Publications by authors named "Jinlu Dong"

4 Publications

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Surface-enhanced Raman scattering for mixing state characterization of individual fine particles during a haze episode in Beijing, China.

J Environ Sci (China) 2021 Jun 22;104:216-224. Epub 2020 Dec 22.

MOE Key Laboratory of Resources and Environmental System Optimization, College of Environmental Science and Engineering, North China Electric Power University, Beijing 102206, China; Guangdong Provincial Key Laboratory of Petrochemcial Pollution Processes and Control, School of Environmental Science and Engineering, Guangdong University of Petrochemical Technology, Maoming 525000, China.

The nondestructive characterization of the mixing state of individual fine particles using the traditional single particle analysis technique remains a challenge. In this study, fine particles were collected during haze events under different pollution levels from September 5 to 11 2017 in Beijing, China. A nondestructive surface-enhanced Raman scattering (SERS) technique was employed to investigate the morphology, chemical composition, and mixing state of the multiple components in the individual fine particles. Optical image and SERS spectral analysis results show that soot existing in the form of opaque material was predominant during clear periods (PM ≤ 75 µg/m). During polluted periods (PM > 75 µg/m), opaque particles mixed with transparent particles (nitrates and sulfates) were generally observed. Direct classical least squares analysis further identified the relative abundances of the three major components of the single particles: soot (69.18%), nitrates (28.71%), and sulfates (2.11%). A negative correlation was observed between the abundance of soot and the mass concentration of PM. Furthermore, mapping analysis revealed that on hazy days, PM existed as a core-shell structure with soot surrounded by nitrates and sulfates. This mixing state analysis method for individual PM particles provides information regarding chemical composition and haze formation mechanisms, and has the potential to facilitate the formulation of haze prevention and control policies.
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http://dx.doi.org/10.1016/j.jes.2020.12.008DOI Listing
June 2021

Large global variations in measured airborne metal concentrations driven by anthropogenic sources.

Sci Rep 2020 12 11;10(1):21817. Epub 2020 Dec 11.

Department of Chemistry, Faculty of Science, University of Dhaka, Dhaka, 1000, Bangladesh.

Globally consistent measurements of airborne metal concentrations in fine particulate matter (PM) are important for understanding potential health impacts, prioritizing air pollution mitigation strategies, and enabling global chemical transport model development. PM filter samples (N ~ 800 from 19 locations) collected from a globally distributed surface particulate matter sampling network (SPARTAN) between January 2013 and April 2019 were analyzed for particulate mass and trace metals content. Metal concentrations exhibited pronounced spatial variation, primarily driven by anthropogenic activities. PM levels of lead, arsenic, chromium, and zinc were significantly enriched at some locations by factors of 100-3000 compared to crustal concentrations. Levels of metals in PM and PM exceeded health guidelines at multiple sites. For example, Dhaka and Kanpur sites exceeded the US National Ambient Air 3-month Quality Standard for lead (150 ng m). Kanpur, Hanoi, Beijing and Dhaka sites had annual mean arsenic concentrations that approached or exceeded the World Health Organization's risk level for arsenic (6.6 ng m). The high concentrations of several potentially harmful metals in densely populated cites worldwide motivates expanded measurements and analyses.
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http://dx.doi.org/10.1038/s41598-020-78789-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7733447PMC
December 2020

Global Sources of Fine Particulate Matter: Interpretation of PM Chemical Composition Observed by SPARTAN using a Global Chemical Transport Model.

Environ Sci Technol 2018 10 1;52(20):11670-11681. Epub 2018 Oct 1.

Center for Environmental Science and Engineering , Indian Institute of Technology Kanpur , Kanpur , 208016 , India.

Exposure to ambient fine particulate matter (PM) is a leading risk factor for the global burden of disease. However, uncertainty remains about PM sources. We use a global chemical transport model (GEOS-Chem) simulation for 2014, constrained by satellite-based estimates of PM to interpret globally dispersed PM mass and composition measurements from the ground-based surface particulate matter network (SPARTAN). Measured site mean PM composition varies substantially for secondary inorganic aerosols (2.4-19.7 μg/m), mineral dust (1.9-14.7 μg/m), residual/organic matter (2.1-40.2 μg/m), and black carbon (1.0-7.3 μg/m). Interpretation of these measurements with the GEOS-Chem model yields insight into sources affecting each site. Globally, combustion sectors such as residential energy use (7.9 μg/m), industry (6.5 μg/m), and power generation (5.6 μg/m) are leading sources of outdoor global population-weighted PM concentrations. Global population-weighted organic mass is driven by the residential energy sector (64%) whereas population-weighted secondary inorganic concentrations arise primarily from industry (33%) and power generation (32%). Simulation-measurement biases for ammonium nitrate and dust identify uncertainty in agricultural and crustal sources. Interpretation of initial PM mass and composition measurements from SPARTAN with the GEOS-Chem model constrained by satellite-based PM provides insight into sources and processes that influence the global spatial variation in PM composition.
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http://dx.doi.org/10.1021/acs.est.8b01658DOI Listing
October 2018

A novel optimal configuration form redundant MEMS inertial sensors based on the orthogonal rotation method.

Sensors (Basel) 2014 Jul 29;14(8):13661-78. Epub 2014 Jul 29.

Marine Navigation Research Institute, College of Automation, Harbin Engineering University, Harbin 150001, China.

In order to improve the accuracy and reliability of micro-electro mechanical systems (MEMS) navigation systems, an orthogonal rotation method-based nine-gyro redundant MEMS configuration is presented. By analyzing the accuracy and reliability characteristics of an inertial navigation system (INS), criteria for redundant configuration design are introduced. Then the orthogonal rotation configuration is formed through a two-rotation of a set of orthogonal inertial sensors around a space vector. A feasible installation method is given for the real engineering realization of this proposed configuration. The performances of the novel configuration and another six configurations are comprehensively compared and analyzed. Simulation and experimentation are also conducted, and the results show that the orthogonal rotation configuration has the best reliability, accuracy and fault detection and isolation (FDI) performance when the number of gyros is nine.
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http://dx.doi.org/10.3390/s140813661DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4179055PMC
July 2014