Sustainability Report

The carbon emissions are calculated based on the as-built quantities of the materials provided by the contractor, using the Singapore Building Carbon Calculator. This calculator follows the Life Cycle Assessment (LCA) ISO 14040/14044. Country-specific embodied carbon values for materials (A1-A3) have been incorporated into this calculator for key exporters of construction materials to Singapore. The assessment covers the carbon emissions of concrete, steel, glass, tiles, paint, waterproofing and plaster used across both the superstructure and substructure of the project.

The assessment recorded a 10.13% reduction in embodied carbon, with the use of recycled reinforcement bars and rods forming the principal documented reduction measure.

CMPB does not use an unverified carbon-capture figure to offset its embodied impact. Although the project incorporates extensive landscaping and green roofs, the available assessment does not quantify their sequestration. Similarly, salvaged Khaya timber is reported as material reuse and avoidance of newly sourced timber, rather than as a speculative carbon offset. The timber from mature Khaya trees previously located on site was treated and repurposed as modular benches, feature walls and mosaics, retaining material already present on the site while reducing the need for newly sourced timber.

CMPB follows a passive-first hierarchy, reducing demand before meeting the remaining load through high-efficiency systems and renewable energy.

Computational Fluid Dynamics (CFD) informed the orientation and configuration of naturally ventilated areas, including the running track and sheltered communal spaces. Daylit atria and high-performance glazing bring natural light deep into the building while limiting solar heat transmission. On the east-facing Public-Facing Block, elliptical precast fins are individually angled to reduce morning heat gain and glare while maintaining outward views. Green roofs and landscaped courtyards further moderate the microclimate and mitigate the urban heat-island effect. 

The remaining cooling demand is served by a high-efficiency chilled-water system with variable-flow pumps, variable-speed cooling-tower fans and optimised equipment sequencing. EC-fan AHUs serve larger spaces, while fan-less passive displacement ventilation (PDV) covers meeting rooms representing approximately 5.5% of total cooling demand. PDV introduces cool air into a low-level zone at low velocity, resulting in less distraught and saving fan energy. The overall air distribution system efficiency is able to achieve 0.141kW/RT.

CMPB's air-conditioning system was engineered for energy efficiency through a holistic approach: cooling systems tailored to space function, optimised water- and air-side equipment selection, and variable-speed drives to cut energy use under partial loads. Key sustainability features include:

• Elevated chilled water temperatures (9.5°C/16.5°C supply/return), enabling the chiller to achieve a COP of 8 or higher whenever cooling load exceeds 40% of capacity — a significant efficiency gain over conventional setups.

• Variable-flow pumping and cooling tower fan controls, allowing the system to dynamically match fluctuating cooling demand rather than running at fixed rates, further trimming energy consumption.

• Extensive load testing and sequencing optimisation, comparing chiller plant configurations across varying part-load conditions to identify the most efficient operating strategy at all times.

Together, the optimised chilled-water plant, air-side systems, variable-speed drives, and control strategies deliver an overall system efficiency of 0.527 kW/RT sustained over 24 hours — demonstrating strong, real-world energy performance.

The chiller plant and AHU energy optimisation solution is also a fully autonomous, closed-loop software and a mathematical digital twin strengthened with computational statistics and self-learning algorithms. The first step in the process is to collect historical data of the building's AC energy usage and operational settings from various sources, including energy meters, building management systems, and other sensors. The data is then analysed and used to create a machine learning model which is trained on the historical data to learn how the building's AC energy consumption varies based on different operational settings. As the model is continuously refined, it can predict the building's AC energy consumption with a high degree of accuracy, allowing for better energy management and reduced operating costs.

The operational emissions per year are calculated based on the Singapore Grid Emission Factor and annual building energy consumption simulated using energy modelling software IES Virtual Environment (IESVE), according to the equipment selections provided by the contractor and operating hours and diversity factor advised by the building owner. 

CMPB reduces maintenance-related emissions through a combination of durable materials, direct maintenance access, replaceability and predictive intervention.

High-traffic floors use homogeneous tiles with a minimum Mohs hardness of 7 and water absorption not exceeding 0.5%. Wet-room walls are tiled, toilet partitions use durable phenolic panels and façade sealants were selected for compatible, non-staining and non-bleeding performance. These material choices extend replacement cycles and reduce recurrent material consumption.

Maintenance routes are also integrated into the architecture: a minimum 1.2-metre access route serves plant rooms and tanks; cooling towers have protected ladder access; and roof landscapes and planters have dedicated maintenance walkways. More than 75% of internal ceiling areas use open or demountable modular ceiling systems, allowing individual services to be accessed and replaced without destroying surrounding finishes. This improves maintainability while reducing the material waste and emissions associated with repair and replacement works.

Predictive maintenance is adopted as one of SMART FM features to further reduce maintenance-related emissions.  The data-driven approach that unifies all available information about a portfolio of building equipment. By leveraging sophisticated machine learning algorithms, it can effectively assess risk, prioritise alerts, and plan maintenance and investment activities. Equipment Fault Detection and Diagnostics (FDD) is a technology that gathers data from building sensors and equipment and employs complex algorithms to uncover potential problems, alert staff to impending issues and identify the root cause of the problem. The system provides easy-to-understand visuals that help technicians quickly identify preventative solutions, resulting in a significant reduction in baseline maintenance costs, capital costs, equipment wear and maintenance emissions. The building therefore treats maintainability not as a post-completion obligation, but as a long-term carbon-reduction strategy.