Characterization of individual aerosol particles collected during haze episodes in Taiyuan

name : Wu Limajor : Applied Chemistry

tutor : Geng Hong

Introduction

An atmospheric phenomenon that leads to low visibility.

definition Haze

infl

uen

ces

Visibility Cloud formation Public health Global climate

origin

Continuous ecnomic growth Increased cosumption of fossil fuels

Objective

• Identify the particle types

• Analyse the Chemical compositons and mophologies of particles

• Compare the relative abundance of particle types

• Investigate transformation information on particles during haze episodes

Quantitative energy-dispersive electron probe X-ray microanalysisLow-Z particle EPMA

Quantitative energy-dispersive electron probe X-ray

microanalysis(ED-EPMA) method, called low-Z particle EPMA,is based on scanning electron microscopy(SEM) coupled with an ultra-thin window eneryg-dispersive X-ray detector.

Quantitative energy-dispersive electron probe X-ray microanalysisLow-Z particle EPMA

Advantages:• Short duration time of sampling• A high degree of quantification• Detecting the mophology and constituent ele

ments• Providing transformation information

Sampling date and site

2011.12.30 4_PM to 2012.1.3 8_AM

(a) a normal sunny day (b) a typical haze day

Sampling Instrument

Name:The modified seven-stage MAY cascade impactor

Flow rate: 20L·min-1

The aerodynamic diameters for stages 1-7:>16µm, 16-8µm, 8-4µm, 4-2µm, 2-1µm, 1-0.5µm,0.5-0.25µm

Data measurement and analysis

1. SEM-EDX (Scanning Electron Microscopy – Energy Dispersive X-ray Spectrometer)

Individual Particle Analysis shape and size : secondary electron images chemical compositions:X-ray spectra 2. Ultra-thin window EDX for low-Z elements detection (e.g., C, N, O, F)3. The net characteristic X-ray intensities of chemical elements are evalu

ated by a nonlinear least-squares fitting using the AXIL programme4. A Monte Carlo simulation with successive approximation is used for q

uantification5. The "expert system" is used to determine the formular concentrations

and particle group distributions

Classification

• Organic Carbon(OC)~~#1,#4,#8• Elemental Carbon(EC)~~#2

• Mineral Dust(CaCO3 、 SiO2 、 aluminosilicates)~~

#3,#5,#6,#7

• Reacted Mineral Dust(reacted CaCO3)~~#9,#10

• (NH4)2SO4/NH4HSO4—containing~~#11,#12

• K—containing~~#13,#14

X-ray spectra and atomic concentratrations of EC and OC

back

Typical SEM image of aerosol particles

collected in Taiyuan

#1 OC

#2 EC

#3 aluminosilicate

#4 OC

#5 CaCO3

#6 SiO2

#7 CaCO3#8 OC

#9 reacted CaCO3

#10 reacted CaCO3

#11 (NH4)2SO4

#12 NH4HSO4

#13 K-rich

#14 K-rich

back

Preliminary statistics

0%

20%

40%

60%

80%

100%

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21样品

相对

丰度

EC OC 初级矿物尘 反应矿物尘 Fe富 颗粒 K富 颗粒 二次颗粒 反应海盐 其他颗粒

0%

20%

40%

60%

80%

100%

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21样品

相对

丰度

EC OC 初级矿物尘 反应矿物尘 Fe富 颗粒 K富 颗粒 二次颗粒 反应海盐 其他颗粒

Relative abundances of different particle types for the 21 sets of samples in stage 4

Relative abundances of different particle types for the 21 sets of samples in stage 5

Preliminary statistics

0%

20%

40%

60%

80%

100%

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21样品

相对

丰度

EC OC 初级矿物尘 反应矿物尘 Fe富 颗粒 K富 颗粒 二次颗粒 反应海盐 其他颗粒

Relative abundances of different particle types for the 21 sets of samples in stage 6

0%

20%

40%

60%

80%

100%

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21样品

相对

丰度

EC OC 初级矿物尘 反应矿物尘 Fe富 颗粒 K富 颗粒 二次颗粒 反应海盐 其他颗粒

Relative abundances of different particle types for the 21 sets of samples in stage 7

Thank you !

Looking forward to your suggestions!