scholarly journals Radiocarbon analysis of elemental and organic carbon in Switzerland during winter-smog episodes from 2008 to 2012 – Part 1: Source apportionment and spatial variability

2014 ◽  
Vol 14 (10) ◽  
pp. 15591-15643 ◽  
Author(s):  
P. Zotter ◽  
V. G. Ciobanu ◽  
Y. L. Zhang ◽  
I. El-Haddad ◽  
M. Macchia ◽  
...  
Keyword(s):  
Air Pollution ◽  
Source Apportionment ◽  
Biomass Burning ◽  
Water Soluble ◽  
Pollution Monitoring ◽  
Carbonaceous Aerosols ◽  
Air Pollution Monitoring ◽  
Wide Range ◽  
The Alps ◽  
North And South

Abstract. While several studies have investigated winter-time air pollution with a wide range of concentration levels, hardly any results are available for longer time periods covering several winter-smog episodes at various locations; e.g. often only a few weeks from a single winter are investigated. Here, we present source apportionment results of winter-smog episodes from 16 air pollution monitoring stations across Switzerland from five consecutive winters. Radiocarbon (14C) analyses of the elemental (EC) and organic (OC) carbon fractions, as well as levoglucosan, major water-soluble ionic species and gas-phase pollutant measurements were used to characterize the different sources of PM10. The most important contributions to PM10 during winter-smog episodes in Switzerland were on average the secondary inorganic constituents (sum of nitrate, sulfate and ammonium = 41 ± 15%) followed by organic matter OM (30 ± 12%) and EC (5 ± 2%). The non-fossil fractions of OC (fNF,OC) ranged on average from 69–85% and 80–95 % for stations north and south of the Alps, respectively, showing that traffic contributes on average only up to ~30% to OC. The non-fossil fraction of EC (fNF,EC), entirely attributable to primary biomass burning, was on average 42 ± 13% and 49 ± 15% for north and south of the Alps, respectively. While a high correlation was observed between fossil EC and nitrogen oxides, both primarily emitted by traffic, these species did not significantly correlate with fossil OC (OCF), which seems to suggest that a considerable amount of OCF is secondary, formed from fossil precursors. Elevated fNF,EC and fNF,OC values and the high correlation of the latter with other wood burning markers, including levoglucosan and water soluble potassium (K+) indicate that biomass burning is the major source of carbonaceous aerosols during winter-smog episodes in Switzerland. The inspection of the non-fossil OC and EC levels and the relation with levoglucosan and water-soluble K+ shows different ratios for stations north and south of the Alps, most likely because of differences in burning technologies, for these two regions in Switzerland.

scholarly journals Radiocarbon analysis of elemental and organic carbon in Switzerland during winter-smog episodes from 2008 to 2012 – Part 1: Source apportionment and spatial variability

2014 ◽  
Vol 14 (24) ◽  
pp. 13551-13570 ◽  
Author(s):  
P. Zotter ◽  
V. G. Ciobanu ◽  
Y. L. Zhang ◽  
I. El-Haddad ◽  
M. Macchia ◽  
...  
Keyword(s):  
Air Pollution ◽  
Source Apportionment ◽  
Water Soluble ◽  
Pollution Monitoring ◽  
Carbonaceous Aerosols ◽  
Air Pollution Monitoring ◽  
Wood Burning ◽  
Wide Range ◽  
The Alps ◽  
North And South

Abstract. While several studies have investigated winter-time air pollution with a wide range of concentration levels, hardly any results are available for longer time periods covering several winter-smog episodes at various locations; e.g., often only a few weeks from a single winter are investigated. Here, we present source apportionment results of winter-smog episodes from 16 air pollution monitoring stations across Switzerland from five consecutive winters. Radiocarbon (14C) analyses of the elemental (EC) and organic (OC) carbon fractions, as well as levoglucosan, major water-soluble ionic species and gas-phase pollutant measurements were used to characterize the different sources of PM10. The most important contributions to PM10 during winter-smog episodes in Switzerland were on average the secondary inorganic constituents (sum of nitrate, sulfate and ammonium = 41 ± 15%) followed by organic matter (OM) (34 ± 13%) and EC (5 ± 2%). The non-fossil fractions of OC (fNF,OC) ranged on average from 69 to 85 and 80 to 95% for stations north and south of the Alps, respectively, showing that traffic contributes on average only up to ~ 30% to OC. The non-fossil fraction of EC (fNF,EC), entirely attributable to primary wood burning, was on average 42 ± 13 and 49 ± 15% for north and south of the Alps, respectively. While a high correlation was observed between fossil EC and nitrogen oxides, both primarily emitted by traffic, these species did not significantly correlate with fossil OC (OCF), which seems to suggest that a considerable amount of OCF is secondary, from fossil precursors. Elevated fNF,EC and fNF,OC values and the high correlation of the latter with other wood burning markers, including levoglucosan and water soluble potassium (K+) indicate that residential wood burning is the major source of carbonaceous aerosols during winter-smog episodes in Switzerland. The inspection of the non-fossil OC and EC levels and the relation with levoglucosan and water-soluble K+ shows different ratios for stations north and south of the Alps (most likely because of differences in burning technologies) for these two regions in Switzerland.

scholarly journals Source apportionment of carbonaceous aerosols in Beijing with radiocarbon and organic tracers: insight into the differences between urban and rural sites

2021 ◽  
Vol 21 (10) ◽  
pp. 8273-8292
Author(s):  
Siqi Hou ◽  
Di Liu ◽  
Jingsha Xu ◽  
Tuan V. Vu ◽  
Xuefang Wu ◽  
...  
Keyword(s):  
Source Apportionment ◽  
Biomass Burning ◽  
Fine Particles ◽  
Water Soluble ◽  
Carbonaceous Aerosol ◽  
Balance Model ◽  
Gas Chromatography Mass Spectrometry ◽  
Urban Site ◽  
Carbonaceous Aerosols ◽  
Carbonaceous Particles

Abstract. Carbonaceous aerosol is a dominant component of fine particles in Beijing. However, it is challenging to apportion its sources. Here, we applied a newly developed method which combined radiocarbon (14C) with organic tracers to apportion the sources of fine carbonaceous particles at an urban (IAP) and a rural (PG) site of Beijing. PM2.5 filter samples (24 h) were collected at both sites from 10 November to 11 December 2016 and from 22 May to 24 June 2017. 14C was determined in 25 aerosol samples (13 at IAP and 12 at PG) representing low pollution to haze conditions. Biomass burning tracers (levoglucosan, mannosan, and galactosan) in the samples were also determined using gas chromatography–mass spectrometry (GC-MS). Higher contributions of fossil-derived OC (OCf) were found at the urban site. The OCf / OC ratio decreased in the summer samples (IAP: 67.8 ± 4.0 % in winter and 54.2 ± 11.7 % in summer; PG: 59.3 ± 5.7 % in winter and 50.0 ± 9.0 % in summer) due to less consumption of coal in the warm season. A novel extended Gelencsér (EG) method incorporating the 14C and organic tracer data was developed to estimate the fossil and non-fossil sources of primary and secondary OC (POC and SOC). It showed that fossil-derived POC was the largest contributor to OC (35.8 ± 10.5 % and 34.1 ± 8.7 % in wintertime for IAP and PG, 28.9 ± 7.4 % and 29.1 ± 9.4 % in summer), regardless of season. SOC contributed 50.0 ± 12.3 % and 47.2 ± 15.5 % at IAP and 42.0 ± 11.7 % and 43.0 ± 13.4 % at PG in the winter and summer sampling periods, respectively, within which the fossil-derived SOC was predominant and contributed more in winter. The non-fossil fractions of SOC increased in summer due to a larger biogenic component. Concentrations of biomass burning OC (OCbb) are resolved by the extended Gelencsér method, with average contributions (to total OC) of 10.6 ± 1.7 % and 10.4 ± 1.5 % in winter at IAP and PG and 6.5 ± 5.2 % and 17.9 ± 3.5 % in summer, respectively. Correlations of water-insoluble OC (WINSOC) and water-soluble OC (WSOC) with POC and SOC showed that although WINSOC was the major contributor to POC, a non-negligible fraction of WINSOC was found in SOC for both fossil and non-fossil sources, especially during winter. In summer, a greater proportion of WSOC from non-fossil sources was found in SOC. Comparisons of the source apportionment results with those obtained from a chemical mass balance model were generally good, except for the cooking aerosol.

scholarly journals Fossil vs. non-fossil sources of fine carbonaceous aerosols in four Chinese cities during the extreme winter haze episode in 2013

2014 ◽  
Vol 14 (19) ◽  
pp. 26257-26296 ◽  
Author(s):  
Y.-L. Zhang ◽  
R.-J. Huang ◽  
I. El Haddad ◽  
K.-F. Ho ◽  
J.-J. Cao ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Organic Carbon ◽  
Source Apportionment ◽  
Biomass Burning ◽  
Crop Residues ◽  
Water Soluble ◽  
World Health ◽  
Biomass Combustion ◽  
Carbonaceous Aerosols ◽  
Haze Episode

Abstract. During winter 2013, extremely high concentrations (i.e. 4–20 times higher than the World Health Organization guideline) of PM2.5 (particulate matter with an aerodynamic diameter <2.5 μm) were reported in several large cities in China. In this work, source apportionment of fine carbonaceous aerosols during this haze episode was conducted at four major cities in China including Xian, Beijing, Shanghai and Guangzhou. An effective statistical analysis of a combined dataset from elemental carbon (EC) and organic carbon (OC), radiocarbon (14C) and biomass-burning marker measurements using Latin-hypercube sampling allowed a quantitative source apportionment of carbonaceous aerosols. We found that fossil emissions from coal combustion and vehicle exhaust dominated EC with a mean contribution of 75 ± 8% at all sites. The remaining 25 ± 8% was exclusively attributed to biomass combustion, consistent with the measurements of biomass-burning markers such as anhydrosugars (levoglucosan and mannosan) and water-soluble potassium (K+). With a combination of the levoglucosan-to-mannosan and levoglucosan-to-K+ ratios, the major source of biomass burning in winter in China is suggested to be combustion of crop residues. The contribution of fossil sources to OC was highest in Beijing (58 ± 5%) and decreased from Shanghai (49 ± 2%) to Xian (38 ± 3%) and Guangzhou (35 ± 7%). Generally, a larger fraction of fossil OC was rather from secondary origins than primary sources for all sites. Non-fossil sources accounted on average for 55 ± 10% and 48 ± 9% of OC and TC, respectively, which suggests that non-fossil emissions were very important contributors of urban carbonaceous aerosols in China. The primary biomass-burning emissions accounted for 40 ± 8%, 48 ± 18%, 53 ± 4% and 65 ± 26% of non-fossil OC for Xian, Beijing, Shanghai and Guangzhou, respectively. Other non-fossil sources excluding primary biomass-burning were mainly attributed to formation of secondary organic carbon (SOC) from non-fossil precursors such as biomass-burning emissions. For each site, we also compared samples from moderately with heavily polluted days according to particulate matter mass. Despite a significant increase of absolute mass concentrations of primary emissions from both, fossil and non-fossil sources, during the heavily polluted events, their relative contribution to TC was even decreased, whereas the portion of SOC was consistently increased at all sites. This observation indicates that SOC was an important fraction in the increment of carbonaceous aerosols during the haze episode in China.

scholarly journals Source apportionment and dynamic changes of carbonaceous aerosols during the haze bloom–decay process in China based on radiocarbon and organic molecular tracers

2015 ◽  
Vol 15 (23) ◽  
pp. 34949-34979 ◽  
Author(s):  
J. Liu ◽  
J. Li ◽  
D. Liu ◽  
P. Ding ◽  
C. Shen ◽  
...  
Keyword(s):  
Organic Carbon ◽  
Source Apportionment ◽  
Biomass Burning ◽  
South China ◽  
Fossil Fuel ◽  
Decay Process ◽  
Water Soluble ◽  
Total Carbon ◽  
Carbonaceous Aerosols ◽  
Fossil Carbon

Abstract. Fine carbonaceous aerosols (CAs) is the key factor influencing the currently filthy air in megacities of China, yet seldom study simultaneously focuses on the origins of different CAs species using specific and powerful source tracers. Here, we present a detailed source apportionment for various CAs fractions, including organic carbon (OC), water-soluble OC (WSOC), water-insoluble OC (WIOC), elemental carbon (EC) and secondary OC (SOC) in the largest cities of North (Beijing, BJ) and South China (Guangzhou, GZ), respectively, using the measurements of radiocarbon and anhydrosugars. Results show that non-fossil fuel sources such as biomass burning and biogenic emission make a significant contribution to the total CAs in Chinese megacities: 56 ± 4 % in BJ and 46 ± 5 % in GZ, respectively. The relative contributions of primary fossil carbon from coal and liquid petroleum combustions, primary non-fossil carbon and secondary organic carbon (SOC) to total carbon are 19, 28 and 54 % in BJ, and 40, 15 and 46 % in GZ, respectively. Non-fossil fuel sources account for 52 % in BJ and 71 % in GZ of SOC, respectively. These results suggest that biomass burning has a greater influence on regional particulate air pollution in North China than in South China. We observed an unabridged haze bloom–decay process in South China, which illustrates that both primary and secondary matter from fossil sources played a key role in the blooming phase of the pollution episode, while haze phase is predominantly driven by fossil-derived secondary organic matter and nitrate.

scholarly journals Source apportionment and dynamic changes of carbonaceous aerosols during the haze bloom-decay process in China based on radiocarbon and organic molecular tracers

2016 ◽  
Vol 16 (5) ◽  
pp. 2985-2996 ◽  
Author(s):  
Junwen Liu ◽  
Jun Li ◽  
Di Liu ◽  
Ping Ding ◽  
Chengde Shen ◽  
...  
Keyword(s):  
Organic Carbon ◽  
Source Apportionment ◽  
Biomass Burning ◽  
South China ◽  
Fossil Fuel ◽  
Decay Process ◽  
Water Soluble ◽  
Total Carbon ◽  
Carbonaceous Aerosols ◽  
Fossil Carbon

Abstract. Fine carbonaceous aerosols (CAs) is the key factor influencing the currently filthy air in megacities in China, yet few studies simultaneously focus on the origins of different CAs species using specific and powerful source tracers. Here, we present a detailed source apportionment for various CAs fractions, including organic carbon (OC), water-soluble OC (WSOC), water-insoluble OC (WIOC), elemental carbon (EC) and secondary OC (SOC) in the largest cities of North (Beijing, BJ) and South China (Guangzhou, GZ), using the measurements of radiocarbon and anhydrosugars. Results show that non-fossil fuel sources such as biomass burning and biogenic emission make a significant contribution to the total CAs in Chinese megacities: 56 ± 4 in BJ and 46 ± 5 % in GZ, respectively. The relative contributions of primary fossil carbon from coal and liquid petroleum combustions, primary non-fossil carbon and secondary organic carbon (SOC) to total carbon are 19, 28 and 54 % in BJ, and 40, 15 and 46 % in GZ, respectively. Non-fossil fuel sources account for 52 in BJ and 71 % in GZ of SOC, respectively. These results suggest that biomass burning has a greater influence on regional particulate air pollution in North China than in South China. We observed an unabridged haze bloom-decay process in South China, which illustrates that both primary and secondary matter from fossil sources played a key role in the blooming phase of the pollution episode, while haze phase is predominantly driven by fossil-derived secondary organic matter and nitrate.

scholarly journals Source Apportionment of Carbonaceous Aerosols in Beijing with Radiocarbon and Organic Tracers: Insight into the Differences between Urban and Rural Sites

2020 ◽  
Author(s):  
Siqi Hou ◽  
Di Liu ◽  
Jingsha Xu ◽  
Tuan V. Vu ◽  
Xuefang Wu ◽  
...  
Keyword(s):  
Source Apportionment ◽  
Biomass Burning ◽  
Fine Particles ◽  
Warm Season ◽  
Water Soluble ◽  
Carbonaceous Aerosol ◽  
Balance Model ◽  
Urban Site ◽  
Carbonaceous Aerosols ◽  
Carbonaceous Particles

Abstract. Carbonaceous aerosol is the dominant component of fine particles in Beijing. However, it is challenging to apportion its sources. Here, we applied a newly developed method which combined radiocarbon (14C) with organic tracers to apportion the sources of fine carbonaceous particles at an urban (IAP) and a rural (PG) site of Beijing. PM2.5 filter samples (24-h) were collected at both sites from 10 November to 11 December 2016 and from 22 May to 24 June 2017. 14C was determined in 25 aerosol samples (13 at IAP and 12 at PG) representing low pollution to haze conditions. Biomass burning tracers (levoglucosan, mannosan and galactosan) in the samples were also determined using GC-MS. Higher contributions of fossil-derived OC (OCf) were found at the urban site. OCf to OC ratio decreased in the summer samples (IAP: 67.8 ± 4.0 % in winter and 54.2 ± 11.7 % in summer; PG: 59.3 ± 5.7 % in winter and 50.0 ± 9.0 % in summer) due to less consumption of coal in the warm season. A novel extended Gelencsér method incorporating the 14C and organic tracer data was developed to estimate the fossil and non-fossil sources of primary and secondary OC (POC and SOC). It showed that fossil-derived POC was the largest contributor to OC (35.8 ± 10.5 % and 34.1 ± 8.7 % in winter time for IAP and PG, 28.9 ± 7.4 % and 28.9 ± 9.6 % in summer), regardless of season. SOC contributed 50.0 ± 12.3 % and 47.2 ± 15.5 % at IAP, and 42.0 ± 11.7 % and 43.0 ± 13.4 % at PG in the winter and summer sampling periods respectively, within which the fossil-derived SOC was predominant and contributed more in winter. The non-fossil fractions of SOC increased in summer due to a larger biogenic component. Concentrations of biomass burning OC (OCbb) are resolved by the extended Gelencsér method with average contributions (to total OC) of 10.6 ± 1.7 % and 10.4 ± 1.5 % in winter at IAP and PG, and 6.5 ± 5.2 % and 17.9 ± 3.5 % in summer, respectively. Correlations of water-insoluble OC (WINSOC), water-soluble OC (WSOC) with POC and SOC showed that although WINSOC was the major contributor to POC, a non-negligible fraction of WINSOC was found in SOC for both fossil and non-fossil sources especially during winter. In summer, a greater proportion of WSOC from non-fossil sources was found in SOC. Comparisons of the source apportionment results with those obtained from a Chemical Mass Balance model were generally good, except for the cooking aerosol.

A COMPARATIVE ANALYSIS AND REVIEW OF VARIOUS AIR POLLUTION MONITORING SCHEMES

2016 ◽  
Vol 5 (1) ◽  
pp. 30
Author(s):  
HASAN MOHD. TAHSEENUL ◽  
CHOURASIA VIJAY S. ◽  
ASUTKAR SANJAY M. ◽  
◽  
◽  
...  
Keyword(s):  
Air Pollution ◽  
Comparative Analysis ◽  
Pollution Monitoring ◽  
Air Pollution Monitoring

scholarly journals H2020 project CAPTOR dataset: raw data collected by low-cost MOX ozone sensors in a real air pollution monitoring network.

Data in Brief ◽  
2021 ◽  
pp. 107127
Author(s):  
Jose M. Barcelo-Ordinas ◽  
Pau Ferrer-Cid ◽  
Jorge Garcia-Vidal ◽  
Mar Viana ◽  
Ana Ripoll
Keyword(s):  
Air Pollution ◽  
Low Cost ◽  
Monitoring Network ◽  
Pollution Monitoring ◽  
Raw Data ◽  
Air Pollution Monitoring

Research on air pollution system based on neural network

2020 ◽  
pp. 1-11
Author(s):  
Zhiqi Jiang ◽  
Xidong Wang
Keyword(s):  
Neural Network ◽  
Air Pollution ◽  
Image Features ◽  
Air Pollutant ◽  
Pollution Monitoring ◽  
System Model ◽  
Process Data ◽  
Deep Convolutional Neural Networks ◽  
Air Pollution Monitoring ◽  
Neural Network Algorithm

This paper conducts in-depth research and analysis on the commonly used models in the simulation process of air pollutant diffusion. Combining with the actual needs of air pollution, this paper builds an air pollution system model based on neural network based on neural network algorithm, and proposes an image classification method based on deep learning and Gaussian aggregation coding. Moreover, this paper proposes a Gaussian aggregation coding layer to encode image features extracted by deep convolutional neural networks. Learn a fixed-size dictionary to represent the features of the image for final classification. In addition, this paper constructs an air pollution monitoring system based on the actual needs of the air system. Finally, this article designs a controlled experiment to verify the model proposed in this article, uses mathematical statistics to process data, and scientifically analyze the statistical results. The research results show that the model constructed in this paper has a certain effect.

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