[et_pb_section fb_built=”1″ admin_label=”section” _builder_version=”3.22″ custom_padding=”0px||0px|||”][et_pb_row column_structure=”2_3,1_3″ admin_label=”row” _builder_version=”4.2.2″ background_size=”initial” background_position=”top_left” background_repeat=”repeat” width=”100%” custom_padding=”0px||0px|||”][et_pb_column type=”2_3″ _builder_version=”3.25″ custom_padding=”|||” custom_padding__hover=”|||”][et_pb_text admin_label=”Text” _builder_version=”4.2.2″ background_size=”initial” background_position=”top_left” background_repeat=”repeat” custom_margin=”-60px||||false|false” custom_padding=”1px|||||”]<\/p>\n
Keywords:\u00a0<\/span><\/strong><\/span>Transport; Decarbonisation; Pathways; Scenarios; Strategies<\/p>\n [\/et_pb_text][et_pb_text admin_label=”Text” _builder_version=”3.27.4″ background_size=”initial” background_position=”top_left” background_repeat=”repeat” custom_padding=”0px|||||”]<\/p>\n The study assessed outputs from the NISMOD transport model to investigate the effects of population change on travel demand, and the subsequent <\/b>impact<\/b><\/span>\u00a0of different sets of options, or \u2018Pathways\u2019, to help achieve the zero-carbon target for transport in England’s Economic Heartland by 2050.<\/b><\/span><\/p>\n One of the main ambitions set out in England\u2019s Economic Heartland\u2019s (EEH) Transport Strategy is for the region\u2019s transport system to be \u2018net-zero carbon\u2019 by 2050, implying a substantial change in the vehicle fleet towards zero-emission vehicles, coupled with technological solutions to improve both vehicle efficiencies and the use of the road and rail networks, and promoting behaviour change of drivers and passengers to reduce the number and nature of motorised trips in the region. Using outputs from the NISMOD Transport model, this research assessed a range of different approaches to reach this challenging target, by considering alternative \u2018Pathways to Decarbonisation\u2019, each of which focuses on a specific approach to change the way that people travel in the future.<\/p>\n EEH has provided data on planned housing developments for each local authority in the region, suggesting that housing growth is predicted to be 27,660 new houses per year, resulting in a total of around 885,000 new houses between 2020 and 2050. Combining these estimated housing figures with projected changes in household occupancy levels, we can generate the EEH future population growth scenario, which projects an extra 1.7 million residents of EEH in 2050, which is around 0.4% per year higher than ONS projections, and much more intensively and variably distributed (see Figure 1).<\/p>\n [\/et_pb_text][et_pb_blurb image=”data:image\/svg+xml;base64,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” _builder_version=”4.2.2″]<\/p>\n Figure 1:<\/strong> Population change comparison between EEH scenario and ONS population projections.<\/p>\n [\/et_pb_blurb][et_pb_text admin_label=”Text” _builder_version=”3.27.4″ background_size=”initial” background_position=”top_left” background_repeat=”repeat” custom_padding=”0px|||||”]<\/p>\n For all Pathways (except BaU) we assume that 100% of motor vehicle traffic in 2050 is made up of zero-carbon vehicles, and that there are differences in the rapidity and nature of technological change, vehicle efficiencies and network capacity utilisation via autonomous vehicles, depending on the Pathway. The Pathways assessed are as follows:<\/p>\n The differences between the Pathways for the rate of change of fuel types in cars are shown in Figure 2.<\/p>\n [\/et_pb_text][et_pb_blurb image=”data:image\/svg+xml;base64,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” _builder_version=”4.2.2″]<\/p>\n Figure 2:<\/strong> Proportion of car engine types for all Pathways.<\/p>\n [\/et_pb_blurb][et_pb_text admin_label=”Text” _builder_version=”3.27.4″ background_size=”initial” background_position=”top_left” background_repeat=”repeat” custom_padding=”0px|||||”]<\/p>\n Here, we present some of the results for emissions and congestion.<\/p>\n Emissions<\/span><\/em><\/strong><\/p>\n The total CO2<\/sub> tailpipe emissions for the region are shown in Figure 3. The rate of decline is linked with the assumed levels of electric, hybrid and hydrogen fuel cell powered vehicles in the fleet, as well as fuel efficiencies, and as we assume that all vehicles in non-BaU Pathways are zero emission by 2050, there are no emissions in 2050 for these Pathways. Note that there is a steady reduction in CO2<\/sub> for BaU as vehicles become more fuel efficient and more electric vehicles enter the fleet.<\/p>\n The differences between the other Pathways are generally related to vehicle kilometres, although emissions drop off more rapidly for the Adapted Fleet Pathway, in which fuel efficiencies are improved more quickly, and there is a slightly more rapid conversion to zero-emitting vehicles.<\/p>\n [\/et_pb_text][et_pb_blurb image=”data:image\/svg+xml;base64,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” _builder_version=”4.2.2″]<\/p>\n Figure 3:<\/strong> CO2<\/sub> emissions in EEH by Pathway and year.<\/p>\n [\/et_pb_blurb][et_pb_text admin_label=”Text” _builder_version=”3.27.4″ background_size=”initial” background_position=”top_left” background_repeat=”repeat” custom_padding=”0px|||||”]<\/p>\n Congestion<\/em><\/strong><\/span><\/p>\n The transport model is able to produce average hourly estimates of link travel times and speeds, which can be compared with free-flowing traffic to give a representation of the levels of congestion within the network. Figure 4 shows the daily profile of average speeds in the EEH road network.<\/p>\n [\/et_pb_text][et_pb_blurb image=”data:image\/svg+xml;base64,PHN2ZyB3aWR0aD0iMTA4MCIgaGVpZ2h0PSI1NDAiIHZpZXdCb3g9IjAgMCAxMDgwIDU0MCIgeG1sbnM9Imh0dHA6Ly93d3cudzMub3JnLzIwMDAvc3ZnIj4KICAgIDxnIGZpbGw9Im5vbmUiIGZpbGwtcnVsZT0iZXZlbm9kZCI+CiAgICAgICAgPHBhdGggZmlsbD0iI0VCRUJFQiIgZD0iTTAgMGgxMDgwdjU0MEgweiIvPgogICAgICAgIDxwYXRoIGQ9Ik00NDUuNjQ5IDU0MGgtOTguOTk1TDE0NC42NDkgMzM3Ljk5NSAwIDQ4Mi42NDR2LTk4Ljk5NWwxMTYuMzY1LTExNi4zNjVjMTUuNjItMTUuNjIgNDAuOTQ3LTE1LjYyIDU2LjU2OCAwTDQ0NS42NSA1NDB6IiBmaWxsLW9wYWNpdHk9Ii4xIiBmaWxsPSIjMDAwIiBmaWxsLXJ1bGU9Im5vbnplcm8iLz4KICAgICAgICA8Y2lyY2xlIGZpbGwtb3BhY2l0eT0iLjA1IiBmaWxsPSIjMDAwIiBjeD0iMzMxIiBjeT0iMTQ4IiByPSI3MCIvPgogICAgICAgIDxwYXRoIGQ9Ik0xMDgwIDM3OXYxMTMuMTM3TDcyOC4xNjIgMTQwLjMgMzI4LjQ2MiA1NDBIMjE1LjMyNEw2OTkuODc4IDU1LjQ0NmMxNS42Mi0xNS42MiA0MC45NDgtMTUuNjIgNTYuNTY4IDBMMTA4MCAzNzl6IiBmaWxsLW9wYWNpdHk9Ii4yIiBmaWxsPSIjMDAwIiBmaWxsLXJ1bGU9Im5vbnplcm8iLz4KICAgIDwvZz4KPC9zdmc+Cg==” _builder_version=”4.2.2″]<\/p>\n Figure 4:<\/strong> Average traffic speeds in the EEH road network, by Pathway.<\/p>\n [\/et_pb_blurb][et_pb_text admin_label=”Text” _builder_version=”3.27.4″ background_size=”initial” background_position=”top_left” background_repeat=”repeat” custom_padding=”0px|||||”]<\/p>\n Compared with the 2015 baseline, the increased levels of traffic result in a generally slower network for all Pathways in 2050, with the morning peak average speed reduced to around 63 kph compared to around 80 kph in 2015. The effect of fewer vehicle kilometres in the Behaviour Shift (policy-led) Pathway can be seen, since the average speeds are slightly higher in 2050 compared with the other Pathways with higher traffic flows.<\/span>\u00a0<\/strong><\/p>\n The Pathways assessed in this study offer distinct approaches to achieving zero-carbon transport by 2050. There are inevitably overlaps between these Pathways. For instance, the impact of increasingly sophisticated interactions between vehicles, transport network, homes and businesses is likely to be a strong driver of change in all possible futures, and we consider it explicitly in Behaviour Shift (policy-led) and Highly Connected Pathways.<\/p>\n The measures and interventions contributing to each Pathway change travel demand. Road pricing measures help to reduce demand, while our assumptions regarding autonomous vehicles provide higher road capacities, so more vehicles can use the same road network, resulting in higher flows. Population growth adds continuing pressure to the transport network, and levels of congestion are expected to increase as population grows.<\/p>\n We have shown that delivering a zero-carbon transport system by 2050 is a challenging target. Measures to change travel behaviour, through increased costs or promoting of sustainable transport modes could help reduce the overall demand on the transport network, but it will require significant effort through governance, legislation and public will to effect such large scale changes.\u00a0<\/p>\n Contributing to the evidence-base for EEH\u2019s Transport Strategy developed during 2020.<\/p>\n [\/et_pb_text][\/et_pb_column][et_pb_column type=”1_3″ _builder_version=”3.25″ custom_padding=”|||” custom_padding__hover=”|||”][et_pb_blurb use_icon=”on” font_icon=”%%165%%” icon_color=”#006f74″ use_circle=”on” circle_color=”#ffffff” icon_placement=”left” _builder_version=”4.2.2″ background_color=”#006f74″ background_layout=”dark” custom_padding=”30px|30px|30px|30px|true|true”]<\/p>\n Institutions:<\/b><\/span><\/p>\n University of Southampton, University of Oxford, England\u2019s Economic Heartland<\/p>\n [\/et_pb_blurb][\/et_pb_column][\/et_pb_row][\/et_pb_section]<\/p>\n","protected":false},"excerpt":{"rendered":" The study assessed outputs from the NISMOD transport model to investigate the effects of population change on travel demand, and the subsequent impact of different sets of options, or \u2018Pathways\u2019, to help achieve the zero-carbon target for transport in England\u2019s Economic Heartland by 2050.<\/p>\n","protected":false},"featured_media":37412,"template":"","meta":{"_et_pb_use_builder":"on","_et_pb_old_content":"","_et_gb_content_width":""},"categories":[88],"areas":[45],"class_list":["post-38228","casestudies","type-casestudies","status-publish","has-post-thumbnail","hentry","category-use-cases","areas-transport"],"_links":{"self":[{"href":"https:\/\/www.itrc.org.uk\/wp-json\/wp\/v2\/casestudies\/38228","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.itrc.org.uk\/wp-json\/wp\/v2\/casestudies"}],"about":[{"href":"https:\/\/www.itrc.org.uk\/wp-json\/wp\/v2\/types\/casestudies"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.itrc.org.uk\/wp-json\/wp\/v2\/media\/37412"}],"wp:attachment":[{"href":"https:\/\/www.itrc.org.uk\/wp-json\/wp\/v2\/media?parent=38228"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.itrc.org.uk\/wp-json\/wp\/v2\/categories?post=38228"},{"taxonomy":"areas","embeddable":true,"href":"https:\/\/www.itrc.org.uk\/wp-json\/wp\/v2\/areas?post=38228"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}Research question & scope<\/strong><\/span><\/h4>\n
Methodology<\/strong><\/span><\/h4>\n
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Results <\/strong><\/span><\/h4>\n
Key findings<\/strong><\/span><\/h4>\n
Impact<\/strong><\/span><\/h4>\n