Next Article in Journal
Events and Festivals as Strategic Tools for Understanding and Assessing the Symbolic Reconfiguration of the World Urban System
Next Article in Special Issue
Light Pollution Beyond the Visible: Insights from People’s Perspectives
Previous Article in Journal
Urban Environment and Momentary Psychological States: A Micro-Scale Study on a University Campus with Network Analysis
Previous Article in Special Issue
Climate Change and Urban Resilience in Smart Cities: Adaptation and Mitigation Strategies in Brazil and Germany
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Effects of Urban Layout, Façade Orientation, and Façade Height on Photosynthetically Active Radiation (PAR) Availability in a Dense Residential Area: A Dynamic Analysis in Shanghai

Liverpool School of Architecture, University of Liverpool, Liverpool L69 7ZN, UK
*
Author to whom correspondence should be addressed.
Urban Sci. 2025, 9(6), 222; https://doi.org/10.3390/urbansci9060222
Submission received: 14 April 2025 / Revised: 31 May 2025 / Accepted: 9 June 2025 / Published: 13 June 2025
(This article belongs to the Special Issue Sustainable Urbanization, Regional Planning and Development)

Abstract

Photosynthetically Active Radiation (PAR) is critical for sustaining plant growth in the ground and on building surfaces, but how to accurately predict PAR availability in a complex urban environment can be a challenge. Using an advanced ray-tracing software (Radiance 4.0) and local weather data, this study presents a dynamic analysis of the effects of layout, façade orientation and height on PAR availability in four high density residential areas in Shanghai city, China. A metric system was also adopted using three light level requirements of outdoor plants (low, medium, high light levels). Key findings included: (1) the urban layout with the highest ratio of building height to north–south facing adjacent building separation achieved the higher levels of PAR availability for low/medium light level plants and the lower levels of PAR availability for high-light plants for middle and low façades and the ground, while high façades in all layouts could see similar PAR availability for all plants. (2) The PAR availability for low/medium-light plants decreased with the increasing façade height, while the PAR availability for high-light plants showed the opposite trend. (3) The north façade and its ground had higher levels of PAR availability for low/medium-light plants and lower levels of PAR availability for high-light plants than other façades. (4) All layouts offered more opportunities to apply high-light and medium-light plants at façades and the ground.

1. Introduction

1.1. Benefits of Greenery Systems in Urban Areas

With rapid population growth and urbanization in the 21st century, cities worldwide are increasingly transformed into high density environments, often at the expense of natural ecosystems [1]. These densely urbanized areas have given rise to critical challenges, including excessive energy consumption, air pollution, and water scarcity, all of which adversely affect human health and wellbeing [2,3]. Therefore, the need for sustainable and liveable cities has become critical. In recent years, as an effective solution to mitigate the negative impacts of high-density urban environments, a greening approach (i.e., the use of plants on and around buildings) has received increasing attention. The urban greening system is the incorporation of green spaces and elements into urban environments and infrastructure, such as streets, public spaces, building roofs, and façades [4,5]. The benefits of urban greening have been highlighted in research studies [4,5,6,7,8]. For urban climates, the urban greening mitigates the urban heat island effect through shading surfaces and facilitating evapotranspiration (for example, two types of green roofs, with 100 mm and 200 mm soil thickness, were found to produce a significant reduction in heat gain of 59% and 96%, respectively) [4], while vegetation can also improve air quality through capturing particulate matter (PM2.5/PM10) and sequestering carbon dioxide [6]. For the urban ecology, by providing habitats for the urban wildlife, these greening systems can enhance biodiversity and support ecological balance in a city [7]. For urban dwellers, greenery systems and the access to nature can promote human physical and mental health [5,8]. Given these advantages, the application of greening systems in urban areas has been applied to improve environment quality and human health, especially in residential areas.

1.2. Applications of Greening Systems in Residential Areas

As one critical component of urban ecosystems, the greening system in residential areas has attracted attention when initiating a sustainable urban design. Given the limited availability of public spaces in high density residential areas, plants are typically installed on building façades, roofs, and the narrow spaces between buildings. Typical applications include vertical greening system (e.g., Bosco Verticale in Milan, One Central Park in Sydney [9,10,11]), green roofs (e.g., Palazzo Verde in Antwerp, Dakparken Anton and Gerard in Eindhoven [12,13]), and ground green spaces [14,15]. The vertical greening system can be categorized into two primary types based on construction methods—green façades and living walls [9]. For green façades, climbing plants (e.g., Parthenocissus, Hydrangea) are planted in the ground and can grow directly on and up the wall [9,10]. Other plants (e.g., shrubs, grass, perennial plants, succulent plants) can be grown in pre-installed containers, which are then developed into modular systems that are attached to walls [9,11]. Green roofs are roofs where different kinds of vegetation/plants grow on engineered substrates [12] and which have four categories, intensive, semi-intensive, single-course extensive, and multi-course extensive, based on the plant type and substrate depth [13]. The intensive and semi-intensive green roofs have deep soil layers and diverse plant species, while single-course and multi-course extensive green roofs use shallow substrates and limited plants species [12,13]. Ground green spaces encompass all vegetated areas at the urban level and are implemented at varying scales [14], including roadside greenery and vegetation barriers along streets, parks and meadows, greenways and corridors (such as green trails for walking/cycling), recreational and urban gardening facilities (such as community gardens) [15]. The design and installation of these greening systems may depend on the availability of solar radiation in a given complex urban environment.

1.3. Photosynthetically Active Radiation (PAR) and Greenery Systems

Light is an essential factor for all plant life cycle stages, from seed germination and vegetative growth to flowering and reproduction [16]. Solar radiation (sunlight) serves as the primary light source for plants. However, plants selectively absorb photosynthetically active radiation (PAR), the 400–700 nanometre (nm) wavelength range of the electromagnetic spectrum that drives the photosynthesis process and fundamentally determines plants growth [17]. PAR is quantified as photosynthetic photon flux density (PPFD), which is defined as the number of photons (light particles) in the 400–700 nm range received by a surface for a specified amount of time [18]. In controllable facilities, such as greenhouses and chambers, PAR has been widely adopted as a key metric for assessing and optimizing plant growth conditions, ensuring that artificial lighting systems meet the spectral and intensity requirements for plant growth [17]. Different types of indoor plants require different PPFDs for growth. Based on needs and tolerances for light, three common types of plants include: low-light plants (538–2690 lux), medium-light plants (2690–10,760 lux), and high-light plants (>10,760 lux) [19]. However, in an urban environment, PAR availability remains understudied. Unlike controlled indoor environments, PAR availability in urban environments is complex and is influenced by site latitude, time of day and obstructions (e.g., buildings and vegetation density) [20]. These constraints can reduce photosynthetic efficiency and impair the ecological performance of greening systems [20]. Therefore, investigating the availability of PAR is necessary when establishing urban greening systems and relevant facilities for growing plants, particularly in urban residential areas.

1.4. Solar Availability in Residential Areas

Solar availability in residential areas has been studied across two spatial scales: ground-level spaces between buildings and building envelopes (roofs and façades) [20,21,22,23]. For the ground-level spaces, studies explored the effects of urban density and building height [24,25]. A high level of urban density can negatively affect solar availability by increasing shading from neighbouring buildings [26,27]. Taller buildings correlate with reduced solar radiation reaching ground surfaces due to the increased vertical obstruction [28]. Studies of building envelope focus on the effects of urban layout and building morphology (e.g., orientation, height, shape) [24]. For the layout, façade-level solar exposure is sensitive to urban form, especially horizontal (e.g., street grid) and vertical (e.g., skyline irregularity) spatial configurations [29]. For the building morphology, increasing building height may reduce incident solar radiation on vertical façades [27]. Street and building orientations can significantly influence the solar distribution across façades [30,31]. In addition, the effects of urban geometry on solar availability are affected by seasonal and geographic factors. For example, in winter in high-latitude cities, low solar altitude angles intensify shading, drastically reducing solar access to both ground and vertical surfaces [27].

1.5. Research Gaps and the Present Study

Given the discussions above, some research gaps can be identified. First, PAR availability has mainly been applied to assess indoor plant growth conditions [17], while the application of PAR availability in terms of the evaluation of urban greening systems has not been widely studied, especially in urban residential areas. Second, early studies focused on the estimation of solar radiation across entire building surfaces [27,29], neglecting PAR variability at vertically stratified positions (e.g., ground, mid-level, and upper façade positions). Third, previous studies applied general urban models and did not include the dynamic analysis of interactions between PAR availability and various building configurations (e.g., building heights, spacing distances, orientations). This type of study is especially in Chinese cities with specific climates and complicated planning constraints.
The present study explored the effects of layout, orientation, and façade height on PAR availability and distributions in a high-density residential area in Shanghai, China. Using advanced ray-tracing simulation software (Radiance) and local weather data, PAR values were simulated at the four façades of each studied building, together with the ground between two adjacent buildings, in four typical residential layouts. A metric system, based on the requirements of outdoor plant for solar radiations, was developed to evaluate the PAR availability. The results could ultimately be developed into evidence-based design guidelines for planning a biophilic city and promoting ecological resilience and public health in rapidly urbanizing regions.

2. Materials and Methods

2.1. Location and Climate

The location studied was Shanghai city in eastern China (Latitude: 31.23° N, Longitude: 121.47° E). Shanghai had a humid subtropical climate with an average annual temperature of 18 °C [32]. The highest average monthly temperature is 31.1 °C, while the lowest average monthly temperature is −5.6 °C. Total annual sunshine hours of Shanghai was 2134.7 [32].

2.2. Urban Models Studied

Four urban models (identified as layouts L1, L2, L3, and L4) were studied in terms of PAR availability (Figure 1). The selection of these urban models was based on two aspects: (1) They were typical residential urban layouts recommend by a local planning regulation in Shanghai [33]. (2) Their layouts and geometries were defined to meet the requirements (environmental performance, fire and structure safety, and transport system) of local and national regulations for the design of residential buildings [33,34,35]. The characteristics of these layouts included the distance between two north–south facing adjacent building façades (D1), and the distance between two east–west facing adjacent building façades (D2), the dimensions of a unit building (height H, width W, and length L), and the ratio of building height to building spacing (H/D1) (see details in Table 1). Given the planning regulations [34,35], the building dimensions and the distances between buildings defined in these models may lead to four high density residential areas. According to Figure 1a,b, for the unit building at each layout, four façades, South (S), North (N), East (E), and West (W), were assessed in this study.
As displayed in Figure 1b,c and Table 1, for the unit building studied in each layout, the PAR availability was calculated at its centre façade position and the ground nearby, i.e., position P1 (aligned with the centre façade, with the height of 0.05 m above the ground and the distance of 0.5 m to the façade), position P2 (at the centre façade of ground floor), position P3 (at the centre façade of middle floor), and position P4 (at the centre façade of top floor). For each layout, a total of 16 positions were calculated to indicate the PAR availability. These represented possible positions for locating vegetation systems on façades and in the ground.

2.3. PAR and Lighting Metrics of Plants

Generally, PAR is quantified in terms of Photosynthetic Photon Flux Density (PPFD, µmol/m2/s) [36]. Table 2 gives the light and PAR requirements of plants [19,37], while Table 3 lists typical outdoor plants, which could be planted at positions on building façades and in the ground in a residential area. The illuminance (lux) (visual part of the solar radiation spectrum) was converted to PPFD (µmoles/m2/s) using the algorithm given in [36,38]:
P P F D = 0.0185 × I l l u m i n a n c e
According to Table 2 and Table 3, three PPFD ranges for sustaining the growth of plants were given [19,37]: (i) low level (LP) (9.95–49.76 µmoles/m2/s), for example, Aglaonema, Dieffenbachia; (ii) medium level (MP) (49.76–199.06 µmoles/m2/s), for example, Ferns, Begonia; (iii) high level (HP) (≥199.06 µmoles/m2/s), for example, Cacti and succulents, Gardenia. A very low PPFD (<9.95 µmol/m2/s) might not be able to sustain the healthy growth of plants. Thus, a PAR metric in this study was applied based on the three PPFD ranges (i, ii, iii).

2.4. Assessment of PAR Availability and Numeric Simulation

The assessment of PAR availability in the four urban layouts were conducted using the following steps:
  • First, the daylight illuminances (lux) at specific positions on the façades and the ground (Figure 1) were simulated using the lighting package DAYSIM/RADIANCE [39] and the weather data of Shanghai (source: energyplus.net/weather-region/asia_wmo_region_2/CHN, accessed on 10 January 2025). The simulation period was a year (365 days), and the daytime period was considered as 06:00–18:00 (step: 1 h). A total of 4757 values of illuminance was achieved at a specific position.
  • Second, the illuminance dataset was converted to the PPFD dataset using Equation (1).
  • Third, the PAR availability at these positions could be indicated by the percentage of time over a year when the PPFD levels fall within each of the three PPFD ranges, such as: APTLP (the percentage when PPFD falling within the low range (LP)), APTMP (the percentage when PPFD falling within the medium range (MP)), APTHP (the percentage when PPFD falling within the high range (HP)).
For each layout, the centre building was selected for simulation, and there were sixteen points analyzed, including 12 façade positions and four ground positions (Figure 1b,c). Based on the recommendations of daylighting estimation and typical materials applied in building surfaces and external ground [40,41], the reflectance of surfaces of buildings and the external ground were set as 0.4 and 0.2, respectively.
The validation studies of RADIANCE and DAYSIM simulation (solar and daylight) have been conducted for over 20 years, including field measurements under various sky conditions [42,43] and analysis in various complex urban environments [44]. For the simulation using RADIANCE and DAYSIM, the ambient settings can determine how indirect light ray (diffuse interreflections) is calculated, significantly affecting accuracy and computation time [39,45]. This study adopted the recommended settings [39] according to the complexity of the urban models studied, such as 1000 (Ambient Divisions), 5 (Ambient Bounce), 20 (Ambient Super-Samples), 300 (Ambient Resolution), and 0.1 (Ambient Accuracy). In addition, a convergence analysis [45] was conducted to further verify the simulations (see Appendix A).

3. Results

This section shows the analysis of the impact of layout, façade height, and orientation on the annual percentages of time in terms of three PPFD ranges: APTLP, APTMP, APTHP.

3.1. Effects of Layout and Façade Height on PAR Availability at the Building

Figure 2 indicates variations of APTLP, APTMP, APTHP at the south façade according to three façade positions (P2, P3, and P4) and four layouts (L1, L2, L3, L4).
For LP (Figure 2a): at P2, the L4 had a higher APTLP value compared with other layouts, while the other three layouts achieved similar APTLP values. At P3, similarly, the highest APTLP value can be found with the L4 and other layouts L2, L3, and L4 achieved the same APTLP value of 10%. However, at P4, there were no big differences in APTLP values between the four layouts. For the three façade positions, all layouts can see the range of APTLP value between 5% and 20%. For MP (Figure 2b), a similar general trend as the LP can be found: at P2 and P3, significantly higher APTMP values were found in L4, whereas all layouts showed similar APTMP values at P4. All APTMP values at the three positions of all layouts ranged from 25% to 40%. For HP (Figure 2c), at P2 and P3, L4 has much lower APTHP values than the other three layouts (P2: 25%, P3: 34%), while L1, L2 and L3, delivered similar APTHP values. At P4, the APTHP values in the four layouts were similar and within a range of 48% to 49%. The range of all APTHP values at the three positions in the four layouts was 25~50%. Figure 2 also shows the varying trends of APTLP, APTMP, and APTHP according to three façade heights. In general, both APTLP and APTMP decreased with the increasing façade height, while the APTHP showed an opposite trend (P4 > P3 > P2).
Table 4 lists the relative differences of PPFD percentages of P3 or P4 ( R A P T _ P ), taking P2 as the reference, which can be calculated by the equation:
R A P T _ P = A P T i , j A P T i , P 2 A P T i , P 2 × 100 %
where A P T i , j is the value of APTLP, APTMP, or APTHP at P3 or P4 (i = LP, MP, HP, j = P3, P4), A P T i , P 2 is the value of APTLP, APTMP, or APTHP at P2 (i = LP, MP, HP).
  • For APTLP, taking P2 as the reference, P3 achieved large reductions (absolute RAPT_P > 10%) for layouts L2, L3 and L4, whilst significantly larger decreases in this value (absolute RAPT_P > 20%) were achieved at P4 for all layouts.
  • For APTMP, taking P2 as the reference, in layouts L1, L2 and L3, a small reduction was found for P3 (absolute RAPT_P < 10%), while P4 showed higher reductions in this value (absolute RAPT_P > 10%). L4 showed the large decrease in APTMP,with the position moving from P2 to P3 and from P2 to P4 (absolute RAPT_P > 10%).
  • For APTHP, P3 delivered significantly higher values than P2 for layouts of L2, L3, and L4 (RAPT_P > 10%), while there were large increases in APTHP when moving from P2 to P4 (RAPT_P > 25%) for all layouts.
Figure 3 shows the varying trends of APTLP, APTMP, APTHP on the north façade with three positions (P2, P3, and P4) and four layouts (L1, L2, L3, L4). For LP (Figure 3a), at P2, L4 exhibited higher APTLP than the other layouts (relative difference ≥ 10%), while at P3, a large difference in PPFD percentage can be found between L3 and L4 (relative difference = 15%). At P4, all layouts achieved the same APTLP of around 9%. For the three positions, all layouts showed a range of APTLP from 5% to 15%. For MP (Figure 3b), at P2 and P3, L4 achieved a significantly higher APTMP than other layouts (relative difference ≥ 10%). All layouts had a similar APTMP value of around 33% at P4. All positions in the four layouts had the APTMP range from 30% to 45%. For HP (Figure 3c), L4 delivered the lowest APTHP compared to the other three layouts at P2 and P3. At P2, L1 had a significantly higher APTHP (relative difference > 10%) compared to the other layouts, while no big difference was found between L2 and L3 (relative difference < 10%). In addition, at P4, no clear differences of APTHP were found between the four layouts (relative difference < 10%). The APTHP values at the three positions for all four layouts ranged from 20% to 45%. Based on Figure 3, for APTLP and APTMP, there was a significant drop with the positions moving from P2 to P4. For APTHP, a significant increase with an increasing height was found for all layouts (P4 > P3 > P2).
Table 5 gives the relative differences of PPFD percentages of P3 or P4 (RAPT_P), taking P2 as the reference. For APTLP, the differences between P2 and P3 were relatively small for L1, L2, and L3 (absolute RAPT_P < 10%), while a larger difference of this value between the two positions was found in L4 (absolute RAPT_P = 13%). For APTMP, small differences between P3 and P2 were seen in all layouts (absolute RAPT_P < 10%), while this value at P4 was significantly lower than at P2 (absolute RAPT_P > 10%). For APTHP, P3 had relatively higher values than P2 in L2, L3, and L4 (RAPT_P > 15%), while P4 had significantly higher values in all layouts (absolute RAPT_P > 20%).
Figure 4 shows the variation of APTLP, APTMP, and APTHP on the east façade with three positions (P2, P3, P4) and four layouts (L1, L2, L3, L4). For APTLP (Figure 4a), L4 had the highest values at P2 and P3, while the other three layouts had similar values (relative difference < 10%). At P4, the same APTLP of around 7% was found in all layouts. The range of APTLP at the three positions in all layouts was 5~15%. For APTMP (Figure 4b), like the APTLP, the significantly higher values were achieved at P2 and P3 for L4 compared with the other layouts. The APTMP for the four layouts had small difference (relative difference < 10%) at P4. For all positions, the four layouts showed an APTMP range from 25% to 45%. For APTHP (Figure 4c), L4 showed a much lower values than the other layouts at P2 and P3. A significantly higher APTHP was achieved at P2 in L1. In addition, small differences of APTHP were found at P4 between all layouts (relative difference < 10%). For the three positions, the range of APTHP in all layouts was 24~50%. According to Figure 4, both values of APTLP and APTMP showed a decrease with the increasing height from P2 to P4, whilst a clear increase in APTHP was found as P4 > P3 > P2.
Table 6 indicates the relative differences of PPFD percentages at P3 or P4 (RAPT_P), taking P2 as the reference. In L2, L3 and L4, P3 and P4 received the significantly lower values of APTLP and APTMP than P2 (absolute RAPT_P > 10%), and the significantly higher values of APTHP than P2 (RAPT_P > 20%). However, L1 cannot see big differences of APTLP, APTMP, APTHP between P2 and P3 (absolute RAPT_P < 10%).
Figure 5 illustrates the variation of APTLP, APTMP, APTHP on the west façade for the three positions (P2, P3, and P4) and the four layouts (L1, L2, L3, L4). For APTLP (Figure 5a), at P2, L4 had higher values compared with other layouts, while other layouts achieved similar values of around 11%. At P3, there was a clear difference in APTLP values only between L4 and L2 (L2 > L4, relative difference > 10%). All layouts had similar APTLP values (around 9%) at P4. In addition, the range of APTLP at the three positions of all layouts was 9~15%. For APTMP (Figure 5b), at P2 and P3, the highest value was found in L4, while similar values were found in the other three layouts. In addition, no big differences in APTMP at P4 could be found in any of the layouts (relative difference < 10%). The three positions in the four layouts show an APTMP range from 25% to 40%. For APTHP (Figure 5c), much lower values were found at P2 and P3 in L4 compared with the other layouts. At P4, the APTHP values in the four layouts were similar, with a range of 46% to 48%. For the three positions in all four layouts, the range of APTHP was from 25% to 50%. According to Figure 5, the values of APTLP and APTMP decreased with the increasing height from P2 to P4. The values of APTHP showed an opposite trend (P4 > P3 > P2).
Table 7 gives the relative differences of PPFD percentages at P3 or P4 (RAPT_P), taking P2 as the reference. For APTLP, taking P2 as the reference, P4 achieved significantly lower values (absolute RAPT_P > 10%) for all layouts, while P3 showed significantly lower values (absolute RAPT_P > 10%) only for L2 and L4. For APTMP, P4 had significantly lower values than P2 (absolute RAPT_P > 20%) for all layouts, while only L3 and L4 showed big differences between P2 and P3 (absolute RAPT_P > 10%). For APTHP, P3 and P4 delivered significantly higher values than P2 for layouts of L2, L3, and L4 (RAPT_P > 10%). In addition, there was no difference in APTHP between P2 and P3 for L1.

3.2. Effect of Layouts on PAR Availability at the Ground

Table 8 indicates the values of APTLP, APTMP, APTHP at the ground positions (P1) near the four building façades (S, N, E, W) in the four layouts (L1, L2, L3, L4). For APTLP and APTMP, L4 delivered relatively higher values than the layouts of L1, L2, and L3 at the ground of each façade, while L1, L2, and L3 did not show any big differences of the two values at the same positions. L1 delivered the largest APTHP values at the ground near each façade, while the lowest values were for L4. L2 and L3 achieved the medium APTHP values in between. In general, for all façades in the four layouts, the ranges of APTLP, APTMP, and APTHP were 8~15%, 25~44%, and 24~49%, respectively.

3.3. Effect of Orientations on PAR Availability at the Building and the Ground

Taking the south façade or the ground near the south façade as the reference, the relative differences of PPFD percentages of the other three façades or the ground near the other three façades ( R A P T _ O ) can be calculated by the equation:
R A P T _ O = A P T i , j A P T i , s o u t h A P T i , s o u t h × 100 %
where A P T i , j is the value of APTLP, APTMP, or APTHP at one specific façade position or the ground near the façade (i = LP, MP, HP, j = north, east, west), A P T i , s o u t h is the value of APTLP, APTMP, or APTHP at the south façade or the ground near the south façade (i = LP, MP, HP).
Table 9 displays the relative differences of APTLP (RAPT_O) at three positions of three façades (north, east, and west). For L1, P2 does not show clear differences of APTLP between the south façade and the other façades (RAPT_O < 10%), while both P3 and P4 had higher APTLP for the north and west façades compared to the south façade (RAPT_O ≥ 10%). Compared with the south façade, the east façade achieved the same APTLP values at P2 and P3, but a much lower APTLP value at P4 (absolute RAPT_O > 10%). For L2, no clear differences in APTLP could be found at P2 for all of the façades, at P3 between the south, east, and west façades, and at P4 between the east and south façades (RAPT_O < 10%), while P3 and P4 showed significant differences of APTLP between the south and north façades, and P4 had big differences in APTLP between the west and south façades (RAPT_O > 20%). For L3, at P2 and P3, other façades showed small differences in APTLP compared with the south façade (RAPT_O ≤ 10%), while relatively bigger differences of APTLP were found between the south façade and the other façades (absolute RAPT_O > 10%). For L4, significant differences of APTLP were found at P2 between the south and west façades, at P4 between the north and south façades, and at P4 between the west and south façades (absolute RAPT_O > 10%).
Table 10 gives the relative differences of APTMP (RAPT_O) at three positions of three façades (north, east, and west). For L1, significant differences of APTMP were found at P3 and P4 between the north and south façades (RAPT_O > 15%). For L2 and L3, all positions at the north façade had significant differences of APTMP from the south façade (RAPT_O > 20%), while no big differences of APTMP were found at all positions between the west and south façades (RAPT_O ≤ 10%). On the east façade, the P2 in both L2 and L3 and the P3 in L3 displayed relatively big differences of APTMP when compared with the south façade (RAPT_O > 10%). For L4, significant differences in APTMP were achieved at all positions of the north façade only (RAPT_O > 10%).
Table 11 shows the relative differences of APTHP (RAPT_O) at the three positions of three façades. Compared with the south façades, the north façades in all layouts showed significant differences of APTHP at three positions (absolute RAPT_O > 10%), while the west façades in all layouts and the east façades in L1 and L4 had no big differences in APTHP at three positions (absolute RAPT_O < 10%). For L2 and L3, the east façades gave relatively big differences in APTHP at P2 only (absolute RAPT_O > 10%).
Table 12 demonstrates the relative differences of APTLP, APTMP, and APTHP (RAPT_O) at the ground position (P1) near three façades (north, east, west), taking the ground position (P1) near the south façade as the reference.
  • APTLP: three façades in L1 and the north façade in L3 had significant differences of APTLP compared with the south façade (absolute RAPT_O > 10%), while no big differences of APTLP was found at any of the façades in L2 and L4, and at the east and west façades in L3 (absolute RAPT_O ≤ 10%).
  • APTMP: the four layouts achieved significantly higher differences of APTMP between the south façade and each of other three façades (RAPT_O ≥ 20%).
  • APTHP: the four layouts showed relatively higher differences of APTHP between the south façade and each of the other three façades (absolute RAPT_O ≥ 15%).

4. Discussion

Based on the results mentioned above (Section 3.1, Section 3.2 and Section 3.3), several key findings can be drawn and discussed as follows.
First, for the top floor of all building façades, no significant impact of layout was found on the PAR availability with the three PPFD ranges (LP, MP, HP). This could indicate that the layout would not influence the selection of plant type at the top floor. According to Figure 6 and Figure 7, at this floor (P4), all layouts had similar low-level obstructions, indicating similar daylight levels (mainly direct sunlight and skylight).
Second, for the middle and ground floors of all building façades and the external ground surfaces, the urban layout L4 achieved the relatively higher PAR availability with MP and LP and the lower PAR availability with HP than the other layouts. However, these positions generally showed small differences of all types of PAR availability between the three urban layouts: L1, L2, and L3. As shown in Table 1 and Figure 6 and Figure 7, L4 had the largest ratio of building height to building spacing and the highest level of obstruction at middle and low façade positions and the ground. Therefore, compared with the other layouts, L4 may deliver more indirect light and less direct light at these positions, resulting in a relatively lower daylight level.
Third, for all building façades in each layout, increasing the façade height reduced the PAR availability with MP and LP but increased the PAR availability with HP. Consequently, the façade height may determine the selection of plant type. Given Figure 6 and Figure 7, when moving from the ground to the top floor, the deceasing level of obstruction can clearly increase the total daylight level, resulting in more opportunities to apply the high-light plants.
Fourth, significant effects of orientation can be found for all types of PAR availability at various positions in all layouts. Compared with the south, east and west façades, the north façade generally received the higher PAR availability with LP and MP and the lower PAR availability with HP. However, there were generally no big differences for all types of PAR availability between the east and west façades for all layouts. At the ground, the south façade achieved the higher PAR availability with HP and the lower PAR availability with MP than other three façades. Given Figure 6 and Figure 7 and the location of Shanghai, the sky can deliver significantly higher direct daylight levels on the south façade than the north façade, even though they have the same obstructions, while similar obstructions of east and west façades would give rise to similar daylight levels.
Finally, for the four layouts, the PAR availability with LP was generally smaller on all façade and ground positions than the PAR availability with MP and HP, while the top floor saw a higher level of the PAR availability with HP than the PAR availability with MP. As shown in Figure 6 and Figure 7, all layouts generally had low and medium levels of obstructions across the building façades and at various ground locations. In addition, the location and climate conditions in Shanghai (humid subtropical climate) can lead to a high level of solar availability over a year [32,33,34,35]. These factors may help create more opportunities to apply the medium-light and high-light plants in these layouts.
Following the findings above, Table 13 presents recommendations for the rank of plant types (HLP, MLP, LLP) which could be applied at various façade and ground positions in the four layouts (L1, L2, L3, L4). For all layouts, HLP and LLP have the highest and the lowest potential to be applied at façade and ground positions, respectively.
The limitations of this study include the following: (1) this study was conducted in Shanghai, which has a special humid subtropical climate and specific urban planning regulations. The findings may not be generalizable to cities with difference climates or urban layouts. (2) The study examined only four typical urban layouts with buildings having uniform heights and orientations. Real-world urban environments have complex and mixed layouts and irregular building geometries, which were not considered. (3) Values of reflectance of building surfaces and ground were fixed as 0.4 and 0.2, respectively, which may not account for variations in real-world materials.
Suggested future work might include the following: (1) more analysis of cities with various climates and urban layouts to improve the generalization of the findings. (2) Validation of simulation results with field measurements in residential areas and PAR availability in hybrid layouts, combining high- and low-rise buildings, could be further explored. (3) The impact of real reflectance values of various materials of façades on PAR availability should be investigated.

5. Conclusions

Using advanced ray-tracing simulation software (Radiance) and local weather data, this study presents a dynamic analysis of PAR availability in a very dense residential area in Shanghai city, China. Effects of layout, façade orientation and façade height on PAR availability in buildings were analyzed using a metric system developed based on the type of outdoor plants. Three ranges of PAR availability (PPFD) for sustaining the growth of plants were applied: low-light plants (9.95–49.76 µmoles/m2/s), medium-light plants (49.76–199.06 µmoles/m2/s), and high-light plants (>199.06 µmoles/m2/s). Four typical urban layouts were assessed (layouts 1–4). Key findings included the following: (1) compared with layouts (1, 2, 3), layout 4 achieved the higher levels of PAR availability for low/medium-light plants and the lower levels of PAR availability for high-light plants at middle and low building façades and on the ground, while high building façades for all layouts can see similar PAR availability for all plants. (2) The PAR availability for low/medium-light plants decreased with the increasing façade height, while the PAR availability for high-light plants showed an opposite trend. (3) North façades and the ground had the higher levels of PAR availability for low/medium-light plants and the lower levels of PAR availability for high-light plants compared with the south, east, and west façades. (4) All layouts may provide a higher potential to apply high-light and medium-light plants at façades and on the ground than the low-light plants.

Author Contributions

Conceptualization, J.D.; methodology, J.D.; software, X.Z.; validation, J.D. and S.S.; formal analysis, X.Z.; investigation, X.Z.; resources, J.D. and X.Z.; data curation, X.Z.; writing—original draft preparation, X.Z.; writing—review and editing, J.D. and S.S.; visualization, X.Z.; supervision, J.D. and S.S.; project administration, J.D. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Data Availability Statement

Dataset available on request from the authors.

Conflicts of Interest

The authors declare no conflicts of interest.

Appendix A

Given suggestions of the validation of RADIANCE simulation [43,45] and the characteristics of the four urban layouts (i.e., simple external environment), a convergence analysis was conducted in terms of three key ambient parameters: Ambient Bounce (AB), Ambient Divisions (AD), and Ambient Resolution (AR). Two urban layouts (L1 and L4) were simulated as they have the largest and the smallest ratios of building height to building spacing (H/D1) of 1.91 and 0.59, respectively.
Figure A1. Convergence analysis of ambient bounce (AB) in L1 and L4: the variation in daylight factor at four positions (P1, P2, P3, P4) with the settings of AB from 1 to 5.
Figure A1. Convergence analysis of ambient bounce (AB) in L1 and L4: the variation in daylight factor at four positions (P1, P2, P3, P4) with the settings of AB from 1 to 5.
Urbansci 09 00222 g0a1
According to Figure A1, no significant differences of daylight factors across the four positions can be found when AB ≥ 2.
Figure A2. Convergence analysis of ambient divisions (AD) in L1 and L4: the variation in daylight factor at four positions (P1, P2, P3, P4) with the settings of AD from 200 to 1000.
Figure A2. Convergence analysis of ambient divisions (AD) in L1 and L4: the variation in daylight factor at four positions (P1, P2, P3, P4) with the settings of AD from 200 to 1000.
Urbansci 09 00222 g0a2
Based on Figure A2, the daylight factors across the four positions tend to converge when AD ≥ 600.
Figure A3. Convergence analysis of ambient resolution (AR) in L1 and L4: the variation in daylight factor at four positions (P1, P2, P3, P4) with the settings of AR from 500 to 300.
Figure A3. Convergence analysis of ambient resolution (AR) in L1 and L4: the variation in daylight factor at four positions (P1, P2, P3, P4) with the settings of AR from 500 to 300.
Urbansci 09 00222 g0a3
For Figure A3, there are no big differences of the daylight factors across the four positions between five AR settings (from 300 to 500).

References

  1. Elmqvist, T.; Fragkias, M.; Goodness, J.; Güneralp, B.; Marcotullio, P.J.; McDonald, R.I.; Parnell, S.; Schewenius, M.; Sendstad, M.; Seto, K.C.; et al. Urbanization, Biodiversity and Ecosystem Services: Challenges and Opportunities: A Global Assessment; Springer Nature: London, UK, 2013; Chapter 2; pp. 13–27. [Google Scholar]
  2. Jackson, L.E. The relationship of urban design to human health and condition. Landsc. Urban Plan. 2003, 64, 191–200. [Google Scholar] [CrossRef]
  3. Liang, L.; Wang, Z.; Li, J. The effect of urbanization on environmental pollution in rapidly developing urban agglomerations. J. Clean. Prod. 2019, 237, 117649. [Google Scholar] [CrossRef]
  4. Raji, B.; Tenpierik, M.J.; Van Den Dobbelsteen, A. The impact of greening systems on building energy performance: A literature review. Renew. Sustain. Energy Rev. 2015, 45, 610–623. [Google Scholar] [CrossRef]
  5. Akpinar, A. How is quality of urban green spaces associated with physical activity and health? Urban For. Urban Green. 2016, 16, 76–83. [Google Scholar] [CrossRef]
  6. Tallis, M.J.; Amorim, J.H.; Calfapietra, C.; Freer-Smith, P.; Grimmond, S.; Kotthaus, S.; Sinnett, D.; Smith, N.; Burgess, S. The impacts of green infrastructure on air quality and temperature. Handb. Green Infrastruct. 2015, 1, 30–49. [Google Scholar]
  7. Zeng, H.; Wang, J.; Guan, M.; Lu, Y.; Liu, H.; Zhao, D. Effects of vegetation structure and environmental characteristics on pollinator diversity in urban green spaces. Urban For. Urban Green. 2023, 84, 127928. [Google Scholar] [CrossRef]
  8. Jabbar, M.; Yusoff, M.M.; Shafie, A. Assessing the role of urban green spaces for human well-being: A systematic review. GeoJournal 2022, 87, 4405–4423. [Google Scholar] [CrossRef]
  9. Medl, A.; Stangl, R.; Florineth, F. Vertical greening systems—A review on recent technologies and research advancement. Build. Environ. 2017, 125, 227–239. [Google Scholar] [CrossRef]
  10. Addo-Bankas, O.; Zhao, Y.; Vymazal, J.; Yuan, Y.; Fu, J.; Wei, T. Green walls: A form of constructed wetland in green buildings. Ecol. Eng. 2021, 169, 106321. [Google Scholar] [CrossRef]
  11. Köhler, M. Green facades—A view back and some visions. Urban Ecosyst. 2008, 11, 423–436. [Google Scholar] [CrossRef]
  12. Shafique, M.; Kim, R.; Rafiq, M. Green roof benefits, opportunities and challenges—A review. Renew. Sustain. Energy Rev. 2018, 90, 757–773. [Google Scholar] [CrossRef]
  13. United States General Service Administration. The Benefits and Challenges of Green Roofs on Public and Commercial Buildings: A Report of the United States General Service Administration; United States General Service Administration: Washington, DC, USA, 2011.
  14. Taylor, L.; Hochuli, D.F. Defining greenspace: Multiple uses across multiple disciplines. Landsc. Urban Plan. 2017, 158, 25–38. [Google Scholar] [CrossRef]
  15. World Health Organization. Urban Green Spaces: A Brief for Action; World Health Organization: Geneva, Switzerland, 2017. [Google Scholar]
  16. Wu, W.; Chen, L.; Liang, R.; Huang, S.; Li, X.; Huang, B.; Luo, H.; Zhang, M.; Wang, X.; Zhu, H. The role of light in regulating plant growth, development and sugar metabolism: A review. Front. Plant Sci. 2025, 15, 1507628. [Google Scholar] [CrossRef]
  17. Iddio, E.; Wang, L.; Thomas, Y.; McMorrow, G.; Denzer, A. Energy efficient operation and modeling for greenhouses: A literature review. Renew. Sustain. Energy Rev. 2020, 117, 109480. [Google Scholar] [CrossRef]
  18. McCree, K.J. Photosynthetically Active Radiation; Springer: Berlin/Heidelberg, Germany, 1981; pp. 41–55. [Google Scholar]
  19. Weisenhorn, J.; Hoidal, N. Lighting for Indoor Plants and Starting Seeds; University of Missouri Extension: Columbia, MO, USA, 2020; Available online: https://extension.umn.edu/planting-and-growing-guides/lighting-indoor-plants (accessed on 15 March 2025).
  20. Lu, M.; Du, J. Assessing the daylight and sunlight availability in high density residential areas: A case in North-east China. Archit. Sci. Rev. 2012, 56, 168–182. [Google Scholar] [CrossRef]
  21. Lu, M.; Du, J. Dynamic evaluation of daylight availability in a highly dense Chinese residential area with a cold climate. Energy Build. 2019, 193, 139–159. [Google Scholar] [CrossRef]
  22. Hong, L.; Zhang, X.; Du, J. A benchmarking analysis of sunlight and daylight availability in a highly dense urban area in southern China. Energy Build. 2024, 323, 114847. [Google Scholar] [CrossRef]
  23. Strømann-Andersen, J.; Sattrup, P.A. The urban canyon and building energy use: Urban density versus daylight and passive solar gains. Energy Build. 2011, 43, 2011–2020. [Google Scholar] [CrossRef]
  24. Formolli, M.; Kleiven, T.; Lobaccaro, G. Assessing solar energy accessibility at high latitudes: A systematic review of urban spatial domains, metrics, and parameters. Renew. Sustain. Energy Rev. 2023, 177, 113231. [Google Scholar] [CrossRef]
  25. Sanaieian, H.; Tenpierik, M.; Van Den Linden, K.; Seraj, F.M.; Shemrani, S.M. Review of the impact of urban block form on thermal performance, solar access and ventilation. Renew. Sustain. Energy Rev. 2014, 38, 551–560. [Google Scholar] [CrossRef]
  26. Kanters, J.; Horvat, M. Solar energy as a design parameter in urban planning. Energy Procedia 2012, 30, 1143–1152. [Google Scholar] [CrossRef]
  27. Chatzipoulka, C.; Compagnon, R.; Nikolopoulou, M. Urban geometry and solar availability on façades and ground of real urban forms: Using London as a case study. Sol. Energy 2016, 138, 53–66. [Google Scholar] [CrossRef]
  28. Yang, X.; Li, Y. The impact of building density and building height heterogeneity on average urban albedo and street surface temperature. Build. Environ. 2015, 90, 146–156. [Google Scholar] [CrossRef]
  29. Cheng, V.; Steemers, K.; Montavon, M.; Compagnon, R. Urban form, density and solar potential. In Proceedings of the PLEA, Geneva, Switzerland, 6 September 2006. [Google Scholar]
  30. Shishegar, N. Street design and urban microclimate: Analyzing the effects of street geometry and orientation on airflow and solar access in urban canyons. J. Clean Energy Technol. 2013, 1, 52–56. [Google Scholar] [CrossRef]
  31. Li, D.; Liu, G.; Liao, S. Solar potential in urban residential buildings. Sol. Energy 2015, 111, 225–235. [Google Scholar] [CrossRef]
  32. National Bureau of Statistics. Shanghai Statistical Yearbook 2023; National Bureau of Statistics: Beijing, China, 2023.
  33. DGJ 08-20-2019; Shanghai Housing and Urban-Rural Development Management Commission (SHURDMC). Design Standard for Residential Buildings. Shanghai Housing and Urban-Rural Development Management Commission: Shanghai, China, 2000.
  34. GB/T 50947–2014; Ministry of Housing and Urban-Rural Development (MHURD). Standard for Assessment Parameters of Sunlight on Building. Ministry of Housing and Urban-Rural Development: Beijing, China, 2014.
  35. GB 50180–2018; Ministry of Housing and Urban-Rural Development (MHURD). Standard for Urban Residential Areas Planning & Design. Ministry of Housing and Urban-Rural Development: Beijing, China, 2018.
  36. Langhans, R.W.; Tibbitts, T.W. Plant Growth Chamber Handbook; Iowa Agricultural and Home Economics Experiment Station: Ames, IA, USA, 1997. [Google Scholar]
  37. Trinklein, D.H. Lighting Indoor Houseplants; University of Missouri Extension: Columbia, MO, USA, 2016; Available online: https://extension.missouri.edu/publications/g6515 (accessed on 15 March 2025).
  38. Thimijan, R.W.; Heins, R.D. Photometric, radiometric, and quantum light units of measure: A review of procedures for interconversion. Hort Sci. 1983, 18, 818–822. [Google Scholar] [CrossRef]
  39. Radiance-Online. Available online: https://www.radiance-online.org/ (accessed on 15 March 2025).
  40. BSI BS 8206-2:2008; Lighting for Buildings—Part 2: Code of Practice for Daylighting. British Standard Institute: London, UK, 2008.
  41. GB 50033–2013; Ministry of Housing and Urban-Rural Development (MHURD). Standard for Daylighting Design of Buildings. Ministry of Housing and Urban-Rural Development: Beijing, China, 2013.
  42. Reinhart, C.; Breton, P. Experimental validation of 3DS MAX design 2009 and DAYSIM 3.0. In Proceedings of the 11th International IBPSA Conference, Glasgow, Scotland, 27–30 July 2009. [Google Scholar]
  43. Mardaljevic, J. Daylight Simulation: Validation, Sky Models and Daylight Coefficients. Ph.D. Thesis, De Montfort University, Leicester, UK, 1999. [Google Scholar]
  44. Compagnon, R. Solar and daylight availability in the urban fabric. Energy Build. 2004, 36, 321–328. [Google Scholar] [CrossRef]
  45. Ward, G.L.; Shakespeare, R. Rendering with Radiance: The Art and Science of Lighting Visualization; Morgan Kaufmann Publishers Inc.: San Francisco, CA, USA, 1998. [Google Scholar]
Figure 1. (a) Typical plan layouts of residential area: L1, L2, L3, and L4; (b) Building dimensions and the calculation positions at the building and the ground (plan view); (c) Building dimensions and the calculation positions at the building and the ground (section view: 1-1).
Figure 1. (a) Typical plan layouts of residential area: L1, L2, L3, and L4; (b) Building dimensions and the calculation positions at the building and the ground (plan view); (c) Building dimensions and the calculation positions at the building and the ground (section view: 1-1).
Urbansci 09 00222 g001
Figure 2. Annual percentages of time of three PPFD ranges at three positions of south façade (P2, P3, P4) in four layouts (L1, L2, L3, L4): (a) APTLP, (b) APTMP, (c) APTHP.
Figure 2. Annual percentages of time of three PPFD ranges at three positions of south façade (P2, P3, P4) in four layouts (L1, L2, L3, L4): (a) APTLP, (b) APTMP, (c) APTHP.
Urbansci 09 00222 g002
Figure 3. Annual percentages of time of three PPFD ranges at three positions of north façade (P2, P3, P4) in four layouts (L1, L2, L3, L4): (a) APTLP, (b) APTMP, (c) APTHP.
Figure 3. Annual percentages of time of three PPFD ranges at three positions of north façade (P2, P3, P4) in four layouts (L1, L2, L3, L4): (a) APTLP, (b) APTMP, (c) APTHP.
Urbansci 09 00222 g003
Figure 4. Annual percentages of time of three PPFD ranges at three positions of east façade (P2, P3, P4) in four layouts (L1, L2, L3, L4): (a) APTLP, (b) APTMP, (c) APTHP.
Figure 4. Annual percentages of time of three PPFD ranges at three positions of east façade (P2, P3, P4) in four layouts (L1, L2, L3, L4): (a) APTLP, (b) APTMP, (c) APTHP.
Urbansci 09 00222 g004
Figure 5. Annual percentages of time of three PPFD ranges at three positions of west façade (P2, P3, P4) in four layouts (L1, L2, L3, L4): (a) APTLP, (b) APTMP, (c) APTHP.
Figure 5. Annual percentages of time of three PPFD ranges at three positions of west façade (P2, P3, P4) in four layouts (L1, L2, L3, L4): (a) APTLP, (b) APTMP, (c) APTHP.
Urbansci 09 00222 g005
Figure 6. Hemispherical views of obstructions at three positions (P2, P3, P4) of south/north façades of the buildings and at the ground (P1) near the south/north façade of the building in four urban models (L1, L2, L3, L4).
Figure 6. Hemispherical views of obstructions at three positions (P2, P3, P4) of south/north façades of the buildings and at the ground (P1) near the south/north façade of the building in four urban models (L1, L2, L3, L4).
Urbansci 09 00222 g006
Figure 7. Hemispherical views of obstructions at three positions (P2, P3, P4) of east/west façades of the buildings and at the ground (P1) near the south/north façade of the building in four urban models (L1, L2, L3, L4).
Figure 7. Hemispherical views of obstructions at three positions (P2, P3, P4) of east/west façades of the buildings and at the ground (P1) near the south/north façade of the building in four urban models (L1, L2, L3, L4).
Urbansci 09 00222 g007
Table 1. Dimensions of four urban layouts and their unit buildings, and the heights of four calculation positions at façades and the ground.
Table 1. Dimensions of four urban layouts and their unit buildings, and the heights of four calculation positions at façades and the ground.
Name of LayoutDistanceBuildingH/D1Height of Calculation Position Above the Ground (m)
D1 (m)D2 (m)L (m)W (m)H (m)Total Number of FloorsP1P2P3P4
L135.617.245.312.420.960.590.051.418.515.6
L236.62322.536.637.6111.020.051.5216.832.1
L353.435.729.416.255181.020.051.5227.553.5
L451.638.626.315.498.4331.910.051.4949.296.9
Table 2. Light and PAR requirements of three types of plants [19,37].
Table 2. Light and PAR requirements of three types of plants [19,37].
TypeIlluminance (Foot-Candles a)Illuminance (lux)PPFD (µmol/m²/s)
Low-light plants[50–250)[538–2690)[9.95–49.76)
Medium-light plants[250–1000)[2690–10,760)[49.76–199.06)
Highlight plants>1000>10,760>199.06
a: Conversion from footcandle to lux: 1 footcandle = 10.76 lux.
Table 3. Examples of three types of plants which can be applied at façades and the ground in a residential area [19,37].
Table 3. Examples of three types of plants which can be applied at façades and the ground in a residential area [19,37].
TypeName
Low-light plants (LLP)Chinese evergreen (Aglaonema), Dumb cane (Dieffenbachia), Dracaena, English ivy (Hedera helix), Philodendron, Homalomena, Pothos (Epipremnum), Arrowhead plant (Syngonium).
Medium-light plants (MLP)Ferns; Begonias (Begonia), Spider plant (Chlorophytum), Schefflera (Schefflera), Grape ivy (Cissus), Croton (Codiaeum), Jade plant (Crassula), Flame violet (Episcia) and Peperomia (Peperomia)
High-light plants (HLP)Cacti and succulents, Orchid cactus (Epiphyllum), Hibiscus, Ti plant (Cordyline), Gardenia (Gardenia) and Caladium
Table 4. Relative differences of PPFD percentages (RAPT_P) of two façade positions (P3, P4), taking the position P2 as the reference (south façade, four layouts: L1, L2, L3, L4).
Table 4. Relative differences of PPFD percentages (RAPT_P) of two façade positions (P3, P4), taking the position P2 as the reference (south façade, four layouts: L1, L2, L3, L4).
Annual PPFD PercentageRAPT_P (%)
L1L2L3L4
P3P4P3P4P3P4P3P4
APTLP−9−27−17−42−23−38−19−56
APTMP−6−21−6−16−3−16−13−29
APTHP826132914303692
Table 5. Relative differences of PPFD percentages (RAPT_P) of two façade positions (P3, P4), taking the position P2 as the reference (north façade, four layouts: L1, L2, L3, L4).
Table 5. Relative differences of PPFD percentages (RAPT_P) of two façade positions (P3, P4), taking the position P2 as the reference (north façade, four layouts: L1, L2, L3, L4).
Annual PPFD PercentageRAPT_P (%)
L1L2L3L4
P3P4P3P4P3P4P3P4
APTLP0−25−8−31−8−25−13−40
APTMP3−11−8−16−8−18−5−21
APTHP−321173718432486
Table 6. Relative differences of PPFD percentages (RAPT_P) of two façade positions (P3, P4), taking the position P2 as the reference (east façade, four layouts: L1, L2, L3, L4).
Table 6. Relative differences of PPFD percentages (RAPT_P) of two façade positions (P3, P4), taking the position P2 as the reference (east façade, four layouts: L1, L2, L3, L4).
Annual PPFD PercentageRAPT_P (%)
L1L2L3L4
P3P4P3P4P3P4P3P4
APTLP−9−36−17−42−25−42−13−53
APTMP−3−18−11−23−11−24−12−32
APTHP5292144214533100
Table 7. Relative differences of PPFD percentages (RAPT_P) of two façade positions (P3, P4), taking the position P2 as the reference (west façade, four layouts: L1, L2, L3, L4).
Table 7. Relative differences of PPFD percentages (RAPT_P) of two façade positions (P3, P4), taking the position P2 as the reference (west façade, four layouts: L1, L2, L3, L4).
Annual PPFD PercentageRAPT_P (%)
L1L2L3L4
P3P4P3P4P3P4P3P4
APTLP0−18−17−25−8−25−14−36
APTMP0−22−9−24−12−21−13−33
APTHP026143414313284
Table 8. Annual percentages of time of three PPFD ranges (APTLP, APTMP, APTHP) at the ground positions (P1) near four building façades (S, N, E, W) in four layouts (L1, L2, L3, L4).
Table 8. Annual percentages of time of three PPFD ranges (APTLP, APTMP, APTHP) at the ground positions (P1) near four building façades (S, N, E, W) in four layouts (L1, L2, L3, L4).
FacadeLayoutAPTLP (%)APTMP (%)APTHP (%)
SL182549
L2102547
L3112645
L4133038
NL193340
L293735
L393735
L4124424
EL1103439
L2113536
L3113635
L4124028
WL1103041
L2113238
L3113139
L4133631
Table 9. Relative differences of APTLP (RAPT_O) at three positions (P2, P3, P4) of three façades (N, E and W) in four layouts (L1, L2, L3, L4), taking the south façade as the reference.
Table 9. Relative differences of APTLP (RAPT_O) at three positions (P2, P3, P4) of three façades (N, E and W) in four layouts (L1, L2, L3, L4), taking the south façade as the reference.
PositionRAPT_O (%)
L1L2L3L4
NEWNEWNEWNEW
P2900800−8−8−8−6−6−13
P318010200010−101000−8
P410−13132902913−131329029
Table 10. Relative differences of APTMP (RAPT_O) at three positions (P2, P3, P4) of three façades (N, E and W) in four layouts (L1, L2, L3, L4), taking the south façade as the reference.
Table 10. Relative differences of APTMP (RAPT_O) at three positions (P2, P3, P4) of three façades (N, E and W) in four layouts (L1, L2, L3, L4), taking the south façade as the reference.
PositionRAPT_O (%)
L1L2L3L4
NEWNEWNEWNEW
P290−32313102919101385
P319332177281432496
P4234−4234027842640
Table 11. Relative differences of APTHP (RAPT_O) at three positions (P2, P3, P4) of three façades (N, E and W) in four layouts (L1, L2, L3, L4), taking the south façade as the reference.
Table 11. Relative differences of APTHP (RAPT_O) at three positions (P2, P3, P4) of three façades (N, E and W) in four layouts (L1, L2, L3, L4), taking the south façade as the reference.
PositionRAPT_O (%)
L1L2L3L4
NEWNEWNEWNEW
P2−1100−21−11−8−26−13−8−16−40
P3−20−2−7−19−5−7−23−7−7−24−6−3
P4−1520−160−4−18−2−6−190−4
Table 12. Relative differences of APTLP, APTMP, APTHP (RAPT_O) at the ground position (P1) near three façades (N, E, W) in four layouts (L1, L2, L3, L4), taking the ground position (P1) near the south façade as the reference.
Table 12. Relative differences of APTLP, APTMP, APTHP (RAPT_O) at the ground position (P1) near three façades (N, E, W) in four layouts (L1, L2, L3, L4), taking the ground position (P1) near the south façade as the reference.
Annual PPFD PercentageRAPT_O (%)
L1L2L3L4
NEWNEWNEWNEW
APTLP132525−101010−1800−8−80
APTMP323620484028484424473320
APTHP−18−20−16−26−23−19−26−26−17−37−26−18
Table 13. Recommendations of the rank of plants (HLP, MLP, LLP) which can be applied at four positions (P1, P2, P3, P4) in terms of façade orientation (S, N, E, W) and layouts (L1, L2, L3, L4).
Table 13. Recommendations of the rank of plants (HLP, MLP, LLP) which can be applied at four positions (P1, P2, P3, P4) in terms of façade orientation (S, N, E, W) and layouts (L1, L2, L3, L4).
LayoutFacadePosition
P1P2P3P4
L1SHLP > MLP > LLPHLP > MLP > LLPHLP > MLP > LLPHLP > MLP > LLP
NHLP > MLP > LLPHLP = MLP > LLPHLP = MLP > LLPHLP > MLP > LLP
EHLP > MLP > LLPHLP = MLP > LLPHLP > MLP > LLPHLP > MLP > LLP
WHLP > MLP > LLPHLP > MLP > LLPHLP > MLP > LLPHLP > MLP > LLP
L2SHLP > MLP > LLPHLP > MLP > LLPHLP > MLP > LLPHLP > MLP > LLP
NHLP = MLP > LLPMLP > HLP > LLPHLP = MLP > LLPHLP > MLP > LLP
EHLP = MLP > LLPHLP = MLP > LLPHLP > MLP > LLPHLP > MLP > LLP
WHLP > MLP > LLPHLP = MLP > LLPHLP > MLP > LLPHLP > MLP > LLP
L3SHLP > MLP > LLPHLP > MLP > LLPHLP > MLP > LLPHLP > MLP > LLP
NHLP = MLP > LLPMLP > HLP > LLPHLP = MLP > LLPHLP > MLP > LLP
EHLP = MLP > LLPHLP = MLP > LLPHLP > MLP > LLPHLP > MLP > LLP
WHLP > MLP > LLPHLP = MLP > LLPHLP > MLP > LLPHLP > MLP > LLP
L4SHLP > MLP > LLPMLP > HLP > LLPHLP = MLP > LLPHLP > MLP > LLP
NMLP > HLP > LLPMLP > HLP > LLPMLP > HLP > LLPHLP > MLP > LLP
EMLP > HLP > LLPHLP > MLP > LLPHLP = MLP > LLPHLP > MLP > LLP
WMLP > HLP > LLPMLP > HLP > LLPHLP = MLP > LLPHLP > MLP > LLP
Note: HLP: high-light plants, MLP: medium-light plants, LLP: low-light plants (see Table 3). ‘A > B’ means that A has the priority. ‘A = B’ means that both A and B can be applied at this position and no one has the priority.
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Zhang, X.; Du, J.; Sharples, S. Effects of Urban Layout, Façade Orientation, and Façade Height on Photosynthetically Active Radiation (PAR) Availability in a Dense Residential Area: A Dynamic Analysis in Shanghai. Urban Sci. 2025, 9, 222. https://doi.org/10.3390/urbansci9060222

AMA Style

Zhang X, Du J, Sharples S. Effects of Urban Layout, Façade Orientation, and Façade Height on Photosynthetically Active Radiation (PAR) Availability in a Dense Residential Area: A Dynamic Analysis in Shanghai. Urban Science. 2025; 9(6):222. https://doi.org/10.3390/urbansci9060222

Chicago/Turabian Style

Zhang, Xi, Jiangtao Du, and Steve Sharples. 2025. "Effects of Urban Layout, Façade Orientation, and Façade Height on Photosynthetically Active Radiation (PAR) Availability in a Dense Residential Area: A Dynamic Analysis in Shanghai" Urban Science 9, no. 6: 222. https://doi.org/10.3390/urbansci9060222

APA Style

Zhang, X., Du, J., & Sharples, S. (2025). Effects of Urban Layout, Façade Orientation, and Façade Height on Photosynthetically Active Radiation (PAR) Availability in a Dense Residential Area: A Dynamic Analysis in Shanghai. Urban Science, 9(6), 222. https://doi.org/10.3390/urbansci9060222

Article Metrics

Back to TopTop