Sustainability
Jul 02, 2024
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This report offers a deep dive into our efforts to harness technology — particularly AI — to drive positive environmental change and operate our business sustainably.
Since our earliest days, we’ve been on an ambitious journey to help build a more sustainable future. An important part of that is sharing what we’ve learned along the way and being transparent about our progress and our challenges. This is especially true given the urgency of the moment — a time when technological advancement is converging with the need for energy transition.
Our annual Environmental Report offers a deep dive into our efforts to harness technology — particularly AI — to drive positive environmental change and operate our business sustainably.
We know that scaling AI and using it to accelerate climate action is just as crucial as addressing the environmental impact associated with it.
To help minimize our environmental footprint, we’ve built world-leading efficient infrastructure for the AI era, including Trillium, our sixth-generation Tensor Processing Unit (TPU), which is over 67% more energy-efficient than TPU v5e.1 We’ve also identified tested practices that our research shows can, when used together, reduce the energy required to train an AI model by up to 100 times and reduce associated emissions by up to 1,000 times.2 All these practices are used at Google today.
We strive to build the world’s most energy-efficient computing infrastructure, supported by responsible water use practices and a commitment to minimizing waste. A Google-owned and -operated data center is, on average, approximately 1.8 times as energy efficient as a typical enterprise data center.3 In 2023, the average annual power usage effectiveness for our data centers was 1.10 compared with the industry average of 1.58,4 meaning that our data centers used about 5.8 times less overhead energy for every unit of IT equipment energy.
Last year we introduced a water risk framework to further identify climate-conscious cooling solutions that consider carbon-free energy (CFE) availability, watershed health and future water needs. We see our growing infrastructure as an opportunity to drive the innovations and investments needed to power a low-carbon economy.
AI holds immense promise to drive climate action. In fact, AI has the potential to help mitigate 5–10% of global greenhouse gas (GHG) emissions by 2030.5 We’re advancing climate action through AI in three key areas:
Through our products, we aim to help individuals, cities and other partners collectively reduce 1 gigaton of carbon equivalent emissions annually by 2030, and we’ll continue to develop technologies that help communities adapt to the effects of climate change.
In 2017, Google became the first major company to match 100% of our annual electricity consumption on a global basis with renewable energy, which we’ve achieved every year since.9 Building on our first two decades of progress, in 2020 we launched our third decade of climate action — our most ambitious yet.
We have a bold goal to reach net-zero emissions across all of our operations and value chain by 2030, supported by a goal to run on 24/7 CFE on every grid where we operate. In addition, we’re working to advance water stewardship, build a circular economy, and restore and enhance nature and biodiversity. This year’s report shows how we continue to make progress across all of these areas:
In spite of the progress we are making, we face significant challenges that we’re actively working through. In 2023, our total GHG emissions increased 13% year-over-year, primarily driven by increased data center energy consumption and supply chain emissions.
While we advanced clean energy on many of the grids where we operate, there are still some hard-to-decarbonize regions like Asia-Pacific where CFE isn't readily available. In addition, we often see longer lead times between initial investments and construction of clean energy projects and the resulting GHG reductions from them. To continue to drive progress toward a low-carbon economy, we most recently introduced a clean transition rate that brings customers and utilities together to drive new clean energy projects in the U.S., and we unveiled an investment to enable 1 gigawatt of new solar capacity in Taiwan.
A sustainable future requires systems-level change, strong government policies and new technologies. We’re committed to collaboration and playing our part, every step of the way.
More Information
This calculation is based on internal data, as of May 2024.
“The Carbon Footprint of Machine Learning Training Will Plateau, Then Shrink,” Computer, vol. 55, July 2022.
According to Google’s own analysis of our more efficient servers, power infrastructure, and cooling systems, compared with data center industry averages based on 2023 data. Uptime Institute’s annual data center survey from 2023 noted that the primary contributor to the flatlining of the industry average PUE is a richer geographical mix of surveyed data centers, with an increasing number of data centers in the Asia, Middle East, Africa, and Latin America regions. Facilities in these regions tend to be smaller in capacity and located in warmer climates—both factors which typically require greater energy consumption.
According to the Uptime Institute's 2023 Global Data Center Survey, the global average PUE of respondents’ data centers was around 1.58. The Institute noted that the primary contributor to the flatlining of the industry average PUE is a richer geographical mix of surveyed data centers, with an increasing number of data centers in the Asia, Middle East, Africa, and Latin America regions. Facilities in these regions tend to be smaller in capacity and located in warmer climates—both factors which typically require greater energy consumption.
“Reduce Carbon and Costs with the Power of AI,” Boston Consulting Group, January 2021.
Google uses an AI prediction model to estimate the expected fuel or energy consumption for each route option when users request driving directions. We identify the route that we predict will consume the least amount of fuel or energy. If this route is not already the fastest one and it offers meaningful energy and fuel savings with only a small increase in driving time, we recommend it to the user. To calculate enabled emissions reductions, we tally the fuel usage from the chosen fuel-efficient routes and subtract it from the predicted fuel consumption that would have occurred on the fastest route without fuel-efficient routing and apply adjustments for factors such as: CO2e factors, fleet mix factors, well-to-wheels factors, and powertrain mismatch factors. We then input the estimated prevented emissions into the EPA’s Greenhouse Gas Equivalencies Calculator to calculate equivalent cars off the road for a year. The cumulative figure covers estimated emissions prevented after fuel-efficient routing was launched, from October 2021 through December 2023, while the annual figure covers estimated emissions prevented from January 2023 through December 2023. Enabled emissions reductions estimates include inherent uncertainty due to factors that include the lack of primary data and precise information about real-world actions and their effects. These factors contribute to a range of possible outcomes, within which we report a central value.
The estimated population covered is based on the forecasted flood risk area, using the WorldPop Global Project Population dataset.
Reductions in stops estimates are based on early data points from Google’s analysis of traffic patterns before and after recommended adjustments to traffic signals that were implemented during tests conducted in 2022 and 2023. Emissions reductions estimates are modeled using a Department of Energy emissions model. A single fuel-based vehicle type is used as an approximation for all traffic, and it is not yet adjusted for local fleet mix. These data points are averaged from coordinated intersections, and are subject to variation based on existing scenarios. We expect these estimates to evolve over time and look forward to sharing continued results as we perform additional analysis.
Alphabet’s percentage of electricity purchased from renewable sources methodology is a custom calculation and is based on a global approach. Percentage of renewable energy is calculated on a calendar-year basis, dividing the volume of renewable electricity (in megawatt-hours) procured for our global operations (i.e., renewable energy procured through our PPA contracts, on-site renewable energy generation, and renewable energy in the electric grids where our facilities are located) by the total volume of electricity consumed by our global operations. The numerator includes all renewable energy procured, regardless of the market in which the renewable energy was consumed. Additional details on Alphabet's criteria and methodology can be found in the “Achieving Our 100% Renewable Energy Purchasing Goal and Going Beyond” disclosure.
A grid region (or regional grid) corresponds to the area over which a single entity manages the operation of the electric power system and ensures that demand and supply are finely balanced. In the United States, this generally means the ISO or RTO in regions that have these regional market structures. If no such structure exists, then Google defines the grid region as the electricity-balancing authority where our data centers are located. Outside of the United States, the grid region most often refers to the geographic boundary of a country, because most grid system operators operate at the national level. Certain regions that span multiple countries are well interconnected and could be considered as one grid; however, our grid mix calculations already include import and export considerations and therefore take into account power flows from neighboring grids. In the future, we may update our definition as we work with grid operators to better understand how transmission constraints or congestion impact CFE measurement within and across grid regions.
The total GW figure represents primarily PPAs, and includes some generation capacity from targeted renewable energy investments where we also receive EACs. Actual generation capacity may vary from the signed amounts based on changes during construction or project terminations.
The Google Renewable Energy Addendum applies to the electricity consumed by suppliers in the manufacturing of Google technical infrastructure and consumer hardware products.
We contracted a third-party to estimate replenishment benefits using the Volumetric Water Benefit Accounting (VWBA) methodology (Reig et al., 2019).
Based on total weight of new Google Pixel and Fitbit retail packaging (excluding adhesive materials and required plastic stickers) as shipped by Google. To meet the request of some retail partners, stickers and/or security tags are applied to some packaging variations and may contain plastic.
Based on total weight of new Google Pixel retail packaging (excluding adhesive materials and required plastic stickers) as shipped by Google. To meet the request of some retail partners, stickers and/or security tags are applied to some packaging variations and may contain plastic.
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