Determine of Nitrogen Dioxide Emissions over Khuoms City in Libya Using MODIS and TROPOMI Satellites

Dawi Muftah  Ageel

doi:10.59743/jmset.v7i2.18

Authors

Dawi Muftah Ageel Department of Geology and Environmental Science, Faculty of Sciences, Elmergib University, Khuoms, Libya.

DOI:

https://doi.org/10.59743/jmset.v7i2.18

Keywords:

TROPOMI, MODIS, Khuoms, Libya

Abstract

Sentinel-5 Forerunner (S-5P), carrying the TROPO round recognition Instrument (TROPOMI) nadir-viewing crystal spectroscope, is that the beginning mission of the Copernicus Program committed to the recognition of air quality. Within the given data the TROPOMI tropospheric gas (NO₂) level-2 (L₂) item has been substantially over capably sullied urban districts by comparison with coincident high-resolution MODIS remote detecting observations (1 km×1 km). Satellite products may be ideally surveyed backed by 5 bands, as an out-measured amount of lackey pixels may be completely mapped within the system of the S-5P approval campaign over Khumos town in Libya. Each piece of information was taken in 2020 over a power station in Khuoms city in Libya, for mapping the level dissemination of tropospheric NO₂, each image pixel was fully covered by approximately 370 to 700 nm for visible spectrum (MODIS and TROPOMI pixels). The TROPOMI and MODIS NO₂ emissions were similar in concept, the regression analysis of both data with well correlated (R²= 0.87), and there is a negative relationship (−0.03×10¹⁵ molec/cm²) recorded when clouds and dust were prevalent over the study area. From the results obtained from MODIS and TROPOMI data, nitrogen dioxide emissions were high to medium (6.6 to 3.2×10¹⁵ molec/cm²) at their source and five kilometers from the source, while the rest of the study area ranged from (2.2 to 0.15×10¹⁵ molec/cm²) low to very low.

References

Boersma K.F., Jacob D.J., and Bucsela E.J.)2018). Validation of OMI tropospheric NO2 observations during INTEX-B and application to constrain NOx emissions over the eastern United States and Mexico. Atmos. Environ. J., 42(19): 4480–4497.

Broccardo S., Heue K.P., Walter D., Meyer C., Kokhanovsky A., van der A.R., Piketh S., Langerman K., and Platt U. )2018(. Intra-pixel variability in satellite tropospheric NO2 column densities derived from simultaneous space-borne and airborne observations over the South African Highveld. Atmos. Meas. Tech. J., 11: 2797-2819.

Cai W. (2017). Weather conditions conducive to Beijing severe haze more frequent under climate change. Nat. Clim. Change, J., 7: 257–262.

Compernolle S., Argyrouli A., Lutz R., and Sneep M. (2020). Validation of the Sentinel-5 Precursor TROPOMI cloud data with Cloudnet, MODIS. Available online at: [http://doi.org/10.5194/amt-122]

Constantin D.E. and Merlaud A. (2016). The AROMAT team: Airborne Romanian Measurements of Aerosols and Trace gases (AROMAT-II), Final report, ESTEC, Noordwijk, The Netherlands.

Dimitropoulou E., Hendrick F., Pinardi, and Van Roozendael M. (2020). Validation of TROPOMI tropospheric NO2 columns using dual-scan MAX-DOAS measurements in Uccle, Brussels. Atmos. Meas. Tech., 1-50.

Friedl M.A., McIver D.K., Hodges J.C.F., Zhang X.Y., Muchoney D., and Schaaf C. (2017). Global land cover mapping from MODIS: algorithm and early results. Remote Sens Env., 83: 287–302.

Grifﬁn D., Zhao X., McLinden, and Wolde M. (2019). High-Resolution Mapping of Nitrogen Diox-ide with TROPOMI: First Results and Validation over the Canadian Oil Sands. Geophys. Res. Lett., 46(10):49–60.

Guo X.M. (2016). Observation and Simulation of the Climate Characteristics of Air Quality and the Effects of Large Topography in Sichuan Basin. Master’s thesis, Nanjing University of Information Engineering, Nanjing, China.

Heue K.P., Wagner T., Broccardo S.P., Walter D., Piketh S.J., Ross K.E., Beirle S., and Platt U. (2018). Direct observation of two dimensional trace gas distributions with an airborne Imaging DOAS instrument. Atmos. Chem. Phys. J., 8(67): 7–19.

Hong Z. and Hu F. (2015). Advances in theories and methods of air pollution prediction. Clim. Environ. Res. J., 225–230

Huijnen V., Eskes H.J., and Poupkou A. (2016). Comparison of OMI NO2 tropospheric columns 30 with an ensemble of global and European regional air quality models. Atmos. Chem. Phys. J., 10: 10-32.

Ialongo I., Virta H., Eskes H., Hovila J., and Douros J. (2019). Comparison of TROPOMI/Sentinel 5 Precursor NO2 observations with ground-based measurements in Helsinki. Atmos. Meas. Tech. J., 3: 29-37.

Ibrahim H.G., Okasha, A.Y. Elatrash M.S. and Elmishregi M.A. (2012a). Emissions of SO2, NOx and PMs from Cement Plant in Vicinity of Khoms City in North Western Libya, Journal of Environmental Science and Engineering A1, 620-628.

Ibrahim H.G., Okasha A.Y., Elatrash M.S., and Al-Meshraghi M.A. (2012b). Investigation of SO2 and NOx Emissions from Khoms Power Stations in Libya. International Conference on Environmental, Biomedical and Biotechnology, 41: 191-195.

Ibrahim H.G., Elatrash M.S., and Okasha A.Y. (2011). Steam Power Plant Design Upgrading (Case Study: Khoms Steam Power Plant). J. of Energy and Environment Research, 1(1): 202-211.

Justice C.O., Townshend J.R.G., Vermote E.F., Masuoka E., Wolfe R.E., Saleous N., Roy D.P., and Morisette J.T. (2015). An overview of MODIS Land data processing and product status. Remote Sens. Env. J., 83: 3–15.

Kim H.C., Lee P., Judd L., Pan L., and Lefer B. (2016). OMI NO2 column densities over North American urban cities: the effect 20 of satellite footprint resolution. Geosci. Model Dev. J., 9: 1111-1123.

Kleipool Q., Ludewig A., Babić L., and Veefkind P. (2018). Pre-launch calibration results of the TROPOMI payload on-board the Sentinel-5 Precursor satellite, Atmos. Meas. Tech Journal., 11: 439-479.

Lamsal L.N., Janz S.J., Krotkov N.A., and Herman J.R. (2017). High-resolution NO2 observations from the Airborne Compact Atmospheric Mapper: Retrieval and validation: High-Resolution NO2 Observations. Journal of Geophysical Research: Atmospheres, 122(3):1953– 1970.

Lawrence J.P., Anand J.S., Vande Hey J.D., White J., Leigh R.R., Monks P.S., and Leigh R.J. (2015). High-resolution measurements from the airborne Atmospheric Nitrogen Dioxide Imager (ANDI). Atmos. Meas. Tech. J., 8: 4735–4754.

Mebust A.K., Russell A.R., Hudman R.C., Valin L.C., and Cohen R.C. (2016). Characterization of wildﬁre NO emissions using MODIS ﬁre radiative power and OMI tropospheric NO2 columns. Atmos. Chem. Phys. J., 11: 5839–5851.

Morisette J.T., Privette J.L., and Justice C.O. (2012). A framework for the validation of MODIS Land products. Remote Sens. Env. J., 83: 77–96.

Okasha A.Y. (2014). Main Industry Stack Emissions Dispersion Over Khoms City in North-Western Libya. International Journal of Innovative Science, Engineering & Technology, 1(10): 635-641.

Okasha A.Y., Hadia E.A., and Elatrash M.S. (2013). Ecological effect of Mergheb cement emissions on the vegetation in the Northwest Libya Here. Inter. J. Sci., 2(9): 34-40.

Ortega I., Koenig T., Sinreich R., Thomson D., and Volkamer R. (2015). The CU 2-D-MAX-DOAS instrument Part1: Retrieval of 3-D distributions of NO and azimuth-dependent OVOC ratios. Atmos. Meas. Tech. J., 8: 2371–2395.

Pinardi G., Van Roozendael M., Hendrick F., and Wittrock F. (2020). Validation of tropospheric NO2 column measurements of GOME-2A and OMI using MAX-DOAS and direct sun network observations. Atmos. Meas. Tech. J., 8: 61–85.

Platt U. and Stutz J. (2014). Differential absorption spectroscopy. In Differential Optical Absorption Spectroscopy. Platt, Stutz, Journal., Eds.; Springer: Cham, Switzerland,135–174.

Shi L., Xing L., Lu G., and Zou J. (2008). Evaluation of rational sulphur dioxide abatement in China. Int. J. Environ. Pollut., 35: 42–57.

USEPA (2016). Pollution by Nitrogen Dioxide (NO2). Available online at: [http://.epa.gov/no2-pollution].

USEPA (2018). Pollution by Nitrogen Dioxide (NO2) Available online at: [http://.epa.gov/no2-pollution]

Van Geffen J.H.G.M., Eskes H., Pinardi G., Verhoelst T., Compernolle S., Sneep M., ter Linden M., Boersma K.F., and Veefkind J.P. (2020). S5P/TROPOMI NO2 retrieval: impact of version V2.2 improvements and preliminary comparisons with OMI and ground-based data. Atmos. Meas. Tech. J., 3: 49-57.

Van Noije T.P.C., Eskes H.J., Dentener F.J., Stevenson, D.S., Ellingsen K., Schultz M.G., and Roozendael, M. V. (2006). Multi-model ensemble simulations of tropospheric NO2 compared with GOME retrievals for the year 2000. Atmospheric chemistry and physics, 6(10): 2943-2979.

Vasilkov A., Qin W., Krotkov N., Lamsal L., Spurr R., Haffner D., Joiner J., Yang E.-S., and Marchenko S. (2017). Accounting for the effects of surface BRDF on satellite cloud and trace-gas retrievals: a new approach based on geometry-dependent Lambertian equivalent reflectivity applied to OMI algorithms. Atmos. Meas. Tech. J., 10: 333–349.

Williams J.E., van Zadelhoff G.J., and Scheele M.P. (2017). The effect of updating scavenging and conversion rates on cloud droplets and ice particles in the TM global chemistry transport model, Technical Report TR-308, KNMI, De Bilt.

Xiao Z. (2011). Study on the Characteristics of Atmospheric NO2 in Sichuan Basin. Chin. Environ. Sci. J., 31: 1782–1788.

Zhang Y., Bocquet M., Mallet V., Seigneur C., and Baklanov A. (2012). Real-time air quality forecasting, part I: History, techniques, and current status. Atmos. Environ., 60: 632–655.

Zhao X., Griffin D., Fioletov V., McLinden C., Cede A., Tiefengraber M., Müller M., Bognar K., Strong K., Boersma F., Eskes H., Davies J., Ogyu A., and Lee S.C. (2020). Assessment of the quality of tropomi high-spatial-resolution No. 2 data products in the greater Toronto area. Atmos. Meas. Tech. J., 13: 2131–2159.