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One of the weaknesses of current line-source models for predicting downwind concentrations from mobile sources is accounting for the dispersion of effluents. Most of the investigators in the field have taken different approaches over the last 50 years, ranging from the use of Pasquill–Gifford (P-G) dispersion curves to the use of equations based on atmospheric turbulence for point source dispersion. Madiraju and Kumar (2021) proposed a three-phase turbulence (TPT) model using the key features of mobile source dispersion that appear in the existing literature. This paper examines the performance of line-source models using an updated TPT model. The generic dispersion equations were considered from the SLINE 1.1, CALINE 4, ADMS, and SLSM models. Multiple air quality field data sets collected by other investigators near the roadways were used during this study. These include field data collected from the Idaho Falls Tracer Experiment 2008 (used as the dataset to compare with the initial model), the CALTRANS Highway 99 Tracer experiment, and the Raleigh 2006 experiment. The predicted concentrations were grouped under unstable and stable atmospheric conditions. The evaluation of the model was performed using several statistical parameters such as FB, NMSE, R2, MG, VG, MSLE, and MAPE. The results indicate that the ADMS and SLINE 1.1 models perform better than CALINE4 and SLSM. SLINE 1.1 tends to overpredict for stable atmospheric conditions and underpredict for unstable atmospheric conditions. A trial test was performed to implement the TPT model in the basic line-source model (SLSM). The results indicate that the majority (FB, NMSE, R2, and MSLE) of the indicators have improved and are in the satisfactory range of a good model performance level. [ABSTRACT FROM AUTHOR]

Air pollution continues to be of concern for Bulgarian cities, mainly due to particulate matter of aerodynamic diameter smaller than 10 δm (PM10). There is public and expert interest in the improvement of two operational air quality modeling systems: the Bulgarian Chemical Weather Forecast System (BgCWFS) and the Local Air Quality Management System (LAQMS) for the city of Plovdiv. The aim of the study is to investigate the effects of satellite data assimilation in BgCWFS on surface concentrations over Bulgaria (resolution 9 km), to downscale BgCWFS output to LAQMS (resolution 250 m), and to examine effects on PM10 in Plovdiv. Data from the Global Ozone Monitoring Experiment-2 (GOME-2) (MetOP satellites) for aerosols, nitrogen dioxide (NO2), and sulfur dioxide (SO2) were assimilated in BgCWFS using objective analysis. Simulation experiments with and without satellite data were conducted for a summer and a winter month. The comparison to surface observations in the country showed improvement of results when using satellite data, especially in the summer due to mineral dust events captured by satellites. The decrease in the normalized mean bias (NMB) over the two months was 43% (PM10) and 73% (SO2). The LAQMS estimated background contributions to PM10 in the city as 32%. The absolute NMB by LAQMS decreased by 38%. [ABSTRACT FROM AUTHOR]

With increasing realization that particles in the air are a major health risk in urban areas, strengthening particle deposition is discussed as a means to air-pollution mitigation. Particles are deposited physically on leaves and thus the process depends on leaf area and surface properties, which change throughout the year. Current state-of-the-art modeling accounts for these changes only by altering leaf longevity, which may be selected by vegetation type and geographic location. Particle removal also depends on weather conditions, which determine deposition and resuspension but generally do not consider properties that are specific to species or plant type. In this study, we modeled

We investigate regional sources contributing to CO during the Korea United States Air Quality (KORUS‐AQ) campaign conducted over Korea (1 May to 10 June 2016) using 17 tagged CO simulations from the Community Atmosphere Model with chemistry (CAM‐chem). The simulations use three spatial resolutions, three anthropogenic emission inventories, two meteorological fields, and nine emission scenarios. These simulations are evaluated against measurements from the DC‐8 aircraft and Measurements Of Pollution In The Troposphere (MOPITT). Results show that simulations using bottom‐up emissions are consistently lower (bias: −34 to −39%) and poorer performing (Taylor skill: 0.38–0.61) than simulations using alternative anthropogenic emissions (bias: −6 to −33%; Taylor skill: 0.48–0.86), particularly for enhanced Asian CO and volatile organic compound (VOC) emission scenarios, suggesting underestimation in modeled CO background and emissions in the region. The ranges of source contributions to modeled CO along DC‐8 aircraft from Korea and southern (90°E to 123°E, 20°N to 29°N), middle (90°E to 123°E, 29°N to 38.5°N), and northern (90°E to 131.5°E, 38.5°N to 45°N) East Asia (EA) are 6–13%, ~5%, 16–28%, and 9–18%, respectively. CO emissions from middle and northern EA can reach Korea via transport within the boundary layer, whereas those from southern EA are transported to Korea mainly through the free troposphere. Emission contributions from middle EA dominate during continental outflow events (29–51%), while Korean emissions play an overall more important role for ground sites (up to 25–49%) and plumes within the boundary layer (up to 25–44%) in Korea. Finally, comparisons with four other source contribution approaches (FLEXPART 9.1 back trajectory calculations driven by Weather Research and Forecasting (WRF) WRF inert tracer, China signature VOCs, and CO to CO2 enhancement ratios) show general consistency with CAM‐chem. Key Points: Korean sources contribute 6‐13% to CO along DC‐8 flight tracks, while contributions of different East Asian subregions vary from 5% to 28%Middle East Asian sources dominate (up to 64%) continental outflows to Korea, but Korean emissions are more important for CO near surfaceContributions using CAM‐chem tags agree with FLEXPART‐WRF back trajectories, WRF NO2 inert tracers, China signature VOCs, and CO/CO2 [ABSTRACT FROM AUTHOR]

The accuracy of atmospheric numerical model is important for the prediction of urban air pollution. This study investigated and quantified the uncertainties of meteorological and air quality model during multi-levels air pollution periods. We simulated the air quality of megacity Shanghai, China with WRF/CMAQ (Weather Research and Forecasting model and Community Multiscale Air Quality model) at both non-pollution and heavy-pollution episodes in 2012. The weather prediction model failed to reproduce the surface temperature and wind speed in condition of high aerosol loading. The accuracy of the air quality model showed a clear dropping tendency from good air quality conditions to heavily polluted episodes. The absolute model bias increased significantly from light air pollution to heavy air pollution for SO (from 2 to 14%) and for PM (from 1 to 33%) in both urban and suburban sites, for CO in urban sites (from 8 to 48%) and for NO in suburban sites (from 1 to 58%). A test of applying the Urban Canopy Model scheme to the WRF model showed fairly good improvement on predicting the meteorology field, but less significant effect on the air pollutants (6% for SO and 19% for NO decease in model bias found only in urban sites). This study gave clear evidence to the sensitivities of the model performance on the air pollution levels. It is suggested to consider this impact as a source for model bias in the model assessment and make improvement in the model development in the future. [ABSTRACT FROM AUTHOR]

Air pollution and associated human exposure are important research areas in Greater Sydney, Australia. Several field campaigns were conducted to characterize the pollution sources and their impacts on ambient air quality including the Sydney Particle Study Stages 1 and 2 (SPS1 and SPS2), and the Measurements of Urban, Marine, and Biogenic Air (MUMBA). In this work, the Weather Research and Forecasting model with chemistry (WRF/Chem) and the coupled WRF/Chem with the Regional Ocean Model System (ROMS) (WRF/Chem-ROMS) are applied during these field campaigns to assess the models’ capability in reproducing atmospheric observations. The model simulations are performed over quadruple-nested domains at grid resolutions of 81-, 27-, 9-, and 3-km over Australia, an area in southeastern Australia, an area in New South Wales, and the Greater Sydney area, respectively. A comprehensive model evaluation is conducted using surface observations from these field campaigns, satellite retrievals, and other data. This paper evaluates the performance of WRF/Chem-ROMS and its sensitivity to spatial grid resolutions. The model generally performs well at 3-, 9-, and 27-km resolutions for sea-surface temperature and boundary layer meteorology in terms of performance statistics, seasonality, and daily variation. Moderate biases occur for temperature at 2-m and wind speed at 10-m in the mornings and evenings due to the inaccurate representation of the nocturnal boundary layer and surface heat fluxes. Larger underpredictions occur for total precipitation due to the limitations of the cloud microphysics scheme or cumulus parameterization. The model performs well at 3-, 9-, and 27-km resolutions for surface O3 in terms of statistics, spatial distributions, and diurnal and daily variations. The model underpredicts PM2.5 and PM10 during SPS1 and MUMBA but overpredicts PM2.5 and underpredicts PM10 during SPS2. These biases are attributed to inaccurate meteorology, precursor emissions, insufficient SO2 conversion to sulfate, inadequate dispersion at finer grid resolutions, and underprediction in secondary organic aerosol. The model gives moderate biases for net shortwave radiation and cloud condensation nuclei but large biases for other radiative and cloud variables. The performance of aerosol optical depth and latent/sensible heat flux varies for different simulation periods. Among all variables evaluated, wind speed at 10-m, precipitation, surface concentrations of CO, NO, NO2, SO2, O3, PM2.5, and PM10, aerosol optical depth, cloud optical thickness, cloud condensation nuclei, and column NO2 show moderate-to-strong sensitivity to spatial grid resolutions. The use of finer grid resolutions (3- or 9-km) can generally improve the performance for those variables. While the performance for most of these variables is consistent with that over the U.S. and East Asia, several differences along with future work are identified to pinpoint reasons for such differences.

We propose a new technique to prepare statistically-robust benchmarking data for evaluating chemical transport model meteorology and air quality parameters within the urban boundary layer. The approach employs atmospheric class-typing, using nocturnal radon measurements to assign atmospheric mixing classes, and can be applied temporally (across the diurnal cycle), or spatially (to create angular distributions of pollutants as a top-down constraint on emissions inventories). In this study only a short (

China's population is exposed to high levels of particulate matter (PM) due to its strong economic growth and associated urbanization and industrialization. To support policy makers to develop cost effective mitigation strategies it is of crucial importance to understand the emission sources as well as formation routes responsible for high pollution levels. In this study we applied the LOTOS-EUROS model with its module to track the contributions of predefined source sectors to China for the year 2013 using the MEIC emission inventory. It is the first application of the model system to a region outside Europe. The source attribution was aimed to provide insight in the sector and area of origin of PM2.5 for the cities of Beijing and Shanghai. The source attribution shows that on average about half of the PM2.5 pollution in both cities originates from the municipality itself. About a quarter of the PM2.5 comes from the neighbouring provinces, whereas the remaining quarter is attributed to long range transport from anthropogenic and natural components. Residential combustion, transport, and industry are identified as the main sources with comparable contributions allocated to these sectors. The importance of the sectors varies throughout the year and differs slightly between the cities. During winter, urban contributions from residential combustion are dominant, whereas industrial and traffic contributions with a larger share of regional transport are more important during summer. The evaluation of the model results against satellite and in-situ observations shows the ability of the LOTOS-EUROS model to capture many features of the variability in particulate matter and its precursors in China. The model shows a systematic underestimation of particulate matter concentrations, especially in winter. This illustrates that modelling particulate matter remains challenging as it comes to components like secondary organic aerosol and suspended dust as well as emissions and formation of PM during winter time haze situations. All in all, the LOTOS-EUROS system proves to be a powerful tool for policy support applications outside Europe as the intermediate complexity of the model allows the assessment of the area and sector of origin over decadal time periods. [ABSTRACT FROM AUTHOR]

Dynamic evaluation of the fully coupled Weather Research and Forecasting (WRF)– Community Multi-scale Air Quality (CMAQ) model ozone simulations over the contiguous United States (CONUS) using two decades of simulations covering the period from 1990 to 2010 is conducted to assess how well the changes in observed ozone air quality are simulated by the model. The changes induced by variations in meteorology and/or emissions are also evaluated during the same timeframe using spectral decomposition of observed and modeled ozone time series with the aim of identifying the underlying forcing mechanisms that control ozone exceedances and making informed recommendations for the optimal use of regional-scale air quality models. The evaluation is focused on the warm season's (i.e., May–September) daily maximum 8-hr (DM8HR) ozone concentrations, the 4th highest (4th) and average of top 10 DM8HR ozone values (top10), as well as the spectrally-decomposed components of the DM8HR ozone time series using the Kolmogorov-Zurbenko (KZ) filter. Results of the dynamic evaluation are presented for six regions in the U.S., consistent with the National Oceanic and Atmospheric Administration (NOAA) climatic regions. During the earlier 11-yr period (1990–2000), the simulated and observed regional average trends are not statistically significant. During the more recent 2000–2010 period, all observed trends are statistically significant and WRF-CMAQ captures the observed downward trend in the Southwest and Midwest but under-predicts the downward trends in observations for the other regions. Observational analysis reveals that it is the magnitude of the long-term forcing that dictates the maximum ozone exceedance potential; there is a strong linear relationship between the long-term forcing and the 4th highest or the average of the top10 ozone concentrations in both observations and model output. This finding indicates that improving the model's ability to reproduce the long-term component will also enable better simulation of ozone extreme values that are of interest to regulatory agencies. [ABSTRACT FROM AUTHOR]

This paper presents the Lagrangian particle model LAPMOD for modeling time-variable emissions in atmosphere of inert and radioactive gases and aerosols. LAPMOD is fully interfaced with the meteorological model CALMET (Scire et al., 1999a), part of the US-EPA recommended CALPUFF modeling system (EPA, 2017), and can also use the meteorological input files produced with the AERMET meteorological processor of US-EPA recommended model AERMOD (EPA, 2004). The paper outlines the theory on which LAPMOD is based and provides the results of the evaluation of LAPMOD against the Kincaid SF 6 and SO 2 classical field studies and tracer experiments. The performance of LAPMOD is successfully evaluated with the Model Evaluation Kit (Olesen, 2005) and compared with that of other air quality models. [ABSTRACT FROM AUTHOR]

A version of the Community Earth System Model modified at the North Carolina State University (CESM-NCSU) is used to simulate the current and future atmosphere following the representative concentration partway scenarios for stabilization of radiative forcing at 4.5 W m −2 (RCP4.5) and radiative forcing of 8.5 W m −2 (RCP8.5). Part I describes the results from a comprehensive evaluation of current decadal simulations. Radiation and most meteorological variables are well simulated in CESM-NCSU. Cloud parameters are not as well simulated due in part to the tuning of model radiation and general biases in cloud variables common to all global chemistry-climate models. The concentrations of most inorganic aerosol species (i.e., SO 4 2- , NH 4 + , and NO 3 − ) are well simulated with normalized mean biases (NMBs) typically less than 20%. However, some notable exceptions are European NH 4 + , which is overpredicted by 33.0–42.2% due to high NH 3 emissions and irreversible coarse mode condensation, and Cl − , that is negatively impacted by errors in emissions driven by wind speed and overpredicted HNO 3 . Carbonaceous aerosols are largely underpredicted following the RCP scenarios due to low emissions of black carbon, organic carbon, and anthropogenic volatile compounds in the RCP inventory and efficient wet removal. This results in underpredictions of PM 2.5 and PM 10 by 6.4–55.7%. The column mass abundances are reasonably well simulated. Larger biases occur in surface mixing ratios of trace gases in CESM-NCSU, likely due to numerical diffusion from the coarse grid spacing of the CESM-NCSU simulations or errors in the magnitudes and vertical structure of emissions. This is especially true for SO 2 and NO 2 . The mixing ratio of O 3 is overpredicted by 38.9–76.0% due to the limitations in the O 3 deposition scheme used in CESM and insufficient titration resulted from large underpredictions in NO 2 . Despite these limitations, CESM-NCSU reproduces reasonably well the current atmosphere in terms of radiation, clouds, meteorology, trace gases, aerosols, and aerosol-cloud interactions, making it suitable for future climate simulations. [ABSTRACT FROM AUTHOR]

China has experienced increasingly severe O 3 pollution in recent years and air quality models (AQMs) have been widely used to understand it and to explore the possible solutions for it. Based on a thorough literature search, this review selected and investigated 212 AQM studies on Chinese O 3 since 2010, with different models and spatial scales. We evaluated the model performance of O 3 simulation and analyzed the main factors influencing the simulation. The correlation coefficients between simulation and observation were larger than 0.5 and the mean normalized biases (NMB) were within ±30% for nearly 80% of the cases collected from AQM studies. GEOS-Chem and CAMx commonly overestimated the ambient O 3 concentration, while the biases for CMAQ, WRF-Chem and NAQPMS were less conclusive. More applications and better model performances were found for the Yangtze River Delta and Pearl River Delta regions. Single-domain simulation provided the best model performance at a horizontal resolution of 12–30 km, and the performance would improve further at 5–10 km with the use of nested-domain and refined local emission inventory. Effective efforts for improvement of the O 3 simulation included incorporating chloride reactions with reactive nitrogen species, better considering the interaction with aerosols, and optimizing the parameterization schemes in meteorological processes and the land-use data. AQMs have been mainly applied in interpreting major driving forces and factors influencing O 3 level, understanding its source-receptor relationship, and evaluating its environmental impacts and policy effectiveness. Based on the diagnosis and detection of various AQM methods, meteorology seemed to always play a positive and, since the implementation of emission control strategy, increasingly important role on the growth of O 3 concentration, and thus should be taken more seriously in the future along with global warming. Source apportionment studies revealed that industry, transport and biogenic sources contributed almost 80% of O 3 in China while only around 30% could be attributed to local contribution during O 3 episodes in megacities. NO X -focused control measures led to a growth of O 3 in urban areas with VOC-limited regime, as well as a shift from VOC-limited to transitional regime in heavily polluted areas of eastern China. VOCs emission control in areas with VOC-limited regime and the negative effect of global warming should be of great concerns on O 3 pollution reduction in the future. • GEOS-Chem and CAMx commonly overestimated O 3 concentrations in China. • The correlation coefficient was over 0.5 and NMB was within ±30% in most cases. • Changed emissions were identified as the major driving force of long-term O 3 growth. • Industry, transportation and biogenic sources contributed almost 80% of O 3 in China. • Current NO X -focused control strategy resulted in a shift to more transitional regime. [ABSTRACT FROM AUTHOR]

Assessment of air quality in complex industrial and urban regions is essential in setting effective policies for sustainable development of society and assisting to improve the environment and thereby support health and safety. In this study, a CFD model fluidyn-PANACHE, dedicated to the dispersion of hazardous gases in complex industrial and urban sites, is critically validated with tracer observations from EMU experiment for two distinct types of sources in two geometrically different environments: (i) Case-A1 (release from an open door in courtyard area of a simple L-shaped building), and (ii) Case-C1 (continuous release over the larger distances around an industrial site featuring numerous buildings and complex local topography). The steady RANS solution is used first to get quick results and comparison with the experimental data shows a good agreement between the modelled and measured concentrations. Nevertheless, in order to examine the performance of the solver, unsteady RANS simulations are performed. A detailed statistical analysis shows that the performance of fluidyn-PANACHE against both Cases of EMU observations is well within the acceptable bounds of statistical measures for air quality applications. It is observed that in a simple geometry with lesser complexity in Case-A1, steady and unsteady simulations give similar performance against the tracer observations and predicts ≈68% points within a factor of two. In a more complex industrial site in Case-C1, unsteady RANS is performing slightly better than the steady simulation and it predicts ≈80.0% points within factor of two, which is higher than ≈67.0% points from the steady simulation. [ABSTRACT FROM AUTHOR]

The U.S. National Oceanic and Atmospheric Administration (NOAA) is responsible for forecasting elevated levels of air pollution within the National Air Quality Forecast Capability (NAQFC). The current research uses measurements gathered in the DISCOVER-AQ Colorado field campaign and the concurrent Front Range Air Pollution and Photochemistry Experiment (FRAPPE) to test performance of the NAQFC CMAQ modeling framework for predicting NH 3 . The DISCOVER-AQ and FRAPPE field campaigns were carried out in July and August 2014 in Northeast Colorado. Model predictions are compared with measurements of NH 3 gas concentrations and the NH 4 + component of fine particulate matter concentrations measured directly by the aircraft in flight. We also compare CMAQ predictions with NH 3 measurements from ground-based monitors within the DISCOVER-AQ Colorado geographic domain, and from the Tropospheric Emission Spectrometer (TES) on the Aura satellite. In situ aircraft measurements carried out in July and August of 2014 suggest that the NAQFC CMAQ model underestimated the NH 3 concentration in Northeastern Colorado by a factor of ∼2.7 (NMB = −63%). Ground-level monitors also produced a similar result. Average satellite-retrieved NH 3 levels also exceeded model predictions by a factor of 1.5–4.2 (NMB = −33 to −76%). The underestimation of NH 3 was not accompanied by an underestimation of particulate NH 4 + , which is further controlled by factors including acid availability, removal rate, and gas-particle partition. The average measured concentration of NH 4 + was close to the average predication (NMB = +18%). Seasonal patterns measured at an AMoN site in the region suggest that the underestimation of NH 3 is not due to the seasonal allocation of emissions, but to the overall annual emissions estimate. The underestimation of NH 3 varied across the study domain, with the largest differences occurring in a region of intensive agriculture near Greeley, Colorado, and in the vicinity of Denver. The NAQFC modeling framework did not include a recently developed bidirectional flux algorithm for NH 3 , which has shown to considerably improve NH 3 modeling in agricultural regions. The bidirectional flux algorithm, however, is not expected to obtain the magnitude of this increase sufficient to overcome the underestimation of NH 3 found in this study. Our results suggest that further improvement of the emission inventories and modeling approaches are required to reduce the bias in NAQFC NH 3 modeling predictions. [ABSTRACT FROM AUTHOR]

In this study, techniques typically used for future air quality projections are applied to a historical 11-year period to assess the performance of the modeling system when the driving meteorological conditions are obtained using dynamical downscaling of coarse-scale fields without correcting toward higher-resolution observations. The Weather Research and Forecasting model and the Community Multiscale Air Quality model are used to simulate regional climate and air quality over the contiguous United States for 2000–2010. The air quality simulations for that historical period are then compared to observations from four national networks. Comparisons are drawn between defined performance metrics and other published modeling results for predicted ozone, fine particulate matter, and speciated fine particulate matter. The results indicate that the historical air quality simulations driven by dynamically downscaled meteorology are typically within defined modeling performance benchmarks and are consistent with results from other published modeling studies using finer-resolution meteorology. This indicates that the regional climate and air quality modeling framework utilized here does not introduce substantial bias, which provides confidence in the method’s use for future air quality projections. [ABSTRACT FROM AUTHOR]

Black carbon (BC) has been simulated for south-west Spain with the air quality model CAMx driven by the MM5 meteorological model, with a spatial resolution of 2 km × 2 km and a temporal resolution of 1 h. The simulation results were evaluated against hourly equivalent black carbon (EBC) concentrations obtained in the cities of Seville and Huelva for a winter period (January 2013) and a summer period (June 2013). A large seasonal variability was observed in PM 2.5 EBC concentration in the two cities, with higher concentrations in wintertime; summertime EBC concentrations were typically less than half those of the wintertime. The model captured the large diurnal, seasonal and day to day variability in these urban areas, mean biases ranged between −0.14 and 0.07 μg m −3 in winter and between 0.01 and 0.29 μg m −3 in summer while hourly PM 2.5 EBC observations ranged between 0.03 μg m −3 to 10.9 μg m −3 . The diurnal variation in EBC concentrations was bimodal, with a morning and evening peak. However, the EBC evening peak was much smaller in summer than in winter. The modelling analysis demonstrates that the seasonal and day to day variability in EBC concentration in these urban areas is primarily driven by the variation in meteorological conditions. An evaluation of the role of regional versus local contributions to EBC concentrations indicates that in the medium size city of Seville, local on-road sources are dominant, whereas in the small size city of Huelva, local as well as regional sources produce a similar contribution. Considering the large diesel share of the vehicle fleet in Spain (currently ∼ 56%), we conclude that continued reduction of BC from diesel on-road sources in these urban areas is indeed a priority, and we suggest that targeted mitigation strategies, for example reducing the heaviest emitters in wintertime, would yield the greatest benefits. [ABSTRACT FROM AUTHOR]

In this work, the application of the online-coupled Weather Research and Forecasting model with chemistry (WRF/Chem) version 3.3.1 is evaluated over East Asia for January, April, July, and October 2005 and compared with results from a previous application of an offline model system, i.e., the Mesoscale Model and Community Multiple Air Quality modeling system (MM5/CMAQ). The evaluation of WRF/Chem is performed using multiple observational datasets from satellites and surface networks in mainland China, Hong Kong, Taiwan, and Japan. WRF/Chem simulates well specific humidity (Q2) and downward longwave and shortwave radiation (GLW and GSW) with normalized mean biases (NMBs) within 24%, but shows moderate to large biases for temperature at 2-m (T2) (NMBs of −9.8% to 75.6%) and precipitation (NMBs of 11.4–92.7%) for some months, and wind speed at 10-m (WS10) (NMBs of 66.5–101%), for all months, indicating some limitations in the YSU planetary boundary layer scheme, the Purdue Lin cloud microphysics, and the Grell–Devenyi ensemble scheme. WRF/Chem can simulate the column abundances of gases reasonably well with NMBs within 30% for most months but moderately to significantly underpredicts the surface concentrations of major species at all sites in nearly all months with NMBs of −72% to −53.8% for CO, −99.4% to −61.7% for NO x , −84.2% to −44.5% for SO 2 , −63.9% to −25.2% for PM 2.5 , and −68.9% to 33.3% for PM 10 , and aerosol optical depth in all months except for October with NMBs of −38.7% to −16.2%. The model significantly overpredicts surface concentrations of O 3 at most sites in nearly all months with NMBs of up to 160.3% and NO 3 - at the Tsinghua site in all months. Possible reasons for large underpredictions include underestimations in the anthropogenic emissions of CO, SO 2 , and primary aerosol, inappropriate vertical distributions of emissions of SO 2 and NO 2 , uncertainties in upper boundary conditions (e.g., for O 3 and CO), missing or inaccurate model representations (e.g., secondary organic aerosol formation, gas/particle partitioning, dust emissions, dry and wet deposition), and inaccurate meteorological fields (e.g., overpredictions in WS10 and precipitation, but underpredictions in T2), as well as the large uncertainties in satellite retrievals (e.g., for column SO 2 ). Comparing to MM5, WRF generally gives worse performance in meteorological predictions, in particular, T2, WS10, GSW, GLW, and cloud fraction in all months, as well as Q2 and precipitation in January and October, due to limitations in the above physics schemes or parameterizations. Comparing to CMAQ, WRF/Chem performs better for surface CO, O 3 , and PM 10 concentrations at most sites in most months, column CO and SO 2 abundances, and AOD. It, however, gives poorer performance for surface NO x concentrations at most sites in most months, surface SO 2 concentrations at all sites in all months, and column NO 2 abundances in January and April. WRF/Chem also gives lower concentrations of most secondary PM and black carbon. Those differences in results are attributed to differences in simulated meteorology, gas-phase chemistry, aerosol thermodynamic and dynamic treatments, dust and sea salt emissions, and wet and dry deposition treatments in both models. [ABSTRACT FROM AUTHOR]

In this study, the Weather Research and Forecasting model with chemistry (WRF-Chem v3.5) is applied to the area of Poland, for a period of 03.07-03.08.2006, when high concentrations of ground level ozone were observed. The meteorological and chemistry simulations were initiated with the ERA-Interim reanalysis and the TNO MACC-II emissions database. Simulations were performed for three one-way nested domains. The results from the innermost domain were examined and compared to measurements of ozone concentrations and meteorological variables. The modelled results show a general underestimation of measured ozone concentrations. For urban and suburban sites it is significantly higher during day time. Domain-wide estimations of temperature were also underestimated, and relative humidity and wind speed were overpredicted. The results may be further improved by adjusting physical parameterisations and including a more detailed emission input data into the model. [ABSTRACT FROM AUTHOR]

The National Air Quality Forecast Capability (NAQFC) and an experimental version of the NAQFC (NAQFC- β) provided flight decision support during the July 2011 NASA DISCOVER-AQ field campaign around Baltimore, Maryland. Ozone forecasts from the NAQFC and NAQFC- β were compared to surface observations at six air quality monitoring stations in the DISCOVER-AQ domain. A bootstrap algorithm was used to test for significant bias and error in the forecasts from each model. Both models produce significant positively biased forecasts in the morning while generally becoming insignificantly biased in the afternoon during peak ozone hours. The NAQFC- β produces higher forecast bias, higher forecast error, and lower correlations than the NAQFC. Forecasts from the two models were also compared to each other to determine the spatial and temporal extent of significant differences in forecasted ozone using a bootstrap algorithm. The NAQFC- β tends to produce an average background ozone mixing ratio of at least 3.51 ppbv greater than the NAQFC throughout the domain at 95 % significance. The difference between the two models is significant during the overnight and early morning hours likely due to the way the Carbon Bond 5 mechanism in the NAQFC- β handles reactive nitrogen recycling and organic peroxide species. The value of information each model provides was tested using a static cost-loss ratio model. By standard measures of forecast skill, the NAQFC generally outperforms the NAQFC- β; however, the NAQFC- β provides greater value of information. This is because standard measures of forecast skill often hide the sensitivity of end users' needs to forecast error. [ABSTRACT FROM AUTHOR]

Air pollution causes adverse effects on human health as well as ecosystems and crop yield and also has an impact on climate change trough short-lived climate forcers. To design mitigation strategies for air pollution, 3D Chemistry Transport Models (CTMs) have been developed to support the decision process. Increases in model resolution may provide more accurate and detailed information, but will cubically increase computational costs and pose additional challenges concerning high resolution input data. The motivation for the present study was therefore to explore the impact of using finer horizontal grid resolution for policy support applications of the European Monitoring and Evaluation Programme (EMEP) model within the Long Range Transboundary Air Pollution (LRTAP) convention. The goal was to determine the “optimum resolution” at which additional computational efforts do not provide increased model performance using presently available input data. Five regional CTMs performed four runs for 2009 over Europe at different horizontal resolutions. The models’ responses to an increase in resolution are broadly consistent for all models. The largest response was found for NO 2 followed by PM 10 and O 3 . Model resolution does not impact model performance for rural background conditions. However, increasing model resolution improves the model performance at stations in and near large conglomerations. The statistical evaluation showed that the increased resolution better reproduces the spatial gradients in pollution regimes, but does not help to improve significantly the model performance for reproducing observed temporal variability. This study clearly shows that increasing model resolution is advantageous, and that leaving a resolution of 50 km in favour of a resolution between 10 and 20 km is practical and worthwhile. As about 70% of the model response to grid resolution is determined by the difference in the spatial emission distribution, improved emission allocation procedures at high spatial and temporal resolution are a crucial factor for further model resolution improvements. [ABSTRACT FROM AUTHOR]

In the United States, regional-scale photochemical models are being used to design emission control strategies needed to meet the relevant National Ambient Air Quality Standards (NAAQS) within the framework of the attainment demonstration process. Previous studies have shown that the current generation of regional photochemical models can have large biases and errors in simulating absolute levels of pollutant concentrations. Studies have also revealed that regional air quality models were not always accurately reproducing even the relative changes in ozone air quality stemming from changes in emissions. This paper introduces four approaches to adjust for model bias and errors in order to provide greater confidence for their use in estimating future concentrations as well as using modeled pollutant concentrations in exposure assessments. The four methods considered here are a mean and variance (MV) adjustment, temporal component decomposition (TC) adjustment of modeled concentrations, and two variants of cumulative distribution function (CDF) mapping. These methods were compared against each other as well as against unadjusted model concentrations and a version of the relative response approach based on unadjusted model predictions. The analysis uses ozone concentrations simulated by the Community Multiscale Air Quality (CMAQ) model for the northeastern United States domain for the years 1996–2005. Ensuring that base case conditions are adequately represented through the combined use of observations and model simulations is shown to result in improved estimates of future air quality under changing emissions and meteorological conditions. [ABSTRACT FROM AUTHOR]

The WRF-CMAQ modelling system was applied for air quality simulation over Europe in the frame of the air quality model evaluation international initiative (AQMEII), phase 2. The models were run for the year 2010 for a domain of 5,000 5,000 km? with a horizontal grid resolution of 25 km. A preliminary evaluation of model results vs. EU surface measurements was conducted using JRC web-based ENSEMBLE platform. Model performance was characterised by overestimation for ozone and underestimation for NO2. Trying to understand this fact, another set of NOx emissions, a more complete one, was prepared and the simulations were repeated for the entire year (BG1 and BG2 sets). The increase of NOx emissions with 30% slightly increase the quality of the simulation - the overestimation of O3 decreases by a few percent and NO2 concentrations increase and reach observed levels at rural sites, while they still remain underpredicted at urban sites. [ABSTRACT FROM AUTHOR]

Model evaluation is performed based on comparison of simulated and observed air pollution concentrations at 25 background stations of the Bulgarian national air quality monitoring network for the year 2013. The DELTA software package, developed within the forum for air quality modelling in Europe - FAIRMODE, is used to analyse model results focusing on maximum daily eight-hour mean ozone concentrations, hourly nitrogen dioxide (NO2) and daily particulate matter (PM10) concentrations. Ozone is overestimated by 38%, minimum daily values are overestimated by a factor of 3. NO2 and PM10 are underestimated by a factor of, respectively, 4 and (5 to 9). The main DELTA model quality objective is respected at 26% of the stations for ozone, 58% of the stations for NO2, and nowhere for PM10. The best model performance is for ozone at rural sites during summer. Possible ways for improvement of model results are discussed. [ABSTRACT FROM AUTHOR]

An evaluation of how CHIMERE estimates the wet deposition of sulphur and nitrogen (oxidised and reduced) on the Iberian Peninsula was performed. The CHIMERE estimates were compared with monthly data measured in the Spanish EMEP stations covering a period of four years (2005-2008) and with results of the EMEP model. The seasonal and spatial variability have also been studied. The model system formed by WRF and CHIMERE underpredicts the wet deposition of reduced nitrogen, while the results for oxidised nitrogen are better than those of the ECMWF-IFS/EMEP model system. WRF/CHIMERE estimates of wet deposition of sulphur seem to correlate quite well with observations, but there is some slight underprediction. Monthly rainfall estimates by both WRF and ECMWF-IFS meteorological models fit observations quite well, with somewhat worse results in summer and at southeastern stations. The reason why wet deposition estimates are not as good as desirable seems not to be related to how the models simulate precipitation. [ABSTRACT FROM AUTHOR]

Particulate matter (PM) air quality in Europe has improved substantially over the past decades, but it still poses a significant threat to human health. Accurate regional scale maps of PM10 concentrations are needed for monitoring progress in mitigation strategies and monitoring compliance with statutory limit values. Chemistry transport models (CTM) use emission databases and simulate the transport and deposition of pollutants. They deliver such maps but are known to be inaccurate. A promising approach is to use geostatistics to model the relationship between the in situ observations and the CTM. This has been shown to be more accurate than using either observations or CTM's alone. This paper presents a spatially varying coefficients (SVC) geostatistical model as an extension of the standard spatially varying intercept (SVI) geostatistical model. SVC allowed the regression coefficient to vary spatially according to a covariance function, the parameters of which were estimated from the data. It was built as a Bayesian hierarchical model and implemented using Markov chain Monte Carlo. The procedure was applied to Airbase PM10 observations and LOTOS-EUROS simulated PM10 for central, southern and eastern Europe. Model-fit diagnostics showed that SVC delivered a better fit to the data than SVI. Mapping the spatially varying coefficients allowed identification of the locations where the CTM performed well or poorly. This could be used for objective CTM evaluation purposes. The posterior predictive simulations were also used to map median PM10 concentrations as well as the probability of exceeding the 50 μg m −3 EU daily PM10 concentration threshold. Although posterior median prediction accuracy was similar for SVI and SVC, SVC better modelled the process and yielded narrower credible intervals. As such, SVC was more appropriate for quantifying uncertainty and for mapping threshold exceedances. The resulting maps may be used to guide air quality assessment and mitigation strategies, including those related to health impacts. [ABSTRACT FROM AUTHOR]

A dispersion model for continuous releases of pollutants in the atmospheric boundary layer is applied to study the influence on modelled concentrations of different estimates of the key micrometeorological variables that represent the dispersion processes. The modelling approach is based on the advection-diffusion equation and includes profiles of wind and eddy diffusivity for the entire atmospheric boundary layer. Their functional forms depend on relevant parameters that represent the turbulent mechanisms in a wide range of stabilities. The Prairie Grass experiments were considered for the evaluation. The model performed satisfactorily in the estimation of the near surface crosswind integrated concentrations. The distinct micrometeorological parameters caused, in general, minor differences in the concentrations. However, a greater impact was found during very stable or unstable conditions. In consequence, in these particular situations, the methodologies to obtain the micrometeorological parameters must be carefully analysed. [ABSTRACT FROM AUTHOR]

Abstract: Changes in climate and emissions will affect future air quality. In this work, simulations of regional air quality during current (2001–2005) and future (2026–2030) winter and summer are conducted with the newly released CMAQ version 5.0 to examine the impacts of simulated future climate and anthropogenic emission projections on air quality over the U.S. Current meteorological and chemical predictions are evaluated against observations to assess the model's capability in reproducing the seasonal differences. WRF and CMAQ capture the overall observational spatial patterns and seasonal differences. Biases in model predictions are attributed to uncertainties in emissions, boundary conditions, and limitations in model physical and chemical treatments as well as the use of a coarse grid resolution. Increased temperatures (up to 3.18 °C) and decreased ventilation (up to 157 m in planetary boundary layer height) are found in both future winter and summer, with more prominent changes in winter. Increases in future temperatures result in increased isoprene and terpene emissions in winter and summer, driving the increase in maximum 8-h average O3 (up to 5.0 ppb) over the eastern U.S. in winter while decreases in NO x emissions drive the decrease in O3 over most of the U.S. in summer. Future PM2.5 concentrations in winter and summer and many of its components decrease due to decreases in primary anthropogenic emissions and the concentrations of secondary anthropogenic pollutants as well as increased precipitation in winter. Future winter and summer dry and wet deposition fluxes are spatially variable and increase with decreasing surface resistance and precipitation, respectively. They decrease with a decrease in ambient particulate concentrations. Anthropogenic emissions play a more important role in summer than in winter for future O3 and PM2.5 levels, with a dominance of the effects of significant emission reductions over those of climate change on future PM2.5 levels. [Copyright &y& Elsevier]

Abstract: Estimating measurement uncertainty for NO2 and PM10 is a complex issue that is normally addressed by experimentalists specifically for every type of instrument and measurement. On the other hand, an estimate of the maximum expected measurement uncertainty is needed when a numerical model is to be evaluated against observations, as proposed in Thunis et al. (2012, referred to as T2012). In a companion paper (Thunis et al., 2013, referred to as T2013) a simplified formulation of the measurement uncertainty in function of the measured concentration is proposed and applied to the simpler case of Ozone. In this paper the same approach is applied for NO2 and PM10, but using different techniques for the uncertainty estimation. For NO2 the Guide to the expression of Uncertainty in Measurement JCGM (2008, referred to as GUM) approach is used and applied on each urban AirBase (1997) measurement over the year 2009. For PM10, the method of the Guide for the Demonstration of Equivalence (ECWG, 2010) is used on data obtained with two different PM samplers used in parallel either during specific monitoring campaign or as available within the AirBase database. The resulting concentration dependent measurement uncertainties are then used to update the MQO (Model Quality Objective) and MPC (Model Performance Criteria) proposed in T2012. An estimate of the measurement uncertainty for annual means is proposed as well. [Copyright &y& Elsevier]

Abstract: Since models are increasingly used for policy support their evaluation is becoming an important issue. One of the possible evaluations is to compare model results to measurements. Statistical performance indicators then provide insight on model performance but do not tell whether model results have reached a sufficient level of quality for a given application. In a previous work Thunis et al. (2012, referred to as T2012) proposed a Model Quality Objective (MQO) based on the root mean square error between measured and modeled concentrations divided by the measurement uncertainty. In T2012 the measurement uncertainty was assumed to remain constant regardless of the concentration level. In the current work this assumption is overcome by quantifying all possible sources of uncertainty for the particular case of O3. Based on these uncertainty source quantifications, a simple relationship is proposed to formulate the measurement uncertainty which is then used to update the MQO and Model Performance Criteria (MPC) proposed in T2012 with more accurate values. The MQO and MPC calculated based on the European monitoring network AIRBASE data provide insight on the expected model results quality for a given application, depending on the geographical area and station type. These station specific MQOs and MPCs have the main advantage of relating expected model performances to the underlying measurement uncertainties. [Copyright &y& Elsevier]

Abstract: Chemically speciated concentrations of PM2.5 (sulphate, ammonium, nitrate, elemental and organic carbon) were simulated in south-west Europe using the three-dimensional air quality model CAMx driven by the MM5 meteorological model. The inner domain covered the south-west region of Spain with a high spatial (2 km × 2 km) and temporal resolution (1 h). The simulation results were evaluated against experimental data obtained in four intensive field campaigns performed in 2008 and 2009 at urban and rural sites. PM2.5 measurements of secondary inorganic compounds and carbonaceous aerosol plus a suite of major and trace elements were determined. High time resolution (10 min) measurements of Black Carbon (BC) were also conducted. The model captured the variability in the ammonium concentrations in both summer and winter periods, although it tended to underestimate the magnitude of concentrations, while for sulphate the performance was better during the summer periods. Particulate ammonium nitrate was only simulated in significant concentrations in the wintertime campaign. This was found to be consistent with the measured composition of PM2.5 where most of nitrate (79–94%) and a significant fraction of sulphate (24–37%) were estimated to be present as non-ammonium salts. These non-ammonium nitrate salts were attributed to the formation of NaNO3. The model PM2.5 primary elemental carbon simulations, evaluated with hourly resolution, captured the diurnal and seasonal variability of PM2.5 BC concentrations at the urban site while poorer performance was observed at the rural site. A large underestimation was observed for simulated PM2.5 organic carbon concentrations during all campaigns. Scenarios of pollution events linked to emissions from south-west Spain, shipping and contributions from more distant emission sources such as Portugal were identified. These results highlight how the distinct features of PM2.5 composition in southern Europe regions, such as the large contribution of non-ammonium salts, need to be taken into account both in model evaluation and in future implementation of aerosol modelling systems. [Copyright &y& Elsevier]

Abstract: In Chemistry Transport Models (CTMs), spatial scale interactions are often represented through off-line coupling between large and small scale models. However, those nested configurations cannot give account of the impact of the local scale on its surroundings. This issue can be critical in areas exposed to air mass recirculation (sea breeze cells) or around regions with sharp pollutant emission gradients (large cities). Such phenomena can still be captured by the mean of adaptive gridding, two-way nesting or using model nudging, but these approaches remain relatively costly. We present here the development and the results of a simple alternative multi-scale approach making use of a horizontal stretched grid, in the Eulerian CTM CHIMERE. This method, called “stretching” or “zooming”, consists in the introduction of local zooms in a single chemistry-transport simulation. It allows bridging online the spatial scales from the city (∼1 km resolution) to the continental area (∼50 km resolution). The CHIMERE model was run over a continental European domain, zoomed over the BeNeLux (Belgium, Netherlands and Luxembourg) area. We demonstrate that, compared with one-way nesting, the zooming method allows the expression of a significant feedback of the refined domain towards the large scale: around the city cluster of BeNeLuX, NO2 and O3 scores are improved. NO2 variability around BeNeLux is also better accounted for, and the net primary pollutant flux transported back towards BeNeLux is reduced. Although the results could not be validated for ozone over BeNeLux, we show that the zooming approach provides a simple and immediate way to better represent scale interactions within a CTM, and constitutes a useful tool for apprehending the hot topic of megacities within their continental environment. [Copyright &y& Elsevier]

Abstract: Background: Air quality models are being increasingly used to estimate long-term individual exposures to air pollution in epidemiological studies. Most of them have been evaluated against measurements from a limited number of monitoring stations, which may not properly reflect the exposure characteristics of the study population. Methods: We evaluated the performance of the high-resolution CALIOPE air quality forecasting system over a large sample of passive measurements of NO2 conducted at 635 home outdoor locations of the Girona province (Spain) during several 4-week sampling campaigns over one year (July 2007–June 2008). Sampling sites were superposed over the 4 km × 4 km CALIOPE grid, and average NO2 modeled concentrations were derived for all measurements conducted during the same sampling campaign at all the sampling sites located within the same grid cell. In addition, the ratio between measured and modeled concentrations for the whole study period at one fixed monitoring station was used to post-process the modeled values at the home outdoor locations. Results: The correlation between measured and modeled concentrations for the entire study area (which includes urban settings, middle-size towns, and rural areas) was 0.78. Modeled concentrations were underestimated in the whole study area. After correcting the modeled concentrations by the measured to modeled ratio at the fixed station (r = 0.25), they were very similar to the measured concentrations (27.7 μg m−3 and 29.3 μg m−3, respectively). However, the performance of the modeling system depends on the type of subarea and is affected by the sub-grid emission sources. Conclusions: The evaluation over the heterogenous Girona province showed that CALIOPE is able to reproduce the spatial variability of 4-week NO2 concentrations at the small regional level. CALIOPE output data is a valuable tool to complement study-specific air pollution measurements by incorporating regional spatial variability as well as short- and long-term temporal variability of background pollution in epidemiological research. [Copyright &y& Elsevier]

A mechanistic exploration of how ozone formation in the Lower Fraser Valley (LFV) has changed over a 20-year (1985–2005) retrospective period was performed using numerical models, observations, and emissions data from four key episodes selected from the 20-year period. The motivation for this study was the observed differences in trends in summertime episodic ozone concentrations recorded at various monitoring stations within the valley; stations in the western part of the valley have generally shown a noticeable reduction in episodic ozone concentrations whereas stations in the eastern part of the valley have shown little or no improvement in their maximum 8-hour averaged ozone concentrations. Concurrent with these air quality changes, there has been a well-documented reduction in ozone precursor emissions along with an observed shift in the population patterns within the valley over the 20-year period. Ozone formation for four episodes, encompassing the different meteorological regimes that occur during LFV ozone events and spanning the retrospective period, were investigated using the Weather Research and Forecasting (WRF)-Sparse Matrix Operator Kernel Emission (SMOKE)-Community Multiscale Air Quality (CMAQ) modelling system. For each episode, two simulations, intended to isolate the effects of emission changes from meteorological changes, were performed: one with emissions set at the 1985 level and the other with emissions set at the 2005 level. Based on analysis of the model output, observational data, and precursor emission inventories, we find that the Port Moody station in the western LFV remains a volatile organic compound (VOC)-sensitive location; the central part of the LFV around the town of Chilliwack has generally changed from being VOC-limited to being NOx-limited; the easternmost part of the valley around the town of Hope has been and remains NOx-limited. Furthermore, based on the observational data and numerical model output, ozone production efficiency as a function of NO has increased noticeably at Chilliwack and likely in the other eastern parts of the valley. This efficiency increase has likely offset some of the benefits resulting from local NOxemission reductions. RÉSUMÉ [Traduit par la rédaction] Nous avons effectué une exploration mécaniste de la façon dont la formation de l'ozone dans la vallée du bas Fraser (VBF) a changé au cours d'une période rétrospective de 20 ans (1985–2005) en nous servant de modèles numériques, d'observations et de données sur les émissions pour quatre épisodes clés choisis dans la période de 20 ans. Ce sont les différences observées entre les tendances dans les concentrations épisodiques d'ozone enregistrées à certaines stations de surveillance dans la vallée qui ont motivé cette étude : les stations dans la partie ouest de la vallée ont généralement affiché une réduction notable des concentrations épisodiques d'ozone alors que les stations dans la partie est de la vallée n'ont montré que peu ou pas d'amélioration dans les valeurs maximales des concentrations moyennes d'ozone sur 8 heures. Concurremment avec ces changements dans la qualité de l'air, il s'est produit une réduction bien documentée dans les émissions de précurseurs de l'ozone en même temps qu'un déplacement observé dans les configurations de population dans la vallée au cours de la période de 20 ans. Nous avons étudié la formation d'ozone au cours de quatre épisodes, englobant les différents régimes météorologiques survenus lors des événements d'ozone dans la VBF et couvrant la période rétrospective, à l'aide du système de modélisation SMOKE (Sparse Matrix Operator Kernel Emissions) – CMAQ (Community Multiscale Air Quality) du WRF (Weather Research and Forecasting). Pour chaque épisode, nous avons effectué deux simulations visant à isoler l'effet des changements dans les émissions de l'effet des changements météorologiques, l'une avec les émissions réglées au niveau de 1985 et l'autre avec les émissions réglées au niveau de 2005. En nous basant sur l'analyse de la sortie du modèle, les données d'observation et les inventaires des émissions de précurseurs, nous trouvons que la stations de Port Moody dans l'ouest de la VBF demeure un endroit sensible aux composés organiques volatiles (COV); la partie centrale de la VBF, autour de la ville de Chilliwack, a généralement changé de « limitée par les COV » à « limitée par les NOx»; la partie la plus à l'est de la vallée, autour de la ville de Hope, était et est restée « limitée par les NOx». De plus, d'après les données d'observation et la sortie du modèle numérique, l'efficacité de la production d'ozone en fonction de NO a notablement augmenté à Chilliwack et vraisemblablement dans les autres parties de l'est de la vallée. Cette augmentation d'efficacité a probablement annulé certains gains provenant des réductions dans les émissions locales de NOx. [ABSTRACT FROM AUTHOR]

Abstract: Air quality within the European Union (EU) is controlled by the Member States'' monitoring networks. In this study, measured data is compared with the EURAD (EURopean Air pollution Dispersion) model system diagnostic output. Simulations for the German state North Rhine-Westphalia (NRW) with a horizontal grid resolution of 5km×5km are analyzed. The comparison is performed for NO2, O3, and PM10, for the 4-year time period from 2002 through 2005. Although the spatial representativity of data of the two systems differs, the analyzed temporal variability of the averages shows good agreement of modeled and observed concentrations for all three parameters. This confirms the applicability of the EURAD model to mesoscale air quality assessment. Discrepancies between the model and observed data occurred at low concentrations close to the detection limits of the analyzers, for high O3 concentrations in summer, and for PM10 before 2004, when earlier versions of the MM5 meteorological module and of the emission inventory were used. Possible causes of O3 overprediction and NO2 underprediction preferably showing up in summer are considered. It is found that modeled Ox =O3 +NO2 leads to better representation of the observations than the individual species themselves. The model performance can probably be increased by further development of the emission inventories and more accurate land use data. These input data seem to be the main reason for deviations between observations and model results. [Copyright &y& Elsevier]

Abstract: In this paper we have coupled the CMAQ and ADMS air quality models to predict hourly concentrations of NO X , NO2 and O3 for London at a spatial scale of 20 m × 20 m. Model evaluation has demonstrated reasonable agreement with measurements from 80 monitoring sites in London. For NO2 the model evaluation statistics gave 73% of the hourly concentrations within a factor of two of observations, a mean bias of −4.7 ppb and normalised mean bias of −0.17, a RMSE value of 17.7 and an r value of 0.58. The equivalent results for O3 were 61% (FAC2), 2.8 ppb (MB), 0.15 (NMB), 12.1 (RMSE) and 0.64 (r). Analysis of the errors in the model predictions by hour of the week showed the need for improvements in predicting the magnitude of road transport related NO X emissions as well as the hourly emissions scaling in the model. These findings are consistent with recent evidence of UK road transport NO X emissions, reported elsewhere. The predictions of wind speed using the WRF model also influenced the model results and contributed to the daytime over prediction of NO X concentrations at the central London background site at Kensington and Chelsea. An investigation of the use of a simple NO–NO2–O3 chemistry scheme showed good performance close to road sources, and this is also consistent with previous studies. The coupling of the two models raises an issue of emissions double counting. Here, we have put forward a pragmatic solution to this problem with the result that a median double counting error of 0.42% exists across 39 roadside sites in London. Finally, whilst the model can be improved, the current results show promise and demonstrate that the use of a combination of regional scale and local scale models can provide a practical modelling tool for policy development at intergovernmental, national and local authority level, as well as for use in epidemiological studies. [Copyright &y& Elsevier]

Abstract: Due to the strong relation between meteorology and air quality, a changing climate is anticipated to significantly impact air pollution. To investigate this effect a synoptic situation in the past which is expected to occur more often in future is analyzed in terms of air quality. In this study the effect of the meteorological conditions in the extreme summer 2003 on the concentration of PM10 and its components is investigated over Europe. To this end measurements of the EMEP network in Europe of the summer 2003 were compared to the average of the summers of a five years period (2003–2007). Furthermore simulation runs were performed with the German chemistry transport model REM-Calgrid and the Dutch model LOTOS-EUROS, to analyze whether state-of-the-art chemistry transport models are able to reproduce the observed concentrations during this episode. The synoptic situation in summer 2003 resulted in 1–10 μg m−3 higher observed PM10 concentrations compared to the five years average. This increase was not reproduced to the same extent by the two models at most of the stations and the two models show evident differences in their PM10 simulations. The correlation between PM10 concentrations and meteorological parameters indicates that observed concentrations increase during weather conditions with high daily maximum temperature. The same holds for elemental carbon which is chosen as an example for a primary component. Low horizontal transport and the absence of wet deposition as a result of low wind speed and little precipitation associated with conditions with high temperatures favour the accumulation of pollutants in the lower troposphere. Although these conditions are reflected in the meteorological input data of the chemistry transport models used in this study, the models were not able to reproduce this relationship; they underestimate the observed high concentrations. This indicates that the underestimation of the variability of PM with meteorology is due to missing but important components and associated emissions or uncertainties therein, e.g. mineral dust, secondary organic aerosols and wild fires. To improve the simulation performance of the chemistry transport models as function of meteorological conditions these emission sources and the formation of secondary organic aerosols have to be included or improved and the dependency of anthropogenic emissions on meteorological conditions should be explicitly taken into account. These are essential issues for the simulation of such extreme conditions. [Copyright &y& Elsevier]

This work regards a model evaluation exercise concerning the WRF meteorological model and in situ measurements collected both over land, at four WMO meteorological stations, and over open sea, by ODAS Italia 1, the only spar buoy in the Mediterranean Sea. In particular, this exercise is finalised to understand the ability of the model to act as meteorological pre-processor to simulate aerosol emissions from the sea, an important factor to correctly predict pollutant levels. The test is carried out for the August to December 2005 period over the Ligurian Sea region, a very complex area where the strong air-sea interactions and orography significantly affect the atmospheric circulation. Performances of two model versions, WRF-ARW 3.0 and WRF-ARW 3.2.1, applied at two different horizontal resolutions, have been compared. The results show that the new parameterisations introduced in WRF 3.2.1 improve the performance of the model with respect to version 3.2.0. Increasing the model domain resolution from 15 km to 5 km does not generally improve the model performance, except for the wind direction reconstruction. The model proved its reliability as meteorological processor, although further efforts are required to improve wind field simulation, mainly in order to reduce the low bias still affecting the reconstruction at high wind speed. [ABSTRACT FROM AUTHOR]

Abstract: Model evaluation studies are essential for determining model performance as well as assessing model deficiencies, and are the focus of the Air Quality Model Evaluation International Initiative (AQMEII). The chemistry-transport model system COSMO–MUSCAT participates in this initiative. In this paper the robustness and variability of the model results against changes in the model setup are analyzed. Special focus is given to the formation of secondary particulate matter and the ability to reproduce unusually high levels of PM10 in Central Europe caused by long-range transported smoke of fires in western Russia. Seven different model configurations are investigated in this study. The COSMO–MUSCAT results are evaluated in comparison with ground-based measurements in Central Europe. The analysis is performed for two selected periods in April/May 2006 and October 2006 which are characterized by elevated concentrations of PM. Furthermore, the sensitivity of the results is studied against the used grid resolution and the meteorological forcing. Here, COSMO–MUSCAT is applied with different horizontal grid sizes and, alternatively, forced by reanalysis data with finer resolution. The use of finer grid resolutions in COSMO–MUSCAT has direct consequences on the meteorological forcing as well as on the calculated emission and deposition rates. The presented results suggest a large impact of the meteorological effects on the PM concentrations. The more accurate spatial appointment of the emissions and deposition fluxes seems to be of little consequence compared to the meteorological forcing. [Copyright &y& Elsevier]

Abstract: Over twenty modeling groups are participating in the Air Quality Model Evaluation International Initiative (AQMEII) in which a variety of mesoscale photochemical and aerosol air quality modeling systems are being applied to continental-scale domains in North America and Europe for 2006 full-year simulations for model inter-comparisons and evaluations. To better understand the reasons for differences in model results among these participating groups, each group was asked to use the same source of emissions and boundary concentration data for their simulations. This paper describes the development and application of the boundary concentration data for this AQMEII modeling exercise. The European project known as GEMS (Global and regional Earth-system Monitoring using Satellite and in-situ data) has produced global-scale re-analyses of air quality for several years, including 2006 (http://gems.ecmwf.int). The GEMS trace gas and aerosol data were made available at 3-hourly intervals on a regular latitude/longitude grid of approximately 1.9° resolution within 2 “cut-outs” from the global model domain. One cut-out was centered over North America and the other over Europe, covering sufficient spatial domain for each modeling group to extract the necessary time- and space-varying (horizontal and vertical) concentrations for their mesoscale model boundaries. Examples of the impact of these boundary concentrations on the AQMEII continental simulations are presented to quantify the sensitivity of the simulations to boundary concentrations. In addition, some participating groups were not able to use the GEMS data and instead relied upon other sources for their boundary concentration specifications. These are noted, and the contrasting impacts of other data sources for boundary data are presented. How one specifies four-dimensional boundary concentrations for mesoscale air quality simulations can have a profound impact on the model results, and hence, this aspect of data preparation must be performed with considerable care. [Copyright &y& Elsevier]

Abstract: Accurate regional air pollution simulation relies strongly on the accuracy of the mesoscale meteorological simulation used to drive the air quality model. The framework of the Air Quality Model Evaluation International Initiative (AQMEII), which involved a large international community of modeling groups in Europe and North America, offered a unique opportunity to evaluate the skill of mesoscale meteorological models for two continents for the same period. More than 20 groups worldwide participated in AQMEII, using several meteorological and chemical transport models with different configurations. The evaluation has been performed over a full year (2006) for both continents. The focus for this particular evaluation was meteorological parameters relevant to air quality processes such as transport and mixing, chemistry, and surface fluxes. The unprecedented scale of the exercise (one year, two continents) allowed us to examine the general characteristics of meteorological models’ skill and uncertainty. In particular, we found that there was a large variability between models or even model versions in predicting key parameters such as surface shortwave radiation. We also found several systematic model biases such as wind speed overestimations, particularly during stable conditions. We conclude that major challenges still remain in the simulation of meteorology, such as nighttime meteorology and cloud/radiation processes, for air quality simulation. [Copyright &y& Elsevier]

Abstract: Sulfur dioxide and nitrogen oxides form two of largest contributors to PM2.5 in Europe; ammonium sulfate ((NH4)2SO4) and ammonium nitrate (NH4NO3). In-situ observations of many chemical components are rather sparse, and thus neither can accurately characterize the distribution of pollutants nor predict the effectiveness of emission control. Understanding (and controlling) the formation regimes for these components is important for the achievement of the reduction objectives established in the European legislation for PM2.5 (20% of PM2.5 triennial for the mean of urban background levels between 2018 and 2020). For this purpose, the present work uses the CALIOPE high-resolution air quality modeling system (12km×12km, 1h) to investigate the formation of SIA (SO4 2−, NO3 − and NH4 +, which involve an important part of PM) and their gaseous precursors (SO2, HNO3 and NH3) over Europe during the year 2004. The CALIOPE system performs well at estimating SIAs when compared to the measurements from EMEP monitoring network, but errors are larger for gaseous precursors. NH3 is underestimated in the warmest months, HNO3 tends to be overestimated in the summer months, and SO2 appears to be systematically overestimated. The temporal treatment of ammonia emission is a probable source of uncertainty in the model representation of SIA. Furthermore, we discuss the annual pattern for each inorganic aerosol and gas precursor species over Europe estimated with the EMEP data and CALIOPE outputs, comparing the performance with other European studies. Spatial distribution of key indicators is used to characterize chemical regimes and understand the sensitivity of SIA components to their emission precursors. Results indicate that SO4 2− is not usually fully neutralized to ammonium sulfate in ambient measurements and is usually fully neutralized in model estimates. CALIOPE and EMEP observations agree that the continental regions in Europe tend to be HNO3-limited for nitrate formation. Regulatory strategies in such regions should focus on reductions in NO x (NO+NO2) rather than NH3 to control ammonium nitrate. This work assesses how well the CALIOPE system reproduces the spatial and temporal variability of SIAs and their gaseous precursors over Europe and complements the measurement findings. [Copyright &y& Elsevier]

Abstract: Air pollution in modern city is very important for people''s health and environment management. In order to improve air quality forecasting and air pollution simulation in China, this paper gives a method of analyzing and evaluating air pollutants ozone using the Community Multiscale Air Quality modeling system. The experiment results clearly show the time serious of ozone concentration at the given area and its spatial distribution at the given time. This method can be applied to other oxids of nitrogen pollutants, and help us to control air pollution in China. [Copyright &y& Elsevier]