Progressively narrow the gap of PM2.5 pollution characteristics at urban and suburban sites in a megacity of Sichuan Basin, China

Nowadays, the fine particle pollution is still severe in some megacities of China, especially in the Sichuan Basin, southwestern China. In order to understand the causes, sources, and impacts of fine particles, we collected PM_2.5 samples and analyzed their chemical composition in typical months from July 2018 to May 2019 at an urban and a suburban (background) site of Chengdu, a megacity in this region. The daily average concentrations of PM_2.5 ranged from 5.6-102.3 µg/m³ and 4.3-110.4 µg/m³ at each site. Secondary inorganics and organic matters were the major components in PM_2.5 at both sites. The proportion of nitrate in PM_2.5 has exceeded sulfate and become the primary inorganic component. SO₂ was easier to transform into sulfate in urban areas because of Mn-catalytic heterogeneous reactions. In contrast, NO₂ was easily converted in suburbs with high aerosol water content. Furthermore, organic carbon in urban was much greater than that in rural, other than elemental carbon. Element Cr and As were the key cancer risk drivers. The main sources of PM_2.5 in urban and suburban areas were all secondary aerosols (42.9%, 32.1%), combustion (16.0%, 25.2%) and vehicle emission (15.2%, 19.2%). From clean period to pollution period, the contributions from combustion and secondary aerosols increased markedly. In addition to tightening vehicle controls, urban areas need to restrict emissions from steel smelters, and suburbs need to minimize coal and biomass combustion in autumn and winter.     

太湖流域面源污染控制对策研究

近年来.随着点源污染得到逐步治理,面源污染已成为水体富营养化的主要污染源,本文介绍了太湖流域面源 污染的现状,分析了其构成,列举了国内外目前治理面源污染的一些措施,并就太湖流域面源污染的特点提出了一些控制 治理对策。     

南京市气溶胶PM2.5中多环芳烃来源识别

对2005年7月至2006年2月采集到的南京市气溶胶Pm2.5 进行季节性初步分析,并对其中的15种优控多环芳烃(PAHs)进行分析研究,通过比值法判断南京市PAHs夏季主要来源于柴油型燃烧,冬季主要来源于柴油和煤型相结合的燃烧.对15种优控PAHs两两之间的相关性分析,发现各化合物之间显著相关,表明各化合物的来源有相似之处.     

PM2.5 chemical source profiles for vehicle exhaust, vegetative burning, geological material, and coal burning in Northwestern Colorado during 1995

PM_2.5 (particles with aerodynamic diameters less than 2.5 μm) chemical source profiles applicable to speciated emissions inventories and receptor model source apportionment are reported for geological material, motor vehicle exhaust, residential coal (RCC) and wood combustion (RWC), forest fires, geothermal hot springs; and coal-fired power generation units from northwestern Colorado during 1995. Fuels and combustion conditions are similar to those of other communities of the inland western US. Coal-fired power station profiles differed substantially between different units using similar coals, with the major difference being lack of selenium in emissions from the only unit that was equipped with a dry limestone sulfur dioxide (SO₂) scrubber. SO₂ abundances relative to fine particle mass emissions in power plant emissions were seven to nine times higher than hydrogen sulfide (H₂S) abundances from geothermal springs, and one to two orders of magnitude higher than SO₂ abundances in RCC emissions, implying that the SO₂ abundance is an important marker for primary particle contributions of non-aged coal-fired power station contributions. The sum of organic and elemental carbon ranged from 1% to 10% of fine particle mass in coal-fired power plant emissions, from 5% to 10% in geological material, >50% in forest fire emissions, >60% in RWC emissions, and >95% in RCC and vehicle exhaust emissions. Water-soluble potassium (K⁺) was most abundant in vegetative burning profiles. K⁺/K ratios ranged from 0.1 in geological material profiles to 0.9 in vegetative burning emissions, confirming previous observations that soluble potassium is a good marker for vegetative burning.     

Polycyclic aromatic hydrocarbons, black carbon, and molecular markers in soils of Switzerland

Polycyclic aromatic hydrocarbons (PAH) were analysed in 23 soil samples (0–10 cm layer) from the Swiss soil monitoring network (NABO) together with total organic carbon (TOC) and black carbon (BC) concentration, as well as some PAH source diagnostic ratios and molecular markers. The concentrations of the sum of 16 EPA priority PAHs ranged from 50 to 619 μg/kg dw. Concentrations increased from arable, permanent and pasture grassland, forest, to urban soils and were 21–89% lower than median numbers reported in the literature for similar Swiss and European soils. NABO soils contained BC in concentrations from 0.4 to 1.8 mg/g dw, except for two sites with markedly higher levels. These numbers corresponded to 1–6% of TOC and were comparable to the limited published BC data in soil and sediments obtained with comparable analytical methods. The various PAH ratios and molecular markers pointed to a domination of pyrogenically formed PAHs in Swiss soils. In concert, the gathered data suggest the following major findings: (1) gas phase PAHs (naphthalene to fluorene) were long-range transported, cold-condensated at higher altitudes, and approaching equilibrium with soil organic matter (OM); (2) (partially) particle-bound PAHs (phenanthrene to benzo[ghi]perylene) were mostly deposited regionally in urban areas, and not equilibrated with soil OM; (3) Diesel combustion appeared to be a major emission source of PAH and BC in urban areas; and (4) wood combustion might have contributed significantly to PAH burdens in some soils of remote/alpine (forest) sites.     

Molecular characterization of effluent organic matter in secondary effluent and reclaimed water: Comparison to natural organic matter in source water

Municipal wastewater reclamation is becoming of increasing importance in the world to solve the problem of water scarcity. A better understanding of the molecular composition of effluent organic matter(Ef OM) in the treated effluents of municipal wastewater treatment plants(WWTPs) is crucial for ensuring the safety of water reuse. In this study, the molecular composition of Ef OM in the secondary effluent of a WWTP in Beijing and the reclaimed water further treated with a coagulation–sedimentation–ozonation process were characterized using a non-target Fourier transform ion cyclotron resonance mass spectrometry(FT-ICR MS) method and compared to that of natural organic matter(NOM) in the local source water from a reservoir. It was found that the molecular composition of Ef OM in the secondary effluent and reclaimed water was dominated by CHOS formulas, while NOM in the source water was dominated by CHO formulas. The CHO formulas of the three samples had similar origins. Anthropogenic surfactants were responsible for the CHOS formulas in Ef OM of the secondary effluent and were not well removed by the coagulation-sedimentation-ozonation treatment process adopted.     

Characterization of submicron particles during autumn in Beijing, China

In this study, we performed a highly time-resolved chemical characterization of nonrefractory submicron particles(NR-PM_1) in Beijing by using an Aerodyne high-resolution time-of-flight aerosol mass spectrometer(HR-ToF-AMS). The results showed the average NR-PM_1 mass concentration to be 56.4 ± 58.0 μg/m~3, with a peak at 307.4 μg/m~3. Due to the high frequency of biomass burning in autumn, submicron particles significantly increased in organic content, which accounted for 51% of NR-PM_1 on average. Secondary inorganic aerosols(sulfate + nitrate + ammonium) accounted for 46% of NR-PM_1, of which sulfate,nitrate, and ammonium contributed 15%, 20%, and 11%, respectively. To determine the intrinsic relationships between the organic and inorganic species, we used the positive matrix factorization(PMF) model to merge the high-resolution mass spectra of the organic species and NO+and NO_2~+ions. The PMF analysis separated the mixed organic and nitrate(NO+and NO_2~+) spectra into four organic factors, including hydrocarbon-like organic aerosol(HOA), oxygenated organic aerosol(OOA), cooking organic aerosol(COA), and biomass burning organic aerosol(BBOA), as well as one nitrate inorganic aerosol(NIA) factor. COA(33%) and OOA(30%) contributed the most to the total organic aerosol(OA) mass, followed by BBOA(20%) and HOA(17%). We successfully quantified the mass concentrations of the organic and inorganic nitrates by the NO+and NO2+ions signal in the organic and NIA factors. The organic nitrate mass varied from 0.01-6.8 μg/m~3, with an average of 1.0 ±1.1 μg/m~3, and organic nitrate components accounted for 10% of the total nitrate mass in this observation.     

Particulate matter pollution in Kunshan High-Tech zone: Source apportionment with trace elements, plume evolution and its monitoring

Particulate matter(PM) in the Kunshan High-Tech zone is studied during a three-month campaign. PM and trace elements are measured by the online pollution monitoring, forecastwarning and source term retrieval system AS3. Hourly measured concentrations of PM_(10), PM_(2.5) and 16 trace elements in the PM_(2.5) section(Ca, Pb, Cu, Cl, V, Cr, Fe, Ti, Mn, Ni, Zn, Ga, As, Se, Sr, Ba)are focused. Source apportionment of trace elements by Positive Matrix Factorization modeling indicates that there are five major sources, including dust, industrial processing, traffic,combustion, and sea salt with contribution rate of 23.68%, 21.66%, 14.30%, 22.03%, and 6.89%,respectively. Prediction of plume dispersion from concrete plant and traffic emissions shows that PM_(10) pollution of concrete plant is three orders of magnitude more than that of the traffic. The influence range can extend to more than 3 km in 1 hr. Because the footprint of the industrial plumes is constantly moving according to the local meteorological conditions, the fixed monitoring sites scattered in a few hundred meters haven't captured the heaviest pollution plume at the local scale of a few km~2. As a more intensive monitoring network is not operationally possible, the use of online modeling gives accurate and quantitative information of plume location, which increases the spatial pollution monitoring capacity and improves the understanding of measurement data. These results indicate that the development of the AS3 system, which combines monitoring equipment and air pollution modeling systems, is beneficial to the real-time pollution monitoring in the industrial zone.     

Quantifying the characteristics of particulate matters captured by urban plants using an automatic approach

It is widely accepted that urban plant leaves can capture airborne particles. Previous studies on the particle capture capacity of plant leaves have mostly focused on particle mass and/or size distribution. Fewer studies, however, have examined the particle density, and the size and shape characteristics of particles, which may have important implications for evaluating the particle capture efficiency of plants, and identifying the particle sources. In addition, the role of different vegetation types is as yet unclear. Here, we chose three species of different vegetation types, and firstly applied an object-based classification approach to automatically identify the particles from scanning electron microscope(SEM)micrographs. We then quantified the particle capture efficiency, and the major sources of particles were identified. We found(1) Rosa xanthina Lindl(shrub species) had greater retention efficiency than Broussonetia papyrifera(broadleaf species) and Pinus bungeana Zucc.(coniferous species), in terms of particle number and particle area cover.(2) 97.9% of the identified particles had diameter ≤10 μm, and 67.1% of them had diameter ≤2.5 μm. 89.8% of the particles had smooth boundaries, with 23.4% of them being nearly spherical.(3) 32.4%–74.1% of the particles were generated from bare soil and construction activities, and 15.5%–23.0% were mainly from vehicle exhaust and cooking fumes.     

Identification and elucidation of anthropogenic source contribution in PM10 pollutant: Insight gain from dispersion and receptor models

Source apportionment study of PM₁₀ (Particulate Matter) in a critically polluted area of Jharia coalfield, India has been carried out using Dispersion model, Principle Component Analysis (PCA) and Chemical Mass Balance (CMB) techniques. Dispersion model Atmospheric Dispersion Model (AERMOD) was introduced to simplify the complexity of sources in Jharia coalfield. PCA and CMB analysis indicates that monitoring stations near the mining area were mainly affected by the emission from open coal mining and its associated activities such as coal transportation, loading and unloading of coal. Mine fire emission also contributed a considerable amount of particulate matters in monitoring stations. Locations in the city area were mostly affected by vehicular, Liquid Petroleum Gas (LPG) & Diesel Generator (DG) set emissions, residential, and commercial activities. The experimental data sampling and their analysis could aid understanding how dispersion based model technique along with receptor model based concept can be strategically used for quantitative analysis of Natural and Anthropogenic sources of PM₁₀.