1
|
Wang Y, Yu H, Li L, Li J, Sun J, Shi J, Li J. Long-term trend of dust event duration over Northwest China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 951:175819. [PMID: 39197795 DOI: 10.1016/j.scitotenv.2024.175819] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/06/2024] [Revised: 08/20/2024] [Accepted: 08/24/2024] [Indexed: 09/01/2024]
Abstract
Dust events in Northwest China have become more variable under regional climate change. Prior research has largely overlooked the spatial-temporal distribution of dust event duration (DED) and its long-term trend. This study systematically analyzed the spatial and temporal variations of DED in Northwest China and explored their associated factors using satellite-derived air quality datasets during 2000-2021. We find that dust event frequency (DEF) and DED generally showed a significant decreasing trend since 2000, but in 2013, DEF and DED started to rebound, with DED in particular, showing a more pronounced rebound in most parts of Northwest China. Correlation analysis with many factors suggests that the rise in near-surface wind speed since 2013 may primarily account for the increase in DEF and DED by enhancing dust generation and suppressing dust dry deposition processes. Further projections reveal that regions close to dust sources are likely to have more frequent and prolonged dust events, while areas far from dust sources will experience a decrease in DEF and DED in the future. These findings are crucial for understanding dust event variations and for guiding local dust management strategies.
Collapse
Affiliation(s)
- Yang Wang
- Key Laboratory for Semi-Arid Climate Change of the Ministry of Education, College of Atmospheric Sciences, and Collaborative Innovation Center for Western Ecological Safety, Lanzhou University, Lanzhou, China
| | - Haojie Yu
- Key Laboratory for Semi-Arid Climate Change of the Ministry of Education, College of Atmospheric Sciences, and Collaborative Innovation Center for Western Ecological Safety, Lanzhou University, Lanzhou, China; College of Earth and Environment Sciences, Lanzhou University, Lanzhou, China
| | - Lan Li
- Key Laboratory for Semi-Arid Climate Change of the Ministry of Education, College of Atmospheric Sciences, and Collaborative Innovation Center for Western Ecological Safety, Lanzhou University, Lanzhou, China
| | - Jiayi Li
- Key Laboratory for Semi-Arid Climate Change of the Ministry of Education, College of Atmospheric Sciences, and Collaborative Innovation Center for Western Ecological Safety, Lanzhou University, Lanzhou, China
| | - Jie Sun
- Key Laboratory for Semi-Arid Climate Change of the Ministry of Education, College of Atmospheric Sciences, and Collaborative Innovation Center for Western Ecological Safety, Lanzhou University, Lanzhou, China
| | - Jinsen Shi
- Key Laboratory for Semi-Arid Climate Change of the Ministry of Education, College of Atmospheric Sciences, and Collaborative Innovation Center for Western Ecological Safety, Lanzhou University, Lanzhou, China.
| | - Jiming Li
- Key Laboratory for Semi-Arid Climate Change of the Ministry of Education, College of Atmospheric Sciences, and Collaborative Innovation Center for Western Ecological Safety, Lanzhou University, Lanzhou, China.
| |
Collapse
|
2
|
Luo N, Zhang Y, Jiang Y, Zuo C, Chen J, Zhao W, Shi W, Yan X. Unveiling global land fine- and coarse-mode aerosol dynamics from 2005 to 2020 using enhanced satellite-based monthly inversion data. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2024; 348:123838. [PMID: 38521397 DOI: 10.1016/j.envpol.2024.123838] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/29/2023] [Revised: 03/09/2024] [Accepted: 03/20/2024] [Indexed: 03/25/2024]
Abstract
Accurate fine-mode and coarse-mode aerosol knowledge is crucial for understanding their impacts on the climate and Earth's ecosystems. However, current satellite-based Fine-Mode Aerosol Optical Depth (FAOD) and Coarse-Mode Aerosol Optical Depth (CAOD) methods have drawbacks including inaccuracies, low spatial coverage, and limited temporal duration. To overcome these issues, we developed new global-scale FAOD and CAOD from 2005 to 2020 using a novel deep learning model capable of the synergistic retrieval of two aerosol sizes. After validation with the aerosol robotic network (AERONET) and sky radiometer network (SKYNET), the new monthly FAOD and CAOD showed significant improvements in accuracy and spatial coverage. From 2005 to 2020, the new data showed that China had the greatest decrease in FAOD and CAOD. In contrast, India and South Latin America had a significant increase in FAOD versus North Africa in CAOD. FAOD in the regions of Argentina, Paraguay, and Uruguay in South America have shown an upward trend. The results reveal that FAOD and CAOD display distinct patterns of change in the same regions, particularly on the west coast of the United States where FAOD is increasing, while CAOD is decreasing. Aside from the year 2020 due to the global COVID-19 pandemic, the analysis showed that although China has seen at least an +85% increase in energy consumption and urban expansion in 2019 compared to 2005 due to the needs of development and construction, the implementation of China's air pollution control policies has led to a significant decrease in FAOD (-46%) and CAOD (-65%) after 2013. This research enriches our comprehension of global fine and coarse aerosol patterns, additional investigations are needed to determine the potential global implications of these changes.
Collapse
Affiliation(s)
- Nana Luo
- School of Geomatics and Urban Information, Beijing University of Civil Engineering and Architecture, Beijing, 102616, China
| | - Yue Zhang
- State Key Laboratory of Remote Sensing Science, Faculty of Geographical Science, Beijing Normal University, Beijing, 100875, China
| | - Yize Jiang
- State Key Laboratory of Remote Sensing Science, Faculty of Geographical Science, Beijing Normal University, Beijing, 100875, China
| | - Chen Zuo
- State Key Laboratory of Remote Sensing Science, Faculty of Geographical Science, Beijing Normal University, Beijing, 100875, China
| | - Jiayi Chen
- State Key Laboratory of Remote Sensing Science, Faculty of Geographical Science, Beijing Normal University, Beijing, 100875, China
| | - Wenji Zhao
- College of Resource Environment and Tourism, Capital Normal University, Beijing, 100048, China
| | - Wenzhong Shi
- Department of Land Surveying and Geo-Informatics, The Hong Kong Polytechnic University, Hong Kong, China
| | - Xing Yan
- State Key Laboratory of Remote Sensing Science, Faculty of Geographical Science, Beijing Normal University, Beijing, 100875, China.
| |
Collapse
|
3
|
Li J, He Q, Ge X, Abbas A, Jin L. Spatio-temporal changes of AOD in Xinjiang of China from 2000 to 2019: Which factor is more influential, natural factor or human factor? PLoS One 2021; 16:e0253942. [PMID: 34411113 PMCID: PMC8376058 DOI: 10.1371/journal.pone.0253942] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2020] [Accepted: 06/15/2021] [Indexed: 12/13/2022] Open
Abstract
Aerosol optical depth (AOD), which represents the optical attenuation, poses a major threat to the production activity, air quality, human health and regional sustainable development of arid and semi-arid areas. To some degree, AOD shows areal air pollution level and possesses obvious spatio-temporal characteristics. However, long-time sequences and detailed AOD information can not be provided due to currently limited monitoring technology. In this paper, a daily AOD product, MODIS-based Multi-angle Implementation of Atmospheric Correction (MAIAC), is deployed to analyze the spatio-temporal characteristics in Xinjiang Uygur Autonomous Region from 2000 to 2019. In addition, the importance of influencing factors for AOD is calculated through Random Forest (RF) Model and the propagation trajectories of pollutants are simulated through Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) Model. Spatio distribution of AOD presents a tendency that AOD value in northern Xinjiang is low while the value in southern Xinjiang is high. Regions with high AOD values are mainly concentrated in Tarim Basin. AOD in southern Xinjiang is the highest, followed by that in eastern Xinjiang and AOD value in northern Xinjiang is the lowest. Seasonal variation of AOD is significant: Spring (0.309) > summer (0.200) > autumn (0.161) > winter (0.158). Average AOD value in Xinjiang is 0.196. AOD appears wavy from 2000 to 2014 with its low inflection point (0.157) appearing in 2005, and then increases, reaching its peak in 2014 (0.223). The obvious downward tendency after 2014 shows that the use of coal to natural gas (NG) conversion project improves the conditions of local environment. According to RF Model, NG contributes most to AOD. HYSPLIT Model reveals that aerosol in southern Xinjiang is related to the short-distant carriage of dust aerosol from the Taklimakan Desert. Aerosol there can affect Inner Mongolia through long-distant transport. Blocked by the Tianshan Mountains, fine dust particles can not cross the Tianshan Mountains to become a factor contributing to AOD in northern Xinjiang.
Collapse
Affiliation(s)
- Jinglong Li
- College of Resources and Environment Sciences, Xinjiang University, Urumqi, Xinjiang, China.,Institute of Desert Meteorology, China Meteorological Administration, Urumqi, Xinjiang, China
| | - Qing He
- College of Resources and Environment Sciences, Xinjiang University, Urumqi, Xinjiang, China.,Institute of Desert Meteorology, China Meteorological Administration, Urumqi, Xinjiang, China
| | - Xiangyu Ge
- College of Resources and Environment Sciences, Xinjiang University, Urumqi, Xinjiang, China.,Key Laboratory of Oasis Ecology, Xinjiang University, Urumqi, Xinjiang, China.,Key Laboratory of Smart City and Environment Modelling of Higher Education Institute, College of Resources and Environment Sciences, Xinjiang University, Urumqi, Xinjiang, China
| | - Alim Abbas
- College of Resources and Environment Sciences, Xinjiang University, Urumqi, Xinjiang, China.,Institute of Desert Meteorology, China Meteorological Administration, Urumqi, Xinjiang, China
| | - Lili Jin
- Department of Atmospheric Sciences, Yunnan University, Kunming, China
| |
Collapse
|
4
|
Analysis of Mineral Aerosol in the Surface Layer over the Caspian Lowland Desert by the Data of 12 Summer Field Campaigns in 2002–2020. ATMOSPHERE 2021. [DOI: 10.3390/atmos12080985] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/25/2023]
Abstract
In-situ knowledge on characteristics of mineral aerosols is important for weather and climate prediction models, particularly for modeling such processes as the entrainment, transport and deposition of aerosols. However, field measurements of the dust emission flux, dust size distribution and its chemical composition under realistic wind conditions remain rare. In this study, we present experimental data over annual expeditions in the arid and semi-arid zones of the Caspian Lowland Desert (Kalmykia, south of Russia); we evaluate characteristics of mineral aerosol concentration and fluxes, estimate its chemical composition and calculate its long-distance transport characteristics. The mass concentration in different years ranges from several tens to several hundred of μg m−3. The significant influence of wind velocity on the value of mass and counting concentration and on the proposed entrainment mechanisms is confirmed. An increased content of anthropogenic elements (S, Sn, Pb, Bi, Mo, Ag, Cd, Hg, etc.), which is characteristic for all observation points in the south of the European Russia, is found. The trajectory analysis show that long-range air particles transport from the Caspian Lowland Desert to the central regions of European Russia tends to increase in the recent decades.
Collapse
|
5
|
Li J, Ge X, He Q, Abbas A. Aerosol optical depth (AOD): spatial and temporal variations and association with meteorological covariates in Taklimakan desert, China. PeerJ 2021; 9:e10542. [PMID: 33505790 PMCID: PMC7792517 DOI: 10.7717/peerj.10542] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2020] [Accepted: 11/20/2020] [Indexed: 12/29/2022] Open
Abstract
Aerosol optical depth (AOD) is a key parameter that reflects aerosol characteristics. However, research on the AOD of dust aerosols and various environmental variables is scarce. Therefore, we conducted in-depth studies on the distributions and variations of AOD in the Taklimakan Desert and its margins, China. We examined the correlation characteristics between AOD and meteorological factors combined with satellite remote sensing detection methods using MCD19A2-MODIS AOD products (from 2000, 2005, 2010, and 2015), MOD13Q1-MODIS normalized difference vegetation index products, and meteorological data. We analyzed the temporal and spatial distributions of AOD, periodic change trends, and important impacts of meteorological factors on AOD in the Taklimakan Desert and its margins. To explore the relationships between desert aerosols and meteorological factors, a random forest model was used along with environmental variables to predict AOD and rank factor contributions. Results indicated that the monthly average AOD exhibited a clear unimodal curve that reached its maximum in April. The AOD values followed the order spring (0.28) > summer (0.27) > autumn (0.18) > winter (0.17). This seasonality is clear and can be related to the frequent sandstorms occurring in spring and early summer. Interannual AOD showed a gradually increasing trend to 2010 then large changes to 2015. AOD tends to increase from south to north. Based on the general trend, the maximum value of AOD is more dispersed and its low-value area is always stable. The climatic index that has the most significant effect on AOD is relative humidity.
Collapse
Affiliation(s)
- Jinglong Li
- College of Resources and Environment Sciences, Xinjiang University, Urumqi, China.,Institute of Desert Meteorology, China Meteorological Administration, Urumqi, China
| | - Xiangyu Ge
- College of Resources and Environment Sciences, Xinjiang University, Urumqi, China.,Key Laboratory of Oasis Ecology, Xinjiang University, Urumqi, China.,Key Laboratory of Smart City and Environment Modelling of Higher Education Institute, College of Resources and Environment Sciences, Xinjiang University, Urumqi, Xinjiang, China
| | - Qing He
- College of Resources and Environment Sciences, Xinjiang University, Urumqi, China.,Institute of Desert Meteorology, China Meteorological Administration, Urumqi, China
| | - Alim Abbas
- College of Resources and Environment Sciences, Xinjiang University, Urumqi, China.,Institute of Desert Meteorology, China Meteorological Administration, Urumqi, China
| |
Collapse
|
6
|
Optical and Physical Characteristics of Aerosol Vertical Layers over Northeastern China. ATMOSPHERE 2020. [DOI: 10.3390/atmos11050501] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
The optical and physical characteristics of the aerosol vertical layers over Northeastern China (NEC) are investigated using the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) Level 2 layer products from 2007 to 2014. To better examine the spatial and temporal variations in the characteristics of aerosols over NEC, the region is divided into three parts (Heilongjiang province, Jilin province, and Liaoning province) to analyze the inter-annual and seasonal variations of nine selected aerosol parameters in each part during night and day times. The results reveal that the values of aerosol optical depth (AOD) increase year by year, over the whole NEC, being relatively high over the Liaoning (LN) province; this might be induced by higher levels of economic development and agricultural activity. The highest AOD values appear in summer, which is plausibly related to the temperate monsoon climate in NEC. Higher AOD values exist during the daytime than at night; this is intuitively the result of higher daytime anthropogenic activities. The base altitude of the lowest aerosol layer (BAL) and the top altitude of the highest aerosol layer (TAH) varied significantly due to the topography of NEC. The number of aerosol layers (N) is relatively large over LN, which might be caused by a relatively stronger atmospheric convection over this landscape. The thickness of the lowest aerosol layer (TLL) bore little relationship with the topography of NEC. The AOD proportion of the lowest aerosol layer (PAODL) is high (0.70 to 0.85 for the entire NEC), indicating that aerosols are mainly concentrated in the lowest layer of the atmosphere. The volume depolarization ratio of the lowest aerosol layer (VDRL) is large during spring and winter due to the presence of dust aerosols. The color ratio of the lowest aerosol layer (CRL) is large during the day due to relatively more human activities taking place than at night. Moreover, there is a significantly positive linear correlation between N and TAH, and a negative logarithm correlation between N and PAODL over NEC. The results of this study could provide researchers and the government departments with detailed and certain optical and physical information about aerosol layers over NEC, to help in the treatment of air pollution over NEC.
Collapse
|
7
|
Li W, Liu X, Zhang Y, Tan Q, Feng M, Song M, Hui L, Qu Y, An J, Gao H. Insights into the phenomenon of an explosive growth and sharp decline in haze: A case study in Beijing. J Environ Sci (China) 2019; 84:122-132. [PMID: 31284903 DOI: 10.1016/j.jes.2019.04.015] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2018] [Revised: 04/15/2019] [Accepted: 04/17/2019] [Indexed: 06/09/2023]
Abstract
A severe haze episode occurred in winter in the North China Plain (NCP), and the phenomenon of an explosive growth and sharp decline in PM2.5 (particulate matter with an aerodynamic diameter equal to or less than 2.5 μm) concentration was observed. To study the systematic causes for this phenomenon, comprehensive observations were conducted in Beijing from November 26 to December 2, 2015; during this period, meteorological parameters, LIDAR data, and the chemical compositions of aerosols were determined. The haze episode was characterized by rapidly varying PM2.5 concentration, and the highest PM2.5 concentration reached 667 μg/m3. During the haze episode, the NCP was dominated by a weak high-pressure system and continuously low PBL (planetary boundary layer) heights, which are unfavorable conditions for the diffusion of pollutants. The large increases in the concentrations of SNA (SO42-, NO3- and NH4+) during the haze implied that the formation of SNA was the largest contribution. Water vapor also played a vital role in the formation of haze by promoting the chemical transformation of secondary pollutants, which led to higher PM2.5 concentrations. The spatial distributions of PM2.5 in Beijing at different times and the backward trajectories of the air masses also indicated that pollutants from surrounding provinces in particular, contributed to the higher PM2.5 concentration.
Collapse
Affiliation(s)
- Wenguang Li
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875, China
| | - Xingang Liu
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875, China.
| | - Yuanhang Zhang
- State Key Joint Laboratory of Environment Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Qinwen Tan
- Chengdu Academy of Environmental Sciences, Chengdu 610072, China
| | - Miao Feng
- Chengdu Academy of Environmental Sciences, Chengdu 610072, China
| | - Mengdi Song
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875, China
| | - Lirong Hui
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875, China
| | - Yu Qu
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
| | - Junling An
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
| | - Haokai Gao
- Environmental monitoring station of Tianjin Port Free Trade Zone, Tianjin 300308, China
| |
Collapse
|
8
|
Zhou Y, Wang Q, Zhang X, Wang Y, Liu S, Wang M, Tian J, Zhu C, Huang R, Zhang Q, Zhang T, Zhou J, Dai W, Cao J. Exploring the impact of chemical composition on aerosol light extinction during winter in a heavily polluted urban area of China. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2019; 247:766-775. [PMID: 31288215 DOI: 10.1016/j.jenvman.2019.06.100] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/05/2018] [Revised: 05/04/2019] [Accepted: 06/23/2019] [Indexed: 06/09/2023]
Abstract
An intensive measurement campaign was conducted in Xi'an, China from December 2012-January 2013 to investigate the chemical composition, formation, and optical properties of PM1. The PM1 mass concentration (average = 138.8 ± 83.2 μg m-3) accounted for ∼50% of the PM2.5 mass. Organic aerosols (OA) and secondary inorganic aerosols (SIA) were the most abundant PM1 components, contributing 53.0% and 35.0% to the mass, respectively. Both primary emissions and aqueous-phase oxidation of secondary aerosols played roles in the pollution episodes. The average light scattering and absorption coefficients during the campaign were 805 ± 581 Mm-1 and 123 ± 96 Mm-1, respectively. Both the mass scattering and mass absorption efficiencies for PM1 were higher than that for PM2.5-1, indicating stronger ability of light extinction for the smaller particles at visible wavelengths compared with the larger ones. The contributions of aerosol species to light extinction coefficients under two visibility conditions were estimated based on multiple linear regression models, and the OA was found to be the largest contributor to light extinction in both cases. A larger contribution of SIA to light extinction for visibility <5 km demonstrated its greater impacts on visibility during heavy pollution conditions. These findings provide insights into the importance of submicron particles for pollution and visibility degradation in northwestern China.
Collapse
Affiliation(s)
- Yaqing Zhou
- State Key Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an, 710061, China; Key Laboratory of Aerosol Chemistry and Physics, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an, 710061, China; University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Qiyuan Wang
- State Key Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an, 710061, China; Key Laboratory of Aerosol Chemistry and Physics, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an, 710061, China; University of Chinese Academy of Sciences, Beijing, 100049, China; CAS Center for Excellence in Quaternary Science and Global Change, Xi'an, 710061, China.
| | - Xu Zhang
- Xi'an Environmental Monitor Station, Xi'an, 710100, China
| | - Yichen Wang
- College of Management, Shenzhen University, Shenzhen, 518060, China
| | - Suixin Liu
- State Key Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an, 710061, China; Key Laboratory of Aerosol Chemistry and Physics, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an, 710061, China; CAS Center for Excellence in Quaternary Science and Global Change, Xi'an, 710061, China
| | - Meng Wang
- State Key Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an, 710061, China; Key Laboratory of Aerosol Chemistry and Physics, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an, 710061, China; University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Jie Tian
- State Key Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an, 710061, China; Key Laboratory of Aerosol Chemistry and Physics, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an, 710061, China; CAS Center for Excellence in Quaternary Science and Global Change, Xi'an, 710061, China
| | - Chongshu Zhu
- State Key Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an, 710061, China; Key Laboratory of Aerosol Chemistry and Physics, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an, 710061, China; CAS Center for Excellence in Quaternary Science and Global Change, Xi'an, 710061, China
| | - Rujin Huang
- State Key Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an, 710061, China; Key Laboratory of Aerosol Chemistry and Physics, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an, 710061, China; CAS Center for Excellence in Quaternary Science and Global Change, Xi'an, 710061, China
| | - Qian Zhang
- School of Environmental & Municipal Engineering, Xi'an University of Architecture and Technology, Xi'an, 710055, China
| | - Ting Zhang
- State Key Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an, 710061, China; Key Laboratory of Aerosol Chemistry and Physics, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an, 710061, China; CAS Center for Excellence in Quaternary Science and Global Change, Xi'an, 710061, China
| | - Jiamao Zhou
- State Key Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an, 710061, China; Key Laboratory of Aerosol Chemistry and Physics, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an, 710061, China; CAS Center for Excellence in Quaternary Science and Global Change, Xi'an, 710061, China
| | - Wenting Dai
- State Key Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an, 710061, China; Key Laboratory of Aerosol Chemistry and Physics, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an, 710061, China; CAS Center for Excellence in Quaternary Science and Global Change, Xi'an, 710061, China
| | - Junji Cao
- State Key Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an, 710061, China; Key Laboratory of Aerosol Chemistry and Physics, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an, 710061, China; CAS Center for Excellence in Quaternary Science and Global Change, Xi'an, 710061, China.
| |
Collapse
|
9
|
Chatzidiakou L, Krause A, Popoola OAM, Di Antonio A, Kellaway M, Han Y, Squires FA, Wang T, Zhang H, Wang Q, Fan Y, Chen S, Hu M, Quint JK, Barratt B, Kelly FJ, Zhu T, Jones RL. Characterising low-cost sensors in highly portable platforms to quantify personal exposure in diverse environments. ATMOSPHERIC MEASUREMENT TECHNIQUES 2019; 12:4643-4657. [PMID: 31534556 PMCID: PMC6751078 DOI: 10.5194/amt-12-1-2019] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/04/2023]
Abstract
The inaccurate quantification of personal exposure to air pollution introduces error and bias in health estimations, severely limiting causal inference in epidemiological research worldwide. Rapid advancements in affordable, miniaturised air pollution sensor technologies offer the potential to address this limitation by capturing the high variability of personal exposure during daily life in large-scale studies with unprecedented spatial and temporal resolution. However, concerns remain regarding the suitability of novel sensing technologies for scientific and policy purposes. In this paper we characterise the performance of a portable personal air quality monitor (PAM) that integrates multiple miniaturised sensors for nitrogen oxides (NO x ), carbon monoxide (CO), ozone (O3) and particulate matter (PM) measurements along with temperature, relative humidity, acceleration, noise and GPS sensors. Overall, the air pollution sensors showed high reproducibility (meanR ¯ 2 = 0.93, min-max: 0.80-1.00) and excellent agreement with standard instrumentation (meanR ¯ 2 = 0.82, min-max: 0.54-0.99) in outdoor, indoor and commuting microenvironments across seasons and different geographical settings. An important outcome of this study is that the error of the PAM is significantly smaller than the error introduced when estimating personal exposure based on sparsely distributed outdoor fixed monitoring stations. Hence, novel sensing technologies such as the ones demonstrated here can revolutionise health studies by providing highly resolved reliable exposure metrics at a large scale to investigate the underlying mechanisms of the effects of air pollution on health.
Collapse
Affiliation(s)
- Lia Chatzidiakou
- Department of Chemistry, University of Cambridge, Cambridge, CB2 1EW, UK
| | - Anika Krause
- Department of Chemistry, University of Cambridge, Cambridge, CB2 1EW, UK
| | | | - Andrea Di Antonio
- Department of Chemistry, University of Cambridge, Cambridge, CB2 1EW, UK
| | | | - Yiqun Han
- MRC-PHE Centre for Environment & Health, Imperial College London and King’s College London, London, W2 1PG, UK
- College of Environmental Sciences and Engineering, Peking University, Beijing, 100871, China
- Department of Analytical, Environmental and Forensic Sciences, King’s College London, London, SE1 9NH, UK
| | | | - Teng Wang
- College of Environmental Sciences and Engineering, Peking University, Beijing, 100871, China
- The Beijing Innovation Center for Engineering Science and Advanced Technology, Peking University, Beijing, 100871, China
| | - Hanbin Zhang
- MRC-PHE Centre for Environment & Health, Imperial College London and King’s College London, London, W2 1PG, UK
- Department of Analytical, Environmental and Forensic Sciences, King’s College London, London, SE1 9NH, UK
- NIHR Health Protection Research Unit in Health Impact of Environmental Hazards, King’s College London, London, SE1 9NH, UK
| | - Qi Wang
- College of Environmental Sciences and Engineering, Peking University, Beijing, 100871, China
- The Beijing Innovation Center for Engineering Science and Advanced Technology, Peking University, Beijing, 100871, China
| | - Yunfei Fan
- College of Environmental Sciences and Engineering, Peking University, Beijing, 100871, China
- The Beijing Innovation Center for Engineering Science and Advanced Technology, Peking University, Beijing, 100871, China
| | - Shiyi Chen
- College of Environmental Sciences and Engineering, Peking University, Beijing, 100871, China
| | - Min Hu
- College of Environmental Sciences and Engineering, Peking University, Beijing, 100871, China
- The Beijing Innovation Center for Engineering Science and Advanced Technology, Peking University, Beijing, 100871, China
| | - Jennifer K. Quint
- National Heart and Lung Institute, Imperial College London, SW3 6LR, UK
| | - Benjamin Barratt
- MRC-PHE Centre for Environment & Health, Imperial College London and King’s College London, London, W2 1PG, UK
- Department of Analytical, Environmental and Forensic Sciences, King’s College London, London, SE1 9NH, UK
- NIHR Health Protection Research Unit in Health Impact of Environmental Hazards, King’s College London, London, SE1 9NH, UK
| | - Frank J. Kelly
- MRC-PHE Centre for Environment & Health, Imperial College London and King’s College London, London, W2 1PG, UK
- Department of Analytical, Environmental and Forensic Sciences, King’s College London, London, SE1 9NH, UK
- NIHR Health Protection Research Unit in Health Impact of Environmental Hazards, King’s College London, London, SE1 9NH, UK
| | - Tong Zhu
- College of Environmental Sciences and Engineering, Peking University, Beijing, 100871, China
- The Beijing Innovation Center for Engineering Science and Advanced Technology, Peking University, Beijing, 100871, China
| | - Roderic L. Jones
- Department of Chemistry, University of Cambridge, Cambridge, CB2 1EW, UK
| |
Collapse
|
10
|
Zheng Y, Che H, Xia X, Wang Y, Wang H, Wu Y, Tao J, Zhao H, An L, Li L, Gui K, Sun T, Li X, Sheng Z, Liu C, Yang X, Liang Y, Zhang L, Liu C, Kuang X, Luo S, You Y, Zhang X. Five-year observation of aerosol optical properties and its radiative effects to planetary boundary layer during air pollution episodes in North China: Intercomparison of a plain site and a mountainous site in Beijing. THE SCIENCE OF THE TOTAL ENVIRONMENT 2019; 674:140-158. [PMID: 31004891 DOI: 10.1016/j.scitotenv.2019.03.418] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/12/2019] [Revised: 03/22/2019] [Accepted: 03/26/2019] [Indexed: 05/16/2023]
Abstract
The aerosol microphysical, optical and radiative properties of the whole column and upper planetary boundary layer (PBL) were investigated during 2013 to 2018 based on long-term sun-photometer observations at a surface site (~106 m a.s.l.) and a mountainous site (~1225 m a.s.l.) in Beijing. Raman-Mie lidar data combined with radiosonde data were used to explore the aerosol radiative effects to PBL during dust and haze episodes. The results showed size distribution exhibited mostly bimodal pattern for the whole column and the upper PBL throughout the year, except in July for the upper PBL, when a trimodal distribution occurred due to the coagulation and hygroscopic growth of fine particles. The seasonal mean values of aerosol optical depth at 440 nm for the upper PBL were 0.31 ± 0.34, 0.30 ± 0.37, 0.17 ± 0.30 and 0.14 ± 0.09 in spring, summer, autumn and winter, respectively. The single-scattering albedo at 440 nm of the upper PBL varied oppositely to that of the whole column, with the monthly mean value between 0.91 and 0.96, indicating weakly to slightly strong absorptive ability at visible spectrum. The monthly mean direct aerosol radiative forcing at the Earth's surface and the top of the atmosphere varied from -40 ± 7 to -105 ± 25 and from -18 ± 4 to -49 ± 17 W m-2, respectively, and the maximum atmospheric heating was found in summer (~66 ± 12 W m-2). From a radiative point of view, during dust episode, the presence of mineral dust heated the lower atmosphere, thus promoting vertical turbulence, causing more air pollutants being transported to the upper air by the increasing PBLH. In contrast, during haze episode, a large quantity of absorbing aerosols (such as black carbon) had a cooling effect on the surface and a heating effect on the upper atmosphere, which favored the stabilization of PBL and occurrence of inversion layer, contributing to the depression of the PBLH.
Collapse
Affiliation(s)
- Yu Zheng
- Key Laboratory of Meteorological Disaster, Ministry of Education/Joint International Research Laboratory of Climate and Environment Change/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 &Technology, Nanjing 210044, China; State Key Laboratory of Severe Weather (LASW) and Institute of Atmospheric Composition, Chinese Academy of Meteorological Sciences, CMA, Beijing 100081, China
| | - Huizheng Che
- State Key Laboratory of Severe Weather (LASW) and Institute of Atmospheric Composition, Chinese Academy of Meteorological Sciences, CMA, Beijing 100081, China.
| | - Xiangao Xia
- Laboratory for Middle Atmosphere and Global Environment Observation (LAGEO), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China; School of Geoscience University of Chinese Academy of Science, Beijing 100049, China
| | - Yaqiang Wang
- State Key Laboratory of Severe Weather (LASW) and Institute of Atmospheric Composition, Chinese Academy of Meteorological Sciences, CMA, Beijing 100081, China
| | - Hong Wang
- State Key Laboratory of Severe Weather (LASW) and Institute of Atmospheric Composition, Chinese Academy of Meteorological Sciences, CMA, Beijing 100081, China
| | - Yunfei Wu
- CAS Key Laboratory of Regional Climate-Environment for Temperate East Asia (RCE-TEA), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
| | - Jun Tao
- South China Institute of Environmental Sciences, Ministry of Environmental Protection, Guangzhou 510655, China
| | - Hujia Zhao
- State Key Laboratory of Severe Weather (LASW) and Institute of Atmospheric Composition, Chinese Academy of Meteorological Sciences, CMA, Beijing 100081, China
| | - Linchang An
- National Meteorological Center, CMA, Beijing 100081, China
| | - Lei Li
- State Key Laboratory of Severe Weather (LASW) and Institute of Atmospheric Composition, Chinese Academy of Meteorological Sciences, CMA, Beijing 100081, China
| | - Ke Gui
- State Key Laboratory of Severe Weather (LASW) and Institute of Atmospheric Composition, Chinese Academy of Meteorological Sciences, CMA, Beijing 100081, China
| | - Tianze Sun
- State Key Laboratory of Severe Weather (LASW) and Institute of Atmospheric Composition, Chinese Academy of Meteorological Sciences, CMA, Beijing 100081, China
| | - Xiaopan Li
- State Key Laboratory of Severe Weather (LASW) and Institute of Atmospheric Composition, Chinese Academy of Meteorological Sciences, CMA, Beijing 100081, China
| | - Zhizhong Sheng
- State Key Laboratory of Severe Weather (LASW) and Institute of Atmospheric Composition, Chinese Academy of Meteorological Sciences, CMA, Beijing 100081, China
| | - Chao Liu
- State Key Laboratory of Severe Weather (LASW) and Institute of Atmospheric Composition, Chinese Academy of Meteorological Sciences, CMA, Beijing 100081, China; School of Surveying and Land Information Engineering, Henan Polytechnic University, Henan 454000, China
| | - Xianyi Yang
- State Key Laboratory of Severe Weather (LASW) and Institute of Atmospheric Composition, Chinese Academy of Meteorological Sciences, CMA, Beijing 100081, China
| | - Yuanxin Liang
- State Key Laboratory of Severe Weather (LASW) and Institute of Atmospheric Composition, Chinese Academy of Meteorological Sciences, CMA, Beijing 100081, China
| | - Lei Zhang
- State Key Laboratory of Severe Weather (LASW) and Institute of Atmospheric Composition, Chinese Academy of Meteorological Sciences, CMA, Beijing 100081, China
| | - Chong Liu
- School of Atmospheric Sciences, Nanjing University, Nanjing 210093, China
| | - Xiang Kuang
- Key Laboratory of Meteorological Disaster, Ministry of Education/Joint International Research Laboratory of Climate and Environment Change/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 &Technology, Nanjing 210044, China
| | - Shi Luo
- Key Laboratory of Meteorological Disaster, Ministry of Education/Joint International Research Laboratory of Climate and Environment Change/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 &Technology, Nanjing 210044, China
| | - Yingchang You
- Key Laboratory of Meteorological Disaster, Ministry of Education/Joint International Research Laboratory of Climate and Environment Change/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 &Technology, Nanjing 210044, China
| | - Xiaoye Zhang
- State Key Laboratory of Severe Weather (LASW) and Institute of Atmospheric Composition, Chinese Academy of Meteorological Sciences, CMA, Beijing 100081, China
| |
Collapse
|
11
|
Temporal Patterns in Fine Particulate Matter Time Series in Beijing: A Calendar View. Sci Rep 2016; 6:32221. [PMID: 27561629 PMCID: PMC4999874 DOI: 10.1038/srep32221] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2016] [Accepted: 08/04/2016] [Indexed: 11/24/2022] Open
Abstract
Extremely high fine particulate matter (PM2.5) concentration has become synonymous to Beijing, the capital of China, posing critical challenges to its sustainable development and leading to major public health concerns. In order to formulate mitigation measures and policies, knowledge on PM2.5 variation patterns should be obtained. While previous studies are limited either because of availability of data, or because of problematic a priori assumptions that PM2.5 concentration follows subjective seasonal, monthly, or weekly patterns, our study aims to reveal the data on a daily basis through visualization rather than imposing subjective periodic patterns upon the data. To achieve this, we conduct two time-series cluster analyses on full-year PM2.5 data in Beijing in 2014, and provide an innovative calendar visualization of PM2.5 measurements throughout the year. Insights from the analysis on temporal variation of PM2.5 concentration show that there are three diurnal patterns and no weekly patterns; seasonal patterns exist but they do not follow a strict temporal division. These findings advance current understanding on temporal patterns in PM2.5 data and offer a different perspective which can help with policy formulation on PM2.5 mitigation.
Collapse
|
12
|
Aerosol Optical Properties over Beijing during the World Athletics Championships and Victory Day Military Parade in August and September 2015. ATMOSPHERE 2016. [DOI: 10.3390/atmos7030047] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
|
13
|
Characteristics of PM1.0, PM2.5, and PM10, and Their Relation to Black Carbon in Wuhan, Central China. ATMOSPHERE 2015. [DOI: 10.3390/atmos6091377] [Citation(s) in RCA: 29] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
|
14
|
An Investigation of Aerosol Scattering and Absorption Properties in Wuhan, Central China. ATMOSPHERE 2015. [DOI: 10.3390/atmos6040503] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
|
15
|
Variations in PM10, PM2.5 and PM1.0 in an Urban Area of the Sichuan Basin and Their Relation to Meteorological Factors. ATMOSPHERE 2015. [DOI: 10.3390/atmos6010150] [Citation(s) in RCA: 85] [Impact Index Per Article: 9.4] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
|
16
|
A Comparison of the Mineral Dust Absorptive Properties between Two Asian Dust Events. ATMOSPHERE 2013. [DOI: 10.3390/atmos4010001] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
|
17
|
Sun H, Pan Z, Liu X. Numerical simulation of spatial-temporal distribution of dust aerosol and its direct radiative effects on East Asian climate. ACTA ACUST UNITED AC 2012. [DOI: 10.1029/2011jd017219] [Citation(s) in RCA: 53] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
|
18
|
Hansell RA, Tsay SC, Hsu NC, Ji Q, Bell SW, Holben BN, Welton EJ, Roush TL, Zhang W, Huang J, Li Z, Chen H. An assessment of the surface longwave direct radiative effect of airborne dust in Zhangye, China, during the Asian Monsoon Years field experiment (2008). ACTA ACUST UNITED AC 2012. [DOI: 10.1029/2011jd017370] [Citation(s) in RCA: 21] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
|
19
|
Koffi B, Schulz M, Bréon FM, Griesfeller J, Winker D, Balkanski Y, Bauer S, Berntsen T, Chin M, Collins WD, Dentener F, Diehl T, Easter R, Ghan S, Ginoux P, Gong S, Horowitz LW, Iversen T, Kirkevåg A, Koch D, Krol M, Myhre G, Stier P, Takemura T. Application of the CALIOP layer product to evaluate the vertical distribution of aerosols estimated by global models: AeroCom phase I results. ACTA ACUST UNITED AC 2012. [DOI: 10.1029/2011jd016858] [Citation(s) in RCA: 140] [Impact Index Per Article: 11.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
|
20
|
Li Z, Li C, Chen H, Tsay SC, Holben B, Huang J, Li B, Maring H, Qian Y, Shi G, Xia X, Yin Y, Zheng Y, Zhuang G. East Asian Studies of Tropospheric Aerosols and their Impact on Regional Climate (EAST-AIRC): An overview. ACTA ACUST UNITED AC 2011. [DOI: 10.1029/2010jd015257] [Citation(s) in RCA: 102] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
|