This study aimed to assess the influence of pollution on the quality of sediments and the risks associated with El-Qusier and Safaga Cities, Red Sea, Egypt, during 2021, divided into four sectors, using multiple pollution indices. To achieve that, we evaluated the metal pollution index (MPI), contamination factor (Cf), pollution load index (PLI), contamination security index (CSI), and anthropogenicity (Anp%). Moreover, carcinogenic and non-carcinogenic risks are used for human health hazards. Results indicated that Mn and Fe recorded the highest concentrations, whereas Cd had the lowest. El-Quseir City sediments were found the following metal ions: Fe > Mn > Ni > Zn > Cu > Co > Pb > Cd, where the order in the Safaga City was: Fe > Mn > Zn > Ni > Cu > Pb > Co > Cd. MPI > 1, this is alarming in the study area due to heavy metal pollution. In addition, C f < 1 in all metals except Cd with contamination degree CD ranged from low to considerable contamination in El-Qusier city. In contrast, contamination ranged from significant to very high in Safaga city. PLI < 1 is lower than the reference at all monitored stations. CSI values ranged from relatively low to moderate. Besides Cd, data reflect each element's low environmental danger (Eri Me 40). This study's risk index (RI) is low to moderate in Sector 1 and high to extremely high in Sector 2. HQ and HI index < 1 means it is safe for human health in order: HI ingestion > HI dermal . CSR for different pathways was recorded as dermal > ingestion, in which total CSR for all paths is considered harmful, and the cancer risk is troublesome and higher than the reference ranges of 1 × 10 -6 -1 × 10 -4 . In conclusion, the examined heavy metals provide environmental hazards across the assessed locations.
Keyphrases
- heavy metals
- risk assessment
- human health
- health risk assessment
- health risk
- metal organic framework
- sewage sludge
- climate change
- magnetic resonance
- computed tomography
- cystic fibrosis
- aqueous solution
- machine learning
- quality improvement
- quantum dots
- transition metal
- big data
- electronic health record
- artificial intelligence