1
|
Chen P, Wang Q, Shao M, Liu R. Significantly underestimated traffic-related ammonia emissions in Chinese megacities: Evidence from satellite observations during COVID-19 lockdowns. CHEMOSPHERE 2024; 361:142497. [PMID: 38825248 DOI: 10.1016/j.chemosphere.2024.142497] [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: 02/21/2024] [Revised: 05/28/2024] [Accepted: 05/30/2024] [Indexed: 06/04/2024]
Abstract
Ammonia (NH3) plays an important role in the formation of atmospheric particulate matter, but the contribution of traffic-related emissions remains unclear, particularly in megacities with a large number of vehicles. Taking the opportunity of the stringent COVID-19 lockdowns implemented in Beijing and Shanghai in 2022, this study aims to estimate the traffic-related NH3 emissions in these two megacities based on satellite observations. Differences between urban and suburban areas during the lockdown and non-lockdown periods are compared. It was found that despite different dominating sources, the overall NH3 concentrations in urban and suburban areas were at a similar level, and the lockdown resulted in a more prominent decrease in urban areas, where traffic activities were most heavily affected. The traffic-related contribution to the total emission was estimated to be ∼30% in megacities, and ∼40% in urban areas, which are about 2-10 times higher than that in previous studies. The findings indicate that the traffic-related NH3 emissions have been significantly underestimated in previous studies and may play a more critical role in the formation of air pollution in megacities, especially in winter, when agricultural emissions are relatively low. This study highlights the importance of traffic-related NH3 emissions in Chinese megacities and the need to reassess the emissions and their impacts on air quality.
Collapse
Affiliation(s)
- Peilin Chen
- State Key Laboratory of Pollution Control and Resources Reuse, School of the Environment, Nanjing University, Nanjing, 210023, China
| | - Qin'geng Wang
- State Key Laboratory of Pollution Control and Resources Reuse, School of the Environment, Nanjing University, Nanjing, 210023, China; Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Nanjing University of Information Science & Technology, Nanjing, 210044, China.
| | - Min Shao
- School of the Environment, Nanjing Normal University, Nanjing, 210046, China
| | - Rui Liu
- State Key Laboratory of Pollution Control and Resources Reuse, School of the Environment, Nanjing University, Nanjing, 210023, China
| |
Collapse
|
2
|
Li D, Liu Y, Zhang W, Shi T, Zhao X, Zhao X, Zheng H, Li R, Wang T, Ren X. The association between the scarlet fever and meteorological factors, air pollutants and their interactions in children in northwest China. INTERNATIONAL JOURNAL OF BIOMETEOROLOGY 2024:10.1007/s00484-024-02722-5. [PMID: 38884798 DOI: 10.1007/s00484-024-02722-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/18/2023] [Revised: 05/08/2024] [Accepted: 06/05/2024] [Indexed: 06/18/2024]
Abstract
Scarlet fever (SF) is an acute respiratory transmitted disease that primarily affects children. The influence of meteorological factors and air pollutants on SF in children has been proved, but the relevant evidence in Northwest China is still lacking. Based on the weekly reported cases of SF in children in Lanzhou, northwest China, from 2014 to 2018, we used geographical detectors, distributed lag nonlinear models (DLNM), and bivariate response models to explore the influence of meteorological factors and air pollutants with SF. It was found that ozone (O3), carbon monoxide (CO), sulfur dioxide (SO2), temperature, pressure, water vapor pressure and wind speed were significantly correlated with SF based on geographical detectors. With the median as reference, the influence of high temperature, low pressure and high pressure on SF has a risk effect (relative risk (RR) > 1), and under extreme conditions, the dangerous effect was still significant. High O3 had the strongest effect at a 6-week delay, with an RR of 5.43 (95%CI: 1.74,16.96). The risk effect of high SO2 was strongest in the week of exposure, and the maximum risk effect was 1.37 (95%CI: 1.08,1.73). The interactions showed synergistic effects between high temperatures and O3, high pressure and high SO2, high nitrogen dioxide (NO2) and high particulate matter with diameter of less than 10 μm (PM10), respectively. In conclusion, high temperature, pressure, high O3 and SO2 were the most important factors affecting the occurrence of SF in children, which will provide theoretical support for follow-up research and disease prevention policy formulation.
Collapse
Affiliation(s)
- Donghua Li
- School of Public Health, Lanzhou University, Chengguan District, Lanzhou City, 730000, Gansu Province, China
| | - Yanchen Liu
- Fu Wai Hospital, Chinese Academy of Medical Sciences, Shenzhen Hospital, Nanshan District, Shenzhen city, 518000, Guangdong Province, China
| | - Wei Zhang
- Lanzhou Center for Disease Control and Prevention, Chengguan District, Lanzhou City, 733000, Gansu Province, China
| | - Tianshan Shi
- School of Public Health, Lanzhou University, Chengguan District, Lanzhou City, 730000, Gansu Province, China
| | - Xiangkai Zhao
- School of Public Health, Zhengzhou University, Zhongyuan District, Zhengzhou City, 450001, Henan Province, China
| | - Xin Zhao
- School of Public Health, Lanzhou University, Chengguan District, Lanzhou City, 730000, Gansu Province, China
| | - Hongmiao Zheng
- School of Public Health, Lanzhou University, Chengguan District, Lanzhou City, 730000, Gansu Province, China
| | - Rui Li
- School of Public Health, Lanzhou University, Chengguan District, Lanzhou City, 730000, Gansu Province, China
| | - Tingrong Wang
- School of Public Health, Lanzhou University, Chengguan District, Lanzhou City, 730000, Gansu Province, China
| | - Xiaowei Ren
- School of Public Health, Lanzhou University, Chengguan District, Lanzhou City, 730000, Gansu Province, China.
| |
Collapse
|
3
|
Ren Y, Guan X, Peng Y, Gong A, Xie H, Chen S, Zhang Q, Zhang X, Wang W, Wang Q. Characterization of VOC emissions and health risk assessment in the plastic manufacturing industry. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2024; 357:120730. [PMID: 38574705 DOI: 10.1016/j.jenvman.2024.120730] [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: 01/22/2024] [Revised: 02/25/2024] [Accepted: 03/19/2024] [Indexed: 04/06/2024]
Abstract
Volatile organic compounds (VOCs) significantly contribute to ozone pollution formation, and many VOCs are known to be harmful to human health. Plastic has become an indispensable material in various industries and daily use scenarios, yet the VOC emissions and associated health risks in the plastic manufacturing industry have received limited attention. In this study, we conducted sampling in three typical plastic manufacturing factories to analyze the emission characteristics of VOCs, ozone formation potential (OFP), and health risks for workers. Isopropanol was detected at relatively high concentrations in all three factories, with concentrations in organized emissions reaching 322.3 μg/m3, 344.8 μg/m3, and 22.6 μg/m3, respectively. Alkanes are the most emitted category of VOCs in plastic factories. However, alkenes and oxygenated volatile organic compounds (OVOCs) exhibit higher OFP. In organized emissions of different types of VOCs in the three factories, alkenes and OVOCs contributed 22.8%, 67%, and 37.8% to the OFP, respectively, highlighting the necessity of controlling them. The hazard index (HI) for all three factories was less than 1, indicating a low non-carcinogenic toxic risk; however, there is still a possibility of non-cancerous health risks in two of the factories, and a potential lifetime cancer risk in all of the three factories. For workers with job tenures exceeding 5 years, there may be potential health risks, hence wearing masks with protective capabilities is necessary. This study provides evidence for reducing VOC emissions and improving management measures to ensure the health protection of workers in the plastic manufacturing industry.
Collapse
Affiliation(s)
- Yuchao Ren
- Big Data Research Center for Ecology and Environment, Environment Research Institute, Shandong University, Qingdao 266237, PR China
| | - Xu Guan
- State Environmental Protection Key Laboratory of Land and Sea Ecological Governance and Systematic Regulation, Shandong Academy for Environmental Planning, Jinan 250101, PR China
| | - Yanbo Peng
- Big Data Research Center for Ecology and Environment, Environment Research Institute, Shandong University, Qingdao 266237, PR China; State Environmental Protection Key Laboratory of Land and Sea Ecological Governance and Systematic Regulation, Shandong Academy for Environmental Planning, Jinan 250101, PR China.
| | - Anbao Gong
- State Environmental Protection Key Laboratory of Land and Sea Ecological Governance and Systematic Regulation, Shandong Academy for Environmental Planning, Jinan 250101, PR China
| | - Huan Xie
- State Environmental Protection Key Laboratory of Land and Sea Ecological Governance and Systematic Regulation, Shandong Academy for Environmental Planning, Jinan 250101, PR China
| | - Shurui Chen
- State Environmental Protection Key Laboratory of Land and Sea Ecological Governance and Systematic Regulation, Shandong Academy for Environmental Planning, Jinan 250101, PR China
| | - Qingzhu Zhang
- Big Data Research Center for Ecology and Environment, Environment Research Institute, Shandong University, Qingdao 266237, PR China.
| | - Xin Zhang
- Big Data Research Center for Ecology and Environment, Environment Research Institute, Shandong University, Qingdao 266237, PR China
| | - Wenxing Wang
- Big Data Research Center for Ecology and Environment, Environment Research Institute, Shandong University, Qingdao 266237, PR China
| | - Qiao Wang
- Big Data Research Center for Ecology and Environment, Environment Research Institute, Shandong University, Qingdao 266237, PR China
| |
Collapse
|
4
|
Wang H, Li J, Wu T, Ma T, Wei L, Zhang H, Yang X, Munger JW, Duan FK, Zhang Y, Feng Y, Zhang Q, Sun Y, Fu P, McElroy MB, Song S. Model Simulations and Predictions of Hydroxymethanesulfonate (HMS) in the Beijing-Tianjin-Hebei Region, China: Roles of Aqueous Aerosols and Atmospheric Acidity. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2024; 58:1589-1600. [PMID: 38154035 DOI: 10.1021/acs.est.3c07306] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/30/2023]
Abstract
Hydroxymethanesulfonate (HMS) has been found to be an abundant organosulfur aerosol compound in the Beijing-Tianjin-Hebei (BTH) region with a measured maximum daily mean concentration of up to 10 μg per cubic meter in winter. However, the production medium of HMS in aerosols is controversial, and it is unknown whether chemical transport models are able to capture the variations of HMS during individual haze events. In this work, we modify the parametrization of HMS chemistry in the nested-grid GEOS-Chem chemical transport model, whose simulations provide a good account of the field measurements during winter haze episodes. We find the contribution of the aqueous aerosol pathway to total HMS is about 36% in winter in Beijing, due primarily to the enhancement effect of the ionic strength on the rate constants of the reaction between dissolved formaldehyde and sulfite. Our simulations suggest that the HMS-to-inorganic sulfate ratio will increase from the baseline of 7% to 13% in the near future, given the ambitious clean air and climate mitigation policies for the BTH region. The more rapid reductions in emissions of SO2 and NOx compared to NH3 alter the atmospheric acidity, which is a critical factor leading to the rising importance of HMS in particulate sulfur species.
Collapse
Affiliation(s)
- Haoqi Wang
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China
- CMA-NKU Cooperative Laboratory for Atmospheric Environment-Health Research, Tianjin 300350, China
| | - Jiacheng Li
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China
- CMA-NKU Cooperative Laboratory for Atmospheric Environment-Health Research, Tianjin 300350, China
| | - Ting Wu
- State Key Laboratory on Odor Pollution Control, Tianjin Academy of Eco-Environmental Sciences, Tianjin 300191, China
| | - Tao Ma
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing 100084, China
| | - Lianfang Wei
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
| | - Hailiang Zhang
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
| | - Xi Yang
- School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts 02138, United States
| | - J William Munger
- School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts 02138, United States
| | - Feng-Kui Duan
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing 100084, China
| | - Yufen Zhang
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China
- CMA-NKU Cooperative Laboratory for Atmospheric Environment-Health Research, Tianjin 300350, China
| | - Yinchang Feng
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China
- CMA-NKU Cooperative Laboratory for Atmospheric Environment-Health Research, Tianjin 300350, China
| | - Qiang Zhang
- Ministry of Education Key Laboratory for Earth System Modelling, Department of Earth System Science, Tsinghua University, Beijing 100084, China
| | - Yele Sun
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
| | - Pingqing Fu
- Institute of Surface-Earth System Science, School of Earth System Science, Tianjin University, Tianjin 300072, China
| | - Michael B McElroy
- School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts 02138, United States
| | - Shaojie Song
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China
- CMA-NKU Cooperative Laboratory for Atmospheric Environment-Health Research, Tianjin 300350, China
- School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts 02138, United States
| |
Collapse
|
5
|
Kocak E, Cobanoglu C, Celik B. Urbanization, industrialization and SO 2 emissions in China: does the innovation ability of cities matter for air quality? ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2023; 30:119879-119892. [PMID: 37930576 DOI: 10.1007/s11356-023-30705-3] [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: 05/08/2023] [Accepted: 10/23/2023] [Indexed: 11/07/2023]
Abstract
This paper aims to detail the relationships between urbanization, industrialization, the innovation ability of cities and local air quality in 284 cities in China using annual data. For the empirical outputs, the panel quantile regression analysis, which considers the heterogeneous nature of the data set, is employed. Initial findings indicate that (i) urbanization and industrialization negatively affect local air quality. (ii) Innovation capability of cities has a direct and improving impact on local air quality. Then, the paper estimates the moderating role of cities' ability to innovate in the polluting effect of urbanization and industrialization on local air quality. Remarkably, empirical evidence indicates that (iii) the innovation ability of cities also moderates the polluting impact of urbanization and industrialization on local air pollution. Based on the findings, the paper confirms the importance of both direct and moderator effects of the innovative environment in cities in tackling air pollution.
Collapse
Affiliation(s)
- Emrah Kocak
- Department of Economics, Erciyes University, Melikgazi-, 38039, Kayseri, Turkey.
- Muma College of Business, University of South Florida, Tampa, FL, 33620, USA.
| | - Cihan Cobanoglu
- Muma College of Business, University of South Florida, Tampa, FL, 33620, USA
| | - Bekir Celik
- Department of Economics, Nuh Naci Yazgan University, Kocasinan-, 38170, Kayseri, Turkey
| |
Collapse
|
6
|
Zhao Y, Li F, Yang Y, Zhang Y, Dai R, Li J, Wang M, Li Z. Driving forces and relationship between air pollution and economic growth based on EKC hypothesis and STIRPAT model: evidence from Henan Province, China. AIR QUALITY, ATMOSPHERE, & HEALTH 2023; 16:1-16. [PMID: 37359389 PMCID: PMC10227404 DOI: 10.1007/s11869-023-01379-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/26/2022] [Accepted: 05/15/2023] [Indexed: 06/28/2023]
Abstract
The aim of this research is to analyze the main influencing factors and relationship between atmospheric environment and economic society. Using the panel data of 18 cities in Henan Province from 2006 to 2020, this paper employed some advanced econometric estimation included entropy method, extended environmental Kuznets curve (EKC) and STIRPAT model to conduct empirical estimations. The results show that most regions in Henan Province have verified the existence of the EKC hypothesis; and the peak of air pollution level in all cities of Henan Province generally occurred in around 2014. Multiple linear Ridge regression indicated that the positive driving forces of air pollution in most cities in Henan Province are industrial structure and population size; the negative driving forces are urbanization level, technical level and greening degree. Finally, we used the grey GM (1, 1) model to predict the atmospheric environment of Henan Province in 2025, 2030, 2035 and 2040. What should pay close attention to is that air pollution levels in northeastern and central Henan Province will continue to remain high.
Collapse
Affiliation(s)
- Yanqi Zhao
- Institute of Resources & Environment, Henan Polytechnic University, Jiaozuo, 454003 China
- Collaborative Innovation Center of Coal Bed Methane and Shale Gas for Central Plains Economic Region, Jiaozuo, 454100 China
- Collaborative Innovation Center of Coal Work Safety and Clean High Efficiency Utilization, Jiaozuo, 454100 China
| | - Fan Li
- Institute of Resources & Environment, Henan Polytechnic University, Jiaozuo, 454003 China
| | - Ying Yang
- Institute of Resources & Environment, Henan Polytechnic University, Jiaozuo, 454003 China
| | - Yue Zhang
- Institute of Resources & Environment, Henan Polytechnic University, Jiaozuo, 454003 China
| | - Rongkun Dai
- Institute of Resources & Environment, Henan Polytechnic University, Jiaozuo, 454003 China
| | - Jianlin Li
- Institute of Resources & Environment, Henan Polytechnic University, Jiaozuo, 454003 China
- Collaborative Innovation Center of Coal Bed Methane and Shale Gas for Central Plains Economic Region, Jiaozuo, 454100 China
- Collaborative Innovation Center of Coal Work Safety and Clean High Efficiency Utilization, Jiaozuo, 454100 China
| | - Mingshi Wang
- Institute of Resources & Environment, Henan Polytechnic University, Jiaozuo, 454003 China
- Collaborative Innovation Center of Coal Bed Methane and Shale Gas for Central Plains Economic Region, Jiaozuo, 454100 China
- Collaborative Innovation Center of Coal Work Safety and Clean High Efficiency Utilization, Jiaozuo, 454100 China
| | - Zhenhua Li
- Institute of Resources & Environment, Henan Polytechnic University, Jiaozuo, 454003 China
- Collaborative Innovation Center of Coal Bed Methane and Shale Gas for Central Plains Economic Region, Jiaozuo, 454100 China
- Collaborative Innovation Center of Coal Work Safety and Clean High Efficiency Utilization, Jiaozuo, 454100 China
| |
Collapse
|
7
|
Wang T, Qu H, Ravindra AV, Ma S, Hu J, Zhang H, Le T, Zhang L. Treatment of complex sulfur-containing solutions in ammonia desulfurization ammonium sulfate production by ultrasonic-assisted ozone technology. ULTRASONICS SONOCHEMISTRY 2023; 95:106386. [PMID: 37003211 PMCID: PMC10457592 DOI: 10.1016/j.ultsonch.2023.106386] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/01/2023] [Revised: 03/10/2023] [Accepted: 03/23/2023] [Indexed: 06/19/2023]
Abstract
In this work, the cause of abnormal color in ammonium sulfate products formed by flue gas desulfurization is revealed by investigating the conversion relationship between different sulfur-containing ions and their behavior in a sulfuric acid medium. Both thiosulfate (S2O32-) and sulfite (SO32- & HSO3-) impurities affect the quality of ammonium sulfate. The S2O32- is the main reason for the yellowing of the product due to the formation of sulfur impurities in concentrated sulfuric acid. To address the yellowing of ammonium sulfate products, a unified technology (US/O3), using ozone (O3) and ultrasonic waves (US) simultaneously, is exploited to remove both thiosulfate and sulfite impurities from the mother liquor. The effect of different reaction parameters on the degree of removal of thiosulfate and sulfite is investigated. The synergistic effect of ultrasound and ozone on ion oxidation is further explored and demonstrated by the comparative experiments with O3 and US/O3. Under the optimized conditions, the thiosulfate and sulfite concentration in the solution is 2.07 and 5.93 g/L, respectively, and the degree of removal is 91.39 and 90.83%, respectively. The product obtained after evaporation and crystallization is pure white and meets the national standard requirements for ammonium sulfate products. Under the same conditions, the US/O3 process has apparent advantages, such as saving reaction time compared with the O3 process alone. Introducing an ultrasonically intensified field improves the generation of oxidation radicals ·OH, 1O2, and ·O2- in the solution. Furthermore, the effectiveness of different oxidation components in the decolorization process is studied by adding other radical shielding agents using the US/O3 process supplemented with EPR analysis. The order of the different oxidation components is O3(86.04%) > 1O2(6.53%) > •OH(4.45%) > •O2-(2.97%) for the oxidation of thiosulfate, and it is O3(86.28%) > •OH(7.49%) > 1O2(4.99%) > •O2-(1.25%) for the oxidation of sulfite.
Collapse
Affiliation(s)
- Tian Wang
- State Key Laboratory of Complex Non-ferrous Metal Resources Clean Utilization, Kunming University of Science and Technology, Kunming 650093, Yunnan, China; Faculty of Metallurgical and Energy Engineering, Kunming University of Science and Technology, Kunming 650093, Yunnan, China
| | - Hongtao Qu
- Yunnan Chihong Zinc and Germanium Co., Ltd., Qujing 655011, Yunnan, China
| | - A V Ravindra
- Department of Physics and Nanotechnology, SRM Institute of Science and Technology, Kattankulathur, Tamilnadu 603203, India
| | - Shaobin Ma
- Yunnan Chihong Zinc and Germanium Co., Ltd., Qujing 655011, Yunnan, China
| | - Jue Hu
- State Key Laboratory of Complex Non-ferrous Metal Resources Clean Utilization, Kunming University of Science and Technology, Kunming 650093, Yunnan, China; Faculty of Metallurgical and Energy Engineering, Kunming University of Science and Technology, Kunming 650093, Yunnan, China
| | - Hong Zhang
- Yunnan Chihong Zinc and Germanium Co., Ltd., Qujing 655011, Yunnan, China
| | - Thiquynhxuan Le
- State Key Laboratory of Complex Non-ferrous Metal Resources Clean Utilization, Kunming University of Science and Technology, Kunming 650093, Yunnan, China; Faculty of Metallurgical and Energy Engineering, Kunming University of Science and Technology, Kunming 650093, Yunnan, China.
| | - Libo Zhang
- State Key Laboratory of Complex Non-ferrous Metal Resources Clean Utilization, Kunming University of Science and Technology, Kunming 650093, Yunnan, China; Faculty of Metallurgical and Energy Engineering, Kunming University of Science and Technology, Kunming 650093, Yunnan, China.
| |
Collapse
|
8
|
She Y, Chen Q, Ye S, Wang P, Wu B, Zhang S. Spatial-temporal heterogeneity and driving factors of PM 2.5 in China: A natural and socioeconomic perspective. Front Public Health 2022; 10:1051116. [PMID: 36466497 PMCID: PMC9713317 DOI: 10.3389/fpubh.2022.1051116] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2022] [Accepted: 11/04/2022] [Indexed: 11/18/2022] Open
Abstract
Background Fine particulate matter (PM2.5), one of the major atmospheric pollutants, has a significant impact on human health. However, the determinant power of natural and socioeconomic factors on the spatial-temporal variation of PM2.5 pollution is controversial in China. Methods In this study, we explored spatial-temporal characteristics and driving factors of PM2.5 through 252 prefecture-level cities in China from 2015 to 2019, based on the spatial autocorrelation and geographically and temporally weighted regression model (GTWR). Results PM2.5 concentrations showed a significant downward trend, with a decline rate of 3.58 μg m-3 a-1, and a 26.49% decrease in 2019 compared to 2015, Eastern and Central China were the two regions with the highest PM2.5 concentrations. The driving force of socioeconomic factors on PM2.5 concentrations was slightly higher than that of natural factors. Population density had a positive significant driving effect on PM2.5 concentrations, and precipitation was the negative main driving factor. The two main driving factors (population density and precipitation) showed that the driving capability in northern region was stronger than that in southern China. North China and Central China were the regions of largest decline, and the reason for the PM2.5 decline might be the transition from a high environmental pollution-based industrial economy to a resource-clean high-tech economy since the implementation the Air Pollution Prevention and Control Action Plan in 2013. Conclusion We need to fully consider the coordinated development of population size and local environmental carrying capacity in terms of control of PM2.5 concentrations in the future. This research is helpful for policy-makers to understand the distribution characteristics of PM2.5 emission and put forward effective policy to alleviate haze pollution.
Collapse
Affiliation(s)
- Yuanyang She
- School of Geography and Environment, Jiangxi Normal University, Nanchang, China,Key Laboratory of Poyang Lake Wetland and Watershed Research, Ministry of Education, Jiangxi Normal University, Nanchang, China
| | - Qingyan Chen
- Science and Technology College, Jiangxi Normal University, Jiujiang, China
| | - Shen Ye
- School of Geography and Environment, Jiangxi Normal University, Nanchang, China,Key Laboratory of Poyang Lake Wetland and Watershed Research, Ministry of Education, Jiangxi Normal University, Nanchang, China
| | - Peng Wang
- School of Geography and Environment, Jiangxi Normal University, Nanchang, China,Key Laboratory of Poyang Lake Wetland and Watershed Research, Ministry of Education, Jiangxi Normal University, Nanchang, China,*Correspondence: Peng Wang
| | - Bobo Wu
- School of Geography and Environment, Jiangxi Normal University, Nanchang, China,Key Laboratory of Poyang Lake Wetland and Watershed Research, Ministry of Education, Jiangxi Normal University, Nanchang, China
| | - Shaoyu Zhang
- School of Geography and Environment, Jiangxi Normal University, Nanchang, China,Key Laboratory of Poyang Lake Wetland and Watershed Research, Ministry of Education, Jiangxi Normal University, Nanchang, China
| |
Collapse
|
9
|
Wang G, Zhu Z, Liu Z, Liu X, Kong F, Nie L, Gao W, Zhao N, Lang J. Ozone pollution in the plate and logistics capital of China: Insight into the formation, source apportionment, and regional transport. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2022; 313:120144. [PMID: 36108885 DOI: 10.1016/j.envpol.2022.120144] [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: 06/22/2022] [Revised: 08/27/2022] [Accepted: 08/30/2022] [Indexed: 06/15/2023]
Abstract
As the logistics and plate capital of China, the sources and regional transport of O3 in Linyi are different from those in other cities because of the significant differences in industrial structure and geographical location. Twenty-five ozone pollution episodes (OPEs, 52 days) were identified in 2021, with a daily maximum 8-h moving average O3 concentration (O3-MDA8) of 184.5 ± 22.5 μg/m3. Oxygenated volatile organic compounds (OVOCs) and aromatics were the dominant contributors to ozone formation potential (OFP), with contributions of approximately 23.5-52.7% and 20.0-40.8%, respectively, followed by alkenes, alkanes, and alkynes. Formaldehyde, an OVOC with high concentrations emitted from the plate industry and vehicles, contributed the most to OFP (22.7 ± 5.5%), although formaldehyde concentrations only accounted for 9.4 ± 2.7% of the total non-methane hydrocarbon (NMHC) concentrations. The source apportionment results indicated that the plate industry was the dominant O3 contributor (27.0%), followed by other sources (21.6%), vehicle-related sources (18.0%), solvent use (16.9%), liquefied petroleum gas (LPG)/natural gas (NG) (8.8%), and combustion sources (7.7%). Therefore, there is an urgent need to control the plating industry in Linyi to mitigate O3 pollution. The backward trajectory, potential source contribution function (PSCF), and concentration weighted trajectory (CWT) models were used to identify the air mass pathways and potential source areas of air pollutants during the OPEs. O3 pollution was predominantly affected by air masses that originated from eastern and local regions, while trajectories from the south contained the highest O3 concentrations (207.0 μg/m3). The potential source area was from east and south Linyi during the OPEs. Therefore, it is critical to implement regional joint prevention and control measures to lower O3 concentrations.
Collapse
Affiliation(s)
- Gang Wang
- Department of Environmental and Safety Engineering, College of Chemistry and Chemical Engineering, China University of Petroleum (East China), Qingdao, 266580, China.
| | - Zhongyi Zhu
- Department of Environmental and Safety Engineering, College of Chemistry and Chemical Engineering, China University of Petroleum (East China), Qingdao, 266580, China
| | - Zhonglin Liu
- Shandong Provincial Eco-Environment Monitoring Center, Linyi, 276000, China
| | - Xiaoyu Liu
- Beijing Municipal Research Institute of Eco-Environmental Protection, Beijing, 100037, China
| | - Fanhua Kong
- Shandong Provincial Eco-Environment Monitoring Center, Linyi, 276000, China
| | - Liman Nie
- Shandong Provincial Eco-Environment Monitoring Center, Linyi, 276000, China
| | - Wenkang Gao
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry (LAPC), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China
| | - Na Zhao
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention, Department of Environmental Science and Engineering, Fudan University, Shanghai, 200433, China
| | - Jianlei Lang
- Key Laboratory of Beijing on Regional Air Pollution Control, Beijing University of Technology, Beijing, 100124, China
| |
Collapse
|
10
|
Wang L, Zhang J, Wei J, Zong J, Lu C, Du Y, Wang Q. Association of ambient air pollution exposure and its variability with subjective sleep quality in China: A multilevel modeling analysis. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2022; 312:120020. [PMID: 36028077 DOI: 10.1016/j.envpol.2022.120020] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/03/2022] [Revised: 08/14/2022] [Accepted: 08/17/2022] [Indexed: 06/15/2023]
Abstract
Growing epidemiological evidence has shown that exposure to ambient air pollution contributes to poor sleep quality. However, whether variability in air pollution exposure affects sleep quality remains unclear. Based on a large sample in China, this study linked individual air pollutant exposure levels and temporal variability with subjective sleep quality. Town-level data on daily air pollution concentration for 30 days prior to the survey date were collected, and the monthly mean value, standard deviations, number of heavily polluted days, and trajectory for six common pollutants were calculated to measure air pollution exposure and its variations. Sleep quality was subjectively assessed using the Pittsburgh Sleep Quality Index (PSQI), and a PSQI score above 5 indicated overall poor sleep quality. Multilevel and negative control models were used. Both air pollution exposure and variability contributed to poor sleep quality. A one-point increase in the one-month mean concentration of particulate matter with aerodynamic diameters of ≤2.5 μm (PM2.5) and ≤10 μm (PM10) led to 0.4% (95% confidence interval (CI): 1.002-1.006) and 0.3% (95% CI: 1.001-1.004) increases in the likelihoods of overall poor sleep quality (PSQI score >5), respectively; the odds ratios of a heavy pollution day with PM2.5 and PM10 were 2.2% (95% CI: 1.012-1.032) and 2.2% (95% CI: 1.012-1.032), respectively. Although the mean concentrations of nitrogen dioxide, sulfur dioxide, and carbon monoxide met the national standard, they contributed to the likelihood of overall poor sleep quality (PSQI score >5). A trajectory of air pollution exposure with maximum variability was associated with a higher likelihood of overall poor sleep quality (PSQI score >5). Subjective measures of sleep latency, duration, and efficiency (derived from PSQI) were affected in most cases. Thus, sleep health improvements should account for air pollution exposure and its variations in China under relatively high air pollution levels.
Collapse
Affiliation(s)
- Lingli Wang
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, China; National Institute for Medical Dataology, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Jingxuan Zhang
- Shandong Provincial Mental Health Center, Jinan City, Shandong, China
| | - Jing Wei
- Department of Atmospheric and Oceanic Science, Earth System Science Interdisciplinary Center, University of Maryland, USA
| | - Jingru Zong
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, China; National Institute for Medical Dataology, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Chunyu Lu
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, China; National Institute for Medical Dataology, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Yajie Du
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, China; National Institute for Medical Dataology, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Qing Wang
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, China; National Institute for Medical Dataology, Cheeloo College of Medicine, Shandong University, Jinan, China.
| |
Collapse
|
11
|
Liu S, Yang X, Duan F, Zhao W. Changes in Air Quality and Drivers for the Heavy PM 2.5 Pollution on the North China Plain Pre- to Post-COVID-19. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:ijerph191912904. [PMID: 36232204 PMCID: PMC9566441 DOI: 10.3390/ijerph191912904] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/31/2022] [Revised: 09/27/2022] [Accepted: 09/29/2022] [Indexed: 06/03/2023]
Abstract
Under the clean air action plans and the lockdown to constrain the coronavirus disease 2019 (COVID-19), the air quality improved significantly. However, fine particulate matter (PM2.5) pollution still occurred on the North China Plain (NCP). This study analyzed the variations of PM2.5, nitrogen dioxide (NO2), sulfur dioxide (SO2), carbon monoxide (CO), and ozone (O3) during 2017-2021 on the northern (Beijing) and southern (Henan) edges of the NCP. Furthermore, the drivers for the PM2.5 pollution episodes pre- to post-COVID-19 in Beijing and Henan were explored by combining air pollutant and meteorological datasets and the weighted potential source contribution function. Results showed air quality generally improved during 2017-2021, except for a slight rebound (3.6%) in NO2 concentration in 2021 in Beijing. Notably, the O3 concentration began to decrease significantly in 2020. The COVID-19 lockdown resulted in a sharp drop in the concentrations of PM2.5, NO2, SO2, and CO in February of 2020, but PM2.5 and CO in Beijing exhibited a delayed decrease in March. For Beijing, the PM2.5 pollution was driven by the initial regional transport and later secondary formation under adverse meteorology. For Henan, the PM2.5 pollution was driven by the primary emissions under the persistent high humidity and stable atmospheric conditions, superimposing small-scale regional transport. Low wind speed, shallow boundary layer, and high humidity are major drivers of heavy PM2.5 pollution. These results provide an important reference for setting mitigation measures not only for the NCP but for the entire world.
Collapse
|
12
|
Javed Z, Bilal M, Qiu Z, Li G, Sandhu O, Mehmood K, Wang Y, Ali MA, Liu C, Wang Y, Xue R, Du D, Zheng X. Spatiotemporal characterization of aerosols and trace gases over the Yangtze River Delta region, China: impact of trans-boundary pollution and meteorology. ENVIRONMENTAL SCIENCES EUROPE 2022; 34:86. [PMID: 36097441 PMCID: PMC9453706 DOI: 10.1186/s12302-022-00668-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/04/2022] [Accepted: 08/21/2022] [Indexed: 06/15/2023]
Abstract
BACKGROUND The spatiotemporal variation of observed trace gases (NO2, SO2, O3) and particulate matter (PM2.5, PM10) were investigated over cities of Yangtze River Delta (YRD) region including Nanjing, Hefei, Shanghai and Hangzhou. Furthermore, the characteristics of different pollution episodes, i.e., haze events (visibility < 7 km, relative humidity < 80%, and PM2.5 > 40 µg/m3) and complex pollution episodes (PM2.5 > 35 µg/m3 and O3 > 160 µg/m3) were studied over the cities of the YRD region. The impact of China clean air action plan on concentration of aerosols and trace gases is examined. The impacts of trans-boundary pollution and different meteorological conditions were also examined. RESULTS The highest annual mean concentrations of PM2.5, PM10, NO2 and O3 were found for 2019 over all the cities. The annual mean concentrations of PM2.5, PM10, and NO2 showed continuous declines from 2019 to 2021 due to emission control measures and implementation of the Clean Air Action plan over all the cities of the YRD region. The annual mean O3 levels showed a decline in 2020 over all the cities of YRD region, which is unprecedented since the beginning of the China's National environmental monitoring program since 2013. However, a slight increase in annual O3 was observed in 2021. The highest overall means of PM2.5, PM10, SO2, and NO2 were observed over Hefei, whereas the highest O3 levels were found in Nanjing. Despite the strict control measures, PM2.5 and PM10 concentrations exceeded the Grade-1 National Ambient Air Quality Standards (NAAQS) and WHO (World Health Organization) guidelines over all the cities of the YRD region. The number of haze days was higher in Hefei and Nanjing, whereas the complex pollution episodes or concurrent occurrence of O3 and PM2.5 pollution days were higher in Hangzhou and Shanghai.The in situ data for SO2 and NO2 showed strong correlation with Tropospheric Monitoring Instrument (TROPOMI) satellite data. CONCLUSIONS Despite the observed reductions in primary pollutants concentrations, the secondary pollutants formation is still a concern for major metropolises. The increase in temperature and lower relative humidity favors the accumulation of O3, while low temperature, low wind speeds and lower relative humidity favor the accumulation of primary pollutants. This study depicts different air pollution problems for different cities inside a region. Therefore, there is a dire need to continuous monitoring and analysis of air quality parameters and design city-specific policies and action plans to effectively deal with the metropolitan pollution. SUPPLEMENTARY INFORMATION The online version contains supplementary material available at 10.1186/s12302-022-00668-2.
Collapse
Affiliation(s)
- Zeeshan Javed
- Institute of Environment and Ecology, School of the Environment and Safety Engineering, Jiangsu University, Zhenjiang, 212013 China
| | - Muhammad Bilal
- School of Marine Sciences, Nanjing University of Information Science and Technology, Nanjing, 210044 China
| | - Zhongfeng Qiu
- School of Marine Sciences, Nanjing University of Information Science and Technology, Nanjing, 210044 China
| | - Guanlin Li
- Institute of Environment and Ecology, School of the Environment and Safety Engineering, Jiangsu University, Zhenjiang, 212013 China
| | - Osama Sandhu
- National Agromet Center, Pakistan Meteorological Department, Islamabad, 44000 Pakistan
| | - Khalid Mehmood
- 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 [CIC-FEMD]/CMA Key Laboratory for Aerosol-Cloud-Precipitation, Nanjing University of Information Science and Technology, Nanjing, 210044 China
| | - Yu Wang
- School of Marine Sciences, Nanjing University of Information Science and Technology, Nanjing, 210044 China
| | - Md. Arfan Ali
- School of Marine Sciences, Nanjing University of Information Science and Technology, Nanjing, 210044 China
| | - Cheng Liu
- Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of China, Hefei, 230026 China
- Key Laboratory of Environmental Optics & Technology, Anhui Institute of Optics and Fine Mechanics, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, 230031 China
- Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen, 361021 China
- Key Laboratory of Precision Scientific Instrumentation of Anhui Higher Education Institutes, University of Science and Technology of China, Hefei, 230026 China
| | - Yuhang Wang
- School of Earth and Atmospheric Sciences, Georgia Institute of Technology, Atlanta, GA 30332 USA
| | - Ruibin Xue
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention [LAP3], Department of Environmental Science and Engineering, Fudan University, Shanghai, 200433 China
| | - Daolin Du
- Institute of Environment and Ecology, School of the Environment and Safety Engineering, Jiangsu University, Zhenjiang, 212013 China
| | - Xiaojun Zheng
- Institute of Environment and Ecology, School of the Environment and Safety Engineering, Jiangsu University, Zhenjiang, 212013 China
| |
Collapse
|
13
|
Zheng M, Wang Y, Yuan L, Chen N, Kong S. Ambient observations indicating an increasing effectiveness of ammonia control in wintertime PM 2.5 reduction in Central China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 824:153708. [PMID: 35182649 DOI: 10.1016/j.scitotenv.2022.153708] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/06/2022] [Revised: 02/02/2022] [Accepted: 02/02/2022] [Indexed: 06/14/2023]
Abstract
Ammonia emission reduction is increasingly being considered one of the control measures to mitigate wintertime fine particulate matter (PM2.5) pollution. Three wintertime observations from 2012 to 2018 in Wuhan, China, were analyzed to examine the effectiveness of ammonia control in wintertime PM2.5 reduction based on the critical total ammonia concentration (CTAC, i.e., the inflection point of effective ammonia control for PM2.5 mass reduction based on the asymmetric response of PM2.5 to ammonia control). The CTAC gradually approached 0% (immediate effectiveness), with values of -26% in 2012, -23% in 2015, and -9% in 2018. At the observed ambient conditions, there were significant positive correlations of the CTAC with sulfate and total nitrate changes, in contrast to the negative correlation of the CTAC with total ammonia change. An approximately 10% total ammonia reduction could offset the decline in CTAC attributed to a 30-40% sulfate or 20-30% total nitrate reduction in Wuhan. This study indicates that the combined control of SO2 + NOx (NO+NO2) remains the preferred way to reduce inorganic particles in Central China at present, despite a tendency of the ambient chemical state moving towards effective ammonia control. However, as the CTAC approaches 0%, the effectiveness of ammonia and NOx reduction measures targeting wintertime PM2.5 can greatly exceed that observed during the 2012-2018 period in Central China.
Collapse
Affiliation(s)
- Mingming Zheng
- School of Chemical and Environmental Engineering, Wuhan Polytechnic University, Wuhan 430023, China; School of Environmental Studies, China University of Geosciences (Wuhan), Wuhan 430074, China; School of Earth and Atmospheric Sciences, Georgia Institute of Technology, Atlanta, GA, USA
| | - Yuhang Wang
- School of Earth and Atmospheric Sciences, Georgia Institute of Technology, Atlanta, GA, USA.
| | - Lianxin Yuan
- Hubei Environment Monitoring Center, Wuhan 430072, China
| | - Nan Chen
- Hubei Environment Monitoring Center, Wuhan 430072, China
| | - Shaofei Kong
- School of Environmental Studies, China University of Geosciences (Wuhan), Wuhan 430074, China.
| |
Collapse
|
14
|
An F, Liu J, Lu W, Jareemit D. Comparison of exposure to traffic-related pollutants on different commuting routes to a primary school in Jinan, China. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2022; 29:43319-43340. [PMID: 35091940 PMCID: PMC8799450 DOI: 10.1007/s11356-021-18362-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/09/2021] [Accepted: 12/23/2021] [Indexed: 06/14/2023]
Abstract
Traffic-related pollutants seriously affect human health, and the commute time to and from school is the time when students are exposed greatest to traffic pollution sources. Field measurements were conducted with hand-held instruments while walking along two selected commuting routes in winter and spring. The measured data were then compared with background monitoring data, and the respiratory deposition dose (RDD) was calculated to assess the exposure risk. Particulate matter intake from 2018 to 2020 was calculated. In winter, the average concentrations of PM2.5 and PM10 were higher in the afternoon than in the morning. The highest concentration was 2.94 times greater than the background value. The low-concentration distribution area of the low-traffic route that is off the main road (route B) was more significant than that of the high-traffic route that is near the main road (route A). Moreover, the RDD of route B was consistently lower than that of route A, while the average annual amount of PM2.5 inhalation on route B in 3 years was 16.3% lower than that on route A. Overall, route B is more suitable than route A for students to commute on foot. Based on the findings, a walking route located within a community is a good choice.
Collapse
Affiliation(s)
- Farun An
- School of Thermal Engineering, Shandong Jianzhu University, #1000 Fengming Road, Jinan, 250101, China
| | - Jiying Liu
- School of Thermal Engineering, Shandong Jianzhu University, #1000 Fengming Road, Jinan, 250101, China.
- Shandong GRAD Group, Built Environment Design and Research Institute, Dezhou, 253000, China.
| | - Wanpeng Lu
- School of Thermal Engineering, Shandong Jianzhu University, #1000 Fengming Road, Jinan, 250101, China
| | - Daranee Jareemit
- Faculty of Architecture and Planning, Thammasat University (Rangsit Campus), Khlong Nueng, 12121, Pathum Thani, Thailand
| |
Collapse
|
15
|
Tonezzer M, Armellini C, Toniutti L. Sensing Performance of Thermal Electronic Noses: A Comparison between ZnO and SnO 2 Nanowires. NANOMATERIALS (BASEL, SWITZERLAND) 2021; 11:2773. [PMID: 34835538 PMCID: PMC8624967 DOI: 10.3390/nano11112773] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/27/2021] [Revised: 10/11/2021] [Accepted: 10/14/2021] [Indexed: 11/21/2022]
Abstract
In recent times, an increasing number of applications in different fields need gas sensors that are miniaturized but also capable of distinguishing different gases and volatiles. Thermal electronic noses are new devices that meet this need, but their performance is still under study. In this work, we compare the performance of two thermal electronic noses based on SnO2 and ZnO nanowires. Using five different target gases (acetone, ammonia, ethanol, hydrogen and nitrogen dioxide), we investigated the ability of the systems to distinguish individual gases and estimate their concentration. SnO2 nanowires proved to be more suitable for this purpose with a detection limit of 32 parts per billion, an always correct classification (100%) and a mean absolute error of 7 parts per million.
Collapse
Affiliation(s)
- Matteo Tonezzer
- IMEM-CNR, Sede di Trento-FBK, Via alla Cascata 56/C, 38123 Trento, Italy
- Center Agriculture Food Environment, University of Trento/Fondazione Edmund Mach, Via E. Mach 1, 38010 San Michele all’Adige, Italy
- Department of Food Quality and Nutrition, Research and Innovation Centre, Fondazione Edmund Mach, Via E. Mach 1, 38098 San Michele all’Adige, Italy
| | - Cristina Armellini
- Institute for Photonics and Nanotechnologies (IFN)-National Research Council (CNR) CSMFO Lab, Via alla Cascata 56/C, 38123 Trento, Italy;
- Fondazione Bruno Kessler (FBK)-Centro Materiali e Microsistemi (CMM), Via alla Cascata 56/C, 38123 Trento, Italy
| | - Laura Toniutti
- Agenzia Provinciale Protezione Ambiente, Settore Qualità Ambientale, U.O. Tutela dell’Aria e Agenti Fisici, Via Lidorno 1, 38123 Trento, Italy;
| |
Collapse
|