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Unexpected anthropogenic emission decreases explain recent atmospheric mercury concentration declines
Get PDFAnthropogenic activities emit ~2,000 Mg y−1 of the toxic pollutant mercury (Hg) into the atmosphere, leading to long-range transport and deposition to remote ecosystems. Global anthropogenic emission inventories report increases in Northern Hemispheric (NH) Hg emissions during the last three decades, in contradiction with the observed decline in atmospheric Hg concentrations at NH measurement stations. Many factors can obscure the link between anthropogenic emissions and atmospheric Hg concentrations, including trends in the reemissions of previously released anthropogenic (“legacy”) Hg, atmospheric sink variability, and spatial heterogeneity of monitoring data. Here, we assess the observed trends in gaseous elemental mercury (Hg0) in the NH and apply biogeochemical box modeling and chemical transport modeling to understand the trend drivers. Using linear mixed effects modeling of observational data from 51 stations, we find negative Hg0 trends in most NH regions, with an overall trend for 2005 to 2020 of −0.011 ± 0.006 ng m−3 y−1 (±2 SD). In contrast to existing emission inventories, our modeling analysis suggests that annual NH anthropogenic emissions must have declined by at least 140 Mg between the years 2005 and 2020 to be consistent with observed trends. Faster declines in 95th percentile Hg0 values than median values in Europe, North America, and East Asian measurement stations corroborate that the likely cause is a decline in nearby anthropogenic emissions rather than background legacy reemissions. Our results are relevant for evaluating the effectiveness of the Minamata Convention on Mercury, demonstrating that existing emission inventories are incompatible with the observed Hg0 declines.publishedVersio
Long-term meteorology-adjusted and unadjusted trends of PM2.5 using the AirGAM model over Delhi, 2007–2022
Get PDFThis 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 (ppublishedVersio
Two Stage Feature Engineering to Predict Air Pollutants in Urban Areas
Get PDFAir 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.acceptedVersio
Opinion: New directions in atmospheric research offered by research infrastructures combined with open and data-intensive science
Get PDFThe acquisition and dissemination of essential information for understanding global biogeochemical interactions between the atmosphere and ecosystems and how climate–ecosystem feedback loops may change atmospheric composition in the future comprise a fundamental prerequisite for societal resilience in the face of climate change. In particular, the detection of trends and seasonality in the abundance of greenhouse gases and short-lived climate-active atmospheric constituents is an important aspect of climate science. Therefore, easy and fast access to reliable, long-term, and high-quality observational environmental data is recognised as fundamental to research and the development of environmental forecasting and assessment services. In our opinion article, we discuss the potential role that environmental research infrastructures in Europe (ENVRI RIs) can play in the context of an integrated global observation system. In particular, we focus on the role of the atmosphere-centred research infrastructures ACTRIS (Aerosol, Clouds and Trace Gases Research Infrastructure), IAGOS (In-service Aircraft for a Global Observing System), and ICOS (Integrated Carbon Observation System), also referred to as ATMO-RIs, with their capabilities for standardised collection and provision of long-term and high-quality observational data, complemented by rich metadata. The ATMO-RIs provide data through open access and offer data interoperability across different research fields including all fields of environmental sciences and beyond. As a result of these capabilities in data collection and provision, we elaborate on the novel research opportunities in atmospheric sciences which arise from the combination of open-access and interoperable observational data, tools, and technologies offered by data-intensive science and the emerging collaboration platform ENVRI-Hub, hosted by the European Open Science Cloud (EOSC).publishedVersio
A critical review to identify data gaps and improve risk assessment of bisphenol A alternatives for human health
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Multi-Scale Soil Salinization Dynamics From Global to Pore Scale: A Review
Get PDFSoil salinization refers to the accumulation of water-soluble salts in the upper part of the soil profile. Excessive levels of soil salinity affects crop production, soil health, and ecosystem functioning. This phenomenon threatens agriculture, food security, soil stability, and fertility leading to land degradation and loss of essential soil ecosystem services that are fundamental to sustaining life. In this review, we synthesize recent advances in soil salinization at various spatial and temporal scales, ranging from global to core, pore, and molecular scales, offering new insights and presenting our perspective on potential future research directions to address key challenges and open questions related to soil salinization. Globally, we identify significant challenges in understanding soil salinity, which are (a) the considerable uncertainty in estimating the total area of salt-affected soils, (b) geographical bias in ground-based measurements of soil salinity, and (c) lack of information and data detailing secondary salinization processes, both in dry- and wetlands, particularly concerning responses to climate change. At the core scale, the impact of salt precipitation with evolving porous structure on the evaporative fluxes from porous media is not fully understood. This knowledge is crucial for accurately predicting soil water loss due to evaporation. Additionally, the effects of transport properties of porous media, such as mixed wettability conditions, on the saline water evaporation and the resulting salt precipitation patterns remain unclear. Furthermore, effective continuum equations must be developed to accurately represent experimental data and pore-scale numerical simulations.publishedVersio
Per- and polyfluoroalkyl substances (PFAS) in surface sediments of the North-east Atlantic Ocean: A non-natural PFAS background
Get PDFThe extreme persistence and environmental mobility of per- and polyfluoroalkyl substances (PFAS) make their presence ubiquitous in the marine environment. Target analysis of 20 most common PFAS revealed the presence of nine perfluoroalkyl acids at low levels in surface sediments from five Norwegian marine areas covering the vast region from the eastern North Sea in the south to the Arctic Ocean north of Svalbard in the north. After correcting for sediment characteristics, no substantial difference in the sum of the nine PFAS (Σ9PFAS) between the five areas was found. Among separate compounds, PFOS, PFOA and PFNA dominate sample composition. Only two compounds, PFOS and PFUnDA, showed a statistically significant difference for one of the areas, the levels of these compounds being somewhat higher in the southernmost area than in the other areas. This may be due to local inputs in the fjords in this area. Open-sea and coastal sediments of the North-east Atlantic outside of locations with significant local sources seem to share a common, anthropogenic “PFAS background”, which may be part of a larger, global pattern.publishedVersio
Emission ensemble approach to improve the development of multi-scale emission inventories
Get PDFMany studies have shown that emission inventories are one of the inputs with the most critical influences on the results of air quality modelling. Comparing emission inventories among themselves is, therefore, essential to build confidence in emission estimates. In this work, we extend the approach of Thunis et al. (2022) to compare emission inventories by building a benchmark that serves as a reference for comparisons. This benchmark is an ensemble that is based on three state-of-the-art EU-wide inventories: CAMS-REG, EMEP and EDGAR. The ensemble-based methodology screens differences between inventories and the ensemble. It excludes differences that are not relevant and identifies among the remaining ones those that need special attention. We applied the ensemble-based screening to both an EU-wide and a local (Poland) inventory. The EU-wide analysis highlighted a large number of inconsistencies. While the origin of some differences between EDGAR and the ensemble can be identified, their magnitude remains to be explained. These differences mostly occur for SO2 (sulfur oxides), PM (particulate matter) and NMVOC (non-methane volatile organic carbon) for the industrial and residential sectors and reach a factor of 10 in some instances. Spatial inconsistencies mostly occur for the industry and other sectors. At the local scale, inconsistencies relate mostly to differences in country sectorial shares that result from different sectors/activities being accounted for in the two types of inventories. This is explained by the fact that some emission sources are omitted in the local inventory due to a lack of appropriate geographically allocated activity data. We identified sectors and pollutants for which discussion between local and EU-wide emission compilers would be needed in order to reduce the magnitude of the observed differences (e.g. in the residential and industrial sectors). The ensemble-based screening proved to be a useful approach to spot inconsistencies by reducing the number of necessary inventory comparisons. With the progressive resolution of inconsistencies and associated inventory improvements, the ensemble will improve. In this sense, we see the ensemble as a useful tool to motivate the community around a single common benchmark and monitor progress towards the improvement of regionally and locally developed emission inventories.publishedVersio
Stepping-up accurate quantification of chlorinated paraffins: Successful certification of the first matrix reference material
Get PDFBackground
Chlorinated paraffins (CPs) are industrial chemicals categorised as persistent organic pollutants because of their toxicity, persistency and tendency to long-range transport, bioaccumulation and biomagnification. Despite having been the subject of environmental attention for decades, analytical methods for CPs still struggle reaching a sufficient degree of accuracy. Among the issues negatively impacting the quantification of CPs, the unavailability of well-characterised standards, both as pure substances and as matrix (certified) reference materials (CRMs), has played a major role. The focus of this study was to provide a matrix CRM as quality control tool to improve the comparability of CPs measurement results.
Results
We present the process of certification of ERM®-CE100, the first fish reference material assigned with certified values for the mass fraction of short-chain and medium-chain chlorinated paraffins (SCCPs and MCCPs, respectively). The certification was performed in accordance with ISO 17034:2016 and ISO Guide 35:2017, with the value assignment step carried out via an intercomparison of laboratories of demonstrated competence in CPs analysis and applying procedures based on different analytical principles. After confirmation of the homogeneity and stability of the CRM, two certified values were assigned for SCCPs, depending on the calibrants used: 31 ± 9 μg kg−1 and 23 ± 7 μg kg−1. The MCCPs certified value was established as 44 ± 17 μg kg−1. All assigned values are relative to wet weight in the CRM that was produced as a fish paste to enhance similarity to routine biota samples.
Significance and novelty
The fish tissue ERM-CE100 is the first matrix CRM commercially available for the analysis of CPs, enabling analytical laboratories to improve the accuracy and the metrological traceability of their measurements. The certified CPs values are based on results obtained by both gas and liquid chromatography coupled with various mass spectrometric techniques, offering thus a broad validity to laboratories employing different analytical methods and equipment.publishedVersio
Spatial Source Contribution and Interannual Variation in Deposition of Dust Aerosols Over the Chinese Loess Plateau
Get PDFThe Chinese Loess Plateau (CLP) in northern China is home to one of the most prominent loess records in the world, reflecting past eolian dust activity in East Asia. However, their interpretation is hampered by ambiguity in the origin of loess-forming dust and an incomplete understanding of the circulation forcing dust accumulation. In this study, we used a novel modeling approach combining a dust emission model FLEXDUST with simulated back trajectories from FLEXPART to trace the dust back to where it was emitted. Over 21 years (1999–2019), we modeled back trajectories for fine (∼2 μm) and super-coarse (∼20 μm) dust particles at six CLP sites during the peak dust storm season from March to May. FLEXPART source-receptor relationships are combined with the dust emission inventory from FLEXDUST to create site-dependent high-resolution maps of the source contribution of deposited dust. The nearby dust emission areas were found to be the main source of dust to the CLP. Dust deposition across the CLP was found to predominantly occur via wet removal, with also some super-coarse dust from distant emission regions being wet deposited following high-level tropospheric transport. The high topography located on the downwind side of the emission area plays an essential role in forcing the emitted super-coarse dust upward. On an interannual scale, the phase of the Arctic Oscillation in the preceding winter was found to have a strong association with the spring deposition rate on the CLP, while the strength of the East Asian Winter Monsoon was less influential.publishedVersio