Aerosol Science and Engineering最新文献

{"title":"Effects of Nationwide COVID-19 Lockdown on Fossil Fuel and Biomass Burning Emissions in India","authors":"Anikender Kumar,&nbsp;Vivek Kumar,&nbsp;Chinmay Kumar Jena,&nbsp;Sanjay Bist,&nbsp;Vijay Kumar Soni","doi":"10.1007/s41810-025-00322-3","DOIUrl":"10.1007/s41810-025-00322-3","url":null,"abstract":"<div><p>The nationwide lockdown imposed in India in various phases to contain the spread of the COVID-19 pandemic led to a substantial reduction in anthropogenic emissions. This study conducts a thorough examination of equivalent black carbon (EBC) aerosol mass concentrations, utilizing a multi-wavelength aethalometer installed at eight stations (Bhuj, Guwahati, Jodhpur, Nagpur, New Delhi, Pune, Ranichauri, and Thiruvananthapuram) under the India Meteorological Department (IMD) EBC observation network from 2016 to 2020. The investigation aimed to assess variations in EBC, specifically its quantitative contributions from biomass burning (EBC_BB) and fossil fuels (EBC_FF), during the lockdown (LD) and unlock (UL) periods in 2020 compared to the 2016–2019 period. Results indicated a 47% reduction in EBC mass concentration during the lockdown period and a 24% reduction during the unlock period compared to the normal period. EBC_FF and EBC_BB concentrations experienced a 53% and 17% decrease, respectively, during the lockdown period, attributable to significant reductions in fossil fuel and biomass burning emissions. Throughout the lockdown period, the average contributions of EBC_FF and EBC_BB to total EBC mass concentrations were 70% and 30%, respectively, whereas during the normal period, these values were 82% and 18%. The observed reductions in equivalent black carbon concentrations aligned with decreased emissions from both transportation and industrial activities. The restrictions during the COVID-19 pandemic lockdown led to a decrease in diffusion radiation and aerosol optical depth (AOD). These findings provide comprehensive insights into the sources of EBC and emission control strategies during the unprecedented COVID-19-induced lockdown. The study contributes valuable information for shaping future emission control strategies aimed at improving air quality and addressing climate concerns.</p></div>","PeriodicalId":36991,"journal":{"name":"Aerosol Science and Engineering","volume":"10 4","pages":"653 - 668"},"PeriodicalIF":2.3,"publicationDate":"2025-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148458666","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"AI-Driven Forecasting of PM10 Concentrations in the Republic of Ireland: Integrating Machine Learning for Urban Air Quality Prediction","authors":"Lakindu Mampitiya,&nbsp;Namal Rathnayake,&nbsp;Ramen Ghosh,&nbsp;Yukinobu Hoshino,&nbsp;Upaka Rathnayake","doi":"10.1007/s41810-025-00325-0","DOIUrl":"10.1007/s41810-025-00325-0","url":null,"abstract":"<div><p>This study introduces artificial intelligence models for the first time in the Republic of Ireland to forecast particulate matter (PM₁₀). By integrating local environmental data with cutting-edge predictive algorithms, this research specifically targets high-impact urban areas in Ireland. The models not only account for complex air quality temporal patterns and meteorological variables but also introduce region-specific calibrations that have not been explored in previous air quality studies. Several state-of-the-art machine learning models: such as XGBoost, CatBoost, ANN, LSTM, Bi LSTM, and an adaptable Ensemble model are trained using available data. Interestingly, climatic variables have a minimum impact on the PM₁₀ concentrations in the tested areas of Ireland. However, they show good correlations with PM_2.5 and NO₂ concentration levels. The performance of the models is tested using widely accepted performance indicators (Coefficient of Determination, Root Mean Square Error, Mean Squared Error, and Mean Absolute Error). Based on the outcome of the models, the PM₁₀ forecast for the next 24 h is presented. The findings of this research can be effectively used to enhance policy decisions to minimize the expected rising pollution levels in the future.</p></div>","PeriodicalId":36991,"journal":{"name":"Aerosol Science and Engineering","volume":"10 4","pages":"700 - 716"},"PeriodicalIF":2.3,"publicationDate":"2025-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s41810-025-00325-0.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148459153","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Airborne Trace Elements in Particulate Matter of a Tropical Megacity of South Vietnam: Characteristics, Potential Sources, and Health Risk Assessment","authors":"Nguyen Duy Dat,&nbsp;Phan Minh Quan,&nbsp;Nhung Thi-Tuyet Hoang","doi":"10.1007/s41810-025-00319-y","DOIUrl":"10.1007/s41810-025-00319-y","url":null,"abstract":"<div><p>This study investigated the characteristics of 17 trace elements in PM₁₀ collected from Thu Duc City—an administrative unit of the biggest city in southern Vietnam in two sampling stages (dry and rainy times). The levels of 17 elements measured in the dry and rainy seasons were 5.28 ± 1.57 and 4.81 ± 1.23 ng/m³, respectively. The total trace elements accounted for 6.25–11.9% of PM₁₀. Rainfall and differing wind directions associated with different emission sources between the two seasons are likely the main factors causing variations in the concentrations and profiles of trace elements. The principal component analysis identified four potential sources of trace elements, including vehicle exhaust (41.7%), multi-industrial activities (30.4%), construction activities and cement production (12.9%), and natural sources (6.35%). Heavy metals pose moderate cancer for children when exposed to PM₁₀. Among the three primary exposure routes, oral ingestion was the main route that humans got exposed to heavy metals in PM₁₀. As &gt; Pb &gt; Zn &gt; Cr &gt; Cu were the main contributors to non-carcinogenic risks, while As &gt; Cr were the major causes of carcinogenic risks. The findings revealed that measures should be implemented to reduce the emissions of these heavy metals and raise public awareness regarding PM₁₀ pollution.</p></div>","PeriodicalId":36991,"journal":{"name":"Aerosol Science and Engineering","volume":"10 4","pages":"603 - 616"},"PeriodicalIF":2.3,"publicationDate":"2025-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148458840","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Meteorologically Normalized Air Quality Trends During COVID in India: Contrast Between Metro vs Non-metro Cities","authors":"Krishnakant Suryawanshi,&nbsp;Abhishek Chakraborty","doi":"10.1007/s41810-025-00315-2","DOIUrl":"10.1007/s41810-025-00315-2","url":null,"abstract":"<div><p>This study aimed to analyze the impact of a nationwide lockdown in India in response to the COVID-19 pandemic on air pollution by investigating variations in pollution levels while taking the meteorological factors into consideration. Air quality data collected from 12 monitoring stations, categorized as traffic, industrial, and other stations, were selected across metro and non-metro cities in India. To incorporate the impact of meteorological parameters into air quality parameters, a Random Forest (RF) machine learning (ML) model was utilized, assuming emissions remained at 2019 levels. Meteorological parameters and time variables were incorporated to predict business-as-usual (BAU) conditions. The findings revealed significant but varying reductions in fine particulate matter (PM_2.5) and nitrogen dioxide (NO₂) levels across all stations and city types during the lockdown. PM_2.5 levels decrement ranged from 13 to 54%, while NO₂ levels decrement ranged from 5 to 87%. Monitoring stations in Metro cities exhibited higher reductions than non-metro ones in NO₂ (average 55.7% compared to 28.3%) and PM_2.5 levels (average 38.8% compared to 30.2%). Ozone increased in metro cities likely due to reduced NO_x levels in VOC-limited environments, whereas in non-metro cities, lower ozone formation may be linked to NO_x-limited conditions were reductions in precursor emissions limited ozone production. The analysis also revealed that pollution levels during the lockdown period displayed relatively lower variations compared to normal conditions, suggesting fewer spikes/drops and faster recovery. Decreased correlations between NO₂ and CO in ten out of twelve stations suggested the emergence of new CO sources. An increase in the percentage of secondary components of PM_2.5 was observed, particularly in stations with O₃ increments, indicating that O₃ contributes to the formation of secondary PM_2.5. This contrast emphasizes the severity of air pollution in Indian cities and underscores the urgency for comprehensive measures to address this issue.</p></div>","PeriodicalId":36991,"journal":{"name":"Aerosol Science and Engineering","volume":"10 4","pages":"568 - 581"},"PeriodicalIF":2.3,"publicationDate":"2025-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148458688","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Temporal Dynamic of the Net Ecosystem Exchange of Carbon Dioxide and Responses to Meteorological Drivers in Mountain Forest Ecosystem of Southeastern China","authors":"Zhang Yan,&nbsp;Ye Jing,&nbsp;Pan Xiaole,&nbsp;Liu Lanzhong,&nbsp;Wang Zifa,&nbsp;Cheng Xueling","doi":"10.1007/s41810-025-00316-1","DOIUrl":"10.1007/s41810-025-00316-1","url":null,"abstract":"<div><p>This study reports the temporal dynamics of the net ecosystem exchange of carbon dioxide (NEE), the importance of various meteorological factors influencing NEE, and the response characteristics of NEE to meteorological changes at different temporal scales (half-hourly, daily and monthly) on the basis of eddy covariance and meteorological data collected from forest ecosystems in southeastern China between June 2022 and May 2024, thereby employing the random forest regression algorithm. The results show that the forest ecosystem in the study area provides a clear carbon sink function, with an estimated daily NEE period of approximately 11–12 h. Notably, this ecosystem functions as a carbon sink almost year-round, with the lowest NEE in summer, followed by spring and autumn, whereas winter shows minimal NEE, resulting in an annual total NEE of −2983.34 g CO₂·m⁻²·a⁻¹. Furthermore, the NEE varies temporally and is influenced by several meteorological factors with varying degrees of impact. Specifically, sub-daily fluctuations are driven primarily by the light intensity, whereas the effect of light decreases at longer time scales, allowing other meteorological factors to exert increased influence. The complex and nonlinear responses of NEE to these meteorological factors often feature thresholds and optimal values. This study contributes to our comprehensive understanding of NEE behavior and provides reference data for improving forest carbon cycle models and developing regional forest management measures.</p></div>","PeriodicalId":36991,"journal":{"name":"Aerosol Science and Engineering","volume":"10 4","pages":"521 - 534"},"PeriodicalIF":2.3,"publicationDate":"2025-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148459084","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Portable Air Purification Device for Occupational Safety of Health Care Professionals","authors":"Navya Sethu,&nbsp;Nayana Patil,&nbsp;Renu Vyas","doi":"10.1007/s41810-025-00317-0","DOIUrl":"10.1007/s41810-025-00317-0","url":null,"abstract":"<div><p>Healthcare personnel in infectious wards are exposed to bioaerosols, necessitating the use of respirators and personal protective equipment (PPE) to prevent pathogen contact. It is critical to evaluate and enhance the efficiency of portable, commercially available Powered Air Purifying Respirator (PAPR) devices to mitigate the risk of airborne microbial infiltering into the human respiratory system. In this study, a portable, cost-effective, and lightweight ultraviolet (UV) disinfection system was designed and developed. The system actively draws in air, effectively inactivates microorganisms, and releases purified air. The modular HEPA-UVC conjugated PAPR device developed by us can be attached to any existing respirator unit. The device was tested for filtering airborne microbes, mainly bacteria and fungi. Further, the efficiency of the device was assessed by calculating the percentage of airborne bacteria cells and fungal spores. The microbial sampling results indicated that UVC treatment along with HEPA filter operated for 15 min could achieve a 92.63% reduction of bacteria and an 80.43% reduction of fungi as compared to the HEPA filter alone. The time of exposure and flow rate were the dominant parameters affecting the number of bioaerosols in the disinfection performance of a UVC lamp. Thus, HEPA air filtration combined with UVC provided an efficient reduction of airborne pathogens from indoor air. The deployment of such integrated systems is extremely useful to provide cleaner air in infectious wards. These portable devices are a viable method to improve safeguarding healthcare personnel against pathogen infection and prevent the spread of airborne diseases.</p></div>","PeriodicalId":36991,"journal":{"name":"Aerosol Science and Engineering","volume":"10 4","pages":"582 - 590"},"PeriodicalIF":2.3,"publicationDate":"2025-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148459085","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An Assessment of PM 2.5 Concentration from Traditional Heating in the Urban Households of Kashmir","authors":"Falak Shabir,&nbsp;Sayed Mohammad Nazim Uddin,&nbsp;Mukesh Gupta","doi":"10.1007/s41810-025-00314-3","DOIUrl":"10.1007/s41810-025-00314-3","url":null,"abstract":"<div><p>Exposure to PM 2.5 is a leading environmental risk factor for many illnesses and premature deaths, causing rising public concern. Urban residents spend around 90% of their time indoors, resulting in indoor air pollutant exposure that can be 100 times greater than that of outdoor air pollution. Despite the widespread usage of traditional heating systems in Kashmiri culture, this is the first research to quantify PM 2.5 concentrations resulting from their use. This study also evaluated the relationship between ventilation and indoor air quality and discussed the research’s policy implications. A laser egg air quality monitor was used to measure PM 2.5 concentrations in 35 households in Srinagar, with data collected at two-hour intervals in both the morning and evening. Our findings reveal exceptionally high PM 2.5 concentrations in households ranging from 225 to 999 µg/m³, above the WHO limit of 5 µg/m³. Households that opened windows for at least 30 min had lower PM 2.5 concentrations (morning: 420.4 µg/m³, evening: 406.5 µg/m³) than those that kept their windows closed (morning: 498.5 µg/m³, evening: 590.6 µg/m³). Outdoor pollution, notably from traffic, also had an impact on indoor air quality. The houses in high-traffic zones had the highest morning and evening PM 2.5 concentrations (530 µg/m³ and 600 µg/m³, respectively), followed by those near sub-traffic zones and far away from traffic. Furthermore, 15 households had members suffering from respiratory issues, and 3 had heart conditions, underscoring the severe health risks of poor indoor air quality. Hence, keeping this study as scoping evidence, it paves the way for further investigation into elucidating the nexus between traditional heating and indoor air quality.</p></div>","PeriodicalId":36991,"journal":{"name":"Aerosol Science and Engineering","volume":"10 4","pages":"553 - 567"},"PeriodicalIF":2.3,"publicationDate":"2025-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148459023","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Emission of Trace Elements from HEMMs Used in Opencast Coal Mines: Chemical Composition of Used Engine Oil and Diesel Soot","authors":"Ambasht Kumar,&nbsp;Suresh Pandian Elumalai","doi":"10.1007/s41810-025-00313-4","DOIUrl":"10.1007/s41810-025-00313-4","url":null,"abstract":"<div><p>Air pollution and source apportionment studies in mining areas often neglect heavy earth-moving machinery (HEMMs) generated pollutants due to the lack of their chemical fingerprints and sampling complexity. This study investigates the chemical composition of diesel soot and used engine oil (UEO) collected from different HEMMs. The morphology and elemental composition of diesel soot were analyzed through FE-SEM with EDX and CHNS analyzer. The FE-SEM image specifies the fractal structure (≥ 150 nm) of agglomerated soot particles (50–100 nm) generated from nano-sized primary soot particles (≤ 25 nm). The peak values of infrared (IR) spectroscopy of DS are almost similar for all HEMMs. The IR spectroscopy of UEO indicated that major spectral peaks occurred at nearly equal wavenumbers of 1377, 1460–64 and 2850–2971 cm⁻¹ for all HEMMs. The trace elements (TEs) concentration in diesel soot and UEO samples were investigated through ICP-OES and AAS (Pb-only) analyzer. The mean TEs concentration (mg kg⁻¹) in UEO were (Ca &gt; Na &gt; 1000) followed by (100 &lt; Al &lt; Fe &lt; Mg &lt; B &lt; Si &lt; Zn &lt; Rb &lt; P &lt; 1000); (10 &lt; Cr &lt; Cu &lt; Ni &lt; V &lt; 100); (01 &lt; Co &lt; Pb &lt; Ti &lt; Sr &lt; Ba &lt; Mo &lt; 10) and (Cd &lt; 1). The mean TEs concentration (mg kg⁻¹) in diesel soot were (Fe &gt; Ca &gt; Al &gt; 5000) followed by (1000 &lt; Mg &lt; Na &lt; P &lt; 5000); (100 &lt; Ba &lt; Pb &lt; Ni &lt; Mo &lt; Ti &lt; Si &lt; Cr &lt; B &lt; Zn &lt; Rb &lt; 1000); (10 &lt; Co &lt; V &lt; Sr &lt; Cu &lt; 100) and (Cd &lt; 05). The increased elemental concentration and higher wear index values (&gt; 1) in UEO samples indicate Cu, Na, B, Fe, Cr, Mo, Cd, Pb, Al, Rb, Co, Ti and Ni as potential marker elements due to engine wear of HEMMs. The observations of this study add valuable information related to chemical fingerprints of HEMMs-generated pollutants for source apportionment studies in mining areas. Overall, this study gives insight into the chemical characteristics of HEMMs generated pollutants.</p></div>","PeriodicalId":36991,"journal":{"name":"Aerosol Science and Engineering","volume":"10 4","pages":"535 - 552"},"PeriodicalIF":2.3,"publicationDate":"2025-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148458926","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessment of PM2.5, PM10, SO2 and NO2 in the Northwestern Indian Himalaya—A Correlation with Tourism and Meteorological Parameters: Regional Collaborative Governance","authors":"Shilpa Thakur,&nbsp;Sheetal Chaudhary,&nbsp;Jagdish Chandra Kuniyal,&nbsp;Archana Bawari,&nbsp;Priyanka Maiti,&nbsp;Renu Lata,&nbsp;Kesar Chand,&nbsp;Anil Kumar Yadava","doi":"10.1007/s41810-025-00306-3","DOIUrl":"10.1007/s41810-025-00306-3","url":null,"abstract":"<div><p>The influx of tourists to fragile mountain ecosystems like the Himalaya can exacerbate particulate matter pollution, as increased vehicular emissions, biomass combustion, and infrastructure development contribute to increased concentrations of PM_2.5 and PM₁₀. The present study attempts to analyse the impact of tourism activities on PM_2.5 and PM₁₀ at Mohal in the Kullu Valley during a span of 6 years (2016–2021). The daily highest concentration was found as 116.21 µg m⁻³ and 162.64 µg m⁻³ for PM_2.5 and PM₁₀, respectively. The particulate matter (PM_2.5 and PM₁₀) concentrations showed an increasing trend during whole study period. The day-to-day average concentration of PM_2.5 and PM₁₀ surpassed the NAAQS limits by 6% and 2%, respectively. In view of seasonal analysis, a higher concentration was found in winter than in autumn and summer, while monsoon season showed the lowest one values. HYSPLIT and CALIPSO highlight regional activities as the primary pollution source. The correlation analysis also showed the effects of meteorological parameters on the assemblage or cluster of air pollutants especially the effect of temperature on PM_2.5 concentration in winter and summer seasons. The annual exceedance factor was moderate in the area but a continuous increase was observed in the values. Karl Pearson’s Correlation analysis reveals the contribution of tourism activities increasing the load of PM_2.5, NO₂ and SO₂. Intending to better manage air quality in the Kullu valley and other Himalayan regions, the present attempt also aims to propose a new multi-scalar framework based on regional collaborative governance of PM_2.5 and PM₁₀ through web scraping techniques and browser extensions.</p></div>","PeriodicalId":36991,"journal":{"name":"Aerosol Science and Engineering","volume":"10 3","pages":"419 - 437"},"PeriodicalIF":2.0,"publicationDate":"2025-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147985131","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluation of Tolerance Index of Commonly Growing Roadside Plants in Urban Traffic Areas of Mymensingh City, Bangladesh Using Air Pollution Tolerance Index and Metal Accumulation Index","authors":"Shahed Mahmud,&nbsp;Sneha Gautam,&nbsp;M. Safiur Rahman,&nbsp;Mahmud Hossain,&nbsp;Golam Mortuza,&nbsp;Md.Badiuzzaman Khan","doi":"10.1007/s41810-025-00311-6","DOIUrl":"10.1007/s41810-025-00311-6","url":null,"abstract":"<div><p>Roadside plants serve as biomonitoring agents by absorbing air pollutants and reducing environmental contamination. The objective of this study was to to assess the air pollution tolerance and heavy metal accumulation capacity of 36 common roadside plant species in Mymensingh, Bangladesh, using the Air Pollution Tolerance Index (APTI) and Metal Accumulation Index (MAI). Various biochemical parameters, including total chlorophyll content, ascorbic acid levels, leaf extract pH, and relative water content, were analysed to evaluate plant susceptibility to pollution. The APTI values among the studied species ranged from 5.64 to 19.23, with <i>Syzygium cumini</i> exhibiting the highest tolerance (APTI 19.23) and <i>Mussaenda frondosa</i> the highest sensitivity (APTI 5.64). Only <i>Syzygium cumini</i> was classified as an intermediate tolerant species, while all other plants were sensitive. Heavy metal analysis using Inductively Coupled Plasma Mass Spectrometry (ICP-MS) revealed that Fe (33.96 mg/kg) was the most accumulated metal, followed by Mn (6.68 mg/kg) and Ni (2.71 mg/kg). <i>Elaeis guineensis</i> had the highest MAI (5.173), while <i>Gardenia jasminoides</i> had the lowest (0.322). Strong correlations were observed between APTI and total chlorophyll content (R² = 0.5927) and between APTI and ascorbic acid (R² = 0.7792), indicating their role in pollution tolerance. The study findings highlight the potential of <i>Syzygium cumini</i> and <i>Elaeis guineensis</i> for air pollution mitigation and biomonitoring, aiding urban planners in selecting appropriate plant species for greener, healthier environments.</p></div>","PeriodicalId":36991,"journal":{"name":"Aerosol Science and Engineering","volume":"10 3","pages":"488 - 508"},"PeriodicalIF":2.0,"publicationDate":"2025-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147985338","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}