Estimating the Reduction in GHG and Environmental Cost of Green Port Strategy at the Port of Kaohsiung – The Perspective of Terminal Operation

  • 林 禹睿

Student thesis: Master's Thesis


Global warming has gradually been a serious problem attracting the attentions of numeral international organizations and academia Greenhouse gas (GHG) emissions such as carbon dioxide (CO2) methane (CH4) sulfur oxides (SOX) nitrogen oxides (NOX) and particulates (PM2 5 and PM10) cause deteriorating global warming and air pollution and affect human health Transport sector is one of the main sources for GHG emissions The Port of Kaohsiung located in the southern of the Island is the largest port of Taiwan’s four international ports and ranks the world’s 13th largest port with 9 9 million twenty-foot equivalent units (TEUs) port cargo throughput in 2013 The environmental damage due to the emissions which are resulted from ships and harbor operations in port area cannot be ignored International ports have widely implemented lots of green port strategies which can be divided into vessel operations (e g reducing ship speeds using low sulfur fuel) and terminal operations (e g adopting alternative marine power (AMP) system using electric rubber tired gantry (RTG) and using electric truck) This study aims to evaluate the changes in GHG emissions and environmental costs using activity based method when the Port of Kaohsiung adopts green port strategies such as AMP system for berthing ships electric RTG and electric truck In order to further understand the impact of the green port strategy adoption on the reduction in GHG emissions and environmental costs four scenarios are considered in this study (i e the completion rate of the development of the green port strategies reaches 30% 50% 80% and 100% respectively) The findings of the study are summarized as follow Three green port strategies significantly reduce GHG emissions by -287 580 tons of CO2 31 64 tons of CH4 391 57 tons of PM2 5 379 45 tons of PM10 372 927 tons of SOX and 10 944 tons of NOX In particular NOX and SOX are the two largest reductions in GHG emissions Among all three green port strategies adopting AMP system reduces the largest emission of CH4 PM2 5 PM10 NOX and SOX but CO2 emission is increased Adopting electric RTG significantly reduces the emissions of CO2 NOX and SOX Adopting electric truck contributes less emission reductions in all GHG pollutants than other two strategies Nevertheless its reductions in CH4 PM2 5 and PM10 emissions are significant More CO2 emission was emitted by berthing ships when AMP system is used than when auxiliary engine is used because the majority in the energy structure of Taiwan is thermal power generation (73 2%) and thus resulting in the inefficiency of utility power generation comparing with auxiliary engine generation Among three green port strategies AMP system is the most effective strategy with contributing the value of $1 95 billion a year electric RTG contributes the value of $222 million a year but electric truck is the least effective one with only contributing the value of $175 million a year Under four scenarios it shows that when the completion rate of green port strategies is 30% it saves $704 million in the environmental cost a year and when the completion rate comes to 100% it saves $2 35 billion of environmental costs a year Finally two managerial suggestions and corresponding policy implications are provided The authority of the Port of Kaohsiung should initiate and implement incentive compatible programs to encourage terminal operators and shipping companies adopt AMP system electric RTG and electric truck for a cleaner and better port environment Next electricity emission factor in Taiwan should be gradually decreased by resolving the construction of nuclear generation and by promoting the ratio of green power with inefficient emission and environmental cost reduction of green port strategies by using utility power Moreover enterprises should be encouraged by tax credit to subscribe green power to further promote sustainably developing environment
Date of Award2015 Jul 31
Original languageEnglish
SupervisorChun-Hsiung Liao (Supervisor)

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