Elsevier

Atmospheric Environment

Volume 147, December 2016, Pages 296-309
Atmospheric Environment

Effects of meteorological conditions on sulfur dioxide air pollution in the North China plain during winters of 2006–2015

https://doi.org/10.1016/j.atmosenv.2016.10.005Get rights and content

Highlights

  • Meteorological conditions with OMI-based high SO2 days in China are studied.

  • Climatological anomaly of meteorological variables in high SO2 days are quantified.

  • Year-to-year winter change of columnar SO2 distribution is mostly due to SO2 emission.

  • Surface SO2 distribution has stronger dependence on meteorology than columnar SO2.

  • Columnar SO2 climatology is not representative to surface SO2 climatology.

Abstract

The last decade has seen frequent occurrences of severe air pollution episodes of high loading in SO2 during winters in the North China Plain (NCP). Using satellite data from the Ozone Monitoring Instrument (OMI), chemistry transport model (GEOS-Chem) simulations, and National Center for Environmental Predication (NCEP) meteorological reanalysis, this study examines meteorological and synoptic conditions associated with air pollution episodes during 2006–2015 winters. OMI-based SO2 data suggest a large decrease (∼30% in area average) of SO2 emissions since 2010. Statistical analysis shows that meteorological conditions associated with the top 10% of OMI-based high SO2 days are found on average to be controlled by high pressure systems with 2 m s−1 lower wind speeds, slightly warmer, 1–2 °C, temperatures and 10–20% higher relative humidities from the surface to 850 hPa. Numerical experiments with GOES-Chem nested grid simulations at 0.5° × 0.667° resolution are conducted for winters of 2009 as a control year, and 2012 and 2013 as years for sensitivity analysis. The experiments reveal that year-to-year change of winter columnar SO2 amounts and distributions in first order are linearly proportional to the change in SO2 emissions, regardless of the differences in meteorological conditions. In contrast, the surface SO2 amounts and distributions exhibit highly non-linear relationships with respect to the emissions and stronger dependence on the meteorological conditions. Longer data records of atmospheric SO2 from space combined with meteorological reanalysis are needed to further study the meteorological variations in air pollution events and the air pollution climatology in the context of climate change.

Introduction

Sulfur dioxide (SO2) gas is emitted both naturally and anthropogenically through volcanic eruptions and fossil fuel combustion. Estimates by the World Health Organization (WHO, 2001) show that economic health impact (excess mortality and morbidity) due to air pollution of SO2 is ∼43.8 billion RMB Yuan (or ∼6.5 billion $) in China. Smith et al. (2011) found that annual emissions of SO2 topped ∼35 Teragrams (Tg) in the US and Canada, and ∼41 Tg SO2 in Western and Central Europe during the 1970s. However, in the last two decades, North America (United States and Canada) and Europe have been steadily reducing their emissions from 24 Tg to 31 Tg, respectively in 1990 to 17 Tg and 14 Tg, respectively in 2000, and to 15 Tg and 11 Tg, respectively in 2005. These decreasing trends contrast with the increasing trend of SO2 in many developing countries; annual emissions by sector and fuel types calculated from satellite data show an increasing trend of SO2 during 1996–2008 and decreasing thereafter in China, with a range of 30–40 Tg per year (Lu et al., 2010).

The distribution of atmospheric SO2 not only depends on the emission of SO2, but also is affected by meteorological conditions. Xue and Yin, 2013 found that at Shanghai, SO2 amounts were negatively correlated with temperature, dew point, relative humidity, wind speed and positively correlated with pressure from October 2004 to September 2012. Bridgman et al. (2002) found that SO2 surface concentrations in the Czech Republic can be influenced by strong variations of wind direction, wind speed and temperature within the seasons. In Trabzon City, Turkey, Cuhadaroglu and Demirci (1997) found that SO2 surface concentrations when compared with humidity, wind and temperature have moderate relations in November and December while having weaker relations during January–April. However in Balikesir, Turkey, SO2 was highly correlated with lower temperatures and lower wind speeds, and less correlated with relative humidity (Ilten and Selici, 2008).

This study investigates how meteorological factors favor high episodes of SO2 pollution events in China through a combined use of a chemistry transport model (CTM), satellite products of SO2, and meteorological reanalysis from the National Center for Environmental Predication (NCEP). Many satellite sensors have the capability to monitor atmospheric SO2 from space, including Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY) (Afe et al., 2004, Richter et al., 2006, Lee et al., 2008, Lee et al., 2009, Zhang et al., 2012), Ozone Monitoring Instrument (OMI) (Krotkov et al., 2008, Carn et al., 2015, Yang et al., 2007, He et al., 2012), and most recently Ozone Mapping and Profiler Suite (OMPS) (Yang et al., 2013). However, these satellite-based SO2 data in the past have been primarily used for estimating SO2 emissions and to some extent to evaluate and improve CTM simulations of atmospheric SO2 (Lee et al., 2009, Lee et al., 2011, Wang et al., 2013). Yang et al. (2013) is among the few studies that have combined meteorological data and satellite SO2 data from OMPS, to study the role of the atmosphere in an air pollution event for the 2013 winter in China. Numerous studies have also conducted ground-based observations and modeling analyses of air pollution events in China (Chan and Yao, 2008, Lu et al., 2010, Lu et al., 2011, Zhang et al., 2015), just to name a few.

Our study area focuses on the North China Plain (NCP) where the SO2 emissions have changed rapidly due to the combination of fast economic growth and implementation of air pollution control policies in the last decade for this region (Li et al., 2010). However, these rapid changes of SO2 emission, together with frequent SO2 pollution episodes also make the NCP a unique place to combine both satellite data and CTM results to study air pollution meteorology (Yang et al., 2013). Past studies of air pollution meteorology have primarily relied on ground-based observations and numerical models (Fiore et al., 2012). Hence, our joint and new analysis of satellite and model data can reveal (to some extent) how the changing climate (including meteorological conditions) may affect SO2 air quality, and thus have important implications for predicting future air quality as the climate continues to change (Fiore et al., 2012). The study period of focus is the meteorological winter (December, January and February) during 2006–2015. We describe the data and model in Section 2, model experiment design and approaches in Section 3, results in Section 4 and conclude the paper in Section 5.

Section snippets

Datasets and study area

Data used in this study over the NCP (110°E−125°E, 30°N-42°N, Fig. 1) include: (1) Level 3 OMI-best pixel scans, (2) hourly data from a CTM driven by the meteorology from the Goddard Earth Observing System (GEOS); and (3) reanalysis meteorological data from NCEP.

OMI data processing for analyzing air pollution meteorology

Daily retrievals from OMI, allocated to grid cells of 0.25° × 0.25°, were filtered with a large solar zenith angle and viewing zenith angle greater than 70°. To further ensure data quality, only SO2 data retrieved with low radiative cloud fractions, less than 0.2, are used in this study. First, we re-grid daily OMI SO2 into a 2.5° by 2.5° mesh to match the resolution of the NCEP reanalysis data. Second, for each grid box, we sort the OMI SO2 data from the highest to the lowest loadings during

Overview

The NCP is flat with topography less than 100 m, (Fig. 1A). However, the Taihang mountain range, located to the west of the NCP can extend higher than 1500 m. Fig. 2B also shows the locations of each province in our study region. During the winter months, the climatological average (1981–2010) for the 850 hPa height ranges from 1440 geopotential meters (gpm) in the northeastern part of the study region to 1530 gpm in the southwestern part, with major cities like Beijing near 1490 gpm and

Summary

Using OMI and GEOS-Chem, we studied the characteristics of how meteorological conditions affect SO2 distributions in the NCP during the winters of 2006–2015. The main conclusions are as follows:

  • OMI SO2 data show that atmospheric SO2 loadings in China have drastically decreased by 30% from the 2006–2010 period to the 2011–2015 period. This can be attributed to the installation of flue-gas desulfurization devices.

  • High SO2 days are found to be associated with stagnant, warm and moist air masses

Acknowledgement

This work. was supported by NASA Aura Science program (grant #: NNX14AG01G managed by Dr. Ken Jucks), Applied Science Program (grant #: NNX15AC28A managed by Dr. John Haynes), and ACMAP program (grant #: NNX15AC30G managed by Dr. Richard Eckman) and by Holland Computing Center and Office for Research and Economic Development in University of Nebraska-Lincoln. We thank Mr. Curtis Walker for proofreading this article.

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