Investigating the correlation between chemical parameters, risk assessment, and sensitivity analysis of fluoride and nitrate in regional groundwater sources using Monte Carlo.

Groundwater is one of the most important sources of drinking and irrigation water in arid and semi-arid areas. This study aimed to investigate the chemical quality of groundwater for drinking and irrigation, assess the non-carcinogenic risk factors resulting from the concentration of fluoride and nitrate ions, and analyze the sensitivity among children, teenagers, and adults using Monte Carlo method. A total of 171 samples were obtained from confined groundwater in Arsanjan. Among other hydrological parameters of water, EC had the highest average (1135.97). TDS ranged from 67.90 to 1878.30 mg/L, with the lowest and highest total hardness values being 2.90 and 680.8, respectively. The water quality index (WQI) results indicated that 33% of the samples were at the poor water level and the irrigation (IWQI) was less than 25 in 96.36% of the samples, which were categorized as excellent. Thus, the majority of the samples were suitable for irrigation purposes. Additionally, the oral and dermal health risks of fluoride and nitrate were less than 1 in all age groups. Concentration factor was the main indicator in the assessment of the non-carcinogenic risk factors of nitrate and fluoride. The results of sensitivity analysis revealed a reverse relationship with body weight. Further, the results of principal component analysis (PCA) showed a negative relationship between fluoride concentration and pH. Hierarchical cluster analysis also showed that the study variables belonged to three main clusters. Some elements in C1 were also found in the first factor in PCA. The elements in C2 were among the dominant compounds of the groundwater resources of the study area, which may be caused by earth cations or human activities. C3 variables may also be one of the consequences of fertilizer use in areas around groundwater sources.

Accumulation, sources, and health risks of phthalic acid esters (PAEs) in road dust from heavily industrialized, urban and rural areas in southern Iran.

In this research, a total of 51 road dust samples were collected from three districts (Asaluyeh, Bushehr, and Goshoui) in the south of Iran from April to June 2022 and analyzed for the concentration of 7 phthalic acid esters (PAEs) compounds. Asaluyeh was considered as an industrial area (near gas and petrochemical industries), Bushehr as an urban area, and Goshoui as a rural area (far from pollution sources). The PAEs concentration of the street dust samples was determined using a mass detection gas chromatography (GC/MS). The mean ± SD levels of Æ©PAEs in samples from industrial, urban, and rural sources were 56.9 ± 11.5, 18.3 ± 9.64, and 5.68 ± 1.85 µg/g, respectively. The mean concentration levels of Æ©PAEs was significantly (P < 0.05) higher in samples from the industrial area than urban and rural areas. The mean levels of di(2-Ethylhexyl) phthalate (DEHP) in industrial, urban, and rural areas were 20.3 ± 8.76, 4.59 ± 1.71, and 2.35 ± 0.98 µg/g, respectively. The results of the PCA analysis indicate that the likely major sources of PAEs in the road dust in the studied areas are the application of various plasticizers in industry, solvents, chemical fertilizers, waste disposal, wastewater (e.g., agricultural, domestic, and industrial), and the use of plastic films and plastic-based irrigation pipes in greenhouses. As well as, it was found that the non-cancer risk of exposure to dust-bound PAEs was higher for children than for adults. These values were <1 for both age groups (children and adults) and the exposure of inhabitants to PAEs in road dust did not pose a notable non-cancer risk. The cancer risk from exposure to DEHP in road dust was below the standard range of 10-6 in all three areas. Further studies that consider different routes of exposure to these contaminants are needed for an accurate risk assessment. Moreover, since higher PAEs level was found in industrial area, decision-makers should adopt strict strategies to control the discharging of pollution from industries to the environment and human societies.

Comprehensive health risk analysis of heavy metal pollution using water quality indices and Monte Carlo simulation in R software.

Rapid urbanization, population growth, agricultural practices, and industrial activities have led to widespread groundwater contamination. This study evaluated heavy metal contamination in residential drinking water in Shiraz, Iran (2021). The analysis involved 80 groundwater samples collected across wet and dry seasons. Water quality was comprehensively assessed using several indices, including the heavy metals evaluation index (HEI), heavy metal pollution index (HPI), contamination degree (CD), and metal index (MI). Carcinogenic and non-carcinogenic risk assessments were conducted using deterministic and probabilistic approaches for exposed populations. In the non-carcinogenic risk assessment, the chronic daily intake (CDI), hazard quotient (HQ), and hazard index (HI) are employed. The precision of risk assessment was bolstered through the utilization of Monte Carlo simulation, executed using the R software platform. Based on the results, in both wet and dry seasons, Zinc (Zn) consistently demonstrates the highest mean concentration, followed by Manganese (Mn) and Chromium (Cr). During the wet and dry seasons, 25% and 40% of the regions exhibited high CD, respectively. According to non-carcinogenic risk assessment, Cr presents the highest CDI and HQ in children and adults, followed by Mn, As and HI values, indicating elevated risk for children. The highest carcinogenic risk was for Cr in adults, while the lowest was for Cd in children. The sensitivity analysis found that heavy metal concentration and ingestion rate significantly impact both carcinogenic and non-carcinogenic risks. These findings provide critical insights for shaping policy and allocating resources towards effectively managing heavy metal contamination in residential drinking water.

The Relationship between Air Pollution and Brain Cancer: A Systematic Review and Meta-Analysis.

Background: There is very little epidemiological evidence on the effects of ambient air pollution on brain tumor risk. The purpose of this study was to determine the relationship between exposure to air pollution and the incidence of brain tumors. Methods: A comprehensive literature search in five international databases, including PubMed/Medline, ProQuest, Scopus, Embase, and ISI/WOS on April 15, 2019, was conducted. The methodology of the present study was based on the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) statement. The Newcastle-Ottawa Quality Assessment Form was used to evaluate the quality of the selected papers. Results: Five studies that measured adult brain tumors as well as their long-term exposure to at least one of the pollutants criteria for air pollution, PM2.5 absorbance, and proximity to traffic (Trafnear) were reviewed. The results showed that the pooled relative risk (RR) for incidence of brain tumor and long term exposure to Trafnear, PM2.5, PM2.5 absorbance, O3 and NOx were RR = 1.07, (95% CI 0.99-1.16), P = 0.079, for Trafnear; RR = 0.90, (95% CI 0.80-1.00), P = 0.064 for PM2.5; RR = 1.63, (95% CI 1.04-2.55), P = 0.031 for PM2.5 absorbance; RR = 1.3, (95% CI 1.03-1.6), P = 0.023 for O3; and RR = 1.16, (95% CI 0.93-1.45), P = 0.173 for NOx. Exposure to other air pollutants had no statistically significant association with brain tumor incidence. Conclusion: The results showed that exposure to air pollutants, such as O3 and PM2.5 absorbance, had the highest correlation with brain tumor incidence. They also showed an absence of correlation between exposure to certain pollutants (SO2, CO, NO2, PM10, PM2.5) and brain tumor incidence.

Short-term exposure to some heavy metals carried with PM10 and cardiovascular system biomarkers during dust storm.

This study aimed to evaluate the effect of short-term exposure to heavy metals (HM) extracted from PM10 on CB in workers' population in an outdoor space located in southern Iran during a dust storm. At first, 44 healthy and non-smoking workers were selected. Then PM10 and Blood samples were collected before and after the dust storm. Finally, HMs associated with PM10 measured by ICP-MS and its effect on the CB, including fibrinogen, CRP, TNF-α, and BP were estimated by ANOVA, Pearson correlation, and Odd Ratio (OR) in SPSS23. Based on the results, the concentration of PM10 and extracted HM such as Cr, As, and Cd was higher than the WHO/EPA standards in dust storms they increased the CB and BP remarkably. Moreover, the level of fibrinogen, blood pressure (BP) and TNF-α in dust storms were higher than in normal conditions (p < 0.05, OR > 3). In addition, As and Cd decreased fibrinogen concentration and systolic BP, respectively. Whereas, TNF-α was associated with concentration of Pb (R = - 0.85) on normal days. Consequently, the HM on PM10 such as As, interferes with the level of investigated CB. These results considered a potential risk for the residents in the southern regions of Iran.

Spatial and temporal variation of CBPI and leakage of heavy metals from cigarette butts into the urban environment.

More than 5 trillion cigarettes are produced in the world every year. This hazardous waste is one of the most important litter in the environment. The purpose of this study was to investigate the density and dispersion of cigarette butts in the urban environment and to estimate the leakage of pollution from it to the environment. For this purpose, the cigarette butt pollution index was used in 14 locations. Observations were made during a year and once a month for each location. The study of the locations was done with the same conditions on weekend and working days. The amount of heavy metal leakage was estimated based on the average weight of cigarette butts and the ratio of metal leakage in different weather conditions. The results showed that the annual average of index for the studied locations was 1.36 (SD 0.11) to 10.6 (SD 1.23). Based on this, 28.5% of the locations were in the low pollution status and 42.8% were in the significant pollution status and worse. On average, the index on weekend decreased by 32.3 percent in all locations, and the average index of the studied locations in spring and summer was 26.2 percent higher than in autumn and winter. The average leakage of heavy metals including chromium, cadmium, zinc, lead, copper, and nickel from littered cigarette butts in commercial, residential, and recreational areas was estimated to be 0.27, 0.079, and 0.17 µg per square meter, respectively. Cigarette butt is one of the most abundant litter in the studied area, which is the source of many pollutants, including heavy metals. This hazardous waste is a serious threat to the urban environment.

Acrylamide; a neurotoxin in popcorns: a systematic review and meta-analysis.

Acrylamide is a known neurotoxic compound for humans. Foods that have high concentrations of acrylamide need to be identified. One of the food products containing acrylamide is popcorn. Popcorn is an important source of snacks for children, especially students. The presented study is a systematic review and meta-analysis of the level of acrylamide in popcorn. The search was done in different databases with the keywords; acrylamide, popcorn, popped corn. 27 articles were found by searching various databases. After initial screening and full text evaluation, 8 articles were selected for systematic review and 6 articles for meta-analysis. The amount of acrylamide in this product was in the range of 1,017.7-106 µg/kg. Microwaved corn contains lower amounts of acrylamide than other methods of preparation. The type of popcorn also had an effect on the amount of acrylamide with Meta-regression. It was found that sweet popcorn contains higher amounts of acrylamide. The overall value of acrylamide concentration in popcorns was calculated to be 459.6 ± 220.3 µg/kg. This amount is high and requires measures to reduce the amount of acrylamide.

An ontology-based study on water quality: probabilistic risk assessment of exposure to fluoride and nitrate in Shiraz drinking water, Iran using fuzzy multi-criteria group decision-making models.

World Health Organization reports that 2.2 million people die yearly from insufficient sanitary drinking water. This ontology-based study focused on investigating the chemical quality of drinking water through a new water quality index designed by fuzzy multi-criteria group decision-making methods, merged with GIS, and, secondly, surveying non-carcinogenic risk assessment of fluoride and nitrate using Monte Carlo simulation and sensitivity analysis in Shiraz's water sources. F-, NO3-, NO2-, EC, TDS, alkalinity, TH, SO42-, Cl-, and Na were applied in the WQI. The NO3- mean concentrations were 23.15 and 27.66 mg/L in the cold and warm seasons, while the mean concentrations of fluoride were 0.50 and 0.46 mg/L during the cold and warm period. The 95th centiles of fluoride's HQs among infants, children, teenagers, and adults were 0.56, 0.7, 0.49, and 0.4, respectively, in the cold season, which was 0.65 and 0.81, respectively, 0.57 and 0.46 for mentioned groups in the warm season. In comparison, the 95th centiles of nitrate's HQs among infants, children, teenagers, and adults were 1.27, 1.59, 1.13, and 0.9, respectively. The HQs were more than 1 for infants, children, and teenagers, so nitrate can have various adverse effects, whereas fluoride does not adversely affect all aging groups in both seasons. Also, nitrate concentration can increase the non-carcinogenic risk, which the IR and ED lead to the HQ increasing. In contrast, BW has a negative effect on risk increasing. Overall, source management of these parameters can significantly reduce the concentration of nitrate and their adverse human health effect.

Effect of land use changes on non-carcinogenic health risks due to nitrate exposure to drinking groundwater.

This study aimed to determine the effect of land-use changes on the non-carcinogenic health risk of nitrate ion exposure of underground drinking water resources in Shiraz (Iran). To this end, 175 chemical samples for the nitrate analysis were regularly taken from 35 drinking water wells of Shiraz from 2013 to 2017, and their results were zoned using GIS. Hazard quotient (HQ) induced by nitrate ion exposure was determined in four age groups: infants, children, adolescents, and adults. Area changes of four types of land-use, including residential, agricultural and green space, industrial, and bare land within a radius of 400 m of drinking water wells, were determined using the GIS and Google Earth software. Then, all data was imported to Matlab 2018 for statistical analysis. The results showed that mean nitrate concentration increased by 2.5 mg L-1 from 2013 to 2017. According to the zoning map, 5 and 11.4% of the area in 2013 and 2017, respectively, exceeded the drinking water standard set by nitrate (i.e., 50 mg/L). Air temperature and precipitation variations also influenced nitrate concentrations and HQ changes (Rtemperature = 0.67). Children's age group was the most vulnerable, and during the study period, this vulnerability was an increasing trend, so that the HQ from 0.93 in 2013 to 0.97 in 2017 has increased. The rate of land-use changes in agricultural, industrial, bare, and urban was -1.8%, 1.3%, -4.6%, and 2.1%, respectively, and the highest correlation was observed between HQ and Diff.l residential land use (Rinfant = 0.55). According to the results, the most influential factor in HQ was air temperature (R = 0.66), and urban land-use change (R > 0.44). To sum up, this study's results showed that land-use changes, especially urban and residential development, significantly affect groundwater nitrate concentration and its degree of HQ. Moreover, increasing temperature and decreasing annual precipitation can also increase the severity of this risk.

A survey of the secondary exposure to organophosphate and organochlorine pesticides and the impact of preventive factors in female villagers.

Organophosphates (OPs) and organochlorine pesticides (OCPs) are two main types of pesticides that are widely used worldwide, and their toxicities have been reported in high-risk individuals, such as farmers and their wives. The aim of this study was to evaluate the levels of mentioned pesticides in farmers' wives (FWs) and compare them with the control group; we also aimed to assess the effect of personal health factors on the biochemical parameters. This case-control study was conducted on two FWs and control groups, consisting of 124 and 62 individuals, respectively. Serum levels of OCPs were measured using gas chromatography (GC) method. In addition, the activity of acetylcholine esterase (AChE), total antioxidant capacity (TAC), and serum levels of malondialdehyde (MDA) were evaluated in all participants. Additionally, the observance of personal health guidelines was assessed. Serum levels of OCPs in the FWs group were significantly higher than the controls. In addition, AChE activity in FWs was significantly lower than the controls. Moreover, it was found that higher levels of education lead to a better observation of most individual health guidelines, which results in reducing the biological adverse effects of pesticides. The results of this study indicated that the use of OCPs, as an illegal pesticide with known toxic and carcinogenic effects, has spread to southern Iran, which may have biological toxic effects. Also, observing the personal health points significantly reduced these complications and it is, therefore, recommended that more attention should be paid to this issue.

Modelling and Optimizing Pyrene Removal from the Soil by Phytoremediation using Response Surface Methodology, Artificial Neural Networks, and Genetic Algorithm.

This study aimed to model and optimize pyrene removal from the soil contaminated by sorghum bicolor plant using Response Surface Methodology (RSM) and Artificial Neural Network (ANN) with Genetic Algorithm (GA) approach. Here, the effects of indole acetic acid (IAA) and pseudomonas aeruginosa bacteria on increasing pyrene removal efficiency by phytoremediation process was studied. The experimental design was done using the Box-Behnken Design (BBD) technique. In the RSM model, the non-linear second-order model was in good agreement with the laboratory results. A two-layer Feed-Forward Back-Propagation Neural Network (FFBPNN) model was designed. Various training algorithms were evaluated and the Levenberg Marquardt (LM) algorithm was selected as the best one. Existence of eight neurons in the hidden layer leads to the highest R and lowest MSE and MAE. The results of the GA determined the optimum performance conditions. The results showed that using indole acetic acid and pseudomonas bacteria increased the efficiency of the sorghum plant in removing pyrene from the soil. The comparison obviously indicated that the prediction capability of the ANN model was much better than that of the RSM model.