TY - JOUR
T1 - A Monte Carlo simulation approach for the assessment of health risk from NO 3- -N perturbation in groundwater
AU - Afrifa, George Y.
AU - Ansah-Narh, Theophilus
AU - Ibrahim, Kwabina
AU - Loh, Yvonne S.A.
AU - Sakyi, Patrick A.
AU - Chegbeleh, Larry Pax
AU - Yidana, Sandow M.
N1 - Publisher Copyright:
© 2023, The Author(s), under exclusive licence to Springer Nature Switzerland AG.
PY - 2023/11
Y1 - 2023/11
N2 - As a prerequisite towards sustainable management of an aquifer system, it is critical to reveal and quantify the relationship between NO3-–N and human health in order to delineate health-risk zones. The various sources of NO3-–N in an environment as well as the interaction of natural and anthropogenic processes, present considerable obstacles when considering a technique to estimate health risk. Another constraint on health risk estimation is choosing right technique. This research applied deterministic and MC approaches coupled with finite mixture model to evaluate the sources and concentrations of NO3-–N in groundwater, and appraise the hazard risks associated with various exposure groups in the Densu Basin in Southern Ghana. The Monte Carlo approach was applied to the data with due cognizance of the various identified sources of NO3-–N, and a hypothetical single source (HSS). The results suggest that the probability of risk for identified NO3-–N sources (human-induced) fall within the ranges of 0.16-- 0.39, 0.15-- 0.30, and 0.12-- 0.24 respectively for infants, children, and adults. The MC technique applied to the HSS concentration recorded a relatively low probability of risk, presenting 0.07-- 0.17, 0.02-- 0.05, and 0.01-- 0.04 for infants, children, and adults respectively. It, therefore, goes without saying that the health hazard caused by the human-induced sources of NO3-–N on exposure groups is comparatively higher than the single sources. The MC simulation based on identified NO3-–N sources appears to have performed better compared to the HSS and the deterministic approach.
AB - As a prerequisite towards sustainable management of an aquifer system, it is critical to reveal and quantify the relationship between NO3-–N and human health in order to delineate health-risk zones. The various sources of NO3-–N in an environment as well as the interaction of natural and anthropogenic processes, present considerable obstacles when considering a technique to estimate health risk. Another constraint on health risk estimation is choosing right technique. This research applied deterministic and MC approaches coupled with finite mixture model to evaluate the sources and concentrations of NO3-–N in groundwater, and appraise the hazard risks associated with various exposure groups in the Densu Basin in Southern Ghana. The Monte Carlo approach was applied to the data with due cognizance of the various identified sources of NO3-–N, and a hypothetical single source (HSS). The results suggest that the probability of risk for identified NO3-–N sources (human-induced) fall within the ranges of 0.16-- 0.39, 0.15-- 0.30, and 0.12-- 0.24 respectively for infants, children, and adults. The MC technique applied to the HSS concentration recorded a relatively low probability of risk, presenting 0.07-- 0.17, 0.02-- 0.05, and 0.01-- 0.04 for infants, children, and adults respectively. It, therefore, goes without saying that the health hazard caused by the human-induced sources of NO3-–N on exposure groups is comparatively higher than the single sources. The MC simulation based on identified NO3-–N sources appears to have performed better compared to the HSS and the deterministic approach.
KW - Anthropogenic activities
KW - Densu Basin
KW - Groundwater nitrate
KW - Health risk assessment
KW - Monte Carlo simulation
KW - Non-carcinogenic
UR - http://www.scopus.com/inward/record.url?scp=85150458789&partnerID=8YFLogxK
U2 - 10.1007/s40808-023-01753-y
DO - 10.1007/s40808-023-01753-y
M3 - Article
AN - SCOPUS:85150458789
SN - 2363-6203
VL - 9
SP - 4539
EP - 4555
JO - Modeling Earth Systems and Environment
JF - Modeling Earth Systems and Environment
IS - 4
ER -