Relative influence of air pollutants and weather conditions on solar radiation – Part 1: Relationship of air pollutants with weather conditions

Summary Air pollution measurements from January 1999 to December 2003 were studied in 14 sites covering most of Egypt, with the aim of understanding the governing processes pollutants phase interaction. The nature of the contributing sources has been investigated, and some attempts have been made to indicate the role played by neighboring regions in determining the air quality at these sites. The seasonal variability of particulate matter (PM₁₀) and some gaseous pollutants (e.g., SO₂, NO₂, CO and O₃) were analyzed. Their relationships with meteorology were also examined. The results reveal that levels of major air pollutants were not significantly different at the rural and background sites during any season. On contrary the high atmospheric loading for PM₁₀, CO and SO₂ was frequently observed in winter at the urban sites. As expected, the prevailing winds were found to have an influence not only on air pollutants but also on the correlation between them.     

基于京津冀高密度地面观测网络的大气污染物浓度地面观测代表性误差估计

地面观测提供空间点的浓度信息,三维化学模式提供网格面的浓度信息,两者在进行对比验证或同化融合时会因为空间尺度不匹配引入误差,即观测代表性误差。本研究将大气污染地面国控监测站与区县监测站结合起来,获得了京津冀地区高密度地面观测数据,利用该数据首次对京津冀地区6项常规大气污染物（PM_2.5、PM₁₀、SO₂、NO₂、CO和O₃）的地面观测代表性误差进行了客观估计,并与Elbern et al.（2007）方法估计的代表性误差进行了对比。结果发现:两种方法对京津冀地区NO₂地面观测代表性误差估计非常接近,但Elbern et al.（2007）方法显著低估了SO₂、CO和O₃地面观测的代表性误差。在此基础上,我们对Elbern et al.（2007）方法及其误差特征参数进行了本地化修正,并增加了PM_2.5和PM₁₀的代表性误差特征参数,建立了京津冀大气污染地面观测代表性误差的客观估计方法。     

2015年济南地区雾霾天气过程大气物理量特征初步分析

文中对比分析了2015年29个雾、霾及雾霾混合天气过程中,章丘探空站L波段探空雷达和山东省气象局院内德国14通道地基微波辐射计观测的温度资料。对观测数据实施了质量控制,检验了精度和可信度,统计分析了宏观物理参量特征和日变化规律。针对雾、霾及雾霾天气过程各选取了一个个例进行分析,分析了大气中PM_2.5、PM₁₀、SO₂、NO₂、O₃、CO含量的变化情况,分析了相对湿度、液态水路径和综合水汽含量等的变化情况。结果表明:两种观测数据一致性较好,拟合优度高于0.97;贴地逆温层存在一定的季节变化,悬垂逆温层存在一定的差异,逆温层的变化、污染参量变化与雾霾的形成有密切关系;不同天气背景对大气物理参量有较大的影响,PM₁₀、AQI（空气质量指数）和CO均在相同时间段出现峰值,有明显的起伏;CO峰值雾霾天气中尤为明显,由早到晚随时间峰值逐渐增大,雾天和霾天峰值较小,雾霾天气明显大于雾天或霾天。     

2009年秋季南京地区一次持续性灰霾天气过程研究

2009年10月14—27日,南京地区发生了一次持续性的灰霾天气过程。利用气象观测资料和污染物浓度监测资料,结合焚烧点监测、后向气流轨迹模拟,分析了颗粒物和气态污染物的浓度演变特征、气象要素特征及产生持续灰霾天气的可能原因。研究表明,该次过程中绝大部分时间能见度低于10 km,空气污染指数最大时达到195。地面PM2.5质量浓度有显著增长,在26日达到最大值为0.782 mg/m3。NO2质量浓度日均值在24日和27日超过了环境空气质量二级标准,其含量分别为0.094和0.099 mg/m3,对应NOx质量浓度分别为0.105和0.108 mg/m3。SO2质量浓度在22日达到峰值,最大值为0.161 mg/m3,平均值为0.083 mg/m3,低于环境空气质量二级标准。分析显示:近半个月内南京地区天气形势稳定,处于持续温度偏高、干燥无雨的状态,非常有利于灰霾天气的发生。卫星监测发现24、25、26日江淮之间中部均有火点,其中24日有50个着火点,25日增加为85个,26日减少为38个,表明有秸秆焚烧现象存在。从后向气流轨迹分析来看,在秸秆焚烧最为严重的3 d内,南京地区主要受到来自东到东北方向气流的影响,有利于秸秆焚烧形成的污染物经气流输送影响南京,造成严重灰霾天气。     

Relative influence of weather conditions and air pollutants on solar radiation – Part 2: Modification of solar radiation over urban and rural sites

Summary In the first part of this study, intensive measurements of particulate matter and trace gaseous were made to assess the characteristics of air pollutants in 14 sites covering most of Egypt, and to present a clear picture about the relationship of air pollutants with meteorology. The goal of this study is to examine the effect of weather conditions and air pollutants on the receipt of solar radiation during cloudless days at five sites. The results have shown, that the relative attenuation of the total solar radiation varied dramatically from 22% in winter to about 9.3% in summer. This finding may be attributed to PM₁₀ and CO effects, which are in the highest level during winter.     

四川盆地一次当地排放和沙尘输送双重影响的区域空气重污染过程研究

针对四川盆地大气污染及其成因的特殊性,本文使用四川盆地18个城市的大气污染监测和气象观测数据以及NCEP1°×1再分析资料,对2017年12月19日～2018年1月3日四川盆地由当地过量排放和外来沙尘输送双重影响的区域性大气污染过程进行分析。结果表明：2017年12月19～28日四川盆地环流场配置不利大气污染物扩散,垂直温度层结稳定,在当地污染源持续排放下污染物浓度缓慢上升,此阶段为静稳型大气污染。之后29日冷空气过程打破前期不利污染物扩散的环流场及垂直温度层结,导致气态污染物下降明显,但伴随冷空气活动的外来沙尘使PM10浓度迅速增大,使四川盆地部分城市出现沙尘型重污染;特别是广元地区受沙尘直接影响最严重,PM10浓度是原来的4.5倍;成都市虽没有通过沙尘天气的表观判断,但对颗粒物离子浓度和化学组分都有显著影响;因此,当时PM10和CO浓度24h比值变化受沙尘输送和天气条件共同影响,在不同时段和地区都存在明显差异,初步揭示出由静稳型大气污染向沙尘型污染转换阶段的内在变化特征,具有重要科学价值。     

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.     

Extreme Particulate Levels at a Western Pacific Coastal City: The Influence of Meteorological Factors and the Contribution of Long-Range Transport

The 4-year data sets (1998–2001) of PM₁₀ and other gaseous pollutants at four rural and urban monitoring sites provided by Environmental Protection Department of Hong Kong have been analyzed for days of extremely high and low PM₁₀ levels. The annual means of PM₁₀ concentrations are between 37 and 57 μg/m³. The level of high PM₁₀ concentration is defined from the comparison of local and international standards. Episode days are mainly controlled by different meteorological conditions: the continental outflow, the land-sea breeze/weak synoptic forcings and the approaching tropical cyclones. Integrated approaches have been used to distinguish between the predominantly “territory wide” and “long-range transport” (LRT) episode days. Case studies of these types of episodes are presented and the number of episode days per year for each type has been estimated. It is found that the LRT contributions are significant and account for ∼66% of the PM₁₀ episode days. Very high correlations between CO and PM₁₀ concentrations, and between SO₂ and PM₁₀ concentrations, can be found during the “territory wide” episode days which implies the important contributions of fossil fuel combustion to the PM₁₀ episodes. The number of “low level” PM₁₀ days per year has decreased by a factor near 3 from 1998 to 2001. Precipitation scavenging is the major process causing low levels of PM₁₀, irrespective of the associated weather systems. The regional annual background level is ∼9 μg/m³. With the exception of seasalt components, the average elemental concentrations of major inorganic species are similar for all of the sites during LRT events and constitute representative compositions of PM₁₀ during such events.     

Local and regional sources of fine and coarse particulate matter based on traffic and background monitoring

The aim of this study was to identify local and exogenous sources affecting particulate matter (PM) levels in five major cities of Northern Europe namely: London, Paris, Hamburg, Copenhagen and Stockholm. Besides local emissions, PM profile at urban and suburban areas of the European Union (EU) is also influenced by regional PM sources due to atmospheric transport, thus geographical city distribution is of a great importance. At each city, PM₁₀, PM_2.5, NO₂, SO₂, CO and O₃ air pollution data from two air pollution monitoring stations of the EU network were used. Different background characteristics of the selected two sampling sites at each city facilitated comparisons, providing a more exact analysis of PM sources. Four source apportionment methods: Pearson correlations among the levels of particulates and gaseous pollutants, characterisation of primal component analysis components, long-range transport analysis and extrapolation of PM size distribution ratios were applied. In general, fine (PM_2.5) and coarse (PM₁₀) particles were highly correlated, thus common sources are suggested. Combustion-originated gaseous pollutants (CO, NO₂, SO₂) were strongly associated to PM₁₀ and PM_2.5, primarily at areas severely affected by traffic. On the contrary, at background stations neighbouring important natural sources of particles or situated in suburban areas with rural background, natural emissions of aerosols were indicated. Series of daily PM_2.5/PM₁₀ ratios showed that minimum fraction values were detected during warm periods, due to higher volumes of airborne biogenic PM coarse, mainly at stations with important natural sources of particles in their vicinity. Hybrid single-particle Lagrangian integrated trajectory model was used, in order to extract 4-day backward air mass trajectories that arrived in the five cities which are under study during days with recorded PM₁₀ exceedances. At all five cities, a significantly large fraction of those trajectories were classified in short- and medium-range clusters, thus transportation of particulates along with slow moving air masses was identified. A finding that supports the assumption of long-range transport is that, at background stations, long-range transportation effects were stronger, in comparison to traffic stations, due to less local particle emissions. Short-range trajectories associated to PM transport in Stockholm, Copenhagen and Hamburg were mainly of a continental origin. All three cities were approached by slow moving air masses originated from Poland and the Czech Republic, whereas Copenhagen and Stockholm were also influenced by short-range trajectories from Germany and France and from Jutland Peninsula and Scandinavian Peninsula, respectively. London and Paris are located to the north-west part of Europe. Trajectories of short and medium length arrived to these two megacities mainly through France, Germany, UK and North Atlantic.     

2020年新冠肺炎疫情管控期江苏省大气污染物浓度变化特征北大核心

利用江苏省大气环境监测站点的大气污染物监测数据,分析了2020年初新冠肺炎疫情管控期间(2—3月)主要大气污染物浓度的变化特征。结果显示,相比于2019、2020年疫情管控期间PM_(2.5)、PM_(10)、NO_(2)、SO_(2)、CO浓度的全省平均降幅分别为37.5%、36.9%、31.9%、28.2%和21.2%。严格管控期的2月和生产恢复期的3月,江苏省十三市PM_(2.5)、PM_(10)浓度同比降幅大致相当,呈现出较好的时间连续性和空间均匀性。但各市臭氧浓度同比变化呈现出较大的时空差异。空间上,沿江以南城市南京、无锡、常州、苏州和镇江五市臭氧浓度明显上升,而其他城市臭氧浓度以下降为主;时间上,2月南京等九市臭氧浓度上升,3月徐州等八市臭氧浓度持平或者下降。假设未发生新冠肺炎疫情以及未采取为阻断疫情蔓延而实施的种种举措,在仅考虑近年来大气污染防治政策持续实施的情况下,与预期降幅相比,疫情管控对NO_(2)实况浓度降幅的影响最大,其次是PM_(2.5)和PM_(10)。     

苏州市一次重霾污染天气过程的数值模拟

本文对苏州地区2015年12月13—15日发生的一次典型的重霾污染天气过程进行了数值模拟,分析了颗粒物及其组分的时空变化特征及其气象影响因子,以期为该区域空气污染治理和预防提供科学依据。结果表明:(1)利用WRF-Chem模式对此次重霾污染天气过程的污染气体成分进行数值模拟后发现,小时平均的PM_(2.5)、PM_(10)、CO、SO_2、NO_2模拟值与实测值的相关系数较高,达到0.68以上,通过了P0.01的显著性检验,且日变化过程对应也较好。(2)通过分析此次污染过程的天气背景,发现污染形成期高空环流比较平直,中层为均匀的弱高压控制,地面受弱高压脊控制,这种形势容易导致颗粒物的堆积。后期地面等压线密集时,风速大,有利于污染物的输送与扩散。(3)通过分析此次污染过程期间气象要素的变化发现,有逆温、风速小、相对湿度大等不利的气象条件是导致此次污染过程发生的重要原因之一。(4)HYSPLIT轨迹分析显示,此次重霾过程主要受北方大范围灰霾颗粒物南下影响,北方污染气团逐步南推,14至15日本地大气扩散条件差、污染物累积,最终导致本地污染加重,从而发生重霾事件。(5)火点图的分布进一步验证了此次重霾污染过程是由外来污染气团输入所导致。     

Size-resolved characteristics of inorganic ionic species in atmospheric aerosols at a regional background site on the South African Highveld

Aerosols consist of organic and inorganic species, and the composition and concentration of these species depends on their sources, chemical transformation and sinks. In this study an assessment of major inorganic ions determined in three aerosol particle size ranges collected for 1 year at Welgegund in South Africa was conducted. SO₄^2? and ammonium (NH₄⁺) dominated the PM₁ size fraction, while SO₄^2? and nitrate (NO₃) dominated the PM_1–2.5 and PM_2.5–10 size fractions. SO₄^2? had the highest contribution in the two smaller size fractions, while NO₃^? had the highest contribution in the PM_2.5–10 size fraction. SO₄^2? and NO₃^? levels were attributed to the impacts of aged air masses passing over major anthropogenic source regions. Comparison of inorganic ion concentrations to levels thereof within a source region influencing Welgegund, indicated higher levels of most species within the source region. However, the comparative ratio of SO₄^2? was significantly lower due to SO₄^2? being formed distant from SO₂ emissions and submicron SO₄^2? having longer atmospheric residencies. The PM at Welgegund was determined to be acidic, mainly due to high concentrations of SO₄^2?. PM₁ and PM_1–2.5 fractions revealed a seasonal pattern, with higher inorganic ion concentrations measured from May to September. Higher concentrations were attributed to decreased wet removal, more pronounced inversion layers trapping pollutants, and increases in household combustion and wild fires during winter. Back trajectory analysis also revealed higher concentrations of inorganic ionic species corresponding to air mass movements over anthropogenic source regions.     

Climate variability of cold surge and its impact on the air quality of Taiwan

Climate change has been receiving wide attention in the last few decades. In order to quantify the climate variability of extreme weather events and their possible impacts on weather parameters and air quality, cold surge events in the past 45 years and the difference in characteristics of air pollutants before and after frontal passage has been examined after December 1993 in Taiwan. The potential impact of climate change on air pollutant concentration and its health implication were presented and discussed. In the past 45 years, the cold surge days (about 18.7 days, or 0.42 day/year) decreased significantly and the average lowest daily temperature for winter in northern Taiwan increased nearly 3°C (0.067°C/year). Based on the definition of cold surge in Taiwan and excluding the stagnation frontal passage, 21 cold surge frontal passage (CSFP) cases and 89 common frontal passage (CFP) events in winter (December–February) were identified in the past 12 years (1993–2005). We take the frontal passage day as the baseline and the differences in air pollutant concentrations and weather-related parameters between the two days before and after the frontal passage days were examined for each case. The averages of the above-mentioned differences during CSFP were compared to the corresponding differences during CFP. During CSFP, the air temperatures after the frontal passage were nearly 4–6°C lower than before the passage at both the background windward stations and urban stations. The average wind speed was about 4–5 m/s higher at the windward stations and less than 2 m/s higher in the major urban areas in Taiwan. During CFP, there was a 2°C increase in temperature but 1 m/s decrease in wind speeds on the day after frontal passage. Because of these meteorological differences, the concentration change of air pollutants during CSFP is significantly greater than that during CFP, especially for PM₁₀ concentration. The difference of PM₁₀ concentration during CSFP can be as large as 20–40 μg/m³ while that during CFP is only about 10 μg/m³. The differences in the other air pollutants such as CO, SO₂, and O₃ during CSFP are greater than those during CFP, but the difference is insignificant. Under the warming trend, less frequent CSFP’s are expected; the impacts on deterioration of air quality and human health are noteworthy.     

Particulate matter and gaseous pollutants during a tropical storm and air pollution episode in Southern Taiwan

Gaseous pollutants and PM_2.5 aerosol particles were investigated during a tropical storm and an air pollution episode in southern Taiwan. Field sampling and chemical analysis of particulate matter and gaseous pollutants were conducted in Daliao and Tzouying in the Kaohsiung area, using a denuder-filter pack system during the period of 22 October to 3 November 2004. Sulfate, nitrate and ammonium were the major ionic species in the PM_2.5, accounting for 46 and 39% of the PM_2.5 for Daliao and Tzouying, respectively. Higher PM_2.5, Cl^?, NO₃^? and NH₄⁺, HNO₂ and NH₃ concentrations were found at night in both stations, whereas higher HNO₃ was found during the day. In general, higher PM_2.5, HCl, NH₃, SO₂, Cl^?, NO₃^?, SO₄^2? and NH₄⁺ concentrations were found in Daliao. The synoptic weather during the experiment was first influenced by Typhoon NOCK-TEN, which resulted in the pollutant concentrations decreasing by about two-thirds. After the tropical thunderstorm system passed, the ambient air quality returned to the previous condition in 12 to 24 h. When there was a strong subsidence accompanied by a high-pressure system, a more stable environment with lower wind speed and mixing height resulted in higher PM_2.5, as well as HNO₂, NH₃, SO₄^2?, Cl^?, NO₃^?, NH₄⁺ and K⁺ concentrations during the episode days. The rainfall is mainly a scavenger of air pollutants in this study, and the stable atmospheric system and the high emission loading are the major reasons for high air pollutant concentrations.     

2015—2019年防城港市空气污染气象条件综合分析

对防城港市影响最大的首要空气污染物为PM_2.5和O₃,空气污染日主要集中在秋冬季。空气污染按500 hPa环流形势可分为西北气流型、偏西气流型及西南气流型;按地面气压场可分为冷高压脊型、均压型、高压后部低压前部型。在无境外输入的情况下,PM_2.5产生在风速小、气温较低、能见度小、湿度较大并且无降雨或降雨不明显的天气环境里,而O₃产生在高温、低湿、日照充足、风速较大和能见度好的天气环境里。在垂直运动方面,中低层的下沉气流利于空气污染物累积。在温度层结分布方面,700~850 hPa的低层存在的逆温层对PM_2.5浓度增加非常重要,近地面的逆温层对PM_2.5浓度增加的作用要比低层弱,而近地面的逆温层对O₃浓度的增加非常重要,但是低层的逆温却不重要。     

The fine and coarse particulate matter at four major Mediterranean cities: local and regional sources

Particulate air pollution is associated with adverse health effects to the population exposed. The aim of this paper is the identification of local and regional sources, affecting PM₁₀ and PM_2.5 levels in four large cities of southern Europe, namely: Lisbon, Madrid, Marseille, and Rome. Air pollution data from seven sampling sites of the European Union network were used. These stations were selected due to their ability of monitoring PM_2.5 concentrations and providing reliable series of data. Each station’s background was also taken into account. Pearson correlation coefficients and primal component analysis components were extracted separately for cold and warm periods in order to define the relationships among particle matters (PM_s) and gaseous pollutants (CO, NO₂, SO₂, and O₃) and evaluate the contributions of local sources. Possible seasonal variations of PM_2.5/PM₁₀ ratio daily values were also used as markers of PM sources, influencing particulate size distribution. Particle emissions were primarily attributed to traffic and secondarily to natural sources. Minimum daily values of PM_2.5/PM₁₀ ratio were observed during warm periods, particularly at suburban stations with rural background, due to dust resuspension and also due to the increase of biogenic coarse PM (pollen, dust, etc.). Hybrid Single-Particle Lagrangian Integrated Trajectory Model trajectory model was used in order to compute the 4-day backward trajectories of the air masses that affected the four cities which are under study during days with recorded PM₁₀ exceedances, within a 5-year period (2003–2007), at 300, 750, and 1,500 m above ground level (AGL). The trajectories were then divided to clusters with a K-means analysis. In all four cities, the influence of slow-moving air masses was associated with a large fraction of PM₁₀ exceedances and with high average and maximum daily mean PM₁₀ concentrations, principally at the 300 m AGL analysis. As far the issue of the increased PM₁₀ concentrations, the results were weaker in Marseille and particularly in Rome, probably due to their greater distance from Northwest Africa, in comparison to Madrid and Lisbon. Dust intrusions from the Sahara desert and transportation of Mediterranean/Atlantic sea spray, were characterized as primary regional sources of exogenous PM₁₀ in all four cities. Continental trajectories from the industrialized northern Italy affected PM₁₀ levels particularly in Marseille and Rome, due to their more eastern geographical position.     

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.     

武汉市大气污染源排放清单及分布特征研究

以武汉市为研究区域,基于实地调查获得典型行业污染源活动水平,以大气污染物排放清单编制技术指南为参考,利用排放因子法建立2014年武汉市大气污染源排放清单,并结合经纬度、人口密度分布、土地利用类型、道路长度等数据将排放清单进行了3 km×3 km网格化处理.结果表明,2014年武汉市SO₂、NO_x、PM₁₀、PM_2.5、CO、BC、OC、VOCs和NH₃排放量分别为10.3、17.0、16.3、7.1、63.1、0.6、0.4、19.8和1.6万t.固定燃烧源为SO₂排放的主要来源,其贡献率约64%;移动源为NO_x的主要来源,其贡献率约51%;颗粒物排放主要来源于扬尘源和工艺过程源;CO和VOCs主要来源于工艺过程源,BC和OC排放均以移动源和生物质燃烧源为主,NH₃排放主要来自农业源.污染物排放主要集中在青山区至新洲区一带.     

安徽省大气污染物浓度的周循环特征评估

大气质量的周循环特征反映了人类周期性的活动规律对大气环境的影响。基于安徽省16个城市PM_(2.5)、PM_(10)、CO、NO_2、SO_2和O_3这6种污染物的监测结果,对安徽省大气污染的周循环特征进行了评估。首先基于原始逐小时污染物浓度时间序列在日和周窗口时间宽度上的滑动平均序列,定义了周循环距平百分率序列的计算方法,排除了日循环和长期低频变化的影响。以此为基础,基于合成分析以及贝叶斯统计分析,发现这6种大气污染物中,PM_(2.5)、PM_(10)、CO和NO_2有着较为明显的周循环变化特征,其周循环距平百分率有着较大的变幅;而O_3的周循环特征相对不明显。主成分分析获得的周循环,第1模态发现除O_3以外的其他5种污染物的周循环有着同样的演进模式,即从周三开始持续到周五的累积和周六之后的衰减;O_3的周循环峰值与谷值与其他污染物存在着大于12 h的滞后,反映了在周循环尺度上O_3距平变化对其光化学反应前体距平变化的滞后响应特征。     

Comparison of Ozone and PM2.5 Concentrations over Urban,Suburban, and Background Sites in China

Surface ozone (O₃) and fine particulate matter (PM_2.5) are dominant air pollutants in China. Concentrations of these pollutants can show significant differences between urban and nonurban areas. However, such contrast has never been explored on the country level. This study investigates the spatiotemporal characteristics of urban-to-suburban and urban-to-background difference for O₃ (Δ[O₃]) and PM_2.5 (Δ[PM_2.5]) concentrations in China using monitoring data from 1171 urban, 110 suburban, and 15 background sites built by the China National Environmental Monitoring Center (CNEMC). On the annual mean basis, the urban-to-suburban Δ[O₃] is ?3.7 ppbv in Beijing–Tianjin–Hebei, 1.0 ppbv in the Yangtze River Delta, ?3.5 ppbv in the Pearl River Delta, and ?3.8 ppbv in the Sichuan Basin. On the contrary, the urban-to-suburban Δ[PM_2.5] is 15.8, ?0.3, 3.5 and 2.4 μg m^?3 in those areas, respectively. The urban-to-suburban contrast is more significant in winter for both Δ[O₃] and Δ[PM_2.5]. In eastern China, urban-to-background differences are also moderate during summer, with ?5.1 to 6.8 ppbv for Δ[O₃] and ?0.1 to 22.5 μg m^?3 for Δ[PM_2.5]. However, such contrasts are much larger in winter, with ?22.2 to 5.5 ppbv for Δ[O₃] and 3.1 to 82.3 μg m^?3 for Δ[PM_2.5]. Since the urban region accounts for only 2% of the whole country’s area, the urban-dominant air quality data from the CNEMC network may overestimate winter [PM_2.5] but underestimate winter [O₃] over the vast domain of China. The study suggests that the CNEMC monitoring data should be used with caution for evaluating chemical models and assessing ecosystem health, which require more data outside urban areas.