新冠肺炎疫情期间遵义市大气污染物的变化

为研究云贵高原城市遵义新冠期间大气污染物变化特征,利用2015—2020年遵义市空气质量监测数据、地面气象观测资料,分析新冠肺炎疫情防控期间遵义市主要大气污染物和气象要素的变化情况,研究空气质量对污染物减排和气象要素变化的响应。结果表明：疫情防控导致遵义市PM_2.5、PM₁₀和NO₂质量浓度明显下降,但O₃质量浓度小幅增加;PM_2.5和NO₂对人为减排的响应更敏感;防控期内遵义市气象条件比较有利于污染物的清除,防控减排措施导致PM_2.5质量浓度下降25.34%。在疫情防控的背景下,O₃浓度较2015—2019年明显偏高,PM_2.5显著下降,这与疫情防控期间人员车辆外出明显减少有关,导致夜间滴定消耗O₃的气体减少。减排措施对防控期间颗粒物污染浓度有明显的削弱作用。     

基于空气质量模拟的江苏省大气污染物排放清单比较研究

大气污染物排放清单是空气质量模拟和空气污染治理的重要依据.本研究比较分析了两套覆盖江苏省的2017年大气污染物排放清单，即分别由上海市环境科学研究院、江苏省环境科学研究院编制的"长三角清单"和"江苏省清单"，并结合区域空气质量模型CMAQ评估不同清单对长三角地区2017年1、4、7、10月的空气质量模拟的影响.清单比较结果表明，除二氧化硫（SO₂）以外，江苏省清单估算的各污染物排放量较长三角清单低.通过与观测数据比较，发现两套清单对SO₂、氮氧化物（NO_x）、臭氧（O₃）和细颗粒物（PM_2.5）的模型模拟性能均较好.江苏省清单与长三角清单两者的模拟结果空间分布接近，其中江苏省清单模拟的PM_2.5和O₃在长三角多数地区略低于长三角清单的模拟结果（1月O₃除外）.江苏省清单与长三角清单均能够用于空气质量模式模拟，可为江苏地区的细颗粒物和光化学烟雾污染的控制策略制定提供参考.     

武汉市大气污染变化趋势预测

以2014年武汉市大气污染源排放清单为基准,结合《武汉市城市空气质量达标规划（2013-2027年）》研究工作,预测了其实施后在控制"两高"行业新增产能、污染源综合治理、淘汰落后产能、控制机动车保有量等方面对武汉市SO₂、NO_x、PM₁₀、PM_2.5的减排量.利用嵌套网格空气质量预报模式系统（NAQPMS）,模拟分析了《达标规划》大气污染治理重点工程实施的空气质量改善效果.结果表明：《达标规划》实施后,2020年武汉市SO₂、NO₂、PM₁₀和PM_2.5排放量将分别比2014年削减22%~66%、6%~37%、14%~40%和17%~46%;武汉市空气质量有所改善,但NO₂和颗粒物年均浓度仍不能达到环境空气质量二级标准.     

2016年冬季南京地区大气污染特征的观测分析

基于2016年11月24日—12月23日南京市草场门站、鼓楼站和仙林站的强化试验观测资料,分析了城市和郊区主要大气污染物的时空变化特征及其与气象要素的相互关系。研究发现：观测期间南京PM_2.5、PM₁₀、NO₂、O₃、CO、SO₂月均质量浓度分别为52.84~84.34 μg·m^-3、88.36~120.34 μg·m^-3、49.98~51.66 μg·m^-3、24.85~50.57 μg·m^-3、0.99~1.2 mg·m^-3和22.1~26.48 μg·m^-3;近地面,城市大气污染物质量浓度高于郊区,其中城市O₃比郊区高61.0%;在城市地区,除NO₂和CO外,鼓楼站大气污染物质量浓度高于草场门站,其中鼓楼站PM_2.5比草场门站高42.7%;PM_2.5小时质量浓度最大为210.93 μg·m^-3,重污染过程出现时风速较低、温度较高,郊区PM₁₀、PM_2.5、NO₂质量浓度呈现高值时的最频风向为南风,O₃和SO₂质量浓度呈现高值时的最频风向分别为西风和西南风,所以郊区大气污染受城市输送影响。利用HYSPLIT模式研究发现12月4—8日和16—20日的污染气团分别来自西部和北方地区,聚类分析发现12月影响南京市的污染气团45%来自西部地区且移动速度较快,55%来自北方地区且移动速度较慢。由此可见,南京市冬季出现的大气污染,其形成不仅与本地排放和局地气象条件有关,而且西部和北方地区的远距离输送也会造成影响。     

城市下垫面影响空气污染的机制分析

本文采用RBLM-chem模式,利用杭州市高分辨率城市建筑等资料,定量分析城市动力效应、热力效应以及城市植被、人为热对SO₂、NO₂、O₃、PM_2.5等主要污染物浓度的影响。结果表明,城市化过程使得大部分城区温度上升约1℃,相对湿度下降约6%,风速下降约0.8 m·s^-1,湍流动能增强约0.03 m²·s^-2。城市动力效应主要通过降低城市风速,使得城区污染物浓度升高,SO₂浓度有近5 μg·m^-3的上升,PM_2.5、O₃浓度也有近15 μg·m^-3的上升。城市热力效应主要通过热岛环流使城区污染物向上输送,令地面污染物浓度降低,在城市大部分区域PM_2.5都有大约10 μg·m^-3的浓度下降。城市动力效应大于热力效应,城市的总体作用是使污染物浓度升高。城市下垫面使污染物浓度上升的另外一个机制是代替了自然有植被的下垫面,使污染物干沉降速度下降,但这一作用小于动力学效应。另一方面,人为热对城市主要污染物浓度都起着减小的作用,其中SO₂、NO₂、O₃、PM_2.5浓度降幅分别在2.5、3.0、6.0、10.0 μg·m^-3左右。城市植被可以显著增加污染物干沉降速度,使主要污染物SO₂、NO₂、O₃和PM_2.5的干沉降速度分别上升0.1、0.1、0.03、0.06 m·s^-1左右,相应地使上述污染物浓度分别下降2.5、6.0、4.0、6.0 μg·m^-3左右。     

关中5市环境空气质量特征与成因分析

基于国家生态环境部发布的环境空气质量监测数据等资料,采取调查研究与量化分析相结合的方法,对关中地区西安、渭南、咸阳、铜川、宝鸡5市空气质量的总体特征和空间差异进行研究.结果表明：颗粒污染物普遍严重超标,其中PM_2.5和PM₁₀分别超标91%和77%;空气污染具有明显的季节性,冬季的首要污染物是PM_2.5和PM₁₀,夏季的主要污染物是O₃;关中空气污染受地形、气象条件和工业排放、采暖、施工、道路扬尘、汽车尾气等人类活动综合影响,大气污染具有相似性,同时表现出一定的差异性.     

唐山市PM2.5和O3行业来源解析

京津冀位于华北平原腹地,面临着严重的空气污染问题,尤其是河北省的重点工业城市唐山,长期位于全国空气质量最差的前十名。为改善空气质量,过去的十多年间我国颁布实施了多项污染防治计划,但唐山的PM_2.5和夏季O₃浓度仍超国家标准。为此,使用WRF(Weather Research and Forecasting Model)-CMAQ(Community Multiscale Air Quality Model)模型量化了唐山市2020年PM_2.5和O₃浓度的行业贡献并分析其协同控制可行性。工业源对唐山市PM_2.5浓度贡献最大,约占45％,其次是居民源约占16％。冬季能源、居民源和农业源占比为全年最高,分别达17％、19％和11％。O₃浓度的背景值约占一半以上,4月占比最高。在非背景值中,唐山O₃浓度最大来源为工业源,约占53％,其次是交通源,约占22％。生物源、交通源和能源行业的贡献在7月有所上升,分别约10％、27％和20％。不同污染情景下对唐山市PM_2.5和O₃的来源比较发现,工业和能源是其最重要的共同来源。     

中美大气化学联合考察实验结果的初步分析与比较

根据临安区域本底站观测资料分析结果得出,中国中纬度地区秋、冬季O₃及其前体物NO_x等浓度偏高,可以对农作物和地表生态系统产生影响.观测结果表明:近地层大气O₃浓度主要决定于地面总辐射量控制下的光化学反应过程;O₃的生成受到前体物NO_x的控制,但O₃与NO_x存在着明显的非线性关系.从PEM-WESTA和B的实验及1995年的观测资料表明,O₃的生成效率随着NO_x浓度的增大而减小.尽管O₃的生成速率秋季比冬季的大,但由于秋季较高的NO_x抑制了过氧基的生成,因此冬季O₃的累积量几乎可以和秋季相比拟.在临安观测的NMHC和NO_x的比值比国外同纬度地区测值要大.这说明在临安本底站O₃的光化学生成中,NMHC不是控制物种.从而提示我们,在这些季节临安O₃光化学产物能够被NO_x浓度所控制.中美大气化学联合考察(PEM-WEST-B)实验期间,台湾省的卡盯站SO₂的平均浓度为0.29ppb,O₃的平均浓度为42.2ppb,可以认为此值为低纬度海岛的本底值.1994年PEM-WEST-B实验期间临安站的观测资料和台湾省的卡盯站资料相比,临安站SO₂的浓度约为卡盯站SO₂浓度的50倍左右,从而可以看出人类活动对大气本底的显着影响.     

冬季南京北郊大气气溶胶中水溶性阴离子特征

2009年冬季在南京北郊进行24 h采样,运用离子色谱法研究大气PM₁₀中水溶性阴离子的分布特征。结果表明:PM₁₀中阴离子的平均总质量浓度在白天和夜间分别为658.21、622.84 μg/m³;PM_2.1则分别为337.86、319.97 μg/m³,阴离子主要存在于细粒子中;主要水溶性阴离子均为SO₄^2-,且海盐对南京北郊大气PM₁₀和PM_2.1中的SO₄^2-质量浓度影响很小。SO₄^2-、Cl^-和F^-粒径谱分布相似,均呈双模态;NO₃^-和NO₂^-主要呈现单模态。SO₄^2-与NO₃^-、F^-与NO₃^-、SO₄^2-与Cl^-的相关系数均大于0.8,相关显著,说明其存在一定的同源性。NO₃^-/SO₄^2-的平均值在白天、夜间分别为0.058 2、0.048 4,说明南京北郊大气污染以固定源为主。分析NO₃^-、SO₄^2-前体物的转化率知道,采样期间SOR和NOR的平均值均大于10%,即SO₄^2-部分来源于SO₂的二次转化,而不是单一来源于一次污染物。     

武汉市冬季灰霾期PM2.5中水溶性无机离子的特征

2018年1月,利用颗粒物采样器采集武汉市大气PM_2.5样品并进行水溶性无机离子（F^-、Cl^-、NO₃^-、SO₄^2-、Na⁺、NH₄⁺、K⁺、Mg²⁺、Ca²⁺）的分析.结果表明,NO₃^-、SO₄^2-、NH₄⁺是PM_2.5中最主要的3种水溶性无机离子,除Mg²⁺与Ca²⁺外,PM_2.5与WSⅡs （水溶性无机离子）之间的相关性显著,且移动源贡献占主导地位.阴阳离子平衡表明武汉市冬季灰霾期PM_2.5呈中性或弱酸性.通过混合单粒子拉格朗日综合轨迹模式模拟并采用分层聚类得出了4种主要的后向气流轨迹及相应的PM_2.5和水溶性离子浓度,结果表明区域传输对此次灰霾期影响较大.     

CHARACTERISTICS AND TRENDS OF CLIMATIC EXTREMES IN CHINA DURING 1959–2014

The spatial and temporal variations of daily maximum temperature(Tmax), daily minimum temperature(Tmin), daily maximum precipitation(Pmax) and daily maximum wind speed(WSmax) were examined in China using Mann-Kendall test and linear regression method. The results indicated that for China as a whole, Tmax, Tmin and Pmax had significant increasing trends at rates of 0.15℃ per decade, 0.45℃ per decade and 0.58 mm per decade,respectively, while WSmax had decreased significantly at 1.18 m·s~(-1) per decade during 1959—2014. In all regions of China, Tmin increased and WSmax decreased significantly. Spatially, Tmax increased significantly at most of the stations in South China(SC), northwestern North China(NC), northeastern Northeast China(NEC), eastern Northwest China(NWC) and eastern Southwest China(SWC), and the increasing trends were significant in NC, SC, NWC and SWC on the regional average. Tmin increased significantly at most of the stations in China, with notable increase in NEC, northern and southeastern NC and northwestern and eastern NWC. Pmax showed no significant trend at most of the stations in China, and on the regional average it decreased significantly in NC but increased in SC, NWC and the mid-lower Yangtze River valley(YR). WSmax decreased significantly at the vast majority of stations in China, with remarkable decrease in northern NC, northern and central YR, central and southern SC and in parts of central NEC and western NWC. With global climate change and rapidly economic development, China has become more vulnerable to climatic extremes and meteorological disasters, so more strategies of mitigation and/or adaptation of climatic extremes,such as environmentally-friendly and low-cost energy production systems and the enhancement of engineering defense measures are necessary for government and social publics.     

Could the Recent Taal Volcano Eruption Trigger an El Ni?o and Lead to Eurasian Warming?

正The Taal Volcano in Luzon is one of the most active and dangerous volcanoes of the Philippines. A recent eruption occurred on 12 January 2020(Fig. 1a), and this volcano is still active with the occurrence of volcanic earthquakes. The eruption has become a deep concern worldwide, not only for its damage on local society, but also for potential hazardous consequences on the Earth's climate and environment.     

ANALYSIS OF “BIMODAL PATTERN” STORM ACTIVITY CHARACTERISTICS OF THE BAY OF BENGAL

Storms that occur at the Bay of Bengal (BoB) are of a bimodal pattern, which is different from that of the other sea areas. By using the NCEP, SST and JTWC data, the causes of the bimodal pattern storm activity of the BoB are diagnosed and analyzed in this paper. The result shows that the seasonal variation of general atmosphere circulation in East Asia has a regulating and controlling impact on the BoB storm activity, and the “bimodal period” of the storm activity corresponds exactly to the seasonal conversion period of atmospheric circulation. The minor wind speed of shear spring and autumn contributed to the storm, which was a crucial factor for the generation and occurrence of the “bimodal pattern” storm activity in the BoB. The analysis on sea surface temperature (SST) shows that the SSTs of all the year around in the BoB area meet the conditions required for the generation of tropical cyclones (TCs). However, the SSTs in the central area of the bay are higher than that of the surrounding areas in spring and autumn, which facilitates the occurrence of a “two-peak” storm activity pattern. The genesis potential index (GPI) quantifies and reflects the environmental conditions for the generation of the BoB storms. For GPI, the intense low-level vortex disturbance in the troposphere and high-humidity atmosphere are the sufficient conditions for storms, while large maximum wind velocity of the ground vortex radius and small vertical wind shear are the necessary conditions of storms.     

LOW-FREQUENCY CIRCULATION AND EXTENDED-RANGE FORECAST IN CONNECTION WITH AUTUMN EXTREME HEAVY RAINFALL PROCESS IN HAINAN

Observed daily precipitation data from the National Meteorological Observatory in Hainan province and daily data from the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis-2 dataset from 1981 to 2014 are used to analyze the relationship between Hainan extreme heavy rainfall processes in autumn (referred to as EHRPs) and 10–30 d low-frequency circulation. Based on the key low-frequency signals and the NCEP Climate Forecast System Version 2 (CFSv2) model forecasting products, a dynamical-statistical method is established for the extended-range forecast of EHRPs. The results suggest that EHRPs have a close relationship with the 10–30 d low-frequency oscillation of 850 hPa zonal wind over Hainan Island and to its north, and that they basically occur during the trough phase of the low-frequency oscillation of zonal wind. The latitudinal propagation of the low-frequency wave train in the middle-high latitudes and the meridional propagation of the low-frequency wave train along the coast of East Asia contribute to the ‘north high (cold), south low (warm)’ pattern near Hainan Island, which results in the zonal wind over Hainan Island and to its north reaching its trough, consequently leading to EHRPs. Considering the link between low-frequency circulation and EHRPs, a low-frequency wave train index (LWTI) is defined and adopted to forecast EHRPs by using NCEP CFSv2 forecasting products. EHRPs are predicted to occur during peak phases of LWTI with value larger than 1 for three or more consecutive forecast days. Hindcast experiments for EHRPs in 2015–2016 indicate that EHRPs can be predicted 8–24 d in advance, with an average period of validity of 16.7 d.     

AN ATTRIBUTION ANALYSIS OF CHANGES IN POTENTIAL EVAPOTRANSPIRATION IN THE BEIJING–TIANJIN–HEBEI REGION UNDER CLIMATE CHANGE

Based on the measurements obtained at 64 national meteorological stations in the Beijing–Tianjin–Hebei (BTH) region between 1970 and 2013, the potential evapotranspiration (ET0) in this region was estimated using the Penman–Monteith equation and its sensitivity to maximum temperature (Tmax), minimum temperature (Tmin), wind speed (Vw), net radiation (Rn) and water vapor pressure (Pwv) was analyzed, respectively. The results are shown as follows. (1) The climatic elements in the BTH region underwent significant changes in the study period. Vw and Rn decreased significantly, whereas Tmin, Tmax and Pwv increased considerably. (2) In the BTH region, ET0 also exhibited a significant decreasing trend, and the sensitivity of ET0 to the climatic elements exhibited seasonal characteristics. Of all the climatic elements, ET0 was most sensitive to Pwv in the fall and winter and Rn in the spring and summer. On the annual scale, ET0 was most sensitive to Pwv, followed by Rn, Vw, Tmax and Tmin. In addition, the sensitivity coefficient of ET0 with respect to Pwv had a negative value for all the areas, indicating that increases in Pwv can prevent ET0 from increasing. (3) The sensitivity of ET0 to Tmin and Tmax was significantly lower than its sensitivity to other climatic elements. However, increases in temperature can lead to changes in Pwv and Rn. The temperature should be considered the key intrinsic climatic element that has caused the "evaporation paradox" phenomenon in the BTH region.     

Revisiting the Concentration Observations and Source Apportionment of Atmospheric Ammonia

正While China’s Air Pollution Prevention and Control Action Plan on particulate matter since 2013 has reduced sulfate significantly, aerosol ammonium nitrate remains high in East China. As the high nitrate abundances are strongly linked with ammonia, reducing ammonia emissions is becoming increasingly important to improve the air quality of China. Although satellite data provide evidence of substantial increases in atmospheric ammonia concentrations over major agricultural regions, long-term surface observation of ammonia concentrations are sparse. In addition, there is still no consensus on     

COMPARATIVE ANALYSIS OF VARIOUS DATA OF AIR–SEA TEMPERATURE DIFFERENCE AND ITS VARIATION ACROSS SOUTH CHINA SEA IN THE PAST 35 YEARS

Using the International Comprehensive Ocean-Atmosphere Data Set(ICOADS) and ERA-Interim data, spatial distributions of air-sea temperature difference(ASTD) in the South China Sea(SCS) for the past 35 years are compared,and variations of spatial and temporal distributions of ASTD in this region are addressed using empirical orthogonal function decomposition and wavelet analysis methods. The results indicate that both ICOADS and ERA-Interim data can reflect actual distribution characteristics of ASTD in the SCS, but values of ASTD from the ERA-Interim data are smaller than those of the ICOADS data in the same region. In addition, the ASTD characteristics from the ERA-Interim data are not obvious inshore. A seesaw-type, north-south distribution of ASTD is dominant in the SCS; i.e., a positive peak in the south is associated with a negative peak in the north in November, and a negative peak in the south is accompanied by a positive peak in the north during April and May. Interannual ASTD variations in summer or autumn are decreasing. There is a seesaw-type distribution of ASTD between Beibu Bay and most of the SCS in summer, and the center of large values is in the Nansha Islands area in autumn. The ASTD in the SCS has a strong quasi-3a oscillation period in all seasons, and a quasi-11 a period in winter and spring. The ASTD is positively correlated with the Nio3.4 index in summer and autumn but negatively correlated in spring and winter.     

Analysis of Atmospheric Boundary Layer Height Characteristics over the Arctic Ocean Using the Aircraft and GPS Soundings

正ERRATUM to: Atmospheric and Oceanic Science Letters, 4(2011), 124-130 On page 126 of the printed edition (Issue 2, Volume 4), Fig. 2 was a wrong figure because the contact author made mistake giving the wrong one. The corrected edition has been updated on our website. The editorial office is sincerely sorry for any     

Index to Vol.31

正AN Junling;see LI Ying et al.;(5),1221—1232AN Junling;see QU Yu et al.;(4),787-800AN Junling;see WANG Feng et al.;(6),1331-1342Ania POLOMSKA-HARLICK;see Jieshun ZHU et al.;(4),743-754Baek-Min KIM;see Seong-Joong KIM et al.;(4),863-878BAI Tao;see LI Gang et al.;(1),66-84BAO Qing;see YANG Jing et al.;(5),1147—1156BEI Naifang;