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Warning over ‘dirty secret’ of toxic chemicals on farmers fields
Environment correspondent
Getty ImagesSuccessive governments have failed to deal with the threat posed by spreading sewage sludge containing toxic chemicals on farmers’ fields, a former chair of the Environment Agency has told the BBC.
About 3.5 million tonnes of sludge – the solid waste produced from human sewage at treatment plants – is put on fields every year as cheap fertiliser.
But campaigners have long warned about a lack of regulation and that sludge could be contaminated with cancer-linked chemicals, microplastics, and other industrial pollutants.
Emma Howard Boyd, who led the EA from 2016 to 2022, says the agency had been aware since 2017 that the sludge can be contaminated with substances, including ‘forever chemicals’.
“Forever chemicals” or PFAS are a group of synthetic chemicals which come from things like non-stick saucepans. They don’t degrade quickly in nature and have been linked to cancer.
Documents seen by BBC News suggest the water industry is now increasingly concerned that farmers could stop accepting the sludge to spread and that water firms have been lobbying regulators and making contingency plans in case rules change.
Ms Howard Boyd says efforts to update rules, which date back to 1989, to include new contaminants were “continually frustrated by the lack of ministerial appetite to deal with this issue.” In a public letter signed by more than 20 others she called on the current Environment Minister Steve Reed, to act now.
The Department for Environment Food and Rural Affairs (Defra) told the BBC regulations around sludge spreading are being looked at. The water companies trade body Water UK told the BBC they were aware of the concerns but that no legal standards for contaminants had been set by the government.
BBC/Jonah FisherUnlike the cleaned water that is discharged from wastewater treatment plants, the sewage sludge, or biosolid as the industry calls it, is considered “exempted waste”.
That means the treatment focuses mainly on killing bacteria and testing for heavy metals in the sludge.
There is no routine testing for chemicals, including “forever chemicals”, which have been developed over the last three decades and are getting into the sewage network from both from domestic and industrial users.
“I think the big concern is because these substances (forever chemicals) are so persistent they’ll stay around in the soil for hundreds, if not thousands of years,” says Alistair Boxall, professor of environmental science at York University.
“It may be in 10 years’ time that we start understanding that these molecules are causing harm,” he said. “Then we’re going to be in a bit of a mess, because we’ll be in a situation where we’ll have soils in the UK that will have residues of these molecules in them, and at the moment we have no way of cleaning that up.”
In 2022, the US state of Maine became the first state to ban the spreading of sludge contaminated with “forever chemicals” after high levels were found in water, soil and crops.
Reports and emails shown to the BBC by Greenpeace’s Unearthed investigation unit and obtained using Freedom of Information Act requests, reveal the water industry is acutely aware that attitudes are changing and is both lobbying government and making contingency plans.
The companies are concerned on two fronts: that general rules regarding the spreading of sludge on land (so called Farming Rules for Water) may soon be tightened due to fears that it’s polluting watercourses and that farmers’ concerns about the chemicals in the sludge might make them unwilling to put it on their fields.
The water industry has already commissioned reports looking at what might happen if the spreading is restricted.
One of them predicts that the “most likely” scenario is a shortfall of about three million hectares in land needed to spread the sludge. The water industry says that would lead to them either incinerating it or putting it into landfill. Both options would bring extra costs that would be passed on to billpayers.
“This investigation is yet more proof that we can’t trust the privatised water companies to deal with waste responsibly,” Reshima Sharma from Greenpeace said.
“So long as they can get away with it, they will just pass any problems on to our countryside and pocket the money they should be investing in solutions.”
Getty ImagesIn 2017 a report commissioned by the Environment Agency found that sludge contained potentially harmful substances, including microplastics and “forever chemicals”, at levels that “may present a risk to human health” and may create soil that is “unsuitable for agriculture”.
It said that “perhaps the biggest risk to the landbank” is from the spreading of physical contaminants such as microplastics into agricultural soil. The report also said it had heard evidence from EA staff indicating that some companies may be using wastewater treatment plants to “mask disposal of individual high risk waste streams not suitable for land spreading”.
“EA colleagues were continually frustrated by the lack of ministerial appetite to deal with this issue,” Ms Howard Boyd, who was chair of the regulator at the time, told the BBC in an email.
“EA proposals since 2020 to reform the regulations were treated with a lack of urgency, hampered by delays in passing requests up to the relevant ministers for decision-making, and a consistent failure by successive secretaries of state to take the matter seriously.”
The letter Ms Howard Boyd has signed jointly signed was organised by campaign group Fighting Dirty. It calls the contents of the sewage sludge a “dirty secret” and demands that Environment Secretary Steve Reed take action.
BBC/Jonah FisherSewage sludge is cheaper than other fertilisers, and can sometimes be free, though farmers may have to spread it themselves.
Julie Lewis-Thompson tells me it has “the smell of death”.
“It lingers in the air for somewhere around two to three weeks,” she tells me when I go to visit in her home on Dartmoor in the south-west of England.
She’s gathered together a group of neighbours who’ve all had direct experience of sewage sludge being spread near their properties. Before we start recording there’s a long discussion about whether they should speak out for fear of upsetting nearby farmers and the contractors who spread the sludge, who are often local.
Many of their concerns are about the smell and about potential contamination of their water sources. One young woman leaves in tears saying it had made her sick.
“The fact it’s spread for free ought to raise a few eyebrows,” Richard Smallwood, a local beef and sheep farmer who doesn’t use sewage sludge, tells me.
“If we’re starting to produce food on grassland and arable land which is filled up to the ear holes with PFAS compounds and nano and micro-plastics that find their way into the food chain I think my job’s over before I begin.”
BBC/Kevin ChurchWith the alternatives to sewage sludge disposal costly, there’s broad agreement that the recycling of sludge into fertiliser has to be made to work.
“In principle, I think using properly treated human sewage to spread on the land, put it back into the ground for growing food in the UK, that’s the right thing to do,” Hugh Fearnley-Whittingstall, the cook, writer and broadcaster, tells me at his small farm and café in east Devon. He’s also signed the protest letter to the environment minister.
“We know it’s happening. Our farmers are rightly worried. We’ve got to take action. Government’s got to take action,” Mr Fearnley-Whittingstall says.
“That means regulations are not voluntary regulations or guidelines, [they should be] legally enforceable regulations that stop these pollutants getting into the sewage and onto our land.”
Despite the concerns there are still plenty of farmers who see the sludge as a cheap way to fertilise their fields.
Will Oliver is on the National Farmers Union Crops Board. He says he applies about 800 tonnes of sewage sludge every year to fields where he grows maize destined for animal feed.
The water company provides the sludge for free and Mr Oliver says he’s careful how much he uses and trusts the company to make sure it doesn’t have chemical contamination.
“If we can be sensible with how it’s used and spread on the land, it can be positive for farmers and for the water companies,” he says.
“I’m doing it because it’s adding value. It’s improving our organic matter. It’s benefitting the crop that I’m growing, and it’s reducing my spend on bagged fertilisers.”
The Department for the Environment, Food and Rural Affairs did not contest anything the former chair of the EA Ms Howard Boyd told the BBC.
“We need to see the safe and sustainable use of sludge in agriculture to help clean up our waterways,” a spokesperson said.
“The Independent Water Commission will explore a range of issues, including the regulatory framework for sludge spreading, and we continue to work closely with the Environment Agency, water companies and farmers in this area.”
Water UK represents the water companies of England and Wales, and a spokesperson said: “Although there are some concerns that some bioresources may contain contaminants, such as microplastics and forever chemicals (PFAS), there are no legal standards for them and, in some cases, no agreed assessment techniques.”
“Any standards and techniques are a matter for the government and the regulator and need to be based on firm evidence and detailed scientific research.”
A study published on June 23 in collaboration with UT and Yale researchers developed an artificial intelligence tool capable of performing and analyzing the heart using echocardiography.
The app, PanEcho, can analyze echocardiograms, or pictures of the heart, using ultrasounds. The tool was developed and trained on nearly one million echocardiographic videos. It can perform 39 echocardiographic tasks and accurately detect conditions such as systolic dysfunction and severe aortic stenosis.
“Our teammates helped identify a total of 39 key measurements and labels that are part of a complete echocardiographic report — basically what a cardiologist would be expected to report on when they’re interpreting an exam,” said Gregory Holste, an author of the study and a doctoral candidate in the Department of Electrical and Computer Engineering. “We train the model to predict those 39 labels. Once that model is trained, you need to evaluate how it performs across those 39 tasks, and we do that through this robust multi site validation.”
Holste said out of the functions PanEcho has, one of the most impressive is its ability to measure left ventricular ejection fraction, or the proportion of blood the left ventricle of the heart pumps out, far more accurately than human experts. Additionally, Holste said PanEcho can analyze the heart as a whole, while humans are limited to looking at the heart from one view at a time.
“What is most unique about PanEcho is that it can do this by synthesizing information across all available views, not just curated single ones,” Holste said. “PanEcho integrates information from the entire exam — from multiple views of the heart to make a more informed, holistic decision about measurements like ejection fraction.”
PanEcho is available for open-source use to allow researchers to use and experiment with the tool for future studies. Holste said the team has already received emails from people trying to “fine-tune” the application for different uses.
“We know that other researchers are working on adapting PanEcho to work on pediatric scans, and this is not something that PanEcho was trained to do out of the box,” Holste said. “But, because it has seen so much data, it can fine-tune and adapt to that domain very quickly. (There are) very exciting possibilities for future research.”
Google announced two new artificial intelligence initiatives on July 7, 2025, designed to support mental health organizations in scaling evidence-based interventions and advancing research into anxiety, depression, and psychosis treatments.
The first initiative involves a comprehensive field guide developed in partnership with Grand Challenges Canada and McKinsey Health Institute. According to the announcement from Dr. Megan Jones Bell, Clinical Director for Consumer and Mental Health at Google, “This guide offers foundational concepts, use cases and considerations for using AI responsibly in mental health treatment, including for enhancing clinician training, personalizing support, streamlining workflows and improving data collection.”
The field guide addresses the global shortage of mental health providers, particularly in low- and middle-income countries. According to analysis from the McKinsey Health Institute cited in the document, “closing this gap could result in more years of life for people around the world, as well as significant economic gains.”
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Summary
Who: Google for Health, Google DeepMind, Grand Challenges Canada, McKinsey Health Institute, and Wellcome Trust, targeting mental health organizations and task-sharing programs globally.
What: Two AI initiatives including a practical field guide for scaling mental health interventions and a multi-year research investment for developing new treatments for anxiety, depression, and psychosis.
When: Announced July 7, 2025, with ongoing development and research partnerships extending multiple years.
Where: Global implementation with focus on low- and middle-income countries where mental health provider shortages are most acute.
Why: Address the global shortage of mental health providers and democratize access to quality, evidence-based mental health support through AI-powered scaling solutions and advanced research.
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The 73-page guide outlines nine specific AI use cases for mental health task-sharing programs, including applicant screening tools, adaptive training interfaces, real-time guidance companions, and provider-client matching systems. These tools aim to address challenges such as supervisor shortages, inconsistent feedback, and protocol drift that limit the effectiveness of current mental health programs.
Task-sharing models allow trained non-mental health professionals to deliver evidence-based mental health services, expanding access in underserved communities. The guide demonstrates how AI can standardize training, reduce administrative burdens, and maintain quality while scaling these programs.
According to the field guide documentation, “By standardizing training and avoiding the need for a human to be involved at every phase of the process, AI can help mental health task-sharing programs effectively scale evidence-based interventions throughout communities, maintaining a high standard of psychological support.”
The second initiative represents a multi-year investment from Google for Health and Google DeepMind in partnership with Wellcome Trust. The funding, which includes research grant funding from the Wellcome Trust, will support research projects developing more precise, objective, and personalized measurement methods for anxiety, depression, and psychosis conditions.
The research partnership aims to explore new therapeutic interventions, potentially including novel medications. This represents an expansion beyond current AI applications into fundamental research for mental health treatment development.
The field guide acknowledges that “the application of AI in task-sharing models is new and only a few pilots have been conducted.” Many of the outlined use cases remain theoretical and require real-world validation across different cultural contexts and healthcare systems.
For the marketing community, these developments signal growing regulatory attention to AI applications in healthcare advertising. Recent California guidance on AI healthcare supervision and Google’s new certification requirements for pharmaceutical advertising demonstrate increased scrutiny of AI-powered health technologies.
The field guide emphasizes the importance of regulatory compliance for AI mental health tools. Several proposed use cases, including triage facilitators and provider-client matching systems, could face classification as medical devices requiring regulatory oversight from authorities like the FDA or EU Medical Device Regulation.
Organizations considering these AI tools must evaluate technical infrastructure requirements, including cloud versus edge computing approaches, data privacy compliance, and integration with existing healthcare systems. The guide recommends starting with pilot programs and establishing governance committees before full-scale implementation.
Technical implementation challenges include model selection between proprietary and open-source systems, data preparation costs ranging from $10,000 to $90,000, and ongoing maintenance expenses of 10 to 30 percent of initial development costs annually.
The initiatives build on growing evidence that task-sharing approaches can improve clinical outcomes while reducing costs. Research cited in the guide shows that mental health task-sharing programs are cost-effective and can increase the number of people treated while reducing mental health symptoms, particularly in low-resource settings.
Real-world implementations highlighted in the guide include The Trevor Project’s AI-powered crisis counselor training bot, which trained more than 1,000 crisis counselors in approximately one year, and Partnership to End Addiction’s embedded AI simulations for peer coach training.
These organizations report improved training efficiency and enhanced quality of coach conversations through AI implementation, suggesting practical benefits for established mental health programs.
The field guide warns that successful AI adoption requires comprehensive planning across technical, ethical, governance, and sustainability dimensions. Organizations must establish clear policies for responsible AI use, conduct risk assessments, and maintain human oversight throughout implementation.
According to the World Health Organization principles referenced in the guide, responsible AI in healthcare must protect autonomy, promote human well-being, ensure transparency, foster responsibility and accountability, ensure inclusiveness, and promote responsive and sustainable development.
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Timeline
- July 7, 2025: Google announces two AI initiatives for mental health research and treatment
- January 2025: California issues guidance requiring physician supervision of healthcare AI systems
- May 2024: FDA reports 981 AI and machine learning software devices authorized for medical use
- Development ongoing: Field guide created through 10+ discovery interviews, expert summit with 20+ specialists, 5+ real-life case studies, and review of 100+ peer-reviewed articles
AI Research
New Research Shows Language Choice Alone Can Guide AI Output Toward Eastern or Western Cultural Outlooks
A new study shows that the language used to prompt AI chatbots can steer them toward different cultural mindsets, even when the question stays the same. Researchers at MIT and Tongji University found that large language models like OpenAI’s GPT and China’s ERNIE change their tone and reasoning depending on whether they’re responding in English or Chinese.
The results indicate that these systems translate language while also reflecting cultural patterns. These patterns appear in how the models provide advice, interpret logic, and handle questions related to social behavior.
Same Question, Different Outlook
The team tested both GPT and ERNIE by running identical tasks in English and Chinese. Across dozens of prompts, they found that when GPT answered in Chinese, it leaned more toward community-driven values and context-based reasoning. In English, its responses tilted toward individualism and sharper logic.
Take social orientation, for instance. In Chinese, GPT was more likely to favor group loyalty and shared goals. In English, it shifted toward personal independence and self-expression. These patterns matched well-documented cultural divides between East and West.
When it came to reasoning, the shift continued. The Chinese version of GPT gave answers that accounted for context, uncertainty, and change over time. It also offered more flexible interpretations, often responding with ranges or multiple options instead of just one answer. In contrast, the English version stuck to direct logic and clearly defined outcomes.
No Nudging Needed
What’s striking is that these shifts occurred without any cultural instructions. The researchers didn’t tell the models to act more “Western” or “Eastern.” They simply changed the input language. That alone was enough to flip the models’ behavior, almost like switching glasses and seeing the world in a new shade.
To check how strong this effect was, the researchers repeated each task more than 100 times. They tweaked prompt formats, varied the examples, and even changed gender pronouns. No matter what they adjusted, the cultural patterns held steady.
Real-World Impact
The study didn’t stop at lab tests. In a separate exercise, GPT was asked to choose between two ad slogans, one that stressed personal benefit, another that highlighted family values. When the prompt came in Chinese, GPT picked the group-centered slogan most of the time. In English, it leaned toward the one focused on the individual.
This might sound small, but it shows how language choice can guide the model’s output in ways that ripple into marketing, decision-making, and even education. People using AI tools in one language may get very different advice than someone asking the same question in another.
Can You Steer It?
The researchers also tested a workaround. They added cultural prompts, telling GPT to imagine itself as a person raised in a specific country. That small nudge helped the model shift its tone, even in English, suggesting that cultural context can be dialed up or down depending on how the prompt is framed.
Why It Matters
The findings concern how language affects the way AI models present information. Differences in response patterns suggest that the input language influences how content is structured and interpreted. As AI tools become more integrated into routine tasks and decision-making processes, language-based variations in output may influence user choices over time.
Notes: This post was edited/created using GenAI tools. Image: DIW-Aigen.
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