Towards automated inclusion of autoxidation chemistry in models: from precursors to atmospheric implications

In the last few decades, atmospheric formation of secondary organic aerosols (SOA) has gained increasing attention due to their impact on air quality and climate. However, methods to predict their abundance are mainly empirical and may fail under real atmospheric conditions. In this work, a close-to-mechanistic approach allowing SOA quantification is presented, with a focus on a chain-like chemical reaction called "autoxidation". A novel framework is employed to (a) describe the gas-phase chemistry, (b) predict the products' molecular structures and (c) explore the contribution of autoxidation chemistry on SOA formation under various conditions. As a proof of concept, the method is applied to benzene, an important anthropogenic SOA precursor. Our results suggest autoxidation to explain up to 100% of the benzene-SOA formed under low-NO x laboratory conditions. Under atmospheric-like day-time conditions, the calculated benzene-aerosol mass continuously forms, as expected based on prior work. Additionally, a prompt increase, driven by the NO3 radical, is predicted by the model at dawn. This increase has not yet been explored experimentally and stresses the potential for atmospheric SOA formation via secondary oxidation of benzene by O3 and NO3.

A 13-year space-based climatological evolution of desert dust aerosols in the Middle East and North Africa regions observed by the CALIPSO

The present study explores the intricacies of CALIPSO Level 3 optimized Aerosol Optical Depth (AOD) and Dust Aerosol Optical Depth (DAOD) products. Hence, the study focused on regions in the Middle East and North Africa (MENA) across different seasons from January 2007 to December 2020. The study utilizes a refined 1° × 1° grid resolution to analyze horizontal distribution patterns, seasonal variations, and the interplay of various aerosol constituents. The Middle East (ME) stands out with intensified AOD during transitional periods, and the Saharan-Sahel Dust (SSD) belt exhibits higher DAOD during specific seasons. Regions with significant industrialization and human activities exhibit high non-dust AOD values, while major dust sources like the SSD and the Arabian Desert showed high DAOD values in the spring and summer seasons. The study reveals seasonal variations in AOD and DAOD, with different regions showing distinct characteristics influenced by topographic and environmental factors. Observational evidence on the vertical distribution of dust layers is crucial for modeling studies to assess the impact of airborne dust particles on radiation and clouds. However, there are challenges in assimilating dust into atmospheric models due to limited ground measurements near dust sources. Further, the statistical metrics highlight regional and seasonal variations in DAOD, Dust Center of Mass, and Dust Top Height. The analysis extends to particle depolarization ratio, aerosol classification, spatial deviation in dust composition, AOD, and cloud properties (e.g., cloud optical thickness and cloud fraction). This has been influenced by several factors such as atmospheric circulation patterns, temperature, humidity, and land cover changes. Trends in AOD and DAOD over timescale indicate regional variations in aerosol concentrations. The study offers valuable insights into the complex atmospheric phenomena shaping the examined regions over the 13 years.

Natural Marine Precursors Boost Continental New Particle Formation and Production of Cloud Condensation Nuclei

Marine dimethyl sulfide (DMS) emissions are the dominant source of natural sulfur in the atmosphere. DMS oxidizes to produce low-volatility acids that potentially nucleate to form particles that may grow into climatically important cloud condensation nuclei (CCN). In this work, we utilize the chemistry transport model ADCHEM to demonstrate that DMS emissions are likely to contribute to the majority of CCN during the biological active period (May-August) at three different forest stations in the Nordic countries. DMS increases CCN concentrations by forming nucleation and Aitken mode particles over the ocean and land, which eventually grow into the accumulation mode by condensation of low-volatility organic compounds from continental vegetation. Our findings provide a new understanding of the exchange of marine precursors between the ocean and land, highlighting their influence as one of the dominant sources of CCN particles over the boreal forest.

Aqueous-phase formation of N-containing secondary organic compounds affected by the ionic strength

The reaction of carbonyl-to-imine/hemiaminal conversion in the atmospheric aqueous phase is a critical pathway to produce the light-absorbing N-containing secondary organic compounds (SOC). The formation mechanism of these compounds has been wildly investigated in bulk solutions with a low ionic strength. However, the ionic strength in the aqueous phase of the polluted atmosphere may be higher. It is still unclear whether and to what extent the inorganic ions can affect the SOC formation. Here we prepared the bulk solution with certain ionic strength, in which glyoxal and ammonium were mixed to mimic the aqueous-phase reaction. Molecular characterization by High-resolution Mass Spectrometry was performed to identify the N-containing products, and the light absorption of the mixtures was measured by ultraviolet-visible spectroscopy. Thirty-nine N-containing compounds were identified and divided into four categories (N-heterocyclic chromophores, high-molecular-weight compounds with N-heterocycle, aliphatic imines/hemiaminals, and the unclassified). It was observed that the longer reaction time and higher ionic strength led to the formation of more N-heterocyclic chromophores and the increasing of the light-absorbance of the mixture. The added inorganic ions were proposed to make the aqueous phase somewhat viscous so that the molecules were prone to undergo consecutive and intramolecular reactions to form the heterocycles. In general, this study revealed that the enhanced ionic strength and prolonged reaction time had the promotion effect on the light-absorbing SOC formation. It implies that the aldehyde-derived aqueous-phase SOC would contribute more light-absorbing particulate matter in the industrial or populated area where inorganic ions are abundant.

Dynamic evaluation of modeled ozone concentrations in Germany with four chemistry transport models

Simulating the ozone variability at regional scales using chemistry transport models (CTMs) remains a challenge. We designed a multi-model intercomparison to evaluate, for the first time, four regional CTMs on a national scale for Germany. Simulations were conducted with LOTOS-EUROS, REM-CALGRID, COSMO-MUSCAT and WRF-Chem for January 1st to December 31st, 2019, using prescribed emission information. In general, all models show good performance in the operational evaluation with average temporal correlations of MDA8 O3 in the range of 0.77-0.87 and RMSE values between 16.3 μg m-3 and 20.6 μg m-3. On average, better models' skill has been observed for rural background stations than for the urban background stations as well as for springtime compared to summertime. Our study confirms that the ensemble mean provides a better model-measurement agreement than individual models. All models capture the larger local photochemical production in summer compared to springtime and observed differences between the urban and the rural background. We introduce a new indicator to evaluate the dynamic response of ozone to temperature. During summertime a large ensemble spread in the ozone sensitivities to temperature is found with (on average) an underestimation of the ozone sensitivity to temperature, which can be linked to a systematic underestimation of mid-level ozone concentrations. During springtime we observed an ozone episode that is not covered by the models which is likely due to deficiencies in the representation of background ozone in the models. We recommend to focus on a diagnostic evaluation aimed at the model descriptions for biogenic emissions and dry deposition as a follow up and to repeat the operational and dynamic analysis for longer timeframes.

New insights into the role of marine plastic-gels in microplastic transfer from water to the atmosphere via bubble bursting

The pervasiveness of microplastics (MPs) in global oceans is raising concerns about their adverse impacts on ecosystems. The mechanistic understanding of MP transport is critical for evaluating its fate, flux, and ecological risks specifically. Currently, bubble bursting is believed to represent an important route for MP transfer from sea surfaces to the atmosphere. However, the detailed mechanisms of the complex physico-chemical interactions between MPs, water composition, and gel particles in the air-sea interface remain unknown. Our results suggested three steps for MP transfer between air-sea phases: (1) MPs incorporating into gel aggregates in the water column; (2) further accumulation of plastic-gel aggregate in the surface layer phase; finally (3) ejection of aggregates from the sea when bubbles of trapped air rise to the surface and burst. The water composition (e.g., high salinity, gel concentration and viscosity) can modulate plastic-gel aggregation and subsequent transport from water to the atmosphere. The possible mechanism may be closely tied to the formation of plastic-gel via cation-linking bridges, thereby enhancing plastic-gel ejection into air. Collectively, this work offers unique insights into the role of marine plastic-gels in determining MP fate and transport, especially at air-sea interfaces. The data also provide a better understanding of the corresponding mechanism that may explain the fates of missing plastics in the ocean.

The Global Atmosphere-aerosol Model ICON-A-HAM2.3-Initial Model Evaluation and Effects of Radiation Balance Tuning on Aerosol Optical Thickness

The Hamburg Aerosol Module version 2.3 (HAM2.3) from the ECHAM6.3-HAM2.3 global atmosphere-aerosol model is coupled to the recently developed icosahedral nonhydrostatic ICON-A (icon-aes-1.3.00) global atmosphere model to yield the new ICON-A-HAM2.3 atmosphere-aerosol model. The ICON-A and ECHAM6.3 host models use different dynamical cores, parameterizations of vertical mixing due to sub-grid scale turbulence, and parameter settings for radiation balance tuning. Here, we study the role of the different host models for simulated aerosol optical thickness (AOT) and evaluate impacts of using HAM2.3 and the ECHAM6-HAM2.3 two-moment cloud microphysics scheme on several meteorological variables. Sensitivity runs show that a positive AOT bias over the subtropical oceans is remedied in ICON-A-HAM2.3 because of a different default setting of a parameter in the moist convection parameterization of the host models. The global mean AOT is biased low compared to MODIS satellite instrument retrievals in ICON-A-HAM2.3 and ECHAM6.3-HAM2.3, but the bias is larger in ICON-A-HAM2.3 because negative AOT biases over the Amazon, the African rain forest, and the northern Indian Ocean are no longer compensated by high biases over the sub-tropical oceans. ICON-A-HAM2.3 shows a moderate improvement with respect to AOT observations at AERONET sites. A multivariable bias score combining biases of several meteorological variables into a single number is larger in ICON-A-HAM2.3 compared to standard ICON-A and standard ECHAM6.3. In the tropics, this multivariable bias is of similar magnitude in ICON-A-HAM2.3 and in ECHAM6.3-HAM2.3. In the extra-tropics, a smaller multivariable bias is found for ICON-A-HAM2.3 than for ECHAM6.3-HAM2.3.

Improving the Representation of Whitecap Fraction and Sea Salt Aerosol Emissions in the ECMWF IFS-AER

The European Centre for Medium-Range Weather Forecasts (ECMWF) operates the Integrated Forecasting System aerosol module (IFS-AER) to provide daily global analysis and forecast of aerosols for the Copernicus Atmosphere Monitoring Service (CAMS). New estimates of sea salt aerosol emissions have been implemented in the IFS-AER using a new parameterization of whitecap fraction as a function of wind speed and sea surface temperature. The effect of whitecap fraction simulated by old and new parameterizations has been evaluated by comparing the IFS-AER new sea salt aerosol characteristics to those of aerosol retrievals. The new parameterization brought a significant improvement as compared to the two parameterizations of sea salt aerosol emissions previously implemented in the IFS-AER. Likewise, the simulated sea salt aerosol optical depth and surface concentration are significantly improved, as compared against ground and remote sensing products.

Source Apportionment of Aerosol at a Coastal Site and Relationships with Precipitation Chemistry: A Case Study over the Southeast United States

This study focuses on the long-term aerosol and precipitation chemistry measurements from colocated monitoring sites in Southern Florida between 2013 and 2018. A positive matrix factorization (PMF) model identified six potential emission sources impacting the study area. The PMF model solution yielded the following source concentration profiles: (i) combustion; (ii) fresh sea salt; (iii) aged sea salt; (iv) secondary sulfate; (v) shipping emissions; and (vi) dust. Based on these results, concentration-weighted trajectory maps were developed to identify sources contributing to the PMF factors. Monthly mean precipitation pH values ranged from 4.98 to 5.58, being positively related to crustal species and negatively related to SO4 2-. Sea salt dominated wet deposition volume-weighted concentrations year-round without much variability in its mass fraction in contrast to stronger seasonal changes in PM2.5 composition where fresh sea salt was far less influential. The highest mean annual deposition fluxes were attributed to Cl-, NO3 -, SO4 2-, and Na+ between April and October. Nitrate is strongly correlated with dust constituents (unlike sea salt) in precipitation samples, indicative of efficient partitioning to dust. Interrelationships between precipitation chemistry and aerosol species based on long-term surface data provide insight into aerosol-cloud-precipitation interactions.

Spatiotemporal variability, source apportionment, and acid-neutralizing capacity of atmospheric wet base-cation deposition in China

Atmospheric wet deposition of base cations (BCs) plays a significant role in providing plant nutrients and buffering acidification. However, the temporal dynamic of wet BC deposition in China during the past two decades remain unclear. Here, we used long-term monitoring and literature data since 2000 to assess the temporal dynamics (seasonal and inter-annual variation), spatial patterns, main influencing factors, source apportionment, and capacity to neutralize the acidity of wet BC depositions at site, regional, and national scales. The results showed that total wet deposition of BCs was, on average, 2.12 keq ha^-1 yr^-1, where Ca²⁺ accounted for 65.57% of the total deposition, followed by Na⁺ (13.21%), Mg²⁺ (13.68%), and K⁺ (7.55%). Qinghai-Tibet had significantly lower BC deposition fluxes than northern, southern, and central China, as well as Inner Mongolia. Exchangeable BCs in soil, PM₁₀ in the atmosphere, energy consumption, and cement production are significantly related to wet BC deposition, which account for 79.17% of the variation in the spatial deposition of BC. Influenced by the strategies to control acid rain and particulate matter in China, interannual variations showed a stabilization trend after a continuous decline from 2000 to 2017, which can be explained by inter-annual changes in PM₁₀, energy consumption and cement production. Statistical methods confirmed that 45.95% of wet BC deposition was derived from crustal contributions, 27.78% from sea salt sources, and 26.27% from anthropogenic sources. Furthermore, we found that wet deposition of BCs neutralized 84.85% of the acidity due to NO₃^- and SO₄^2- depositions. Under the emissions reduction strategy, there has been a decrease in the deposition of BC. However, SO₄^2- and NO₃^- depositions decreased faster than BC deposition, which buffered a higher proportion of acidic depositions. Our findings contribute to an improved understanding of wet BC deposition in China, an evaluation of their capacity to neutralize acidity, and important parameters for acidification models.

Relationships Between Supermicrometer Sea Salt Aerosol and Marine Boundary Layer Conditions: Insights From Repeated Identical Flight Patterns

The MONterey Aerosol Research Campaign (MONARC) in May-June 2019 featured 14 repeated identical flights off the California coast over the open ocean at the same time each flight day. The objective of this study is to use MONARC data along with machine learning analysis to evaluate relationships between both supermicrometer sea salt aerosol number (N>1) and volume (V>1) concentrations and wind speed, wind direction, sea surface temperature (SST), ambient temperature (Tamb), turbulent kinetic energy (TKE), relative humidity (RH), marine boundary layer (MBL) depth, and drizzle rate. Selected findings from this study include the following: (i) Near surface (<60 m) N>1 and V>1 concentration ranges were 0.1-4.6 cm-3 and 0.3-28.2 μm3 cm-3, respectively; (ii) four meteorological regimes were identified during MONARC with each resulting in different N>1 and V>1 concentrations and also varying horizontal and vertical profiles; (iii) the relative predictive strength of the MBL properties varies depending on predicting N>1 or V>1, with MBL depth being more highly ranked for predicting N>1 and with TKE being higher for predicting V>1; (iv) MBL depths >400 m (<200 m) often correspond to lower (higher) N>1 and V>1 concentrations; (v) enhanced drizzle rates coincide with reduced N>1 and V>1 concentrations; (vi) N>1 and V>1 concentrations exhibit an overall negative relationship with SST and RH and an overall positive relationship with Tamb; and (vii) wind speed and direction were relatively weak predictors of N>1 and V>1.

Time-Dependent Downscaling of PM2.5 Predictions from CAMS Air Quality Models to Urban Monitoring Sites in Budapest

Budapest, the capital of Hungary, has been facing serious air pollution episodes in the heating season similar to other metropolises. In the city a dense urban air quality monitoring network is available; however, air quality prediction is still challenging. For this purpose, 24-h PM2.5 forecasts obtained from seven individual models of the Copernicus Atmosphere Monitoring Service (CAMS) were downscaled by using hourly measurements at six urban monitoring sites in Budapest for the heating season of 2018–2019. A 10-day long training period was applied to fit spatially consistent model weights in a linear combination of CAMS models for each day, and the 10-day additive bias was also corrected. Results were compared to the CAMS ensemble median, the 10-day bias-corrected CAMS ensemble median, and the 24-h persistence. Downscaling reduced the root mean square error (RMSE) by 1.4 µg/m3 for the heating season and by 4.3 µg/m3 for episodes compared to the CAMS ensemble, mainly by eliminating the general underestimation of PM2.5 peaks. As a side-effect, an overestimation was introduced in rapidly clearing conditions. Although the bias-corrected ensemble and model fusion had similar overall performance, the latter was more efficient in episodes. Downscaling of the CAMS models was found to be capable and necessary to capture high wintertime PM2.5 concentrations for the short-range air quality prediction in Budapest.

Global high-resolution emissions of soil NOx, sea salt aerosols, and biogenic volatile organic compounds

Natural emissions of air pollutants from the surface play major roles in air quality and climate change. In particular, nitrogen oxides (NOx) emitted from soils contribute ~15% of global NOx emissions, sea salt aerosols are a major player in the climate and chemistry of the marine atmosphere, and biogenic emissions are the dominant source of non-methane volatile organic compounds at the global scale. These natural emissions are often estimated using nonlinear parameterizations, which are sensitive to the horizontal resolutions of inputted meteorological and ancillary data. Here we use the HEMCO model to compute these emissions worldwide at horizontal resolutions of 0.5° lat. × 0.625° lon. for 1980-2017 and 0.25° lat. × 0.3125° lon. for 2014-2017. We further offer the respective emissions at lower resolutions, which can be used to evaluate the impacts of resolution on estimated global and regional emissions. Our long-term high-resolution emission datasets offer useful information to study natural pollution sources and their impacts on air quality, climate, and the carbon cycle.

Examination of the ocean as a source for atmospheric microplastics

Global plastic litter pollution has been increasing alongside demand since plastic products gained commercial popularity in the 1930's. Current plastic pollutant research has generally assumed that once plastics enter the ocean they are there to stay, retained permanently within the ocean currents, biota or sediment until eventual deposition on the sea floor or become washed up onto the beach. In contrast to this, we suggest it appears that some plastic particles could be leaving the sea and entering the atmosphere along with sea salt, bacteria, virus' and algae. This occurs via the process of bubble burst ejection and wave action, for example from strong wind or sea state turbulence. In this manuscript we review evidence from the existing literature which is relevant to this theory and follow this with a pilot study which analyses microplastics (MP) in sea spray. Here we show first evidence of MP particles, analysed by μRaman, in marine boundary layer air samples on the French Atlantic coast during both onshore (average of 2.9MP/m3) and offshore (average of 9.6MP/m3) winds. Notably, during sampling, the convergence of sea breeze meant our samples were dominated by sea spray, increasing our capacity to sample MPs if they were released from the sea. Our results indicate a potential for MPs to be released from the marine environment into the atmosphere by sea-spray giving a globally extrapolated figure of 136000 ton/yr blowing on shore.

Atmospheric Research Over the Western North Atlantic Ocean Region and North American East Coast: A Review of Past Work and Challenges Ahead

Decades of atmospheric research have focused on the Western North Atlantic Ocean (WNAO) region because of its unique location that offers accessibility for airborne and ship measurements, gradients in important atmospheric parameters, and a range of meteorological regimes leading to diverse conditions that are poorly understood. This work reviews these scientific investigations for the WNAO region, including the East Coast of North America and the island of Bermuda. Over 50 field campaigns and long-term monitoring programs, in addition to 715 peer-reviewed publications between 1946 and 2019 have provided a firm foundation of knowledge for these areas. Of particular importance in this region has been extensive work at the island of Bermuda that is host to important time series records of oceanic and atmospheric variables. Our review categorizes WNAO atmospheric research into eight major categories, with some studies fitting into multiple categories (relative %): Aerosols (25%), Gases (24%), Development/Validation of Techniques, Models, and Retrievals (18%), Meteorology and Transport (9%), Air-Sea Interactions (8%), Clouds/Storms (8%), Atmospheric Deposition (7%), and Aerosol-Cloud Interactions (2%). Recommendations for future research are provided in the categories highlighted above.

Current state of the global operational aerosol multi-model ensemble: An update from the International Cooperative for Aerosol Prediction (ICAP)

Since the first International Cooperative for Aerosol Prediction (ICAP) multi-model ensemble (MME) study, the number of ICAP global operational aerosol models has increased from five to nine. An update of the current ICAP status is provided, along with an evaluation of the performance of ICAP-MME over 2012-2017, with a focus on June 2016-May 2017. Evaluated with ground-based Aerosol Robotic Network (AERONET) aerosol optical depth (AOD) and data assimilation quality MODerate-resolution Imaging Spectroradiometer (MODIS) retrieval products, the ICAP-MME AOD consensus remains the overall top-scoring and most consistent performer among all models in terms of root-mean-square error (RMSE), bias and correlation for total, fine- and coarse-mode AODs as well as dust AOD; this is similar to the first ICAP-MME study. Further, over the years, the performance of ICAP-MME is relatively stable and reliable compared to more variability in the individual models. The extent to which the AOD forecast error of ICAP-MME can be predicted is also examined. Leading predictors are found to be the consensus mean and spread. Regression models of absolute forecast errors were built for AOD forecasts of different lengths for potential applications. ICAP-MME performance in terms of modal AOD RMSEs of the 21 regionally representative sites over 2012-2017 suggests a general tendency for model improvements in fine-mode AOD, especially over Asia. No significant improvement in coarse-mode AOD is found overall for this time period.

A systematic review on global pollution status of particulate matter-associated potential toxic elements and health perspectives in urban environment

Airborne particulate matter (PM) that is a heterogeneous mixture of particles with a variety of chemical components and physical features acts as a potential risk to human health. The ability to pose health risk depends upon the size, concentration and chemical composition of the suspended particles. Potential toxic elements (PTEs) associated with PM have multiple sources of origin, and each source has the ability to generate multiple particulate PTEs. In urban areas, automobile, industrial emissions, construction and demolition activities are the major anthropogenic sources of pollution. Fine particles associated with PTEs have the ability to penetrate deep into respiratory system resulting in an increasing range of adverse health effects, at ever-lower concentrations. In-depth investigation of PTEs content and mode of occurrence in PM is important from both environmental and pathological point of view. Considering this air pollution risk, several studies had addressed the issues related to these pollutants in road and street dust, indicating high pollution level than the air quality guidelines. Observed from the literature, particulate PTEs pollution can lead to respiratory symptoms, cardiovascular problems, lungs cancer, reduced lungs function, asthma and severe case mortality. Due to the important role of PM and associated PTEs, detailed knowledge of their impacts on human health is of key importance.

Large-Scale Modeling of Absorbing Aerosols and Their Semi-Direct Effects

Radiative effects of absorbing black carbon and mineral dust aerosols are estimated from global aerosol climate model simulations with fixed sea surface temperatures as a boundary condition. Semi-direct effects are approximated as the residual between the total direct radiative effect and the instantaneous direct radiative effect of the simulated absorbing aerosol species. No distinction is made for aerosols from natural and anthropogenic sources. Results for global average are highly uncertain due to high model variability, but consistent with previous estimates. The global average results for black carbon aerosol semi-direct effects are small due to cancellation of regionally positive or negative effects, and may be positive or negative overall, depending on the model setup. The presence of mineral dust aerosol above dark surfaces and below a layer containing black carbon aerosol may enhance the reflectivity and act to enhance the positive radiative effect of black carbon aerosol. When mineral dust is absent the semi-direct effect at the top-of-atmosphere of black carbon aerosol from both anthropogenic and natural sources is −0.03 Wm−2, while averaging to +0.09 Wm−2 if dust is included.

Evaluation and error apportionment of an ensemble of atmospheric chemistry transport modeling systems: multivariable temporal and spatial breakdown

Through the comparison of several regional-scale chemistry transport modeling systems that simulate meteorology and air quality over the European and North American continents, this study aims at (i) apportioning error to the responsible processes using timescale analysis, (ii) helping to detect causes of model error, and (iii) identifying the processes and temporal scales most urgently requiring dedicated investigations. The analysis is conducted within the framework of the third phase of the Air Quality Model Evaluation International Initiative (AQMEII) and tackles model performance gauging through measurement-to-model comparison, error decomposition, and time series analysis of the models biases for several fields (ozone, CO, SO2, NO, NO2, PM10, PM2.5, wind speed, and temperature). The operational metrics (magnitude of the error, sign of the bias, associativity) provide an overallsense of model strengths and deficiencies, while apportioning the error to its constituent parts (bias, variance, and covariance) can help assess the nature and quality of the error. Each of the error components is analyzed independently and apportioned to specific processes based on the corresponding timescale (long scale, synoptic, diurnal, and intraday) using the error apportionment technique devised in the former phases of AQMEII. The application of the error apportionment method to the AQMEII Phase 3 simulations provides several key insights. In addition to reaffirming the strong impact of model inputs (emission and boundary conditions) and poor representation of the stable boundary layer on model bias, results also highlighted the high interdependencies among meteorological and chemical variables, as well as among their errors. This indicates that the evaluation of air quality model performance for individual pollutants needs to be supported by complementary analysis of meteorological fields and chemical precursors to provide results that are more insightful from a model development perspective. This will require evaluaion methods that are able to frame the impact on error of processes, conditions, and fluxes at the surface. For example, error due to emission and boundary conditions is dominant for primary species (CO, particulate matter (PM)), while errors due to meteorology and chemistry are most relevant to secondary species, such as ozone. Some further aspects emerged whose interpretation requires additional consideration, such as the uniformity of the synoptic error being region- and model-independent, observed for several pollutants; the source of unexplained variance for the diurnal component; and the type of error caused by deposition and at which scale.

Predicting annual average particulate concentration in urban areas

Particulate matter concentrations are in most cities a major environmental problem. This is also the case in Greece where, despite the various measures taken in the past, the problem still persists. In this aspect, a cost efficient, comprehensive method was developed in order to help decision makers to take the most appropriate measures towards particulates pollution abatement. The method is based on the source apportionment estimation from the application of 3D meteorological and dispersion modeling and is validated with the use of 10 years (2002-2012) PM10 monitoring data, in Athens, Greece, as well as using PM10 emission data for the same area and time period. It appears that the methodology can be used for estimating yearly average PM10 concentrations in a quite realistic manner, giving thus the decision makers the possibility to evaluate ex ante the effectiveness of specific abatement measures.