Atmospheric Pollution Research最新文献

{"title":"Removal characteristics of PCDD/Fs by an adsorbent injection coupled with a baghouse filter system","authors":"Kai Zhang ,&nbsp;Hong Yu ,&nbsp;Shengyong Lu ,&nbsp;Juan Qiu ,&nbsp;Pei Ning ,&nbsp;Xueyong Hou ,&nbsp;Ling Zhu ,&nbsp;Yaqi Peng","doi":"10.1016/j.apr.2024.102243","DOIUrl":"https://doi.org/10.1016/j.apr.2024.102243","url":null,"abstract":"<div><p>In this study, we explore the influence of the baghouse differential pressure, the baghouse running time, and activated carbon addition on dioxin emissions at the baghouse outlet during waste incineration. The experimental results showed that there was a critical value of the baghouse differential pressure. When the baghouse differential pressure was less than the critical value, the dioxin toxic equivalent at the baghouse outlet decreased with an increase in the differential pressure; and when the baghouse differential pressure was greater than the critical value, the dioxin toxic equivalent increased with an increase in the differential pressure. There was also a critical value for the influence of the baghouse running time on the dioxin emissions at the baghouse outlet. Within the range of experimental data, as the baghouse running time increased, the dioxin toxic equivalent at the baghouse outlet first decreased and then maintained a stable fluctuation. The addition of activated carbon effectively reduced the dioxin toxic equivalent at the baghouse outlet, which decreased with an increase in the amount of added activated carbon. This study provides a preliminary reference and data support to control dioxins during waste incineration.</p></div>","PeriodicalId":8604,"journal":{"name":"Atmospheric Pollution Research","volume":"15 10","pages":"Article 102243"},"PeriodicalIF":3.9,"publicationDate":"2024-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141539258","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":"Spatial relevance of synergistic effects between air pollutants and carbon dioxide emission reductions: A case study in the Bohai Rim region of China","authors":"Nan Han ,&nbsp;Di Li ,&nbsp;Zenglin Han ,&nbsp;Hongye Wang ,&nbsp;Ye Duan","doi":"10.1016/j.apr.2024.102238","DOIUrl":"https://doi.org/10.1016/j.apr.2024.102238","url":null,"abstract":"<div><p>Analyzing the spatial correlation of synergistic effect of reducing air pollutants and carbon dioxide (SERAC) between cities, which are spatial hubs characterized by dense populations, industries, and energy usage, provides a foundation for devising regional joint prevention and control policies tailored to local circumstances at this scale. The study analyzed 43 cities in the Bohai Rim region, assessing synergistic emission reduction effects from 2006 to 2020 using a coupled coordination model based on air pollutants (AP) and carbon dioxide (CO₂) emission trends. Social network analysis is employed to investigate the structural characteristics and robustness of the spatial correlation network and to unveil the position and significance of each city within the network. The study found that: (1) AP emission equivalent peaked in 2011, while the growth rate of CO₂ emission equivalent slowed down in the Bohai Rim region. (2) The low-value areas for the SERAC are spatially clustered in Beijing, Tianjin, and Tangshan, with 90% of the cities in a coordinated state. (3) The network showcasing the spatial correlation between the SERAC features both “local clustering” and “global correlation” coexisting, and its robustness needs improvement. (4) Membership within the plates is relatively stable. On this basis, it is proposed that the Bohai Rim region can enhance the SERAC by establishing a “lead-follow” inter-city mechanism, strengthen the stabilizing role of core entities, implement differentiated emission reduction measures in communities, and expand regional cooperation, ultimately reducing costs and increasing efficiency.</p></div>","PeriodicalId":8604,"journal":{"name":"Atmospheric Pollution Research","volume":"15 10","pages":"Article 102238"},"PeriodicalIF":3.9,"publicationDate":"2024-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141481573","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":"Investigating nuisance dust complaints: Combining high frequency dust deposition records and source identification using integrated microanalytical techniques","authors":"Kathryn L. Linge ,&nbsp;Kari Pitts ,&nbsp;Silvia Black ,&nbsp;Angela Downey ,&nbsp;Mark Brand ,&nbsp;Peter Taylor ,&nbsp;Colin Priddis","doi":"10.1016/j.apr.2024.102241","DOIUrl":"https://doi.org/10.1016/j.apr.2024.102241","url":null,"abstract":"<div><p>While ducted dust emissions from industry are usually well regulated and controlled, fugitive dust emissions can be difficult to quantify or differentiate from off-site emissions, particularly where fugitive emissions are transient or intermittent. In this study, sources of nuisance dust were investigated using a novel dust deposition sampling methodology, followed by chemical and mineralogical analysis using optical microscopy, x-ray diffraction (XRD), scanning electron microscopy with energy dispersive x-ray spectrometry (SEM-EDS), and isotope ratio mass spectrometry analysis. Dust deposition over 24 h was collected on horizontally orientated 300 mm square glass panels at 6 sites in the region of interest. This method captured very small (&lt;10 mg) masses of dust and could distinguish very small variations in dust deposition at different sites and on different days. Comparison samples collected from potential dust sources at a nearby lime manufacturing facility, and other potential fugitive dust sources in the region were differentiated using XRD mineralogy, visual appearance by optical microscopy and SEM-EDS analysis of individual particles. Comparison of selected dust samples to reference samples indicated most dust deposition at the study sites consisted of soil or sand. However, dust deposition at two sites was sometimes composed of a material that was similar in composition to lime that had been rehydrated to portlandite, but not yet fully carbonated to calcite. Subsequent analysis of δ¹³C and δ¹⁸O for selected dust samples from these two sites were consistent with rapid and recent carbonation of small particles in an alkaline environment, which could have occurred during the atmospheric release and transport of lime, and ruled out fugitive dust emission from lime stockpiles existing on site. Combining the information obtained from high frequency record of dust deposition with targeted mineralogical, isotopic and morphological examinations provided new insight into the source of fugitive dust emissions in this area.</p></div>","PeriodicalId":8604,"journal":{"name":"Atmospheric Pollution Research","volume":"15 10","pages":"Article 102241"},"PeriodicalIF":3.9,"publicationDate":"2024-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141481572","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":"Analysis of excessive NOx emission from tampered heavy-duty vehicles based on real-time data and its impact on air pollution","authors":"Yong Li ,&nbsp;Huanqin Wang ,&nbsp;Mengqi Fu ,&nbsp;Jing Wang ,&nbsp;Yanyan Yang ,&nbsp;Huaqiao Gui","doi":"10.1016/j.apr.2024.102240","DOIUrl":"https://doi.org/10.1016/j.apr.2024.102240","url":null,"abstract":"<div><p>Vehicle tampering leads to substantial excessive emissions, but few methods could identify the tampered ones from vehicles on road accurately in one day or less. A fast response model based on real time data from terminal box (T-BOX) was built in this study for heavy-duty vehicle tampering identification, which could identify the tampered vehicles from vehicles with excessive emission caused by bad driving conditions, low ambient temperature or on-board diagnostic (OBD) faults. By analyzing the existing means of tampering in the last decade, the vehicle tampering identification model was established according to the data characteristics of tampered vehicles. Two main modules based on emission and emission factors were built and three corrections were added in the model to avoid disturbances led to misjudge. In our research, 66 heavy-duty vehicles from the big data platform were used to screen for vehicle tampering. It was found that 15 vehicles existed excessive emissions, and 2 vehicles were tampered. Tampered vehicles only account for 3% of the sample, but emitted 1.4 times nitrogen oxides (NOx) of total emission of other vehicles. The model solved the problem that the traditional model could not identify the vehicle tampering accurately. It could be used in emission accounting and management of tampered vehicles for government.</p></div>","PeriodicalId":8604,"journal":{"name":"Atmospheric Pollution Research","volume":"15 10","pages":"Article 102240"},"PeriodicalIF":3.9,"publicationDate":"2024-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141539259","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":"Dust model sensitivity to dust source mask, sandblasting efficiency, air density, and land use: Implications for model improvement","authors":"Janak R. Joshi","doi":"10.1016/j.apr.2024.102230","DOIUrl":"https://doi.org/10.1016/j.apr.2024.102230","url":null,"abstract":"<div><p>This study compares dust storm simulations using two commonly adopted methods for representing four important dust emission parameters. Compared with a dynamic dust source mask based on land use and vegetation cover, a static mask based solely on land use overestimates dust concentration and optical depth by a factor of 2, besides generating spurious emissions. The results reinforce that seasonal variations in vegetation cover can significantly affect dust emissions. For sandblasting efficiency, a clay-dependent semiempirical expression produces 12 times more dust than does a physics-based expression. Simulations using model-predicted versus constant air density differ by only 8%. However, this difference (often overlooked) could range between 12% and 22% for annual simulations over global dust source regions. Simulations with updated versus old land use data, using the same dust source mask, differ twofold, indicating the significant impact of land use change on regional dust emission in central Arizona. The difference between simulations within each of the four pairs is generally larger than the uncertainty due to meteorology. The simulations align better with observation when using the dynamic dust source mask, the physics-based sandblasting efficiency, and the up-to-date land use data. Given the high sensitivity of dust to surface conditions, the results discussed have implications for improving the dust cycle in weather and climate models and for interpreting model intercomparisons.</p></div>","PeriodicalId":8604,"journal":{"name":"Atmospheric Pollution Research","volume":"15 10","pages":"Article 102230"},"PeriodicalIF":3.9,"publicationDate":"2024-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141539257","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":"Evaluating exhaust emissions from heterogeneous car fleet through real-time field-generated dataset","authors":"Abhinav Pandey ,&nbsp;Govind Pandey ,&nbsp;Rajeev Kumar Mishra","doi":"10.1016/j.apr.2024.102232","DOIUrl":"https://doi.org/10.1016/j.apr.2024.102232","url":null,"abstract":"<div><p>Light-duty vehicular exhaust remains one of the key sources of ambient air pollution globally, despite concerted mitigation efforts by the countries worldwide. It is of top scientific interest to explore vehicular variables affecting such emission from passenger cars through real-time monitoring (N = 1561). The research investigated emission parameters such as CO, HC, CO₂, O₂, λ (Lambda) and Air-fuel ratio (AFR), alongside the vehicular variables, namely, age, mileage, emission norm and maintenance category. The model-oriented study found the car age (R_rangeA = 0.81–0.98 for E_COI; 0.72–0.96 for E_HCI; 0.74–0.91 for λ_FI and 0.75–0.93 for AFR_FI, respectively) and mileage (R_rangeM = 0.71–0.98 for E_COI; 0.75–0.95 for E_HCI; 0.69–0.93 for λ_FI and 0.68–0.92 for AFR_FI, respectively) to be the most significant aspects. Further, the study reported that the emissions improved with the progression of in-use norms (tighter the norm, lower the emission). Interestingly, the maintenance level of cars is found to be directly and inversely related to both CO and HC emissions in different testing modes. It further presents car model-wise emission equations for car age and mileage as which can be used to accurately predict the exhaust emission from cars. The research outlines the need to incorporate car mileage, maintenance level and applicable emission norm into the present environmental policy, particularly in the developing countries. An improved emission testing, real-time emission data and appropriate environment regulation are the three major steps towards urban air quality improvement policy.</p></div>","PeriodicalId":8604,"journal":{"name":"Atmospheric Pollution Research","volume":"15 10","pages":"Article 102232"},"PeriodicalIF":3.9,"publicationDate":"2024-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141481571","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":"Machine learning models application for spatiotemporal patterns of particulate matter prediction and forecasting over Morocco in north of Africa","authors":"Sbai Salah Eddine ,&nbsp;Lalla Btissam Drissi ,&nbsp;Nezha Mejjad ,&nbsp;Jamal Mabrouki ,&nbsp;Aleksey A. Romanov","doi":"10.1016/j.apr.2024.102239","DOIUrl":"https://doi.org/10.1016/j.apr.2024.102239","url":null,"abstract":"<div><p>Atmospheric air pollution exposure raises morbidity and mortality rates and is a major cause of the world's illness burden. In this context, we explored spatial and temporal trends in particulate matter PM10 from 2003 to 2020 over Morocco to assess air pollution exposure. We use the capabilities of ML models to study PM10 trends using 26 predictor variables, including meteorological parameters, volatile organic compounds, atmospheric oxidants, and aerosol optical depth data from the Copernicus Atmosphere Monitoring Service (CAMS). For this purpose, three ML models were built: Multiple Linear Regression (MLR), Random Forest Regression (RFR), and Generalized Additive Model (GAM). To match and optimize these models, a set of ML algorithms has been coupled with each model. The results show all these models are highly accurate in predicting and forecasting PM10 total column trends. Cross-validation showed that GAM had better prediction ability for the PM10 total column with R² = 0.994 and a very low root mean squared error (RMSE) not exceeding 0.046 × 10⁻¹⁶ kg/m². The GAM model showed much higher predictive ability and lower bias than the other models. This finding can be explained by the advantages of GAMs, including their ability to capture complex and non-linear patterns in the data, making them particularly useful when relationships are not easily represented by linear models. This study has presented a comprehensive methodology for predicting the spatiotemporal variability of PM10. The proposed methodology holds potential applicability across all regions, facilitating the generation of high-resolution PM10 monitoring and the establishment of systems for the early detection of air pollution incidents in Morocco. Furthermore, the developed models exhibit versatility, enabling their application for estimating future trends of individual pollutants or making real-time predictions of air quality levels. This research contributes to advancing the understanding and proactive management of air quality in the context of Morocco, offering valuable insights for pollution control efforts.</p></div>","PeriodicalId":8604,"journal":{"name":"Atmospheric Pollution Research","volume":"15 9","pages":"Article 102239"},"PeriodicalIF":3.9,"publicationDate":"2024-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141482818","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":"Validation of cheap axial passive sampler and procedure suitable for atmospheric NO2 community-based monitoring","authors":"Alma Moretta ,&nbsp;Daniele Sofia ,&nbsp;Maria Ricciardi ,&nbsp;Vincenzo Venditto ,&nbsp;Antonio Proto","doi":"10.1016/j.apr.2024.102234","DOIUrl":"https://doi.org/10.1016/j.apr.2024.102234","url":null,"abstract":"<div><p>Nitrogen dioxide (NO₂) is an air pollutant highly impacting on human health, and its measurement is crucial for air quality assessment. Use of passive samplers for long-term large-scale monitoring is a reasonably reliable and economic alternative to more sophisticated and expensive equipment employed in active air sampling by environmental control authorities. In recent years the Citizen Science approach, based on low-cost devices, is spreading more and more in environmental control. Passive samplers available on the market (like the consolidated “Palmes” tubes) are often used in community-based monitoring campaigns. We describe validation of a new cheap axial diffusion tube for NO₂ monitoring, used in combination with a new user-friendly App for smartphone that represents an innovation to speed up recording of geo-localization and exposition period data. Affordability and availability of materials, simple construction protocol and easy App procedure, allow possible self-production by school students and non-expert users, making the proposed tube a potential tool to realize extended Citizen Science monitoring campaigns. Accuracy within 25% and precision within 20%, evidenced in validation, show comparability of the tube performance with Palmes-type tubes and agreement with the official monitoring station results. Two small-scale trial monitoring campaigns, involving high school students, were performed to test the efficacy of the proposed “tube-App” system in combining educational impact and community value of air quality monitoring.</p></div>","PeriodicalId":8604,"journal":{"name":"Atmospheric Pollution Research","volume":"15 9","pages":"Article 102234"},"PeriodicalIF":3.9,"publicationDate":"2024-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1309104224001995/pdfft?md5=390563cb80cb754bf9b22957ed25a2ac&pid=1-s2.0-S1309104224001995-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141482569","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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":"Magnetic properties and load of potentially toxic heavy metals carried by the coarse and fine fractions of indoor dust","authors":"Beata Górka-Kostrubiec,&nbsp;Katarzyna Dudzisz","doi":"10.1016/j.apr.2024.102237","DOIUrl":"https://doi.org/10.1016/j.apr.2024.102237","url":null,"abstract":"<div><p>The granulometric fractions of indoor dust, categorized as coarse (grain size of 1.00–0.071 mm) and fine (grain size &lt;0.071 mm), were investigated to discern variations in their magnetic properties and contents of potentially toxic heavy metals. Monthly dust samples were gathered from January 2021 to December 2022 from a private apartment situated on the outskirts of a large urban agglomeration (Warsaw, Poland). To assess indoor dust, several magnetic parameters, including mass-specific magnetic susceptibility, were employed. Portable X-ray fluorescence measurements were utilized to evaluate the enrichment of granulometric fractions in harmful heavy metals. The study reveals a comparable composition of magnetic minerals irrespective of grain size (magnetite and metallic iron), with variations observed in the domain state of magnetic particles (contribution of single-domain (SD) grains to multi-domain (MD)). Seasonal fluctuations were predominantly noted in the distribution of the fine fraction's mass during the warm season (May–July). A notable increase was observed in the fine fraction's mass contribution to the total dust mass compared to the winter season (December and February). The fine fraction was highly enriched in toxic metals, including Pb, Cr, Cu, Mn, Fe, and Sr. Pollution Load index is 6–8 for the fine fraction and 2–8 for the coarse fraction. The increase in the fine fraction mass induces linear changes in magnetic susceptibility, likely associated with the rise in anthropogenic magnetic particles. This finding holds significant implications for human health, as fine particles laden with toxic heavy metals can enter the human respiratory tract causing adverse health effects.</p></div>","PeriodicalId":8604,"journal":{"name":"Atmospheric Pollution Research","volume":"15 9","pages":"Article 102237"},"PeriodicalIF":3.9,"publicationDate":"2024-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141482817","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":"Source apportionment of fine particulate matter in middle Indo-Gangetic Plain by coupled radiocarbon –molecular organic tracer method","authors":"Ningombam Linthoingambi Devi ,&nbsp;Amrendra Kumar ,&nbsp;Ishwar Chandra Yadav ,&nbsp;Sonke Szidat ,&nbsp;Rajveer Sharma","doi":"10.1016/j.apr.2024.102231","DOIUrl":"https://doi.org/10.1016/j.apr.2024.102231","url":null,"abstract":"<div><p>Despite significant emissions of fine particulate matter (FPM) from the Indo-Gangetic Plain (IGP) that affect the climate and air quality in the region, the sources of these emissions are not adequately addressed. This research uses a combined radiocarbon-molecular organic tracer technique to investigate the degree of contamination, seasonal fluctuations, and contribution of FPM in the middle IGP (Patna), India. The findings indicated levoglucosan (L) as the single primary BB tracer chemical, ranging from 149 ng/m³ to 490 ng/m³ (median 282 ng/m³). Winter (median 462 ng/m³) showed a 2–3 times higher level of L than the monsoon season (median 180 ng/m³). A significant association of L with other organic tracers such as galactosan (G), mannosan (M), vallinic acid, syringic acid, p-hydroxybenzoic acid (pHA) and dehydroabietic acid (DHAA)(<em>r</em> = 0.53 to 0.89, <em>p</em> &lt; 0.05), and moderate connection with Cl⁻ (<em>r</em> = 0.21, <em>p</em> &lt; 0.05), SO₄²⁻ (<em>r</em> = 0.29, <em>p</em> &lt; 0.05), and NO₃- (<em>r</em> = 0.22, <em>p</em> &lt; 0.05) indicated significant BB contribution. However, non-sea salt (nss-K⁺) was not related to L. Based on seven days of air mass back trajectories and MODIS active fire counts analysis, we conclude that OAs composition is not the local origin but is also impacted by long-range atmospheric transport from Pakistan/Afghanistan, followed by the Bay of Bengal and the Arabian Sea. Chemical analysis of organic tracers and positive matrix factorization (PMF) modeling study identified three unique sources, i.e., biomass burning, secondary aerosols formation, and mixed type (fossil fuels and construction dust) as the primary source of FPM in Patna, accounted for 46.1 %, 28.9 %, and 24.9 %, of total emissions, respectively. The radiocarbon (¹⁴ C) analysis of total carbon (TC) samples further supported this conclusion. The results of ^{the 14} C study indicated that emissions from BB, such as wood and stubble, were responsible for 57% of the TC concentration.</p></div>","PeriodicalId":8604,"journal":{"name":"Atmospheric Pollution Research","volume":"15 10","pages":"Article 102231"},"PeriodicalIF":3.9,"publicationDate":"2024-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141539261","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}