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Article

Elevator Selection Methodology for Existing Residential Buildings Oriented Toward Living Quality Improvement

School of Architecture and Urban Planning, Beijing University of Civil Engineering and Architecture, Beijing 100044, China
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Author to whom correspondence should be addressed.
Sustainability 2025, 17(7), 3225; https://doi.org/10.3390/su17073225
Submission received: 25 February 2025 / Revised: 28 March 2025 / Accepted: 2 April 2025 / Published: 4 April 2025
(This article belongs to the Special Issue Healthy Aging and Sustainable Development Goals)

Abstract

:
With the intensification of aging populations and economic development, installing elevators in existing residential buildings has become crucial for achieving SDG 11 (Sustainable Cities and Communities). While elevator retrofits improve accessibility, they may also compromise living quality through obstructed ventilation, reduced daylighting, visual interference, and noise pollution. Despite provincial guidelines in China specifying elevator types for retrofitting, the lack of clear selection criteria complicates implementation. This study addresses the challenge of scientifically selecting elevator types that balance accessibility improvements with minimal impact on residential environments. Focusing on 50 operational elevator retrofits in eight Beijing communities employing eight half-landing elevator models from the Beijing Multi-story Residential Elevator Retrofit Guidelines, we establish a comprehensive evaluation framework integrating objective measurements (indoor ventilation, noise, daylighting, and external visibility) and subjective resident assessments. Taking Xicheng District’s Yutaoyuan Community as a case study, this research identifies the optimal elevator configuration through a multi-criteria analysis. The proposed methodology offers two key contributions: (1) a practical elevator selection system providing technical and theoretical support for nationwide retrofitting projects, and (2) a quantifiable assessment tool aligning with the 2030 Sustainable Development Agenda for urban renewal objectives.

1. Introduction

According to projections from China’s National Bureau of Statistics, the proportion of the population aged 60 and above in mainland China will reach approximately 25% by 2030, marking the nation’s transition from a “mildly aging” to a “moderately aging” society during the 14th Five-Year Plan period [1,2,3]. Home-based elderly care, as a critical strategy for addressing population aging and a key component of China’s elderly service system, remains and will continue to be the dominant form of elderly care [4,5]. Retrofitting elevators in existing multi-story residential buildings is both an essential measure for facilitating aging in place and a significant public concern prioritized by governments at all levels [6,7]. As of August 2024, 26 provinces, autonomous regions, and municipalities in China have issued official documents such as “Technical Guidelines for Elevator Retrofitting in Existing Multi-Story Residential Buildings” [8,9].
Field investigations across over 30 communities in Beijing’s Dongcheng, Xicheng, and Haidian districts either retrofitted with elevators or that are planning retrofits revealed multiple elevator model options available for identical building types. Taking Xicheng District as an example, the “Beijing Technical Guidelines for Elevator Retrofitting” (hereafter “Guidelines”) [8] issued in 2020 specify 13 commonly used elevator models (abbreviated as “Elevator n”). The elevator configurations were categorized into two types based on stopping positions: semi-level stop and level-level stop. Furthermore, the semi-level stop elevators were subdivided into eight types (Figure 1), while the level-level stop elevators were classified into five types, with classifications determined by factors including elevator shaft location, connecting corridor length, entrance door and accessible ramp positions, as well as window dimensions and placement. However, no standardized criteria exist for selecting optimal elevator types based on specific building characteristics. This ambiguity has led to issues such as excessive costs, spatial inefficiency, and reduced living quality when inappropriate models are chosen, subsequently dampening community enthusiasm for retrofits and slowing overall progress.
As a critical issue concerning people’s livelihood, domestic theoretical research on elevator retrofitting primarily focuses on installation procedures, negotiation methods, and optimization of supportive policies [10,11,12]. Practical studies in China mainly concentrate on summarizing the common patterns of residential elevator additions, proposing design rules for overall planning, architectural design, structural design, and electromechanical equipment [13,14,15]. Developed countries such as those in Europe and America have earlier adopted systematic evaluation methods in existing building retrofits. For instance, some U.S. states enforce elevator installations in multi-story residential buildings through the “Accessibility Design Standards” (ADA) and optimize solutions based on user satisfaction surveys (e.g., noise and privacy perception) [16]. Germany employs energy consumption simulations and life cycle cost analysis (LCCA) to select elevator models yet often overlooks residential quality and comfort indicators [17]. Japan introduced the “Universal Design” concept in aging community renovations, emphasizing the seamless integration of elevators with building forms, but its evaluation system prioritizes technical compliance over residents’ subjective experiences [18]. In summary, current research both domestically and internationally often segregates objective and subjective indicators, lacking a comprehensive evaluation framework that precisely aligns with residents’ living quality and in-depth qualitative and quantitative analyses of retrofitting details. This reliance on subjective preferences alone fails to comprehensively and effectively address public concerns. Therefore, it is essential to focus on currently implemented residential elevator retrofitting projects, integrating the scientific analysis of objective data with subjective questionnaires, to develop a more objective and multidimensional comprehensive selection method for existing residential elevator retrofits.

2. Comprehensive Methodology for Elevator Configuration Selection in Existing Multi-Story Residential Buildings

2.1. Experimental, Investigated, and Survey Subjects

The experimental subject refers to a building scheduled for elevator retrofitting where the proposed comprehensive elevator selection methodology (hereafter “the Methodology”) prioritizing living quality in existing residential buildings is ultimately applied and validated. Surveyed subjects are retrofitted buildings selected based on their alignment with the experimental subject’s architectural features and compatible elevator types. These buildings undergo field measurements and simulations for indoor ventilation, noise, lighting, and visual access. Discrepancies between measured and simulated data inform parameter adjustments to ensure simulation accuracy for subsequent experimental analyses. Respondents are residents of both experimental and surveyed buildings, providing critical data through questionnaires and interviews.
Experimental subject: The experimental subject was Yutao Garden Community in Xicheng District, Beijing, located in Xinjiekou Subdistrict, where 70% of residents are aged 65 or older. During the “Evaluation of Elevator Retrofitting in Multi-Story Residential Buildings in Xinjiekou, Xicheng District”, surveys revealed that 52% of residents experience difficulties with stair access, 27% limit their mobility due to physical constraints, and 11% are entirely homebound, underscoring strong community demand for elevator retrofits [19,20].
The community features three-units-per-floor layouts, with each unit comprising two bedrooms and one living room. The total floor area per level is 212 m2 (185 m2 net area + 27 m2 shared space). Following the “Guidelines”, eight half-floor landing elevator models are compatible with this building type. The Methodology evaluates these models to identify the optimal choice for preserving living quality.
Surveyed subject: Surveyed buildings were selected based on architectural congruence with the experimental subject:
(1) Flat building facades with exterior walls aligned uniformly;
(2) Slab-style residential buildings measuring 18 m (width) × 12 m (depth), with rooms adjacent to the retrofit façade having a 4 m depth (length-to-width ratio: 1.45);
(3) Central stairwells with landing platforms flush with room boundaries, featuring symmetrical layouts along the stairwell’s longitudinal axis;
(4) Six exterior-facing rooms per floor with operable windows, yielding a 16.3% window-to-wall ratio on the retrofit façade.
Eight communities meeting these criteria were selected (Figure 2): Xihuangchenggen South Street No. 45, Xihuangchenggen South Street Zone 1, Chegongzhuangzhongli, Xiaomachangnanli, Huaibaishu North Street, Ministry of Materials Compound, Honglianzhongli, and Hongju South Street No. 1. Each community implemented one of the eight half-floor landing elevator models specified in the “Guidelines”. Parameter calibration was conducted by comparing field measurements with simulations, ensuring errors remained below 10% to guarantee simulation reliability [21,22].
The half-floor stop elevator retrofitting method involves positioning the elevator lobby at the staircase landing, requiring residents to ascend or descend half a flight of stairs to reach their target floor. This approach is suitable for space-constrained older residential buildings, offering lower installation costs but not achieving full accessibility. In contrast, the level-stop method directly connects the elevator lobby to residents’ balconies or rooms, providing full accessibility but requiring more installation space and potentially affecting natural lighting and ventilation [23,24]. Considering the limited land availability and complex utility networks in the experimental site, Yutao Yuan Community, the half-floor stop method was adopted to minimize impacts on the existing environment. Therefore, this study focused on identifying the optimal elevator type under the half-floor stop approach, with the research subjects being 50 residential units that already implemented this retrofitting method [25].
The study’s respondents comprised 48 residents from 10 buildings scheduled for elevator retrofitting and 196 residents from 40 buildings where elevator retrofitting was already completed, totaling 244 participants. A stratified sampling method was employed, with stratification based on gender, floor distribution, and elevator type. The sample consisted of 54.78% males and 45.22% females, approximating a 1:1 ratio. The distribution of respondents across floors was balanced, with a ratio of ground-floor residents, mid-floor residents, and top-floor residents of approximately 1:3:1. Within each elevator type group, secondary stratification by floor ensured balanced representation, capturing the opinions and experiences of residents across different elevator types and floor levels [26,27].
The questionnaire collected information on user demographics, residential quality satisfaction, elevator costs, and operational maintenance. Demographic data included property ownership, years since construction, design lifespan, gender, age, physical condition, occupation, floor level, the lead department for elevator installation, and information acquisition channels. Residential quality assessment focused on residents’ subjective evaluations of various environmental indicators. Cost analysis covered purchase and installation expenses, while operational aspects included maintenance and safety management.
Reliability was assessed using Cronbach’s α coefficient to evaluate internal consistency. A pre-test sample of 30 yielded an α of 0.873 for the residential quality perception dimension, exceeding the 0.7 threshold, indicating good reliability [28]. Validity testing encompassed content and construct validity. For content validity, three architecture professors and two sociology professors independently reviewed the questionnaire, resulting in the removal of three ambiguous items and adjustment of five scale items, retaining 20 core questions directly related to residential quality. The final content validity ratio (CVR) was ≥0.8, confirming content validity [29]. Construct validity was established through exploratory factor analysis (EFA), which validated the four-factor structure of the residential quality perception module (KMO = 0.787, Bartlett’s Test p < 0.001), with a cumulative variance explanation rate of 76.2% [30].

2.2. Factors Influencing Elevator Type Selection

To identify the optimal elevator type for specific building layouts, it is crucial to establish evaluation criteria for comparing different models [31,32]. The primary channels through which the public learns about elevator retrofitting in existing residential buildings and provides feedback include:
(1) Academic research and publications by scholars on influencing factors;
(2) Discussions on social media platforms regarding implementation progress, challenges, and trade-offs;
(3) Policy documents on government websites. This study integrates findings from the existing literature with crawled web data, filtering and ranking information based on discussion frequency and relevance to identify key factors affecting elevator selection.
The literature review revealed diverse perspectives on influencing factors: Li Wanrong and Song Kun [33] summarized functional, economic, and operational dimensions using a combination of quantitative and qualitative methods. Liu Yang and Liu Lin [34] explored the relationship between elevator retrofitting and living quality through six aspects: accessibility, ventilation, daylighting, visual access, site conditions, and universal design. Wang Jianjun and Xiong Zhenzhen [23] categorized influencing factors into four areas: building layout, indoor environmental quality, structural safety, and underground utilities. Chai Yiping [35] discussed challenges related to indoor environmental impacts, structural safety, and funding mechanisms.
In summary, research has gradually shifted focus from sociological stakeholder coordination [36,37,38] to technical considerations, emphasizing comprehensive evaluations of post-retrofit living quality, construction costs, and operational sustainability. Scholars universally recommend objective assessments to minimize adverse impacts on daylighting, ventilation, structural safety, fire safety, and aesthetics [39,40,41,42].
Based on the conclusions from the literature review, this study filtered and integrated web data. In September 2024, 982 trending topics and 14,232 comments under the keyword “elevator retrofitting in existing residential buildings” were collected from Google, Baidu, Xiaohongshu, Bilibili, and Weibo. After removing irrelevant information and merging semantically similar entries, factors influencing living quality post-retrofitting were identified from public concerns (Figure 3).
An analysis of the web data revealed 4077 valid entries, with public concerns primarily focused on three areas: living quality (2670 entries), construction costs (1125 entries), and operational maintenance (282 entries). Living quality-related topics accounted for over half of the discussions, highlighting it as the dominant public concern. Regarding construction costs, a comparison of post-subsidy installation prices from three contractors—Beijing Xingjia Construction Engineering Co., Ltd. (Beijing, China), Beijing Urban Construction Group Co., Ltd. (Beijing, China), and Beijing Fangdi Tianyu Special Equipment Installation Co., Ltd. (Beijing, China)—showed prices ranging from RMB 242,000 to RMB 274,000 per unit. This translated to a household contribution difference of RMB 1000–3400. Among 244 surveyed residents, 208 (85.2%) prioritized the impact of elevator retrofitting on indoor living quality over cost variations. Operational costs followed a standardized tiered pricing model: RMB 500 per household for three-story buildings, increasing by RMB 100 per additional floor. Given the overwhelming focus on living quality, this study adopted it as the primary criterion for elevator selection.

2.3. Evaluation Process of the Comprehensive Selection Methodology

Based on the literature review and crawled web data, this study established an evaluation framework comprising four factors: indoor ventilation, indoor noise, indoor daylighting, and external visual access (Figure 4). The specific evaluation process was as follows:
(1) Determining the weight of each factor: This study employed the Analytic Hierarchy Process (AHP) to ascertain the weight of each evaluation factor within the comprehensive assessment framework.
The first step involved constructing a hierarchical structure model, where post-retrofitting indoor residential quality is designated as the goal layer (A) and indoor ventilation (B1), indoor noise (B2), indoor daylighting (B3), and outdoor view (B4) are established as the criterion layer.
The second step entailed designing a judgment matrix questionnaire based on the 1–9 scale method, which was distributed to 244 respondents who were required to pairwise compare the importance of the four criterion layer factors.
The third step involved constructing a comprehensive judgment matrix by aggregating all valid questionnaire data using the geometric mean method, forming a judgment matrix from the criterion layer to the goal layer to ensure the statistical significance of group decision-making.
The fourth step calculated the weights and conducted consistency checks, using the square root method to compute the eigenvector, obtain initial weight values, and perform consistency tests to ensure the credibility of the weight distribution [43].
(2) Parameter adjustment based on software simulations for surveyed subjects: This step ensured the accuracy of subsequent simulation analyses for the experimental subject. The surveyed subjects were first grouped by their installed elevator types, resulting in eight groups of five subjects each, with identical elevator types within each group. Simulations and field measurements were conducted for each group, and discrepancies between simulated and measured data were analyzed. Simulation parameters were adjusted until the error between simulated and measured data fell within 10% of the measured data, concluding the adjustment process [21,44].
(3) Application analysis based on the experimental subject: After obtaining simulation parameters for indoor wind, sound, light, and visual environments in the second step, these settings were applied to simulate the experimental subject. The analysis results were then converted into quantifiable evaluation values using relevant standards. The detailed quantification process is described in Section 4 of this paper.
(4) Determine the optimal elevator type and summarize findings: After quantifying the analysis results for indoor wind, sound, light, and visual environments, weighted scores were calculated for each elevator type based on the weights determined in the first step. The elevator types were then ranked according to their scores to identify the optimal type for the experimental subject. Finally, the comprehensive evaluation process was summarized by analyzing building typology, standard floor layouts, unit characteristics of the surveyed and experimental subjects, as well as the plan and structural features of different elevator types.

3. Weights of Factors in the Comprehensive Selection Methodology

As described in Section 2.3, the weights of factors influencing elevator retrofitting were determined through the Analytic Hierarchy Process (AHP) based on feedback from 244 residents (Figure 5). The prioritized weights of factors, as identified by residents, were as follows: indoor noise (42.192%) > indoor ventilation (34.01%) > indoor daylighting (18.952%) > external visual access (4.846%) (Figure 6). The AHP calculations yielded a maximum eigenvalue of 8.98, a consistency index (CI) of 0.122, and a corresponding random index (RI) of 1.404 from the RI table. Consequently, the consistency ratio (CR) was calculated as CR = CI/RI = 0.087, which is less than 0.1, indicating high reliability of the AHP results (Table 1) [45,46].

4. Evaluation Criteria in the Comprehensive Selection Methodology

4.1. Evaluation Results of Indoor Ventilation

First, field measurements were conducted on the surveyed objects. The indoor air velocity was measured using a DELIXI-1603A anemometer (Manufacturer: Delixi Electric, City: Yueqing, Country: China). The measurement points were arranged in a grid pattern. Since the dimensions of all rooms in the selected surveyed objects were less than 10 m, they were classified as small rooms. The spacing between measurement points was set to no more than one-fourth to one-third of the shorter side length of the room to capture the variation in air velocity within the room. Therefore, the spacing was set to one-third of the shorter side length of each room. The measurement height was 1.5 m, corresponding to the human breathing zone height [47,48,49]. The measurements were taken daily from 14:00 to 17:00 between 10 October and 20 October 2024. During the measurement process, certain errors may have arisen due to the precision limitations of the handheld anemometer (DELIXI-1603A with a nominal error of ±3%) and constraints in the measurement point arrangement (e.g., omission of localized airflow variations in corners, door gaps, and window crevices). However, by increasing the number of measurements at each point and controlling the deviation between measurements, the results can effectively reflect the actual indoor ventilation performance [50]. Each measurement point was recorded three times. If the difference between the maximum and minimum values at a single point exceeded 10% of the minimum value, additional measurements were taken; otherwise, the measurement was concluded [21,44].
Indoor wind environment simulations were conducted using the eddy3d v0.4.1.2 within Grasshopper, which is based on the steady-state RANS (Reynolds-Averaged Navier–Stokes) model. Compared to other CFD software, eddy3d excels in predicting steady-state building airflow and indoor ventilation with higher computational efficiency and accuracy [51]. The simulation utilized meteorological data for Beijing in 2023 from the Energy Plus website (epw format). Variations in epw data across different years and the simplified treatment of complex wall flow in eddy3d’s turbulence model may have led to the underestimation of local vortex intensity [52]. Therefore, this study adjusted the default software settings through grouped parameter tuning and sensitivity analysis based on measured data. By testing grid resolutions (0.3 m, 0.5 m, 0.8 m) and iteration counts (500, 1000, 1500), it was found that errors increased by over 5% when grid resolution exceeded 0.5 m, and wind speed fluctuations were less than 1% after 1000 iterations. Comparing simulation results with measured data and balancing accuracy and computational speed, the parameters were set as follows: wind tunnel dimensions of 100 m × 100 m × 80 m, background grid resolution of 0.5 m × 0.5 m, building grid refinement level of 3, iteration count of 1000, and wind speed measurement plane at 1.5 m above the indoor floor level. Under these settings, the maximum simulation error was 0.02 m/s for E3-3F, which was less than 10% of the measured value (Figure 7), indicating high reliability of the simulation data [53,54,55].
After obtaining the simulation parameters, the experimental subject was analyzed (Figure 8) and the results were scored using the PMV (predicted mean vote) method according to the ASHRAE 55–2017 standard [56] (Figure 9). The calculation method is shown in Equation (1), where the indoor wind comfort rating (dimensionless) ranges from 0 to 100, with higher values indicating better indoor wind comfort; v represents the indoor wind speed (m/s) and k is the steepness coefficient of the Gaussian correction term (dimensionless), controlling the decay rate of ratings in high wind speed areas (based on an air temperature of 22 °C, relative humidity of 50%, metabolic rate of 70 W/m2, and clothing insulation of 1.0 clo; k = 5 was derived from the ASHRAE 55–2017 standard table.
C r w = 100 · v 0.3 2 · 2 v 0.3 · e k · v 0.3 0.3 2
The final indoor ventilation evaluation scores were as follows: Elevator Type 2 (86.427) > Elevator Type 4 (85.089) > Elevator Type 5 (76.659) > Elevator Type 7 (71.682) > Elevator Type 8 (68.458) > Elevator Type 1 (52.120) > Elevator Type 6 (50.377) > Elevator Type 3 (43.577) (Table 2).

4.2. Evaluation Results of Indoor Noise

First, a measured analysis was conducted for each survey subject using the SMART SENSOR-AM824 sound level meter (Manufacturer: Smart Sensor, City: Dongguan, Country: China) to measure indoor sound pressure levels. The arrangement of measurement points for indoor acoustic environments and the methods for data validity verification were consistent with those for indoor wind environments [57,58]. Multiple measurements were taken to reduce errors caused by the sound level meter’s precision limitations (SMART SENSOR-AM824 with a nominal error of ±1.5 dB) and incomplete isolation of background noise. This was achieved by controlling the deviation between maximum and minimum values and calculating the mean. For indoor acoustic environment simulations, Pachyderm Acoustic v2.6.0.5 was employed. This software includes a built-in elevator room frequency spectrum library and allows the customization of sound power level curves, offering advantages over generic acoustic software (e.g., Odeon) that uses simplified point source models. The primary noise sources in the simulation were the elevator room and elevator car noise sources provided by Pachyderm Acoustic. By comparing simulation results with measured data and balancing accuracy and computational speed, the final simulation parameters were determined as follows: acoustic properties of building materials were set for typical multi-story residential buildings, the iteration count was set to 800, and the noise measurement plane was positioned 1.5 m above the indoor floor level [59,60,61,62]. Under these settings, the maximum error was 4.459 dB for E3-6F, which was less than 10% of the measured value (Figure 10), indicating high reliability of the simulation data [21,44].
After obtaining the simulation parameters, the experimental subjects were analyzed (Figure 11) and the results were scored using the weighted delta JND method in Pachyderm Acoustic [63,64] (Figure 12). The calculation method is shown in Equation (2), where the indoor acoustic comfort rating (dimensionless) ranges from 0 to 100, with higher values indicating less noise impact on residential quality and greater comfort; L represents the noise sound pressure level (dB) and k is the decay exponent (dimensionless), determined as k = 1.43 based on the delta JND method and the room dimensions (all sides less than 10 m, classified as a small room).
C r A = 100 · 1 L 70 k
The final indoor noise evaluation scores were as follows: Elevator Type 6 (90.091) > Elevator Type 2 (86.338) > Elevator Type 1 (80.717) > Elevator Type 3 (78.292) > Elevator Type 7 (72.241) > Elevator Type 8 (70.426) > Elevator Type 4 (69.325) > Elevator Type 5 (68.667) (Table 3).

4.3. Evaluation Results of Indoor Daylighting

Indoor daylighting measurements were conducted using the SMART SENSOR-AS823 illuminance meter (Manufacturer: Smart Sensor, City: Shenzhen, Country: China) to measure indoor illuminance levels. The arrangement of measurement points for indoor daylighting, data validity verification, and methods were consistent with those for indoor ventilation. For indoor daylighting simulations, the Daylight Simulation plugin in Ladybug was employed, utilizing meteorological data for Beijing in 2023 from the Energy Plus website (epw format). Multiple measurements were taken to reduce errors caused by the illuminance meter’s precision limitations (SMART SENSOR-AS823 with a nominal error of ±5%) by controlling the deviation between maximum and minimum values and calculating the mean. By comparing simulation results with measured data and balancing accuracy and computational speed, the final simulation parameters were determined as follows: the acoustic properties of building materials were set for typical multi-story residential buildings, the building grid refinement level was set to 3, the iteration count was set to 700, and the daylighting measurement plane was positioned 1.5 m above the indoor floor level. Under these settings, the maximum error was 4.734% for E4-3F, which was less than 10% of the measured value (Figure 13), indicating high reliability of the simulation data [64,65,66].
After obtaining the simulation parameters, the experimental subjects were analyzed (Figure 14) and the results were scored according to the T/CECS 462-2017 “Evaluation Standard for Healthy Residential Buildings” [32] (Figure 15). The calculation method is shown in Equation (3), where E represents the Effective Daylight Area Ratio (dimensionless), ranging from 0 to 100, with higher values indicating a greater proportion of indoor area meeting effective daylighting criteria; the numerator is the area where the indoor daylight factor meets the standard, and the denominator is the total indoor area.
E = A c A t × 100 %
The final indoor daylighting evaluation scores were as follows: Elevator Type 5 (92.760) > Elevator Type 3 (86.836) > Elevator Type 4 (80.643) > Elevator Type 6 (77.318) > Elevator Type 1 (76.823) > Elevator Type 8 (73.177) > Elevator Type 7 (72.890) > Elevator Type 2 (63.990) (Table 4).

4.4. Evaluation Results of External Visual Access

For indoor visual aspects, the outdoor view ratio was adopted as the evaluation metric, defined as the proportion of outdoor landscape visible to occupants through windows or other openings in the building. Since the calculation results are solely influenced by the building and elevator layout, as well as the position and size of windows and doors, and do not involve fluid simulation, the software simulation results directly represented the actual measurements. Therefore, for indoor visual aspects, no comparison or feedback calibration between measured and simulated data was conducted based on survey subjects. Instead, the experimental subjects were directly used for parameter calibration. The View Analysis plugin in Ladybug was employed and, by comparing simulation results with measured data and balancing accuracy and computational speed, the final simulation parameters were determined as follows: view analysis precision was set to level 3, the iteration count was set to 50, and the outdoor view ratio analysis plane was positioned 1.5 m above the indoor floor level.
After obtaining the simulation parameters, the experimental subjects were analyzed (Figure 16), and the results were scored according to the LEED v4.1 “Green Building Rating System” [67,68,69] (Figure 17). The calculation method is shown in Equations (4) and (5), where x represents the outdoor view ratio; the numerator is the actual visible outdoor area; the denominator is the theoretical maximum visible area; the Indoor Outdoor View Evaluation Score (dimensionless) ranges from 0 to 100, with higher scores indicating greater occupant comfort regarding outdoor views; and k is the curve steepness coefficient, set to k = 2.5 based on the LEED v4.1 standard.
x = A v A m × 100 %
E ( x ) = 100 · sin 2 π x 70 · e k · x 35 35 2
The final outdoor view evaluation scores were as follows: Elevator Type 5 (92.760) > Elevator Type 3 (86.836) > Elevator Type 4 (80.643) > Elevator Type 6 (77.318) > Elevator Type 1 (76.823) > Elevator Type 8 (73.177) > Elevator Type 7 (72.890) > Elevator Type 2 (63.990) (Table 5).

4.5. Optimal Elevator Selection for the Typical Building Type in Yutao Garden Community

Through a comprehensive evaluation of indoor ventilation, indoor noise, indoor daylighting, and external visual access, eight semi-level entrance elevators compatible with the standard building type in Yutao Garden Community, as listed in the “Atlas” issued by the Beijing Municipal Commission of Housing and Urban-Rural Development, were scored. The final scores were as follows: Elevator 2 (73.036) > Elevator 4 (67.863) > Elevator 5 (65.412) > Elevator 8 (64.517) > Elevator 7 (64.474) > Elevator 6 (63.053) > Elevator 1 (59.214) > Elevator 3 (58.680) (Table 6). Based on residential quality considerations, Elevator Model 2 was the most suitable option for the standard building type in Yutao Garden Community.

5. Conclusions

The field measurements and simulation results of the surveyed and experimental objects demonstrate that different types of elevator additions have significant impacts on the living quality of existing residential buildings. Although elevator installations inevitably affect the physical environment of residences, such as daylighting and ventilation, selecting an appropriate elevator type can effectively mitigate these impacts.
This study addresses the challenges and lack of scientific basis in selecting elevator types for existing residential buildings. Based on the proposed comprehensive selection methodology, the characteristics and extent of impacts of the eight elevator types listed in the “Atlas” on indoor living quality are summarized in terms of indoor ventilation, indoor noise, indoor daylighting, and external visual access.
(1) Indoor ventilation: The elevator shaft should ideally be positioned directly opposite the stairwell, with the elevator corridor length approximately 2.2 m, and the window area facing the prevailing summer wind direction should be maximized.
A comparison was made between the elevator types with the highest and lowest indoor ventilation scores. For E2, the elevator shaft was positioned directly opposite the staircase, with a connecting corridor length of 2.4 m, which is closer to the optimal corridor length (2.2 m) compared to other models. It featured windows on both sides with the largest window area, resulting in an average simulated wind speed of 0.255 m/s across all floors, demonstrating the best indoor ventilation performance. In contrast, E3 had an elevator shaft not positioned opposite the staircase, with windows oriented away from the prevailing summer wind direction and a smaller window area, yielding an average simulated wind speed of 0.186 m/s, indicating the poorest indoor ventilation performance. To minimize the impact of elevator installation on indoor ventilation, the following measures are recommended:
  • The elevator shaft should ideally be positioned directly opposite the staircase: When the elevator shaft is aligned with the staircase, the impact on indoor ventilation is minimized, as seen in elevator models 2, 4, 5, and 8. Positioning the shaft on either side of the staircase significantly increases the impact, as observed in models 1, 3, 6, and 7.
  • The length of the elevator-connecting corridor should be approximately 2.2 m: For example, in Beijing, where buildings are typically oriented north–south, a controlled variable analysis of the corridor length (ranging from 0 m to 3 m, with increments of 0.2 m, totaling 16 simulations) was conducted under the condition that the corridor faces the staircase without windows. The results showed that a corridor length of 2.2 m achieved the best ventilation, with an average indoor wind speed of 0.271 m/s. If the corridor is positioned on the sides of the building, a shorter corridor length reduces the impact on indoor ventilation.
  • The elevator corridor should feature windows on both sides, preferably facing east: The corridor’s window configuration can be single-sided or double-sided, with a larger total window area favoring better indoor ventilation. For single-sided windows, a smaller angle between the window orientation and the prevailing summer wind direction of the building’s location enhances ventilation.
(2) Indoor noise: The elevator corridor should be detached from the building, and the distance between the elevator shaft and the building should be maximized.
A comparison was made between the elevator types with the highest and lowest indoor noise scores. For E6, the elevator shaft was detached from the building, and the elevator entrance door was not directly opposite the staircase. The connecting corridor length was 1.8 m, aligning with the noise-reducing layout described above. The average simulated sound pressure level across all floors was 36.663 dB, indicating the minimal impact of elevator noise on the residential interior. In contrast, E5 had an elevator shaft attached to the building, with the entrance door directly opposite the staircase and no connecting corridor. The average simulated sound pressure level across all floors was 51.172 dB, representing the greatest impact of elevator noise on the residential interior. To minimize the impact of elevator installation on indoor acoustic environments, the following measures are recommended:
  • The elevator shaft should ideally be detached from the building: When the elevator shaft is attached to the building, the noise generated has the greatest impact on the interior. If the elevator shaft is detached and connected via a corridor, noise transmission into the interior is more likely when the corridor is perpendicular to the building. However, a corridor parallel to the building significantly reduces noise transmission.
  • The length of the elevator-connecting corridor should preferably exceed 2 m: The greater the distance between the elevator shaft and the building, the smaller the impact of generated noise on the interior, with noise decreasing exponentially as the distance increases.
(3) Indoor daylighting: The elevator shaft should preferably be attached to the building, and the corridor should be constructed with glass curtain walls with high light transmittance. If the corridor is built with opaque materials, the window area should be maximized.
A comparison was made between the elevator types with the highest and lowest indoor daylighting scores. For E5, the elevator shaft was attached to the building, and no connecting corridor was installed. The average simulated value of effective daylighting areas across all floors was 56.305%, indicating the minimal impact of elevator installation on indoor daylighting. In contrast, for E2, the elevator shaft was detached from the building, and the connecting corridor was the longest among the eight models (2.4 m). The average simulated value of effective daylighting areas across all floors was 38.801%, representing the greatest impact of elevator installation on indoor daylighting. To minimize the impact of elevator installation on indoor daylighting, the following measures are recommended:
  • The length of the elevator-connecting corridor should be as short as possible: longer corridors are less favorable for indoor daylighting.
  • The corridor material should preferably be a glass curtain wall with an increased window area: If the corridor is constructed with opaque materials and partially windowed, a larger window area enhances indoor daylighting. If the corridor is made of transparent materials, higher light transmittance of the construction materials improves indoor daylighting.
(4) External visual access: Glass curtain walls with high light transmittance should be used, and the elevator shaft should preferably be attached to the building. If an elevator corridor is necessary, it should be connected perpendicularly to the building, and its length should be minimized. If obstacles such as drainage pipes or heating pipes in front of the building require the elevator shaft to be positioned on the left or right side of the corridor, the preferences of the building residents should be thoroughly considered. The elevator should be positioned near non-living spaces such as bathrooms or storage rooms, where external visual access is less critical, and affected residents should be provided with appropriate financial compensation.
A comparison was made between the elevator types with the highest and lowest outdoor view scores. For E2, the elevator shaft was detached from the building, and the connecting corridor was relatively long (2.4 m). However, it featured a double-sided window design, resulting in a simulated outdoor view ratio of 35.316% for the standard floor, achieving the highest outdoor view score after elevator installation. In contrast, for E4, the connecting corridor length was 1.5 m, and no windows were installed. The average simulated value of effective daylighting areas across all floors was 15.886%, representing the lowest outdoor view score after elevator installation. To minimize the impact of elevator installation on outdoor views, the following measures are recommended:
  • High light transmittance materials for corridor and shaft: The higher the light transmittance of the materials used for the corridor and shaft is, the better the external visual access from the interior will be.
  • Minimize corridor length and connect perpendicularly: If the elevator shaft is directly connected to the building, the impact on external visual access is minimized. If the shaft is connected via a corridor, a parallel arrangement significantly reduces external visual access for adjacent rooms, potentially blocking the view entirely. For example, in Elevator Model 1, where the shaft is positioned on the left side of the corridor, the external visual access for adjacent bathrooms and dining rooms is reduced to less than 10%. Therefore, a perpendicularly connected corridor provides better external visual access compared to a parallel arrangement.
(5) Summary: The proposed comprehensive selection methodology in this study provides a new approach to address the challenges and lack of scientific basis in selecting elevator types for existing residential buildings in old neighborhoods.
Nationwide, this method is also applicable to buildings with different layouts and unit types, as well as the various elevator types specified in the elevator installation standards of other provinces, demonstrating high scalability.
For the Beijing area, the surveyed and experimental objects in this study exhibit significant similarities in building type, standard floor plan, and unit characteristics. After applying the comprehensive selection methodology, the scores of each elevator type across the evaluation factors and the final total scores show a high degree of regularity. Based on the shared characteristics of the experimental and surveyed objects mentioned in Section 2.1, the following recommendations are proposed for buildings with these characteristics:
The comprehensive ranking of the eight semi-level stop elevator types in the “Atlas” (Elevator 2 > Elevator 4 > Elevator 5 > Elevator 8 > Elevator 7 > Elevator 6 > Elevator 1 > Elevator 3) derived in Section 4.5 provides direct and valuable reference for elevator selection in Beijing-area buildings that meet the characteristics described in Section 2.1.
From the perspective of living quality, considering indoor ventilation, noise, daylighting, and external visual access, the selected elevator type should have its shaft positioned directly opposite the stairwell, with the elevator entrance door facing the stairwell, and the corridor length should ideally be 1.8 m. If an L-shaped corridor is unavoidable due to objective constraints, the length of the corridor parallel to the building should be minimized. The corridor and shaft should be constructed with high light transmittance materials, and the corridor should have windows on both sides or a single side facing the prevailing summer wind direction (southeast in Beijing).
(6) Future research prospects: First, establish a collaborative evaluation system for multiple types of elevators. While this study focuses on semi-stop elevators, future work could incorporate level-stop and machine-room-less elevators to develop a comprehensive evaluation system across stopping modes. Additionally, the applicability of this method in different climate zones should be validated. Second, expand the current research scope across multiple dimensions. While the current evaluation framework emphasizes the physical environment, future studies could integrate structural safety (e.g., seismic adaptability in earthquake-prone areas), energy efficiency (e.g., carbon emissions from elevator operation), and economic costs (e.g., life cycle maintenance expenses) to form a multi-objective optimization model. Third, conduct long-term post-use evaluations of the experimental subjects. Selected experimental cases should be monitored for 5–10 years to analyze the cumulative effects of elevator aging on ventilation, noise, daylighting, and other factors.

Author Contributions

Conceptualization, D.C. and C.L.; methodology, C.L. and R.G.; software, R.G. and E.J.; validation, D.C., C.L. and R.G.; formal analysis, R.G., E.J. and C.L.; investigation, R.G.; resources, E.J.; data curation, R.G.; writing—original draft preparation, R.G.; writing—review and editing, D.C.; visualization, C.L.; supervision, D.C.; project administration, D.C.; funding acquisition, D.C. All authors have read and agreed to the published version of the manuscript.

Funding

The authors gratefully acknowledge financial support from the General Program of the National Natural Science Foundation of China (Grant No. 52178003) and the Graduate Innovation Project of BUCEA (Grant No. PG2024002).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The original contributions presented in the study are included in the article; further inquiries can be directed to the corresponding authors.

Conflicts of Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

References

  1. Ageing and Health in China. Available online: https://www.who.int/china/health-topics/ageing (accessed on 12 September 2024).
  2. China’s Demographic Outlook and Implications for 2035. Available online: https://www.eiu.com/n/chinas-demographic-outlook-and-implications-for-2035/ (accessed on 4 August 2024).
  3. Over One-Fifth of Chinese Population Older than 60, Says Official Report. Available online: https://english.www.gov.cn/news/202410/12/content_WS6709cb9ac6d0868f4e8ebbda.html (accessed on 4 August 2024).
  4. Shao, Q.H.; Yuan, J.F.; Ma, J.W.; Ding, H.X.; Huang, W. Exploring the determinants of synergetic development of social organizations participating in home-based elderly care service: An SEM method. PLoS ONE 2020, 15, e0244880. [Google Scholar]
  5. Wong, K.C.; Wong, F.K.Y.; Yeung, W.F.; Chang, K. The effect of complex interventions on supporting self-care among community-dwelling older adults: A systematic review and meta-analysis. Age Ageing 2018, 47, 185–193. [Google Scholar] [PubMed]
  6. Chu, Y.Q.; Shen, S.G. Adoption of Major Housing Adaptation Policy Innovation for Older Adults by Provincial Governments in China: The Case of Existing Multifamily Dwelling Elevator Retrofit Projects. Int. J. Environ. Res. Public Health 2022, 19, 6124. [Google Scholar] [CrossRef] [PubMed]
  7. Gan, C.; Chen, M.Y.; Rowe, P. Beijing’s Selected Older Neighborhoods Measurement from the Perspective of Aging. Sustainability 2020, 12, 4112. [Google Scholar] [CrossRef]
  8. Notice from Beijing Municipal Commission of Housing and Urban-Rural Development and Other Four Departments on the Issuance of the “Operational Guidelines for Installing Elevators in Existing Multi-Storey Residential Buildings in Beijing (Trial)”. Available online: https://www.beijing.gov.cn/zhengce/zhengcefagui/202309/t20230919_3261730.html (accessed on 15 October 2024).
  9. Technical Guidelines for Installing Elevators in Existing Multi-Storey Residential Buildings in Shenzhen. Available online: https://zjj.sz.gov.cn/attachment/1/1379/1379781/10970548.pdf (accessed on 10 November 2024).
  10. De Almeida, A.; Hirzel, S.; Patrão, C.; Fong, J.; Dütschke, E. Energy-efficient elevators and escalators in Europe: An analysis of energy efficiency potentials and policy measures. Energy Build. 2012, 47, 151–158. [Google Scholar]
  11. Ma, S.C.; Li, T.T.; Yang, Y.F. Housing Price Appreciation Effects of Elevator Installation in Old Residential Areas: Empirical Evidence Based on a Multiperiod DID Model. Adv. Civ. Eng. 2022, 2022, 122–156. [Google Scholar]
  12. Guo, B.; Zhang, L.; Li, Y. Research on the path of residents’ willingness to upgrade by installing elevators in old residential quarters based on safety precautions. Saf. Sci. 2019, 118, 389–396. [Google Scholar]
  13. Retolaza, I.; Zulaika, I.; Remirez, A.; Cabello, M.J.; Campos, M.A.; Ramos, A. New design for installation (DFI) methodology for large size and long life cycle products: Application to an elevator. Proc. Des. Soc. 2021, 1, 2237–2246. [Google Scholar]
  14. Al-Kodmany, K. Elevator technology improvements: A snapshot. Encyclopedia 2023, 3, 530–548. [Google Scholar] [CrossRef]
  15. Torres, J.; Garay-Martinez, R.; Oregi, X.; Torrens-Galdiz, J.I.; Uriarte-Arrien, A.; Pracucci, A.; Casadei, O.; Magnani, S.; Arroyo, N.; Cea, A.M. Plug and play modular façade construction system for renovation for residential buildings. Buildings 2021, 11, 419. [Google Scholar] [CrossRef]
  16. Arditi, A. Rethinking ADA signage standards for low-vision accessibility. J. Vis. 2017, 17, 20. [Google Scholar] [CrossRef] [PubMed]
  17. Usman, M.; Jonas, D.; Frey, G. A methodology for multi-criteria assessment of renewable integrated energy supply options and alternative HVAC systems in a household. Energy Build. 2022, 273, 112397. [Google Scholar] [CrossRef]
  18. McCormack, G.R.; Nesdoly, A.; Ghoneim, D.; McHugh, T.L. Realtors’ Perceptions of Social and Physical Neighborhood Characteristics Associated with Active Living: A Canadian Perspective. Int. J. Environ. Res. Public Health 2020, 17, 9150. [Google Scholar] [CrossRef]
  19. Jade Peach Garden. Available online: https://baike.baidu.com/item/%E7%8E%89%E6%A1%83%E5%9B%AD/10692590?fr=aladdin (accessed on 15 September 2024).
  20. Xinjiekou Street. Available online: https://baike.baidu.com/item/%E6%96%B0%E8%A1%97%E5%8F%A3%E8%A1%97%E9%81%93/3321085?fr=aladdin (accessed on 15 September 2024).
  21. Coakley, D.; Raftery, P.; Keane, M. A review of methods to match building energy simulation models to measured data. Renew. Sustain. Energy Rev. 2014, 37, 123–141. [Google Scholar] [CrossRef]
  22. Kellner, M.I.; Madachy, R.J.; Raffo, D.M. Software process simulation modeling: Why? what? how? J. Syst. Softw. 1999, 46, 91–105. [Google Scholar] [CrossRef]
  23. Jianjun, W.; Zhenzhen, X.; Dongbin, L. Feasibility study on installing elevators in existing multi story residential buildings. Build. Sci. 2020, 36, 1–6. [Google Scholar]
  24. Wei, L. Analysis of Typical Issues in Structural Construction Drawings for Elevator Installation in Existing Buildings. Build. Struct. 2020, 50, 852–856. [Google Scholar]
  25. Chen, X. Research on Problem of Installing Elevators in Old Communities. In Proceedings of the 2023 International Conference on Economic Management, Financial Innovation and Public Service (EMFIPS 2023), Cangzhou, China, 29–30 December 2023; pp. 491–501. [Google Scholar]
  26. Dai, X.; Li, Z.; Ma, L.; Jin, J. The Spatio-Temporal Pattern and Spatial Effect of Installation of Lifts in Old Residential Buildings: Evidence from Hangzhou in China. Land 2022, 11, 1600. [Google Scholar] [CrossRef]
  27. Li, Y.; Zheng, W.; Zhou, Q. Knowledge-driven urban innovation: Dynamics of elevator installation in aging residential communities. J. Knowl. Econ. 2024, 344, 1–45. [Google Scholar] [CrossRef]
  28. Karimian, Z.; Abolghasemi, M. Re-architecture for requirements of academic space development in the universities: Design and validitation of RASD questionnaire. Sci. Rep. 2025, 15, 19. [Google Scholar] [CrossRef]
  29. Liu, Y.F.; Wang, P.; Luo, X.; Zhang, M.; Zhao, T.L.; Yang, Y.Z.; Sun, Y.K.; Liu, X.D.; Liu, J.H. Analysis of flexible energy use behavior of rural residents based on two-stage questionnaire: A case study in Xi’an, China. Energy Build. 2022, 269, 112246. [Google Scholar] [CrossRef]
  30. Kong, Z.; Utzinger, D.M.; Freihoefer, K.; Steege, T. The impact of interior design on visual discomfort reduction: A field study integrating lighting environments with POE survey. Build. Environ. 2018, 138, 135–148. [Google Scholar]
  31. Shukla, V.V.; Tambe, P.P. Decision Factors in the Selection of Elevator. i-Manag. J. Mech. Eng. 2018, 8, 155–168. [Google Scholar]
  32. Wang, Y.; Chong, H.-Y.; Liao, P.-C.; Ren, H. Interactive mechanism of working environments and construction behaviors with cognitive work analysis: An elevator installation case study. Int. J. Occup. Saf. Ergon. 2019, 25, 362–376. [Google Scholar] [CrossRef]
  33. Wanrong, L.; Kun, S.; Keyu, W.; Li, C.; Lin, F. Research on post use evaluation of elevators installed in existing residential buildings in response to public concerns. J. West. Hum. Settl. Environ. 2024, 39, 122–128. [Google Scholar]
  34. Yang, L.; Lin, L. Research on the correlation between elevator design and living quality in multi story residential buildings. Hous. Ind. 2022, 190, 11–15. [Google Scholar]
  35. YiPing, C. Research on adding elevators to existing multi story residential buildings. Hous. Sci. 2015, 35, 45–47. [Google Scholar]
  36. Jie, L.; Xuejie, R.; Shuai, S. Research on Pricing Mechanism of PPP Project for Installing Elevators in Old Urban Residential Areas. Price Theory Pract. 2023, 12, 93–98. [Google Scholar]
  37. Lv, J.; Gan, T.; Ye, L. Rebuilding the ‘Nearby’: Space Production and Community Generation—Taking the Installation of Elevators in the Old Community of G Community in Shanghai as an Example. J. Shanghai Inst. Adm. 2024, 25, 68–82. [Google Scholar]
  38. WeiZhe, S. The dilemma, criticism, and countermeasures of installing elevators in existing residential buildings. Hebei Law 2022, 40, 159–184. [Google Scholar]
  39. Yang, Z.; Benxiao, Z.; Liya, Y.; Guotao, C. Analysis of Elevator Installation Strategies in Multi party Co built Old Residential Areas from the Perspective of Collective Action Theory: A Case Study of Country Garden in Hangzhou City. Urban Rural Plan. 2024, 4, 57–65. [Google Scholar]
  40. Lin, H.; Lin, C. Agenda setting for adding elevators in dual aging communities based on multi-source flow theory: Taking the installation of elevators in C old community in Kunshan City as an example. Technol. Ind. 2024, 24, 10–18. [Google Scholar]
  41. Qi, Z.; Qian, L. Research on the Multi Subject Behavioral Strategy Selection of Installing Elevators in Old Residential Areas. Proj. Manag. Technol. 2024, 22, 95–103. [Google Scholar]
  42. Mao, H.; Qu, Y.; Li, A. Analysis of the Challenges and Solutions Faced by Installing Elevators in Old Residential Areas. China Elev. 2024, 35, 63–65. [Google Scholar]
  43. Han, J.W.; Ma, H.; Wang, M.H.; Li, J.Q. Construction and improvement strategies of an age-friendly evaluation system for public spaces in affordable housing communities: A case study of Shenzhen. Front. Public Health 2024, 12, 1399852. [Google Scholar]
  44. Bennett, N.D.; Croke, B.F.; Guariso, G.; Guillaume, J.H.; Hamilton, S.H.; Jakeman, A.J.; Marsili-Libelli, S.; Newham, L.T.; Norton, J.P.; Perrin, C. Characterising performance of environmental models. Environ. Model. Softw. 2013, 40, 1–20. [Google Scholar]
  45. Podvezko, V. Application of AHP technique. J. Bus. Econ. Manag. 2009, 315, 181–189. [Google Scholar]
  46. Shim, J.P. Bibliographical research on the analytic hierarchy process (AHP). Socio-Econ. Plan. Sci. 1989, 23, 161–167. [Google Scholar]
  47. Licina, D.; Pantelic, J.; Melikov, A.; Sekhar, C.; Tham, K.W. Experimental investigation of the human convective boundary layer in a quiescent indoor environment. Build. Environ. 2014, 75, 79–91. [Google Scholar]
  48. Wu, J.; Weng, W.; Shen, L.; Fu, M. Transient and continuous effects of indoor human movement on nanoparticle concentrations in a sitting person’s breathing zone. Sci. Total Environ. 2022, 805, 149970. [Google Scholar]
  49. Zhang, T.T.; Yin, S.; Wang, S. Quantify impacted scope of human expired air under different head postures and varying exhalation rates. Build. Environ. 2011, 46, 1928–1936. [Google Scholar] [PubMed]
  50. Cheng, C.C.; Lee, D.; Huang, B.S. Estimated thermal sensation models by physiological parameters during wind chill stimulation in the indoor environment. Energy Build. 2018, 172, 337–348. [Google Scholar] [CrossRef]
  51. Kastner, P.; Dogan, T. Eddy3D: A toolkit for decoupled outdoor thermal comfort simulations in urban areas. Build. Environ. 2022, 212, 108639. [Google Scholar] [CrossRef]
  52. Xiao, X.; Zhou, J.L.; Yang, W. Review of calculating models of unsteady natural ventilation rate due to wind fluctuations. Indoor Built Environ. 2022, 31, 2199–2215. [Google Scholar] [CrossRef]
  53. Zhang, F.; Ryu, Y. Simulation study on indoor air distribution and indoor humidity distribution of three ventilation patterns using computational fluid dynamics. Sustainability 2021, 13, 3630. [Google Scholar] [CrossRef]
  54. Li, Y.; Tao, X.; Zhang, Y.; Li, W. Combining use of natural ventilation, external shading, cool roof and thermal mass to improve indoor thermal environment: Field measurements and simulation study. J. Build. Eng. 2024, 86, 108904. [Google Scholar] [CrossRef]
  55. Xu, F.; Gao, Z. Study on indoor air quality and fresh air energy consumption under different ventilation modes in 24-hour occupied bedrooms in Nanjing, using Modelica-based simulation. Energy Build. 2022, 257, 111805. [Google Scholar] [CrossRef]
  56. Carlucci, S.; Erba, S.; Pagliano, L.; de Dear, R. ASHRAE Likelihood of Dissatisfaction: A new right-here and right-now thermal comfort index for assessing the Likelihood of dissatisfaction according to the ASHRAE adaptive comfort model. Energy Build. 2021, 250, 111286. [Google Scholar] [CrossRef]
  57. Khan, J.; Hussain, T.; Javed, M.T.; Meraj, S. Effect of indoor environmental quality on human comfort and performance: A review. In Ergonomics for Improved Productivity; Springer: Berlin/Heidelberg, Germany, 2021; pp. 335–345. [Google Scholar]
  58. Yang, T.; Cabani, A.; Chafouk, H. A survey of recent indoor localization scenarios and methodologies. Sensors 2021, 21, 8086. [Google Scholar] [CrossRef]
  59. Kang, M.-W.; Oh, Y.-K. Analysis of frequency characteristics and evaluation methods of elevator noise. J. Acoust. Soc. Korea 2021, 40, 607–614. [Google Scholar]
  60. Kang, M.-W.; Oh, Y.-K. A study on the location of microphones in measurement considering the frequency characteristics of elevator noise in households. J. Acoust. Soc. Korea 2023, 42, 124–132. [Google Scholar]
  61. Pan, J.; Li, H.; Chen, W.; Wei, Y. Elevator Performance Evaluation Based on the Analysis of the Running Sound. In Proceedings of the 2021 Global Reliability and Prognostics and Health Management (PHM-Nanjing), Nanjing, China, 15–17 October 2021; pp. 1–6. [Google Scholar]
  62. Peng, H.; Lv, Z.; Chen, M. Research on the Impact Test and Control Countermeasures of Residential Elevator Operation Noise. E3S Web Conf. 2021, 237, 01033. [Google Scholar]
  63. Zaporozhets, O.; Fiks, B.; Jagniatinskis, A.; Tokarev, V.; Karpenko, S.; Mickaitis, M. Indoor noise A-level assessment related to the environmental noise spectrum on the building facade. Appl. Acoust. 2022, 185, 108380. [Google Scholar]
  64. Zeng, Y.; Sun, H.; Lin, B.; Zhang, Q. Non-visual effects of office light environment: Field evaluation, model comparison, and spectral analysis. Build. Environ. 2021, 197, 107859. [Google Scholar]
  65. Wang, Y.; Yang, W.; Wang, Q. Multi-objective parametric optimization of the composite external shading for the classroom based on lighting, energy consumption, and visual comfort. Energy Build. 2022, 275, 112441. [Google Scholar]
  66. Leccese, F.; Rocca, M.; Salvadori, G.; Belloni, E.; Buratti, C. Towards a holistic approach to indoor environmental quality assessment: Weighting schemes to combine effects of multiple environmental factors. Energy Build. 2021, 245, 111056. [Google Scholar]
  67. Lin, T.-Y.; Le, A.-V.; Chan, Y.-C. Evaluation of window view preference using quantitative and qualitative factors of window view content. Build. Environ. 2022, 213, 108886. [Google Scholar]
  68. Ko, W.H.; Kent, M.G.; Schiavon, S.; Levitt, B.; Betti, G. A window view quality assessment framework. Leukos 2022, 18, 268–293. [Google Scholar]
  69. Le, D.M.; Park, D.Y.; Baek, J.; Karunyasopon, P.; Chang, S. Multi-criteria decision making for adaptive façade optimal design in varied climates: Energy, daylight, occupants’ comfort, and outdoor view analysis. Build. Environ. 2022, 223, 109479. [Google Scholar]
Figure 1. Common half-floor landing elevator types for existing buildings in Beijing.
Figure 1. Common half-floor landing elevator types for existing buildings in Beijing.
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Figure 2. Standard floor plans of surveyed and experimental buildings.
Figure 2. Standard floor plans of surveyed and experimental buildings.
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Figure 3. Statistics of public concerns regarding post-retrofit impacts on living quality.
Figure 3. Statistics of public concerns regarding post-retrofit impacts on living quality.
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Figure 4. Evaluation workflow for the living quality-oriented comprehensive elevator selection methodology.
Figure 4. Evaluation workflow for the living quality-oriented comprehensive elevator selection methodology.
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Figure 5. AHP hierarchy analysis indices of factors influencing elevator retrofitting.
Figure 5. AHP hierarchy analysis indices of factors influencing elevator retrofitting.
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Figure 6. Weight distribution of factors influencing elevator retrofitting.
Figure 6. Weight distribution of factors influencing elevator retrofitting.
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Figure 7. Error between measured and simulated indoor average wind speeds for surveyed buildings.
Figure 7. Error between measured and simulated indoor average wind speeds for surveyed buildings.
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Figure 8. Wind speed contour map at 1.5 m above floor level in the experimental building.
Figure 8. Wind speed contour map at 1.5 m above floor level in the experimental building.
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Figure 9. Ventilation performance scores of eight elevator types for the experimental building.
Figure 9. Ventilation performance scores of eight elevator types for the experimental building.
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Figure 10. Error between measured and simulated indoor average sound pressure levels for surveyed buildings.
Figure 10. Error between measured and simulated indoor average sound pressure levels for surveyed buildings.
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Figure 11. Sound pressure level contour map at 1.5 m above floor level in the experimental building.
Figure 11. Sound pressure level contour map at 1.5 m above floor level in the experimental building.
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Figure 12. Noise performance scores of eight elevator types for the experimental building.
Figure 12. Noise performance scores of eight elevator types for the experimental building.
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Figure 13. Error between measured and simulated indoor average effective daylight factors for surveyed buildings.
Figure 13. Error between measured and simulated indoor average effective daylight factors for surveyed buildings.
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Figure 14. Effective daylight distribution contour map at 1.5 m above floor level in the experimental building.
Figure 14. Effective daylight distribution contour map at 1.5 m above floor level in the experimental building.
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Figure 15. Daylighting performance scores of eight elevator types for the experimental building.
Figure 15. Daylighting performance scores of eight elevator types for the experimental building.
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Figure 16. Visual access contour map at 1.5 m above floor level in surveyed buildings.
Figure 16. Visual access contour map at 1.5 m above floor level in surveyed buildings.
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Figure 17. Visual access performance scores of eight elevator types for the experimental building.
Figure 17. Visual access performance scores of eight elevator types for the experimental building.
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Table 1. AHP hierarchy analysis results of factors influencing elevator retrofitting.
Table 1. AHP hierarchy analysis results of factors influencing elevator retrofitting.
Influencing FactorsEigenvectorWeight (%)Maximum EigenvalueCI Value
Indoor Ventilation1.3634.018.980.14
Indoor Noise1.68842.192
Indoor Daylighting0.75818.952
External Visual Access0.1944.846
Table 2. Measured and simulated indoor ventilation evaluations for experimental and surveyed buildings.
Table 2. Measured and simulated indoor ventilation evaluations for experimental and surveyed buildings.
Research Object\Influencing FactorsMeasured Average Wind Speed at Each Floor (m/s)Simulated Average Wind Speed at Each Floor (m/s)Overall Score
Ground
Floor
(1F)
Middle
Floor
(3F)
Top
Floor
(6F)
Ground Floor
(1F)
Middle
Floor
(3F)
Top
Floor
(6F)
Research
Object
No. 45 Courtyard, South Xihuangchenggen Street (E1)0.1870.1550.2140.1950.1650.211\
District 1, South
Xihuangchenggen Street (E2)
0.2530.2230.240.2690.2310.259\
Chegongzhuang Zhongli
Community (E3)
0.20.2370.1810.2090.2170.185\
Xiaomachang Nanli
Community (E4)
0.2510.2450.2250.2370.2650.246\
Huaibaishu Street Beili
Community (E5)
0.2460.2510.2840.2650.2320.275\
Wuzi Department
Courtyard (E6)
0.1930.1800.2260.2120.1740.231\
Honglian Zhongli
Community (E7)
0.1760.2270.2230.1850.2200.228\
No. 1 Courtyard, Hongju
South Street (E8)
0.280.1950.2210.2970.2090.216\
Experimental ObjectYutao Yuan Community
(Current situation)
0.1870.1550.2140.1950.1650.211\
Yutao Yuan Community (E1)\\\0.1740.1890.23552.120
Yutao Yuan Community (E2)\\\0.2270.2690.26886.427
Yutao Yuan Community (E3)\\\0.1420.1920.22443.577
Yutao Yuan Community (E4)\\\0.2170.2540.28585.089
Yutao Yuan Community (E5)\\\0.1950.2290.28775.659
Yutao Yuan Community (E6)\\\0.1600.2160.21450.377
Yutao Yuan Community (E7)\\\0.1920.2390.27776.051
Yutao Yuan Community (E8)\\\0.1770.2440.25168.458
As described in Section 2.3 the role of the survey subjects was to calibrate the software by comparing their measured and simulated values. Therefore, Table 2 only records the measured and simulated values of the survey subjects, without including final scores. As outlined in Section 2.3, the accuracy of the simulated data for the experimental subjects was ensured after software calibration. Since the experimental subjects were in a pre-retrofitting state without actual elevator installations, only simulation analysis was conducted for these subjects and no further measured analysis was performed.
Table 3. Measured and simulated indoor noise evaluations for experimental and surveyed buildings.
Table 3. Measured and simulated indoor noise evaluations for experimental and surveyed buildings.
Research Object\Influencing FactorsMeasured Average Sound
Pressure Level
for Each Floor (dB)
Simulated Average Sound Pressure Level
for Each Floor (dB)
Overall Score
Ground
Floor
(1F)
Middle
Floor
(3F)
Top
Floor
(6F)
Ground Floor
(1F)
Middle
Floor
(3F)
Top
Floor
(6F)
Research ObjectNo. 45 Courtyard, South Xihuangchenggen Street (E1)39.37845.82846.50038.67442.908843.379\
District 1, South
Xihuangchenggen Street (E2)
23.47227.64133.01222.11827.51032.204\
Chegongzhuang Zhongli
Community (E3)
43.43648.27649.05640.970445.44853.515\
Xiaomachang Nanli
Community (E4)
47.37162.03663.37643.43560.15062.118\
Huaibaishu Street Beili
Community (E5)
48.27653.80455.56045.78951.01754.579\
Wuzi Department
Courtyard (E6)
29.79836.64437.81126.76639.26741.721\
Honglian Zhongli
Community (E7)
43.30253.80355.42744.97451.17757.351\
No. 1 Courtyard, Hongju
South Street (E8)
43.30048.98754.31539.03148.67051.382\
Experimental ObjectYutao Yuan Community (E1)\\\31.88745.96148.23873.486
Yutao Yuan Community (E2)\\\29.96643.57149.96774.714
Yutao Yuan Community (E3)\\\32.47844.78752.21171.813
Yutao Yuan Community (E4)\\\29.87651.50456.16067.552
Yutao Yuan Community (E5)\\\36.62556.52660.36457.803
Yutao Yuan Community (E6)\\\31.87637.37940.71580.552
Yutao Yuan Community (E7)\\\34.07948.94452.62768.588
Yutao Yuan Community (E8)\\\24.12655.55657.16467.935
The recording considerations for Table 3 follow the same protocol as Table 2.
Table 4. Measured and simulated indoor daylighting evaluations for experimental and surveyed buildings.
Table 4. Measured and simulated indoor daylighting evaluations for experimental and surveyed buildings.
Research Object\Influencing FactorsProportion of Measured
Indoor Effective Daylight Area (%)
Proportion of Simulated
Indoor Effective Daylight Area (%)
Overall Score
Ground
Floor
(1F)
Middle
Floor
(3F)
Top
Floor
(6F)
Ground Floor
(1F)
Middle
Floor
(3F)
Top
Floor
(6F)
Research ObjectNo. 45 Courtyard, South Xihuangchenggen Street (E1)42.34651.90656.68944.66849.72155.496\
District 1, South
Xihuangchenggen Street (E2)
44.98738.94142.45942.15937.71040.866\
Chegongzhuang Zhongli
Community (E3)
52.29561.50662.58852.06259.80861.498\
Xiaomachang Nanli
Community (E4)
51.89859.08266.37753.04254.34867.578\
Huaibaishu Street Beili
Community (E5)
60.29863.61472.11758.77665.06068.664\
Wuzi Department
Courtyard (E6)
44.64653.05257.84647.35050.07757.098\
Honglian Zhongli
Community (E7)
47.45545.05551.00544.35646.92252.980\
No. 1 Courtyard, Hongju
South Street (E8)
39.66045.07749.51041.87446.61952.417\
Experimental ObjectYutao Yuan Community
(Current situation)
\\\57.05963.97875.200\
Yutao Yuan Community (E1)\\\42.26448.02848.71346.334
Yutao Yuan Community (E2)\\\30.61840.80545.01638.801
Yutao Yuan Community (E3)\\\47.49752.94658.03052.824
Yutao Yuan Community (E4)\\\46.86448.33755.77750.326
Yutao Yuan Community (E5)\\\47.23056.57465.11056.304
Yutao Yuan Community (E6)\\\42.43048.32552.02847.594
Yutao Yuan Community (E7)\\\34.18744.39447.81642.132
Yutao Yuan Community (E8)\\\37.50543.35548.70143.187
The recording considerations for Table 4 follow the same protocol as Table 2.
Table 5. Simulated indoor visual access evaluations for experimental and surveyed buildings.
Table 5. Simulated indoor visual access evaluations for experimental and surveyed buildings.
Research Object\Influencing FactorsSimulated Average Exterior View Ratio for Each Floor (%)Overall Score
Ground
Floor (1F)
Middle
Floor (3F)
Top
Floor (6F)
Experimental ObjectYutao Yuan Community
(Current situation)
\29.166\\
Yutao Yuan Community (E1)\20.040\35.129
Yutao Yuan Community (E2)\35.316\98.338
Yutao Yuan Community (E3)\27.006\73.252
Yutao Yuan Community (E4)\15.866\18.273
Yutao Yuan Community (E5)\37.620\95.384
Yutao Yuan Community (E6)\24.663\60.123
Yutao Yuan Community (E7)\19.972\34.801
Yutao Yuan Community (E8)\30.768\90.531
Since outdoor visibility is solely affected by window position and size as well as outdoor obstructions, regardless of floor level, this table exclusively presents the outdoor visibility data for standard floors after installing each of the eight elevator types on the experimental subjects.
Table 6. Living quality-oriented elevator evaluation matrix for retrofit candidates in Yutao Garden Community.
Table 6. Living quality-oriented elevator evaluation matrix for retrofit candidates in Yutao Garden Community.
Elevator
Model\Evaluation
Factors
Indoor
Ventilation
(13.978%)
Indoor
Noise
(13.383%)
Indoor
Daylighting
(10.716%)
Exterior
View
(5.484%)
Overall Score
E152.12073.48646.33435.12959.214
E286.42774.71438.80198.33873.036
E343.57771.81352.82473.25258.680
E485.08967.55250.32618.27367.863
E575.65957.80356.30495.38465.412
E650.37780.55247.59460.12363.053
E776.05168.58842.13234.80164.474
E868.45867.93543.18790.53164.517
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Chen, D.; Li, C.; Gong, R.; Jin, E. Elevator Selection Methodology for Existing Residential Buildings Oriented Toward Living Quality Improvement. Sustainability 2025, 17, 3225. https://doi.org/10.3390/su17073225

AMA Style

Chen D, Li C, Gong R, Jin E. Elevator Selection Methodology for Existing Residential Buildings Oriented Toward Living Quality Improvement. Sustainability. 2025; 17(7):3225. https://doi.org/10.3390/su17073225

Chicago/Turabian Style

Chen, Dongxiao, Chunqing Li, Rulong Gong, and Enlin Jin. 2025. "Elevator Selection Methodology for Existing Residential Buildings Oriented Toward Living Quality Improvement" Sustainability 17, no. 7: 3225. https://doi.org/10.3390/su17073225

APA Style

Chen, D., Li, C., Gong, R., & Jin, E. (2025). Elevator Selection Methodology for Existing Residential Buildings Oriented Toward Living Quality Improvement. Sustainability, 17(7), 3225. https://doi.org/10.3390/su17073225

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