气象因素对西安市西南城区大气中臭氧及其前体物的影响

利用西安市2015年连续观测的O_3及其前体物NO、NO_2和CO质量浓度数据,分析其随时间变化的污染特征,结合气象要素进行相关性分析并拟合方程。结果表明:受局地光化学反应的影响,西安市夏季O_3浓度最高,且因O_3-8h造成的污染占总污染天数的1/3。冬季光化学反应减弱,但前体物排放源增强,NO、NO_2和CO出现最大浓度值。O_3浓度日变化呈单峰型,最高值出现在16:00左右,夜间维持较低水平。NO、NO_2和CO的日变化呈现白天低,夜间高的双峰型。O_3与温度、风速呈正相关,与相对湿度呈负相关,NO、NO_2和CO与风速呈负相关。受上风向污染源的影响,在东北、偏北和偏东气流控制下,易出现O_3浓度高值。夏季O_3质量浓度与气象要素的拟合度较好,可利用常规气象要素对O_3浓度趋势进行预测分析。     

南京北郊冬季大气S0_2、N0_2和0_3的变化特征

利用差分吸收光谱仪DOAS(differential optical absorption spectroscopy),对2007年11月-2008年1月南京北郊大气SO_2、NO_2和O_3进行了观测.结合Parsivel降水粒子谱仪和自动气象站的资料,对冬季大气污染气体的浓度变化规律及降水和风速风向对其的影响进行了分析.结果表明,南京北郊大气SO_2浓度较高,呈明显双峰特征,分别在12时(北京时,下同)和00时达最大,受附近排放源的影响最大,东风及南风时比静风时SO_2浓度更高.降水对SO_2湿清除效果明显,清除系数平均为0.168h~(-1).NO_2气体呈明显单峰特征,在18时达最高值.南京北郊是NO_2源区之一,主要受附近高速公路汽车尾气排放源的影响.静风时NO_2浓度最高.O_3浓度受NO_2的影响较明显.O_3日变化呈单峰特征,在15时达最大值,静风时O_3浓度最低.降水对O_3的间接影响较明显,在降水时,白天由于太阳辐射较弱,O_3浓度降低;夜晚NO浓度较低,使得O_3浓度升高.     

内蒙古乌兰察布市集宁区O_3污染特征及影响因子

利用2015—2017年内蒙古乌兰察布市集宁区空气质量数据和常规气象观测资料,对集宁地区O_3污染现状、时间变化特征及其影响因子进行统计分析。结果表明:集宁地区O_3污染日数逐年增加,已经成为该地首要污染物。O_3质量浓度变化具有明显的季节性,污染易发于春末和夏季; O_3质量浓度日变化呈单峰型,午后达到峰值,傍晚前后开始衰减,一直持续至第二日清晨。O_3质量浓度的变化与气象要素关系密切,较高的气温易提升光化学反应速率;低云量的多少也影响O_3质量浓度增长率和下降率;偏南风和适中的风速利于O_3前体物及O_3的输送和累积。集宁地区的NO_2和CO是重要的O_3前体物,NO_2对O_3质量浓度变化的影响更直接和显著,CO作为初始"燃料"为O_3的生成提供基础条件。     

河北石家庄市近地层臭氧浓度特征及气象条件分析

利用2016年3月至2018年2月河北石家庄市环境监测站O_3及其前体物质量浓度逐时和逐日观测资料,以及气象站逐日气象观测数据,分析石家庄市近地层O_3质量浓度的时间变化特征及其与前体物NO_2、CO和气象条件的关系。结果表明:石家庄市O_3污染2017年比2016年严重,2017年比2016年O_3超标日数增加30 d,超标率上升8%,O_3年平均质量浓度上升17μg·m~(-3)。O_3质量浓度具有明显的季节变化特征,自夏季、春季、秋季、冬季依次降低,5—9月O_3质量浓度较高,平均值超过160μg·m~(-3),6月达到峰值208μg·m~(-3)。O_3质量浓度的日变化表现为单峰型分布,最低值出现在07:00左右,峰值在14:00—16:00。太阳辐射强、气温高、日照时数长、能见度好、无降水和相对湿度较低的条件下,石家庄市易出现O_3浓度超标天气。前体物NO_2、CO与O_3质量浓度之间夏季呈现显著正相关,而冬季则呈显著负相关。     

地理位置和盛行风向对惠州市空气质量的影响

利用惠州市区2013—2016年逐时的风向风速和大气污染物浓度资料,分析了风向风速与污染物质量浓度的关系、地理位置和盛行风向对惠州市空气质量的影响。结果表明:①惠州市污染物质量浓度与风向风速密切相关。当风向为ESE、SE、SSE、S、SSW时,SO_2、CO、NO、NO_2、NO_x、PM₁₀和PM_2.5的全年平均质量浓度最低;当风向为SW、WSW、W、WNW、NW时,全年平均质量浓度最高。O_3在风向为WSW、W、WNW、NW时,全年平均质量浓度明显高于其他风向,均在72μg/m^3以上。在冬半年,当风向为偏西北风时,SO_2、CO、NO、NO_2、NO_x、O_3、PM₁₀和PM_2.5质量浓度与年平均相比增加了5%～33%;当风向为偏南风时,SO_2、CO、NO、NO_2、NO_x、PM₁₀和PM_2.5质量浓度与年平均相比减少了3%～17%。②地理位置、盛行风向和周边城市分布与惠州市空气质量密切相关。位于惠州市国控点东侧的河源市和汕尾市或南海海域环境空气综合质量指数低,空气质量优良率高,惠州市东北风和东南风全年出现频率分别为40.3%和27.3%;而位于惠州市国控点偏西侧的广州市和东莞市环境空气综合质量指数较高,空气质量优良率较低,惠州市偏西风全年出现频率(有W的合计)仅17.8%。     

洛阳市臭氧污染特征及其与气象因子的关系

为了了解洛阳市O_3污染特征及其影响因素,利用2017年洛阳市7个国控点监测到的O_3、NO_2浓度及气象要素逐时数据,统计分析了2017年洛阳市O_3及NO_2的时间分布特征及NO_2浓度、气象因子对O_3浓度的影响。结果表明,洛阳市2017年O_3日最大8 h第90百分位数浓度为200μg/m~3,是二级标准的1.25倍。O_3和NO_2浓度存在明显的季节性变化特征,O_3浓度夏季最高,冬季的最低;NO_2浓度冬季最高,夏季的则最低。O_3浓度的日变化呈现为单峰分布,午后浓度较高,峰值出现在15:00左右;NO_2受机动车早晚高峰影响,表现为双峰分布,峰值分别出现在08:00和21:00。O_3与NO_2浓度呈现出良好的负指数函数关系,当洛阳市NO_2浓度低于40μg/m~3时,存在着O_3浓度超标的风险。高温低湿条件下有利于O_3的生成,当温度超过27℃时,洛阳市O_3小时浓度开始出现超标现象,且温度越高,超标风险越大;当相对湿度低于40%时,O_3小时平均浓度超标率最高为63.30%,随着相对湿度的增加,超标率逐渐降低,当相对湿度大于70%时,未出现O_3小时浓度超标现象。     

郑州市气态污染物的变化特征分析

利用2015-2018年郑州市气态污染物(SO_2、CO、NO_2和O_3)的浓度数据和郑州市气象数据资料,分析了郑州市气态污染物浓度的变化趋势和影响因素。结果显示:2015-2018年郑州市SO_2、CO、NO_2的年均浓度逐年降低,但其污染物浓度在31个省会城市中排名相对靠后,污染较为严重。SO_2、CO和NO_2浓度均为冬季的最高,其次是春季和秋季的,夏季的最低,O_3浓度与之相反。气态污染物浓度与气象因素的相关性分析结果表明:SO_2、NO_2、CO浓度均与温度呈显著负相关,O_3浓度与温度呈显著正相关;各污染物与气压的相关性与温度相反;SO_2、NO_2、CO浓度与降水量均呈负相关,降水对O_3的具体影响还有待深入研究。     

西宁近地面臭氧特征及其影响因素

利用青藏高原东北部城市西宁2015—2017年O_3质量浓度和各气象要素数据(紫外辐射、最高气温等),分析近地面O_3变化特征及其影响因素,结果表明:该地区臭氧平均质量浓度呈现单峰型日变化规律。每年6—8月O_3质量浓度最大,12月至翌年2月最小。依据环境空气质量指数AQI统计分析,6—8月污染天气O_3占首要污染物总天数的72%。O_3与NO_2、CO呈极显著负相关,臭氧日最大1 h平均质量浓度与紫外辐射、日最高气温呈极显著正相关,与日平均气压、日最高气压、日最低气压呈极显著负相关,与日平均相对湿度相关性不显著。不同季节不同高度风速大小和风向频率对O_3质量浓度影响不同,500 h Pa盛行风向以WNW为主时有利于扩散。2017年青海省大部地区O_3月平均质量浓度总体呈先增加后减小变化趋势。纬度越低,海拔越高的地区,O_3质量浓度升高越早。降水量的差异对O_3质量浓度影响较小。     

长三角地区城市O_3和PM_(2.5)污染特征及影响因素分析

O_3和PM_(2.5)是影响长三角地区空气质量的主要污染物。利用2016年33个城市大气环境监测站6项污染物的小时浓度及4个省会城市的气象数据进行统计分析,研究了该地区O_3和PM_(2.5)浓度的时空分布特征及其影响因素。结果表明:长三角地区O_3年平均浓度为50～73μg·m~(-3),平均为61μg·m~(-3);除芜湖和宣城外,其余31城市均存在不同程度的超标状况,超标率为0.34%～18.86%,平均为5.68%。O_3在5月和9月达到浓度高值;四季O_3日变化均呈单峰型,峰值出现在15∶00,夏季O_3峰值浓度最高值为157μg·m~(-3)。O_3浓度沿海城市整体高于内陆城市;夏季宿迁—淮安—滁州片区O_3污染较重。O_3与NO_2、CO显著负相关,且与NO_2相关性较强;O_3与气温、日照时数显著正相关,与相对湿度、降水呈负相关。PM_(2.5)年平均浓度在25～62μg·m~(-3)范围内,平均为49μg·m~(-3);各城市均出现PM_(2.5)超标,滁州PM_(2.5)超标率最大,为23.91%。PM_(2.5)在3月和12、1月达到浓度峰值;其日变化呈双峰型,09∶00—10∶00和22∶00—23∶00达到峰值。冬季徐州PM_(2.5)浓度最高,为102μg·m~(-3)。PM_(2.5)与NO_2、CO、SO_2、PM_(10)显著正相关,与气温、风速、降水负相关。     

降雨天气对大气污染物浓度的影响分析

利用2014—2016年的中国气象局地面观测资料和中国环境保护部公布的6种大气污染物浓度数据,对降雨天气前后的大气污染物浓度变化进行分析。结果表明:在京津冀、长三角和珠三角区域,降雨天气后6种大气污染物浓度降低的时次约占43%—60%,其中PM_(10)浓度降低最为明显,PM_(2.5)、O_3、SO_2和NO_2次之,最不明显的是CO。一般而言,降水天气前大气污染物浓度越高,降雨后浓度降低的时次所占比例越大,浓度降低值也越大,但当降雨天气前大气污染物浓度较低时,降雨天气后浓度升高的个例也很多,约占21%—61%。京津冀地区由于平均大气污染物浓度较高,降水天气对大气污染浓度的降低效果比长三角和珠三角地区更明显。对于大多数降雨时次,小时降水量越大,大气污染物浓度降低的时次所占比例越大,但浓度降低值反而越小。例外的是,小时雨强大于10 mm的降雨后,京津冀地区的O_3和SO_2浓度以及长三角地区的PM_(10)、PM_(2.5)和SO_2浓度降低程度不如小时雨强小于10 mm时;而珠三角地区的NO_2和O_3在降雨后的浓度变化对小时雨强不敏感。在京津冀地区,降雨天气对较大浓度的O_3清除作用非常明显。在长三角和珠三角地区,降雨前CO浓度较低时,降雨后浓度升高时次比浓度减小的多;另外,降雨天气对SO_2的清除作用非常明显。     

Diurnal and seasonal variations of wind farm impacts on land surface temperature over western Texas

This paper analyzes seasonal and diurnal variations of MODerate resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) data at ~1.1 km for the period of 2003–2011 over a region in West-Central Texas, where four of the world’s largest wind farms are located. Seasonal anomalies are created from MODIS Terra (~10:30 a.m. and 10:30 p.m. local solar time) and Aqua (~1:30 a.m. and 1:30 p.m. local solar time) LSTs, and their spatiotemporal variability is analyzed by comparing the LST changes between wind farm pixels (WFPs) and nearby non wind farm pixels (NNWFPs) using different methods under different quality controls. Our analyses show consistently that there is a warming effect of 0.31–0.70 °C at nighttime for the nine-year period during which data was collected over WFPs relative to NNWFPs, in all seasons for both Terra and Aqua measurements, while the changes at daytime are much noisier. The nighttime warming effect is much larger in summer than winter and at ~10:30 p.m. than ~1:30 a.m. and hence the largest warming effect is observed at ~10:30 p.m. in summer. The spatial pattern and magnitude of this warming effect couple very well with the geographic distribution of wind turbines and such coupling is stronger at nighttime than daytime and in summer than winter. Together, these results suggest that the warming effect observed in MODIS over wind farms are very likely attributable to the development of wind farms. This inference is consistent with the increasing number of operational wind turbines with time during the study period, the diurnal and seasonal variations in the frequency of wind speed and direction distribution, and the changes in near-surface atmospheric boundary layer (ABL) conditions due to wind farm operations. The nocturnal ABL is typically stable and much thinner than the daytime ABL and hence the turbine enhanced vertical mixing produces a stronger nighttime effect. The stronger wind speed and the higher frequency of the wind speed within the optimal power generation range in summer than winter and at nighttime than daytime likely drives wind turbines to generate more electricity and turbulence and consequently results in the strongest warming effect at nighttime in summer. Similarly, the stronger wind speed and the higher frequency of optimal wind speed at ~10:30 p.m. than that at ~1:30 a.m. might help explain, to some extent, why the nighttime LST warming effect is slightly larger at ~10:30 p.m. than ~1:30 a.m. The nighttime warming effect seen in spring and fall are smaller than that in summer and can be explained similarly.     

杭州市区大气臭氧浓度变化及气象要素影响

利用2005-2007年杭州市区大气O₃连续监测资料, 分析了O₃浓度变化特征, 在此基础上结合气象观测资料, 分析了大气O₃与天气系统间的关系, 建立了O₃与气象要素间的多元回归方程。结果表明: 2007年O₃平均浓度和最大小时浓度分别为44 μg.m-3和348 μg.m-3, 比上一年增加20%左右, 超标现象也越来越严重; O₃浓度有明显的季节变化, 夏季高、冬季低; 大气O₃浓度超标主要出现在高压后部和高压控制等天气类型。在紫外线强度较强时O₃浓度也高, 二者呈显著正相关; 对O₃与各种气象因子进行多元回归分析表明: O₃主要受到温度、相对湿度、日照等因素影响。     

北京市夏季臭氧变化特征的观测研究

利用2002年7月至8月325m气象塔资料研究了北京市夏季近地层臭氧浓度变化特征及其与气象因子的关系。结果表明：北京市夏季边界层臭氧浓度日变化显著．臭氧浓度随高度增加而增加；臭氧多数为单峰型分布，双峰型仅分布在底层；臭氧峰值出现时间与气温峰值出现时间基本一致，或略有落后。     

北京秋季地面O3的一维模式模拟研究

用一维光化学模式,基本模拟出静稳天气条件下2001年9月9日北京几个主要大气污染物种:O3、NO、NO2、CO以及SO2的日变化特点,并解释了影响O3及NO、NO2、CO和SO2日变化的控制因子作用。初步分析认为,地面O3对非甲烷碳氢化合物(NMHC)的变化很敏感。NMHC的增加或减少,将会造成O3的明显改变。造成9月9日夜间20:00~23:00一次污染物NO、CO和SO2浓度急剧升高的原因是由于夜间大气层结稳定情况下,大气的垂直扩散减弱,污染物在底层积累造成的。由于实际大气中,影响O3生成和损耗的机制很复杂,同时大气的平流输送是影响O3及其他污染物分布的重要因素,用一维模式虽然能够揭示出影响O3变化的几个因子的作用,但要深入分析O3产生和消耗机制,还需要用三维模式。     

Carbon dioxide concentration and flux in an urban residential area in Seoul,Korea

The carbon dioxide （CO2） concentrations and fluxes measured at a height of 17.5 m above the ground by a sonic anemometer and an open-path gas analyzer at an urban residential site in Seoul, Korea from February 2011 to January 2012 were analyzed. The annual mean CO2 concentration was found to be 750 mg m-3, with a maximum monthly mean concentration of 827 mg m-3 in January and a minimum value of 679 mg m-3 in August. Meanwhile, the annual mean CO2 flux was found to be 0.45 mg m-2 s-1, with a maximum monthly mean flux of 0.91 mg m-2 s-1 in January and a minimum value of 0.19 mg m-2 s-1 in June. The hourly mean CO2 concentration was found to show a significant diurnal variation; a maximum at 0700-0900 LST and a minimum at 1400-1600 LST, with a large diurnal range in winter and a small one in summer, mainly caused by diurnal changes in mixing height, CO2 flux, and surface complexity. The hourly mean CO2 flux was also found to show a significant diurnal variation, but it showed two maxima at 0700-0900 LST and 2100-2400 LST, and two minima at 1100-1500 LST and 0300-0500 LST, mainly caused by a diurnal pattern in CO2 emissions and sinks from road traffic, domestic heating and cooking by liquefied natural gas use, and the different horizontal distribution of CO2 sources and sinks near the site. Differential advection with respect to wind direction was also found to be a cause of diurnal variations in both the CO2 concentration and flux.     

Temporal variations in surface ozone and its precursors and meteorological effects at an urban site in China

Continuous measurements of ozone and its precursors including NO, NO₂, and CO at an urban site (32°03′N, 118°44′E) in Nanjing, China during the period from January 2000 to February 2003 are presented. The effects of local meteorological conditions and distant transports associated with seasonal changed Asian monsoons on the temporal variations of O₃ and its precursors are studied by statistical, backward trajectory, and episode analyses. The diurnal variation in O₃ shows high concentrations during daytime and low concentrations during late night and early morning, while the precursors show high concentrations during night and early morning and low concentrations during daytime. The diurnal variations in air pollutants are closely related to those in local meteorological conditions. Both temperature and wind speed have significant positive correlations with O₃ and significant negative correlations with the precursors. Relative humidity has a significant negative correlation with O₃ and significant positive correlations with the precursors. The seasonal variation in O₃ shows low concentrations in late autumn and winter and high concentrations in late spring and early summer, while the precursors show high concentrations in late autumn and winter and low concentrations in summer. Local mobile and stationary sources make a great contribution to the precursors, but distant transports also play a very important role in the seasonal variations of the air pollutants. The distant transport associated with the southeastern maritime monsoon contributes substantially to the O₃ because the originally clean maritime air mass is polluted when passing over the highly industrialized and urbanized areas in the Yangtze River Delta. The high frequency of this type of air mass in summer causes the fact that a common seasonal characteristic of surface O₃ in East Asia, summer minimum, is not observed at this site. The distant transports associated with the northern continental monsoons that dominate in autumn and winter are related to the high concentrations of the precursors in these two seasons. This study can contribute to a better understanding of the O₃ pollution in vast inland of China affected by meteorological conditions and the rapid urbanization and industrialization.     

基于观测的污染气体区域排放特征

利用2006年9月—2007年8月河北省固城生态与农业气象试验基地 (固城站) 反应性气体观测数据获得了CO与NO_x,CO与SO₂,SO₂与NO_x体积分数比的变化特征,并将观测得到的体积分数比与从INTEX-B等排放源资料得到的排放比进行比较研究。当风向来自北方向 (北京) 时,固城站的CO和NO_x体积分数显著高于其他方向,而来自南方向 (保定、石家庄) 时,SO₂体积分数显著高于其他方向。固城站观测到的CO与SO₂,CO与NO_x体积分数比分别为43.7和31.6,较排放比高出2~12倍。分析表明:排放源清单对CO排放低估了大约2倍以上,生物质燃料燃烧,尤其是收获季节大规模秸秆燃烧排放可能是重要的且被低估了的源。从观测数据估计得到秸秆燃烧期比平时CO大约多排放了90%±30%,忽略秸秆燃烧期额外排放对CO排放强度估计有重要影响。未来排放源清单编制和使用需要更加关注我国农业区秸秆燃烧排放对排放强度的影响。     

Characteristics of gaseous pollutants near a main traffic line in Beijing and its influencing factors

Automobile exhaust emissions are becoming increasingly serious with the drastic increase of the number of vehicles in Beijing. In order to investigate the air pollution level and characteristics in the areas near the main traffic lines in Beijing and to identify the contributions from traffic and other sources, gaseous pollutants including NOx, CO, O₃, SO₂, and meteorological parameters have been monitored at a monitoring site and a contrasting site in winter and summer in 2006. The volumes of vehicles on Beiyuan Road were recorded. The average concentrations of NO, NO₂, NOx, CO, O₃, and SO₂ at the monitoring site were 0.148 mg/m³, 0.107 mg/m³, 0.333 mg/m³, 5.110 mg/m³, 0.006 mg/m³, and 0.157 mg/m³, respectively during the sampling period in winter and 0.021 mg/m³, 0.068 mg/m³, 0.101 mg/m³, 4.170 mg/m³, 0.083 mg/m³, and 0.056 mg/m³, respectively in summer. The high concentrations of CO and O₃ reflect the influence of vehicles emission near the traffic lines evidently. The higher concentrations of CO, NO and O₃ in summer may indicate that the characteristics of traffic pollution were more pronounced in summer. Results of regression analysis showed that in winter the concentrations of SO₂ and CO were significantly positively correlated with the emission of heating boilers at night and negatively correlated with wind speed in daytime. The concentrations of NO and NOx were negatively correlated with wind speed, positively correlated with emission of heating boilers in daytime and positively correlated with traffic density at nighttime. The concentrations of NO₂ were positively correlated with the emission of heating boilers in daytime and traffic density at nighttime. In summer, the air quality at the monitoring site and the contrasting site was mainly influenced by the traffic emissions.     

基于MODIS卫星资料研究三峡工程对库区地表温度的影响

利用2001-2012年MODIS地表温度资料,分析了三峡库区蓄水后水体对冬、夏两季白天和夜间地表温度的影响。由于下垫面水陆和地势的影响,白天地表温度高值区主要位于四川盆地东部,夜间则主要出现在长江江面;温度日较差在长江和海拔较高地区较小,且夏季水体日较差小于冬季。分别用水体和I～X缓冲区地表温度减去XI缓冲区去除气候背景场影响,发现冬季白天地表温度趋势在水体及I～VI缓冲区由下降转为上升,夜间地表温度在相同距离内显著升高。利用蓄水后（2003-2012年）地表温度或日较差分别减去蓄水前（2001-2002年）剔除地形影响,发现：冬季,三峡工程水库蓄水对局地地表温度具有增温效果,且强度和范围夜间大于白天;夏季,对地表温度有降温作用,白天大于夜间;同时,冬、夏季的温度日较差减小;且水体对局地地表温度和日较差的影响随距水体距离的增加而减小,其影响范围基本维持在0～8 km范围内。