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33 pages, 22566 KB

Open AccessArticle

Spatiotemporal Variation and Coupling Relationship Between Air Quality and Environment-Urban-Economy-Associated Factors: A Case Study of 31 Provinces in China During 2015~2022

by Xiaoning Wang, Linlin Liu, Lingxia Chen, Xuemei Yang, Yue Yin, Yanan Luan, Zhihao Li, Guofu Huang, Jimei Song and Chuanxi Yang

Sustainability 2026, 18(8), 4080; https://doi.org/10.3390/su18084080 - 20 Apr 2026

Viewed by 336

Abstract

In this study, global spatial autocorrelation, local spatial autocorrelation, Spearman correlation analysis, gray correlation analysis, entropy weight method, and the gravity model were used to analyze the spatiotemporal variation and environment-urban-economy-associated factors of air quality of 31 provinces in China during 2015~2022. From [...] Read more.

In this study, global spatial autocorrelation, local spatial autocorrelation, Spearman correlation analysis, gray correlation analysis, entropy weight method, and the gravity model were used to analyze the spatiotemporal variation and environment-urban-economy-associated factors of air quality of 31 provinces in China during 2015~2022. From 2015 to 2022, the Air Quality Index (AQI) exhibited a downward trend in 30 out of 31 Chinese provinces, with the exception of Shaanxi Province. Concurrently, the annual average concentrations of PM_2.5, PM₁₀, SO₂, NO₂, and CO declined across the study period. High-high clusters and low-high outliers were observed in northern China, whereas low-low clusters and high-low outliers were distributed in southern China. Twelve provinces (38.7%) showed positive correlation (0.095~0.95), 18 provinces (58.1%) showed negative correlation (−0.76~0.095), and only Anhui showed no correlation between AQI and O₃. The comprehensive AQI quality presented a dual-core model in Sichuan (in the southwest) and Henan (in the central part) of China, while the comprehensive AQI improvement rate presented a single-core model in Jiangsu in the east of China. The gravity models incorporating AQI and GDP revealed that both air quality and economic performance improved over the study period. The spatial pattern of pollution evolved from a multi-core structure to a non-core structure, whereas the pattern of economic growth transitioned from a non-core structure to a dual-core structure, with the Beijing-Tianjin-Hebei region and the Yangtze River Delta emerging as the primary urban agglomerations. Full article

(This article belongs to the Special Issue Air Pollution and Sustainability)

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28 pages, 3022 KB

Open AccessArticle

Air Quality and Climate Co-Benefits of Pakistan’s Transport Sector: A Multi-Pollutant Scenario Assessment

by Kaleem Anwar Mir, Pallav Purohit, Shahbaz Mehmood and Arif Goheer

Sustainability 2026, 18(8), 3954; https://doi.org/10.3390/su18083954 - 16 Apr 2026

Viewed by 773

Abstract

The transport sector is a major contributor to urban air pollution and greenhouse gas emissions in Pakistan, posing significant challenges to sustainable development and climate commitments. This study develops the first technology-resolved, high-resolution, multi-pollutant emission inventory and scenario analysis for Pakistan’s transport sector, [...] Read more.

The transport sector is a major contributor to urban air pollution and greenhouse gas emissions in Pakistan, posing significant challenges to sustainable development and climate commitments. This study develops the first technology-resolved, high-resolution, multi-pollutant emission inventory and scenario analysis for Pakistan’s transport sector, addressing key gaps in previous studies that lacked integrated multi-pollutant assessments, comprehensive coverage of non-road sources, and long-term scenario comparisons. The analysis integrates road and non-road transport sources within the Greenhouse Gas–Air Pollution Interactions and Synergies (GAINS) modeling framework. Emissions are projected for 2024–2050 under a business-as-usual (BAU) scenario and three mitigation pathways: an Electric Vehicle Transition (EVT) emphasizing transport electrification, a Euro-VI scenario focusing on stringent fuel and vehicle emission standards, and an integrated nationally determined contribution strategy (NDC+) scenario combining electrification, regulatory improvements, and structural transport reforms. In 2024, transport-related emissions are estimated at approximately 22 kt of fine particulate matter (PM_2.5), over 300 kt of nitrogen oxides (NO_x), and nearly 39 Mt of carbon dioxide (CO₂), alongside substantial emissions of other gaseous pollutants and short-lived climate forcers. By 2050, the NDC+ scenario achieves the largest reductions relative to business-as-usual, demonstrating that coordinated electrification and emission control strategies can simultaneously reduce air pollution and greenhouse gas emissions. The results demonstrate strong synergies between climate mitigation and air quality improvement, showing that integrated strategies combining electrification with stringent emission standards can simultaneously reduce greenhouse gas emissions and major air pollutants while advancing cleaner and more sustainable mobility. This analysis provides a consistent and policy-relevant evidence base derived from best-available data and modeling tools to support Pakistan’s NDC implementation, sustainable mobility planning, and integrated air quality and climate strategies, with lessons transferable to other rapidly developing economies. Full article

(This article belongs to the Special Issue Air Pollution and Sustainability)

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25 pages, 3914 KB

Open AccessArticle

Air Pollution Regulation for Sustainable Development in China: A BERTopic Analysis of 12,081 Policies

by Yifen Xia and Yuanzhuo Wu

Sustainability 2026, 18(5), 2272; https://doi.org/10.3390/su18052272 - 26 Feb 2026

Cited by 1 | Viewed by 712

Abstract

Air pollution governance is crucial to China’s sustainable development, and the complexity of the low-carbon transition necessitates a systematic assessment of the evolving policy landscape. This study constructs a large-scale corpus of air pollution environmental regulation documents issued by the central government and [...] Read more.

Air pollution governance is crucial to China’s sustainable development, and the complexity of the low-carbon transition necessitates a systematic assessment of the evolving policy landscape. This study constructs a large-scale corpus of air pollution environmental regulation documents issued by the central government and 31 provincial-level governments, collected through large-scale web crawling from official government portals. This study utilizes the BERTopic model to extract policy topics and systematically analyze policies through topic content, topic hierarchy, topic similarity, and clustering structure, as well as dynamic topic evolution over time. Key findings are as follows: (1) The BERTopic results identify 31 policy topics, and Topic 0–Topic 11 collectively account for 82.8% of all documents. (2) The topics mainly focus on three areas: comprehensive air pollution control and enforcement, structural low-carbon and energy transition, and governance capacity building through monitoring, fiscal incentives, and carbon accounting. (3) Hierarchical and similarity analyses indicate three relatively stable core thematic groups, alongside two specialized peripheral themes. (4) Over the study period, dynamic topic trends show a shift in policy emphasis from air quality-oriented control toward low-carbon transition and supporting policy instruments. These findings clarify the thematic structure and evolution of China’s environmental policies, offering an evidence base for improving integrated air pollution governance toward sustainable development. Full article

(This article belongs to the Special Issue Air Pollution and Sustainability)

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17 pages, 2897 KB

Open AccessArticle

An Environmental Equity Framework to Design Sustainable Air Quality Standards

by Cristóbal De La Maza, Francisco Fernández, Matías Otth, Nicolás Rojas, Antonio Menchaca and Luis Abdón Cifuentes

Sustainability 2026, 18(4), 1824; https://doi.org/10.3390/su18041824 - 11 Feb 2026

Viewed by 1065

Abstract

Air pollution is a leading global environmental and health threat, imposing heavy economic and social burdens that are unevenly distributed across populations and pose major challenges for sustainable development. This study develops a novel environmental equity framework for designing sustainable air quality standards [...] Read more.

Air pollution is a leading global environmental and health threat, imposing heavy economic and social burdens that are unevenly distributed across populations and pose major challenges for sustainable development. This study develops a novel environmental equity framework for designing sustainable air quality standards at the national level, covering all Chilean communes. The analysis integrates satellite-derived PM_2.5 estimates calibrated with ground-based monitoring stations, administrative health records and national socio-economic surveys to estimate the costs, benefits, and distributional impacts of alternative air quality standards. The results show that current PM_2.5 exposure contributes to more than 5750 premature deaths annually and increases income inequality by about 6%. Implementing stricter standards yields substantial net social benefits, with a maximum benefit at an annual average concentration of around 10 µg/m³, simultaneously improving social sustainability by reducing pollution-adjusted inequality. However, achieving the strictest WHO target (5 µg/m³) would entail disproportionately high costs. The proposed framework provides a decision support tool for sustainability-oriented regulations, enabling policymakers to balance environmental protection, economic efficiency and social equity in the design of air quality standards. Full article

(This article belongs to the Special Issue Air Pollution and Sustainability)

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17 pages, 1532 KB

Open AccessArticle

Methodological and Uncertainty-Focused Evaluation of Tiered Approaches for Maritime Black Carbon Inventories in the Philippines

by Janine Tubera Guevarra and Kyoungrean Kim

Sustainability 2026, 18(3), 1549; https://doi.org/10.3390/su18031549 - 3 Feb 2026

Viewed by 532

Abstract

Black carbon (BC) is a short-lived climate pollutant with substantial warming and health impacts, yet its contribution from maritime activities in data-limited regions remains poorly constrained. This study conducts a methodological and uncertainty-focused evaluation of tier-based emission inventory approaches from the European Monitoring [...] Read more.

Black carbon (BC) is a short-lived climate pollutant with substantial warming and health impacts, yet its contribution from maritime activities in data-limited regions remains poorly constrained. This study conducts a methodological and uncertainty-focused evaluation of tier-based emission inventory approaches from the European Monitoring and Evaluation Programme/European Environment Agency (EMEP/EEA) Guidebook, examining fuel-based (Tier I) and activity-based (Tier III) methodologies using national fuel statistics, port call activity, vessel registry data, and an operational Philippine Coast Guard dataset. Monte Carlo uncertainty analysis, spatial mapping, and hotspot intensity analysis are applied to evaluate how each tier responds to data limitations and parameter uncertainty rather than to reconcile absolute emission magnitudes. Results indicate that Tier I provides scalability for national reporting but exhibits substantial uncertainty for gasoline-dominated segments due to reliance on particulate matter-based proxies, underscoring the role of Tier II as a targeted refinement option. Tier III applies an activity-based formulation using fuel consumption resolved by operational phase and phase-specific emission factors, consistent with EMEP/EEA Tier III guidance. These findings are integrated into a decision-oriented synthesis to support informed selection and combination of tiered emission approaches under data-limited maritime conditions aligned with national and international climate commitments. Full article

(This article belongs to the Special Issue Air Pollution and Sustainability)

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23 pages, 2342 KB

Open AccessArticle

A Socio-Environmental Index for Assessing Air Quality Based on PM Concentrations in a Latin American Megacity

by Angie Daniela Barrera-Heredia, Carlos Alfonso Zafra-Mejía and Nelson Javier Cely-Calixto

Sustainability 2026, 18(2), 1097; https://doi.org/10.3390/su18021097 - 21 Jan 2026

Viewed by 1013

Abstract

Air pollution represents one of the foremost environmental and public health challenges of the twenty-first century, with differentiated impacts according to the socio-economic and urban conditions of affected populations. It therefore remains necessary to integrate social and spatial factors into air quality assessment, [...] Read more.

Air pollution represents one of the foremost environmental and public health challenges of the twenty-first century, with differentiated impacts according to the socio-economic and urban conditions of affected populations. It therefore remains necessary to integrate social and spatial factors into air quality assessment, going beyond purely physicochemical approaches. This study aims to develop a socio-environmental index to assess air quality (SAQI) based on particulate matter (PM) concentrations in two urban areas of Bogota (Colombia). The methodology is structured in three phases: (i) a global review of reported socio-environmental indices over the past decade, (ii) construction of the index via integration of environmental and socio-economic variables collected in the locality of Kennedy, and (iii) comparative validation of the index in the locality of Barrios Unidos to assess robustness and transferability. The structure of the proposed SAQI assigns 45% weight to the socio-economic dimension and 55% to environmental exposure (PM_2.5 and PM₁₀ concentrations). During the development phase in Kennedy, annual PM_2.5 concentrations were systematically found to exceed World Health Organization guidelines by factors ranging between 4.0 and 5.7 (24.5 ± 2.89 µg/m³). The comparative application in Barrios Unidos (SAQI = 12, “good”) and Kennedy (SAQI = 21.8, “acceptable”) revealed an 81.5% socio-environmental gap driven by PM concentrations up to 49.8% higher and greater social vulnerability in Kennedy. The methodological divergence compared to the local technical index—IBOCA (45.2 in Kennedy)—underscores the added value of the SAQI developed to capture effective socio-environmental risk. The SAQI developed in this work is a potential decision-making tool that guides public policies toward fairer and more equitable air quality management in urban areas of developing countries. Full article

(This article belongs to the Special Issue Air Pollution and Sustainability)

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29 pages, 2497 KB

Open AccessArticle

Experimental and Simulation-Based Study of Acid Gas Removal in Packed Columns with Different Packing Materials

by Ersin Üresin

Sustainability 2025, 17(23), 10495; https://doi.org/10.3390/su172310495 - 23 Nov 2025

Viewed by 1646

Abstract

In this study, both experimental and simulation approaches were employed to investigate the removal efficiency of gaseous pollutants using two different types of packing materials—random and structured packings—under varying gas flow rates and column diameters. A synthetic gas mixture containing 2200 ppm H [...] Read more.

In this study, both experimental and simulation approaches were employed to investigate the removal efficiency of gaseous pollutants using two different types of packing materials—random and structured packings—under varying gas flow rates and column diameters. A synthetic gas mixture containing 2200 ppm H₂S and 26.75% CO₂ was used to evaluate the performance of the system. Simulation studies were conducted using Aspen Plus^TM V9, and the results were validated with experimental data. H₂S removal efficiencies were found to range between 79% and 98%, while CO₂ removal ranged from 6% to 20%. Comparative analyses revealed that an increase in gas flow rate and column diameter led to a decrease in pollutant removal efficiency for both types of packings. A previously unobserved packing-dependent scaling effect was revealed: increasing column diameter decreases removal efficiency for random packings but enhances it (up to a threshold) for structured packings, offering new scale-up guidelines. Most notably, a previously unobserved trend was identified: increasing column diameter exerts opposing effects on removal efficiency depending on packing type—a packing-dependent scaling behavior with significant implications for industrial column design. The findings provide valuable insights into the design and optimization of industrial-scale gas treatment systems, demonstrating that simulation data can effectively support the selection of appropriate column dimensions, gas flow rates, and packing types for varying pollutant concentrations. A mechanistic analysis revealed that the superior H₂S removal over CO₂ arises from its higher solubility, instantaneous reaction with OH⁻, and greater enhancement factor, with structured packings mitigating maldistribution effects at larger column diameters—offering new scale-up insights supported by the literature. Full article

(This article belongs to the Special Issue Air Pollution and Sustainability)

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24 pages, 6234 KB

Open AccessArticle

Towards Sustainable Air Quality in Coal-Heated Cities: A Case Study from Astana, Kazakhstan

by Akmaral Agibayeva, Aiganym Kumisbek, Aslan Nauyryzbay, Egemen Avcu, Kuanysh Zhalgasbayev, Ferhat Karaca and Mert Guney

Sustainability 2025, 17(22), 10214; https://doi.org/10.3390/su172210214 - 14 Nov 2025

Cited by 1 | Viewed by 1300

Abstract

Despite severe particulate matter (PM) pollution in Central Asia, limited air composition and health impact data are hindering sustainable air quality management and resilient urban planning. This study provides the first comprehensive assessment of PM_2.5 and PM_2.5–10 in the urban environment [...] Read more.

Despite severe particulate matter (PM) pollution in Central Asia, limited air composition and health impact data are hindering sustainable air quality management and resilient urban planning. This study provides the first comprehensive assessment of PM_2.5 and PM_2.5–10 in the urban environment of Astana, Kazakhstan, a rapidly expanding city with intense winter heating demands. We characterized PM and atmospheric precipitation and assessed health risks using bioaccessible fractions of PM-bound potentially toxic elements (PTEs). Among 388 samples, PM_2.5 and PM_2.5–10 concentrations peaked at 534 and 1564 μg·m⁻³, respectively. Scanning electron microscopy (SEM) identified soot and coal fly ash, indicating fossil fuel combustion as a major source. Precipitation characterization also showed elevated SO₄²⁻ (17.8 μg⋅L⁻¹), V (108 μg⋅L⁻¹), Ni (84.0 μg⋅L⁻¹), and Mn (63.2 μg⋅L⁻¹). Bioaccessibility tests showed high solubility for Fe (16,229 mg·kg⁻¹) followed by V: key indicators of combustion emissions. Non-carcinogenic risk for Ni and V exceeded acceptable limits for adults and children (e.g., HQ: 6.07 for V for adults). Carcinogenic risk exceeded the threshold 10⁻⁶ for Cd (adults), Co, Cr, and Ni. These findings may help advance urban air quality management via integrating bioaccessibility-based health risk assessment and source apportionment, supporting evidence-driven policies for environmentally responsible development in rapidly urbanizing cold-climate regions. Full article

(This article belongs to the Special Issue Air Pollution and Sustainability)

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24 pages, 15793 KB

Open AccessArticle

AirCalypse: A Case Study of Temporal and User-Behaviour Contrasts in Social Media for Urban Air Pollution Monitoring in New Delhi Before and During COVID-19

by Prithviraj Pramanik, Tamal Mondal, Sirshendu Arosh and Mousumi Saha

Sustainability 2025, 17(19), 8924; https://doi.org/10.3390/su17198924 - 8 Oct 2025

Viewed by 1690

Abstract

Air pollution has become a significant concern for human health, especially in developing countries. Among Primary Pollutants, particulate matter 2.5 (

{PM}_{2.5}

), refers to airborne particles which have a diameter of 2.5 micrometres or less, and has become a widely used [...] Read more.

Air pollution has become a significant concern for human health, especially in developing countries. Among Primary Pollutants, particulate matter 2.5 (

{PM}_{2.5}

), refers to airborne particles which have a diameter of 2.5 micrometres or less, and has become a widely used measure for monitoring air quality globally. The standard go-to method usually uses Federal Reference Grade sensors to understand air quality. But, they are quite cost-prohibitive, so the popular alternative is low-cost (LC) air quality sensors. Even LC air quality monitors do not cover many areas, especially across the global south. On the other hand, the ubiquitous use of online social media OSM has led to its evolution in participatory sensing. While it does not function as a physical sensor, it can be a proxy indicator of public perception on the topic under study. OSM platforms such as Twitter/X and Reddit have already demonstrated their value in understanding human perception across various domains, including air quality monitoring. This study focuses on understanding air pollution in a resource-constrained setting by examining how the community perception on social media can complement traditional monitoring. We leverage metadata readily available from social media user data to find patterns with air quality fluctuations before and during the pandemic. We use the US Embassy

{PM}_{2.5}

data for baseline measurement. In the study, we empirically analyse the variations in quantitative & intent-based community perception in seasonal & pandemic outbreaks with varying air quality. We compare the baseline against temporal & user-specific attributes of Twitter/X relating to tweets like daily frequency of tweets, tweet lags 1–5, user followers, user verified, and user lists memberships across two timelines: pre-COVID-19 (20 March 2019– 29 February 2020) & COVID-19 (1 March 2020–20 September 2020). Our analysis examines both the quantitative and the intent-based community engagement, highlighting the significance of features like user authenticity, tweet recurrence rates, and intensity of participation. Furthermore, we show how behavioural patterns in the online discussions diverged across the two periods, which reflected the broader shifts in the air pollution levels and the public attention. This study empirically demonstrates the significance of X/Twitter metadata, beyond standard tweet content, and provides additional features for modelling and understanding air quality in developing countries. Full article

(This article belongs to the Special Issue Air Pollution and Sustainability)

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13 pages, 4616 KB

Open AccessArticle

Influence of Loadshedding on Air Quality: A South African Scenario

by Kanya Xongo, Moleboheng Molefe and Lerato Shikwambana

Sustainability 2025, 17(19), 8758; https://doi.org/10.3390/su17198758 - 29 Sep 2025

Viewed by 1643

Abstract

In many developing countries, including South Africa, electricity providers have consistently faced challenges in meeting rising energy demands. Since 2008, South Africa has implemented widespread electricity rationing—commonly referred to as “loadshedding”—due to a combination of operational inefficiencies and structural constraints. Loadshedding continues to [...] Read more.

In many developing countries, including South Africa, electricity providers have consistently faced challenges in meeting rising energy demands. Since 2008, South Africa has implemented widespread electricity rationing—commonly referred to as “loadshedding”—due to a combination of operational inefficiencies and structural constraints. Loadshedding continues to be a critical challenge in South Africa, significantly affecting the economy, livelihoods, public health, and broader socio-economic conditions. This study explores the link between loadshedding and air quality by analyzing atmospheric emissions during two contrasting periods: 2019, a year with minimal loadshedding; and 2023, which experienced severe and prolonged outages. The analysis reveals a decline in nitrogen dioxide (NO₂) and sulfur dioxide (SO₂) levels during the intense loadshedding period of 2023. The results indicate that, beyond the influence of weather patterns, reductions in emissions—such as those caused by decreased electricity generation—contribute meaningfully to improved air quality. Overall, the data suggest that reduced power production during high levels of loadshedding links with lower emissions and enhanced air quality. These findings reinforce the potential benefits of transitioning to cleaner, alternative energy sources for achieving long-term reductions in air pollution and fostering a healthier environment. Remote sensing is a critical tool for environmental monitoring in developing countries, offering cost-effective, wide-area data collection to address issues like air pollution, and climate impact. It supports policy-making by providing timely, objective insights for sustainable development, resource management, and disaster response, aligning with SDGs. Full article

(This article belongs to the Special Issue Air Pollution and Sustainability)

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14 pages, 1897 KB

Open AccessArticle

Contribution of Traffic Emissions to PM_2.5 Concentrations at Bus Stops in Denver, Colorado

by Priyanka deSouza, Philip Hopke, Christian L’Orange, Peter C. Ibsen, Carl Green, Jr., Brady Graeber, Brendan Cicione, Ruth Mekonnen, Saadhana Purushothama, Patrick L. Kinney and John Volckens

Sustainability 2025, 17(17), 7707; https://doi.org/10.3390/su17177707 - 27 Aug 2025

Cited by 1 | Viewed by 1702

Abstract

Individuals are routinely exposed to traffic-related air pollution on their commutes, which has significant health impacts. Mitigating exposure to traffic-related pollution is a key urban sustainability concern. In Denver, Colorado, low-income Americans are more likely to rely on buses and spend time waiting [...] Read more.

Individuals are routinely exposed to traffic-related air pollution on their commutes, which has significant health impacts. Mitigating exposure to traffic-related pollution is a key urban sustainability concern. In Denver, Colorado, low-income Americans are more likely to rely on buses and spend time waiting at bus stops. Evaluating the contribution of traffic emissions at bus stops can provide important information on risks experienced by these populations. We measured PM_2.5 constituents at eight bus stops and one background reference site in Denver, in the summer of 2023. Source profiles, including gasoline emissions from traffic, were estimated using Positive Matrix Factorization (PMF) analysis of PM_2.5 constituents collected at a Chemical Speciation Network site in our study region. The contributions of the different sources at each bus stop were estimated by regressing the vector of species concentrations at each site (dependent variable) on the source-profile matrix from the PMF analysis (independent variables). Traffic-related emissions (~2.5–6.6 μg/m³) and secondary organics (~3–5 μg/m³) contributed to PM_2.5 at the bus stops in our dataset. The highest traffic-related emissions-derived PM_2.5 concentrations were observed at bus stops near local sources: a gas station and a car wash. The contribution of traffic-related emissions was lower at the background site (~1 μg/m³). Full article

(This article belongs to the Special Issue Air Pollution and Sustainability)

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18 pages, 665 KB

Open AccessArticle

Hanoi Air Quantitative Report: A Cross-Sectional Study of Knowledge, Awareness, and Sustainable Practices Related to Air Pollution Among Residents of Hanoi, Vietnam

by Laura Vanderbloemen, Pranee Liamputtong, Oanh Thi Kieu Nguyen, Khanh Vo Ngoc Hoang, Huy Xuan Huynh, Mai Phuong Hoang, Man Gia Tran, Phat Hoang Nguyen, Tran Ngoc Huyen Pham, Dev Kapil, Ahmed Elgebaly and Andrew W. Taylor-Robinson

Sustainability 2025, 17(14), 6557; https://doi.org/10.3390/su17146557 - 18 Jul 2025

Viewed by 6617

Abstract

This study contributes to the broader sustainability discourse by evaluating public knowledge, awareness, and practices regarding air pollution among residents of Hanoi, Vietnam, focusing on its causes, health impacts, and mitigation strategies. A cross-sectional survey was conducted with 521 individuals in suburbs around [...] Read more.

This study contributes to the broader sustainability discourse by evaluating public knowledge, awareness, and practices regarding air pollution among residents of Hanoi, Vietnam, focusing on its causes, health impacts, and mitigation strategies. A cross-sectional survey was conducted with 521 individuals in suburbs around Hanoi. A multistage sampling technique, combining cluster and simple random sampling, was used for participant recruitment. Three central and three suburban districts of Hanoi were randomly selected as clusters. One individual from each household was invited to participate and answer a structured survey, which assessed perceptions of air pollution, its human-induced causes, recognised health impacts, and individual and community-level mitigation behaviours. Nearly all participants (98.3%) were aware of air pollution, with 65.3% attributing it to human activities and 61.2% recognising specific air pollutants as primary contributors. The majority (93.9%) acknowledged health impacts, citing respiratory infections (55.1%) and sinus issues (51.2%) as prevalent concerns. Vulnerable groups, such as children under 5 (82.3%) and adults over 65 years old (77.4%), were identified as disproportionately affected. Social media (68.9%) and television (58.3%) were the dominant sources of information. Despite a recognition of air pollution’s importance (98.5%), there was limited engagement in systemic sustainability actions, such as supporting renewable energy initiatives. Most participants (84.3%) reported personal mitigation efforts, including energy-saving practices (35.5%) and walking instead of driving a car or bike (35.3%). While awareness of air pollution and its health impacts is high among Hanoi residents, proactive engagement in systemic solutions remains limited. Policymakers should prioritise community-based programs, public–private partnerships, sustainability education, and culturally tailored policy interventions to bridge gaps between awareness and action. Tailored interventions addressing demographic and cultural factors are essential to fostering socio-environmental sustainability in rapidly urbanising contexts. Full article

(This article belongs to the Special Issue Air Pollution and Sustainability)

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24 pages, 7113 KB

Open AccessArticle

A Study of the Impact of Industrial Land Development on PM_2.5 Concentrations in China

by Qing Liu, Weihao Huang, Shilong Wu, Lianghui Tian and Hui Ren

Sustainability 2025, 17(12), 5327; https://doi.org/10.3390/su17125327 - 9 Jun 2025

Viewed by 1196

Abstract

To promote the sustainable use of land resources and improve air pollution control, this study investigates the spatiotemporal dynamics of industrial land development and the heterogeneity of PM_2.5 concentrations across regions. Based on national land transaction data and PM_2.5 raster datasets, [...] Read more.

To promote the sustainable use of land resources and improve air pollution control, this study investigates the spatiotemporal dynamics of industrial land development and the heterogeneity of PM_2.5 concentrations across regions. Based on national land transaction data and PM_2.5 raster datasets, the analysis employs Moran’s I, a hot and cold spot analysis, and multivariate linear regression to examine how the transaction frequency, transaction area, and total transaction price of industrial land influence PM_2.5 concentrations in 286 cities from 2010 to 2021. The study focuses on quantifying the impact of industrial land development on PM_2.5 concentrations. The main findings are as follows: (1) the frequency of industrial land transactions varies significantly across regions, with clear intra-regional differences. The transaction area and total transaction price decrease in the following order: “East-West-Central-North-East” and “East-Central-West-North-East”, respectively. (2) The spatial clustering of PM_2.5 concentrations has intensified, with hot spots concentrated in Eastern and Central cities. Cold spots are distributed in bands along the Southern coast and scattered patterns in Heilongjiang Province. (3) The influence of industrial land development on PM_2.5 concentrations has generally weakened nationwide, with the strongest effects observed in the Eastern region. Among the development indicators, the impact of the transaction area is increasing, while those of the transaction frequency and total price are declining, showing clear regional disparities. Therefore, integrating sustainable development principles into the adjustment of the industrial land market is essential for effective air pollution prevention. Full article

(This article belongs to the Special Issue Air Pollution and Sustainability)

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22 pages, 504 KB

Open AccessArticle

Air Pollution and the Innovation Gap: A Challenge for Sustainable Growth in Emerging and Growth Leading Economies (EAGLE)

by Junhui Shi, Umar Farooq, Mosab I. Tabash, Hosam Alden Riyadh and Tha’er Abdelwahab Almajali

Sustainability 2025, 17(10), 4423; https://doi.org/10.3390/su17104423 - 13 May 2025

Cited by 7 | Viewed by 2118

Abstract

As emerging economies play a pivotal role in global growth, understanding the impact of environmental factors, especially air pollution, on innovation is crucial. This study empirically examines the relationship between air pollution and innovation performance in EAGLE (emerging and growth leading economies) using [...] Read more.

As emerging economies play a pivotal role in global growth, understanding the impact of environmental factors, especially air pollution, on innovation is crucial. This study empirically examines the relationship between air pollution and innovation performance in EAGLE (emerging and growth leading economies) using a 20-year dataset (2000–2019) and employing 2SLS (two-stage least square) and FMOLS (fully modified ordinary least square) estimation techniques. The key findings of the study reveal that air pollution hampers R&D activities and patent applications by weakening human capital, diverting resources, and creating an unfavorable research environment. The results remain robust across multiple control variables and alternative estimation techniques. These findings highlight the urgent need for pollution control policies to mitigate its adverse effects on innovation, offering valuable insights for policymakers striving to enhance innovation resilience amid environmental challenges. This study uniquely explores the causal impact of air pollution on the macro-level innovation performance of a country. Full article

(This article belongs to the Special Issue Air Pollution and Sustainability)

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27 pages, 11279 KB

Open AccessArticle

Identifying the Main Urban Density Factors and Their Heterogeneous Effects on PM_2.5 Concentrations in High-Density Historic Neighborhoods from a Social-Biophysical Perspective: A Case Study in Beijing

by Yi Wang, Haomiao Cheng, Bin Cai and Fanding Xiang

Sustainability 2025, 17(8), 3309; https://doi.org/10.3390/su17083309 - 8 Apr 2025

Viewed by 2288

Abstract

The contradiction between urban density and sustainable environmental development is increasingly prominent. Although numerous studies have examined the impact of urban density on air pollution at the macro level, most previous research at the micro scale has either neglected socioeconomic factors, failed to [...] Read more.

The contradiction between urban density and sustainable environmental development is increasingly prominent. Although numerous studies have examined the impact of urban density on air pollution at the macro level, most previous research at the micro scale has either neglected socioeconomic factors, failed to analyze heterogeneous effects, or ignored historic neighborhoods where high pollution coexists with high density. By considering population, commercial buildings, vegetation, and road factors, an integrated social-biophysical perspective was introduced to evaluate how urban density influences PM_2.5 concentration in a historic neighborhood. The study area was divided into 56 units of 120 m × 150 m granularity, as determined by the precision of the LBS population data. The lasso regression and quantile regression were adopted to explore the main factors affecting PM_2.5 and their heterogeneous effects. The results showed that (1) building density was the most important driving factor of pollutants. It had a strong and consistent negative effect on PM_2.5 concentrations at all quantile levels, indicating the homogeneity effect. (2) Short-term human mobility represented by the visiting population density was the second main factor influencing pollutants, which has a significantly positive influence on PM_2.5. The heterogeneous effects suggested that the areas with moderate pollution levels were the key areas to control PM_2.5. (3) Vegetation Patch Shape Index was the third main factor, which has a positive influence on PM_2.5, indicating the complex vegetation patterns are not conducive to PM_2.5 dispersion in historic neighborhoods. Its heterogeneous effect presented a curvilinear trend, peaking at the 50th quantile, indicating that moderately polluted areas are the most responsive to improvements in vegetation morphology for PM_2.5 reduction. These findings can provide effective support for the improvement of air quality in historical neighborhoods of the city’s central area. Full article

(This article belongs to the Special Issue Air Pollution and Sustainability)

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The Asian Tropopause Aerosol Layer: Spatio-Temporal Characteristics, Trends, and Climate Effects

by Hongchao Liu and Junjie Ma

Sustainability 2025, 17(8), 3381; https://doi.org/10.3390/su17083381 - 10 Apr 2025

Cited by 1 | Viewed by 1263

Abstract

During the South Asian Summer Monsoon (SASM), intense large-scale uplift and strong deep convective activity over South Asia lead to the formation of a high aerosol concentration zone in the Upper Troposphere and Lower Stratosphere (UTLS), known as the Asian Troposphere Aerosol Layer [...] Read more.

During the South Asian Summer Monsoon (SASM), intense large-scale uplift and strong deep convective activity over South Asia lead to the formation of a high aerosol concentration zone in the Upper Troposphere and Lower Stratosphere (UTLS), known as the Asian Troposphere Aerosol Layer (ATAL), which appears from June to August. ATAL not only influences the exchange processes of material and energy between the troposphere and stratosphere, but also affects the global climate by altering radiation, cloud formation, and precipitation processes. Therefore, examining the spatiotemporal distribution and climate impacts of ATAL is essential for understanding climate change and evaluating the feasibility of geoengineering. This study systematically reviews research progress on the three-dimensional spatiotemporal distribution, trends, sources, and climatic effects of ATAL. Findings reveal a prominent aerosol layer at the top of the Asian troposphere, and the SASM region potentially serving as a critical conduit for constituents of the boundary layer to reach the stratosphere. However, simulated ATAL components differ significantly across models, particularly in terms of vertical distribution patterns. The precise three-dimensional structure and long-term evolution of ATAL remain unclear, presenting challenges for assessing its climate impact. To advance the understanding of the roles of ATAL in climate change, three future research directions are proposed. Full article

(This article belongs to the Special Issue Air Pollution and Sustainability)

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