Simulating mesoscale transport and diffusion of radioactive noble gases using the Lagrangian particle dispersion model

In order to simulate the impact of mesoscale wind fields and to assess potential capability of atmospheric Lagrangian particle dispersion model (LPDM) as an emergency response model for the decision supports, two different simulations of LPDM with the mesoscale prognostic model MM5 (Mesoscale Model ver. 5) were driven. The first simulation of radioactive noble gas ((85)Kr exponent) emitted during JCO accident occurred from 30 September to 3 October 1999 at Tokai, Japan showed that the first arriving short pulse was found in Tsukuba located at 60km away from the accidental area. However, the released radioactive noble gas was transported back to the origin site about 2 days later due to the mesoscale meteorological wind circulation, enhancing the levels of (85)Kr with the secondary peak in Tsukuba. The second simulation of atmospheric dilution factors (the ratio of concentration to the emission rate, chi/Q), during the underground nuclear test (UNT) performed by North Korea showed that high chi/Q moved to the eastward and extended toward southward in accordance with the mesoscale atmospheric circulations generated by mesoscale prognostic model MM5. In comparison with the measurements, the simulated horizontal distribution patterns of (85)Kr during the JCO are well accord with that of observation in Tsukuba such as the existence of secondary peak which is associated with the mesoscale circulations. However, the simulated level of (85)Kr anomaly was found to be significantly lower than the observations, and some interpretations on these discrepancies were described. Applications of LPDM to two mesoscale emergency response dispersion cases suggest the potential capability of LPDM to be used as a decision support model provided accurate emission rate of accident in case of a large accident.     

青海高原一次沙尘重污染天气成因分析

利用常规观测的卫星云图资料、地面资料、探空资料、地面污染物监测数据,结合拉格朗日粒子扩散模型(LPDM)污染源溯源方法,对2018年2月青海高原一次沙尘重污染天气的主要成因以及沙尘传输特征进行了分析。结果表明:此次重污染天气受高空低槽东移影响,在300~700 hPa形成了强烈的辐散下沉,槽后的高空急流随之东移。在其东移过程中,受高空急流动量下传及偏北气流中的冷空气共同作用,青海东部出现了大风沙尘天气。边界层中逆温层的存在是此次污染天气持续的重要原因之一,加之未出现明显降水,不利于大气污染物的扩散。通过运用LPDM对此次污染天气的运动轨迹进行分析来看,气团影响的模拟高度层距离地面100 m,气团层趋势一致。研究区地处青藏高原,海拔较高,0~100 m高度的气团足迹可以反映出PM 10污染气团的输送路径。同时,0~100 m是主要的人为源排放空间,也是对人类活动影响较大的区域。气团足迹与PM 10浓度的变化趋势一致,即青海东部沙尘污染主要是由河西走廊沙尘倒灌进入青海东部导致,这与天气学分析结果一致。     

G20峰会期间杭州市大气区域输送特征研究

利用拉格朗日扩散模型评估G20峰会期间杭州市大气区域输送特征，结果表明，G20峰会开幕期间杭州市的气团来源由西南内陆转为杭州湾和东海地区，且传输速度较快，空气污染得到显著清除。保障期间污染情形下，苏北、安徽、江西等地的气团输送更强，浙北和苏南地区输送减弱。在管控情形下，浙北的PM_2.5一次排放潜在贡献降低了15%，减排管控措施有效降低了周边地区一次排放对杭州市的空气污染输送。1981—2016年G20峰会历史同期，浙江省对杭州市的气团贡献年际变化幅度为26%~85%，平均贡献为63%。     

基于OCO-2卫星观测的浙江省典型城市CO2柱浓度变化特征及碳排放重点源识别应用

为有效制定城市层面的低碳发展政策，实现碳达峰的发展目标，利用碳卫星2号（OCO-2）监测的高分辨率大气CO₂柱浓度数据（XCO₂），分析浙江省杭州、宁波和嘉兴3个典型城市的XCO₂变化特征，以及人类活动和XCO₂变化的关系；识别城市碳排放热点区域，评估碳排放热点源对XCO₂的影响，并利用拉格朗日粒子扩散模型（LPDM）进行验证。结果表明：（1）2016—2021年3个城市的XCO₂年增长量分别为3.1×10^-6，2.3×10^-6和2.2×10^-6，杭州的增长量最为明显；杭州和宁波在2019—2021年XCO₂增量明显，分别为8.0×10^-6和5.7×10^-6。杭州XCO₂的变化趋势与临安大气本底站CO₂观测数据的变化趋势一致。（2）与2017年相比，3个城市的建筑用地面积都略有增加，分别增加了0.9%，2.2%和4.8%；从人口和GDP数据来看，2016—2021年3个城市也均呈持续增加的变化趋势。表明CO₂浓度升高与人类活动密切相关。（3）XCO₂正距平高值区域基本都对应了碳排放热点源（电力企业）的下风向地区，电力企业CO₂的排放会导致下风向地区的XCO₂出现局地性增长，增量为7×10^-6～9×10^-6。