Abstract. Shanghai, with a population of over 20 million, is the largest mega-city in China. Rapidly increasing industrial and metropolitan emissions have deteriorated its air quality in the past decades, with fine particle pollution as one of the major issues. However, systematic characterization of atmospheric fine particles with advanced measurement techniques has been very scarce in Shanghai. During 2010 Shanghai World Expo, we deployed a high-resolution time-of-flight aerosol mass spectrometer (HR-ToF-AMS) and a single particle soot photometer (SP2) in urban Shanghai between 15 May and 10 June 2010 to measure fine particles with a high time resolution. The 4-min resolution PM1 mass concentration ranged from 5.5 to 155 μg m−3, with an average of 29.2 μg m−3. On average, sulfate and organic matter (OM) were the most abundant PM1 components, accounting for 33.3 and 28.7% of the total mass, respectively, while the fraction of nitrate showed an increasing trend with the increasing PM1 loading, indicating the photochemical nature of high fine particle pollution in Shanghai. Taking advantage of HR-ToF-AMS and SP2, OM was found to have an average OM/OC ratio (organic matter mass/organic carbon mass) of 1.55 and black carbon (BC) had an average number fraction of internally mixed BC of 41.2%. Positive matrix factorization (PMF) analysis on the high resolution organic mass spectral dataset identified a hydrocarbon-like (HOA), a semi-volatile oxygenated (SV-OOA), and a low-volatility oxygenated (LV-OOA) organic aerosol component, which on average accounted for 24.0, 46.8, and 29.2% of the total organic mass, respectively. The diurnal patterns of them with interesting time delay possibly implied a photochemical oxidizing process from HOA (and/or its concurrently emitted gaseous organic pollutants) to SV-OOA to LV-OOA. Back trajectory analysis indicated that the northwesterly continental air mass represented the most severe pollutant regional transport condition with the highest nitrate and SV-OOA fractions. In addition, the results in Shanghai were compared with similar measurements performed recently in other mega-cities in the world.
Abstract. The strong spectral dependence of light absorption of brown carbon (BrC) aerosol is regarded to influence aerosol's radiative forcing significantly. The Absorption Angstrom Exponent (AAE) method was widely used in previous studies to attribute light absorption of BrC at shorter wavelengths for ambient aerosol, with a theoretical assumption that the AAE of "pure" black carbon (BC) aerosol equals to 1.0. In this study, the previous AAE method was improved by statistical analysis and applied in both urban and rural environments in the Pearl River Delta (PRD) region of China. A three-wavelength photo-acoustic soot spectrometer (PASS-3) and aerosol mass spectrometers (AMS) were used to explore the relationship between the measured AAE and the relative abundance of organic aerosol to BC. The regression and extrapolation analysis revealed that the more realistic AAE values for "pure" BC aerosol were 0.86, 0.82, and 1.02 at 405 nm, and 0.70, 0.71, and 0.86 at 532 nm, in the campaigns of urban_winter, urban_fall, and rural_fall, respectively. Roadway tunnel experiments were also conducted, and the results further supported the representativeness of the obtained AAE values for "pure" BC aerosol in the urban environments. Finally, the average aerosol light absorption contribution of BrC was quantified to be 11.7, 6.3, and 12.1 % (with relative uncertainties of 4, 4, and 7 %) at 405 nm, and 10.0, 4.1, and 5.5 % (with relative uncertainties of 2, 2, and 5 %) at 532 nm, in the campaigns of urban_winter, urban_fall, and rural_fall, respectively. The relatively higher BrC absorption contribution at 405 nm in the rural_fall campaign was likely a result of the biomass burning events nearby, which was supported by the biomass burning simulation experiments performed in this study. The results of this paper indicate that the brown carbon contribution to aerosol light absorption at shorter wavelengths is not negligible in the highly urbanized and industrialized PRD region.
In order to study how to better suppress image noise, improve image resolution, and enhance the visual effect of images, three-dimensional joint filtering – block matching (BM3D) algorithm is used to explore image denoising and image detail retention, and in image denoising, sparse expression and low rank recovery theory are introduced. The results show that BM3D algorithm has a good effect in removing Gaussian white noise, but it is lacking in suppressing impulse noise and mixed noise. The non-local BM3D algorithm is superior to sparse expression and low rank recovery in removing Gaussian white noise, but sparse expression and low rank recovery has a good effect in removing impulse noise.
Abstract. Highly time-resolved in-situ measurements of airborne particles were made at Mt. Yulong (3410 m above sea level) on the southeastern edge of the Tibetan Plateau in China from 20 March to 14 April in 2015. Detailed chemical composition was measured by a high-resolution time-of-flight aerosol mass spectrometer together with other online instruments. Average mass concentration of the submicron particles (PM1) was 5.7 ± 5.4 μg m−3 during the field campaign, ranging from 0.1 μg m−3 up to 33.3 μg m−3. Organic aerosol (OA) was the dominant component in PM1, with a fraction of 68 %. Three OA factors, i.e., biomass-burning organic aerosol (BBOA), biomass-burning-influenced oxygenated organic aerosol (OOA-BB) and oxygenated organic aerosol (OOA), were resolved using positive matrix factorization analysis. The two oxygenated OA factors accounted for 87 % of the total OA mass. Three biomass burning events were identified by examining the enhancement of black carbon concentrations and the f60 (the ratio of the signal at m/z 60 from the mass spectrum to the total signal of OA). Back trajectories of air masses and satellite fire map data were integrated to identify the biomass burning locations and pollutants transport. The western air mass from Southeast Asia with active biomass burning activities transported large amount of air pollutants, resulting in elevated organic concentrations up to 4-fold higher than that of the background condition. This study at Mt. Yulong characterizes the tropospheric background aerosols of the Tibetan Plateau during pre-monsoon season, and provides clear evidence that the southeastern edge of the Tibetan Plateau is affected by transport of anthropogenic aerosols from Southeast Asia.
Abstract. The Pearl River Delta (PRD) of China, which has a population of more than 58 million people, is one of the largest agglomerations of cities in the world and ever experienced severe PM2.5 pollution at the beginning of this century. Due to the implementation of strong pollution control in recent decades, PM2.5 in the PRD has continuously decreased to relatively lower levels in China. To comprehensively understand the current PM2.5 sources in the PRD to support future air pollution control strategy in similar regions, we performed regional-scale PM2.5 field observations coupled with a state-of-the-art source apportionment model at six sites in four seasons in 2015. The regional annual average PM2.5 concentration was determined to be 37 μg/m3, which is still more than three times the WHO standard, with organic matter (36.9 %) and SO4−2 (23.6 %) as the most abundant species. A novel multilinear engine (ME-2) model was then applied to the PM2.5 dataset in the PRD to perform source apportionment with predetermined constraints, which produced more environmentally meaningful results compared to those obtained using traditional positive matrix factorization (PMF) modeling. The regional annual average PM2.5 source structure was retrieved to be secondary sulfate (21 %), vehicle emissions (14 %), industrial emissions (13 %), secondary nitrate (11 %), biomass burning(11 %), secondary organic aerosol (SOA, 7 %), coal burning (6 %), fugitive dust (5 %), ship emissions (3 %) and aged sea salt (2 %). Analyzing the spatial distribution of PM2.5 sources under different weather conditions clearly identified the central PRD area as the key emission area for SO2, NOx, coal burning, biomass burning, industrial emissions and vehicle emissions. It was further estimated that under the polluted northerly air flow in winter, local emissions in the central PRD area accounted for approximately 45 % of the total PM2.5, with secondary nitrate and biomass burning being most abundant; in contrast, the regional transport from outside the PRD accounted for more than half of PM2.5, with secondary sulfate representing the most abundant transported species.
'/%3e%3cuse xlink:href='%23a' transform='rotate(23.036 .093 25.536)'/%3e%3cuse xlink:href='%23a' transform='rotate(45.87 1.273 16.18)'/%3e%3cuse xlink:href='%23a' transform='rotate(69.945 .996 12.078)'/%3e%3cuse xlink:href='%23a' transform='rotate(20.66 -19.689 31.932)'/%3e%3c/svg%3e)