Identification

Title

Simulations of sulfate–nitrate–ammonium (SNA) aerosols during the extreme haze events over northern China in October 2014

Abstract

Extreme haze events have occurred frequently over China in recent years. Although many studies have investigated the formation mechanisms associated with PM2.5 for heavily polluted regions in China based on observational data, adequately predicting peak PM2.5 concentrations is still challenging for regional air quality models. In this study, we evaluate the performance of one configuration of the Weather Research and Forecasting model coupled with chemistry (WRF-Chem) and use the model to investigate the sensitivity of heterogeneous reactions on simulated peak sulfate, nitrate, and ammonium concentrations in the vicinity of Beijing during four extreme haze episodes in October 2014 over the North China Plain. The highest observed PM2.5 concentration of 469 mu g m(-3) occurred in Beijing. Comparisons with observations show that the model reproduced the temporal variability in PM2.5 with the highest PM2.5 values on polluted days (defined as days in which observed PM2.5 is greater than 75 mu g m(-3)), but predictions of sulfate, nitrate, and ammonium were too low on days with the highest observed concentrations. Observational data indicate that the sulfur/nitric oxidation rates are strongly correlated with relative humidity during periods of peak PM2.5; however, the model failed to reproduce the highest PM2.5 concentrations due to missing heterogeneous/aqueous reactions. As the parameterizations of those heterogeneous reactions are not well established yet, estimates of SO2-to-H2SO4 and NO2/NO3- to-HNO3 reaction rates that depend on relative humidity were applied, which improved the simulation of sulfate, nitrate, and ammonium enhancement on polluted days in terms of both concentrations and partitioning among those species. Sensitivity simulations showed that the extremely high heterogeneous reaction rates and also higher emission rates than those reported in the emission inventory were likely important factors contributing to those peak PM2.5 concentrations.

Resource type

document

Resource locator

Unique resource identifier

code

http://n2t.net/ark:/85065/d7wd4288

codeSpace

Dataset language

eng

Spatial reference system

code identifying the spatial reference system

Classification of spatial data and services

Topic category

geoscientificInformation

Keywords

Keyword set

keyword value

Text

originating controlled vocabulary

title

Resource Type

reference date

date type

publication

effective date

2016-01-01T00:00:00Z

Geographic location

West bounding longitude

East bounding longitude

North bounding latitude

South bounding latitude

Temporal reference

Temporal extent

Begin position

End position

Dataset reference date

date type

publication

effective date

2016-08-30T00:00:00Z

Frequency of update

Quality and validity

Lineage

Conformity

Data format

name of format

version of format

Constraints related to access and use

Constraint set

Use constraints

Limitations on public access

None

Responsible organisations

Responsible party

contact position

OpenSky Support

organisation name

UCAR/NCAR - Library

full postal address

PO Box 3000

Boulder

80307-3000

email address

opensky@ucar.edu

web address

http://opensky.ucar.edu/

name: homepage

responsible party role

pointOfContact

Metadata on metadata

Metadata point of contact