Influences of ambient air pollutants and meteorological conditions on ozone variations in Kaohsiung, Taiwan

Original Paper

Abstract

The complex process of ozone formation, its precursor compounds (volatile organic compounds (VOCs) and nitrogen oxides (NOx)) emissions, accompanying with meteorological conditions, makes troposphere ozone difficult to control. This study applies dynamic factor analysis (DFA) to investigate the time series of ambient ozone concentrations and their associations with meteorological variables. The analyses were applied on the hourly data collected at the four monitoring stations in Kaohsiung (Taiwan) during the 72-h periods with three events in high and low ozone episodes in 2009. According to the optimal DFA model, NOx negatively control ozone variations in all events. Relative humidity (RH) only negatively influences the ozone fluctuations in low ozone episode. The sea–land wind speed (i.e. west direction) and air temperature positively affect ozone fluctuations in high ozone episode. CO significantly influences ozone fluctuations in main city area for high ozone episode and in all stations for low ozone episode. However, VOC did not significantly correlate with ozone fluctuations for both ozone episodes. The results show that ozone conditions of both episodes were in NOx-saturated regimes, where increased NOx would result in lower ozone. Temperature, RH, and sea–land wind speed can be treated as metrological variables, which significantly vary the concentrations of surface-level ozone. This study shows DFA can provide a quantitative insight into the temporal variations of CO, NOx, and meteorological conditions effects on ozone variations that will be a reference to air quality management in the study area.

Keywords

Dynamic factor analysis Volatile organic compounds Sea–land wind Nitrogen oxides Carbon monoxide NOx-saturated 

References

  1. Abdul-Wahab SA, Bakheit CS, Al-Alawi SM (2005) Principal component and multiple regression analysis in modelling of ground-level ozone and factors affecting its concentrations. Environ Model Softw 20:1263–1271CrossRefGoogle Scholar
  2. Akaike H (1974) A new look at the statistical model identification. IEEE Trans Autom Control 19:716–723CrossRefGoogle Scholar
  3. Ashmore MR (2005) Assessing the future global impacts of ozone on vegetation. Plant Cell Environ 28:949–964CrossRefGoogle Scholar
  4. Barros N, Toll I, Soriano C, Jiménez P, Borrego C, Baldasano JM (2003) Urban photochemical pollution in the Iberian peninsula: the Lisbon and Barcelona airsheds. J Air Waste Manag Assoc 53:347–359Google Scholar
  5. Campo-Bescós MA, Muñoz-Carpena R, Kaplan DA, Southworth J, Zhu L, Waylen PR (2013) Beyond precipitation: physiographic gradients dictate the relative importance of environmental drivers on savanna vegetation. PLoS One 8:e72348CrossRefGoogle Scholar
  6. Carter WPL (1994) Development of ozone reactivity scales for volatile organic compounds. J Air Waste Manag Assoc 44:881–899CrossRefGoogle Scholar
  7. Chang CC, Chena TY, Lina CY, Yuan CS, Liu SC (2005) Effects of reactive hydrocarbons on ozone formation in southern Taiwan. Atmos Environ 39:2867–2878CrossRefGoogle Scholar
  8. Chelani AB, Devotta S (2006) Air quality forecasting using a hybrid autoregressive and nonlinear model. Atmos Environ 40:1774–1780CrossRefGoogle Scholar
  9. Cheng WL (2002) Ozone distribution in coastal central Taiwan under sea-breeze conditions. Atmos Environ 36:3445–3459CrossRefGoogle Scholar
  10. Duan JC, Tan JH, Yang L, Wu S, Hao JM (2008) Concentration, sources and ozone formation potential of volatile organic compounds (VOCs) during ozone episode in Beijing. Atmos Res 88:25–35CrossRefGoogle Scholar
  11. Erzini K (2005) Trends in NE Atlantic landings (southern Portugal): identifying the relative importance of fisheries and environmental variables. Fish Oceanogr 14:195–209CrossRefGoogle Scholar
  12. Felipe-Sotelo M, Gustems L, Hernández I, Terrado M, Tauler R (2006) Investigation of geographical and temporal distribution of tropospheric ozone in Catalonia (North–East Spain) during the period 2000–2004 using multivariate data analysis methods. Atmos Environ 40:7421–7436CrossRefGoogle Scholar
  13. Gabusi V, Volta M (2005) Seasonal modelling assessment of ozone sensitivity to precursors in northern Italy. Atmos Environ 39:2795–2804CrossRefGoogle Scholar
  14. Geddes JA, Murphy JG, Wang DK (2009) Long term changes in nitrogen oxides and volatile organic compounds in Toronto and the challenges facing local ozone control. Atmos Environ 43:3407–3415CrossRefGoogle Scholar
  15. Hastie DR, Narayan J, Schiller C, Niki H, Shepson PB, Sills DML, Taylor PA, Moroz WJ, Druummond JW, Reid N, Taylor R, Roussel PB, Melo OT (1999) Observational evidence for the impact of the lake breeze circulation on ozone concentrations in Southern Ontario. Atmos Environ 33:323–335CrossRefGoogle Scholar
  16. Highland Statistics (2000) Software package for multivariate analysis and multivariate time series analysis Version 2. Highland Statistics, Ltd., Newburgh, UKGoogle Scholar
  17. Holland DM, Principe PP, Vorburger L (1999) Rural ozone: trends and exceedances at CASTNet sites. Environ Sci Technol 33:43–48CrossRefGoogle Scholar
  18. Jacob DJ, Winner DA (2009) Effect of climate change on air quality. Atmos Environ 43:51–63CrossRefGoogle Scholar
  19. Jacob DJ, Logan JA, Gardner GM, Yevich RM, Spivakovsky CM, Wofsy SC, Sillman S, Prather MJ (1993) Factors regulating ozone over the United-States and its export to the global atmosphere. J Geophys Res 98:14817–14826CrossRefGoogle Scholar
  20. Kambezidis HD, Weidauer D, Melas D, Ulbricht M (1998) Air quality in the Athens Basin during sea breeze and non-sea breeze days using laser-remote-sensing technique. Atmos Environ 32:2173–2182Google Scholar
  21. Kaplan D, Muñoz-Carpena R (2011) Complementary effects of surface water and groundwater on soil moisture dynamics in a degraded coastal floodplain forest. J Hydrol 398(3–4):221–234CrossRefGoogle Scholar
  22. Kaplan D, Muñoz-Carpena R, Ritter A (2010) Untangling complex shallow groundwater dynamics in the floodplain wetlands of a southeastern U.S. coastal river. Water Resour Res 46:W08528. doi:10.1029/2009WR009038 Google Scholar
  23. Kim SE (2008) Tree-based threshold modeling for short-term forecast of daily maximum ozone level. Stoch Env Res Risk Assess 24(1):19–28. doi:10.1007/s00477-008-0295-6 CrossRefGoogle Scholar
  24. Kumar U, Jain VK (2010) ARIMA forecasting of ambient air pollutants (O3, NO, NO2 and CO). Stoch Env Res Risk Assess 24(5):751–760CrossRefGoogle Scholar
  25. Kuo YM, Chang FJ (2010) Dynamic factor analysis for estimating ground water arsenic trends. J Environ Qual 39:176–184CrossRefGoogle Scholar
  26. Kuo YM, Lin HJ (2010) Dynamic factor analysis of long-term growth trends of the intertidal seagrass Thalassia hemprichii in southern Taiwan. Estuar Coast Shelf Sci 86:225–236CrossRefGoogle Scholar
  27. Kuo YM, Chu HJ, Pan TY, Yu HL (2011a) Investigating common trends of annual maximum rainfalls during heavy rainfall events in southern Taiwan. J Hydrol 409:749–758CrossRefGoogle Scholar
  28. Kuo YM, Wang SW, Jang CS, Yeh N, Yu HL (2011b) Identifying the factors influencing PM2.5 in southern Taiwan using dynamic factor analysis. Atmos Environ 45(39):7276–7285CrossRefGoogle Scholar
  29. Kuo YM, Jang CS, Yu HL, Chen SC, Chu HJ (2013) Identifying nearshore groundwater and river hydrochemical variables influencing water quality of Kaoping River Eestuary using dynamic factor analysis. J Hydrol 486:39–47CrossRefGoogle Scholar
  30. Levy H (1971) Normal atmosphere: large radical and formaldehyde concentrations predicted. Science 173:141–143CrossRefGoogle Scholar
  31. Ligas A, Sartor P, Colloca F (2011) Trends in population dynamics and fishery of Parapenaeus longirostris and Nephrops norvegicus in the Tyrrhenian Sea (NW Mediterranean): the relative importance of fishery and environmental variables. Mar Ecol 32:25–35CrossRefGoogle Scholar
  32. Liu CM, Huang CY, Shieh SL, Wu CC (1994) Important meteorological parameters for ozone episodes experienced in the Taipei Basin. Atmos Environ 28:159–173CrossRefGoogle Scholar
  33. Martins LC, Latorre-Mdo R, Saldiva PH, Braga AL (2002) Air pollution and emergency room visits due to chronic lower respiratory diseases in the elderly: an ecological time-series study in São Paulo, Brazil. J Occup Environ Med 44:622–627CrossRefGoogle Scholar
  34. McElory JL, Smith TB (1986) Vertical pollutant distributions and boundary layer structure observed by air-borne lidar near the complex Southern California coastline. Atmos Environ 20:1555–1566CrossRefGoogle Scholar
  35. Mudway IS, Kelly FJ (2000) Ozone and the lung: a sensitive issue. Mol Aspects Med 21:1–48CrossRefGoogle Scholar
  36. Munñz-Carpena R, Ritter RA, Li YC (2005) Dynamic factor analysis of groundwater quality trends in an agricultural area adjacent to Everglades National Park. J Contam Hydrol 80(1–2):49–70CrossRefGoogle Scholar
  37. Na K, Moon KC, Kim YP (2005) Source contribution to aromatic VOC concentration and ozone formation potential in the atmosphere of Seoul. Atmos Environ 39:5517–5524CrossRefGoogle Scholar
  38. Nash JE, Sutcliffe JV (1970) River flow forecasting through conceptual models part 1-A discussion of principles. J Hydrol 10:282–290CrossRefGoogle Scholar
  39. Ohura T, Amagai T, Fusaya M (2006) Regional assessment of ambient volatile organic compounds in an industry harbor area, Shizuoka, Japan. Atmos Environ 40:238–248CrossRefGoogle Scholar
  40. Pinto DM, Blande JD, Souza SR, Nerg AM, Holopainen JK (2010) Plant volatile organic compounds (VOCs) in ozone (O3) polluted atmospheres: the ecological effects. J Chem Ecol 36:22–34CrossRefGoogle Scholar
  41. Pun BK, Seigneur C, White W (2003) Day-of-week behavior of atmospheric ozone in three U.S. Cities. J Air Waste Manag Assoc 53:789–801CrossRefGoogle Scholar
  42. Ras MR, Marcé RM, Borrull F (2009) Characterization of ozone precursor volatile organic compounds in urban atmospheres and around the petrochemical industry in the Tarragona region. Sci Total Environ 407:4312–4319CrossRefGoogle Scholar
  43. Ritter A, Muñoz-Carpena R (2006) Dynamic factor modeling of ground and surface water levels in an agricultural area adjacent to Everglades National Park. J Hydrol 317:340–354CrossRefGoogle Scholar
  44. Ritter A, Muñoz-Carpena R, Bosch DD, Schaffer B, Potter TL (2007) Agricultural land use and hydrology affect variability of shallow groundwater nitrate concentration in South Florida. Hydrol Process 21:2464–2473CrossRefGoogle Scholar
  45. Ritter A, Regalado CM, Muñoz-Carpena R (2009) Temporal common trends of topsoil water dynamics in a humid subtropical forest watershed. Vadose Zone Hydrol 8:437–449CrossRefGoogle Scholar
  46. Seinfeld JH, Pandis SN (2006) Atmospheric chemistry and physics—from air pollution to climate change, 2nd edn. Wiley, New YorkGoogle Scholar
  47. Shumway RH, Stoffer DS (1982) An approach to time series smoothing and forecasting using the EM algorithm. J Time Ser Anal 3:253–264CrossRefGoogle Scholar
  48. Sillman S (1999) The relation between O3, NOx and hydrocarbons in urban and polluted rural environments. Atmos Environ 33:1821–1845Google Scholar
  49. Silva Dias MAF, Machado AJ (1997) The role of local circulations in summertime convective development and nocturnal fog in São Paulo, Brazil. Bound Layer Meteorol 82:135–157CrossRefGoogle Scholar
  50. Stathopoulou E, Mihalakakou G, Santamouris M, Bagiorgas HS (2008) On the impact of temperature on tropospheric ozone concentration levels in urban environments. J Earth Syst Sci 117(3):227–236CrossRefGoogle Scholar
  51. Swartman RK, Ogunlade O (1967) A statistical relationship between solar radiation’, sunshine and relative humidity in the tropics. Atmosphere 5(2):25–34Google Scholar
  52. Tamerius JD, Wise EK, Uejio CK, McCoy AL, Comrie AC (2007) Climate and human health: synthesizing environmental complexity and uncertainty. Stoch Env Res Risk Assess 21(5):601–613CrossRefGoogle Scholar
  53. Taylor GE Jr (2001) Risk assessment of tropospheric ozone: human health, natural resources, and ecology. Human Ecol Risk Assess 7:1183–1193CrossRefGoogle Scholar
  54. Vukovich FM, Sherwell J (2003) An examination of the relationship between certain meteorological parameters and surface ozone variations in the Baltimore–Washington corridor. Atmos Environ 37:971–981CrossRefGoogle Scholar
  55. Wakamatsu S, Uno I, Ohara T, Schere KL (1999) A study of the relationship between photochemical ozone and its precursor emissions of nitrogen oxides and hydrocarbons in Tokyo and surrounding areas. Atmos Environ 33:3097–3108CrossRefGoogle Scholar
  56. Walcek CJ, Yuan HH (1999) Calculated influence of temperature-related factors on ozone formation rates in the lower troposphere. J Appl Meteorol 34:1056–1069CrossRefGoogle Scholar
  57. You X, Selvan AS, Cherry NM, Kim HM (2008) Determinants of airborne concentrations of volatile organic compounds in rural areas of Western Canada. J Eposure Sci Environ Epidemiol 18:117–128CrossRefGoogle Scholar
  58. Zhan W, Zhang Y, Ma W, Yu Q, Chen L (2013) Estimating influences of urbanizations on meteorology and air quality of a Central Business District in Shanghai, China. Stoch Environ Res Risk Assess 27:353–365CrossRefGoogle Scholar
  59. Zuur AF, Pierce GJ (2004) Common trends in Northeast Atlantic squid time series. J Sea Res 52:57–72CrossRefGoogle Scholar
  60. Zuur AF, Tuck ID, Bailey N (2003a) Dynamic factor analysis to estimate common trends in fisheries time series. Can J Fish Aquat Sci 60:542–552CrossRefGoogle Scholar
  61. Zuur AF, Fryer RJ, Jolliffe IT, Dekker R, Beukema JJ (2003b) Estimating common trends in multivariate time series using dynamic factor analysis. Environmetrics 14:665–685CrossRefGoogle Scholar
  62. Zuur AF, Ieno EN, Smith GM (2007) Analysing ecological data. Springer, New YorkCrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  1. 1.School of Environmental StudiesChina University of GeosciencesWuhanPeople’s Republic of China
  2. 2.Department of Bioenvironmental Systems EngineeringNational Taiwan UniversityTaipeiTaiwan
  3. 3.State Key Laboratory of Biogeology and Environmental GeologyChina University of GeosciencesWuhanPeople’s Republic of China

Personalised recommendations