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| 1 | Characteristics of one-year observation of VOCs,NOx, and O_3 at an urban site in Wuhan, China显示文摘A continuous online observation of ozone and its precursors(NOx, VOCs) was carried out in central urban Wuhan from September 2016 to August 2017. The concentration levels of ozone,NOx, VOCs and their variations in urban Wuhan were analyzed, as well as effects of VOCs on ozone photochemical generation and the main controlling factors for ozone production. During the observation period, the average concentrations of ozone and NOx in Wuhan was 22.63 and30.14 ppbv, respectively, and the average concentration of VOCs was 32.61 ppbv(42.3% alkanes,13.0% alkenes, 10.0% aromatics, 7.3% acetylene, 9.9% OVOCs, and 10.5% halohydrocarbons).Ozone concentration was higher in spring and summer as compared with autumn and winter,wheras VOCs and NOx concentratios were lower in spring and summer but higher in autumn and winter. Aromatics and alkenes, two of VOCs species, showed the highest contributions to ozone formation potential in Wuhan(35.7% alkenes, 35.4 aromatics, 17.5% alkanes, 8.6% OVOCs,1.6% halogenated hydrocarbons, and 1.4% acetylene). Among all VOCs species, those with the highest contribution were ethylene, m-xylene, toluene, propylene and o-xylene. The contribution of these five compounds to the total ozone formation potential concentration was 43.90%.Ozone-controlling factors in Wuhan changed within one day; during the early morning hours(6:00–9:00), VOCs/NOx was low, and ozone generation followed a VOCs-limited regime.However, during the peak time of ozone concentration(12:00–16:00), the ratio of VOCs/NOx was relatively high, suggesting that ozone generation followed a NOx-limited regime. | Yichang Yang Xingang Liu Jun Zheng Qinwen Tan Miao Feng Yu Qu Junling An Nianliang Cheng | 2019 | Journal of Environmental Sciences2019，31，5： | 26 |
| 2 | Overview of Urban PM_(2. 5) Numerical Forecast Models in China显示文摘This paper made an overview and introduction of urban PM_(2. 5)numerical forecast models in China,and mainly introduced air quality simulated forecast system of Beijing,Shanghai,and Nanjing. On this basis,it discussed development direction and existing problems of urban PM_(2. 5)forecast models in China. Besides,it revealed significance of numerical models for air quality forecast. In a heavy air pollution of Beijing- Tianjin- Hebei in October 6- 12 th of 2014,the forecast results indicated that pollutants was transported from south to north,so the regional transport exerts great influence on concentration of PM_(2. 5). | Nianliang CHENG Hongxia LI Fan MENG Fahe CHAI | 2015 | Asian Agricultural Research2015，7，10： | 4 |
| 3 | Aerosol optical properties under different pollution levels in the Pearl River Delta(PRD) region of China显示文摘To clarify the aerosol hygroscopic growth and optical properties of the Pearl River Delta(PRD)region,integrated observations were conducted in Heshan City of Guangdong Province from October 19 to November 17,2014.The concentrations and chemical compositions of PM2.5,aerosol optical properties and meteorological parameters were measured.The mean value of PM2.5 increased from less than 35(excellent)to 35-75μg/m^3(good)and then to greater than 75μg/m^3(pollution),corresponding to mean PM2.5 values of 24.9,51.2,and 93.3μg/m^3,respectively.The aerosol scattering hygroscopic growth factor(f(RH=80%))values were 2.0,2.12,and 2.18 for the excellent,good,and pollution levels,respectively.The atmospheric extinction coefficient(σext)and the absorption coefficient of aerosols(σap)increased,and the single scattering albedo(SSA)decreased from the excellent to the pollution levels.For different air mass sources,under excellent and good levels,the land air mass from northern Heshan had lower f(RH)andσsp values.In addition,the mixed aerosol from the sea and coastal cities had lower f(RH)and showed that the local sources of coastal cities have higher scattering characteristics in pollution periods. | Liuwei Kong Min Hu Qinwen Tan Miao Feng Yu Qu Junling An Yuanhang Zhang Xingang Liu Nianliang Cheng | 2020 | Journal of Environmental Sciences2020，32，1： | 3 |
| 4 | A framework for investigating the air quality variation characteristics based on the monitoring data: Case study for Beijing during 2013–2016显示文摘In this study, an analysis framework based on the regular monitoring data was proposed for investigating the annual/inter-annual air quality variation and the contributions from different factors(i.e., seasons, pollution periods and airflow directions), through a case study in Beijing from 2013 to 2016. The results showed that the annual mean concentrations(MC) of PM_(2.5), SO_2, NO_2 and CO had decreased with annual mean ratios of 7.5%, 28.6%, 4.6%and 15.5% from 2013 to 2016, respectively. Among seasons, the MC in winter contributed the largest fractions(25.8%~46.4%) to the annual MC, and the change of MC in summer contributed most to the inter-annual MC variation(IMCV) of PM_(2.5) and NO2. For different pollution periods, gradually increase of frequency of S-1(PM_(2.5), 0~ 75 μg/m^3) made S-1 become the largest contributor(28.8%) to the MC of PM_(2.5) in 2016, it had a negative contribution(-13.1%) to the IMCV of PM_(2.5); obvious decreases of frequencies of heavily polluted and severely polluted dominated(44.7% and 39.5%) the IMCV of PM_(2.5). For different airflow directions, the MC of pollutants under the south airflow had the most significant decrease(22.5%~62.5%), and those decrease contributed most to the IMCV of PM_(2.5)(143.3%),SO2(72.0%), NO_2(55.5%) and CO(190.3%); the west airflow had negative influences to the IMCV of PM_(2.5), NO_2 and CO. The framework is helpful for further analysis and utilization of the large amounts of monitoring data; and the analysis results can provide scientific supports for the formulation or adjustment of further air pollution mitigation policy. | Jixian Cui Jianlei Lang Tian Chen Shushuai Mao Shuiyuan Cheng Zhanshan Wang Nianliang Cheng | 2019 | Journal of Environmental Sciences2019，31，7： | 2 |
| 5 | Study on the Current Situation and Source Apportionment of PM_(2.5) Pollution in China显示文摘In this paper,using concentration data of PM2. 5in 2013 in China and referring to a lot of literature,we preliminary studied the pollution of fine particulate matter and summarized PM2. 5source apportionment in the key cities in China. Our results showed that PM2. 5showed significant spatial and temporal distribution; high surface concentrations of PM2. 5concentrated mainly in the North China Plain,the Sichuan Basin,Yangtze River Delta and other regions; the average annual concentration of PM2. 5was about 80μg / m3 in North China Plain; Seasonal changes in the concentration of PM2. 5was winter > spring > autumn > summer; fired sources,industrial sources,vehicle exhaust were the major sources of PM2. 5; motor vehicle exhaust mostly contributed 10%- 30% to PM2. 5. This review provides a fundamental understanding of PM2. 5source apportionment and serves as an important reference for future source apportionment studies to be widely conducted in China. | Nianliang CHENG Shangyin GAO Yunting LI Bingfen CHENG Kuikui YUAN | 2015 | Asian Agricultural Research2015，7，1： | 1 |
| 6 | Impact of China's SO_2 Emissions on SO_2 Concentration and Sulfur Deposition in Japan显示文摘Based on the monitored data of references,EANET and the CMAQ( 4. 7. 1) model scenario simulations,the annual average concentration of SO2 in China in the recent 10 years and the contribution of China's SO2 emissions to SO2 concentration and sulfur deposition at various sites in Japan downwind were analyzed. The results showed that from 2001 to 2009 annual average concentration of SO2 was 0- 150 μg / m3 and showed a decreasing trend on the whole in China. The correlation coefficient of annual average concentration of SO2 at different sites in Japan and China's SO2 emissions was lower than that of annual average concentration and emission of SO2 in China's cities on the whole,showing that SO2 discharged in China had small impact on SO2 concentration in Japan. The contribution rate of China's SO2 emissions to annual average concentration of SO2 at various sites in Japan in 2010 was 7. 5%- 44. 0%,averaging 22. 6%; the annual average volume concentration of SO2 at different sites in Japan caused by China's SO2 emissions was 0- 0. 5 × 10- 9. The contribution rate of China's SO2 emissions to sulfur deposition at various sites in Japan in 2010 varied from 8. 0% to 41. 0%,averaging 22. 1%. | Liu Yanyan Cheng Nianliang Li Junjie Luo Yueping | 2015 | Meteorological and Environmental Research2015，6，5： | 0 |
| 7 | Comparisons of two serious air pollution episodes in winter and summer in Beijing显示文摘Characteristics of two serious air pollution episodes(9–15 January, as the winter case; and30 June to 1 July, as the summer case), which occurred in Beijing in 2013 were investigated and compared using multi-method observations and numerical simulations. During these two air pollution episodes, PM_(2.5) concentrations varied significantly within Beijing, with PM_(2.5) concentrations in southern parts of Beijing being significantly higher than in northern areas. Typically, heavy air pollution episodes begin in the southern parts and disperse towards the northern parts of Beijing. Clearly, synoptic patterns and the stability of atmospheric circulation patterns were the main factors controlling air pollution in Beijing.During the winter case, a warm center above 900 h Pa occurred over Beijing. Meanwhile, in the summer case, although there was only a weak inversion, the convective inhibition energy was strong(over 200 J/k G). This clearly influenced the duration of the air pollution event. Except for the local accumulation and secondary atmospheric reactions in both cases, regional straw burnings contributed a lot to the PM_(2.5) concentrations in summer case.Using the CAMxmodel, we established that regional transport contributed almost 59% to the PM_(2.5) averaged concentration in Beijing in the winter case, but only 31% in the summer case. Thus, the winter case was a typical regional air pollution episode, while the summer case resulted from local accumulation straw burnings transportation and strong secondary atmospheric reactions. Given that air pollution is a regional problem in China, consistent and simultaneous implementation of regional prevention and control strategies is necessary to improve regional air quality. | Nianliang Cheng Yunting Li Bingfen Cheng Xin Wang Fan Meng Qin Wang Qihong Qiu | 2018 | Journal of Environmental Sciences2018，30，7： | 0 |
| 8 | ‘Aerosol optical properties under different pollution levels in the pearl river delta(PRD)region of China’J.Environ.Sci.87(2020)49–59显示文摘The authors regret | Liuwei Kong Min Hu Qinwen Tan Miao Feng Yu Qu Junling An Yuanhang Zhang Xingang Liu Nianliang Cheng | 2021 | Journal of Environmental Sciences2021，33，6： | 0 |
| 9 | Numerical Simulation of Distribution and Deposition of PM_(2. 5) in Eastern China in 2010显示文摘The spatial distribution and deposition of PM_(2. 5) in coastal areas of eastern China in 2010 were simulated using the CMAQ model. The results show that the simulated data were consistent with the observed data,and the model could simulate the regional distribution of PM_(2. 5) concentration. There were obvious seasonal variations in PM_(2. 5) concentration in eastern China,and the spatial distribution of PM_(2. 5) concentration which increased from the edge to the center of a city coincided well with that of the sources. In North China,the high-value center of PM_(2. 5) concentration reached above 120 μg/m^3. Wet deposition was the main way to remove PM_(2. 5) ,and wet deposition flux of PM_(2. 5) was at least five times more than that of the dry deposition flux. Deposition flux of PM_(2. 5) was the largest in summer,while it was the smallest in winter. The high-value center of deposition flux of PM_(2. 5) in eastern China exceeded 30 mg /( m^2·d). Wet deposition of PM_(2. 5) in each province or region accounted for more than 91% of total deposition of PM_(2. 5) . Total deposition of PM_(2. 5) in all simulated regions amounted to 4. 67 × 10~6 t/a,and total deposition of PM_(2. 5) in Beijing,Tianjin and Hebei was up to 1. 65 × 10~6 t/a. | Cheng Nianliang Wang Xiao Feng Yu | 2015 | Meteorological and Environmental Research2015，6，7： | 0 |
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