Found 10483 publications. Showing page 253 of 420:
2003
2014
Global black carbon emissions from 2015-2022 constrained by observations and transport modelling
Black carbon (BC) is a product of incomplete combustion, is climate relevant and has negative impacts on human health. It absorbs radiation as an aerosol in the atmosphere, but also changes the albedo of snow covered surfaces and leads to earlier melting. The origins are either anthropogenic or natural, with different annual cycles. While anthropogenic sources like domestic burning peak in the winter, natural sources like wild fires and agricultural burning peak during spring and summer. Due to its short lifetime are the global atmospheric concentrations highly variable.We use ground based observational data from different global networks, and the atmospheric transport model FLEXPART driven by ERA5 meteorological analysis, emission inventories and the inversion framework FLEXINVERT. By minimizing the mismatch modelled and observed BC concentration we improve the emission inventories for natural emissions (GFAS) and anthropogenic emissions (LRTAP). For every year up to 50 stations are used and each observation is matched with a 50 day FLEXPART backward calculation.We discuss the distribution and sources of global BC aerosols over the period 2015 to 2022 and compare existing emission inventories with the improved constraints of the global BC emissions derived with the FLEXINVERT inversion framework.
2026
Global Atmospheric Microplastics Emissions Estimated Using Constrained Bayesian Inverse Modeling
We present an analysis of global atmospheric microplastics (MPs) concentration and deposition measurements using constrained Bayesian inverse modeling to estimate global MPs emissions. The proposed Bayesian framework explicitly accounts for unknown ratios between size fractions inherent to MPs measurements and incorporates prior emission information to stabilize the inversion. The coupling between observations and unknown emissions is established using the atmospheric transport model FLEXPART version 11 operated in backward mode for each measurement. Model parameters are inferred using a variational Bayes approach, resulting in an iterative estimation scheme that updates both model parameters and the effective spatial structure of the computational domain. This methodology reduces the need for manual intervention during the inversion process and limits potential bias in the results. The resulting global MPs emission estimates are evaluated against previously published ones. Acknowledgment:This research has been supported by the Czech Science Foundation (grant no. GA24-10400S). N.E. was funded by the Norwegian Research Council (NFR) project MAGIC (No.: 334086). FLEXPART model simulations are cross-atmospheric research infrastructure services provided by ATMO-ACCESS (EU grant agreement No 101008004). The computations were performed on resources provided by Sigma2 - the National Infrastructure for High Performance Computing and Data Storage in Norway.
2026
Global and regional trends of atmospheric sulfur
The profound changes in global SO2 emissions over the last decades have affected atmospheric composition on a regional and global scale with large impact on air quality, atmospheric deposition and the radiative forcing of sulfate aerosols. Reproduction of historical atmospheric pollution levels based on global aerosol models and emission changes is crucial to prove that such models are able to predict future scenarios. Here, we analyze consistency of trends in observations of sulfur components in air and precipitation from major regional networks and estimates from six different global aerosol models from 1990 until 2015. There are large interregional differences in the sulfur trends consistently captured by the models and observations, especially for North America and Europe. Europe had the largest reductions in sulfur emissions in the first part of the period while the highest reduction came later in North America and East Asia. The uncertainties in both the emissions and the representativity of the observations are larger in Asia. However, emissions from East Asia clearly increased from 2000 to 2005 followed by a decrease, while in India a steady increase over the whole period has been observed and modelled. The agreement between a bottom-up approach, which uses emissions and process-based chemical transport models, with independent observations gives an improved confidence in the understanding of the atmospheric sulfur budget.
2019
2009
2016
2016
2024
Global agricultural ammonia emissions simulated with the ORCHIDEE land surface mode
Ammonia (NH3) is an important atmospheric constituent. It plays a role in air quality and climate through the formation of ammonium sulfate and ammonium nitrate particles. It has also an impact on ecosystems through deposition processes. About 85 % of NH3 global anthropogenic emissions are related to food and feed production and, in particular, to the use of mineral fertilizers and manure management. Most global chemistry transport models (CTMs) rely on bottom-up emission inventories, which are subject to significant uncertainties. In this study, we estimate emissions from livestock by developing a new module to calculate ammonia emissions from the whole agricultural sector (from housing and storage to grazing and fertilizer application) within the ORCHIDEE (Organising Carbon and Hydrology In Dynamic Ecosystems) global land surface model. We detail the approach used for quantifying livestock feed management, manure application, and indoor and soil emissions and subsequently evaluate the model performance. Our results reflect China, India, Africa, Latin America, the USA, and Europe as the main contributors to global NH3 emissions, accounting for 80 % of the total budget. The global calculated emissions reach 44 Tg N yr−1 over the 2005–2015 period, which is within the range estimated by previous work. Key parameters (e.g., the pH of the manure, timing of N application, and atmospheric NH3 surface concentration) that drive the soil emissions have also been tested in order to assess the sensitivity of our model. Manure pH is the parameter to which modeled emissions are the most sensitive, with a 10 % change in emissions per percent change in pH. Even though we found an underestimation in our emissions over Europe (−26 %) and an overestimation in the USA (+56 %) compared with previous work, other hot spot regions are consistent. The calculated emission seasonality is in very good agreement with satellite-based emissions. These encouraging results prove the potential of coupling ORCHIDEE land-based emissions to CTMs, which are currently forced by bottom-up anthropogenic-centered inventories such as the CEDS (Community Emissions Data System).
2023
NILU har, på oppdrag fra Glasopor AS ved Onsøy i Fredrikstad, kartlagt utslipp av støv fra anlegget og effekter på ytre miljø. Bedriften ønsker å oppgradere anlegget og øke produksjonen og har søkt om ny utslippstillatelse. I den forbindelse har Statsforvalteren oppfølgende spørsmål med krav om dokumentasjon knyttet til utslipp av støv og påvirkning på ytre miljø. For å svare på disse spørsmålene har NILU gjennomført målinger, beregning av utslipp og spredningsberegninger. Rapporten skal inngå i dokumentasjonen som oversendes norske myndigheter.
NILU
2024