We evaluate public health and climate impacts of low-sulphur fuels in global shipping. Using high-resolution emissions inventories, integrated atmospheric models, and health risk functions, we assess ...ship-related PM
pollution impacts in 2020 with and without the use of low-sulphur fuels. Cleaner marine fuels will reduce ship-related premature mortality and morbidity by 34 and 54%, respectively, representing a ~ 2.6% global reduction in PM
cardiovascular and lung cancer deaths and a ~3.6% global reduction in childhood asthma. Despite these reductions, low-sulphur marine fuels will still account for ~250k deaths and ~6.4 M childhood asthma cases annually, and more stringent standards beyond 2020 may provide additional health benefits. Lower sulphur fuels also reduce radiative cooling from ship aerosols by ~80%, equating to a ~3% increase in current estimates of total anthropogenic forcing. Therefore, stronger international shipping policies may need to achieve climate and health targets by jointly reducing greenhouse gases and air pollution.
Previous studies have reported a decrease in air pollution levels following the enforcement of lockdown measures during the first wave of the COVID-19 pandemic. However, these investigations were ...mostly based on simple pre-post comparisons using past years as a reference and did not assess the role of different policy interventions. This study contributes to knowledge by quantifying the association between specific lockdown measures and the decrease in NO
, O
, PM
, and PM
levels across 47 European cities. It also estimated the number of avoided deaths during the period. This paper used new modelled data from the Copernicus Atmosphere Monitoring Service (CAMS) to define business-as-usual and lockdown scenarios of daily air pollution trends. This study applies a spatio-temporal Bayesian non-linear mixed effect model to quantify the changes in pollutant concentrations associated with the stringency indices of individual policy measures. The results indicated non-linear associations with a stronger decrease in NO
compared to PM
and PM
concentrations at very strict policy levels. Differences across interventions were also identified, specifically the strong effects of actions linked to school/workplace closure, limitations on gatherings, and stay-at-home requirements. Finally, the observed decrease in pollution potentially resulted in hundreds of avoided deaths across Europe.
In Europe, more than one quarter of the adult population and one third of the children suffer from pollinosis, but the geographical variability is large. In Belgium, at least ~ 10% of the people ...develop allergies due to birch pollen. These patients may benefit from a forecasting system that raises alerts when episodes with huge amount of airborne birch pollen grains are expected. Such a forecast system for birch pollen was established for the Belgian territory in 2023 based on the pollen emission and transport model System for Integrated modeLling of Atmospheric coMposition (SILAM). The question, however, is which uncertainty in modelling and forecasting airborne pollen levels can be expected? Here, we assess the uncertainty in modelling airborne birch pollen levels near the surface using SILAM in a Monte Carlo error approach summarized by the relative Coefficient of Variation (CV%) as descriptive statistic for the season of 2018 in Belgium. For the major inputs that drive the birch pollen model—the amount and location of birch trees (0.1° × 0.1° map), the start and end of the birch pollen season (1° × 1° map), and the ripening temperature of birch catkins—sets of 100 randomly sampled data layers were prepared for running SILAM 100 times. For each set of model input, 100 spatio-temporal maps of airborne birch pollen levels were produced and its spread was quantified by the CV%. We show that the spatial uncertainty of pollen emissions sources in SILAM is substantially high, but that the uncertainties of the parameters determining the start and end of the season are at least equally important. By accumulating the effects of all investigated model input uncertainties including the impact of the catkins-ripening temperature, CV% values of 50% and more are obtained when quantifying the variation of the modelled airborne birch pollen levels. These errors are in line with reported values from the current reference method for monitoring airborne birch pollen grains near the surface.
Abstract
African desert dust is emitted and long-range transported with multiple effects on climate, air quality, cryosphere, and ecosystems. On 21–23 February 2021, dust from a sand and dust storm ...in northern Africa was transported to Finland, north of 60°N. The episode was predicted 5 days in advance by the global operational SILAM forecast, and its key features were confirmed and detailed by a retrospective analysis. The scavenging of dust by snowfall and freezing rain in Finland resulted in a rare case of substantial mineral dust contamination of snow surfaces over a large area in the southern part of the country. A citizen science campaign was set up to collect contaminated snow samples prepared according to the scientists’ instructions. The campaign gained wide national interest in television, radio, newspapers and social media, and dust samples were received from 525 locations in Finland, up to 64.3°N. The samples were utilised in investigating the ability of an atmospheric dispersion model to simulate the dust episode. The analysis confirmed that dust came from a wide Sahara and Sahel area from 5000 km away. Our results reveal the features of this rare event and demonstrate how deposition samples can be used to evaluate the skills and limitations of current atmospheric models in simulating transport of African dust towards northern Europe.
In the Arctic areas, the influence of global climate change is enhanced. Enabling a better understanding of the changes in the Arctic environment is of the utmost importance. The deposition of local ...and long-range transported air pollutants includes light-absorbing aerosols, such as black carbon (BC), which darken bright surfaces and induce snow melt. In 2009–2013, surface snow was sampled on a weekly basis during autumn, winter and spring at the Arctic Space Center of the Finnish Meteorological Institute in Sodankylä, which is located north of the Arctic Circle (67.37° N, 26.63° E). Snow samples were analyzed for BC with an Organic/Elemental Carbon Aerosol (OCEC) analyzer. These data were combined with SILAM modeling (System for Integrated modeLing of Atmospheric coMposition) to reveal the origin and temporal (weekly, monthly, and seasonal) variability of black carbon in seasonal snow. Quantitative footprint calculations for the BC observations were performed with the SILAM-model considering emission sources at all heights and including also the sensitivity to the local and near-surface sources. The median BC concentration in snow was 25 μg/kg (number of samples n = 107, skewness γ1 = 0.12, 75th percentile Q3 = 42 μg/kg), determined as μg-EC/L-H2O. During snow accumulation season, the median surface snow black carbon concentration was 21 μg/kg (n = 78, γ1 = 1.5, Q3 = 33 μg/kg), and during melt season, it was 57 μg/kg (n = 29, γ1 = 2.2, Q3 = 85 μg/kg). The melt period was identified using snow depth data from the Sodankylä station. The highest values in spring represented the enrichment of BC to the snow surface due to seasonal snow melt. The spring melt BC enrichment ratio was 2.7 (calculated as the ratio of median spring melt season concentration to median accumulation season snow concentration). The results showed that increased surface snow BC concentrations (>30 μg/kg) were due to air masses originating from the Murmansk region in Russia, where smelting and mining industries are located. The temporal variability of BC in snow was high and depended on atmospheric and cryospheric processes, mostly the origin of BC due to atmospheric transport and dry and wet deposition processes, as well as post-depositional snow processes.
This review analyzes the state and recent progress in the field of information support for pollen allergy sufferers. For decades, information available for the patients and allergologists consisted ...of pollen counts, which are vital but insufficient. New technology paves the way to substantial increase in amount and diversity of the data. This paper reviews old and newly suggested methods to predict pollen and air pollutant concentrations in the air and proposes an allergy risk concept, which combines the pollen and pollution information and transforms it into a qualitative risk index. This new index is available in an app (Mobile Airways Sentinel NetworK-air) that was developed in the frame of the European Union grant Impact of Air POLLution on sleep, Asthma and Rhinitis (a project of European Institute of Innovation and Technology-Health). On-going transformation of the pollen allergy information support is based on new technological solutions for pollen and air quality monitoring and predictions. The new information-technology and artificial-intelligence-based solutions help to convert this information into easy-to-use services for both medical practitioners and allergy sufferers.
We evaluate the statistical properties of low-level jets (LLJs) observed by means of a network of Doppler sodars in the Moscow region, Russia. Continuous long-term measurements of the echo-signal ...intensity and wind-velocity profiles were carried out in July 2005 and in 2008–2010 synchronously in the centre of Moscow and at a rural site. The summertime nocturnal LLJs have a very clear diurnal cycle and exhibit features predicted by the Blackadar mechanism. In contrast, the long-lasting wintertime jets do not have any clear diurnal variability. The urban environment strongly influences LLJs in both seasons: above the city LLJs are higher, weaker and observed more rarely than at the rural site. In very cold periods (air temperature below −8°C) no LLJs were observed over the city, instead convection emerged in the urban boundary layer. The results are based on observations made in July 2005, January and December 2009, and January 2011.
The Innovative Strategies for Observations in the Arctic Atmospheric Boundary Layer Program (ISOBAR) is a research project investigating stable atmospheric boundary layer (SBL) processes, whose ...representation still poses significant challenges in state-of-the-art numerical weather prediction (NWP) models. In ISOBAR ground-based flux and profile observations are combined with boundary layer remote sensing methods and the extensive usage of different unmanned aircraft systems (UAS). During February 2017 and 2018 we carried out two major field campaigns over the sea ice of the northern Baltic Sea, close to the Finnish island of Hailuoto at 65°N. In total 14 intensive observational periods (IOPs) resulted in extensive SBL datasets with unprecedented spatiotemporal resolution, which will form the basis for various numerical modeling experiments. First results from the campaigns indicate numerous very stable boundary layer (VSBL) cases, characterized by strong stratification, weak winds, and clear skies, and give detailed insight in the temporal evolution and vertical structure of the entire SBL. The SBL is subject to rapid changes in its vertical structure, responding to a variety of different processes. In particular, we study cases involving a shear instability associated with a low-level jet, a rapid strong cooling event observed a few meters above ground, and a strong wave-breaking event that triggers intensive near-surface turbulence. Furthermore, we use observations from one IOP to validate three different atmospheric models. The unique finescale observations resulting from the ISOBAR observational approach will aid future research activities, focusing on a better understanding of the SBL and its implementation in numerical models.
Continuous sodar measurements of wind profiles have been carried out at the Zvenigorod Scientific Station of the Obukhov Institute of Atmospheric Physics since 2008. The station is located in a ...slightly inhomogeneous rural area about 45 km west of Moscow, Russia. The data were used to determine the parameters of wind and turbulence within low-level jets in the stable atmospheric boundary layer (ABL). Along with the mean velocity profiles, the profiles of variances of wind speed components from the sodar and the profiles of temperature from a microwave radiometer have been used to quantify turbulence and thermal stratification. Data from two sonic anemometers were used to get the near-surface parameters. The typical standard deviation of the vertical wind component sigma sub(w) within the low-level jet is about 5% of the maximum wind speed in the jet. No noticeable vertical variation of sigma sub(w) across the jets was detected in several earlier sodar campaigns, and it was not found in the present study. An increase in horizontal variances was detected in zones of substantial wind shear, which agrees with earlier published lidar data. Quasi-periodic structures in the sodar return signal, which appear in sodar echograms as braid-shaped patterns, were found to emerge preferably when a substantial increase of wind shear occurs at the top of the stable ABL. The braid patterns in the sodar echograms were not accompanied by any noticeable increase of observed sigma sub(w), which disagrees with earlier data and indicates that such patterns may originate from various phenomena.
The aim of the research project “Innovative Strategies for Observations in the Arctic Atmospheric Boundary Layer (ISOBAR)” is to substantially increase the understanding of the stable atmospheric ...boundary layer (SBL) through a combination of well-established and innovative observation methods as well as by models of different complexity. During three weeks in February 2017, a first field campaign was carried out over the sea ice of the Bothnian Bay in the vicinity of the Finnish island of Hailuoto. Observations were based on ground-based eddy-covariance (EC), automatic weather stations (AWS) and remote-sensing instrumentation as well as more than 150 flight missions by several different Unmanned Aerial Vehicles (UAVs) during mostly stable and very stable boundary layer conditions. The structure of the atmospheric boundary layer (ABL) and above could be resolved at a very high vertical resolution, especially close to the ground, by combining surface-based measurements with UAV observations, i.e., multicopter and fixed-wing profiles up to 200 m agl and 1800 m agl, respectively. Repeated multicopter profiles provided detailed information on the evolution of the SBL, in addition to the continuous SODAR and LIDAR wind measurements. The paper describes the campaign and the potential of the collected data set for future SBL research and focuses on both the UAV operations and the benefits of complementing established measurement methods by UAV measurements to enable SBL observations at an unprecedented spatial and temporal resolution.
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