Effects of boundary layer particle formation on cloud droplet number and changes in cloud albedo from 1850 to 2000

We use a global aerosol microphysics model to estimate the effect of particle formation through activation nucleation in the boundary layer (BL) on cloud droplet number concentration (CDNC) on global and regional scales. The calculations are carried out for years 1850 and 2000 using historical emissions inventories for primary particles and aerosol precursor gases. Predicted CDNC in 2000 are in good agreement with in-situ observations when activation nucleation is included. We find that BL particle formation increases global annual mean CDNC by approximately the same relative amount in both years (16.0% in 1850 and 13.5% in 2000). As a result, global mean changes in cloud albedo are similar with and without BL particle formation. However, there are substantial regional effects of up to 50% enhancement or suppression of the 1850–2000 albedo change. Over most modern-day polluted northern hemisphere regions, including BL particle formation scheme suppresses the 1850–2000 increase in CDNC and cloud albedo because BL particle formation is already large in 1850. Over the Arctic the albedo change is suppressed by 23% in the annual mean and by 43% in summer when BL particle formation is taken into account. The albedo change of the persistent stratocumulus cloud deck west of Chile is enhanced by 49%

Large methane releases lead to strong aerosol forcing and reduced cloudiness

The release of vast quantities of methane into the atmosphere as a result of clathrate destabilization is a potential mechanism for rapid amplification of global warming. Previous studies have calculated the enhanced warming based mainly on the radiative effect of the methane itself, with smaller contributions from the associated carbon dioxide or ozone increases. Here, we study the effect of strongly elevated methane (CH4) levels on oxidant and aerosol particle concentrations using a combination of chemistry-transport and general circulation models. A 10-fold increase in methane concentrations is predicted to significantly decrease hydroxyl radical (OH) concentrations, while moderately increasing ozone (O3). These changes lead to a 70 % increase in the atmospheric lifetime of methane, and an 18 % decrease in global mean cloud droplet number concentrations (CDNC). The CDNC change causes a radiative forcing that is comparable in magnitude to the longwave radiative forcing ("enhanced greenhouse effect") of the added methane. Together, the indirect CH4-O3 and CH4-OH-aerosol forcings could more than double the warming effect of large methane increases. Our findings may help explain the anomalously large temperature changes associated with historic methane releases

Anthropogenic aerosol forcing - insights from multiple estimates from aerosol-climate models with reduced complexity

This study assesses the change in anthropogenic aerosol forcing from the mid-1970s to the mid-2000s. Both decades had similar global-mean anthropogenic aerosol optical depths but substantially different global distributions. For both years, we quantify (i) the forcing spread due to model-internal variability and (ii) the forcing spread among models. Our assessment is based on new ensembles of atmosphere-only simulations with five state-of-the-art Earth system models. Four of these models will be used in the sixth Coupled Model Intercomparison Project (CMIP6; Eyring et al., 2016). Here, the complexity of the anthropogenic aerosol has been reduced in the participating models. In all our simulations, we prescribe the same patterns of the anthropogenic aerosol optical properties and associated effects on the cloud droplet number concentration. We calculate the instantaneous radiative forcing (RF) and the effective radiative forcing (ERF). Their difference defines the net contribution from rapid adjustments. Our simulations show a model spread in ERF from -0.4 to -0.9 W m(-2). The standard deviation in annual ERF is 0.3 W m(-2), based on 180 individual estimates from each participating model. This result implies that identifying the model spread in ERF due to systematic differences requires averaging over a sufficiently large number of years. Moreover, we find almost identical ERFs for the mid-1970s and mid-2000s for individual models, although there are major model differences in natural aerosols and clouds. The model-ensemble mean ERF is -0.54 W m(-2) for the pre-industrial era to the mid-1970s and -0.59 W m(-2) for the pre-industrial era to the mid-2000s. Our result suggests that comparing ERF changes between two observable periods rather than absolute magnitudes relative to a poorly constrained pre-industrial state might provide a better test for a model's ability to represent transient climate changes.Peer reviewe

Intercomparison of modal and sectional aerosol microphysics representations within the same 3-D global chemical transport model

In the most advanced aerosol-climate models it is common to represent the aerosol particle size distribution in terms of several log-normal modes. This approach, motivated by computational efficiency, makes assumptions about the shape of the particle distribution that may not always capture the properties of global aerosol. Here, a global modal aerosol microphysics module (GLOMAP-mode) is evaluated and improved by comparing against a sectional version (GLOMAP-bin) and observations in the same 3-D global offline chemistry transport model. With both schemes, the model captures the main features of the global particle size distribution, with sub-micron aerosol approximately unimodal in continental regions and bi-modal in marine regions. Initial bin-mode comparisons showed that the current values for two size distribution parameter settings in the modal scheme (mode widths and inter-modal separation sizes) resulted in clear biases compared to the sectional scheme. By adjusting these parameters in the modal scheme, much better agreement is achieved against the bin scheme and observations. Annual mean surface-level mass of sulphate, sea-salt, black carbon (BC) and organic carbon (OC) are within 25% in the two schemes in nearly all regions. Surface level concentrations of condensation nuclei (CN), cloud condensation nuclei (CCN), surface area density and condensation sink also compare within 25% in most regions. However, marine CCN concentrations between 30° N and 30° S are systematically 25–60% higher in the modal model, which we attribute to differences in size-resolved particle growth or cloud-processing. Larger differences also exist in regions or seasons dominated by biomass burning and in free-troposphere and high-latitude regions. Indeed, in the free-troposphere, GLOMAP-mode BC is a factor 2–4 higher than GLOMAP-bin, likely due to differences in size-resolved scavenging. Nevertheless, in most parts of the atmosphere, we conclude that bin-mode differences are much less than model-observation differences, although some processes are missing in these runs which may pose a bigger challenge to modal schemes (e.g., boundary layer nucleation and ultra-fine sea-spray). The findings here underline the need for a spectrum of complexity in global models, with size-resolved aerosol properties predicted by modal schemes needing to be continually benchmarked and improved against freely evolving sectional schemes and observations

How our Dreams Changed During the COVID-19 Pandemic: Effects and Correlates of Dream Recall Frequency - a Multinational Study on 19,355 Adults

Objective: Many have reported odd dreams during the pandemic. Given that dreams are associated with mental health, understanding these changes could provide crucial information about wellbeing during the pandemic. This study explored associations between COVID-19 and dream recall frequency (DRF), and related social, health, and mental health factors. Methods: We conducted a cross-sectional web survey of 19,355 individuals in 14 countries from May to July 2020. We collected data on COVID-19, mental health, sleep and DRF during the pandemic. We performed McNemar Tests to compare low (<3 nights per week) and high DRF (≥3 nights per week) before and during COVID-19 and to evaluate changes in sleep variables segmented by DRF. Chi-square tests were conducted to compare characteristics between low and high DRF. Logistic regression analyses were conducted to examine associations between various independent variables and DRF. Results: Reports of high DRF during the pandemic were higher than before the pandemic (P<0.001). Female gender (aOR=1.25, 95% CI 1.10-1.41), nightmares (aOR=4.22, 95% CI 3.45-5.17), sleep talking (aOR= 2.36, 1.73-3.23), sleep maintenance problems (aOR=1.34, 95% CI 1.15-1.56), symptoms of REM sleep behavior disorder (RBD; aOR=1.24, 95% CI 1.09-1.41) and repeated disturbing thoughts (posttraumatic stress disorder (PTSD) symptoms) were associated with high DRF. Age group 55-64 years (aOR=0.69, 95% CI 0.58-0.83) reported less high DRF than younger participants. Unadjusted OR showed associations between depression, anxiety, and DRF; however, in adjusted regression depression (aOR= 0.71, 0.59-0.86) and anxiety (aOR=0.79, 95% CI 0.66-0.94) were negatively associated with high DRF. Conclusion and relevance: DRF was higher than pre-pandemic levels across four continents. DRF was associated with gender and parasomnias like nightmares and RBD symptoms, sleep maintenance problems, PTSD symptoms and negatively associated with depression and anxiety. The results implicate that COVID-19 is reflected in our dreams as an expression of the emotional intensity of the pandemic. Keywords: collective threat; mental health; parasomnia; sleep; sleep disorder.Peer reviewe

Dream-enactment behaviours during the COVID-19 pandemic: an international COVID-19 sleep study

There has been increasing concern about the long-term impact of coronavirus disease 2019 (COVID-19) as evidenced by anecdotal case reports of acute-onset parkinsonism and the polysomnographic feature of increased rapid eye movement sleep electromyographic activity. This study aimed to determine the prevalence and correlates of dream-enactment behaviours, a hallmark of rapid eye movement sleep behaviour disorder, which is a prodrome of α-synucleinopathy. This online survey was conducted between May and August 2020 in 15 countries/regions targeting adult participants (aged ≥18 years) from the general population with a harmonised structured questionnaire on sleep patterns and disorders, COVID-19 diagnosis and symptoms. We assessed dream-enactment behaviours using the Rapid Eye Movement Sleep Behaviour Disorder Single-Question Screen with an additional question on their frequency. Among 26,539 respondents, 21,870 (82.2%) answered all items that were analysed in this study (mean [SD] age 41.6&nbsp;[15.8]&nbsp;years; female sex 65.5%). The weighted prevalence of lifetime and weekly dream-enactment behaviours was 19.4% and 3.1% and were found to be 1.8- and 2.9-times higher in COVID-19-positive cases, respectively. Both lifetime and weekly dream-enactment behaviours were associated with young age, male sex, smoking, alcohol consumption, higher physical activity level, nightmares, COVID-19 diagnosis, olfactory impairment, obstructive sleep apnea symptoms, mood, and post-traumatic stress disorder features. Among COVID-19-positive cases, weekly dream-enactment behaviours were positively associated with the severity of COVID-19. Dream-enactment behaviours are common among the general population during the COVID-19 pandemic and further increase among patients with COVID-19. Further studies are needed to investigate the potential neurodegenerative effect of COVID-19

Global atmospheric particle formation from CERN CLOUD measurements

Fundamental questions remain about the origin of newly formed atmospheric aerosol particles because data from laboratory measurements have been insufficient to build global models. In contrast, gas-phase chemistry models have been based on laboratory kinetics measurements for decades. Here we build a global model of aerosol formation using extensive laboratory-measured nucleation rates involving sulfuric acid, ammonia, ions and organic compounds. The simulations and a comparison with atmospheric observations show that nearly all nucleation throughout the present-day atmosphere involves ammonia or biogenic organic compounds in addition to sulfuric acid. A significant fraction of nucleation involves ions, but the relatively weak dependence on ion concentrations indicates that for the processes studied variations in cosmic ray intensity do not significantly affect climate via nucleation in the present-day atmosphere

Evidence of atmospheric nanoparticle formation from emissions of marine microorganisms

International audienceEarth, as a whole, can be considered as a living organism emitting gases and particles into its atmosphere, in order to regulate its own temperature. In particular, oceans may respond to climate change by emitting particles that ultimately will influence cloud coverage. At the global scale, a large fraction of the aerosol number concentration is formed by nucleation of gas-phase species, but this process has never been directly observed above oceans. Here we present, using semicontrolled seawater-air enclosures, evidence that nucleation may occur from marine biological emissions in the atmosphere of the open ocean. We identify iodine-containing species as major precursors for new particle clusters’ formation, while questioning the role of the commonly accepted dimethyl sulfide oxidation products, in forming new particle clusters in the region investigated and within a time scale on the order of an hour. We further show that amines would sustain the new particle formation process by growing the new clusters to larger sizes. Our results suggest that iodine-containing species and amines are correlated to different biological tracers. These observations, if generalized, would call for a substantial change of modeling approaches of the sea-to-air interactions

Primary versus secondary contributions to particle number concentrations in the European boundary layer

It is important to understand the relative contribution of primary and secondary particles to regional and global aerosol so that models can attribute aerosol radiative forcing to different sources. In large-scale models, there is considerable uncertainty associated with treatments of particle formation (nucleation) in the boundary layer (BL) and in the size distribution of emitted primary particles, leading to uncertainties in predicted cloud condensation nuclei (CCN) concentrations. Here we quantify how primary particle emissions and secondary particle formation influence size-resolved particle number concentrations in the BL using a global aerosol microphysics model and aircraft and ground site observations made during the May 2008 campaign of the European Integrated Project on Aerosol Cloud Climate Air Quality Interactions (EUCAARI). We tested four different parameterisations for BL nucleation and two assumptions for the emission size distribution of anthropogenic and wildfire carbonaceous particles. When we emit carbonaceous particles at small sizes (as recommended by the Aerosol Intercomparison project, AEROCOM), the spatial distributions of campaign-mean number concentrations of particles with diameter >50 nm (N50) and >100 nm (N100) were well captured by the model (R2≥0.8) and the normalised mean bias (NMB) was also small (−18% for N50 and −1% for N100). Emission of carbonaceous particles at larger sizes, which we consider to be more realistic for low spatial resolution global models, results in equally good correlation but larger bias (R2≥0.8, NMB = −52% and −29%), which could be partly but not entirely compensated by BL nucleation. Within the uncertainty of the observations and accounting for the uncertainty in the size of emitted primary particles, BL nucleation makes a statistically significant contribution to CCN-sized particles at less than a quarter of the ground sites. Our results show that a major source of uncertainty in CCN-sized particles in polluted European air is the emitted size of primary carbonaceous particles. New information is required not just from direct observations, but also to determine the "effective emission size" and composition of primary particles appropriate for different resolution models

Persistent short nighttime sleep duration is associated with a greater post-COVID risk in fully mRNA-vaccinated individuals

Short nighttime sleep duration impairs the immune response to virus vaccination, and long nighttime sleep duration is associated with poor health status. Thus, we hypothesized that short (9 h) nighttime sleepers have a higher post-COVID risk than normal nighttime sleepers, despite two doses of mRNA vaccine (which has previously been linked to lower odds of long-lasting COVID-19 symptoms). Post-COVID was defined as experiencing at least one core COVID-19 symptom for at least three months (e.g., shortness of breath). Multivariate logistic regression adjusting for age, sex, BMI, and other factors showed in 9717 respondents (age span 18–99) that two mRNA vaccinations lowered the risk of suffering from post-COVID by about 21% (p < 0.001). When restricting the analysis to double-vaccinated respondents (n = 5918), short and long sleepers exhibited a greater post-COVID risk than normal sleepers (adjusted OR [95%-CI], 1.56 [1.29, 1.88] and 1.87 [1.32, 2.66], respectively). Among respondents with persistent sleep duration patterns during the pandemic compared to before the pandemic, short but not long sleep duration was significantly associated with the post-COVID risk (adjusted OR [95%-CI], 1.59 [1.24, 2.03] and 1.18 [0.70, 1.97], respectively). No significant association between sleep duration and post-COVID symptoms was observed in those reporting positive SARS-CoV-2 test results (n = 538). Our findings suggest that two mRNA vaccinations against SARS-CoV-2 are associated with a lower post-COVID risk. However, this protection may be less pronounced among those sleeping less than 6 h per night. Our findings warrant replication in cohorts with individuals with confirmed SARS-CoV-2 infection.info:eu-repo/semantics/publishedVersio