Implementation of state-of-the-art ternary new-particle formation scheme to the regional chemical transport model PMCAMx-UF in Europe

The particle formation scheme within PMCAMx-UF, a three-dimensional chemical transport model, was updated with particle formation rates for the ternary H2SO4-NH3-H2O pathway simulated by the Atmospheric Cluster Dynamics Code (ACDC) using quantum chemical input data. The model was applied over Europe for May 2008, during which the EUCAARI-LONGREX (European Aerosol Cloud Climate and Air Quality Interactions-Long-Range Experiment) campaign was carried out, providing aircraft vertical profiles of aerosol number concentrations. The updated model reproduces the observed number concentrations of particles larger than 4 nm within 1 order of magnitude throughout the atmospheric column. This agreement is encouraging considering the fact that no semi-empirical fitting was needed to obtain realistic particle formation rates. The cloud adjustment scheme for modifying the photolysis rate profiles within PMCAMx-UF was also updated with the TUV (Tropospheric Ultraviolet and Visible) radiative-transfer model. Results show that, although the effect of the new cloud adjustment scheme on total number concentrations is small, enhanced new-particle formation is predicted near cloudy regions. This is due to the enhanced radiation above and in the vicinity of the clouds, which in turn leads to higher production of sulfuric acid. The sensitivity of the results to including emissions from natural sources is also discussed.Peer reviewe

Antimicrobial resistance among migrants in Europe: a systematic review and meta-analysis

BACKGROUND: Rates of antimicrobial resistance (AMR) are rising globally and there is concern that increased migration is contributing to the burden of antibiotic resistance in Europe. However, the effect of migration on the burden of AMR in Europe has not yet been comprehensively examined. Therefore, we did a systematic review and meta-analysis to identify and synthesise data for AMR carriage or infection in migrants to Europe to examine differences in patterns of AMR across migrant groups and in different settings. METHODS: For this systematic review and meta-analysis, we searched MEDLINE, Embase, PubMed, and Scopus with no language restrictions from Jan 1, 2000, to Jan 18, 2017, for primary data from observational studies reporting antibacterial resistance in common bacterial pathogens among migrants to 21 European Union-15 and European Economic Area countries. To be eligible for inclusion, studies had to report data on carriage or infection with laboratory-confirmed antibiotic-resistant organisms in migrant populations. We extracted data from eligible studies and assessed quality using piloted, standardised forms. We did not examine drug resistance in tuberculosis and excluded articles solely reporting on this parameter. We also excluded articles in which migrant status was determined by ethnicity, country of birth of participants' parents, or was not defined, and articles in which data were not disaggregated by migrant status. Outcomes were carriage of or infection with antibiotic-resistant organisms. We used random-effects models to calculate the pooled prevalence of each outcome. The study protocol is registered with PROSPERO, number CRD42016043681. FINDINGS: We identified 2274 articles, of which 23 observational studies reporting on antibiotic resistance in 2319 migrants were included. The pooled prevalence of any AMR carriage or AMR infection in migrants was 25·4% (95% CI 19·1-31·8; I2 =98%), including meticillin-resistant Staphylococcus aureus (7·8%, 4·8-10·7; I2 =92%) and antibiotic-resistant Gram-negative bacteria (27·2%, 17·6-36·8; I2 =94%). The pooled prevalence of any AMR carriage or infection was higher in refugees and asylum seekers (33·0%, 18·3-47·6; I2 =98%) than in other migrant groups (6·6%, 1·8-11·3; I2 =92%). The pooled prevalence of antibiotic-resistant organisms was slightly higher in high-migrant community settings (33·1%, 11·1-55·1; I2 =96%) than in migrants in hospitals (24·3%, 16·1-32·6; I2 =98%). We did not find evidence of high rates of transmission of AMR from migrant to host populations. INTERPRETATION: Migrants are exposed to conditions favouring the emergence of drug resistance during transit and in host countries in Europe. Increased antibiotic resistance among refugees and asylum seekers and in high-migrant community settings (such as refugee camps and detention facilities) highlights the need for improved living conditions, access to health care, and initiatives to facilitate detection of and appropriate high-quality treatment for antibiotic-resistant infections during transit and in host countries. Protocols for the prevention and control of infection and for antibiotic surveillance need to be integrated in all aspects of health care, which should be accessible for all migrant groups, and should target determinants of AMR before, during, and after migration. FUNDING: UK National Institute for Health Research Imperial Biomedical Research Centre, Imperial College Healthcare Charity, the Wellcome Trust, and UK National Institute for Health Research Health Protection Research Unit in Healthcare-associated Infections and Antimictobial Resistance at Imperial College London

Surgical site infection after gastrointestinal surgery in high-income, middle-income, and low-income countries: a prospective, international, multicentre cohort study

Background: Surgical site infection (SSI) is one of the most common infections associated with health care, but its importance as a global health priority is not fully understood. We quantified the burden of SSI after gastrointestinal surgery in countries in all parts of the world. Methods: This international, prospective, multicentre cohort study included consecutive patients undergoing elective or emergency gastrointestinal resection within 2-week time periods at any health-care facility in any country. Countries with participating centres were stratified into high-income, middle-income, and low-income groups according to the UN's Human Development Index (HDI). Data variables from the GlobalSurg 1 study and other studies that have been found to affect the likelihood of SSI were entered into risk adjustment models. The primary outcome measure was the 30-day SSI incidence (defined by US Centers for Disease Control and Prevention criteria for superficial and deep incisional SSI). Relationships with explanatory variables were examined using Bayesian multilevel logistic regression models. This trial is registered with ClinicalTrials.gov, number NCT02662231. Findings: Between Jan 4, 2016, and July 31, 2016, 13 265 records were submitted for analysis. 12 539 patients from 343 hospitals in 66 countries were included. 7339 (58·5%) patient were from high-HDI countries (193 hospitals in 30 countries), 3918 (31·2%) patients were from middle-HDI countries (82 hospitals in 18 countries), and 1282 (10·2%) patients were from low-HDI countries (68 hospitals in 18 countries). In total, 1538 (12·3%) patients had SSI within 30 days of surgery. The incidence of SSI varied between countries with high (691 [9·4%] of 7339 patients), middle (549 [14·0%] of 3918 patients), and low (298 [23·2%] of 1282) HDI (p < 0·001). The highest SSI incidence in each HDI group was after dirty surgery (102 [17·8%] of 574 patients in high-HDI countries; 74 [31·4%] of 236 patients in middle-HDI countries; 72 [39·8%] of 181 patients in low-HDI countries). Following risk factor adjustment, patients in low-HDI countries were at greatest risk of SSI (adjusted odds ratio 1·60, 95% credible interval 1·05–2·37; p=0·030). 132 (21·6%) of 610 patients with an SSI and a microbiology culture result had an infection that was resistant to the prophylactic antibiotic used. Resistant infections were detected in 49 (16·6%) of 295 patients in high-HDI countries, in 37 (19·8%) of 187 patients in middle-HDI countries, and in 46 (35·9%) of 128 patients in low-HDI countries (p < 0·001). Interpretation: Countries with a low HDI carry a disproportionately greater burden of SSI than countries with a middle or high HDI and might have higher rates of antibiotic resistance. In view of WHO recommendations on SSI prevention that highlight the absence of high-quality interventional research, urgent, pragmatic, randomised trials based in LMICs are needed to assess measures aiming to reduce this preventable complication

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation

Global, regional, and national burden of disorders affecting the nervous system, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BackgroundDisorders affecting the nervous system are diverse and include neurodevelopmental disorders, late-life neurodegeneration, and newly emergent conditions, such as cognitive impairment following COVID-19. Previous publications from the Global Burden of Disease, Injuries, and Risk Factor Study estimated the burden of 15 neurological conditions in 2015 and 2016, but these analyses did not include neurodevelopmental disorders, as defined by the International Classification of Diseases (ICD)-11, or a subset of cases of congenital, neonatal, and infectious conditions that cause neurological damage. Here, we estimate nervous system health loss caused by 37 unique conditions and their associated risk factors globally, regionally, and nationally from 1990 to 2021.MethodsWe estimated mortality, prevalence, years lived with disability (YLDs), years of life lost (YLLs), and disability-adjusted life-years (DALYs), with corresponding 95% uncertainty intervals (UIs), by age and sex in 204 countries and territories, from 1990 to 2021. We included morbidity and deaths due to neurological conditions, for which health loss is directly due to damage to the CNS or peripheral nervous system. We also isolated neurological health loss from conditions for which nervous system morbidity is a consequence, but not the primary feature, including a subset of congenital conditions (ie, chromosomal anomalies and congenital birth defects), neonatal conditions (ie, jaundice, preterm birth, and sepsis), infectious diseases (ie, COVID-19, cystic echinococcosis, malaria, syphilis, and Zika virus disease), and diabetic neuropathy. By conducting a sequela-level analysis of the health outcomes for these conditions, only cases where nervous system damage occurred were included, and YLDs were recalculated to isolate the non-fatal burden directly attributable to nervous system health loss. A comorbidity correction was used to calculate total prevalence of all conditions that affect the nervous system combined.FindingsGlobally, the 37 conditions affecting the nervous system were collectively ranked as the leading group cause of DALYs in 2021 (443 million, 95% UI 378–521), affecting 3·40 billion (3·20–3·62) individuals (43·1%, 40·5–45·9 of the global population); global DALY counts attributed to these conditions increased by 18·2% (8·7–26·7) between 1990 and 2021. Age-standardised rates of deaths per 100 000 people attributed to these conditions decreased from 1990 to 2021 by 33·6% (27·6–38·8), and age-standardised rates of DALYs attributed to these conditions decreased by 27·0% (21·5–32·4). Age-standardised prevalence was almost stable, with a change of 1·5% (0·7–2·4). The ten conditions with the highest age-standardised DALYs in 2021 were stroke, neonatal encephalopathy, migraine, Alzheimer's disease and other dementias, diabetic neuropathy, meningitis, epilepsy, neurological complications due to preterm birth, autism spectrum disorder, and nervous system cancer.InterpretationAs the leading cause of overall disease burden in the world, with increasing global DALY counts, effective prevention, treatment, and rehabilitation strategies for disorders affecting the nervous system are needed

Code: PMCAMx-UF version 2.1 (Particulate Matter Comprehensive Air-quality Model with extensions – Ultra-Fine)

&lt;p&gt;PMCAMx-UF is a three-dimensional chemical transport model (CTM) that simulates the aerosol number size distribution in addition to the mass and composition size distribution (Jung et al.,&nbsp;2010; Fountoukis et al.,&nbsp;2012) and is described in detail in Patoulias et al.&nbsp;(2018). PMCAMx-UF is based on the framework of PMCAMx (Gaydos et al.,&nbsp;2007; Karydis et al.,&nbsp;2007), describing the processes of horizontal and vertical advection, emissions, horizontal and vertical dispersion, wet and dry deposition, aqueous and aerosol phase chemistry, and aerosol dynamics and thermodynamics.&nbsp;&lt;/p&gt;&lt;p&gt;For the simulation of aerosol microphysics, PMCAMx-UF uses the updated version of DMANx, which simulates the processes of coagulation, condensation/evaporation, and nucleation (Patoulias et al.,&nbsp;2015) with the two-moment aerosol sectional (TOMAS) algorithm (Adams and Seinfeld, 2002; Jung et al.,&nbsp;2006). A key feature of TOMAS is its ability to independently track two moments of the aerosol size distribution for each size bin: the aerosol number and mass concentration. The aerosol size distribution is discretized into 41 sections covering the diameter range from approximately 0.8 nm&nbsp;to 10 µm. The lowest boundary is at 3.75 × 10−25 kg&nbsp;of dry aerosol mass per particle. Each successive boundary has twice the mass of the previous one. The particle components modeled include sulfate, ammonium, nitrate, sodium, chloride, crustal material, water, elemental carbon, primary organic aerosol (POA), and eight surrogate SOA components. The nucleation rate is calculated using a scaled ternary parameterization based on the original expressions of Napari et al.&nbsp;(2002) with a scaling factor of 10−6&nbsp;following the suggestions of Fountoukis et al.&nbsp;(2012). The binary parameterization of Vehkamäki et al.&nbsp;(2002) is employed if the&nbsp;NH3&nbsp;concentration is below a threshold value of 0.01 ppt.&lt;/p&gt;&lt;p&gt;Coagulation of particles in the atmosphere is an important sink of aerosol number but is also a mechanism by which freshly nucleated particles grow to larger sizes. Following Adams and Seinfeld (2002), TOMAS assumes that the aerosol particles coagulate via Brownian diffusion and that the effects of gravitational settling and turbulence on coagulation are negligible. The calculation of the coagulation coefficients is based on the wet diameters of the particles. These wet diameters are calculated following the approach of Gaydos et al.&nbsp;(2005).&lt;/p&gt;&lt;p&gt;The extended SAPRC (Statewide Air Pollution Research Center) chemical mechanism (Carter, 2000; Environ, 2003), which includes 219 reactions of 64&nbsp;gases and 18&nbsp;free radicals, is used for the gas phase chemistry mechanism in PMCAMx-UF. The SAPRC version used for this work includes five lumped alkanes (ALK1–5), two lumped olefins (OLE1 and OLE2), two lumped aromatics (ARO1 and ARO2), isoprene (ISOP), a lumped monoterpene (TERP), and a lumped sesquiterpene species (SESQ). Condensation of gas-phase species to existing aerosol particles is an important source of aerosol mass and a means by which small particles grow to CCN sizes. Sulfuric acid is assumed to be in pseudo-steady state in PMCAMx-UF. This pseudo-steady-state approximation (PSSA) for sulfuric acid proposed by Pierce and Adams (2009) increases the computational speed with a small loss in accuracy. Jung et al.&nbsp;(2010) evaluated the performance of PSSA for sulfuric acid in DMAN against a&nbsp;fourth-order Runge–Kutta algorithm and showed that PSSA was accurate and computationally efficient. Condensation of ammonia is simulated following the approach described by Jung et al.&nbsp;(2006). Ammonia condensation on the ultrafine particles ends when sulfate is fully neutralized to ammonium sulfate.&lt;/p&gt

Προσομοίωση του σχηματισμού και ανάπτυξης των ατμοσφαιρικών νανοσωματιδίων

Atmospheric aerosols, also known as atmospheric particulate matter (PM), are suspended particles (solid or liquid) in air, with diameters ranging from 1 nm to approximately 100 μm. PM affects the Earth’s radiative budget and thus global climate, via its so-called direct and indirect radiative effects, and also has adverse effects on human health. It can be classified as primary (emitted directly in the particulate phase) or secondary (formed in the atmosphere through a series of chemical reactions). Typically, PM consists of a mixture of inorganic and organic chemical species including nitrate, sulfate, ammonium, organic material, elemental carbon, sea salt, crustal species and water. Organic aerosol (OA) represents a significant fraction of the mass sub-micrometer PM, but its sources and chemical composition are yet to be elucidated. Black carbon (BC) is the other carbonaceous PM component and is emitted by incomplete combustion processes (biomass burning, traffic, etc.). BC contributes to global warming because it absorbs sunlight and is one of the most toxic PM constituents. Particles smaller than 100 nm are defined as nanoparticles or ultrafine particles. These particles have low mass, high number concentrations and if they manage to survive coagulation with larger particles they can become cloud condensation nuclei (CCN) affecting the cloud droplet number. The change of CCN concentration affects cloud optical properties and lifetime, perturbing the energy balance of the planet. The role of condensation of organic vapors and the chemical aging on formation and growth on ultrafine particles are still unknown. The first objective of the present work was to extend the state-of-the-art 3-D chemical transport model PMCAMx-UF to quantify the effects of organic pollutants on the nanoparticle concentrations in our atmosphere. PMCAMx-UF was applied in Europe and its predictions were evaluated against field observations from stations across Europe and a Zeppelin. The model performed well both at the ground and aloft with a tendency to overestimate the total particle number concentration. The condensation of organics led to an increase (50-120%) of the CCN concentration mainly in central and northern Europe, but decreased the concentration of particles larger than 10 nm by 10-30%. The performance of the model was improved further when later generations of reactions of organic pollutants (chemical aging) were simulated.Finally, a new model was developed which simulates not only the BC size distribution and concentration but also its mixing state in the atmosphere. The model simulates multiple particle size distributions with different proportions of BC for each aerosol population to account for the multidimensional structure of the size/composition of ambient aerosol. Simulations show that urban traffic-related and ship emissions can significantly change the mixing state of aerosols from a fully internally mixed state to an external-like mixture with multiple levels of mixing states predicted during a week-long simulation. We introduce a new mixing state index, Φ, which can range zero (external mixture) to one (internal mixture). Φ varied over Europe from 0.2 to 0.6 showing the complicated effect of fresh emissions, coagulation, condensation and photochemistry on the mixing state of BC-containing aerosol. These effects are not included in existing air quality and climate models.Τα ατμοσφαιρικά αερολύματα, γνωστά και ως ατμοσφαιρικά σωματίδια, είναι αιωρούμενα σωματίδια (στερεά ή υγρά) στον αέρα με διαμέτρους που κυμαίνονται από 1 nm έως περίπου 100 μm. Το ατμοσφαιρικά αερολύματα επηρεάζουν τον προϋπολογισμό ακτινοβολία της Γης και συνεπώς το παγκόσμιο κλίμα μέσω των αποκαλούμενων άμεσων και έμμεσων επιδράσεων ακτινοβολίας τους, ενώ έχουν επίσης αρνητικές επιπτώσεις στην ανθρώπινη υγεία. Μπορούν να ταξινομηθούν ως πρωτογενή (εκπεμπόμενα απευθείας στη φάση των σωματιδίων) ή δευτερογενή (σχηματίζονται στην ατμόσφαιρα μέσω μιας σειράς χημικών αντιδράσεων). Συνήθως, τα ατμοσφαιρικά σωματίδια αποτελούνται από ένα μείγμα ανόργανων και οργανικών χημικών ειδών, συμπεριλαμβανομένων των νιτρικών, θειικών, αμμωνιακών, οργανικών ενώσεων, στοιχειακού άνθρακα, θαλάσσιου άλατος, κρυσταλλικών ενώσεων και νερού. Το οργανικό αερόλυμα αντιπροσωπεύει ένα σημαντικό κλάσμα της μάζας των ατμοσφαιρικών σωματιδίων, αλλά οι πηγές και η χημική του σύνθεση δεν έχουν διευκρινιστεί ακόμη. Ο μαύρος άνθρακας είναι το άλλο ανθρακούχο συστατικό των ατμοσφαιρικών σωματιδίων και εκπέμπεται από ελλιπείς διεργασίες καύσης (καύση βιομάζας, κυκλοφορία κ.λπ.). Επίσης, συμβάλλει στην υπερθέρμανση του πλανήτη, επειδή απορροφά το φως του ήλιου και είναι ένα από τα πιο τοξικά συστατικά του ατμοσφαιρικού αερολύματος.Τα σωματίδια μικρότερα των 100 nm ορίζονται ως νανοσωματίδια ή πολύ λεπτά σωματίδια. Αυτά τα σωματίδια έχουν χαμηλή μάζα, υψηλές συγκεντρώσεις αριθμού και αν κατορθώσουν να επιζήσουν της συσσωμάτωσης με μεγαλύτερα σωματίδια, μπορούν να γίνουν πυρήνες συμπύκνωσης νέφους επηρεάζοντας τον αριθμό των σταγονιδίων σύννεφων. Η μεταβολή της συγκέντρωσης των πυρήνων συμπύκνωσης νέφους, επηρεάζει τις οπτικές ιδιότητες του νέφους αλλά και τη διάρκεια ζωής του, διαταράσσοντας το ενεργειακό ισοζύγιο του πλανήτη. Ο ρόλος της συμπύκνωσης των οργανικών ατμών και της χημικής γήρανσης στον σχηματισμό και την ανάπτυξη σε πολύ λεπτά σωματίδια είναι ακόμη άγνωστος.Ο πρώτος στόχος της παρούσας εργασίας ήταν να επεκταθεί το μοντέλο χημικής μεταφοράς, 3-D PMCAMx-UF, για την ποσοτικοποίηση των επιδράσεων των οργανικών ρύπων στις συγκεντρώσεις νανοσωματιδίων στην ατμόσφαιρα. Το PMCAMx-UF εφαρμόστηκε στην Ευρώπη και οι προβλέψεις του αξιολογήθηκαν βάσει μετρήσεων από σταθμούς σε όλη την Ευρώπη και εναέριων μετρήσεων από Zeppelin. Το μοντέλο προσομοίωσε αρκετά καλά τόσο με τις μετρήσεις στο έδαφος όσο και με τις μετρήσεις του Zeppelin, με μια τάση να υπερεκτιμά τη συνολική συγκέντρωση αριθμού σωματιδίων. Η συμπύκνωση των οργανικών ουσιών οδήγησε σε αύξηση (50-120%) της συγκέντρωσης των πυρήνων συμπύκνωσης νέφους, κυρίως στην κεντρική και βόρεια Ευρώπη, αλλά μείωσε τη συγκέντρωση σωματιδίων μεγαλύτερων από 10 nm κατά 10-30%. Η απόδοση του μοντέλου βελτιώθηκε περαιτέρω όταν προσομοιώθηκαν μεταγενέστερες γενιές αντιδράσεων οργανικών ρύπων (π.χ. χημική γήρανση).Τέλος, αναπτύχθηκε ένα νέο μοντέλο που προσομοιώνει όχι μόνο την κατανομή και τη συγκέντρωση του μεγέθους του μαύρου άνθρακα, αλλά και την κατάσταση ανάμιξης του στην ατμόσφαιρα. Το μοντέλο προσομοιώνει πολλαπλές κατανομές μεγέθους σωματιδίων με διαφορετικές αναλογίες μαύρου άνθρακα για κάθε αερόλυμα, ώστε να ληφθεί υπόψη η πολυδιάστατη δομή του μεγέθους/σύνθεσης του περιβαλλοντικού αερολύματος. Οι προσομοιώσεις δείχνουν ότι οι εκπομπές που συνδέονται με την αστική κυκλοφορία και τις εκπομπές των πλοίων, μπορούν να αλλάξουν σημαντικά την κατάσταση ανάμειξης των αερολυμάτων, από ένα πλήρως εσωτερικά αναμεμιγμένο σε ένα εξωτερικά αναμεμιγμένο μείγμα με πολλαπλά επίπεδα συνθηκών ανάμιξης, τα οποία προβλέπονται κατά τη διάρκεια μιας εβδομαδιαίας προσομοίωσης. Για αυτό το λόγο, εισάγαμε έναν νέο δείκτη κατάστασης ανάμιξης, Φ, ο οποίος μπορεί να κυμαίνεται από το μηδέν (εξωτερικά αναμεμιγμένο μείγμα) ως τη μονάδα (εσωτερικά αναμεμιγμένο). Το Φ ποικίλει στην περιοχή της Ευρώπης από 0.2 έως 0.6, παρουσιάζοντας την περίπλοκη επίδραση των φρέσκων εκπομπών, της συσσωμάτωσης, της συμπύκνωσης και της φωτοχημείας στην κατάσταση ανάμιξης του αερολύματος που περιέχει μαύρο άνθρακα. Αυτές οι επιπτώσεις δεν περιλαμβάνονται στα υπάρχοντα μοντέλα παρατήρησης της ποιότητας του αέρα και του κλίματος

Simulation of the size-composition distribution of atmospheric nanoparticles over Europe

PMCAMx-UF, a three-dimensional chemical transport model focusing on the simulation of the ultrafine particle size distribution and composition has been extended with the addition of the volatility basis set (VBS) approach for the simulation of organic aerosol (OA). The model was applied in Europe to quantify the effect of secondary semi-volatile organic vapors on particle number concentrations. The model predictions were evaluated against field observations collected during the PEGASOS 2012 campaign. The measurements included both ground and airborne measurements, from stations across Europe and a zeppelin measuring above Po Valley. The ground level concentrations of particles with a diameter larger than 100 nm (N-100) were reproduced with a daily normalized mean error of 40% and a daily normalized mean bias of -20 %. PMCAMx-UF tended to overestimate the concentration of particles with a diameter larger than 10 nm (N-10) with a daily normalized mean bias of 75 %. The model was able to reproduce, within a factor of 2, 85% of the N-10 and 75% of the N-100 zeppelin measurements above ground. The condensation of organics led to an increase (50 %-120 %) in the N-100 concentration mainly in central and northern Europe, while the N-10 concentration decreased by 10 %-30 %. Including the VBS in PMCAMx-UF improved its ability to simulate aerosol number concentration compared to simulations neglecting organic condensation on ultrafine particles.Peer reviewe

Size-resolved aerosol pH over Europe during summer

The dependence of aerosol acidity on particle size, location, and altitude over Europe during a summertime period is investigated using the hybrid version of aerosol dynamics in the chemical transport model PMCAMx. The pH changes more with particle size in northern and southern Europe owing to the enhanced presence of non-volatile cations (Na, Ca, K, Mg) in the larger particles. Differences of up to 1-4 pH units are predicted between sub- and supermicron particles, while the average pH of PM1-2.5 can be as much as 1 unit higher than that of PM1. Most aerosol water over continental Europe is associated with PM1, while coarse particles dominate the water content in the marine and coastal areas due to the relatively higher levels of hygroscopic sea salt. Particles of all sizes become increasingly acidic with altitude (0.5-2.5 units pH decrease over 2.5 km) primarily because of the decrease in aerosol liquid water content (driven by humidity changes) with height. Inorganic nitrate is strongly affected by aerosol pH with the highest average nitrate levels predicted for the PM1-5 range and over locations where the pH exceeds 3. Dust tends to increase aerosol pH for all particle sizes and nitrate concentrations for supermicron range particles. This effect of dust is quite sensitive to its calcium content. The size-dependent pH differences carry important implications for pH-sensitive processes in the aerosol