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How data cleaned New York City's air

With air quality worsening in London, Adam Fudawkowski asks whether there is anything we can learn from New York City's air quality programme.

Adam Fudakowski
Adam Fudakowski

Aug 10, 2017

As any Londoner will tell you, air pollution in large cities is a big problem. It was a similar story in New York City at the turn of the century. This was until Michael Bloomberg became Mayor of the city and leveraged data to transform the air quality.

Bloomberg’s recent piece in the Evening Standard emphasised the key role data played in tackling New York City’s crippling air quality problems when he first became Mayor of the city in 2002.

Whilst contemplating how to reach his ambitious goal of having the cleanest air of any large US city, Bloomberg wrote, “we first needed better data – because if you can’t measure the problem, you can’t manage it.”

To ensure adequate data was collected, Bloomberg placed 150 air-quality sensors at street level around New York City. Using the subsequent data, it was deduced that buildings using dirty heating oils were accountable for more pollution than all of the vehicles on the roads of New York City.

Equipped with this data, New York City officials were able to ban the dirtiest-burning oils and began incentivising investments into cleaner energy. The results were dramatic, with air quality levels becoming the cleanest in over 50 years and life expectancy increasing by three years.

If New York City officials could leverage data to achieve such dramatic and positive results, the same can be done in the UK’s housing sector.

How could similar results be achieved in the housing sector?

UK affordable housing landlords face similarly complex tasks as those faced by Bloomberg in 2002. Collectively, they manage nearly five million properties in a country where 88 per cent of the housing stock was built before 1990.

It is their responsibility to ensure large property portfolios meet various standards, namely the Decent Homes Standard and Energy Efficiency Standard for Social Housing (EESSH), all whilst ensuring resident well-being is maintained and improved. Ultimately, the provision of data would make these challenges more straightforward.

The benefits of data are unquestionable. However, gathering the data can be difficult – the equipment is expensive and often cumbersome. Moreover, there is the added difficulty of convincing residents of the benefits of such equipment. The technology must benefit the landlord, to justify the return on investment, and it must also benefit the resident in a tangible way. It must be unobtrusive and simple to use.

Gather Data

We believe Switchee is the obvious solution to this dilemma. Switchee uses five sensors that monitor heat, light, motion, air pressure and humidity. Data from these sensors is used to build an occupancy pattern for each home, without the need for resident engagement. Learning occupancy allows Switchee to optimise heating settings, reducing fuel bills by up to 15% and delivering real value for residents.

Meanwhile, the same data can be used to allow landlords to access remote live building KPIs such as thermal performance, condensation risk and heating system alerts. Asset managers can use this information to better understand specific problems and make targeted, proactive improvements – much like the Bloomberg’s analysts in New York City.

At Switchee, it is our mission to combat fuel poverty and empower landlords with remote data insight that save them money and improve well-being for their residents.

Adam Fudakowski

Adam is Switchee's Executive Chair and co-founder. Following his Manufacturing Engineering degree at Cambridge, Adam worked as a Graduate Analyst at Boston Consulting Group, advising global clients on business strategy in pharmaceuticals and retail. Adam then co-founded a successful medical device company Nanoclave. Adam completed an MBA at INSEAD in 2014.

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