Building Floor Space Research Articles

Has the provincial-level residential building sector reached the carbon peak? An integrated assessment model

Assessing the historical peak situation at the provincial level is critical to better predict the future evolution of residential building carbon emissions. However, the provincial carbon peak status of this sector is still unclear. To this end, this study proposes a carbon peak situation integrated assessment model (CPSIAM), which is utilized to comprehensively evaluate the provincial peak situation of total carbon emissions, carbon emissions per capita and carbon emissions per floor space of urban and rural residential buildings and figure out carbon peaking progress in each province. Then, the driving mechanism of differentiated carbon peak status of provincial residential building carbon emissions are examined using the panel STIRPAT model and group regression model. Results show that as for the three residential building carbon emission indicators, Heilongjiang and Shanghai have both reached their full peaks as of 2020, however the former is in passive decline and the latter is in an active peak. Population, population structure, and floor space per capita are the main variables causing the differentiated peak status. This study not only offers a general methodological system for assessing the regional carbon peak situation, but also empowers policymakers to develop effective and differentiated emission-reduction measures based on their knowledge of peaked regions.

A case study of the impact of regional knowledge services and management on regional economic development

Background. Knowledge can give an important contribution to local economic development, but the correlation between library activities and local economic development has not been clarified yet. The purpose of this investigation is to discuss the correlations between library output measures and regional economic measures.Methodology. The raw data obtained via the website of the National Bureau of Statistics of China have been analyzed by correlation coefficient calculations and multivariate regressions. Results and discussion. It was found that there are significant positive correlations between the data of the regional public libraries such as the collections of public libraries owned per person, the total number of circulation of public libraries, the Number of Seats of Reading Room in Public Libraries, the Floor Space of Buildings of Public Libraries Owned per 10000 Population, the Number of Lectures in Public Libraries and the data of their economic development. Linear relationships between library activities and the gross regional product of the five provinces in China and one of China’s direct-controlled municipalities were observed after multivariate regressions were performed on the data.Conclusions. It can be concluded that economic development can benefit the development of libraries, and better education or a more educated population has resulted in more library use. The correlation analysis and multivariate regression analysis can be developed as a new way to measure the societal value of public libraries orientated for economic development or other targets.

Timetable and roadmap for achieving carbon peak and carbon neutrality of China's building sector

Carbon mitigation effectiveness in the building sector profoundly determines the achievement of the “Dual carbon” target. However, the timetable and roadmap for the building sector to achieve such a target are still lacking. This study constructs a STIRPAT-PLS model framework to clarify the impact of the key factors from various dimensions on building carbon emissions across sub-sectors. Then, a dynamic scenario simulation model is established and applied in China to explore the dynamic evolutionary paths, and the timetable and roadmap are ultimately formulated. The results show that building sector will probably peak at 2.99 (± 0.09) Gt CO2 in 2036 (± 1). Rural residential buildings will peak earliest in 2026 (± 1), followed by urban residential and commercial buildings: in 2036 (± 2) and 2038 (± 1). Achieving carbon neutrality will require the building sector to peak its carbon emissions in 2026 with 2.16–2.40 Gt CO2. The remaining 0.56–0.81 Gt CO2 by 2060 will be offset by negative carbon technologies. Dynamic sensitivity analysis shows that building floor space per capita and energy intensity significantly promote the emission peaks, and population and building floor space per capita markedly impact the peaking times. This study can promote the development of the theory and model for carbon emissions prediction. It can also offer a scientific basis for governments to set effective carbon-reduction targets and paths.

A Fast Method for Identifying Room Configurations from Unit Boundaries in Existing Residential Buildings

Prediction of interior room layout from observations on the exterior boundaries of a unit is sometimes needed in cases of emergencies when unit entry is denied. Seeing that 3D laser scanners are becoming smaller, lighter, and easier to carry around, this paper attempts to offer a fast method that can automatically reconstruct a room model relying merely on the 3D point cloud of the unit boundaries. The method first partitions the building floor space to generate the so-called “room seeds” from the intersections of lines that are extended from the detected wall segments. Then, the grammar approach compares different possible room configurations through a trial-and-error process to find the most possible one. The proposed method is tested on a real residential building case for validation. The proposed method may be useful in emergent cases when exact floor plans are not available. The method can be extended to other Manhattan-type buildings as long as the grammar rules are settled.

Spatiotemporal patterns and driving mechanism of carbon emissions in China's urban residential building sector

Revealing the regional differences and drivers of provincial urban residential building sector carbon emissions (URBCE) is critical for regional collaborative emission reduction in achieving the “Dural carbon” targets. This study tries to innovatively construct a framework for the exploration of the spatiotemporal patterns and driving mechanism of Chinese URBCE in 30 provinces during 2000–2019, combining kernel density estimation, spatial autocorrelation analysis and temporal-spatial LMDI model. Results indicate that: (1) A vast majority of regions have undergone a sharp growth in URBCE, with the regional gap of URBCE gradually widening. (2) Besides, the spatial pattern of regional URBCE is basically stable, with High-High distributed in the Northeast and North China, and Low-Low concentrated in the Southwest. (3) Urban residential building floor space per capita, population, and urbanization are promotive driving forces, while carbon intensity and energy intensity are increasingly inhibiting. This study can provide policymakers a better understanding of URBCE and help them develop regionally-specific emission reduction strategies. Additionally, it offers fresh perspective on how to research the spatiotemporal disparities of carbon emissions in other sectors and nations, and could be of international significance.

Urban Expansion Monitoring Based on the Digital Surface Model—A Case Study of the Beijing–Tianjin–Hebei Plain

Although urban expansion statistics have been widely carried out, large-scale and rapid monitoring is still worth doing in order to improve the efficiency of statistics, as well as make up for the omissions and deficiencies of construction expansion statistics with multi-year intervals. This paper presents a study of urban expansion in the Beijing–Tianjin–Hebei plain based on ALOS Global Digital Surface Model “ALOS World 3D-30 m” (AW3D30 DSM), Shuttle Radar Topography Mission (SRTM) DSM, and Landsat 7 ETM+ images. Through the evaluation of errors and the elimination of non-building changes, a relatively objective result is derived. The neighborhood block statistics of the construction height expansion reveal that from 2000 to 2009, the largest centralized construction expansion mainly occurred between the Second Ring Road and the Fifth Ring Road of Beijing, followed by Yizhuang, Shunyi, Tianjin Central City, and Langfang. Zonal statistics also show a significant imbalance in the expansion of construction in the counties of the Beijing–Tianjin–Hebei plain. For example, Chaoyang, Dongcheng, Xicheng, Xuanwu, Chongwen, Nankai, Heping, and Hexi have a larger construction expansion; however, other counties present a relatively slow rate of building expansion. Furthermore, the correlation coefficient between the statistical average building height expansion per unit area (ABHE, by our method) and the actual average completed building floor space per unit area (ACBFS) derived from the Beijing Statistical Yearbook (BSY) is 0.9436, which proves that this method is feasible. With the continuous improvement of DSM data quality in the future, the method proposed in this paper can provide rapid and large-scale statistics to study more urban construction expansion in the world.

Investigation of the Fabrication Suitability, Structural Performance, and Sustainability of Natural Fibers in Coreless Filament Winding.

Coreless filament winding is an emerging fabrication technology in the field of building construction with the potential to significantly decrease construction material consumption, while being fully automatable. Therefore, this technology could offer a solution to the increasing worldwide demand for building floor space in the next decades by optimizing and reducing the material usage. Current research focuses mainly on the design and engineering aspects while using carbon and glass fibers with epoxy resin; however, in order to move towards more sustainable structures, other fiber and resin material systems should also be assessed. This study integrates a selection of potential alternative fibers into the coreless filament winding process by adapting the fabrication equipment and process. A bio-based epoxy resin was introduced and compared to a conventional petroleum-based one. Generic coreless wound components were created for evaluating the fabrication suitability of selected alternative fibers. Four-point bending tests were performed for assessing the structural performance in relation to the sustainability of twelve alternative fibers and two resins. In this study, embodied energy and global warming potential from the literature were used as life-cycle assessment indexes to compare the material systems. Among the investigated fibers, flax showed the highest potential while bio-based resins are advisable at low fiber volume ratios.

A Comparison of Hospital Area Measurement in Germany, Canada, Australia, and the United States: Part 1.

Objectives:This article compares national standards for area measurements of healthcare facilities in four countries and examines the risks and differences that can arise when comparing building areas of healthcare facilities internationally.Background:In the planning and management of healthcare facilities, the utilization and comparison of building floor areas plays a major role. Differences in terminology, classification, and methodology help to reduce planning and cost risks when applied on a local and national level. The proper allocation of building floor space is vital in the design of room programs, determination of floor space, construction costs, and operating costs.Methods:Each of the four hospital area measurement standards is compared to discern similarities and differences.Results:Most countries use a three-tier system of hospital area measurement: building gross area, department gross area, and department net area. Few differences were found between country standards for department area, though the German standards do not fully address this tier. Variation is found in whether a country includes certain functions in the hospital area—such as research space, shell space, or central energy plants—which can have a significant impact on the overall hospital area.Conclusions:This article informs further development of individual country standards and highlights principles to consider for international hospital area comparison.

Parametric estimation of supplier's plant construction costs

Cost engineers of buying enterprises perform detailed product cost calculations of externally manufactured components. The aim of these calculations is to determine what a product should cost and to support purchasing functions in fact-based negotiations. While product cost engineers have deep knowledge in the calculation of direct cost, they need support in the calculation of supplier´s indirect cost categories. The calculation of industrial rent, which is expressed in annual cost per m² of occupied plant building floor space can be improved by providing accurate construction cost estimates. Construction costs are strongly impacting the calculation of supplier´s annual building depreciation, which is a crucial cost driver for the determination of the industrial rent. Academic literature is actually not providing an accurate and suitable cost model for product cost engineers, which is estimating construction cost per m² depending on different industrial building categories and alternative supplier plant locations. The paper aims to close this gap by applying linear regression analysis on a set of European construction cost data considering two industrial building categories: “warehouses/basic factory units” and “high-tech factories”. By regressing construction cost against construction labor rates within different supplier plant locations it was possible to form suitable and accurate parametric regression functions with R² values between 0.74 and 0.88. Next to high R² values acceptable mean average percentage errors between 7.45% and 11.77% could be realized by comparing estimated with observed construction cost. The estimation of industrial construction costs based on the paper´s results can be used to improve the calculation of industrial rent, which is one cost element, that has to be covered within product cost engineer´s Should Cost Calculations.

A Foreword from the Editor

Low-carbon and intelligent construction are two of the current research hot spots in the Architecture, Engineering, Construction, and Facilities Management (AEC/FM) field. Green building, smart city, AI, BIM, and sustainable development have become high-frequency words in the field[1]. The lack of the adoption of digital technologies (e.g., BIM, AI, digital twin) will lead to project delays, cost inefficiencies, poor quality, and tedious management[2]. Emerging innovations of those digital technologies are bringing a new evolutionary process of engineering applications towards more sustainable and intelligent development[3-4]. In October 2021, the United Nations Environment Programme (UNEP) and Global Alliance for Buildings and Construction (GlobalABC) release the heavyweight report Global Status Report on the Building and Construction Industry 2021[1]. The report states that since the signing of the Paris Agreement in 2015, CO2 emissions from the buildings and construction sector have peaked in recent years and subsequently fallen to 2007 levels in 2020. This current decline is due mostly to the COVID-19 pandemic; however, this decline appears to be temporary as emissions pick up again with increasing economic activity. Whereas transformative, long-term progress in sector decarbonizing remains limited[1]. To achieve the Paris Agreement, the global buildings and construction sector must almost completely decarbonize by 2050. Collectively, stakeholders in the sector must seize the opportunity that the COVID-19 economic recovery period offers to foster transformation for decarbonizing the sector. The sector must simultaneously meet a projected near-doubling of global demand for energy services in buildings and at least a doubling of floor space as developing economies continue to respond to the growing demand for building floor space, access to energy services and economic activities. Therefore, to meet the future needs and developments of this fast-growing field, a brand-new journal, Journal of Building Design and Environment (JBDE) has been launched. JBDE is a semi-annual, double-blind peer reviewed, open access journal, dedicated to publishing original research articles/reviews—amongst other submission categories—on the research and application of sustainability and intelligence in the field of construction engineering and design. The scope of JBDE covers (but is not limited to) the following: Civil and Infrastructure Engineering Building and Structural Design Construction Materials Built Environment Construction Engineering and Management Computer Aided-Design and Simulation Energy and Buildings Sustainable Development Urban Planningand Resilience Architectural Aesthetics and Townscape To further encourage research in this area, our publisher, Omniscient Pte. Ltd. has decided to waive article processing charge for the first two issues of the journal’s first volume. Therefore, we strongly welcome all who are interested in building design and environment research to join us authors, reviewers or editorial board members. It is the hope of the entire editorial team of JBDE that this journal will fulfil the needs of those specialising in building design and facilitate discourses and advances in the field.

Temporal changes in sectoral carbon productivity and corresponding driving factors: implications for carbon governance in Zhejiang province

Effective regulations of carbon productivity (CP) at the sectoral level offer a practical path to implement cost-effective CO2 reduction measures. To date, few studies on the temporal changes in sectoral CP have identified driving factors that can be regulated through policy interventions. We took Zhejiang Province (P.R. China) as a case study to assess the changes in CP of 41 economic sectors covering primary, secondary and tertiary industries during 2010–2017 and analyze the underlying driving factors of these changes. During the period, 31 sectors increased their CP, 12 of which decreased in energy-related CO2 emissions and increased in economic values and were potentially usable in ‘carbon peaking and carbon neutrality’ pilots. Meanwhile, 10 sectors reduced their CP, which had priority in the promotion of low-carbon technologies and implementation of transformative policies. We identified that the major contributors to the changes of sectoral CP are the factors involving electricity consumption, projects completed and put into use, water use efficiency, foreign investment and floor space of buildings. Our findings recommended improvement in the infrastructures and institutions of electricity consumption, the efficiency of the procedures for project approval, the utilization of water resources and the low-carbon investment in fixed assets on sectoral level.

Spatiotemporal Changes in Vertical Heterogeneity: High-Rise Office Building Floor Space in Sydney, Australia

Mixed-use development is increasingly popular in land use planning and zoning, fostering a combination of residential, commercial, and cultural uses into one space. However, there is a lack of understanding of the vertical mix office space within a high-rise commercial building and the dynamics of the industry mix between buildings. This paper examines the spatiotemporal patterns of industry mix between and within office buildings in Sydney CBD from 2006 to 2017, using the data obtained from the City of Sydney floor space and employment surveys. This is the first study that identifies the dynamics of an industrial ecosystem in central Sydney, which has transformed to homophily land blocks, with increasing vertically heterogeneous office buildings, over the past decade. In addition, the study found that the significant clustering of anchor tenants, such as finances, hospitalities, and knowledge-based industries, are apparent.

How does income level impact residential-building heating energy consumption? Micro-level evidence from household surveys

Soaring building heating energy consumption (BHEC), along with rising income, is threatening carbon abatement efforts. However, the influencing mechanism of income on BHEC remains unclear. This study establishes a theoretical model of the impact of income on BHEC from three perspectives: building physical characteristics, building use characteristics and energy-consuming equipment characteristics. Then, we adopt a stepwise hierarchical regression method to examine the direct and intermediary effects between income and BHEC using microdata from 662 households in Chongqing, China. The results show that household income, residential building floor space, the amount of heating equipment, building energy efficiency standards, and the heating method significantly impact BHEC. Moreover, the direct effect of income on BHEC is up to 84%. The amount of heating equipment and residential building floor space are both strong intermediaries between income and BHEC, contributing 18.8% and 15.8%, respectively. The heating method is a weak intermediary, only contributing approximately 1% of the impact. Overall, this study can promote the development of the related theory of BHEC and provide a reference for the government to implement more effective energy-efficient policies on the local scale and even on the national and global scales.

Gauging the impacts of urbanization on CO2 emissions from the construction industry: Evidence from China

The construction industry has aided rapid urbanization in China, significantly contributing to CO2 emissions. However, few studies have investigated the impacts of urbanization on CO2 emissions from the construction industry and the regional heterogeneity or considered the construction-related factors for urban construction scale to represent urbanization. To compensate for these limitations, this study aimed to explore the impacts of urbanization on CO2 emissions from the construction industry. Herein, the urban construction scale was used to represent urbanization, along with population size, economic growth, and technology level. An augmented Stochastic Impacts by Regression on Population, Affluence, and Technology model was used to estimate the cross-province panel data from three regions in China during 2008–2017. The heterogeneity due to regional differences in urbanization levels was addressed by classifying China into three regions— urbanized, urbanizing, and under-urbanized. The findings suggest that population size, economic growth, construction of residential buildings, and technology level were the primary factors impacting CO2 emissions, and the impact presented a declining trend from the urbanized to the urbanizing and under-urbanized regions. Specifically, an inverted U-shaped relationship existed between CO2 emissions and urban economic growth, and the urbanized region indicated a higher inflection point than other regions. The urbanization ratio was negatively correlated with CO2 emissions, while the energy intensity, per capita floor space of urban residential buildings, and per capita length of drainpipes were positively correlated with the CO2 emissions in all three regions. Further, the technology level was conducive to CO2 emissions reduction, however, it requires further improvement. The per capita area of paved roads exerted significantly negative effects in the urbanized region and insignificant in the urbanizing and under-urbanized regions. Overall, these results can help formulate policies to mitigate the construction industry's carbon emissions.

A New Estimate of Building Floor Space in North America

Floor space is a key variable used to understand the energy and material demands of buildings. Using recent data sets of building footprints, we employ a random forest regression model to estimate the total floor space (conditioned and unconditioned) of the North American building stock. Our estimate for total floor space in 2016 is 88033 (+15907/-21861) million m2, which is 2.9 times higher than current estimates from national statistics offices. We also show how floor space per capita (m2 cap-1) is not constant across the North American region, highlighting the heterogeneous nature of building stocks. As a critical variable in integrated assessment models to project energy and material demands, this result suggests that there is much more unconditioned floor space than previously realized. Furthermore, when estimating material stocks, flows, and associated embodied carbon emissions, total floor space per-capita estimates, such as those presented in this study, offer a more comprehensive approach in comparison to national statistics that do not capture unconditioned floor space. This result also calls for an investigation as to why there is such a vast difference between estimates of conditioned and total floor space.

Space-planning Solutions for New Type of Retail and Warehouse Buildings

Modern trade formats require changes to the typology of trade buildings. New titles and space-planning solutions emerge to build new trade and warehouse buildings. This article deals with the analysis and identification of the specific features of space-planning solutions for such buildings. A new type of public trade or warehouse building is characterized by large storage areas (70-85% of the overall area of premises), extensive product ranges, and small retail areas (up to 3-4% of the overall area). Orders and payments are made via the Internet of the digital terminals in the retail area. High (over 5.5 m) shelf and pallet storage practices are used. At warehouses, attics, panels, and built-in structures are used for storing things or as utility rooms, and seldom as office and amenity rooms. The buildings have the frame structure of metal and partially concrete.Simple room architecture and suspended sandwich panel facades make these buildings look like warehouses. The built-up area for the majority of the facilities is over 10,000-15,000 square meters. The overall building floor space is over 15,000 square meters.

What Is the Amount of China's Building Floor Space from 1996 to 2014?

The amount of building floor space (BFS) plays a key role in the energy and material demand prediction. Unfortunately, BFS estimation has faced the challenge of ineffective and inadequate approaches, and thus reliable data concerning China’s BFS is unavailable. This study proposes a new estimation method for China’s BFS and then estimates historical BFS by type in China from 1996 to 2014. The results show that total Chinese BFS grew from 28.1 billion m2 in 1996 to 61.3 billion m2 in 2014, increasing more than twice, with an annual growth rate of 4.4% from 1996 to 2014. During 1996–2014, urban residential BFS witnessed the highest annual increase rate (9.3%), while the growth rate for commercial and rural residential BFS was lower: 4.4% and 1.6%, respectively. By comparing with available statistics data, this study finds the model deviations are well below 5%, which indicates the reliability of the proposed method and robustness of the results. The proposed method not only can address the deficiencies of statistic yearbook and overcome the shortages of previous estimation approaches but also can derive more accurate and reliable data. This study lays a sound basis for the following study on building stock and building energy efficiency work.

Estimating exposure of residential assets to natural hazards in Europe using open data

Abstract. Natural hazards affect many types of tangible assets, the most valuable of which are often residential assets, comprising buildings and household contents. Yet, information necessary to derive exposure in terms of monetary value at the level of individual houses is often not available. This includes building type, size, quality, or age. In this study, we provide a universal method for estimating exposure of residential assets using only publicly available or open data. Using building footprints (polygons) from OpenStreetMap as a starting point, we utilized high-resolution elevation models of 30 European capitals and pan-European raster datasets to construct a Bayesian-network-based model that is able to predict building height. The model was then validated with a dataset of (1) buildings in Poland endangered by sea level rise, for which the number of floors is known, and (2) a sample of Dutch and German houses affected in the past by fluvial and pluvial floods, for which usable floor space area is known. Floor space of buildings is an important basis for approximating their economic value, including household contents. Here, we provide average national-level gross replacement costs of the stock of residential assets in 30 European countries, in nominal and real prices, covering the years 2000–2017. We either relied on existing estimates of the total stock of assets or made new calculations using the perpetual inventory method, which were then translated into exposure per square metre of floor space using data on countries' dwelling stocks. The study shows that the resulting standardized residential exposure values provide much better coverage and consistency compared to previous studies.

Exploring the impact of urbanization on urban building carbon emissions in China: Evidence from a provincial panel data model

Urbanization is a significant factor for soaring building carbon emissions. However, few studies have explored how the urbanization influences urban building carbon emissions. This study attempts to establish a comprehensive framework for urbanization and systematically explore the multiple effects exerted by urbanization on urban building carbon emissions from both quantity and structure dimensions based on the STIRPAT model, using the panel data of China’s 30 provinces from 2000 to 2015. Urbanization is measured from three perspectives: population, economy and space. Results show that the urban population and urban building floor space contribute negatively to the carbon emissions in the urban building sector, while the added value of the tertiary industry positively influences urban building carbon emissions in the quantity dimension. In the structure dimension, the percentage of the urban population on the total population exerts a positive impact on the increase of urban building carbon emissions, but the percentage of the tertiary industry and the plot ratio of the urban buildings play a role in cutting down urban building carbon emissions. This study provides deeper insights for the concomitant effects of urbanization on carbon emissions and can be conducive to the realization of energy conservation and carbon emission targets.

Modeling the Spatial Dimensions of Warehouse Rent Determinants: A Case Study of Seoul Metropolitan Area, South Korea

The spatial mismatch between warehouse locations and urban freight demand mainly driven by logistics sprawl can have negative environmental impacts, due to the increase in average trucking distances. This study investigated the spatial dimension of warehouse rent determinants identifying the regional specifics of supply and demand of warehouse facilities and services. Based on the case of the Seoul Metropolitan Area in South Korea, spatial autoregressive regression (SAR) and mixed geographically weighted regression (MGWR) models were developed to explain the spatial stationary and non-stationary relationship between warehouse rent and the explanatory variables, including the transactional characteristics of the rental contracts, physical characteristics of the buildings, location factors, and various warehousing services. The MGWR results identified the distance to the nearest highway interchange, repackaging service, and built-in ramps as globally fixed variables and contract floor space, total building floor space, building age, and land price as locally varying variables. The results of this study allowed us to provide meaningful insights into the sustainable development of urban logistics facilities through a better understanding of the interaction between logistics activities, transportation infrastructure, and land use.