SMART CITY NARRATIVES – WORKING PAPER 3 Decarbonising Public Transport in Hong Kong
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SMART CITY NARRATIVES – WORKING PAPER 3 Decarbonising Public Transport in Hong Kong John Ure For the Inter-Modal Transport Data Sharing Programme January 2021 Table of Contents A. The Environment .......................................................................................................... 2 The Scope of the Problem and of the Solution ........................................................................... 2 Health Costs and Benefits ......................................................................................................... 3 B: Decarbonising Public Transport in Hong Kong ............................................................... 5 1. Taxis ................................................................................................................................. 5 2. Ferries .............................................................................................................................. 7 3. Trams and Trolley Buses .................................................................................................... 8 4. Public Light Buses (PLBs) ................................................................................................. 10 5. Franchised Single and Double-Decker Buses .................................................................... 12 5.1. Battery Electric Buses (BEBs) ................................................................................................................ 13 5.2. Recharging/Refuelling Infrastructure ................................................................................................... 15 Batteries and Recharging ............................................................................................................................. 15 Business models ........................................................................................................................................... 16 Hydrogen Fuel Cells ...................................................................................................................................... 17 Fuel Cells versus Batteries ............................................................................................................................ 17 6. Walking .......................................................................................................................... 19 Connectivity ................................................................................................................................................. 20 7. Cycling ............................................................................................................................ 23 Annex A: Electricity or Fuel Cells ..................................................................................... 26 Annex B: Central Estimates of Life-Time Cycle Cost Estimates .......................................... 27 Annex C: Batteries .......................................................................................................... 34 Annex D: An ITF Model for Urban Passenger Transport ................................................... 36 1 Smart City Narratives A. The Environment This section of the Report deals with ways in which the Data Trust model can assist in public policy making for decarbonising public transport using the Exchange Square PTI Proof-of-Concept model. The first step is to understand the scope of the problem and the nature of challenge. The second step is to make simplifying assumptions for the purposes of the initial analytics and/or obtain better detailed data on emission levels per vehicle/km. The Scope of the Problem and of the Solution Smart cities do not prematurely kill their citizens through poor air quality, and in large numbers. Given that air pollution contributes to global warming and to climate change smart cities take effective preventative measures and those that don’t are not smart. The solutions in part lie in the development and application of new and innovative ‘green’ technologies and in part in the will to use them effectively by understanding their social impact and the costs and the benefits involved. Premature deaths and the loss of work time and of productivity cost societies significantly in both human and dollar terms – the so-called Value of Statistical Life or VOSL – and minimising these costs constitute the immediate benefits, while the longer term benefit is the prevention and reversal of global warming. On the other side of the equation are the dollar costs of adopting the preventive measures, for example, in the case of public service vehicles such as buses, ferries, taxis and trams, the dollar costs of replacing motorised vehicles driven by internal combustion engines with electric vehicles driven by battery or fuel cells plus the building a recharging/refuelling infrastructure. But e-vehicles (EVs) and other applications such as digital technologies that consumes electricity, driven by batteries or by hydrogen fuel cells – hydrogen being the most common element on the planet – come at several costs. The major cost is their generation. Power stations mostly exude carbon; hydrogen extraction exudes methane, both greenhouse gases (GHG). Electricity generation is estimated to be the largest single source of carbon (67%) in Hong Kong.1 Another growing cost is the disposal of toxic waste from spent batteries and components of digital devices – there are more microchips in a family car than onboard the first space craft to the moon. It is not in the scope of this Report to examine the challenges of power generation, but to note that they are relevant to the pace of adoption of pure EVs as internal combustion engines (ICEs) and hybrid vehicles are phased out. The practical options seem to be twofold: (i) ) phase out ICEs gradually by introducing more hybrids until such time as all ICEs can be eliminated; (ii) phase out all vehicles driven by ICEs as soon as they can be replaced by EVs irrespective of cost. The former policy option is driven by two considerations. First, EVs remain in their development stage, the recharging infrastructure has still to be built, and heavy vehicles such as double-decker buses which need regularly recharging to complete their schedules may not be technically or commercially available until the mid-2020s. Second, it has been suggested that since EVs raise the demand for electricity their introduction together with tackling the issue of power generation should be synchronised because as one source of pollution falls 1 Council for Sustainable Development (2020) Report on Public Engagement on Long-term Decarbonisation Strategy https://www.susdev.org.hk/download/report/council_report_e.pdf 2 another may increase. However, while a shift to EVs in general will raise the demand for electricity generation, the methods of tackling the problems of power generation are independent of the ways in which power is used, while the impact of roadside pollution is so immediate on pedestrian health it needs to be prioritised. This shifts the balance of argument to the second policy preference, but inevitably subject to the availability of funds which for public transport implies some level of subsidy. The cost-benefit analysis follows below. Meanwhile, if an immediate or a very short term wholesale shift to EVs is not practical, a move to hybrid vehicles can at least achieve some instant reduction in tailpipe emissions. Health Costs and Benefits The following paragraphs estimate the health costs of pollution arising from the over 6,000 franchised public buses in Hong Kong. Health costs are typically counted as the Value of Statistical Life (VOSL) attributed to premature deaths arising from pollutants together with the costs associated with visits to doctors, time spent in hospitals with respiratory diseases associated with pollution, and the resulting loss of productivity. The difficulty is there have been two major studies in Hong Kong over recent years (2011 and 2016) of the Health Impact Assessment (HIA) and the Economic Impact Assessment (EIA) of pollutants, one by the School of Public Health, the University of Hong Kong (HKU) published in the Open Epidemiology Journal (2011) 2 and one from the School of Health and Primary Care, Chinese University of Hong Kong (CUHK) and posted on the website of the Environmental Protection Department (2016),3 and they come to widely differing estimates of the EIA. Using the CUHK model, this Report arrives (see below) at an estimate annual health cost of HKD800 million, but the cost would be considerably less using the HKU model. At the centre of the analysis is an estimation of the RR (Relative Risk) to a baseline level of pollutants. The base line is typically that of the World Health Organisation (WHO) of 10μm/m3 for 3 PM2.5 and 40μm/m for NO2. In the case of Hong Kong, the levels used in the CUHK 2016 study were 3 3 28.6μm/m for PM2.5 and 52.7μm/m for NO2. The difference between the two levels is referred to as the attributable fraction. According to the CUHK model using 42,000 total deaths recorded in 2012, the estimated number of premature (preventable) deaths was 6,308 and the total health costs came to a staggering HKD99.55 billion.4 But the question is how much of the total arose from franchised public bus and public light bus (PLB) emissions. An estimate of the source of these pollutants in 2007 was 53% from Hong Kong and the rest from outside the territory.5 Using this estimate In the absence of more up-to-date data, the total cost due to local pollution