Seasonal variations of anhydrosugars in PM2.5 in the Pearl River Delta Region, China

Anhydrosugars including levoglucosan and mannosan are the most effective organic tracers for biomass burning aerosol in the atmosphere. In this study, to investigate the contribution of biomass burning emissions to the aerosol burden in the Pearl River Delta (PRD) region, China, 24-hour integrated PM2.5 samples were collected simultaneously at four locations, (i) Guangzhou (GZ), (ii) Zhaoqing (ZQ) in Guangdong province, (iii) Hok Tsui (HT) and (iv) Hong Kong Polytechnic University (PU) in Hong Kong, in four seasons between 2006 and 2007. Levoglucosan and mannosan, together with water-soluble inorganic ions and water-soluble organic carbon (WSOC), were determined to elucidate the seasonal and spatial variations in biomass burning contributions. The concentrations of levoglucosan and mannosan were on average 82.4±123 and 5.8±8.6 ng m−3, respectively. The WSOC concentrations ranged from 0.2 to 9.4 µg m−3, with an average of 2.1±1.6 µg m−3. The relative contributions of biomass burning emissions to OC were 33% in QZ, 12% in GZ, 4% at PU and 5% at HT, respectively, estimated by the measured levoglucosan to organic carbon ratio (LG/OC) relative to literature-derived LG/OC values. The contributions from biomass burning emissions were in general 1.7–2.8 times higher in winter than those in other seasons. Further, it was inferred from diagnostic tracer ratios that a significant fraction of biomass burning emissions was derived from burning of hard wood and likely also from field burning of agricultural residues, such as rice straw, in the PRD region. Our results highlight the contributions from biomass/biofuel burning activities on the regional aerosol budget in South China

A possible pathway for rapid growth of sulfate during haze days in China

Rapid industrialization and urbanization have caused frequent occurrence of haze in China during wintertime in recent years. The sulfate aerosol is one of the most important components of fine particles (PM[subscript 2. 5]) in the atmosphere, contributing significantly to the haze formation. However, the heterogeneous formation mechanism of sulfate remains poorly characterized. The relationships of the observed sulfate with PM[subscript 2. 5], iron, and relative humidity in Xi'an, China have been employed to evaluate the mechanism and to develop a parameterization of the sulfate heterogeneous formation involving aerosol water for incorporation into atmospheric chemical transport models. Model simulations with the proposed parameterization can successfully reproduce the observed sulfate rapid growth and diurnal variations in Xi'an and Beijing, China. Reasonable representation of sulfate heterogeneous formation in chemical transport models considerably improves the PM2. 5 simulations, providing the underlying basis for better understanding the haze formation and supporting the design and implementation of emission control strategies

Brown Carbon Aerosol in Urban Xi’an, Northwest China: TheComposition and Light Absorption Properties

Light-absorbing organic carbon (i.e., brown carbon or BrC) in the atmospheric aerosol has significant contribution to light absorption and radiative forcing. However, the link between BrC optical properties and chemical composition remains poorly constrained. In this study, we combine spectrophotometric measurements and chemical analyses of BrC samples collected from July 2008 to June 2009 in urban Xi'an, Northwest China. Elevated BrC was observed in winter (5 times higher than in summer), largely due to increased emissions from wintertime domestic biomass burning. The light absorption coefficient of methanol-soluble BrC at 365 nm (on average approximately twice that of water-soluble BrC) was found to correlate strongly with both parent polycyclic aromatic hydrocarbons (parent-PAHs, 27 species) and their carbonyl oxygenated derivatives (carbonyl-OPAHs, 15 species) in all seasons (r(2) > 0.61). These measured parent-PAHs and carbonyl-OPAHs account for on average similar to 1.7% of the overall absorption of methanol-soluble BrC, about 5 times higher than their mass fraction in total organic carbon (OC, similar to 0.35%). The fractional solar absorption by BrC relative to element carbon (EC) in the ultraviolet range (300-400 nm) is significant during winter (42 +/- 18% for water-soluble BrC and 76 +/- 29% for methanol-soluble BrC), which may greatly affect the radiative balance and tropospheric photochemistry and therefore the climate and air quality

Contributions of residential coal combustion to the air qualityin Beijing–Tianjin–Hebei (BTH), China: a case study

In the present study, the WRF-Chem model is used to assess contributions of residential coal combustion (RCC) emissions to the air quality in Beijing-Tianjin-Hebei (BTH) during a persistent air pollution episode from 9 to 25 January 2014. In general, the predicted temporal variations and spatial distributions of the mass concentrations of air pollutants are in good agreement with observations at monitoring sites in BTH. The WRF-Chem model also reasonably reproduces the temporal variations in aerosol species when compared with the aerosol mass spectrometer measurements in Beijing. The RCC emissions play an important role in the haze formation in BTH, contributing about 23.1% of PM2.5 (fine particulate matter) and 42.6% of SO2 during the simulation period on average. Organic aerosols dominate the PM2.5 from the RCC emissions in BTH, with a contribution of 42.8 %, followed by sulfate (17.1 %). The air quality in Beijing is remarkably improved when the RCC emissions in BTH and the surrounding areas are excluded in model simulations, with a 30% decrease in PM2.5 mass concentrations. However, if only the RCC emissions in Beijing are excluded, the local PM2.5 mass concentration is decreased by 18.0% on average. Our results suggest that the implementation of the residential coal replacement by clean energy sources in Beijing is beneficial to the local air quality. Should residential coal replacement be carried out in BTH and its surrounding areas, the air quality in Beijing would be improved remarkably. Further studies would need to consider uncertainties in the emission inventory and meteorological fields

A Study of Chinese-Style Management in the Twenty-First Century

Management is a science imbued with practicality. Chinese society is striving to maintain harmony while undergoing construction. This unprecedented venture has enormous implications for management in the broadest sense. Chinese-style management in the twenty-first century is based on 5,000 years of history and culture in China. The He-he philosophy is a basic guiding principle and an important historical model. He-he management works on the principle of making the past serve the present, and making foreign things serve China. It is a managerial science that brings together the reality of China's reforms and opening-up to a market economy, useful aspects of foreign managerial thought and practice, and the enduring characteristics of China's ancient cultural heritage.

Impact of city lockdown on the air quality of COVID-19-hit of Wuhan city

A series of strict lockdownmeasures were implemented in the areas of China worst affected by coronavirus disease 19, including Wuhan, to prevent the disease spreading. The lockdown had a substantial environmental impact, because traffic pollution and industrial emissions are important factors affecting air quality and public health in the region. After the lockdown, the average monthly air quality index (AQI) in Wuhan was 59.7, which is 33.9% lower than that before the lockdown(January 23, 2020) and 47.5% lower than that during the corresponding period (113.6) from 2015 to 2019. Compared with the conditions before the lockdown, fine particulate matter (PM2.5) decreased by 36.9% and remained the main pollutant. Nitrogen dioxide (NO2) showed the largest decrease of approximately 53.3%, and ozone (O-3) increased by 116.6%. The proportions of fixed-source emissions and transported external-source emissions in this area increased. After the lockdown, O-3 pollution was highly negatively correlated with the NO2 concentration, and the radiation increase caused by the PM2.5 reduction was not the main reason for the increase in O-3. This indicates that the generation of secondary pollutants is influenced by multiple factors and is not only governed by emission reduction. (C) 2020 Elsevier B.V. All rights reserved

Seasonal Variation, Sources and Transport of Aerosols at Lijiang, Southeast Tibetan Plateau

Aerosol samples were collected during pre-monsoon, monsoon and post-monsoon periods in 2009 in Lijiang, a tourism city located on the southeast Tibetan Plateau, southwest China. To determine the seasonal variation and sources of aerosol species, main elements and water soluble ions were analyzed. The results showed that crustal elements (Si, K, Ca, Ti and Fe) were the main elements with an enrichment whose enrichment factor (EF) value were lower than 10, with the large value (except Ca) occurring during the pre-monsoon period. The EF values of S, Cl, Zn, As, Br, Sb, Pb, and Cu were higher than those of the crustal elements and the large concentration appeared during the monsoon period. Ca2+ and SO42- were the dominant cation and anion, respectively. The greatest value of total ionic concentration was found during the monsoon period, mainly because of the high concentration of SO42- and NH4+. Using the positive matrix factorization model, it was found that the main sources of species were from crustal source, transport from south Asia and eastern China, local vehicle emissions and sea salt. Further results indicated that the pollutants mixed with dust, anthropogenic pollutants and biomass burning emissions can be transported to Lijiang from south Asia and Southeast Asia during the pre-monsoon period. In addition, pollutants rich in SO42- and heavy metal from the Sichuan Basin and eastern Yunnan Province can also be occasionally transported to Lijiang during the monsoon period. The seasonal differences in chemical composition and transportation pathway may have important implications for regional climate change

Quantitative Inversion of Lunar Surface Chemistry Based on Hyperspectral Feature Bands and Extremely Randomized Trees Algorithm

In situ resource utilization (ISRU) is required for the operation of both medium and long-term exploration missions to provide metallic materials for the construction of lunar base infrastructure and H2O and O2 for life support. The study of the distribution of the lunar surface elements (Fe, Ti, Al, and Si) is the basis for the in situ utilization of mineral resources. With the arrival of the era of big data, the application of big data concepts and technical methods to lunar surface chemistry inversion has become an inevitable trend. This paper is guided by big data theory, and the Apollo 17 region and the area near the Copernicus crater are selected for analysis. The dimensionality of the first-order differential spectral features of lunar soil samples is reduced based on Pearson correlation analysis and the successive projections algorithm (SPA), and the extremely randomized trees (Extra-Trees) algorithm is applied to Chang’E-1 Interference Imaging Spectrometer (IIM) data to establish a prediction model for the lunar surface chemistry and generate FeO, TiO2, Al2O3, and SiO2 distribution maps. The results show that the optimum number of variables for FeO, TiO2, Al2O3, and SiO2 is 17, 5, 8, and 30, respectively. The accuracy of the Extra-Trees model using the best variables was improved over that of the original band model, with determination coefficients (R2) of 0.962, 0.944, 0.964, and 0.860 for FeO, TiO2, Al2O3, and SiO2, and root mean square errors (RMSEs) of 1.028, 0.672, 0.942, and 0.897, respectively. The modeling feature variables and model preference methods in this study can improve the inversion accuracy of chemical abundance to some extent, demonstrating the potential of IIM data in predicting chemical abundance and providing a good data basis for lunar geological evolution studies and ISRU

Quantitative Inversion of Lunar Surface Chemistry Based on Hyperspectral Feature Bands and Extremely Randomized Trees Algorithm

In situ resource utilization (ISRU) is required for the operation of both medium and long-term exploration missions to provide metallic materials for the construction of lunar base infrastructure and H2O and O2 for life support. The study of the distribution of the lunar surface elements (Fe, Ti, Al, and Si) is the basis for the in situ utilization of mineral resources. With the arrival of the era of big data, the application of big data concepts and technical methods to lunar surface chemistry inversion has become an inevitable trend. This paper is guided by big data theory, and the Apollo 17 region and the area near the Copernicus crater are selected for analysis. The dimensionality of the first-order differential spectral features of lunar soil samples is reduced based on Pearson correlation analysis and the successive projections algorithm (SPA), and the extremely randomized trees (Extra-Trees) algorithm is applied to Chang’E-1 Interference Imaging Spectrometer (IIM) data to establish a prediction model for the lunar surface chemistry and generate FeO, TiO2, Al2O3, and SiO2 distribution maps. The results show that the optimum number of variables for FeO, TiO2, Al2O3, and SiO2 is 17, 5, 8, and 30, respectively. The accuracy of the Extra-Trees model using the best variables was improved over that of the original band model, with determination coefficients (R2) of 0.962, 0.944, 0.964, and 0.860 for FeO, TiO2, Al2O3, and SiO2, and root mean square errors (RMSEs) of 1.028, 0.672, 0.942, and 0.897, respectively. The modeling feature variables and model preference methods in this study can improve the inversion accuracy of chemical abundance to some extent, demonstrating the potential of IIM data in predicting chemical abundance and providing a good data basis for lunar geological evolution studies and ISRU

Azaarenes in fine particulate matter from the atmosphere of a Chinese megacity

Azaarenes (AZAs) are toxicologically relevant organic compounds with physicochemical properties that are significantly different from the well-studied polycyclic aromatic hydrocarbons (PAHs). However, little is known about their concentrations, seasonal variations, fate, and relationship with PAHs in air. This paper reports the temporal variations in the concentrations and composition patterns of AZAs in PM2.5 that was sampled once per 6 days from outdoor air of Xi'an, China from July 2008 to August 2009. The concentrations of the aAZAs, quinoline (QUI), benzo[h]quinoline (BQI), and acridine (ACR) in PM2.5 were 213-6441, 185-520, 69-2483, and 10-3544 pg m(-3), respectively. These concentrations were higher than those measured in urban areas of Western Europe. AZA compositional patterns were dominated by BQI and ACR. The high concentration of AZAs, high AZA/related PAH ratio, and the dominance of three-ring AZAs (BQI and ACR) in PM2.5 of Xi'an are all in contrast to observations from Western European and North American cities. This contrast likely reflects differences in coal type and the more intense use of coal in China. The PM2.5-bound concentration of AZA in winter season (W) was higher than during the summer season (S) with W/S ratios of 5.7, 1.4, 4.1, and 13, for aAZAs, QUI, BQI, and ACR, respectively. Despite their significantly different physicochemical properties, AZAs were significantly (p < 0.05) positively correlated with their related PAHs and pyrogenic elemental carbon. The changes in AZA concentrations were positively correlated with ambient pressure but negatively correlated with ambient temperature, wind speed, and relative humidity. This trend is similar to that observed for the related PAHs. We conclude that Xi'an and possibly other Chinese cities have higher emission of AZAs into their atmosphere because of the more pronounced use of coal. We also conclude that in spite of differences in physicochemical properties between AZAs and related PAHs, the atmospheric dynamics and relationships with meteorological factors of both compound groups are similar