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1.
苏州市一次重霾污染天气过程的数值模拟 总被引：1，自引：1，他引：0
本文对苏州地区2015年12月13—15日发生的一次典型的重霾污染天气过程进行了数值模拟,分析了颗粒物及其组分的时空变化特征及其气象影响因子,以期为该区域空气污染治理和预防提供科学依据。结果表明:(1)利用WRF-Chem模式对此次重霾污染天气过程的污染气体成分进行数值模拟后发现,小时平均的PM_(2.5)、PM_(10)、CO、SO_2、NO_2模拟值与实测值的相关系数较高,达到0.68以上,通过了P0.01的显著性检验,且日变化过程对应也较好。(2)通过分析此次污染过程的天气背景,发现污染形成期高空环流比较平直,中层为均匀的弱高压控制,地面受弱高压脊控制,这种形势容易导致颗粒物的堆积。后期地面等压线密集时,风速大,有利于污染物的输送与扩散。(3)通过分析此次污染过程期间气象要素的变化发现,有逆温、风速小、相对湿度大等不利的气象条件是导致此次污染过程发生的重要原因之一。(4)HYSPLIT轨迹分析显示,此次重霾过程主要受北方大范围灰霾颗粒物南下影响,北方污染气团逐步南推,14至15日本地大气扩散条件差、污染物累积,最终导致本地污染加重,从而发生重霾事件。(5)火点图的分布进一步验证了此次重霾污染过程是由外来污染气团输入所导致。 相似文献
2.
ABSTRACTWidespread forest fire events occurred in the foothills of North Western Himalaya during 24 April to 2 May 2016 (Event-1) and 20–30 May 2018 (Event-2). Their impacts were investigated on the distribution of pollutant gases ozone (O3), carbon monoxide (CO), and oxides of nitrogen (NOx) over Uttarakhand using simulations of Weather Research and Forecasting model coupled with chemistry (WRF-Chem) and in-situ observations of these gases over Dehradun, the capital of Uttarakhand. During Event-1, the observed CO mixing ratio over Dehradun increased from 25 April 2016 onwards, attained maximum (705.8 ± 258 ppbv) on 2 May 2016 and subsequently decreased. The rate of increase of daily baseline CO was 29 ppbv/day during HFAP (High Fire Activity Period). During Event-2, daily average concentrations of CO, O3, and NOx showed systematic increase over Dehradun during HFAP period. The rate of increase of CO was 9 ppbv/day, while it was very small for NOx and O3. To quantitatively estimate the influence of forest fire emissions, two WRF-Chem simulations were made: one with biomass burning (BB) emissions and other without BB emissions. These simulations showed 52% (34%) enhancement in CO, 52% (32%) enhancement in NOx, and 11% (9%) enhancement in O3 during HFAP for Event-1 (Event-2). A clear positive correlation (r = 0.89 for Event-1, r = 0.69 for Event-2) was found between ?O3 (O3with BB minus O3without BB) and ?CO (COwith BB minus COwithout BB), indicating rapid production of ozone in the fire plumes. For both the events, the vertical distribution of ?O3, ?CO, and ?NOx showed that forest fire emissions influenced the air quality upto 6.5 km altitude. Peaks in ?O3, ?CO, and ?NOx during different days suggested the role of varying dispersion and horizontal mixing of fire plumes. 相似文献
3.
Urban air pollution in Pakistan is a serious challenge and it causes significant damage to human health and ecosystems. This paper presents a modelling study using the Weather Research and Forecasting Model coupled with Chemistry(WRF-Chem) to simulate the spatial distributions and temporal variations of aerosol concentrations over Pakistan, focusing on contributions of domestic emission sectors(transport, industry, residential, and energy) to mass concentrations of sulfate(SO2–4), nitrate(NO–3), ammonium(NH+4), black carbon(BC), and organic carbon(OC) during the months of January, April, July, and October in 2010. Sensitivity studies indicate that, averaged over January, April, July, and October of 2010, energy and industry sectors have the largest contributions to SO2–4 concentrations, each of which contributes about 10%?20% to SO2– 4over the polluted eastern Pakistan. The contributions from residential and transport sectors to NO–3 concentrations reach 40%?50% in central Pakistan. The residential sector has the highest contribution of 50%–80% to BC and OC loading in northeastern and southern Pakistan. Examination of sector contributions to aerosol levels in Lahore, the most polluted city in Pakistan, suggests that reductions in emissions in the residential sector should be an efficient measure for improving particulate matter air quality in this region. 相似文献
4.
利用WRF-Chem大气化学模式,选择2015年12月中旬发生在我国的大范围空气污染过程,在采用同样化学方案条件下,针对模式中不同物理过程及其参数化方案开展了地面PM_(2.5)预报的敏感性试验。结果表明:该模式能较好展示此次PM_(2.5)污染的演变过程,与实况也较接近,但对青海经宁夏至内蒙的PM_(2.5)高值区出现了漏报现象,这可能是模式外边界未对污染物做更新所致。对地面PM_(2.5)的预报,各物理过程的敏感度不同,边界层(含近地面层)过程的影响要明显大于积云对流及微物理过程的影响,不同的参数化方案会造成不同的预报误差。边界层过程QNSE和与其配套的近地面层方案的组合是预报的较佳组合;而TEMF和与其配套的组合以及ACM2和Pleim-X的组合则不佳。合理的物理过程参数化方案有助于提高PM_(2.5)预报质量。模式预报对排放源也有适应过程,其Spin-up时间较气象要素长。 相似文献
5.
A coupled meteorology and aerosol/chemistry model WRF-Chem(Weather Research and Forecast model coupled with Chemistry) was used to conduct a pair of simulations with present-day(PD) and preindustrial(PI) emissions over East Asia to examine the aerosol indirect effect on clouds.As a result of an increase in aerosols in January,the cloud droplet number increased by 650 cm-3 over the ocean and East China,400 cm-3 over Central and Southwest China,and less than 200 cm-3 over North China.The cloud liquid water path(LWP) increased by 40-60 g m-2 over the ocean and Southeast China and 30 g m-2 over Central China;the LWP increased less than 5 g m-2 or decreased by 5 g m-2 over North China.The effective radius(Re) decreased by more than 4 μm over Southwest,Central,and Southeast China and 2μm over North China.In July,variations in cloud properties were more uniform;the cloud droplet number increased by approximately 250-400 cm-3,the LWP increased by approximately 30-50 g m-2,and Re decreased by approximately 3 ?m over most regions of China.In response to cloud property changes from PI to PD,shortwave(SW) cloud radiative forcing strengthened by 30 W m-2 over the ocean and 10 W m-2 over Southeast China,and it weakened slightly by approximately 2-10 W m-2 over Central and Southwest China in January.In July,SW cloud radiative forcing strengthened by 15 W m-2 over Southeast and North China and weakened by 10 W m-2 over Central China.The different responses of SW cloud radiative forcing in different regions was related to cloud feedbacks and natural variability. 相似文献
6.
以粤港澳大湾区为例,利用卫星遥感资料结合大气化学模式模拟,分析2003―2018年城市热岛强度、气溶胶光学厚度的变化规律,定性和定量研究气溶胶对白天城市热岛强度的影响。结果表明：2003―2018年粤港澳大湾区城市热岛强度呈波动上升趋势,夏季热岛强度最大,冬季热岛强度最小;气溶胶光学厚度呈波动下降趋势,春季气溶胶光学厚度最大,冬季气溶胶光学厚度最小。在年际和季节尺度,城市热岛强度与城区、郊区气溶胶光学厚度之差均呈弱的正相关。基于WRF-Chem的模拟实验表明,气溶胶的存在导致城区、郊区地表向下总辐射减少、地表温度降低,且城区地表向下总辐射减少多于郊区、降温幅度大于郊区,进而导致了热岛强度减弱。气溶胶对城市热岛强度的贡献率为?2.187%,冬季贡献率绝对值略高于夏季。 相似文献
7.
应用大气化学模式WRF-Chem(Weather Research and Forecast-Chemistry),分别选用亚洲排放源清单INTEX-B(Intercontinental Chemical Transport Experiment-Phase B)、REASv2.1(Regional Emission inventory in Asia version 2.1)以及全球排放源清单HTAP_v2(Hemispheric Transport of Air Pollution version 2),对浙江省2013年12月进行模拟,分别记为IN、RE和HT试验,研究人为源排放清单对大气污染物浓度数值模拟的影响。结果表明,3组试验合理的反映出PM2.5(空气动力学当量直径小于等于2.5μm的颗粒物,即细颗粒物)、PM10(空气动力学当量直径小于等于10μm的颗粒物,即可吸入颗粒物)和NO_2近地面浓度的时空分布特征,相关系数为0.5~0.8,85%以上的模拟值落在观测值的0.5~2倍范围内,但对SO_2近地面浓度模拟较差。IN、RE、HT试验对PM2.5和PM10的模拟偏差均成递减趋势,约为30%、16%和6%,HT试验的模拟值更加接近观测。INTEX-B清单中PM2.5的一次排放与二次气溶胶前提物SO_2均高于REAS与HTAP清单,因此会导致更多的硫酸盐生成,从而进一步增加PM2.5浓度。HTAP_v2清单中较低的NH3排放会抑制硝酸盐的生成,从而有助于降低PM2.5浓度。3个清单的基准年与模拟年的差异对SO_2浓度模拟的准确性影响更大,INTEX-B清单中SO_2排放量明显高于REASv2.1与HTAP_v2清单,尤其在浙北和沿海工业发达地区,导致IN试验模拟的SO_2在这些地区存在明显高估。3组试验模拟的NO_2浓度偏差最小且更为接近(-8%~4%),主要原因是3个清单在浙江省的NOx排放十分一致。从3组试验结果之间的差异程度来看,浙江省范围内PM2.5、PM10、SO_2和NO_2逐日浓度模拟值之间的平均差异程度分别约为14%、15%、51%和16%,最大差异程度分别为69%、78%、137%和132%。月均浓度与逐日浓度的平均差异程度基本一致,但最大差异程度明显更低。总体来看3组试验模拟的PM2.5、PM10与NO_2的差异程度明显低于SO_2。 相似文献
8.
The lake-breeze at Taihu Lake generates a different specific heat capacity between the water body and the surrounding land. Taihu Lake has a significant impact on the atmospheric conditions and the air quality in the Yangtze River Delta. This phenomenon is referred to as the Taihu Lake effect. In this study, two simulations were conducted to determine the impact of the Taihu Lake effect in the reference experiment(R-E) and sensitivity experiments(NO TH). The control simulations demonstrated that the meteorological field and the spatial distribution of ozone(O3) concentrations over Taihu lake obviously changed once the land-use type of water body was substituted by cropland. The surface temperature of Taihu Lake was reduced under the impact of Taihu Lake, and a huge temperature difference caused a strong lake-breeze effect. The results also showed that the difference in the average concentrations of O3 between the R-E and NO TH experiments reached 12 ppbv in most areas of Taihu Lake, all day, on 20 May 2014. During daytime(0800–1600 LST, LST=UTC+8), the influence of the Taihu Lake effect on O3 in the Suzhou region was not significant. However, the influence of the Taihu Lake effect on O3 in the Suzhou region was obvious during nighttime(1800–2400 LST). The larger changes in the physical and chemical processes were horizontal and vertical advections under the influence of the Taihu Lake effect in Taihu Lake. 相似文献
9.
The Saharan dust event that occurred between the 22nd and 30th of June 2012 influenced the atmospheric radiative properties over North Africa, the Iberian Peninsula, the Western Mediterranean basin, extending its effects to France and Southern England. This event is well documented in satellite imagery, as well as on the air quality stations over the Iberian Peninsula and the AERONET NASA network. In order to assess the effect of the model vertical resolution on the extinction coefficient fields, as a proxy to the particulate matter concentrations in the atmosphere, the WRF-Chem model was applied during this period over a mother domain with a resolution of 18 km, covering Europe and North Africa. To this end five model setups differing in the number of vertical levels were tested. Model skills were evaluated by comparing the model results with CALIPSO and EARLINET LIDAR data. Results show that the model is able to simulate the higher level aerosol transport but it is susceptible to the vertical resolution used. This is due to the thickness of the transport layers which is, eventually, thinner than the vertical resolution of the model. When comparing model results to the observed vertical profiles, it becomes evident that the broad features of the extinction coefficient profile are generally reproduced in all model configurations, but finer details are captured only by the higher resolution simulations. 相似文献
10.
基于WRF/Chem（Weather Research Forecasting/Chemistry）模式对2015年11月25日至12月2日我国北方一次大范围PM2.5（空气动力学当量直径小于等于2.5 μm的颗粒物,即细颗粒物）重污染过程进行了模拟。与观测资料对比表明,模式能够较好地模拟出PM2.5浓度及气象因素的变化趋势,结果适用于此次污染事件的机理分析。动力、热力条件及化学转化等因素对此次强污染事件形成的机理分析表明,动力因子主要通过表面风和垂直风切变的减弱对此次污染事件造成影响,边界层逆温等热力因子促进了大气稳定性的增强,不利于污染物扩散。依据PM2.5组成成分变化分析可知,硝酸盐、硫酸盐和有机碳在此次事件中含量增加,说明机动车汽车尾气和燃煤排放所致的二次气溶胶生成对PM2.5污染加剧起重要贡献。多元线性回归分析和多因子相对贡献率量化解析结果表明,热力因子在此次污染过程中起主要作用,方差贡献率为52%,动力因子次之,方差贡献率为34%,而化学转化方差贡献率约为14%,说明气象条件,尤其是热力条件是引起此次污染事件的主要原因。 相似文献