{"title":"绘制重型车辆的氢需求:一种空间分解方法","authors":"Warsini Handayani, Xuan Zhu, Fang Lee Cooke","doi":"10.1186/s42162-025-00550-4","DOIUrl":null,"url":null,"abstract":"<div><p>Hydrogen is the key to decarbonising heavy-duty transport. Understanding the distribution of hydrogen demand is crucial for effective planning and development of infrastructure. However, current data on future hydrogen demand is often coarse and aggregated, limiting its utility for detailed analysis and decision-making. This study developed a spatial disaggregation approach to estimating hydrogen demand for heavy-duty trucks and mapping the spatial distribution of hydrogen demand across multiple scales in Australia. By integrating spatial datasets with economic factors, market penetration rates, and technical specifications of hydrogen fuel cell vehicles, the approach disaggregates the projected demand into specific demand centres, allowing for the mapping of regional hydrogen demand patterns and the identification of key centres of hydrogen demand based on heavy-duty truck traffic flow projections under different scenarios. This approach was applied to Australia, and the findings offered valuable insights that can help policymakers and stakeholders plan and develop hydrogen infrastructure, such as optimising hydrogen refuelling station locations, and support the transition to a low-carbon, heavy-duty transport sector.</p></div>","PeriodicalId":538,"journal":{"name":"Energy Informatics","volume":"8 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2025-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://energyinformatics.springeropen.com/counter/pdf/10.1186/s42162-025-00550-4","citationCount":"0","resultStr":"{\"title\":\"Mapping hydrogen demand for heavy-duty vehicles: a spatial disaggregation approach\",\"authors\":\"Warsini Handayani, Xuan Zhu, Fang Lee Cooke\",\"doi\":\"10.1186/s42162-025-00550-4\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Hydrogen is the key to decarbonising heavy-duty transport. Understanding the distribution of hydrogen demand is crucial for effective planning and development of infrastructure. However, current data on future hydrogen demand is often coarse and aggregated, limiting its utility for detailed analysis and decision-making. This study developed a spatial disaggregation approach to estimating hydrogen demand for heavy-duty trucks and mapping the spatial distribution of hydrogen demand across multiple scales in Australia. By integrating spatial datasets with economic factors, market penetration rates, and technical specifications of hydrogen fuel cell vehicles, the approach disaggregates the projected demand into specific demand centres, allowing for the mapping of regional hydrogen demand patterns and the identification of key centres of hydrogen demand based on heavy-duty truck traffic flow projections under different scenarios. This approach was applied to Australia, and the findings offered valuable insights that can help policymakers and stakeholders plan and develop hydrogen infrastructure, such as optimising hydrogen refuelling station locations, and support the transition to a low-carbon, heavy-duty transport sector.</p></div>\",\"PeriodicalId\":538,\"journal\":{\"name\":\"Energy Informatics\",\"volume\":\"8 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2025-07-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://energyinformatics.springeropen.com/counter/pdf/10.1186/s42162-025-00550-4\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Energy Informatics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://link.springer.com/article/10.1186/s42162-025-00550-4\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"Energy\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Energy Informatics","FirstCategoryId":"1085","ListUrlMain":"https://link.springer.com/article/10.1186/s42162-025-00550-4","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"Energy","Score":null,"Total":0}
Mapping hydrogen demand for heavy-duty vehicles: a spatial disaggregation approach
Hydrogen is the key to decarbonising heavy-duty transport. Understanding the distribution of hydrogen demand is crucial for effective planning and development of infrastructure. However, current data on future hydrogen demand is often coarse and aggregated, limiting its utility for detailed analysis and decision-making. This study developed a spatial disaggregation approach to estimating hydrogen demand for heavy-duty trucks and mapping the spatial distribution of hydrogen demand across multiple scales in Australia. By integrating spatial datasets with economic factors, market penetration rates, and technical specifications of hydrogen fuel cell vehicles, the approach disaggregates the projected demand into specific demand centres, allowing for the mapping of regional hydrogen demand patterns and the identification of key centres of hydrogen demand based on heavy-duty truck traffic flow projections under different scenarios. This approach was applied to Australia, and the findings offered valuable insights that can help policymakers and stakeholders plan and develop hydrogen infrastructure, such as optimising hydrogen refuelling station locations, and support the transition to a low-carbon, heavy-duty transport sector.