# Energy consumption, CO2 emissions and electricity costs of commercial building lighting in Southeast Asia

### Data gathering

Energy audit and lighting data of commercial buildings (such as hospital, hotel, library, mosque, office, retail and university) in Brunei Darussalam^{17}Malaysia^{15,17,18,19,20}Singapore^{17.21} and Thailand^{22.23} found in the literature were collected. Information collected includes building types, year of energy audit performed, annual electricity consumption, building floor area, building energy intensity and percentage of lighting usage. Data from a library building in Brunei Darussalam was collected and measured on site. Library building and lighting information includes building floor area, building hours, types of lamps installed and to be retrofitted, number of lamps installed, working and to be retrofitted, and rated lamp wattage installed and to be retrofitted. Carbon intensities of selected countries from 2005 to 2020 for CO_{2} emissions calculation is from Our World in Data (https://ourworldindata.org/co2/country/brunei, accessed 13 June 2022).

Electrical tariffs for commercial buildings in selected countries are from Department of Electrical Services, Brunei Darussalam (http://www.electrical.gov.bn/elektrik/SitePages/Tarif%20Elektrik.aspx, accessed 13 June 2022), Tenaga Nasional Berhad, Malaysia (https://www.tnb.com.my/assets/files/Tariff_booklet.pdf, accessed June 13, 2022), Energy Market Authority of Singapore (https://www.ema.gov .sg /statistic.aspx?sta_sid=20190319gX6WhmRypOKm, accessed June 13, 2022) and Thailand Board of Investment (https://www.boi.go.th/index.php?page=utility_costs, accessed June 13, 2022). The average electricity tariffs for commercial buildings in the respective countries were used to estimate electricity costs for lighting, which are B$0.10/kWh for Brunei Darussalam, RM0.23/kWh (~ 0.07 B$/kWh) for Malaysia, 0.26 $S/kWh (~ 0.26 B$/kWh) for Singapore and 3.32 baht/kWh (~ 0.13 B$/kWh) for Thailand.

### Estimated energy consumption, CO_{2} emissions and electricity costs for lighting

Energy consumption, CO_{2} lighting electricity emissions and costs for each building type in the selected countries were calculated using the following equations:

$$mathrm{Building ,energy, intensity},, BEI, ({{mathrm{kWh}}/{mathrm{m}^{2}}}/{mathrm{year}}) :,,{ B}EI=frac{E}{A}$$

(1)

$$mathrm{Energy, consumption, for, lighting}, , {overline{E} }_{L}, (mathrm{kWh}/mathrm{m}^{2}/ mathrm{year}):, , { overline{E} }_{L}=BEItimes L$$

(2)

$$mathrm{Or}, , , {overline{E} }_{L}=frac{{E}_{L}}{A}$$

(3)

$${mathrm{CO}}_{2}, mathrm{ emissions , due , to , lighting},, { EM}_{{CO}_{2}},({ mathrm{kg},{mathrm{CO}_{2}}/{mathrm{m}^{2}}}/{mathrm{year}}:, , {EM}_{{ CO }_{2}}={overline{E} }_{L}times CI$$

(4)

$$mathrm{ Electricity, cost, for, lighting},, , {C}_{L}, (mathrm{B$}/mathrm{m}^{2}/ mathrm{year}: , , {C}_{L}={overline{E} }_{L}times AND$$

(5)

where (E) is the annual energy consumption of the building (kWh/year), ({E}_{L}) is the annual lighting energy consumption (kWh/year), (A) is the floor area of the building (m^{2}), (L) is the percentage of average commercial building lighting energy consumption (%), (THIS) is the carbon intensity of the corresponding year (kg CO_{2}/kWh) and (AND) is the electricity tariff for tertiary buildings (B$/kWh).

Linear regression models for energy consumption, CO_{2} Emissions and electricity costs for commercial building lighting in Southeast Asia were developed from the calculated data. The results were illustrated as correlation graphs of energy consumption, CO_{2} emissions and electricity costs for lighting compared to the BEI of commercial buildings in Southeast Asia. Then, a decarbonization pathway for the lighting of tertiary buildings in Southeast Asia was proposed by creating a plot of CO_{2} emissions due to lighting compared to the corresponding year. The annual cost of electricity for lighting different types of commercial buildings in Southeast Asia has been projected to 2050, assuming an annual electricity price increase of 5%. The study also projected the annual cost of electricity for lighting to 2050 for commercial buildings in the same region for increases of 5%, 10% and 15% in the annual electricity price.

### Estimated energy consumption, CO_{2} emissions and electricity costs of different lighting systems for a library building in Brunei Darussalam

The annual energy consumption of artificial lighting (fluorescent and incandescent) and LED, ({overline{E} }_{L}) (kWh/m^{2}/year), for a library in Brunei Darussalam was calculated using Equation. (6):

$${overline{E} }_{L}=frac{Htimes sum {left(Ntimes Pright)}_{i}}{A}$$

(6)

where (H) is the hours of operation of the building for the corresponding year (h), (NOT) is the number of lamps, (P) is the rated power of the lamp (kW) (fluorescent lamp: 0.036 kW; incandescent lamp: 0.017 kW; T8 LED tube: 0.008 kW and LED bulb: 0.004 kW), index (I) represents the lamp types (fluorescent lamp, incandescent lamp, T8 LED tube or LED bulb) and (A) is the floor area of the building (m^{2}) (~1642m^{2}).

The library building in Brunei Darussalam considered in this study has a total of 423 lamps installed, of which 407 are fluorescent lamps and 16 are incandescent lamps. These quantities of lamps have been assumed for 2010 when it is a new building. A site visit to the library in 2020 revealed that there were a total of 338 working lights, of which 326 are fluorescent lights and 12 are incandescent lights. For the calculation of LED lighting energy consumption, it was assumed that the same number of lamps were replaced so that the library building has 407 T8 LED tubes and 16 LED bulbs in 2010 and 338 tubes T8 LED and 12 LED bulbs in 2020. The annual energy consumption of artificial lighting (fluorescent and incandescent) and LED have been projected for 2030, 2040 and 2050, assuming that they have the same percentage decrease as between 2010 and 2020 (i.e. 20.7%). For the calculation of the energy consumption of artificial and natural (or mixed) lighting, a 14%^{24} energy savings related to artificial lighting in the library building were counted in 2010, 2020, 2030, 2040 and 2050.

Then, the calculated annual energy consumption for different lighting systems was applied to the derived correlation shown in Fig. 2a to get the corresponding BEI values for the library with different lighting systems. With known BEI, the annual CO_{2} emissions from different lighting systems can be estimated using the derived correlation shown in Fig. 2b. The energy consumption and decarbonization pathway of different lighting systems for a library in Brunei Darussalam was compared to commercial buildings in the region. The annual electricity costs for the various lighting systems in the library building were calculated using the equation. (5) for 2010 and projected until 2050, assuming an annual increase in the price of electricity of 5%. The result was compared to the annual cost of electricity for lighting a library in the region. Finally, the calculated and estimated CO_{2} the emissions and annual cost of electricity for lighting a library building in Brunei Darussalam were compared to assess the accuracy of the correlations proposed in this study.