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Fuel 2017年 207卷 830-830页

作者： Qianyun Chang Chenghang Zheng Zhengda Yang Mengxiang Fang Xiang Gao Zhongyang Luo Kefa Cen State Key Laboratory of Clean Energy Utilization State Environmental Protection Center for Coal-Fired Air Pollution Control Zhejiang University Hangzhou 310027 China

Vertical Transport of Ultrafine Particles and Turbulence Evolution Impact on New Particle Formation at the Surface & Canton Tower

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SSRN 2023年

作者： Wu, Hao Li, Zhanqing Hai, Shangfei Gao, Yang Jiang, Jingkun Zhao, Bin Cribb, Maureen Zhang, Dongmei Pu, Dongyang Liu, Mengqi Wang, Chunling Lan, Jing Wang, Yuying Key Laboratory of China Meteorological Administration Atmospheric Sounding School of Electrical Engineering Chengdu University of Information Technology Chengdu610225 China Department of Atmospheric and Oceanic Science University of Maryland College ParkMD20742 United States College of Oceanic and Atmospheric Sciences Ocean University of China Qingdao266100 China Frontiers Science Center for Deep Ocean Multispheres and Earth System Key Laboratory of Marine Environmental Science and Ecology Ministry of Education Ocean University of China Qingdao266100 China School of Environment State Key Joint Laboratory of Environment Simulation and Pollution Control Tsinghua University Beijing100084 China State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex Beijing100084 China College of Global Change and Earth System Science Beijing Normal University Beijing100875 China Guangzhou Climate and Agrometeorology Center Guangzhou511430 China Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration Nanjing University of Information Science & Technology Nanjing210044 China

New particle formation (NPF) is a key process occurring in the planetary boundary layer (PBL). Newly formed particles are an important source of aerosols and cloud condensation nuclei (CCN) that influence clouds and climate, while the distribution of these new particles at different altitudes has rarely been studied. In-situ measurements of ultrafine particles (UFP) observed at the ground and at the top of the Canton Tower (454 m) located in downtown Guangzhou in southern China were analyzed using the measurements of multiple meteorological and physicochemical quantities, as both observed during a field campaign and simulated with the WRF-chem model. We found that turbulence and NPF characters vary considerably with heights, with UFP concentration diminishing by half from the surface to the tower top. This indicates the UFP transports upward from the ground in the lower boundary layer. A consistent relationship is established between the occurrences of NPF and the evolution of turbulence. The correlation between the exchange ratio at the tower top has correlated well with nucleation growth, suggesting that turbulence can play an important role in the episodes of NPF growth, whose growth rate is closely related to the turbulence exchange ratio, effectively dictating the ultrafine particle concentration before and during the lockdown period. A new mechanism is thus hypothesized: NPF happens eailer near the surface and grows faster at the upper PBL, attributed to condensable vapors being transported by turbulent vertical mixing in the boundary layer. Model simulations using the WRF-Chem model reveal that the exchange ratio changed the NPF parameters, supporting the proposed mechanism that the evolution of the PBL variation has a significant impact on NPF, which should not be omitted in the NPF research, since this physical factor could be a dominant one in the NPF mechanism. © 2023, The Authors. All rights reserved.

关键词： Turbulence

A Python Toolkit for Integrating Geographic Information System into Regulatory Dispersion Models for Refined pollution Modeling

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SSRN 2024年

作者： Liu, Haobing Gao, Pengfei Xiang, Sheng Zhu, Hong Chen, Jia Fu, Qingyan The Key Laboratory of Road and Traffic Engineering Ministry of Education Tongji University 4800 Caoan Road Jiading District Shanghai China College of Environmental Science and Engineering Tongji University 1239 Siping Road Yangpu District Shanghai China Shanghai Institute of Urban and Rural Construction and Transportation Development 75 Wanping South Road Xuhui District Shanghai China Shanghai Environmental Monitoring Center 55 Sanjiang Road Xuhui District Shanghai China State Environmental Protection Key Laboratory of Formation and Prevention of Urban Air Pollution Complex Shanghai Academy of Environmental Sciences 508 Qinzhou Road Xuhui District Shanghai China

AERMOD is designated as U.S. environmental protection Agency (EPA)’s preferred air dispersion model for refined transportation project hot-spot analyses beginning in 2020. One of the key challenges in its modeling process is spatially encoding roadway geometry, especially when simulating highways with complex geometric designs. This research proposed an open-source Python package, GTA, which enables conversion of publicly available roadway Geographic Information System (GIS) layers into defined sources, and source-based emission rates from MOtor Vehicle Emissions Simulator (MOVES) output for AERMOD modeling. The research selected two sub-networks in Atlanta, and conducted a comprehensive analysis in terms of annual PM2.5 concentration results and the speed of preparing AERMOD input files for highway network modeling both manually and using software developed based on the proposed methodology. The results prove that the proposed methodology significantly expedites the AERMOD input preparation process, and facilitates convenient testing of multiple modeling configurations for multi-scenario or sensitivity analysis. © 2024, The Authors. All rights reserved.

关键词： Geographic information systems

Converting Roadway GIS Layer to Aermod Geometry for Refined Pm Project-Level Modeling

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SSRN 2024年

AERMOD is designated as U.S. environmental protection Agency (EPA)’s preferred air dispersion model for refined transportation project hot-spot analyses beginning in 2020. One of the key challenges in its modeling process is spatially encoding roadway geometry, especially when simulating highways with complex geometric designs. This research proposed a geometric methodology that enables automatic conversion of publicly available roadway GIS layers into various defined sources, and source-based emission rates from MOVES output for AERMOD modeling. Taking advantage of the proposed methodology, the research selected two sub-networks from the Atlanta, and conducted a comprehensive analysis in terms of annual PM2.5 concentration results and the speed of preparing AERMOD input files for highway network modeling both manually and using software developed based on the proposed methodology. The results prove that the proposed methodology significantly expedites the AERMOD input preparation process, and facilitates convenient testing of multiple modeling configurations for multi-scenario or sensitivity analysis. © 2024, The Authors. All rights reserved.

关键词： Sensitivity analysis

Unexpected Trade-Offs of Fossil Fuel Reduction on PM2.5and O3pollution Regulation Can Be Offset by Synergistic control of VOCs source

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ACS ES&T Air

ACS ES&T air 2024年第7期1卷 660-669页

作者： Guoliang Shi Haofei Yu Jie Li Zhang Zhang Feng Wang Junbo Huang Yue Li Yulong Yan Yinchang Feng Armistead G. Russell State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control Tianjin Key Laboratory of Urban Transport Emission Research College of Environmental Science and Engineering Nankai University Tianjin 300350 People’s Republic of China China Meteorological Administration-Nankai University (CMA-NKU) Cooperative Laboratory for Atmospheric Environment-Health Research College of Environmental Science and Engineering Nankai University Tianjin 300350 China Department of Civil Environmental and Construction Engineering University of Central Florida Orlando Florida 32816 United States School of Environmental Science and Safety Engineering Tianjin University of Technology Tianjin 300384 China College of Computer Science Nankai University Tianjin 300350 China School of Environment Beijing Jiaotong University Beijing 100044 China School of Civil and Environmental Engineering Georgia Institute of Technology Atlanta Georgia 30332-0512 United States

Particulate matter (PM2.5) and ozone (O3) are typical air pollutants that require effective simultaneous control. Current PM2.5and O3co-mitigation strategies are primarily focused on the emission optimization of nitrogen oxides (NOx) and volatile organic compounds (VOCs); however, fundamental mechanisms underlying these co-mitigation efforts remain largely unanswered. Here, utilizing an atmospheric chemistry model combined with machine learning technique, we extend the scope of coordinated control efforts beyond just precursors by identifying and controlling common sources of PM2.5and O3, which are fossil fuel combustion sources including coal combustion, industrial emission, and vehicle exhausts. We conducted further sensitivity simulations and found that reducing fossil fuel combustion emissions significantly lowers PM2.5levels but has trade-off effects on O3control, which is attributable to the suppressed aerosol sink of hydroperoxyl radicals and the enhanced atmospheric oxidizing capacity. Furthermore, this unexpected enhancement of O3can be offset by synergistically controlling certain other specific VOCs sources. For example, during days with high levels of both PM2.5and O3pollution, a 40% reduction of VOCs sources at the corresponding level of coal combustion reduction is predicted to lead to an ∼13 ppb (∼14%) reduction in O3concentration. Our results provide the scientific evidence and theoretical framework for mitigating PM2.5and O3pollution through joint control of fossil fuel combustion sources and specific VOCs sources.

关键词： environmental pollution Fossil fuels Particulate matter Redox reactions Volatile organic compounds

Impact on Changes of air Quality in Xiamen airport During Covid-19 Lockdown

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SSRN 2022年

作者： Han, Bo Yao, Tingwei Li, Guojian Zhang, Yiye Dai, Qili Yu, Jian School of Transportation Science and Engineering Civil Aviation University of China Tianjin China Research Centre for Environment and Sustainable Development of Civil Aviation Administration of China Civil Aviation University of China Tianjin China Airline Operating Center Xiamen Airlines Xiamen China State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control College of Environmental Science and Engineering Nankai University Tianjin China CMA-NKU Cooperative Laboratory for Atmospheric Environment-Health Research Tianjin China

Emission reductions from transportation sector during COVID-19 lockdown significantly lowered NO 2 concentration in urban areas. Due to the reduction of flights, it would be interesting to know if such an intervention would really affect air quality. Here a generalized additive model was applied to predict NO 2 and PM 2.5 concentrations near Xiamen airport under business-as-usual scenario (no flight-ban) and compared it with the observed levels during the lockdown. The result indicates that NO 2 concentrations decreased to a much greater extent than PM 2.5 due to the lockdown policies. Therefore changes in airport-related emissions during the lockdown did have a discernable impact on local air quality. Contribution of airport-related emissions to this reduction in NO 2 was small. In contrast, the reduction from flight-ban reduced PM 2.5 concentrations by ~13.2%, while NO 2 decreased by only ~0.7%. Thus, impact of airport operations on the nearby community is underappreciated. © 2022, The Authors. All rights reserved.

关键词： air quality

source Identification and Apportionment of Ambient Particulate Matter Using an Advanced Computer-controlled Scanning Electron Microscopy (Ccsem) in Beijing

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SSRN 2022年

作者： Zhao, Peng Zhao, Pusheng Tang, Jie Li, Jiang He, Yanyun Li, Mengyan Feng, Yinchang State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control College of Environmental Science and Engineering Nankai University Tianjin300350 China China Meteorological Administration China Joint Laboratory for Electron Microscopy Analysis of Atmospheric Particles Beijing100012 China Beijing Met High–Tech Co. Ltd. Beijing102200 China Chinese Academy of Meteorological Sciences Beijing100081 China CMA-NKU Cooperative Laboratory for Atmospheric Environment-Health Research Tianjin300350 China

The use of electron microscopy to analyze the morphology, components, and sources of atmospheric particles has been studied extensively worldwide. However, in China, there are few studies on single-particle source analysis based on computer-controlled scanning electron microscopy (CCSEM) technology for a large number of particles, and the related technical methods need to be established and improved. In this study, ambient particulate matter (PM) was collected simultaneously from urban, suburban and background areas of Beijing and subsequently characterized using the IntelliSEM-EPAS technique (an advanced CCSEM). The deposition velocity model was used to deduce the size distribution and calculate the concentration of ambient PM. Based on the k-means algorithm and empirical rules, all particles investigated were quantitatively apportioned to nine major sources, including soil/road dust, carbonates-silicates, carbonates, irregular carbonaceous particles, irregular iron oxides, combustion/industry, calcium sulfate, secondary particles and salt-related particles. The size-resolved contributions (mass and number) of different sources were calculated. Soil/road dust (65.1%), carbonate-silicate (16.1%) and carbonate (7.1%) were the top three sources contributing to PM 10 mass. This study was the first localized application of IntelliSEM-EPAS technology in China, demonstrating its great promise in PM source apportionment. For further accurate and refined source apportionment, it is essential to build localized individual particle source profiles in the near future. © 2022, The Authors. All rights reserved.

关键词： Silicates

Correction to "Emission Measurements on a Large Sample of Heavy-Duty Diesel Trucks in China by Using Mobile Plume Chasing"

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environmental science & technology 2023年第45期57卷 17659页

作者： Hui Wang Shaojun Zhang Xiaomeng Wu Yifan Wen Zhenhua Li Ye Wu School of Environment State Key Joint Laboratory of Environment Simulation and Pollution Control Tsinghua University Beijing 100084 P. R. China. State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex Beijing 100084 P. R. China. Beijing Laboratory of Environmental Frontier Technologies School of Environment Tsinghua University Beijing 100084 China.

Online Analysis of Volatile and Semivolatile Organic Compounds in Water Matrices Using a Dual-Channel Comprehensive Two-Dimensional Gas Chromatography Coupled with Time-of-Flight Mass Spectrometry System

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SSRN 2024年

作者： Chen, Guangxu Wu, Manman Ma, Qin Li, Mei Zhou, Zhen Xu, Jingwei Waterhouse, Geoffrey I.N. Song, Ninghui Zhao, Wei-Wei School of Environment and Energy State Key Laboratory of Luminescent Materials and Devices Guangdong Provincial Key Laboratory of Atmospheric Environment and Pollution Control South China University of Technology Guangzhou510006 China Hangzhou Lin'an Ecological Environment Monitoring Station Hangzhou311300 China Institute of Mass Spectrometry and Atmospheric Environment Guangdong Provincial Engineering Research Center for Online Source Apportionment System of Air Pollution Jinan University Guangzhou510632 China Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality Guangzhou510632 China Guangdong MS Institute of Scientific Instrument Innovation Guangzhou510530 China School of Chemical Sciences The University of Auckland Auckland1142 New Zealand Nanjing Institute of Environmental Sciences Ministry of Ecology and Environment Nanjing210042 China State Key Laboratory of Analytical Chemistry for Life Science School of Chemistry and Chemical Engineering Nanjing University Nanjing210023 China

Monitoring organic compounds in aquatic matrices can be a complex and time-consuming process. To address this issue, we present a novel approach that uses a dual-channel comprehensive two-dimensional gas chromatography–time-of-flight mass spectrometry (GC × GC–TOFMS) system equipped with an automatic pretreatment platform for online monitoring of volatile organic compounds (VOCs) and semivolatile organic compounds (SVOCs) in water matrices. Our automatic pretreatment platform incorporates headspace sampling (HS) and liquid–liquid extraction (LLE) to extract VOCs and SVOCs from water matrices. The GC × GC–TOFMS system features a dual-channel analytical structure column configuration, allowing for the sequential analysis of VOCs in the GC–TOFMS mode and SVOCs in the GC × GC–TOFMS mode. We quantitatively detected 55 and 104 target VOCs and SVOCs, respectively, in a water sample using the instrument system. Our method demonstrated excellent correlation coefficients ranging from 0.990 to 1.000, method detection limit ranging from 0.08 to 4.78 μg·L−1, relative standard deviation below 19.3%, and recovery rates ranging from 50.0% to 124.0%. To validate the online monitoring capabilities of our system, we tested the target SVOCs at three different concentration levels over a 3-day period. Most compounds exhibited recovery rates ranging from 70.0% to 130.0%. Furthermore, we applied our method to analyze a real water sample and successfully detected more than 100 target and nontarget VOCs/SVOCs, including alcohols, aldehydes, ketones, acids, esters, and phenols. Our results indicated the potential of our novel instrument system for effective screening and analysis of organic contaminants in aquatic matrices. This innovation provides a promising solution for improving the efficiency and accuracy of organic compound monitoring in water matrices. © 2024, The Authors. All rights reserved.

关键词： Volatile organic compounds

Observations of Atmospheric Co2 and Co Based on In-Situ and Ground-Based Remote Sensing Measurements at Hefei Site, China

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SSRN 2022年

作者： Shan, Changgong Wang, Wei Xie, Yu Wu, Peng Xu, Jiaqing Zeng, Xiangyu Zha, Lingling Zhu, Qianqian Sun, Youwen Hu, Qihou Liu, Cheng Jones, Nicholas Key Laboratory of Environmental Optics and Technology Anhui Institute of Optics and Fine Mechanics Chinese Academy of Sciences Hefei230031 China Department of Precision Machinery and Precision Instrumentation University of Science and Technology of China Hefei230026 China Center for Excellence in Regional Atmospheric Environment Institute of Urban Environment Chinese Academy of Sciences Xiamen361021 China Key Laboratory of Precision Scientific Instrumentation of Anhui Higher Education Institutes University of Science and Technology of China Hefei230026 China Anhui Province Key Laboratory of Polar Environment and Global Change University of Science and Technology of China Hefei230026 China Department of Automation Hefei University Anhui Hefei230601 China School of Earth Atmospheric and Life Sciences University of Wollongong Northfields Ave WollongongNSW2522 Australia State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex Beijing100084 China

The characteristics of long time series of CO2 and CO surface concentrations, tropospheric and total column dry-air mole fractions (DMF) from May 2015 to December 2019 were investigated. Both CO2 and CO show different seasonality for the three datasets. The annual increasing trend of CO2 is similar for all three datasets. However, the annual decreasing trend of CO for surface concentration is high compared to the other two measurements, mainly due to the improved combustion efficiency from power generation in recent years. The correlation between the tropospheric and total atmospheric CO2 and CO is higher than that between the surface concentration and tropospheric CO2 and CO. This is because the tropospheric and total atmospheric results both have common vertical profiles for CO2 and CO respective mole fractions that was observed in troposphere. Furthermore, the enhancement ratios of CO2 to CO derived from the three datasets during the period from 2016 to 2019 were compared. The ratio of ∆CO2 to ∆CO has an obvious increase with altitude each year, which means that the combustion efficiencies obtained from the three datasets are different. All ratios for the three datasets showed a slight increasing trend in recent years, which is attributed to increased combustion efficiency due to governmental measures for energy savings and emission reductions. © 2022, The Authors. All rights reserved.

关键词： Carbon dioxide