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1.
Size-segregated particle samples were collected using a Berner 5-stage impactor (stages 1?C5: 0.05?C0.14?C0.42?C1.2?C3.5?C10???m aerodynamic diameter). The means for all 169?days and for different categories of days were used for a characterization. The sorting criteria were (a) the distinction between winter (Wi, November to April) and summer (Su, May to October), (b) the distinction between air mass inflow from a sector West (W, 210?°?C320?°) and from a sector East (E, 35?°?C140?°). For the assignment of the air mass origin 96-h backward trajectories were used and four categories (WiW, WiE, SuW and SuE) with 48, 18, 42 and 29?days were established. The lowest mean particle mass concentrations were found for SuW and the highest for WiE with relative mass concentration distributions of 5.9, 28.2, 36.5, 18.0, and 11.4?% and 3.5, 22.7, 52.6, 16.7, and 4.5?% for stages 1?C5, respectively. The mass closure for water soluble ions, water, organic material (OM) and elemental carbon (EC) accounts for 81?C99?% of the gravimetric mass in Wi and for 60?C81?% for Su, depending on the stage. The fractions of nitrate were relatively high for WiW while sulphate fractions are high for WiE. The estimated concentrations of secondary organic carbon (SOA) on stage 3 for WiW, WiE, SuW and SuE were 0.32, 1.25, 0.27 and 0.58???gm?3, respectively. The highest amount of SOA is found for WiE, representing 59?% of organic carbon (OC). The highest difference in the percentages of SOA in OC was found between winter (WiW 55?%, WiE 59?%) and summer (SuW and SuE 74?%) indicating photochemical processes during long-range transport. The mean Carbon Preference Indices (CPI) are highest for SuE (stage 4: 7.57 and stage 5: 9.82) resulting mainly from plant wax abrasion in the surrounding forests. For WiE the mean PAH concentration on stage 3 (9.7?ngm?3) is about five times higher than for WiW, indicating long range transport following domestic heating and other combustion processes.  相似文献   

2.
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   

3.
The concentrations of PM10, PM2.5 and their water-soluble ionic species were determined for the samples collected during January to December, 2007 at New Delhi (28.63° N, 77.18° E), India. The annual mean PM10 and PM2.5 concentrations (± standard deviation) were about 219 (± 84) and 97 (±56) μgm−3 respectively, about twice the prescribed Indian National Ambient Air Quality Standards values. The monthly average ratio of PM2.5/PM10 varied between 0.18 (June) and 0.86 (February) with an annual mean of ∼0.48 (±0.2), suggesting the dominance of coarser in summer and fine size particles in winter. The difference between the concentrations of PM10 and PM2.5, is deemed as the contribution of the coarse fraction (PM10−2.5). The analyzed coarse fractions mainly composed of secondary inorganic aerosols species (16.0 μgm−3, 13.07%), mineral matter (12.32 μgm−3, 10.06%) and salt particles (4.92 μgm−3, 4.02%). PM2.5 are mainly made up of undetermined fractions (39.46 μgm−3, 40.9%), secondary inorganic aerosols (26.15 μgm−3, 27.1%), salt aerosols (22.48 μgm−3, 23.3%) and mineral matter (8.41 μgm−3, 8.7%). The black carbon aerosols concentrations measured at a nearby (∼300 m) location to aerosol sampling site, registered an annual mean of ∼14 (±12) μgm−3, which is significantly large compared to those observed at other locations in India. The source identifications are made for the ionic species in PM10 and PM2.5. The results are discussed by way of correlations and factor analyses. The significant correlations of Cl, SO42−, K+, Na+, Ca2+, NO3 and Mg2+ with PM2.5 on one hand and Mg2+ with PM10 on the other suggest the dominance of anthropogenic and soil origin aerosols in Delhi.  相似文献   

4.
Airborne particulates were monitored at an urban location of middle Indo-Gangetic Plain (IGP) and subsequently analyzed for particulate diversity and mixing states. Exceptionally high particulate loadings were found both in case of coarser (PM10: 157.5 ± 102.9 μgm?3, n = 46) and finer particulates (PM2.5: 92.5 ± 49.8 μgm?3). Based on particulate morphology and elemental composition, five different clusters of particulates namely tarball, soot, sulphur-rich, aluminosilicate and mineral species were found to dominate. Soot particles (0.1–5 μm) were found to be partly coated, having voids filled by coating material without being completely engulfed. A specific type of amorphous, carbonaceous spherules was evident in wintertime fine particulates signifying emissions from biomass burning and wild fire. Traces of S, Na and Ca were found associated with carbonaceous agglomerates suggesting its metal scavenging behavior. Particle laden filters were further processed for metallic and water soluble ionic species to constitute aerosol composition. Coarser particulates were characterized with higher metallic species (9.2–17.8 %), mostly of crustal origin (Ca: 5.5 %; Fe: 1.6 %; Zn: 1.3 % and Na: 3.8 %) while PM2.5 also revealed their association with metallic components (6.0–14.9 %) having Ca (4.6 %), Fe (0.9 %) and K (0.8 %) as principle constituents. Ca, Na and NH4 + found to generate chloride and sulphate salts thus affecting particulate hygroscopicity. Elevated fractions of NO3 ? and K+ in PM2.5 signified contribution of biomass burning while presence of Cl? with carbonaceous aerosols having traces of Si and K denoted contribution of farming and burning practices. Black carbon aerosol exhibited significant seasonal variability (6.9?21.9 μgm?3) which support larger association of carbonaceous aerosols in particle micrograph.  相似文献   

5.

This study presents the chemical composition (carbonaceous and nitrogenous components) of aerosols (PM2.5 and PM10) along with stable isotopic composition (δ13C and δ15N) collected during winter and the summer months of 2015–16 to explore the possible sources of aerosols in megacity Delhi, India. The mean concentrations (mean?±?standard deviation at 1σ) of PM2.5 and PM10 were 223?±?69 µg m?3 and 328?±?65 µg m?3, respectively during winter season whereas the mean concentrations of PM2.5 and PM10 were 147?±?22 µg m?3 and 236?±?61 µg m?3, respectively during summer season. The mean value of δ13C (range: ??26.4 to ??23.4‰) and δ15N (range: 3.3 to 14.4‰) of PM2.5 were ??25.3?±?0.5‰ and 8.9?±?2.1‰, respectively during winter season whereas the mean value of δ13C (range: ??26.7 to ??25.3‰) and δ15N (range: 2.8 to 11.5‰) of PM2.5 were ??26.1?±?0.4‰ and 6.4?±?2.5‰, respectively during the summer season. Comparison of stable C and N isotopic fingerprints of major identical sources suggested that major portion of PM2.5 and PM10 at Delhi were mainly from fossil fuel combustion (FFC), biomass burning (BB) (C-3 and C-4 type vegitation), secondary aerosols (SAs) and road dust (SD). The correlation analysis of δ13C with other C (OC, TC, OC/EC and OC/WSOC) components and δ15N with other N components (TN, NH4+ and NO3?) are also support the source identification of isotopic signatures.

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6.
An extensive aerosol sampling program was conducted during January-December 2006 over Kolkata (22o33?? N and 88o20?? E), a mega-city in eastern India in order to understand the sources, distributions and properties of atmospheric fine mode aerosol (PM2.5). The primary focus of this study is to determine the relative contribution of natural and anthropogenic as well as local and transported components to the total fine mode aerosol loading and their seasonal distributions over the metropolis. The average concentrations of fine mode aerosol was found to be 71.2?±?25.2???gm-3 varying between 34.5???gm-3 in monsoon and 112.6???gm-3 in winter. The formation pathways of major secondary aerosol components like nitrate and sulphate in different seasons are discussed. A long range transport of dust aerosol from arid and semi-arid regions of western India and beyond was observed during pre-monsoon which significantly enriched the total aerosol concentration. Vehicular emissions, biomass burning and transported dust particles were the major sources of PM2.5 from local and continental regions whereas sea-salt aerosol was the major source of PM2.5 from marine source regions.  相似文献   

7.
A strong dust-storm (23–25 April, 2009) occurred in the provinces of Inner Mongolia, Gansu, and Shanxi, North China. Cities along the storm path (from north to south: Xi’ning, Lanzhou, Chengdu, Changsha, and Guangzhou) all experienced a sharp increase in particle matter (PM10) concentration. This is the first case that an Asian dust storm hit Guangzhou in Southern China. The impacts of dust storm on the characteristics of PM were investigated using samples collected in Guangzhou during 27–29 April, 2009. In addition, the mass concentration and chemical composition during a normal non-dust period (12–14 May, 2009) were compared with those in dust period. The results show that the concentration of PM10 during the dust episode (0.231 mg m?3) was twice higher than that in the non-dust episode (0.103 mg m?3). Chemical analysis showed that concentrations of metal elements, enrichment factors of metal elements, and soluble ions during the dust episode were very different from those of non-dust. The total concentration of metal elements content in PM10 was 53.5 μg m?3 in the dust episode, which is about two times higher than that in non-dust episode (28.5 μg m?3). Increases in concentrations of Na, Ti, Zn, Cu, and Cr ranged from zero to 100% during the dust episode. However, the enrichment factors in non-dust episode were higher than that in dust-storm period, indicating that the above five chemicals originated mainly from local sources in Guangzhou. The concentrations of K, Mg, Al, Fe, Mn, V, and Co increased by over 100% in the dust episode, indicating their origins of remote sources. In the dust period, some water-soluble ions increased in PM10, but the main components in PM10 were SO4 ?, NO3 ? and NH4 +. At last, we assessed the sources of dusts by analyzing synoptic situation and back trajectories of air mass in Guangzhou, and demonstrated that the main source of the dust storm was from Mongolia.  相似文献   

8.
Zhang  Xiaoyu  Ji  Guixiang  Peng  Xiaowu  Kong  Lingya  Zhao  Xin  Ying  Rongrong  Yin  Wenjun  Xu  Tian  Cheng  Juan  Wang  Lin 《Journal of Atmospheric Chemistry》2022,79(2):101-115

In this study, 123 PM2.5 filter samples were collected in Wuhan, Hubei province from December 2014 to November 2015. Water- soluble inorganic ions (WSIIs), elemental carbon (EC), organic carbon (OC) and inorganic elements were measured. Source apportionment and back trajectory was investigated by the positive matrix factorization (PMF) model and the hybrid single particle lagrangian integrated trajectory (HYSPLIT) model, respectively. The annual PM2.5 concentration was 80.5?±?38.2 μg/m3, with higher PM2.5 in winter and lower in summer. WSIIs, OC, EC, as well as elements contributed 46.8%, 14.8%, 6.7% and 8% to PM2.5 mass concentration, respectively. SO42?, NO3? and NH4+ were the dominant components, accounting for 40.2% of PM2.5 concentrations. S, K, Cl, Ba, Fe, Ca and I were the main inorganic elements, and accounted for 65.2% of the elemental composition. The ratio of NO3?/SO42? was 0.86?±?0.72, indicating that stationary sources play dominant role on PM2.5 concentration. The ratio of OC/EC was 2.9?±?1.4, suggesting the existence of secondary organic carbon (SOC). Five sources were identified using PMF model, which included secondary inorganic aerosols (SIA), coal combustion, industry, vehicle emission, fugitive dust. SIA, coal combustion, as well as industry were the dominant contributors to PM2.5 pollution, accounting for 34.7%, 20.5%, 19.6%, respectively.

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9.
This study elucidates the characteristics of ambient PM2.5 (fine) and PM1 (submicron) samples collected between July 2009 and June 2010 in Raipur, India, in terms of water soluble ions, i.e. Na+, NH 4 + , K+, Mg2+, Ca2+, Cl?, NO 3 ? and SO 4 2? . The total number of PM2.5 and PM1 samples collected with eight stage cascade impactor was 120. Annual mean concentrations of PM2.5 and PM1 were 150.9?±?78.6 μg/m3 and 72.5?±?39.0 μg/m3, respectively. The higher particulate matter (PM) mass concentrations during the winter season are essentially due to the increase of biomass burning and temperature inversion. Out of above 8 ions, the most abundant ions were SO 4 2? , NO 3 ? and NH 4 + for both PM2.5 and PM1 aerosols; their average concentrations were 7.86?±?5.86 μg/m3, 3.12?±?2.63 μg/m3 and 1.94?±?1.28 μg/m3 for PM2.5, and 5.61?±?3.79 μg/m3, 1.81?±?1.21 μg/m3 and 1.26?±?0.88 μg/m3 for PM1, respectively. The major secondary species SO 4 2? , NO 3 ? and NH 4 + accounted for 5.81%, 1.88% and 1.40% of the total mass of PM2.5 and 11.10%, 2.68%, and 2.48% of the total mass of PM1, respectively. The source identification was conducted for the ionic species in PM2.5 and PM1 aerosols. The results are discussed by the way of correlations and principal component analysis. Spearman correlation indicated that Cl? and K+ in PM2.5 and PM1 can be originated from similar type of sources. Principal component analysis reveals that there are two major sources (anthropogenic and natural such as soil derived particles) for PM2.5 and PM1 fractions.  相似文献   

10.
Inhalable particles (PM10), with aerodynamic equivalent diameters that are generally 10 micrometers or smaller, are basic pollutants in many areas, especially in northern China, and thus the pollution from PM10 inhalable particulate matter is a growing concern for public health. Independent long-term observations are necessary to evaluate the efficacy of PM10 reduction actions. Variations in the PM10 concentration from 2006 to 2017 at an observation station (NJ) in Beijing were recorded and analyzed. The average value ±1 standard deviation of daily mean PM10 concentrations was 138.8 ±96.1 μg m-3 for 1307 days (accounting for 34.7% of the total days), showing PM10 concentration exceeding the National Ambient Air Quality Standard (NAAQS) 24-h average of 150 μg m-3. Particulate concentration depended upon various meteorological conditions as also observed in this work: at low wind speed (<4 m s-1), the concentrations of PM10 revealed a downward trend with -19 μg m-3 per unit of wind speed, but when wind speed rose (>4 m s-1), the values increased by 49 μg m-3 per unit of wind speed. In Beijing, air masses from northwest China, especially from the Gobi Desert and other desert areas, had net contributions to long-range transport of natural dust, enhancing the PM10 concentrations by up to 29%. Overall, PM10 mass concentration showed a significant downward trend with -8.0 μg/m3/yr from 2006 to 2017. Although with higher fluctuations in recorded data, similar downward trends derived from the ) in 2017 still exceeded the NAAQS standard. The results showed that there is still a long way to go to reduce PM10 in Beijing.  相似文献   

11.

Size-segregated aerosol particles were collected using a high volume MOUDI sampler at a coastal urban site in Xiamen Bay, China, from March 2018 to June 2020 to examine the seasonal characteristics of aerosol and water-soluble inorganic ions (WSIIs) and the dry deposition of nitrogen species. During the study period, the annual average concentrations of PM1, PM2.5, PM10, and TSP were 14.8?±?5.6, 21.1?±?9.0, 35.4?±?14.2 μg m?3, and 45.2?±?21.3 μg m?3, respectively. The seasonal variations of aerosol concentrations were impacted by the monsoon with the lowest value in summer and the higher values in other seasons. For WSIIs, the annual average concentrations were 6.3?±?3.3, 2.1?±?1.2, 3.3?±?1.5, and 1.6?±?0.8 μg m?3 in PM1, PM1-2.5, PM2.5–10, and PM>10, respectively. In addition, pronounced seasonal variations of WSIIs in PM1 and PM1-2.5 were observed, with the highest concentration in spring-winter and the lowest in summer. The size distribution showed that SO42?, NH4+ and K+ were consistently present in the submicron particles while Ca2+, Mg2+, Na+ and Cl? mainly accumulated in the size range of 2.5–10 μm, reflecting their different dominant sources. In spring, fall and winter, a bimodal distribution of NO3? was observed with one peak at 2.5–10 μm and another peak at 0.44–1 μm. In summer, however, the fine mode peak disappeared, likely due to the unfavorable conditions for the formation of NH4NO3. For NH4+ and SO42?, their dominant peak at 0.25–0.44 μm in summer and fall shifted to 0.44–1 μm in spring and winter. Although the concentration of NO3–N was lower than NH4–N, the dry deposition flux of NO3–N (35.77?±?24.49 μmol N m?2 d?1) was much higher than that of NH4–N (10.95?±?11.89 μmol N m?2 d?1), mainly due to the larger deposition velocities of NO3–N. The contribution of sea-salt particles to the total particulate inorganic N deposition was estimated to be 23.9—52.8%. Dry deposition of particulate inorganic N accounted for 0.95% of other terrestrial N influxes. The annual total N deposition can create a new productivity of 3.55 mgC m?2 d?1, accounting for 1.3–4.7% of the primary productivity in Xiamen Bay. In light of these results, atmospheric N deposition could have a significant influence on biogeochemistry cycle of nutrients with respect to projected increase of anthropogenic emissions from mobile sources in coastal region.

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12.

Pre and Post-Monsoon levels of ambient SO2, NO2, PM2.5 and the trace metals Fe, Cu, etc. were measured at industrial and residential regions of the Kochi urban area in South India for a period of two years. The mean PM2.5, SO2 and NO2 concentrations across all sites were 38.98?±?1.38 µg/m3, 2.78?±?0.85 µg/m3 and 11.90?±?4.68 µg/m3 respectively, which is lower than many other Indian cities. There was little difference in any on the measured species between the seasons. A few sites exceeded the NAAQS (define acronym and state standard) and most of the sites exceeded WHO (define acronym and state standard) standard for PM2.5. The average trace metal concentrations (ng/m3) were found to be Fe (32.58)?>?Zn (31.93)?>?Ni (10.13)?>?Cr (5.48)?>?Pb (5.37)?>?Cu (3.24). The maximum concentration of trace metals except Pb were reported in industrial areas. The enrichment factor, of metals relative to crustal material, indicated anthropogenic dominance over natural sources for the trace metal concentration in Kochi’s atmosphere. This work demonstrates the importance of air quality monitoring in this area.

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13.
Ambient concentrations of organic carbon (OC), elemental carbon (EC) and water soluble inorganic ionic components (WSIC) of PM10 were studied at Giridih, Jharkhand, a sub-urban site near the Indo Gangatic Plain (IGP) of India during two consecutive winter seasons (November 2011–February 2012 and November 2012–February 2013). The abundance of carbonaceous and water soluble inorganic species of PM10 was recorded at the study site of Giridih. During winter 2011–12, the average concentrations of PM10, OC, EC and WSIC were 180.2?±?46.4; 37.2?±?6.2; 15.2?±?5.4 and 18.0?±?5.1 μg m?3, respectively. Similar concentrations of PM10, OC, EC and WSIC were also recorded during winter 2012–13. In the present case, a positive linear trend is observed between OC and EC at sampling site of Giridih indicates the coal burning, as well as dispersed coal powder and vehicular emissions may be the source of carbonaceous aerosols. The principal components analysis (PCA) also identifies the contribution of coal burning? +?soil dust, vehicular emissions?+?biomass burning and seconday aerosol to PM10 mass concentration at the study site. Backward trajectoy and potential source contributing function (PSCF) analysis indicated that the aerosols being transported to Giridih from upwind IGP (Punjab, Haryana, Uttar Pradesh and Bihar) and surrounding region.  相似文献   

14.
This paper deals with the atmospheric concentrations of PM5 and PM2.5 particulate matter and its water soluble constituents along with the size distribution of ions and spatial variation at three different residential environments in a semiarid region in India. Samples were collected from the indoors and outdoors of urban, rural and roadside sites of Agra during October 2007–March 2008. The mean concentrations of PM2.5 indoors and outdoors were 178 μgm−3 and 195 μgm−3 while the mean concentrations of PM5 indoors and outdoors were 231.8 μgm−3 and 265.2 μgm−3 respectively. Out of the total aerosol mass, water soluble constituents contributed an average of 80% (33% anions, 50% cations) in PM5 and 70% (29% anions, 43% cations) in PM2.5. The indoor–outdoor ratio of water soluble components suggested additional aerosol indoor sources at rural and roadside sites. Indoor–outdoor correlations were also determined which show poor relationships among concentrations of aerosol ions at all three sites. Univariate Pearson correlation coefficients among water soluble aerosols were determined to evaluate the relationship between aerosol ions in indoor and outdoor air.  相似文献   

15.
Campaigns were conducted to measure Organic Carbon (OC) and Elemental Carbon (EC) in PM2.5 during winter and summer 2003 in Beijing. Modest differences of PM2.5 and PM10 mean concentrations were observed between the winter and summer campaigns. The mean PM2.5/PM10 ratio in both seasons was around 60%, indicating PM2.5 contributed significantly to PM10. The mean concentrations of OC and EC in PM2.5 were 11.2±7.5 and 6.0±5.0μg m-3 for the winter campaign, and 9.4±2.1 and 4.3±3.0 μg m-3 for the summer campaign, respectively. Diurnal concentrations of OC and EC in PM2.5 were found high at night and low during the daytime in winter, and characterized by an obvious minimum in the summer afternoon. The mean OC/EC ratio was 1.87±0.09 for winter and Z39±0.49 for summer. The higher OC/EC ratio in summer indicates some formation of Secondary Organic Carbon (SOC). The estimated SOC was 2.8 μg m-3 for winter and 4.2μg m-3 for summer.  相似文献   

16.
PM10 samples were collected to characterize the seasonal and annual trends of carbonaceous content in PM10 at an urban site of megacity Delhi, India from January 2010 to December 2017. Organic carbon (OC) and elemental carbon (EC) concentrations were quantified by thermal-optical transmission (TOT) method of PM10 samples collected at Delhi. The average concentrations of PM10, OC, EC and TCA (total carbonaceous aerosol) were 222?±?87 (range: 48.2–583.8 μg m?3), 25.6?±?14.0 (range: 4.2–82.5 μg m?3), 8.7?±?5.8 (range: 0.8–35.6 μg m?3) and 54.7?±?30.6 μg m?3 (range: 8.4–175.2 μg m?3), respectively during entire sampling period. The average secondary organic carbon (SOC) concentration ranged from 2.5–9.1 μg m?3 in PM10, accounting from 14 to 28% of total OC mass concentration of PM10. Significant seasonal variations were recorded in concentrations of PM10, OC, EC and TCA with maxima during winter and minima during monsoon seasons. In the present study, the positive linear trend between OC and EC were recorded during winter (R2?=?0.53), summer (R2?=?0.59) and monsoon (R2?=?0.78) seasons. This behaviour suggests the contribution of similar sources and common atmospheric processes in both the fractions. OC/EC weight ratio suggested that vehicular emissions, fossil fuel combustion and biomass burning could be the major sources of carbonaceous aerosols of PM10 at the megacity Delhi, India. Trajectory analysis indicates that the air mass approches to the sampling site is mainly from Indo Gangetic plain (IGP) region (Uttar Pradesh, Haryana and Punjab etc.), Thar desert, Afghanistan, Pakistan and surrounding areas.  相似文献   

17.
PM2.5 is a big issue as it is considerably more harmful than other sizes of particulate matter. World Health Organization (WHO) recommends 25 μg m?3 as the daily average concentration, and 10 μg m?3 per day as an annual average. To keep up with global trends, it is first necessary to understand the current status and characteristics of PM2.5 concentrations in Korea. Using the PM2.5 data measured by Seoul Metropolitan City from November 2005 to March 2012, the author analyzed its statistical characteristics and correlations with other air pollutants. For the time period from 2005 to 2012, the annual average concentration of PM2.5 was 27 μg m?3, three times the WHO standard. Also, the daily average PM2.5 concentration of 215 days per year also exceeded the WHO standard. However, the number days exceeding the Korean daily average standard of 50 μg m?3 to be enacted in 2014 was only three. PM2.5 concentration had a high correlation (r = 0.84) with PM10, and also showed high correlations with gaseous pollutants, such as SO2, NO2, and CO, but not O3. This study suggests that the Korean government should strengthen their standard to match the criteria used by WHO.  相似文献   

18.
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   

19.
Haze-fog conditions over northern India are associated with visibility degradation and severe attenuation of solar radiation by airborne particles with various chemical compositions. PM2.5 samples have been collected in Delhi, India from December 2011 to November 2012 and analyzed for carbonaceous and inorganic species. PM10 measurements were made simultaneously such that PM10–2.5 could be estimated by difference. This study analyzes the temporal variation of PM2.5 and carbonaceous particles (CP), focusing on identification of the primary and secondary aerosol emissions, estimations of light extinction coefficient (bext) and the contributions by the major PM2.5 chemical components. The annual mean concentrations of PM2.5, organic carbon (OC), elemental carbon (EC) and PM10–2.5 were found to be 153.6 ± 59.8, 33.5 ± 15.9, 6.9 ± 3.9 and 91.1 ± 99.9 μg m?3, respectively. Total CP, secondary organic aerosols and major anions (e.g., SO4 2? and NO3 ?) maximize during the post-monsoon and winter due to fossil fuel combustion and biomass burning. PM10–2.5 is more abundant during the pre-monsoon and post-monsoon. The OC/EC varies from 2.45 to 9.26 (mean of 5.18 ± 1.47), indicating the influence of multiple combustion sources. The bext exhibits highest values (910 ± 280 and 1221 ± 371 Mm?1) in post-monsoon and winter and lowest in monsoon (363 ± 110 and 457 ± 133 Mm?1) as estimated via the original and revised IMPROVE algorithms, respectively. Organic matter (OM =1.6 × OC) accounts for ~39 % and ~48 % of the bext, followed by (NH4)2SO4 (~21 % and ~24 %) and EC (~13 % and ~10 %), according to the original and revised algorithms, respectively. The bext estimates via the two IMPROVE versions are highly correlated (R2 = 0.95, root mean square error = 38 % and mean bias error = 28 %) and are strongly related to visibility impairment (r = ?0.72), mostly associated with anthropogenic rather than natural PM contributions. Therefore, reduction of CP and precursor gas emissions represents an urgent opportunity for air quality improvement across Delhi.  相似文献   

20.
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., PM2.5 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 PM2.5 (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 PM2.5 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.  相似文献   

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