scholarly journals An Integrated Method for Factor Number Selection of PMF Model: Case Study on Source Apportionment of Ambient Volatile Organic Compounds in Wuhan

Atmosphere ◽  
2018 ◽  
Vol 9 (10) ◽  
pp. 390 ◽  
Author(s):  
Fenjuan Wang ◽  
Zhenyi Zhang ◽  
Costanza Acciai ◽  
Zhangxiong Zhong ◽  
Zhaokai Huang ◽  
...  
Keyword(s):  
Volatile Organic Compounds ◽  
Source Apportionment ◽  
Correlation Coefficient ◽  
Organic Compounds ◽  
Industrial Emissions ◽  
Integrated Method ◽  
Pmf Model ◽  
Volatile Organic ◽  
Measurement Period

The positive matrix factorization (PMF) model is widely used for source apportionment of volatile organic compounds (VOCs). The question about how to select the proper number of factors, however, is rarely studied. In this study, an integrated method to determine the most appropriate number of sources was developed and its application was demonstrated by case study in Wuhan. The concentrations of 103 ambient volatile organic compounds (VOCs) were measured intensively using online gas chromatography/mass spectrometry (GC/MS) during spring 2014 in an urban residential area of Wuhan, China. During the measurement period, the average temperature was approximately 25 °C with very little domestic heating and cooling. The concentrations of the most abundant VOCs (ethane, ethylene, propane, acetylene, n-butane, benzene, and toluene) in Wuhan were comparable to other studies in urban areas in China and other countries. The newly developed integrated method to determine the most appropriate number of sources is in combination of a fixed minimum threshold value for the correlation coefficient, the average weighted correlation coefficient of each species, and the normalized minimum error. Seven sources were identified by using the integrated method, and they were vehicular emissions (45.4%), industrial emissions (22.5%), combustion of coal (14.7%), liquefied petroleum gas (LPG) (9.7%), industrial solvents (4.4%), and pesticides (3.3%) and refrigerants. The orientations of emission sources have been characterized taking into account the frequency of wind directions and contributions of sources in each wind direction for the measurement period. It has been concluded that the vehicle exhaust contribution is greater than 40% distributed in all directions, whereas industrial emissions are mainly attributed to the west southwest and south southwest.

scholarly journals Spatial Distribution, Source Apportionment, Ozone Formation Potential, and Health Risks of Volatile Organic Compounds over a Typical Central Plain City in China

Atmosphere ◽  
2020 ◽  
Vol 11 (12) ◽  
pp. 1365
Author(s):  
Kun He ◽  
Zhenxing Shen ◽  
Jian Sun ◽  
Yali Lei ◽  
Yue Zhang ◽  
...  
Keyword(s):  
Volatile Organic Compounds ◽  
Source Apportionment ◽  
Organic Compounds ◽  
Health Risks ◽  
Urban Areas ◽  
High Time Resolution ◽  
Ozone Formation ◽  
Industrial Site ◽  
Industrial Emissions ◽  
Volatile Organic

The profiles, contributions to ozone formation, and associated health risks of 56 volatile organic compounds (VOCs) species were investigated using high time resolution observations from photochemical assessment monitoring stations (PAMs) in Luoyang, China. The daily averaged concentration of total VOCs (TVOCs) was 21.66 ± 10.34 ppbv in urban areas, 14.45 ± 7.40 ppbv in suburbs, and 37.58 ± 13.99 ppbv in an industrial zone. Overall, the VOCs levels in these nine sites followed a decreasing sequence of alkanes > aromatics > alkenes > alkyne. Diurnal variations in VOCs exhibited two peaks at 8:00–9:00 and 19:00–20:00, with one valley at 23:00–24:00. Source apportionment indicated that vehicle and industrial emissions were the dominant sources of VOCs in urban and suburban sites. The industrial site displayed extreme levels, with contributions from petrochemical-related sources of up to 38.3%. Alkenes and aromatics displayed the highest ozone formation potentials because of their high photochemical reactivity. Cancer and noncancer risks in the industrial site were higher than those in the urban and suburban areas, and USEPA possible risk thresholds were reached in the industrial site, indicating PAMs VOC–related health problems cannot be ignored. Therefore, vehicle and industrial emissions should be prioritized when considering VOCs and O3 control strategies in Luoyang.

Characteristics, reactivity and source apportionment of ambient volatile organic compounds (VOCs) in a typical tourist city

2019 ◽  
Vol 215 ◽  
pp. 116898 ◽  
Author(s):  
Xufeng Zhang ◽  
Yuanyuan Yin ◽  
Jianhui Wen ◽  
Shilei Huang ◽  
Deming Han ◽  
...  
Keyword(s):  
Volatile Organic Compounds ◽  
Source Apportionment ◽  
Organic Compounds ◽  
Volatile Organic

scholarly journals Source apportionment of volatile organic compounds in the northwest Indo-Gangetic Plain using a positive matrix factorization model

2019 ◽  
Vol 19 (24) ◽  
pp. 15467-15482 ◽  
Author(s):  
◽  
Baerbel Sinha ◽  
Vinayak Sinha
Keyword(s):  
Volatile Organic Compounds ◽  
Organic Compounds ◽  
Waste Disposal ◽  
Isocyanic Acid ◽  
Transport Sector ◽  
Emission Inventories ◽  
Gangetic Plain ◽  
Pmf Model ◽  
Volatile Organic ◽  
Indo Gangetic Plain

Abstract. In this study we undertook quantitative source apportionment for 32 volatile organic compounds (VOCs) measured at a suburban site in the densely populated northwest Indo-Gangetic Plain using the US EPA PMF 5.0 model. Six sources were resolved by the PMF model. In descending order of their contribution to the total VOC burden these are “biofuel use and waste disposal” (23.2 %), “wheat-residue burning”(22.4 %), “cars” (16.2 %), “mixed daytime sources”(15.7 %) “industrial emissions and solvent use”(11.8 %), and “two-wheelers” (8.6 %). Wheat-residue burning is the largest contributor to the total ozone formation potential (32.4 %). For the emerging contaminant isocyanic acid, photochemical formation from precursors (37 %) and wheat-residue burning (25 %) were the largest contributors to human exposure. Wheat-residue burning was also the single largest source of the photochemical precursors of isocyanic acid, namely, formamide, acetamide and propanamide, indicating that this source must be most urgently targeted to reduce human concentration exposure to isocyanic acid in the month of May. Our results highlight that for accurate air quality forecasting and modeling it is essential that emissions are attributed only to the months in which the activity actually occurs. This is important for emissions from crop residue burning, which occur in May and from mid-October to the end of November. The SOA formation potential is dominated by cars (36.9 %) and two-wheelers (21.1 %), which also jointly account for 47% of the human class I carcinogen benzene in the PMF model. This stands in stark contrast to various emission inventories which estimate only a minor contribution of the transport sector to the benzene exposure (∼10 %) and consider residential biofuel use, agricultural residue burning and industry to be more important benzene sources. Overall it appears that none of the emission inventories represent the regional emissions in an ideal manner. Our PMF solution suggests that transport sector emissions may be underestimated by GAINSv5.0 and EDGARv4.3.2 and overestimated by REASv2.1, while the combined effect of residential biofuel use and waste disposal emissions as well as the VOC burden associated with solvent use and industrial sources may be overestimated by all emission inventories. The agricultural waste burning emissions of some of the detected compound groups (ketones, aldehydes and acids) appear to be missing in the EDGARv4.3.2 inventory.

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