Carbon Footprint Assessments For Data Operations
Companies worldwide are increasingly aware of their environmental impact and the necessity to mitigate it. Aligning with global sustainability goals not only enhances reputation but also positions businesses as responsible leaders in their industries. With 46% of businesses now prioritising sustainability criteria from their partners, and 34% of consumers willing to pay premiums for sustainable products, the business case for environmental stewardship is clear.
Why Data Is A Problem
Data centres, the backbone of the modern digital economy, significantly contribute to global carbon emissions. By 2025, these centres are projected to account for 3.2% of the world's total carbon output. For instance, Facebook's data centres alone consumed over 7.17 terawatt-hours of electricity in 2020—equivalent to the annual consumption of San Francisco. Much of this energy is attributed to hardware infrastructure like servers, which can consume hundreds of watts each, leading to massive energy demands in large-scale data operations. Additionally, data transmission over networks further exacerbates these environmental impacts. As the demand for data services continues to grow exponentially, the associated energy consumption and carbon emissions are expected to rise, necessitating action from companies to implement sustainable practices.
So, How Can You Track Your Usage?
To effectively reduce the carbon footprint of data operations, you will need to apply a meticulous emission tracking and analysis. This involves capturing detailed emissions data from every component of your data pipeline(s). Tools such as ElectricityMap offer insights into the carbon intensity of energy sources, while metrics like Power Usage Effectiveness (PUE) gauge the efficiency of data centres. Mapping out your physical infrastructure such as servers, storage devices, and networking equipment will allow you to calculate how much power you are using and the probable emissions based on where these assets are located. So too should you try and understand your operational data metrics such as the volume of data you process, storage used, and network traffic.
Conducting a thorough analysis allows companies to identify the most carbon-intensive processes and target them for improvement. Furthermore, incorporating machine learning can enhance the accuracy of emissions tracking and provide predictive insights, enabling more effective decision-making in reducing the carbon footprint of data operations.
How Can You Reduce Your Usage?
Transitioning to cleaner energy sources, optimising energy consumption, and adopting technologies like batch processing can significantly curb carbon emissions. Major corporations like Microsoft have already achieved carbon neutrality in their data operations through such initiatives. Additionally, companies can explore innovative cooling solutions, such as liquid cooling and advanced airflow management, to reduce the energy required for cooling data centres. Implementing energy-efficient hardware and virtualisation technologies can also play a crucial role in minimising energy usage. By investing in research and development of new technologies, businesses can continually improve their sustainability efforts and set industry standards for reducing carbon emissions.
For many companies, you might not own your data infrastructure, but you can still seek out eco-friendly providers, look for certifications such as ISO 14001 (environmental management) or LEED (energy and environmental design) and try and find suppliers who use renewable energy sources or publishes detailed sustainability reports.
What Are The Benefits?
Environmental Impact and Corporate Social Responsibility (CSR)
Reducing the environmental footprint isn't just about compliance, it's about demonstrating corporate social responsibility. Companies that actively work to minimise their carbon emissions foster goodwill among environmentally-conscious consumers and stakeholders. This commitment not only enhances reputation but also attracts a loyal customer base.
Cost Savings
Efficient energy management not only reduces environmental impact but also lowers operational costs significantly. Companies that optimise their energy usage often benefit from substantial savings. Additionally, aligning with sustainability goals can unlock financial incentives such as subsidies and tax relief. If you want to read more about sustainable and economical strategies make sure to read our previous report focused on data usages.
Who Is Setting An Example?
Leading tech giants like Google and Amazon are setting benchmarks for sustainability in data operations. Google aims to operate on carbon-free energy 24/7 by 2030, while Amazon has committed to achieving net-zero carbon emissions by 2040. These initiatives not only drive innovation but also appeal to a growing market of eco-conscious consumers. Smaller companies can follow these examples by setting ambitious sustainability goals and transparently reporting progress. Partnering with environmental organisations and participating in industry-wide sustainability initiatives can amplify these efforts.
Conclusion
If your company is serious about reducing its carbon, than your data infrastructure is a key area to investigate. Data centres account for 2.5% to 3.7% of global GHG emissions, exceeding GHG emissions from the aviation industry (2.4%) and this is only likely to grow thanks to innovations like AI and Machine Learning.
If you are looking for some friendly advice on how best to process your data to save cost and the environment then why not get in touch with the team at 173tech?