Pub Date : 2023-04-19DOI: 10.1080/10807039.2023.2202262
P. Hien, P. K. Long
Abstract We assess the radiological impact on Vietnam from a hypothetical accident at the Fanchenggang nuclear power plant (F-NPP), 65 km from Vietnam’s Mongcai city. The accident was assumed to release, among other types of radionuclides, 1E + 16 Bq 131I in 24 h. The simulation of radioactive plumes using the FLEXPART model has revealed peak concentrations of radionuclides in the air and dry and wet depositions on the ground marking the passage of radioactive plumes over the receptor sites. The northeast monsoon wind drives the peak dry depositions in winter, while the peak wet depositions are associated mainly with the high monsoon rainfall in summer. The accident impact, reflected in the frequency of plume passage over the receptor site and the resultant radiation dose to people, decreases exponentially with the distance to F-NPP. The impact on Mongcai was most severe, implying people would be advised to stay indoors during plume passage. Meanwhile, at Danang, 630 km south of F-NPP, the impact was insignificant, as plumes rarely passed through, and the maximum dose was as low as the annual dose due to exposure from naturally occurring radionuclides in soils.
{"title":"Assessing the potential radiological impacts on Vietnam from a hypothetical accident at a nearby Chinese nuclear power plant","authors":"P. Hien, P. K. Long","doi":"10.1080/10807039.2023.2202262","DOIUrl":"https://doi.org/10.1080/10807039.2023.2202262","url":null,"abstract":"Abstract We assess the radiological impact on Vietnam from a hypothetical accident at the Fanchenggang nuclear power plant (F-NPP), 65 km from Vietnam’s Mongcai city. The accident was assumed to release, among other types of radionuclides, 1E + 16 Bq 131I in 24 h. The simulation of radioactive plumes using the FLEXPART model has revealed peak concentrations of radionuclides in the air and dry and wet depositions on the ground marking the passage of radioactive plumes over the receptor sites. The northeast monsoon wind drives the peak dry depositions in winter, while the peak wet depositions are associated mainly with the high monsoon rainfall in summer. The accident impact, reflected in the frequency of plume passage over the receptor site and the resultant radiation dose to people, decreases exponentially with the distance to F-NPP. The impact on Mongcai was most severe, implying people would be advised to stay indoors during plume passage. Meanwhile, at Danang, 630 km south of F-NPP, the impact was insignificant, as plumes rarely passed through, and the maximum dose was as low as the annual dose due to exposure from naturally occurring radionuclides in soils.","PeriodicalId":13141,"journal":{"name":"Human and Ecological Risk Assessment: An International Journal","volume":"74 1","pages":"916 - 926"},"PeriodicalIF":0.0,"publicationDate":"2023-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83998290","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract Water shortages and groundwater depletion are critical issues in the world, leading to unsustainable agricultural production and adverse ecological impacts. Here, the new Multifactor-Quantitative joint Prediction Model (MQPM) is developed to quantitatively predict the Groundwater Storage Anomalies (GWSA), which includes an annual multifactor module and a monthly quantitative module. The correlative coefficients from two modules between simulated GWSA and observed GWSA reach up to 0.98 and 0.87, respectively. Taking Beijing as an example, results show that GWSA trends before South-to-North Water Diversion (SNWD) (2005–2014) and after SNWD (2015–2018) are at a rate of −3.00 × 108 m3/yr and 1.95 × 108 m3/yr, respectively, which reflects the effectiveness of water diversion. Additionally, the predicted results show that GWSA from the multifactor module will increase to 45.97 × 108 m3 by 2028. The quantitative module designs four scenarios under different climate changes and policies, from which the predicted GWSA with values ranging from 28.49 × 108 m3 to 63.06 × 108 m3. For the latter module, the groundwater level will recover to ∼8.9 m up to 2028, combining multiple favorable conditions. Finally, factors consisting of water diversion, climate change, and water-saving policies have a vital influence on groundwater variations, and contributions of these factors to the GWSA account for 46%, 27%, and 27%, respectively.
{"title":"Assessing groundwater storage anomalies in Beijing based on the new multifactor-quantitative joint prediction model","authors":"Qingqing Wang, Wei Zheng, Wenjie Yin, Aiping Feng, Guohua Kang, Yifan Shen, Gangqiang Zhang, Shuai Yang","doi":"10.1080/10807039.2023.2182130","DOIUrl":"https://doi.org/10.1080/10807039.2023.2182130","url":null,"abstract":"Abstract Water shortages and groundwater depletion are critical issues in the world, leading to unsustainable agricultural production and adverse ecological impacts. Here, the new Multifactor-Quantitative joint Prediction Model (MQPM) is developed to quantitatively predict the Groundwater Storage Anomalies (GWSA), which includes an annual multifactor module and a monthly quantitative module. The correlative coefficients from two modules between simulated GWSA and observed GWSA reach up to 0.98 and 0.87, respectively. Taking Beijing as an example, results show that GWSA trends before South-to-North Water Diversion (SNWD) (2005–2014) and after SNWD (2015–2018) are at a rate of −3.00 × 108 m3/yr and 1.95 × 108 m3/yr, respectively, which reflects the effectiveness of water diversion. Additionally, the predicted results show that GWSA from the multifactor module will increase to 45.97 × 108 m3 by 2028. The quantitative module designs four scenarios under different climate changes and policies, from which the predicted GWSA with values ranging from 28.49 × 108 m3 to 63.06 × 108 m3. For the latter module, the groundwater level will recover to ∼8.9 m up to 2028, combining multiple favorable conditions. Finally, factors consisting of water diversion, climate change, and water-saving policies have a vital influence on groundwater variations, and contributions of these factors to the GWSA account for 46%, 27%, and 27%, respectively.","PeriodicalId":13141,"journal":{"name":"Human and Ecological Risk Assessment: An International Journal","volume":"66 1","pages":"881 - 901"},"PeriodicalIF":0.0,"publicationDate":"2023-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81462091","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-04-10DOI: 10.1080/10807039.2023.2196702
M. Hosseinzadeh, Rasoul Hemmatjo, Zahra Moutab Sahihazar, S. Galvani, M. Hajaghazadeh
Abstract This study assessed the health risks of paint industry workers exposed to benzene, toluene, ethylbenzene, and xylene (BTEX) compounds using a probabilistic approach. Air samples were collected using charcoal tubes according to the NIOSH 1501 method and analyzed by a GC-FID. The EPA risk assessment model was used to assess the lifetime carcinogenic and non-carcinogenic risks posed by BTEX. A sensitivity analysis was performed to clarify the influence of input parameters on the health risks. In the paint production, paint packing, and thinner packing workshops, the concentration of at least two aromatic compounds exceeded the occupational exposure limit. Ethylbenzene posed greater carcinogenic risks than benzene. The individual and total cancer risk of benzene and ethylbenzene exceeded the 1E–4 level, indicating a definite cancer risk in all workshops of the factory. The mean of total non-cancer risk exceeded the standard (hazard index = 1) in all workshops with xylene as the most contributing aromatics in non-cancer risk. Putty production (428.5), thinner packing (340.79), and spray paint packing (148.45) were the workshops with the greatest hazard index. Sensitivity analysis indicated that the concentration of ethylbenzene and xylene contributed the most to cancer (73.0%) and non-cancer (87.8%) risks. These findings can help managers better understand BTEX-related risks faced by paint manufacturing workers and the need to control BTEX contamination to reduce health risks below the standard in paint industry.
{"title":"Probabilistic health risk assessment of occupational exposure to BTEX in a paint manufacturing plant using Monte-Carlo simulation","authors":"M. Hosseinzadeh, Rasoul Hemmatjo, Zahra Moutab Sahihazar, S. Galvani, M. Hajaghazadeh","doi":"10.1080/10807039.2023.2196702","DOIUrl":"https://doi.org/10.1080/10807039.2023.2196702","url":null,"abstract":"Abstract This study assessed the health risks of paint industry workers exposed to benzene, toluene, ethylbenzene, and xylene (BTEX) compounds using a probabilistic approach. Air samples were collected using charcoal tubes according to the NIOSH 1501 method and analyzed by a GC-FID. The EPA risk assessment model was used to assess the lifetime carcinogenic and non-carcinogenic risks posed by BTEX. A sensitivity analysis was performed to clarify the influence of input parameters on the health risks. In the paint production, paint packing, and thinner packing workshops, the concentration of at least two aromatic compounds exceeded the occupational exposure limit. Ethylbenzene posed greater carcinogenic risks than benzene. The individual and total cancer risk of benzene and ethylbenzene exceeded the 1E–4 level, indicating a definite cancer risk in all workshops of the factory. The mean of total non-cancer risk exceeded the standard (hazard index = 1) in all workshops with xylene as the most contributing aromatics in non-cancer risk. Putty production (428.5), thinner packing (340.79), and spray paint packing (148.45) were the workshops with the greatest hazard index. Sensitivity analysis indicated that the concentration of ethylbenzene and xylene contributed the most to cancer (73.0%) and non-cancer (87.8%) risks. These findings can help managers better understand BTEX-related risks faced by paint manufacturing workers and the need to control BTEX contamination to reduce health risks below the standard in paint industry.","PeriodicalId":13141,"journal":{"name":"Human and Ecological Risk Assessment: An International Journal","volume":"42 1","pages":"859 - 880"},"PeriodicalIF":0.0,"publicationDate":"2023-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86132895","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-04-05DOI: 10.1080/10807039.2023.2194998
Giang Pham Thai, Lua Dang Thi, Loan Vu Thi Kieu, Nguyet Nguyen Thi Minh, Thanh Ha Pham Thi, Huy Tong Tran, Jeong Dae Seong, Han Kyungmin
Abstract Ecosystem and aquaculture in estuary areas are sensitive to climate change and severe climatic events. In this study, three environmental monitoring events were carried out on a 1800-ha clam culture area in Giao Thuy district, Nam Dinh province, Vietnam. The first monitoring was carried out in fair weather. The second and 3rd monitorings were conducted two days after the Ma On and Noru storms, respectively. The variation of water and sediment physicochemical variables, zoobenthos and plankton composition and density, and clam pathogen were investigated at five locations. In addition, long-term variations of temperature, rainfall, and sunshine duration in the area were investigated. The results illustrated the increased temperature, rainfall, and sunshine duration tendency. The clam-cultured species and activities had substantially changed. Ma On and Noru negatively impacted water quality by decreasing the water quality index by 39% and 30%, respectively. Storms decreased water salinity, alkalinity, and sediment’s phosphorus, iron, lead. However, they increased water’s nitrite, phosphorus, total suspended solid, phytoplankton, zooplankton density, and sediment’s total nitrogen, cadimium. The total Vibrio spp. density in clam highly fluctuated between the two storm events. The effect of storm varied according to site location. Shallow and domestic wastewater adjacent sites suffered high risks of extreme temperature, salinity variation, and organic pollution.
{"title":"Potential risks of climate change and tropical storms on ecosystem and clams culture activities in Giao Thuy, Nam Dinh, Vietnam","authors":"Giang Pham Thai, Lua Dang Thi, Loan Vu Thi Kieu, Nguyet Nguyen Thi Minh, Thanh Ha Pham Thi, Huy Tong Tran, Jeong Dae Seong, Han Kyungmin","doi":"10.1080/10807039.2023.2194998","DOIUrl":"https://doi.org/10.1080/10807039.2023.2194998","url":null,"abstract":"Abstract Ecosystem and aquaculture in estuary areas are sensitive to climate change and severe climatic events. In this study, three environmental monitoring events were carried out on a 1800-ha clam culture area in Giao Thuy district, Nam Dinh province, Vietnam. The first monitoring was carried out in fair weather. The second and 3rd monitorings were conducted two days after the Ma On and Noru storms, respectively. The variation of water and sediment physicochemical variables, zoobenthos and plankton composition and density, and clam pathogen were investigated at five locations. In addition, long-term variations of temperature, rainfall, and sunshine duration in the area were investigated. The results illustrated the increased temperature, rainfall, and sunshine duration tendency. The clam-cultured species and activities had substantially changed. Ma On and Noru negatively impacted water quality by decreasing the water quality index by 39% and 30%, respectively. Storms decreased water salinity, alkalinity, and sediment’s phosphorus, iron, lead. However, they increased water’s nitrite, phosphorus, total suspended solid, phytoplankton, zooplankton density, and sediment’s total nitrogen, cadimium. The total Vibrio spp. density in clam highly fluctuated between the two storm events. The effect of storm varied according to site location. Shallow and domestic wastewater adjacent sites suffered high risks of extreme temperature, salinity variation, and organic pollution.","PeriodicalId":13141,"journal":{"name":"Human and Ecological Risk Assessment: An International Journal","volume":"82 1","pages":"836 - 858"},"PeriodicalIF":0.0,"publicationDate":"2023-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82283350","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-04-03DOI: 10.1080/10807039.2023.2192292
H. Dao, V. M. Dinh, Anh Nguyen, Quan T. Dang, Hue T. Nguyen, Muu T. Nguyen, Duc Minh Nguyen, Linh H. Duong, Anh Q. Nguyen, Anh T. M. Pham, T. Q. Le, Trang T. T. Hoang, T. T. Dao, P. M. Le, T. N. Nguyen, L. Nguyen, T. T. M. Tran, T. M. Tran, M. Nguyen
Abstract Arsenic (As) in rice has been known as a worldwide human health threat that results originally from the accumulation of As in soil in many rice cultivation regions. This study aims to evaluate As levels in the soil–rice system in the Mekong River delta (MRD) with special focuses on the geographical distribution and the relation to soil physio-chemical properties. It was found that soil As contents varied from 0.3 to 15.9 mg kg−1 ( = 7.22 ± 0.3 mg kg−1), whereas straw As content was about one order of magnitude lower ( = 0.92 ± 0.1 mg kg−1). The content of As in grain varied from “not detectable” to 1115 µg kg−1 ( = 73 ± 19 µg kg−1). Relatively similar geographical distribution patterns were observed for soil As and straw As, meanwhile grain As did not reveal a clear association with straw As and soil As. The accumulation of As in rice (straw and grain) were likely affected by various factors, but the mutual effects of soil As pool and soil properties were the most obvious. The East coastal area of the MRD has been identified as a vulnerable area to As threat. This finding suggests that in addition to the action plans to preserve coastal paddy soils from the threats of sea level rise and salt intrusion, contamination of As should also be considered.
摘要水稻中的砷(As)已被认为是一个全球性的人类健康威胁，其主要原因是砷在许多水稻种植区的土壤中积累。本研究旨在评价湄公河三角洲土壤-水稻系统中砷含量，重点研究其地理分布及其与土壤理化性质的关系。土壤As含量变化范围为0.3 ~ 15.9 mg kg - 1(= 7.22±0.3 mg kg - 1)，而秸秆As含量低约1个数量级(= 0.92±0.1 mg kg - 1)。砷在籽粒中的含量从“不可检测”到1115µg kg - 1(= 73±19µg kg - 1)。土壤砷和秸秆砷的地理分布格局较为相似，而籽粒砷与秸秆砷和土壤砷的相关性不明显。水稻(秸秆和籽粒)中砷的积累可能受到多种因素的影响，但土壤砷库与土壤性质的相互影响最为明显。MRD的东部沿海地区已被确定为易受威胁的地区。这一发现表明，除了保护沿海水稻土免受海平面上升和盐入侵威胁的行动计划外，还应考虑砷的污染。
{"title":"Arsenic in the soil–rice system of the Mekong River delta","authors":"H. Dao, V. M. Dinh, Anh Nguyen, Quan T. Dang, Hue T. Nguyen, Muu T. Nguyen, Duc Minh Nguyen, Linh H. Duong, Anh Q. Nguyen, Anh T. M. Pham, T. Q. Le, Trang T. T. Hoang, T. T. Dao, P. M. Le, T. N. Nguyen, L. Nguyen, T. T. M. Tran, T. M. Tran, M. Nguyen","doi":"10.1080/10807039.2023.2192292","DOIUrl":"https://doi.org/10.1080/10807039.2023.2192292","url":null,"abstract":"Abstract Arsenic (As) in rice has been known as a worldwide human health threat that results originally from the accumulation of As in soil in many rice cultivation regions. This study aims to evaluate As levels in the soil–rice system in the Mekong River delta (MRD) with special focuses on the geographical distribution and the relation to soil physio-chemical properties. It was found that soil As contents varied from 0.3 to 15.9 mg kg−1 ( = 7.22 ± 0.3 mg kg−1), whereas straw As content was about one order of magnitude lower ( = 0.92 ± 0.1 mg kg−1). The content of As in grain varied from “not detectable” to 1115 µg kg−1 ( = 73 ± 19 µg kg−1). Relatively similar geographical distribution patterns were observed for soil As and straw As, meanwhile grain As did not reveal a clear association with straw As and soil As. The accumulation of As in rice (straw and grain) were likely affected by various factors, but the mutual effects of soil As pool and soil properties were the most obvious. The East coastal area of the MRD has been identified as a vulnerable area to As threat. This finding suggests that in addition to the action plans to preserve coastal paddy soils from the threats of sea level rise and salt intrusion, contamination of As should also be considered.","PeriodicalId":13141,"journal":{"name":"Human and Ecological Risk Assessment: An International Journal","volume":"9 1","pages":"801 - 816"},"PeriodicalIF":0.0,"publicationDate":"2023-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83192348","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-27DOI: 10.1080/10807039.2023.2192293
Peng Wang, Qin Zhang, Yan Cai
Abstract Under the sustainability goals, how to promote the integration of port resources and reduce the ecological risks is important for the water transportation industry. Port cities in Jiangsu Province, a major coastal area in China, face a huge risk of resource waste. This paper aims to take Jiangsu as an example, understand the evolution of the spatial structure and the evolution of the water transportation industry, and explore the factors affecting development from the perspective of low-carbon development. Based on ArcGIS and multi-source data, methods such as Standard Deviation Ellipse (SDE) were used to understand the evolution, and the factors influencing the evolution at different stages were explored based on the green total factors such as industrial pollutions. It shows that the scale of the water transportation is expanding, but the industrial upgrading is not realized and has multiple agglomeration cores. The evolution was initially more affected by non-interventional factors such as geographical environment, while later the influence weakened significantly. The disordered development of water transportation industry has been worsening the current inefficient industrial structure and environmental risks. Further integration of industrial structure is needed, and strong administrative means are needed to help tap the unrealized spatial potential of resource integration.
{"title":"Spatial evolution of water transportation industry based on multi-source data: understanding the structural consolidation and integration demand in coastal cities","authors":"Peng Wang, Qin Zhang, Yan Cai","doi":"10.1080/10807039.2023.2192293","DOIUrl":"https://doi.org/10.1080/10807039.2023.2192293","url":null,"abstract":"Abstract Under the sustainability goals, how to promote the integration of port resources and reduce the ecological risks is important for the water transportation industry. Port cities in Jiangsu Province, a major coastal area in China, face a huge risk of resource waste. This paper aims to take Jiangsu as an example, understand the evolution of the spatial structure and the evolution of the water transportation industry, and explore the factors affecting development from the perspective of low-carbon development. Based on ArcGIS and multi-source data, methods such as Standard Deviation Ellipse (SDE) were used to understand the evolution, and the factors influencing the evolution at different stages were explored based on the green total factors such as industrial pollutions. It shows that the scale of the water transportation is expanding, but the industrial upgrading is not realized and has multiple agglomeration cores. The evolution was initially more affected by non-interventional factors such as geographical environment, while later the influence weakened significantly. The disordered development of water transportation industry has been worsening the current inefficient industrial structure and environmental risks. Further integration of industrial structure is needed, and strong administrative means are needed to help tap the unrealized spatial potential of resource integration.","PeriodicalId":13141,"journal":{"name":"Human and Ecological Risk Assessment: An International Journal","volume":"41 1","pages":"817 - 835"},"PeriodicalIF":0.0,"publicationDate":"2023-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90373658","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-23DOI: 10.1080/10807039.2023.2188417
S. Mallik, Saikat Das, Abhigyan Chakraborty, U. Mishra, Swapan Talukdar, Somnath Bera, G. Ramana
Abstract Groundwater contamination caused by elevated nitrate levels and its associated health effects is a serious global concern. The U.S. Environmental Protection Agency has developed a method for assessing potential human health risks from groundwater contamination that involves extensive groundwater sampling and analysis. However, this approach can be labor intensive and stand as a constraint to the robustness of the traditional approach. Here in machine learning (ML) could be alternative approaches to bridging the contemporary challenges. Machine learning models (ML) such as deep neural networks (DNN), gradient boosting machines (GBM), random forests (RF) and generalized linear models (GLM) can provide alternative solutions to overcome these limitations. In this study, the effectiveness of Hybrid Monte Carlo Machine Learning (MC-ML) models was evaluated by predicting health risks using hazard quotients. A total of 32 groundwater samples were collected and analyzed for nitrate and physical properties during the pre- and post-monsoon seasons. The results showed that the groundwater was severely contaminated by elevated nitrate concentrations, leading to high hazard quotient values. The prediction model results and validation using error and performance metrics showed that the Hybrid MC-DNN model outperformed the other models in both the training and testing phases. These results suggest that this surrogate approach could be a promising alternative to traditional health risk assessment methods.
{"title":"Prediction of non-carcinogenic health risk using Hybrid Monte Carlo-machine learning approach","authors":"S. Mallik, Saikat Das, Abhigyan Chakraborty, U. Mishra, Swapan Talukdar, Somnath Bera, G. Ramana","doi":"10.1080/10807039.2023.2188417","DOIUrl":"https://doi.org/10.1080/10807039.2023.2188417","url":null,"abstract":"Abstract Groundwater contamination caused by elevated nitrate levels and its associated health effects is a serious global concern. The U.S. Environmental Protection Agency has developed a method for assessing potential human health risks from groundwater contamination that involves extensive groundwater sampling and analysis. However, this approach can be labor intensive and stand as a constraint to the robustness of the traditional approach. Here in machine learning (ML) could be alternative approaches to bridging the contemporary challenges. Machine learning models (ML) such as deep neural networks (DNN), gradient boosting machines (GBM), random forests (RF) and generalized linear models (GLM) can provide alternative solutions to overcome these limitations. In this study, the effectiveness of Hybrid Monte Carlo Machine Learning (MC-ML) models was evaluated by predicting health risks using hazard quotients. A total of 32 groundwater samples were collected and analyzed for nitrate and physical properties during the pre- and post-monsoon seasons. The results showed that the groundwater was severely contaminated by elevated nitrate concentrations, leading to high hazard quotient values. The prediction model results and validation using error and performance metrics showed that the Hybrid MC-DNN model outperformed the other models in both the training and testing phases. These results suggest that this surrogate approach could be a promising alternative to traditional health risk assessment methods.","PeriodicalId":13141,"journal":{"name":"Human and Ecological Risk Assessment: An International Journal","volume":"16 1","pages":"777 - 800"},"PeriodicalIF":0.0,"publicationDate":"2023-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86551880","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-02-15DOI: 10.1080/10807039.2023.2178879
P. Kumari, A. Misra
Abstract High fluoride intake via groundwater is a very serious problem for human health, especially in children. The present study focused on the health risk in children between 5–15 years due to higher consumption of fluoride in water used for potable purposes. A total of 195 samples of groundwater were analyzed for water parameters like pH, EC, TDS, fluoride, etc. On the basis of the primary data on the quality of drinking water, non-carcinogenic health risks of excessive fluoride intake in children were evaluated. Findings showed that the concentration of fluoride in Munger lies from 0.029 to 12 (mg/l) and 13.8% of total samples contain fluoride exceeding the allowable limit (1.5 mg/l). Hazard quotient value through ingestion of drinking water with high-level fluoride content varies from 0.625 to 8.571 whereas via dermal exposure hazard, quotient value lies in between 0.001 to 0.012. Therefore, the total hazard quotient obtained in Munger varied from 0.626 to 8.58. This indicates that children in Munger are highly vulnerable to non-carcinogenic health risks via prolonged fluoride intake mainly through the drinking water pathway. The outcome of the sensitivity analysis revealed that the concentration of fluoride is the most influential parameter in non-carcinogenic health risk.
{"title":"Potential health risk assessment and distribution of fluoride in groundwater of Munger, Bihar India: a case study","authors":"P. Kumari, A. Misra","doi":"10.1080/10807039.2023.2178879","DOIUrl":"https://doi.org/10.1080/10807039.2023.2178879","url":null,"abstract":"Abstract High fluoride intake via groundwater is a very serious problem for human health, especially in children. The present study focused on the health risk in children between 5–15 years due to higher consumption of fluoride in water used for potable purposes. A total of 195 samples of groundwater were analyzed for water parameters like pH, EC, TDS, fluoride, etc. On the basis of the primary data on the quality of drinking water, non-carcinogenic health risks of excessive fluoride intake in children were evaluated. Findings showed that the concentration of fluoride in Munger lies from 0.029 to 12 (mg/l) and 13.8% of total samples contain fluoride exceeding the allowable limit (1.5 mg/l). Hazard quotient value through ingestion of drinking water with high-level fluoride content varies from 0.625 to 8.571 whereas via dermal exposure hazard, quotient value lies in between 0.001 to 0.012. Therefore, the total hazard quotient obtained in Munger varied from 0.626 to 8.58. This indicates that children in Munger are highly vulnerable to non-carcinogenic health risks via prolonged fluoride intake mainly through the drinking water pathway. The outcome of the sensitivity analysis revealed that the concentration of fluoride is the most influential parameter in non-carcinogenic health risk.","PeriodicalId":13141,"journal":{"name":"Human and Ecological Risk Assessment: An International Journal","volume":"21 1","pages":"757 - 776"},"PeriodicalIF":0.0,"publicationDate":"2023-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74174642","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-02-07DOI: 10.1080/10807039.2022.2092835
Jamil Ahmed, L. Wong, N. Channa, Waqas Ahmed, Y. P. Chua, Muhammad Zakir Shaikh
Abstract Arsenic exposure through drinking water is a serious public health concern in the southern province of Pakistan. Little information on As exposure to children at school settings is available in Pakistan. The current study aimed to assess arsenic contamination through drinking water sources and estimate its health risk to the children, the potentially malnourished Pakistan population. We used risk assessment models to estimate the hazard quotient index and lifetime cancer risk. Spatial data analysis methods were used to investigate the spatial pattern of As contamination and its relationship with the area's hydrogeology. Across the 423 sampled schools, the drinking water exceeded the WHO permissible limits (19.6% for arsenic and 15% for iron). The arsenic's average incremental lifetime cancer risk (ILCR) exceeded the USEPA permissible limit. The arsenic hotspots were mainly located in the central districts. The present study's findings elaborate that the reduction is the controlling phenomenon in the lower Indus basin in the active flood plains, which is the primary source of fresh groundwater in Sindh and pH-induced dissolution is the second phenomenon observed only in the irrigated area, especially at the boundary of the hotspots. These findings are helpful to inform policymakers on measures to ensure prior treatment of As in the drinking water for the schools in areas adjacent to the riverbank.
{"title":"Arsenic contamination and potential health risk to primary school children through drinking water sources","authors":"Jamil Ahmed, L. Wong, N. Channa, Waqas Ahmed, Y. P. Chua, Muhammad Zakir Shaikh","doi":"10.1080/10807039.2022.2092835","DOIUrl":"https://doi.org/10.1080/10807039.2022.2092835","url":null,"abstract":"Abstract Arsenic exposure through drinking water is a serious public health concern in the southern province of Pakistan. Little information on As exposure to children at school settings is available in Pakistan. The current study aimed to assess arsenic contamination through drinking water sources and estimate its health risk to the children, the potentially malnourished Pakistan population. We used risk assessment models to estimate the hazard quotient index and lifetime cancer risk. Spatial data analysis methods were used to investigate the spatial pattern of As contamination and its relationship with the area's hydrogeology. Across the 423 sampled schools, the drinking water exceeded the WHO permissible limits (19.6% for arsenic and 15% for iron). The arsenic's average incremental lifetime cancer risk (ILCR) exceeded the USEPA permissible limit. The arsenic hotspots were mainly located in the central districts. The present study's findings elaborate that the reduction is the controlling phenomenon in the lower Indus basin in the active flood plains, which is the primary source of fresh groundwater in Sindh and pH-induced dissolution is the second phenomenon observed only in the irrigated area, especially at the boundary of the hotspots. These findings are helpful to inform policymakers on measures to ensure prior treatment of As in the drinking water for the schools in areas adjacent to the riverbank.","PeriodicalId":13141,"journal":{"name":"Human and Ecological Risk Assessment: An International Journal","volume":"1 1","pages":"369 - 389"},"PeriodicalIF":0.0,"publicationDate":"2023-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87612690","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-30DOI: 10.1080/10807039.2023.2169898
Y. O. Khaniabadi, P. Bahrami, Pouran Moulaei Birgani, R. Rashidi, H. R. Naqvi, K. Anbari
Abstract The aims of this study were to i) assess the relationship between COVID-19 cases with PM10 concentration and ii) investigation premature deaths due to cardiovascular (M-CVD) and respiratory (M-RD) diseases in three classification levels (PM10<50µg m−3 in normal days, 50–200 µg m−3 in dusty days, and >200 µg m−3 in MED storm), by using daily averages of PM10 concentrations. The number of M-CVD and M-RD were estimated by concentration-response model, per 105 people during 2017 to 2021. The results showed that 187, 183, 163, 215, and 206 days were observed with the PM10 concentrations lower than 50 µg m−3 during 2017 to 2021, and 178, 180, 200, 150, and 149 days were subtotal with exceeding PM10 from the WHO guideline (50 µg m−3), respectively. A positive correlation (r2=0.33, p < 0.05) was found to be between the number of COVID-19 cases and PM10 mean concentrations (r = 0.589, p = 0.046). Our findings showed that the highest M-CVD and M-RD were among exposed people at dusty days (50 < PM10≤ 200 μg m−3) in 2019. The total M-CVD and M-RD from 2017 to 2021 were 11.78 and 12.2, 18.25 and 17.4, 22.29 and 23.78, 10.33 and 7.6, 10.37 and 9.95 per 105 people, respectively which 31.48% of health effects were related to PM10 concentrations more than 200 μg m−3.
{"title":"Risk assessment of exposure to the Middle Eastern dust storms in Iran","authors":"Y. O. Khaniabadi, P. Bahrami, Pouran Moulaei Birgani, R. Rashidi, H. R. Naqvi, K. Anbari","doi":"10.1080/10807039.2023.2169898","DOIUrl":"https://doi.org/10.1080/10807039.2023.2169898","url":null,"abstract":"Abstract The aims of this study were to i) assess the relationship between COVID-19 cases with PM10 concentration and ii) investigation premature deaths due to cardiovascular (M-CVD) and respiratory (M-RD) diseases in three classification levels (PM10<50µg m−3 in normal days, 50–200 µg m−3 in dusty days, and >200 µg m−3 in MED storm), by using daily averages of PM10 concentrations. The number of M-CVD and M-RD were estimated by concentration-response model, per 105 people during 2017 to 2021. The results showed that 187, 183, 163, 215, and 206 days were observed with the PM10 concentrations lower than 50 µg m−3 during 2017 to 2021, and 178, 180, 200, 150, and 149 days were subtotal with exceeding PM10 from the WHO guideline (50 µg m−3), respectively. A positive correlation (r2=0.33, p < 0.05) was found to be between the number of COVID-19 cases and PM10 mean concentrations (r = 0.589, p = 0.046). Our findings showed that the highest M-CVD and M-RD were among exposed people at dusty days (50 < PM10≤ 200 μg m−3) in 2019. The total M-CVD and M-RD from 2017 to 2021 were 11.78 and 12.2, 18.25 and 17.4, 22.29 and 23.78, 10.33 and 7.6, 10.37 and 9.95 per 105 people, respectively which 31.48% of health effects were related to PM10 concentrations more than 200 μg m−3.","PeriodicalId":13141,"journal":{"name":"Human and Ecological Risk Assessment: An International Journal","volume":"9 1","pages":"743 - 756"},"PeriodicalIF":0.0,"publicationDate":"2023-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89129513","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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