The world’s largest airports consume enormous amounts of energy—comparable to the needs of small cities. A significant portion of this energy is dedicated to cooling. In particular, the air conditioning of terminals, data centers, cargo warehouses, and maintenance hangars generates high cooling costs, often amounting to tens of millions of dollars per year. Typically, energy expenses account for 10–15% of an airport’s operating budget—with cooling costs representing a large share of that expense. The following report examines the cooling costs of the 50 busiest airports worldwide, breaking down the analysis into the areas of terminal buildings, data centers, cargo warehouses, and hangars. It also explores how artificial intelligence (AI) is already being applied in the energy management of these airports and what new cost-saving potentials a solution like Stromfee AI might offer.
Cooling Costs in Different Airport Areas
Terminals (Passenger Buildings)
Terminal buildings account for the largest portion of an airport’s cooling energy consumption. In many cases, over 50% of an airport’s total energy consumption is due to the terminals, which must be lit, ventilated, and air-conditioned nearly around the clock. Within the terminals, approximately 70% of the energy consumption is attributed solely to HVAC (Heating, Ventilation, and Air Conditioning) systems.The exact cooling demand strongly depends on the climate and building design:
Temperate climates: approximately 0.5–1 kWh per passenger
Hot, tropical regions: approximately 3–5 kWh per passenger
Examples:
Vienna Airport: about 0.9–1.0 kWh of cooling energy per passenger
Kansai Airport in Osaka: about 5.4 kWh per passenger
Singapore Changi: roughly 70% of the total electricity consumption is devoted to air conditioning and ventilation
Data Centers (IT Infrastructure)
Data centers and server rooms also contribute to cooling costs, although to a lesser extent than terminals. Airports operate extensive IT infrastructures for air traffic control, ticketing, surveillance, and communications—which run 24/7 and require uninterrupted cooling to protect sensitive hardware.In many traditional data centers, up to 40% of the total energy consumption is used for cooling IT equipment. However, because the area is much smaller than that of the terminals, the absolute costs are lower. Modern airports with their own data centers can significantly reduce energy consumption through measures such as free cooling and optimized hot/cold aisle configurations.
Cargo Warehouses (Cargo/Logistics Areas)
Cargo and storage halls typically require less air conditioning than passenger terminals. Standard cargo warehouses are often only ventilated rather than fully air-conditioned—except for specialized cooling areas designed to store temperature-sensitive goods (such as perishable foods or pharmaceuticals).Although these specialized areas have a high specific cooling energy demand, their overall area is relatively small, so the cooling costs generally represent only a small percentage of the total. However, due to rising demands—such as increased transport of temperature-sensitive products—this share may increase in the future.
Maintenance Hangars
Aircraft hangars are vast spaces used for aircraft maintenance and storage. Due to their enormous volume and frequent door openings, fully air-conditioning these spaces is usually uneconomical. In temperate climates, hangars often remain unheated and uncooled (except for the workshops and offices inside).In very hot climates or tropical regions, however, hangars are sometimes cooled or ventilated more intensively to maintain a tolerable working environment and protect sensitive components. Consequently, the cooling costs for hangars are generally much lower than those for terminals.
Estimated Cooling Costs for the Top 50 Airports (in Million US Dollars per Year)
The following table provides an estimate of the annual cooling costs for the 50 busiest airports, broken down into terminals, data centers, cargo warehouses, and hangars. These estimates are based on typical consumption values for different climate zones and an assumed average electricity cost of 0.10 USD per kWh.
Airport (IATA) | Terminals | Data Centers | Cargo Warehouses | Hangars | Total |
Atlanta (ATL) – USA, temperate | 24.0 Mio. $ | 1.5 Mio. $ | 1.5 Mio. $ | 0.5 Mio. $ | 27.6 Mio. $ |
Beijing-Capital (PEK) – China, continental | 17.5 Mio. $ | 1.0 Mio. $ | 1.0 Mio. $ | 0.5 Mio. $ | 20.0 Mio. $ |
Los Angeles (LAX) – USA, mild | 11.5 Mio. $ | 0.8 Mio. $ | 0.6 Mio. $ | 0.3 Mio. $ | 13.2 Mio. $ |
Dubai (DXB) – UAE, desert climate | 30.0 Mio. $ | 2.0 Mio. $ | 2.0 Mio. $ | 0.5 Mio. $ | 34.5 Mio. $ |
Tokyo-Haneda (HND) – Japan, humid-hot | 15.0 Mio. $ | 1.0 Mio. $ | 0.8 Mio. $ | 0.3 Mio. $ | 17.1 Mio. $ |
Chicago-O’Hare (ORD) – USA, continental | 8.5 Mio. $ | 0.8 Mio. $ | 0.6 Mio. $ | 0.2 Mio. $ | 10.1 Mio. $ |
London-Heathrow (LHR) – UK, mild | 6.5 Mio. $ | 0.6 Mio. $ | 0.5 Mio. $ | 0.2 Mio. $ | 7.8 Mio. $ |
Shanghai-Pudong (PVG) – China, subtropical | 12.5 Mio. $ | 1.0 Mio. $ | 1.2 Mio. $ | 0.5 Mio. $ | 15.2 Mio. $ |
Paris-CDG (CDG) – France, mild | 6.0 Mio. $ | 0.6 Mio. $ | 0.5 Mio. $ | 0.2 Mio. $ | 7.6 Mio. $ |
Dallas/Fort Worth (DFW) – USA, hot | 19.0 Mio. $ | 1.5 Mio. $ | 1.5 Mio. $ | 0.5 Mio. $ | 22.5 Mio. $ |
Guangzhou (CAN) – China, subtropical | 18.0 Mio. $ | 1.5 Mio. $ | 1.5 Mio. $ | 0.5 Mio. $ | 22.0 Mio. $ |
Amsterdam-Schiphol (AMS) – NL, mild | 4.5 Mio. $ | 0.5 Mio. $ | 0.5 Mio. $ | 0.2 Mio. $ | 5.7 Mio. $ |
Hong Kong (HKG) – Hong Kong, subtropical | 17.5 Mio. $ | 1.5 Mio. $ | 2.0 Mio. $ | 0.4 Mio. $ | 21.4 Mio. $ |
Seoul-Incheon (ICN) – South Korea, temperate | 11.5 Mio. $ | 1.0 Mio. $ | 1.5 Mio. $ | 0.2 Mio. $ | 14.2 Mio. $ |
Frankfurt (FRA) – Germany, mild | 6.0 Mio. $ | 0.5 Mio. $ | 0.4 Mio. $ | 0.2 Mio. $ | 7.1 Mio. $ |
Denver (DEN) – USA, cool | 5.5 Mio. $ | 0.5 Mio. $ | 0.7 Mio. $ | 0.2 Mio. $ | 6.9 Mio. $ |
Delhi (DEL) – India, hot and dry | 16.0 Mio. $ | 1.5 Mio. $ | 2.5 Mio. $ | 0.5 Mio. $ | 20.5 Mio. $ |
Singapore-Changi (SIN) – tropical | 22.0 Mio. $ | 2.0 Mio. $ | 2.5 Mio. $ | 0.8 Mio. $ | 27.3 Mio. $ |
Bangkok (BKK) – Thailand, tropical | 21.0 Mio. $ | 1.5 Mio. $ | 2.5 Mio. $ | 1.0 Mio. $ | 26.0 Mio. $ |
New York-JFK (JFK) – USA, humid | 7.5 Mio. $ | 0.7 Mio. $ | 0.9 Mio. $ | 0.3 Mio. $ | 9.4 Mio. $ |
Kuala Lumpur (KUL) – Malaysia, tropical | 20.0 Mio. $ | 1.5 Mio. $ | 2.8 Mio. $ | 0.6 Mio. $ | 24.9 Mio. $ |
Madrid-Barajas (MAD) – Spain, hot | 9.5 Mio. $ | 0.8 Mio. $ | 1.8 Mio. $ | 0.2 Mio. $ | 12.3 Mio. $ |
San Francisco (SFO) – USA, mild | 3.5 Mio. $ | 0.4 Mio. $ | 0.6 Mio. $ | 0.1 Mio. $ | 4.6 Mio. $ |
Chengdu (CTU) – China, humid | 8.5 Mio. $ | 0.8 Mio. $ | 1.6 Mio. $ | 0.3 Mio. $ | 11.2 Mio. $ |
Jakarta (CGK) – Indonesia, tropical | 17.5 Mio. $ | 1.5 Mio. $ | 2.5 Mio. $ | 0.3 Mio. $ | 21.8 Mio. $ |
Shenzhen (SZX) – China, subtropical | 12.5 Mio. $ | 1.0 Mio. $ | 2.0 Mio. $ | 0.4 Mio. $ | 15.9 Mio. $ |
Barcelona (BCN) – Spain, warm | 6.5 Mio. $ | 0.5 Mio. $ | 0.7 Mio. $ | 0.2 Mio. $ | 7.9 Mio. $ |
Istanbul (IST) – Turkey, mixed climate | 6.5 Mio. $ | 0.5 Mio. $ | 0.6 Mio. $ | 0.2 Mio. $ | 7.8 Mio. $ |
Seattle-Tacoma (SEA) – USA, cool | 2.0 Mio. $ | 0.3 Mio. $ | 0.2 Mio. $ | 0.1 Mio. $ | 2.6 Mio. $ |
Las Vegas (LAS) – USA, desert | 17.0 Mio. $ | 1.5 Mio. $ | 1.8 Mio. $ | 0.3 Mio. $ | 20.6 Mio. $ |
Orlando (MCO) – USA, subtropical | 12.5 Mio. $ | 1.0 Mio. $ | 1.4 Mio. $ | 0.3 Mio. $ | 15.2 Mio. $ |
Toronto Pearson (YYZ) – Canada, cold | 4.0 Mio. $ | 0.4 Mio. $ | 0.5 Mio. $ | 0.2 Mio. $ | 5.0 Mio. $ |
Mexico City (MEX) – Mexico, mild | 3.2 Mio. $ | 0.3 Mio. $ | 0.4 Mio. $ | 0.1 Mio. $ | 4.0 Mio. $ |
Charlotte (CLT) – USA, warm | 8.0 Mio. $ | 0.8 Mio. $ | 1.0 Mio. $ | 0.2 Mio. $ | 10.0 Mio. $ |
Moscow-Sheremetyevo (SVO) – Russia, cold | 2.0 Mio. $ | 0.2 Mio. $ | 0.2 Mio. $ | 0.1 Mio. $ | 2.5 Mio. $ |
Taipei-Taoyuan (TPE) – Taiwan, subtropical | 12.0 Mio. $ | 1.0 Mio. $ | 1.3 Mio. $ | 0.3 Mio. $ | 14.6 Mio. $ |
Kunming (KMG) – China, mild | 3.8 Mio. $ | 0.4 Mio. $ | 0.5 Mio. $ | 0.1 Mio. $ | 4.8 Mio. $ |
Munich (MUC) – Germany, mild | 3.8 Mio. $ | 0.4 Mio. $ | 0.5 Mio. $ | 0.1 Mio. $ | 4.8 Mio. $ |
Manila (MNL) – Philippines, tropical | 15.5 Mio. $ | 1.5 Mio. $ | 1.8 Mio. $ | 0.4 Mio. $ | 19.2 Mio. $ |
Xi’an (XIY) – China, hot summers | 7.5 Mio. $ | 0.6 Mio. $ | 1.2 Mio. $ | 0.2 Mio. $ | 9.4 Mio. $ |
Mumbai (BOM) – India, tropical | 11.5 Mio. $ | 1.0 Mio. $ | 1.3 Mio. $ | 0.3 Mio. $ | 14.1 Mio. $ |
London-Gatwick (LGW) – UK, mild | 2.5 Mio. $ | 0.3 Mio. $ | 0.4 Mio. $ | 0.1 Mio. $ | 3.3 Mio. $ |
Newark (EWR) – USA, temperate | 4.5 Mio. $ | 0.4 Mio. $ | 0.5 Mio. $ | 0.2 Mio. $ | 5.6 Mio. $ |
Phoenix (PHX) – USA, desert | 15.5 Mio. $ | 1.3 Mio. $ | 1.5 Mio. $ | 0.2 Mio. $ | 18.5 Mio. $ |
Miami (MIA) – USA, tropical | 11.5 Mio. $ | 1.0 Mio. $ | 1.0 Mio. $ | 0.3 Mio. $ | 13.8 Mio. $ |
Shanghai-Hongqiao (SHA) – China, subtropical | 7.5 Mio. $ | 0.7 Mio. $ | 0.8 Mio. $ | 0.1 Mio. $ | 9.1 Mio. $ |
Houston-Intercontinental (IAH) – USA, hot | 11.0 Mio. $ | 1.0 Mio. $ | 1.2 Mio. $ | 0.3 Mio. $ | 13.5 Mio. $ |
Chongqing (CKG) – China, very hot | 11.0 Mio. $ | 1.0 Mio. $ | 1.2 Mio. $ | 0.2 Mio. $ | 13.4 Mio. $ |
Sydney (SYD) – Australia, warm | 7.0 Mio. $ | 0.6 Mio. $ | 1.0 Mio. $ | 0.3 Mio. $ | 8.9 Mio. $ |
Tokyo-Narita (NRT) – Japan, humid-hot | 7.0 Mio. $ | 0.6 Mio. $ | 1.0 Mio. $ | 0.3 Mio. $ | 8.9 Mio. $ |
Note: The figures are rough estimates based on typical consumption values and climatic conditions. Efficiency improvements and modern installations can lead to significant variations.
AI in Airport Energy Management
Given the high energy costs, an increasing number of airports are turning to digital energy management solutions and artificial intelligence (AI) to operate their facilities more efficiently. The spectrum of applications ranges from intelligent building management systems (BMS) to self-learning algorithms that optimize energy consumption in real time.
Current AI Solutions and Examples
Modernized Building Automation Systems: Many airports are upgrading their BMS to control air conditioning based on demand. For example, Dublin’s system achieved a 33% reduction in energy consumption despite increasing passenger numbers.
Brisbane Airport (Australia): A pilot project using an AI-based HVAC optimization system (e.g., from BrainBox AI) resulted in a 12% reduction in energy consumption and a 17% decrease in equipment runtime.
Dubai International: In collaboration with Siemens, data analytics is used to optimize climate and water systems, with measures expected to save about 50 GWh of electricity annually.
Potential of Stromfee AI
Stromfee AI is designed to connect and control all energy-related systems at an airport holistically. New possibilities include:
Integrated Control: Connecting terminal air conditioning, lighting, IT infrastructure, cargo cooling facilities, and even apron air conditioning systems into one synchronized system.
Predictive Climate Control: Utilizing weather and passenger data to optimize cooling in advance—for example, pre-cooling during periods of lower electricity rates.
Load Shifting and Energy Storage: Optimizing the use of existing cooling and heating storage systems to mitigate peak demand.
Zone-Specific Optimization: Fine-tuning the air conditioning based on real-time occupancy data for different terminal zones.
Optimizing IT Cooling: Dynamically adjusting data center temperatures to avoid thermal hotspots.
Early Warning and Predictive Maintenance: Detecting slight efficiency losses and automatically triggering maintenance actions to prevent further cost increases.
Pilot projects have shown that AI-based measures can reduce energy consumption by 10–20%. With an integrated solution like Stromfee AI, it is conceivable that cost reductions of 20–30% could be achieved—equating to annual savings of 100–180 million dollars for the largest airports. Additionally, such measures contribute significantly to CO₂ reductions, making them not only economically attractive but also environmentally vital.
Conclusion
The analysis demonstrates that airports around the world incur substantial cooling costs—especially in hot climates. With an estimated total annual cooling expenditure of around 600 million dollars among the top 50 airports, there is enormous potential for savings. Modern AI solutions in energy management have already delivered promising results, and a holistic platform like Stromfee AI could further enhance these savings. In addition to lowering operating costs, such technologies play an important role in making airport infrastructures more sustainable and environmentally friendly.
References
[2] L701–L708
[14] L17–L23
[28] L417–L424
[15] L265–L273
[2] L680–L687
[32] L908–L916
[32] L875–L883
[16] L1–L4
[1] L7–L8
[33] L75–L83
[31] L27–L31
[28] L427–L435
[28] L460–L468
[24] L268–L276
[26] L91–L99
[18] L9–L17
[34] L232–L239
[34] L225–L233
[35] L23–L28
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