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Sensitivity Modeling Study for an Ozone Occurrence during the 1996 Paso Del Norte Ozone Campaign

Lu, Duanjun; Reddy, Remata S.; Fitzgerald, Rosa; Stockwell, William R.; Williams, Quinton L.; Tchounwou, Paul B.
Fonte: Molecular Diversity Preservation International (MDPI) Publicador: Molecular Diversity Preservation International (MDPI)
Tipo: Artigo de Revista Científica
EN
Relevância na Pesquisa
16.76%
Surface ozone pollution has been a persistent environmental problem in the US and Europe as well as the developing countries. A key prerequisite to find effective alternatives to meeting an ozone air quality standard is to understand the importance of local anthropogenic emissions, the significance of biogenic emissions, and the contribution of long-range transport. In this study, an air quality modeling system that includes chemistry and transport, CMAQ, an emission processing model, SMOKE, and a mesoscale numerical meteorological model, WRF, has been applied to investigate an ozone event occurring during the period of the 1996 Paso del Norte Ozone Campaign. The results show that the modeling system exhibits the capability to simulate this high ozone occurrence by providing a comparable temporal variation of surface ozone concentration at one station and to capture the spatial evolution of the event. Several sensitivity tests were also conducted to identify the contributions to high surface ozone concentration from eight VOC subspecies, biogenic VOCs, anthropogenic VOCs and long-range transportation of ozone and its precursors. It is found that the reductions of ETH, ISOP, PAR, OLE and FORM help to mitigate the surface ozone concentration...

Spatial-temporal association between fine particulate matter and daily mortality

Choi, Jungsoon; Fuentes, Montserrat; Reich, Brian J.
Fonte: PubMed Publicador: PubMed
Tipo: Artigo de Revista Científica
Publicado em 15/06/2009 EN
Relevância na Pesquisa
16.76%
Fine particulate matter (PM2.5) is a mixture of pollutants that has been linked to serious health problems, including premature mortality. Since the chemical composition of PM2.5 varies across space and time, the association between PM2.5 and mortality could also change with space and season. In this work we develop and implement a statistical multi-stage Bayesian framework that provides a very broad, flexible approach to studying the spatiotemporal associations between mortality and population exposure to daily PM2.5 mass, while accounting for different sources of uncertainty. In stage 1, we map ambient PM2.5 air concentrations using all available monitoring data (IMPROVE and FRM) and an air quality model (CMAQ) at different spatial and temporal scales. In stage 2, we examine the spatial temporal relationships between the health end-points and the exposures to PM2.5 by introducing a spatial-temporal generalized Poisson regression model. We adjust for time-varying confounders, such as seasonal trends. A common seasonal trends model is to use a fixed number of basis functions to account for these confounders, but the results can be sensitive to the number of basis functions. In this study, the number of the basis functions is treated as an unknown parameter in our Bayesian model and we use a space-time stochastic search variable selection approach. We apply our methods to a data set in North Carolina for the year 2001.

A mechanistic modeling system for estimating large scale emissions and transport of pollen and co-allergens

Efstathiou, Christos; Isukapalli, Sastry; Georgopoulos, Panos
Fonte: PubMed Publicador: PubMed
Tipo: Artigo de Revista Científica
Publicado em 01/04/2011 EN
Relevância na Pesquisa
18.13%
Allergic airway diseases represent a complex health problem which can be exacerbated by the synergistic action of pollen particles and air pollutants such as ozone. Understanding human exposures to aeroallergens requires accurate estimates of the spatial distribution of airborne pollen levels as well as of various air pollutants at different times. However, currently there are no established methods for estimating allergenic pollen emissions and concentrations over large geographic areas such as the United States. A mechanistic modeling system for describing pollen emissions and transport over extensive domains has been developed by adapting components of existing regional scale air quality models and vegetation databases. First, components of the Biogenic Emissions Inventory System (BEIS) were adapted to predict pollen emission patterns. Subsequently, the transport module of the Community Multiscale Air Quality (CMAQ) modeling system was modified to incorporate description of pollen transport. The combined model, CMAQ-pollen, allows for simultaneous prediction of multiple air pollutants and pollen levels in a single model simulation, and uses consistent assumptions related to the transport of multiple chemicals and pollen species. Application case studies for evaluating the combined modeling system included the simulation of birch and ragweed pollen levels for the year 2002...

Comparison of exposure estimation methods for air pollutants: Ambient monitoring data and regional air quality simulation

Bravo, Mercedes A.; Fuentes, Montserrat; Zhang, Yang; Burr, Michael J.; Bell, Michelle L.
Fonte: PubMed Publicador: PubMed
Tipo: Artigo de Revista Científica
EN
Relevância na Pesquisa
17.43%
Air quality modeling could potentially improve exposure estimates for use in epidemiological studies. We investigated this application of air quality modeling by estimating location-specific (point) and spatially-aggregated (county level) exposure concentrations of particulate matter with an aerodynamic diameter less than or equal to 2.5 µm (PM2.5) and ozone (O3) for the eastern U.S. in 2002 using the Community Multi-scale Air Quality (CMAQ) modeling system and a traditional approach using ambient monitors. The monitoring approach produced estimates for 370 and 454 counties for PM2.5 and O3, respectively. Modeled estimates included 1861 counties, covering 50% more population. The population uncovered by monitors differed from those near monitors (e.g., urbanicity, race, education, age, unemployment, income, modeled pollutant levels). CMAQ overestimated O3 (annual normalized mean bias = 4.30%), while modeled PM2.5 had an annual normalized mean bias of −2.09%, although bias varied seasonally, from 32% in November to −27% in July. Epidemiology may benefit from air quality modeling, with improved spatial and temporal resolution and the ability to study populations far from monitors that may differ from those near monitors. However...

One way coupling of CMAQ and a road source dispersion model for fine scale air pollution predictions

Beevers, Sean D.; Kitwiroon, Nutthida; Williams, Martin L.; Carslaw, David C.
Fonte: Pergamon Publicador: Pergamon
Tipo: Artigo de Revista Científica
Publicado em /11/2012 EN
Relevância na Pesquisa
27.43%
In this paper we have coupled the CMAQ and ADMS air quality models to predict hourly concentrations of NOX, 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 NOX emissions as well as the hourly emissions scaling in the model. These findings are consistent with recent evidence of UK road transport NOX 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 NOX 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...

Quantifying the Sources of the Severe Haze over the Southern Hebei Using the CMAQ Model

Yang, Jing; Zhang, Pu; Meng, Chenchen; Su, Jie; Wei, Zhe; Zhang, Fenfen; Wei, Wei; Zhao, Xiujuan
Fonte: Hindawi Publishing Corporation Publicador: Hindawi Publishing Corporation
Tipo: Artigo de Revista Científica
Publicado em 15/09/2013 EN
Relevância na Pesquisa
27.43%
The Southern Hebei of China has experienced an obvious increase of the haze occurrence frequency in the recent years. It has turned out to be one of the most seriously polluted areas in China. This study is aimed at quantifying the sources of the serious haze pollution over the Southern Hebei area, using the Mesoscale Modeling System Generation 5 (MM5) and the Models-3/Community Multiscale Air Quality Model (CMAQ) modeling system. The sectoral contributions by the local and the surrounding regions to the fine particulate matter (PM2.5) concentrations in the two representative cities, Shijiazhuang and Xingtai, were analyzed by applying the method of scenario analysis. It will provide useful information to the policy making in the severe air pollution control in the Southern Hebei area.

Air Quality Modeling in Support of the Near-Road Exposures and Effects of Urban Air Pollutants Study (NEXUS)

Isakov, Vlad; Arunachalam, Saravanan; Batterman, Stuart; Bereznicki, Sarah; Burke, Janet; Dionisio, Kathie; Garcia, Val; Heist, David; Perry, Steve; Snyder, Michelle; Vette, Alan
Fonte: MDPI Publicador: MDPI
Tipo: Artigo de Revista Científica
EN
Relevância na Pesquisa
16.76%
A major challenge in traffic-related air pollution exposure studies is the lack of information regarding pollutant exposure characterization. Air quality modeling can provide spatially and temporally varying exposure estimates for examining relationships between traffic-related air pollutants and adverse health outcomes. A hybrid air quality modeling approach was used to estimate exposure to traffic-related air pollutants in support of the Near-Road Exposures and Effects of Urban Air Pollutants Study (NEXUS) conducted in Detroit (Michigan, USA). Model-based exposure metrics, associated with local variations of emissions and meteorology, were estimated using a combination of the American Meteorological Society/Environmental Protection Agency Regulatory Model (AERMOD) and Research LINE-source dispersion model for near-surface releases (RLINE) dispersion models, local emission source information from the National Emissions Inventory, detailed road network locations and traffic activity, and meteorological data from the Detroit City Airport. The regional background contribution was estimated using a combination of the Community Multi-scale Air Quality (CMAQ) and the Space-Time Ordinary Kriging (STOK) models. To capture the near-road pollutant gradients...

A Spectral Method for Spatial Downscaling

Reich, Brian J.; Chang, Howard H.; Foley, Kristen M.
Fonte: PubMed Publicador: PubMed
Tipo: Artigo de Revista Científica
EN
Relevância na Pesquisa
17.43%
Complex computer models play a crucial role in air quality research. These models are used to evaluate potential regulatory impacts of emission control strategies and to estimate air quality in areas without monitoring data. For both of these purposes, it is important to calibrate model output with monitoring data to adjust for model biases and improve spatial prediction. In this article, we propose a new spectral method to study and exploit complex relationships between model output and monitoring data. Spectral methods allow us to estimate the relationship between model output and monitoring data separately at different spatial scales, and to use model output for prediction only at the appropriate scales. The proposed method is computationally efficient and can be implemented using standard software. We apply the method to compare Community Multiscale Air Quality (CMAQ) model output with ozone measurements in the United States in July 2005. We find that CMAQ captures large-scale spatial trends, but has low correlation with the monitoring data at small spatial scales.

Dispersion Modeling of Traffic-Related Air Pollutant Exposures and Health Effects Among Children with Asthma in Detroit, Michigan

Batterman, Stuart; Ganguly, Rajiv; Isakov, Vlad; Burke, Janet; Arunachalam, Saravanan; Snyder, Michelle; Robins, Thomas; Lewis, Toby
Fonte: PubMed Publicador: PubMed
Tipo: Artigo de Revista Científica
Publicado em //2014 EN
Relevância na Pesquisa
16.76%
Vehicular traffic is a major source of ambient air pollution in urban areas. Traffic-related air pollutants, including carbon monoxide, nitrogen oxides, particulate matter less than 2.5 μm in diameter, and diesel exhaust emissions, have been associated with adverse human health effects, especially in areas near major roads. In addition to emissions from vehicles, ambient concentrations of air pollutants include contributions from stationary sources and background (or regional) sources. Although dispersion models have been widely used to evaluate air quality strategies and policies and can represent the spatial and temporal variation in environments near roads, the use of these models in health studies to estimate air pollutant exposures has been relatively limited. This paper summarizes the modeling system used to estimate exposures in the Near-Roadway Exposure and Urban Air Pollutant Study, an epidemiological study that examined 139 children with asthma or symptoms consistent with asthma, most of whom lived near major roads in Detroit, Michigan. Air pollutant concentrations were estimated with a hybrid modeling framework that included detailed inventories of mobile and stationary sources on local and regional scales; the RLINE, AERMOD...

Risk-based Prioritization among Air Pollution Control Strategies in the Yangtze River Delta, China

Fu, Joshua S.; Zhuang, Guoshun; Zhou, Ying; Levy, Jonathan Ian
Fonte: National Institute of Environmental Health Sciences Publicador: National Institute of Environmental Health Sciences
Tipo: Artigo de Revista Científica
EN_US
Relevância na Pesquisa
27.43%
Background: The Yangtze River Delta (YRD) in China is a densely populated region with recent dramatic increases in energy consumption and atmospheric emissions. Objectives: We studied how different emission sectors influence population exposures and the corresponding health risks, to inform air pollution control strategy design. Methods: We applied the Community Multiscale Air Quality (CMAQ) Modeling System to model the marginal contribution to baseline concentrations from different sectors. We focused on nitrogen oxide (NOx) control while considering other pollutants that affect fine particulate matter [aerodynamic diameter (leq 2.5 mu m (PM_{2.5}))] and ozone concentrations. We developed concentration–response (C-R) functions for (PM_{2.5}) and ozone mortality for China to evaluate the anticipated health benefits. Results: In the YRD, health benefits per ton of emission reductions varied significantly across pollutants, with reductions of primary (PM_{2.5}) from the industry sector and mobile sources showing the greatest benefits of 0.1 fewer deaths per year per ton of emission reduction. Combining estimates of health benefits per ton with potential emission reductions, the greatest mortality reduction of 12,000 fewer deaths per year [95% confidence interval (CI)...

Examination of the Community Multiscale Air Quality (CMAQ) model performance over the North American and European domains

APPEL Wyat; CHAMEL Charles; RESELLE Shawn; RONG-MING H; RAO St; GALMARINI Stefano; Sokhi Ranjeet S.; FRANCIS X.v.
Fonte: PERGAMON PRESS LTD. Publicador: PERGAMON PRESS LTD.
Tipo: Articles in Journals Formato: Printed
ENG
Relevância na Pesquisa
27.43%
The CMAQ modeling system has been used to simulate the air quality for North America and Europe for the entire year of 2006 as part of the Air Quality Model Evaluation International Initiative (AQMEII). The operational model performance of tropospheric ozone (O3), fine particulate matter (PM2.5) and total particulate matter (PM10) for the two continents has been assessed. The model underestimates daytime (8ame8pm LST) O3 mixing ratios by 13% in the winter for North America, primarily due to an underestimation of daytime O3 mixing ratios in the middle and lower troposphere from the lateral boundary conditions. The model overestimates winter daytime O3 mixing ratios in Europe by an average of 8.4%. The model underestimates daytime O3 by 4e5% in the spring for both continents, while in the summer daytime O3 is overestimated by 9.8% for North America and slightly underestimated by 1.6% for Europe. The model overestimates daytime O3 in the fall for both continents, grossly overestimating daytime O3 by over 30% for Europe. The performance for PM2.5 varies both seasonally and geographically for the two continents. For North American, PM2.5 is overestimated in the winter and fall, with an average Normalized Mean Bias (NMB) greater than 30%...

Influence of uncertainties in vertical mixing algorithms on an air quality model

Tang, Wei
Fonte: Universidade Rice Publicador: Universidade Rice
ENG
Relevância na Pesquisa
17.43%
Vertical diffusion of trace pollutants is a very important physical process that influences pollutant concentrations. However, there are large uncertainties in the numerical modeling of this process, which could affect model predictions of pollutant levels and their responsiveness to emission controls. Uncertainties could result from the formulation of vertical diffusion schemes or from errors in eddy diffusivity and dry deposition velocity parameters associated with this process. Inter-comparisons between different model configurations and sensitivity analysis of model parameters can be used to help quantify these uncertainties. In this study, a comprehensive evaluation of two vertical diffusion schemes, EDDY and ACM2, was performed by comparing ground-level concentrations and vertical profiles generated using the CMAQ model with measurement data from the Texas Air Quality Study II. In addition, new capabilities of conducting sensitivity analysis to dry deposition velocity and eddy diffusivity were implemented into the CMAQ-DDM model. The results show that the ACM2 scheme tends to predict larger secondary pollutant concentrations and smaller primary pollutant concentrations at the surface compared to the EDDY scheme. Differences between the two vertical diffusion schemes and uncertainties in dry deposition velocity may cause temporal variations in the responsiveness of ozone to both NOx and VOC control respectively.

Modeling the Dynamic Change of Air Quality and its Response to Emission Trends

Zhou, Wei
Fonte: Universidade Rice Publicador: Universidade Rice
Relevância na Pesquisa
17.43%
This thesis focuses on evaluating atmospheric chemistry and transport models’ capability in simulating the chemistry and dynamics of power plant plumes, evaluating their strengths and weaknesses in predicting air quality trends at regional scales, and exploring air quality trends in an urban area. First, the Community Mutlti-scale Air Quality (CMAQ) model is applied to simulate the physical and chemical evolution of power plant plumes (PPPs) during the second Texas Air Quality Study (TexAQS) in 2006. SO2 and NOy were observed to be rapidly removed from PPPs on cloudy days but not on cloud-free days, indicating efficient aqueous processing of these compounds in clouds, while the model fails to capture the rapid loss of SO2 and NOy in some plumes on the cloudy day. Adjustments to cloud liquid water content (QC) and the default metal concentrations in the cloud module could explain some of the SO2 loss while NOy in the model was insensitive to QC. Second, CMAQ is applied to simulate the ozone (O3) change after the NOx SIP Call and mobile emission controls in the eastern U.S. from 2002 to 2006. Observed downward changes in 8-hour O3 concentrations in the NOx SIP Call region were under-predicted by 26%–66%. The under-prediction in O3 improvements could be alleviated by 5%–31% by constraining NOx emissions in each year based on observed NOx concentrations while temperature biases or uncertainties in chemical reactions had minor impact on simulated O3 trends. Third...

Seasonal distribution and modeling of diesel particulate matter in the Southeast US

Fonte: Universidade Católica de Temuco Publicador: Universidade Católica de Temuco
Tipo: Artículo de Revista
EN
Relevância na Pesquisa
27.43%
The fine and ultra fine size of diesel particulate mater (DPM) are of great health concern and significantly contribute to the overall cancer risk. In addition, diesel particles may contribute a warming effect on the planet's climate. The composition of these particles is composed principally of elemental carbon (EC) with adsorbed organic compounds, sulfate, nitrate, ammonia, metals, and other trace elements. The purpose of this study was to depict the seasonality and modeling of particulate matter in the Southeastern US produced by the diesel fueled sources (DFSs). The modeling results came from four one-month cases including March, June, September, and December to represent different seasons in 2003 by linking Models-3/CMAQ and SMOKE. The 1999 National Emissions Inventory Version 3 (NEI99) was used in this analysis for point, area, and non-road sources, whereas the National Mobile Inventory Model (NMIM) was used to create the on-road emissions. Three urban areas, Atlanta, Birmingham, and Nashville were selected to analyze the DPM emissions and concentrations. Even though the model performance was not very strong, it could be considered satisfactory to conduct seasonal distribution analysis for DPM. Important hourly DPM seasonality was observed in each city...

Simulated Effects of Climate Change on Summertime Nitrogen Deposition in the Eastern US

Civerolo, Kevin L.; Hogrefe, Christian; Lynn, Barry; Rosenzweig, Cynthia; Goldberg, Richard; Klein-Rosenthal, Joyce Ellen; Knowlton, Kim; Kinney, Patrick L.
Fonte: Elsevier BV Publicador: Elsevier BV
Tipo: Artigo de Revista Científica
EN_US
Relevância na Pesquisa
27.43%
It is anticipated that climate change may impact regional-scale air quality and atmospheric deposition in the coming decades. To simulate the effects of climate change on nitrogen (N) deposition across numerous watersheds in the eastern US, we applied the NASA Goddard Institute for Space Studies General Circulation Model (GISS-GCM), Fifth Generation Pennsylvania State University/National Center for Atmospheric Research Mesoscale Model (MM5), Sparse Matrix Operator Kernel Emissions (SMOKE) modeling system, and the US Environmental Protection Agency Community Multiscale Air Quality (CMAQ) Model. Keeping chemical initial and boundary conditions, land use, and anthropogenic area and point source emissions fixed, this modeling system was applied over five summers (June–August) from 1993 to 1997 and five summers from 2053 to 2057. Over these eastern US watersheds, the modeling system estimated 3–14% increases in summertime N deposition as a result of climate change. This increase is primarily due to the direct effects of climate change on atmospheric conditions and chemistry. Wet N deposition is predicted to increase as a result of increased precipitation, while dry N deposition is predicted to increase as higher surface temperatures favor gas-phase nitric acid to particulate nitrate. The simulated increase suggests that additional reductions in N oxides and/or ammonia may be needed to fully realize the anticipated benefits of planned reduction strategies...

Simulating Regional-Scale Ozone Climatology over the Eastern United States: Model Evaluation Results

Hogrefe, C.; Biswas, J.; Lynn, B.; Civerolo, K.; Ku, J.-Y.; Klein-Rosenthal, Joyce Ellen; Rosenzweig, C.; Goldberg, R.; Kinney, P.L.
Fonte: Elsevier BV Publicador: Elsevier BV
Tipo: Artigo de Revista Científica
EN_US
Relevância na Pesquisa
17.99%
To study the potential impacts of climate change on air quality and public health over the eastern United States, a coupled global/regional-scale modeling system consisting of the NASA-Goddard Institute for Space Studies Atmosphere–Ocean model, the MM5 mesoscale meteorological model and the Community Multiscale Air Quality (CMAQ) model for air quality has been developed. Evaluation results of the modeling system used to simulate climate and ozone air quality over the eastern United States during the five summers of 1993–1997 are presented in this paper. The results indicate that MM5 and CMAQ capture interannual and synoptic-scale variability present in surface temperature and ozone observations in the current climate, while the magnitude of fluctuations on shorter time scales is underestimated. A comparison of observed and predicted spatial patterns of daily maximum ozone concentrations shows best performance in predicting patterns for average and above-average ozone concentrations. The frequency distributions of the duration of extreme heat and ozone events show similar features for both model predictions and observations. Finally, application of a synoptic map-typing procedure reveals that the MM5/CMAQ system succeeded in simulating the average ozone concentrations associated with several frequent pressure patterns...

Air Pollution Metric Analysis While Determining Susceptible Periods of Pregnancy for Low Birth Weight

Warren, Joshua L.; Fuentes, Montserrat; Herring, Amy H.; Langlois, Peter H.
Fonte: Hindawi Publishing Corporation Publicador: Hindawi Publishing Corporation
Tipo: Artigo de Revista Científica
Publicado em 30/01/2013 EN
Relevância na Pesquisa
17.99%
Multiple metrics to characterize air pollution are available for use in environmental health analyses in addition to the standard Air Quality System (AQS) pollution monitoring data. These metrics have complete spatial-temporal coverage across a domain and are therefore crucial in calculating pollution exposures in geographic areas where AQS monitors are not present. We investigate the impact that two of these metrics, output from a deterministic chemistry model (CMAQ) and from a spatial-temporal downscaler statistical model which combines information from AQS and CMAQ (DS), have on risk assessment. Using each metric, we analyze ambient ozone's effect on low birth weight utilizing a Bayesian temporal probit regression model. Weekly windows of susceptibility are identified and analyzed jointly for all births in a subdomain of Texas, 2001–2004, and results from the different pollution metrics are compared. Increased exposures during weeks 20–23 of the pregnancy are identified as being associated with low birth weight by the DS metric. Use of the CMAQ output alone results in increased variability of the final risk assessment estimates, while calibrating the CMAQ through use of the DS metric provides results more closely resembling those of the AQS. The AQS data are still preferred when available.

Caliope: an operational air quality forecasting system for the Iberian Peninsula, Balearic Islands and Canary Islands – first annual evaluation and ongoing developments

Baldasano, J. M.; Jiménez-Guerrero, P.; Jorba, O.; Pérez, C.; López, E.; Güereca, P.; Martín, F.; Vivanco, M. G.; Palomino, I.; Querol, Xavier; Pandolfi, M.; Sanz, M. J.; Diéguez, J. J.
Fonte: Copernicus Publications Publicador: Copernicus Publications
Tipo: Artículo Formato: 705431 bytes; application/pdf
ENG
Relevância na Pesquisa
17.43%
10 pages, 4 figures, 2 tables.-- Contributed to: 7th EMS Annual Meeting and 8th European Conference on Applications of Meteorology 2007 (San Lorenzo de El Escorial, Spain, Oct 1-5, 2007).; The Caliope project funded by the Spanish Ministry of the Environment establishes an air quality forecasting system for Spain to increase the knowledge on transport and dynamics of pollutants in Spain, to assure the accomplishment of legislation and to inform the population about the levels of pollutants, topics in which the European Commission has shown a great concern. The present contribution describes the first quantitative verification study performed so far with two chemistry transport models (CMAQ and CHIMERE) for a reference year (2004) at medium spatial resolution (around 20×20 km for the Iberian Peninsula). Both models perform similarly in the case of ground-level ozone. The mean normalised gross error MNGE remains below 15–20% during summertime, when ozone episodes occur, outlining the good skills of the system concerning the forecasting of air quality in Spain. Furthermore, the ongoing developments of the system towards high resolution modelling (4×4 km for Spain, 12×12 km for Europe, 1 h temporal resolution) and the integration with observations within the Caliope umbrella are described.; This work is funded by the Caliope project of the Spanish Ministry of the Environment (441/2006/3-12.1 and A357/200/2-12.1). CMAQ and DREAM simulations were performed in the MareNostrum supercomputer hosted by the Barcelona Supercomputing Center (BSC).; Peer reviewed

Understanding the impact of recent advances in isoprene photooxidation on simulations of regional air quality

Xie, Y.; Carter, W. P. L.; Nolte, C. G.; Luecken, D. J.; Hutzell, W. T.; Wennberg, P. O.; Cohen, R. C.; Pinder, R. W.
Fonte: Copernicus Publicador: Copernicus
Tipo: Article; PeerReviewed Formato: application/pdf
Publicado em //2013
Relevância na Pesquisa
17.43%
The CMAQ (Community Multiscale Air Quality) us model in combination with observations for INTEX-NA/ICARTT (Intercontinental Chemical Transport Experiment–North America/International Consortium for Atmospheric Research on Transport and Transformation) 2004 are used to evaluate recent advances in isoprene oxidation chemistry and provide constraints on isoprene nitrate yields, isoprene nitrate lifetimes, and NO_x recycling rates. We incorporate recent advances in isoprene oxidation chemistry into the SAPRC-07 chemical mechanism within the US EPA (United States Environmental Protection Agency) CMAQ model. The results show improved model performance for a range of species compared against aircraft observations from the INTEX-NA/ICARTT 2004 field campaign. We further investigate the key processes in isoprene nitrate chemistry and evaluate the impact of uncertainties in the isoprene nitrate yield, NO_x (NO_x = NO + NO_2) recycling efficiency, dry deposition velocity, and RO_2 + HO_2 reaction rates. We focus our examination on the southeastern United States, which is impacted by both abundant isoprene emissions and high levels of anthropogenic pollutants. We find that NO_x concentrations increase by 4–9% as a result of reduced removal by isoprene nitrate chemistry. O3 increases by 2 ppbv as a result of changes in NO_x. OH concentrations increase by 30%...

Role of isoprene in secondary organic aerosol formation on a regional scale

Zhang, Yang; Huang, Jian-Ping; Henze, Daven K.; Seinfeld, John H.
Fonte: American Geophysical Union Publicador: American Geophysical Union
Tipo: Article; PeerReviewed Formato: application/pdf
Publicado em 23/10/2007
Relevância na Pesquisa
17.43%
The role of isoprene as a source of secondary organic aerosol (SOA) is studied using laboratory-derived SOA yields and the U.S. Environmental Protection Agency regional-scale Community Multiscale Air Quality (CMAQ) modeling system over a domain comprising the contiguous United States, southern Canada, and northern Mexico. Isoprene is predicted to be a significant source of biogenic SOA, leading to increases up to 3.8 μg m^(−3) in the planetary boundary layer (PBL, defined as 0–2.85 km) and 0.44 μg m^(−3) in the free troposphere over that in the absence of isoprene. While the addition of isoprene to the class of SOA-forming organics in CMAQ increases appreciably predicted fine-particle organic carbon (OC_(2.5)) in the eastern and southeastern U.S., total OC_(2.5) is still underpredicted in these regions. SOA formation is highly sensitive to the value of the enthalpy of vaporization of the SOA. The role of isoprene SOA is examined in a sensitivity study at values of 42 and 156 kJ mol^(−1); both are commonly used in 3-D aerosol models. Prediction of ambient levels of SOA in atmospheric models remains a challenging problem because of the importance of emissions inventories for SOA-forming organics, representation of gas phase atmospheric chemistry leading to semivolatile products...