDEs) and several dechloranes, using gas chromatography with high-resolution mass spectrometry. The most common shape was hard fragment (81%) and the most common polymer was polyethylene (73%). Plastic contamination did not differ between either age class, and we found no correlation between neither the amount and mass of plastic particles and the concentration of additives. After comparison with previous studies on adult fulmars, we do not recommend using chicks for biomonitoring adults because chicks seem to ingest more plastics than adults.
2022
Plastic burdens in northern fulmars from Svalbard: looking back 25 years
The northern fulmar Fulmarus glacialis ingests a larger number of (micro)plastics than many other seabirds due to its feeding habits and gut morphology. Since 2002, they are bioindicators of marine plastics in the North Sea region, and data are needed to extend the programme to other parts of their distribution areas, such as the Arctic. In this study, we provide data on ingested plastics by fulmars collected in 1997 in Kongsfjorden, Svalbard. An extraction protocol with KOH was used and for half of the birds, the gizzard and the proventricular contents were analysed separately. Ninety-one percent of the birds had ingested at least one piece of plastic with an average of 10.3 (±11.9 SD) pieces. The gizzards contained significantly more plastics than the proventriculus. Hard fragments and polyethylene were the most common characteristics. Twelve percent of the birds exceeded the EcoQO value of 0.1 g.
2022
Thyroid hormone disrupting chemicals (THDCs) are of major concern in ecotoxicology. With the increased number of emerging chemicals on the market there is a need to screen for potential THDCs in a cost-efficient way, and in silico modeling is an alternative to address this issue. In this study homology modeling and docking was used to screen a list of 626 compounds for potential thyroid hormone disrupting properties in two gull species. The tested compounds were known contaminants or emerging contaminants predicted to have the potential to reach the Arctic. Models of transthyretin (TTR) and thyroid hormone receptor α and β (TRα and TRβ) from the Arctic top predator glaucous gull (Larus hyperboreus) and temperate predator herring gull (Larus argentatus) were constructed and used to predict the binding affinity of the compounds to the thyroid hormone (TH) binding sites. The modeling predicted that 28, 4 and 330 of the contaminants would bind to TRα, TRβ and TTR respectively. These compounds were in general halogenated, aromatic and had polar functional groups, like that of THs. However, the predicted binders did not necessarily have all these properties, such as the per- and polyfluoroalkyl substances that are not aromatic and still bind to the proteins.
2020
We have used the NASA Goddard Institute for Space Studies (GISS) Earth system model GISS-E2.1 to study the future budgets and trends of global and regional CH4 under different emission scenarios, using both the prescribed GHG concentrations as well as the interactive CH4 sources and sinks setup of the model, to quantify the model performance and its sensitivity to CH4 sources and sinks. We have used the Current Legislation (CLE) and the maximum feasible reduction (MFR) emission scenarios from the ECLIPSE V6b emission database to simulate the future evolution of CH4 sources, sinks, and levels from 2015 to 2050. Results show that the prescribed GHG version underestimates the observed surface CH4 concentrations during the period between 1995 and 2023 by 1%, with the largest underestimations over the continental emission regions, while the interactive simulation underestimates the observations by 2%, with the biases largest over oceans and smaller over the continents. For the future, the MFR scenario simulates lower global surface CH4 concentrations and burdens compared to the CLE scenario, however in both cases, global surface CH4 and burden continue to increase through 2050 compared to present day. In addition, the interactive simulation calculates slightly larger O3 and OH mixing ratios, in particular over the northern hemisphere, leading to slightly decreased CH4 lifetime in the present day. The CH4 forcing is projected to increase in both scenarios, in particular in the CLE scenario, from 0.53 W m−2 in the present day to 0.73 W m−2 in 2050. In addition, the interactive simulations estimate slightly higher tropospheric O3 forcing compared to prescribed simulations, due to slightly higher O3 mixing ratios simulated by the interactive models. While in the CLE, tropospheric O3 forcing continues to increase, the MFR scenario leads to a decrease in tropospheric O3 forcing, leading to a climate benefit. Our results highlight that in the interactive models, the response of concentrations are not necessarily linear with the changes in emissions as the chemistry is non-linear, and dependent on the oxidative capacity of the atmosphere. Therefore, it is important to have the CH4 sources and chemical sinks to be represented comprehensively in climate models.
2025
The role of SVOCs in the initial film formation and soiling of unvarnished paintings
In recent years increased research efforts and environmental improvements have been directed towards the preventive conservation of the monumental, unvarnished oil paintings on canvas (1909–1916) by Edvard Munch (1863–1944) housed in the University of Oslo Aula. Surface soiling of the paintings has been a documented issue since their display, and the modern-day effect of air-borne particulates and gases on the painting surfaces remains hitherto undocumented. For the first time in the Aula, this study has measured the in-situ time-dependent mass deposit of air pollution onto vertical surfaces over the period of one year (2021–2022). Concomitant measurements of the concentrations of ozone (O3) and nitrogen dioxide (NO2) were also taken, to complement periodic data from 2020. The mass deposit was measured through incremental weight changes of Teflon membrane filters, and quartz filters for analysis of elemental/organic carbon (EC/OC), whilst the gaseous pollutants were measured using passive gas samplers. Indoor-to-outdoor ratios (I/O) for O3 were noted to be higher than those suggested by earlier data, whereas NO2 I/O ratios were found to be lower, indicating a stronger oxidising atmosphere in the Aula. Just over half of the deposited mass on the quartz filters was found to be OC, with no EC detected. Surprisingly, an overall decrease in the mass deposit from three to twelve months was measured on the Teflon membrane filters. It was hypothesised, based on models reported in the literature, that the source of the OC on the filters was mainly gaseous, semi-volatile organic compounds (SVOCs), which were present in an adsorption/desorption equilibrium that was dependent on possible SVOC emission episodes, relative humidity levels, gaseous oxidative reactions and the particulate matter deposit. A simple mathematical model is proposed to rationalise the observed mass deposits on the filters, together with a discussion of uncertainties affecting the measurements. The hypothesis preliminarily indicates the possible and previously unconsidered role of SVOCs on the initial film formation of soiling layers on the Aula paintings, and could bear implications for their monitoring in the preventive care of unvarnished oil paintings on canvas.
2023
Rapid growth in urbanization and industrialization leads to an increase in air pollution and poor air quality. Because of its adverse effects on the natural environment and human health, it’s been declared a “silent public health emergency”. To deal with this global challenge, accurate prediction of air pollution is important for stakeholders to take required actions. In recent years, deep learning-based forecasting models show promise for more effective and efficient forecasting of air quality than other approaches. In this study, we made a comparative analysis of various deep learning-based single-step forecasting models such as long short term memory (LSTM), gated recurrent unit (GRU), and a statistical model to predict five air pollutants namely Nitrogen Dioxide (NO 2 ), Ozone (O 3 ), Sulphur Dioxide (SO 2 ), and Particulate Matter (PM2.5, and PM10). For empirical evaluation, we used a publicly available dataset collected in Northern Ireland, using an air quality monitoring station situated in Belfast city centre. It measures the concentration of air pollutants. The performance of forecasting models is evaluated based on three performance metrics: (a) root mean square error (RMSE), (b) mean absolute error (MAE) and (c) R-squared ( R2 ). The result shows that deep learning models consistently achieved the least RMSE compared to the statistical models with a value of 0.59. In addition, the deep learning model is also found to have the highest R2 score of 0.856.
2023
The Arctic is one of the most rapidly warming regions of the Earth, with predicted temperature increases of 5–7 ∘C and the accompanying extensive retreat of Arctic glacial systems by 2100. Retreating glaciers will reveal new land surfaces for microbial colonisation, ultimately succeeding to tundra over decades to centuries. An unexplored dimension to these changes is the impact upon the emission and consumption of halogenated organic compounds (halocarbons). Halocarbons are involved in several important atmospheric processes, including ozone destruction, and despite considerable research, uncertainties remain in the natural cycles of some of these compounds. Using flux chambers, we measured halocarbon fluxes across the glacier forefield (the area between the present-day position of a glacier's ice-front and that at the last glacial maximum) of a high-Arctic glacier in Svalbard, spanning recently exposed sediments (<10 years) to approximately 1950-year-old tundra. Forefield land surfaces were found to consume methyl chloride (CH3Cl) and methyl bromide (CH3Br), with both consumption and emission of methyl iodide (CH3I) observed. Bromoform (CHBr3) and dibromomethane (CH2Br2) have rarely been measured from terrestrial sources but were here found to be emitted across the forefield. Novel measurements conducted on terrestrial cyanobacterial mats covering relatively young surfaces showed similar measured fluxes to the oldest, vegetated tundra sites for CH3Cl, CH3Br, and CH3I (which were consumed) and for CHCl3 and CHBr3 (which were emitted). Consumption rates of CH3Cl and CH3Br and emission rates of CHCl3 from tundra and cyanobacterial mat sites were within the ranges reported from older and more established Arctic tundra elsewhere. Rough calculations showed total emissions and consumptions of these gases across the Arctic were small relative to other sources and sinks due to the small surface area represented by glacier forefields. We have demonstrated that glacier forefields can consume and emit halocarbons despite their young age and low soil development, particularly when cyanobacterial mats are present.
2020
To estimate the oxidative potential (OP) of particulate matter (PM), two commonly used cell-free, molecular probes were applied: dithiothreitol (DTT) and dichloro-dihydro-fluorescein diacetate (DCFH-DA), and their performance was compared with 9,10-bis (phenylethynyl) anthracene-nitroxide (BPEAnit). To the best of our knowledge, this is the first study in which the performance of the DTT and DCFH has been compared with the BPEAnit probe. The average concentrations of PM, organic carbon (OC) and elemental carbon (EC) for fine (PM2.5) and coarse (PM10) particles were determined. The results were 44.8 ± 13.7, 9.8 ± 5.1 and 9.3 ± 4.8 µg·m−3 for PM2.5 and 75.5 ± 25.1, 16.3 ± 8.7 and 11.8 ± 5.3 µg·m−3 for PM10, respectively, for PM, OC and EC. The water-soluble organic carbon (WSOC) fraction accounted for 42 ± 14% and 28 ± 9% of organic carbon in PM2.5 and PM10, respectively. The average volume normalized OP values for the three assays depended on both the sampling periods and the PM fractions. The OPBPEAnit had its peak at 2 p.m.; in the afternoon, it was three times higher compared to the morning and late afternoon values. The DCFH and BPEAnit results were correlated (r = 0.64), while there was no good agreement between the BPEAnit and the DTT (r = 0.14). The total organic content of PM does not necessarily represent oxidative capacity and it shows varying correlation with the OP. With respect to the two PM fractions studied, the OP was mostly associated with smaller particles.
2019
In this study, we use the Whole Atmosphere Community Climate Model, forced by present-day atmospheric composition and coupled to a Slab Ocean Model, to simulate the state of the climate under grand solar minimum forcing scenarios. Idealized experiments prescribe time-invariant solar irradiance reductions that are either uniform (percentage-wise) across the total solar radiation spectrum (TOTC) or spectrally localized in the ultraviolet (UV) band (SCUV). We compare the equilibrium condition of these experiments with the equilibrium condition of a control simulation, forced by perpetual solar maximum conditions. In SCUV, we observe large stratospheric cooling due to ozone reduction. In both the Northern Hemisphere (NH) and the Southern Hemisphere (SH), this is accompanied by a weakening of the polar night jet during the cold season. In TOTC, dynamically induced polar stratospheric cooling is observed in the transition seasons over the NH, without any ozone deficit. The global temperature cooling values, compared with the control climate, are 0.55±0.03 K in TOTC and 0.39±0.03 K in SCUV. The reductions in total meridional heat transport outside of the subtropics are similar in the two experiments, especially in the SH. Despite substantial differences in stratospheric forcing, similarities exist between the two experiments, such as cloudiness; meridional heating transport in the SH; and strong cooling in the NH during wintertime, although this cooling affects two different regions, namely, North America in TOTC and the Euro–Asian continent in SCUV.
2023
A comprehensive quantification of global nitrous oxide sources and sinks
Nitrous oxide (N2O), like carbon dioxide, is a long-lived greenhouse gas that accumulates in the atmosphere. Over the past 150 years, increasing atmospheric N2O concentrations have contributed to stratospheric ozone depletion1 and climate change2, with the current rate of increase estimated at 2 per cent per decade. Existing national inventories do not provide a full picture of N2O emissions, owing to their omission of natural sources and limitations in methodology for attributing anthropogenic sources. Here we present a global N2O inventory that incorporates both natural and anthropogenic sources and accounts for the interaction between nitrogen additions and the biochemical processes that control N2O emissions. We use bottom-up (inventory, statistical extrapolation of flux measurements, process-based land and ocean modelling) and top-down (atmospheric inversion) approaches to provide a comprehensive quantification of global N2O sources and sinks resulting from 21 natural and human sectors between 1980 and 2016. Global N2O emissions were 17.0 (minimum–maximum estimates: 12.2–23.5) teragrams of nitrogen per year (bottom-up) and 16.9 (15.9–17.7) teragrams of nitrogen per year (top-down) between 2007 and 2016. Global human-induced emissions, which are dominated by nitrogen additions to croplands, increased by 30% over the past four decades to 7.3 (4.2–11.4) teragrams of nitrogen per year. This increase was mainly responsible for the growth in the atmospheric burden. Our findings point to growing N2O emissions in emerging economies—particularly Brazil, China and India. Analysis of process-based model estimates reveals an emerging N2O–climate feedback resulting from interactions between nitrogen additions and climate change. The recent growth in N2O emissions exceeds some of the highest projected emission scenarios3,4, underscoring the urgency to mitigate N2O emissions.
2020