Academic literature on the topic 'CMAQ model'
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Journal articles on the topic "CMAQ model"
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Efstathiou, Christos I., Elizabeth Adams, Carlie J. Coats, et al. "Enabling high-performance cloud computing for the Community Multiscale Air Quality Model (CMAQ) version 5.3.3: performance evaluation and benefits for the user community." Geoscientific Model Development 17, no. 18 (2024): 7001–27. http://dx.doi.org/10.5194/gmd-17-7001-2024.
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Abstract. The Community Multiscale Air Quality Model (CMAQ) is a local- to hemispheric-scale numerical air quality modeling system developed by the U.S. Environmental Protection Agency (USEPA) and supported by the Community Modeling and Analysis System (CMAS) center. CMAQ is used for regulatory purposes by the USEPA program offices and state and local air agencies and is also widely used by the broader global research community to simulate and understand complex air quality processes and for computational environmental fate and transport and climate and health impact studies. Leveraging state-of-the-science cloud computing resources for high-performance computing (HPC) applications, CMAQ is now available as a fully tested, publicly available technology stack (HPC cluster and software stack) for two major cloud service providers (CSPs). Specifically, CMAQ configurations and supporting materials have been developed for use on their HPC clusters, including extensive online documentation, tutorials and guidelines to scale and optimize air quality simulations using their services. These resources allow modelers to rapidly bring together CMAQ, cloud-hosted datasets, and visualization and evaluation tools on ephemeral clusters that can be deployed quickly and reliably worldwide. Described here are considerations in CMAQ version 5.3.3 cloud use and the supported resources for each CSP, presented through a benchmark application suite that was developed as an example of a typical simulation for testing and verifying components of the modeling system. The outcomes of this effort are to provide findings from performing CMAQ simulations on the cloud using popular vendor-provided resources, to enable the user community to adapt this for their own needs, and to identify specific areas of potential optimization with respect to storage and compute architectures.
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Appel, K. W., S. J. Roselle, R. C. Gilliam, and J. E. Pleim. "Sensitivity of the Community Multiscale Air Quality (CMAQ) model v4.7 results for the eastern United States to MM5 and WRF meteorological drivers." Geoscientific Model Development 3, no. 1 (2010): 169–88. http://dx.doi.org/10.5194/gmd-3-169-2010.
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Abstract. This paper presents a comparison of the operational performances of two Community Multiscale Air Quality (CMAQ) model v4.7 simulations that utilize input data from the 5th-generation Mesoscale Model (MM5) and the Weather Research and Forecasting (WRF) meteorological models. Two sets of CMAQ model simulations were performed for January and August 2006. One set utilized MM5 meteorology (MM5-CMAQ) and the other utilized WRF meteorology (WRF-CMAQ), while all other model inputs and options were kept the same. For January, predicted ozone (O3) mixing ratios were higher in the Southeast and lower Mid-west regions in the WRF-CMAQ simulation, resulting in slightly higher bias and error as compared to the MM5-CMAQ simulations. The higher predicted O3 mixing ratios are attributed to less dry deposition of O3 in the WRF-CMAQ simulation due to differences in the calculation of the vegetation fraction between the MM5 and WRF models. The WRF-CMAQ results showed better performance for particulate sulfate (SO42−), similar performance for nitrate (NO3−), and slightly worse performance for nitric acid (HNO3), total carbon (TC) and total fine particulate (PM2.5) mass than the corresponding MM5-CMAQ results. For August, predictions of O3 were notably higher in the WRF-CMAQ simulation, particularly in the southern United States, resulting in increased model bias. Concentrations of predicted particulate SO42− were lower in the region surrounding the Ohio Valley and higher along the Gulf of Mexico in the WRF-CMAQ simulation, contributing to poorer model performance. The primary causes of the differences in the MM5-CMAQ and WRF-CMAQ simulations appear to be due to differences in the calculation of wind speed, planetary boundary layer height, cloud cover and the friction velocity (u∗) in the MM5 and WRF model simulations, while differences in the calculation of vegetation fraction and several other parameters result in smaller differences in the predicted CMAQ model concentrations. The performance for SO42−, NO3− and NH4+ wet deposition was similar for both simulations for January and August.
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Itahashi, Syuichi, Kazuyo Yamaji, Satoru Chatani, Kunihiro Hisatsune, Shinji Saito, and Hiroshi Hayami. "Model Performance Differences in Sulfate Aerosol in Winter over Japan Based on Regional Chemical Transport Models of CMAQ and CAMx." Atmosphere 9, no. 12 (2018): 488. http://dx.doi.org/10.3390/atmos9120488.
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Sulfate aerosol (SO42−) is a major component of particulate matter in Japan. The Japanese model intercomparison study, J-STREAM, found that although SO42− is well captured by models, it is underestimated during winter. In the first phase of J-STREAM, we refined the Fe- and Mn-catalyzed oxidation and partly improved the underestimation. The winter haze in December 2016 was a target period in the second phase. The results from the Community Multiscale Air Quality (CMAQ) and Comprehensive Air quality Model with eXtentions (CAMx) regional chemical transport models were compared with observations from the network over Japan and intensive observations at Nagoya and Tokyo. Statistical analysis showed both models satisfied the suggested model performance criteria. CMAQ sensitivity simulations explained the improvements in model performance. CMAQ modeled lower SO42− concentrations than CAMx, despite increased aqueous oxidation via the metal catalysis pathway and NO2 reaction in CMAQ. Deposition explained this difference. A scatter plot demonstrated that the lower SO42− concentration in CMAQ than in CAMx arose from the lower SO2 concentration and higher SO42− wet deposition in CMAQ. The dry deposition velocity caused the difference in SO2 concentration. These results suggest the importance of deposition in improving our understanding of ambient concentration behavior.
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Wong, David C., Jeff Willison, Jonathan E. Pleim, et al. "Development of the MPAS-CMAQ coupled system (V1.0) for multiscale global air quality modeling." Geoscientific Model Development 17, no. 21 (2024): 7855–66. http://dx.doi.org/10.5194/gmd-17-7855-2024.
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Abstract. The Community Multiscale Air Quality (CMAQ) model has been used for regulatory purposes at the U.S. EPA and in the research community for decades. In 2012, we released the Weather Research and Forecasting (WRF)-CMAQ coupled model that enables aerosol information from CMAQ to affect meteorological processes through direct effects on shortwave radiation. Both CMAQ and WRF-CMAQ are considered limited-area models. Recently, we have extended domain coverage to the global scale by linking the meteorological Model for Prediction Across Scales – Atmosphere (MPAS-A, hereafter referred simply to as MPAS) with CMAQ to form the MPAS-CMAQ global coupled model. To configure these three different models, i.e., CMAQ (offline), WRF-CMAQ, and MPAS-CMAQ, we have developed the Advanced Air Quality Modeling System (AAQMS) for constructing each of them effortlessly. We evaluate this newly built MPAS-CMAQ coupled model using two global configurations: a 120 km uniform mesh and a 92–25 km variable mesh with the finer area over North America. Preliminary computational tests show good scalability and model evaluation, when using a 3-year simulation (2014–2016) for the uniform mesh case and a monthly simulation of January and July 2016 for the variable mesh case, on ozone and PM2.5 and show reasonable performance with respect to observations. The 92–25 km configuration has a high bias in wintertime surface ozone across the United States, and this bias is consistent with the 120 km result. Summertime surface ozone in the 92–25 km configuration is less biased than the 120 km case. The MPAS-CMAQ system reasonably reproduces the daily variability of daily average PM from the Air Quality System (AQS) network.
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Appel, K. W., S. J. Roselle, R. C. Gilliam, and J. E. Pleim. "Sensitivity of the Community Multiscale Air Quality (CMAQ) Model v4.7 results for the eastern United States to MM5 and WRF meteorological drivers." Geoscientific Model Development Discussions 2, no. 2 (2009): 1081–114. http://dx.doi.org/10.5194/gmdd-2-1081-2009.
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Abstract. This paper presents a comparison of the operational performances of two Community Multiscale Air Quality (CMAQ) model v4.7 simulations that utilize input data from the 5th-generation Mesoscale Model (MM5) and the Weather Research and Forecasting (WRF) meteorological models. Two sets of CMAQ model simulations were performed for January and August 2006. One set utilized MM5 meteorology (MM5-CMAQ) and the other utilized WRF meteorology (WRF-CMAQ), while all other model inputs and options were kept the same. For January, predicted ozone (O3) concentrations were higher in the Southeast and lower Mid-west regions in the WRF-CMAQ simulation, resulting in slightly higher bias and error as compared to the MM5-CMAQ simulations. The higher predicted O3 concentrations are attributed to less dry deposition of O3 in the WRF-CMAQ simulation due to differences in the calculation of the vegetation fraction between the MM5 and WRF models. The WRF-CMAQ results showed better performance for particulate sulfate (SO42−), similar performance for nitrate (NO3−) and total nitrate (TNO3), and slightly worse performance for total carbon (TC) and total fine particulate (PM2.5) mass than the corresponding MM5-CMAQ results. For August, predictions of O3 were notably higher in the WRF-CMAQ simulation, particularly in the southern United States, resulting in increased model bias. Concentrations of predicted particulate SO42− were lower in the region surrounding the Ohio Valley and higher along the Gulf of Mexico in the WRF-CMAQ simulation, contributing to poorer model performance. The primary cause of the differences in predicted concentrations between the MM5-CMAQ and WRF-CMAQ simulations is due to differences in the calculation of the friction velocity (u*) in MM5 and WRF models, which has a large effect on the dry deposition of NO, NO2 and HNO3. Differences in the calculation of the vegetation fraction and the predicted cloud cover, along with several other minor differences in the simulations also affect the predicted concentrations from CMAQ. The performance for SO42−, NO3− and NH4+ wet deposition was similar for both simulations for January and August.
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Bash, J. O., E. J. Cooter, R. L. Dennis, J. T. Walker, and J. E. Pleim. "Evaluation of a regional air-quality model with bidirectional NH<sub>3</sub> exchange coupled to an agroecosystem model." Biogeosciences 10, no. 3 (2013): 1635–45. http://dx.doi.org/10.5194/bg-10-1635-2013.
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Abstract. Atmospheric ammonia (NH3) is the primary atmospheric base and an important precursor for inorganic particulate matter and when deposited NH3 contributes to surface water eutrophication, soil acidification and decline in species biodiversity. Flux measurements indicate that the air–surface exchange of NH3 is bidirectional. However, the effects of bidirectional exchange, soil biogeochemistry and human activity are not parameterized in air quality models. The US Environmental Protection Agency's (EPA) Community Multiscale Air-Quality (CMAQ) model with bidirectional NH3 exchange has been coupled with the United States Department of Agriculture's (USDA) Environmental Policy Integrated Climate (EPIC) agroecosystem model. The coupled CMAQ-EPIC model relies on EPIC fertilization timing, rate and composition while CMAQ models the soil ammonium (NH4&amp;plus;) pool by conserving the ammonium mass due to fertilization, evasion, deposition, and nitrification processes. This mechanistically coupled modeling system reduced the biases and error in NHx (NH3 &amp;plus; NH4&amp;plus;) wet deposition and in ambient aerosol concentrations in an annual 2002 Continental US (CONUS) domain simulation when compared to a 2002 annual simulation of CMAQ without bidirectional exchange. Fertilizer emissions estimated in CMAQ 5.0 with bidirectional exchange exhibits markedly different seasonal dynamics than the US EPA's National Emissions Inventory (NEI), with lower emissions in the spring and fall and higher emissions in July.
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Liu, Jiachen, Eric Chen, and Shannon L. Capps. "The first application of a numerically exact, higher-order sensitivity analysis approach for atmospheric modelling: implementation of the hyperdual-step method in the Community Multiscale Air Quality Model (CMAQ) version 5.3.2." Geoscientific Model Development 17, no. 2 (2024): 567–85. http://dx.doi.org/10.5194/gmd-17-567-2024.
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Abstract. Sensitivity analysis in chemical transport models quantifies the response of output variables to changes in input parameters. This information is valuable for researchers engaged in data assimilation and model development. Additionally, environmental decision-makers depend upon these expected responses of concentrations to emissions when designing and justifying air pollution control strategies. Existing sensitivity analysis methods include the finite-difference method, the direct decoupled method (DDM), the complex variable method, and the adjoint method. These methods are either prone to significant numerical errors when applied to nonlinear models with complex components (e.g. finite difference and complex step methods) or difficult to maintain when the original model is updated (e.g. direct decoupled and adjoint methods). Here, we present the implementation of the hyperdual-step method in the Community Multiscale Air Quality Model (CMAQ) version 5.3.2 as CMAQ-hyd. CMAQ-hyd can be applied to compute numerically exact first- and second-order sensitivities of species concentrations with respect to emissions or concentrations. Compared to CMAQ-DDM and CMAQ-adjoint, CMAQ-hyd is more straightforward to update and maintain, while it remains free of subtractive cancellation and truncation errors, just as those augmented models do. To evaluate the accuracy of the implementation, the sensitivities computed by CMAQ-hyd are compared with those calculated with other traditional methods or a hybrid of the traditional and advanced methods. We demonstrate the capability of CMAQ-hyd with the newly implemented gas-phase chemistry and biogenic aerosol formation mechanism in CMAQ. We also explore the cross-sensitivity of monoterpene nitrate aerosol formation to its anthropogenic and biogenic precursors to show the additional sensitivity information computed by CMAQ-hyd. Compared with the traditional finite difference method, CMAQ-hyd consumes fewer computational resources when the same sensitivity coefficients are calculated. This novel method implemented in CMAQ is also computationally competitive with other existing methods and could be further optimized to reduce memory and computational time overheads.
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Hogrefe, Christian, Peng Liu, George Pouliot, et al. "Impacts of different characterizations of large-scale background on simulated regional-scale ozone over the continental United States." Atmospheric Chemistry and Physics 18, no. 5 (2018): 3839–64. http://dx.doi.org/10.5194/acp-18-3839-2018.
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Abstract. This study analyzes simulated regional-scale ozone burdens both near the surface and aloft, estimates process contributions to these burdens, and calculates the sensitivity of the simulated regional-scale ozone burden to several key model inputs with a particular emphasis on boundary conditions derived from hemispheric or global-scale models. The Community Multiscale Air Quality (CMAQ) model simulations supporting this analysis were performed over the continental US for the year 2010 within the context of the Air Quality Model Evaluation International Initiative (AQMEII) and Task Force on Hemispheric Transport of Air Pollution (TF-HTAP) activities. CMAQ process analysis (PA) results highlight the dominant role of horizontal and vertical advection on the ozone burden in the mid-to-upper troposphere and lower stratosphere. Vertical mixing, including mixing by convective clouds, couples fluctuations in free-tropospheric ozone to ozone in lower layers. Hypothetical bounding scenarios were performed to quantify the effects of emissions, boundary conditions, and ozone dry deposition on the simulated ozone burden. Analysis of these simulations confirms that the characterization of ozone outside the regional-scale modeling domain can have a profound impact on simulated regional-scale ozone. This was further investigated by using data from four hemispheric or global modeling systems (Chemistry – Integrated Forecasting Model (C-IFS), CMAQ extended for hemispheric applications (H-CMAQ), the Goddard Earth Observing System model coupled to chemistry (GEOS-Chem), and AM3) to derive alternate boundary conditions for the regional-scale CMAQ simulations. The regional-scale CMAQ simulations using these four different boundary conditions showed that the largest ozone abundance in the upper layers was simulated when using boundary conditions from GEOS-Chem, followed by the simulations using C-IFS, AM3, and H-CMAQ boundary conditions, consistent with the analysis of the ozone fields from the global models along the CMAQ boundaries. Using boundary conditions from AM3 yielded higher springtime ozone columns burdens in the middle and lower troposphere compared to boundary conditions from the other models. For surface ozone, the differences between the AM3-driven CMAQ simulations and the CMAQ simulations driven by other large-scale models are especially pronounced during spring and winter where they can reach more than 10 ppb for seasonal mean ozone mixing ratios and as much as 15 ppb for domain-averaged daily maximum 8 h average ozone on individual days. In contrast, the differences between the C-IFS-, GEOS-Chem-, and H-CMAQ-driven regional-scale CMAQ simulations are typically smaller. Comparing simulated surface ozone mixing ratios to observations and computing seasonal and regional model performance statistics revealed that boundary conditions can have a substantial impact on model performance. Further analysis showed that boundary conditions can affect model performance across the entire range of the observed distribution, although the impacts tend to be lower during summer and for the very highest observed percentiles. The results are discussed in the context of future model development and analysis opportunities.
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Wilkins, Joseph L., George Pouliot, Kristen Foley, Wyat Appel, and Thomas Pierce. "The impact of US wildland fires on ozone and particulate matter: a comparison of measurements and CMAQ model predictions from 2008 to 2012." International Journal of Wildland Fire 27, no. 10 (2018): 684. http://dx.doi.org/10.1071/wf18053.
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Wildland fire emissions are routinely estimated in the US Environmental Protection Agency’s National Emissions Inventory, specifically for fine particulate matter (PM2.5) and precursors to ozone (O3); however, there is a large amount of uncertainty in this sector. We employ a brute-force zero-out sensitivity method to estimate the impact of wildland fire emissions on air quality across the contiguous US using the Community Multiscale Air Quality (CMAQ) modelling system. These simulations are designed to assess the importance of wildland fire emissions on CMAQ model performance and are not intended for regulatory assessments. CMAQ ver. 5.0.1 estimated that fires contributed 11% to the mean PM2.5 and less than 1% to the mean O3 concentrations during 2008–2012. Adding fires to CMAQ increases the number of ‘grid-cell days’ with PM2.5 above 35 µg m−3 by a factor of 4 and the number of grid-cell days with maximum daily 8-h average O3 above 70 ppb by 14%. Although CMAQ simulations of specific fires have improved with the latest model version (e.g. for the 2008 California wildfire episode, the correlation r = 0.82 with CMAQ ver. 5.0.1 v. r = 0.68 for CMAQ ver. 4.7.1), the model still exhibits a low bias at higher observed concentrations and a high bias at lower observed concentrations. Given the large impact of wildland fire emissions on simulated concentrations of elevated PM2.5 and O3, improvements are recommended on how these emissions are characterised and distributed vertically in the model.
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Sukprasert, Supitcha, Hikari Shimadera, Shin Araki, et al. "Improving Machine Learning Based PM2.5 Prediction by Segregating Biomass Emission Factor from Chemical Transport Model." E3S Web of Conferences 530 (2024): 01004. http://dx.doi.org/10.1051/e3sconf/202453001004.
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Located in the heart of Mainland Southeast Asia, Thailand is associated with high biomass burning (BB) activities from local and neighbouring countries. The seasonal pattern of BB manifests itself as a potential predictor for PM2.5 concentration. Consequently, we enhanced machine learning based PM2.5 prediction by segregating BB factor from the Community Multiscale Air Quality (CMAQ). Two Light Gradient Boosting Machine (LightGBM) models with different CMAQ predictors were developed: the BB-integrated model, which incorporated CMAQ-simulated PM2.5 from all emission sources and the BB-segregated model, which incorporated CMAQ-simulated PM2.5 from sources other than BB (CMAQ_PM25_Othr) and CMAQ-simulated PM2.5 from BB emissions (CMAQ_PM25_BB). The two models had shared control predictors, which included simulated meteorological variables from WRF model, population, elevation, and land-use variables, and they were evaluated using a crossvalidation (CV). The BB-segregated model outperformed the BB-integrated model, achieving overall-CV R2 values of 0.86 and 0.82, respectively. The analysis of feature importance for the BB-segregated model indicates that CMAQ_PM25_Othr and CMAQ_PM25_BB are the two most significant predictors. These findings emphasize the importance of considering BB emissions when predicting PM2.5 concentrations, particularly in regions with high BB activities.
Dissertations / Theses on the topic "CMAQ model"
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Pederzoli, Anna. "The application of an Eulerian chemical and transport model (CMAQ) at fine scale resolution to the UK." Thesis, University of Edinburgh, 2008. http://hdl.handle.net/1842/3127.
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Present-day numerical air quality models are considered essential tools for predicting future air pollutant concentrations and depositions, contributing to the development of new effective strategies for the control and the reduction of pollutant emissions. They simulate concentrations and depositions of pollutants on a wide range of scales (global, national, urban scale) and they are used for identifying critical areas, integrating measurements and achieving a deeper scientific understanding of the physical and chemical processes involving air pollutants in the atmosphere. The use of comprehensive air quality models started in the late 1970s and since then their development has increased rapidly, hand in hand with the rapid increase in computational resources. Today more and more complex and computationally expensive numerical models are available to the scientific community. One of these tools is the Community Multi-Scale Air Quality System (CMAQ), developed in the 1990s by the US Environmental Protection Agency (EPA) and currently widely applied across the world for air pollution studies. This work focuses on the application of CMAQ to the United Kingdom, for estimating concentrations and depositions of acidifying pollutants (NOX, NHX, SOX) on a national scale. The work is divided into seven chapters, the first one describing the main issues related to the emission and dispersion in the atmosphere of acidifying species. It also includes a brief overview of the main international policies signed in the last thirty years in order to reduce the problem of acidification in Europe, as well as a brief description of some models mentioned in this thesis. The second one describes the main features of CMAQ and addresses some issues such as the use of a nesting process for achieving temporally and spatially resolved boundary concentrations, and the implementation of the model on parallel machines, essential for reducing the simulation computing time. It also describes how this study is part of a wider context, which includes the application of CMAQ in the United Kingdom by other users with different scientific purposes (aerosols processes, air quality in the urban area of London, contribution of UK power stations to concentrations and depositions etc.). The third part of the thesis focuses on the application and evaluation over the United Kingdom of the 5th Generation Mesoscale Model MM5, used for providing 3D meteorological input fields to CMAQ. This study was performed assuming that an accurate representation of depositions and concentrations of chemical species cannot be achieved without a good estimate of the meteorological parameters involved in most of the atmospheric processes (transport, photochemistry, aerosol processes, cloud processes etc.). The fourth part of the thesis describes the preliminary implementation of the Sparse Matrix Operational Kernel Emission System (SMOKE) in the United Kingdom. The processor provides input emissions to CMAQ. The use of SMOKE is usually avoided in CMAQ applications of outside America, and CMAQ input emission files are prepared by the application of other software. The reason is that the model requires radical changes for being applied outside Northern and Central America. Some of these changes have been made in this study such as the adaptation of the European emission inventory EMEP and the UK National Inventory NAEI to the modelling system for point and area sources, the introduction of new European emission temporal profiles in substitution of the American ones and the introduction of new geographical references for the spatial allocation of emissions. In the fifth chapter the results of CMAQ application over the UK are discussed. The study focuses on NOX, SO2, NH3 and + 4 NH . Maps of concentration are presented and modelled data are compared to measurements from two different air quality networks in the UK. An analysis of the performance of CMAQ over the UK is also performed. In the final chapter an annual inter-comparison between CMAQ and the Lagrangian transport model FRAME is carried out. Maps of annual wet deposition fluxes of NHX, NOY and SOX for year 1999 are presented. The results of both models are compared to one another and they are also compared to values from the UK official data set CBED. Finally, the last chapter suggests the work that has to be done in the future with CMAQ and it summarizes the conclusions.
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Johansson, Sara. "Coupling of the Weather Research and Forecasting model (WRF) with the Community Multiscale Air Qualitymodel (CMAQ), and analysing the forecasted ozone and nitrogendioxide concentrations." Thesis, Uppsala universitet, Luft-, vatten och landskapslära, 2007. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-303924.
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Air quality forecasts are of great value since several pollutants in our environment effect both human health, global climate, vegetation, crop yields, animals, materials and acidification of forests and lakes. Air-quality forecasts help to make people aware of the presence and the quantity of pollutants, and give them a chance to protect themselves, their business and the Earth. Many different air-quality models are in daily use all over the world, providing citizens with forecasts of air quality and warnings of unhealthy air quality if recommended highest concentrations are exceeded. This study adapts the WRF meteorological model (Weather research and Forecasting model) to be a driver of the CMAQ air-quality model (models-3 Community Multiscale Air Quality model). Forecasts of ozone and nitrogen dioxide concentrations from this coupled WRF/CMAQ modelling system are tested against observed data during a four-day period in May, 2006. The Lower Fraser Valley study area is a fertile valley surrounded by mountain chains in southwest British Columbia, Canada. The valley stretches from the Pacific coast eastwards towards the Rocky Mountains. This valley hosts more than 2 million people and it is west Canada’s fastest growing region. The Lower Fraser Valley holds a big city, Vancouver, several suburbs, numerous industries and a widespread agricultural production. During the analysed four-day period in May, a synoptic high-pressure built over the region, favoring high concentrations of pollutants as ozone and nitrogen dioxide. The created WRF/CMAQ model forecasted an acceptable magnitude of nitrogen dioxide but the daily variations are not recreated properly by the model. The WRF/CMAQ model forecasts the daily variation of ozone in a satisfying way, but the forecasted concentrations are overestimated by between 20 and 30 ppb throughout the study. Factors that could contribute to the elevated ozone concentrations were investigated, and it was found that the weather forecasting model WRF was not generating fully reliable meteorological values, which in turn hurt the air-quality forecasts. As the WRF model usually is a good weather forecasting model, the short spin-up time for the model could be a probable cause for its poor performance.<br>Prognoser över luftkvaliteten är mycket värdefulla, då flera luftföroreningar i vår närmiljö påverkar människans hälsa, det globala klimatet, vegetation, djur, material och bidrar till försurning av skog och vattendrag. Luftkvalitetsprognoser gör människan mer medveten om närvaron av luftföroreningar och i vilken mängd de finns. De ger människan en chans att vidta skyddsåtgärder för att skydda sig själv, sitt eventuella levebröd, och Jorden. Många olika luftkvalitetsmodeller används idag dagligdags över hela världen och förser invånare med prognoser för luftkvaliteten och varningar om koncentrationerna av föroreningar överstiger rekommenderade värden. I denna studie används väderprognosmodellen WRF (Weather Research and Forecasting model) för att driva luftkvalitetsmodellen CMAQ (models-3 Community Multiscale Air Quality model). Prognoser av ozon- och kvävedioxidhalterna i luften från den kopplade WRF/CMAQ modellen analyseras mot observerade data under en fyra dagars period i maj, 2006. Studieområdet Lower Fraser Valley är en bördig dalgång som är omgiven av bergskedjor i sydvästra British Columbia, Kanada. Dalen sträcker sig från Stilla havskusten och österut mot Klippiga bergen. I denna dalgång bor mer än 2 miljoner människor och det är västra Kanadas snabbast växande region. Lower Fraser Valley rymmer en storstad, Vancouver, flera förorter, många industrier och även stora jordbruksområden. Den fyra dagars period i maj som analyseras karaktäriseras av ett högtrycksbetonat synoptiskt väderläge med lokala variationer, vilka tillsammans är gynnsamma för att uppmäta höga koncentrationer av luftföroreningar som ozon och kvävedioxid. Den skapade WRF/CMAQ modellen prognostiserar godtagbar magnitud hos kvävedioxid men den dagliga variationen återskapas inte av modellen. Modellen prognostiserar den dagliga variationen av ozonkoncentration på ett tillfredsställande sätt, men storleksmässigt ligger koncentrationerna en faktor 20-30 ppb för högt rakt av under hela studien. Kringliggande faktorer som kan påverka koncentrationen ozon studeras närmare och det framkommer att den meteorologiska prognosmodellen WRF inte genererar fullt tillförlitliga värden för en rättvisande luftkvalitetsprognos. Då WRF modellen vanligtvis är en bra prognosmodell kan den korta initialiseringstiden för modellen vara en trolig orsak till dess otillräckliga prestation.
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Kaynak, Burcak. "Assimilation of trace gas retrievals obtained from satellite (SCIAMACHY), aircraft and ground observations into a regional scale air quality model (CMAQ-DDM/3D)." Diss., Georgia Institute of Technology, 2009. http://hdl.handle.net/1853/37134.
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A major opportunity for using satellite observations of tropospheric chemical concentrations is to improve our scientific understanding of atmospheric processes by integrated analysis of satellite, aircraft, and ground-based observations with global and regional scale models. One endpoint of such efforts is to reduce modeling biases and uncertainties. The idea of coupling these observations with a regional scale air quality model was the starting point of this research. The overall objective of this research was to improve the NOₓ emission inventories by integrating observations from different platforms and regional air quality modeling. Specific objectives were: 1) Comparison of satellite NO₂ retrievals with simulated NO₂ by the regional air quality model. Comparison of simulated tropospheric gas concentrations simulated by the regional air quality model, with aircraft and ground-based observations; 3) Assessment of the uncertainties in comparing satellite NO₂ retrievals with NOₓ emissions estimates and model simulations; 4) Identification of biases in emission inventories by data assimilation of satellite NO₂ retrievals, and ground-based NO, NO₂ and O₃ observations with an iterative inverse method using the regional air quality model coupled with sensitivity calculations; 5) Improvement of our understanding of NOₓ emissions, and the interaction between regional and global air pollution by an integrated analysis of satellite NO₂ retrievals with the regional air quality model. Along with these objectives, a lightning NOₓ emission inventory was prepared for two months of summer 2004 to account for a significant upper level NOₓ source. Spatially-resolved weekly NO₂ variations from satellite retrievals were compared with estimated NOₓ emissions for different region types. Data assimilation of satellite NO₂ retrievals, and ground-based NO, NO₂ and O₃ observations were performed to evaluate the NOₓ emission inventory. This research contributes to a better understanding of the use of satellite NO₂ retrievals in air quality modeling, and improvements in the NOₓ emission inventories by correcting some of the inconsistencies that were found in the inventories. Therefore, it may provide groups that develop emissions estimates guidance on areas for improvement. In addition, this research indicates the weaknesses and the strengths of the satellite NO₂ retrievals and offers suggestions to improve the quality of the retrievals for further use in the tropospheric air pollution research.
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Gou, Tianyi. "Computational Tools for Chemical Data Assimilation with CMAQ." Thesis, Virginia Tech, 2010. http://hdl.handle.net/10919/31017.
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The Community Multiscale Air Quality (CMAQ) system is the Environmental Protection Agency's main modeling tool for atmospheric pollution studies. CMAQ-ADJ, the adjoint model of CMAQ, offers new analysis capabilities such as receptor-oriented sensitivity analysis and chemical data assimilation.
This thesis presents the construction, validation, and properties of new adjoint modules in CMAQ, and illustrates their use
in sensitivity analyses and data assimilation experiments. The new module of discrete adjoint of advection is implemented with the aid of automatic differentiation tool (TAMC) and is fully validated by comparing the adjoint sensitivities with finite difference values.
In addition, adjoint sensitivity with respect to boundary conditions and boundary condition scaling factors are developed and validated in CMAQ.
To investigate numerically the impact of the continuous and discrete advection adjoints on data assimilation, various four dimensional variational (4D-Var) data assimilation experiments are carried out with the 1D advection PDE, and with CMAQ advection using synthetic and real observation data. The results show that optimization procedure gives better estimates of the reference initial condition and converges faster when using gradients computed by the continuous adjoint approach. This counter-intuitive result is explained using the nonlinearity properties of the piecewise parabolic method (the numerical discretization of advection in CMAQ).
Data assimilation experiments are carried out using real observation data. The simulation domain encompasses Texas and the simulation period
is August 30 to September 1, 2006. Data assimilation is used to improve both initial and boundary conditions. These experiments further
validate the tools developed in this thesis.<br>Master of Science
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Soldon, Brian T. "The International Space Station comparative maintenance analysis model (CMAM)." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2004. http://library.nps.navy.mil/uhtbin/hyperion/04Sep%5FSoldon.pdf.
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Croteau, Pierre Charles. "An assessment of the Canadian Middle Atmosphere Model (CMAM) using satellite observations." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1998. http://www.collectionscanada.ca/obj/s4/f2/dsk2/tape15/PQDD_0032/MQ27341.pdf.
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PEDRUZZI, R. "AVALIAÇÃO DE DESEMPENHO DO MODELO FOTOQUÍMICO CMAQ UTILIZANDO DIFERENTES CONDIÇÕES DE CONTORNO EM UMA REGIÃO URBANA E INDUSTRIALIZADA." Universidade Federal do Espírito Santo, 2016. http://repositorio.ufes.br/handle/10/10317.
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Previous issue date: 2016-04-13<br>O objetivo principal deste trabalho foi avaliar a influência das condições de contorno nas simulações com o modelo CMAQ sobre a Região Metropolitana da Grande Vitória (RMGV) para os poluentes, ozônio (O3) e material particulado inalável (MP10). Foram feitos quatro cenários de simulação para o mês de agosto de 2010 com diferentes condições de contorno. O primeiro cenário (M1) utilizando condições de contorno fixas, invariáveis com o tempo com concentrações nulas (zero) para todos os poluentes; um segundo cenário (M2) com valores fixos de concentração, invariável com o tempo com valores médios obtidos através do monitoramento das estações de qualidade da RMGV e de estações de Aracruz ao Norte e Anchieta ao sul; o terceiro cenário (M3) utilizou condições de contorno variáveis com o tempo provenientes de uma simulação prévia do CMAQ com um domínio maior, centralizado sobre a mesma área (RMGV); e por fim o quarto cenário (M4) que utilizou valores de concentrações variáveis com o tempo para as bordas oriundas de simulações com o modelo global GEOS-Chem. Todos os cenários utilizaram as mesmas condições de meteorológicas e emissões de poluentes, com condições meteorológicas geradas pelo modelo WRF versão 3.6.1 e emissões atmosféricas provenientes do inventário de emissões oficial da RMGV. As simulações de qualidade do ar foram feitas com domínio 61 x79 km centrado nas coordenadas -20,25ºS; -40,28ºW com resolução de 1 km, utilizando o CB05 e Aero6 e ainda o analisador de processos do CMAQ (PROCAN). Os resultados das simulações foram comparados com os dados medidos em estações de monitoramento da RMGV. Os resultados mostraram que para MP10 as condições de contorno não foram tão influentes nas concentrações simuladas, com pequenas variações das concentrações entre eles, porém, de um modo geral, os métodos M3 e M4 alcançaram os melhores resultados para estatística, entretanto o método M2 não está totalmente equivocado, porém deve-se ter cautela em usar esse método. Foram observados comportamentos diferentes entre as estações de monitoramento onde houve umas com valores superestimados em algumas horas e outras com valores subestimados, ocorrido provavelmente, por causa do tamanho da grade associado com as condições meteorológicas e variação temporal das emissões. Para o ozônio, notou-se que as condições de contorno influenciam diretamente nas concentrações modeladas, podendo inclusive influenciar no aumento da produção do O3 não apenas por reações químicas, mas também por processos de advecção e difusão atmosférica. Foi observado que cenário M1 faz com que as concentrações de O3 modeladas sejam bem pequenas, não representando a realidade. No cenário M2 as concentrações foram superestimadas, tanto nas estações quanto nas áreas próximas aos limites do domínio, principalmente na porção Oeste. Os cenários M3 e M4 alcançaram os melhores resultados de concentrações e estatística, sendo estes os mais aconselháveis quando o objetivo é avaliar o ozônio. Como o domínio final utilizado na modelagem do CMAQ foi de apenas 61 x 79km, observou-se que as condições de fronteira influenciam diretamente em toda grade do domínio, principalmente para ozônio, ao utilizar o processador de analises (PROCAN). Quando as concentrações de contorno são altas, independentes de serem fixas ou variantes com o tempo, os processos de advecção e difusão turbulenta promovem um incremento muito maior nas regiões de fronteira com a RMGV, aumentando a concentração.
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SANTIAGO, A. M. "Formação e transporte de material particulado na Região Metropolitana da Grande Vitória/ES: utilização e avaliação do desempenho do modelo CMAQ." Universidade Federal do Espírito Santo, 2015. http://repositorio.ufes.br/handle/10/10323.
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Previous issue date: 2015-03-31<br>Este trabalho teve como principal objetivo avaliar a formação e o transporte de Material Particulado na Região Metropolitana da Grande Vitória (RMGV) utilizando o The Models-3 Community Multiscale Air Quality Modeling System (CMAQ). Em particular, investigou-se a resposta de material particulado a mudanças nas fontes de emissões veiculares e industriais. No inverno de 2012 (de 22 a 31 de julho) foi realizada uma campanha experimental utilizando o LIDAR para caracterizar o comportamento da Camada Limite Atmosférica (CLA) e o SODAR para medir a estrutura vertical da atmosfera na RMGV. Também foram utilizados dados coletados pelas estações meteorológicas e de qualidade do ar da região para validação dos resultados numéricos. Os campos meteorológicos tridimensionais foram modelados utilizando o modelo meteorológico Weather Research and Forecasting (WRF) na versão 3.4.1 durante o período de 15 a 31 de julho de 2012. Fez-se uso de quatro domínios aninhados com resolução de grade 27 quilômetros (70 × 70 células), 9 km (100 x 100 células), 3 km (100 x 100 células), 1 km (células 120 x 120) e todos com 21 níveis verticais. Para as simulações com o CMAQ, utilizou-se e domínio com resolução de 1 km com corte para 79 x 61 células, o qual abrange as cidades de Cariacica, Laranjeiras, Serra, Viana, Vila Velha e Vitória. As simulações com o modelo CMAQ foram realizadas de 22 de julho a 31 de 2012 (240 horas). O modelo SMOKE foi aplicado para construir um inventário de emissões, espacialmente e temporalmente resolvido para RMGV utilizando o inventário de emissões oficial do Estado. As simulações de qualidade do ar utilizaram concentrações medidas como as condições iniciais e de fronteira. Foram utilizadas as opções AERO4 e Carbon Bond V disponíveis na versão 4.6 do modelo CMAQ para descrição dos processos de aerossol, química da fase aquosa e gasosa. Três diferentes cenários foram simulados: considerando o atual inventário de emissões (caso base), considerando a exclusão de fontes de emissões veiculares (cenário 1) e considerando a exclusão das emissões industriais (cenário 2). Os resultados apontam valores máximos de concentração de partículas sobre a Ponta de Tubarão devido à concentração industrial, entretanto, observa-se claramente a influência veicular na região. Observou-se uma queda na concentração de MP10 em relação ao caso base e nos dois cenários de redução de emissão, 85 % e 24 % para Laranjeiras, 82 % e 25 % para Enseada e 89 % e 23% para Cariacica, sem a presença de emissões veiculares e sem a presença de emissões industriais, respectivamente. Observou-se uma queda na concentração de MP2,5 em relação ao caso base foi de aproximadamente 75,4 % e 19,4 % para Laranjeiras, 74,5 % e 19,9 % para Enseada e 79,1 % e 7,8% para Cariacica, sem a presença de emissões veiculares e sem a presença de emissões industrias, respectivamente. Os resultados simulados mostraram que a fração carbonácea no material particulado da RMGV é de aproximadamente 60 % da massa total de MP10, logo os cenários simulados de supressão das principais fontes da região, causaram maiores impactos na concentração de carbono orgânico e elementar do que nas concentrações de sulfato, nitrato e amônio as quais eram muito pequenas no caso base e permaneceram sem alterações significativas. Estes resultados reforçam a necessidade de atualizar o inventario de fontes de emissão da RMGV, o qual considera a fonte veicular como principal fonte de MP na região. Políticas de controle de concentração de MP devem considerar o papel de aerossóis orgânicos e do carbono elementar, visto que estes correspondem a maior fração da massa total do MP10.
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Fournier, David. "Metro regenerative braking energy : optimization through rescheduling : mathematical model and greedy heuristics compared to MILP and CMA-ES." Paris 7, 2014. http://www.theses.fr/2014PA077144.
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The use of regenerative braking is a key factor to reduce the energy consumption of a metro line. In the case where no device can store the energy produced during braking, only the metros that are accelerating at the same time can benefit from it. Maximizing the power transfers between accelerating and braking metros thus provides a simple strategy to benefit from regenerative energy without any other hardware device. In this thesis, we use a mathematical timetable model to classify various metro energy optimization rescheduling problems studied in the literature and prove their NP-hardness by polynomial reductions of SAT. We then focus on the problem of minimizing the global energy consumption of a metro timetable by modifying the dwell times in stations. We present a greedy heuristic algorithm which aims at locally synchronizing braking metros along the timetable with accelerating metros in their time neighbourhood, using a non-linear approximation of energy transfers. On a benchmark of six small size timetables, we show that our greedy heuristics performs better than CPLEX using a MILP formulation of the problem, even when it is able to prove the optimality of a linear approximation of the objective function. We also show that it runs ten times faster than a state-of-the-art evolutionary algorithm, called the covariance matrix adaptation evolution strategy (CMA-ES), using the same non-linear objective function on these small size instances. On real data leading to 10000 decision variables on which both MILP and CMA-ES do not provide solutions, the dedicated algorithm of our thesis computes solutions with a reduction of energy consumption ranging from 5% to 9%<br>The use of regenerative braking is a key factor to reduce the energy consumption of a metro line. In the case where no device can store the energy produced during braking, only the metros that are accelerating at the same time can benefit from it. Maximizing the power transfers between accelerating and braking metros thus provides a simple strategy to benefit from regenerative energy without any other hardware device. In this thesis, we use a mathematical timetable model to classify various metro energy optimization rescheduling problems studied in the literature and prove their NP-hardness by polynomial reductions of SAT. We then focus on the problem of minimizing the global energy consumption of a metro timetable by modifying the dwell times in stations. We present a greedy heuristic algorithm which aims at locally synchronizing braking metros along the timetable with accelerating metros in their time neighbourhood, using a non-linear approximation of energy transfers. On a benchmark of six small size timetables, we show that our greedy heuristics performs better than CPLEX using a MILP formulation of the problem, even when it is able to prove the optimality of a linear approximation of the objective function. We also show that it runs ten times faster than a state-of-the-art evolutionary algorithm, called the covariance matrix adaptation evolution strategy (CMA-ES), using the saure non-linear objective function on these small size instances. On real data leading to 10000 decision variables on which both MILP and CMA-ES do not provide solutions, the dedicated algorithm of our thesis computes solutions with a reduction of energy consumption ranging from 5% to 9%
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Scarfe, Peter Craig. "Error minimising gradients for improving cerebellar model articulation controller performance." Thesis, Curtin University, 2009. http://hdl.handle.net/20.500.11937/1241.
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In motion control applications where the desired trajectory velocity exceeds an actuator’s maximum velocity limitations, large position errors will occur between the desired and actual trajectory responses. In these situations standard control approaches cannot predict the output saturation of the actuator and thus the associated error summation cannot be minimised.An adaptive feedforward control solution such as the Cerebellar Model Articulation Controller (CMAC) is able to provide an inherent level of prediction for these situations, moving the system output in the direction of the excessive desired velocity before actuator saturation occurs. However the pre-empting level of a CMAC is not adaptive, and thus the optimal point in time to start moving the system output in the direction of the excessive desired velocity remains unsolved. While the CMAC can adaptively minimise an actuator’s position error, the minimisation of the summation of error over time created by the divergence of the desired and actual trajectory responses requires an additional adaptive level of control.This thesis presents an improved method of training CMACs to minimise the summation of error over time created when the desired trajectory velocity exceeds the actuator’s maximum velocity limitations. This improved method called the Error Minimising Gradient Controller (EMGC) is able to adaptively modify a CMAC’s training signal so that the CMAC will start to move the output of the system in the direction of the excessive desired velocity with an optimised pre-empting level.The EMGC was originally created to minimise the loss of linguistic information conveyed through an actuated series of concatenated hand sign gestures reproducing deafblind sign language. The EMGC concept however is able to be implemented on any system where the error summation associated with excessive desired velocities needs to be minimised, with the EMGC producing an improved output approximation over using a CMAC alone.In this thesis, the EMGC was tested and benchmarked against a feedforward / feedback combined controller using a CMAC and PID controller. The EMGC was tested on an air-muscle actuator for a variety of situations comprising of a position discontinuity in a continuous desired trajectory. Tested situations included various discontinuity magnitudes together with varying approach and departure gradient profiles.Testing demonstrated that the addition of an EMGC can reduce a situation’s error summation magnitude if the base CMAC controller has not already provided a prior enough pre-empting output in the direction of the situation. The addition of an EMGC to a CMAC produces an improved approximation of reproduced motion trajectories, not only minimising position error for a single sampling instance, but also over time for periodic signals.
Books on the topic "CMAQ model"
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Eskandarian, Azim. A reference model dynamics-CMAC algorithm for simulation and control of robotic manipulators. George Washington University, 1991.
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W, Byun D., Ching J. K. S, and United States. Environmental Protection Agency. Office of Research and Development, eds. Science algorithms of the EPA models-3 community multiscale air quality (CMAQ) modeling system. U.S. Environmental Protection Agency, Office of Research and Development, 1999.
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Low Choy, Samantha, Justine Murray, Allan James, and Kerrie Mengersen. Combining monitoring data and computer model output in assessing environmental exposure. Edited by Anthony O'Hagan and Mike West. Oxford University Press, 2018. http://dx.doi.org/10.1093/oxfordhb/9780198703174.013.18.
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This article discusses an approach that combines monitoring data and computer model outputs for environmental exposure assessment. It describes the application of Bayesian data fusion methods using spatial Gaussian process models in studies of weekly wet deposition data for 2001 from 120 sites monitored by the US National Atmospheric Deposition Program (NADP) in the eastern United States. The article first provides an overview of environmental computer models, with a focus on the CMAQ (Community Multi-Scale Air Quality) Eta forecast model, before considering some algorithmic and pseudo-statistical approaches in weather prediction. It then reviews current state of the art fusion methods for environmental data analysis and introduces a non-dynamic downscaling approach. The static version of the dynamic spatial model is used to analyse the NADP weekly wet deposition data.
Book chapters on the topic "CMAQ model"
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Akyuz, Ezgi, Fulya Cingiroglu, Alper Unal, and Burcak Kaynak. "An Updated Agriculture Emissions Inventory and Contribution Estimation Using WRF-CMAQ Model for Turkey." In Air Pollution Modeling and its Application XXVIII. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-12786-1_40.
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Wong, David, Hosein Foroutan, Jonathan E. Pleim, et al. "A Proof-of-Concept for Linking the Global Meteorological Model, MPAS-a with the Air Quality Model, CMAQ." In Springer Proceedings in Complexity. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-22055-6_6.
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Syrakov, Dimiter, Emilia Georgieva, Maria Prodanova, et al. "Application of WRF-CMAQ Model System for Analysis of Sulfur and Nitrogen Deposition over Bulgaria." In Numerical Methods and Applications. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-10692-8_54.
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Santiago, Manuel, Ariel F. Stein, Fantine Ngan, and Marta G. Vivanco. "Evaluation of SOA Formation Using a Box Model Version of CMAQ and Chamber Experimental Data." In Computational Science and Its Applications - ICCSA 2011. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-21931-3_29.
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Arnold, J. R., and Robin L. Dennis. "First Results from Operational Testing of the U.S. EPA Models 3/ Community Multiscale Model for Air Quality (CMAQ)." In Air Pollution Modeling and Its Application XIV. Springer US, 2004. http://dx.doi.org/10.1007/0-306-47460-3_65.
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Byun, Daewon W., Jason K. S. Ching, Joan Novak, and Jeff Young. "Development and Implementation of the EPA’s Models-3 Initial Operating Version: Community Multi-Scale Air Quality (CMAQ) Model." In Air Pollution Modeling and Its Application XII. Springer US, 1998. http://dx.doi.org/10.1007/978-1-4757-9128-0_37.
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Ran, Limei, Ellen Cooter, Verel Benson, and Qun He. "Development of an Agricultural Fertilizer Modeling System for Bi-Directional Ammonia Fluxes in the CMAQ Model." In Air Pollution Modeling and its Application XXI. Springer Netherlands, 2011. http://dx.doi.org/10.1007/978-94-007-1359-8_36.
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Sidi, Fahim, Wyat Appel, Jesse Bash, et al. "The Community Multiscale Air Quality (CMAQ) Model Version 5.4: Updates and Results from Northern Hemispheric Scale Evaluation." In Springer Proceedings in Complexity. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-70424-6_10.
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Pleim, Jonathan, Robert Gilliam, Wyat Appel, and Limei Ran. "Recent Advances in Modeling of the Atmospheric Boundary Layer and Land Surface in the Coupled WRF-CMAQ Model." In Springer Proceedings in Complexity. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-24478-5_64.
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Jiang, Xiangyu, and Eun-Hye Yoo. "Evaluating the Effect of Domain Size of the Community Multiscale Air Quality (CMAQ) Model on Regional PM2.5 Simulations." In Geospatial Technologies for Urban Health. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-19573-1_4.
Full textConference papers on the topic "CMAQ model"
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Albertini, C., S. Fernández, L. G. Muñoz, A. Pellicano, and J. P. Rossi. "Erosion-Corrosion Analysis and Prediction Methods in Gas Plant Facilities." In CORROSION 2011. NACE International, 2011. https://doi.org/10.5006/c2011-11357.
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Abstract Both localized corrosion and erosion-corrosion mechanisms are significant hazards to pressure vessels and pipeline systems involved in gas production and treatment operations. Process conditions tend to promote aggressive corrosion on the most common alloys used in these systems, including carbon steels, low alloy steels and stainless steels. In recent years, the author's organization has initiated a systematic process involving the use of engineering prediction models for production, gas treatment and compression equipment in erosive and corrosive service. This initiative was complementary to a long term strategy called the CMAS (Corrosion Management Assurance System). Based on continuous monitoring, inspection and mitigation programs, CMAS is specifically directed towards detection, quantification and control of active damage mechanisms. This paper describes the development and results of the CMAS program in the following areas: Process simulation of gas treatment and compression equipment, including both thermodynamic and multiphase flow analysis.Empirical corrosion, erosion and corrosion-erosion rate estimates.Application of customized models to materials selection, remaining life prediction and risk assessment techniques, which constitute the nuclei of the CMAS process.
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Hong, He, Zhou Entao, Sun Wei, Zhou Shichang, Shi Weixiang, and Lin Tingqi. "The Neural Network Identification of the Electro-Hydraulic Servo System." In ASME 1997 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 1997. http://dx.doi.org/10.1115/imece1997-1278.
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Abstract A new kind of neural network based on RBFN and CMAC is proposed in this paper. The learning speed is very fast so that it can be used to identify the hydraulic servo system on line. A new model structure used for the identification of the hydraulic servo system with large alternating disturbance is also proposed in this paper. The simulation results are very satisfactory.
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Kodadi, Sharadha, Durga Praveen Deevi, Naga Sushma Allur, Koteswararao Dondapati, Himabindu Chetlapalli, and Thinagaran Perumal. "CMAC-based API Security with Transformer Model for Intrusion Detection in SDN-IoT Networks." In 2025 International Conference on Intelligent Computing and Control Systems (ICICCS). IEEE, 2025. https://doi.org/10.1109/iciccs65191.2025.10985207.
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Cordero, Lina, Nabin Malakar, Yonghua Wu, Barry Gross, Fred Moshary, and Mike Ku. "Assessing satellite based PM2.5 estimates against CMAQ model forecasts." In SPIE Remote Sensing, edited by Adolfo Comeron, Evgueni I. Kassianov, Klaus Schäfer, Karin Stein, and John D. Gonglewski. SPIE, 2013. http://dx.doi.org/10.1117/12.2029320.
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Ma, Shuangchen. "Seasonal Simulation of Ozone by Air Quality Model-CMAQ in the Great Lakes." In 2010 4th International Conference on Bioinformatics and Biomedical Engineering (iCBBE). IEEE, 2010. http://dx.doi.org/10.1109/icbbe.2010.5516066.
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San José, R., J. L. Pérez, J. L. Morant, and R. M. González. "Elevated PM10 and PM2.5 concentrations in Europe: a model experiment with MM5-CMAQ and WRF-CHEM." In AIR POLLUTION 2008. WIT Press, 2008. http://dx.doi.org/10.2495/air080011.
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Zhou, Cheng, Hengqing Li, Guang Pan, Chun Ding, and Guiqin Zhang. "Analysis of the possibility of air quality achieving the standard of Dongying based on WRF-CMAQ Model." In Proceedings of the 2019 3rd International Forum on Environment, Materials and Energy (IFEME 2019). Atlantis Press, 2019. http://dx.doi.org/10.2991/ifeme-19.2019.66.
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Lee, Yi-Ju, Fang-Yi Cheng, Chih-Yung Feng, and Zhih-Min Yang. "Impact of the weighted loss function on the innovative CMAQ-CNN PM2.5 forecasting model." In 2023 Asia Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC). IEEE, 2023. http://dx.doi.org/10.1109/apsipaasc58517.2023.10317249.
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San José, R., J. L. Pérez, and R. M. González. "Air quality street level simulations by using an integrated mesoscale air quality modelling system (MM5-CMAQ-EMIMO) and a CFD model (MIMO): Madrid case study." In AIR POLLUTION 2006. WIT Press, 2006. http://dx.doi.org/10.2495/air06005.
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Abdelhameed, Magdy Mohamed, and Sabri Cetinkunt. "Adaptive Learning Algorithm for Cerebellar Model Articulation Controller: Neural Network Based Hybrid-Type Controller—Part I." In ASME 2000 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2000. http://dx.doi.org/10.1115/imece2000-2200.
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Abstract Cerebellar model articulation controller (CMAC) is a useful neural network learning technique. It was developed two decades ago but yet lacks an adequate learning algorithm, especially when it is used in a hybrid- type controller. This work is intended to introduce a simulation study for examining the performance of a hybrid-type control system based on the conventional learning algorithm of CMAC neural network. This study showed that the control system is unstable. Then a new adaptive learning algorithm of a CMAC based hybrid- type controller is proposed. The main features of the proposed learning algorithm, as well as the effects of the newly introduced parameters of this algorithm have been studied extensively via simulation case studies. The simulation results showed that the proposed learning algorithm is a robust in stabilizing the control system. Also, this proposed learning algorithm preserved all the known advantages of the CMAC neural network. Part II of this work is dedicated to validate the effectiveness of the proposed CMAC learning algorithm experimentally.
Reports on the topic "CMAQ model"
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McDonnell, Todd, Michael Bell, Emmi Felker-Quinn, et al. Exceedance of critical loads of nitrogen and sulfur deposition across national parks: Comparing 2015?2017 CMAQ and TDep model outputs. National Park Service, 2024. http://dx.doi.org/10.36967/2305350.
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Atmospheric deposition can alter biological communities through a variety of pathways. Atmospheric nitrogen (N) deposition causes some plant and animal species to increase growth and/or abundance. Other species then can be outcompeted and eliminated from the biological community. Deposition of reactive N (Nr) to watersheds can impact both aquatic and terrestrial ecosystem elements and contribute to eutrophication and acidification effects. Atmospheric sulfur (S) deposition has been the primary driver of soil and surface water acidification of acid-sensitive ecosystems, resulting in adverse effects on aquatic biota and forest health. Critical loads (CLs) of atmospheric N and S deposition are used to establish thresholds of ecosystem impacts associated with a given level of deposition. The CLs of N for a decline in sensitive lichen species richness (3.1 kg-N ha-1 yr-1) and to protect herbaceous species richness (6-16 kg-N ha-1 yr-1) were chosen to evaluate N impacts at lower and higher levels of deposition. To evaluate S impacts, CLs for a decline in sensitive lichen species richness (2.3 kg-S ha-1 yr-1) and the CL to protect acid neutralizing capacity (ANC) of lakes and streams (0-31 kg-S ha-1 yr-1) were chosen. Locations where the deposition is higher than the CL are considered to have deposition in ?exceedance? of the CL. Exceedances can be calculated using more than one method for estimating deposition. This report quantifies differences in atmospheric deposition estimates generated by two modeling approaches (Total Deposition [TDep] and Community Multiscale Air Quality [CMAQ]) using representative annual deposition estimates for 2017 across the conterminous US. Given that TDep represents a measurement-based adjustment of CMAQ model results, this project evaluates the extent to which those adjustments affect the magnitude and spatial extent of critical load exceedances as compared with using deposition estimates directly from CMAQ for all National Park Service (NPS) units with available data. This analysis showed that selection of the deposition data source was most important in consideration of CL exceedance for lichen species richness. The extent of CL exceedance was less affected by the deposition data source for CLs to protect herbaceous species richness and surface water acidification. Results from this study can be used to guide natural resource management and policy in the context of understanding uncertainty in air pollution effects caused by atmospheric N and S deposition across a broad set of federally protected NPS units. The results can also provide insight into where local deposition measurements elucidate risk to ecosystem health.
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Fitzpatrick, Patrick, and Yee Lau. CONCORDE Meteorological Analysis (CMA) - Data Guide. The University of Southern Mississippi, 2023. http://dx.doi.org/10.18785/sose.003.
Full textAbstract:
CONCORDE is the CONsortium for oil spill exposure pathways in COastal River-Dominated Ecosystems (CONCORDE), and is an interdisciplinary research program funded by the Gulf of Mexico Research Initiative (GoMRI) to conduct scientific studies of the impacts of oil, dispersed oil and dispersant on the Gulf’s ecosystem (Greer et al. 2018). A CONCORDE goal is to implement a synthesis model containing circulation and biogeochemistry components of the Northern Gulf of Mexico shelf system which can ultimately aid in prediction of oil spill transport and impacts. The CONCORDE Meteorological Analysis (CMA) is an hourly gridded NetCDF dataset which provides atmospheric forcing for the synthesis model. CMA includes a variety of parameters from multiple sources. The Real-Time Mesoscale Analysis (RTMA; De Pondeca et al. 2011) provides the surface momentum and the thermodynamic atmospheric data. The radiation parameters and total cloud cover percentage are from the North American Mesoscale (NAM) Forecast System fields. The hourly precipitation is extracted from the Next Generation Weather Radar (NEXRAD) Level-III. Gridded sea surface temperature fields (SST) are computed daily using a 10-day running mean of the Advanced Very High-Resolution Radiometer (AVHRR) SST product. The Coupled Ocean-Atmosphere Response Experiment flux (COARE) algorithm calculates sensible heat flux and surface momentum stresses (Fairall et al. 2003). CMA’s spatial domain’s lowest west grid point is at 90.13°W, 29°N, and the highest east grid point is at 87.05°W, 30.94°N. The grid spacing is 0.01 degree, and the grid dimension is 309 by 195.
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Goeckeritz, Joel, Nathan Schank, Ryan L Wood, Beverly L Roeder, and Alonzo D Cook. Use of Urinary Bladder Matrix Conduits in a Rat Model of Sciatic Nerve Regeneration after Nerve Transection Injury. Science Repository, 2022. http://dx.doi.org/10.31487/j.rgm.2022.03.01.
Full textAbstract:
Previous research has demonstrated the use of single-channel porcine-derived urinary bladder matrix (UBM) conduits in segmental-loss, peripheral nerve repairs as comparable to criterion-standard nerve autografts. This study aimed to replicate and expand upon this research with additional novel UBM conduits and coupled therapies. Fifty-four Wistar Albino rats were divided into 6 groups, and each underwent a surgical neurectomy to remove a 7-millimeter section of the sciatic nerve. Bridging of this nerve gap and treatment for each group was as follows: i) reverse autograft—the segmented nerve was reversed 180 degrees and used to reconnect the proximal and distal nerve stumps; ii) the nerve gap was bridged via a silicone conduit; iii) a single-channel UBM conduit; iv) a multi-channel UBM conduit; v) a single-channel UBM conduit identical to group 3 coupled with fortnightly transcutaneous electrical nerve stimulation (TENS); vi) or, a multi-channel UBM conduit identical to group 4 coupled with fortnightly TENS. The extent of nerve recovery was assessed by behavioural parameters: foot fault asymmetry scoring measured weekly for six weeks; electrophysiological parameters: compound muscle action potential (CMAP) amplitudes, measured at weeks 0 and 6; and morphological parameters: total fascicle areas, myelinated fiber counts, fiber densities, and fiber sizes measured at week 6. All the above parameters demonstrated recovery of the test groups (3-6) as being either comparable or less than that of reverse autograft, but none were shown to outperform reverse autograft. As such, UBM conduits may yet prove to be an effective treatment to repair relatively short segmental peripheral nerve injuries, but further research is required to demonstrate greater efficacy over nerve autografts.
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Goeckeritz, Joel, Nathan Schank, Ryan L Wood, Beverly L Roeder, and Alonzo D Cook. Use of Urinary Bladder Matrix Conduits in a Rat Model of Sciatic Nerve Regeneration after Nerve Transection Injury. Science Repository, 2022. http://dx.doi.org/10.31487/j.rgm.2022.03.01.sup.
Full textAbstract:
Previous research has demonstrated the use of single-channel porcine-derived urinary bladder matrix (UBM) conduits in segmental-loss, peripheral nerve repairs as comparable to criterion-standard nerve autografts. This study aimed to replicate and expand upon this research with additional novel UBM conduits and coupled therapies. Fifty-four Wistar Albino rats were divided into 6 groups, and each underwent a surgical neurectomy to remove a 7-millimeter section of the sciatic nerve. Bridging of this nerve gap and treatment for each group was as follows: i) reverse autograft—the segmented nerve was reversed 180 degrees and used to reconnect the proximal and distal nerve stumps; ii) the nerve gap was bridged via a silicone conduit; iii) a single-channel UBM conduit; iv) a multi-channel UBM conduit; v) a single-channel UBM conduit identical to group 3 coupled with fortnightly transcutaneous electrical nerve stimulation (TENS); vi) or, a multi-channel UBM conduit identical to group 4 coupled with fortnightly TENS. The extent of nerve recovery was assessed by behavioural parameters: foot fault asymmetry scoring measured weekly for six weeks; electrophysiological parameters: compound muscle action potential (CMAP) amplitudes, measured at weeks 0 and 6; and morphological parameters: total fascicle areas, myelinated fiber counts, fiber densities, and fiber sizes measured at week 6. All the above parameters demonstrated recovery of the test groups (3-6) as being either comparable or less than that of reverse autograft, but none were shown to outperform reverse autograft. As such, UBM conduits may yet prove to be an effective treatment to repair relatively short segmental peripheral nerve injuries, but further research is required to demonstrate greater efficacy over nerve autografts.