Air Quality In Cities Research Articles

AI-Driven Adaptive Ventilation Systems For Real-Time Pollution Control In Industrial And Urban Settings: A Systematic Review

The escalating urbanization and industrial activities in cities have significantly impacted air quality, posing health risks and environmental challenges that demand innovative solutions. This review systematically explores the integration of artificial intelligence (AI) and Internet of Things (IoT) sensors within smart cities, focusing on their role in real-time air quality monitoring and dynamic response mechanisms. By adhering to PRISMA guidelines, we analyze recent advancements in AI-driven automated control systems, which utilize IoT sensors to continuously monitor pollutants, including nitrogen dioxide (NO₂), sulfur dioxide (SO₂), carbon monoxide (CO), and particulate matter (PM). The data gathered by these sensors feed into AI algorithms that facilitate immediate, adaptive responses, such as modifying traffic light sequences to alleviate congestion and notifying nearby facilities to adjust emissions during high pollution periods. This review synthesizes findings on the effectiveness, limitations, and scalability of these systems, highlighting key challenges like sensor data accuracy, privacy considerations, and the infrastructure required for city-wide deployment. The paper concludes by emphasizing the transformative potential of AI and IoT in fostering sustainable urban environments and presents recommendations for future research and policy improvements to optimize smart city air quality management.

Impact of COVID-19 on Air Quality in Major Cities of Bangladesh: A Temporal Analysis (2018–2023)

Impact of COVID-19 on Air Quality in Major Cities of Bangladesh: A Temporal Analysis (2018–2023)

Impact of construction activities on the air quality of Agra city, Uttar Pradesh, India

The current research work was carried out to comprehensively assessed the impact of construction activities on the air quality. Seven sites were chosen along the metro line construction in Agra, Uttar Pradesh, India, to meet the study's goals. The monitoring was performed for 24 hours at each site using the respirable dust sampler (RDS) with a gaseous sampling attachment. The raw data was processed to calculate the Air Quality Index (AQI). The data obtained indicate that all the examined sites had PM10 (particulate matter having the diameter less than or equal to 10 micron) values above the National Ambient Air Quality Standards (NAAQ) values of 100 µg/m3, while SS-05 and SS-06 had PM2.5 (particulate matter having the diameter less than or equal to 2.5 micron) values above the NAAQ values of 60 µg/m3. Values of CO, SO2, and NO2 were discovered to be lower than the NAAQ standard limits. Because PM10's sub index (Si) was found to be the greatest across all locations, it was determined to be the criterion pollutant among all the metrics. Based on the AQI value, the research area's overall air quality was determined to be moderately polluted. At every location, a variety of management techniques, including mist guns, water spraying, and planting, are regularly used to reduce air pollution. Effective implementation of applied air pollution control measures is required to make the air clean and safe for breathing.

Air quality in a small city: criteria pollutants, volatile organic compounds, metals, and microbes.

This work presents a year-long integral study of air quality parameters in Ciudad Real, a small city in the center of Spain, and its influence on the nearby national park, Las Tablas de Daimiel. The study covers meteorological parameters and criteria pollutants such as O3, NO, NO2, SO2, and PM10. Additionally, for each month, a 1-week campaign was performed sampling air in sorbent tubes with 8-h time resolution to analyze anthropogenic volatile organic compounds and the effects of seasons, daytime, and working-weekend days. During these campaigns, 24-h PM2.5 samples were also collected to measure the load of bacteria and fungi, as well as the trace concentrations of elements.The city and the national park NOx profiles showed that emissions from the town had a non-perceivable effect on the protected area. PM10 levels in Ciudad Real were influenced by Saharan intrusions, as was the national park; however, Ciudad Real had a higher contribution from anthropogenic sources. Ozone levels were lower in the city during the cold season due to the higher concentration of NOx and have not changed significantly in the last decade.The VOCs with higher average concentrations were toluene, m,p-xylene, benzene, methylene chloride, and o-xylene, with traffic being the main source of these pollutants in the city. For benzene and carbon tetrachloride levels, weak carcinogenic risks were estimated. In PM2.5, the most abundant metals were Na, Zn, Mg, Ca, Al, Fe, and K. The carcinogenic and non-carcinogenic risks estimated from the levels of the studied metals were negligible. Bacterial and fungal counts positively correlated with the concentration of PM2.5. Microbial community composition showed seasonal variability, with the dominance of human pathogenic bacteria which correlated with certain pollutants such as SO2. Bacillus and Cutibacterium were the most abundant genera.

Analysis of the Impact of Meteorological Factors on Predicting Air Quality in South Tangerang City using Random Forest Method

Air pollution has become one of the most significant environmental problems in many cities throughout the world, which can endanger public health and the environment. Understanding the impact of meteorological conditions on air quality is very important to understanding air pollution patterns. This study investigates the influence of meteorological variables on air quality predictions in South Tangerang City, Indonesia, using the Random Forest method. Modeling is carried out by building two scenarios, namely predictions using meteorological variables and predictions without meteorological variables. Prediction performance analysis is measured using MAE, MSE, RMSE, R-square, and accuracy. The accuracy results of the research show that predictions without meteorological variables provide good prediction results with a value of 86.42%, but predictions with meteorological variables have better performance with a value reaching 98.99%. The largest error values from each model were 2.58 MAE, 71.82 MSE, and 8.4747 RMSE obtained in prediction modeling without meteorological variables, while the smallest error values were obtained in prediction modeling using meteorological variables, namely 0.00, 0.01, and 0.0219, respectively, for MAE, MSE, and RMSE. This research contributes to a better understanding of the relationship between meteorology and air pollution and air quality in urban areas and helps develop targeted mitigation strategies to improve air quality and public health, especially in South Tangerang City and the surrounding area.

Predicting and analysing air quality in smart cities using virtual sensors

Virtual sensors have become essential in generating synthetic data to support smart city initiatives, mainly when physical sensors are absent or inaccessible. They play a crucial role in monitoring air pollutants, benefiting those with health sensitivities, and aiding city planning in the context of smart cities. This research focuses on creating reliable victual sensors for air pollutant measurement through deep learning and machine learning models, providing a cost-effective solution to address the scarcity of physical sensors and data inaccuracies. The main contribution lies in improving smart cities by providing essential health-related data to mitigate the harmful effects of air pollution on residents. Continuous monitoring empowers officials and residents to reduce pollution exposure, ultimately improving public health. The study found that gradient-boosted trees are effective for daily and hourly predictions, emphasizing the vital role of virtual sensors in advancing data-driven decision-making and improving environmental quality in smart cities. The results showed that our model was better using the boosted trees method with an RMSE of approximately 10%.

Urban air quality comparison on bike and driving routes: a case study for UK

Air quality in cities is very important in both tackling climate change and promoting healthy sustainable urban living. Understanding the air quality around cities has been a challenge faced by local authorities around the world. With the new net zero targets in place, government and charitable organisations across the UK have been trying hard to both monitor and control air pollutants to influence citizen behavior towards environmentally friendly living. This study looks at urban air quality in two UK cities with the idea of understanding air quality and its relation to the mode of transport, health and well-being. This case study compares the urban air quality as Particulate Matter (PM 10 and PM 2.5) and gaseous pollutants (NO 2) on the bike and motor driving routes in Cambridge and Colchester. The study designed experiments and data collection campaigns to understand the factors leading to air quality fluctuations in urban traffic routes. The resulting measurements show that NO 2 concentrations are higher in motor driving routes and in certain locations on the bike routes that are part of (or very close to) the motor route. The PM concentrations are generally higher near parks and open greenspaces but can be argued to be within the recommended limits. Finally, this paper proposes steps to improve the urban infrastructure to tackle emissions and spread awareness among the citizens.

Assessing the Effectiveness of Punjab Traffic and Motorway Police's Anti-Smoke Campaign on Reducing Smog Levels in Punjab (Pakistan)

Smog represents a critical environmental hazard contributing to severe health problems. Punjab faces significant environmental challenges, including resource scarcity, pollution, and climate change. This study assessed the effectiveness of anti-smog enforcement measures targeting motorists in Punjab. Time series data were collected from reputable sources, including the World Bank, Punjab Environmental Protection Agency, and Pakistan Bureau of Statistics. The data were analyzed using descriptive statistics and t-test methodology. Results indicated that air quality in most major cities of Punjab fall within the range of 101-150, classified as "unhealthy for sensitive groups." Further analysis revealed significant changes in enforcement actions between 2020 and 2024. The Punjab Traffic Police has truly made remarkable progress in enforcing traffic regulations across 36 districts of Punjab, issuing an impressive 179,170 tickets for smoke-emitting vehicle violations in just a few months of 2024. This surpasses the 160,973 fines issued in the entire year of 2023, representing an 11% increase in enforcement against pollution-causing vehicles. Fine collection from violators showed a corresponding significant increase. The t-test results demonstrated a significant decrease in vehicular emissions between 2020 and 2024. To establish Punjab as a model for smog-free roadways, these enforcement efforts must be sustained systematically.

Enhancing or attenuating? How patronage ties moderate the impact of performance feedback on performance improvement in the public sector

ABSTRACT This research investigates how performance feedback affects public organizations’ performance improvement and, more importantly, how patronage ties moderate the impact. Using China’s official city air quality ranking as the case, our empirical analyses with standard panel data models and the regression discontinuity design find that negative performance feedback leads to subsequent performance improvement and, more crucially and interestingly, that patronage ties enhance, rather than attenuate, this effect. Essentially, this study deepens and extends the performance feedback theory in the public sector by bringing in informal political institutions as boundary conditions, offering more nuanced understandings of organizational responses to performance feedback.

Spatiotemporal Distribution Characteristics of Ground-level-ozone and Its Relationship with Meteorological Conditions in a Representative City in the Bohai Rim from 2017 to 2022

In recent years, ground-level-ozone（O3） pollution in urban areas in the Bohai Rim has attracted wide attention. Based on the analysis of the spatiotemporal distribution characteristics of O3 concentration in Dongying, a representative city in the Bohai Rim from 2017 to 2022, the effects of meteorological factors and sea-land breeze circulation on O3 concentration were evaluated. The results showed that： ① From 2017 to 2022, the annual assessment value of O3 concentration in Dongying showed a fluctuating upward trend, and the pollution days with O3 as the primary pollutant increased. O3 pollution mainly occurred in spring, summer, and autumn, with the most severe O3 pollution episodes typically occurring in May and June, and the duration of O3 pollution season tended to be longer. The monthly variation in the daily maximum 8-h average ozone （MDA8 O3） presented a bimodal distribution, with significant increases in the 5th and 25th percentiles, and the spatial distribution was "high in the north and south, low in the middle." In addition, the nocturnal O3 concentration in recent years in Dongying also showed a significant increase trend. ② Meteorological factors greatly influenced O3 concentration in Dongying. When the temperature was greater than 30℃, the relative humidity was less than 50%, and the wind direction was south-southwest or east-northeast, a high O3 value was more likely to occur. Meteorological factors contributed 30% of the MDA8 O3 variation in Dongying during the study period. In the case of moderate and severe O3 pollution, the contribution of meteorological factors to the change in MDA8 O3 could be as high as 40%. ③ To some extent, sea-land breeze contributed to the occurrence of MDA8 O3 exceeding the secondary standard limit value of the National Ambient Air Quality Standard. In the afternoon, the hourly concentration of O3 during the sea-land breeze days was approximately 20 μg·m-3 higher than that during the non-sea-land breeze days. On the days of moderate and severe O3 pollution, the O3 concentration during the sea-land breeze days from 10：00 to 16：00 was higher than that during non-sea-land breeze days, and the O3 concentration was also at a high level from 20：00 to 23：00 on sea-land breeze days. In the O3 pollution season, the sea-land breeze could significantly affect the O3 level in coastal cities, which could bring significant challenges for O3 pollution prevention and control in this region. In the future, cities in the Bohai Rim need to further strengthen regional joint prevention and control of O3 pollution and increase emission reduction efforts of nitrogen oxides and volatile organic compounds. This strategy could effectively lower pollutant concentrations within the land breeze air mass, consequently reducing the impact of the sea breeze air mass on air quality in cities in the Bohai Rim.

Wildfires impact on PM2.5 concentration in galicia Spain

Wildfire intensity and severity have been increasing in the Iberian Peninsula in recent years, particularly in the Galicia region, due to rising temperatures and accumulating drier combustible vegetation in unmanaged lands. This leads to substantial emissions of air pollutants, notably fine particles (PM2.5), posing a risk to public health. This study aims to assess the impact of local and regional wildfires on PM2.5 levels in Galicia's main cities and their implications for air quality and public health. Over a decade (2013–2022), PM2.5 data during wildfire seasons were analyzed using statistical methods and Lagrangian tracking to monitor smoke plume evolution. The results reveal a notable increase in PM2.5 concentration during the wildfire season (June–November) in Galicia, surpassing health guidelines during extreme events and posing a significant health risk to the population. Regional wildfire analyses indicate that smoke plumes from Northern Portugal contribute to pollution in Galician cities, influencing the seasonality of heightened PM2.5 levels. During extensive wildfires, elevated PM2.5 concentration values persisted for several days, potentially exacerbating health concerns in Galicia. These findings underscore the urgency of implementing air pollution prevention and management measures in the region, including developing effective alerts for large-scale events and improved wildfire management strategies to mitigate their impact on air quality in Galician cities.

Reduction Potential of Gaseous Emissions in European Ports Using Cold Ironing

Providing electrical power to ships while they are docked, cold ironing allows ships to turn off their engines and reduces emissions of air pollutants and greenhouse gases. This study identifies and assesses ship and port emissions and analyzes the potential for emission reduction achievable by cold ironing in European ports. It includes (1) a review of the current state of cold ironing in European ports; (2) an analysis of the time spent in ports by ships; (3) a quantification of emissions potentially avoided by means of a larger-scale use of cold ironing in Europe; (4) an estimation of the benefits achievable and the perspective to play a role in meeting emission reduction targets, improving air quality in port cities; (5) an analysis of the challenges and limitations of larger-scale cold ironing implementation; (6) potential solutions to overcome them. The results of this study could have important implications for (a) the shipping industry, which could benefit from the need for additional standardized electrical equipment onboard; (b) port authorities, which could benefit from providing additional services to the ships; (c) policymakers working to reduce emissions and promote energy efficiency, who could better approach their local and global targets.

Assessing and monitoring air quality in cities and urban areas with a portable, modular and low-cost sensor station: calibration challenges

ABSTRACT Air pollution affects not only the air in cities but also extends to all indoor environments (homes, offices, schools, public places, transportation, etc.), where we spend between 80% and 90% of our time. Both indoor and outdoor air quality have emerged as significant health concerns and are integral to national strategies implemented by health and environmental institutes in each country. Recently, complaints regarding outdoor air quality have risen in cities, primarily due to automobile traffic and industrial activities in urban areas, and also indoors within homes, offices, and schools. The following paper presents a methodology for the calibration of low-cost monitoring stations based on measurements in a couple of cities in Colombia as part of the development of a project to reduce the environmental awareness gap in urban areas for the estimation of the air quality through low-cost, flexible, modular, and mobile air quality monitoring station design that could be used to assess air pollution in different indoor and outdoor environments. With the implementation of the low-cost stations, we have calibrated and evaluated the performance of the stations using usual linear regression methods, but we have also explored the use of unsupervised estimation with the help of machine learning algorithms, specifically with Random Forest estimators. We have found a significant improvement with using Random Forest for station calibration compared with those found using simple linear regressions for calibration effects. We have found that all the models offer a significant improvement in terms of RMSE. The regression model improves RMSE by up to 70%, while the multiple regression model does so by up to 73%. However, it is the Random Forest that shows the most remarkable improvement, with a reduction in RMSE of up to 86%.

Assessment of ambient air quality of Lucknow city post monsoon 2023

This study monitoring and assessment of air pollutants, including lead and nickel trace metals, gases such as sulphur dioxide (SO2) and nitrogen dioxide (NO2), and respirable suspended particulate matter (PM10) and fine particulate matter (PM2.5), were done at nine locations that were divided into three categories: residential, commercial, and industrial of the ambient air quality in the city of the post-monsoon. With an average of 148.9 µg m-3, the 24-hour concentrations of PM10 ranged from 58.5 to 337.8 µg m-3, whereas the 24-hour concentrations of PM2.5 ranged from 32.5 to 118.4 µg m-3, with an average of 70.5 µg m-3. At every location, the mean concentrations of PM10 exceeded the allowable threshold of 100 µg m-3. While PM2.5 levels, with the exception of Aliganj, Vikas Nagar, and Chowk, exceeded the 60µg m-3 national limit. Pb and Ni, which are PM10 trace elements, range from 0.0028 to 0.0370 µg m-3, with an average of 0.0147 µg m-3 for Pb and 1.30 to 11.75 µg m-3, with an average of 6.62 µg m-3 for Ni. During a 24-hour period, the levels of SO2 varied between 7.9 and 57.7 µg m-3, with an average of 20.8 µg m-3. Conversely, the levels of NO2 varied between 9.3 and 89.0 µg m-3, with an average of 37.8. Between µg m-3 the post-monsoon of 2022 and 2023, SO2 concentrations declined by 16.0% and NO2 values increased by 22.0%, respectively. On the other hand, average SO2 and NO2 levels were significantly lower than the 80µg m-3permitted limits set by the CPCB (NAAQS-2009).

Monitoring of atmospheric air quality in cities participating in the federal project “Clean Air” of the Far Eastern Economic Region

Introduction. Air pollution over 2021 was associated with about 6.7 thousand additional deaths and almost 1.1 million additional cases of illness among the Russian population. Conducting an atmospheric air quality assessment for the subsequent selection of priority measures aimed at reducing its negative impact on public health is the main task of the Clean Air federal project. The aim of the study is to assess the management of monitoring and air quality in the cities of Komsomolsk-on-Amur, Petrovsk-Zabaykalsky, and Ussuriysk before the implementation of the federal project “Clean Air”. Materials and methods. The monitoring programs for atmospheric air quality, the results of laboratory studies for 2021 were used. The number, location of observation posts, volumes, frequency of sampling, a list of indicators, the total number of samples, the number of samples exceeding the MPC, average annual, maximum one-time concentrations of pollutants were analyzed. Results. In Komsomolsk-on-Amur, atmospheric air quality monitoring was carried out at 4 stationary and 3 route posts, Ussuriysk – 1 mobile and 1 stationary post, Petrovsk-Zabaikalsky – 1 stationary post. All studied cities are characterized by systematic excesses of hygienic standards for specific indicators. The level of air pollution in the city of Komsomolsk-on-Amur is assessed as very high, in the cities of Ussuriysk and Petrovsk-Zabaikalsky – low. Despite the low level of air pollution, these towns are characterized by systematic excesses of hygienic standards of some indicators. Limitations. The study analyzed the management of monitoring and the results of laboratory studies of atmospheric air only in the cities of Komsomolsk-on-Amur, Ussuriysk, Petrovsk-Zabaykalsky. Conclusion. The existing monitoring system in the Ussuriysk, Komsomolsk-on-Amur and Petrovsk-Zabaykalsky cities fails to allow an objective assessing of the quality of atmospheric air and its impact on public health. To objective evaluation of the impact of atmospheric air quality on the health of the population of the studied cities, measures to optimize the monitoring system were proposed.

Combination of toxicological and epidemiological approaches for estimating the health impact of atmospheric pollutants. A proof of concept for NO2

BackgroundRegular monitoring of the air pollutant nitrogen dioxide (NO2), an indicator for traffic-related emissions, is a priority in urban environments. The health impacts associated with NO2 exposure are the result of a combination of factors, including concentration, duration of exposure, and interactions with other pollutants. WHO has established air quality guidelines based on epidemiological studies. ObjectiveThis study develops a new concept "Health Impact Pathways (HIPs)" using adversity as a probabilistic indicator of health effects. For this purpose, it integrates available toxicological and epidemiological information, using Adverse Outcome Pathways (AOPs), in order to understand chemical-biological interactions and their consequences on health. MethodsLiterature review and meta-analysis of toxicological data supported by expert judgment were performed to establish: a) adversity pathways, b) quantitative criteria for scoring the observed toxicological effects (adversity indicators), c) NO2 exposure - adversity relationship for both long-term (1–36 months) and shortterm (1–7 days). The NO2 daily concentrations from January 2001 to December 2022, were obtained from Madrid city Air Quality network monitoring database. Adversity levels were compared with relative risk levels for all-cause and respiratory mortality estimated using linear equations from WHO 2021 guidelines. ResultsNon-linear relations were obtained for all long- and short-term NO2 related adversity indicators; for long-term effects, the best fitting was obtained with a modified Haber's law model with an exponential coefficient for the exposure time of 0.25. Estimations are presented for a set of case studies for Madrid city, covering temporal and spatial variability. A clear improvement trend along the two decades was observed, as well as high inter- and intra-station variability; the adversity indicators provided integrated information on the temporal and spatial evolution of population level risk. DiscussionThe proposed HIP conceptual approach offers promising advances for integrating experimental and epidemiological data. The next step is linking the concentration-adversity relationship with population health impacts through probability estimations, the preliminary estimations confirm the need for assessing independently different population groups.

The impact of shipping on the air quality in European port cities with a detailed analysis for Rotterdam

Air quality in cities with large maritime ports is considerably impacted by emissions from shipping activity which is of a growing relevance due to an increasing relative contribution. To explore the extent of shipping emissions to ambient air quality, simulations with the chemical transport model LOTOS-EUROS (LOng Term Ozone Simulation – EURopean Operational Smog model) were performed for the year 2018 at an approximate 1 × 1 km resolution for six European cities with large ports, i.e., Rotterdam, Antwerp, Hamburg, Amsterdam, Le Havre, and London. It was found that depending on the investigated city, 6.5%–62% of the nitrogen dioxide (NO2) concentration in the city centres is attributable to shipping activities. This corresponds to contributions of 1.8–11.5 μg/m3 to the ambient air NO2 concentrations. The average NO2 contribution of shipping in these six cities was 28% (7.1 μg/m3). The largest relative contribution was found for Le Havre where 62% (10.8 μg/m3) of the annual average NO2 concentration was caused by shipping emissions. The largest absolute contribution is found for the city centre of Hamburg with 11.5 μg/m3 (41%). The lowest absolute and relative contribution (respectively 1.8 μg/m3 and 6.5%) are found for London, also having the smallest port in terms of tonnage throughput, which is one of the influential factors that determine emission totals, investigated in this study. For the other investigated pollutants, i.e., PM2.5, PM10 and SO2, contributions from shipping were less pronounced with average contribution for all cities of 10% (1.2 μg/m3) 7% (1.5 μg/m3) and 4% (0.16 μg/m3) respectively. To assess the effect of model choices on these results, this study also looked into the choice of simulation resolution and relations between meteorological parameters and NO2 concentrations. Following simulations with varying chemical transport model resolutions (1 × 1 km to 24 × 24 km), it is found that a decrease in ambient air pollutant concentrations away from localized emission sources is more pronounced at higher (1 × 1 km) model resolutions and source contributions are influenced more significantly than total concentrations. Considering meteorology, generally low wind speeds (1–2 m/s) lead to high NO2 concentration in city centres. For the cities where the port is much closer to the city centre (e.g., London, Le Havre, Hamburg and Antwerp) the absolute NO2 concentrations as well as the contributions from shipping emissions become highest for windless conditions. The high concentrations (>60 μg/m3 NO2) only occur when wind speeds fall below 6 m/s.

Impact of PAHs compounds on air quality in Maragheh city: Probabilistic risk assessment and source apportionment

This study explores the concentrations and spatial distribution of polycyclic aromatic hydrocarbons (PAHs) in the ambient air of Maragheh city, Iran, while evaluating their potential health implications. PAHs levels were examined in PAHs-bound to particulate matter samples collected from diverse locations across the city. The results showed that in all sampling points, there was contamination by PAHs. The mean total PAHs concentration was 11.5 ng.m−3, with Benzo[a]pyrene (BaP) emerging as the predominant compound. Comparative analysis with other cities revealed relatively lower BaP levels in Maragheh, yet surpassing WHO guidelines in 92 % of samples. Spatial assessment heightened pollution in areas characterized by heavy traffic and industrial operations. Based on PCA analysis, it appears that 74 % of PAHs compounds originate from vehicle emissions, 13 % from the combustion of petroleum, and 6 % from a possible petroleum source. Health risk appraisal uncovered escalated carcinogenic and mutagenic hazards, especially among children. While risks remained below USEPA thresholds, ongoing monitoring and targeted interventions are advised to mitigate PAHs pollution in Maragheh and similar urban locales. Future endeavors should prioritize source elucidation, health impact assessments, and public awareness initiatives to safeguard community well-being.

Comparison of the polluted dust plume and natural dust air mass in a spring dust event in Beijing 2023

The occurrence of extreme weather events is becoming more frequent due to global climate change. A long-lasting dust outbreak in the spring of 2023 was triggered by Mongolia cyclones and cold fronts in the dust source areas. In this study, we illustrate the spatial distribution, the transport path of the dust and its influence on the air quality of downstream cities utilizing ground-based and space-borne measurements. Results indicate a more complicated pollution, coexisting of polluted dust stage S1 and pure dust stage S2. In S1, the aerosol was characterized by a dual-layer vertical structure—high extinction coefficient of nearly 1.0 km−1 with a low particle depolarized ratio (PDR) of < 0.1 under 500 m, and a small extinction coefficient of 0.3 km−1 with a high PDR of 0.15 above 500 m. Then the intrusion of the Mongolian cyclone carried new dust plumes on 10 March, suggesting the onset of pure dust period S2. The source transition was also confirmed by the MODIS, CALIPSO and Hysplit observations. The pure Asian dust evolved rapidly with one thickening layer and distributed homogeneously in the boundary layer. The PDR increased significantly to the peak of 0.35 and resulted in the peak PM10 value of > 1300 µg/m3. PM10 positively correlated with trace gases in S1 while varying inversely with the pollution gases in S2. The results help to shed light on the classification of different types of dust and also be useful in developing an effective strategy to forecast air pollution in downstream areas.

Impact of Air Emission Reduction Measures during the Asian Games on Air Quality and Health Risks in Hangzhou and Surrounding Cities

The purpose of this study was to analyze the air quality in Hangzhou and its surrounding areas during the 2023 Asian Games and assess the impact of safeguard measures on air quality. By comparing air quality monitoring data from Hangzhou and nearby cities between 23 September 2023, and 8 October 2023, with the same period in 2022, the analysis focused on the changes in air quality and the impact of PM2.5 and O3 on human health. The results show that during the 2023 Asian Games in Hangzhou, compared to the same period in 2022, the concentrations of pollutants showed the following changes: PM10 and NO2 concentrations decreased by 16.1% and 34.1%, respectively. PM2.5, CO, and O3 concentrations increased by 0.9%, 9.5%, and 14.4%, respectively. Spatially, compared with the same period in 2022, the PM2.5 concentration in Quzhou City decreased the most, reaching 23%, while the PM2.5 concentration in Huzhou City increased the most, reaching 27.1%. The largest decrease in PM10 concentration is in Wenzhou City, which is up to 28.2%, while the largest increase is in Zhoushan City, which is 9.2%. The concentration of NO2 generally decreases in all regions, with the biggest decrease in Zhoushan City, which reaches 36.2%. The concentration of CO only decreases in Shaoxing, and the highest increase is in Huzhou City. In terms of O3, the largest proportion increase is 23% in Ningbo. During the 2023 Asian Games in Hangzhou, the number of deaths from all-cause and cardiovascular diseases caused by short-term exposure to PM2.5 was 1780 and 795, respectively, which was 8.2% lower than the same period in 2022. During the Asian Games, the number of deaths from all-cause and cardiovascular diseases due to short-term exposure to O3 was 7332 and 3177, respectively, an increase of 2.8% compared with the same period in 2022.