Τετάρτη, 13 Μαρτίου 2019

Environment

The evolution of an aerosol event observed from aircraft in Beijing: An insight into regional pollution transport

Publication date: 1 June 2019

Source: Atmospheric Environment, Volume 206

Author(s): Ping Tian, Dantong Liu, Mengyu Huang, Quan Liu, Delong Zhao, Liang Ran, Zhaoze Deng, Yunfei Wu, Shizuo Fu, Kai Bi, Qian Gao, Hui He, Huiwen Xue, Deping Ding

Abstract

To investigate the transport and formation mechanism of pollution in Beijing, this study explored the vertical profiles of aerosol properties using aircraft measurement during a regional transport (RT) pollution event from 10th to 12th December 2016. The aerosol chemical composition and size distribution were characterized. Different vertical structures exhibited during three periods (defined as before RT, during RT, and after RT) for this pollution event. Before RT, PM2.5 and black carbon (BC) mass loading were at low level in the mixing layer (ML) when the clean northerly air mass dominated. During RT, an elevated aerosol layer, in which BC and PM2.5 mass concentrations were about 1.5 times higher than that at the ground level, was found in the upper ML (at 400–900 m) over Beijing. This elevated aerosol layer was advected by the prevailing southwesterly air mass which transported the pollutants from the intensively polluted southwestern region over Beijing. These aerosols through RT featured with pronounced secondary compositions and large coatings on BC particles. After RT, the pollutants were significantly diluted by the prevailing NW air mass, whereas the aerosol concentration almost maintained in the near surface, leading to notable vertical gradient. The continued surface pollution may result from the low wind speed and secondary aerosol formation in the next day. This study suggests that only the ground observation could not fully explain the pollution event, but the variation of vertical structure of aerosol properties should be considered to elucidate the formation mechanism of pollution over Beijing.

Graphical abstract

Comparison of vertical BC profiles between Beijing and Baoding show that the BC mass concentration of Baoding was 4 times larger than that of Beijing on December 10, and 1.6 times smaller than that of Beijing on December11. It is very interesting to found an enhanced BC layer from 400 to 900 m in upper mixing layer over Beijing on December11. The meteorological analysis indicated that the enhanced layer was caused by the regional transport from the surface area in the southern part of North China Plain. Through vertical mixing in the mixing layer in Beijing, the ground PM2.5 mass concentration was increased quickly. Our results verified that the rapidly increase of pollution in Beijing was caused by southern transport at high altitude.

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Sources and gas-particle partitioning of atmospheric parent, oxygenated, and nitrated polycyclic aromatic hydrocarbons in a humid city in southwest China

Publication date: 1 June 2019

Source: Atmospheric Environment, Volume 206

Author(s): Huilin Hu, Mi Tian, Leiming Zhang, Fumo Yang, Chao Peng, Yang Chen, Guangming Shi, Xiaojiang Yao, Changtan Jiang, Jun Wang

Abstract

Polycyclic aromatic hydrocarbons (PAHs) derivatives, such as oxygenated PAHs (OPAHs) and nitrated PAHs (NPAHs), some of which are more toxic and persistent than parent PAHs, have been ubiquitously detected in the environment. Gaseous and particulate PAHs, OPAHs, and NPAHs in the air were measured in an urban environment of Chongqing in southwest China in 2016. Annual average concentrations were 79.9 ± 40.5 ng/m³, 93.7 ± 75.2 ng/m³ and 1.65 ± 1.43 ng/m³ for ∑29 PAHs, ∑10 OPAHs and ∑27 NPAHs, respectively. PAHs had highest level in winter and lowest level in summer while NPAHs and OPAHs showed relatively higher concentrations in summer than spring and autumn, which may be explained by stronger secondary formation of NPAHs and OPAHs in summer. Source apportionment analysis revealed that biomass burning, coal combustion, and petroleum combustion were the main sources for PAHs, while secondary formation, especially in summer, contributed greatly to OPAHs and NPAHs. Gas/particle partition coefficient (logKP) of PAHs, OPAHs and NPAHs, calculated from our observation data, was found to correlate well with the corresponding subcooled liquid vapor pressures (logPLo). The shallower slope of the linear regression between logKP and logPLo for PAHs (−0.61 to −0.52) than OPAHs or NPAHs (−2.14 to −0.73) indicated stronger absorption into the atmospheric particles for PAHs. Three gas/particle partitioning models were evaluated, including the Junger-Pankow adsorption model, the KOA absorption model, and the Dual octanol-air/soot-air model. Compared to the measured values of particle-bound fractions, model predicted values were in reasonable range for PAHs, but were underestimated for NPAHs and OPAHs, suggesting that other important factors such as the influence of RH should be incorporated in gas/particle partitioning models for less hydrophobic compounds, especially in humid areas.

Graphical abstract

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Gaussian Markov Random Fields versus Linear Mixed Models for satellite-based PM2.5 assessment: Evidence from the Northeastern USA

Publication date: 15 May 2019

Source: Atmospheric Environment, Volume 205

Author(s): Ron Sarafian, Itai Kloog, Allan C. Just, Johnathan D. Rosenblatt

Abstract

Studying the effects of air-pollution on health is a key area in environmental epidemiology. An accurate estimation of air-pollution effects requires spatio-temporally resolved datasets of air-pollution, especially, Fine Particulate Matter (PM). Satellite-based technology has greatly enhanced the ability to provide PM assessments in locations where direct measurement is impossible.

Indirect PM measurement is a statistical prediction problem. The spatio-temporal statistical literature offer various predictive models: Gaussian Random Fields (GRF) and Linear Mixed Models (LMM), in particular. GRF emphasize the spatio-temporal structure in the data, but are computationally demanding to fit. LMMs are computationally easier to fit, but require some tampering to deal with space and time.

Recent advances in the spatio-temporal statistical literature propose to alleviate the computation burden of GRFs by approximating them with Gaussian Markov Random Fields (GMRFs). Since LMMs and GMRFs are both computationally feasible, the question arises: which is statistically better? We show that despite the great popularity of LMMs in environmental monitoring and pollution assessment, LMMs are statistically inferior to GMRF for measuring PM in the Northeastern USA.



Quantification of manganese species in particulate matter collected in an urban area nearby a manganese alloy plant

Publication date: 15 May 2019

Source: Atmospheric Environment, Volume 205

Author(s): A. Hernández-Pellón, P. Mazón, I. Fernández-Olmo

Abstract

A sequential extraction test was used to evaluate the manganese (Mn) species in PM10 samples collected in an urban area impacted by a Mn alloy plant, where the annual guideline value for Mn in air according to the World Health Organization (WHO) is frequently exceeded (i.e. > 150 ng m−3). The average Mn level in this campaign was 208.6 ng m−3, reaching maximum daily values up to 1138.9 ng m−3. Manganese species were dominated by water-soluble Mn (49.9%), followed by metallic Mn (Mn0) and Mn2+ (27.1%), insoluble Mn (14.6%), and Mn3+ and Mn4+ (8.8%). This study reveals, on one hand, the higher fraction of water-soluble Mn species present in atmospheric aerosols in comparison with aerosols collected in work environments of the Mn alloy industry, which is attributed to the reaction between emitted Mn oxides and gaseous pollutants (SO2, NO2 and HCl) during transport in the atmosphere. On the other hand, there was a non-negligible fraction of more toxic species (Mn3+ and Mn4+), which are more potent than Mn2+ to induce reactive oxygen species.



Air pollution modeling and exposure assessment during pregnancy in the French Longitudinal Study of Children (ELFE)

Publication date: 15 May 2019

Source: Atmospheric Environment, Volume 205

Author(s): Emmanuel Riviere, Julien Bernard, Agnès Hulin, Jonathan Virga, Fabrice Dugay, Marie-Aline Charles, Marie Cheminat, Jérôme Cortinovis, François Ducroz, Anne Laborie, Laure Malherbe, Damien Piga, Elsa Real, Pierre-Yves Robic, Cécile Zaros, Emie Seyve, Johanna Lepeule

Abstract

We developed a nation-wide exposure model to NO2, PM10 and PM2.5 at a fine spatial and temporal resolution for France in order to study air pollutants exposure during pregnancy for the French Longitudinal Study of Children (ELFE).

The exposure to air pollutants was estimated daily for years 2010 and 2011 by combining three simulation models at the national and regional scale (CHIMERE) and at the local urban scale (ADMS-Urban or SIRANE). The spatial resolution was 4 km for the national scale model, 3–4 km for regional models and from 10 to 200 m for urban-scale models. We developed a confidence index (from 0 to 10) based on the target plot to identify the best model to estimate exposure for a given address, year and pollutant. Air pollution exposure during pregnancy was then estimated using each modeling scale for the 17,427 women participating in the ELFE cohort. We described the exposure of the women during different time windows of pregnancy using each of the three models and using the most suitable model as estimated by the confidence index.

The exposure estimates obtained from the three models were quite similar and highly correlated (spearman correlation between 0.64 and 0.96), especially for the national and regional models. For NO2 and PM10 predicted by the urban models, the minimum values were lower and the maximum values and the variability were higher, compared to the regional and national models. The averaged confidence indexes were comprised between 5.6 and 8 depending on the pollutant, year and exposure model considered. The best confidence index was observed for urban modeling (10) and the lowest for the regional modeling (0). In average during pregnancy, using the most suitable model, women were exposed to 21 μg/m3 for NO2, 16 μg/m3 for PM2.5 and 24 μg/m3 for PM10.

To our knowledge, this is the first study combining three modeling tools available at different scales to estimate NO2, PM10 and PM2.5 concentrations at a fine spatial and temporal resolution over a large geographical area. The confidence index provides guidance in the choice of the exposure model. These exposure estimates will be used to investigate potential effects of air pollutants on the pregnant woman health and on health of the fetus and development of the child.



Bioavailable iron production in airborne mineral dust: Controls by chemical composition and solar flux

Publication date: 15 May 2019

Source: Atmospheric Environment, Volume 205

Author(s): Eshani Hettiarachchi, Richard L. Reynolds, Harland L. Goldstein, Bruce Moskowitz, Gayan Rubasinghege

Abstract

A large part of oceanic biological production is limited by the scarcity of dissolved iron. Mineral dust aerosol, processed under acidic atmospheric conditions, is the primary natural source of bioavailable iron to oceanic life. However, synergistic and antagonistic effects of non-Fe-containing minerals on atmospheric processing of Fe-containing minerals and Fe solubilization are poorly understood. The current study focuses on mineralogical influences of non-Fe-bearing semiconductor minerals, such as titanium dioxide (TiO2), on the dissolution of iron in selected natural mineral dust aerosols under atmospherically relevant conditions. Further, the role of elevated Ti concentrations in dust is evaluated using magnetite, a proxy for Fe(II) containing minerals, under both dark and light conditions. Our results highlight that relatively higher Ti:Fe ratios, regardless of their total Fe content, enhances the total iron dissolution in mineral dust aerosols as well as in magnetite. Moreover, elevated Ti percentages also yield high Fe(II) fractions in mineral dust systems under dark conditions. Upon irradiation however, dissolved Fe(II) is suppressed by high Ti levels due to the involvement of photochemical redox cycling reactions with hydroxyl radicals (OH). These synergistic and antagonistic effects of Ti are further evaluated by altering the chemical composition of natural dusts with artificially added anatase (TiO2) and synthetic amorphous titania. The current study reveals important mineralogical controls by non-Fe-bearing minerals on dust iron dissolution to better understand global iron mobilization.

Graphical abstract

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Assessing the impact of Chinese FY-3/MERSI AOD data assimilation on air quality forecasts: Sand dust events in northeast China

Publication date: 15 May 2019

Source: Atmospheric Environment, Volume 205

Author(s): Yansong Bao, Liuhua Zhu, Qin Guan, Yuanhong Guan, Qifeng Lu, George P. Petropoulos, Huizheng Che, Gohar Ali, Yan Dong, Zhaokang Tang, Yingjie Gu, Weiyao Tang, Yue Hou

Abstract

Aerosol optical depth (AOD) is an important parameter characterizing the optical properties of atmospheric aerosols and can be used to indicate aerosol loading and evaluate air quality. In this study, a FY-3/medium-resolution spectral imager (MERSI) AOD data assimilation (DA) system was developed using a three-dimensional variational DA method to assess the impact of Chinese FY-3/MERSI AOD data assimilation on air quality forecasts. Two typical sand-dust weather events occurred during the spring season of years 2010 and 2011 were selected as case study. The DA system and Weather Research and Forecasting model coupled with a chemical model (WRF-Chem) were used to evaluate the impacts of FY-3/MERSI AOD DA on air quality forecasts. This was based on comparisons between modeled AOD data and AOD data acquired by the Aerosol Robotic Network (AERONET) and Moderate Resolution Imaging Spectroradiometer (MODIS) satellites. Results from both case studies revealed that FY-3/MERSI AOD DA apparently improved the air quality forecasts. Key findings of the FY-3/MERSI AOD DA experiments included: (1) FY-3/MERSI AOD DA adjusted the simulated aerosol particle content of the WRF-Chem model and efficiently improved the extinction coefficient fields below 500 hPa. Moreover, AOD DA had the strongest effect on adjusting the extinction coefficients at 750 hPa (approximately 2 km). Compared with the AOD background field, the AOD analysis field was similar to the satellite observation field. (2) Compared with the control experiments without DA, the AOD DA experiment produced more accurate 24-h AOD forecasts, more consistent with the AERONET and satellite observations. (3) Due to the spatial distribution and intensity difference of satellite AOD data, satellite AOD data assimilation has obvious individual characteristics for the improvement of particle concentration prediction. Our study findings suggest that the developed DA system can facilitate the effective use of AOD data acquired by Chinese satellites in air quality forecasting models and can improve dust forecasting results.



Climatological study for understanding the aerosol radiative effects at southwest Atlantic coast of Europe

Publication date: 15 May 2019

Source: Atmospheric Environment, Volume 205

Author(s): M. Sorribas, E. Andrews, J.A. Ogren, A. del Águila, R. Fraile, P. Sheridan, M. Yela

Abstract

In order to describe the means, variability and trends of the aerosol radiative effects on the southwest Atlantic coast of Europe, 11 years of aerosol light scattering (σsp) and 4 years of aerosol light absorption (σap) are analyzed. A 2006–2016 trend analysis of σsp for D < 10 μm indicates statistically significant trends for March, May–June and September–November, with a decreasing trend ranging from −1.5 to −2.8 Mm−1/year. In the 2009–2016 period, the decreasing trend is only observed for the months of June and September. For scattering Ångström exponent (SAE) there is an increasing trend during June with a rate of 0.059/year and a decreasing trend during October with −0.060/year. The trends observed may be caused by a reduction of Saharan dust aerosol or a drop in particle loading in anthropogenic influenced air masses. The relationship between SAE and absorption Ångström exponent is used to assess the aerosol typing. Based on this typing, the sub-micron particles are dominated by black carbon, mixed black and brown carbon or marine with anthropogenic influences, while the super-micrometer particles are desert dust and sea spray aerosol. The mean and standard deviation of the dry aerosol direct radiative effect at the top of the atmosphere (DRETOA) are −4.7 ± 4.2 W m−2. DRETOAfor marine aerosol shows all observations more negative than −4 W m−2 and for anthropogenic aerosol type, DRETOA ranges from −5.0 to −13.0 W m−2. DRETOA of regional marine aerosol ranges from −3 to −7 W m−2, as it consists of a mixture of sea salt and anthropogenic aerosol. The variability in DRETOA is mainly dependent on AOD, given that variations in backscatter fraction and the single scattering albedo tend to counteract each other in the radiative forcing efficiency equation. The results shown here may help in interpretation of satellite retrieval products and provide context for model evaluation.



Estimate of boundary-layer depth in Nanjing city using aerosol lidar data during 2016–2017 winter

Publication date: 15 May 2019

Source: Atmospheric Environment, Volume 205

Author(s): Sihui Fan, Zhiqiu Gao, John Kalogiros, Yubin Li, Jian Yin, Xin Li

Abstract

The planetary boundary-layer (PBL) structure was investigated using observations from single aerosol lidar, eddy covariance (EC) system, and automatic meteorological station (AWS) in the north of Nanjing city during an air pollution episode in 2016–2017 winter. Based on seven days' observations under clear to polluted day, we present the temporal variations of the aerosol extinction profiles observed by lidar, and then inter-compare PBL depth retrieved from individual gradient methods. The results show that the gradient method (GM) generated the lowest PBL depth. In contrast to the cubic root gradient method (CRGM), which determined PBL depth ranging from 172 m to 1575 m during the observation period, the logarithm gradient method (LGM) and normalized gradient method (NGM) generated similar results and both tended to overestimate PBL depth on polluted days. The CRGM performed better than LGM and NGM in case of multiple backscatter layers and could detect low level layers, while the GM was biased at low heights probably due to the effect of lidar overlap function. Based on these measurements, the evolution of boundary layer structures and PBL depth over clean days and polluted days were compared. The results show that (1) on clean days, the strong surface turbulence exchange make the PBL depth fully developed and the PBL depth had obvious characteristics of diurnal variation; the maximum depth of PBL was 1560 m for CRGM; and (2) on polluted days, the high pressure system and lower wind was favorable to the accumulation of air pollutants, and thus generating less turbulence by reducing surface radiation. These conditions on polluted days led to smaller PBL depth than those on clean days, and the maximum depth of PBL was 660 m for CRGM. Besides, the diurnal variation of PBL depth on polluted days was weaker than those on clean days.



Modelling aerosol optical properties over urban environment (New Delhi) constrained with balloon observation

Publication date: 15 May 2019

Source: Atmospheric Environment, Volume 205

Author(s): A. Ahlawat, S.K. Mishra, V. Goel, C. Sharma, B.P. Singh, A. Wiedensohler

Abstract

Vertical variation in aerosol optical properties [e.g. Single Scattering Albedo (SSA) and aerosol extinction coefficient] over a polluted environment is extremely important for better understanding of columnar radiative characteristics. The present case study over a typical polluted environment (New Delhi) discusses the vertical profile (ground to 700 m) of modelled optical properties of atmospheric particles at different altitudes. Here, we used the aerosol physico-chemical data generated in the tethered balloon-based observation conducted at CSIR-NPL, New Delhi (28° 38′ 10″ N, 77° 10′ 17″ E) from 21st −27th February 2014. Based on the microscopic observations of individual particles, we developed the aerosol model shapes (coated spheres) for simulating their optical properties. Total three cases were considered for simulating the aerosol optics at varying altitude; Case A: External mixture of coated dust and coated sulfate particles; Case B: External mixture of coated dust, coated sulfate, coated OC (Organic Carbon) and coated EC (Elemental Carbon) (with assumption that 6% EC at ground level); Case C: External mixture of coated dust, coated sulfate, coated OC and coated EC (with assumption that 10% EC at ground level). At 550 nm wavelength, the value of SSA has been found to be highest (i.e. 0.985) at 200 m altitude for Case A while Case B (i.e. 0.9523) and Case C (i.e. 0.9291) show highest values at 500 m altitude. SSA was found to be maximum at 500 m altitude for both Case B and Case C due to the presence of lowest graphitic counts at that particular altitude. Case B and Case C exhibit similar pattern but differ in magnitude, this is due to two EC extremities at ground level i.e. minima (6%) and maxima (10%). The percentage deviation in SSA from ground level to 700 m was found to be highest for Case C (i.e. 5.95%) followed by Case B (i.e. 4.19%) and Case A (i.e. 1.4%). Modelled aerosol optical properties within boundary layer may improve our understanding about the thermodynamics of lower atmosphere.



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