Changes in air pollutants during the COVID-19 lockdown in Beijing:Insights from a machine-learning technique and implications for future control policy

基于2015-2020年北京35个环境空气站和20个气象站观测资料,应用机器学习方法(随机森林算法)分离了气象条件和源排放对大气污染物浓度的影响.结果发现,为应对疫情采取的隔离措施使北京2020年春节期间大气污染物浓度降低了35.1％-51.8％;其中,背景站氮氧化物和一氧化碳浓度的降幅最大,超过了以往报道较多的交通站...     

Reductions of PM<Subscript>2.5</Subscript> in Beijing-Tianjin-Hebei urban agglomerations during the 2008 Olympic Games

The Atmospheric Environmental Monitoring Network successfully undertook the task of monitoring the atmospheric quality of Beijing and its surrounding area during the 2008 Olympics.The results of this monitoring show that high concentrations of PM2.5 pollution exhibited a regional pattern during the monitoring period(1 June-30 October 2008).The PM2.5 mass concentrations were 53 μg m 3,66 μg m 3,and 82 μg m 3 at the background site,in Beijing,and in the Beijing-Tianjin-Hebei urban agglomerations,respectively.The PM2.5 levels were lowest during the 2008 Olympic Games(8-24 August):35 μg m 3 at the background site,42 μg m 3 in Beijing and 57 μg m 3 in the region.These levels represent decreases of 49%,48%,and 56%,respectively,compared to the prophase mean concentration before the Olympic Games.Emission control measures contributed 62%-82% of the declines observed in Beijing,and meteorological conditions represented 18%-38%.The concentration of fine particles met the goals set for a "Green Olympics."     

Comparison of PM2.5 and CO2 Concentrations in Large Cities of China during the COVID-19 Lockdown

Estimating the impacts on PM_2.5pollution and CO₂emissions by human activities in different urban regions is important for developing efficient policies.In early 2020,China implemented a lockdown policy to contain the spread of COVID-19,resulting in a significant reduction of human activities.This event presents a convenient opportunity to study the impact of human activities in the transportation and industrial sectors on air pollution.Here,we investigate the variations in air quality attributed to the COVID-19 lockdown policy in the megacities of China by combining in-situ environmental and meteorological datasets,the Suomi-NPP/VIIRS and the CO₂emissions from the Carbon Monitor project.Our study shows that PM_2.5concentrations in the spring of 2020 decreased by 41.87%in the Yangtze River Delta(YRD)and 43.30%in the Pearl River Delta(PRD),respectively,owing to the significant shutdown of traffic and manufacturing industries.However,PM_2.5concentrations in the Beijing-Tianjin-Hebei(BTH)region only decreased by 2.01%because the energy and steel industries were not fully paused.In addition,unfavorable weather conditions contributed to further increases in the PM_2.5concentration.Furthermore,CO₂concentrations were not significantly affected in China during the short-term emission reduction,despite a 19.52%reduction in CO₂emissions compared to the same period in 2019.Our results suggest that concerted efforts from different emission sectors and effective long-term emission reduction strategies are necessary to control air pollution and CO₂emissions.     

武汉地区疫情管控期间空气质量变化及改善措施研究

2020年1月23日起,武汉地区施行了严格的交通管控措施,对当地的人为活动产生了重大影响。本文基于地面监测站网和卫星遥感分析了管控期间武汉地区的主要大气成分的变化,并研究了人为排放下降对O₃和细颗粒物（PM2.5）污染的影响。研究发现,由于管控期间施行机动车禁行政策,武汉地区的NO₂浓度与2019年同期相比下降53.2%,挥发性有机物（VOCs）下降了25.1%;与NO₂和VOCs的显著下降不同,O₃日最大8小时滑动平均第90百分位浓度平均值与去年同期相比上升16.5%,尤其是2月温度同比增高超过5°C,紫外辐射增长超过100%,O₃浓度显著高于去年同期,说明应基于O₃前体物NO_x和VOCs 活性种类的非线性定量关系加强协同减排;同时,管控期间PM2.5浓度与去年同期相比下降了35.6%,但是PM2.5浓度低值主要集中在风速较大、扩散较好的2月,其他时段PM2.5浓度下降并不明显;值得注意的是,与2月的显著下降不同,3月硝酸盐的浓度同比变化不大,说明导致NO_x转化为硝酸盐的大气氧化能力并未受到较大削减,武汉地区颗粒物减排应基于颗粒物不同组分的形成机理,加强颗粒物一次排放源和关键前体物控制。     

2020年上半年“COVID-19”疫情期间气象条件变化对四川盆地城市污染物质量浓度影响初步分析

大气污染物质量浓度变化主要受气象条件和人为排放变化所控制。2020年上半年在“新冠”疫情影响背景条件下,四川盆地的六项主要污染物质量浓度较往年有不同程度的变化,为了区分这些变化受气象条件和人为排放变化各自的影响程度,开展了气象条件变化对四川盆地污染物质量浓度影响的初步分析。分析结果表明:2020年1～6月整体空气质量优于2019年同期。主要影响污染物浓度的气象参数中,成都平原、川东北地区平均风速与往年相当,川南地区平均风速低于往年。从2020年3月开始,盆地各个城市的总降水量明显偏少,其中5月降水偏少情况最为严重,对应的相对湿度在5月同比较低。平均温度2020年高于2019年,尤其是5、6月平均温度较往年偏高大约4～5°C。月日照总时长从3、4月开始明显长于往年。用固定污染源,改变初始气象条件的方法进行数值模拟结果表明,PM2.5和PM10相似,1、2月模拟结果低于2019年,3、4月高于往年,5、6月同比偏低,主要偏差区域在川南城市群。SO₂ 在1、2月气象条件有利于扩散,3月川东北不利扩散,其余月份差距不明显。NO₂在2月气象条件较为不利,CO不利的月份为4月。4月气象条件有利于臭氧扩散,而5、6月盆地气象条件对O₃污染过程起了较强的推动作用。定量分析各个城市污染物浓度贡献率表明,受疫情影响,除臭氧外的颗粒物和气体污染物在1~4月人为排放贡献为负,5、6月由于全面复工复产,导致盆地的污染物浓度也有所上升,人为排放贡献率也大幅增加。O₃由于人为排放增加与不利气象条件叠加,导致盆地O₃污染情况较为严重。     

Size Distributions of Aerosol Sulfates and Nitrates in Beijing during the 2008 Olympic Games: Impacts of Pollution Control Measures and Regional Transport

For the 2008 Olympic Games, drastic control measures were implemented on industrial and urban emissions of sulfur dioxide (SO₂), nitrogen oxides (NO_x) and other pollutants to address the issues of poor air quality in Beijing. To investigate the effects of SO₂ and NO_x reductions on the particulate sulfate and nitrate concentrations as well as their size distributions, size-segregated aerosol samples were collected using micro-orifice uniform deposit impactors (MOUDIs) at urban and downwind rural sites in Beijing before and after full-scale controls. During the sampling period, the mass concentrations of fine particles (PM_1.8) at the urban and rural sites were 94.0 and 85.9 μg m^-3, respectively. More than 90% of the sulfates and ～60% of nitrates formed as fine particles. Benefiting from the advantageous meteorological conditions and the source controls, sulfates were observed in rather low concentrations and primarily in condensation mode during the Olympics. The effects of the control measures were separately analyzed for the northerly and the southerly air-mass-dominated days to account for any bias. After the control measures were implemented, PM, sulfates, and nitrates were significantly reduced when the northerly air masses prevailed, with a higher percentage of reduction in larger particles. The droplet mode particles, which dominated the sulfates and nitrates before the controls were implemented, were remarkably reduced in mass concentration after the control measures were implemented. Nevertheless, when the polluted southerly air masses prevailed, the local source control measures in Beijing did not effectively reduce the ambient sulfate concentration due to the enormous regional contribution from the North China Plain.     

不同代表性浓度路径情景下2045-2050年中国气溶胶分布变化的分析

基于来自于CMIP5中CESM模式的三种RCP情景下的气象场的降尺度模拟,应用区域空气质量模式系统RAMS-CMAQ模拟2045-2050年中国地区气溶胶浓度.三种RCP情景下气象场的降尺度模拟表明,与RCP2.6相比,在RCP4.5和RCP8.5下,华北和华南的近地表温度差减小,风速在华北和华南地区增加,在中部地区下...     

新冠肺炎疫情期间中国人为碳排放和大气污染物的变化

利用行业经济活动数据、1 580个地面监测站和6套卫星反演数据,分析了我国新冠肺炎疫情期间人为碳排放和主要大气污染物的变化。与2019年第一季度相比,2020年同期我国碳排放降低9.8%,其中交通部门降幅最大达到43.4%。与2019年2-3月相比,疫情期间全国地表臭氧浓度同比升高1.9 nL/L(5%),其中华北平原以降低为主,东南部地区以上升为主。PM2.5浓度同比下降12.6μg·m^-3(24.9%),其中长三角降幅最大。二氧化氮(NO2)的地面浓度和对流层柱浓度在京津冀、珠三角和长三角都降低20%~30%,体现了高低层的一致性。地面一氧化碳(CO)浓度同比降低17%,而对流层CO柱浓度升高2.5%,可能原因是境外生物质燃烧输送提升了我国南方高层大气的CO浓度。中东部地区气溶胶光学厚度显著降低,导致地表晴空短波辐射同比升高11.6 W·m^-2(9.6%)。     

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...     

Observations of Aerosol Optical Properties in the Beijing Urban Area in Summer

To investigate aerosol optical properties in the Beijing metropolitan area,aerosol absorption coefficient(Ab) ,scattering coefficient(Sc) ,and fine particulate matter(PM2.5) were measured in the Beijing urban area from 20 May to 30 August 2009.The average Ab,Sc,single scattering albedo(SSA) ,and PM2.5 concentration were 58.0±39.5 M m-1,343.5±353.7 M m-1,0.80±0.10 and 63.6±50.0-g m-3,respectively,during the observation period.Ab,Sc,and SSA all showed single peak diurnal variations,with their maximum values being measured at 0500,1000,and 1300 local time,respectively.Ab and Sc had a strong positive correlation with PM2.5,and Ab,Sc,and PM2.5 all had positive correlations with relative humidity and negative correlations with wind speed.     

Characterization of Organic Aerosol at a Rural Site in the North China Plain Region: Sources,Volatility and Organonitrates

The North China Plain(NCP) is a region that experiences serious aerosol pollution. A number of studies have focused on aerosol pollution in urban areas in the NCP region; however, research on characterizing aerosols in rural NCP areas is comparatively limited. In this study, we deployed a TD-HR-AMS(thermodenuder high-resolution aerosol mass spectrometer) system at a rural site in the NCP region in summer 2013 to characterize the chemical compositions and volatility of submicron aerosols(PM_1). The average PM_1 mass concentration was 51.2 ± 48.0 μg m~(-3) and organic aerosol(OA) contributed most(35.4%) to PM_1. Positive matrix factorization(PMF) analysis of OA measurements identified four OA factors, including hydrocarbon-like OA(HOA, accounting for 18.4%), biomass burning OA(BBOA, 29.4%), lessoxidized oxygenated OA(LO-OOA, 30.8%) and more-oxidized oxygenated OA(MO-OOA, 21.4%). The volatility sequence of the OA factors was HOA BBOA LO-OOA MO-OOA, consistent with their oxygen-to-carbon(O:C)ratios. Additionally, the mean concentration of organonitrates(ON) was 1.48-3.39 μg m~(-3), contributing 8.1%–19% of OA based on cross validation of two estimation methods with the high-resolution time-of-flight aerosol mass spectrometer(HRToF-AMS) measurement. Correlation analysis shows that ON were more correlated with BBOA and black carbon emitted from biomass burning but poorly correlated with LO-OOA. Also, volatility analysis for ON further confirmed that particulate ON formation might be closely associated with primary emissions in rural NCP areas.     

天津夏季大气消光性质的研究

利用2010年夏季天津城市边界层观测站颗粒物、黑碳气溶胶、氮氧化物(NOX)浓度、地面能见度和气象梯度观测资料,分析了天津夏季大气消光特性及低能见度事件产生的原因。结果表明,天津夏季主要污染物为PM10和PM2.5,大气气溶胶消光系数为529.06M.m-1,其中,吸收系数为50.17M.m-1,散射系数为478.89M.m-1,气体吸收系数为7.74M.m-1,气溶胶单次散射反射率为0.87。天津夏季边界层大气状态有近一半的时间为中性或偏稳定层结,当出现中性或偏稳定层结大气时则有接近一半的情况出现低能见度事件(能见度<5km),影响人们的日常生活。     

广州地区旱季一次典型灰霾过程的特征及成因分析

通过研究2009年11月广州市气溶胶颗粒物质量浓度(PM10、PM2.5、PM1)、黑碳浓度、散射系数(Scatter)等大气成分要素,以及微波辐射计、激光雷达及风廓线雷达所探测的风、温、湿等边界层结构,统计分析广州旱季一次典型灰霾过程(2009年11月23—29日)中气溶胶颗粒物及其光学特性的时空变化特征,并配合天气形势背景、边界层结构对其形成原因进行详细分析。在典型灰霾过程中,黑碳浓度高达58.7μg/m3,散射系数高达1 902.7 Mm-1,PM10浓度高达423.5μg/m3,PM2.5浓度高达355.7μg/m3,PM1浓度高达286.5μg/m3。通过对同期的气象条件分析表明在广州地区旱季,区域性污染过程,特别是灰霾天气的形成具有以下三种气象条件:大气边界层高度较低;高压变性出海的天气形势与之密切相关;在偏东和偏南气流带来的高湿度环境下,气溶胶吸湿增长效应显著,导致出现严重灰霾天气。     

天空辐射计观测反演北京城区气溶胶光学特性

利用2018年10月—2019年9月天空辐射计观测数据反演北京城区气溶胶光学特性参数,重点分析污染过程中气溶胶光学特性与气象条件的相关性。结果表明:500 nm气溶胶光学厚度在2—7月较大,最高值出现在6月,为0.71。单次散射反照率最高值出现在8月,为0.96;最低值出现在5月,为0.89。440~870 nm ?ngstr?m波长指数最高值出现在夏季,为1.11;最低值出现在春季,为0.89。统计发现污染日数仅占总日数的17%,其中62%为轻度污染;污染和清洁天气条件下PM_2.5浓度分别为107.22 μg·m-3和47.16 μg·m-3,500 nm气溶胶光学厚度分别为0.85和0.49,单次散射反照率分别为0.96和0.92;冬季?ngstr?m波长指数在污染天气条件下（1.02）大于清洁天气（0.91）,春季相反。结合天空辐射计、激光雷达和气象数据分析2019年1月一次污染事件,可知低风速与高湿度等不利气象条件、气溶胶粒子的吸湿增长和二次转化、污染物局地排放及区域输送共同导致污染事件发生。     

Influences of meteorological conditions on interannual variations of particulate matter pollution during winter in the Beijing–Tianjin–Hebei area

To investigate the interannual variations of particulate matter (PM) pollution in winter, this paper examines the pollution characteristics of PM with aerodynamic diameters of less than 2.5 and 10 μm (i.e., PM_2.5 and PM₁₀), and their relationship to meteorological conditions over the Beijing municipality, Tianjin municipality, and Hebei Province—an area called Jing–Jin–Ji (JJJ, hereinafter)—in December 2013–16. The meteorological conditions during this period are also analyzed. The regional average concentrations of PM_2.5 (PM₁₀) over the JJJ area during this period were 148.6 (236.4), 100.1 (166.4), 140.5 (204.5), and 141.7 (203.1) μg m^–3, respectively. The high occurrence frequencies of cold air outbreaks, a strong Siberian high, high wind speeds and boundary layer height, and low temperature and relative humidity, were direct meteorological causes of the low PM concentration in December 2014. A combined analysis of PM pollution and meteorological conditions implied that control measures have resulted in an effective improvement in air quality. Using the same emissions inventory in December 2013–16, a modeling analysis showed emissions of PM_2.5 to decrease by 12.7%, 8.6%, and 8.3% in December 2014, 2015, and 2016, respectively, each compared with the previous year, over the JJJ area.     

2007和2008年夏季北京奥运馆大气PM10与PM2.5质量浓度变化特征

为了监测北京奥运主场馆附近大气颗粒物的污染状况以及评估奥运污染源减排措施对北京大气颗粒物质量浓度变化的影响,利用颗粒物在线监测仪器TEOM于2007年和2008年夏季,在奥运主场馆附近的中国科学院遥感应用研究所办公楼楼顶对大气颗粒物PM10和PM2.5进行了连续同步观测。结果表明,2007年夏季监测点附近大气PM10与PM2.5质量浓度的平均值分别为153.9和71.2μg.m-3,而2008年夏季PM10与PM2.5质量浓度的平均值分别为85.2和52.8μg.m-3。与奥运前一年同时段相比,奥运时段大气PM10和PM2.5的质量浓度分别下降44.5%和25.1%。对比分析奥运前后的2次典型污染过程发现,空气相对湿度的增加和偏南气流输送的共同影响易造成大气颗粒物的累积增长,而降雨的湿清除作用和偏北气流则会使大气颗粒物浓度迅速降低。在相近的气象条件下,奥运前后的污染过程中,大气细粒子的日均增长速率分别为25.1和13.9μg.m-3.d-1,而大气粗粒子的日均增长速率分别为20.8和2.2μg.m-3.d-1,奥运时段污染累积过程中大气粗、细粒子的增长速率分别显著低于和略低于奥运前同时段污染过程中颗粒物的增长速率。污染源减排措施的实施是奥运期间大气颗粒物质量浓度降低的主要原因,从控制效果来看,奥运期间实施的污染源减排措施对大气粗粒子的控制效果明显好于大气细粒子。     

秸秆燃烧对北京秋季气溶胶浓度和短波辐射影响的模拟研究

利用地面细颗粒物（PM2.5）浓度和气象常规观测资料、地基 AERONET观测资料、GFED生物质燃烧排放清单和大气化学—天气耦合模式WRF-Chem,模拟研究了华北地区2014年10月气象要素和大气污染物的时空演变,重点关注北京10月7～11日的一次重霾事件及其天气形势、边界层气象特征、输送路径、PM2.5及其化学成分浓度变化等特征,以及秸秆燃烧对华北和北京地区细颗粒物浓度和地面短波辐射的影响。与观测资料的对比结果显示,模式可以很好地模拟北京地区地面气象要素和PM2.5质量浓度,考虑秸秆燃烧排放源可以明显改进北京PM2.5浓度模拟的准确性,但在重度污染情况下,模式总体上低估气溶胶光学厚度和高估地面短波辐射。10月7～11日北京地区重霾事件主要是不利气象条件下人为污染物累积和区域输送造成,也受到华北地区南部秸秆燃烧的影响。河南北部、河北南部和山东西部大面积秸秆燃烧释放的气态污染物和颗粒物在南风的作用下输送至北京,秸秆燃烧对北京地区地面PM2.5、有机碳（OC）、硝酸盐、铵盐、硫酸盐和黑碳（BC）的平均贡献率分别为24.6%、36.8%、23.2%、22.6%、7.1%和19.8%,秸秆燃烧产生的气溶胶可以导致北京地面平均短波辐射最大减小超过20 W m－2,约占总气溶胶导致地表短波辐射变化的24%。     

2016年11—12月北京及周边重污染过程PM2.5特征

该文对2016年11—12月北京及周边地区不同站点重污染期间PM_2.5质量浓度变化特征进行分析,并结合地面和探空气象要素及化学组分等对重污染成因进行深入探讨,比较了其中两次持续3 d及以上重污染过程的异同。结果表明:重污染期间北京及周边地区PM_2.5质量浓度较高,北京上甸子站、顺义站、朝阳站的PM_2.5质量浓度分别为73.1,130.8,226.0 μg·m-3,河北保定站和石家庄站分别为357.8 μg·m-3和346.9 μg·m-3。12月17—21日重污染过程比11月3—5日持续时间更长且PM_2.5质量浓度更高。通过对11—12月所有重污染过程分析发现,北京颗粒物重污染发生的主要气象条件是静稳天气。在排放源相对稳定情况下,逆温层的结构、演变和持续时间决定了重污染的程度,其中污染持续时间和污染期间的主导逆温层类型演变对重污染程度有较好的指示作用。较低的水平风速、逆温层的持续出现及更多的燃煤和机动车尾气排放是12月17—21日污染偏重的原因。     

北京雾、霾天细粒子质量浓度垂直梯度变化的观测

近年来北京城市区域雾霾天气显著增加,不仅严重影响工农业生产和交通运输,还严重影响人体健康.2007年夏秋季节,北京325 m气象塔8、80和240m平台梯度观测结果表明,雾、霾、晴三种典型天气状况大气细粒子质量浓度垂直分布各有特点,雾天(11月5～6日)低层浓度明显偏高,6日从低到高3层PM2.5(空气动力学直径小于等于2.5μ的大气气溶胶)浓度日均值分别为352.6±79.3、224.7±69.0、214.8±32.8 μg·m~(-3);霾天(8月19～20日)细粒子上下混合均匀,19日从低到高3层PM2.5浓度分别为89.8±29.3、88.9±29.8、90.0±31.7 μg·m~(-3);晴天(8月22～23日)细粒子昼夜变化明显,夜间在80 m高度出现明显分层,23日80 m以下平均值为32.6±13.1μg·m~(-3),240 m平均值为27.4±13.5μg·m~(-3).雾天细粒子主要来源于局地,霾天细粒子污染表现为时空分布十分均匀的城市群区域污染特征且污染物积累;连续晴天细粒子明显被清除.     

北京PM1中的化学组成及其控制对策思考

通过分析北京城区2007年夏季和秋季、2008年冬季和春季4个季节PM₁中硫酸盐、硝酸盐、铵盐、有机物和黑碳等气溶胶化学组成,结合对我国及全球主要区域PM₁₀中上述气溶胶组分及矿物气溶胶组成的评估,发现因受干旱区产生的沙尘和城市逸散性粉尘的共同影响,整个亚洲大陆,尤其是我国的矿物气溶胶浓度与欧美国家城市区域气溶胶总和的平均值相当或更高。我国在重视控制PM_2.5等细粒子污染的同时,不应忽视对PM_2.5~PM₁₀之间粗粒子的控制力度;北京城区春、夏、秋、冬的PM₁平均质量浓度分别约为94,74,66 μg·m-3和91 μg·m-3,全年平均约为81 μg·m-3,其中有机物气溶胶约占41%,硫酸盐占16%,硝酸盐占13%,铵盐占8%,黑碳和氯化物分别占11%和3%,细矿物气溶胶约贡献7%。对于PM_2.5污染的控制,关键是消减PM₁中主要气溶胶粒子的排放与转化,其中对有机物的控制更为重要,尽管对于北京而言进一步污染控制的难度已经很大。从科学上来说,即使我国的控制措施能百分之百实现,也很难稳定地达到欧美国家的空气质量水平,因为我国本底矿物气溶胶的浓度较高。应进一步评估各项控制措施的适用性,并制定考虑我国人群健康状况的PM_2.5空气质量标准。