| City dashboard (2022) | |
|---|---|
| Population | 7.4 million |
| Surface area (km2) | 2,760 |
| Mobility demand (km) | 106 billion |
| Mobility demand per person per day (km) | 39.3 |
| Mobility emissions (CO2e) | 8.4 megatons |
| Emissions per person per day (CO2e) | 3.15 kilograms |
Urban mobility global warming impact (2030)
0.0°C
Emissions reductions required to reach the 1.5°C target by 2030
-0%
0.0MtCO2e
Introduction
Hong Kong offers a great mix of mobility services with a balanced modal share between public transit (71%), cars (15%), walking (13%), and other modes.
The mobility demand is strong, accounting for 106 billion kilometers (66 billion miles) traveled in 2022, generating 8.4 MtCO2e.
Hong Kong has a well-developed public transit system and cycling infrastructure, and only 15% of the distance traveled in 2022 in Hong Kong was via cars, contributing to just 29% of emissions. But despite an impressive low modal share of cars, Hong Kong remains off track to reaching the 1.5°C target by 2030,
largely due to its carbon-intensive power grid composition.
Current situation
Based on city plans, mobility demand is expected to grow by 11% by 2030 while CO2 emissions
are forecasted to remain steady due to greater electric vehicle adoption.
Electric vehicle market shares will likely increase rapidly because of a government ban on gasoline-powered car sales starting in 2035, as well as increased investments in charging infrastructure.
Hong Kong’s Climate Action Plan 2050, a $240 billion project, aims for net-zero electricity generation by 2050 and zero vehicle emissions before 2050 through electrification, improvement of traffic management through congestion pricing and other methods, and the further development of sustainably fueled transport. Beyond commitments to electrify its fleet, Hong Kong plans to enhance active mobility infrastructure with expanded pedestrian walkways and improved accessibility to facilities.
However, Hong Kong’s commitments to address transport emissions are still roughly 5.0 MtCO2e short of the target, requiring an additional 59% decrease in emissions on top of current government commitments by 2030 to stay within 1.5°C of warming.
Optimization
We explored four different optimization scenarios:
Hong Kong’s excellent public transit infrastructure makes it an effective lever to reduce personal car modal shares. However, because of the carbon-intensive electric grid, the city’s ability to further optimize is limited. Within our optimization paradigm, the only way for Hong Kong to achieve the 1.5°C target by 2030 is by pairing demand reduction with significant modal shifts. Reducing demand is not an easy option and may not be realistic. Without a sharp reduction of power grid emissions, Hong Kong would need to reduce mobility demand by building denser housing or a 15-minute city. To avoid going down that path, the city should consider pursuing a lower carbon grid paired with an electrification of both public and private transport.
* indicates the scenario that achieves the greatest realistic emissions reduction
When simulating realistic modal shifts, achieving 1.5°C would not be possible. When allowing larger shifts, achieving 1.5°C would require extreme changes: a reduction in total mobility demand of 38% or approximately 15.2 kilometers (9.4 miles) per person per day compared to 2022.
Reduce personal car use:
Decarbonize the power grid:
Promote active mobility:
When simulating realistic modal shifts, achieving 1.5°C would not be possible. When allowing larger shifts, achieving 1.5°C would require extreme changes: a reduction in total mobility demand of 38% or approximately 15.2 kilometers (9.4 miles) per person per day compared to 2022.
Reduce personal car use:
Decarbonize the power grid:
Accelerate electrification of the fleet:
When simulating realistic modal shifts, achieving 1.5°C would not be possible. When allowing larger shifts, achieving 1.5°C would require extreme changes: a reduction in total mobility demand of 38% or approximately 15.2 kilometers (9.4 miles) per person per day compared to 2022.
Reduce personal car use:
Decarbonize the power grid:
Promote active mobility:
When simulating realistic modal shifts, achieving 1.5°C would not be possible. When allowing larger shifts, achieving 1.5°C would require extreme changes: a reduction in total mobility demand of 20% or approximately 8.5 kilometers (5.3 miles) per person per day compared to 2030 projections.
Reduce personal car use:
Decarbonize the power grid:
Promote active mobility:
