The proposed Project will be the first methanol plant in Sarawak. The plant will have a production capacity of 5,000 metric tonnes per day (MTPD) of methanol and will employ about 300 skilled workers and staff. With an estimated total investment of RM 4.2 billion, it is expected to contribute to the economic growth of Bintulu, the State of Sarawak and Malaysia as a whole.

The proposed Project also represents an opportunity to develop a value-adding downstream processing facility from the utilisation of Sarawak reserves and natural gas.

The key project elements included the following:

• A profile of the existing environmental condition within a 5 km radius of the Project site. This element focussed on the identification and mapping of the existing environmental conditions in the immediate area, highlighting the existing land capability, the land use, Environmentally Sensitive Areas (ESA) and the key environmental issues. This included a review of the institutional and legal set-up and identification of the main issues, opportunities and constraints
• Dispersion Modelling conducted with the USEPA’s AERMOD model (Version 16218, December 2016) and one year of meteorological data generated by the Mesoscale Meteorological Model (MM5). Three emission scenarios were assessed. The first is when there are control measures to limit emission within allowable limits, the second is based on the worst case without control measures scenario and the third is during emergency flaring. Air pollutants that were assessed were particulate matter (PM) as PM₁₀ and PM_2.5, sulphur dioxide (SO₂), nitrogen dioxide (NO₂), hydrogen sulphide (H₂S), ammonia (NH₃) and total organic compound (TOC).
• Quantitative Risk Assessment (QRA) that identifies possible major accident hazards in the proposed project based on the physical and chemical properties (i.e. flash point, boiling point, heat of combustion) of substances stored in this project site.
• Assessment of noise levels against the permissible noise limit at the project boundary and noise mapping of noise sources using CadnaA.