Impact of meteorological parameters on aerosol optical depth and particulate matter in Lahore

• Autorzy: Ur Rehman, Zahid , Tariq, Salman , ul Haq , Zia , Khan, Muhammad
• Języki publikacji: EN

Abstrakty

EN

Particulate pollution has become one of the major issues in the mega-cities of Pakistan. As with the increase in rapid urbanization, poor air quality, climate change, and health-related issues are increasing gradually in Lahore. Therefore, the implications for the variability of air pollution need to be better understood for the improvement of air quality. So, in this article, we used aerosol robotic network (AERONET) and moderate resolution imaging spectroradiometer (MODIS) datasets along with the variability of different meteorological parameters (temperature, wind speed, relative humidity, dew point, and sea level pressure) over Lahore during 2006 to 2022. Moreover, the multi-linear regression model is used to analyse the linear relation of AERONET-retrieved aerosol optical depth (AOD) and particulate matter (PM2.5) with MODIS-retrieved AOD during the time period. Both AOD and PM2.5 increase gradually throughout the time period. AERONET-retrieved AOD showed a significant variability during the time period where each meteorological parameter gives a significant value (p < 0.05) except pressure (p > 0.05). The AERONET-retrieved AOD and PM2.5 give a strong positive value (0.78 and 0.63) of the coefficient of correlation. Seasonally, the value of the coefficient of correlation is observed high during summer (0.92) followed by autumn, spring, and winter. Considering the outcomes of this study, different methods like using better quality of fuel, use of public transport, plantation of trees, etc., can be employed to reduce air pollution.

Słowa kluczowe

PL

AOD; PM 2.5; AERONET; MLR; Lahore

EN

AOD; PM 2.5; AERONET; MLR; Lahore

• Czasopismo: Acta Geophysica
• Rocznik: 2024
• Tom: Vol. 72, no. 2
• Strony: 1377--1395
• Opis fizyczny: Bibliogr. 77 poz.

Twórcy

autor

Ur Rehman, Zahid

• Department of Space Science, University of the Punjab, Lahore, Pakistan,

autor

Tariq, Salman

• Department of Space Science, University of the Punjab, Lahore, Pakistan,
• Remote Sensing, GIS and Climatic Research Lab (National Center of GIS and Space Applications), Centre for Remote Sensing, University of the Punjab, Lahore, Pakistan

autor

ul Haq , Zia

• Department of Space Science, University of the Punjab, Lahore, Pakistan
• Remote Sensing, GIS and Climatic Research Lab (National Center of GIS and Space Applications), Centre for Remote Sensing, University of the Punjab, Lahore, Pakistan

autor

Khan, Muhammad

• Remote Sensing, GIS and Climatic Research Lab (National Center of GIS and Space Applications), Centre for Remote Sensing, University of the Punjab, Lahore, Pakistan

Bibliografia

• 1. Abdullah L (2015) Linear relationship between CO2 emissions and economic variables: evidence from a developed country and a developing country. J Sustain Dev 8(2):66. https://doi.org/10. 5539/jsd.v8n2p66
• 2. Alam K, Iqbal MJ, Blaschke T, Qureshi S, Khan G (2010) Monitoring spatio-temporal variations in aerosols and aerosol-cloud interactions over Pakistan using MODIS data. Adv Space Res 46(9):1162-1176. https://doi.Org/10.1016/j.asr.2010.06.025
• 3. Alam K, Trautmann T, Blaschke T (2011) Aerosol optical properties and radiative forcing over mega-city Karachi. Atmos Res 101(3):773-782. https://doi.org/10.1016/j.atmosres.2011.05.007
• 4. Alam K, Trautmann T, Blaschke T, Majid H (2012) Aerosol optical and radiative properties during summer and winter seasons over Lahore and Karachi. Atmos Environ 50:234-245. https://doi.org/ 10.1016/j.atmosenv.2011.12.027
• 5. Alam K, Khan R, Blaschke T, Mukhtiar A (2014a) Variability of aerosol optical depth and their impact on cloud properties in Pakistan. J Atmos Solar Terr Phys 107:104-112. https://doi.org/10.1016/j. jastp.2013.11.012
• 6. Alam K, Mukhtar A, Shahid I, Blaschke T, Majid H, Rahman S, Khan R, Rahman N (2014b) Source apportionment and characterization of particulate matter (PM10) in urban environment of Lahore. Aerosol Air Qual Res 14(7):1851-1861. https://doi.org/10.4209/ aaqr.2014.01.0005
• 7. Alemayehu YA, Asfaw SL, Terfie TA (2020) Exposure to urban particulate matter and its association with human health risks. Environ Sci Pollut Res 27(22):27491-27506. https://doi.org/10.1007/ s11356-020-09132-1
• 8. Ali M, Tariq S, Mahmood K, Daud A, Batool A, ul Haq Z (2013) A study of aerosol properties over Lahore (Pakistan) by using AERONET data. Asia-Pac J Atmos Sci 50(2):153-162. https://doi.org/ 10.1007/S13143-014-0004-Y
• 9. Ali M, Tariq S, Mahmood K, Daud A, Batool A, ul Haq Z (2014) A study of aerosol properties over Lahore (Pakistan) by using AERONET data. Asia-Pac J Atmos Sci 50(2):153-162. https://doi.org/ 10.1007/S13143-014-0004-Y
• 10. Ali G, Bao Y, Ullah W, Ullah S, Guan Q, Liu X, Li L, Lei Y, Li G, Ma J (2020) Spatiotemporal trends of aerosols over urban regions in Pakistan and their possible links to meteorological parameters. Atmosphere 11(3):306. https://doi.org/10.3390/atmos11030306
• 11. Ambade B, Sankar TK, Kumar A, Gautam AS, Gautam S (2021) COVID-19 lockdowns reduce the black carbon and polycyclic aromatic hydrocarbons of the Asian atmosphere: source apportionment and health hazard evaluation. Environ Dev Sustain 23(8):12252-12271. https://doi.org/10.1007/s10668-020-01167-1
• 12. Badarinath KVS, Kharol SK, Sharma AR, Krishna Prasad V (2009) Analysis of aerosol and carbon monoxide characteristics over Arabian Sea during crop residue burning period in the Indo-Gangetic plains using multi-satellite remote sensing datasets. J Atmos Solar Terr Phys 71(12):1267-1276. https://doi.org/10.1016/j.jastp.2009. 04.004
• 13. Basharat U, Tariq S, Nawaz M, Khan M, Bonah E, Fendzi W (2023) Heliyon seasonal correlation of aerosols with soil moisture, evapotranspiration, and vegetation over Pakistan using remote sensing. Heliyon 9(10):e20635. https://doi.org/10.1016/j.heliy on.2023.e20635
• 14. Bell ML, Dominici F, Ebisu K, Zeger SL, Samet JM (2007) Spatial and temporal variation in PM2.5 chemical composition in the United States for health effects studies. Environ Health Perspect 115(7):989-995. https://doi.org/10.1289/ehp.9621
• 15. Biswas KF, Husain L (2009) Atmospheric pollution and emission sources in South Asian urban region. Assembly 11(March):7785
• 16. Buis JP, Setzer A, Holben BN, Eck TF, Slutsker I, Tanre D, Vermote E, Reagan JA, Kaufman YJ, Nakajima T, Lavenu F, Jankowiak I, Smirnov A (1996) AERONET—a federated instrument network and data archive for aerosol characterization. Remote Sens 4257(98):1147
• 17. Chelani AB (2019) Estimating PM2.5 concentration from satellite derived aerosol optical depth and meteorological variables using a combination model. Atmos Pollut Res 10(3):847-857. https:// doi.org/10.1016/j.apr.2018.12.013
• 18. Du K, Huang J, Wang W, Zeng Y, Li X, Zhao F (2024) Monitoring low-temperature stress in winter wheat using TROPOMI solar-induced chlorophyll fluorescence. IEEE Trans Geosci Remote Sens 62:1-11. https://doi.org/10.1109/TGRS.2024.3351141
• 19. Duan J, Ju T, Wang Q, Li F, Fan J, Huang R, Liang Z, Zhang G, Geng T (2021) Absorbable aerosols based on OMI data: a case study in three provinces of Northeast China. Environ Monit Assess 193(8):1-17. https://doi.org/10.1007/s10661-021-09249-x
• 20. Dubovik O, King MD (2000) A flexible inversion algorithm for retrieval of aerosol optical properties from Sun and Sky radiance measurements. J Geophys Res Atmos 105(D16):20673-20696. https://doi.org/10.1029/2000JD900282
• 21. Englert N (2004) Fine particles and human health-a review of epidemiological studies. Toxicol Lett 149(1-3):235-242. https://doi. org/10.1016/j.toxlet.2003.12.035
• 22. 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
• 23. Huang J, Ma H, Sedano F, Lewis P, Liang S, Wu Q, Su W, Zhang X, Zhu D (2019) Evaluation of regional estimates of winter wheat yield by assimilating three remotely sensed reflectance datasets into the coupled WOFOST-PROSAIL model. Eur J Agron 102:113. https://doi.org/10.1016/j.eja.2018.10.008
• 24. Jung J, Souri AH, Wong DC, Lee S, Jeon W, Kim J, Choi Y (2019) The impact of the direct effect of aerosols on meteorology and air quality using aerosol optical depth assimilation during the KORUS-AQ campaign. J Geophys Res Atmos 124(14):8303-8319. https://doi.org/10.1029/2019JD030641
• 25. Kamarul Zaman NAF, Kanniah KD, Kaskaoutis DG (2017) Estimating particulate matter using satellite based aerosol optical depth and meteorological variables in Malaysia. Atmos Res 193:142-162. https://doi.org/10.1016/j.atmosres.2017.04.019
• 26. Kaufman YJ, Wald AE, Remer LA, Gao BC, Li RR, Flynn L (1997) MODIS 2.1-pm channel-correlation with visible reflectance for use in remote sensing of aerosol. IEEE Trans Geosci Remote Sens 35(5):1286-1298. https://doi.org/10.1109/36.628795
• 27. Kaufman YJ, Tanré D, Boucher O (2002) A satellite view of aerosols in the climate system. Nature 419:215-223
• 28. Keat SC, Chun BB, San LH, Jafri MZM (2015) Multiple regression analysis in modelling of carbon dioxide emissions by energy consumption use in Malaysia. In: AIP conference proceedings, vol 1657. https://doi.org/10.1063/1.4915185
• 29. Khan M, Tariq S, Haq ZU (2023) Variations in the aerosol index and its relationship with meteorological parameters over Pakistan using remote sensing. Environ Sci Pollut Res. https://doi.org/ 10.1007/S11356-023-25613-5
• 30. Khanum F, Chaudhry MN, Kumar P (2017) Characterization of five-year observation data of fine particulate matter in the metropolitan area of Lahore. Air Qual Atmos Health 10(6):725-736. https://doi.org/10.1007/s11869-017-0464-1
• 31. Li W, Wang W, Sun R, Li M, Liu H, Shi Y, Fu S (2023) Influence of nitrogen addition on the functional diversity and biomass of fine roots in warm-temperate and subtropical forests. Forest Ecol Manage 545:121309. https://doi.org/10.1016/j.foreco.2023.121309
• 32. Lodhi A, Ghauri B, Rafiq M, Rahman S, Shafique S (2009) Particulate matter (PM2.5) concentration and source apportionment in Lahore. J Braz Chem Soc 20(10):1811-1820
• 33. Lu HY, Wu YL, Mutuku JK, Chang KH (2019) Various sources of PM2.5 and their impact on the air quality in Tainan city Taiwan. Aerosol Air Qual Res 19(3):601-619. https://doi.org/10.4209/ aaqr.2019.01.0024
• 34. Mehmood U, Azhar A, Qayyum F, Nawaz H, Tariq S, ul Haq Z (2021) Air pollution and hospitalization in megacities: empirical evidence from Pakistan. Environ Sci Pollut Res. https://doi. org/10.1007/s11356-021-14158-0
• 35. Nathans LL, Oswald FL, Nimon K (2012) Interpreting multiple linear regression: a guidebook of variable importance. Pract Assess Res Eval 17(9):1-19
• 36. Qayyum F, Mehmood U, Tariq S, ul Haq Z, Nawaz H (2021) Particulate matter (PM2.5) and diseases: an autoregressive distributed lag (ARDL) technique. Environ Sci Pollut Res 28(47):67511-67518. https://doi.org/10.1007/S11356-021-15178-6
• 37. Ranjan RR, Joshi HP, Iyer KN (2007) Spectral variation of total column aerosol optical depth over Rajkot: a tropical semi-arid Indian station. Aerosol Air Qual Res 7(1):33-45. https://doi. org/10.4209/aaqr.2006.08.0012
• 38. Ranjan AK, Patra AK, Gorai AK (2021) A review on estimation of particulate matter from satellite-based aerosol optical depth: data, methods, and challenges. Asia-Pac J Atmos Sci 57(3):679-699. https://doi.org/10.1007/s13143-020-00215-0
• 39. Saeed SF, Younas A (2004) Variation in fog intensity/duration and El Nino. Pak J Meteorol 1(1):49-58
• 40. Sarker T, Corradetti R, Zahan M (2013) Energy sources and carbon emissions in the iron and steel industry sector in South Asia. Int J Energy Econ Policy 3(1):30-42
• 41. Sathe Y, Kulkarni S, Gupta P, Kaginalkar A, Islam S, Gargava P (2019) Application of moderate resolution imaging spectrora-diometer (MODIS) aerosol optical depth (AOD) and weather research forecasting (WRF) model meteorological data for assessment of fine particulate matter (PM2.5) over India. Atmos Pollut Res 10(2):418-434. https://doi.org/10.1016/j.apr.2018. 08.016
• 42. Shahid MZ, Shahid I, Zahid M (2022) Inter-annual variability and distribution of aerosols during winters and aerosol optical thickness over Northeastern Pakistan. Int J Environ Sci Technol 19(2):875-888. https://doi.org/10.1007/s13762-020-02994-5
• 43. Shang K, Xu L, Liu X, Yin Z, Liu Z, Li X, Zheng W (2023) Study of urban heat island effect in Hangzhou metropolitan area based on SW-TES algorithm and image dichotomous model. SAGE Open 13(4). https://doi.org/10.1177/21582440231208851
• 44. Sharma AR, Kharol SK, Badarinath KVS, Singh D (2010) Impact of agriculture crop residue burning on atmospheric aerosol loading: a study over Punjab State India. Ann Geophys 28(2):367-379. https://doi.org/10.5194/angeo-28-367-2010
• 45. Shaw N, Gorai AK (2020) Study of aerosol optical depth using satellite data (MODIS Aqua) over Indian Territory and its relation to particulate matter concentration. Environ Dev Sustain 22(1):265-279. https://doi.org/10.1007/s10668-018-0198-8
• 46. Smirnov A, Holben BN, Eck TF, Dubovik O, Slutsker I (2000) Cloudscreening and quality control algorithms for the AERONET database RID C-2121-2009 RID A-8235-2009. Remote Sens Environ 73(3):337-349
• 47. Soni M, Payra S, Verma S (2018) Particulate matter estimation over a semi arid region Jaipur, India using satellite AOD and meteorological parameters. Atmos Pollut Res 9(5):949-958. https://doi. org/10.1016/j.apr.2018.03.001
• 48. Su F, He X, Dai M, Yang J, Hamanaka A, Yu Y, Li W, Li J (2023) Estimation of the cavity volume in the gasification zone for underground coal gasification under different oxygen flow conditions. Energy 285:129309. https://doi.org/10.1016/j.energy.2023.129309
• 49. Tariq S, Khan M (2023) An investigation of nighttime variability in air quality of Naples (Italy) using wavelet coherence. Air Qual Atmos Health. https://doi.org/10.1007/s11869-023-01440-y
• 50. Tariq S, Khan M (2023) Assessment of nighttime air quality over an urban location in Indo-Gangetic plain using remote sensing observations. Atmos Polluti Res 15:101982. https://doi.org/10.1016/J. APR.2023.101982
• 51. Tariq S, ul Haq Z (2018) Ground-based remote sensing of aerosol properties over a coastal megacity of Pakistan. Adv Meteorol 2018:1-12. https://doi.org/10.1155/2018/3582191
• 52. Tariq S, ul Haq Z (2020) Investigating the aerosol optical depth and angstrom exponent and their relationships with meteorological parameters over Lahore in Pakistan. Proc Natil Acad Sci India Sect A Phys Sci 90(5):861-867. https://doi.org/10.1007/ s40010-018-0575-6
• 53. Tariq S, ul Haq Z, Ali M (2015a) Analysis of optical and physical properties of aerosols during crop residue burning event of october 2010 over Lahore Pakistan. Atmos Pollut Res 6(6):969-978. https://doi.org/10.1016/j.apr.2015.05.002
• 54. Tariq S, ul Zia H, Ali M (2016) Satellite and ground-based remote sensing of aerosols during intense haze event of october 2013 over Lahore Pakistan. Asia-Pac J Atmos Sci 52(1):25-33. https://doi. org/10.1007/s13143-015-0084-3
• 55. Tariq S, ul Haq Z, Imran A, Mehmood U, Aslam MU, Mahmood K (2017) CO2 emissions from Pakistan and India and their relationship with economic variables. Appl Ecol Environ Res 15(4):1301-1312. https://doi.org/10.15666/aeer/1504_13011312
• 56. Tariq S, Nawaz H, ul Haq Z, Mehmood U (2021) Investigating the relationship of aerosols with enhanced vegetation index and meteorological parameters over Pakistan. Atmos Pollut Res. https://doi. org/10.1016/j.apr.2021.101080
• 57. Tariq S, ul Haq Z, Nawaz H, Mehmood U, Babar ZB (2022) Remote sensing of aerosols due to biomass burning over Kanpur, Sao-Paulo, Ilorin and Canberra. J Atmos Chem. https://doi.org/10. 1007/S10874-022-09444-1
• 58. Tariq S, Mariam A, ul Haq Z, Mehmood U (2022) Spatial and temporal variations in PM2.5 and associated health risk assessment in Saudi Arabia using remote sensing. Chemosphere 308(P2):136296. https://doi.org/10.1016/j.chemosphere.2022.136296
• 59. Tariq S, Qayyum F, ul Haq Z, Mehmood U (2022b) Long-term spatiotemporal trends in aerosol optical depth and its relationship with enhanced vegetation index and meteorological parameters over South Asia. Environ Sci Pollut Res 29(20):30638-30655. https:// doi.org/10.1007/s11356-021-17887-4
• 60. Tariq S, Mariam A, Mehmood U, ul Haq Z (2023) Long term spatiotemporal trends and health risk assessment of remotely sensed PM2.5 concentrations in Nigeria. Environ Pollut. https://doi.org/ 10.1016/J.ENVPOL.2023.121382
• 61. Tariq S, Qayyum F, ul Haq Z, Mehmood U (2023b) Remote sensing of nighttime air quality over the megacity of Lahore Pakistan. Urban Clim 49(February):101498. https://doi.org/10.1016/j.uclim.2023. 101498
• 62. Tiwari S, Payra S, Mohan M, Verma S, Bisht DS (2011) Visibility degradation during foggy period due to anthropogenic urban aerosol at Delhi. India Atmos Pollut Res 2(1):116-120. https://doi.org/ 10.5094/APR.2011.014
• 63. van Donkelaar A, Martin RV, Brauer M, Kahn R, Levy R, Verduzco C, Villeneuve PJ (2010) Global estimates of ambient fine particulate matter concentrations from satellite-based aerosol optical depth: development and application. Environ Health Perspect 118(6):847-855. https://doi.org/10.1289/ehp.0901623
• 64. Wang X, Wang T, Xu J, Shen Z, Yang Y, Chen A, Piao S (2022) Enhanced habitat loss of the Himalayan endemic flora driven by warming-forced upslope tree expansion. Nature Ecol Evol 6(7):890-899. https://doi.org/10.1038/s41559-022-01774-3
• 65. Wen Z, Wang Q, Ma Y, Jacinthe PA, Liu G, Li S, Shang Y, Tao H, Fang C, Lyu L, Zhang B, Song K, Song K (2024a) Remote estimates of suspended particulate matter in global lakes using machine learning models. Int Soil Water Cons Res 12(1):200-216. https:// doi.org/10.1016/j.iswcr.2023.07.002
• 66. Wen Z, Shang Y, Lyu L, Tao H, Liu G, Fang C, Li S, Song K (2024b) Re-estimating China's lake CO2 flux considering spatiotemporal variability. Environ Sci Ecotechnol 19: https://doi.org/10.1016/j. ese.2023.100337
• 67. Yang SH, Jeong JI, Park RJ, Kim MJ (2020) Impact of meteorological changes on particulate matter and aerosol optical depth in Seoul during the months of June over recent decades. Atmosphere 11(12):1-19. https://doi.org/10.3390/atmos11121282
• 68. Yasmeen Z, Rasul G, Zahid M (2012) Impact of aerosols on winter fog of Pakistan. Pak J Meteorol 8(16):21-30
• 69. Yin Z, Liu Z, Liu X, Zheng W, Yin L (2023) Urban heat islands and their effects on thermal comfort in the US: New York and New Jersey. Ecol Indic 154:110765. https://doi.org/10.1016/j.ecolind. 2023.110765
• 70. Yu X, Zhu B, Yin Y, Fan S, Chen A (2011) Seasonal variation of columnar aerosol optical properties in Yangtze River Delta in China. Adv Atmos Sci 28(6):1326-1335. https://doi.org/10.1007/ s00376-011-0158-9
• 71. Zafar Q, Zafar S, Holben B (2018) Seasonal assessment and classification of aerosols transported to Lahore using AERONET and MODIS deep blue retrievals. Int J Climatol 38(2):1022-1040. https://doi.org/10.1002/joc.5230
• 72. Zeydan Ö, Wang Y (2019) Using MODIS derived aerosol optical depth to estimate ground-level PM2.5 concentrations over Turkey. Atmos Pollut Res 10(5):1565-1576. https://doi.org/10.1016/j.apr.2019. 05.005
• 73. Zhang S, Bai X, Zhao C, Tan Q, Luo G, Wang J, Xi H (2021) Global CO2 Consumption by Silicate Rock Chemical Weathering: Its Past and Future. Earth's Future 9(5):e1938E-e2020E. https://doi. org/10.1029/2020EF001938
• 74. Zhao TXP, Laszlo I, Minnis P, Remer L (2005) Comparison and analysis of two aerosol retrievals over the ocean in the Terra/Clouds and the Earth’s radiant energy system-moderate resolution imaging spectroradiometer single scanner footprint data: 1. Global evaluation. J Geophys Res Atmos 110(21):1-15. https://doi.org/10.1029/ 2005JD005851
• 75. Zhao Z, Cao J, Shen Z, Huang RJ, Hu T, Wang P, Zhang T, Liu S (2015) Atm spheric pollution site over Northeast of Tibet Plateau. Atmos Pollut Res 6(5):815-823. https://doi.org/10.5094/ APR.2015.090
• 76. Zhao Y, Hu M, Jin Y, Chen F, Wang X, Wang B, Ren H (2023) Predicting the transmission trend of respiratory viruses in new regions via geospatial similarity learning. International Journal of Applied Earth Observation and Geoinformation 125:103559. https://doi. org/10.1016/j.jag.2023.103559
• 77. Zhu W, Chen J, Sun Q, Li Z, Tan W, Wei Y (2022) Reconstructing of high-spatial-resolution three-dimensional electron density by ingesting SAR-derived VTEC into IRI model. IEEE Geosci Remote Sens Lett 19. https://doi.org/10.1109/LGRS.2022.31782 42

Identyfikatory

DOI

10.1007/s11600-024-01291-w