Atmospheric ambient trace element concentrations of PM10 at urban and sub-urban sites: source apportionment and health risk estimation

In this study, PM₁₀ concentrations and elemental (Al, Fe, Sc, V, Cr, Mn, Co, Ni, Cu, Zn, As, Se, Mo, Ag, Cd, Sn, Sb, Ba, Pb, and Bi) contents of particles were determined in Düzce, Turkey. The particulate matter samplings were carried out in the winter and summer seasons simultaneously in both urban and sub-urban sampling sites. The average PM₁₀ concentration measured in the winter season was 86.4 and 27.3 μg/m³, respectively, in the urban and sub-urban sampling sites, while it was measured as 53.2 and 34.7 μg/m³ in the summer season. According to the results, it was observed that the PM₁₀ levels and the element concentrations reached higher levels, especially at the urban sampling site, in the winter season. The positive matrix factorization model (PMF) was applied to the data set for source apportionment. Analysis with the PMF model revealed six factors for both the urban (coal combustion, traffic, oil combustion, industry, biomass combustion, and soil) and sub-urban (industry, oil combustion, traffic, road dust, soil resuspension, domestic heating) sampling sites. Loadings of grouped elements on these factors showed that the major sources of the elements in the atmosphere of Düzce were traffic, fossil fuel combustion, and metal industry-related emissions.     

南京市大气颗粒物中多环芳烃变化特征

逐月采集南京市大气中不同粒径的颗粒物,采用HPLC分析了2010年每个月PM_(10)和PM_(2.5)颗粒物样品中的多环芳烃(PAHs)的种类和浓度水平。结果表明:PM_(10)中PAHs年均值为25.07 ng/m~3,范围为11.03~53.56 ng/m3;PM_(2.5)中PAHs年均值为19.04 ng/m~3,范围为10.82~36.43 ng/m~3。PM_(10)和PM_(2.5)中PAHs总体浓度有着相似的变化趋势,呈现凹形变化曲线;在南京市大气颗粒物中吸附的PAHs大部分以5~6环的高环数组分为主,大部分PAHs和∑PAHs的相关性较好,年度变化幅度不大,分析结果表明,颗粒物中PAHs的来源与稳定的排放源相关,机动车排放不容忽视,与北方城市燃煤污染有着较大的区别。     

Characterisation of Particulate Matter Sampled during a Study of Children's Personal Exposure to Airborne Particulate Matter in a UK Urban Environment

The personal exposure of children aged 9 – 11 years to particulate matter (PM₁₀ and PM_2.5) was carried out between January and September 1997 in the London Borough of Barnet. Personal sampling along with home, garden and classroom microenvironmental monitoring was completed for all ten children. Each child was monitored for five days during winter, spring and summer. All children completed daily time activity diaries to provide information on any potential activities that could influence their exposure to particulate matter. Each evening a household activity questionnaire was also completed by the parents. Personal Environmental Monitors were used to sample personal exposure to PM₁₀ and PM_2.5. Harvard Impactors were used for the microenvironmental sampling of both size fractions. The children's mean personal exposure concentrations for PM₁₀ during winter, spring and summer were 72, 54 and 35 µg/m³ respectively and for PM_2.5 22, 17 and 18 µg/m³ respectively. In order to determine the potential sources of particulate matter, analysis of the Teflon filters has been undertaken. The physical characteristics of the particles have been identified using Scanning Electron Microscopy. The relationships between personal exposure concentrations and the different microenvironments will be discussed.     

Seasonal Variations of PM10 and TSP in Residential and Industrial Sites in an Urban Area of Kolkata, India

The objective of the study is to investigate seasonal and spatial variations of PM₁₀ (particulate matter with aerodynamic diameter less than or equal to 10 μm) and TSP (total suspended particulate matter) of an Indian Metropolis with high pollution and population density from November 2003 to November 2004. Ambient concentration measurements of PM₁₀ and TSP were carried out at two monitoring sites of an urban region of Kolkata. Monitoring sites have been selected based on the dominant activities of the area. Meteorological parameters such as wind speed, wind direction, rainfall, temperature and relative humidity were also collected simultaneously during the sampling period from Indian Meteorological Department, Kolkata. The 24 h average concentrations of PM₁₀ and TSP were found in the range 68.2–280.6 μg/m³ and 139.3–580.3 μg/m³ for residential (Kasba) area, while 62.4–401.2 μg/m³ and 125.7–732.1 μg/m³ for industrial (Cossipore) area, respectively. Winter concentrations of particulate pollutants were higher than other seasons, irrespective of the monitoring sites. It indicates a longer residence time of particulates in the atmosphere during winter due to low winds and low mixing height. Spread of air pollution sources and non-uniform mixing conditions in an urban area often result in spatial variation of pollutant concentrations. The higher particulate pollution at industrial area may be attributed due to resuspension of road dust, soil dust, automobile traffic and nearby industrial emissions. Particle size analysis result shows that PM₁₀ is about 52% of TSP at residential area and 54% at industrial area.     

Receptor model-based source apportionment of particulate pollution in Hyderabad, India

Air quality in Hyderabad, India, often exceeds the national ambient air quality standards, especially for particulate matter (PM), which, in 2010, averaged 82.2?±?24.6, 96.2?±?12.1, and 64.3?±?21.2 μg/m³ of PM₁₀, at commercial, industrial, and residential monitoring stations, respectively, exceeding the national ambient standard of 60 μg/m³. In 2005, following an ordinance passed by the Supreme Court of India, a source apportionment study was conducted to quantify source contributions to PM pollution in Hyderabad, using the chemical mass balance (version 8.2) receptor model for 180 ambient samples collected at three stations for PM₁₀ and PM_2.5 size fractions for three seasons. The receptor modeling results indicated that the PM₁₀ pollution is dominated by the direct vehicular exhaust and road dust (more than 60 %). PM_2.5 with higher propensity to enter the human respiratory tracks, has mixed sources of vehicle exhaust, industrial coal combustion, garbage burning, and secondary PM. In order to improve the air quality in the city, these findings demonstrate the need to control emissions from all known sources and particularly focus on the low-hanging fruits like road dust and waste burning, while the technological and institutional advancements in the transport and industrial sectors are bound to enhance efficiencies. Andhra Pradesh Pollution Control Board utilized these results to prepare an air pollution control action plan for the city.     

北京地区不同季节PM2.5和PM10浓度对地面气象因素的响应

利用2013年1月—2014年12月北京地区PM_(2.5)和PM_(10)监测数据和同期近地面气象观测数据,采用非参数分析法(Spearman秩相关系数)研究了北京地区PM_(2.5)和PM_(10)的浓度对不同季节地面气象因素的响应。结果表明:北京地区大气颗粒物浓度水平具有明显的季节特征,冬季大气颗粒物污染最严重,夏季最轻。不同季节影响颗粒物浓度水平的气象因素各不相同,其中风速和日照时数为主要影响因素。PM_(2.5)和PM_(10)质量浓度对气象因素变化的响应程度也有较大区别,PM_(2.5)/PM_(10)比值冬季最高,PM_(2.5)影响最大,春季最低,PM_(10)影响最大。这些结论可对制订科学有效的大气污染控制策略提供参考。     

Assessment of Ambient Air Quality in Urban Centres of Haryana (India) in Relation to Different Anthropogenic Activities and Health Risks

Considering the mounting evidences of the effects of air pollution on health, the present study was undertaken to assess the ambient air quality status in the fast growing urban centres of Haryana state, India. The samples were collected for total suspended particulate matter (TSPM), respirable suspended particulate matter (PM₁₀), sulfur dioxide (SO₂), and oxides of nitrogen (NO₂) during different seasons from 8 districts of Haryana during January, 1999 to September, 2000. The four types of sampling sites with different anthropogenic activities i.e. residential, sensitive, commercial and industrial were identified in each city. The ambient air concentration of TSPM and PM₁₀ observed was well above the prescribed standards at almost all the sites. The average ambient air concentrations of SO₂ and NO₂ were found below the permissible limits at all the centres. Comparatively higher concentration of SO₂ was observed during winter seasons, which seems to be related with the enhanced combustion of fuel for space heating and relatively stable atmospheric conditions. Air Quality Index (AQI) prepared for these cities shows that residential, sensitive and commercial areas were moderately to severely polluted which is a cause of concern for the residents of these cities. The high levels of TSPM and SO₂ especially in winter are of major health concern because of their synergistic action. The data from Hisar city reveals a significant increase in the total number of hospital visits/admissions of the patients with acute respiratory diseases during winter season when the level of air pollutants was high.     

Assessment of indoor and outdoor particulate air pollution at an urban background site in Iran

The relationship between indoor and outdoor particulate air pollution was investigated at an urban background site on the Payambar Azam Campus of Mazandaran University of Medical Sciences in Sari, Northern Iran. The concentration of particulate matter sized with a diameter less than 1 μm (PM_1.0), 2.5 μm (PM_2.5), and 10 μm (PM₁₀) was evaluated at 5 outdoor and 12 indoor locations. Indoor sites included classrooms, corridors, and office sites in four university buildings. Outdoor PM concentrations were characterized at five locations around the university campus. Indoor and outdoor PM measurements (1-min resolution) were conducted in parallel during weekday mornings and afternoons. No difference found between indoor PM₁₀ (50.1 ± 32.1 μg/m³) and outdoor PM₁₀ concentrations (46.5 ± 26.0 μg/m³), indoor PM_2.5 (22.6 ± 17.4 μg/m³) and outdoor PM_2.5 concentration (22.2 ± 15.4 μg/m³), or indoor PM_1.0 (14.5 ± 13.4 μg/m³) and outdoor mean PM_1.0 concentrations (14.2 ± 12.3 μg/m³). Despite these similar concentrations, no correlations were found between outdoor and indoor PM levels. The present findings are not only of importance for the potential health effects of particulate air pollution on people who spend their daytime over a period of several hours in closed and confined spaces located at a university campus but also can inform regulatory about the improvement of indoor air quality, especially in developing countries.     

Atmospheric aerosols at a regional background Himalayan site—Mukteshwar, India

Continuous aerosol measurements were made at a regional background station (Mukteshwar) located in a rural Himalayan mountain terrain from December 2005 to December 2008 for a period of 3 years. The average concentrations of particulate matter less than or equal to 10 μm (PM₁₀), particulate matter less than or equal to 2.5 μm (PM_2.5) and black carbon (BC) are 46.0, 26.6 and 0.85 μg/m³ during the study period. Majority of the PM₁₀ values lie below 100 μg/m³ while majority of the PM_2.5 values lie below 30 μg/m³. It is further seen that during the monsoon months, especially July and August, the average values are comparatively low. It is also noted that the PM_2.5/PM₁₀ ratios between 0.50 and 0.75 have the maximum frequency distribution in the data set. Furthermore, the monthly mean ratio of BC to PM_2.5 mass lies between 3.0 and 7.5 % during the study period. Though the average PM₁₀ and PM_2.5 concentrations during the study period are less than the respective Indian ambient air quality standards, however, they are still above the WHO guidelines and would have adverse health impacts. This shows that even in rural/background regions that are far away from major pollution sources or urban areas, the aerosol concentrations are significant and require long-term monitoring, source quantification and aerosol model simulations.     

PAHs in PM2.5 in Zhengzhou: concentration,carcinogenic risk analysis,and source apportionment

Ambient air samples were collected at two different locations between 2011 and 2012 in Zhengzhou, China in order to assess the concentration level, health risks, as well as the sources of polycyclic aromatic hydrocarbons (PAHs) in particulate matter (PM_2.5). The mean annual levels of PM_2.5 observed at industry site and residential site were 172?±?121 and 160?±?72 μg m^?3, respectively, which were about five times the annual value of proposed PM_2.5 standard (35 μg m^?3) in China. The PM_2.5 in all daily samples (n?=?47) exceeds the proposed PM_2.5 standard in China (75 μg m^?3) at both industrial and residential sites. Seasonal variations of PM_2.5 showed a clear trend of winter?>?autumn?>?spring?>?summer at both sites. The total concentrations of 16 PM_2.5-associated PAHs ranged from 61?±?51 to 431?±?281 and 38?±?25 to 254?±?189 ng m^?3, with mean value of 176?±?233 and 111?±?146 ng m^?3 at industry and residential sites, respectively. The major species were fluoranthene, pyrene, chrysene, benzo[b]fluoranthene and benzo[k]fluoranthene, and the concentration levels of PAHs in PM_2.5 were higher in winter than those of other seasons at both sites. The annual mean values of toxicity equivalency concentrations of ∑₁₆PAHs in PM_2.5 were 22.8 and 13.5 ng m^?3 in industry and residential area, respectively. In this study, the risk level of adult citizens through inhalation exposure to PAHs was calculated. The average estimates of lifetime inhalation cancer risks were approximately 8.9?×?10^?7 and 6.3?×?10^?7 for industry and residential sites, respectively. The main sources of 16 PAHs from both diagnostic ratios and principle component analysis identified as vehicular emissions and coal combustion.     

Suspended Particulate Matter Distribution in Rural-Industrial Satna and in Urban-Industrial South Delhi

An air quality sampling program was designed and implemented to collect the baseline concentrations of respirable suspended particulates (RSP = PM₁₀), non-respirable suspended particulates (NRSP) and fine suspended particulates (FSP = PM_2.5). Over a three-week period, a 24-h average concentrations were calculated from the samples collected at an industrial site in Southern Delhi and compared to datasets collected in Satna by Envirotech Limited, Okhla, Delhi in order to establish the characteristic difference in emission patterns. PM_2.5, PM₁₀, and total suspended particulates (TSP) concentrations at Satna were 20.5 ± 6.0, 102.1 ± 41.1, and 387.6 ± 222.4 μg m⁻³ and at Delhi were 126.7 ± 28.6, 268.6 ± 39.1, and 687.7 ± 117.4 μg m⁻³. Values at Delhi were well above the standard limit for 24-h PM_2.5 United States National Ambient Air Quality Standards (USNAAQS; 65 μg m⁻³), while values at Satna were under the standard limit. Results were compared with various worldwide studies. These comparisons suggest an immediate need for the promulgation of new PM_2.5 standards. The position of PM₁₀ in Delhi is drastic and needs an immediate attention. PM₁₀ levels at Delhi were also well above the standard limit for 24-h PM₁₀ National Ambient Air Quality Standards (NAAQS; 150 μg m⁻³), while levels at Satna remained under the standard limit. PM_2.5/PM₁₀ values were also calculated to determine PM_2.5 contribution. At Satna, PM_2.5 contribution to PM₁₀ was only 20% compared to 47% in Delhi. TSP values at Delhi were well above, while TSP values at Satna were under, the standard limit for 24-h TSP NAAQS (500 μg m⁻³). At Satna, the PM₁₀ contribution to TSP was only 26% compared to 39% in Delhi. The correlation between PM₁₀, PM_2.5, and TSP were also calculated in order to gain an insight to their sources. Both in Satna and in Delhi, none of the sources was dominant a varied pattern of emissions was obtained, showing the presence of heterogeneous emission density and that nonrespirable suspended particulate (NRSP) formed the greatest part of the particulate load.     

Using Archive Data to Investigate Trends in the Sources and Composition of Urban PM10 Particulate Matter: Application to Edinburgh (U.K.) Between 1992 and 1997

By extending the method of Stedman (1998), daily dataof atmospheric concentrations of gravimetricPM₁₀, black smoke (BS) and sulphate aerosol (SA)from national networks were analysed to determine thetrends in time of the contribution of different sources of particulate matter to total PM₁₀ measured in central Edinburgh. Since BS is an indicator of combustion-related primary sources of particulate matter, the quantity obtained by subtraction of daily BS from daily PM₁₀ is indicative of the contribution to total PM₁₀ from other primary sources and from secondary aerosol. This PM₁₀-BS statistic was regressed on SA, since SA is an indicator of variation in secondary aerosol source. For Edinburgh, SA is a considerably better indicator of PM₁₀-BS during summer than winter (reflecting the much greater photochemical generation of secondary aerosol in summer) and there is evidence that the contribution of other secondary aerosol (presumably nitrate aerosol) has increased relative to SA between 1992 and 1997. The concentration of non-combustion primary particulate material (marine aerosol, suspended dust) to PM₁₀ in Edinburgh has not changed over this period but is about twice that calculated as the U.K. national average. The increasing input to PM₁₀ from secondary aerosol sources at regional rather than urban scale has important implications for ensuring local air quality compliance. The method should have general applicability to other locations.     

Differences in the Spatial Distribution and Chemical Composition of PM10 Between the UK and Poland

The Fine Resolution Atmospheric Multi-pollutant Exchange Model was used to calculate the spatial distribution and chemical composition of PM₁₀ concentrations for two geographically remote countries in Europe—the UK and Poland—for the year 2007. These countries are diverse in terms of pollutant emissions as well as climate conditions. Information on the contribution of natural and anthropogenic as well as national and imported particles in total PM₁₀ concentrations in both countries is presented. The paper shows that the modelled national annual average PM₁₀ concentrations, calculated for the entire country area, are similar for the UK and Poland and close to 12 μg m^?3. Secondary inorganic aerosols dominate the total PM₁₀ concentrations in Poland. Primary particulate matter has the greatest contribution to total PM₁₀ in the UK, with large contribution of base cations. Anthropogenic sources predominate (81 %) in total PM₁₀ concentrations in Poland, whereas natural prevail in the UK—hence, the future reduction of PM₁₀ air concentrations by emissions reduction could be more difficult in the UK than in Poland.     

Air Pollution Concentrations of PM2.5, PM10 and NO2 at Ambient and Kerbsite and Their Correlation in Metro City – Mumbai

Ambient concentrations of PM_2.5 and PM₁₀ are of concern with respect to effects on human health and environment. Increased levels of mortality and morbidity have been associated with respirable particulate air pollution. In India, it is not yet mandatory to monitor PM_2.5 levels therefore very limited information is available on PM_2.5 levels. To understand the fine particle pollution and also correlate with PM₁₀ which are monitored regularly in compliance with ambient air quality standards. This study was carried out to monitor PM_2.5, PM₁₀, and NO₂ for about one year in a residential cum commercial area of Mumbai city with a view to understand their correlation. The average PM_2.5 concentration at ambient and Kerbsite was 43 and 69 μg/m³. The correlation coefficients between PM_2.5 and PM₁₀ at ambient and Kerbsite were 0.83 and 0.85 respectively thus indicating that most of the PM_2.5 and PM₁₀ are from similar sources. TSP, PM₁₀ levels exceeded Central Pollution Control Board(CPCB) standard during winter season. PM_2.5 levels also exceeded 24 hourly average USEPA standard during winter season indicating unhealthy air quality.     

Characteristics of Carbonaceous Aerosol at Taichung Harbor, Taiwan during Summer and Autumn Period of 2005

In recent years, suspended particle pollution has become a serious problem in Taiwan. The carbonaceous materials EC and OC are play important roles in various atmospheric processes. The primary OC/EC ratio approach is applied to assess the contribution of secondary organic aerosol (SOA) to the PM_2.5 and PM₁₀ mass at the Taichung harbor sampling site. The results indicated that the average EC and OC concentration were 1.06 and 6.50 μg m⁻³, respectively, in fine particulate. And the average EC and OC concentration were 4.04 and 40.32 μg m⁻³, respectively, in coarse particulate at Taichung Harbor sampling site. In addition, and the average EC/OC rations was 8.72 in fine particle, respectively, at Taichung Harbor, Taiwan during summer and autumn period of 2005. The fine particle exhibited high particulate concentrations in October, and lower concentration particulate occurred in August. And in this study OC and EC concentrations in this study are compared with those in other cities. The results of EC and OC concentration in this study are also compare with those other cities.     

Indoor exposure to respirable particulate matter and particulate-phase PAHs in rural homes in North India

In order to evaluate the exposure of the northern India rural population to polyaromatic hydrocarbon (PAH) inhalation, indoor pollution was assessed by collecting and analyzing the respirable particulate matter PM_2.5 and PM₁₀ in several homes of the village Bhithauli near Lucknow, UP. The home selection was determined by a survey. Given the nature of biomass used for cooking, homes were divided into two groups, one using all kinds of biomass and the second type using plant materials only. Indoor mean concentrations of PM_2.5 and associated PAHs during cooking ranged from 1.19 ± 0.29 to 2.38 ± 0.35 and 6.21 ± 1.54 to 12.43 ± 1.15 μg/m³, respectively. Similarly, PM₁₀ and total PAHs were in the range of 3.95 ± 1.21 to 8.81 ± 0.78 and 7.75 ± 1.42 to 15.77 ± 1.05 μg/m³, respectively. The pollutant levels during cooking were significantly higher compared to the noncooking period. The study confirmed that indoor pollution depends on the kind of biomass fuel used for cooking.     

Distribution of PM2.5 and PM10-2.5 in PM10 Fraction in Ambient Air Due to Vehicular Pollution in Kolkata Megacity

This research paper aims at establishing baseline PM₁₀ and PM_2.5 concentration levels, which could be effectively used to develop and upgrade the standards in air pollution in developing countries. The relative contribution of fine fractions (PM_2.5) and coarser fractions (PM_10-2.5) to PM₁₀ fractions were investigates in a megacity which is overcrowded and congested due to lack of road network and deteriorated air quality because of vehicular pollution. The present study was carried out during the winter of 2002. The average 24h PM₁₀ concentration was 304 μg/m³, which is 3 times more than the Indian National Ambient Air Quality Standards (NAAQS) and higher PM₁₀ concentration was due to fine fraction (PM_2.5) released by vehicular exhaust. The 24h average PM_2.5 concentration was found 179 μg/m³, which is exceeded USEPA and EU standards of 65 and 50 μg/m³ respectively for the winter. India does not have any PM_2.5 standards. The 24 h average PM_10-2.5 concentrations were found 126 μg/m³. The PM_2.5 constituted more than 59% of PM₁₀ and whereas PM₁₀-PM_2.5 fractions constituted 41% of PM₁₀. The correlation between PM₁₀ and PM_2.5 was found higher as PM_2.5 comprised major proportion of PM₁₀ fractions contributed by vehicular emissions.     

Particulate matter levels in a South American megacity: the metropolitan area of Lima-Callao,Peru

The temporal and spatial trends in the variability of PM₁₀ and PM_2.5 from 2010 to 2015 in the metropolitan area of Lima-Callao, Peru, are studied and interpreted in this work. The mean annual concentrations of PM₁₀ and PM_2.5 have ranges (averages) of 133–45 μg m^?3 (84 μg m^?3) and 35–16 μg m^?3 (26 μg m^?3) for the monitoring sites under study. In general, the highest annual concentrations are observed in the eastern part of the city, which is a result of the pattern of persistent local winds entering from the coast in a south-southwest direction. Seasonal fluctuations in the particulate matter (PM) concentrations are observed; these can be explained by subsidence thermal inversion. There is also a daytime pattern that corresponds to the peak traffic of a total of 9 million trips a day. The PM_2.5 value is approximately 40% of the PM₁₀ value. This proportion can be explained by PM₁₀ re-suspension due to weather conditions. The long-term trends based on the Theil-Sen estimator reveal decreasing PM₁₀ concentrations on the order of ?4.3 and ?5.3% year^?1 at two stations. For the other stations, no significant trend is observed. The metropolitan area of Lima-Callao is ranked 12th and 16th in terms of PM₁₀ and PM_2.5, respectively, out of 39 megacities. The annual World Health Organization thresholds and national air quality standards are exceeded. A large fraction of the Lima population is exposed to PM concentrations that exceed protection thresholds. Hence, the development of pollution control and reduction measures is paramount.     

Interpretation of roadside PM10 monitoring data from Sunderland,United Kingdom

Roadside PM₁₀ has been monitored by Partisol® at three sitesin Sunderland between August 1997 and February 1998. The sites chosen were an inner city kerbside site; a roadside site adjacentto a dual carriageway on the outskirts of Sunderland with an openaspect; and a rural site.The results indicate that there is a seasonal variation in the relationship between the sites in terms of monitored PM₁₀.In the winter there is a poor correlation between the sites whereas in the summer significant correlations are obtained. Of the sites monitored PM₁₀ is consistently highest at the inner city roadside site. During the summer, exceedances of theU.K. 50 g m^-3 standard (DETR, 2000) are associated with conditions suitable for the build-up of photochemical pollutionhowever during the winter period exceedances are recorded duringa variety of weather conditions.At the dual carriageway site PM_2.5 has also been recorded and contributions to measured PM₁₀ are 77% in summer and68% in winter. The results illustrate a number of inconsistencies between this study utilising the Partisol® andothers reporting results where PM₁₀ has been monitored by TEOM®.     

Determination of road dust loadings and chemical characteristics using resuspension

The contribution of fugitive dust from traffic to air pollution can no longer be ignored in China. In order to obtain the road dust loadings and to understand the chemical characteristics of PM₁₀ and PM_2.5 from typical road dust, different paved roads in eight districts of Beijing were selected for dust collection during the four seasons of 2005. Ninety-eight samples from 28 roads were obtained. The samples were resuspended using equipment assembled to simulate the rising process of road dust caused by the wind or wheels in order to obtain the PM₁₀ and PM_2.5 filter samples. The average road dust loading was 3.82 g m^− 2, with the highest of 24.22 g m^− 2 being in Hutongs in the rural–urban continuum during winter. The road dust loadings on higher-grade roads were lower than those on lower-grade roads. Attention should be paid to the pollution in the rural–urban continuum areas. The sums of element abundances measured were 16.17% and 18.50% for PM₁₀ and PM_2.5 in road dust. The average abundances of OC and EC in PM₁₀ and PM_2.5 in road dust were 11.52%, 2.01% and 12.50%, 2.06%, respectively. The abundance of elements, water-soluble ions, and OC, EC in PM₁₀ and PM_2.5 resuspended from road dust did not change greatly with seasons and road types. The soil dust, construction dust, dust emitted from burning coal, vehicle exhaust, and deposition of particles in the air were the main sources of road dust in Beijing. Affected by the application of snow-melting agents in Beijing during winter, the amount of Cl⁻ and Na⁺ was much higher during that time than in the other seasons. This will have a certain influence on roads, bridges, vegetations, and groundwater.