• Title/Summary/Keyword: anthropogenic volatile organic compounds

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Environmental Geochemical characteristics of urban runoff and sediments from gully pot along the main roads in urban area: Heavy metals and VOCs contamination (대도시 지표수와 퇴적물의 환경지구화학적 특성: 중금속 및 VOCs 오염)

  • 이평구;박성원;전치완;신성천
    • Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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    • 2000.11a
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    • pp.129-135
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    • 2000
  • Four types of land use were selected for sampling and study with different characteristics of heavy metal contamination during the period from August 1998 to June 2000. A series of studies have been carried out concerning the physicochemical characteristics of the sediments settling down in a gully pot to evaluate the contamination of Pb, Zn, Cd, Co, Cr and Cu. An examination of six elements indicated that Zn, Cu and Pb were the heavy metals severely impacted by anthropogenic input in Seoul. An assessment of 60 volatile organic compounds (VOCs) in urban runoff and ground water was conducted based on samples collected from 31 sites and 12 wells, respectively, in Seoul City. The higher levels of alkyl benzenes in urban runoff indicated that Seoul areas were mainly contaminated through traffic sources.

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Emission Characteristics of VOC due to Major Industrial Activities in the Ban Wall Industrial Complex (안산시 반월공단을 중심으로 한 주요 배출시설의 업종 및 배출시설별 VOC의 배출특성)

  • Im, M.S.;Kim, K.H.;Choi, Y.J.;Jeon, E.C.
    • Journal of Korean Society for Atmospheric Environment
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    • v.22 no.3
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    • pp.325-336
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    • 2006
  • The presence of volatile organic compounds (VOC), produced and released from both anthropogenic and natural sources, can accelerate the degradation of air quality in the surrounding area. In this study, we investigated the emission concentrations of VOC based on a total of 115 sample analysis made from 47 companies (representing 17 types of industry) at the Ban Wall industrial complex (Jun. 2004 to Jan. 2005). Through a statistical analysis of these measurement data, we inspected the emission characteristics of VOC in relation with industrial type and processing unit. When these data were compared each other, toluene was found to record the highest value of 423 ppb followed by ethylbenzene (68.3 ppb), m, p-xylene (43.6 ppb), o-xylene (27.2 ppb), styrene (23.9 ppb), and benzene (16.4 pub). In addition, by converting these VOC concentration data into malodor intensity, we attempted to account for their distribution patterns in terms of relative contribution to the malodor formation. The results of odor intensity conversion generally indicated that the odor intensities of individual VOC do not exceed the degree of 1. When our VOC results were compared against other odorous compounds measured concurrently, the results were highly contrasting each other. Despite relative insignificance as odorous compounds, these VOCs are generally found ubiquitously and in abundant quantities in this strong source area.

Seasonal impact to air qualities in industrial areas of the Arabian Gulf region

  • Al-Taani, Ahmed A.;Howari, Fares M.;Nazzal, Yousef;Yousef, Ahmad
    • Environmental Engineering Research
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    • v.23 no.2
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    • pp.143-149
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    • 2018
  • Air quality conditions and pollution status have been evaluated in the industrial area between Sharjah and Ajman border in UAE. Daily concentrations of $O_3$, CO, $NO_2$, $SO_2$, $PM_{2.5}$, $PM_{10}$, Total Volatile Organic Compounds (TVOC) and Total Suspended Particulate (TSP) have been monitored from Sept. 2015 to April 2016. The monthly average concentrations of $O_3$, CO, $NO_2$, $SO_2$, TVOC were within the UAE ambient air quality standards during the survey period. However, $PM_{10}$ and TSP levels exceeded the recommended limits in Sept. 2015, Oct. 2015 and March 2016. Temporal variations in air quality parameters showed highest levels in March 2016 for $PM_{2.5}$, $PM_{10}$, $NO_2$, TVOC and TSP, whereas $O_3$, $SO_2$ and CO showed relatively low values in this month. $PM_{2.5}$ levels in ambient air were above the EPA guideline of $35{\mu}g/m^3$ in all months. $PM_{2.5}$ was the critical ambient air pollutant with Index for Pollutant ($I_p$) values varying from 103-209, indicating Air Quality Index categories of unhealthy for sensitive groups (62.5%) to unhealthy (25%) to very unhealthy (12.5%). The $I_p$ average values of $PM_{2.5}$ decreased from Sept. 2015 to reach lowest value in Dec. 2015 before increasing gradually, peaking in March 2016. These results suggest the potential health risks associated with $PM_{2.5}$ is low in winter, where the prevailing meteorological conditions of lower temperatures, higher humidity, higher wind speed reduced particulate matter. The results revealed the industrial area is impacted by anthropogenic and natural sources of particulate matter.

Numerical Analysis on Biogenic Emission Sources Contributing to Urban Ozone Concentration in Osaka, Japan

  • Nishimura, Hiroshi;Shimadera, Hikari;Kondo, Akira;Akiyama, Kazuyo;Inoue, Yoshio
    • Asian Journal of Atmospheric Environment
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    • v.9 no.4
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    • pp.259-271
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    • 2015
  • This study conducted analyses on biogenic volatile organic compounds (BVOC) emission sources contributing to urban ozone ($O_3$) concentration in Osaka Prefecture, Japan in summer 2010 by using the Weather Research and Forecasting model (WRF) version 3.5.1 and the Community Multiscale Air Quality model (CMAQ) version 5.0.1. This prefecture is characterized by highly urbanized area with small forest area. The contributions of source regions surrounding Osaka were estimated by comparing the baseline case and zero-out cases for BVOC emissions from each source region. The zero-out emission runs showed that the BVOC emissions substantially contributed to urban $O_3$ concentration in Osaka (10.3 ppb: 15.9% of mean daily maximum 1-h $O_3$ concentration) with day-by-day variations of contributing source regions, which were qualitatively explained by backward trajectory analyses. Although $O_3$ concentrations were especially high on 23 July and 2 August 2010, the contribution of BVOC on 23 July (35.4 ppb: 25.6% of daily maximum $O_3$) was much larger than that on 2 August (20.9 ppb: 14.2% of daily maximum $O_3$). To investigate this difference, additional zero-out cases for anthropogenic VOC (AVOC) emissions from Osaka and for VOC emissions on the target days were performed. On 23 July, the urban $O_3$ concentration in Osaka was dominantly increased by the transport from the northwestern region outside Osaka with large contribution of $O_3$ that was produced through BVOC reactions by the day before and was retained over the nocturnal boundary layer. On 2 August, the concentration was dominantly increased by the local photochemical production inside Osaka under weak wind condition with the particularly large contribution of AVOC emitted from Osaka on the day.

VOCs Emission Characteristics and Psychological Effects of Interior Decorated Conifers (침엽수 판재의 VOCs 방산특성 및 심신안정 효과)

  • Lee, Hee-Young;Park, Sang-Bum;Kim, Eun-Il;Lee, Sang-Min;Park, Jong-Young
    • Journal of the Korea Furniture Society
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    • v.20 no.2
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    • pp.115-121
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    • 2009
  • This study examined the emission characteristics and psychological effects of volatile organic compounds (VOCs) emitted from wooden boards made of Pinus densiflora and Chamaecyparis obtusa, conifer commonly found in korean forests. Boards made of those species were used to decorate interior of a test room. Different proportions of interior (20%, 40%, 60%, 80% and 100% against the entire interior of the room) were decorated. Electroencephalogram and VOCs in the test room were measured 24 hours after interior decorated. As the results, when 40% of interior of the room decorated with both species of boards, the largest amount of alpha wave was detected. For board made of P. densiflora, as the proportion of interior decorated increased both natural VOCs(NVOCs) and anthropogenic VOCs(AVOCs) were increased. on the other hand, When interior decorated with board made of C, obtusa, little differences in VOCs with different area of interior decorated was detected. Board made of P. densiflor emitted a slightly higher amount of AVOCs than boards made of C. obtusa. NVOCs emitted from board made of P. densiflora was three to fifteen times more than NVOCs emitted from board made of C. obtusa.

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Characteristics of Ozone Concentrations around an Urban Valley based on the Intensive Air Quality Measurement during Spring and Summer of 2006 (2006년 봄, 여름철 대기오염물질 집중측정을 통한 도시 계곡지역의 오존농도 특성 분석)

  • Song, Sang-Keun;Kim, Yoo-Keun;Kang, Jae-Eun
    • Journal of Korean Society for Atmospheric Environment
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    • v.25 no.4
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    • pp.289-303
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    • 2009
  • The chemical and meteorological effects on the concentration variations of ozone ($O_3$) were evaluated based on the intensive air quality measurement (5 pollutants and aromatic volatile organic compounds (AVOCs)) in and out-side an urban valley during spring and summer of 2006. The 5 pollutants measured in the study area include $O_3$, $NO_2$, NO, $PM_{10}$, and CO; the AVOCs include benzene (BEN), toluene (TOL), ethylbenzene (EB), m,p-xylene (MPX), and o-xylene (OX). For the purpose of this study, study areas were classified into two categories: valley area (VA) with a semi-closed topography covering a number of industrial complex, public building, and mountains and non-valley area (NVA) surrounding the suburban and residential areas. In general, the mean concentration levels of most pollutants (except for $PM_{10}$) in the VA were higher than those in the NVA. It was found that the average $O_3$ increase in the VA during spring might result from the combined effects such as the photochemical production from diverse anthropogenic sources and the $O_3$ accumulation due to geographical features (e.g., the semi-closed topography) and wind conditions (e.g., a low wind speed). In addition, the nocturnal $O_3$ increase in the VA during spring was primarily caused by local wind conditions (e.g., mountain and valley winds) with the low wind speed (approximately $1{\sim}2\;m\;s^{-1}$). On the other hand, the $O_3$ difference between the two areas during summer might be because of the photo-chemical production with the $O_3$ precursors (especially the AVOCs) rather than the contribution of wind conditions.

Potential Source of PM10, PM2.5, and OC and EC in Seoul During Spring 2016 (2016년 봄철 서울의 PM10, PM2.5 및 OC와 EC 배출원 기여도 추정)

  • Ham, Jeeyoung;Lee, Hae Jung;Cha, Joo Wan;Ryoo, Sang-Boom
    • Atmosphere
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    • v.27 no.1
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    • pp.41-54
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    • 2017
  • Organic carbon (OC) and elemental carbon (EC) in $PM_{2.5}$ were measured using Sunset OC/EC Field Analyzer at Seoul Hwangsa Monitoring Center from March to April, 2016. The mean concentrations of OC and EC during the entire period were $4.4{\pm}2.0{\mu}gC\;m^{-3}$ and $1.4{\pm}0.6{\mu}gC\;m^{-3}$, respectively. OC/EC ratio was $3.4{\pm}1.0$. The average concentrations of $PM_{10}$ and $PM_{2.5}$ were $57.4{\pm}25.9$ and $39.7{\pm}19.8{\mu}g\;m^{-3}$, respectively, which were detected by an optical particle counter. The OC and EC peaks were observed in the morning, which were impacted by vehicle emission, however, their diurnal variations were not noticeable. This is determined to be contributed by the long-range transported OC or secondary formation via photochemical reaction by volatile organic compounds at afternoon. A conditional probability function (CPF) model was used to identify the local source of pollution. High concentrations of $PM_{10}$ and $PM_{2.5}$ were observed from the westerly wind, regardless of wind speed. When wind velocity was high, a mixing plume of dust and pollution during long-range transport from China in spring was observed. In contrast, pollution in low wind velocity was from local source, regardless of direction. To know the effect of long-range transport on pollution, a concentration weighted trajectory (CWT) model was analyzed based on a potential source contribution function (PSCF) model in which 75 percentiles high concentration was picked out for CWT analysis. $PM_{10}$, $PM_{2.5}$, OC, and EC were dominantly contributed from China in spring, and EC results were similar in both PSCF and CWT. In conclusion, Seoul air quality in spring was mainly affected by a mixture of local pollution and anthropogenic pollutants originated in China than the Asian dust.

Influence of Land Cover Map and Its Vegetation Emission Factor on Ozone Concentration Simulation (토지피복 지도와 식생 배출계수가 오존농도 모의에 미치는 영향)

  • Kyeongsu Kim;Seung-Jae Lee
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.25 no.1
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    • pp.48-59
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    • 2023
  • Ground-level ozone affects human health and plant growth. Ozone is produced by chemical reactions between oxides of nitrogen (NOx) and volatile organic compounds (VOCs) from anthropogenic and biogenic sources. In this study, two different land cover and emission factor datasets were input to the MEGAN v2.1 emission model to examine how these parameters contribute to the biogenic emissions and ozone production. Four input sensitivity scenarios (A, B, C and D) were generated from land cover and vegetation emission factors combination. The effects of BVOCs emissions by scenario were also investigated. From air quality modeling result using CAMx, maximum 1 hour ozone concentrations were estimated 62 ppb, 60 ppb, 68 ppb, 65 ppb, 55 ppb for scenarios A, B, C, D and E, respectively. For maximum 8 hour ozone concentration, 57 ppb, 56 ppb, 63 ppb, 60 ppb, and 53 ppb were estimated by scenario. The minimum difference by land cover was up to 25 ppb and by emission factor that was up to 35 ppb. From the modeling performance evaluation using ground ozone measurement over the six regions (East Seoul, West Seoul, Incheon, Namyangju, Wonju, and Daegu), the model performed well in terms of the correlation coefficient (0.6 to 0.82). For the 4 urban regions (East Seoul, West Seoul, Incheon, and Namyangju), ozone simulations were not quite sensitive to the change of BVOC emissions. For rural regions (Wonju and Daegu) , however, BVOC emission affected ozone concentration much more than previously mentioned regions, especially in case of scenario C. This implies the importance of biogenic emissions on ozone production over the sub-urban to rural regions.