Metals and Metalloid Concentrations in Fish, Its Spatial Distribution in PPC, Philippines and the Attributable Risks.

Fish is an important source of protein in human meals around the world. However, the fish that we are eating may be contaminated with toxicants such as metals and metalloids (MMs), which may pose health risks to consumers. Information on MMs content in fishes and their potential spatial distribution scenarios would provide knowledge to the community to create strategies and protect human health. Hence, this study assessed and determined the health risk levels of MMs in both brackish and marine water fish (BMF) in Puerto Princesa City (PPC), Palawan Province, Philippines. PPC has an existing abandoned open mine pit near the PPC coastline called the "pit lake". The concentrations of As, Ba, Cu, Fe, Mn, Hg, and Zn in fishes were analyzed using portable Olympus Vanta X-ray Fluorescence (pXRF), and the spatial distribution of MMs concentrations in BMF was analyzed using a GIS (geographic information system). Fishes were sampled from fishing boat landing sites and nearby seafood markets. The results revealed that the concentration of MMs in marine fish was generally higher than the brackish water fish. It was recorded that the Hg concentration in marine water fish meat was higher than in brackish water fish meat. The Mn concentration in marine water fish exceeded the permissible limits set by international bodies. An elevated concentration of Mn in BMF was detected across the northern part of PPC, and an elevated concentration of Hg in marine fishes was recorded in the southeast area, where the fish landing sites are located. Ba was also detected in BMF across the southern part of PPC. Moreover, an elevated concentration of Cu was detected in MBF in the northeast and in marine fish in the southeastern area of PPC. Further, this paper elaborates the non-carcinogenic and carcinogenic risks of these fishes to the PPC population and tourists with respect to the MMs content in fish meat.

Detection of Heavy Metals, Their Distribution in Tilapia spp., and Health Risks Assessment.

Concentrations of heavy metals (HMs) were assessed in Tilapia spp. from selected communities in Calapan City, Philippines. Eleven (11) inland farmed tilapia samples were collected and analyzed for HMs concentration using X-ray fluorescence (XRF). The 11 fish samples were cut into seven pieces, according to the fish body parts, constituting a total of 77 samples. These fish samples were then labeled as bone, fins, head, meat, skin, and viscera. Results showed that the mean concentration of Cd in all parts of tilapia exceeded the Food and Agriculture Organization/World Health Organization (FAO/WHO) limits. The highest concentration was recorded in the fins, which was sevenfold higher than the limit. The trend of the mean concentration of Cd in different parts of tilapia was fins > viscera > skin > tail > head > meat > bone. The target hazard quotient (THQ) recorded a value less than 1. This means that the population exposed to tilapia, within the area where fish samples originated, were not at risk to non-carcinogens. The concentrations of Cu, Pb, Mn, Hg, and Zn in different parts, particularly in skin, fins, and viscera, also exceeded the FAO/WHO limits. The calculated cancer risk (CR) in consuming the fish skin, meat, fins, bone, viscera, and head was higher than the USEPA limit. This indicated a possible carcinogenic risk when consumed regularly. Most of the correlations observed between HMs in various parts of the tilapia had positive (direct) relationships, which were attributed to the HM toxicity target organ characteristics. Results of the principal component analysis (PCA) showed that most of the dominating HMs recorded in tilapia were attributable to anthropogenic activities and natural weathering within the watershed of agricultural areas. The agriculture area comprises about 86.83% of the overall land area of Calapan City. The identified carcinogenic risks were associated with Cd. Therefore, regular monitoring of HMs in inland fishes, their habitat, and surface water quality shall be carried out. This information is useful in creating strategies in metals concentration monitoring, health risks reduction program, and relevant guidelines that would reduce the accumulation of HM in fish.

Quantitative Assessment and Spatial Analysis of Metals and Metalloids in Soil Using the Geo-Accumulation Index in the Capital Town of Romblon Province, Philippines.

The municipality of Romblon in the Philippines is an island known for its marble industry. The subsurface of the Philippines is known for its limestone. The production of marble into slab, tiles, and novelty items requires heavy equipment to cut rocks and boulders. The finishing of marble requires polishing to smoothen the surface. During the manufacturing process, massive amounts of particulates and slurry are produced, and with a lack of technology and human expertise, the environment can be adversely affected. Hence, this study assessed and monitored the environmental conditions in the municipality of Romblon, particularly the soils and sediments, which were affected due to uncontrolled discharges and particulates deposition. A total of fifty-six soil and twenty-three sediment samples were collected and used to estimate the metal and metalloid (MM) concentrations in the whole area using a neural network-particle swarm optimization inverse distance weighting model (NN-PSO). There were nine MMs; e.g., As, Cr, Ni, Pb, Cu, Ba, Mn, Zn and Fe, with significant concentrations detected in the area in both soils and sediments. The geo-accumulation index was computed to assess the level of contamination in the area, and only the soil exhibited contamination with zinc, while others were still on a safe level. Nemerow's pollution index (NPI) was calculated for the samples collected, and soil was evaluated and seen to have a light pollution level, while sediment was considered as "clean". Furthermore, the single ecological risk (Er) index for both soil and sediment samples was considered to be a low pollution risk because all values of Er were less than 40.

An innovative reuse of bottom ash from municipal solid waste incinerators as substrates of constructed wetlands.

The incineration of municipal solid waste has been important in waste management, but it raises another environmental issue concerning residue treatment. This study describes an innovative use of naturally aged incineration bottom ash (AIBA) as an alternative substrate for horizontal subsurface flow (HSSF) constructed wetlands (CW). Although experimental results from a period lasting for 396 days only revealed slightly higher removal ratios in HSSF with AIBA (HSSF-E) than in HSSF-traditional pebble beds (HSSF-C), increasing from 67% to 76% for BOD, 44%-51% for TKN, 47%-54% for NH3-N, and 44%-52% for TN. The data indicate that the use of AIBA in HSSF CW can achieves a certain removal efficiency of BOD and nitrogen species. Interestingly, the total phosphorus removal rates also increased significantly from 20% in HSSF-C to 36% in HSSF-E. These observations on the use of AIBA in HSSF CW confirmed that AIBA is a suitable alternative for use as a substrate for HSSF CWs and identified an additional way to reuse incineration bottom ash. Design criteria for a CW using AIBA as a partial substrate is proposed to improve the pollutant removal performance of HSSF CWs.

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

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.

Neuro-Particle Swarm Optimization Based In-Situ Prediction Model for Heavy Metals Concentration in Groundwater and Surface Water.

Limited monitoring activities to assess data on heavy metal (HM) concentration contribute to worldwide concern for the environmental quality and the degree of toxicants in areas where there are elevated metals concentrations. Hence, this study used in-situ physicochemical parameters to the limited data on HM concentration in SW and GW. The site of the study was Marinduque Island Province in the Philippines, which experienced two mining disasters. Prediction model results showed that the SW models during the dry and wet seasons recorded a mean squared error (MSE) ranging from 6 × 10-7 to 0.070276. The GW models recorded a range from 5 × 10-8 to 0.045373, all of which were approaching the ideal MSE value of 0. Kling-Gupta efficiency values of developed models were all greater than 0.95. The developed neural network-particle swarm optimization (NN-PSO) models for SW and GW were compared to linear and support vector machine (SVM) models and previously published deterministic and artificial intelligence (AI) models. The findings indicated that the developed NN-PSO models are superior to the developed linear and SVM models, up to 1.60 and 1.40 times greater than the best model observed created by linear and SVM models for SW and GW, respectively. The developed models were also on par with previously published deterministic and AI-based models considering their prediction capability. Sensitivity analysis using Olden's connection weights approach showed that pH influenced the concentration of HM significantly. Established on the research findings, it can be stated that the NN-PSO is an effective and practical approach in the prediction of HM concentration in water resources that contributes a solution to the limited HM concentration monitored data.

Health Risks Due to Metal Concentrations in Soil and Vegetables from the Six Municipalities of the Island Province in the Philippines.

This paper investigated the health risks due to metal concentrations in soil and vegetables from the island province in the Philippines and the potential ecological risks. The concentrations of Cd, Cr, Cu, Fe, Mn, Ni, Pb, and Zn in vegetables and soil in six municipalities of the province were analyzed using the Inductively Coupled Plasma Optical Emission Spectrometry (ICP-OES) Perkin Elmer Optima 8000. It was recorded that all metal concentrations in the soil, except for Cd, exceeded the soil quality standard (SQS). The concentration of Fe and Mn was highest among other metals. The Nemerow synthetical pollution index (Pn) in all soil samples was under Class V which means severe pollution level. Likewise, the risk index (RI) of soil ranged from high to very high pollution risk. Most of the metal concentrations in the vegetables analyzed also exceeded the maximum permissible limit (MPL). All health hazard indices (HHIs) were less than 1, which means potential low non-carcinogenic risk to human population by vegetable consumption. However, it was found that concentration of Cr and Ni in vegetables is a potential health hazard having concentrations exceeding the maximum threshold limit. A 75% temporary consumption reduction of bitter melon, eggplant, sweet potato tops, and string beans produced from two municipalities may be helpful in reducing exposure to target metals. Additional studies are needed to confirm this recommendation. Spatial correlation analysis showed that six out of target metals had datasets that were more spatially clustered than would be expected. The recorded data are useful for creation of research direction, and aid in developing strategies for remediation, tools, and programs for improving environmental and vegetable quality monitoring.

A Hybrid Neural Network-Particle Swarm Optimization Informed Spatial Interpolation Technique for Groundwater Quality Mapping in a Small Island Province of the Philippines.

Water quality monitoring demands the use of spatial interpolation techniques due to on-ground challenges. The implementation of various spatial interpolation methods results in significant variations from the true spatial distribution of water quality in a specific location. The aim of this research is to improve mapping prediction capabilities of spatial interpolation algorithms by using a neural network with the particle swarm optimization (NN-PSO) technique. Hybrid interpolation approaches were evaluated and compared by cross-validation using mean absolute error (MAE) and Pearson's correlation coefficient (R). The governing interpolation techniques for the physicochemical parameters of groundwater (GW) and heavy metal concentrations were the geostatistical approaches combined with NN-PSO. The best methods for physicochemical characteristics and heavy metal concentrations were observed to have the least MAE and R values, ranging from 1.7 to 4.3 times and 1.2 to 5.6 times higher than the interpolation technique without the NN-PSO for the dry and wet season, respectively. The hybrid interpolation methods exhibit an improved performance as compared to the non-hybrid methods. The application of NN-PSO technique to spatial interpolation methods was found to be a promising approach for improving the accuracy of spatial maps for GW quality.

Transition Metals in Freshwater Crustaceans, Tilapia, and Inland Water: Hazardous to the Population of the Small Island Province.

This paper elaborates on the potential toxicants detected in inland water, freshwater crustaceans, and tilapia in an island that experienced mining disasters in 1993 and 1996. Specimen samples were collected in six municipalities of the island province in 2019 and presence of metals (Cd, Cr, Cu, Fe, Mn, Ni, Pb, and Zn) were analyzed using Inductively Coupled Plasma-Optical Emission Spectrometer (ICP-OES). Potential ecological risks analysis followed the Hakanson approach. Canonical correspondence analysis PAST Version 3.22, IBM SPSS 25.0, and Pearson correlation were employed for statistical analysis, and GIS Pro 2.5 for mapping of sampling locations and spatial distribution. Results showed that Mn and Zn concentration was highest in surface water (SW) and groundwater (GW), respectively. All metal concentration values exceeded the maximum permissible limit by regulatory international organizations. Elevated concentration of Cr, Cu, Fe, Mn, and Zn was detected in both crustaceans and tilapia. The calculated health hazard indices were greater than one, which means potential high adverse effects on public health when ingested. The municipality of Sta. Cruz and Torrijos recorded higher potential ecological risk among the six municipalities. Results of the correlation analysis suggested that metals in SW and GW have a similar origin, mutual dependence, and identical behavior during transport.

Application of an innovative front aeration and internal recirculation strategy to improve the removal of pollutants in subsurface flow constructed wetlands.

The pollutant removal performance of traditional horizontal subsurface flow (HSSF) constructed wetlands (CWs) is limited because of the dissolved oxygen (DO) supply is insufficient. The aeration of HSSF CWs usually improves their pollutant removal performance, but a high DO induces the accumulation of nitrate-nitrogen (NO3--N) and suppresses the improvement of total nitrogen (TN) removal. In this study, an integrated solution that involved in-tank front aeration and internal recirculation (FAIR) was used to improve the pollutant removal performance of HSSF CWs. Based on the experimental results, the FAIR system significantly increased the removal efficiencies of biochemical oxygen demand (BOD) from 53.8-76.0% to 82.0-91.7% and reduced the BOD concentration in the effluent to below 10 mg L-1. The removal efficiency of ammonia-nitrogen (NH3-N) increased from 15.1-78.3% to 98.5-98.6% while the removal efficiencies of the total Kjeldahl nitrogen (TKN) of the control and FAIR HSSF CWs were 18.2-77.1% and 93.5-94.3%, respectively. HSSF CWs with FAIR outperformed aerated HSSF CWs in the removal of NH3-N and TKN. The effects of two recirculation flow ratios (Rr = recirculation flow rate/influent flow rate), 14.3 and 3.0, on the improvement of pollutant removal performance were investigated. The lower Rr did not significantly affect the improvement of BOD, NH3-N, and TKN, but a higher Rr resulted in more severe accumulation of NO3--N. The removal efficiency of TN in control HSSF CWs ranged from 20.4% to 75.5%, and in the FAIR HSSF CW was 71.6% for Rr = 14.3 and 81.3% for Rr = 3.0. However, the FAIR system did not enhance the removal performance of total phosphorus, suggesting that the DO level and internal recirculation were not dominant mechanisms for the removal of phosphorous. The easy maintenance of the FAIR system made it a superior modification for improving the pollutant removal performance of HSSF CWs.

Adsorption of indium(III) ions from aqueous solution using chitosan-coated bentonite beads.

Batch adsorption study was utilized in evaluating the potential suitability of chitosan-coated bentonite (CCB) as an adsorbent in the removal of indium ions from aqueous solution. The percentage (%) removal and adsorption capacity of indium(III) were examined as a function of solution pH, initial concentration, adsorbent dosage and temperature. The experimental data were fitted with several isotherm models, where the equilibrium data was best described by Langmuir isotherm. The mean energy (E) value was found in the range of 1-8kJ/mol, indicating that the governing type of adsorption of indium(III) onto CCB is essentially physical. Thermodynamic parameters, including Gibbs free energy, enthalpy, and entropy indicated that the indium(III) ions adsorption onto CCB was feasible, spontaneous and endothermic in the temperature range of 278-318K. The kinetics was evaluated utilizing the pseudo-first order and pseudo-second order model. The adsorption kinetics of indium(III) best fits the pseudo-second order (R(2)>0.99), which implies that chemical sorption as the rate-limiting step.