Atmospheric Pollution Research最新文献

{"title":"Causes, emission characteristics, and health risks of persistent free radicals and reactive oxygen species in PM2.5 produced by smoldering incense","authors":"Yu-Chieh Wang ,&nbsp;Bo-Yu Chen ,&nbsp;Yen-Hsien Li ,&nbsp;Tzu-Hsien Tseng ,&nbsp;Chon-Lin Lee ,&nbsp;Wei-Min Ching","doi":"10.1016/j.apr.2025.102583","DOIUrl":"10.1016/j.apr.2025.102583","url":null,"abstract":"<div><div>This study investigated persistent free radicals (PFRs) and reactive oxygen species (ROS) using electron paramagnetic resonance in PM2.5 produced by smoldering incense. The Raman spectroscopy was used to define the structure of carbon on PM2.5. The predominant type of PFRs detected was carbon-oxygen radicals, and their 1/e lifetimes range from 1,164 to 4,932 days. One identified source of PFRs was graphite structural defects, which contribute to catalytic reactivity and the subsequent production of hydroxyl radicals. Incense-generated PM2.5 produces ROS, including hydroxyl and alkyl radicals. Among the eight types of incense PM2.5 examined, PFR emission rates were found to range from 3.2E16 ± 9.0E15 to 8.8E16 ± 5.0E16 spins/g, and ROS emission rates ranged from 1.6E18 to 7.6E18 spins/g. The high chemical reactivity of both PFRs and ROS may pose significant health risks. The health risk of PFRs content in PM2.5 is often assessed using a cigarette tar-based method. It has been estimated that the amount of PM-bound PFRs generated from burning a single incense stick is approximately equivalent to that produced by the cigarette tar amount from one to two cigarettes. Non-thermal plasma intervention reduced the amount of PM2.5 but increased the concentration of PFRs and ROS. The results of real samples indicate that the concentration of PFRs in PM2.5 from indoor incense burning in suburban areas is higher than that in busy urban traffic areas. The intervention will increase the concentration of PFRs. Given the lifestyle of spending extended periods indoors, studying the incense PM2.5-bound radicals is important.</div></div>","PeriodicalId":8604,"journal":{"name":"Atmospheric Pollution Research","volume":"16 9","pages":"Article 102583"},"PeriodicalIF":3.9,"publicationDate":"2025-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144069706","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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":"Particulate concentration associated with multiple burn units in complex terrain: A numerical study","authors":"Michael T. Kiefer ,&nbsp;Joseph J. Charney ,&nbsp;Shiyuan Zhong ,&nbsp;Xindi Bian ,&nbsp;Warren E. Heilman ,&nbsp;Joseph Seitz","doi":"10.1016/j.apr.2025.102573","DOIUrl":"10.1016/j.apr.2025.102573","url":null,"abstract":"<div><div>Smoke from low-intensity prescribed fires jeopardizes the health and safety of both on-the-ground fire personnel and nearby communities, mainly through compromised air quality and reduced visibility. Accurate prediction of smoke dispersion is crucial to prevent unintended, potentially hazardous smoke intrusions into populated areas. This work addresses three specific knowledge gaps that limit smoke prediction accuracy: (i) the influence of complex terrain on smoke behavior, (ii) the effects of multiple active burn units, and (iii) the role of buoyant plume rise. A previously-validated Lagrangian particle dispersion model is employed to simulate particle dispersion in and around a river gap through an eastern Pennsylvania ridgeline. A series of idealized simulations is conducted in which particles are released within five 1-km x 1-km release zones, with fifteen combinations of release zones and release depths (chosen to roughly represent the impact of hypothetical fires of increasing intensity on buoyant plume rise and plume height). Results show that particle concentration magnitude and distribution downwind of the river gap are nonlinearly related to the number and location of release zones. Furthermore, the relative contribution from an individual source to downstream concentration may vary depending on whether buoyant plume rise is substantial enough to distribute particles throughout or above the mixed layer or is negligible with only near-surface distribution of particles. Overall, the results suggest that downstream smoke concentration magnitude and distribution are linked to both the spatial arrangement of sources and the plume characteristics, highlighting the need for consideration of these factors in smoke management strategies.</div></div>","PeriodicalId":8604,"journal":{"name":"Atmospheric Pollution Research","volume":"16 9","pages":"Article 102573"},"PeriodicalIF":3.9,"publicationDate":"2025-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144070377","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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":"Identification of best machine learning model for the real-time vehicular data based prediction of PM2.5 and PM10","authors":"Rohit Kumar ,&nbsp;Ramagopal V.S. Uppaluri","doi":"10.1016/j.apr.2025.102575","DOIUrl":"10.1016/j.apr.2025.102575","url":null,"abstract":"<div><div>In fast-developing urban regions such as the Guwahati City, the particulate matter (PM₁₀ and PM_2.5) concentration prediction is vital to ascertain air quality and public health. Utilizing a large dataset that constitutes historical real-time pollution data, vehicular population count (petrol and diesel), and meteorological characteristics (temperature, wind direction, solar radiation, relative humidity, wind speed) data, the article applies alternate machine-learning algorithms for the prediction of PM_2.5 and PM₁₀ levels in the Guwahati city. The intricate temporal patterns and seasonality inclines of the air pollution data were captured with the alternate ML models namely Extreme Gradient Boosting, Decision Tree, Random Forest, Support Vector Regression, K nearest neighbour and Multilayer Perceptron. The models were assessed for their efficacy with important metrics such as the coefficient of determination, root mean square error and mean absolute error. The algorithmic performance based data analysis was undertaken to analyze upon the sensitive influence of lag features, rolling statistics, seasonal decomposition components, temporal features and seasonality-specific issues on the model performance. Accordingly, they highlight the efficacy of machine learning models for their ability and effectiveness to predict air quality parameters. The explorations convey that ensemble techniques such as the Extreme Gradient Boosting outperform other models in terms of the lowest RMSE values of 0.024 μg/m³ and 0.041 μg/m³ for PM_2.5 and PM₁₀ respectively; MAE values of 0.017 and 0.027 for PM_2.5 and PM₁₀ respectively and coefficient of determination values of 0.96 for PM_2.5 and values of 0.92 for PM₁₀. Accordingly, the conducted investigations can foster the implementation of pragmatic policies that are to be meticulously followed to safeguard the air quality of the city.</div></div>","PeriodicalId":8604,"journal":{"name":"Atmospheric Pollution Research","volume":"16 9","pages":"Article 102575"},"PeriodicalIF":3.9,"publicationDate":"2025-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143941408","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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":"Real-time analysis of NOx emissions in heavy-duty diesel vehicles: Impact of speed and variations across vehicle groups","authors":"Luis Fhernando Mendonça da Silva ,&nbsp;Mariana Ribeiro Barros de Alencar ,&nbsp;André Heriberto Moraes Nunes ,&nbsp;Adriana Gioda","doi":"10.1016/j.apr.2025.102572","DOIUrl":"10.1016/j.apr.2025.102572","url":null,"abstract":"<div><div>This study analyzes the NOx emission factors of heavy-duty diesel vehicles monitored in the Metropolitan Region of Rio de Janeiro (MRRJ) between February 2022 and April 2024, with the aim of assessing compliance with the PROCONVE (Air Pollution Control Program for Vehicles) program. To the best of our knowledge, this study is unprecedented in the country and one of the few studies conducted in Latin America. The results showed great variability in NOx emissions, reflecting differences in emission control technologies, vehicle age, maintenance conditions, and operational characteristics. The average NOx emissions for the fourteen vehicles were 3322 ± 106 ppm, ranging from 1.51 to 1257 ppm. The analysis indicated that vehicle weight influenced emissions, with greater variability in the lightest vehicles. Engine power was another relevant factor, with intermediate-power vehicles (188 kW and 191 kW) presenting the lowest emissions, challenging the assumption that more powerful engines always generate more emissions. Regarding the age of the vehicles, the newer ones emitted less NOx than the older ones. When converting the emission factors to g kWh⁻¹ using a theoretical conversion factor, more than 50 % of the vehicles exceeded the 2 g kWh⁻¹ limit established by the PROCONVE P-7 standard. It should be noted that the actual load conditions of the engine are different and therefore this comparison is qualitative only. Most of the monitored vehicles operated at low speeds (up to 40 km h⁻¹), typical of urban environments, highlighting the influence of traffic conditions on emissions. The analysis revealed different behaviors among vehicle groups: emissions increased with speed for WM vehicles, which operate between the MRRJ and the mountainous regions, while they decreased for M vehicles, which deliver dry cargo within the MRRJ, mainly in the southern zone of Rio de Janeiro. The results reinforce the need for environmental policies aimed at fleet renewal, adoption of advanced emission control technologies, and promotion of more efficient driving practices. Future studies should investigate the relationship between operating conditions, speed variability and NOx emissions in different contexts.</div></div>","PeriodicalId":8604,"journal":{"name":"Atmospheric Pollution Research","volume":"16 9","pages":"Article 102572"},"PeriodicalIF":3.9,"publicationDate":"2025-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143941407","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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":"Impact of climate dataset variability on spatiotemporal modelling of PM2.5 concentration using deep neural network models","authors":"Mark Joseph Calubad ,&nbsp;Mamad Tamamadin ,&nbsp;Jurng-Jae Yee","doi":"10.1016/j.apr.2025.102577","DOIUrl":"10.1016/j.apr.2025.102577","url":null,"abstract":"<div><div>Meteorological parameters have been used as features in spatiotemporal PM_2.5 models owing to their influence on the formation, concentration, and dispersion of PM_2.5 particles. This study investigated the effectiveness of various meteorological datasets, resampled using different methods, in predicting PM_2.5 concentrations with optimized deep neural network (DNN) models. The results showed that a cubic-spline-resampled European Centre for Medium-Range Weather Forecasts (ECMWF) dataset, as a meteorological feature in the DNN models, produced the best results in predicting PM_2.5 values with MAE and RMSE values of 3.597 and 5.363 μg/m³, respectively. Day of the year, the aerosol optical depth, and temperature were the features with the most significant influence in predicting PM_2.5 concentrations based on their SHAP values for each DNN models. The distribution and correlations between resampled values of each resampling method and dataset combination were discussed. This study also discusses future exploration for improving the spatiotemporal PM_2.5-concentration modelling process.</div></div>","PeriodicalId":8604,"journal":{"name":"Atmospheric Pollution Research","volume":"16 9","pages":"Article 102577"},"PeriodicalIF":3.9,"publicationDate":"2025-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144147951","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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":"Biomonitoring of elements airborne pollution in European Mediterranean region by two Tillandsia species","authors":"Alexandre Gonzalez ,&nbsp;Zohra Benfodda ,&nbsp;David Bénimélis ,&nbsp;Damien Bourgeois ,&nbsp;Jean-Xavier Fontaine ,&nbsp;Roland Molinié ,&nbsp;Patrick Meffre","doi":"10.1016/j.apr.2025.102576","DOIUrl":"10.1016/j.apr.2025.102576","url":null,"abstract":"<div><div><em>Tillandsia</em> genus belongs to the Bromeliaceae family plants and some species display active or passive biomonitoring capacities in their natural habitat as it has been described mostly in the American continent. However, <em>Tillandsia aeranthos</em> (Loisiel.) Desf. and <em>Tillandsia bergeri</em> Mez have never been studied for their metal air pollution biomonitor potential. A recent study conducted in our laboratory brought to light the maximum capacity of elements bioconcentration into these two species leaves. The aim of the present study is to determine if <em>T. aeranthos</em> and <em>T. bergeri</em> acclimated to Southern/European region are good biomonitors for airborne elements pollution. Twelve elements were chosen to evaluate the biomonitoring potential (As, Ba, Co, Cr, Cu, Fe, Mn, Ni, Pb, Sn, Ti and Zn). After sampling, the content of the twelve elements in leaves was measured by Inductively Coupled Plasma-Optical Emission Spectrometry and Inductively Coupled Plasma-Mass Spectrometry. Data sets were treated according to sampling sites by box plots over time and Principal Component Analysis. The results showed differences between the two species, with <em>T. bergeri</em> possessing a higher capacity in accumulating elements than <em>T. aeranthos</em>. Fe, Zn and Co showed a higher contribution in the accumulation process in the two <em>Tillandsia</em> species leading to the hypothesis of a good affinity of the two species with these elements. Values obtained for five elements (As, Cr, Ni, Pb and Zn) were compared with values recorded by a monitoring station close to sampling sites showing the efficiency of these two <em>Tillandsia</em> species as biomonitors. High Co accumulation rates obtained in both <em>Tillandsia</em> species were particularly intriguing but could not be rationalized as this metal is not currently monitored by air pollution station in this region. <em>T. aeranthos</em> and <em>T. bergeri</em> proved their efficiency for the biomonitoring of elements air pollution, especially for Co, Fe and Zn.</div></div>","PeriodicalId":8604,"journal":{"name":"Atmospheric Pollution Research","volume":"16 8","pages":"Article 102576"},"PeriodicalIF":3.9,"publicationDate":"2025-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143937573","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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":"Short-term PM2.5 exposure among 3-year cancer survivors with incident cardiovascular disease before and during the COVID-19 pandemic period","authors":"Hyun-Young Shin ,&nbsp;Hyeokjong Lee ,&nbsp;Jihun Song ,&nbsp;Sun Jae Park ,&nbsp;Jaewon Kim ,&nbsp;Sangwoo Park ,&nbsp;Hye Jun Kim ,&nbsp;Jina Chung ,&nbsp;Kyae Hyung Kim ,&nbsp;Sang Min Park","doi":"10.1016/j.apr.2025.102574","DOIUrl":"10.1016/j.apr.2025.102574","url":null,"abstract":"<div><div>Particulate matter (PM_2.5) exposure is suggested to the development of cardiovascular disease (CVD) in cancer survivors. During the COVID-19 pandemic, PM₂.₅ concentration levels exhibited temporal variability, which may have contributed to differential health impacts on populations. The purpose of this study is to explore the association between the variance in PM_2.5 exposure prior to and during the COVID-19 period and the incidence of CVD among cancer survivors. Utilizing big data from the Korea National Health Insurance Service, three-year cancer survivors diagnosed between 2009 and 2018 and new CVD event after 2015 were extracted. The association between short-term exposure PM_2.5 and the incidence of CVD was analyzed by using the conditional logistic model in the design of time-stratified case-crossover. 39,581 cancer survivors who developed CVD were collected. Elevated levels of PM_2.5 were associated with increased CVD risk before COVID19 social distancing (lag 0 aOR 1.030, 95 % CI 1.014–1.046; lag 0–1 aOR 1.027, 95 % CI 1.009–1.045). On the other hand, the association between outdoors exposure of PM_2.5 and the incidence of CVD disappeared in cancer survivors during COVID19 period (lag 0 aOR 0.998, 95 % CI 0.916–1.087; lag 0–1 aOR 1.001, 95 % CI 0.971–1.032). This study aims to investigate the association between PM₂.₅ exposure variability and CVD incidence among cancer survivors during the pre-pandemic and COVID-19 pandemic periods. Further research is required to elucidate the mechanistic pathways and establish causal relationships underlying the cardiovascular consequences of PM₂.₅ exposure fluctuations in cancer survivor.</div></div>","PeriodicalId":8604,"journal":{"name":"Atmospheric Pollution Research","volume":"16 9","pages":"Article 102574"},"PeriodicalIF":3.9,"publicationDate":"2025-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143935202","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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":"Diesel generator exhaust emissions: Chemical characterization and cytotoxicity in bladder spheroids","authors":"Nansi Fakhri ,&nbsp;Amani Yehya ,&nbsp;Michelle El Kawak ,&nbsp;Marc Fadel ,&nbsp;Eliane Farah ,&nbsp;Konstantina Oikonomou ,&nbsp;Jean Sciare ,&nbsp;Dominique Courcot ,&nbsp;Frédéric Ledoux ,&nbsp;Charbel Afif ,&nbsp;Wassim Abou-Kheir ,&nbsp;Hassan R. Dhaini","doi":"10.1016/j.apr.2025.102571","DOIUrl":"10.1016/j.apr.2025.102571","url":null,"abstract":"<div><div>Diesel generators, widely used in developing countries, compensating for long power outages and blackouts, are significant sources of air pollution. In this study, diesel exhaust particulate matter (DEPM) samples were collected from two midsize generators operating in Beirut by cascade impaction, and gravimetrically analyzed for size. The smallest fraction captured on quartz filter was then chemically characterized for its constituents, and examined for its cytotoxicity on 2D and 3D human uroepithelial cell cultures. Results showed that 87 % of collected PM are quasi-ultrafine (&lt;0.33 μm in diameter), and marked high emissions of organic and elemental carbon (OC/EC), elements and metals, particularly Ca, Fe, S, Al, and Ti, and polyaromatic hydrocarbons (PAHs), mainly Benzo[g,h,i]perylene and Dibenzo[a,h]anthracene, as well as high emissions of dioxins, furans and polychlorinated biphenyls (PCBs), particularly OCDD, 1,2,3,4,6,7,8 HpCDF, and PCB118. In addition, <em>in vitro</em> testing showed decreased proliferation, viability, and spheroid formation ability only at high concentrations. In conclusion, DEPM from domestic generators consists of a wide panel of potent toxicants, notably genotoxic, carcinogenic, and endocrine disrupting compounds. Additionally, <em>in vitro</em> results provide a solid basis to further examine the potential contribution of DEPM to bladder tumorigenesis in established cell culture models.</div></div>","PeriodicalId":8604,"journal":{"name":"Atmospheric Pollution Research","volume":"16 9","pages":"Article 102571"},"PeriodicalIF":3.9,"publicationDate":"2025-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144069707","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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":"Personal exposure and internal dose to particulate matter in a Mediterranean coastal city","authors":"Eleni Mammi-Galani,&nbsp;Mihalis Lazaridis","doi":"10.1016/j.apr.2025.102570","DOIUrl":"10.1016/j.apr.2025.102570","url":null,"abstract":"<div><div>The direct method of personal monitoring was selected with the aim to estimate the exposure and the subsequent dose of residents a coastal Mediterranean city (Chania Greece), to ambient particles. Eight subjects conducted daily real-time measurements, for 3 days each, with the use of an optical particle sizer. The subjects kept a diary of activities and of the microenvironments they visited. Additionally, a time resolution of 1 min was selected, in order to study the impact of various activities and indoor sources on human exposure and consequently on the human dose. The highest personal mean exposure in particle number concentration (PN_0.3-10) was 80 particles/cm³, with average daily exposure 50 ± 16 particles/cm³, while the highest particle mass (PM₁₀) daily exposure was 36.1 μg/m³ with average PM₁₀ exposure concentration 18.7 ± 8.07 μg/m³. The impact of various activities on the indoor concentrations was also studied, with cooking resulting in sharp elevations in particle concentration, while other household activities also impacted the particles levels. Additionally, the dosimetry model, ExDoM2, was used to calculate the deposition and dose for both PN_0.3-10 and PM₁₀. The retention of PM₁₀ in the respiratory tract, the mass transferred to the oesophagus, and their absorption to blood was also estimated. The model results indicated that the highest PM₁₀ dose occurred in the extrathoracic region (ET) of the respiratory tract (RT) and after the 3 days of exposure, the highest amount of particles was transferred to the oesophagus.</div></div>","PeriodicalId":8604,"journal":{"name":"Atmospheric Pollution Research","volume":"16 9","pages":"Article 102570"},"PeriodicalIF":3.9,"publicationDate":"2025-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143941608","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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":"Useful hourly measurements of formaldehyde at PAMS sites in New York","authors":"O.V. Rattigan,&nbsp;P. Furdyna,&nbsp;M. Hirsch,&nbsp;A.C. Teora,&nbsp;H.D. Felton,&nbsp;R.Y. Tian,&nbsp;M.A. Ninneman,&nbsp;W. Hao","doi":"10.1016/j.apr.2025.102568","DOIUrl":"10.1016/j.apr.2025.102568","url":null,"abstract":"<div><div>Hourly measurements of HCHO were carried out over a period of 2–3 years, at two New York sites (New York Botanical Gardens (NYBG) and Flax Pond) using Picarro cavity ring-down spectroscopy instruments, model G2307. HCHO data was corrected for the baseline drift by sampling zero air for 10 min on an hourly basis. The zero corrected HCHO data were then compared to collocated HCHO data from 2,4-dinitrophenylhydrazine (DNPH) cartridge samples. The difference averaged on a quarterly basis was used to adjust for the Picarro instrumental bias. The corrected Picarro data were found to agree well with collocated measurements from an Aerodyne Tunable Infrared Laser Direct Absorption Spectroscopy (TILDAS) instrument. HCHO showed a pronounced diel pattern in summer, with peak concentrations of 3.4–3.9 parts per billion by volume (ppbv), around noon to early afternoon, and a minimum of 1.4–1.9 ppbv, around 4–5 a.m. A strong seasonal gradient was observed with mean summer concentrations a factor of 2–3 higher than in winter, indicating the importance of secondary production. HCHO concentrations simulated by the Community Multiscale Air Quality model were lower than observed at NYBG, indicating that the emissions of HCHO and biogenic isoprene may be too low in urban areas. At Flax Pond modeled HCHO values were generally closer to observed concentrations except for April and May when modeled values were lower. The Picarro G2307 has the potential to provide accurate high temporal resolution HCHO data in the sub ppbv range, which is useful for model evaluation provided it is corrected for baseline drift and instrumental bias.</div></div>","PeriodicalId":8604,"journal":{"name":"Atmospheric Pollution Research","volume":"16 8","pages":"Article 102568"},"PeriodicalIF":3.9,"publicationDate":"2025-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143922136","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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}