共查询到19条相似文献，搜索用时 264 毫秒
1.
利用MODIS AOD(Aerosol Optical Depth)3 km分辨率的L2产品并辅以地面气象测量站点和环保监测站点的逐小时数据,对2017—2018年南京地面各站点进行数据匹配,分析估算PM_(2.5)的各相关组合因子,然后利用GA-BP神经网络算法构建卫星数据辅以地面气象数据来估算PM_(2.5)质量浓度的机器学习模型。结果表明:(1)GA-BP神经网络算法对PM_(2.5)进行估算是有效可行的,且比BP效果改善明显。(2)在多源数据的各输入变量中,选择AOD变量加辅助变量的GA-BP算法模型共构建了9组分季节试验,其中应用在2017年数据的试验6最好,表现为秋季冬季夏季春季,秋季R~2最大为0.91(RMSE为11.79μg·m~(-3)),春季R~2最小为0.65(RMSE为8.67μg·m~(-3))。 相似文献
2.
中国地区MODIS气溶胶产品的验证及反演误差分析 总被引：1，自引：0，他引：1
《高原气象》2016,(3)
利用中国地区AERONET(AErosol RObotic NETwork)地基观测资料对Terra/Aqua MODIS(Moderate Resolution Imaging Spectroradiometer)气溶胶产品精度进行验证,提供资料可靠性分析,并分析了各地区MODIS反演气溶胶光学厚度(Aerosol Optical Depth,AOD)的误差来源,为进一步改进算法提供依据。结果表明:(1)香河、兴隆、榆林、寿县、合肥、香港和台湾等站点MODIS AOD的质量较好。对大多数站点,Terra和Aqua MODIS AOD质量差别不大,除个别站点Terra略优于Aqua。(2)选取香河、太湖、SACOL、北京、兴隆和台湾成功大学站进行详细分析。香河站Terra和Aqua MODIS AOD质量均较好,相关系数分别为0.96和0.97,且落在期望误差内的百分数分别为72%和65%。太湖和北京站MODIS AOD存在统一高估现象,可以通过拟合直线的截距对其进行汀正,得到较接近真实值的AOD。SACOL,Terra和AquaMODISAOD与AERONETAOD的相关系数分别为0.66和0 77,且存在一定的高估。同时验证SACOL MODIS Deep Blue AOD,总体上其精度低于MODIS C005 AOD。兴隆和成功大学站反演误差均小于期望误差,数据质量较好。(3)误差分析表明香河和SACOL站的MODIS反演误差主要来自地表反射率关系的不合适;太湖和北京站的反演误差可能是由于地表和气溶胶模型两方面的共同作用导致的。个别站点随着云量增大,MODIS反演结果对AOD的高估也越大。 相似文献
3.
《气象与环境科学》2020,(1)
为深入了解晋城市颗粒物浓度时空分布特征,对晋城市2017年12月至2018年5月国控点、小型站和微型站PM_(2.5)及PM_(10)小时浓度数据进行收集整理,并进行空间插值分析和时间变化趋势分析及与气象监测数据的相关分析。结果表明:颗粒物浓度在冬、春季节具有明显差异,冬季PM_(10)与PM_(2.5)高值区主要位于东北部及东南小部分区域,春季PM_(10)高值区位于城区南部区域,PM_(2.5)高值区主要集中于城区。晋城市城区和郊区PM_(10)与PM_(2.5)月均浓度整体呈单峰型变化,PM_(10)在4月份最高(157.54±5.67μg·m~(-3)),PM_(2.5)在1月份最高(94.08±2.25μg·m~(-3))。冬季PM_(2.5)/PM_(10)平均为0.57,春季平均为0.45。颗粒物小时浓度的变化呈现单峰单谷的型式,冬季PM_(10)与PM_(2.5)小时平均浓度最高值均出现在10时,春季均出现在09时。监测期间晋城市PM_(10)与PM_(2.5)的小时浓度值与相对湿度有较高的正相关性(p0.01),与风速、风向有较高的负相关性(p0.01),与温度和气压的相关性较低。冬季,东北至正南风向时,PM_(10)与PM_(2.5)的浓度普遍高于西北风向时的浓度,对晋城冬、春季国控点颗粒物浓度贡献率最高的风向风速为东南偏南风向,风速在1 m/s以内。 相似文献
4.
京津冀地区气溶胶光学厚度反演及其空间分布特征 总被引：1，自引：0，他引：1
《气象与环境学报》2017,(3)
利用2014年9月1日至2015年5月31日Terra/MODIS MOD 021KM数据,以京津冀地区为研究区域,采用深蓝算法和查找表法反演京津冀地区1 km分辨率的气溶胶光学厚度,并将反演的气溶胶光学厚度与NASA产品和CE-318观测的气溶胶光学厚度进行比较。结果表明:反演的气溶胶光学厚度与NASA MOD 04_L2(10 km×10 km)和MOD 04_3K(3 km×3 km)两种气溶胶产品的空间分布具有高度的一致性,且空间分辨率更高;反演的气溶胶光学厚度与石家庄站CE-318观测气溶胶光学厚度的平均绝对误差为0.07左右,二者之间的相关系数R~2=0.956。卫星过境时,1 km反演的气溶胶光学厚度与MOD 04_L2气溶胶产品的平均误差约为0.06,反演的气溶胶光学厚度与MOD 04_3K气溶胶产品的平均误差约为0.03。对反演的气溶胶光学厚度与河北省PM_(2.5)和PM_(10)质量浓度的空间分布进行相关性分析表明,气溶胶光学厚度AOD与PM_(2.5)和PM_(10)质量浓度的相关系数分别为0.745、0.663,说明1 km反演的AOD可以有效反映区域PM_(2.5)和PM_(10)质量浓度的空间分布。 相似文献
5.
对FY-4A卫星的气溶胶光学厚度（AOD）产品进行检验,并根据卫星相关观测资料,通过改进后的PMRS方法,反演得到中国近地面PM2.5质量浓度网格化分布。结果表明,FY-4A卫星反演不同站点AOD与地基观测网（AERONET）观测结果吻合较好,但存在一定的低估或高估现象,相关系数区间为0.54—0.87。将细粒子比（FMF）以0.4为界进行划分,FMF＞0.4时,拟合结果较FMF≤0.4时更接近于AERONET观测结果;但FMF≤0.4时,卫星反演的AOD稳定性优于FMF＞0.4时。通过引入AOD的大小,改进FMF＞0.4时对细粒子柱状体积消光比（VEf）的估算算法,并通过改进后的PMRS方法对中国近地面PM2.5浓度进行逐时反演,其反演结果和地面观测结果相关较好,其中,乌鲁木齐、石家庄和徐州观测点的相关系数均高于0.7,但数值上仍存在高估或低估,误差结果由多种因素决定。空间分布中,卫星反演的中国2019年近地面PM2.5浓度月均值与近地面观测的结果有较好的对应关系,二者逐月演变趋势基本一致,基本可以反映出中国近地面大气细粒子的空间分布,特别是秋、冬季京津冀周边区域、汾渭平原等污染高值区均与地面观测对应较好。 相似文献
6.
《气象与环境学报》2016,(5)
利用京津冀地区80个环境监测站PM_(2.5)浓度的逐时监测资料和常规气象站的观测资料,分析了2013年1月京津冀地区3次典型重污染天气过程PM_(2.5)浓度的分布和演变特征,选取PM_(2.5)浓度快速增长时段的风场特征分析外来源对北京地区污染输送的影响。结果表明:2013年1月京津冀地区存在3个PM_(2.5)浓度高值中心,分别位于石家庄—保定、廊坊和唐山地区。北京地区外来源主要来自河北省中南部的石家庄—保定及廊坊一带,主要通过边界层偏南风远距离输送影响北京地区,边界层辐合线和逆温结构加剧了污染物在北京地区的累积。随着静稳时间的增长,PM_(2.5)污染物向燕山和太行山前输送堆积,造成北京地区PM_(2.5)浓度高于河北省中南部地区,北京市郊区PM_(2.5)浓度高于城区。 相似文献
7.
NOAA/AVHRR与EOS/MODIS遥感产品NDVI序列的对比及其校正 总被引：2，自引：1，他引：2
利用Terra、Aqua两颗卫星的MODIS资料、NOAA-16和17的AVHRR资料,通过对太阳和卫星天顶角及方位角等引起的大气效应订正、大气气溶胶等粒子的散射订正以及NOAA系列卫星信号的衰减订正,得到以上四颗卫星一系列的NDVI产品;对比分析了上午星Terra和NOAA-17,下午星Aqua和NOAA-16两组不同卫星传感器NDVI的差异及其与光谱响应函数的关系。结果表明,Terra和Aqua卫星NDVI随卫星观测角度的不同差异较大,平均NDVI是一种更适合的MODIS/NDVI产品算法,它代表了观测角为±30°之间的NDVI值的分布,在大气和角度的订正基础上,本研究采用了三阶多项式再次订正了观测角引起的NDVI变化;NOAA-16和17所获得的NDVI值较MODIS得到的NDVI值小很多,以MODIS的NDVI产品为标准,应用光谱响应函数将NOAA系列NDVI进行归一化处理,所得的结果基本与MODIS所得的NDVI相当;该方法基本能实现NDVI产品序列的延伸,其资料序列有时空可比性。 相似文献
8.
合肥市PM_(2.5)对城市辐射和气温的影响 总被引：2，自引：0，他引：2
本文利用2013年2月—2014年3月安徽省合肥市地面总辐射(即向下短波辐射)、气温、地面温度、相对湿度等气象资料和PM_(2.5)浓度资料,分析了合肥地区PM_(2.5)和地面总辐射、地温和气温的关系,研究发现:(1)PM_(2.5)浓度是影响总辐射的重要人为因子,在中午无云条件下,地面总辐射与PM_(2.5)的浓度呈现较强的负相关关系,相关系数为-0.62。归一化地面总辐射和PM_(2.5)的相关系数为-0.76,在早晨和傍晚的相关系数较小。平均而言,白天无云时PM_(2.5)浓度每增加1μg·m-3,地面总辐射下降0.92 W·m-2。(2)在白天无云时,气温、地面温度和PM_(2.5)浓度有明显负相关关系,PM_(2.5)浓度对地面温度的影响远大于对气温的影响,在夏季的影响高于其它季节。气温、地温和PM_(2.5)浓度的线性拟合直线的平均斜率分别为-0.022和-0.12,相当于PM_(2.5)浓度增加10μg·m-3,地温和气温分别平均下降0.22℃和1.2℃。(3)在天气尺度上,PM_(2.5)浓度对总辐射、气温和地面温度有非常明显的影响,在2013年9月清洁个例和2013年12月的污染个例中,PM_(2.5)浓度每增加1μg·m-3,将引起总辐射下降1.8 W·m-2和0.5 W·m-2,地温下降0.11℃和0.02℃,气温下降0.03℃和0.01℃,因此在天气预报过程中也需要考虑空气污染状况。 相似文献
9.
依据一种基于建筑用地比例和土地利用信息熵的城乡站点划分方法,将西安市环境与气象站点划分为城区、郊区和两类乡村站,讨论其PM2.5的城乡分布特征及与城市热岛效应强度(Urban Heat Island Intensity,UHII)间的相关关系。结果表明,不同季节西安市呈现不同的PM2.5城乡分布特征和日变化特征,两类乡村站点PM2.5差异明显且下风向乡村站点(乡村D)对应的UHIID对城区和乡村的影响程度大于上风向乡村站点(乡村U)对应的UHIIU。在城区较多本地排放的影响下,乡村PM2.5浓度与 UHIIU(或UHIID)相关系数均大于城区。随着UHIID的增加,城乡PM2.5相对浓度差值(RUPIID)整体呈下降趋势且UHIID与RUPIID在春夏秋季显著负相关。UHIID增大,城区近地面PM2.5的水平扩散能力减弱,但PM2.5的垂直扩散能力较乡村更强,从而UHIID通过影响PM2.5的传输扩散特征,进一步影响西安市RUPIID。 相似文献
10.
利用2014—2016年西安、咸阳、宝鸡、渭南、铜川的逐日PM_(10)质量浓度和同期美国国家航空航天局(NASA)的MODIS气溶胶产品(3 km),提取有效的气溶胶光学厚度(AOD)数据并进行标高及湿度订正,得到近地面"干"消光系数(AODSEC-RH),分析关中及5个地市PM_(10)质量浓度、AOD、AODSEC-RH的月、季、年时空变化特征。结果显示:近3 a关中及5个地市PM_(10)质量浓度均呈递减趋势;1月为峰值,7月为谷值,全年呈波动变化,冬季最大;3月较厚的逆温层及较稳定的大气致使污染不易扩散,PM_(10)质量浓度下降缓慢;4—5月降水开始增多,PM_(10)质量浓度下降较快;夏季PM_(10)质量浓度最低;10月雾和霾天气活跃,PM_(10)质量浓度迅速回升。西安年平均PM_(10)质量浓度较其他4市偏高,关中四季的PM_(10)质量浓度高值区均位于西安、咸阳、渭南市。近3 a关中整体AOD有所下降,高值区也位于西安、咸阳、渭南。夏季高温高湿,气溶胶吸湿强,AOD最大;其次为春季,气温回升、空气干燥、植被稀少,大风为沙尘天气提供了充分的动力,AOD次高;秋冬季AOD整体偏小。经标高及湿度订正的AODSEC-RH夏季明显降低,冬季明显升高,时空变化特征更接近于PM_(10)质量浓度,能充分体现近地面污染特征。 相似文献
11.
面对日益严峻的大气污染形势,针对卫星气溶胶光学厚度（AOD）资料在灰霾数值预报领域的合理有效利用问题,使用WRF-Chem（WRF coupled with Chemistry）大气化学模式以及GSI（Gridpoint Statistical Interpolation）三维变分同化系统,利用MODIS和FY-3A/MERSI AOD资料,对一次灰霾天气过程进行了同化预报试验。试验结果显示,同化卫星AOD资料有效改善了模式初始场,MODIS和MERSI同化试验分别在AOD分析场的中心强度和空间分布各具优势,且对PM2.5和PM10的后续预报改进明显;从统计分析上看,同化试验的预报效果整体上好于控制试验,同化试验中PM2.5和PM10预报值的平均值、中值、平均偏差、均方根误差等指标均明显优于控制试验,且MODIS和MERSI同化试验分别在PM2.5和PM10预报统计结果中体现出了优势;卫星AOD资料同化能明显降低污染事件的空报率和漏报率,提高预报的TS评分和ETS评分。不同卫星AOD资料的差异对分析场中AOD的分布和强度产生了相应影响,进而影响了模式的灰霾预报效果;本次试验中,MODIS和MERSI AOD同化试验分别在PM2.5和PM10预报的评分上表现更佳。结果表明,卫星AOD资料同化对数值预报产生了积极的效果。 相似文献
12.
采用大气辐射传输模式SES2以及2013年1月—2015年10月欧洲中期天气预报中心细网格再分析资料计算了北京地区4个观测站地面接收的短波辐射通量,分析了晴天和云天北京城郊气溶胶对总辐射的定量影响时空变化特征。结果表明:北京城区和近郊区气溶胶对总辐射的影响约为远郊区的2倍,北京南部和西部气溶胶对辐射的影响较大,晴天和云天北京城区和近郊区气溶胶对总辐射的削减值分别为146.23~180.99 W·m-2和202.11~217.02 W·m-2,晴天总辐射削减空间差异较大;秋冬季气溶胶对总辐射的影响明显大于春夏季,北京市观象台秋冬季气溶胶对总辐射的削减作用最大可达60%,较春夏季高10%~20%;北京城郊总辐射和直接辐射削减率与气溶胶光学厚度变化均呈线性关系,近地面PM2.5浓度对辐射的影响不容忽视。 相似文献
13.
A. L. Dement’eva G. S. Zhamsueva A. S. Zayakhanov V. V. Tsydypov A. A. Ayurzhanaev D. Azzayaa D. Oyunchimeg 《Russian Meteorology and Hydrology》2013,38(2):80-87
Results are presented of monitoring measurements of the mass concentration of PM10 (particles with the size of less than 10 μm) and PM2.5 (less than 2.5 μm) fine-dispersed aerosol fractions at the Sainshand and Zamyn-Üüd stations located in the Gobi Desert of Mongolia. Revealed are the annual variations of the mass concentration of PM10 and PM2.5 fine-dispersed aerosol fractions at these stations in 2008. The maximum values of monthly mean concentration during the year were observed in May in the period of dust storms. On the days with the steady calm weather, the mass concentrations of PM10 and PM2.5 varied within 5–8 μg/m3 (PM10) and 3–5 μg/m3 (PM2.5) at the Sainshand station. During the dust storms, the maximum values of concentration exceeded 1400 μg/m3 (PM10) and 380 μg/m3 (PM2.5) that is by 28 (PM10) and 15 (PM2.5) times higher than the maximum permissible concentration for the European Union. Results are given of studying the frequency and duration of dust storms in recent 20 years (1991–2010) in the Eastern Gobi Desert. 相似文献
14.
This study compares the aerosol optical depth (AOD) Level 2 Collection 5 products from the Terra and Aqua Moderate Resolution Imaging Spectroradiometers (MODIS) with ground-based measurements from a Microtops II sun photometer over Sanya (18.23°N, 109.52°E), a tropical coastal site in China, from July 2005 to June 2006. The results indicate that the Terra and Aqua MODIS AOD retrievals at 550 nm have good correlations with the measurements from the Microtops II sun photometer. The correlation coefficients for the linear regression fits (R²) are 0.83 for Terra and 0.78 for Aqua, and the regressed intercepts are near zero (0.005 for Terra, 0.009 for Aqua). However, the Terra and Aqua MODIS are found to consistently underestimate AOD with respect to the Microtops II sun photometer, with slope values of 0.805 (Terra) and 0.767 (Aqua). The comparison of the monthly mean AOD indicates that for each month, the Terra and Aqua MODIS retrievals are matched with corresponding Microtops measurements but are systematically less than those of the Microtops. This validation study indicates that the Terra and Aqua MODIS AOD retrievals can adequately characterize the AOD distributions over the tropical coastal region of China, but further efforts to eliminate systematic errors are needed. 相似文献
15.
Surface ozone (O3) and fine particulate matter (PM2.5) 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 PM2.5 (Δ[PM2.5]) 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[PM2.5] 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[PM2.5]. 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[PM2.5]. 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[PM2.5]. 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 [PM2.5] 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. 相似文献
16.
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)。 相似文献
17.
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, PM2.5, 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 (PM2.5) 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 PM2.5, 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 PM2.5/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. 相似文献
18.
Hongyan LUO Xiao TANG Huangjian WU Lei KONG Qian WU Kai CAO Yating SONG Xuechun LUO Yao WANG Jiang ZHU Zifa WANG 《大气科学进展》2022,39(10):1709-1720
China national air quality monitoring network has become the core data source for air quality assessment and management in China. However, during network construction, the significant change in numbers of monitoring sites with time is easily ignored, which brings uncertainty to air quality assessments. This study aims to analyze the impact of change in numbers of stations on national and regional air quality assessments in China during 2013–18. The results indicate that the change in numbers of stations has different impacts on fine particulate matter (PM2.5) and ozone concentration assessments. The increasing number of sites makes the estimated national and regional PM2.5 concentration slightly lower by 0.6?2.2 μg m?3 and 1.4?6.0 μg m?3 respectively from 2013 to 2018. The main reason is that over time, the monitoring network expands from the urban centers to the suburban areas with low population densities and pollutant emissions. For ozone, the increasing number of stations affects the long-term trends of the estimated concentration, especially the national trends, which changed from a slight upward trend to a downward trend in 2014?15. Besides, the impact of the increasing number of sites on ozone assessment exhibits a seasonal difference at the 0.05 significance level in that the added sites make the estimated concentration higher in winter and lower in summer. These results suggest that the change in numbers of monitoring sites is an important uncertainty factor in national and regional air quality assessments, that needs to be considered in long-term concentration assessment, trend analysis, and trend driving force analysis. 相似文献
19.
The insular suburban site of Castillo de Bellver was selected for the study of the variability of PM levels and composition in the Western Mediterranean Basin (WMB).Mean annual (in 2004) PM10 and PM2.5 levels at this site were 29 and 20 µg/m3, respectively. These levels may be regarded as relatively low when compared with other suburban insular locations in the Eastern Mediterranean Basin (EMB), but they are higher than those recorded at most of the European suburban sites, especially in Northern and Western Europe. Seasonal variability of PM levels at this site is governed by meteorology rather than local emissions, whereas the daily cycles are clearly defined by the anthropogenic emissions, mainly coming from the urban area of Palma de Mallorca and the harbour area of the same city.Concerning the aerosol composition at this site, the main PM constituent is the mineral matter (29% in PM10 and 16 % in PM2.5), more than 50% (in PM10) being attributable to African dust. The amount of secondary inorganic aerosols is also very high (27% in PM10 and 34% in PM2.5), with the predominance of fine ammonium sulphate, and in a less proportion fine ammonium nitrate (in winter) and coarse Ca and Na nitrate (with higher importance in summer). The carbonaceous particles, dominantly fine, account for 17% of PM10 and 25% of PM2.5. The elemental carbon/organic carbon (EC/OC) ratio reached a mean value of 0.17, similar to those observed at regional background sites in the WMB coast of Spain. The sea spray aerosols (mainly coarse) represented around 10% of PM10, and only 4% in PM2.5. Finally, the unaccounted fraction increased from 15% to 20% in PM2.5, being mostly attributed to water.The concentrations of trace elements in PM10 and PM2.5 were usually in the range to those observed in regional background sites in the Iberian Peninsula, with the exception of the typical tracers of road traffic such as Cu, Sb, Zn, Sn and Ba, which presented concentrations in the range of urban sites of Iberia. Other elements such as Cr, Zr, Hf and Co have been identified as the main tracers of the harbour contributions. 相似文献