It is commonly accepted that the concentration of people in high-density urban city centers, which are typically dominated by medium- and high-rise buildings located close to public transit systems, offers greater overall energy efficiency and lower life-cycle greenhouse gas emissions than lower-density expanded suburbs, which are dominated by low-rise single-family buildings and larger per-person automobile travel requirements. However, few studies have combined quantitative analyses of the life-cycle energy use of both buildings and transportation in both urban and suburban areas, especially in American cities. This work uses a variety of data sources to provide a quantitative comparison of the life-cycle energy consumption associated with residential life (including buildings, transportation, and supporting infrastructure) in prototypical downtown high-rises and suburban low-rises in and around Chicago, IL. We estimate that downtown high-rise living in Chicago, IL accounts for approximately 25% more life-cycle energy per person per year than suburban low-rise living, on average, contrary to some common beliefs (best estimates were ~141 and ~113 GJ/person/year, respectively). Building operational energy use was found to be the largest contributor of the total life-cycle energy in both the downtown high-rise and suburban low-rise cases, followed by vehicle operational energy.

There has been a long-standing debate about whether urban living is more or less sustainable than suburban living, and quality of life (QoL) is one of several key measures of the social sustainability of residential living. However, to our knowledge, no study to date has examined life satisfaction among residents of downtown high-rise living compared to residents living in suburban low-rise housing. Further, very few studies have utilized building or neighborhood-scale data sets to evaluate residents’ life satisfaction, and even fewer have controlled for both individual and household-level variables such as gender, age, household size, annual income, and length of residence, to evaluate residents’ life satisfaction across different living scenarios. Therefore, the goal of this study was to investigate residents’ satisfaction with their place of residence as well as overall life in general via surveys of individuals living in existing high-rise residential buildings in downtown Chicago, IL, and in existing low-rise residential buildings in suburban Oak Park, IL. Over 1500 individuals were contacted directly, resulting in over 500 responses. The number of fully completed responses for this study was 177, including 94 from residents of four downtown high-rise buildings and 83 from residents in suburban low-rise homes. Residents living in downtown high-rise buildings had significantly higher life satisfaction scores than residents living in suburban low-rise homes when controlling for demographic differences; however, the differences were small, as housing type explained less than 5% of the observed variance in life satisfaction outcomes. The research also evaluated five life satisfaction domains including travel, accessibility, social interaction, safety, and overall residential environment (ORE). In all cases, residents of the downtown high-rises reported higher satisfaction levels, although the scores on all these five satisfaction domains reported from both urban scenarios were very high. Moreover, all five satisfaction domains were highly associated with each other, and accessibility and safety were found as the strongest predictors of ORE for individuals.

It is widely accepted that the concentration of people living in high-density city centers offers greater operational energy efficiency and lower greenhouse gas emissions than lower-density expanded suburbs. The prevailing assumption is that lower-density suburbs are dominated by larger low-rise buildings that have higher building energy use requirements and greater per-person automobile travel requirements than high-density city centers dominated by medium- and high-rise buildings located in close proximity to a variety of public transit systems. However, very few studies to date have utilized empirical data at an individual household scale to evaluate differences in the operational energy (OE) footprints for both building and transportation energy end-uses between high-rise urban and low-rise suburban households. Therefore, this work collects empirical data on building and transportation OE consumption by individuals and households living in two economically similar groups: existing high-rise residential buildings in downtown Chicago, IL, USA and existing low-rise residential buildings in suburban Oak Park, IL, USA. Data were collected from over 500 households via an online survey. We considered the following components of residential living: (1) building OE (BOE), which includes electricity and/or natural gas use for all building energy end-uses; and (2) transportation OE (TOE), which includes the OE for multiple modes of transportation (i.e., automobile, bus, subway, regional train, etc.) based on average travel behavior in each location, as well as the OE for supporting transportation infrastructure. We estimate that downtown high-rise living in this sample of residences in Chicago, IL accounts for approximately 427 GJ of primary OE per household per year, on average, which was 14% lower than the average for suburban low-rise living in the Oak Park, IL homes (499 GJ per household per year). However, on a per-person basis, downtown high-rise living accounts for approximately 246 GJ of primary OE per person per year, which was approximately 61% higher than suburban low-rise living (153 GJ per person per year). In both building types, building OE was the single largest contributor to total OE use. This study accurately captured the energy requirements associated with realistic behaviors and lifestyles of occupants of both low-rise suburban and high-rise urban households, and found that building OE dominates the total OE, which suggests that efforts to reduce building OE should be given high priority in building design and management as well as urban planning.

Mixed-use high-rise buildings are vertical superpositions of various business types in the category of mixed-use development. It has become a highly intensive organizational form in the urban high-density environment. Under China’s “height limit” policy, the simple superposition of business types does not meet the government requirements for planning, construction, and management, and does not fully utilize the advantages of the mixed development mode. The single utilization rate index used in the past could not accurately describe such buildings’ usage value and spatial variation characteristics. In this study, a quantitative analysis of data from eight construction projects was carried out, and a utilization rate index system was established at three levels, namely, the typical floor utilization rate k₁, business utilization rate k₂, and building utilization rate k₃. In terms of k₁, the emphasis was placed on the design elements of the mixed-use development and the variation of relative indicators. In k₂ and k₃, it was found that the business type, floor area, and utilization rate were negatively correlated. In conclusion, by establishing a hierarchical utilization rate calculation method, the efficiency values and design characteristics of mixed-use high-rise (MUHR) buildings were explored, which provide references for the future design of such buildings.

The urban design process is complex and interdisciplinary, especially in the context of high-density cities with high-rise buildings. The design of high-rise buildings requires input from a variety of stakeholders in the city, who often represent conflicting requirements and interests. However, conventional design approaches struggle to address this complexity. This study introduced a generative urban design approach and applied it to a case study for high-rise urban development in Guangzhou, China. Specifically, 7500 urban forms were generated with variables such as street networks, block offset, building typology, and green space, and then were evaluated and optimized via multi-objective evolutionary algorithms. A total of 30,000 performance values were generated through various simulations. This study also presented a two-round, quantitative evaluation process against eight performance objectives from environmental, social, and economic aspects, including urban density, green space area, Daylight Potential, construction cost, Heat Stress, Green Space Accessibility, View Interest, and Shadow Impact.