Analysing of atmospheric conditions and their effects on air quality in Istanbul using SODAR and CEILOMETER.
Air pollution
Ceilometer
HYSPLIT System
Istanbul
SODAR
WRF model
Journal
Environmental science and pollution research international
ISSN: 1614-7499
Titre abrégé: Environ Sci Pollut Res Int
Pays: Germany
ID NLM: 9441769
Informations de publication
Date de publication:
Mar 2022
Mar 2022
Historique:
received:
09
04
2021
accepted:
05
10
2021
pubmed:
15
10
2021
medline:
12
2
2022
entrez:
14
10
2021
Statut:
ppublish
Résumé
In this study, first, air pollution that is caused by the air pollutants' concentration exceeding the limit value in Istanbul between 2017 and 2020 were analysed. In addition to this analysis, the effects of meteorological parameters on pollution were also examined within the same period of time. Second, for a 14-day period during which the concentration values of the air pollutants were calculated higher than the standards, therefore, were selected as an episode. In that respect, measurements of both pollutant and meteorological parameters were obtained from air quality monitoring stations. The Weather Research and Forecasting (WRF) model was used to examine the changes of meteorological parameters in the surface and upper atmospheric levels. The cross-correlation function (CCF) was performed together with both air quality monitoring station and the WRF model output data to examine the effects of temporal changes in meteorological parameters on air pollutant concentrations on a temporal scale. In addition, some meteorological parameters were obtained from remote sensing systems (SODAR and Ceilometer). Finally, with the help of the trajectory analysis model, it was determined whether the pollutant parameters were transported or not. Consequently, within a 3-year period, the most critical parameters in terms of pollution throughout the city were assessed as NO
Identifiants
pubmed: 34647206
doi: 10.1007/s11356-021-16958-w
pii: 10.1007/s11356-021-16958-w
doi:
Substances chimiques
Air Pollutants
0
Particulate Matter
0
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
16213-16232Subventions
Organisme : Türkiye Bilimsel ve Teknolojik Araştirma Kurumu
ID : 116Y224
Informations de copyright
© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.
Références
Angevine WM, Senff CJ (2015) Observational technique: remote. Revision of the previous edition article by Angevine, Senff Westwater. 1:271–279, © 2003, Elseiver Ltd.
Avdakovic S, Dedovic MM, Dautbasic N, Dizdarevic J (2016) The influence of wind speed, humidity, temperature and air pressure on pollutants concentrations of PM10—Sarejevo case study using wavelet cohorence approach. XI International Symposium on Telecommunications (BIHTEL). Sarejovo, Bosnia and Herzegovina. 24–26 October, 2016
Beyrich F, Görsdorf U (1995) Composing the diurnal cycle of mixing height from simultaneous SODAR and wind profiler measurements. Bound Layer Meteorol 76:387–394. https://doi.org/10.1007/BF00709240
doi: 10.1007/BF00709240
Biral (2020) CBME80B cloud ceilometer datasheet. https://www.biral.com/wp-content/uploads/2015/07/CBME80B-CLOUD-CEILOMETER-DS-DOC101422.01A.pdf Accessed 10 Sep 2020
Coulter RL (1979) A comparision of three methods for measuring mixing layer height. J Appl Meteorol 18:1495–1499. https://doi.org/10.1175/1520-0450(1979)0182.0.co;2
doi: 10.1175/1520-0450(1979)0182.0.co;2
Çapraz Ö, Efe B, Deniz A (2016) Study on the association between air pollution and mortality in İstanbul, 2007–2012. Atmos Pol Res 7(1):147–154. https://doi.org/10.1016/j.apr.2015.08.006
doi: 10.1016/j.apr.2015.08.006
Çapraz Ö, Deniz A, Doğan N (2017) Effects of air pollution on respiratory hospital admissions in İstanbul, Turkey, 2013 to 2015. Chemosphere 181:544–550. https://doi.org/10.1016/j.chemosphere.2017.04.105
doi: 10.1016/j.chemosphere.2017.04.105
Çapraz Ö, Deniz A (2020) Particulate matter (PM
DeSouza P (2020) Air pollution in Kenya: a review. Air Qual Atmos Health 13:1487–1495. https://doi.org/10.1007/s11869-020-00902-x
doi: 10.1007/s11869-020-00902-x
Devera PCS, Ernest Ray P, Murthy BS, Pandithurai G, Sharma S, Vernekar KG (1995) Intercomparison of nocturnal lower atmospheric structure observed with LIDAR and SODAR techniques at Pune. Indian J Appl Meteorology 34:1375–1383. https://doi.org/10.1175/1520-0450(1995)034%3c1375:IONLAS%3e2.0.CO;2
doi: 10.1175/1520-0450(1995)034<1375:IONLAS>2.0.CO;2
Efe B, Lupo AR, Deniz A (2019) The relationship between atmospheric blocking and precipitation changes in Turkey between 1877 and 2016. Theor Appl Climatol 138(3–4):1573–1590. https://doi.org/10.1007/s00704-019-02902-z
doi: 10.1007/s00704-019-02902-z
Efe B, Sezen İ, Lupo AR, Deniz A (2020a) The relationship between atmospheric blocking and temperature anomalies in Turkey between 1977–2016. Int J Climatol 40(2):1022–1037. https://doi.org/10.1002/joc.6253
doi: 10.1002/joc.6253
Efe B, Lupo AR, Deniz A (2020b) Extreme temperatures linked to the atmospheric blocking events in Turkey between 1977 and 2016. Nat Hazards 104(2):1879–1898. https://doi.org/10.1007/s11069-020-04252-ws
doi: 10.1007/s11069-020-04252-ws
Emeis S, Münkel C, Vogt S, Müller WJ, Schafer K (2004) Atmospheric boundary layer structure from simultaneous SODAR, RASS and ceilometer measurements. Atmos Environ 38:273–286. https://doi.org/10.1016/j.atmosenv.2003.09.054
doi: 10.1016/j.atmosenv.2003.09.054
Emeis S, Schaefer K, Münkel C (2009) Observation of the structure of the urban boundary layer with different ceilometers and validation by RASS data. Meteorol Z 18(2):149–154. https://doi.org/10.1127/0941-2948/2009/0365
doi: 10.1127/0941-2948/2009/0365
Freedman JM, Fitzjarrald DR, Moore KE, Skai RK (2001) Boundary layer clouds and vegetation atmosphere feedbacs. J Clim 12(2):180–197. https://doi.org/10.1175/1520-0442(2001)013%3c0180:BLCAVA%3e2.0.CO;2
doi: 10.1175/1520-0442(2001)013<0180:BLCAVA>2.0.CO;2
Gera BS, Singh G, Ojha VK, Saxena N, Gupta PK, Dutta HN (2000) Studies of boundary layer parameters and air pollution concentration at different traffic junctions. Proceedings of 10
Gurjar BR, Lelieveld J (2005) New directions: megacities andglobal change. Atmos Environ 39:391–393. https://doi.org/10.1016/j.atmosenv.2004.11.002
doi: 10.1016/j.atmosenv.2004.11.002
Gurjar BR, Butler TM, Lawrence MG, Lelieveld J (2008) Evaluation of emissions and air quality in megacities. Atmos Environ 42(7):1593–1606. https://doi.org/10.1016/j.atmosenv.2007.10.048
doi: 10.1016/j.atmosenv.2007.10.048
Guttikunda SK, Carmichael GR, Calori G, Eck C, Woo JH (2003) The contribution of megacities to regionalsulfur pollution in Asia. Atmos Environ 37:11–22. https://doi.org/10.1016/S1352-2310(02)00821-X
doi: 10.1016/S1352-2310(02)00821-X
Iacono MJ, Delamere JS, Mlawer EJ, Shephard MW, Clough SA, Collins WD (2008) Radiative forcing by long-lived greenhouse gases: Calculations with the AER radiative transfer models. J Geophys Res 113:D13103. https://doi.org/10.1029/2008JD009944
doi: 10.1029/2008JD009944
IMM (İstanbul Metropolitan Municipality) Environmental Protection and Control Department (2020) Measuring devices. https://havakalitesi.ibb.gov.tr/Icerik/hakkimizda/olcum-cihazlari Accessed 30 September 2020
İncecik S, İm U (2012) Air pollution in mega cities: a case study of Istanbul. Air pollution - monitoring, modelling and health. Intech Open Access Publisher, 77–116
Janjic ZI (1994) The step-mountain eta coordinate model: further developments of the convection, viscous sublayer, and turbulence closure schemes. Mon Wea Rev 122(5):927–945. https://doi.org/10.1175/1520-0493(1994)122%3c0927:TSMECM%3e2.0.CO;2
doi: 10.1175/1520-0493(1994)122<0927:TSMECM>2.0.CO;2
Keder J, Berger P, Cerny A, Engst P, Folttiny F, Strizik M (2002) Operational measurement of air pollution concentrations in the Czech 90 Republic by combined LIDAR/SODAR techniques. Proceedings of 11
Keder J, Strizik M, Berger P, Cerny A, Engst P, Nemcova I (2004) Remote sensing detection of atmospheric pollutants by differential absorption LIDAR 510M/SODAR PA2 mobile system. Meteorol Atmos Phys 85:155–164
doi: 10.1007/s00703-003-0042-y
Lawrence MG, Butler TM, Steinkamp J, Gurjar BR, Lelieveld J (2007) Regional pollution potentials of megacities and other major population centers. Atmos Chem Phys 7:3969–3987. https://doi.org/10.5194/acp-7-3969-2007
doi: 10.5194/acp-7-3969-2007
Li Y, Chen Q, Zhao H, Wang L, Tao R (2015) Variations in PM10, PM2.5 and PM1.0 in an urban area of the sichuan basin and their relation to meteorological factors. Atmosphere 6(1):150–163. https://doi.org/10.3390/atmos6010150
Liu Z, Yu L (2020) Stay or Leave? The role of air pollution in urban migration choices. Ecological Economics 177 https://doi.org/10.1016/j.ecolecon.2020.106780
Lupo AR, Jensen AD, Mokhov II, Timazhev AV, Eichler T, Efe B (2019) Changes in global blocking character in recent decades. Atmosphere 10(92). https://doi.org/10.3390/atmos10020092
Maciejewska K (2020) Short-term impact of PM2.5, PM10, and PMc on mortality and morbidity in the agglomeration of Warsaw. Poland Air Qual Atmos Health 13:659–672. https://doi.org/10.1007/s11869-020-00831-9
doi: 10.1007/s11869-020-00831-9
Marc M, Tobiszewski M, Zabiegala B, de la Guardia M, Namiesnik J (2015) Current air quality analytics and monitoring: a review. Anal Chim Acta 853:116–126. https://doi.org/10.1016/j.aca.2014.10.018
doi: 10.1016/j.aca.2014.10.018
Marsik FJ, Fischer KW, McDonald TD, Samson PJ (1995) Comparison of methods for estimating mixing layer height used during the 1992 Atlanta field initiative. J Appl Meteorol 34:1802–1814. https://doi.org/10.1175/1520-0450(1995)034%3c1802:COMFEM%3e2.0.CO;2
doi: 10.1175/1520-0450(1995)034<1802:COMFEM>2.0.CO;2
MEU (Ministry of Environment and Urbanization) (2008) Air quality assessment and management regulation. https://www.resmigazete.gov.tr/eskiler/2008/06/20080606-6.htm Accessed 16 September 2020
Monin AS, Obukhov M (1954) Basic laws of turbulent-mixing in the surface layer of the atmosphere. Contrib Geophys Inst Acad Sci USSR 151:163–187 ((in Russian))
NOAA (2020) HYSPLIT atmospheric transport and dispersion modeling system. https://www.ready.noaa.gov/HYSPLIT.php . Accessed 22 September 2020
Özdemir ET, Deniz A, Yavuz V, Çiftçi ND, Akbayır İ (2018) Investigation of the air quality relationship in İstanbul. Fresen Environ Bull 27(1):30–36
Özdemir ET, Çapraz Ö, Deniz A (2020) Investigation of the relationship between extreme pressure values and particulate matter (PM10) values for megacity Istanbul. J Anatolian Environ Animal Sci 5(4):484–490
Öztürk M (2017) Temperature inversion increasing air pollution. http://www.cevresehirkutuphanesi.com/assets/files/slider_pdf/ro17bNm6ttR8.pdf . Accessed 18 Sep 2020 (in Turkish)
Peña A, Gryning S E, Floors R (2014) The turning of the wind in the atmospheric boundary layer. Journal of Physics: Conference Series (Vol. 524, No. 1, p. 012118). IOP Publishing. https://doi.org/10.1088/1742-6596/524/1/012118
Peng J, Grimmond CSB, Fu X, Chang Y, Zhang G, Guo J, Tang C, Gao J, Xu X, Tan J (2017) Ceilometer-based analysis of Shangai’s boundary layer Height (under rain and fog free conditions). J Atmos Ocean Tech 34(4):749–764. https://doi.org/10.1175/JTECH-D-16-0132.1
doi: 10.1175/JTECH-D-16-0132.1
Remtech (2020). Remtech PA-O SODAR acoustic wind profiler. https://www.remtechinc.com/sites/default/files/inline-files/PA-0.pdf Accessed 24 Sep 2020
Rife DL, Davis CA (2005) Verification of temporal variations in mesoscale numerical wind forecasts. Mon Wea Rev 133:3368–3381. https://doi.org/10.1175/MWR3052.1
doi: 10.1175/MWR3052.1
Schafer K, Jardines EF, Emeis S, Grutter M, Kurtenbach R, Wiesen P, Münkel C (2009) Determination of mixing layer heights by ceilometer and influences upon air quality at Mexico City airport. The International Society for Optical Engineering https://doi.org/10.1117/12.830425
Signal SP (1993) Monitoring air pollution related meteorology using SODAR. Appl Phys B 57:65–82. https://doi.org/10.1007/BF00324102
doi: 10.1007/BF00324102
Spiridonov V, Ancev N, Jakimovski B, Velinov G (2020) Improvement of chemical initialization in the air quality forecast system in North Macedonia, based on WRF-Chem model. Air Qual Atmos Health https://doi.org/10.1007/s11869-020-00933-4
Stieb DM, Doiron MS, Blagden P, Burnett RT (2005) Estimating the public health burden attributable to air pollution: an illustration using the development of an alternative air quality index. J of Toxicology and Env Health, Part A 68(13):1275–1288
doi: 10.1080/15287390590936120
Teixeira J, Hogan T (2002) Boundary layer clouds in a global atmospheric model: simple cloud cover parametrizations. J Climate 15(11):1261–1276. https://doi.org/10.1175/1520-0442(2002)015%3c1261:BLCIAG%3e2.0.CO;2
doi: 10.1175/1520-0442(2002)015<1261:BLCIAG>2.0.CO;2
Tewari MF, Chen F, Wang W, Dudhia J, LeMone MA, Mitchell K, Ek M, Gayno G, Wegiel J, Cuenca RH (2004) Implementation and verification of the unified NOAH land surface model in the WRF model. 20
Thompson G, Field PR, Rasmussen RM, Hall WD (2008) Explicit forecasts of winter precipitation using an improved bulk microphysics scheme: Part II: Implementation of a new snow parameterization. Mon Wea Rev 136:5095–5115. https://doi.org/10.1175/2008MWR2387.1
doi: 10.1175/2008MWR2387.1
UNCSD (2001) Protection of the atmosphere-report to the secretary general. E/CN.17/2001/2, Commission for Sustainable Development, New York, USA
Unal YS, Toros H, Deniz A, Incecik S (2011) Influence of meteorological factors and emission sources on spatial and temporal variations of PM10 concentrations in Istanbul metropolitan area. Atmos Environ 45(31):5504–5513. https://doi.org/10.1016/j.atmosenv.2011.06.039
doi: 10.1016/j.atmosenv.2011.06.039
Wiedenmann JM, Lupo AR, Mokhov II, Tikhonova EA (2002) The Climatology of Blocking Anticyclones for the Northern and Southern Hemispheres: Block Intensity as a Diagnostic. Journal of Climate 15(23):3459–3473. https://doi.org/10.1175/15200442(2002)015<3459:TCOBAF>2.0.CO;2
Zhang C, Wang Y, Hamilton K (2011) Improved representation of boundary layer clouds over the Southeast Pacific in ARW-WRF using a modified Tiedtke Cumulus Parameterization Scheme. Mon Wea Rev 139(11):3489–3513. https://doi.org/10.1175/MWR-D-10-05091.1
doi: 10.1175/MWR-D-10-05091.1