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dc.contributor.authorDasari, Hari Prasad
dc.contributor.authorDesamsetti, Srinivas
dc.contributor.authorLangodan, Sabique
dc.contributor.authorRama Krishna, L.N.K
dc.contributor.authorSingh, Shyamcharan
dc.contributor.authorHoteit, Ibrahim
dc.date.accessioned2020-06-04T13:10:01Z
dc.date.available2020-06-04T13:10:01Z
dc.date.issued2020-05-28
dc.identifier.citationDasari, H. P., Desamsetti, S., Langodan, S., Rama Krishna, L. N. ., Singh, S., & Hoteit, I. (2020). Air-quality assessment over the world’s Most Ambitious Project, NEOM in Kingdom of Saudi Arabia. IOP Conference Series: Earth and Environmental Science, 489, 012025. doi:10.1088/1755-1315/489/1/012025
dc.identifier.issn1755-1315
dc.identifier.doi10.1088/1755-1315/489/1/012025
dc.identifier.urihttp://hdl.handle.net/10754/663053
dc.description.abstractNEOM is an under-development transnational city and economic zone spreading over an area of 26,500 sq.km along the northern Red Sea coast of Saudi Arabia, bordering Jordan and Egypt. This work analyzes the meteorological parameters and air pollution dispersion over the NEOM region based on observations and air-quality dispersion modeling. The Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model was implemented to simulate air parcel trajectories, as well as transport, dispersion, chemical transformation, and deposition. To drive HYSPLIT, high-resolution meteorological data generated at 600 m resolution by downscaling ECMWF global reanalysis using the Weather Research and Forecasting (WRF) were used. The United Sates Environmental Protection Agency Air Pollutant Emission Factors 42 emission inventory was used to initialize HYSPLIT. A continuous three-year meteorological and air-quality data from WRF-HYSPLIT model is used to analyze the spatial and temporal distributions of air pollutants’ concentration over the NEOM region. Strong land and sea breezes resulting from the differential heating dominates the diurnal dispersion and distribution of pollutants in the NEOM region. The spatial distributions of the mean seasonal ambient air pollution dispersion show similar patterns, with relatively higher concentrations in spring and winter. This is more pronounced in the spatial distributions of the maximum concentrations of different pollutants, which show the maximum concentrations in the spring and winter due to lower boundary layer heights. The predicted maximum concentrations of NOX (~40 mg/m3), SO2 (~25 mg/m3), CO (~10 mg/m3), VOC (~0.05 mg/m3), and PMT (~4 mg/m3) over the study region remain well below the National Air Quality standards recommended by the Saudi General Authority for Meteorology and Environment Protection and the Royal commission. Our analysis provides needed information to understand the state of the air quality over the NEOM region, providing fundamental contribution to the environment impact assessment and planning in the region.
dc.description.sponsorshipThe study was supported by King Abdullah University of Science and Technology (KAUST) under the “Virtual Red Sea Initiative”, Award Number REP/1/3268-01-01 and the Saudi ARAMCO-KAUST Marine Environmental Research Center (SAKMERC). The research made use of the Supercomputing Laboratory resources at KAUST.
dc.publisherIOP Publishing
dc.relation.urlhttps://iopscience.iop.org/article/10.1088/1755-1315/489/1/012025
dc.rightsThe Content from this work may be used under the terms of theCreative Commons Attribution 3.0 licence. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.
dc.rights.uriCreative Commons Attribution 3.0 licence
dc.titleAir-quality assessment over the world’s Most Ambitious Project, NEOM in Kingdom of Saudi Arabia
dc.typeArticle
dc.contributor.departmentBiological and Environmental Sciences and Engineering (BESE) Division
dc.contributor.departmentEarth Fluid Modeling and Prediction Group
dc.contributor.departmentEarth Science and Engineering Program
dc.contributor.departmentPhysical Science and Engineering (PSE) Division
dc.contributor.departmentRed Sea Research Center (RSRC)
dc.identifier.journalIOP Conference Series: Earth and Environmental Science
dc.eprint.versionPost-print
dc.contributor.institutionEnstec Services Limited, Cambridge, UK.
dc.identifier.volume489
dc.identifier.pages012025
kaust.personDasari, Hari Prasad
kaust.personDesamsetti, Srinivas
kaust.personLangodan, Sabique
kaust.personRama Krishna, L.N.K
kaust.personHoteit, Ibrahim
kaust.grant.numberREP/1/3268-01-01
refterms.dateFOA2020-06-04T13:12:30Z
kaust.acknowledged.supportUnitSupercomputing Laboratory


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