Skip to main content
Log in

Temporal change of PM10 and its mass fraction during a dust storm in September 2009 in Australia

Air Quality, Atmosphere & Health Aims and scope Submit manuscript

Abstract

Frequent dust storms are a major concern in Australia due to associated human health risks and potential economic losses. From 23 to 24 September 2009, a dust storm passed over many east coast regions of Australia. This blanketed them with dust and reduced the visibility to a few hundred meters for several hours. The respirable particulate matter less than 10 μm (PM10) was monitored at 22 locations across New South Wales (NSW) by the Environmental Protection Agency. In addition, samples were collected in Sydney using a nine-stage cascade impactor both during and after the dust storm. The PM10 concentration over most of NSW jumped from less than 50 μg/m3 to more than 10,000 μg/m3 within a couple of hours and then dropped again to more normal levels (<50 μg/m3). The normal bimodal particle size distribution was observed to change to a multimodal distribution during a dust storm event. Also, the elemental ratio of Al to Si increased from 0.14 to 0.39 during the storm. An Al/Si ratio >0.3 indicates that the dust originated from inland desert areas and indeed was closely matched to Lake Eyre Basin crustal element data indicating it had travelled from central Australia to the eastern coasts.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

References

  • Allen AG, Nemitz E, Shi JP, Harrison RM, Greenwood JC (2001) Size distributions of trace metals in atmospheric aerosols in the United Kingdom. Atmos Environ 35:4581–4591. doi:10.1016/S1352-2310(01)00190-X

    Article  CAS  Google Scholar 

  • Aryal RK et al (2008) Seasonal PM10 dynamics in Kathmandu Valley. Atmos Environ 42:8623–8633

    Article  CAS  Google Scholar 

  • Aryal R, Kandel D, Acharya D, Chong MN, Beecham S (2012) Unusual Sydney dust storm and its mineralogical and organic characteristics. Environ Chem 9:537–546. doi:10.1071/EN12131

    Article  CAS  Google Scholar 

  • Aryal R, Kim A, Lee B-K, Kamruzzaman M, Beecham S (2013) Characteristics of atmospheric particulate matter and metals in industrial sites in Korea. Environ Pollut 2:10–21. doi:10.5539/ep.v2n4p10

    CAS  Google Scholar 

  • Ayala A, Brauer M, Mauderly JL, Samet JM (2012) Air pollutants and sources associated with health effects. Air Qual Atmos Health 5:151–167

    Article  CAS  Google Scholar 

  • Blanco A, de Tomasi F, Filippo E, Manno D, Perrone MR, Serra R, Tafuro AM, Tepore A (2003) Characterization of African dust over southern Italy. Atmos Chem Phys Discuss 3:2147–2159. doi:10.5194/acpd-3-4633-2003

    Article  CAS  Google Scholar 

  • Bowler JM (1976) Aridity in Australia: age, origins and expression in aeolian landforms and sediments. Earth Science Reviews, 12:279–310

  • Chan YC, Vowles PD, McTainsh GH, Simpson RW, Cohen DD, Bailey GM, McOrist GD (2000) Characterisation and source identification of PM10 aerosol samples collected with a high volume cascade impactor in Brisbane (Australia). Sci Total Environ 262:5–19. doi:10.1016/S0048-9697(00)00571-4

    Article  CAS  Google Scholar 

  • Cohen DD et al (2004) Multielemental analysis and characterization of fine aerosols at several key ACE-Asia sites. J Geophys Res D-Atmos 109(D19S12):11–18

    Google Scholar 

  • Cohen DD, Stelcer E, Garton D, Crawford J (2011) Fine particle characterisation, source apportionment and long range dust transport into the Sydney Basin: a long term study between 1998 and 2009. Atmos Pollut Res 2:182–189

    Article  CAS  Google Scholar 

  • Didyk BM, Simoneit BRT, Alvaro Pezoa L, Luis Riveros M, Anselmo Flores A (2000) Urban aerosol particles of Santiago, Chile: organic content and molecular characterization. Atmos Environ 34:1167–1179. doi:10.1016/S1352-2310(99)00403-3

    Article  CAS  Google Scholar 

  • Donaldson K, MacNee W (2001) Potential mechanisms of adverse pulmonary and cardiovascular effects of particulate air pollution (PM10). Int J Hyg Environ Health 203:411–415

    Article  CAS  Google Scholar 

  • Ekström M, McTainsh GH, Chappell A (2004) Australian dust storms: temporal trends and relationships with synoptic pressure distributions (1960–99). Int J Climatol 24:1581–1599

    Article  Google Scholar 

  • Goldberg MS, Burnett RT, Yale J-F, Valois M-F, Brook JR (2006) Associations between ambient air pollution and daily mortality among persons with diabetes and cardiovascular disease. Environ Res 100:255–267

    Article  CAS  Google Scholar 

  • Guerzoni S, Molinaroli E, Chester R (1997) Saharan dust inputs to the western Mediterranean Sea: depositional patterns, geochemistry and sedimentological implications. Deep-Sea Res II Top Stud Oceanogr 44:631–654. doi:10.1016/S0967-0645(96)00096-3

    Article  CAS  Google Scholar 

  • Jayaratne ER, Johnson GR, McGarry P, Cheung HC, Morawska L (2011) Characteristics of airborne ultrafine and coarse particles during the Australian dust storm of 23 September 2009. Atmos Environ 45:3996–4001. doi:10.1016/j.atmosenv.2011.04.059

    Article  CAS  Google Scholar 

  • Kamruzzaman M, Beecham S, Metcalfe AV (2011) Non-stationarity in rainfall and temperature in the Murray Darling Basin. Hydrol Process 25:1659–1675. doi:10.1002/hyp.7928

    Article  Google Scholar 

  • Kan H, Chen B (2003) Air pollution and daily mortality in Shanghai: a time-series study. Arch Environ Health 58:360–367

    Google Scholar 

  • Karanasiou AA, Sitaras IE, Siskos PA, Eleftheriadis K (2007) Size distribution and sources of trace metals and n-alkanes in the Athens urban aerosol during summer. Atmos Environ 41:2368–2381. doi:10.1016/j.atmosenv.2006.11.006

    Article  CAS  Google Scholar 

  • Kim KW, Kim YJ, Oh SJ (2001) Visibility impairment during Yellow Sand periods in the urban atmosphere of Kwangju, Korea. Atmos Environ 35:5157–5167

    Article  CAS  Google Scholar 

  • Knight AW, McTainsh GH, Simpson RW (1995) Sediment loads in an Australian dust storm: implications for present and past dust processes. CATENA 24:195–213. doi:10.1016/0341-8162(95)00026-O

    Article  Google Scholar 

  • Kuenzli N et al (2000) Public-health impact of outdoor and traffic-related air pollution: a European assessment. Lancet 356:795–801

    Article  Google Scholar 

  • Kulshrestha A, Satsangi PG, Masih J, Taneja A (2009) Metal concentration of PM2.5 and PM10 particles and seasonal variations in urban and rural environment of Agra, India. Sci Total Environ 407:6196–6204

    Article  CAS  Google Scholar 

  • Lee BK, Lee CH (2008) Analysis of acidic components, heavy metals and PAHS of particulate in the Changwon-Masan area of Korea. Environ Monit Assess 136:21–33

    Article  CAS  Google Scholar 

  • Leys JF, Heidenreich SK, Strong CL, McTainsh GH, Quigley S (2011) PM10 concentrations and mass transport during “Red Dawn”—Sydney 23 September 2009. Aeolian Res 3:327–342

    Article  Google Scholar 

  • Li X, Ge L, Dong Y, Chang H-C (2010) Estimating the greatest dust storm in eastern Australia with MODIS satellite images. In: Geoscience and Remote Sensing Symposium (IGARSS), 2010 I.E. International. 2010 IEEE, pp 1039–1042

  • Lim JM, Lee JH, Moon JH, Chung YS, Kim KH (2010) Airborne PM10 and metals from multifarious sources in an industrial complex area. Atmos Res 96:53–64

    Article  CAS  Google Scholar 

  • Limbeck A, Handler M, Puls C, Zbiral J, Bauer H, Puxbaum H (2009) Impact of mineral components and selected trace metals on ambient PM10 concentrations. Atmos Environ 43:530–538

    Article  CAS  Google Scholar 

  • Lu H-C (2002) The statistical characters of PM10 concentration in Taiwan area. Atmos Environ 36:491–502

    Article  CAS  Google Scholar 

  • Lyamani H, Olmo F, Alados-Arboledas L (2005) Saharan dust outbreak over southeastern Spain as detected by sun photometer. Atmos Environ 39:7276–7284

    CAS  Google Scholar 

  • Marcazzan GM, Vaccaro S, Valli G, Vecchi R (2001) Characterisation of PM10 and PM2.5 particulate matter in the ambient air of Milan (Italy). Atmos Environ 35:4639–4650

    Article  CAS  Google Scholar 

  • McTainsh G, Lynch A, Tews E (1998) Climatic controls upon dust storm occurrence in eastern Australia. J Arid Environ 39:457–466

    Article  Google Scholar 

  • Mehta S et al (2013) Air pollution and admissions for acute lower respiratory infections in young children of Ho Chi Minh City Air Quality. Atmos Health 6:167–179

    Article  CAS  Google Scholar 

  • Middleton NJ (1984) Dust storms in Australia: frequency, distribution and seasonality. Search 15:46–47

    Google Scholar 

  • Offenberg JH, Baker JE (2000) Aerosol size distributions of elemental and organic carbon in urban and over-water atmospheres. Atmos Environ 34:1509–1517. doi:10.1016/S1352-2310(99)00412-4

    Article  CAS  Google Scholar 

  • Ostro B, Chestnut L, Vichit-Vadakan N, Laixuthai A (1999) The impact of particulate matter on daily mortality in Bangkok, Thailand. J Air Waste Manag Assoc 49(SPEC. ISS.):100–107

  • Radhi M, Box MA, Box GP, Mitchell RM, Cohen DD, Stelcer E, Keywood MD (2010a) Optical, physical and chemical characteristics of Australian continental aerosols: Results from a field experiment. Atmos Chem Phys 10:5925–5942

    Article  CAS  Google Scholar 

  • Radhi M, Box MA, Box GP, Mitchell RM, Cohen DD, Stelcer E, Keywood MD (2010b) Size-resolved mass and chemical properties of dust aerosols from Australia’s Lake Eyre Basin. Atmos Environ 44:3519–3528

    Article  CAS  Google Scholar 

  • Ragosta M, Caggiano R, D’Emilio M, Sabia S, Trippetta S, Macchiato M (2006) PM10 and heavy metal measurements in an industrial area of southern Italy. Atmos Res 81:304–319

    Article  CAS  Google Scholar 

  • Santamaria J, Fernández M, Mendez J, Bomboi M (1990) Particle size distribution of metals in the atmosphere of Madrid (Spain) Freseniu’s. J Anal Chem 337:362–365

    Article  CAS  Google Scholar 

  • Spurny KR (1996) Aerosol air pollution its chemistry and size dependent health effects. J Aerosol Sci 27:S473–S474

    Article  Google Scholar 

  • Stefanski R, Sivakumar M (2009) Impacts of sand and dust storms on agriculture and potential agricultural applications of a SDSWS. In: IOP Conference Series: Earth and Environmental Science. vol 1. IOP Publishing, p 012016

  • Strong CL, Parsons K, McTainsh GH, Sheehan A (2011) Dust transporting wind systems in the lower Lake Eyre Basin, Australia: a preliminary study. Aeolian Res 2:205–214. doi:10.1016/j.aeolia.2010.11.001

    Article  Google Scholar 

  • Tozer PR (2012) The cost of red dawn to the NSW economy. 56th Conference on Australian Agricultural and Resource Economics Society, Fremantle

    Google Scholar 

  • Tozer P, Leys J (2013) Dust storms—what do they really cost? Rangel J 35:131–142. doi:10.1071/RJ12085

    Article  Google Scholar 

  • Vanderstraeten P et al (2008) Dust storm originate from Sahara covering Western Europe: a case study. Atmos Environ 42:5489–5493. doi:10.1016/j.atmosenv.2008.02.063

    Article  CAS  Google Scholar 

  • Viidanoja J, Sillanpää M, Laakia J, Kerminen V-M, Hillamo R, Aarnio P, Koskentalo T (2002) Organic and black carbon in PM2.5 and PM10: 1 year of data from an urban site in Helsinki, Finland. Atmos Environ 36:3183–3193. doi:10.1016/S1352-2310(02)00205-4

    Article  CAS  Google Scholar 

  • Wang X, Oenema O, Hoogmoed W, Perdok U, Cai D (2006) Dust storm erosion and its impact on soil carbon and nitrogen losses in northern China. Catena 66:221–227

    Article  Google Scholar 

  • Washington R, Todd M, Middleton NJ, Goudie AS (2003) Dust-storm source areas determined by the total ozone monitoring spectrometer and surface observations. Ann Assoc Am Geogr 93:297–313

    Article  Google Scholar 

  • Watanabe M et al (2011) Correlation between Asian dust storms and worsening asthma in Western Japan. Allergol Int 60:267

    Article  CAS  Google Scholar 

  • Xie S, Yu T, Zhang Y, Zeng L, Qi L, Tang X (2005) Characteristics of PM10, SO2, NOx and O3 in ambient air during the dust storm period in Beijing. Sci Total Environ 345:153–164. doi:10.1016/j.scitotenv.2004.10.013

    Article  CAS  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Rupak Aryal.

Appendices

Appendix 1

 

Liverpool

Prospect

Macarthur

Bringelly

Chullora

Randwick

Rozelle

Richmond

Lindfield

St Marys

Vineyard

Albion Park

Wollongong

Kembla Grange

Wallsend

Newcastle

Beresfield

Tamworth

Albury

Wagga Wagga

Bathurst

Monash, ACT

Latitude

33.93

33.79

34.07

33.90

33.89

33.93

33.87

33.62

33.78

33.80

33.66

34.58

34.42

34.48

32.90

32.93

32.80

31.11

36.05

35.10

33.40

35.43

Longitude

150.91

150.91

150.78

150.76

151.05

151.24

151.16

150.75

151.15

150.77

150.85

150.79

150.89

150.82

151.67

151.76

151.66

150.91

146.97

147.36

149.57

149.10

22/09 1:00

17.2

15.2

16.5

17.4

17.7

17.9

18.9

19.1

16.9

13.7

17

22.3

 

18.3

17.7

28.5

20.3

3.6

14.4

9.1

8.7

11.5

2:00

15.9

14.5

17.6

24.3

18.2

17.2

19.8

8.3

17.7

7.4

15.4

18.1

 

18.3

19.7

29.2

21.9

6.2

12.8

8.5

4.5

12.0

3:00

14.6

13.9

15

25

14

19.5

17

11.3

12.8

6.5

12.9

20.6

30.4

19.5

8.7

21.7

20.5

6.4

25.7

14.4

4.5

4.5

4:00

14.7

14.4

14.1

20.4

14.7

22.1

18.8

18.9

14

13.6

14.4

20.8

40.5

22.2

8.2

17.4

22.9

5.8

36.7

28.5

4.5

14.0

5:00

14.9

11.1

18

10.1

18.3

24.5

18.9

14.2

10.6

16.6

12.6

17.8

25.3

18.8

5.9

24.1

19.3

9.9

65.2

52.7

6.9

9.0

6:00

14.2

9.1

18.5

7.6

48.1

5.5

6.4

8.9

9.9

7.8

9.1

17.6

16.3

16.9

15.2

25.3

17.9

9.2

55.1

114

9.3

5.5

7:00

33.3

12.1

22.1

22.3

91.3

12.8

8.2

13.3

9.6

13.8

9

19

17

18.4

31.4

26

19.4

16.4

19.2

89.7

13.7

3.5

8:00

17.5

14.5

21.1

29

35.2

11.6

11.5

15

13

23.4

14.6

20.7

21.4

28.1

20.1

20.3

20.7

13.5

23.7

61.1

15.2

29.5

9:00

 

25.6

22.1

27.8

22

21.2

20.4

19.9

17.9

15.8

14.2

37.8

39.7

93.5

22.1

21.4

16.9

17.6

17.6

67.3

18.7

148.5

10:00

 

28.8

51

42.9

43.9

31

28.6

22.4

21.7

18.6

16.9

305.7

80.7

266.2

36.4

36.1

29.9

20.1

10.3

24

19.4

209.5

11:00

 

27.8

50.9

55

35.9

30.8

30.7

41.2

22.2

30.9

30.5

342.1

144.3

289.9

46.8

39.1

37.4

34.7

4.5

39.6

31.1

166.0

12:00

51.7

49.5

38.4

62.2

61.4

36.2

29.3

80.4

33.2

44.5

46.9

186.3

132.4

175.4

54.4

48.2

57.7

31.5

6.2

52.1

19.9

132.5

13:00

60.5

46.4

41.7

63.7

97

39.8

43.1

38.4

36

46.4

41.7

75.7

63.1

90

110.2

113.8

44.7

20.4

5

56.4

22

100.5

14:00

40.7

40.5

59.7

44.3

69.1

45.3

39.8

35.9

44.5

39

44.5

59.4

52.4

76.5

47.4

43.9

17.5

24.4

6

53.3

23.1

262.5

15:00

48.1

44.7

69.7

53

78.3

43.5

50.3

39

47.6

45.5

42.3

69.5

55.3

69.9

29.3

28.3

10.5

19

7.6

81.9

23.6

630.5

16:00

48.7

38.4

66.3

53.4

54.1

41.8

42

34.7

40

43.8

35

93

67.2

128.6

25.9

23.6

15.6

19.8

6.7

138.9

22.9

851.0

17:00

50.7

40.9

61.9

62.5

52

42.1

38.7

27.8

30.6

48.1

32.4

119.6

74.6

125.1

27.5

25.1

19.4

19.3

5.8

196.5

26.8

681.0

18:00

40.2

38.2

56.7

48.6

38

36.2

35.5

32

26.7

39

36.9

121.5

86.1

73.7

25.9

18.7

17.1

21.3

13

213.1

25.8

586.5

19:00

46

50

28.9

44.3

62.4

48.6

53

45.3

34.7

43.4

44.8

16.1

13.2

13.6

23.6

22.2

19

17.9

10.3

210.1

4.4

497.0

20:00

4.9

4.7

5.7

4.5

7

12.2

23.4

10

19.3

0.7

11

10.7

11.1

11.8

15.8

17.1

17.1

15.4

12.3

243.2

10.8

418.5

21:00

11.2

12.3

6.4

15.2

15.7

13.3

15.6

14

14.7

12.2

10.8

11.8

 

8.4

16.7

22.4

22.5

10.6

8.8

210.4

11.5

123.5

22:00

6

8.6

9.9

11

11.2

11.5

8.8

17.4

15.8

8.3

14.4

9.6

10

34.5

25.1

32.2

28.9

11.8

5.5

154.3

18.1

46.5

23:00

13.4

11.1

13.8

15.6

11.3

12.6

8.8

13.6

9.7

14.3

16.8

13.7

16.7

17.1

15.2

17.8

17.8

14.2

6.8

105.7

17.1

33.5

23/09 0:00

13.4

17.5

15.1

16.1

16.2

14.5

13.4

20.6

14.8

15.7

17.5

17.6

21

20.7

11.2

14.2

12.2

26.2

5.6

105.4

18.6

35.5

1:00

10.8

16.9

11.7

12.4

11.9

6

7.4

10.6

12.2

8.3

7.7

12.1

16

14.7

6.6

6.6

7.6

18

21.1

679.7

28.7

33.5

2:00

16.3

14.8

15.2

16.3

17.3

16.9

15.7

10.6

14.7

10.7

12.4

21.1

20.9

24.2

11.8

11.8

6.8

10.9

50

178.6

424.6

32.5

3:00

14.3

27.1

13.1

21.9

46.6

39.3

73.6

20

71.3

10.7

28.3

15.4

19.6

20

30.9

18.1

22.5

41.1

51.3

87.4

4,268.2

36.5

4:00

47.4

98.6

38.8

36.9

92

79.4

96.2

331.7

77.3

77.1

180

340.1

20.5

141.4

63.2

59

27.6

1,631.4

53

40.8

15,388.2

 

5:00

2,559.9

2,151.5

1,983.4

5,238.9

1,155.3

518.2

627.4

5,039

690.6

4,758.8

4,216.2

5,470.7

3,193.9

4,503.9

34.4

26.3

25.3

3,128.5

45

24

11,512.1

1,475.0

6:00

13,516

11,682.3

10,282.1

15,366.1

10,220

7,714.1

7,333

11,160

7,570.7

13,888

11,174.4

10,995.3

7,406.4

8,408.1

2,590.4

2,253

3,987.7

5,216.9

53

23.9

6,186.6

710.0

7:00

9,650.5

10,871.2

8,127.6

9,477.3

9,758.2

11,799

10,083

8,422.1

9,538.8

10,009.2

9,656.6

11,376.8

9,576.9

9,481.8

7,962.1

8,967.3

8,362.4

6,804.6

49.3

13.7

4,238.5

179.5

8:00

5,574.4

5,193.4

3,045.3

4,888.2

5,459

8,530.1

7,283.2

3,575.8

6,989.5

3,607.9

3,569.1

1,849.8

3,801.9

1,939.7

8,997.4

10,651.2

9,209.8

4,576.8

18.2

11.4

1,667.9

75.0

9:00

2,446.6

3,518.3

1,643.8

1,703.7

3,210.1

4,699.1

4,147.2

3,624.8

4,534.2

2,472.7

4,366.5

894.8

1,297.1

1,085.8

7,620.3

9,282.1

7,023.6

4,685.5

15

14.2

2,371.5

15.0

10:00

1,223.3

2,024.8

724.9

1,026.6

1,776.8

2,964

2,824

2,499.1

3,001.3

1,710.6

2,697.8

439.2

482.2

486.5

6,255.6

7,322.4

6,437.4

4,650.2

16.5

18

2,314.5

 

11:00

1,297.4

2,163.9

396.1

1,052.9

1,706.2

2,277.6

2,415.3

2,104.5

2,632.6

1,701.8

2,485.7

297.3

333.8

492.1

4,875.9

5,811.7

4,472.6

3,173.8

14.9

14.3

837.4

1.5

12:00

773

1,535.2

231.1

665.6

1,079.8

1,621.7

1,444.4

1,161.7

1,739.2

833.9

1,117.3

313.1

420.8

870.3

2,985.8

3,894.3

 

2,757.6

10.8

8.6

905.3

 

13:00

195.2

358

416

170.3

284

566.7

445.6

699.2

587.5

237.1

562

134.2

356.3

219.7

2,490.2

2,940.1

 

2,451.7

13.7

9.1

345.4

0.5

14:00

113.5

213.4

213.5

226.5

123.1

183.3

219.3

283.1

379.7

159.8

319.8

105.4

130.9

123.1

1,759

 

1,764.4

1,090.3

12.6

13.2

115.7

2.5

15:00

103.7

99.7

64.7

71.6

86.6

195.8

105.3

124

144.5

69.5

119.5

58.7

98.6

119.6

976.8

 

980.7

840.1

10.1

11.1

13.4

10.0

16:00

68.1

53.6

50.3

76.7

42.4

98

51.7

38

66

42.5

49.2

22.3

30

55.2

 

838

671.3

566.8

13.9

15.8

15.2

7.5

17:00

77.5

21

40.1

93.6

109

80.8

35.4

39

42.2

1

36.6

66.1

49.4

46

 

564.6

401.1

461

9.5

13.1

12.1

3.0

18:00

32.9

50.2

34.7

61.1

56.3

34.5

70.9

33.8

23.1

47.9

23.8

51.1

48.9

46

303.2

331

266.8

321

8.3

17.1

19

9.5

19:00

27.4

67.5

43.4

41.8

22.5

28.5

44.6

22.1

45.8

43.6

26.5

44.2

21.8

12.4

149.7

178.9

115.5

144.3

7.5

13.2

22.1

5.5

20:00

41.8

2.7

34.6

35.9

27.8

57.9

33.6

15.3

21.1

51.6

22.5

57

28.2

19.9

72.6

87.3

65.7

104.3

9.1

11.9

23.1

7.5

21:00

43.4

58.1

40.9

41.9

34.4

44.8

51.5

18.9

35.3

23.3

22.1

44.2

84.7

29.1

44.3

54.5

42.1

104.3

4.9

9.2

20.7

2.0

22:00

41.9

43.3

23.9

41.2

36.2

43.1

48.2

31.2

43

35

41.7

12.1

19.6

14.4

31.4

37.9

34.1

76.7

4.3

10.8

5.3

4.0

23:00

20.7

40.8

19.6

24.9

22.3

31.9

28

12.9

29.4

17.8

17.9

2.1

8.2

7.7

25.7

32.1

30.9

80.2

4.6

7.9

0.1

2.5

24/09 0:00

18.7

20.1

15.2

21.5

15.6

24.3

23.8

18

20.6

47.7

19.1

7.9

22

15

19.1

22.1

22.7

58.5

4.2

6.1

9.4

4.0

1:00

16.1

31.6

2.7

16.7

18.9

15.3

19.9

14.5

21.2

 

25.7

7.5

13.8

13.6

13.4

19.1

26

42.7

5

3.4

 

0.5

2:00

 

3.3

13.5

4.9

 

11.6

  

20

13.5

7.8

3

10.3

1.2

17.1

18.6

28.9

32.8

4.2

5.3

3.2

2.0

3:00

15.4

2.1

6

13.2

10.3

2.6

6.2

 

2.7

  

13.4

 

8

16.7

23.3

26.8

21.4

5.8

5.9

 

0.5

4:00

5.6

24.5

4.3

9.9

5.4

5.6

12.7

8.6

15.3

18.1

   

0.7

18.6

23.5

27.3

20.9

5.6

5.6

6.7

 

5:00

 

14.8

9.7

5

3.1

2.9

8.8

16.5

24

25.5

16.4

11.3

15.5

17

18.1

21.7

23.8

16.1

6.6

7.2

9.4

3.5

6:00

13.2

18.3

18.1

14.3

17.8

3.8

11

2.2

10

25.3

19.1

10.5

17

10.3

16.2

21.6

22

10.4

5.7

9.1

0.1

0.5

7:00

21.7

40.9

17.8

21.3

26.1

26.8

22.6

71.5

23.4

40.2

30.6

20.8

16.3

16.5

19.3

21.4

25.4

19.3

9.1

7.8

13.5

 

8:00

13.1

7

8.3

18.6

20.6

23.2

22.7

 

18.9

 

12.9

6.3

8.7

11.7

19.1

23.2

23.7

48.1

10.6

9

  

9:00

10.8

7.9

11.1

1.8

13.7

10.6

9.1

18

6.4

12.8

 

12

13.2

18.8

17.4

23

20.3

 

12.7

13.5

 

3.0

10:00

2.9

11.6

 

5.2

14.5

 

15.6

18.3

14.7

12.8

6.9

6.3

13.3

16.8

23.5

22.8

23.3

 

14

8.1

  

11:00

 

12.3

  

10.6

6.2

  

6.8

8.9

9.2

  

2.9

17.3

22.9

24

20

10.9

4.7

 

7.0

12:00

6.7

 

11

11.5

8.5

21.6

10.8

14.9

 

2

  

15.2

21.6

17.7

18.1

17.3

9.5

13.7

8

4.4

2.5

13:00

18.7

23.9

11.1

29.7

16.7

 

15.3

32.3

30.8

43.5

25.9

47.5

9.5

 

40.9

22.9

22.9

 

9.6

11.3

27.2

 

14:00

29.3

33.5

11.5

 

33

24.4

31.9

 

20.8

 

19.8

40.3

23.2

 

32.5

38.7

33.9

 

9.1

4.9

11.2

 

15:00

  

13.6

 

9.1

106

22.8

 

6.7

23.6

11.1

29.5

7.6

14.7

38

42.1

31.5

39.8

12.8

 

16.3

6.5

16:00

  

18.7

47.5

29.2

33.9

15.7

11.7

14.2

19.5

27.1

27.3

13.7

26.6

34.6

38.4

28.2

32.7

12.1

10.1

15.3

 

17:00

 

4.2

13.1

37.9

26.9

 

39.5

13.6

28.8

18.4

25.6

24.5

17.7

23.4

26

52.1

25.8

35.2

13.5

12.2

1.8

6.0

18:00

58

10.2

11.9

30.4

25

27.1

15.3

13

23.3

10.8

3.8

23.4

 

11

20.4

52.4

26.3

44.1

13.8

14.6

0.4

2.5

19:00

39.5

12.2

8.6

26.1

23.6

12

26

14.1

19.8

3.7

4.9

18.9

11

10.3

22.7

79.6

27.2

21

16.8

18.1

29.9

9.0

20:00

30.9

10.2

10.6

20

6.9

4.9

7.7

10.2

11.2

11.1

5.3

16.7

30.5

10.6

29.8

67.1

35.1

31.6

14

22.8

38

0.0

21:00

24.4

8.4

7.1

18.8

14.2

12.1

11

10.7

16.5

7.6

15.7

16.8

16.5

8.6

25

22.1

32

22.7

16.8

31.1

27.8

6.0

22:00

21.1

10.7

7.1

17.7

12.2

12.5

19.1

11.7

13.3

17.2

21.7

14.5

6.2

7.8

19.2

19.7

29.8

26.5

17.8

24.2

1.5

7.5

23:00

23

11

6.7

20.7

25.9

13.4

24.2

12

15.5

31.4

15.3

14

8.9

8.7

12.4

6.3

19.9

25.6

6

23.9

4.8

8.0

Appendix 2. PM10 concentration before, during, and after the dust storm across NSW every 3 h

figure afigure a

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Aryal, R., Beecham, S., Kamruzzaman, M. et al. Temporal change of PM10 and its mass fraction during a dust storm in September 2009 in Australia. Air Qual Atmos Health 8, 483–494 (2015). https://doi.org/10.1007/s11869-014-0297-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11869-014-0297-0

Keywords

Navigation