Atmospheric Environment最新文献

{"title":"Dust trace metals implications on school’s indoor air quality linked to human health risk at Khurianwala (Pakistan)","authors":"Muhammad Hassan Bashir ,&nbsp;Atiq ur Rehman ,&nbsp;Hamaad Raza Ahmad ,&nbsp;Amor Hedfi ,&nbsp;Manel Ben Ali ,&nbsp;Fehmi Boufahja ,&nbsp;Khaled Elmnasri ,&nbsp;Ezzeddine Mahmoudi ,&nbsp;Muhammad Tahir Shehzad","doi":"10.1016/j.atmosenv.2024.120889","DOIUrl":"10.1016/j.atmosenv.2024.120889","url":null,"abstract":"<div><div>In an environment, trace metals (TMs) are characterized by high density and potential toxicity. Airborne dust particles distribute TMs in the environment including educational institutes that enters the human body and cause severe health issues. Therefore, this research aimed at quantifying the concentration of cadmium (Cd), copper (Cu), nickel (Ni), lead (Pb), and zinc (Zn) present in classroom dust and determine associated health risk through different environmental models by employing R-studio. Dust samples from 12 schools situated in rural and urban areas and close to the industrial zones in Khurrianwala, Faisalabad were analyzed on atomic absorption spectrophotometer. The results showed that the dust samples contained Cd, Cu, Ni, Pb, and Zn in ranges of 0.02–2.5, 2.5–24.3, 5.4–41.5, 3.6–55.8, and 5.8–146.7 mg kg⁻¹, respectively. The geo-accumulation index indicated that dust samples were contaminated with Cd and Pb. The contamination factor revealed that Ni and Cu contamination was minimal in all schools, while Cd and Pb showed moderate to high contamination at each school. Excluding rural regions, the pollution load index was high in industrial zone and urban regions. The hazard quotient indicated a little chance of non-carcinogenic risk in children from dust ingestion. The non-carcinogenic health hazard range (HI &lt; 1) and the total cancer risk range (10⁻⁶ &lt; TCR ≤10⁻⁴) were inferior for cancer-causing in adults and children, respectively. Findings of the study suggested that assessing the health risk caused by TMs contaminated dust in the school environment is essential to avoid any health complications in adults and children.</div></div>","PeriodicalId":250,"journal":{"name":"Atmospheric Environment","volume":"339 ","pages":"Article 120889"},"PeriodicalIF":4.2,"publicationDate":"2024-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142540148","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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":"Evaluating and comparison of WRF-chem model configurations for wind field impact on the April 2022 dust episode in western Iran","authors":"Elham Mobarak Hassan ,&nbsp;Mahnaz Karimkhani ,&nbsp;Jeff Sepehri (Jafar)","doi":"10.1016/j.atmosenv.2024.120892","DOIUrl":"10.1016/j.atmosenv.2024.120892","url":null,"abstract":"<div><div>Accurate estimation of wind direction and speed is essential for enhancing the simulation and prediction of dust storms. Being highly susceptible to dust storms, Western Iran necessitates a detailed evaluation of dust concentration and wind fields. This study employs the WRF-Chem model to simulate these parameters over the period from April 7 to 26, 2022. Four different model configurations were tested, involving the Yonsei University (YSU) and Mellor-Yamada-Janjic (MYJ) boundary layer schemes, as well as the Lin and WRF Single-Moment 6-Class (WSM6) microphysics schemes. The results indicate that during the selected period, different synoptic systems led to the release of dust from Iraq and Saudi Arabia and its transport to western Iran. The mid-level southerly and southwesterly wind directions have a significant impact on dust transport to the northwestern regions of Iran by high and complex mountainous terrain. The horizontal and vertical distribution of simulated dust demonstrates good agreement with TERRA satellite imagery, MERRA-2 dust surface concentration, and CALIPSO, respectively. The daily dust concentration of the WRF-Chem model has a correlation of −0.32 to −0.96 with visibility and 0.68 to 0.86 with MERRA-2 data in Western Iran. The simulated dust concentration relation with visibility and AERONET AOD (Aerosol Optical Depth at 500 nm) was calculated at −0.78 and 0.29, respectively in Zanjan station. The horizontal and vertical distribution, temporal series, and statistical indices of the wind field show that the WRF-Chem model performs well in the Iran West boundary, especially in the west and northwest, where the 10-m wind speed increased to 14 m s⁻¹. The boundary layer scheme in the WRF-Chem model has a more significant impact than the microphysics scheme in simulated 10-m wind speed and dust concentration. The final result shows that the combination of the YSU boundary layer and WSM6 microphysics schemes performs very well in simulating wind fields and dust in western Iran under various weather conditions.</div></div>","PeriodicalId":250,"journal":{"name":"Atmospheric Environment","volume":"340 ","pages":"Article 120892"},"PeriodicalIF":4.2,"publicationDate":"2024-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142662939","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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":"Accelerated surface brightening in China: The decisive role of reduced anthropogenic aerosol emissions","authors":"Qixiang Chen ,&nbsp;Chunlin Huang ,&nbsp;Zhaohui Ruan ,&nbsp;Ming Xu ,&nbsp;Hongxia Li ,&nbsp;Xinlei Han ,&nbsp;Shikui Dong ,&nbsp;Xing Yang","doi":"10.1016/j.atmosenv.2024.120893","DOIUrl":"10.1016/j.atmosenv.2024.120893","url":null,"abstract":"<div><div>A profound comprehension of the key determinants behind the fluctuations in surface solar radiation (SSR) over decadal timescales is essential for advancing the fields of energy meteorology, climatology, and solar resources. While there is a general agreement among prior research on the significant impact of aerosols on SSR, a granular understanding of the specific influence that varying aerosol types exert on SSR remains elusive. This investigation delves into the respective impacts of aerosols and cloud radiative effects across China, utilizing data from the Clouds and the Earth's Radiant Energy System (CERES). It further dissects the distinct impacts of different aerosol types on the decadal-scale variations in SSR, employing spectral aerosol optical depths derived from the MODIS aerosol products. The findings reveal a predominantly positive trend in SSR, ranging from 1.5 to 2.5 W/m²/yr between the years 2011 and 2022 for the majority of China's regions. However, certain areas within Northeast and Western China exhibit a decline in SSR exceeding −1 W/m²/yr. Notably, in Eastern China, a downward trend in aerosol radiative effect is observed, with a pronounced reduction of approximately −2 W/m²/yr noted specifically during the summer in Northern China. The study infers that the reduction in urban industrial emissions and biomass burning aerosols is linked to the acceleration of the brightening phenomenon in China. Our results underscore that stringent regulation of anthropogenic emissions could yield dual benefits: environmental amelioration and an upsurge in solar resource. These insights merit serious contemplation in the formulation of future policy and decision-making frameworks.</div></div>","PeriodicalId":250,"journal":{"name":"Atmospheric Environment","volume":"340 ","pages":"Article 120893"},"PeriodicalIF":4.2,"publicationDate":"2024-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142553163","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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":"Combined-phase source apportionment of ambient PM2.5, PAHs and VOCs from an industrialized environment: Consequences of photochemical initial concentrations","authors":"Uwayemi M. Sofowote ,&nbsp;Ewa Dabek-Zlotorzynska ,&nbsp;Mahmoud M. Yassine ,&nbsp;Dennis Mooibroek ,&nbsp;May Siu ,&nbsp;Valbona Celo ,&nbsp;Philip K. Hopke","doi":"10.1016/j.atmosenv.2024.120894","DOIUrl":"10.1016/j.atmosenv.2024.120894","url":null,"abstract":"<div><div>Air pollutants in the particulate (PM_2.5 species, PAHs) and gaseous phases (VOCs) collected between 2013 and 2019 once every three or six days for a period of 24 hours in an industrialized city in Ontario were analyzed to apportion their common sources. The consequences of using these species jointly for receptor modelling were assessed via combined-phase source apportionment that used the data <em>as is</em>, and in a protocol that factored in the potential for photochemical losses of gas-phase species. Thus, photochemically corrected initial concentrations (PIC) were calculated. Analyses of the inputs followed either with positive matrix factorization or its dispersion-normalized variant (DN-PMF). Comparisons of applying PMF to the originally observed input data (BASE) and DN-PMF on data with PIC corrections were made. When the inputs consisted only of VOCs, three factors were resolved with BASE PMF: natural gas, vehicular emissions, and industrial emissions co-emitted with summertime gasoline evaporation. A fourth factor was obtained, representing reactive VOCs when DN-PIC PMF was used. When the combined phase input data were analyzed, nine factors were resolved for both BASE and DN-PIC PMF. These factors in order of diminishing average PM mass contributions were: particulate sulphate, secondary organic aerosol (SOA), particulate nitrate (pNO3), biomass burning with natural gas, crustal matter, winter blend of gasoline, coking/coal combustion, steelmaking, and summer blend/light duty vehicular emissions. When BASE and DN-PIC PMF results are compared, the average PM mass contribution of the summer gasoline fuel factor increased from 2% in BASE case to 5%, suggesting severe underestimation of this source's contributions without DN-PIC. Also, substantial increases of reactive VOCs in the SOA factor, and PAHs with ≥four rings in the pNO3 and steelmaking factors were observed with DN-PIC PMF compared to the BASE PMF case, indicating that for SOA, reactive VOCs at this location contributed to SOA sources.</div></div>","PeriodicalId":250,"journal":{"name":"Atmospheric Environment","volume":"340 ","pages":"Article 120894"},"PeriodicalIF":4.2,"publicationDate":"2024-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142560920","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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":"Deciphering the key drivers of oxidative potential during ammonium nitrate-mediated aqueous-phase photoreaction of methoxyphenols","authors":"Racliffe Weng Seng Lai ,&nbsp;Tian Qiu ,&nbsp;Xuyang Zhang ,&nbsp;Yalin Wang ,&nbsp;Tianwei Hao ,&nbsp;Xinlei Ge ,&nbsp;Lin Du ,&nbsp;Mingjin Tang ,&nbsp;Ka In Hoi ,&nbsp;Kai Meng Mok ,&nbsp;Yong Jie Li","doi":"10.1016/j.atmosenv.2024.120895","DOIUrl":"10.1016/j.atmosenv.2024.120895","url":null,"abstract":"<div><div>Methoxyphenols are released in abundance from lignin pyrolysis during biomass burning. Apart from being atmospheric brown carbon components that absorb solar radiation and warm the climate, methoxyphenols also undergo photoreaction in the atmospheric aqueous phase and form secondary organic aerosols (aqSOA). While efforts have been devoted to understanding chemical evolutions and climate-related optical properties of aqSOA, their potential health impacts also require timely investigations. Herein, we used the dithiothreitol (DTT) assay to investigate oxidative potential of the aqSOA formed during the 8-h aqueous-phase photoreaction of two typical methoxyphenols, vanillin and vanillic acid, under pH 2 or 8, and with or without ammonia nitrate. The highest DTT consumption rates (R_DTT) were observed for vanillin aqSOA formed in the presence of ammonia nitrate and at pH 8. At pH 2, although R_DTT increased rapidly during early photoreaction, it reduced after prolonged illumination. High-resolution mass spectrometry and linear regression analyses were performed to correlate the photoreaction products with the observed R_DTT. Results showed that three products that present quinone, lactone and dimer structures, respectively, should be the key drivers of elevated R_DTT for aqSOA formed during photoreaction of vanillin and vanillic acid alone, whereas it shifted to the nitrogen-containing aromatic compounds during their photoreaction with ammonia nitrate. Our results have revealed the role of nitrogen-containing aromatic compounds in the oxidative potential and health effects of aqSOA from biomass burning, which was rarely recognized before and warrants immediate assessments.</div></div>","PeriodicalId":250,"journal":{"name":"Atmospheric Environment","volume":"340 ","pages":"Article 120895"},"PeriodicalIF":4.2,"publicationDate":"2024-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142662934","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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":"Aerosol classification under non-clear sky conditions based on geostationary satellite FY-4A and machine learning models","authors":"Bin Chen ,&nbsp;Qia Ye ,&nbsp;Xingzhao Zhou ,&nbsp;Zhihao Song ,&nbsp;Yuxiang Ren","doi":"10.1016/j.atmosenv.2024.120891","DOIUrl":"10.1016/j.atmosenv.2024.120891","url":null,"abstract":"<div><div>Accurately identifying and classifying aerosols is a key to understanding their sources, assessing their chemical and physical changes, and comprehending their feedback mechanisms within climate system. However, existing aerosol classification methods have two limitations: First, ground remote sensing products have limited spatial coverage, and polar orbit satellite data suffer from low temporal resolution. Second, satellite-based aerosol classification methods are affected by cloud interference, resulting in data gaps. To overcome these challenges, this study utilized the extreme tree algorithm (ET) and integrated the FY-4A TOAR dataset with meteorological and geographical information, using a sequential forward selection method for optimal input feature selection. Focusing on the Asian region (70–140°E, 15–55°N), three models were used to generate hourly aerosol classification products: the Clear air-Cloud-Aerosol-Mixed cloud and aerosol (CCAM-ET) model, the Dust-Polluted dust-Other aerosols-Mixed aerosols (DPOM-ET) model under clear sky conditions, and the DPOM-ET model under non-clear sky conditions. The evaluated accuracy of the CCAM-ET model was 85%, demonstrating its effectiveness in identifying cloud and aerosol under various conditions. The CCAM model can achieve an accuracy of 78% when aerosols are located above clouds and 59% when they are below clouds. The DPOM-ET model achieved an evaluation accuracy of 89% for clear sky areas and 87% for non-clear sky areas, respectively, and was superior to traditional methods. Long-term data indicated a significant correlation between the distributions of different types of aerosols and human activity. Polluted dust is common in southwest China during spring and in northern China during winter. Additionally, from 2018 to 2020, dust occurrences decreased on the Indian Peninsula, while non-dust aerosols increased significantly in India and Southeast Asia.</div></div>","PeriodicalId":250,"journal":{"name":"Atmospheric Environment","volume":"339 ","pages":"Article 120891"},"PeriodicalIF":4.2,"publicationDate":"2024-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142551937","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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":"Elucidating the impacts of aerosol radiative effects for mitigating surface O3 and PM2.5 in Delhi, India during crop residue burning period","authors":"Lakhima Chutia ,&nbsp;Jun Wang ,&nbsp;Huanxin Zhang ,&nbsp;Xi Chen ,&nbsp;Lorena Castro Garcia ,&nbsp;Nathan Janechek","doi":"10.1016/j.atmosenv.2024.120890","DOIUrl":"10.1016/j.atmosenv.2024.120890","url":null,"abstract":"<div><div>Atmospheric aerosol radiative effects regulate surface air pollution (O₃ and PM_2.5) via both the aerosol–photolysis effect (APE) and the aerosol–radiation feedback (ARF) on meteorology. Here, we elucidate the roles of APE and ARF on surface O₃ and PM_2.5 in the heavily polluted megacity, Delhi, India by using a regional model (WRF-Chem) with constraints from limited surface observations. While APE reduces surface O₃ (by 6.1%) and PM_2.5 concentrations (by 2.4% via impeding the secondary aerosol formations), ARF contributes to a 2.5% and 17.5% increase in surface O₃ and PM_2.5, respectively. The ARF from smoke enhances PM_2.5 (by 8%), black carbon (by 10%), and primary organic aerosol (by 18%) during late autumn when crop residue burning is significant. The synergistic APE and ARF have a negligible impact on the total concentrations of O₃ and PM_2.5. Hence, the reduction of PM_2.5 may lead to O₃ escalation due to weakened APE. Sensitivity experiments indicate the need and effectiveness of reducing VOC emission for the co-benefits of mitigating both O₃ and PM_2.5 concentrations in Delhi.</div></div>","PeriodicalId":250,"journal":{"name":"Atmospheric Environment","volume":"339 ","pages":"Article 120890"},"PeriodicalIF":4.2,"publicationDate":"2024-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142551936","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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":"Exposure to particulate matter when commuting in the urban area of Grenoble, France","authors":"Marie-Laure Aix,&nbsp;Mélaine Claitte,&nbsp;Dominique J. Bicout","doi":"10.1016/j.atmosenv.2024.120887","DOIUrl":"10.1016/j.atmosenv.2024.120887","url":null,"abstract":"<div><div>Air pollution is a major cause of mortality and chronic diseases worldwide, with particulate matter (PM) being the primary contributor to this burden. Few studies have yet been carried out on the effect of modes of transport, times of day or travel locations on the exposure of individuals to PM. We conducted an experiment in Grenoble, France, in spring 2022 to study factors determining the individual exposure to PM. Using low-cost sensors (LCS), PM₁ (PM &lt; 1 μm) and PM_2.5 (PM &lt; 2.5 μm) levels were measured in four transport modes (bike, walk, bus, and tramway), across four different streets and at three different times of the day. Findings are: (i) - the mode of transport plays a more important role on levels of PM_ratios (PM concentration ratio to reference) than the time of the day or the location, (ii) - PM_ratios and inhalation doses are higher in active modes of transport (bike, walk) than in passive ones (bus, tram), (iii) – levels of exposure to PM are ranked as: tram &lt; bus &lt; walk &lt; bike, and (iv) – a statistical model has been developed to predict PM_ratios as a function of transport mode, travel period, street ratio, and traffic. Exposures to PM in trams are found 12%–25% and 13%–20% lower than in passive modes of transport for PM₁ and PM_2.5, respectively. Wearing LCSs makes it possible to estimate commuters' exposure to PM and their use should be encouraged for prevention purposes.</div></div>","PeriodicalId":250,"journal":{"name":"Atmospheric Environment","volume":"339 ","pages":"Article 120887"},"PeriodicalIF":4.2,"publicationDate":"2024-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142529968","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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":"Development of a city-level surface ozone forecasting system using deep learning techniques and air quality model: Application in eastern China","authors":"Qianyun Li ,&nbsp;Jie Li ,&nbsp;Zixi Wang ,&nbsp;Bing Liu ,&nbsp;Wei Wang ,&nbsp;Zifa Wang","doi":"10.1016/j.atmosenv.2024.120865","DOIUrl":"10.1016/j.atmosenv.2024.120865","url":null,"abstract":"<div><div>Utilizing regional air quality models to accurately forecast surface ozone (O₃) concentrations, particularly high concentrations, is essential for protecting public health. However, forecasts of air quality model often deviate from site observations due to the limitation of grid resolution and uncertainties from emission sources, meteorological conditions, and chemical reaction mechanisms. Especially, the underestimation is significant under condition of high O₃ concentrations. Moreover, such deviations tend to accumulate as forecast lead time increases, compounding the challenges associated with reliable air quality forecast. In this study, we employed AlexNet architecture, a classical convolutional neural network, combined with multiple variables related to meteorology, chemistry, emission and geography to establish a non-linear relationship between grid-scale input variables and site-scale hourly O₃ forecast biases in Eastern China, aiming to realize accurate city-level ozone forecast based on a regional air quality prediction model (i.e., Nested Air Quality Prediction Model System, NAQPMS). By assigning weights to high-bias samples and high-concentration samples within the loss function, the proposed Weighted AlexNet model (W_AlexNet) effectively reduced forecast biases and enhanced its capability to predict O₃ pollution levels. Compared to NAQPMS, W_AlexNet model demonstrated a 25.71% improvement in RMSE and a 7.17% increase in IOA averagely for hourly O₃ (O₃-1h) forecasts across four different lead times (24-h, 48-h, 72-h, and 96-h). Notably, W_AlexNet model alleviated the tendency of NAQPMS to underestimate high concentrations and showed a superior performance in improving O₃-1h pollution level forecasts, particularly for the 72-h and 96-h lead times. W_AlexNet model can effectively mitigate the bias accumulation effect over increasing lead times, thereby enhancing the reliability of longer-term forecasts. Thus, the W_AlexNet model serves as a post-processing model that can calibrate forecast biases in air quality prediction models, significantly improving the accuracy of O₃ high concentration forecasts and providing more precise early warnings of O₃ pollution. This underscores its utility in air quality management.</div></div>","PeriodicalId":250,"journal":{"name":"Atmospheric Environment","volume":"339 ","pages":"Article 120865"},"PeriodicalIF":4.2,"publicationDate":"2024-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142529965","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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":"Calibration of NO, SO2, and PM using Airify: A low-cost sensor cluster for air quality monitoring","authors":"Marian-Emanuel Ionascu ,&nbsp;Marius Marcu ,&nbsp;Razvan Bogdan ,&nbsp;Marius Darie","doi":"10.1016/j.atmosenv.2024.120841","DOIUrl":"10.1016/j.atmosenv.2024.120841","url":null,"abstract":"<div><div>During the past decade, substantial efforts have been dedicated to advancing cost-effective sensor platforms for air quality monitoring. Calibration is a crucial step in ensuring that the data quality of low-cost air monitoring systems meets established standards. Recent research has extensively evaluated low-cost air monitoring platforms against the data quality objectives set by the European Directive. This paper introduces a novel calibration model for low-cost air quality sensors, significantly improving the accuracy of the measurement of nitric oxide (NO), sulfur dioxide (SO₂), and particulate matter (PM₁, PM_2.5, and PM₁₀), while promoting accessibility and adaptability in environmental monitoring technologies. This study extends the evaluation of a developed platform capable of integrating a diverse array of sensors to measure up to 12 parameters. Our proposed models demonstrate a significant improvement, achieving a 60% better accuracy for SO₂. Additionally, these models deliver similar results for PM_x and NO or exceed those of state of the art research. The calibration methodology meets the requirements of the Data Quality Objectives (DQO) for all monitored parameters and also achieves indicative levels for PM parameters.</div></div>","PeriodicalId":250,"journal":{"name":"Atmospheric Environment","volume":"339 ","pages":"Article 120841"},"PeriodicalIF":4.2,"publicationDate":"2024-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142529964","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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}