呼和浩特市区污染状况分析

文章利用呼和浩特市2006—2009年环境监测点监测的SO2、NO2和PM10平均浓度资料进行统计分析,得到:(1)呼和浩特市SO2日平均浓度在0.017～0.188mg·m-3之间,超标率为4.0%,NO2在0.026～0.081mg·m-3之间,未超过国家二级标准,PM10在0.036～0.332mg·m-3之间,超标率达到6.5%;(2)污染物浓度最小的月份是7月、8月,最大的月份是1月和12月;(3)近年呼和浩特污染物浓度总体呈下降趋势。     

Particulate matter trends and quantification of the spring sand-dust contribution in Hohhot,Inner Mongolia,from 2013 to 2017

2013年9月国务院颁布了《大气污染防治行动计划》.研究其实施前后呼和浩特市大气污染物浓度变化及及原因;同时,分析了春季沙尘天气对于呼和浩特市大气环境颗粒物浓度的定量影响.结果表明:呼和浩特市大气环境质量持续改善,但大气污染物浓度仍然较高.PM2.5和PM10年均浓度分别超过国家二级标准22.9％和35.7％;2013-2017年春季PM2.5和PM10浓度降幅较大,沙尘天气对呼和浩特市PM2.5,PM10,和TSP浓度的绝对贡献范围分别在0.6-5.2μg m-3,9.0-16.9 μg m-3和 14.7-30.0 μg m-3.     

潍坊市区近10年空气质量与气象条件的关系

运用潍坊市环境监测中心站 1 993～ 2 0 0 2年的潍坊市区空气质量逐日监测资料与潍坊市气象局气象观测资料 ,分析了 1 0年间潍坊市区空气质量的时空特征、变化趋势及与气象条件的关系。结果表明 ,在影响潍坊市区空气质量的主要三种污染物———二氧化硫 (SO2 )、氮氧化物 (NOX)和总悬浮颗粒 (TSP)中总悬浮颗粒是首要污染物 ;三种污染物随季节的分布规律是 :冬半年 ( 1 1～ 4月 )偏多 ,夏半年 ( 5～ 1 0月 )偏少 ;三种污染物的变化趋势是随年代减少 ,年减少率SO2 为 0 0 0 54mg·m- 3,NOX 为0 0 0 1 6mg·m- 3,TSP为 0 0 0 6 2mg·m- 3。按国家标准分级 ,空气质量 3级以上 (API>1 0 0 )的日数占 33 5% ,年递减率为 5 96天。针对市区空气质量特征又重点分析了混合层高度、雾与其它天气现象 (烟尘、浮尘、扬沙 )与空气污染的关系。     

采暖期和非采暖期西安大气颗粒物中水溶性组分的化学特征

为了探讨采暖期和非采暖期西安大气颗粒物水溶性组分的化学特征和来源,分别于2005年冬季(2005年12月-2006年2月)和2006年夏季(6～8月)采集西安大气PM2.5和TSP样品,分析其中Na+、NH4+、K+、Mg2+、Ca2+、F-、Cl-、Br-、NO-2、NO-3和SO2-4共11种水溶性离子的浓度,并对其季节特征和来源进行了研究.结果显示,采暖期西安大气PM2.5和TSP中11种水溶性离子的平均浓度分别为53.2μg·m-3和110.3μg·m-3,非采暖期分别为51.3 μg·m-3和89.3μg·m-3.SO2-4、NO-3和NH+4在PM2.5和TSP中均为最主要的离子组分,浓度之和在采暖期分别占到PM2.5和TSP总离子浓度的78%和76%,在非采暖期则占到88%和76%.PM2.5和TSP中,NH+4、SO2-4和NO-3三者之间都有很好的相关性,其在颗粒物中的主要结合形式为(NH4)2SO4、NH4 HSO4和NH4 NO3.硫的转化率(SOR)和氮的转化率(NOR)在非采暖期明显大于采暖期,揭示SO2-4和NO-3的形成机制为气相氧化,主要受温度的控制.阴阳离子平衡和pH值测定的结果表明西安市大气PM2.5稍偏酸性,TSP为碱性,无论是粗、细粒子采暖期比非采暖期更偏酸性.对比10年前的研究结果,显示西安市大气污染控制措施大大降低了采暖期气溶胶中二次组分的污染程度,但主要污染排放源已逐渐由燃煤型向机动车排放转化.     

银川市大气颗粒物物理化学特征研究Ⅰ:大气颗粒物浓度特征

根据大量的大气环境监测资料,系统分析了银川市市区、郊区以及市中各功能区(居民区、商业区、文教区、工业区、交通区、娱乐区)大气颗粒物的TSP(TotalSuspendedParticles)、PM10(粒径小于等于10μm的粒子)和PM2.5(粒径小于等于2.5μm的粒子)质量浓度的季节分布、日变化以及随高度的分布特征。结果表明:银川市背景大气TSP平均值为0.126～0.248mg·m-3,低于国家三级污染标准;银川市区TSP日平均浓度的年平均值为0.47～0.78mg·m-3,超过国家二级标准0.57～1.6倍,超标率高达61.3%～92.5%,日均最大值超标7.9倍;春夏秋冬4季中,以冬春两季日平均浓度最高,其原因是燃煤取暖和沙尘暴多发。各功能区中商业区、交通区、居民区的TSP较高,这显然与人为活动、机动车辆排放密切相关,TSP日变化均呈现出与人为活动相一致的规律性;TSP的空间分布表明城市高于郊区,规模大、人口密度高、商业网点密集的城区TSP较高。各粒径粒子的质量浓度随高度递减,PM10占TSP的比例却随高度增加,说明PM10随高度增加。地面呼吸带高度上PM10和PM2.5均较高,可能与低空排放源有关。春季风沙期是大气污染最为严重的季节。     

我国地面O3、NOX、SO2背景值的观测研究

从1994年8月至1995年8月，在龙凤山、临安大气污染监测站和瓦里关大气本底基准观象台对O3、NOX及SO2首次进行了长期的连续观测。初步分析表明:3站地面O3的平均浓度、月际分布和日变化特征因地理环境、海拔高度和天气条件的不同，表现出明显的差异性。平均地面O3浓度，龙凤山为34.8×10-9,临安为39.1×10-9,瓦里关山为49.3×10-9,龙凤山和临安的月平均地面O3浓度分布较复杂，在6～7月和12月～1月较低，10月底～11月初较高。而在瓦里关山，月平均地面O3浓度变化较平稳，6月份最大，12月最小。龙凤山和临安地面O3平均日变化量较大，下午浓度最高，清晨最小；而瓦里关山地面O3平均日变化较小，上午浓度略低；NOX和SO2的分布具有明显的局地性特征，在龙凤山，临安和瓦里关山，3站的总平均浓度分别为2.7×10-9（NOX）和0.7×10-9(SO2),8.1×10-9(NOX)和16.1×10-9（SO2），0.04×10-9（NOX）和0.15×10-9（SO2）。     

春节期间禁燃烟花爆竹对南京市空气质量影响

利用2014年和2015年春节期间南京市城区与郊区主要污染物(PM10、PM2.5、SO2和NO2)浓度监测资料和气象观测资料,分析了禁燃烟花爆竹对南京市空气质量的影响。结果表明:2015年春节期间禁燃烟花爆竹对南京市空气质量改善显著。2015年春节期间,南京市AQI同比2014年春节期间下降了20%—30%,除夕至正月初三期间空气质量为优良;同时,SO2和NO2质量浓度变化幅度较小且均达到空气质量二级标准;PM10和PM2.5质量浓度变化趋势与2014年春节期间相反,且变化幅度比SO2和NO2质量浓度大,变化幅度分别为13.0—234.5μg·m-3和17.5—320.4μg·m-3。PM10和PM2.5是造成南京市春节期间空气质量污染的主要污染物,其中PM2.5所占比重较大,但2015年春节期间PM10和PM2.5最高小时浓度分别占2014年春节期间的51.0%、40.0%。此外,2015年春节期间南京市城区与郊区PM2.5浓度比2014年春节期间均降低且差异较小。春节期间气象因素对南京市污染物扩散具有较大影响,但禁燃烟花爆竹对PM2.5浓度的降低起决定性作用。     

乌鲁木齐市不同天气条件下TSP水溶性离子特征分析

利用2009年乌鲁木齐4个大气总悬浮颗粒物（TSP）观测站点样品,采用离子色谱仪测定了不同天气条件下TSP中水溶性离子成分,分析了水溶性离子变化特征及影响因素,结果表明：不同天气条件对乌鲁木齐市TSP中的NH4 、Ca2 、NO3-和SO42-浓度具有明显的影响。降水对离子有清除作用,使其在TSP中浓度减小。大风及沙尘天气使TSP中Ca2 浓度大幅增加,其它离子增加幅度很小。连续污染日,各离子在大气中累积至较高浓度,是同期晴天条件下的2-7倍。气象因素对采暖期TSP离子浓度变化影响较大。非采暖期乌鲁木齐市TSP离子浓度主要受到自然因素引起的土壤尘和建筑尘的影响。     

通辽市可吸入颗粒物质量浓度变化监测分析

文章基于通辽市2011年6月至2013年5月可吸入颗粒物质量浓度(PM10)资料数据,统计结果表明:(1)PM10年均质量浓度为85.92μg·m-3,未达到国家环境空气质量二级标准;(2)PM10季均质量浓度特征是春季冬季秋季夏季,PM10月平均质量浓度与季节分布基本一致;(3)PM10质量浓度在一周中呈现出单峰变化的特点,不同季节PM10质量浓度周变化不同;(4)PM10质量浓度日变化呈现双峰型分布。PM10浓度峰值从夏季到冬季逐渐推迟,这主要与日出日落时间和其他气象条件,以及上下班交通高峰相关;春季峰值还与沙尘天气发生时间有关。     

北京市2020年TSP水溶性离子特征研究

大气颗粒物中水溶性离子成分对大气中酸度变化有着重要影响,研究2020年疫情期间人们出行变化对TSP水溶性离子的影响,并对污染来源进行分析,为有针对性地开展大气治理工作提供数据支持。利用大流量采样器采集2020年疫情期间北京南郊观象台全年的总悬浮颗粒物（TSP）,提取其水溶液,用离子色谱法进行离子分析,并利用ISOPRROIA模型计算其pH值。结果表明,2020年疫情期间TSP质量浓度为17216±9051 μg/m3,其中水溶性离子成分占TSP质量分数的1763%。2020年1—5月,疫情主要防控阶段,车辆较少,南郊观象台主要为混合型污染。2020年6—12月,逐步复工复产,车辆变多,南郊观象台主要受到移动源污染影响。疫情期间TSP主要的水溶性成分为Na2SO4和NaNO3,其pH值大多显酸性,部分呈现中性。2020年1—5月,TSP的pH值在一定程度上受到SO2-4和NO3-的共同影响,离子的质量浓度越大,其酸性在一定程度上越强。TSP中的部分NO3-是由NO2转化而来。     

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.     

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.     

IMPACT OF ATMOSPHERIC LOW-FREQUENCY OSCILLATION ON THE IMMIGRATION OF NILAPARVATA LUGENS(STL) IN HUNAN AND JIANGXI PROVINCES

Various features of the atmospheric environment affect the number of migratory insects, besides their initial population. However, little is known about the impact of atmospheric low-frequency oscillation(10 to 90 days) on insect migration. A case study was conducted to ascertain the influence of low-frequency atmospheric oscillation on the immigration of brown planthopper, Nilaparvata lugens(Stl), in Hunan and Jiangxi provinces. The results showed the following:(1) The number of immigrating N. lugens from April to June of 2007 through 2016 mainly exhibited a periodic oscillation of 10 to 20 days.(2) The 10-20 d low-frequency number of immigrating N. lugens was significantly correlated with a low-frequency wind field and a geopotential height field at 850 h Pa.(3) During the peak phase of immigration, southwest or south winds served as a driving force and carried N. lugens populations northward, and when in the back of the trough and the front of the ridge, the downward airflow created a favorable condition for N. lugens to land in the study area. In conclusion, the northward migration of N. lugens was influenced by a low-frequency atmospheric circulation based on the analysis of dynamics. This study was the first research connecting atmospheric low-frequency oscillation to insect migration.     

A COMPARATIVE ANALYSIS OF ATMOSPHERIC AND OCEANIC CONDITIONS BEFORE THE OCCURRENCE OF TWO TYPES OF EL NIO EVENTS

The atmospheric and oceanic conditions before the onset of EP El Ni?o and CP El Ni?o in nearly 30 years are compared and analyzed by using 850 hPa wind, 20℃ isotherm depth, sea surface temperature and the Wheeler and Hendon index. The results are as follows: In the western equatorial Pacific, the occurrence of the anomalously strong westerly winds of the EP El Ni?o is earlier than that of the CP El Ni?o. Its intensity is far stronger than that of the CP El Ni?o. Two months before the El Ni?o, the anomaly westerly winds of the EP El Ni?o have extended to the eastern Pacific region, while the westerly wind anomaly of the CP El Ni?o can only extend to the west of the dateline three months before the El Ni?o and later stay there. Unlike the EP El Ni?o, the CP El Ni?o is always associated with easterly wind anomaly in the eastern equatorial Pacific before its onset. The thermocline depth anomaly of the EP El Ni?o can significantly move eastward and deepen. In addition, we also find that the evolution of thermocline is ahead of the development of the sea surface temperature for the EP El Ni?o. The strong MJO activity of the EP El Ni?o in the western and central Pacific is earlier than that of the CP El Ni?o. Measured by the standard deviation of the zonal wind square, the intensity of MJO activity of the EP El Ni?o is significantly greater than that of the CP El Ni?o before the onset of El Ni?o.     

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.     

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.     

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