Search Results (1,712)

Accurate crop mapping is essential for food security and water resource management in semi-arid North Africa. This study evaluated four machine learning algorithms for crop classification using Sentinel-2 NDVI time series in the Al Haouz region, Morocco with a time series of 12 dates (December 2023–May 2024) using 105,869 ground reference samples. Support Vector Machine (SVM) achieved the highest performance (macro F1-score = 0.80, Overall Accuracy = 81%), followed by XGBoost (0.79), Random Forest (0.79), and Decision Tree (0.71). Class-wise analysis revealed excellent discrimination for apricots (F1 = 0.99) due to distinctive spring phenology, while citrus showed the lowest accuracy (F1 = 0.61) due to confusion with olives. Dynamic Time Warping (DTW) analysis quantified phenological similarity between crops, revealing that classification confusion correlates with profile similarity. Temporal sensitivity analysis revealed that reducing acquisitions from 12 to 8 dates results in only 2.4% performance loss, offering significant operational advantages for resource-limited contexts. February–March acquisitions proved most discriminative, coinciding with peak vegetative differentiation. These findings provide practical recommendations for operational crop monitoring in semi-arid African regions facing water scarcity and food security challenges. Full article

Against the backdrop of accelerating globalization and the reconfiguration of ecological security patterns, border regions—serving as critical carriers of national spatial governance—exhibit pronounced spatial heterogeneity and stage-dependent characteristics in land use evolution that warrant systematic investigation. This study focuses on global border zones to reveal the trends and evolutionary pathways of land use change, thereby providing a scientific basis for border spatial governance. Using the period of 1992–2020, four phases of global land cover data from the European Space Agency (ESA) were employed. Buffer zones of 50 km, 100 km, and 150 km were established along global national boundaries, and the study period was divided into three decadal stages. Border types were classified into terrestrial borders, coastal borders, and island borders. An integrated indicator system was constructed, including the Single Land Use Dynamic Degree (SLUDD), Integrated Land Use Dynamic Degree (ILUDD), and Weighted Composite Transition Intensity. A multi-scale nested analytical framework coupled with transition matrices was applied to assess land use evolution across global, continental, and bilateral national scales. The results indicate the following: (1) Distinct evolutionary pathways exist among border types. Terrestrial borders exhibit a combination of development and ecological restoration, with staged peaks in urban expansion; coastal borders are dominated by a unidirectional conversion from cropland to built-up land; and island borders demonstrate concurrent agricultural decline, ecological recovery, and built-up expansion. (2) From 1992 to 2020, global border land use underwent a transition from high-intensity transformations to low-intensity steady adjustments. Major changes were centered on the expansion of production space, outward diffusion of built-up areas, and vegetation restructuring. High-intensity changes were concentrated near boundary zones and attenuated significantly with increasing buffer distance. (3) At the continental scale, stable hierarchical patterns emerge in terms of change intensity, spatial gradients, and transition structures. Borders in Eurasia and North America show higher activity, Africa exhibits widespread diffusion, and South America and Oceania are characterized by forest boundary reshaping and vegetation adjustments, respectively. (4) Typical border regions can be categorized into three evolutionary types: forest ecological frontiers, agricultural expansion zones, and land–sea composite corridors. Regional trajectories vary significantly, with Southeast Asia transitioning rapidly toward stabilization, West Africa retaining periodic high-intensity disturbances, and South America remaining in a low-intensity adjustment state. This study clarifies the evolutionary patterns and boundary effect ranges of global border land use, providing theoretical support and empirical references for resource allocation and ecological regulation in border regions. It also lays the groundwork for refining border typologies, quantifying driving mechanisms, and developing differentiated cross-border governance strategies. Full article

The molecular epidemiology and antiretroviral (ARV) drug resistance of human immunodeficiency virus type 1 (HIV-1) remain incompletely outlined in the Middle East and North Africa (MENA). The aim of this retrospective molecular epidemiology study was to analyze MENA HIV-1 sequences for phylogenetic clustering and to delineate surveillance drug-resistance mutations (SDRMs) for nucleoside reverse-transcriptase inhibitors (NRTIs), non-nucleoside reverse-transcriptase inhibitors (NNRTIs), and protease inhibitors (PIs) across various periods, locations, and subtypes/circulating recombinant forms (CRFs). Viral sequences were retrieved from the Los Alamos HIV Sequence Database as of 15 April 2026. Analyses were done using multiple sub-gene regions (two env regions (n = 224 and n = 60) and PR (n = 2413) and RT (n = 2103) of the pol gene). Phylogeny construction was conducted using maximum-likelihood estimation, while ARV drug resistance analysis was conducted using the Stanford HIVdb algorithm. The HIV-1 MENA sequences showed a remarkable genetic diversity, with co-circulation of multiple subtypes/CRFs, including subtype B in the Maghreb, Levant, and Egypt sub-regions, subtypes A1, G, CRF01_AE, and CRF02_AG in the Gulf Cooperation Council (GCC) and Yemen sub-region, and subtypes C and D in the Horn of Africa and Sudan sub-region. The percentage of MENA HIV-1 sequences in clusters was 10.3% for env1, 8.3% for env2, 22.0% for PR and 37.2% for RT. Phylogenetic reconstruction hinted at a structured epidemic dominated by small transmission units, with most clusters comprising dyads (n = 260) or networks (n = 142) and a limited number of large clusters (n = 8) that were largely confined within national boundaries, with only occasional cross-border linkages (n = 8). Overall SDRM prevalence was 3.2% in the PR region and 14.9% in the RT region, with a higher percentage of NNRTI-associated mutations (10.0%) than NRTI-associated mutations (9.1%) and dual-class resistance observed in 4.1% of sequences. Phylogenetic clustering was not associated with the probability of harboring SDRMs; however, negative binomial models showed that non-clustered sequences had a greater burden of NRTI-associated mutations, whereas no such association was observed for NNRTI- or PI-associated mutations. The findings showed predominantly localized and fragmented MENA HIV-1 transmission dynamics. Heterogeneous ARV drug resistance dynamics indicated that resistance emergence might be shaped by broader epidemiologic and treatment-related factors rather than ongoing clustered transmission. There is a need for coordinated molecular surveillance and optimized ART strategies across the MENA countries. Full article

Generative AI (GenAI) adoption in higher education (HE) raises significant ethical concerns. The focus is shifting from rules- or outcomes-based learning environments towards the development of moral character, personality traits, integrity, and practical wisdom (phronesis). However, most existing AI ethics validation instruments are predominantly shaped by Global North paradigms. In Global South HE contexts, in particular, open distance e-learning (ODEL) HE institutions (HEIs) characterised by limited direct supervision and a digital divide, validation remains scant. Ethical risks are intensified by the adoption and integration of GenAI tools, such as large language models (LLMs), to enhance teaching, learning, research, and student support, thus recognising the need to develop and validate virtue ethics scales. The current paper attempts to address this gap by validating the Virtue Ethics Measurement Scale (VEMS) within South Africa’s largest comprehensive ODEL institution. Guided by the positivist paradigm, a 36-item cross-sectional survey of 503 undergraduate and postgraduate students measured six virtue dimensions (justice, honesty, responsibility, care, prudence, and fortitude). Confirmatory factor analysis (CFA) compared four competing models. The single-factor model showed poor fit, rejecting unidimensionality. A second-order hierarchical model demonstrated an acceptable fit (χ²/df = 2.992, CFI = 0.933, RMSEA (Root Mean Square Error of Approximation) = 0.063, SRMR (Standardized Root Mean Squared Residual) = 0.043) with subscale reliabilities ranging from Cronbach’s α = 0.84 to 0.90, supporting a multidimensional yet hierarchical virtue structure. The VEMS offers a psychometrically sound instrument for evaluating ethical AI use in ODEL institutions. This aligns with virtue ethics theory, which emphasises that moral character is a constellation of dispositions (e.g., honesty, care, prudence) rather than a single trait. The VEMS thus enables HEIs to assess students’ virtues, design targeted ethics capacity-development programmes, and inform policy reform for responsible GenAI adoption in under-researched Global South HE settings. Full article

Climate change is intensifying crop yield variability across arid and semi-arid regions, yet the effectiveness of widely implemented adaptation strategies remains insufficiently quantified. We systematically reviewed 157 crop modeling studies over two decades (2005–2024) to assess yield responses and adaptation effectiveness for five crops (maize, wheat, rice, sorghum, and barley). Using a predefined set of inclusion criteria across six databases (ProQuest, Web of Science, Scopus, Google Scholar, Taylor & Francis Online, and JSTOR) in an independent dual review, the results show that rising temperatures and erratic precipitation substantially reduced maize yields by 20.32% (range = 0.4–63%) and wheat yield by 15% (range = 0.05–64%), followed by rice (14.72%, range = 4–37%) and sorghum (14.54%, range = 1–36%). Localized adaptation partially offset approximately 12–19% of climate-driven reductions. An “adaptation effectiveness gap,” representing the difference between local adaptation benefits and global mean potential, showed that most locations achieved 7% greater than global benchmarks for comparable strategies. East and South Asia, as well as Eastern Africa, underperformed, whereas Europe and North America exceeded the global average. Disparities emanated from data limitations, methodology, and local agronomic conditions. This review offers a transferable framework for guiding effective, region-specific climate adaptation planning. Full article

Background: Geranium robertianum L. (GR) is a perennial herbaceous plant that belongs to the Geraniaceae family, widely distributed across temperate regions of Europe, Asia, North Africa, and America. It has been used in traditional ethnomedicine for its antibacterial, haemostatic, and anti-allergic properties in the treatment of oropharyngeal conditions, wounds, and inflammatory diseases. Beyond these traditional applications, pharmacological studies have documented several biological activities of its extracts and constituents. Objective: The aim of this review is to evaluate the therapeutic potential of GR by examining the phytochemical composition and the pharmacological properties relevant to dental medicine. Methods: A literature screening was conducted (PubMed, Google Scholar, PubMed Central), with focus on studies concerning phytochemical composition, pharmacological effects, and potential applications of GR and its major bioactive constituents in oral health. Results: Phytochemical analysis reveals that GR is characterized by a rich content of polyphenols, particularly tannins, flavonoids, and phenolic acids, with geraniin, ellagic acid, gallic acid, quercetin, and kaempferol identified as its principal bioactive constituents. Recent studies have confirmed that these constituents are responsible for the plant’s therapeutic potential in oral medicine. These compounds possess a variety of effects, from antibacterial and anti-inflammatory properties to antifungal and antiviral activities, as well as antioxidant, wound-healing, and anticancer benefits relevant to dental medicine. Conclusions: Despite its long-standing traditional use, GR remains largely underexplored in the context of oral health. This gap in the literature highlights GR as a promising phytotherapeutic candidate, calling for further in vitro and in vivo studies in order to investigate its efficacy and establish its mechanism of action in dental medicine. Full article

Dairy product spoilage is primarily caused by microbial contamination and lipase activity. Systematically assessing contamination risks and elucidating the structural and functional characteristics of key lipases form a crucial foundation for achieving precise prevention and control. This article integrated 79 studies (2003–2025) to preliminarily explore the geographical distribution characteristics of spoilage bacterial contamination. The combined contamination rates were relatively high in South America (89.5%), North America (88.3%) and Asia (87.3%), followed by Europe (86.0%) and Oceania (82.2%), while Africa showed a lower rate (57.6%) based on limited data. Product-level risk differences were also identified. Considering data robustness, in addition to raw milk (92.6%), milk powder also showed a high contamination rate (86.8%). The spoilage bacterial community was highly concentrated, with Bacillus (40.7%) and Pseudomonas (20.3%) as the dominant genera, and Pseudomonas fluorescens (21.1%) and Bacillus licheniformis (20.1%) as the core spoilage species. Furthermore, structural analysis of 37 key lipases demonstrated that these enzymes universally possess a hydrophobic surface, high lipid affinity, and a conserved α/β hydrolase folding conformation. Based on these predictions, we propose a structural hypothesis: these characteristics may be related to their retained activity after thermal processing. Unlike traditional meta-analyses that merely report pollution rates, and unlike independent bioinformatics studies that analyze lipases from arbitrary strains, this study ensures that the lipases analyzed have epidemiological relevance. This work provides scientific grounds for monitoring, early warning, and risk assessment of dairy spoilage. It also lays a theoretical foundation for developing novel inhibitors targeting thermostable lipases. Full article

The genus Glaucium (Papaveraceae), comprising approximately 30 species, is widely distributed across the Mediterranean region, Europe, North Africa, and Central and Southwest Asia. In the flora of Türkiye, the genus is represented by 11 taxa and is commonly known as “boynuzlu gelincik” and “çömlek çatlatan”. The aim of this study is to explore the analgesic and anti-inflammatory properties of Glaucium corniculatum (L.) Rud subsp. refractum (NAB) Cullen, and Glaucium leiocarpum Boiss., which are found in Türkiye and are known for their high alkaloid content. Traditionally, G. leiocarpum has been used for wound care, cuts, bruises, acne, hemorrhoids, headache, and diarrhea, while G. corniculatum subsp. refractum has been employed as an antitussive and for external applications against ocular inflammations. Ethanolic extracts and crude alkaloid fractions from the aerial parts were evaluated in vivo in anti-inflammatory and antinociceptive test models. Anti-inflammatory activity was assessed by the carrageenan-induced paw edema model, while antinociceptive activity was determined using tail-flick and hot-plate tests. G. leiocarpum ethanolic extract (200 mg/kg) showed the highest anti-inflammatory activity, effectively suppressing carrageenan-induced edema (1.58 ± 0.30–1.73 ± 0.51 mL), and displayed the strongest antinociceptive activity, with tail-flick latencies reaching 23.91 ± 2.08 s (90 min) and 22.23 ± 1.97 s (150 min) and hot-plate latencies of 22.27 ± 4.76 s (30 min) and 23.00 ± 4.61 s (90 min). Bioactivity-guided fractionation of the most active extract was carried out using various chromatographic techniques. Thin-layer chromatography (TLC) and high-performance liquid chromatography (HPLC) analyses were employed throughout the isolation process to monitor fractions and determine their phytochemical profiles. As a result, two compounds were obtained and subsequently evaluated for their biological activities. The chemical structures of the isolated compounds were elucidated by spectroscopic methods, including ¹H-NMR, ¹³C-NMR, 2D-NMR, and LC-MS analyses as kaempferol-3-O-glucorhamnoside and quercetin-3-O-glucorhamnoside. Biological activity evaluation demonstrated that these compounds significantly contributed to the observed antinociceptive activity. These findings confirm that Glaucium species are traditionally used and highlight their potential to provide bioactive compounds with anti-inflammatory and pain-relieving effects. Full article

Argan oil (Argania spinosa L.) is a culturally and economically significant product in North Africa, yet little is known about how extraction practices shape its nutritional and sensory qualities. The present study compares mechanical cold pressing with solvent extraction (diethyl ether and petroleum ether) on roasted and unroasted kernels from Algerian argan trees. The comparison focused on lipid recovery, fatty acid composition, sterol profile, and volatile compounds as nutritional, functional, and sensory-related quality indicators. Diethyl ether extraction achieved the highest lipid recovery and was associated with higher relative proportions of oleic acid and β-sitosterol, which may be relevant for oxidative-stability-related and compositional quality considerations. In contrast, mechanical pressing preserved the authentic sterolic profile, dominated by schottenol (44.1%) and spinasterol (32.6%), characteristic of traditional argan oil. Roasting intensified Maillard-derived volatiles, notably pyrazines and furans, defining the roasted–nutty aroma of culinary-grade oils. The originality of this study lies in the integrated evaluation of extraction efficiency, fatty acid composition, sterol authenticity markers, and aroma-related volatile compounds in argan oil produced from Mostaganem kernels under roasted and unroasted conditions. These results reveal that extraction and pre-treatment are decisive levers for tailoring argan oil’s nutritional, functional, and sensory attributes, providing practical guidance for selecting processing conditions according to the intended food, culinary, cosmetic, or neutral-aroma application. The findings also support process standardization, product differentiation, authenticity preservation, and the sustainable valorization of Algerian argan oil in global food systems. Full article

The Arab world has produced almost no published data on public awareness of botanic gardens, despite having 53 institutions registered with Botanic Gardens Conservation International (BGCI) across 16 of the 22 League of Arab States (LAS) member states. Between October 2024 and December 2025, we administered an 18-item bilingual (Arabic and English) online questionnaire across the 22 LAS member states via paid Facebook advertising, complemented by an institutional inventory from BGCI GardenSearch and an Arabic–French–English triangulation that identified 16 additional non-BGCI operational institutions. Pearson and Spearman correlations between BGCI count and 6 awareness indicators were computed for the 13 countries with n ≥ 10. The survey returned 613 valid responses from all 22 nationalities. Among respondents in this Facebook-recruited sample, 87.4% had heard of botanic gardens (95% CI 84.6–89.8) and 98.9% considered them important for conservation, although only 63.5% reported familiarity with their conservation role. Local awareness ranged from 30% (Palestine) to 100% (Sudan, Lebanon). No BGCI–awareness correlation reached p < 0.05; Q5 recognition reached marginal significance (Spearman ρ = 0.525, p = 0.065). We did not detect a statistically significant association between BGCI institutional count and country-level awareness indicators. Because this analysis rests on only 13 countries, the absence of a significant correlation should not be read as evidence that no association exists. The 35-point gap between affirmation of conservation importance and functional familiarity marks the most actionable target for science communication. We disclose the limitations of Facebook-based recruitment and gender imbalance. Full article

Saline habitats, which include both coastal and inland, host specialised halophytic communities that can withstand high salinity. Coastal communities are shaped by tidal inundation and marine connectivity, whereas inland saline habitats are driven by evaporation, groundwater salinisation, and greater landscape isolation. These contrasting hydrological and environmental variables likely drive divergent patterns of genetic diversity, influencing local adaptation, connectivity, and evolutionary divergence, which is important for understanding species persistence and guiding conservation of saline ecosystems under environmental change. This systematic review brings together phylogeographic studies on halophytic species from both environments to uncover global drivers of genetic difference. A systematic search of Web of Science, Scopus, and PubMed was done, and 20 studies were identified focusing on key genera including Salicornia, Sarcocornia, Suaeda, and Triglochin. Distinct genetic clades were often associated with habitat type or geographic region, indicating repeated divergence linked to coastal–inland environmental gradients. Genetic differentiation between coastal and inland halophyte populations is primarily driven by habitat fragmentation, restricted gene flow, historical refugia and recolonisation, salinity-mediated adaptation, and differences in dispersal capacity. As a result, coastal populations are generally more genetically connected, whereas inland populations tend to be more isolated, structured, and evolutionarily divergent. The data also showed a strong regional bias; while research is well established in Europe, Asia, and North America, African inland saline ecosystems are critically understudied. We conclude that habitat connectivity and dispersal pathways are the primary determinants of halophyte genetic structure. Future research must integrate ecological niche modelling and landscape genetics to resolve the evolutionary dynamics of these taxa, particularly in under-sampled regions such as southern Africa, to support effective conservation of saline biodiversity. However, the synthesis is constrained by the small number of eligible studies (n = 23) and their uneven geographic distribution, with limited representation from Africa, South America, and Australia, which restricts the ability to draw fully global conclusions. Recognising and protecting these systems is essential for safeguarding global saline biodiversity. Full article

Colistin (polymyxin E), a last-resort antibiotic for the treatment of multidrug-resistant Gram-negative bacterial infections, is becoming increasingly compromised by the rapid emergence and dissemination of resistance. The extensive use of colistin in agriculture and veterinary medicine has accelerated the spread of plasmid-mediated mobile colistin resistance (mcr) genes, facilitating transmission across human, animal, and environmental reservoirs. This review provides a comprehensive overview of the epidemiology, molecular mechanisms, and geographical distribution of colistin resistance in the Middle East and North Africa (MENA) region. Analysis of the available literature indicates that Tunisia reports the highest prevalence of colistin-resistant Gram-negative bacteria in North Africa (58.09%), followed by Egypt (24.76%), Algeria (14.29%), and Libya (2.86%). Across the region, mcr-1 is the predominant plasmid-mediated resistance determinant, whereas chromosomal alterations involving the mgrB, pmrA/pmrB, and phoP/phoQ regulatory systems are the principal non-plasmid-mediated mechanisms. Resistance has been documented in major clinical pathogens, including Escherichia coli, Klebsiella pneumoniae, Acinetobacter baumannii, and Pseudomonas aeruginosa, as well as in livestock, poultry, aquaculture, wildlife, food products, and environmental samples, highlighting the interconnected nature of resistance transmission under a One Health framework. The evidence demonstrates substantial geographical variability and significant gaps in surveillance across several MENA countries, limiting accurate regional burden estimates. Strengthening antimicrobial stewardship, harmonized surveillance programs, molecular monitoring of resistance determinants, and the implementation of One Health strategies are essential to limit the continued emergence and dissemination of colistin resistance throughout the region. Full article

Once regarded as a benign, clinically overlooked organism, Theileria orientalis has undergone a paradigm shift in its perceived status and is now recognised as a tick-borne haemoparasite of clinical and economic importance. Severe outbreaks characterised by haemolytic anaemia, reproductive losses, and mortality, primarily associated with the Ikeda and Chitose genotypes, have been increasingly reported in Australasia, Asia, and North America. In Europe and parts of Africa, however, the epidemiological status of T. orientalis remains poorly defined, despite increasing molecular evidence of circulation and reports of predominantly subclinical infections. The parasite is transmitted transstadially in ixodid ticks, with Haemaphysalis longicornis as the principal confirmed biological vector, although vector competence remains unverified for most suspected tick species. This narrative review was based on a comprehensive PubMed search from database inception up to the date of initial manuscript submission, supplemented by reference-list screening and targeted searches. This review synthesises current knowledge on taxonomy, life cycle, transmission, genetic diversity based on the major piroplasm surface protein gene, global epidemiology, pathogenesis, clinical manifestations, co-infections, production losses, diagnostics, and control strategies. Key gaps include limited understanding of the mechanisms driving erythrocyte destruction, insufficient experimental confirmation of vector competence, absence of licensed vaccines, and incomplete epidemiological data in several regions. Future research priorities are discussed in the context of climate change and the expanding geographic distribution of tick vectors. Full article

Background/Objectives: Maternal, perinatal, and neonatal mortality remain major global health challenges, causing approximately 2.5 million neonatal deaths annually, particularly in low- and middle-income countries (LMICs). Although Artificial Intelligence (AI), including Machine Learning (ML) and Deep Learning (DL), is increasingly used to support healthcare decision-making, a comprehensive synthesis of its application to prevent prenatal, preterm birth, and neonatal deaths is lacking. This study systematically reviews the current state of research in this field. Methods: A Structured Literature Review (SLR) was conducted following a combined methodological framework integrating Massaro’s protocol and PRISMA 2020 guidelines. Searches were performed in Scopus, IEEE Xplore, and Google Scholar using domain-specific keywords. From 459 identified publications, 46 peer-reviewed studies published between 2018 and 2024 were selected through a four-step filtering and quality assessment process. Bibliometric and thematic analyses were performed. Results: ML techniques accounted for 71.7% of the selected studies, whereas DL approaches represented 28.3%. Neonatal death prediction was the most frequently investigated outcome (34.7% of publications). Most studies originated from Europe (39.1%) and North America (30.4%), while research from Latin America and Sub-Saharan Africa was scarce despite the high mortality burden in these regions. Key barriers included non-standardized clinical records, limited interoperability of health information systems, and the underrepresentation of LMIC populations in training datasets. Conclusions: AI shows significant potential for reducing maternal and neonatal mortality through predictive analytics. However, important geographical and methodological gaps remain. Future research should prioritize inclusive datasets and predictive frameworks adapted to resource-constrained healthcare settings. Full article

Mitigating population exposure to fine particulate matter (PM_2.5) is a core prerequisite for advancing Sustainable Development Goal 11.6.2 and global urban sustainability. This study integrated 0.1° × 0.1° gridded PM_2.5 reanalysis data, WorldPop high-resolution population datasets, and official SDG 11.6.2 scoring records spanning 2000–2019, and adopted multi-scale spatial statistics and population-weighted exposure models to systematically explore the spatiotemporal differentiation of global PM_2.5 concentrations and associated population exposure risks, as well as their coupling relationship with SDG 11.6.2 implementation progress. This study employs ArcGIS 10.6 software to harmonize the spatial scales of multi-source heterogeneous data through spatial statistics and resampling methods, and applies the SDSN (Sustainable Development Solutions Network) standardized scoring framework to quantify long-term progress across regions in meeting urban air quality targets. The results reveal significant latitudinal spatial heterogeneity in global PM_2.5 concentrations, with values ranging from 0.95 to 262.15 μg/m³; severe pollution hotspots exceeding 35 μg/m³ were agglomerated across Asia, Africa and South America, while Canada, Greenland, the Tibetan Plateau and eastern Russia maintained ultra-low PM_2.5 levels below 5 μg/m³. Global SDG 11.6.2 standardized scores rose steadily from 71.05 in 2000 to 76.64 in 2019, with Asia and Africa achieving the most remarkable score growth despite low initial baselines. Regional gaps in target realization remained stark: North America, Oceania and Northern Europe basically met the PM_2.5 sustainability standards, whereas densely populated regions of Asia and Africa faced critical governance challenges. Among nine typical countries, only China and India recorded population-weighted PM_2.5 concentrations above 25 μg/m³ in 2019; China’s air pollution control policies delivered continuous emission reductions after 2013, while India sustained extremely high exposure risks. From 2010 to 2019, the global range of urban population-weighted PM_2.5 concentrations narrowed, yet Afghanistan, Tajikistan and North Korea remained the most severely exposed nations. This study verifies the severe cross-regional inequity of PM_2.5 exposure risks under the SDG framework, and provides multi-scale empirical evidence for differentiated air quality governance and international collaborative interventions to accelerate the delivery of the 2030 sustainable development agenda. Full article