Urban morphology for passive–active energy efficiency in residential complexes: a scoping review and framework for early-stage design in the MENA region

1 Introduction

Urban design choices reshape microclimates by altering solar access, shading, and airflow, thereby modulating UHI intensity and building energy performance (Rahmani and Sharifi, 2025; Rostami and Nasrollahi, 2025). Empirical and simulation work shows that morphology indicators such as (H/W), sky-view factor (SVF), and orientation strongly affect block-scale solar exposure patterns and outdoor thermal stress (Zhan et al., 2024). The transition toward low-energy and low-carbon cities has made urban form an increasingly important object of energy research, particularly in residential neighborhoods where the cumulative effect of early design decisions can lock in energy demand for decades (Liu et al., 2023a). At this scale, energy performance is not determined only by building technologies or material specifications, but also by the spatial logic of the urban fabric itself (Yang et al., 2025; Hashemi and Mills, 2025). Morphological urban indicators such as building height, plan dimensions, orientation, spacing, density, shape factor, etc., influence solar exposure, mutual shading, compactness, ventilation potential, and the balance between heat gains and heat losses, thereby affecting both passive and active energy behavior (Liu et al., 2024). This perspective is especially relevant in the Middle East and North Africa (MENA), where extreme heat, rapid urban growth, and cooling-dominated electricity demand make the energy implications of urban morphology particularly acute. According to the International Energy Agency, cooling already accounts for nearly half of peak electricity demand in MENA and about one-quarter of annual electricity demand, while cooling and desalination together are projected to drive close to 40% of the region’s electricity-demand growth to 2035 (IEA, 2025). At the same time, the region possesses exceptionally favorable solar conditions: World Bank solar resource assessments show that countries in the Middle East and North Africa dominate the global group with “excellent” PV conditions, where average daily output exceeds 4.5 kWh/kWp and seasonal variability remains comparatively low (Energy Sector Management Assistance Program (ESMAP), 2020). These combined conditions mean that residential urban patterns in MENA should no longer be conceived merely as arrangements that consume energy, but as spatial systems that can simultaneously reduce cooling demand and enhance on-site solar energy production from the earliest design stage.

Despite this strategic relevance, the current body of literature remains fragmented in both scope and method. The reviewed studies demonstrate a growing interest in the relationship between urban morphology and energy performance, covering topics such as building-form optimization and BIPV integration (Alhussain et al., 2024), urban-parameter optimization in hot climates (Hashemi and Mills, 2025), climate-responsive block morphology (Aydin and Oral, 2024; Aburmalah and Üzümcüoğlu, 2025), passive design alternatives for new communities, solar-responsive district design (Harbi et al., 2024; Mahaya et al., 2022), height–layout strategies (Ghasemi Sangi et al., 2023), performance-oriented urban energy frameworks (Mangan et al., 2021), and district-scale assessments of cooling demand and roof-integrated PV generation (Zambito et al., 2022). However, these studies differ substantially in analytical scale, indicator selection, outcome metrics, and modeling logic, which makes comparison difficult and limits cumulative knowledge building. The problem is not only that morphological indicators are numerous, but that they are also interrelated and often reported inconsistently across studies; similar urban properties are expressed through different proxies, while building-, layout-, and site-scale indicators are frequently examined in partial isolation rather than as a connected system (Narimani Abar et al., 2023; Li G. et al., 2025; Li H. et al., 2025). A second limitation lies in the imbalance between passive and active performance assessment. Most of the reviewed studies concentrate on passive outcomes such as heating and cooling loads, energy use intensity, or solar access, whereas only a limited subset simultaneously addresses active solar-energy generation through PV or BIPV systems (Alhussain et al., 2024; Harbi et al., 2024; Mahaya et al., 2022; Zambito et al., 2022). A third limitation is contextual: although the dominant climate zones in the reviewed sample—particularly Csa, BWh, and BSk—are highly relevant to MENA, several studies were conducted outside actual MENA cities, which means that much of the available guidance is climatically transferable but not fully region-specific, e.g., (Alhussain et al., 2024; Aydin and Oral, 2024; Mangan et al., 2021). As a result, designers are left with a large set of interdependent indicators but without a sufficiently integrated method for translating them into early-stage urban design decisions that jointly address cooling reduction, solar harvesting, and pathway planning toward zero-energy residential districts (Zhao et al., 2023).

Recent review literature has substantially advanced understanding of individual components of energy-efficient urban design, yet the field remains fragmented across passive urban morphology, solar access, urban climate, and active district-energy systems. Reviews on Local Climate Zones and urban heat islands synthesize how urban form, high density, surface materials, and limited vegetation influence urban heat dynamics and identify mitigation strategies such as greening, permeable surfaces, and reflective materials (Rahmani and Sharifi, 2025). Reviews on sunlight availability and solar radiation acquisition examine the effects of urban morphology indicators such as density, plot ratio, sky-view factor, street-canyon geometry, building height, and spacing on solar access and outdoor/indoor solar performance (Rostami and Nasrollahi, 2025; Liu et al., 2024). Other recent reviews focus on specific domains, including BIPV and solar building-envelope potential in urban contexts (Zhao et al., 2023), the impact of urban climate and UHI on building heating and cooling performance (Hashemi and Mills, 2025), multidimensional Positive Energy District assessment (Yang et al., 2025), and the relationship between urban form, density, and residential energy use (Narimani Abar et al., 2023). However, these studies generally address either passive form–microclimate interactions or active renewable/district-energy systems, rather than integrating both as coupled design levers for early-stage neighborhood planning. The present review is therefore positioned to fill this gap by synthesizing passive strategies, such as density, orientation, urban form, solar access, greenery, and heat-mitigation measures, together with active strategies, such as PV/BIPV, storage, grid interaction, and Positive Energy District concepts. In doing so, it advances beyond previous reviews by translating the evidence into a cross-scale, design-oriented framework that links early urban morphology decisions to both energy demand reduction and renewable energy generation potential. Table 1 presents a comparison between the previous literature studies.

Table 1. Previous literature reviews for a passive–active energy efficiency urban design.

In response to these limitations, this paper aims to narrow the broad problem of urban energy performance to a specific methodological contribution. A scoping review is warranted to map what has been done and pinpoint gaps in aligning reducing cooling loads through passive urban form with generating solar energy with active PV design within the early-stage design decisions. The scoping review is attempting to map post 2020 studies for the extent, range, and nature of research that links urban morphology to passive-active energy efficiency outcomes in residential complexes to identify evidence clusters and gaps that can inform climate-aware, early-stage design decisions. The objective of this paper is to develop a framework for passive–active energy-efficient urban design tailored to the MENA context. The framework is based on the reviewed literature and is intended to convert a dispersed knowledge base into an operational sequence for early-stage design. The study assesses the balance between energy consumption and energy production, which is essential for evaluating progress toward zero-energy concepts in residential neighborhoods. This contribution is particularly significant for MENA not only because the region faces a structural cooling challenge, but also because recent United Nations Environment Program UNEP guidance for high-ambient-temperature MENA countries stresses the need for integrated cooling strategies that connect energy efficiency, climate response, and implementation planning (UNEP, 2026). Accordingly, the paper argues that a structured methodological framework is needed to help designers navigate the complexity of interrelated urban morphological indicators and to support the design of residential urban patterns that can save and produce energy from the outset, rather than attempting to retrofit performance after fundamental morphological decisions have already been fixed.

1.1 Review objectives

The research objectives can be stated as:

• To synthesize post 2020—evidence on how urban morphology indicators influence passive energy efficiency outcomes, particularly cooling load reduction, and active solar energy outcomes (photovoltaic potential and yield) in residential complexes at the early design stage.
• To identify the urban morphology indicators most frequently applied in relation to passive and active energy outcomes, and to examine how these indicators are defined, operationalized, and measured across the literature.
• To map the main evidence gaps, methodological inconsistencies, and unresolved issues that currently limit reliable early-stage guidance for passive and active energy-efficient urban design.
• To propose a parametric passive-active urban design framework for the early-stage design of residential neighborhoods in the MENA region, with the aim of reducing cooling energy demand, enhancing photovoltaic energy generation, and supporting progress toward zero-energy urban patterns.

1.2 Climatic context

According to the Köppen–Geiger climate classification, the MENA region includes a broad range of climate zones, although hot desert (BWh) is the most dominant, covering much of North Africa and the Arabian Peninsula. These areas are characterized by extremely low annual rainfall, often below 100 mm, and very high summer temperatures, while cold desert (BWk) occurs more locally in upland and continental interior areas (Hamed et al., 2023; M’hamdi et al., 2022; Trájer, 2023). Semi-arid steppe climates, including hot semi-arid (BSh) and cold semi-arid (BSk), form transitional belts between desert and more temperate zones, with slightly higher rainfall but continued water scarcity and strong seasonal variation (Tanarhte et al., 2024; Valjarević et al., 2025). Mediterranean climates, particularly hot-summer (Csa) and warm-summer (Csb), are found along the Mediterranean coast and in upland regions, with dry summers, more wet winters, and moderate annual precipitation (Zerboni and Nicoll, 2019; Apreda et al., 2020). Tropical savannah (Aw) appears in southern Sudan and the Sahel, while temperate (C) and cold (D) climates occur in coastal, mountainous, and northern Middle Eastern areas (Wefers et al., 2026).

1.3 Scoping review timeframe

The review was restricted to studies published from January 2020 to the final search date in 2025 because this period captures the point at which the literature became both substantially larger and methodologically more relevant to early-stage urban-energy design. As shown in Figure 1, Preliminary searches showed a marked rise in publication volume after 2020, with records increasing from 39 (Web of Science) and 38 (Scopus) in 2010–2014, and 86 and 89 in 2015–2019, to 177 and 202, respectively, from 2020 onward. This expansion coincided with the rapid maturation of parametric and simulation-based urban design workflows, which are particularly necessary in morphology–energy research because urban form is governed by numerous interdependent urban morphological indicators—such as density, height, spacing, aspect ratio, and orientation—that are difficult to evaluate through single-scenario analysis. In recent studies, parametric design tools, understood as variable-driven modeling environments that generate and test multiple design iterations, have increasingly been operationalized through Rhino–Grasshopper and linked simulation platforms, enabling integrated assessment of solar access, thermal comfort, airflow, and energy performance during early design stages (Bedra et al., 2023; Ibrahim et al., 2021; Castrejon-Esparza et al., 2025). In the early 2000s, the first tools supporting dynamic parametric manipulation established the field’s conceptual foundations (ElSayed et al., 2025). The release of Grasshopper in 2008 marked a major inflection point (Shao et al., 2026; Bakmohammadi and Noorzai, 2020). During the 2010s, expanding plugin ecosystems significantly accelerated adoption in design practice (Natanian and Auer, 2020; Preisinger and Heimrath, 2014). Since 2020, AI, generative methods, and cloud workflows have rapidly extended parametric design to more complex urban-scale applications (Shen et al., 2026; Fichera et al., 2025; Bounnah and Bourbia, 2026). Restricting the review to the post-2020 period also aligns the evidence base with the contemporary economics of photovoltaics, as solar PV had become one of the lowest-cost options for new electricity generation by 2020, the global weighted-average levelized cost of electricity for utility-scale PV declined by a further 7% in 2020, and PV module prices continued to fall through 2024 (IRENA, 2024; IEA PVPS, 2025). Accordingly, post-2020 studies are more comparable to current solar deployment conditions than studies produced under earlier cost regimes.

2 Methods

2.1 Scoping reviews

The study followed the PRISMA extension for scoping reviews (Tricco et al., 2018), implementing eligibility criteria, information sources, database search strategy, selection of sources of evidence, data charting, and synthesis.

2.2 Eligibility criteria for relevant studies

The study included papers from two databases (Scopus and web of science), peer-reviewed, English-language full texts on residential complexes at block/neighborhood scale during the early design stage. Studies had to operationalize at least one urban-morphology indicator (e.g., H/W, SVF, density, spacing, orientation, etc.) and report design strategy for passive urban form to reduce energy consumption and/or active solar design for energy production (rooftop/façade PV potential/yield). Review papers were used as background only and shaping background knowledge for this review. The review focused on studies published from 2020 to 2025, as mentioned in section 1–3. As an extra inclusion limitation, articles which were conducted in climate zones that do not consume high energy for cooling loads were excluded and special concern were given to studies done in climate zone that are like the MENA region climate according to the Köppen (or Köppen-Geiger) climate classification system. Moreover, If the study examines only microclimate or microclimatic parameters without interpreting data for passive cooling loads decreasing or active solar energy production then it was excluded for the “insufficient data” reason.

2.3 Information sources

Scopus and Web of Science were searched for peer-reviewed, English-language publications. Gray literature and other databases were not included. Conceptually, the search strategy covered four domains: (1) urban context or urban morphology; (2) urban morphology and design parameters; (3) passive-energy, solar, and photovoltaic outcomes; and (4) residential settings. Synonyms, abbreviations, and spelling variants within each domain were connected using the Boolean operator OR, while the principal conceptual domains were combined using AND according to the database-specific syntax of Scopus and Web of Science. The final eligibility search was conducted in January 2026 and was restricted to publications dated from 1 January 2020 to 31 December 2025. The complete database-specific search strings and applied limits are presented in Table 2, while the corresponding retrieval totals are reported in Section 2.4 and Figure 2. Records were exported in CSV format with author, title, publication year, source, DOI, abstract, and keyword information. A separate exploratory search covering 2010–2025 was conducted solely to describe publication trends in Figure 1; records identified through that exploratory search were not entered into the eligibility-screening process or included in the PRISMA counts.

Table 2. The advanced-search string.

2.4 Selection of sources of evidence

Records retrieved from Scopus and Web of Science were exported to Microsoft Excel and screened following a structured two-stage process. The database search identified 373 records, including 196 from Scopus and 177 from Web of Science. After removing 92 duplicates, 281 titles and abstracts were screened. Screening was conducted using Rayyan, with both authors independently reviewing titles and abstracts against the predefined eligibility criteria. Disagreements were resolved through discussion and consensus between the two authors. Based on the predefined eligibility criteria, 216 records were excluded at the title and abstract stage. Sixty-five full-text articles were then assessed for eligibility, of which 32 were excluded. Full-text screening was also conducted by both authors, and final inclusion decisions were agreed upon by consensus. The final review included 33 studies, including 14 studies classified within the MENA-climate subset. The full selection pathway and exclusion reasons are presented in the PRISMA-ScR flow diagram in Figure 2.

2.5 Data charting process

A data-charting template was co-developed and piloted by the two authors using Microsoft Excel. The template captured bibliographic information, study context, methodological approach, urban morphology indicators, early-stage design indicators, passive design strategies, active solar/PV metrics, validation procedures, and reported outcomes. Data were charted independently by the authors, compared for consistency, and any discrepancies or ambiguous items were resolved through discussion. The final charting items are summarized in Table 3.

Table 3. Data charting items.

2.6 Synthesis of results

Evidence was synthesized narratively and in tables. Studies were grouped by outcome domain (passive active or both), morphology indicator, climate zone, and method/workflow. Review papers were not included in the evidence synthesis. When identified during screening, they were consulted only to cross-check relevant terminology and to contextualize reported research gaps, particularly gaps related to underrepresented urban morphological indicators, methodological approaches, validation procedures, and passive or active energy outcomes.

3 Results

3.1 Articles analysis

Along the selected time span, the last 3 years witnessed accelerating interest in early-stage residential urban morphology, and passive- active energy efficiency outcomes. Publication volume increased to reach 9, 7, 8 papers for the years 2023, 2024, and 2025, respectively. Figure 3 shows the distribution of included studies across years. The study area across the 33 included publications were distributed along 16 countries, however the greater interest was recorded in China. According to the Köppen climate classification, the reviewed studies are unevenly distributed across climate zones. Most publications focus on humid subtropical (Cfa; e.g., Jiang and Araji, 2023; Shi et al., 2025), and Mediterranean (Csa; e.g., Harbi et al., 2024; Mangan et al., 2021; Abu Dab’at and Alqadi, 2024; Murathan and Manioğlu, 2025) cities, which together account for more than half of the papers sample. A second tier of cases is located in warm-summer or monsoon subtropical climates (Cwa) e.g., (Cui et al., 2025; Chen et al., 2020; Lin et al., 2025), and mid-latitude steppe climates (BSk) e.g., (Ghasemi Sangi et al., 2023; Liu et al., 2025). Only a small proportion of studies address climate zones that are similar to the dominant climate zone in the MENA region; just four studies examined hot desert (BWh) and/or semi-arid steppe (BSh) contexts (Alhussain et al., 2024; Zambito et al., 2022; Hegazy, 2020). The temperate oceanic (Cfb) and cold continental (Dfb, Dwa) climates were represented in some studies, e.g., (Merollari and Dervishi, 2024; Wu and Liu, 2023). Overall, the evidence base is clearly skewed toward temperate–subtropical settings, with limited coverage of arid and hot desert regions. Figure 4 shows the distribution of included studies across countries and different climate zones.

3.2 Early-design stage guidance outcomes

All the included studies were conducted with the aim of informing decisions made during the early stages of urban form design, whether explicitly or implicitly. In some cases, this objective was clearly stated, with the studies directly positioning their findings as guidance for early-stage design development (Ismaail and Mahboob, 2024). In other cases, the early-stage design relevance was less explicitly articulated, yet it could still be inferred from the nature of the investigated urban morphological indicators, scenarios, and design-oriented outcomes (Harbi et al., 2024; Xu et al., 2023). The authors in (Mutani and Todeschi, 2020) state the simplified urban-scale model “can also be used as a decision tool to support urban design explorations and for policy purposes.” Results in other studies are explicitly translated into urban design and planning guidance (Cui et al., 2025). Some studies continued to develop an evaluation procedure to assess the most influential urban indicators and their inter-correlations to inform design decisions on urban density, building form and BIPV layout before detailed design (Jiang and Araji, 2023).

3.3 The examined morphological urban indicators

Across the included studies, urban morphology indicators fall into a small set of repeatedly operationalized families. Through the reviewed literature, urban morphology indicators were systematically categorized by authors into three primary sets: building-level, layout, and site-scale indicators. These morphological indicators provide a comprehensive perspective for linking physical form to passive and active energy efficiency outcomes. The recurrence of urban morphological indicators across the three categories is markedly uneven within each category. As reflected by the relative prominence of the indicators, building-related parameters are the most repeatedly reported, particularly building height and building plan, followed by building orientation, surface-to-volume ratio, density, and shape factor. Layout indicators also show substantial repetition, with density emerging as the dominant parameter, followed by aspect ratio (H/W), spacing, sky view factor (SVF), and building distribution, which together capture the spatial structure of the urban fabric. In contrast, site indicators are minimally represented, with site area appearing as the principal recurring variable. The overlap of certain indicators across more than one category further indicates that urban morphology is inherently multi-scalar and that several key descriptors influence energy performance simultaneously at the building and urban-layout levels. Figure 5 shows the three main categories of urban morphology indicators and the percentage of the recurrence of indicators across the three categories. However, terminology often varies across studies with different labels and calculation methods for some indicators. The following subsections illustrate the three categories of the urban indicators, and Table 4 shows definitions of different indicators and related indicators and references from where they were retrieved.

Table 4. Urban morphological indicators definitions and related indicators.

3.3.1 Building-level morphological indicators

As buildings considered as the main component of any urban layout, the first morphological indicator to be mentioned is building plan. Building plan is primarily captured through aspect ratios, with length and width relations (LWR, L/W, or R) as mentioned in some studies such as (Mangan et al., 2021; Liu et al., 2025; Merollari and Dervishi, 2024). Absolute area measures describe the scale and building footprint or ground-floor area, floor area per story, unit or module size, parcel area, and the core area percentage (Aydin and Oral, 2024; Jiang and Araji, 2023; Murathan and Manioğlu, 2025; Hegazy, 2020; Sagdicoglu et al., 2025). Grid-based building form is encoded genetically in two studies (Shi et al., 2025; Murathan and Manioğlu, 2025). Building height is often expressed as absolute dimensions for individual buildings; metric heights or storey counts such as maximum building height, height by orientation, and number of floors per block. This indicator was examined in most of included articles, for example (Alhussain et al., 2024; Jiang and Araji, 2023; Ismaail and Mahboob, 2024). When multiple height regimes coexist on one site, statistical indicators such as average building height (ABH), height distribution of blocks, and the standard deviation of building heights (SDBH, BHsd) instead to capture the central tendency and variability of the whole ensemble, offering a more synthetic description of mixed-height fabrics; for examples as mentioned in (Ghasemi Sangi et al., 2023; Liu et al., 2023b).

Across the reviewed literature, envelope-related indicators used frequently and reflected many properties of buildings skin. Roof-to-façade area ratio is identically defined in two studies, as roof area divided by façade area (Merollari and Dervishi, 2024; Tian and Xu, 2021). Plan area and envelope measures appear in three studies, combining footprint area and core percentage with envelope-to-site ratios repeated in (Jiang and Araji, 2023; Merollari and Dervishi, 2024; Tian and Xu, 2021). Overhang morphology is captured once via overhang projection fraction. Wall and window material properties (reflectance, transmittance and U-value) are each defined once per surface type in a single study (Chen et al., 2020). Window-to-wall ratio is consistently defined but discretized differently across three studies (Jiang and Araji, 2023; Abu Dab’at and Alqadi, 2024; Chen et al., 2020). Another morphological indicator at the building level is building orientation is repeatedly studied as a generic variable under labels such as “BO” or “Orientation,” (Liu et al., 2023a; Mangan et al., 2021; Liu et al., 2025). Other entries specify how orientation is quantified, for example as the mean façade angle to south (OAS), the rotation angle of a project building between 0–180°, settlement direction relative to streets, or block orientation in cardinal/angular form (Aydin and Oral, 2024; Cui et al., 2025; Chen et al., 2020; Dhanraj et al., 2023).

Building form is captured through plan aspect ratio and footprint-based typologies (Aydin and Oral, 2024; Mangan et al., 2021; Abu Dab’at and Alqadi, 2024; Xu et al., 2023; Dhanraj et al., 2023). Many indicators operationalize building form categorically (such as slab or courtyard types) all defined by footprint shape and building compactness (Abu Dab’at and Alqadi, 2024; Xu et al., 2023). Most studies use “building shape coefficient” and “shape factor” for closely related envelope-compactness indices based on surface-to-volume ratios, so it is reasonable to place them in a single category such as building shape coefficient. Across the studies, all indicators express building shape coefficient as a ratio of external envelope to enclosed volume, despite labels varied to include shape coefficient (SCB, BSC), envelope-volume ratio (E/V), Average Shape Ratio (ASR), or surface-to-volume ratio (S/V; Ghasemi Sangi et al., 2023; Abu Dab’at and Alqadi, 2024; Cui et al., 2025; Lin et al., 2025; Liu et al., 2025; Merollari and Dervishi, 2024; Tian and Xu, 2021). Building density (BD) consistently captures ground-level intensity of built occupation but with two main operationalizations. Four studies define BD as a building coverage ratio, i.e., building footprint divided by site or block area, whether expressed directly as footprint/site area, percentage of site area, or fraction of occupied 10 × 10 m grid cells (Zambito et al., 2022; Shi et al., 2025; Tian and Xu, 2021; Jin et al., 2023).

3.3.2 Layout morphological indicators

Across studies, layout composition is mainly described through categorical indicators of how buildings and open spaces are arranged. Several terms capture horizontal distribution patterns: spatial patterns of buildings and open space, scattered degree, space or layout types, block pattern, open-space location within plots, cluster categories, and building position (attached, semi-attached, detached), all emphasizing relative placement rather than metric distances (Shi et al., 2025; Lin et al., 2025; Hegazy, 2020; Wu and Liu, 2023; Xu et al., 2023; Jin et al., 2023). Setback and spacing indicators translate these patterns into explicit distances, specifying side and rear setbacks, minimum separations between detached units, and context distance classified as small/medium/large (Hegazy, 2020; Trepci et al., 2021). Building spacing indicators describe horizontal separations between buildings or between buildings and circulation space. Collectively, this family of spacing metrics appears in at least five closely related formulations across four studies. Minimum building spacing, inter-building distance, block spacing and building interval all measure center-to-center or wall-to-wall distances between neighboring buildings in meters, differing mainly in whether they report minimum or average values and whether spacing is set by daylight, fire-safety requirements or shading criteria (Ghasemi Sangi et al., 2023; Cui et al., 2025; Sagdicoglu et al., 2025; Tian and Xu, 2021). Distances from blocks to adjacent buildings or roads, together with explicit road-width classes of 10–20 m, extend this concept to the street right-of-way (Ghasemi Sangi et al., 2023; Murathan and Manioğlu, 2025; Cui et al., 2025; Sagdicoglu et al., 2025; Tian and Xu, 2021; Dhanraj et al., 2023). A second group of indicators measures distance to centers: building-to-centroid distance and its standard deviation capture the internal spatial dispersion of buildings within a block (Cui et al., 2025), whereas distance from the city center records each block’s position in the wider urban structure (Mahaya et al., 2022). Finally, urban typology is expressed through block-type labels (tower, open courtyard, slab, hybrid) and a more generic “urban typology,” representing a repeated but variably detailed categorization of block-scale form (Mahaya et al., 2022; Mangan et al., 2021).

Layout density across the reviewed studies is captured by interrelated indicators linking built floor area, building footprint and open space to land area. The most common group is floor-area ratio (FAR) as described in many studies such as (Chen et al., 2020; Lin et al., 2025; Ismaail and Mahboob, 2024; Sagdicoglu et al., 2025). Other indicators were retrieved for representing density; plot ratio and floor-space index (FSI), e.g., (Aydin and Oral, 2024; Mangan et al., 2021; Murathan and Manioğlu, 2025), all defined as total building floor area divided by plot or urban area and repeated in many entries, sometimes as continuous values and sometimes fixed at specific levels. Ground coverage is described by ground space index (GSI) e.g., (Hegazy, 2020; Tian and Xu, 2021), or Building coverage ratio (BCR) e.g., (Jiang and Araji, 2023), built area ratio, e.g., (Cui et al., 2025); which all measure building footprint per land area but differ in whether they express coverage as a ratio or categorical bands. Open Space Ratio (OSR) provides a complementary open-space metric, defined either as open space per site area or as (1–GSI)/FSI, i.e., open space per unit floor area (Mahaya et al., 2022; Murathan and Manioğlu, 2025). Additional indices—volume-based density and impervious/pervious surface fractions—extend density representation to three-dimensional massing and ground-surface composition (Harbi et al., 2024; Hegazy, 2020; Wu and Liu, 2023).

Heigh to width relations are consistently used to characterize urban canyon geometry, with most studies defining H/W as building or canyon height divided by street width or distance between buildings, e.g., (Harbi et al., 2024; Lin et al., 2025; Xu et al., 2023). Two formulations labeled “aspect ratio (AR)” are equivalent, specifying the ratio of building height to building interval or spacing, and can be grouped with H/W (Merollari and Dervishi, 2024; Tian and Xu, 2021). Directional variants provide average aspect ratios by street orientation, adding anisotropy to the same basic measure (22). Sky view factor (SVF) is consistently defined as the fraction of the sky dome visible from a given point, expressed as a dimensionless value between 0 and 1 (Murathan and Manioğlu, 2025; Wu and Liu, 2023; Mutani and Todeschi, 2020). Several formulations emphasize different contexts—ground-level SVF with typical values, building-level SVF computed as the average of ground and roof, and mean SVF to represent overall canyon openness—but all retain the same mathematical meaning and (Murathan and Manioğlu, 2025; Wu and Liu, 2023; Mutani and Todeschi, 2020; Liu et al., 2023b). Two studies merely name SVF without further specification, indicating the same indicator is reused at least six times with varying levels of descriptive detail (Murathan and Manioğlu, 2025; Wu and Liu, 2023; Xu et al., 2023; Mutani and Todeschi, 2020; Liu et al., 2023b; Xie et al., 2023). Vegetation within the urban layout is represented by two conceptually related but methodologically distinct indicators. NDVI is a remotely sensed spectral index that expresses relative vegetation abundance or greenness on a dimensionless scale, without explicit reference to site area or plant structure (Mutani and Todeschi, 2020). In contrast, the green plot ratio GPR-W/GPR-S is a leaf-area-based density metric, defined as the ratio of total leaf area of all plants to site area, with separate values for winter and summer to capture seasonal foliage change (Murathan and Manioğlu, 2025). Thus, NDVI appears once as a generic greenery indicator, whereas GPR is introduced as a two-season variant of a single green plot ratio measure, offering a more morphologically grounded description of vegetative massing (Murathan and Manioğlu, 2025; Mutani and Todeschi, 2020).

3.3.3 Site morphological indicators

Site-scale indicators in the reviewed studies describe both plot geometry and its position in the wider urban structure. Block site area (BSA) and land area (LA) both quantify total site area in m² and can be treated as repeated formulations of the same plan-area measure (Cui et al., 2025; Lin et al., 2025). Site width and length provide the primary linear dimensions from which area or frontage can be derived (Alhussain et al., 2024). Locational context is captured through distance to the city center (DisCity) and distance to the nearest road (DisRoad), which together express the site’s macro- and micro-accessibility within the network (Liu et al., 2025). Finally, adjacent street width specifies the cross-sectional size of bordering streets, complementing DisRoad by characterizing the immediate street environment rather than simple proximity (Sagdicoglu et al., 2025).

3.4 Morphological indicators connected to passive or active energy efficiency outcomes

Across the 33 included studies, 14 studies were conducted for passive outcomes, 4 studies were conducted for active outcomes (PV/solar), and 15 studies were conducted for combined outcomes (active and passive). Figure 6 shows the frequency of urban morphological indicators examined in passive, active, and combined outcomes. Building-scale parameters dominate overall, particularly building height (Alhussain et al., 2024; Mahaya et al., 2022; Jiang and Araji, 2023; Lin et al., 2025; Merollari and Dervishi, 2024; Wu and Liu, 2023; Xia and Li, 2021), layout density (Alhussain et al., 2024; Mahaya et al., 2022; Jiang and Araji, 2023; Xie et al., 2023; Xia and Li, 2021) and building plan (Jiang and Araji, 2023; Merollari and Dervishi, 2024), which appear most frequently are highlighting their central role in linking passive and active outcomes. Passive-focused studies emphasize building height (Mangan et al., 2021; Abu Dab’at and Alqadi, 2024; Hegazy, 2020; Ismaail and Mahboob, 2024; Dhanraj et al., 2023; Trepci et al., 2021) and layout density (Abu Dab’at and Alqadi, 2024; Murathan and Manioğlu, 2025; Liu et al., 2025; Hegazy, 2020; Chen et al., 2024) reflecting their importance in cooling loads mitigation. Active-focused studies give relatively more attention to density (Shi et al., 2025; Tian and Xu, 2021), building distribution (Jin et al., 2023), and orientation (Cui et al., 2025), consistent with solar exposure requirements. In contrast, indicators such as vegetation, population density, block-level shading, and occupancy are comparatively underrepresented. Overall, the distribution suggests a strong research convergence around density, height, and geometric form as integrative indicators bridging passive cooling and solar energy generation objectives.

3.5 Tools used for passive and active analyses

Rhino and Grasshopper clearly dominate as urban form modeling platforms, being used in well over half of the studies for creating parametric 3D block and district geometries; e.g., (Alhussain et al., 2024; Abu Dab’at and Alqadi, 2024; Cui et al., 2025; Lin et al., 2025; Merollari and Dervishi, 2024; Xia and Li, 2021). Once the forms are built in Rhino/Grasshopper, different plug-ins are chained for simulation: Ladybug is mainly used for importing weather files and mapping solar access or climate-based indicators (Liu et al., 2023a; Ghasemi Sangi et al., 2023), while Honeybee links Rhino/Grasshopper models to EnergyPlus and Radiance for building energy and daylight/solar simulations; e.g., (Ghasemi Sangi et al., 2023; Murathan and Manioğlu, 2025; Liu et al., 2023b; Xie et al., 2023). Dragonfly and the Urban Weather Generator extend this workflow to neighborhood-scale weather files and modified EPW data (Liu et al., 2023a; Wu and Liu, 2023; Liu et al., 2023b). Other Grasshopper-based add-ons include DIVA and Archsim for daylight and energy simulation in early-stage layouts (Jiang and Araji, 2023), Radiance/GenCumulativeSky and Daysim for detailed solar and daylight metrics (Liu et al., 2023a; Merollari and Dervishi, 2024; Wu and Liu, 2023; Xia and Li, 2021), and VITALITY chain for performance assessment in one study (Cui et al., 2025). Beyond the Rhino software, several papers rely on stand-alone energy tools such as DesignBuilder (front-end to EnergyPlus; Mangan et al., 2021; Abu Dab’at and Alqadi, 2024; Hegazy, 2020), Autodesk Revit with Green Building Studio (Aydin and Oral, 2024; Ismaail and Mahboob, 2024), CitySim Pro for district energy balance (Harbi et al., 2024; Zambito et al., 2022), and DOE prototype models coupled to EnergyPlus (Trepci et al., 2021), while two studies replace physics-based engines with machine-learning simulators implemented in Python or other ML environments (Liu et al., 2025; Dhanraj et al., 2023).

A subset of work explicitly incorporates microclimate simulation: ENVI-met is used either coupled one-way to EnergyPlus via Grasshopper (ENVI-met output providing boundary microclimate for EnergyPlus; Murathan and Manioğlu, 2025) or alongside EnergyPlus/OpenStudio in a two-stage workflow (Chen et al., 2024). Meteonorm appears as the main generator of hourly climate data for CitySim and other energy models (Harbi et al., 2024; Mahaya et al., 2022; Mangan et al., 2021), complementing or replacing typical EPW files. Across the sample, additional modeling and simulation tools include EnergyPlus itself as the core engine in many workflows (Chen et al., 2020), OpenStudio as an alternative interface (Xia and Li, 2021; Chen et al., 2024) for roof-scale electricity yield calculations (Zambito et al., 2022).

For morphology acquisition and GIS-based analysis, a variety of platforms are used: ArcGIS/ArcGIS Pro (including GIS 10.4) for locating residential blocks, extracting roof/floor area (Aburmalah and Üzümcüoğlu, 2025; Abu Dab’at and Alqadi, 2024; Jin et al., 2023); Relief Visualization Toolbox with a DSM of Turin to derive 3D morphology (Mutani and Todeschi, 2020); and web-mapping sources such as Baidu Maps (and Baidu geo-databases; Cui et al., 2025; Xie et al., 2023; Chen et al., 2024), OpenStreetMap (Mahaya et al., 2022; Murathan and Manioğlu, 2025; Xie et al., 2023), and Google Maps (Hamed et al., 2023) satellite imagery to reconstruct building footprints, heights and block patterns. One study additionally cites BIGEMAP and generic GIS platforms for deriving ENVI-met input morphology (Chen et al., 2024), while several others rely on satellite imagery and field surveys directly, without naming a GIS package (Murathan and Manioğlu, 2025; Sagdicoglu et al., 2025; Dhanraj et al., 2023). In contrast, a large group of studies do not use external GIS or 3D city model, instead generating hypothetical parametric forms entirely inside Rhino/Grasshopper or DesignBuilder (Xu et al., 2023; Sagdicoglu et al., 2025; Wang et al., 2025). Table 5 views the different methods used across previous studies.

Table 5. Methods used for passive and active analyses.

3.6 Validation in different studies

Validation methodologies across the analyzed literature exhibit a significant spectrum of rigor, ranging from direct empirical verification to a total reliance on the established credibility of simulation engines. Several studies employ robust field validation by comparing simulation outputs against historical EUI data (Alhussain et al., 2024), empirical datasets from dozens of existing buildings (Jiang and Araji, 2023), or actual local utility consumption records (Harbi et al., 2024; Shi et al., 2025; Lin et al., 2025). For instance, specific field measurements such as in Murathan and Manioğlu (2025) and Xu et al. (2023) and comparative heating demand analysis (Aburmalah and Üzümcüoğlu, 2025) provide high-fidelity calibration for thermal models. Other researchers utilize alternative methods, such as model-to-model validation (Ghasemi Sangi et al., 2023), benchmarking against Department of Energy (DOE) prototype buildings (Trepci et al., 2021), or internal validation through algorithm convergence and qualitative plausibility checks (Liu et al., 2025; Xu et al., 2023; Sagdicoglu et al., 2025; Dhanraj et al., 2023). Conversely, a notable portion of the research does not report explicit calibration or case-specific validation against measured energy or PV data (Aydin and Oral, 2024; Mangan et al., 2021; Zambito et al., 2022; Hegazy, 2020; Merollari and Dervishi, 2024; Xia and Li, 2021; Chen et al., 2024). In these instances, authors frequently justify the absence of direct validation by citing the use of industry-standard or “previously validated” software engines like EnergyPlus and Radiance (Chen et al., 2020; Wu and Liu, 2023; Tian and Xu, 2021) or by acknowledging the inherent logistical limitations of acquiring field data for large-scale urban modeling (Abu Dab’at and Alqadi, 2024; Liu et al., 2023b).

3.7 Insights for the MENA region

3.7.1 Number of studies that are located in similar climate zones

In the present review sample, only a limited share of the studies examining passive and active energy efficiency outcomes at the urban-design scale were conducted in actual MENA cities, with a considerable portion of the evidence instead derived from climatically analogous contexts. This pattern is consistent with broader regional reviews indicating that studies on passive design in the Middle East remain relatively few. Nevertheless, the dominance of Csa, BWh, and BSk climates in the reviewed sample suggests strong climatic relevance to many MENA settings. The need for more region-specific research is pressing, as electricity demand in MENA is projected to rise sharply, with around 40% of the increase to 2035 expected to come from cooling and desalination, while solar PV capacity is on course to expand tenfold over the same period. At the same time, regional reviews, policy frameworks, and net-zero roadmaps indicate substantial potential to combine climate-responsive urban form, passive cooling, efficient systems, and renewable energy integration to support near-zero and zero-emission targets; simulation evidence for representative MENA cases has already shown that improving building fabric and integrating photovoltaics can reduce primary energy demand by more than 70%. With respect to outcome type, passive performance clearly dominates the sample: 10 studies assess passive outcomes only, without modeling active systems (Aydin and Oral, 2024; Aburmalah and Üzümcüoğlu, 2025; Ghasemi Sangi et al., 2023; Mangan et al., 2021; Abu Dab’at and Alqadi, 2024; Murathan and Manioğlu, 2025; Hegazy, 2020; Ismaail and Mahboob, 2024; Sagdicoglu et al., 2025; Dhanraj et al., 2023) whereas only four studies examine both passive and active outcomes (Alhussain et al., 2024; Harbi et al., 2024; Mahaya et al., 2022; Zambito et al., 2022); notably, where active measures are included, they are almost entirely solar-based, focusing on PV/BIPV configuration, solar suitability, self-consumption, and the share of cooling demand met by PV rather than on broader active-system strategies (Alhussain et al., 2024; Harbi et al., 2024; Mahaya et al., 2022; Zambito et al., 2022).

The 14 reviewed studies collectively examine how urban morphology influences building and district energy performance, but they differ in purpose, analytical scale, and the extent to which active renewable systems are incorporated. One group primarily seeks to optimize urban form or specific morphological parameters to reduce cooling energy demand in residential contexts (Aydin and Oral, 2024; Aburmalah and Üzümcüoğlu, 2025; Ghasemi Sangi et al., 2023; Abu Dab’at and Alqadi, 2024; Hegazy, 2020; Ismaail and Mahboob, 2024; Sagdicoglu et al., 2025; Dhanraj et al., 2023). A second group links morphology with solar-responsive design and renewable integration by examining BIPV-oriented building form, PV/solar energy production, solar performance in apartment districts, and the capacity of roof-integrated PV to offset neighborhood cooling demand (Alhussain et al., 2024; Harbi et al., 2024; Mahaya et al., 2022; Zambito et al., 2022). A third strand broadens the assessment framework by incorporating additional criteria such as CO₂ emissions, life-cycle energy cost, outdoor thermal comfort, and urban heat-island effects alongside energy demand (Aydin and Oral, 2024; Mangan et al., 2021; Liu et al., 2025). Despite these differences, the studies are highly comparable in that they are predominantly simulation-based, focus mainly on residential urban fabrics, and treat morphological indicators as the main explanatory factors for passive outcomes such as cooling demand, EUI, electricity use, solar access, and cooling-load intensity. Geographically, the sample combines MENA cases with climatically analogous non-MENA settings, indicating that part of the knowledge base relevant to the region is still inferred from comparable external contexts. In terms of climate distribution, the literature is strongly concentrated in warm-dry and Mediterranean conditions: Csa appears in nine studies, BWh in four studies, BSk in four publications, and BSh in only one; when all climate occurrences are counted, this corresponds to 50.0% Csa, 22.2% BWh, 22.2% BSk, and 5.6% BSh across 18 total climate-zone mentions in the 14 publications. With respect to outcome type, passive performance clearly dominates the sample: 10 studies assess passive outcomes only, without modeling active systems, whereas only four studies examine both passive and active outcomes; notably, where active measures are included, they are almost entirely solar-based, focusing on PV/BIPV configuration, solar suitability, self-consumption, and the share of cooling demand met by PV rather than on broader active-system strategies. Table 6 shows the 14 studies, purpose of study, city, and climate zone according to the Köppen climate classification. Figure 7 shows the percentage of the distribution of climate zones for the 14 studies.

Table 6. Studies that are located in similar climate zones of the MENA region.

3.7.2 Contributions to energy-efficient urban forms in MENA-like climates

Across hot-desert (BWh), hot semi-arid (BSh) and hot-summer Mediterranean (Csa) contexts comparable to much of the MENA region, the reviewed studies converge on integrated early-stage design guidance that explicitly link urban morphology with passive and active energy performance. Parametric morphological models coupled with simultaneous rooftop/façade PV are used to minimize cooling loads while maximizing PV yield (Alhussain et al., 2024). Trade-off based conceptual-design models for hot-desert housing allow rapid ranking of alternative residential forms by combined thermal comfort, cooling demand and solar potential (Ismaail and Mahboob, 2024; Sagdicoglu et al., 2025). GIS–BIM workflows quantify how street geometry, density and layout scale influence neighborhood energy demand in hot-summer Mediterranean cities, providing guidance for block and canyon design (Aburmalah and Üzümcüoğlu, 2025; Hegazy, 2020). Several studies develop automatic 3D morphology-generation and solar-simulation pipelines for existing or planned residential districts, enabling fast exploration of PV yield under local shading and regulatory constraints (Ghasemi Sangi et al., 2023; Wu and Liu, 2023). Work in North African climates extends this to PV/solar-energy systems, delivering some of the first detailed techno-economic assessments of roof-integrated PV for multifamily housing (Harbi et al., 2024; Sagdicoglu et al., 2025). Other contributions propose urban-design frameworks that jointly evaluate building energy use, outdoor thermal comfort and urban-heat-island indicators at block scale, supporting climate-sensitive infill in hot dry cities (Abu Dab’at and Alqadi, 2024). Multi-city parametric studies in archetypal Mediterranean climates synthesize these insights into systematic urban-form design spaces, mapping combinations of density, height and envelope form that minimize cooling loads while preserving roof solar access (Mahaya et al., 2022; Dhanraj et al., 2023). Collectively, these studies translate generic principles of compactness, shading and solar exposure into climate-calibrated design support directly applicable to early-stage residential planning in MENA-type climate.

3.7.3 Critical synthesis of consistent, contradictory, and climate-dependent findings in MENA-like climates

The evidence from the 14 studies located in MENA-like climates indicates that urban morphology affects energy performance through a limited set of recurrent mechanisms: solar exposure, mutual shading, surface-to-volume ratio, canyon geometry, building spacing, height distribution, and the availability of roof and façade surfaces for solar-energy systems. A consistent finding across hot-desert, semi-arid, and hot-summer Mediterranean contexts is that compactness, attached or semi-attached forms, courtyard/perimeter arrangements, and reduced exposed envelope area generally decrease cooling loads by increasing self-shading and limiting direct solar gains (Aburmalah and Üzümcüoğlu, 2025; Abu Dab’at and Alqadi, 2024; Hegazy, 2020; Ismaail and Mahboob, 2024; Sagdicoglu et al., 2025; Dhanraj et al., 2023). Similarly, H/W ratio, street width, orientation, building height, FAR/FSI, GSI, OSR, and spacing repeatedly emerge as influential early-stage parameters because they control the balance between solar access and shading at both building and block scales (Aydin and Oral, 2024; Aburmalah and Üzümcüoğlu, 2025; Mahaya et al., 2022; Mangan et al., 2021; Abu Dab’at and Alqadi, 2024; Murathan and Manioğlu, 2025). For active systems, the reviewed studies show that PV and solar-thermal performance depend not only on the quantity of available roof or façade area, but also on shading, façade orientation, canyon geometry, and the temporal match between solar production and cooling demand (Alhussain et al., 2024; Harbi et al., 2024; Mahaya et al., 2022; Zambito et al., 2022).

However, the findings are not uniform, and several apparent contradictions emerge when indicators are interpreted without considering climate, season, or performance objective. Higher density and compactness can reduce cooling demand in hot conditions, but they may also reduce winter solar gains, daylight access, sky view, and PV/BIPV potential (Aburmalah and Üzümcüoğlu, 2025; Harbi et al., 2024; Mahaya et al., 2022; Abu Dab’at and Alqadi, 2024). Conversely, more open, taller, or widely spaced blocks can improve solar access, ventilation, and roof/façade exposure for PV or solar thermal systems, but st the same time, may increase cooling loads by exposing more envelope area to solar radiation (Harbi et al., 2024; Mahaya et al., 2022; Ghasemi Sangi et al., 2023; Zambito et al., 2022). Height also shows contradictory behavior: in some cases, low-rise attached forms are preferable because they reduce energy use and exposed surfaces (Hegazy, 2020; Ismaail and Mahboob, 2024), while other studies show that specific height distributions or taller forms can reduce heating demand or improve solar availability under semi-arid and Mediterranean conditions (Mahaya et al., 2022; Ghasemi Sangi et al., 2023; Zambito et al., 2022). Likewise, larger built-up ratios may increase absolute electricity consumption while reducing energy use intensity per square meter, indicating that total demand and normalized performance can lead to different design rankings (Hegazy, 2020).

These contradictions are largely climate-dependent. In hot-desert and hot-humid contexts courtyard-block cases, cooling reduction is the dominant objective, so compact, shaded, low-to-mid-rise, and attached configurations are generally preferred, provided that daylight and ventilation are protected through setbacks, courts, or spacing (Hegazy, 2020; Ismaail and Mahboob, 2024; Dhanraj et al., 2023). In hot-summer Mediterranean climates such as Hebron, Istanbul, Gaziantep, Guelma, Athens, and Rome, the optimal form is more seasonal: compactness and shading reduce summer cooling loads, while openness, wider streets, and solar access may reduce winter heating demand and improve solar-energy potential (Aburmalah and Üzümcüoğlu, 2025; Harbi et al., 2024; Mangan et al., 2021; Zambito et al., 2022; Abu Dab’at and Alqadi, 2024; Murathan and Manioğlu, 2025; Sagdicoglu et al., 2025). In cold semi-arid contexts such as Tehran, Batna, and Madrid, winter solar availability becomes more important, so the same density or height strategy may improve heating performance but worsen cooling or solar-control performance in summer (Mahaya et al., 2022; Ghasemi Sangi et al., 2023; Zambito et al., 2022). Therefore, the collective evidence suggests that no single morphological parameter has a universally positive or negative effect. Instead, MENA-oriented urban energy design requires climate-calibrated, multi-objective evaluation in which compactness, density, height, spacing, street geometry, and PV/BIPV placement are assessed together rather than independently.

3.7.4 Trade-offs between passive cooling, density and solar harvesting

The trade-off analyses investigate that forms maximizing PV area or yield rarely coincide with those minimizing cooling demand in hot-desert and hot-summer Mediterranean settings (Alhussain et al., 2024; Harbi et al., 2024; Ismaail and Mahboob, 2024; Sagdicoglu et al., 2025),. Rooftop-dominated PV layouts effectively cover midday cooling load peaks but tend to over-generate at noon, but it may also produce surplus electricity around noon (Alhussain et al., 2024). This indicates that roof and façade PV should be treated as complementary strategies rather than interchangeable solar surfaces. Also, compact courtyard or perimeter blocks reduce cooling loads and outdoor heat stress, but also limit sky view and roof area, constraining PV coverage and sometimes reducing daylight penetration (Aburmalah and Üzümcüoğlu, 2025; Hegazy, 2020; Ismaail and Mahboob, 2024). In contrast, taller or more widely spaced blocks improve solar access and ventilation and accommodate larger PV arrays, yet their higher exposed envelope area increases cooling energy use (Harbi et al., 2024; Mahaya et al., 2022; Wu and Liu, 2023). Studies that simultaneously evaluate building loads and urban-climate metrics also show that strategies reducing winter heating (e.g., higher compactness) can amplify summer cooling needs in hot climates, requiring explicit weighting of seasonal performance (Mangan et al., 2021; Abu Dab’at and Alqadi, 2024),. One study further demonstrates that the same morphology may favor one active solar technology while penalizing another: high density and high site coverage improved solar-thermal output but reduced PV productivity because of mutual shading and reduced air circulation for PV cooling (Harbi et al., 2024). The trade-off is also seasonal. In Csa and BSk climates, wider streets or larger inter-building distances can increase winter solar access and reduce heating demand, but they may increase summer cooling demand by exposing façades and outdoor spaces to more solar radiation (Aydin and Oral, 2024; Mangan et al., 2021; Abu Dab’at and Alqadi, 2024; Murathan and Manioğlu, 2025; Sagdicoglu et al., 2025). Conversely, compact and shaded morphologies may be beneficial for cooling-dominated hot climates but less suitable where winter heating or solar-energy harvesting is also a priority (Aburmalah and Üzümcüoğlu, 2025; Mahaya et al., 2022; Ghasemi Sangi et al., 2023). Therefore, the evidence suggests that early-stage design in MENA-like climates should not aim to maximize density, compactness, or PV area separately. Instead, it should identify balanced morphological solutions that jointly consider cooling demand, heating demand, daylight, outdoor thermal comfort, UHI mitigation, and PV/BIPV generation. This supports a multi-objective design approach in which compactness, height, street geometry, spacing, orientation, and solar-system configuration are optimized according to the dominant climate conditions and the intended balance between passive and active energy performance (Alhussain et al., 2024; Aburmalah and Üzümcüoğlu, 2025; Zambito et al., 2022; Abu Dab’at and Alqadi, 2024; Murathan and Manioğlu, 2025; Hegazy, 2020; Ismaail and Mahboob, 2024; Sagdicoglu et al., 2025; Dhanraj et al., 2023).

4 Discussion

4.1 Classification and interrelationships of urban morphological indicators for energy performance assessment

According to the reviewed literature, morphological indicators are diverse, dispersed across studies, and strongly interrelated, which makes their interpretation and comparison challenging. To address this complexity, the most frequently reported indicators influencing active and passive energy-efficiency outcomes were systematically organized and their interconnections were mapped, as illustrated in Figure 8. The figure classifies the indicators into three principal categories: building, layout, and site indicators. Within each group, indicators are further divided into geometric indicators and derived indicators. Geometric indicators refer to the primary physical dimensions and spatial attributes of the urban form, such as building plan dimensions, height, spacing, orientation, site dimensions, and vegetation. In contrast, derived indicators represent composite measures calculated from one or more geometric indicators, including density indices, building shape coefficient, aspect ratio (H/W), block typology, window-to-wall ratio, shape factor, surface coverage properties, elongation, and building aspect ratio. This classification clarifies how basic geometric properties are transformed into higher-level morphological descriptors that are more directly associated with energy-performance assessment.

4.2 Current gaps and challenges

Our scoping review shows that most recent studies examine either passive microclimate control through morphology or active solar harvesting, but rarely both, within a single early stage. This fragmentation is the main barrier to climate aware decisions when mass and urban geometry are still fluid. The review revealed that current research is fragmented across some interrelated gaps, as follows:

• Evidence or contextual gap: Fragmented findings and inconsistent data were detected regarding climate context, local climate zone effects, mixed effect for specific urban parameter (i.e., density), these challenges limit transferable design rules. Moreover, diverse urban morphology indicators and methods impede a unified framework combining energy consumption and PV generation. According to the results, climate zones representative of the MENA region were rarely addressed in the reviewed studies. This underrepresentation is notable, given that these climates require greater attention in passive urban planning strategies to mitigate heat exposure and reduce cooling demand. At the same time, they offer substantial potential for active urban design interventions, particularly for integrating solar energy systems and enhancing on-site renewable energy generation. Accordingly, future research should place stronger emphasis on MENA climate contexts to support the development of urban forms that simultaneously improve thermal performance and maximize solar energy utilization.
• Data and knowledge gap: Comprehensiveness of urban morphology indicators still lacking and energy/ PV interactions underexplored, while analysis of how vegetation, blue–green infrastructure, urban agriculture and morphology metrics affect energy and microclimate is limited
• Methodological gap: Urban energy modeling faces data gaps regarding level of details (LoD) limits and computational challenges. Also, cooling energy demand and solar potential are modeled separately, requiring integrated frameworks. Comprehensive assessment of cooling demand and on-site energy generation motivates machine learning for urban scale energy/solar estimation.
• Empirical gap: Reviews of urban modeling and simulation tools report challenges in validating city-scale simulations due to limited metered data, spatial aggregation and archetype uncertainties. Similar validation gaps affect high-resolution solar potential models, underscoring the need for open datasets and explicit uncertainty analyses.
• Practical knowledge gap: Policy reviews seldom translate into concrete, demand and PV urban form guidelines, and design workflows rarely exploit morphology–energy practical insights. Addressing this requires integration between researchers, architects, urban designers, planers, policy makers and stakeholders to shift practical knowledge from technical findings to planning and design guidelines.

4.3 Proposed methodological framework for passive–active energy-efficient urban design in MENA region

The proposed framework in Figure 9 represents the main contribution of this review because it translates fragmented evidence on urban morphology, passive cooling, solar access, and PV/BIPV integration into a coherent methodological pathway for early-stage passive–active energy-efficient urban design in the MENA region. The reviewed studies show that urban morphology is commonly assessed through building-, layout-, and site-scale indicators, yet these indicators are often examined either from a passive energy-demand perspective or from an active solar-energy perspective, with limited integration between the two. To address this gap, the proposed framework organizes the design process into five phases that move from morphological indicator definition and parametric scenario generation to passive design evaluation, environmental and energy simulation, active solar design, energy-balance assessment, and finally ML-supported decision-making. The framework is not intended to prescribe a single optimal urban form, but to provide a transferable workflow for testing alternative urban configurations under MENA and MENA-like climatic conditions. This is supported by the reviewed MENA-like studies, which demonstrate the relevance of parametric morphology, passive cooling, solar radiation assessment, PV integration, and energy-balance evaluation for hot-desert, semi-arid, and hot-summer Mediterranean contexts.

Phase 0 establishes the input structure of the framework by organizing urban morphological indicators into three categories (building, layout, and site) and further distinguishing them as geometric or derived indicators. By embedding these morphological indicators within a parametric design environment, the framework transforms morphology from a descriptive set of indicators into a controllable system of design parameters. This is important because many previous studies tested selected urban morphological indicators in isolation, whereas the proposed approach enables systematic exploration of interdependent urban morphology scenarios and therefore better reflects the multi-scalar nature of relationships.

Phase 1 focuses on passive design, where the generated scenarios are evaluated through passive strategies aimed primarily at minimizing cooling demand, which is high priority in the MENA region. The explicit inclusion of validation is also a methodological strength, because it reduces the risk of drawing design conclusions from unverified simulation outputs and reinforces the reliability of the framework before scenario scaling. A passive-first sequence is especially appropriate for MENA, where cooling already accounts for nearly half of peak electricity demand and around one-quarter of annual electricity demand, and where cooling is expected to be the largest driver of electricity demand growth to 2035.

Phase 2 extends the workflow from passive form optimization to environmental design through simulation of solar radiation, urban heat island effects, and cooling loads, which are then translated into energy-consumption outcomes. This phase addresses a second gap in the literature: although many studies evaluate either building energy demand or outdoor environmental behavior, fewer treat them as coupled processes within the same methodological sequence. The proposed framework therefore acknowledges that urban morphology influences not only indoor energy use, but also the surrounding microclimate, which in turn feeds back into cooling demand. This coupling is particularly important in MENA applications, where high ambient temperatures, intense solar exposure, and compact urban configurations interact strongly in shaping thermal stress and energy use.

Phase 3 introduces active design through solar energy integration. In contrast to the majority of reviewed studies, which stop at passive optimization, this stage uses the environmental simulation outputs to inform early-stage decisions on PV array, size, placement, and configuration; thereby linking urban form directly to on-site renewable generation. This addresses a clear gap in literature, namely the limited inclusion of active systems and the frequent methodological separation between demand reduction and energy supply. The importance of this stage is amplified in MENA, where World Bank solar resource assessments indicate that countries in the Middle East and North Africa dominate the group of countries with excellent PV conditions, defined by average daily PV output above 4.5 kWh/kWp, with many such high-potential settings also exhibiting relatively low seasonality in output (Energy Sector Management Assistance Program (ESMAP), 2020). In methodological terms, this means that active solar design should not be treated as an add-on, but as a logically integrated response to a regionally abundant resource.

Phase 4 provides the assessment layer of the framework through explicit energy-balance analysis, in which cooling demand is compared with PV power generation for each scenario. This step is critical because it converts separate passive and active metrics into a unified performance logic that can reveal whether a given urban configuration moves the project closer to, or farther from, zero-energy targets. In the reviewed literature, energy demand and solar yield are often reported independently, and only a limited number of studies synthesize them in a common evaluative structure. The energy-balance stage therefore closes an important methodological gap by moving beyond isolated optimization objectives and enabling direct comparison of design alternatives in terms of net performance. Equally important, the outputs of this phase form a structured scenario database that can serve as data input for decision-making and machine-learning applications.

The final layer of the framework extends beyond simulation to decision support. By feeding the scenario outputs into a machine-learning approach, the framework addresses the translational gap between computationally intensive research methods and the practical need for rapid early-stage guidance in design and planning. This is a significant advance over most reviewed studies, which remain case-specific and simulation-heavy, limiting their direct use in routine planning practice. In this sense, the proposed framework does not end with analysis; it creates a reusable knowledge structure that can support surrogate modeling, scenario ranking, and evidence-based policy or design decisions at larger scales.

To clarify the applicability of the framework, it was further checked against representative studies included in the review. Each phase corresponds to methods or outputs already demonstrated in the reviewed literature: parametric morphology generation and indicator testing are used in studies of residential blocks and urban districts (Alhussain et al., 2024; Aburmalah and Üzümcüoğlu, 2025; Mahaya et al., 2022; Ghasemi Sangi et al., 2023; Abu Dab’at and Alqadi, 2024; Murathan and Manioğlu, 2025; Hegazy, 2020; Ismaail and Mahboob, 2024; Sagdicoglu et al., 2025; Dhanraj et al., 2023); passive cooling and energy-demand assessment are addressed in hot-desert, semi-arid, and Mediterranean cases (Aburmalah and Üzümcüoğlu, 2025; Abu Dab’at and Alqadi, 2024; Hegazy, 2020; Ismaail and Mahboob, 2024; Sagdicoglu et al., 2025; Dhanraj et al., 2023); solar radiation and PV/BIPV potential assessment are demonstrated in studies linking urban form with roof/façade solar availability and PV generation (Alhussain et al., 2024; Harbi et al., 2024; Mahaya et al., 2022; Zambito et al., 2022; Wu and Liu, 2023); and energy-balance or demand–generation comparison is reported in studies that jointly assess cooling demand and solar-energy contribution (Alhussain et al., 2024; Harbi et al., 2024; Zambito et al., 2022). Therefore, while the framework remains methodological, it is conceptually validated by mapping its phases to representative reviewed studies and by demonstrating how these phases can be applied to a typical MENA residential neighborhood scenario: first generating alternative urban morphologies, then screening them for cooling reduction, solar exposure, PV/BIPV potential, and finally comparing cooling demand with on-site solar generation.

Machine learning is proposed as a suitable decision-support layer because the framework generates a large number of parametric urban scenarios with multiple interdependent inputs and outputs. Urban morphology indicators interact non-linearly with cooling demand and PV/BIPV generation. Running detailed environmental and energy simulations for every possible early-stage design alternative can be computationally expensive and difficult to integrate into routine planning workflows. Once a sufficient scenario database is generated and validated through simulation, ML models can act as surrogate models that rapidly estimate energy demand, PV yield, and net-energy performance for new design alternatives. In this way, ML does not replace physical simulation; rather, it extends the framework by enabling rapid scenario screening, sensitivity analysis, feature-importance evaluation, and ranking of passive–active design options. This makes the proposed framework more practical for early-stage urban design in the MENA region, where designers need fast feedback on trade-offs between passive cooling and solar-energy harvesting.

Overall, the framework offers a passive-to-active, multi-scale, and performance-based pathway for zero-energy urban design in MENA. Its main strength lies in its sequence: first reduce cooling demand through morphology and passive strategies, then quantify environmental effects, next optimize solar harvest, and finally assess the balance between demand and generation. This sequence is especially suited to the MENA context because the region combines severe cooling pressures with strong solar opportunity. Rather than prescribing a single optimal urban form, the framework provides a robust methodological structure that can be adapted to different cities, climate subzones, and project scales while remaining aligned with the broader objective of achieving zero-energy urban concepts in hot, solar-rich environments.

4.4 Limitations of findings

Although this review focuses on the MENA region, the number of studies conducted directly within MENA countries remains limited. Therefore, part of the synthesis relies on studies from MENA-like climates, including hot-desert, hot semi-arid, cold semi-arid, and hot-summer Mediterranean contexts. These studies are relevant because they share comparable climatic drivers such as high solar radiation, cooling-dominated energy demand, seasonal overheating risk, and the need to balance shading with solar-energy harvesting. However, climatic similarity does not necessarily imply full regional equivalence. The transferability of findings to MENA cities may be affected by local construction systems, envelope standards, cooling technologies, occupancy patterns, energy tariffs, electricity subsidies, urban regulations, socio-economic conditions, and the availability of reliable urban and energy datasets.

Another limitation of this review is that it deliberately focuses on urban morphological indicators that can inform early design-phase decisions. Accordingly, the review prioritizes parameters that can be tested during conceptual urban and neighborhood design, while later-stage factors such as detailed envelope construction, HVAC efficiency, occupant behavior, operational schedules, energy tariffs, regulatory implementation, and post-occupancy performance are not examined in equal depth. Therefore, the findings should be interpreted as morphology-based guidance for comparing early urban-form alternatives, rather than as final predictions of building or district energy performance. Further locally calibrated simulations and monitored studies are needed to validate these relationships under specific MENA urban contexts.

5 Conclusion

This scoping review demonstrates that urban morphology is a decisive factor in shaping both passive and active energy performance in residential neighborhoods, particularly during the early design phase when massing, density, orientation, spacing, street geometry, and block configuration are still flexible. The reviewed literature confirms that urban morphological indicators are not studied evenly: indicators related to early design stage decisions across the three categories (layout, buildings and site) are frequently examined. The review also shows that passive performance outcomes, especially cooling demand, solar exposure, outdoor thermal comfort, and microclimate regulation, are more frequently investigated than active solar-energy generation, despite the strong relevance of PV and BIPV integration for MENA cities. A key finding is that the effect of urban morphology is context-dependent rather than universally positive or negative. Compact and dense urban forms can reduce cooling loads by increasing mutual shading, reducing exposed envelope area, and limiting direct solar gains, which is highly relevant for hot-desert and semi-arid climates. However, the same compactness may reduce daylight availability, sky view, winter solar access, and roof or façade surfaces suitable for PV/BIPV installation. Conversely, more open or taller configurations may improve solar access, ventilation, and PV potential, but can increase cooling demand through greater solar exposure and larger exposed envelope areas. Therefore, the review confirms that no single urban morphology indicator can be optimized in isolation. Early-stage energy-efficient urban design requires a multi-objective balance between passive cooling, solar access, and active design for renewable-energy generation.

The main scientific contribution of this paper is the development of a methodological framework that integrates the classification of urban morphological indicators with parametric design, passive design optimization, environmental and energy simulation, validation, early-stage PV assessment, and energy-balance evaluation. By combining these steps into a single workflow, the framework addresses a major gap between isolated morphology-energy studies and the practical requirements of urban designers and planners. The proposed framework is particularly relevant for MENA contexts, where cooling loads are high, solar radiation is abundant, and early decisions regarding density, orientation, spacing, and urban form can strongly influence both energy demand and renewable-energy generation potential. From a practical perspective, the framework offers a structured pathway for comparing alternative residential urban patterns during the conceptual design stage. It can help architects, urban designers, planners, and decision-makers evaluate whether a proposed urban form reduces cooling demand, preserves adequate daylight and solar access, supports PV/BIPV integration, and contributes to neighborhood-level energy balance. This is important because energy-efficient urban design in MENA cities cannot rely only on compactness, shading, or solar harvesting separately. Instead, it requires coordinated decisions that balance passive and active strategies according to local climate, urban density, building typology, and performance priorities.

MENA city-based evidence remains limited, so that the review partly draws on MENA-like climates. Because the review targets early-stage morphological indicators, later-stage operational factors are less detailed, and transferability may vary with construction systems, envelope standards, cooling technologies, occupancy, tariffs, regulations, socio-economic conditions, and data availability. Methodological differences in scale, tools, climate files, validation, and metrics also prevent universal quantitative thresholds for individual urban form parameters in MENA contexts at present. Future research should move beyond the separate assessment of passive urban morphology and active solar-energy systems toward integrated, climate-responsive frameworks for early-stage urban design in the MENA region. Priority should be given to locally validated studies that test how compact city principles, LCZ-based urban climate classification, zero−/positive-energy neighborhood concepts, and climate-responsive design strategies can be combined under hot-desert, semi-arid, and hot-summer Mediterranean conditions. More multi-objective studies are needed to quantify trade-offs between passive cooling and solar harvesting, especially because forms that reduce heat gain through shading and compactness may also limit solar access and PV yield. Future work should develop open datasets, monitored case studies, uncertainty analyses, and locally calibrated simulation or machine-learning models that jointly evaluate energy demand, urban microclimate, outdoor thermal comfort, and renewable-energy generation. Such research would support the translation of morphology-energy evidence into practical planning guidelines for MENA cities while recognizing that the proposed relationships require further testing across different building types, urban fabrics, regulatory contexts, and socio-economic conditions.

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Supplementary material

The Supplementary material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/frsc.2026.1908111/full#supplementary-material

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Footnotes

Edited by: Roberto Alonso González-Lezcano, CEU San Pablo University, Spain

Reviewed by: Muhammad Azzam Ismail, Ajman University, United Arab Emirates

Nandini Halder, Vishwakarma University, India