WHY WE ARE ADDING AIR TO OFF GAS

 The air given to HD & HDR (High pressure de composer & HD Re boiler) by GB 401 (Blower) for Passivation of the stainless steel and different equipment for passivation

pbaboo

Participant

• Expert

Offline

Registered On: August 8, 2014

Topics: 1

Replies: 935

Dear Sravan Kumar,
Your Process is MTC so, the whole air given to CO2 compressor in suction line for passivation. Your process is conventional type means you have no stripper. The passivation air should be just sufficient for passivation because finally all the inerts vent out through M.P. section along with inerts some amount of ammonia also loosed through it.
In non-conventional or stripping process some amount of air given to stripper bottom for bottom dome passivation however Titanium stripper not required additional air for passivation some dissolved oxygen is sufficient for passivation.
The CO2 having some amount of Hydrogen so the chances of explosion in MP section.
There are following manner to avoid explosive mixture
1. To remove Hydrogen in CO2 Compressor.
2. To add NG in MP condenser (in case of recovery of inerts gas as fuel.)
3. To add steam in MP vents d/s if inerts gas not recovered (vent to B/D)
Danger of Choking Burner in case of recovering inerts as a fuel,
The NG is having some amount of CO2 (2-5% depends upon source), so the Carbonate/Carbamate formation takes place and resulted choking of burner to avoid this phenomenon Some separate burner to be used for inerts fuel don’t mixed with NG.
Some plants recovers these inerts as a fuels.
If you remove Hydrogen in CO2 compressor then No question from recovering fuel because fuel (Hydrogen) already remove from Compressor.

Newly designed ammonia receiver

https://ureaknowhow.com/newly-designed-ammonia-receiver/

EPFO extends three months’ time for Employers to upload wage details etc. regarding Pension on Higher Wages

 

EPFO extends three months’ time for Employers to upload wage details etc. regarding Pension on Higher Wages

Posted On: 29 SEP 2023 6:00PM by PIB Delhi

Earlier an online facility was made available by EPFO for submitting Applications for Validation of Option /Joint Options for pension on higher wages. The facility was for eligible pensioners / members in compliance with the Hon’ble Supreme Court order dated 04.11.2022. The facility was launched on 26.02.2023 and was to remain available only till 03.05.2023. However, considering the representations of the employees, the time limit was extended to 26.06.2023 in order to provide complete four months’ time to eligible pensioners / members for filing applications.

A last opportunity of 15 days was further given to remove any difficulty faced by the eligible pensioners/ members. Accordingly, the last date for submission of Applications for Validation of Option / Joint Options by employees was extended to 11.07.2023.  17.49 lakh Applications for Validation of Option / Joint Options have been received from pensioners / members till 11.07.2023.

In view of representations received from Employers & Employers’ Associations wherein requests were made to extend time period for uploading wage details of applicant pensioners / members, the employers were also given further period of three months to submit wage details etc. online latest by 30.09.2023.

Now, again many representations have been received from Employers & Employers’ Associations wherein requests have been made to extend further time period for uploading wage details of applicant pensioners / members. 5.52 lakh Applications for Validation of Option / Joint Options are still pending with employers, as on 29.09.2023.

Therefore, the request has been considered sympathetically and the Chairman, Central Board of Trustees has extended the time, for the employers to submit wage details etc till 31.12.2023.

PM urges citizens to join Shramdaan on Oct 1, 2023

 

PM urges citizens to join Shramdaan on Oct 1, 2023

Posted On: 29 SEP 2023 10:12AM by PIB Delhi

The Prime Minister, Shri Narendra Modi has urged citizens to join the Shramdaan, a cleanliness initiative as part of Swachh Bharat on 1st October 2023 at 10 AM. 

Sharing a post on X by Swachh Bharat Urban, the Prime Minister said;

“1st October at 10 AM, we come together for a pivotal cleanliness initiative. 

A Swachh Bharat is a shared responsibility, and every effort counts. Join this noble endeavour to usher in a cleaner future.”

Environ Eng Sci. 2012 Apr; 29(4): 262–269.

doi: 10.1089/ees.2010.0421

PMCID: PMC3313607

PMID: 22493559

Nonmethane Hydrocarbons in Ambient Air of Hazy and Normal Days in Foshan, South China

Songjun Guo,1 Fumo Yang,2 Jihua Tan,2,* and Jingchun Duan3

Author information Article notes Copyright and License information PMC Disclaimer

Go to:

Abstract

A first study of nonmethane hydrocarbons (NMHCs) on hazy and normal days was performed in Foshan for providing deep insight into the local deteriorating air quality. Ethane, propane, i-pentane, ethene, propene, ethyne, benzene, and toluene were eight most abundant compounds, accounting for 71%–85% of total NMHCs. Most hydrocarbons showed much higher levels on hazy days than normal days together with hydrocarbon/ethyne ratios and diurnal variations, indicating hazy days are more dominated by vehicular emission. Correlation coefficients (R2) of ethane, propane, ethane, propene, benzene, and total NMHCs with ethyne were 0.62–0.83, indicating these compounds are mainly related to vehicular emission. R2 analysis indicated that solvent usage is responsible for toluene and other aromatic hydrocarbons (e.g., ethylbezene). Benzene/toluene (B/T) ratio was 0.44±0.23 during whole sampling periods, again indicating vehicular emission is the dominant source. Lower B/T ratio (0.30±0.14) on hazy days than that (0.58±0.21) on normal days suggested that solvent usage emitted toluene.

Key words: : air pollution control processes, atmospheric chemistry, air quality, haze

Go to:

Introduction

Nonmethane hydrocarbons (NMHCs) are the major classes of organic pollutants and the key ozone (O3) precursors in atmosphere (Poisson et al., 2000; Xiao and Zhu, 2003; Caselli et al., 2010), which can significantly affect the atmospheric photochemical chemistry and human health (Atkinson, 2000; Elbir et al., 2007; Mudliar et al., 2010). Their sources in urban air are usually dominated by anthropogenic emissions including liquefied petroleum gas (LPG) leakage, solvent usage, and vehicular emission (Barletta et al., 2005; Tang et al., 2007; Duan et al., 2008). Recent studies on NMHCs showed that they have frequently exhibited much higher levels in Pearl River Delta (PRD), a rapidly developed region as well as a highly polluted area in south China (Wang et al., 2002; Tang et al., 2007; Shao et al., 2009). Although NMHCs have been widely investigated in PRD (Liu et al., 2008; Shao et al., 2009), for instance, leakage from vehicles fueled by LPG contributed mainly to ambient propane in Guangzhou (Tang et al., 2007); however, much remains unclear about the behaviors of NMHCs under conditions of particular pollution episodes, for example, hazy days, which will provide us deep insight into the local air pollution.

Haze is defined as a weather phenomenon that leads to visibility of <10 km in China (CMA, 2003), which is formed from moisture, dust, and vapor in the atmosphere. Urban haze generally results from excessive air pollutants emitted by anthropogenic sources and gas-to-particle conversion (Watson, 2002; Fu et al., 2008). Especially, haze is closely related to meteorological conditions and air pollution differing from those in normal days (Sun et al., 2006; Mao et al., 2008), because it is affected by the air contaminants with special characteristics (Wang et al., 2006; Lü et al., 2009). Recently, haze pollution has been an increasing concern among the public, scientific, and governments because of its negative impact on visibility, human health, and even the global climate (Yadav et al., 2003; Kang et al., 2004; Che et al., 2009).

The growing haze and photochemical smog involving NMHCs has now become the major air pollution items in PRD region. Air pollutants such as carbonyls and particles have been studied on hazy days of Guangzhou in PRD (Lü et al., 2009; Tan et al., 2006, 2009); until now, very few studies on atmospheric NMHCs during haze episodes have been conducted, although hazy days often occur in the local region, particularly in winter time (Lü et al., 2009; Tan et al., 2009). Especially, no data on NMHCs are available in the most highly polluted city named Foshan (GDEMC, 2008), an intensive industrialization area in PRD. With the rapid economic development of Foshan during the past three decades, large amounts of air pollutants were released into the air and then resulted in a rapid deterioration of the local air quality. Considering that both photochemical smog involving NMHCs and haze pollution in Foshan are becoming more deteriorate now than before, the objectives of this study mainly aim at (1) studying variation characteristics of NMHCs between hazy days and normal days in Foshan and (2) providing original data of NMHCs for local environmental protection agency to manage the rapidly deteriorating air quality in Foshan.

Go to:

Experimental

Site description

Foshan is the third largest city in central Guangdong province of PRD (the PRD region has a total population of 120 million people) in southern China, which experiences a humid subtropical climate. The prefectural area under the city's jurisdiction covers about 3840 km2 and a population of 5.9 million, of which 3.6 million reside in the city proper. The city has become relatively affluent compared with other cities in China and is home to many large private enterprises. Foshan has been recently the production base of leathers, ceramics, and plastic products of China, for example, its production of microwave cooker ranks first in the country. The sampling site (longitude 113°06′E and latitude 23°02′N) is located on the roof of a 10-storey building (30 m above the ground) in the urban central of Foshan, which is surrounded by residential buildings, business offices, and roads (Fig. 1).

FIG. 1.

Location of sampling site during sampling periods in Foshan, China.

Air sampling

Hydrocarbon samples on December 6–8, 10–13, and 27–31, 2008, were collected each day at 08:30 (morning), 14:30 (afternoon), and 19:00 (evening). Hazy days (Fig. 2) demonstrated lower visibility (≤10 km), lower wind speed (WS), and higher temperature than that on normal days (Tan et al., 2009). The samples were collected by 2-L commercial stainless steel canisters (Polar Ware Company), inside of which were electrically polished (Lü et al., 2006). All canisters were precleaned five times using ultrapure N2 (>99.999%) and then preevacuated by a canister cleaner (Entech Instruments, Inc.; Model 3100) before sampling. Sampling was performed according to the USEPA Compendium Method To-14A (Wang et al., 2002). A flow-controlling valve was used to collect 10 min integrated sample by slightly opening the valve, and the sampling inlet was placed at ∼1.5 m above the roof of the building, through which air was drawn by opening the valve. During sampling periods, data of traffic volume in Foshan were collected from Foshan Environmental Protection Bureau by our sampling staff to evaluate possible effects of vehicles on hydrocarbons.

FIG. 2.

Averages of visibility, wind speed, and temperature during sampling periods.

Analysis

The analytical method has been reported in our previous studies in detail (Wang et al., 2002; Lü et al., 2006). Briefly, samples were concentrated in the Model 7100 preconcentrator (Entech Instruments, Inc.) and then injected into an HP6890 gas chromatography coupled to an HP5973 mass-selective detector. A RESTEK RTX-1 capillary column (60 m×0.32 mm×1.0 μm) was used in the system. The column temperature was initially held at 40°C for 2 min, then programmed at a rate of 6°C/min−1 to 230°C, and isothermal held for 5 min. Compounds were identified by their retention times and mass spectra. Standard gas mixtures (1.0 ppm; Supeclo To-14 Calibration Mix) were first dynamically diluted with zero air, then sampled, and analyzed using identical conditions to those for the field samples, and seven-point calibration (0.0, 1.0, 5.0, 10.0, 20.0, 40.0, 50.0 ppbv) was performed. During analysis, the sample volume for each injection was 250 mL, and the detection limits of the method for all compounds were <0.2 ppb. The relative deviations in the duplicate samples were ≤5%, for example, it was 2% for alkanes and 5% for alkenes.

Go to:

Results and Discussion

Concentrations

To evaluate pollution levels of hydrocarbons between hazy days and normal days in Foshan, a total of 24 hydrocarbons were measured for data comparison (hazy days vs. normal days) during sampling periods (Table 1). Total NMHCs ranged from 96 to 342 ppbv with a mean of 175.16±66.97 ppbv on hazy days, whereas it ranged from 39 to 128 ppbv (with a mean of 76.96±21.24 ppbv) on normal days. On both hazy and normal days, ethane, propane, i-pentane, ethene, propene, ethyne, benzene, and toluene are the eight most abundant hydrocarbons, accounting for 71%–85% of total NMHCs (Table 1).

Table 1.

Concentrations (ppbv) of Hydrocarbons, O3, and NO2 During Sampling Periods in Foshan, China

	Hazy days (December 10–13 and 27–28, 2008)						Normal days (December 6–8 and 29–31, 2008)
Hydrocarbons	Morninga	Afternoona	Eveninga	Meanb	Min.c	Max.c	Morninga	Afternoona	Eveninga	Meanb	Min.c	Max.c
Ethane	22.71±9.47	11.95±6.17	16.57±8.31	17.08±8.86	7.61	38.47	11.95±3.14	8.69±1.78	11.67±3.28	10.77±3.05	5.53	17.12
Propane	17.50±7.49	13.14±4.11	16.22±3.69	15.62±5.39	7.57	29.01	10.34±1.21	8.86±1.24	11.33±2.41	10.18±1.92	6.56	14.32
n-Butane	5.68±1.87	3.49±1.17	4.42±1.37	4.53±1.68	2.24	9.00	2.27±0.60	1.83±0.62	2.40±0.98	2.17±0.75	0.74	3.73
i-Butane	5.32±2.24	3.14±1.23	4.39±1.15	4.28±1.78	1.85	8.48	1.97±0.58	1.35±0.65	2.00±1.00	1.77±0.78	0.23	3.81
n-Pentane	1.65±1.24	0.79±0.51	1.61±1.08	1.35±1.02	0.14	4.05	0.71±0.33	0.66±0.50	1.17±0.71	0.85±0.55	0.11	2.48
i-Pentane	14.91±8.37	30.99±10.67	18.49±12.72	21.46±12.33	5.28	43.37	6.11±6.69	6.84±2.99	6.27±3.64	6.41±4.45	1.61	19.20
Cyclopentane	0.35±0.17	0.26±0.10	0.36±0.14	0.32±0.14	0.05	0.56	0.15±0.12	0.15±0.09	0.26±0.11	0.19±0.12	0.05	0.43
n-Hexane	2.09±1.63	3.99±6.09	2.41±1.57	2.83±3.62	0.60	16.26	0.94±0.83	0.79±0.52	2.66±4.46	1.47±2.63	0.23	11.75
Cyclohexane	0.50±0.37	0.27±0.18	0.57±0.50	0.45±0.38	0.08	1.52	0.16±0.09	0.16±0.14	0.77±1.24	0.36±0.74	0.06	3.28
n-Heptane	2.15±2.08	0.55±0.41	2.44±2.40	1.71±1.94	0.18	6.02	0.31±0.16	0.32±0.37	0.66±0.62	0.43±0.43	0.09	1.83
n-Octane	2.34±1.81	1.18±1.00	3.34±2.32	2.29±1.91	0.37	7.01	0.29±0.10	0.31±0.13	0.64±0.44	0.41±0.31	0.20	1.24
Total alkanesd	75.18±27.71	69.74±22.63	70.82±23.16	71.91±23.24	38.37	117.81	35.20±3.13	29.95±5.40	39.83±12.55	35.00±8.66	24.22	62.36
Ethene	30.65±18.40	16.59±3.64	32.74±7.56	26.66±13.22	11.21	64.98	13.83±6.61	10.03±4.69	16.66±6.25	13.51±6.21	1.49	26.24
Propene	10.04±5.76	5.20±2.79	10.90±3.10	8.71±4.64	2.02	18.20	5.12±1.65	3.59±1.64	6.24±3.17	4.99±2.41	1.44	10.38
i-Butene	2.65±1.70	1.56±0.66	3.28±1.84	2.50±1.59	0.84	6.10	1.42±0.46	1.10±0.84	1.59±0.93	1.37±0.75	0.46	2.91
trans-2-Butene	0.99±0.73	0.37±0.22	1.29±0.46	0.88±0.62	0.12	2.08	0.32±0.08	0.27±0.09	0.45±0.20	0.35±0.15	0.14	0.70
cis-2-Butene	0.70±0.50	0.28±0.11	0.87±0.45	0.62±0.45	0.12	1.50	0.27±0.09	0.23±0.10	0.44±0.25	0.31±0.18	0.13	0.78
Isoprene	0.37±0.26	0.37±0.11	0.60±0.13	0.45±0.20	0.15	0.81	0.22±0.07	0.26±0.17	0.30±0.16	0.26±0.13	0.06	0.57
trans-2-Pentene	0.55±0.31	0.16±0.08	0.47±0.31	0.39±0.30	0.08	0.90	0.15±0.06	0.14±0.09	0.24±0.18	0.18±0.12	0.03	0.52
Total alkenesd	45.95±26.34	24.52±7.02	50.15±11.77	40.21±19.82	15.48	93.75	21.35±7.54	15.62±6.38	25.92±9.71	20.97±8.67	4.94	38.67
Ethyne	36.12±15.74	25.68±8.64	35.30±13.05	32.36±12.99	18.31	64.10	13.51±2.80	11.91±2.91	14.62±3.73	13.35±3.19	7.03	19.76
Benzene	5.61±4.58	3.66±3.38	8.08±2.98	5.78±3.95	1.24	14.29	1.89±0.64	2.18±1.23	2.92±1.06	2.33±1.04	0.44	4.16
Toluene	20.28±10.11	10.29±5.51	19.77±8.90	16.78±9.20	5.13	34.78	3.98±2.43	3.21±1.43	4.02±2.32	3.74±2.02	1.40	7.95
Ethylbenzene	5.60±5.72	1.88±1.75	5.55±4.02	4.34±4.30	0.43	13.06	0.92±1.01	0.45±0.18	0.87±0.69	0.75±0.70	0.21	2.81
m-/p-Xylene	2.71±2.47	1.09±1.43	3.57±1.99	2.46±2.17	0.14	5.97	0.67±0.63	0.29±0.13	0.62±0.45	0.53±0.46	0.13	1.63
o-Xylene	1.69±1.71	0.57±0.63	1.68±1.16	1.31±1.29	0.10	4.31	0.35±0.35	0.22±0.15	0.35±0.28	0.30±0.26	0.06	1.00
Total aromaticsd	35.89±23.52	17.48±11.97	38.65±16.99	30.67±19.58	7.04	67.29	7.82±4.85	6.35±3.02	8.78±4.57	7.65±4.10	2.90	16.41
Total NMHCsd	193.14±90.75	137.42±39.20	194.92±53.96	175.16±66.97	95.97	342.95	77.88±11.34	63.83±15.47	89.16±27.92	76.96±21.24	39.09	128.07
NO2e	13.31±4.00	13.39±6.15	20.05±9.85	15.58±7.41	7.30	32.14	30.92±17.43	27.43±18.15	18.34±18.29	25.57±16.37	6.33	63.30
O3e	4.71±3.70	33.29±14.25	3.27±0.90	13.75±16.32	0.47	46.67	5.68±4.74	25.36±3.93	3.12±0.89	11.38±10.77	1.40	31.27

Open in a separate window

aThe arithmetic mean and standard deviation for data collected from the same sampling duration.

bThe total arithmetic mean and standard deviation for all data on hazy or normal days.

cThe minimum (Min.) (or the maximum [Max.]) value of data on hazy or normal days.

dTotal alkanes, total alkenes, total aromatics, and total NMHCs were the sum of the listed alkanes, alkenes, aromatics, and all hydrocarbon concentrations, respectively.

eData of O3 and NO2 concentrations were collected from Foshan Environmental Protection Bureau (EPB), Foshan.

NMHC, nonmethane hydrocarbon.

As shown in Table 1, the concentrations of most hydrocarbons on hazy days were higher than that on normal days, for example, ethyne increased by ∼142% from normal days to hazy days. The variation trends of hydrocarbons have also been observed for other air pollutants such as carbonyls and particles between hazy days and normal days in Guangzhou (Lü et al., 2006; Tan et al., 2009), indicating that hazy days represent more serious pollution of hydrocarbons than normal days. Data of evaluated O3 levels on hazy days (13.75 ppbv) and normal days (11.38 ppbv) (Table 1) suggested that hazy days are more oxidative, which will likely lead to much more losses of hydrocarbons on hazy days. The observed higher levels of NMHCs on hazy days might be due to accumulation of hydrocarbons under steady weather conditions, for example, lower visibility and WS on hazy days (Fig. 2).

Diurnal patterns

Most hydrocarbons showed higher levels in the morning and evening, especially on hazy days (Table 1), for example, ethyne on hazy days decreased by ∼30% from morning to afternoon and then increased by ∼37% from afternoon to evening. This diurnal variation pattern (Fig. 3) implied the dominant emission from vehicles, as traffic volume reaches its highest level at rush hours in the morning and evening. The lowest levels in the afternoon are also likely the results of reaction with OH and increased mixing height of the planetary boundary layer (Tang et al., 2007). In addition, the average WS in the afternoon was higher than that in the morning (or evening) (Fig. 2), resulting in stronger ventilation and then diluting the air pollutants. However, i-pentane, a marker for gasoline evaporation (Barletta et al., 2005), exhibited the highest levels (30.99±10.67 ppbv) in the afternoon, especially on hazy days. The higher temperature in the afternoon than in the morning (or evening) (Fig. 2) is conducive to evaporation of solvent containing i-pentane, which was supported by the highest level of i-pentane occurring in the afternoon (Fig. 3).

FIG. 3.

Mean diurnal variations of abundant hydrocarbons during sampling periods.

Averagely, alkanes, alkenes, and aromatic hydrocarbons accounted for 36%–51%, 18%–26%, and 12%–19% of total NMHCs on hazy days (they were 45%–48%, 23%–29%, and 9%–10% on normal days), respectively (Table 1). On hazy days, ethyne contributed first (19%), followed by ethene (15%), i-pentane (14%), ethane (10%), toluene (9%), propane (9%), propene (5%), and benzene (3%). On normal days, ethyne contributed first (18%), followed by ethene (17%), ethane (14%), propane (14%), i-pentane (9%), propene (6%), toluene (5%), and benzene (3%). Considering that ethyne is a tracer for vehicular exhaust (Barletta et al., 2005), i-pentane is a marker for gasoline evaporation, and toluene is emitted from vehicles, painting, and industrial processes (solvent usage) (Barletta et al., 2002), the contribution ranking of these abundant compounds to total NMHCs was closely associated with vehicular emission, gasoline evaporation, and solvent application. Especially, the concentration of toluene in total NMHCs showed the largest distinction between hazy days and normal days compared with other seven abundant compounds. This might be due to different meteorological conditions (Fig. 2) and different photochemical activities of toluene (Atkinson, 2000) in the two day types.

Levels in relation to meteorology

Meteorological conditions can affect air pollutants and have been long recognized as being associated with the worst air pollution episodes (Lü et al., 2006; Tan et al., 2009). Figure 4 plots the relationships of total NMHCs with visibility and WS. On hazy days, total NMHCs did not show clear variation trends under lower visibility conditions (0–5 km), but it decreased with the increasing of visibility when visibility was 5–10 km. Total NMHCs also showed no statistical variation trend together with WS being ≤2 m/s for most samples on hazy days (Fig. 4), indicating that the dilution effect of WS on hydrocarbons is negligible on hazy days. In addition, no clear boundaries were observed for both relative humidity (RH) and temperature between hazy days and normal days, and RH ranged from 40% to 90% for most samples during sampling periods (Fig. 4). On the whole, hazy days demonstrated lower visibility, lower WS (≤2 m/s), and higher levels of hydrocarbons compared with normal days in this study.

FIG. 4.

Meteorological conditions in relation to total NMHCs during sampling periods. NMHC, nonmethane hydrocarbon.

Sources of hydrocarbons

Generally, alkenes and alkynes are characteristic products of combustion engines (Barletta et al., 2005). In urban environments, vehicular emission is by far the most important source (Tang et al., 2007), which has been supported by the highest level of ethyne (a tracer for vehicular emission) in this study (Table 1). To assess the impact of vehicles on hydrocarbon levels, mean hydrocarbon/ethyne ratios were calculated for individual hydrocarbons between hazy days and normal days (Fig. 5). It was expected that the lower hydrocarbon/ethyne ratios mean that air hydrocarbons are more dominated by vehicular emission. For most hydrocarbons, the hydrocarbon/ethyne ratios on hazy days were approximately less than those in normal days, although traffic volume showed no significant differences in the two day types (Fig. 5), indicating vehicular emission is more dominant on hazy days. However, toluene exhibited significant higher ratios on hazy days, likely suggesting additional source differing from vehicles, because toluene is also emitted from solvent usage including painting, printing, and dry cleaning (Na et al., 2003; Yan et al., 2010).

FIG. 5.

Variations of traffic volume and mean hydrocarbon/ethyne ratio during sampling periods.

To clearly identify the influence of vehicular emission on ambient hydrocarbons, correlation coefficients (R2) of abundant hydrocarbons with ethyne are calculated in Table 2. Ethane, propane, ethane, propene, and benzene showed good correlations (R2=0.62–0.83) with ethyne, indicating that their sources are mainly vehicular emission; the R2 of total NMHCs with ethyne was 0.76–0.79, indicating that ambient hydrocarbons are mainly related to vehicles. Especially, R2 of propane with ethyne (R2=0.62) on hazy days were significantly lower than that (R2=0.83) on normal days (Table 2), suggesting the more intensive photochemical activity of propane (Atkinson, 2000) on hazy days compared with normal days.

Table 2.

Correlation Coefficients (R2) of Hydrocarbons with Ethyne and Toluene

	R2 with ethyne			R2 with toluene
Hydrocarbons	Hazy days	Normal days	Hydrocarbons	Hazy days	Normal days
Ethane	0.62	0.65	Benzene	0.53	0.48
Propane	0.62	0.83	Ethylbezene	0.78	0.84
Ethene	0.66	0.63	m/p-Xylene	0.79	0.85
Propene	0.66	0.76	o-Xylene	0.70	0.81
Benzene	0.67	0.73	Total aromatics	0.93	0.98
Toluene	0.49	0.55
Total NMHCs	0.76	0.79

Open in a separate window

Toluene is emitted from both vehicular emission and solvent usage (painting, printing, dry cleaning, etc.) (Klimont et al., 2002; Na et al., 2003; Yan et al., 2010), and most of the solvents did not contain benzene (Na et al., 2003). In this study, abundant toluene showed weak correlation (R2=0.48–0.55) with benzene and ethyne, leading us to believe that ambient toluene could be used as a reliable marker for solvent usage during sampling periods. As can be seen in Table 2, ethylbezene, m/p-xylene, and o-xylene showed good correlations (R2=0.70–0.85) with toluene, indicating they mainly come from a similar source as that of toluene, for example, solvent usage. Especially, R2 of ethylbezene, m/p-xylene, and o-xylene with toluene on normal days were higher than that on hazy days. This may be explained by more intensive photochemical activity of toluene on hazy days. Generally, radiation can be weaker because of scattering by haze and oxidants may be titrated by the high concentration of hydrocarbons as well as active nitrogen oxides such as nitric oxide (Atkinson, 2000) on hazy days. In this study, O3 levels during sampling periods in Foshan were used to evaluate the oxidative activities of toluene between hazy days and normal days, because O3 is the crucial intermediate species in photochemical reactions of ambient hydrocarbons and represents the major photochemical oxidant in the atmosphere. As can be seen in Table 1, the mean O3 levels in the morning (or evening) on hazy days were approximately equal to those on normal days. However, in the afternoon, hazy days showed much higher levels of O3 (33.29 ppbv) than normal days (25.36 ppbv). Therefore, hazy days in this study are considered to be more intensive oxidation than normal days, resulting in weaker correlations of toluene with these aromatic hydrocarbons. Moreover, total aromatics showed rather good correlation with toluene (R2=0.93–0.98), indicating ambient aromatic hydrocarbons are mainly related to the same source as that of toluene.

To further differentiate vehicular emission and other combustion sources, the benzene-to-toluene ratio (B/T) was considered. A B/T ratio of ∼0.5 (wt/wt) was reported to be characteristic of vehicular emission (Barletta et al., 2005), and higher B/T ratios represented the sources from burning of biofuel, charcoal, and coal (Duan et al., 2008). During whole sampling periods, the mean B/T ratio was 0.44±0.23, indicating the dominant emission from vehicles. On hazy days, the B/T ratios (a mean of 0.30±0.14) were 0.23±0.12 in the morning, 0.29±0.17 in the afternoon, and 0.37±0.10 in the evening; on normal days, they were 0.47±0.13 in the morning, 0.57±0.24 in the afternoon, and 0.70±0.22 in the evening (with a mean of 0.58±0.21 on normal days). In this study, ambient hydrocarbons on hazy days are mainly dominated by vehicular emission, which may raise the B/T ratio on hazy days compared with normal days, because benzene was mainly emitted from vehicles as discussed earlier. The rate constants (kOH) for gas-phase reactions of OH radical with benzene and toluene are 1.23×1012 and 5.95×1012 cm−3·molecule−1·s−1, respectively (Yassaa et al., 2006). Then, the faster removal rate of toluene under conditions of more intensive oxidation may also raise the B/T ratios on hazy days. However, the measured mean B/T value (0.30) on hazy days was much lower than that (0.58) on normal days. The observed significant difference of measured mean B/T ratios between hazy days and normal days suggests the following fact. The lower WS, weaker air convection, and weaker atmospheric diffusion on hazy days (Fig. 2) might be more prone to accumulations of toluene with high levels compared with low levels of benzene. The difference was more likely to benefit from solvent usage emitting toluene based on the R2 analysis above, resulting in the reduction of B/T values on hazy days, because a large amount of trades involving painting, printing, and dry cleaning are very well developed in Foshan.

Go to:

Conclusions

Ethane, propane, i-pentane, ethene, propene, ethyne, benzene, and toluene are eight most abundant hydrocarbons on hazy and normal days of Foshan, accounting for 71%–85% of total NMHCs. Concentrations of most hydrocarbons on hazy days were greater than that on normal days together with diurnal variations and the hydrocarbon/ethyne ratios, indicating that hazy days are more dominated by vehicles than normal days. R2 analysis indicated that ethane, propane, ethane, propene, benzene, and total NMHCs are mainly related to vehicular emission, whereas solvent usage is responsible for toluene and other aromatic hydrocarbons. The mean B/T ratio was 0.44±0.23 during whole sampling periods, again indicating the dominant vehicular emission. The mean B/T ratio showed a lower value (0.30±0.14) on hazy days than that (0.58±0. 21) on normal days, suggesting that solvent usage emitted toluene during sampling periods.

Go to:

Acknowledgments

The authors acknowledge the research support by Knowledge Innovation Program of the Chinese Academy of Sciences (Grant No. XMXX280732) and State Key Joint Laboratory of Environment Simulation and Pollution Control (10K13ESPCT). The authors are thankful to all staff for participating in air sampling. The authors thank Professor X.M. Wang and his group at State Key Laboratory Organic Geochemistry (China) for analyzing the air samples. Especially, the authors sincerely appreciate anonymous reviewers for their constructive criticisms and positive comments on this article.

Go to:

Author Disclosure Statement

No competing financial interests exist.

Go to:

References

• Atkinson R. Atmospheric chemistry of VOCs and NOx. Atmos. Environ. 2000;34:2063. [Google Scholar]
• Barletta B. Meinardi S. Rowland F.S. Chan C.Y. Wang X.M. Zou X.C. Chan L.Y. Blake D.R. Volatile organic compounds in 43 Chinese cities. Atmos. Environ. 2005;39:5979. [Google Scholar]
• Barletta B. Meinardi S. Simpson I.J. Khwaja H.A. Blake D.R. Rowlandm F.S. Mixing ratios of volatile organic compounds (VOCs) in the atmosphere of Karachi, Pakistan. Atmos. Environ. 2002;36:3429. [Google Scholar]
• Caselli M. de Gennaro G. Marzocca A. Trizio L. Tutino M. Assessment of the impact of the vehicular traffic on BTEX concentration in ring roads in urban areas of Bari (Italy) Chemosphere. 2010;81:306. [PubMed] [Google Scholar]
• Che H. Zhang X. Li Y. Zhou Z. Qu J.J. Hao X. Haze trends over the capital cities of 31 provinces in China, 1981–2005. Theor. Appl. Climatol. 2009;97:235. [Google Scholar]
• China Meteorological Administration (CMA) Specification of Surface Meteorological Observation, Beijing. Beijing: China Meteorological Press; 2003. p. 21. (in Chinese). [Google Scholar]
• Duan J. Tan J. Yang L. Wu S. Hao J. Concentration, sources and ozone formation potential of volatile organic compounds (VOCs) during ozone episode in Beijing. Atmos. Res. 2008;88:25. [Google Scholar]
• Elbir T. Cetin B. Cetin E. Bayram A. Odabasi M. Characterization of volatile organic compounds (VOCs) and their sources in the air of Izmir, Turkey. Environ. Monit. Assess. 2007;133:149. [PubMed] [Google Scholar]
• Fu Q. Zhuang G. Wang J. Xu C. Huang K. Li J. Hou B. Lu T. Streets D.G. Mechanism of formation of the heaviest pollution episode ever recorded in the Yangtze River Delta, China. Atmos. Environ. 2008;42:2023. [Google Scholar]
• Guangdong Province Environmental Protection Monitoring Center (GDEMC) Pearl River Delta Regional Air Quality Monitoring Network, A Report of Monitoring Results in 2006. Guangzhou, China: Guangdong Province Press; 2008. [Google Scholar]
• Kang C.M. Lee H.S. Kang B.W. Lee S.K. Sunwoo Y. Chemical characteristics of acidic gas pollutants and PM2.5 species during hazy episodes in Seoul, South Korea. Atmos. Environ. 2004;38:4749. [Google Scholar]
• Klimont Z. Streets D.G. Gupta S. Cofala J. Lixin F. Ichilawa Y. Anthropogenic emissions of non-methane volatile organic compounds in China. Atmos. Environ. 2002;36:1309. [Google Scholar]
• Liu Y. Shao M. Lu S. Chang C. Wang J. Fu L. Source apportionment of ambient volatile organic compounds in the Pearl River Delta, China: Part II. Atmos. Environ. 2008;42:6261. [Google Scholar]
• Lü H. Cai Q. Wen S. Chi Y. Guo S. Sheng G. Fu J. Antizar-Ladislao B. Carbonyl compounds in the ambient air of hazy days and clear days in Guangzhou, China. Atmos. Res. 2009;94:363. [Google Scholar]
• Lü H. Wen S. Feng Y. Wang X. Bi X. Sheng G. Fu J. Indoor and outdoor carbonyl compounds and BTEX in the hospitals of Guangzhou, China. Sci. Total Environ. 2006;368:574. [PubMed] [Google Scholar]
• Mao T. Wang Y. Jiang J. Wu F. Wang M. The vertical distributions of VOCs in the atmosphere of Beijing in autumn. Sci. Total Environ. 2008;390:97. [PubMed] [Google Scholar]
• Mudliar S. Giri B. Padoley K. Satpute D. Dixit R. Bhatt P. Pandey R. Juwarkar A. Vaidya A. Bioreactors for treatment of VOCs and odours: A review. J. Environ. Manage. 2010;91:1039. [PubMed] [Google Scholar]
• Na K. Kim Y.P. Moon K.C. Diurnal characteristics of volatile organic compounds in the Seoul atmosphere. Atmos. Environ. 2003;37:733. [Google Scholar]
• Poisson N. Kanakidou M. Crutzen P.J. Impact of nonmethane hydrocarbons on tropospheric chemistry and the oxidizing power of the global troposphere: 3-dimensional modelling results. J. Atmos. Chem. 2000;36:157. [Google Scholar]
• Shao M. Zhang Y. Zeng L. Tang X. Zhang J. Zhong L. Wang B. Ground-level ozone in the pearl river delta and the roles of VOC and NOx in its production. J. Environ. Manage. 2009;90:512. [PubMed] [Google Scholar]
• Sun Y.L. Zhuang G.S. Tang A.H. Wang Y. An Z.S. Chemical characteristics of PM2.5 and PM10 in haze-fog episodes in Beijing. Environ. Sci. Technol. 2006;40:3148. [PubMed] [Google Scholar]
• Tan J. Duan J. Chen D. Wang X. Guo S. Bi X. Sheng G. He K. Fu J. Chemical characteristics of haze during summer and winter in Guangzhou. Atmos. Res. 2009;94:238. [Google Scholar]
• Tan J.H. Bi X.H. Duan J.C. Kenneth A.R. Sheng G.Y. Fu J.M. Seasonal variation of particulate polycyclic aromatic hydrocarbons associated with PM10 in Guangzhou, China. Atmos. Res. 2006;80:250. [Google Scholar]
• Tang J.H. Chan L.Y. Chan C.Y. Li Y.S. Chang C.C. Liu S.C. Wu D. Li Y.D. Characteristics and diurnal variations of NMHCs at urban, suburban, and rural sites in the pearl river delta and a remote site in South China. Atmos. Environ. 2007;41:8620. [Google Scholar]
• Wang X.M. Sheng G.Y. Fu J.M. Urban roadside aromatic hydrocarbons in three cities of the Pearl River delta, People's Republic of China. Atmos. Environ. 2002;36:5141. [Google Scholar]
• Wang Y. Zhuang G. Sun Y. An Z. The variation of characteristics and formation mechanisms of aerosols in dust, haze, and clear days in Beijing. Atmos. Environ. 2006;40:6579. [Google Scholar]
• Watson J.G. Visibility: Science and regulation. J. Air Waste Manage. Assoc. 2002;52:628. [PubMed] [Google Scholar]
• Xiao H. Zhu B. Modeling study of photochemical ozone creation potential of non-methane hydrocarbon. Water Air Soil Pollut. 2003;145:3. [Google Scholar]
• Yadav A.K. Kumar K. Kasim A. Singh M.P. Parida S.K. Sharan M. Visibility and incidence of respiratory diseases during the 1998 haze episode in Brunei Darussalam. Pure Appl. Geophys. 2003;160:265. [Google Scholar]
• Yan B. Shao M. Lu S. Wang B. Source profiles of volatile organic compounds associated with solvent use in Beijing, China. Atmos. Environ. 2010;44:1919. [Google Scholar]
• Yassaa N. Brancaleoni E. Frattoni M. Ciccioli P. Isomeric analysis of BTEXs in the atmosphere using β-cyclodextrin capillary chromatography coupled with thermal desorption and mass spectrometry. Chemosphere. 2006;63:502. [PubMed] [Google Scholar]