Abstract
The interrelationships between air quality, land cover change, and road networks in the Lagos megacity have not been explored. Globally, there are knowledge gaps in understanding these dynamics, especially using remote sensing data. This study used multi-temporal and multi-spectral Landsat imageries at four epochs (2002, 2013, 2015, and 2020) to evaluate the aerosol optical thickness (AOT) levels in relation to land cover and road networks in the Lagos megacity. A look-up table (LUT) was generated using Py6S, a python-based 6S module, to simulate the AOT using land surface reflectance and top of atmosphere reflectance. A comparative assessment of the method against in situ measurements of particulate matter (PM) at different locations shows a strong positive correlation between the imagery-derived AOT values and the PMs. The AOT concentration across the land cover and road networks showed an increasing trend from 2002 to 2020, which could be explained by urbanization in the megacity. The higher concentration of AOT along the major roads is attributed to the high air pollutants released from vehicles, including home/office generators and industries along the road corridors. The continuous rise in pollutant values requires urgent intervention and mitigation efforts. Remote sensing-based AOT monitoring is a possible solution.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
Data Availability
The datasets generated and analyzed during the current study are available from the corresponding author on reasonable request.
References
Adeyanju AA, Manohar K (2017) Effects of vehicular emission on environmental pollution in Lagos. Sci-Afric J Sci Issues Res Essays 5(4):34–51
Adeyewa ZD, Oluleye A (2011) International journal of remote relationships between aerosol index, ozone, solar zenith angle and surface reflectivity : a case study of satellite observations over Lagos. Int J Remote Sens 37–41. https://doi.org/10.1080/01431161003705883
Akinyoola JA, Eresanya EO, Orimoogunje OOI, Oladosu K (2018) Monitoring the spatio-temporal aerosol loading over Nigeria. Model Earth Syst Environ 4(4):1365–1375. https://doi.org/10.1007/s40808-018-0485-2
Alademomi AS, Okolie CJ, Daramola OE, Agboola RO, Salami TJ (2020) Assessing the relationship of LST, NDVI and EVI with land cover changes in the Lagos Lagoon environment. Quaestiones Geographicae 39(3):87–109. https://doi.org/10.2478/quageo-2020-0025
Alademomi AS, Okolie CJ, Daramola OE, Akinnusi SA, Adediran E, Olanrewaju HO, Alabi AO, Salami TJ, Odumosu J (2022) The interrelationship between LST, NDVI, NDBI, and land cover change in a section of Lagos metropolis, Nigeria. Appl Geomat 14:299–314. https://doi.org/10.1007/s12518-022-00434-2
Alani RA, Ayejuyo OO, Akinrinade OE et al (2019) The level PM2.5 and the elemental compositions of some potential receptor locations in Lagos, Nigeria. Air Qual Atmos Health 12:1251–1258. https://doi.org/10.1007/s11869-019-00743-3
Anderson JR (1971) Land use classification schemes used in selected recent geographic applications of remote sensing. Photogrammetric Engineering 37(4):379–387
Car Mart (2022). Lagos state vehicle registration and plate number verification. https://www.carmart.ng/public/blog/lagos-state-vehicle-registration-and-plate-number-verification/ (Date accessed: 10th June, 2022)
CNN Travel (2019). Marketplace Africa: employees in Lagos are stressed, burned out and exhausted because of ‘hellish traffic’. https://edition.cnn.com/travel/article/traffic-stress-lagos-nigeria/index.html (Date accessed: 30 July 2021)
Das S, Angadi DP (2020) Land use-land cover (LULC) transformation and its relation with land surface temperature changes: a case study of Barrackpore Subdivision, West Bengal, India. Remote Sensing Applications: Society and Environment 19(May):100322. https://doi.org/10.1016/j.rsase.2020.100322
Deuzé JL et al (2001) Remote sensing of aerosols over land surfaces from POLDER-ADEOS-1 polarized measurements. J Geophys Res 106(D5):4913–4926. https://doi.org/10.1029/2000JD900364
Ding H, Shi J, Wang Y, Wei L (2015) An improved dark-object subtraction method for atmospheric correction of Landsat 8. Proc of SPIE 9815:1–8. https://doi.org/10.1117/12.2205567
Faisal KA, Yue W, Abdullahi AG, Hamed R, Noman AAA (2021) Analyzing urban growth and land cover change scenario in Lagos, Nigeria using multi-temporal remote sensing data and GIS to mitigate flooding. Geomat Nat Haz Risk 12(1):631–652. https://doi.org/10.1080/19475705.2021.1887940
Herman JR, Bhartia PK, Torres O, Hsu C, Seftor C, Celarier E (1997) Global distribution of UV-absorbing aerosols from Nimbus 7/TOMS data. J Geophys Res Atmos 102(14):16911–16922. https://doi.org/10.1029/96jd03680
Holben BN et al (1998) AERONET-A federated instrument network anddata archive for aerosol characterization. Remote Sens Environ 66:1–16
Joshi J, Kandpal KC, Rawat N (2019) Estimation of air pollution using multi-temporal remote sensing technique for Dehradun District, Uttarakhand. Int J Adv Remote Sens GIS 8(1):2919–2932. https://doi.org/10.23953/cloud.ijarsg.400
Kaufman YJ, Sendra C (1988) Algorithm for automatic atmospheric corrections to visible and near-ir satellite imagery. Int J Remote Sens 9(8):1357–1381. https://doi.org/10.1080/01431168808954942
Kaufman YJ, Tanré D, Gordon HR, Nakajima T, Lenoble J, Frouin R, Grassl H, Herman BM, King MD, Teillet PM (1997) Passive remote sensing of tropospheric aerosol and atmospheric correction for the aerosol effect. J Geophys Res Atmos 102(14):16815–16830. https://doi.org/10.1029/97jd01496
L3Harris Geospatial (2021) Software & Technology ENVI. https://www.l3harrisgeospatial.com/Software-Technology/ENVI (Date accessed: 30 July 2021)
Levy RC, Remer LA, Kleidman RG, Mattoo S, Ichoku C, Kahn R, Eck TF (2010) Global evaluation of the Collection 5 MODIS dark-target aerosol products over land. Atmos Chem Phys 10(21):10399–10420. https://doi.org/10.5194/acp-10-10399-2010
Levy RC, Remer LA, Mattoo S, Vermote EF, Kaufman YJ (2007) Second-generation operational algorithm: Retrieval of aerosol properties over land from inversion of Moderate Resolution Imaging Spectroradiometer spectral reflectance. J Geophys Res Atmos 112(13):1–21. https://doi.org/10.1029/2006JD007811
Liu J, Ding J, Li L, Li X, Zhang Z, Ran S, Ge X, Zhang J, Wang J (2020) Characteristics of aerosol optical depth over land types in central Asia. Sci Total Environ 727:138676. https://doi.org/10.1016/j.scitotenv.2020.138676
Luo N, Sing M, Zhao W, Yan X, Xiao F (2015) Improved aerosol retrieval algorithm using Landsat images and its application for PM 10 monitoring over urban areas. Atmos Res 153:264–275. https://doi.org/10.1016/j.atmosres.2014.08.012
Mayer B, Kylling A (2005) Technical note: the libRadtran software package for radiative transfer calculations - Description and examples of use. Atmos Chem Phys 5(7):1855–1877. https://doi.org/10.5194/acp-5-1855-2005
Miller J (2019) Costs and benefits of soot-free road transport in Nigeria (Issue August). https://theicct.org/sites/default/files/publications/ICCT_Sootfree_transport_20190826.pdf%0Ahttps://trid.trb.org/view/1649938
Mogaji E (2020) Impact of COVID-19 on transportation in Lagos, Nigeria. Transp Res Interdiscip Perspect 6 https://doi.org/10.1016/j.trip.2020.100154
Njoku LK, Rumide JT, Akinola MO, Adesuyi AA, Jolaoso AO (2016) Ambient air quality monitoring in Metropolitan City of Lagos, Nigeria. J Appl Sci Environ Manag 20(1):178–185. https://doi.org/10.4314/jasem.v20i1.21
Obiefuna JN, Nwilo PC, Atagbaza AO, Okolie CJ (2013) Spatial changes in the wetlands of Lagos/Lekki lagoons of Lagos, Nigeria. J Sustain Dev 6(7):123–133. https://doi.org/10.5539/jsd.v6n7p123
Obiefuna JN, Okolie CJ, Atagbaza AO, Nwilo PC, Akindeju FO (2021a) Spatio-temporal land cover dynamics and emerging landscape patterns in western part of Lagos State, Nigeria. Environ Socio-Econ Stud 9(3):53–69. https://doi.org/10.2478/environ-2021-0017
Obiefuna JN, Okolie CJ, Nwilo PC, Daramola OE, Isiofia L (2021b) Potential influence of urban sprawl and changing land surface temperature on outdoor thermal comfort in Lagos State, Nigeria. Quaest Geogr 40(1):5–23. https://doi.org/10.2478/quageo-2021-0001
Oguntunde PE, Odetunmibi OA, Adejumo AO (2014) A study of probability models in monitoring environmental pollution in Nigeria. J Probab Stat
Okolie CJ, Ayodele EG, Mbu-Ogar E, Akinnusi SA, Daramola OE, Tella A, Alani RA, Alademomi AS (2021) Remote sensing approach for aerosol optical thickness (AOT) monitoring in relation to the road network in Lagos Metropolis, Nigeria. In: Proceedings of the 3rd Intercontinental Geoinformation Days (IGD) Conference, Mersin University, Turkey, 17th – 18th November 2021
Olowoporoku AO, Longhurst JWS, Barnes JH (2012) Framing air pollution as a major health risk in Lagos, Nigeria. WIT Trans Ecol Environ 157:479–486. https://doi.org/10.2495/AIR120421
Oluyemi EA, Asubiojo OI (2001) Ambient air particulate matter in Lagos, Nigeria. Bull Chem Soc Ethiop 15(2):97–108
Omari K, Abuelgasim A, Alhebsi K (2019) Aerosol optical depth retrieval over the city of Abu Dhabi, United Arab Emirates ( UAE ) using Landsat-8 OLI images. Atmos Pollut Res 10(4):1075–1083. https://doi.org/10.1016/j.apr.2019.01.015
Ou Y, Chen F, Zhao W, Yan X, Zhang Q (2017) Landsat 8-based inversion methods for aerosol optical depths in the Beijing area. Atmos Pollut Res 8(2):267–274. https://doi.org/10.1016/j.apr.2016.09.004
Prakash BM, Mahadevaswamy M, Mahesh S, Vishala, N (2016) Prediction of air pollutants dispersion emitted from point and line sources along the highway passing through industrial area of Mysuru- AERMOD and CALINE4 models. Int J Innov Res Sci Eng Technol 5(8):14497–14508. https://doi.org/10.15680/IJIRSET.2016.0508027
Ranjan AK, Patra AK, Gorai AK (2020) A review on estimation of particulate matter from satellite-based aerosol optical depth: data, methods, and challenges. Asia Pac J Atmos Sci. https://doi.org/10.1007/s13143-020-00215-0
Sun L, Wei J, Bilal M, Tian X, Jia C, Guo Y (2016) Aerosol optical depth retrieval over bright areas using Landsat 8 OLI images. Remote Sens (Basel) 8(23):1–14. https://doi.org/10.3390/rs8010023
Taiwo AM, Arowolo TA, Abdullahi KL, Taiwo OT (2015) Particulate matter pollution in Nigeria: a review. In: Proceedings of the 14th International Conference on Environmental Science and Technology, September, 3–5
Tanre D, Deschamps PY, Leffe AD (1979) Atmospheric modelling for space measurements of ground reflectances, including bidirectional properties. Appl Optics 18(21)
Tella A, Abdul-Lateef B, Ibrahima F (2021) Spatio-temporal modelling of the influence of climatic variables and seasonal variation on PM10 in Malaysia using multivariate regression (MVR) and GIS. Geomat Nat Haz Risk 12:443–468
Tian L, Hou W, Chen J, Chen C, Pan X (2018) Spatiotemporal changes in PM2.5 and their relationships with land-use and people in Hangzhou. Int J Environ Res Public Health 15(10):1–14. https://doi.org/10.3390/ijerph15102192
UNEP (2016) Actions on air quality: policies & programmes for improving air quality around the world. In: Actions on Air Quality. https://doi.org/10.18356/9811f020-en
Vermote EF, Tanre D, Deuze JL, Herman M, Morcette JJ (1997) Second simulation of the satellite signal in the solar spectrum, 6S: an overview. IEEE Trans Geosci Remote Sens 35(3):675–686. https://doi.org/10.1109/36.581987
Wei X, Chang NB, Bai K, Gao W (2020) Satellite remote sensing of aerosol optical depth: advances, challenges, and perspectives. Crit Rev Environ Sci Technol 50(16):1640–1725. https://doi.org/10.1080/10643389.2019.1665944
Wilson RT (2013) Py6S: A python interface to the 6s radiative transfer model. Comput Geosci 51:166–171. https://doi.org/10.1016/j.cageo.2012.08.002
Yang H, Chen W, Liang Z (2017) Impact of land use on PM 2.5 pollution in a representative city of Middle China. https://doi.org/10.3390/ijerph14050462
Yusuf KA, Oluwole S, Abdusalam IO, Adewusi GR (2013) Spatial patterns of urban air pollution in an industrial estate, Lagos, Nigeria spatial patterns of urban air pollution in an industrial estate, Lagos, Nigeria. Int J Eng Invent 2(4):1–9
Zhang L, Shi R, Liu C, Zhou C (2015) Retrieval of aerosol optical depth over Beijing using Landsat8 / OLI data. Proceedings of SPIE 9610:1–8. https://doi.org/10.1117/12.2186761
Zhang Y, Liu Z, Wang Y, Ye Z, Leng L (2014) Inversion of aerosol optical depth based on the CCD and IRS sensors on the HJ-1 satellites. Remote Sens (Basel) 6:8760–8778. https://doi.org/10.3390/rs6098760
Zhao WJ, Ou Y, Chen F, Zhao W, Yan X, Zhang Q (2016) Landsat 8-based inversion methods for aerosol optical depths in the Beijing area atmospheric pollution research Landsat 8-based inversion methods for aerosol optical depths in the Beijing area. Atmos Pollut Res 8(2):267–274. https://doi.org/10.1016/j.apr.2016.09.004
Acknowledgements
The authors would like to thank the NASA/USGS for free access to Landsat imageries and the Air Quality Monitoring Group (AQM) Unilag for providing the ground-based PM data. The authors also commend Jorge Vicent Servera for their support in using the Py6S model.
Author information
Authors and Affiliations
Contributions
Emmanuel Ayodele, Conceptualization, writing — review and editing, supervision, project administration.
Chukwuma Okolie, Conceptualization, validation, formal analysis, writing—review and editing, visualization, supervision
Samuel Akinnusi, Conceptualization, methodology, software, formal analysis, validation, investigation, data curation, writing—original draft, review and editing, visualization
Erom Mbu-Ogar, Methodology, software, formal analysis, validation, investigation, writing—original draft, visualization
Rose Alani, Resources, data curation, writing—review and editing
Olagoke Daramola, Conceptualization, methodology, software, supervision
Abdulwaheed Tella, Methodology, investigation, writing—review and editing
Corresponding author
Ethics declarations
Ethical approval
Not applicable
Consent to participate
Not applicable
Consent for publication
Not applicable
Competing interests
The authors declare no competing interests.
Additional information
Responsible Editor: Philippe Garrigues
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Ayodele, E., Okolie, C., Akinnusi, S. et al. An assessment of the spatio-temporal dynamics of Landsat-derived aerosol concentration in relation with land cover and road networks in the Lagos megacity. Environ Sci Pollut Res 30, 43279–43299 (2023). https://doi.org/10.1007/s11356-022-25042-w
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11356-022-25042-w