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Huan Jing Ke Xue ; 40(10): 4412-4422, 2019 Oct 08.
Artigo em Chinês | MEDLINE | ID: mdl-31854808


A comparative analysis was conducted using total ozone products derived from monitoring atmospheric composition and climate (MACC) reanalysis data validated with ozone data from the atmospheric infrared sounder (AIRS) satellite and ground-based ozone measurements. The results indicate that the relative deviation of total ozone from the MACC reanalysis data and the ground-based ozone total data is controlled within 17%, and all of the correlation coefficients were between 0.79 and 0.97. The total ozone values from the MACC reanalysis data showed good consistency with the ground-based ozone measurements. With respect to the spatial distribution of multi-year averages, the relative deviation of total ozone values in the MACC reanalysis data and the AIRS satellite data was between -3% and 5%. The total ozone values in the MACC reanalysis data were higher than those from AIRS measurements for the Qinghai-Tibet Plateau and the coastal areas of South China, and were lower for northeast China. Furthermore, the seasonal variations in total ozone values in the MACC reanalysis data were consistent with AIRS data. At Mt. Waliguan station, the monthly averaged trends for near-surface ozone in the MACC reanalysis data were also consistent with surface ozone concentrations; the MACC reanalysis data reflect the observed trends for surface-based ozone measurements in spring, summer, and autumn, but show a large deviation in winter.

Huan Jing Ke Xue ; 40(1): 76-85, 2019 Jan 08.
Artigo em Chinês | MEDLINE | ID: mdl-30628261


Day-night PM2.5 samples were continuously collected in Chengdu from January 1 to 20, 2017, and the concentrations of major chemical components (water-soluble ions and carbonaceous components) were measured in the laboratory. During the observation period, the average mass concentration of PM2.5 was (127.1±59.9) µg·m-3. The mass concentration of water-soluble ions was (56.5±25.7) µg·m-3 and SO42-, NO3-, and NH4+ were the most dominant ions with a concentration of (13.6±5.5), (21.4±12.0), and (13.3±5.7) µg·m-3, respectively, accounting for 85.6% of the water-soluble ions. The average mass concentrations of organic carbon (OC) and elemental carbon (EC) were 34.0 and 6.1 µg·m-3, respectively, accounting for 26.8% and 4.8% of the PM2.5 mass concentration, respectively. The comparison of the average day-night concentration shows that the daytime and nighttime mass concentrations of PM2.5 are (120.4±56.4) and (133.8±64.0) µg·m-3, respectively, and that the nighttime pollution is more serious. The SO42-, NO3-, and NH4+ concentrations are higher during the day than at night, which is related to daytime light, which promotes the formation of secondary ions. The Cl-, K+, OC, and EC concentrations increase significantly, which may be affected by increased emissions from coal and material combustion. Based on the literature review and comparison of the winter chemical composition of PM2.5 in Chengdu in recent years, the SO42- concentration significantly decreases from 50.6 µg·m-3 in 2010 to 13.6 µg·m-3 in 2017. The NO3- concentration changes little; it is maintained at~20 µg·m-3. The analysis of the acid-alkali ion balance shows that PM2.5 in Chengdu is alkaline due to the relative overgrowth of NH4+, which is different from previous partially acidic results. The average value of NO3-/SO42- is 1.57. Mobile sources have a greater impact on the PM2.5 pollution in Chengdu in winter. The correlation coefficients of OC and EC between daytime and nighttime are 0.82 and 0.90, respectively (P<0.01), which indicates that the OC and EC sources are consistent. The SOC estimation shows that the SOC concentrations during the day and night are 8.5 µg·m-3 and 11.9 µg·m-3, respectively, accounting for 28.1% and 30.8% of the OC, respectively. The K+/EC average value is 0.31 and the correlation coefficient between K+ and OC is 0.87 (P<0.01), indicating that biomass combustion has a certain influence on the carbonaceous aerosol in Chengdu in winter. The principal component analysis shows that the winter PM2.5 in Chengdu mainly originates from combustion sources (coal burning, biomass burning, etc.), secondary inorganic sources, and soil and dust sources. The contribution rates are 32.8%, 34.5%, and 21.5%, respectively.

Huan Jing Ke Xue ; 39(3): 972-979, 2018 Mar 08.
Artigo em Chinês | MEDLINE | ID: mdl-29965439


Observed data regarding the visibility and aerosol chemical composition from May 2013 to May 2014 were used to analyze the variation of visibility, the relationship between aerosol chemical composition and visibility variations, and their contributions to atmospheric light extinction. An important effect of secondary inorganic salt extinction on the visibility impairment was determined. The present study suggests that the average visibility during the observation period was (6.78±3.68) km, and there was obvious seasonal variation in the visibility. Fine particles with size less than 2.1 µm have a great influence on visibility, with the main chemical components of SO42-, NO3-, NH4+, and OC. The secondary inorganic ions make significant contributions to visibility degradation. The mean light extinction coefficient of Nanjing was (527.2±295.2) Mm-1, which was calculated by using the revised IMPROVE equation. Regarding the chemical composition of PM2.1, the most contributive species to the light extinction coefficient were ammonium sulfate, ammonium nitrate, and organic species, which accounted for 80.6%. Although the light extinction contribution of organic matter was as high as 43.51% on a clear day (VR>10 km), with the decrease of visibility, the extinction contribution of organic matter decreased, but the contribution of secondary inorganic salt increased. The contribution of extinction was 58.96% for heavy haze days with low visibility (VR<5 km). This proves that the secondary inorganic salt extinction plays a significant role in visibility impairment.

Huan Jing Ke Xue ; 38(2): 476-484, 2017 Feb 08.
Artigo em Chinês | MEDLINE | ID: mdl-29964502


Based on the MODIS-Aqua aerosol optical depth (AOD) products from 2003 to 2014, Nighttime Lights Time data from DMSP satellites and basic meteorological data, the AOD spatial distributions of interannual and seasonal variations over three northeastern provinces of China(Liaoning, Jilin, Heilongjiang) were analyzed. It was found that there was a northeast-southwest area of high annual average AOD composed of Dalian, Shenyang, Changchun, Harbin and other cities, the 12-year average AOD value was 0.4-0.8. The low AOD occurred in the eastern and northern areas of the three northeastern provinces of China, where the forest-covering rate was high, and the 12-year average AOD value was less than 0.3. The seasonal variations of annual average AOD showed an increasing trend from spring to summer, then decreased in autumn and increased again in winter. The interannual variations of AOD over three northeastern provinces of China showed a decreasing trend in most areas, but the increasing trend occurred in the northeast-southwest region with the axis formed by Shenyang, Changchun and Harbin, revealing the polarization in recent 10 years over three northeastern provinces of China. In addition, spatial distribution of annual average AOD over three northeastern provinces of China in the years of strong and weak Western North Pacific Summer Monsoon was studied. Affected by the surface wind field, annual average AOD in weak monsoon years was higher than that in strong monsoon years.

Huan Jing Ke Xue ; 36(8): 2775-83, 2015 Aug.
Artigo em Chinês | MEDLINE | ID: mdl-26592003


Emission inventory of air pollutants is the key to understand the spatial and temporal distribution of atmospheric pollutants and to accurately simulate the ambient air quality. The currently established emission inventories are still limited on spatial and temporal resolution which greatly influences the numerical prediction accuracy of air quality. With coal-fired stationary sources considered, this study analyzed the total emissions and monthly variation of main pollutants from them in 2012 as the basic year, by collecting the on-line monitoring data for power plants and atmospheric verifiable accounting tables of Jiangsu Province. Emission factors in documents are summarized and adopted. Results indicated that the emission amounts of SO2, NOx, TSP, PM10, PM2.5, CO, EC, OC, NMVOC and NH3 were 106.0, 278.3, 40.9, 32.7, 21.7, 582.0, 3.6, 2.5, 17.3 and 2.2 kt, respectively. They presented monthly variation with high emission amounts in February, March, July, August and December and low emissions in September and October. The reason may be that more coal are consumed which leads to the increase of pollutants emitted, to satisfy the needs, of heat and electricity power supply in cold and hot periods. Local emission factors are needed for emission inventory studies and the monthly variation should be considered when emission inventories are used in air quality simulation.

Poluentes Atmosféricos/análise , Carvão Mineral , Monitoramento Ambiental , Centrais Elétricas , China , Análise Espaço-Temporal