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Arsenic in drinking water obtained from wells causes massive adverse health outcomes, including premature deaths from cancers and cardiovascular disease, in many parts of the world and particularly in the Indian subcontinent.
But in the absence of testing on the tens of millions of wells being used for drinking water, the team from Manchester, Patna and Zurich got together to create prediction models by using data from the wells that have been tested in India.
“The outcome of this open-access joint Indo-UK study will help create greater awareness of hazardous arsenic distribution in wells amongst the population,” said Biswajit Chakraborty, a senior scientist at the National Institute of Hydrology in India and co-author of the study published in the ‘International Journal for Environmental Research and Public Health.’
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But what is new, and described as particularly concerning, is that the model also finds an elevated probability of high arsenic well-waters in other Indian areas, where previously arsenic hazard was generally not considered to be a major concern. These areas include parts of south-west and central India and are mostly areas underlain by sediments and sedimentary rocks.
Researchers have in the past constructed similar prediction models for individual countries, on a regional and global scale, but there has been no detailed model focused solely on India published so far.
The international collaboration to address this gap was largely built on a joint India-UK Water Quality project named FAR-GANGA.
“The model outputs are a good example of the benefits of international collaboration. The work would have been much more difficult to achieve without the joint India-UK Water Quality programme project, FAR-GANGA,” said Professor David Polya, a researcher at the University of Manchester and the UK lead and co-author of the study.
Their work suggests follow up to help better define specific areas in which action is required to reduce adverse public health outcomes from drinking high arsenic well waters. They also highlight the importance of systematic testing of hazards, not just in known high hazard areas, but also through random sampling of all wells used for drinking water.
The lead author of the study was Dr Joel Podgorski, a senior scientist at the Swiss Federal Institute of Aquatic Science and Technology (Eawag), who conducted much of the study whilst a Postdoctoral Impact Research Fellow at the University of Manchester.
“This study demonstrates how the increasing availability of data can be used to better understand the scope of public health crises,” said Dr Podgorski.
The University of Manchester pointed out that there are known and important limitations to this kind of modelling approach. The output model can only be as good as the data upon which it is based; the model is based largely on satellite-derived data and so is less reliable for deeper wells; the model does not consider variations of well water arsenic with time. Lastly, the arsenic content of well-waters is known to change massively over very short distances, so for a particular well, the model will never be a better substitute for a good chemical analysis of the water produced from that well.
“Nevertheless, the model does suggest new areas in India in which follow-up sampling of well water and analysis for arsenic should be done; this will help save lives in those areas,” it notes.
Ruohan Wu, a postgraduate researcher at the University of Manchester, was also part of the research team, which the university said is symbolic of its strong links with business, public authorities and students in India.