In Situ Measurements of Domestic Water Quality and Health Risks by Elevated Concentration of Heavy Metals and Metalloids Using Monte Carlo and MLGI Methods

Delia B Senoro; Kevin Lawrence M de Jesus; Ronnel C Nolos; Ma Rowela L Lamac; Khainah M Deseo; Carlito B Tabelin

doi:10.3390/toxics10070342

In Situ Measurements of Domestic Water Quality and Health Risks by Elevated Concentration of Heavy Metals and Metalloids Using Monte Carlo and MLGI Methods

Toxics. 2022 Jun 21;10(7):342. doi: 10.3390/toxics10070342.

Authors

Delia B Senoro^{1

2

3

4

5}, Kevin Lawrence M de Jesus^{1

2

3}, Ronnel C Nolos^{1

5

6}, Ma Rowela L Lamac^{5

6}, Khainah M Deseo^{1

5}, Carlito B Tabelin⁷

Affiliations

¹ Resiliency and Sustainable Development Laboratory, Yuchengco Innovation Center, Mapua University, Intramuros, Manila 1002, Philippines.
² School of Graduate Studies, Mapua University, Intramuros, Manila 1002, Philippines.
³ School of Chemical, Biological, Materials Engineering and Sciences, Mapua University, Intramuros, Manila 1002, Philippines.
⁴ School of Civil, Environmental, and Geological Engineering, Mapua University, Intramuros, Manila 1002, Philippines.
⁵ Mapua-MSC Joint Research Laboratory, Marinduque State College, Boac 4900, Philippines.
⁶ Department of Environmental Science, College of Natural and Allied Health Sciences, Marinduque State College, Boac 4900, Philippines.
⁷ School of Minerals and Energy Resources Engineering, University of New South Wales, Sydney 2052, Australia.

Abstract

The domestic water (DW) quality of an island province in the Philippines that experienced two major mining disasters in the 1990s was assessed and evaluated in 2021 utilizing the heavy metals pollution index (MPI), Nemerow's pollution index (NPI), and the total carcinogenic risk (TCR) index. The island province sources its DW supply from groundwater (GW), surface water (SW), tap water (TP), and water refilling stations (WRS). This DW supply is used for drinking and cooking by the population. In situ analyses were carried out using an Olympus Vanta X-ray fluorescence spectrometer (XRF) and Accusensing Metals Analysis System (MAS) G1 and the target heavy metals and metalloids (HMM) were arsenic (As), barium (Ba), copper (Cu), iron (Fe), lead (Pb), manganese (Mn), nickel (Ni), and zinc (Zn). The carcinogenic risk was evaluated using the Monte Carlo (MC) method while a machine learning geostatistical interpolation (MLGI) technique was employed to create spatial maps of the metal concentrations and health risk indices. The MPI values calculated at all sampling locations for all water samples indicated a high pollution. Additionally, the NPI values computed at all sampling locations for all DW samples were categorized as "highly polluted". The results showed that the health quotient indices (HQI) for As and Pb were significantly greater than 1 in all water sources, indicating a probable significant health risk (HR) to the population of the island province. Additionally, As exhibited the highest carcinogenic risk (CR), which was observed in TW samples. This accounted for 89.7% of the total CR observed in TW. Furthermore, all sampling locations exceeded the recommended maximum threshold level of 1.0 × 10^-4 by the USEPA. Spatial distribution maps of the contaminant concentrations and health risks provide valuable information to households and guide local government units as well as regional and national agencies in developing strategic interventions to improve DW quality in the island province.

Keywords: carcinogenic risk; domestic water; machine learning; metal pollution; spatial distribution maps.

Grants and funding

D-HIVE 4B Capital/Department of Science and Technology