An evaluation of real-time air quality forecasts and their urban emissions over eastern Texas during the summer of 2006 Second Texas Air Quality Study field study

被引:48
|
作者
McKeen, S. [1 ,2 ]
Grell, G. [1 ,7 ]
Peckham, S. [1 ,7 ]
Wilczak, J. [5 ]
Djalalova, I. [1 ,5 ]
Hsie, E. -Y. [1 ,2 ]
Frost, G. [1 ,2 ]
Peischl, J. [1 ,2 ]
Schwarz, J. [1 ,2 ]
Spackman, R. [1 ,2 ]
Holloway, J. [1 ,2 ]
de Gouw, J. [2 ]
Warneke, C. [1 ,2 ]
Gong, W. [6 ]
Bouchet, V. [3 ]
Gaudreault, S. [3 ]
Racine, J. [3 ]
McHenry, J. [10 ]
McQueen, J. [11 ]
Lee, P. [8 ]
Tang, Y. [11 ]
Carmichael, G. R. [4 ]
Mathur, R. [9 ]
机构
[1] Univ Colorado, Cooperat Inst Res Environm Sci, Boulder, CO 80309 USA
[2] NOAA, Div Chem Sci, Earth Syst Res Lab, Boulder, CO 80305 USA
[3] Environm Canada, Meteorol Serv Canada, Dorval, PQ H9P 1J3, Canada
[4] Univ Iowa, Ctr Global & Reg Environm Res, Iowa City, IA 52242 USA
[5] NOAA, Div Phys Sci, Earth Syst Res Lab, Boulder, CO 80305 USA
[6] Environm Canada, Sci & Technol Branch, Toronto, ON M3H 5T4, Canada
[7] NOAA, Global Sci Div, Earth Syst Res Lab, Boulder, CO 80305 USA
[8] NOAA, Air Resources Lab, Silver Spring, MD 20910 USA
[9] US EPA, Natl Exposure Res Lab, Res Triangle Pk, NC 27711 USA
[10] N Carolina Supercomp Ctr, Baron Adv Meteorol Syst, Res Triangle Pk, NC 27709 USA
[11] NOAA, Environm Modeling Ctr, Natl Ctr Environm Predict, Natl Weather Serv, Camp Springs, MD 20746 USA
关键词
SECONDARY ORGANIC AEROSOL; CHEMICAL-TRANSPORT MODEL; MULTISCALE GEM MODEL; OZONE FORMATION; UNITED-STATES; TRACE-P; PART I; HOUSTON; CHEMISTRY; ENSEMBLE;
D O I
10.1029/2008JD011697
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
Forecasts of ozone (O-3) and particulate matter (diameter less than 2.5 mu m, PM2.5) from seven air quality forecast models (AQFMs) are statistically evaluated against observations collected during August and September of 2006 (49 days) through the Aerometric Information Retrieval Now (AIRNow) network throughout eastern Texas and adjoining states. Ensemble O-3 and PM2.5 forecasts created by combining the seven separate forecasts with equal weighting, and simple bias-corrected forecasts, are also evaluated in terms of standard statistical measures, threshold statistics, and variance analysis. For O-3 the models and ensemble generally show statistical skill relative to persistence for the entire region, but fail to predict high-O-3 events in the Houston region. For PM2.5, none of the models, or ensemble, shows statistical skill, and all but one model have significant low bias. Comprehensive comparisons with the full suite of chemical and aerosol measurements collected aboard the NOAA WP-3 aircraft during the summer 2006 Second Texas Air Quality Study and the Gulf of Mexico Atmospheric Composition and Climate Study (TexAQS II/GoMACCS) field study are performed to help diagnose sources of model bias at the surface. Aircraft flights specifically designed for sampling of Houston and Dallas urban plumes are used to determine model and observed upwind or background biases, and downwind excess concentrations that are used to infer relative emission rates. Relative emissions from the U. S. Environmental Protection Agency 1999 National Emission Inventory (NEI-99) version 3 emissions inventory (used in two of the model forecasts) are evaluated on the basis of comparisons between observed and model concentration difference ratios. Model comparisons demonstrate that concentration difference ratios yield a reasonably accurate measure (within 25%) of relative input emissions. Boundary layer height and wind data are combined with the observed up-wind and downwind concentration differences to estimate absolute emissions. When the NEI-99 inventory is modified to include observed NOy emissions from continuous monitors and expected NOx decreases from mobile sources between 1999 and 2006, good agreement is found with those derived from the observations for both Houston and Dallas. However, the emission inventories consistently overpredict the ratio of CO to NOy. The ratios of ethylene and aromatics to NOy are reasonably consistent with observations over Dallas, but are significantly underpredicted for Houston. Excess ratios of PM2.5 to NOy reasonably match observations for most models but the organic carbon fraction of PM2.5 is significantly underpredicted, pointing to compensating error between secondary organic aerosol (SOA) formation and primary emissions within the models' photochemistry and emissions. Rapid SOA formation associated with both Houston and Dallas is inferred to occur within 1 to 3 h downwind of the urban centers, and none of the models reproduce this feature.
引用
收藏
页数:26
相关论文
共 50 条
  • [41] Evaluation of WRF-Chem air quality forecasts during the AEROMMA and STAQS 2023 field campaigns
    Acdan, Juanito Jerrold Mariano
    Pierce, R. Bradley
    Kuang, Shi
    McKinney, Todd
    Stevenson, Darby
    Newchurch, Michael J.
    Pfister, Gabriele
    Ma, Siqi
    Tong, Daniel
    JOURNAL OF THE AIR & WASTE MANAGEMENT ASSOCIATION, 2024, 74 (11) : 783 - 803
  • [42] An adjoint sensitivity analysis and 4D-Var data assimilation study of Texas air quality
    Zhang, Lin
    Constantinescu, E. M.
    Sandu, A.
    Tang, Y.
    Chai, T.
    Carmichael, G. R.
    Byun, D.
    Olaguer, E.
    ATMOSPHERIC ENVIRONMENT, 2008, 42 (23) : 5787 - 5804
  • [43] REAL-TIME FORECASTING METHOD OF URBAN AIR QUALITY BASED ON OBSERVATION SITES AND THIESSEN POLYGONS
    Liu, Xuefeng
    Ye, Fenxiao
    Liu, Yuling
    Xie, Xiange
    Fan, Jingjing
    INTERNATIONAL JOURNAL ON SMART SENSING AND INTELLIGENT SYSTEMS, 2015, 8 (04) : 2065 - 2082
  • [44] Urban air quality evaluation over Kut city using field survey and Geomatic techniques
    Mohammed, Zainab
    Ziboon, Abdulrazzak
    Kamal, Ali
    Alfaraj, Mahdi
    3RD INTERNATIONAL CONFERENCE ON BUILDINGS, CONSTRUCTION AND ENVIRONMENTAL ENGINEERING, BCEE3-2017, 2018, 162
  • [45] A real-time operational forecast model for meteorology and air quality during peak air pollution episodes in Oslo, Norway
    Berge, E
    Walker, SE
    Sorteberg, A
    Lenkopane, M
    Eastwood, S
    Jablonska, HI
    Koltzow, MO
    URBAN AIR QUALITY - RECENT ADVANCES, PROCEEDINGS, 2002, : 745 - 757
  • [46] Ventilation and Air Quality in Student Dormitories in China: A Case Study during Summer in Nanjing
    Yang, Zhe
    Shen, Jialei
    Gao, Zhi
    INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH, 2018, 15 (07)
  • [47] Characteristics of Ozone Concentrations around an Urban Valley based on the Intensive Air Quality Measurement during Spring and Summer of 2006
    Song, Sang-Keun
    Kim, Yoo-Keun
    Kang, Jae-Eun
    JOURNAL OF KOREAN SOCIETY FOR ATMOSPHERIC ENVIRONMENT, 2009, 25 (04) : 289 - 303
  • [48] The use of MM5-CMAQ air pollution modelling system for real-time and forecasted air quality impact of industrial emissions
    José, RS
    Pérez, JL
    González, RM
    Advances in Air Pollution Modeling for Environmental Security, 2005, 54 : 327 - 336
  • [49] Restricted Anthropogenic Activities and Improved Urban Air Quality in China: Evidence from Real-Time and Remotely Sensed Datasets Using Air Quality Zonal Modeling
    Rahaman, Saidur
    Jahangir, Selim
    Chen, Ruishan
    Kumar, Pankaj
    ATMOSPHERE, 2022, 13 (06)
  • [50] A Study of Traffic Emissions Based on Floating Car Data for Urban Scale Air Quality Applications
    Russo, Felicita
    Villani, Maria Gabriella
    D'Elia, Ilaria
    D'Isidoro, Massimo
    Liberto, Carlo
    Piersanti, Antonio
    Tinarelli, Gianni
    Valenti, Gaetano
    Ciancarella, Luisella
    ATMOSPHERE, 2021, 12 (08)