Sushant K. Singh

Health Risk Assessment Due to Groundwater Arsenic Contamination: Children Are at High Risk

ABSTRACT Health risk assessment due to groundwater As contamination was conducted in two As-prone panchayats, Rampur Diara (RD) and Haldichapra (HC) of the Maner block of the Patna district, Bihar (India). All 100% of the water samples surveyed were found to be contaminated with As with a mean value of 52 μg/L (n = 10) in RD and 231 μg/L (n = 10) in HC, both exceeding the World Health Organization (WHO) guideline of 10 μg/L and the Bureau of Indian Standards (BIS) standard of 50 μg/L, respectively. The average calculated per capita consumption of As through drinking water in RD ranged from 120 μg/day for 5–10-year-old children to 320 μg/day for adults older than 41 years, while in HC the average calculated As through consumption ranged from 580 μg/day for 5–10-year-old children to 1470 μg/day for adults older than 41 years. Hazard quotients were calculated to be between 12.1 to 41.6 for the RD population and 58.3 to 192.5 for the HC population, both exceeding the typical toxic risk index 1. In addition, cancer risk of 19 per 1000 was found for RD children and 87 per 1000 for HC children. Visible symptoms of Arsenicosis were also observed in the area.

Mapping composite vulnerability to groundwater arsenic contamination: an analytical framework and a case study in India

Groundwater arsenic (As) contamination affects millions of people in South Asia. In this paper, we propose a composite vulnerability framework to identify, for mitigation, the population who are at the highest risk of suffering adverse impacts from exposure to As and warrant mitigation measures. Bihar, India, which was selected for the case study, has large areas with As concentrations far exceeding the upper limits of acceptable level of As in drinking water. Drawing on the existing social science research, we identify a host of socioeconomic and demographic variables, in addition to As concentration in groundwater, which compound a community’s vulnerability to the adverse effects of As. The result is a “composite vulnerability index,” which consists of biophysical, socioeconomic, and demographic factors that collectively determine a community’s overall vulnerability to As. Additionally, using geographic information systems (GIS), we represent the composite vulnerability index visually through a set of maps, which highlight the interaction between different community characteristics to generate unique community vulnerability profiles. In summary, this paper outlines a systematic approach to understanding vulnerability to groundwater As, as both social and natural construct, which can be applied to different geographic areas, and to improving decision making and planning pertaining to diverse environmental problems.

Conceptual framework of a cloud-based decision support system for arsenic health risk assessment

Because of the lack of sustainable arsenic mitigation technologies and awareness of the possible health risks due to arsenic consumption, nearly 200 million people are potentially exposed to elevated levels of arsenic through drinking water in over 100 countries. Cloud computing (CC) could help bridge the gaps between wireless communication and data generated through environmental and/or health interventions. This study offers a conceptual framework of a cloud-based decision support system for arsenic health risk assessment (CC-AHRA). It also explains how the CC-AHRA could help assist exposed communities in assessing cancer risk due to arsenic exposure through drinking water. The study also discusses how the CC-AHRA can help water management authorities, professionals, researchers, and private enterprises in making informed decisions toward reducing the likely health risks due to arsenic consumption.

Evaluating Hydrogeological and Topographic Controls on Groundwater Arsenic Contamination in the Middle-Ganga Plain in India: Towards Developing Sustainable Arsenic Mitigation Models

We investigated the spatial distribution and severity of groundwater arsenic contamination in three previously un-studied villages located near the confluence of the Rivers Ganges and Sone, within the Maner block of Patna district in the Bihar State, India. We also gathered information on the demographic, socioeconomic and health issues of local residents in order to identify at-risk populations due to the exposure to elevated concentrations of arsenic. Arsenic concentrations were measured in 157 drinking water sources, which were tested using field-tests kits. Spatial patterns in arsenic distribution were compared with local physiographic and hydrogeologic parameters. Arsenic levels exceeding the WHO and the BIS standards (10 μg/L and 50 μg/L respectively) were found in all three villages, with a maximum of 300 μg/L. The shallow aquifers (≤50 m below ground surface) and older hand pumps were found to be arsenic contaminated. The deeper aquifers (>50 m) exhibited arsenic levels within permissible limits. Elevated arsenic levels are observed close to the River Ganges. However, a moderate (r = 0.240, p = 0.031) positive correlation with the surface water flow direction indicates that arsenic migrates from south to north and from west to east in the study area. This suggests that River Sone alluvium is a potential source of arsenic contamination in Bihar.

Groundwater Arsenic Contamination in the Ganga River Basin: A Future Health Danger

This study highlights the severity of arsenic contamination in the Ganga River basin (GRB), which encompasses significant geographic portions of India, Bangladesh, Nepal, and Tibet. The entire GRB experiences elevated levels of arsenic in the groundwater (up to 4730 µg/L), irrigation water (~1000 µg/L), and in food materials (up to 3947 µg/kg), all exceeding the World Health Organization’s standards for drinking water, the United Nations Food and Agricultural Organization’s standard for irrigation water (100 µg/L), and the Chinese Ministry of Health’s standard for food in South Asia (0.15 mg/kg), respectively. Several individuals demonstrated dermal, neurological, reproductive, cognitive, and cancerous effects; many children have been diagnosed with a range of arsenicosis symptoms, and numerous arsenic-induced deaths of youthful victims are reported in the GRB. Victims of arsenic exposure face critical social challenges in the form of social isolation and hatred by their respective communities. Reluctance to establish arsenic standards and unsustainable arsenic mitigation programs have aggravated the arsenic calamity in the GRB and put millions of lives in danger. This alarming situation resembles a ticking time bomb. We feel that after 29 years of arsenic research in the GRB, we have seen the tip of the iceberg with respect to the actual magnitude of the catastrophe; thus, a reduced arsenic standard for drinking water, testing all available drinking water sources, and sustainable and cost-effective arsenic mitigation programs that include the participation of the people are urgently needed.

Evaluating two freely available geocoding tools for geographical inconsistencies and geocoding errors

BackgroundGeocoding is highly prone to error for various reasons. This paper examines the geographical inconsistencies associated with geocoding errors seen when using two freely available geocoding tools, Google Sheets and ggmap.MethodsTwo hundred restaurants, all recipients of California’s Center of Excellence award, were selected for the analysis. The geocoded addresses were plotted on maps using QGIS, Google Maps, OpenStreetMap (OSM), and Google Earth for visualization, comparison, and validation. A stepwise method of analyzing the geographical inconsistencies is provided that can be adapted for any locational analytics.Results and discussionBoth Google Sheets and ggmap were able to successfully geocode all 200 addresses, but ggmap incorrectly geocoded eight addresses as being more than 2,000 miles from their actual location. Addresses containing the ampersand character, &, caused ggmap to incorrectly geocode their location. After replacing the ampersand with the word and, ggmap was able to correctly geocode those addresses. The corrected locations plotted on Google Maps and OSM were similar, and they exactly matched the actual locations when plotted on Google Earth.ConclusionsBoth Google Sheets and ggmap are equally capable of geocoding physical locations, but R users are advised that addresses for geocoding must be free of the ampersand character if correct results are to be obtained. In addition, geocoded outputs should be plotted on a map using QGIS, ArcGIS, Google Maps, OSM, R, or any other such mapping tools for visualization and validation. This will ensure a high-quality geospatial analysis of places or events when locational information is vital for decision-making.