• 한국대기환경학회지
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• 제34권2호
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• pp.356-365
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• 2018

While social networks have become very popular and powerful way of connecting people and sharing new information, they also effectively spread wrong or biased information to the public. We examine the so-called "Shandong peninsular rumor" that claims Chinese government is responsible for the increased air pollution in South Korea and Japan, by moving pollution-causing industries near Beijing to the Shandong peninsular which is close to South Korea. We demonstrate that the amounts of $NO_x$ and $SO_2$ emissions inferred by space-borne monitoring and regional air quality models show clear declining trends in past several years. We do not have any evidences to support the relation of Shandong peninsular emissions change to South Korean air quality.

• 자원ㆍ환경경제연구
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• 제29권1호
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• pp.23-45
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• 2020

중국의 급속한 경제성장은 환경에 커다란 부하를 초래하였고, 이를 통해 대기오염 문제도 심각해졌다. 본 연구는 중국의 대기오염 원인을 경험적으로 분석하였다. 표준오차 패널수정 추정기법(PCSE)을 이용하여 중국의 30개 성을 대상으로 아황산가스 및 질소산화물의 배출요인을 분석하였다. 아황산가스의 경우 일인당 실질소득이 증가할수록 배출 수준이 감소하고, 질소산화물은 일인당 실질소득과 역N자형의 관계에 있는 것으로 분석되었다. 소득 이외의 배출 요인으로 우선 전기소비량은 아황산가스나 질소산화물을 증가시키는 요인이었고, 석탄소비량은 아황산가스 배출을 증가시키는 반면에 천연가스 소비량은 아황산가스 배출을 감소시키는 요인으로 나타났다. 한편 에너지 산업에 대한 투자와 폐가스 처리에 대한 투자는 아황산가스 배출을 감소시키는 결정요인이지만 질소산화물 배출에 영향을 미치지 않는 것으로 나타났다. 한편 디젤 소비량, 트럭 비율 및 차량 수는 질소산화물 배출을 증가시키는 것으로 나타났다. 강수량의 증가도 아황산가스와 질소산화물의 배출을 감소시킨 요인이었다. 끝으로 본 연구의 정책적 시사점과 향후 연구방향을 제시하였다.

• 한국대기환경학회지
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• 제34권1호
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• pp.87-100
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• 2018

Fast economic growth and urbanization of China have been causing air pollution not only over its domestic but transboundary atmosphere. Recent high fine particle pollution episodes in China made the government move toward more stringent air pollution control policies - which are mostly fuel switching and emissions control. In this research, we tried to understand characteristics of Chinese emissions and their change by analyzing its emissions inventory by year, sector, and region. From the inter-comparison of existing bottom-up emission inventories, we found relatively good agreements (<20% difference) for $SO_2$ and $NO_x$, but 30% or more discrepancies for some pollutants. Inter-comparison with top-down $NO_x$ emissions estimates also showed 20~50% differences by year. The regional distribution and inter-annual changes of emissions revealed different stages of energy/fuel mix and policy penetration. Early increase of pollutants emissions in the eastern part of China might give strong influences to the Korean peninsular in early 2000s but, more stringent control in that region would help improving air pollution in Korea in near future.

• Asian Journal of Atmospheric Environment
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• 제11권1호
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• pp.33-36
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• 2017

China is suffering from severe air pollution especially fine $PM_{2.5}$ pollution. In 2015, the annual average $PM_{2.5}$ concentration of the 338 municipal cities was $50{\mu}g/m^3$, 78% cities at or above the prefectural level failed to comply with the $PM_{2.5}$ concentration standards. The $13^{th}$ Five-Year Plan for National Economic and Social Development set the goal that the annual average concentration of $PM_{2.5}$ in the municipal cities which failed to attain the ambient air quality standards shall be decreased by 18% by 2020 (CCCPC, 2016). In this study, an air pollution control scenario during the $13^{th}$ Five-Year Plan period was proposed and the $SO_2$, $NO_x$ and PM emission reductions in response to different measures in 31 provincial-level regions mainland China by 2020 were estimated. The air quality in the target year (2020) was simulated using the WRF-CMAQ model. The results showed that by 2020, the emissions of $SO_2$, $NO_x$ and primary PM in mainland China will be reduced by 4.19 million tons, 3.94 million tons and 4.41 million tons, a drop of 23%, 21% and 25% respectively compared with that in 2015, and the annual average concentration of $PM_{2.5}$ will decrease by 19%. Coal-fired power plant contributes the most pollutant emission reduction.

• Asian Journal of Atmospheric Environment
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• 제6권2호
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• pp.83-95
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• 2012

China has been a top producer and exporter of refined lead products in the world since the year 2000. After the phasing-out of leaded gasoline in the late 1990s, non-ferrous metallurgy and coal combustion have been identified as potential major sources of aerosol lead in China. This paper presents the single particle analytical results of ambient aerosol particles collected near a lead smelter using a scanning electron microscopy- energy dispersive x-ray spectroscopy (SEM-EDX). Aerosol particle samples were collected over a 24-hour period, starting from 8 pm on 31 May 2002, using a high volume TSP sampler. For this near source sample, 73 particles among 377 particles analyzed (accounting for 19.4%) were lead-containing particles mixed with other species (S, Cl, K, Ca, and/or C), which probably appeared to be from a nearby lead smelter. Lead-containing particles of less than $2{\mu}m$ size in the near source sample were most frequently encountered with the relative abundances of 42%. SEM-EDX analysis of individual standard particles, such as PbO, PbS, $PbSO_4$, $PbCl_2$, and $PbCO_3$, was also performed to assist in the clear identification of lead-containing aerosol particles. Lead-containing particles were frequently associated with arsenic and zinc, indicating that the smelter had emitted those species during the non-ferrous metallurgical process. The frequently encountered particles following the lead-containing particles were mineral dust particles, such as aluminosilicates (denoted as AlSi), $SiO_2$, and $CaCO_3$. Nitrate- and sulfate-containing particles were encountered frequently in $2-4{\mu}m$ size range, and existed mostly in the forms of $Ca(NO_3,SO_4)/C$, $(Mg,Ca)SO_4/C$, and $AlSi+(NO_3,SO_4)$. Particles containing metals (e.g., Fe, Cu, and As) in this near source sample had relative abundances of approximately 10%. Although the airborne particles collected near the lead smelter contained elevated levels of lead, other types of particles, such as $CaCO_3$-containing, carbonaceous, metal-containing, nitrates, sulfates, and fly-ash particles, showed the unique signatures of samples influenced by emissions from the lead smelter.