Supplementary material for

The blue skies in Beijing during APEC 2014: A quantitative

assessment of emission control efficiency and meteorological

influence

Hongli Liu1#, Jing He1#, Jianping Guo1*, Yucong Miao1, Jinfang Yin1, Yuan Wang2,

Hui Xu1*, Huan Liu1,3, Yan Yan1, Yuan Li1, and Panmao Zhai1

1State Key Laboratory of Severe Weather, Chinese Academy of Meteorological

Sciences, Beijing 100081, China

2Division of Geological and Planetary Sciences, California Institute of Technology,

Pasadena, CA 91125, USA.

3College of Earth Sciences, University of Chinese Academy of Sciences, Beijing

100049, China

# These co-authors contribute equally to this work.

*Correspondence to: Dr./Prof. Jianping Guo (jpguocams@gmail.com)

Dr. Hui Xu (dx0120xh@163.com)

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Table S1. The absolute changes (μg/m3) and relative changes (%) of simulated PM2.5

concentrations under different schemes relative to simulated PM2.5 concentrations

using scheme "None" in urban areas of Beijing and Huairou district for five episodes.

The standard deviation for the modeled results are also listed.

Schemes EpisodesPM2.5 Changes STD

Urban Areas Huairou Urban Areas Huairou

Ctrl

P1_acc -55.3(-39.4%) -32.5(-35.7%) 25.4(3.8%) 10.0(2.1%)

P1_dis -25.4(-36.3%) -20.7(-38.3%) 14.9(7.0%) 2.4(2.7%)

Clean -32.8(-41.3%) -11.4(-34.9%) 12.8(2.4%) 7.3(5.8%)

P2_acc -59.9(-40.3%) -33.0(-39.8%) 20.8(2.7%) 5.2(0.7%)

P2_dis -31.1(-37.8%) -21.8(-40.7%) 17.7(6.2%) 4.9(1.3%)

Beijing

P1_acc -46.1(-31.8%) -26.2(-27.6%) 25.1(7.1%) 9.1(3.3%)

P1_dis -21.2(-28.5%) -17.9(-34.5%) 14.3(10.9%) 2.2(3.7%)

Clean -30.1(-37.4%) -10.6(-31.8%) 12.5(3.6%) 7.5(7.6%)

P2_acc -51.3(-33.5%) -29.9(-34.9%) 20.6(4.5%) 4.9(1.1%)

P2_dis -26.6(-31.2%) -19.5(-37.0%) 17.2(9.1%) 4.9(2.1%)

Beijing_Vehicle

P1_acc -10.9(-9.0%) -8.1(-8.7%) 3.7(1.7%) 4.7(2.7%)

P1_dis -7.9(-11.4%) -2.6(-5.0%) 4.6(1.7%) 1.7(3.4%)

Clean -9.2(-14.0%) -3.2(-10.9%) 1.0(3.3%) 0.4(4.0%)

P2_acc -14.5(-11.8%) -7.0(-10.3%) 0.8(2.9%) 1.6(3.4%)

P2_dis -9.9(-12.9%) -2.8(-5.1%) 5.0(2.1%) 2.2(4.0%)

300km

P1_acc -6.8(-5.6%) -5.2(-7.6%) 1.0(2.1%) 0.6(1.3%)

P1_dis -3.9(-7.1%) -2.3(-3.9%) 0.9(2.9%) 0.1(1.1%)

Clean -3.3(-4.9%) -1.1(-4.2%) 0.7(2.1%) 0.3(2.2%)

P2_acc -9.4(-7.9%) -4.2(-6.5%) 0.2(2.3%) 0.4(0.5%)

P2_dis -4.9(-7.2%) -2.4(-4.0%) 1.1(2.4%) 0.1(1.1%)

No Beijing

P1_acc -9.6(-6.9%) -5.8(-7.5%) 0.7(2.8%) 0.9(1.0%)

P1_dis -4.2(-7.6%) -2.8(-3.9%) 0.9(3.6%) 0.2(0.8%)

Clean -2.8(-3.9%) -0.9(-3.1%) 0.4(1.5%) 0.2(1.8%)

P2_acc -8.3(-6.5%) -3.2(-4.8%) 0.2(1.8%) 0.4(0.3%)

P2_dis -5.7(-7.7%) -2.3(-3.6%) 1.2(2.6%) 0.2(1.1%)

Hebei

P1_acc -5.3(-3.9%) -3.5(-4.3%) 1.1(1.2%) 0.8(0.2%)

P1_dis -0.9(-1.5%) -1.1(-1.4%) 0.4(0.7%) 0.2(0.2%)

Clean -1.6(-2.1%) -0.4(-0.7%) 0.08(0.6%) 0.09(0.2%)

P2_acc -4.3(-3.6%) -1.3(-2.0%) 0.2(1.4%) 0.2(0.5%)

P2_dis -1.3(-2.0%) -0.6(-1.0%) 0.4(0.4%) 0.07(0.4%)

Hebei_Vehicle P1_acc -0.6(-0.5%) -0.8(-1.1%) 0.3(0.3%) 0.5(0.3%)

P1_dis -0.07(-0.1%) -0.2(-0.4%) 0.3(0.4%) 0.05(0.1%)

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Clean -0.2(-0.4%) -0.07(-0.1%) 0.1(0.2%) 0.005(0.1%)

P2_acc -1.4(-1.3%) -0.4(-0.9%) 0.3(0.8%) 0.07(0.3%)

P2_dis -0.4(-0.6%) -0.1(-0.3%) 0.3(0.2%) 0.02(0.1%)

300km_Vehicle

P1_acc -0.1(-0.1%) -0.05(-0.0%) 0.07(0.07%) 0.01(0.0%)

P1_dis -0.04(-0.0%) -0.007(-0.0%) 0.05(0.05%) 0.002(0.0%)

Clean -0.01(-0.0%) -0.01(-0.0%) 0.005(0.00%) 0.007(0.0%)

P2_acc -0.2(-0.2%) -0.07(-0.17%) 0.04(0.12%) 0.02(0.0%)

P2_dis -0.05(-0.0%) -0.002(-0.0%) 0.06(0.06%) 0.003(0.0%)

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Figure S1. Spatial distribution of SO2, NOX, NH3, PM2.5 emission rates (with a

resolution of 54km) in November as derived from the emission inventory compiled by

Cao et al. (2006) .

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Figure S2. Spatial distribution of SO2, NOX, NH3, PM2.5 emission rates (with a

resolution of 54km) in November as derived from the 2010 emission inventory used

in the simulation.

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Figure S3. Fitting analysis of observed and simulated PM2.5 in BTH averaged over (a)

Episode "P1", (b) Episode "Clean" and (c) Episode "P2". All of the 73 measurement

sites in BTH (close-up map in Fig. 1) are used. The correlation coefficients between

the observed and simulated results are given in blue in each panel.

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Figure S4. Time series of model simulated (red solid lines) and ground-based

observed (black dashed lines) hourly PM2.5 concentrations averaged over sites of (a)

Beijing, (b) Tianjin and (c) Hebei during APEC 2014. The grey shaded area indicates

one standard deviation of observed average PM2.5. The mean deviation (MD) for the

observed and simulated PM2.5 is given in blue in each panel.

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Figure S5. Spatial distributions of model simulated dilution factor (wind speed times mixing height) during (a) Episode "P1_acc", (b) Episode "P1_dis", (c) Episode "Clean", (d) Episode "P2_acc", and (e) Episode "P2_dis". The greater the dilution factor, more favorable the atmosphere for the dilution of aerosol pollutants. The black dot indicates the location of Beijing.

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