[Pollution Characteristics of Carbonaceous Components in PM10 and PM2.5 of Road Dust Fall and Soil Dust in Xi'an].

To investigate the pollution characteristics of carbonaceous components in PM10 and PM2.5 of road dust fall and soil dust in Xi'an and enrich their source profiles, samples from five sites of road dust fall and 16 sites of soil dust were collected in Xi'an from April to May 2015. The ZDA-CY01 particulate matter resuspension sampler was used to obtain PM10 and PM2.5 samples, and the Model5L-NDIR OC and EC analyzer were used to determine the concentrations of organic carbon (OC) and elemental carbon (EC) in PM10 and PM2.5. The pollution and sources of carbonaceous aerosol in PM10 and PM2.5 were investigated by analyzing OC and EC characteristics, ratio, and the principal component analysis statistical model. The results showed that the proportions of OC in PM10 and PM2.5 at the various dust fall sites differed, ranging from 6.0% to 19.4% and 7.6% to 29.8%, respectively. The ratios of EC in PM10 and PM2.5at the different dust fall sites were relatively small, accounting for 0.6%-2.2% and 0.2%-3.6% in urban sites, respectively; however, EC was almost undetectable in most peripheral soil dust. The proportions of carbonaceous components in PM10 and PM2.5 followed the order of urban road dust fall>external control dust>river beach soil dust>soil dust and urban road dust fall>soil dust>external control dust>river beach soil dust, respectively. OC dominated the carbonaceous aerosols at the different sites, which was relatively low in urban road dust fall. The OC to total carbon (TC) ratios in PM10 and PM2.5 at urban road dust fall were 85.2%-95.3% and 87.9%-98.9%, respectively. The OC to TC ratios in PM10 and PM2.5 of soil dust were relatively high, exceeding 99%. Carbonaceous components were primarily concentrated in fine particles. The pollution distribution of carbonaceous components in the urban road dust fall sites was consistent, whereas that in the different soil dust sites were quite different. The carbonaceous components in urban road dust fall and soil dust were primarily affected by pollutant source emissions such as biomass burning, coal burning, gasoline, and diesel vehicle exhaust. There were differences in the source contribution rates of carbonaceous aerosols in PM10 and PM2.5.

[Characteristics and Source Apportionment of Black Carbon Over the Eastern Tibetan Plateau].

As the most important absorbing aerosol, black carbon (BC) can affect radiation, clouds, and surface snow cover over the Tibetan Plateau. In this study, the BC mass concentrations were measured using a seven-channel aethalometer (AE-33) in Litang County over the eastern Tibetan Plateau from July 5 to September 5, 2017. The aethalometer model, potential source contribution function (PSCF), and concentration-weighted trajectory (CWT) models were used to analyze the variation characteristics, potential sources, and affecting areas of BC. The results showed that the mass concentration of ρ(BC) in Litang ranged from 0.4 to 4699.8 ng·m-3, with an average value of 816.4 ng·m-3, accounting for 5.96% of PM2.5. The average mass concentrations of ρ(BCliquid) and ρ(BCsolid) in Litang were 486.1 ng·m-3 and 398.5 ng·m-3, respectively, with a C of 0.51. The ρ(BC) mass concentration was mainly distributed from 0-2000 ng·m-3, which accounted for 92.5% of the total observation period. The diurnal variation in BC, BCliquid, and BCsolid showed a bimodal distribution, with the peaks appearing at 08:00 and 20:00, respectively. The first peak was mainly related to traffic sources and incomplete combustion of carbonaceous materials, whereas the second peak was mainly related to incomplete combustion of carbonaceous materials. The potential sources and affecting areas of PM2.5 and BC were different. Imports from abroad had a greater impact on the concentrations of PM2.5 and BC in Litang, and the affecting areas were mainly transmitted to the northeast in China. The high-value centers were mainly concentrated in the surrounding areas of Litang.

[Emission Characteristics of Organic Carbon and Elemental Carbon in PM10 and PM2.5 from Vehicle Exhaust and Civil Combustion Fuels].

To study the emission characteristics of carbonaceous aerosol in particulate matter emitted from vehicle exhaust and main civil combustion fuels, organic carbon (OC) and elemental carbon (EC) in PM10 and PM2.5 samples from vehicle sources (gasoline vehicles, light duty diesel vehicles, and heavy duty diesel vehicles), civil coal (chunk coal and briquette coal), and biomass fuels (wheat straw, wood plank, and grape branches) were collected and analyzed by using a multifunctional portable dilution channel sampler and the Model 5L-NDIR OC/EC analyzer. The results showed that there were significant differences in the proportion of carbonaceous aerosols in PM10 and PM2.5from different emission sources. The proportions of total carbon (TC) in PM10 and PM2.5 of different emission sources were 40.8%-68.5% and 30.5%-70.9%, respectively, and the OC/EC were 1.49-31.56 and 1.90-87.57, respectively. The carbon components produced by different emission sources were dominated by OC, and the OC/TC values in PM10 and PM2.5 were 56.3%-97.0% and 65.0%-98.7%, respectively. The proportions of OC in carbonaceous aerosols in PM10and PM2.5 were in the descending order of:briquette coal>chunk coal>gasoline vehicle>wood plank>wheat straw>light duty diesel vehicle>heavy duty diesel vehicle and briquette coal>gasoline car>grape branches>chunk coal>light duty diesel vehicle>heavy duty diesel vehicle, respectively. The main components of carbonaceous aerosols in PM10 and PM2.5 emitted from the various emission sources were different, and source apportionment of carbonaceous aerosols could be accurately distinguished by their ingredient composition profiles.

Local Corrosion Behaviors in the Coarse-Grained Heat-Affected Zone in a Newly Developed Zr-Ti-Al-RE Deoxidized High-Strength Low-Alloy Steel.

Oxide metallurgy technology can improve the microstructure of a coarse-grained heat-affected zone (CGHAZ) but introduces extra inclusions. Local corrosion behavior of the CGHAZ of a Zr-Ti-Al-RE deoxidized steel was investigated in this work using theoretical calculations and experimental verification. The modified inclusions have a (Zr-Mg-Al-Ca-RE)Ox core claded by a CaS and TiN shell. CaS dissolves first, followed by the oxide core, leaving TiN parts. This confirms that the addition of rare earth can reduce lattice distortion and prevent a galvanic couple between the inclusions and the matrix, while the chemical dissolution of CaS causes localized acidification, resulting in the pitting corrosion initiation.

[Temporal and Spatial Variations in Black Carbon Aerosol in Different Atmospheric Background Stations in China from 2006 to 2020].

Black carbon (BC) aerosol emissions are complex and have important environmental and meteorological effects. In China, the temporal and spatial variations in BC in different atmospheric environmental conditions need to be fully understood. Based on the long-term observational BC data in seven atmospheric background stations in China from 2006 to 2020, combined with meteorological data, emission source data, enhanced vegetation index (EVI) data, and aerosol optical depth (AOD) data, we comprehensively analyzed the characteristics of temporal and spatial variations, long-term evolution, and influencing factors of BC in China. The results showed that the BC and AOD values of different atmospheric environments in China were quite different, and BC positively contributed to AOD. The spatial distribution was high in the east and low in the west owing to the differences in emission sources and meteorological conditions. The ρ(BC) and AOD values were higher to the east of the "Hu Huanyong" line, such as at the Mt. Longfeng, Shangdianzi, Lin'an, and Jinsha stations, where the average values were (1699±2213)-(3392±2131) ng·m-3 and 0.36±0.32-0.72±0.37, respectively. These values were lower to the west of the "Hu Huanyong" line, such as at the Akedala, Mt. Waliguan, and Shangri-La stations, where the average values were (287±226)-(398±308) ng·m-3 and 0.20±0.13-0.22±0.19, respectively. The interannual variability in BC included differences between different atmospheric background stations, which could be divided into four categories:low interannual variability, such as at the Akedala station; an initial increase followed by a decrease and subsequent stabilization, such as at the Mt. Waliguan station; an initial decrease followed by stabilization, such as at the Shangri-La station; and an initial stabilization followed by a decrease, such as at the Mt. Longfeng, Shangdianzi, Jinsha, and Lin'an stations. Seasonal variations in BC included differences in different atmospheric background stations. The BC mass concentrations were lowest in autumn and higher in winter and spring west of the "Hu Huanyong" line and were highest in winter and lowest in summer east of the "Hu Huanyong" line. BC contributed to the AOD being larger in all stations in the spring and summer and contributed less at the stations west of the "Hu Huanyong" line in autumn and the stations east of the "Hu Huanyong" line in winter. The diurnal variations in BC were mainly bimodally distributed in the different atmospheric background stations, but the peak times varied in different stations and seasons.

[Characteristics of Atmospheric Particulate Matter Pollution and the Unique Wind and Underlying Surface Impact in the Twain-Hu Basin in Winter].

To understand the recent characteristics of atmospheric environmental changes in the Twain-Hu(Hunan-Hubei) Basin, including the middle reaches of the Yangtze River, this paper uses near-surface PM2.5 and PM10 observational data for the Twain-Hu Basin in the winters of 2015 to 2019, combined with wind-speed, topography, the normalized difference vegetation index(NDVI), and other datasets. The results show that:① PM2.5 pollution occurred frequently in the winters of 2015-2019 in the Twain-Hu Basin, and Xiangyang and Jingmen in the western part of the basin, experience PM2.5 pollution on an average of 62 and 61 days in winter(PM2.5>75 µg·m-3). And the heavy pollution days in Xiangyang reached 19 more days(PM2.5>150 µg·m-3), indicating that the Twain-Hu Basin is an air pollution center in the middle reaches of the Yangtze River Basin; ② Spatially, pollution in the Twain-Hu Basin is heavier in the northwest than in the southeast, and in the urban agglomeration, which is mainly related to the regional transport of air pollutants by the winter monsoon and the high levels of emissions from urban areas; ③ A "U-shaped" nonlinear relationship was observed between near-surface wind speeds and PM2.5 and PM10 concentrations. The inflection points of PM2.5 and PM10 concentrations were 153 and 210 µg·m-3, respectively. This implies that the accumulation of local atmospheric particulate matter in the Twain-Hu Basin dominates light/medium pollution, while the regional transport of air pollutants dominates period of severe pollution; and ④ PM2.5 and PM10 in winter were significantly negatively correlated with terrain height and the NDVI, which reflects the atmospheric environmental effects of topography and urbanization.

[Evaluation of MACC Reanalysis Ozone Data over China Using Ground-based and AIRS Satellite Observations].

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.

[Analysis of Pollution Characteristics and Sources of PM2.5 Chemical Components in Chengdu in Winter].

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.

[Important Effect of Secondary Inorganic Salt Extinction on Visibility Impairment in the Northern Suburb of Nanjing].

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.

[Variations in Aerosol Optical Depth over Three Northeastern Provinces of China, in 2003-2014].

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.

[Analysis on Emission Inventory and Temporal-Spatial Characteristics of Pollutants from Key Coal-Fired Stationary Sources in Jiangsu Province by On-Line Monitoring Data].

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.