Rapid industrial and economic growth has meant a large amount of aerosols in the atmosphere with strong radiative forcing (RF) upon the climate system. Over parts of the globe, the negative forcing of aerosols has overcompensated for the positive forcing of greenhouse gases. Aerosol RF is determined by emissions and various chemical-transport-radiative processes in the atmosphere, a multi-factor problem whose individual contributors have not been well quantified.

In this study, we analyze the major factors affecting RF of secondary inorganic aerosols (SIOAs, including sulfate, nitrate and ammonium), primary organic aerosol (POA), and black carbon (BC). We analyze the RF of aerosols produced by 11 major regions across the globe, including but not limited to East Asia, Southeast Asia, South Asia, North America, and Western Europe. Factors analyzed include population size, per capita gross domestic production (GDP), emission intensity (i.e., emissions per unit GDP), chemical efficiency (i.e., mass per unit emissions) and radiative efficiency (i.e., RF per unit mass).

We find that among the 11 regions, East Asia produces the largest emissions and aerosol RF, due to relatively high emission intensity and a tremendous population size. South Asia produce the second largest RF of SIOA and BC and the highest RF of POA, in part due to its highest chemical efficiency among all regions. Although Southeast Asia also has large emissions, its aerosol RF is alleviated by its lowest chemical efficiency. The chemical efficiency and radiative efficiency of BC produced by the Middle East–North Africa are the highest across the regions, whereas its RF is lowered by a small per capita GDP. Both North America and Western Europe have low emission intensity, compensating for the effects on RF of large population sizes and per capita GDP.

There has been a momentum to transfer industries to Southeast Asia and South Asia, and such transition is expected to continue in the coming years. The resulting relocation of emissions would meant drastic changes in both the spatial distribution and the magnitude of RF, with consequences on regional and global climate forcing. Our findings are relevant to global aerosol control and climate mitigation.

Using the GRIMM-1107 aerosol sampler, GOES-9 DCD satellite images, HYSPLIT backward trajectories and WRF-model version 3.6, high PM1, PM2.5 and PM10 concentrations were investigated at Gangneung city on the Korean eastern coast from 0000 LST March 26 to 0000 LST April 4, 2004 during a Yellow dust period. During the Yellow dust period, maximum PM10 (PM2.5 and PM1) concentration was 3.3 (1.1 and 1.01) times higher than a non-dust period. Dust particles from the Gobi Desert and Nei-Mongo reaching a coast city, Gangneung of Korea by strong northwesterly winds should combine with particulates and gases emitted from the city and were trapped inside a calm zone both by internal gravity waves (IGW) in the eastern lee side of the mountains and were prevented by an easterly wind from the East Sea, resulting in very high PM concentrations at 09:00 LST (starting time of office hour), March 30. However, the combined dust particles should be uplifted from the coastal surface to the top of the mountain to the west inside the TIBL (about 300 m depth) due to daytime thermal heating of the ground surface, resulting in very low ground based PM concentrations at 15:00 LST, comparing to one at 09:00 LST. At night, daytime uplifted dust particles transporting from the China and the city should move toward the ground surface inside stable nocturnal surface inversion layer much thinner than the daytime TIBL and combine again nighttime local particulates emitted from road vehicles and residential heating boilers, resulting in maximum ground-based PM concentrations at 20:00 LST.

Future change in surface ozone in a warming climate is an important question for the United States. Analyses of historical ozone change in response to climate change, although useful for validating theories regarding future ozone changes, are complicated by concurrent changes in anthropogenic emissions. Here we find that the individual contributions of climate and precursor emissions to US historical ozone changes over 1990–2014 can be distinguished by contrasting the changes in daytime versus nighttime ozone, based on an analysis of observed and simulated annual mean ozone time series. In particular, climate variability has determined ozone interannual variability, particularly for the daytime ozone, while reductions of anthropogenic NO_x emissions have primarily driven an increase in the nighttime ozone. Our results have important implications for future ozone change studies and ozone mitigation.

The source-receptor relationship (SRR) of PM2.5 over East Asia for the year 2013 has been studied by using offline coupled meteorology – chemical transport model NHM-Chem (Kajino et al., 2015) under the framework of the Joint Research on Long-range Transboundary Air Pollutants in Northeast Asia (LTP project). Eight source-receptor regions was considered: Northwest China (NWC), Northeast China (NEC), North China (NC), South and Southwest China (SSWC), East China (EC), North Korea (NKR), South Korea (SK), and Japan (JP). In winter, spring, and autumn, 60-90% of PM2.5 concentration in the regions of China was originated to the same region. The rest was originated to the other regions but inside China. 30-40% and 20% of PM2.5 in Korea and Japan were domestic origin and the majority of the rest was originated to NEC and NC. In contrast in summer the long-range transport from the Asian continent to Japan was less influential and the domestic contribution to PM2.5 in Japan was 60%, whereas the domestic contribution to PM2.5 in Korea remained low 30-40% same as the other seasons and the contribution from EC was much larger (40-50%) than NEC and NC (less than 10%) to NKR and SKR. In order to validate our SRR, the simulation result has been compared with a set of observation data: total mass concentration of PM2.5 and PM10, chemical compositions of PM1, PM2.5 and total size, and aerosol optical parameters. The model consistently reproduced the observed physical and chemical properties, such as PM2.5/PM10 ratios, PM1/total size or PM2.5/total size chemical composition ratios, and the angstrom exponent.

Anthropogenic emissions in East Asia will be a concerning issue in regional, and global scales. In China, on one hand, NOx emissions have been rising continuously, on the other hand, SO₂ emissions reached a peak in 2005-2006 and have declined since then. These drastic changes in emissions of acidifying species are likely to have caused substantial changes not only on atmospheric concentration but also in precipitation chemistry. The absolute concentration of chemical compounds in precipitation is inherently linked to precipitation amount; therefore, the ratio of nitrate to non-seasalt sulfate concentration (‘Ratio’) in precipitation is useful as an index for evaluating acidification. In our previous study, the long-term behavior of ‘Ratio’ in precipitation during 2000-2011 was investigated, and it showed relatively flat trend between 2000 and 2005, and subsequently increases between 2006 and 2011 over China, Korea, and Japan. These changes in ‘Ratio’ corresponded well to the changes of NOx/SO₂ emissions ratio in China. Numerical model analysis clarified that the impacts of NOx increase and SO₂ decrease in China have almost equally contributed to this ‘Ratio’ trend in East Asia. The limitation of our previous study was the observation dataset above China, because EANET observation covers Central (Xi’an) and Southern (Chongqing, Xiamen, and Zhuhai) China. In this study, the observation network across Northern China around Beijing from December 2007 to November 2010 is included to further promote our knowledge on the precipitation chemistry. We would like to present the seasonal behavior of ‘Ratio’ in China and downwind regions of Korea and Japan. The regional differences of ‘Ratio’ over Northern, Central, and Southern China will be also discussed.

As the world’s top trading country, China is now the most polluted country. However, a large portion of pollution produced in China is associated with its production of goods for foreign consumption via international trade. Along with China’s rapid economic growth in recent years, its economic-trade structure and volume have been changing all the time, resulting in large changes in total emissions and the shares of trade-related emissions. Here, we assess the influence of China’s changing total and export-related emissions between 2000 and 2009 on its atmospheric pollution loadings and transport, by exploiting simulations of a global chemical transport model GEOS-Chem. We find that both air pollution  related to Chinese exports (PRE) which including nitrogen oxides (NOx), sulfur dioxide (SO2), carbon monoxide (CO), black carbon (BC), and primary organic aerosol (POA), and its share in total Chinese pollution have experienced continuous rapid growth until 2007, exposing more and more people to severely polluted air. After 2007, PRE decreases due to strengthened emission controls accompanied by declined exports as a result of the global financial crisis. Although production for exports contribute less than 35% SO2 over China in any year, the increasing trend of trade-related SO2 contributes 51% of integral trend. The changing PRE of China also affects its downwind regions such as the western United States. The contribution of export-related Chinese pollution to surface sulfate concentrations over the western United States has increased from 3% in 2000 to 12% in 2007. Overall, we find that the interannual variation of trade and associated production is a critical factor driving the trend of pollution over China and its downwind regions.

Wildfires are important sources of ozone by emitting large amounts of NOx and NMVOC, main ozone precursors. Increasing wildfire activities in the US Intermountain West presents a challenge for the region to attain a stringent ozone air quality standard in summer. Here we quantify the wildfire influences on the ozone variability, trends, and exceedance days over this region in the summers 1989-2010 with a Lagrangian and statistical approach. We define a Fire Index using backward trajectories computed by a Lagrangian model (FLEXPART), and develop statistical models based on the Fire Index and meteorological parameters to interpret daily maximum 8-h average (MDA8) ozone concentrations measured at 13 Intermountain West surface sites. We show that the statistical models better capture the wildfire ozone enhancements compared to those from a Eulerian chemical transport model (GEOS-Chem), which largely overestimates wildfire ozone influences near the source regions and fails to capture ozone production from wildfires at long distance, reflecting deficiencies in current Eulerian models to capture small-scale emissions. Wildfires enhance the Intermountain West regional summer mean MDA8 ozone concentration by 0.3-2 ppbv (daily episodic enhancements reach 20 ppbv), with large interannual variability strongly correlated with the total MDA8 ozone and mainly driven by meteorological variations. They also contribute 20% of the measured increasing but statistically insignificant trends of 0.14-0.19 ppbv year-1 in the past two decades. We find significant fire impacts on the exceedance days. 35% (38%) of the high-ozone days with MDA8 exceeds 65 ppbv (70 ppbv) would not be presented in the absence of wildfires.

Mineral dust particles play a key role in air quality and climate in East Asia through increasing aerosol concentrations, degrading atmospheric visibility, providing surfaces for heterogeneous reactions, and acting as carriers for long range transported air pollutants, cloud condensation nuclei (CCN), and ice nuclei (IN). Large uncertainties remain in dust emission modules used in current models, and quantifications of their role as CCN and IN. In this work, an advanced online-coupled climate-chemistry model, WRF-CAM5, has been applied to East Asia with triple-nested grid resolutions centering Beijing areas during 2006, 2010, and 2011 to study the role of dust in air quality and climate. WRF/CAM5 includes a dust emission module that can realistically reproduce dust emissions and offers two aerosol activation parameterizations (the default ARG00 and a new FN series) and four heterogeneous ice nucleation parameterizations (the default Meyers and new Niemand, DeMott, and Phillips parameterizations). It accounts for aerosol direct effect and indirect effects on cumulus and mix-phase clouds.

The baseline results show an overall good performance for model predictions, which is sensitive to the grid resolutions with better performance at finer resolutions. The sensitivity simulation using the FN series predicts much higher cloud droplet number concentrations (CDNC) and cloud optical depth and improves their model performance. The inclusion of adsorptive activation of dust in the FN series shows 40-45% enhancement for CDNC at different grid resolutions. The sensitivity simulation with the Niemand parameterization produces much higher nucleated ice crystal number concentrations in dust source region, leading to much higher cloud ice number and mass concentrations and ice water path. By acting as CCN and IN, dust particles have different impacts on cloud water and ice number concentrations, radiation, and temperature at 2-m and precipitation, depending on whether the dominant role of dust is CCN or IN.

China has suffered severe regional hazes in recent years. Understanding the sources and formation mechanisms is vital to the emission control strategies to reduce regional hazes. This paper utilized a backward trajectory model, two receptor models, measured hourly concentrations of major pollutants, as well as MODIS-derived AOD to study the characteristics and pollution sources for a regional haze episode during January 21 to February 8, 2014 in Wuhan. The results showed that during the relatively clean air (PM_2.5 concentrations less than 75 mgm^-3), haze (PM_2.5 concentrations greater than 75 mg m^-3 but less than 200 mg m⁻³), and heavy haze cases (PM_2.5 concentrations more than 200 mg m^-3), the average concentrations of PM_2.5 were 42.1 ± 15.7 mg m^-3, 124.5 ± 35.3 mg m^-3 and 268.02 ± 45.4 mg m^-3, respectively. The back trajectory cluster analysis indicated that the mainly clusters were north (57.8%), northeast-north (20.9%) and south (19.5%) for the heavy haze cases. The results of the receptor models showed that for the haze and heavy haze cases, predominant pollutants were derived from the north and south of Wuhan such as Baoding and Handan in Hebei province, Zhumadian and Jiaozuo in Henan province, Changsha and Zhuzhou in Hunan province. These results revealed that the large emissions of air pollutants had caused pollution to occur on the regional scales. Thus, it is vital to put air pollution controls for all surrounding areas into effect, especially for the districts in the north and south of Wuhan.

Satellite observation is a powerful way to analysis annual and seasonal variations of nitrogen dioxide (NO₂). However, many retrievals of vertical column densities (VCDs) of  NO₂ normally do not explicitly account for aerosol optical effects and surface reflectance anisotropy that vary with space and time. In order to study spatial-temporal variation of NO₂ and influences of these two factors on NO₂ variations, we use an improved retrieval of NO₂ VCDs over China, called the POMINO, based on measurements from the Ozone Monitoring Instrument (OMI), and we compare the results of without aerosol, without surface reflectance treatments and without both to the original POMINO product. Here, we use Ensemble Empirical Mode Decomposition (EEMD) to separate different temporal variations automatically.

Considering different economic development patterns between Eastern China and Western China, we focus on annual and seasonal variations from 2005 to 2015 of representative areas of these two places. Furthermore, we will study correspondent spatial-temporal variations of aerosols, represented by MODIS aerosol optical depth (AOD) data, and surface reflectance, represented by MODIS bidirectional reflectance distribution function (BRDF) data.

Over the past three decades, Beijing has suffered from air pollution and heavy haze because of its decades-long burst of economic growth and rapidly expanding clout. In this study, the impact of the thermal power industries from the Beijing-Tianjin-Hebei regions on Beijing haze formation in 2013 was studied by the two-way coupled WRF-CMAQ model. The model simulations are carried out over the eastern Asian (36 km resolution), eastern China (12 km resolution) and Beijing-Tianjin-Hebei (4 km resolution) domains.  Evaluations of model performance on PM_2.5, PM₁₀, O₃, SO₂, NO₂, CO, and AQI are carried out by comparing to satellite observation data and surface monitoring networks over the eastern China. To study the impact of the thermal power industries from the Beijing-Tianjin-Hebei regions on Beijing haze formation, the six scenario sensitivity cases for the model simulations have been designed as follows: Case-1: baseline scenario; Case-2: special emissions limits, namely, the implementation of special emission limits in air pollutant emission standards for the thermal power plants; Case-3: Ultra-low emissions, namely, all units meet ultra-low emission standards; Case-4: adjustment of industrial structures, namely, eliminate all small units below 200MW in the baseline scenario (Case-1); Case-5: the emission scenario with the emissions of 50, 35 and 5 mg m^-3 for NOx, SO₂ and smoke dust, respectively; and Case-6: the emission scenario with the emissions of 25, 15 and 1 mg m^-3 for NOx, SO₂ and smoke dust, respectively. The simulation results show that the thermal power industries from the Beijing-Tianjin-Hebei regions have impact on Beijing’s severe haze formation. On the basis of the model simulations for the 12-km resolution domain, we find that comparing to the baseline scenario of the Case 1, the PM_2.5 concentrations for the Cases 2, 3, 4, 5, and 6 can be lower by 5.72%, 6.15%, 2.34%, 8.49% and 11.57% respectively..

The eastern Mediterranean region is at the crossroads of different air masses, which have resided over different parts of Europe, Africa and Asia. The resulting concomitant influences of industrial emissions, biomass burning, oceanic emissions and desert dust strongly impact the pollution levels in this region. An intensive field measurement campaign (CYprus PHotochemistry EXperiment, CYPHEX-2014) was conducted in the north-west of Cyprus in the summer of 2014 to obtain a comprehensive understanding of the atmospheric chemistry and its subsequent impact on the air quality of this region. One of the key components of atmospheric chemistry is the hydroxyl radical (OH), the major gas phase oxidant in the troposphere, produced from the ubiquitous combination of water, sunlight and ozone. While the measurement of OH is extremely difficult due to its short lifetime and low concentration, its measurements are crucial to determine the fate and lifetime of major atmospheric pollutants, including greenhouse gases e.g. methane. The OH radicals along with the hydroperoxyl radicals (HO₂) initiate, participate and control almost all of the lower atmosphere's chemical pathways, including oxidation of hydrocarbons, formation of secondary organic aerosols and cycling between primary and secondary pollutants e.g. NO_x and O₃. While HO_x (OH+HO₂) recycling has been shown to keep up the oxidation capacity of the atmosphere in forested environments, measurements of OH and HO₂ during CYPHEX allowed us to investigate the buffering capacity of the atmosphere in the Eastern Mediterranean, under impact of pollution plumes from continental Europe and marine air masses from the Mediterranean. The self-cleaning capacity of the atmosphere over Cyprus and its subsequent impact on air quality will be discussed during the presentation.

To find out the effect of the air pollution reduction policies, long term trend of the air pollutant should be analyzed. Kolmogorov-Zurbenko(KZ) filter is a low pass filter produced through repeated iterations of a moving average to separate each variable into its temporal components. The moving average for a KZ(m, p) filter is calculated by a filter with window length m and p iterations. The output of the first pass then becomes the input for the next pass. Adjusting the window length and the number of iterations makes it possible to control the filtering of different scales of motion. To decompose the daily mean PM10 into each time component, we suppose the original time series is composed of long term trend, seasonal variation and short term component. The short-term component is attributable to weather and short-term fluctuations in precursor emissions, the seasonal component is a result of changes in the solar angle, and the long-term trend results from changes in overall emissions, pollutant transport, climate, policy, and/or economics. The daily mean PM10 decreased sharply from 60.2 ug/m³ in 2002 to 44.7 ug/m³ in 2012 but it is growing slightly after then. It suggests that there was a long-term downward trend after 2005. The difference between unadjusted and meteorologically adjusted PM10 is small. So we can find out that PM10 is unaffected by the meteorological variables(daily mean temperature, solar radiation, relative humidity, wind speed) in Busan.

This work was funded by the Korea Meteorological Administration Research and Development Program under Grant KMIPA2015-8070.

The purpose of this study is to investigate and simulate quantitatively the background concentrations over Northeast Asia. As a first step, the decade-long trend of PM10 background concentration observed at surface over China, Korea, and Japan was analyzed. According to the LTP project, 3 background stations of China, 3 stations of Korea, and 2 stations of Japan were selected as background sites, and daily averaged observed data during the period from 2000 to 2010 were used to analyze. The concentration levels and the recent characteristics of background concentrations were discussed in detail

Second, modeling simulation using reduced emission data set according to current and future emission scenario has conducted, respectively to see the trend of both current and future background in and around Korean Peninsula. FNL data was selected as input/boundary data for WRF modeling, and meteorological field was produced by simulating WRF. Then, WRF output data was converted to the form of CMAQ input data by using MCIP. To simulate air quality, CMAQ was selected as atmospheric chemical transport model, and CREATE which has been developed by NIER and Konkuk University was employed as emission data set for CMAQ modeling. To show the effects of emission reduction of each of countries: China, Japan, and Korea, our model domain was set to encompass 3 countries, and it is assumed that emission in Korea was turned off, and simulated model using Brute-Force method to see the effect of emission reduction on background concentration in Korea. In addition as well, January, April, July, and October were selected as modeling period. It was tried to interpret the effects of reductions of each country by comparing the modeling result using reduced emission data with the modeling result using original emission data, investigating quantitatively the background concentrations and their seasonal variations.

* This research was supported by Basis Science Research Program through the National Research Foundation of Korea(NRF) funded by the Ministry of Education(201523980001).

High particulate matter episodes occur due to complex factors such as long-range transport of air pollutants, stagnant air condition, increase of emissions and topographical feature. Especially the meteorological condition plays the important role in variation of the particulate matter concentration timely. In this study, the duration of high particulate matter episodes during 2010-2014 in Busan were analyzed. This study was aimed at investigation for the causes of multi-day high particulate matter episodes. The target area in this study is Busan located in the southeast coastal area of the Korean peninsula. The days with the daily mean PM10 > 100 ug/m³ or PM2.5 > 50 ug/m³ were defined as high particulate matter episodes excluding yellow dust days. Among the 118 days of high particulate matter episodes, 8 days were in extended episodes that lasted for four consecutive days and 9 days were in episodes that lasted for three consecutive days. We conducted numerical simulation using the WRF/SMOKE/CMAQ mesoscale model system to understand meteorological parameters and analyze the process of high particulate matter productions on the consecutive days among high PM episodes. The Weather Research and Forecasting(WRF) is the meteorological model and the Community Multiscale Air Quality(CMAQ) is the chemistry and transport model. The Sparse Matrix Operator Kernel Emissions(SMOKE) is also used for emissions data processing. The synoptic meteorological pattern, mixed layer depth, relative humidity, wind speed, and surface temperature were considered to be the meteorological factors. As the major results, the anticyclone and transports of air pollutants from west or northwest were investigated and the mixed layer depth was less than 1500m for multi day high particulate matter episodes in Busan, Korea.