The Aerosol-Radiation Interaction Effects of Different Particulate Matter Components during Heavy Pollution Periods in China

The Beijing-Tianjin-Hebei (BTH) region experienced heavy air pollution in December 2015, which provided a good opportunity to explore the aerosol-radiation interaction (ARI) effects of different particulate matter (PM) components (sulfate, nitrate, and black carbon (BC)). In this study, five tests were conducted by the Weather Research and Forecasting—Chemistry (WRF-Chem) model. The tests included scenario 1 simulation with ARI turned on, scenario 2 simulation with ARI turned off, scenario3 simulation without NOx/NO3− emissions and with ARI turned on, scenario 4 simulation without SO2/SO42− emissions and with ARI turned on, and scenario 5 simulation without BC emissions and with ARI turned on. The ARI decreased the downward shortwave radiation (SWDOWN) and the temperature at 2 m (T2), reduced the planetary boundary layer (PBL) height (PBLH), and increased the relative humidity (RH) at 2 m in the region. These factors also contribute to pollution accumulation. The results revealed that BC aerosols have a stronger effect on the reduction in SWDOWN than sulfate (SO42−) and nitrate (NO3−). BC aerosols produce both cooling and heating effects, while SO42− aerosols produce only cooling effects. The PBL decreased and RH2 increased due to the aerosol feedback effect of sulfate, nitrate, and BC. The ARI effect on meteorological factors during the nonheavy pollution period was much smaller than that during the pollution period.

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Environmental and human health impact of different powertrain passenger cars in a life cycle perspective. A focus on health risk and oxidative potential of particulate matter components

The Science of The Total Environment ◽

10.1016/j.scitotenv.2021.150171 ◽

2021 ◽

pp. 150171

Author(s):

Federico Sisani ◽

Francesco Di Maria ◽

Daniela Cesari

Keyword(s):

Particulate Matter ◽

Life Cycle ◽

Health Risk ◽

Human Health ◽

Health Impact ◽

Passenger Cars ◽

Oxidative Potential ◽

Human Health Impact ◽

Life Cycle Perspective ◽

Particulate Matter Components

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Particulate matter components, sources, and health: Systematic approaches to testing effects

Journal of the Air & Waste Management Association ◽

10.1080/10962247.2014.1001884 ◽

2015 ◽

Vol 65 (5) ◽

pp. 544-558 ◽

Cited By ~ 70

Author(s):

Kate Adams ◽

Daniel S. Greenbaum ◽

Rashid Shaikh ◽

Annemoon M. van Erp ◽

Armistead G. Russell

Keyword(s):

Particulate Matter ◽

Testing Effects ◽

Particulate Matter Components

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Associations Between Fine Particulate Matter Components and Daily Mortality in Nagoya, Japan

Journal of Epidemiology ◽

10.2188/jea.je20150039 ◽

2016 ◽

Vol 26 (5) ◽

pp. 249-257 ◽

Cited By ~ 20

Author(s):

Kayo Ueda ◽

Makiko Yamagami ◽

Fumikazu Ikemori ◽

Kunihiro Hisatsune ◽

Hiroshi Nitta

Keyword(s):

Particulate Matter ◽

Fine Particulate Matter ◽

Daily Mortality ◽

Fine Particulate ◽

Particulate Matter Components

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Why do models perform differently on particulate matter over East Asia? A multi-model intercomparison study for MICS-Asia III

Atmospheric Chemistry and Physics ◽

10.5194/acp-20-7393-2020 ◽

2020 ◽

Vol 20 (12) ◽

pp. 7393-7410 ◽

Cited By ~ 3

Author(s):

Jiani Tan ◽

Joshua S. Fu ◽

Gregory R. Carmichael ◽

Syuichi Itahashi ◽

Zhining Tao ◽

...

Keyword(s):

Particulate Matter ◽

Air Quality ◽

East Asia ◽

Dust Emission ◽

Sulfur Oxidation ◽

Atmospheric Modeling ◽

Weather Research And Forecasting ◽

Forecasting Model ◽

Air Quality Prediction ◽

Weather Research

Abstract. This study compares the performance of 12 regional chemical transport models (CTMs) from the third phase of the Model Inter-Comparison Study for Asia (MICS-Asia III) on simulating the particulate matter (PM) over East Asia (EA) in 2010. The participating models include the Weather Research and Forecasting model coupled with Community Multiscale Air Quality (WRF-CMAQ; v4.7.1 and v5.0.2), the Regional Atmospheric Modeling System coupled with CMAQ (RAMS-CMAQ; v4.7.1 and v5.0.2), the Weather Research and Forecasting model coupled with chemistry (WRF-Chem; v3.6.1 and v3.7.1), Goddard Earth Observing System coupled with chemistry (GEOS-Chem), a non-hydrostatic model coupled with chemistry (NHM-Chem), the Nested Air Quality Prediction Modeling System (NAQPMS) and the NASA-Unified WRF (NU-WRF). This study investigates three model processes as the possible reasons for different model performances on PM. (1) Models perform very differently in the gas–particle conversion of sulfur (S) and oxidized nitrogen (N). The model differences in sulfur oxidation ratio (50 %) are of the same magnitude as that in SO42- concentrations. The gas–particle conversion is one of the main reasons for different model performances on fine mode PM. (2) Models without dust emission modules can perform well on PM10 at non-dust-affected sites but largely underestimate (up to 50 %) the PM10 concentrations at dust sites. The implementation of dust emission modules in the models has largely improved the model accuracies at dust sites (reduce model bias to −20 %). However, both the magnitude and distribution of dust pollution are not fully captured. (3) The amounts of modeled depositions vary among models by 75 %, 39 %, 21 % and 38 % for S wet, S dry, N wet and N dry depositions, respectively. Large inter-model differences are found in the washout ratios of wet deposition (at most 170 % in India) and dry deposition velocities (generally 0.3–2 cm s−1 differences over inland regions).

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