Yerramilli Anjaneyulu, Dodla Venkata Bhaskar Rao, Challa Venkata Srinivas, Myles Latoya, Pendergrass William R, Vogel Christoph A, Dasari Hari Prasad, Tuluri Francis, Baham Julius M, Hughes Robert L, Patrick Chuck, Young John H, Swanier Shelton J, Hardy Mark G
Trent Lott Geospatial and Visualization Research Center, College of Science Engineering and Technology, Jackson State University, Jackson, MS 39217 USA.
Air Qual Atmos Health. 2012 Dec;5(4):401-412. doi: 10.1007/s11869-010-0132-1. Epub 2011 Jan 14.
Fine particulate matter (PM(2.5)) is majorly formed by precursor gases, such as sulfur dioxide (SO(2)) and nitrogen oxides (NO(x)), which are emitted largely from intense industrial operations and transportation activities. PM(2.5) has been shown to affect respiratory health in humans. Evaluation of source regions and assessment of emission source contributions in the Gulf Coast region of the USA will be useful for the development of PM(2.5) regulatory and mitigation strategies. In the present study, the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model driven by the Weather Research & Forecasting (WRF) model is used to identify the emission source locations and transportation trends. Meteorological observations as well as PM(2.5) sulfate and nitric acid concentrations were collected at two sites during the Mississippi Coastal Atmospheric Dispersion Study, a summer 2009 field experiment along the Mississippi Gulf Coast. Meteorological fields during the campaign were simulated using WRF with three nested domains of 36, 12, and 4 km horizontal resolutions and 43 vertical levels and validated with North American Mesoscale Analysis. The HYSPLIT model was integrated with meteorological fields derived from the WRF model to identify the source locations using backward trajectory analysis. The backward trajectories for a 24-h period were plotted at 1-h intervals starting from two observation locations to identify probable sources. The back trajectories distinctly indicated the sources to be in the direction between south and west, thus to have origin from local Mississippi, neighboring Louisiana state, and Gulf of Mexico. Out of the eight power plants located within the radius of 300 km of the two monitoring sites examined as sources, only Watson, Cajun, and Morrow power plants fall in the path of the derived back trajectories. Forward dispersions patterns computed using HYSPLIT were plotted from each of these source locations using the hourly mean emission concentrations as computed from past annual emission strength data to assess extent of their contribution. An assessment of the relative contributions from the eight sources reveal that only Cajun and Morrow power plants contribute to the observations at the Wiggins Airport to a certain extent while none of the eight power plants contribute to the observations at Harrison Central High School. As these observations represent a moderate event with daily average values of 5-8 μg m(-3) for sulfate and 1-3 μg m(-3) for HNO(3) with differences between the two spatially varied sites, the local sources may also be significant contributors for the observed values of PM(2.5).
细颗粒物（PM₂.₅）主要由前驱气体形成，如二氧化硫（SO₂）和氮氧化物（NOₓ），这些气体主要来自密集的工业活动和交通活动。已有研究表明，PM₂.₅会影响人类呼吸系统健康。评估美国墨西哥湾沿岸地区的源区以及排放源贡献，将有助于制定PM₂.₅监管和减排策略。在本研究中，利用由天气研究与预报（WRF）模型驱动的混合单粒子拉格朗日积分轨迹（HYSPLIT）模型来确定排放源位置和传输趋势。在2009年夏季沿密西西比湾海岸进行的密西西比海岸大气扩散研究期间，在两个站点收集了气象观测数据以及PM₂.₅、硫酸盐和硝酸的浓度。利用WRF对活动期间的气象场进行了模拟，该模型有三个水平分辨率分别为36公里、12公里和4公里且垂直层数为43层的嵌套区域，并通过北美中尺度分析进行了验证。将HYSPLIT模型与从WRF模型导出的气象场相结合，通过反向轨迹分析来确定源位置。从两个观测位置开始，以1小时间隔绘制24小时周期的反向轨迹，以确定可能的源。反向轨迹清楚地表明源位于南和西之间的方向，因此源来自密西西比本地、相邻的路易斯安那州以及墨西哥湾。在所考察的作为源的两个监测站点半径300公里范围内的8座发电厂中，只有沃森、卡真和莫罗发电厂位于导出的反向轨迹路径上。利用HYSPLIT计算的向前扩散模式，从这些源位置中的每一个位置出发，使用根据过去年度排放强度数据计算出的每小时平均排放浓度进行绘制，以评估它们的贡献程度。对这8个源的相对贡献评估表明，只有卡真和莫罗发电厂在一定程度上对威金斯机场的观测值有贡献，而这8座发电厂中没有一座对哈里森中央高中的观测值有贡献。由于这些观测代表了一个中等事件，硫酸盐的日平均值为5 - 8μg m⁻³，硝酸为1 - 3μg m⁻³，且两个空间不同站点之间存在差异，本地源也可能是观测到的PM₂.₅值的重要贡献者。
