|Andri Mubarak||Industrial Engineering Department, Universitas Indonesia|
|Fachruddin Zainal||Global Production Engineering, Technische Universität Berlin|
Southeast Asia, as the world fastest growing market, has become the destination for multinational companies to operate their businesses. The increasing number of companies in the region will result in raised levels of CO2 emissions because of their transport and logistics activity. This paper aims to develop a CO2 emissions framework by considering the actual conditions of the region, and by calculating the level of emissions with a case study of Indonesia. Several steps were involved in the design of the framework. First, research was conducted on available frameworks which estimate CO2 emissions in logistics. Second, the model for CO2 emissions calculation was built by breaking down all the factors influencing calculations. Third, the model was applied using distribution network data of companies in Indonesia. The output of the research is a framework which helps companies to calculate CO2 emissions, and which gauges the level of such emissions generated by companies operating in Indonesia. In addition, the impact of the different distribution network scenarios on the amount of CO2 emissions produced is assessed.
CO2 emissions calculation model; Greenhouse gas emissions; Logistics in Southeast Asia; Sustainable logistics; Transport and logistics
In 2009, The World Economic Forum calculated that the transport and logistics sector was responsible for 5.5% of total emissions from human activity, at around 2,800 mega-tonnes annually (World Economic Forum, 2009). In addition, Hao et al. (2015) found that the freight transport sector was responsible for 788 mega-tonnes of emissions, which represented around 8% of national Greenhouse Gas (GHG) emissions in China in 2013. The release of GHG emissions into the atmosphere increases heat, which ultimately leads to global warming (UNEP, 2003). Additionally, Abbasi and Nilsson (2016) discuss several negative impacts of logistics activities, such as visual pollution, congestion, intimidation, vibration, injuries and accidents.
As a fast-growing market with low-cost operations, many businesses have decided to move their production plants to Southeast Asia (SEA). Rao (2002) states that the region is an exciting location for most global manufacturing companies. The main driver of this movement is the cheaper production process. By increasing the number of companies that operate in SEA, this factor also increases the level of CO2 emissions from transport and logistics activities. As Southeast Asia has become a good option for production plants, environmental issues need to be addressed to avoid severe problems in the future (Hart, 1997).
The effort to calculate CO2 emissions from companies in transport and logistics, known as a green logistics activity (Sbihi & Eglese, 2007), is a useful consideration for companies before developing the right policy for CO2 emissions reduction. Currently, frameworks, calculation tools, methodologies and reporting formats which can be used to calculate CO2 emissions can be easily accessed. The problem with these tools is the absence of a global method specific to logistics operations (Greene & Lewis, 2016).
Measuring CO2 emissions more accurately, with consideration of the actual conditions in Southeast Asia, has been one of the challenges faced by companies in the region. A holistic approach is needed in terms of CO2 emissions reduction in the logistics sector, supported by different measurements (Nilsson et al., 2013). There are several standards for CO2 emissions calculation, but none is specifically aimed at companies in Southeast Asia. Moreover, little research has been conducted on CO2 emissions calculation in transport and logistics specifically for companies in Southeast Asia, one of the few examples being recent research developed in SEA by Binh & Tuan (2016). In the other area, Padfield et al. (2011) conducted research to measure CO2 emissions for consumption and production of food in Southeast Asia specifically for the Malaysian food sector. The development of a calculation model for CO2 emissions in Southeast Asia will help local companies to achieve more accurate measurement of their impact and will represent the actual conditions found in the region. Companies can use the results of the CO2 emissions calculation when developing initiatives as part of sustainability efforts in their business operations.
In comparison to the current models of CO2 emissions calculation, the model developed in this study represents the actual conditions of the transport and logistics activity of companies in Southeast Asia by implementing a standard input adjusted to the conditions of the region. Therefore, the level of CO2 emissions generated by the model is better than in the other models. Another advantage of this model is that it can be used without high investment.
The results of the calculations indicate an increase in CO2 emissions in 2018, even though the scenario uses the same distribution network. Increasing demand will increase the number of transportation modes used, leading to higher energy consumption. Another interesting finding is the contribution of trucks to CO2 emissions. Road transportation produced more than 50% of CO2 emissions in 2018. Moreover, Indonesia consists of 13,466 islands, which shows that sea transportation plays an important role in connecting these (Central Intelligence Agency, 2017). However, the results show that sea transportation is not used optimally. Changing the use of trucks to sea transportation could be one alternative to reduce CO2 emissions.
With regard to future research, this study was developed without
considering the financial aspect, especially how initiatives in CO2
emissions reduction could have a positive impact on this. Therefore, the model
would be more effective if it identified the relationship between the financial
aspect, distribution networks and the level of CO2 emissions
Abbasi, M., Nilsson, F., 2016. Developing Environmentally Sustainable Logistics: Exploring Themes and Challenges from a Logistics Service Providers’ Perspective. Transportation Research Part D: Transport and Environment, Volume 46, pp. 273–283
Binh, N., Tuan, V., 2016. Greenhouse Gas Emission from Freight Transport-accounting for the Rice Supply Chain in Vietnam. Procedia CIRP, Volume 40, pp. 46–49
Central Intelligence Agency, 2017. The World Factbook. Available online at https:// www.cia.gov / library/ publications/ the-world-factbook/ geos/ vm.html, Accessed on September 2018
COFRET, 2011. Existing Methods and Tools for Calculation of Carbon Footprint of Transport and Logistics, DLR - Deutsches Zentrum für Luft- und Raumfahrt. Available online at http:// www.cofret-project.eu / downloads/ pdf/ COFRET_Deliverable_2.1_final.pdf, Accessed on September 1, 2017
Greene, S., Lewis, A., 2016. GLEC Framework for Logistics Emissions Methodologies. Report Global Logistics Emission Council, Smart Freight Center, Amsterdam, Netherland
Hao, H., Geng, Y., Li, W., Guo, B., 2015. Energy Consumption and GHG Emissions from China´s Freight Transport Sector: Scenarios through 2050. Energy Policy, Volume 85, pp. 94–101
Hart, S., 1997. Beyond Greening: Strategies for a Sustainable World, Harvard Business Review. Available online at http:// dnr.wi.gov / topic/ SmallBusiness/ documents/ sustainability/ BeyondGreeningStrategiesForASustainableWorld.pdf. Accessed on August 20, 2017
Mariano, E.B., Gobbo Jr, J.A., Camioto, F.d.C., Rebelatto, D.A.d.N., 2017. CO2 Emissions and Logistics Performance: A Composite Index Proposal. Journal of Cleaner Production, Volume 163, pp. 1–13
Miodrag, Z., Kaffka, J., Clausen, U., Munsel, L., Drost, S., 2016. Assessment of Emissions Caused by Logistics Handling Operations in Multimodal-terminals. Transportation Research Procedia, Volume 14, pp. 2754–2761
Nilsson, L., Khan, J., Andersson, F., Klintman, M., Hildingsson, R., Kronsell, A., Pettersson, F., Palsson, H., Smedby, N., 2013. I Ljuset av Framtiden: Styrning mot Nollutsläpp är 250 (In the Future of the Future: Control Against Emissions is 250). Lunds Universitet, Lunds, Sweden
Padfield, R., Papargyropoulou, E.Preece, C., 2017. A Preliminary Assessment of Greenhouse Gas Emission Trends in The Production and Consumption of Food in Malaysia. International Journal of Technology. Volume 3(1), pp.56–66
Rao, P., 2002. Greening the Supply Chain: A New Initiative in South East Asia. International Journal of Operations & Production Management, Volume 22(6), pp. 632–655
Sbihi, A., Eglese, R.W., 2007. Combinatorial Optimization and Green Logistics. Journal of Operation Research, Volume 5(2), pp. 99–116
Straube, F., Doch, S., 2011. A Contribution to Sustainable Logistics and Supply Chain- Conceptual Design to Evaluate Ecological and Economical Cause-Effect Relations in Logistics Planning Processes. In: Advances in Sustainable Manufacturing, Proceeding of the 8th Global Conference on Sustainable Manufacturing 2011, Abu Dhabi, 22-24 November, UAE
UNEP, 2003. How Will Global Warming Affect My World? A Simplified Guide to the IPCC´s "Climate Change 2001: Impacts, Adaptation and Vulnerability”. Available online at http:// staging.unep.org / delc/ Portals/ 119/ ipcc_wgii_guide-E.pdf. Accessed on August 23, 2017
World Economic Forum, 2009. Supply Chain Decarbonization: The role of Logistics and Transport in Reducing Supply Chain Carbon Emission. The Framework of the Logistics and Transport Partnership Programme, Geneva, Switzerland