Spatial Distribution Of Volatile Organic Compounds Research Articles

Pollution Characteristics and Risk Assessment of Volatile Organic Compounds in Songhua Lake, China

In order to assess the dangers to human health and the environment from Songhua Lake's volatile organic compounds (VOCs) pollution. A total of 18 VOCs were found in the water samples that were collected at 26 sampling locations in Songhua Lake utilizing the purge and trap technique and gas chromatography-mass spectrometry (GC-MS). Toluene and naphthalene had the highest detection rates among them, reaching 96.15%; trans-1,2-dichloroethylene, 1,2-dichloroethane, and isopropyl benzene had the lowest rates, only 3.85%. The maximum and average concentrations of 1,1-dichloroethane were 20.93 μg/L and 4.16 μg/L, respectively, the maximum concentration of isopropyl benzene was only 0.02 μg/L, and the average concentration was also the lowest. The spatial distribution of VOCs in Song Hua Lake was typically described as "high in the northwest and low in the southeast," with a concentration range of 0.00 to 23.21 μg/L. An examination of the current situation reveals that human activity-related ecological deterioration is the primary cause of the VOCs contamination in Songhua Lake. The results of the risk assessment revealed that there were only moderate ecological risks to aquatic organisms and that the non-carcinogenic and carcinogenic risk indices of Songhua Lake were within the safe range. Additionally, there were no non-carcinogenic or carcinogenic threats to the health of people as a whole.

Spatial and temporal variations of volatile organic compounds using passive air samplers in the multi-industrial city of Ulsan, Korea.

The source-receptor relationship of volatile organic compounds (VOCs) is an important environmental concern, particularly in large industrial cities; however, only a few studies have identified VOC sources using high spatial resolution data. In this study, 28 VOCs were monitored in Ulsan, the biggest multi-industrial city in Korea. Passive air samplers were seasonally deployed at eight urban and six industrial sites. The target compounds were detected at all sites. No significant seasonal variations of VOCs were observed probably due to the continuous emissions from major industrial facilities. Benzene, toluene, ethylbenzene, xylenes, and styrene accounted for 66-86% of the concentration of Σ28 VOCs. The spatial distribution of the individual VOCs clearly indicated that petrochemical, automobile, non-ferrous, and shipbuilding industries were major VOC sources. Seasonal wind patterns were found to play a role in the spatial distribution of VOCs. Diagnostic ratios also confirmed that the industrial complexes were the dominant VOC sources. The results of principal component analysis and correlation analyses identified the influence of specific compounds from each industrial complex on individual sites. To the best of our knowledge, this is the first comprehensive report on the seasonal distribution of VOCs with high spatial resolution in a metropolitan industrial city in Korea.

A land use regression model for predicting ambient volatile organic compound concentrations in Toronto, Canada

More than 25 studies have employed land use regression (LUR) models to estimate nitrogen oxides and to a lesser extent particulate matter indicators, but these methods have been less commonly applied to ambient concentrations of volatile organic compounds (VOCs). Some VOCs have high plausibility as sources of health effects and others are specific indicators of motor vehicle exhaust. We used LUR models to estimate spatial variability of VOCs in Toronto, Canada. Benzene, n-hexane and total hydrocarbons (THC) were measured from July 25 to August 9, 2006 at 50 locations using the TraceAir organic vapor monitors. Nitrogen dioxide (NO 2) was also sampled to assess its spatial pattern agreement with VOC exposures. Buffers for land use, population density, traffic density, physical geography, and remote sensing measures of greenness and surface brightness were also tested. The remote sensing measures have the highest correlations with VOCs and NO 2 levels (i.e., explains >36% of the variance). Our regression models explain 66–68% of the variance in the spatial distribution of VOCs, compared to 81% for the NO 2 model. The ranks of agreement between various VOCs range from 48 to 63% and increases substantially – up to 75% – for the top and bottom quartile groups. Agreements between NO 2 and VOCs are much smaller with an average rank of 36%. Future epidemiologic studies may therefore benefit from using VOCs as potential toxic agents for traffic-related pollutants.