scholarly journals Technical Note – AQMEII4 Activity 1: Evaluation of Wet and Dry Deposition Schemes as an Integral Part of Regional-Scale Air Quality Models

2021 ◽  
Author(s):  
Stefano Galmarini ◽  
Paul Makar ◽  
Olivia Clifton ◽  
Christian Hogrefe ◽  
Jesse Bash ◽  
...  

Abstract. We present in this technical note the research protocol for Phase 4 of the Air Quality Model Evaluation International Initiative (AQMEII4). This research initiative is divided in two activities, collectively having three goals: (i) to define the current state of the science with respect to representations of wet and especially dry deposition in regional models, (ii) to quantify the extent to which different dry deposition parameterizations influence retrospective air pollutant concentration and flux predictions, and (iii) to identify, through the use of a common set of detailed diagnostics, sensitivity simulations, model evaluation, and reducing input uncertainty, the specific causes for the current range of these predictions. Activity 1 is dedicated to the diagnostic evaluation of wet and dry deposition processes in regional air quality models (described in this paper), and Activity 2 to the evaluation of dry deposition point models against ozone flux measurements at multiple towers with multiyear observations (Part 2). The scope of these papers is to present the scientific protocols for AQMEII4, as well to summarize the technical information associated with the different dry deposition approaches used by the participating research groups of AQMEII4. In addition to describing all common aspects and data used for this multi-model evaluation activity, most importantly, we present the strategy devised to allow a common process-level comparison of dry deposition obtained from models using sometimes very different dry deposition schemes. The strategy is based on adding detailed diagnostics to the algorithms used in the dry deposition modules of existing regional air quality models, in particular archiving land use/land cover (LULC)-specific diagnostics and creating standardized LULC categories to facilitate cross-comparison of LULC-specific dry deposition parameters and processes, as well as archiving effective conductance and effective flux as means for comparing the relative influence of different pathways towards the net or total dry deposition. This new approach, along with an analysis of precipitation and wet deposition fields, will provide an unprecedented process-oriented comparison of deposition in regional air-quality models. Examples of how specific dry deposition schemes used in participating models have been reduced to the common set of comparable diagnostics defined for AQMEII4 are also presented.

2013 ◽  
Vol 6 (1) ◽  
pp. 521-584
Author(s):  
E. Solazzo ◽  
R. Bianconi ◽  
G. Pirovano ◽  
M. D. Moran ◽  
R. Vautard ◽  
...  

Abstract. The evaluation of regional air quality models is a challenging task, not only for the intrinsic complexity of the topic but also in view of the difficulties in finding sufficiently abundant, harmonized and time/space-well-distributed measurement data. This study, conducted in the framework of AQMEII (Air Quality Model Evaluation International Initiative), evaluates 4-D model predictions obtained from 15 modelling groups and relating to the air quality of the full year of 2006 over the North American and European continents. The modelled variables are ozone, CO, wind speed and direction, temperature, and relative humidity. Model evaluation is supported by the high quality in-flight measurements collected by instrumented commercial aircrafts in the context of the MOZAIC programme. The models are evaluated at five selected domains positioned around major airports, four in North America (Portland, Philadelphia, Atlanta, Dallas) and one in Europe (Frankfurt). Due to the extraordinary scale of the exercise (number of models and variables, spatial and temporal extent), this study is primarily aimed at illustrating the potential for using MOZAIC data for regional-scale evaluation and the capabilities of models to simulate concentration and meteorological fields in the vertical rather than just at the ground. We apply various approaches, metrics, and methods to analyze this complex dataset. Results of the investigation indicate that, while the observed meteorological fields are modelled with some success, modelling CO in and above the boundary layer remains a challenge and modelling ozone also has room for significant improvement. We note, however, that the high sensitivity of models to height, season, location, and metric makes the results rather difficult to interpret and to generalize. With this work, though, we set the stage for future process-oriented and in-depth diagnostic analyses.


2013 ◽  
Vol 13 (15) ◽  
pp. 7451-7471 ◽  
Author(s):  
A. Colette ◽  
B. Bessagnet ◽  
R. Vautard ◽  
S. Szopa ◽  
S. Rao ◽  
...  

Abstract. To quantify changes in air pollution over Europe at the 2050 horizon, we designed a comprehensive modelling system that captures the external factors considered to be most relevant, and that relies on up-to-date and consistent sets of air pollution and climate policy scenarios. Global and regional climate as well as global chemistry simulations are based on the recent representative concentration pathways (RCP) produced for the Fifth Assessment Report (AR5) of the IPCC (Intergovernmental Panel on Climate Change) whereas regional air quality modelling is based on the updated emissions scenarios produced in the framework of the Global Energy Assessment. We explored two diverse scenarios: a reference scenario where climate policies are absent and a mitigation scenario which limits global temperature rise to within 2 °C by the end of this century. This first assessment of projected air quality and climate at the regional scale based on CMIP5 (5th Coupled Model Intercomparison Project) climate simulations is in line with the existing literature using CMIP3. The discrepancy between air quality simulations obtained with a climate model or with meteorological reanalyses is pointed out. Sensitivity simulations show that the main factor driving future air quality projections is air pollutant emissions, rather than climate change or intercontinental transport of pollution. Whereas the well documented "climate penalty" that weights upon ozone (increase of ozone pollution with global warming) over Europe is confirmed, other features appear less robust compared to the literature, such as the impact of climate on PM2.5. The quantitative disentangling of external factors shows that, while several published studies focused on the climate penalty bearing upon ozone, the contribution of the global ozone burden is somewhat overlooked in the literature.


2013 ◽  
Vol 13 (3) ◽  
pp. 6455-6499 ◽  
Author(s):  
A. Colette ◽  
B. Bessagnet ◽  
R. Vautard ◽  
S. Szopa ◽  
S. Rao ◽  
...  

Abstract. To quantify changes in air pollution in Europe at the 2050 horizon, we designed a comprehensive modelling system that captures the external factors considered to be most relevant and relies on up-to-date and consistent sets of air pollution and climate policy scenarios. Global and regional climate as well as global chemistry simulations are based on the recent Representative Concentrations Pathways (RCP) produced for the Fifth Assessment Report (AR5) of IPCC whereas regional air quality modelling is based on the updated emissions scenarios produced in the framework of the Global Energy Assessment. We explored two diverse scenarios: a reference scenario where climate policies are absent and a mitigation scenario which limits global temperature rise to within 2 °C by the end of this century. This first assessment of projected air quality and climate at the regional scale based on CMIP5 (5th Climate Model Intercomparison Project) climate simulations is in line with the existing literature using CMIP3. The discrepancy between air quality simulations obtained with a climate model or with meteorological reanalyses is pointed out. Sensitivity simulations show that the main factor driving future air quality projections is air pollutant emissions, rather than climate change or long range transport. Whereas the well documented "climate penalty" bearing upon ozone over Europe is confirmed, other features appear less robust compared to the literature: such as the impact of climate on PM2.5. The quantitative disentangling of each contributing factor shows that the magnitude of the ozone climate penalty has been overstated in the past while on the contrary the contribution of the global ozone burden is overlooked in the literature.


2014 ◽  
Vol 7 (3) ◽  
pp. 1001-1024 ◽  
Author(s):  
P. A. Makar ◽  
R. Nissen ◽  
A. Teakles ◽  
J. Zhang ◽  
Q. Zheng ◽  
...  

Abstract. The balance between turbulent transport and emissions is a key issue in understanding the formation of O3 and particulate matter with diameters less than 2.5 μm (PM2.5). Discrepancies between observed and simulated concentrations for these species have, in the past, been ascribed to insufficient turbulent mixing, particularly for atmospherically stable environments. This assumption may be simplistic – turbulent mixing deficiencies may explain only part of these discrepancies, and as turbulence parameterizations are improved, the timing of primary PM2.5 emissions may play a much more significant role in the further reduction of model error. In a study of these issues, two regional air-quality models, the Community Multi-scale Air Quality model (CMAQ, version 4.6) and A Unified Regional Air-quality Modelling System (AURAMS, version 1.4.2), were compared to observations for a domain in north-western North America. The air-quality models made use of the same emissions inventory, emissions processing system, meteorological driving model, and model domain, map projection and horizontal grid, eliminating these factors as potential sources of discrepancies between model predictions. The initial statistical comparison between the models and monitoring network data showed that AURAMS' O3 simulations outperformed those of this version of CMAQ4.6, while CMAQ4.6 outperformed AURAMS for most PM2.5 statistical measures. A process analysis of the models revealed that many of the differences between the models' results could be attributed to the strength of turbulent diffusion, via the choice of an a priori lower limit in the magnitude of vertical diffusion coefficients, with AURAMS using 0.1 m2 s−1 and CMAQ4.6 using 1.0 m2 s−1. The use of the larger CMAQ4.6 value for the lower limit of vertical diffusivity within AURAMS resulted in a similar performance for the two models (with AURAMS also showing improved PM2.5, yet degraded O3, and a similar time series as CMAQ4.6). The differences between model results were most noticeable at night, when the higher minimum turbulent diffusivity resulted in an erroneous secondary peak in predicted night-time O3. A spatially invariant and relatively high lower limit in diffusivity could not reduce errors in both O3 and PM2.5 fields, implying that other factors aside from the strength of turbulence might be responsible for the PM2.5 over-predictions. Further investigation showed that the magnitude, timing and spatial allocation of area source emissions could result in improvements to PM2.5 performance with minimal O3 performance degradation. AURAMS was then used to investigate a land-use-dependant lower limit in diffusivity of 1.0 m2 s−1 in urban regions, linearly scaling to 0.01 m2s−1 in rural areas, as employed in CMAQ5.0.1. This strategy was found to significantly improve mean statistics for PM2.5 throughout the day and mean O3 statistics at night, while significantly degrading (halving) midday PM2.5 correlation coefficients and slope of observed to model simulations. Time series of domain-wide model error statistics aggregated by local hour were shown to be a useful tool for performance analysis, with significant variations in performance occurring at different hours of the day. The use of the land-use-dependant lower limit in diffusivity was also shown to reduce the model's sensitivity to the temporal allocation of its emissions inputs. The modelling scenarios suggest that while turbulence plays a key role in O3 and PM2.5 formation in urban regions, and in their downwind transport, the spatial and temporal allocation of primary PM2.5 emissions also has a potentially significant impact on PM2.5 concentration levels. The results show the complex nature of the interactions between turbulence and emissions, and the potential of the strength of the former to mask the impact of changes in the latter.


Author(s):  
Alice B. Gilliland ◽  
James M. Godowitch ◽  
Christian Hogrefe ◽  
S. T. Rao

Author(s):  
Günther Mauersberger ◽  
A. I. Flossmann ◽  
H. R. Pruppacher ◽  
William R. Stockwell ◽  
Thomas Schönemeyer ◽  
...  

2017 ◽  
Vol 10 (9) ◽  
pp. 3255-3276 ◽  
Author(s):  
Augustin Colette ◽  
Camilla Andersson ◽  
Astrid Manders ◽  
Kathleen Mar ◽  
Mihaela Mircea ◽  
...  

Abstract. The EURODELTA-Trends multi-model chemistry-transport experiment has been designed to facilitate a better understanding of the evolution of air pollution and its drivers for the period 1990–2010 in Europe. The main objective of the experiment is to assess the efficiency of air pollutant emissions mitigation measures in improving regional-scale air quality. The present paper formulates the main scientific questions and policy issues being addressed by the EURODELTA-Trends modelling experiment with an emphasis on how the design and technical features of the modelling experiment answer these questions. The experiment is designed in three tiers, with increasing degrees of computational demand in order to facilitate the participation of as many modelling teams as possible. The basic experiment consists of simulations for the years 1990, 2000, and 2010. Sensitivity analysis for the same three years using various combinations of (i) anthropogenic emissions, (ii) chemical boundary conditions, and (iii) meteorology complements it. The most demanding tier consists of two complete time series from 1990 to 2010, simulated using either time-varying emissions for corresponding years or constant emissions. Eight chemistry-transport models have contributed with calculation results to at least one experiment tier, and five models have – to date – completed the full set of simulations (and 21-year trend calculations have been performed by four models). The modelling results are publicly available for further use by the scientific community. The main expected outcomes are (i) an evaluation of the models' performances for the three reference years, (ii) an evaluation of the skill of the models in capturing observed air pollution trends for the 1990–2010 time period, (iii) attribution analyses of the respective role of driving factors (e.g. emissions, boundary conditions, meteorology), (iv) a dataset based on a multi-model approach, to provide more robust model results for use in impact studies related to human health, ecosystem, and radiative forcing.


Author(s):  
Daiwen Kang ◽  
Brian K. Eder ◽  
Kenneth L. Schere

2020 ◽  
Vol 20 (11) ◽  
pp. 6395-6415
Author(s):  
Goran Gašparac ◽  
Amela Jeričević ◽  
Prashant Kumar ◽  
Branko Grisogono

Abstract. The application of regional-scale air quality models is an important tool in air quality assessment and management. For this reason, the understanding of model abilities and performances is mandatory. The main objective of this research was to investigate the spatial and temporal variability of background particulate matter (PM) concentrations, to evaluate the regional air quality modelling performance in simulating PM concentrations during statically stable conditions and to investigate processes that contribute to regionally increased PM concentrations with a focus on eastern and central Europe. The temporal and spatial variability of observed PM was analysed at 310 rural background stations in Europe during 2011. Two different regional air quality modelling systems (offline coupled European Monitoring and Evaluation Programme, EMEP, and online coupled Weather Research and Forecasting with Chemistry) were applied to simulate the transport of pollutants and to further investigate the processes that contributed to increased concentrations during high-pollution episodes. Background PM measurements from rural background stations, wind speed, surface pressure and ambient temperature data from 920 meteorological stations across Europe, classified according to the elevation, were used for the evaluation of individual model performance. Among the sea-level stations (up to 200 m), the best modelling performance, in terms of meteorology and chemistry, was found for both models. The underestimated modelled PM concentrations in some cases indicated the importance of the accurate assessment of regional air pollution transport under statically stable atmospheric conditions and the necessity of further model improvements.


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