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Liu B, Yang Y, Fu Y, Zhao Y, Chen W, Wei S, Zuo X, Zhu Y, Ye H, Zhang M, Zhang P, Yang L, Wang W, Pan J. In-house ammonia induced lung impairment and oxidative stress of ducks. Poult Sci 2024; 103:103622. [PMID: 38513550 PMCID: PMC10973188 DOI: 10.1016/j.psj.2024.103622] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2023] [Revised: 02/20/2024] [Accepted: 03/01/2024] [Indexed: 03/23/2024] Open
Abstract
Ammonia (NH3) is a toxic gas that in intensive poultry houses, damages the poultry health and induces various diseases. This study investigated the effects of NH3 exposure (0, 15, 30, and 45 ppm) on growth performance, serum biochemical indexes, antioxidative indicators, tracheal and lung impairments in Pekin ducks. A total of 288 one-day-old Pekin male ducks were randomly allocated to 4 groups with 6 replicates and slaughtered after the 21-d test period. Our results showed that 45 ppm NH3 significantly reduced the average daily feed intake (ADFI) of Pekin ducks. Ammonia exposure significantly reduced liver, lung, kidney, and heart indexes, and lowered the relative weight of the ileum. With the increasing of in-house NH3, serum NH3 and uric acid (UA) concentrations of ducks were significantly increased, as well as liver malondialdehyde (MDA), superoxide dismutase (SOD), and glutathione peroxidase (GPX-Px) contents. High NH3 also induced trachea and lung injury, thereby increasing levels of tumor necrosis factor-α (TNF-α) and interleukin-4 (IL-4) in the lung, and decreasing the mRNA expressions of zonula occludens 1 (ZO-1) and claudin 3 (CLDN3) in the lung. In conclusion, in-house NH3 decrease the growth performance in ducks, induce trachea and lung injuries and meanwhile increase the compensatory antioxidant activity for host protection.
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Affiliation(s)
- Bo Liu
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science, South China Agricultural University Guangzhou, China; Changsha Sanwang Feed Co. Ltd, Changsha, China
| | - Yongjie Yang
- Key Laboratory of Animal Nutrition and Healthy Breeding, Ministry of Agriculture, Wen's Foodstuff Group Co. Ltd, Yunfu, China
| | - Yang Fu
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science, South China Agricultural University Guangzhou, China
| | - Yue Zhao
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science, South China Agricultural University Guangzhou, China
| | - Wenjing Chen
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science, South China Agricultural University Guangzhou, China
| | - Shi Wei
- Key Laboratory of Animal Nutrition and Healthy Breeding, Ministry of Agriculture, Wen's Foodstuff Group Co. Ltd, Yunfu, China
| | - Xin Zuo
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science, South China Agricultural University Guangzhou, China
| | - Yongwen Zhu
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science, South China Agricultural University Guangzhou, China
| | - Hui Ye
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science, South China Agricultural University Guangzhou, China
| | - Minhong Zhang
- State Key Laboratory of Animal Nutrition, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Pekin, China
| | - Peng Zhang
- Chimelong Group Co., Guangzhou 511430, China
| | - Lin Yang
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science, South China Agricultural University Guangzhou, China
| | - Wence Wang
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science, South China Agricultural University Guangzhou, China.
| | - Jie Pan
- Hunan Shihua Biotech Co. Ltd., Changsha, China
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Shi R, Zhang F, Shen Y, Shen J, Xu B, Kuang B, Xu Z, Jin L, Tang Q, Tian X, Wang Z. Aerosol liquid water in PM 2.5 and its roles in secondary aerosol formation at a regional site of Yangtze River Delta. J Environ Sci (China) 2024; 138:684-696. [PMID: 38135431 DOI: 10.1016/j.jes.2023.04.030] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2022] [Revised: 04/22/2023] [Accepted: 04/22/2023] [Indexed: 12/24/2023]
Abstract
Aerosol liquid water content (ALWC) plays an important role in secondary aerosol formation. In this study, a whole year field campaign was conducted at Shanxi in north Zhejiang Province during 2021. ALWC estimated by ISORROPIA-II was then investigated to explore its characteristics and relationship with secondary aerosols. ALWC exhibited a highest value in spring (66.38 µg/m3), followed by winter (45.08 µg/m3), summer (41.64 µg/m3), and autumn (35.01 µg/m3), respectively. It was supposed that the secondary inorganic aerosols (SIA) were facilitated under higher ALWC conditions (RH > 80%), while the secondary organic species tended to form under lower ALWC levels. Higher RH (> 80%) promoted the NO3- formation via gas-particle partitioning, while SO42- was generated at a relative lower RH (> 50%). The ALWC was more sensitive to NO3- (R = 0.94) than SO42- (R = 0.90). Thus, the self-amplifying processes between the ALWC and SIA enhanced the particle mass growth. The sensitivity of ALWC and OX (NO2 + O3) to secondary organic carbon (SOC) varied in different seasons at Shanxi, more sensitive to aqueous-phase reactions (daytime R = 0.84; nighttime R = 0.54) than photochemical oxidation (daytime R = 0.23; nighttime R = 0.41) in wintertime with a high level of OX (daytime: 130-140 µg/m3; nighttime: 100-140 µg/m3). The self-amplifying process of ALWC and SIA and the aqueous-phase formation of SOC will enhance aerosol formation, contributing to air pollution and reduction of visibility.
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Affiliation(s)
- Ruifang Shi
- College of Environmental and Resource Sciences, Zhejiang Provincial Key Laboratory of Organic Pollution Process and Control, Zhejiang University, Hangzhou 310058, China
| | - Fei Zhang
- College of Environmental and Resource Sciences, Zhejiang Provincial Key Laboratory of Organic Pollution Process and Control, Zhejiang University, Hangzhou 310058, China
| | - Yemin Shen
- Zhejiang Ecological and Environmental Monitoring Center, Hangzhou 310012, China
| | - Jiasi Shen
- Zhejiang Ecological and Environmental Monitoring Center, Hangzhou 310012, China
| | - Bingye Xu
- Zhejiang Ecological and Environmental Monitoring Center, Hangzhou 310012, China
| | - Binyu Kuang
- College of Environmental and Resource Sciences, Zhejiang Provincial Key Laboratory of Organic Pollution Process and Control, Zhejiang University, Hangzhou 310058, China
| | - Zhengning Xu
- College of Environmental and Resource Sciences, Zhejiang Provincial Key Laboratory of Organic Pollution Process and Control, Zhejiang University, Hangzhou 310058, China
| | - Lingling Jin
- Zhejiang Ecological and Environmental Monitoring Center, Hangzhou 310012, China
| | - Qian Tang
- Zhejiang Ecological and Environmental Monitoring Center, Hangzhou 310012, China
| | - Xudong Tian
- Zhejiang Ecological and Environmental Monitoring Center, Hangzhou 310012, China
| | - Zhibin Wang
- College of Environmental and Resource Sciences, Zhejiang Provincial Key Laboratory of Organic Pollution Process and Control, Zhejiang University, Hangzhou 310058, China; ZJU-Hangzhou Global Scientific and Technological Innovation Center, Zhejiang University, Hangzhou 311215, China.
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Mollaamin F, Monajjemi M. Tailoring and functionalizing the graphitic-like GaN and GaP nanostructures as selective sensors for NO, NO 2, and NH 3 adsorbing: a DFT study. J Mol Model 2023; 29:170. [PMID: 37148380 DOI: 10.1007/s00894-023-05567-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2023] [Accepted: 04/19/2023] [Indexed: 05/08/2023]
Abstract
CONTEXT Langmuir adsorption of gas molecules of NO, NO2, and NH3 on the graphitic GaN and GaP sheets has been accomplished using density functional theory. The changes of charge density have shown a more important charge transfer for GaN compared to GaP which acts both as the electron donor while gas molecules act as the stronger electron acceptors through adsorption on the graphitic-like GaN surface. The adsorption of NO and NO2 molecules introduced spin polarization in the PL-GaN sheet, indicating that it can be employed as a magnetic gas sensor for NO and NO2 sensing. METHODS The partial electron density states based on "PDOS" graphs have explained that the NO and NO2 states in both of GaN and GaP nanosheets, respectively, have more of the conduction band between - 5 and - 10 eV, while expanded contribution of phosphorus states is close to gallium states, but nitrogen and oxygen states have minor contributions. GaN and GaP nanosheets represent having enough capability for adsorbing gases of NO, NO2, and NH3 through charge transfer from nitrogen atom and oxygen atom to the gallium element owing to intra-atomic and interatomic interactions. Ga sites in GaN and GaP nanosheets have higher interaction energy from Van der Waals' forces with gas molecules.
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Affiliation(s)
- Fatemeh Mollaamin
- Department of Biology, Faculty of Science, Kastamonu University, Kastamonu, Turkey.
| | - Majid Monajjemi
- Department of Chemical Engineering, Central Tehran Branch, Islamic Azad University, Tehran, Iran
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Cheng L, Ye Z, Cheng S, Guo X. Agricultural ammonia emissions and its impact on PM 2.5 concentrations in the Beijing-Tianjin-Hebei region from 2000 to 2018. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2021; 291:118162. [PMID: 34555794 DOI: 10.1016/j.envpol.2021.118162] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/03/2021] [Revised: 09/07/2021] [Accepted: 09/09/2021] [Indexed: 06/13/2023]
Abstract
Ammonia (NH3) discharged from agricultural activities to the atmosphere plays a crucial role in the formation of secondary inorganic aerosols. This study analyzed the temporal-spatial development of agricultural NH3 emissions from 2000 to 2018 in the Beijing-Tianjin-Hebei (BTH) region and assessed the effects of reducing PM2.5 by removing agricultural NH3 using an air quality model. The results showed that the interannual agricultural NH3 emissions in the BTH region exhibited a stairs trend from 2000 to 2018, with an average of 971.63 Gg. In particular, agricultural NH3 emissions in the BTH region reached a maximum in summer when the temperature was high and were more concentrated in the southern plains compared to the northern areas. Under the reduction scenario (RS), the agricultural NH3 emissions in the BTH region in 2015, 2016, 2017, and 2018 were reduced by 2.95%, 4.10%, 18.75%, and 10.21%, resulting in a reduction of 0.5%, 0.5%, 2.5%, and 1.2% of annual mean PM2.5 concentration, respectively, compared with the baseline scenario (BS). Furthermore, agricultural NH3 emissions contributed 12.6, 12.1, 11.9, and 11.3 μg m-3 to PM2.5 concentrations in 2015, 2016, 2017, and 2018 under the zero-emission scenario (ZS), respectively. However, the contribution rates exhibited a slightly increasing trend from 20.5% in 2015 to 24.6% in 2018. These findings could provide a new understanding of agricultural NH3 emission trends and their impacts on PM2.5 concentration based on actual NH3 mitigation ratios in recent years, thereby guiding the formulation of future control strategies.
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Affiliation(s)
- Long Cheng
- College of Environmental & Energy Engineering, Key Laboratory of Beijing on Regional Air Pollution Control, Beijing University of Technology, Beijing, 100124, China
| | - Zhilan Ye
- College of Environmental & Energy Engineering, Key Laboratory of Beijing on Regional Air Pollution Control, Beijing University of Technology, Beijing, 100124, China
| | - Shuiyuan Cheng
- College of Environmental & Energy Engineering, Key Laboratory of Beijing on Regional Air Pollution Control, Beijing University of Technology, Beijing, 100124, China
| | - Xiurui Guo
- College of Environmental & Energy Engineering, Key Laboratory of Beijing on Regional Air Pollution Control, Beijing University of Technology, Beijing, 100124, China.
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Bhunia GS, Ding D. Temporal and spatial statistical analysis of ambient air quality of Assam (India). JOURNAL OF THE AIR & WASTE MANAGEMENT ASSOCIATION (1995) 2020; 70:775-794. [PMID: 32442037 DOI: 10.1080/10962247.2020.1772406] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/12/2019] [Revised: 02/07/2020] [Accepted: 03/11/2020] [Indexed: 06/11/2023]
Abstract
UNLABELLED Present paper represents the spatio-temporal variation of air quality and performances of geostatistical tools for the identification of pollutants zone in various districts of Assam (India). Geographic Information System (GIS) and geostatistical analysis were utilized to estimate the spatio-temporal variations (2015-2017) of gaseous and particulate air pollutants. Data of 23 fixed monitoring stations were collected from the Central Pollution Control Board (CPCB). It was observed that SO2 and NOx concentrations are the major pollutants to the deterioration of air quality in Assam State. Exploratory data analysis was considered for the determination of spatial and temporal patterns of air pollutants. Air Quality index (AQI) was calculated based on the air pollutants and particulate matter. Radial Basis Function (RBF) interpolation techniques were used to analyze the spatial and temporal variation of air quality in Assam. Cross-validation is applied to evaluate the accuracy of interpolation methods in terms of Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), Nash-Sutcliffe Equation (NSE) and Accuracy Factor (ACFT). In 2015, the high value of AQI portrayed in the central and northeast of the state. In 2016, the central and entire east of the study area was recorded the highest value of AQI. In 2017, it was observed that mostly the central part of the state recorded the high value of AQI. The spatio-temporal variation trend of air pollutants provides sound scientific basis for its management and control. This information of air pollution congregation would be valuable for urban planners and decision architects to efficiently administer air quality for health and environmental purposes. IMPLICATIONS Guwahati is one of the most polluted cities in India provided a novel evidence to find out the impact of air pollution. Present study has been suffered from several limitations, like (i) the daily or weekly concentration of air pollutants was not gained due to limited monitoring technique, (2) dearth of regular information of PM2.5 collection, which were not regularly connected. Present study is used to estimate the spatio-temporal variations (2015-2017) of gaseous and particulate air pollutants using GIS and spatial statistical approach. Probably, this is the first study to report the spatial and temporal variation of air quality distribution in Assam. Results showed there is a negative impact on the ambient air quality status of Assam. These industries and mining areas contribute significantly to the air pollution in this deltaic region. This district-wise information of air pollution congregation would be valuable for urban planners and decision architects to efficiently administer air quality for health and environmental purposes. The dissimilarity in geographical dissemination of the pollutant concentration has been more helpful in seasonal inevitability. Consequently, a continuous set of data and more parameters can be included to attain more reliable results.
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Affiliation(s)
| | - Ding Ding
- Department of Architecture and Urban Design, Chinese Culture University , Taipei, Taiwan, Republic of China
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Guo X, Ye Z, Chen D, Wu H, Shen Y, Liu J, Cheng S. Prediction and mitigation potential of anthropogenic ammonia emissions within the Beijing-Tianjin-Hebei region, China. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2020; 259:113863. [PMID: 31918139 DOI: 10.1016/j.envpol.2019.113863] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/26/2019] [Revised: 12/19/2019] [Accepted: 12/19/2019] [Indexed: 06/10/2023]
Abstract
Large ammonia (NH3) emissions contribute approximately 8-30% to the fine particle pollution in China and highlight the need for understanding the emission trends and mitigation effects of NH3 in the future. The purpose of this study is to predict the NH3 emissions and analyze the mitigation potential up to year 2040 by scenario analysis based on the established new NH3 emission inventory from anthropogenic sources for the Beijing-Tianjin-Hebei (BTH) region. The results showed that the total NH3 emission in the BTH region was estimated at 966.14 Gg in 2016. Under the Business-as-Usual (BAU) scenario, the total NH3 emissions in 2030 and 2040 would increase by 13% and 26% compared with 2016 levels, with average annual growth rates of 0.9% and 1.0%, respectively. Livestock will continue to dominate NH3 emissions in the future, with the proportions of total emissions increasing from 57% in 2016 to 64% in 2030 and 68% in 2040. The share of the second-largest NH3 emission source, synthetic fertilizer application, will decrease from 36% in 2016 to 31% in 2030 and 27% in 2040. Among five other sources, the largest change occurred in waste disposal, increasing notably by 3.31 times from 2016 to 2040 owing to rapid urbanization. Under the Combined Options (CO) scenario, the total NH3 emissions could be reduced by as much as 34% by 2030 and 50% by 2040 compared with the BAU scenario, which is attributed to livestock (24% in 2030, 37% in 2040) and synthetic fertilizer application (10% in 2030, 13% in 2040), respectively. This study can give a reliable estimation of anthropogenic NH3 emission in the BTH region during 2020-2040 and provide a valuable reference for effective mitigation measures and control strategies for policy makers.
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Affiliation(s)
- Xiurui Guo
- College of Environmental & Energy Engineering, Key Laboratory of Beijing on Regional Air Pollution Control, Beijing University of Technology, Beijing, 100124, China.
| | - Zhilan Ye
- College of Environmental & Energy Engineering, Key Laboratory of Beijing on Regional Air Pollution Control, Beijing University of Technology, Beijing, 100124, China.
| | - Dongsheng Chen
- College of Environmental & Energy Engineering, Key Laboratory of Beijing on Regional Air Pollution Control, Beijing University of Technology, Beijing, 100124, China.
| | - Hongkan Wu
- College of Environmental & Energy Engineering, Key Laboratory of Beijing on Regional Air Pollution Control, Beijing University of Technology, Beijing, 100124, China.
| | - Yaqian Shen
- College of Environmental & Energy Engineering, Key Laboratory of Beijing on Regional Air Pollution Control, Beijing University of Technology, Beijing, 100124, China.
| | - Junfang Liu
- College of Environmental & Energy Engineering, Key Laboratory of Beijing on Regional Air Pollution Control, Beijing University of Technology, Beijing, 100124, China.
| | - Shuiyuan Cheng
- College of Environmental & Energy Engineering, Key Laboratory of Beijing on Regional Air Pollution Control, Beijing University of Technology, Beijing, 100124, China.
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Hidy GM. An historical experiment: Los Angeles smog evolution observed by blimp. JOURNAL OF THE AIR & WASTE MANAGEMENT ASSOCIATION (1995) 2018; 68:643-655. [PMID: 29432064 DOI: 10.1080/10962247.2018.1433251] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/02/2017] [Revised: 01/05/2018] [Accepted: 01/23/2018] [Indexed: 06/08/2023]
Abstract
UNLABELLED Observations of smog over the Los Angeles Basin (LAB) links high oxidant mixing ratios with poor visibility, sometimes <5 km. By the 1970s, investigators recognized that most of the aerosol affecting visibility was from gaseous oxidation products, sulfate, nitrate, and organic carbon. This led to the 1972-1973 Aerosol Characterization Experiment (ACHEX), which included observations at the ground and from aircraft. Part of ACHEX was the measurement of smog by blimp in a Lagrangian-like format. The experiment on September 6, 1973, demonstrated that a blimp could travel with the wind across the LAB, observing ozone (O3) and precursors, and particles of different size ranges. These included condensation nuclei (CN) concentrations dominated by particles of ≤ 0.1 µm diameter and light scattering coefficient (bsc) representing mainly particles of 0.1-2.0 µm diameter. The results indicated a pollutant variation similar to that measured at a fixed site. Ozone was produced in an air mass, reaching a maximum of ~400 ppb in the presence of nitrogen oxides (NOx) and nonmethane hydrocarbons (NMHCs), then declined. Although the photochemistry was developing, bsc grew with O3 mixing ratio to a quasi-steady state at ~9-10 × 10-4 m-1, decreasing in value much later with decease in O3. The light scattering coefficient was found to be positively associated with the O3 mixing ratio, whereas CN concentrations were negatively proportional to O3 mixing ratio. The blimp experiment was supported with aircraft vertical profiles and ground-level observations from a mobile laboratory. The blimp flight obtained combined gas and particle changes aloft that could not be obtained by ground or fixed-wing aircraft measurements alone. The experiment was partially successful in achieving a true Lagrangian characterization of smog chemistry in a constrained or defined "open" air mass. IMPLICATIONS The Los Angeles experiment demonstrated the use of a blimp as a platform for measurement of air pollution traveling with an air mass across an urban area. The method added unique data showing the relationship between photochemical smog chemistry and aerosol dynamics in smog. The method offers an alternative to reliance on smog chamber and modeling observations to designing air quality management strategies for reactive pollutants.
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Affiliation(s)
- G M Hidy
- a Envair/Aerochem , Placitas , NM , USA
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An J, Cao Q, Zou J, Wang H, Duan Q, Shi Y, Chen C, Wang J. Seasonal Variation in Water-Soluble Ions in Airborne Particulate Deposition in the Suburban Nanjing Area, Yangtze River Delta, China, During Haze Days and Normal Days. ARCHIVES OF ENVIRONMENTAL CONTAMINATION AND TOXICOLOGY 2018; 74:1-15. [PMID: 28889236 DOI: 10.1007/s00244-017-0447-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/23/2017] [Accepted: 08/30/2017] [Indexed: 06/07/2023]
Abstract
To investigate the seasonal variation and characterization of water-soluble ions (WSIs) present in airborne particle deposition (APD) during Haze Days (visibility ≤7.5 km) and Normal Days (visibility >7.5 km) in suburban Nanjing area, 151 filter samples were collected from 18 May 2013 to 26 May 2014. Ten different WSIs from the samples were determined by Ion Chromatography. The results indicated that secondary WSIs (NH4+, NO3-, and SO42-) were the main ions in the WSIs, averaging 17.2, 18.5, and 17.1 μg/m3, respectively, and accounting respectively 20.9, 22.5, and 20.8% of the total WSIs. On Haze Days, the concentration of WSIs increased dramatically in fine size (particle size <2.1 μm), especially for NH4+, NO3-, and SO42- (increased by 52.6, 71.3, and 73.1%, respectively), whereas the concentrations of WSIs increased slowly in coarse size (2.1 μm < particle size < 10 μm), in which NH4+, NO3-, and SO42- increased by 14.7, 27.2, and 54.5%, respectively. According to the backward trajectories and the principal component analysis analysis, Nanjing APD were mainly derived from the soil dust in northern China (35%) in the spring, from ocean air masses (61 and 55%) in the summer and the autumn, and from local air masses (73%) in the winter. On summer Haze Days, secondary components in PM2.1 consisted mainly of (NH4)2SO4 and NH4NO3, whereas secondary components in PM2.1-10 consisted mainly of (NH4)2SO4, NH4Cl, and NH4NO3. The increasing concentrations of secondary components increase the light extinction coefficients of aerosol on winter and autumn Haze Days. The concentrations of WSIs in fine size rose sharply on Haze Days, leading the visibility to exponential decline. Differently, the concentrations of WSIs in coarse size were not the main cause in the change of the visibility.
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Affiliation(s)
- Junlin An
- Key Laboratory of Meteorological Disaster, Ministry of Education (KLME), Joint International Research Laboratory of Climate and Environment Change (ILCEC), Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, Nanjing University of Information Science and Technology, Nanjing, 210044, China.
| | - Qimin Cao
- Key Laboratory of Meteorological Disaster, Ministry of Education (KLME), Joint International Research Laboratory of Climate and Environment Change (ILCEC), Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, Nanjing University of Information Science and Technology, Nanjing, 210044, China
| | - Jianan Zou
- Key Laboratory of Meteorological Disaster, Ministry of Education (KLME), Joint International Research Laboratory of Climate and Environment Change (ILCEC), Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, Nanjing University of Information Science and Technology, Nanjing, 210044, China
- Key Laboratory of Arid Climatic Changes and Disaster Reduction of Gansu Province, School of Atmospheric Sciences, Lanzhou University, Lanzhou, 730000, China
| | - Honglei Wang
- Key Laboratory of Meteorological Disaster, Ministry of Education (KLME), Joint International Research Laboratory of Climate and Environment Change (ILCEC), Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, Nanjing University of Information Science and Technology, Nanjing, 210044, China
| | - Qing Duan
- Key Laboratory of Meteorological Disaster, Ministry of Education (KLME), Joint International Research Laboratory of Climate and Environment Change (ILCEC), Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, Nanjing University of Information Science and Technology, Nanjing, 210044, China
| | - Yuanzhe Shi
- Key Laboratory of Meteorological Disaster, Ministry of Education (KLME), Joint International Research Laboratory of Climate and Environment Change (ILCEC), Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, Nanjing University of Information Science and Technology, Nanjing, 210044, China
| | - Chen Chen
- Key Laboratory of Meteorological Disaster, Ministry of Education (KLME), Joint International Research Laboratory of Climate and Environment Change (ILCEC), Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, Nanjing University of Information Science and Technology, Nanjing, 210044, China
| | - Junxiu Wang
- Key Laboratory of Meteorological Disaster, Ministry of Education (KLME), Joint International Research Laboratory of Climate and Environment Change (ILCEC), Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, Nanjing University of Information Science and Technology, Nanjing, 210044, China
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Affiliation(s)
| | | | - Sergey A. Nizkorodov
- Department
of Chemistry, University of California, Irvine, Irvine, California 92697, United States
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