Asian Journal of atmospheric environment
Asian Journal of atmospheric environment Asian Journal of atmospheric environment
Asian Journal of atmospheric environment

Current Issue

Asian Journal of Atmospheric Environment - Vol. 13 , No. 2

[ Research Article ]
Asian Journal of Atmospheric Environment - Vol. 13, No. 2, pp.73-87
Abbreviation: Asian J. Atmos. Environ
ISSN: 1976-6912 (Print) 2287-1160 (Online)
Print publication date 30 Jun 2019
Received 03 Dec 2018 Revised 07 Mar 2019 Accepted 20 Mar 2019

Measurements on Stationary Source Emissions and Assessing Impact on Ambient Air Quality around Two Indian Refineries
Deepanjan Majumdar* ; Anil Bhanarkar1) ; Ashok Gangadhar Gavane1) ; Chalapati Rao1)
Kolkata Zonal Centre, CSIR-National Environmental Engineering Research Institute (CSIR-NEERI), i-8, Sector C, EKDP, EM Bypass, Kolkata -700107, India
1)Air Pollution Control Division, CSIR-National Environmental Engineering Research Institute (CSIR-NEERI), Nehru Marg, Nagpur - 440 020, India

Correspondence to : *Tel: +91-33-24421988 E-mail:

Copyright © 2019 by Asian Journal of Atmospheric Environment
This is an open-access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (, which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.


Emissions of particulate matter (PM), SO2 and NO2 from stationary sources and their concentration along with benzene and CO in ambient air around two Indian refineries were studied. Prediction of ground level concentration (GLC) of SO2, NO2 and PM was made by dispersion modeling. In Refinery 1, highest SO2 emission (646 mg Nm-3) were detected in Sulphur Recovery Unit while NOx emissions ranged from 57.8 to 445.0 mg Nm-3, respectively from various units. In Refinery 2, highest SO2 emission (935 mg Nm-3) was observed from Utility Boiler while NO2 emissions ranged from 13 to 235 mg Nm-3. Above emissions were within the stipulated emission standards prescribed by Central Pollution Control Board of India. Further, ambient concentrations of the above in the vicinity of these refineries were below their prescribed national ambient air quality standards. Air quality in terms of air quality index (AQI) was moderate or good at the study sites. Dispersion modelling exercise indicated that the observed GLC of SO2 and NO2 could be reasonably predicted by ISC-AERMOD model for both refineries while there was moderate to substantial difference between observed and modeled PM values due to presence of several sources of particulate emissions in the region that could not be considered in the model.

Keywords: Air pollution, Dispersion modeling, Ground level concentration, ISC-AERMOD, Stack emission


Petroleum refineries are well-known sources of a wide variety of air pollutants. India is one of the major consumers of petroleum products in the world and was the 4th largest consumer of oil and petroleum products after USA, China, and Japan in 2011 (USEIA, 2013) and its demand was forecasted to rise further (IBEF, 2017). India’s current refining capacity is 230 million metric tonnes per annum (MMPTA), including the just commissioned 15 MMPTA refinery at Paradip (IBEF, 2017). The public sector accounts for 66% (150 million metric tonnes) of the total refining capacity while the private sector accounts for the rest 34% or 80 million metric tonnes. Currently, there are 22 petroleum refineries operating across India (PPAC, 2018), some of which are located in populated areas, making the issue of air pollution from these refineries significant.

Refineries emit various inorganic and organic compounds into the atmosphere (Al-Hamad and Khan, 2008; Cetin et al., 2003). Factors like process energy consumption, crude feed quality, types of refined products, fuels combusted for process energy generation, etc. govern the emissions (Karras, 2010). Gaseous sulfur compounds are the most important air pollutants generated in petroleum refineries, sulfur dioxide (SO2) being the major one (USEPA, 1995; CPCB, 1981a), the others being oxides of nitrogen (NOx) and volatile organic compounds (VOCs) (Cetin et al., 2003). VOC emissions from petroleum refineries may be substantial, however these are mostly released as fugitive emissions. Fluid Catalytic Cracking (FCC) unit is the major contributor to SO2 and particulate matter (PM) emissions (Yateem et al., 2011). Refinery emits SO2, NOx and PM in the range of 30-6,000, 60-700 and 10-3,000 tonnes per million tonne of crude processed (Srivastava et al., 2010). The general range of SO2 and nitrogen oxides (NOx) emissions are reported to be 0.143-0.892, 0.010-0.8 kg t-1 in Indian refineries (Srivastava et al., 2010). Some studies have reported 5-6 times higher SO2 concentrations in ambient air over workplaces in refineries in India and other countries (Shie, 2013; Rao et al., 2012). As per some reports, SO2, nitrogen dioxide (NO2) and BTEX concentrations exhibited diurnal as well as seasonal variations around refineries (Rao et al., 2007; Chiu et al., 2005; Lin et al., 2004; Pimpisut et al., 2003). Chiu et al. (2005) reported higher concentrations of ambient SO2 and NO2 during daytime. Day and night time values, recorded by Lin et al. (2004) were 123 and 154 ppbv for benzene, 137 and 139 ppbv for toluene, 1.7 and 2.3 ppbv for ethylbenzene and 4.1 and 4.7 ppbv for p-xylene, respectively.

Attrition of cold makeup catalyst, charging and operating conditions are mostly responsible for particulate emissions in a refinery (Yateem et al., 2011). Sánchez de la Campa et al. (2011) reported emissions of fine and metalliferous particulate emissions from the oil refinery complex in San Roque. Particulates are mostly carbonaceous in nature or sometimes fine metalliferous that are mostly partitioned into <0.33 μm, whereas emissions from production of purified terephthallic acid (PTA) were coarser.

Emissions from petroleum refinery are important as they have adverse impacts on local ecosystems (Al-Jahdali and Bin Bisher, 2008; Korte and Boedefeld, 1978) and health (Simonsen et al., 2010; Smargiassi et al., 2009; Barberino et al., 2005; Tasi et al., 2003; Luginaah et al., 2000; Yang et al., 2000; Bertazzi et al., 1989). Various international organizations and national pollution control authorities have imposed ambient air quality and emission standards for petroleum refineries (World Bank, 1998; USEPA, 1997; CPCB, 1985, 1981b). Ministry of Environment, Forest and Climate Change (MoEFCC), India, erstwhile Ministry of Environment and Forest (MoEF), has promulgated emission standards for Indian petroleum refineries (MoEF, 2008).

Information on particulate and gaseous emissions from petroleum refinery in India is very limited. Estimating emissions from stationary sources & likely impacts on local and regional air quality is important for understanding environmental sustainability around petroleum refineries and information and updates on the same are therefore important. In this paper, we report stationary source emissions along with observed and predicted ambient air quality around two Indian refineries that are situated in two very distant geographical regions and surroundings. We have also presented dispersion modeling of stationary source emissions as a tool for predicting concentration of air pollutants at ground level. The present work would improve the common understanding of the source emissions from refineries and their likely effects on regional ambient air quality.

2. 1 The Refineries

Two refineries (designated as Refinery 1 and Refinery 2) were selected for stationary source and air quality monitoring assignment. The two refineries selected are situated at different corners of India and also in different landuse pattern; one is located inland whereas the other is located at a coastal area. These refineries were chosen to understand emission patterns from refineries of different capacities and also to evaluate effects on ambient air quality in two different geographical areas and meteorological regimes. Refinery 1 is located in North Eastern part of India at Numaligarh in Assam, having a crude oil refining capacity of 3.0 MMTPA at the time of study. Superior kerosene oil (SKO), high speed diesel (HSD) and Aviation Turbine Fuel (ATF) are produced by Hydrocracker Technology for producing low sulphur products. Internally produced naphtha is used as fuel in the hydrogen generation unit (H2U) and a fuel in captive power plant. Other product included Liquefied Petroleum Gas (LPG), Petroleum Coke, Parafin Wax and Sulphur. Low NOx burners are in place to minimize NOx generation from furnaces. There are two gas turbine generators (GTGs) with Heat Recovery Steam Generators (HRSGs), each having rated capacity of 30 MW.

Refinery 2 is located in the coastal area of Kochi in Kerala, situated in Southern part of India, that refined about 9.5 MMTPA crude oil at the time of study. This refinery has state of the art crude distillation unit and secondary processing units. Products from this refinery include LPG, Naphtha, Aviation Turbine Fuel, Kerosene, High Speed Diesel, Fuel Oils, Motor Spirit and Asphalt. Other products included Benzene, Toluene, Propylene, Poly Iso Butene, Bitumen and Sulphur.

2. 2 Reconnaissance

Reconnaissance was conducted in the selected refineries for collection of secondary data on processes (Table 1), raw material consumption and environment management for planning on source emission and ambient air quality monitoring. Emission standards for particulates, SO2 and NOx prescribed by the State Pollution Control Boards in their ‘consent to operate’ letter to the industry were collected and studied.

Table 1. 
Summary of various operations in the selected refineries.
Process units Unit summary
Crude Distillation Unit (CDU) Crude oil is preheated to a temperature of 360-385°C in an atmospheric furnace and introduced in a crude distillation column wherefrom oil, kerosene and heavy naphtha are obtained.
Vacuum distillation unit (VDU) A vacuum heater heats up hot reduced crude oil from CDU, then introduced in a VDU wherefrom vacuum diesel, vacuum gas oil (VGO) and vacuum residue (VR) are obtained.
Delayed Coking Unit (DCU) Residue from VDU is heated to 502°C in a coker furnace and then it undergoes cracking and polymerization in a coke chamber, forming raw petroleum coke (RPC), which is then processed at coke calcination unit.
Coke Calcination Unit (CCU) RPC is put through a screen, crushed and then stored in RPC silos or introduced to a rotary kiln where it is dried, heated to 1,250-1,350°C to drive off moisture while hydrocarbons and other volatile matter are burnt off.
Hydrogen Generation Unit (H2U) Naphtha undergoes desulphurization by hydrogenation and adsorption on S adsorber. It then enters reforming section to get converted to synthetic gases like H2, CO and CO2. CO is converted to CO2 in shift conversion section and finally mixed gas is purified in gas purification section (PSA) to recover 99.9% pure H2.
Hydrocracker Unit (HCU) The feeds to this unit are vacuum gas oil coming from VDU/CDU and coker distillates from CDU which are heated to a desired temperature and partially cracked on catalyst bed in presence of H2 coming from H2U.
Naphtha Hydrotreater/Hydro Desulphurisation (NHDT/NHDS) Unit This unit desulfurize naphtha obtained from crude distillation by using hydrogen (Hydrodesulfurization) which is necessary before sending naphtha to the Catalytic Reforming Unit.
Catalytic Reforming Unit (CRU) This unit converts naphtha-boiling range molecules into higher-octane products which have higher aromatics, olefins and cyclic hydrocarbons. Isomerization Unit (IU) This unit produces higher-octane molecules from linear molecules to blend with gasoline or introduced to alkylation units.
Sulphur Recovery Unit (SRU) This unit recovers sulphur from H2S-rich gas from sour-water-stripping unit and acid-gas coming from amine regeneration unit.
Vis Breaker Unit (VBU) Biturox Unit produces Bitumen from Vacuum Residue (VR) obtained from VDU. Furnace Oil (FO) can also made from VR by feeding the later to a VBU.
Fluid Catalytic Cracking Unit (FCCU) FCC unit processes VGO whereby heavier molecules are converted to LPG, Gasoline, and Diesel.
Diesel Hydro Desulphurisation (DHDS) Unit This unit converts S in presence of H2 to produce H2S to reduce S level in HSD.
Kerosene Hydro Desulphurisation (KHDS) Unit Aviation Turbine Fuel (ATF) and Mineral Turpentine Oil (MTO) are produced from Kerosene obtained from crude distillation by treating in a MEROX unit or KHDS.
Hydrotreater Unit (HDS) This process is used for selective hydrogen addition to olefins & aromatics in order to saturate them. Another important purpose is S & N compounds removal present in feedstock by selective hydrogenation.
Captive Power Production
Utility Boiler (UB) It is a single-burner boiler, generating steam for running generator.
Heat Recovery Steam Generator (HRSG) The unit drives a generator with the help of steam generated by circulating water through the exit of utility boiler to capture the waste heat coming out of from boiler. It consists of a steam turbine.

2. 3 Stationary Source Emission Monitoring

The method prescribed by Bureau of Indian Standards (IS: 11255, Part 1 and 3-1985) was used for stationary source emission monitoring and determination of stack gas flow rate and concentration of analytes (BIS, 1985). Stationary source monitoring for particulate matter (PM) estimation was carried out under isokinetic flow conditions for a period ranging from 1-2 h under normal plant operations. A thermocouple sensor attached to a pyrometer and a modified “S-type” Pitot tube fabricated from SS 304 in conjunction with a stack monitoring kit (Model VSS-1) was used to estimate temperature of flue gas and differential flue gas pressure, respectively, from which flue gas velocity and flow-rate were calculated. A dry gas meter was used to record total volume of gas sampled. Particulate matter present in stack gas was collected in glass fibre thimble filters (19×90 mm; Whatman) capable of collecting particulates down to 0.3 μm and withstanding temperature up to 600°C. The thimble filters were conditioned at 50°C and 10% relative humidity (RH) in an oven followed by its storage in a humidity controlled dessicator before initial weighing. The same conditioning was also applied to the thimble filters after sampling and before final weighing. PM concentration in stack gas (mg Nm-3) was estimated as gain in thimble weight against normalized volume (Nm3) of sampled stack gas.

A USEPA certified flue gas analyzer (Model Testo 350, Testo GMBH, Germany) fitted with electrochemical sensors was used for monitoring of O2, SO2, nitric oxide (NO), NO2 and carbon monoxide (CO) in the stack gas. This analyzer was calibrated with standard certified concentrations of CO, SO2, NO and NO2 and was zero-calibrated with fresh air just before sampling, as per standard usage protocol. The fuel cell sensors deployed in the analyzer for SO2 and NO2 analysis, slowly and steadily decline in their output with time and therefore, must be recalibrated for a new zero at a pollution free ambient condition before they are used (Powrtech Solutions, Inc.,; accessed on 25.2.2019). Subsequently, concentrations of PM, CO, SO2, NO and NOx measured in stack gas (mg Nm-3) were first corrected to 6% carbon dioxide (CO2) concentration and then integrated with stack gas flow rate (Nm3 h-1) to estimate their emission rates (kg h-1) and emission load (MT y-1), considering continuous operation thoughout the year.

2. 4 Ambient Air Quality Monitoring

Ambient air monitoring (24-hourly) for a three-week period was conducted during the month of February for Refinery 1 and September for Refinery 2 at various locations around the refineries selected as per ASTM guidelines (ASTM, 2005). The locations of ambient air quality stations with respect to the refineries are depicted in Fig. 1. Fine Particulate Samplers (Model APM 550, Envirotech, Delhi, India) were used for monitoring PM10 in ambient air. Ambient air enters APM 550 through an omnidirectional inlet designed to give aerodynamic cut-point for particles larger than 10 microns. The samplers were run at 16.7 LPM flow rate without Wins Impactor for PM10 sampling. Calibration of flow rate of the instrument was undertaken by a Low Flow Calibrator (Model: APM-523, Envirotech) calibrated within 10-20 LPM flow range with error range of -0.4- 8.20% full scale and expanded uncertainty (k=2) of +1.05% with traceability to FCRI, Palakkad. The combined (and expanded) uncertainty associated to atmospheric particulate measurements depends on uncertainty components (standard deviations) of relevant measurements viz. flow rate, time, mass, temperature, pressure, etc. Calibration for size is also critical. Therefore, uncertainties in impactor designing can be further added as one of the components of uncertainties (Aggarwal et al., 2013). Thermoelectrically cooled gaseous samplers (Model VTG II) were used to sample SO2 and NO2 by IS 5182 (Part 2): 2001 Method (BIS, 2001) and IS 5182 (Part 6): 2006 Method (BIS, 2006), respectively. The temporary ambient air quality monitoring stations were established with assured power supply, round the clock vigilance and facility for periodic sample collection. SO2 and NO2 were sampled at 1 LPM flow rate in impingers filled with designated absorbing media for SO2 or NO2. The IS 5182 Method (Part 2)-2001 (BIS, 2001) was used for SO2 sampling and analysis. The impingers were calibrated by pipetting 35 mL absorbing reagent in 5 mL calibrated pipette and checking correctness of markings on the impingers. Sampling for SO2 was undertaken for 24 hours continuously. This method allowed estimation of SO2 in the range of 25 to 1,050 μg m-3 and concentrations <25 μg m-3 were measured by withdrawing higher air volumes. Likely NOx interference was reduced by adding 1 mL of 0.06% sulphamic acid while ozone (O3) was allowed to get decomposed by making the solution to stand for some time. Interference of trace metals was minimized by addition of 0.01% ethylene diamine tetra acetic acid (EDTA) to the absorbing solution before sampling. Calibration curve was drawn with the help of serial dilution of stock sulphite solution.

Fig. 1. 
Maps of study areas with marked refinery boundaries and ambient air quality monitoring stations (N1-N4) around Refinery 1 and (K1-K6) around Refinery 2.

Measurement of NO2 was undertaken by sampling for 24 hours continuously following IS Method 5182 (Part 6): 2006 (BIS, 2006). The range of the method is reported to be 6 to 750 μg NO2 m-3 (0.003 to 0.4 ppm) while the analysis range is 0.04 to 2.0 μg NO2 mL-1. Under 50 mL absorbing reagent, sampling rate of 200 cm3 min-1 for 24 h and absorption efficiency of 82%, method range is reported to be 6 to 420 μg NO2 m-3 (0.003 to 0.22 ppm). NO2 concentrations (420 to 750 μg NO2 m-3) (0.22 to 0.4 ppm) are measured accurately by 1 : 1 dilution of sample. The positive and negative interferences of nitric oxide (NO) and CO2 are low and therefore no correction was applied. Potential interference from SO2 is minimized by letting SO2 convert to SO4 = by adding hydrogen peroxide. In this method, reported intra-laboratory standard deviation was reported to be 8 μg m-3 (0.004 ppm) while inter-laboratory standard deviation was 11 μg m-3 (0.006 ppm) over a range of 50-300 μg NO m-3 (0.027 to 1.16 ppm) (BIS, 2006).

On the other hand, CO was sampled in Tedlar Bags (SKC Inc., USA) passively through portable air sampling pumps and were analyzed ex situ in a CO analyzer (Model CO11, Environmental SA, France). Stability of CO in Tedler Bags is reported to be good and Tedler bags have been used earlier by various researchers to sample CO (Johnson, 2009; Chudchawal et al., 2000). SKC Tedlar bags are reported to have CO recovery rate of 90% within 48 hours after collection (Coyne et al., 2011). USEPA recommends Tedlar bags for determination of CO emissions from stationary sources in Method 10A (; accessed on 26.2.2019) and 10B (; accessed on 26.2. 2019). Standard recommendation for calibration by the manufacturer was followed and instrument calibration was done by two-point calibration process by zero air and a NIST traceable certified 100 ppm CO (Chemtron Laboratory, Mumbai, India). A suitable calibration coefficient was applied for correction of the obtained sample CO values. The instrument noise was 0.05 ppm and it had a lower detectable limit of 0.1 ppm CO (i.e. 100 ppb) and so anything below this concentration is reported as below detectable limit (BDL). This family of instrument complies with ISO 4224 and EN 14626:2005 standards, EPA, automatic reference method RFCA-206-147 in United States, TÜV No. 936/21206773/B, according to EN 14626. As per TÜV-Report (TÜV, 2008), the combined standard uncertainty and actual expanded uncertainty of CO analyzer (CO12M) in measuring CO had been found to be 0.1490-0.4433 μmol mol-1 and 7.11- 10.29% which were good enough to fulfil the requirements of European Standard EN 14626.

Benzene was analyzed in a BTEX analyzer (Model VOC72M). This agreed with EN 14662-3 standard for measurement of benzene based on chromatographic separation of compounds in conjunction with photoionization detector (PID) (10.6 eV) (Environnement SA,; accessed on 25.11.2018). It is TUV Compliant following EN 14662-3. Sampling is done in a sorbent trap at a flow about 12 mL min-1 that corresponds to a 165 mL sample volume in a 15-minute cycle. After sampling cycle, the trap is quickly heated to 35 to 380°C within 2 seconds to thermally desorb benzene and elute the same into GC column. Optimal separation in column is achieved by following a multi-ramp thermal cycle from 25°C to 160°C for flushing all the heavy compounds. The GC column is a stainless steel made (15 m×0.25 mm×1 μm, apolar). Measuring range of this instrument is maximum 1,000 μg m-3 with a lower detectable limit of ≤0.05 μg m-3 benzene and measuring noise of ≤0.025 μg m-3 at 0.5 μg m-3 benzene.

To record the prevailing meteorological conditions in the areas under study, meteorological data was collected from a portable meteorological station erected at a height of at least 10 meters at each refinery. Collection of meteorological data was carried out simultaneously with ambient air monitoring and windrose diagrams were prepared to understand and demarcate the zone (direction) of possible maximum pollutant concentrations during the study period. The study area maps are presented in Fig. 1.

2. 5 Air Quality Modelling

USEPA’s Industrial Source Complex Short Term (ISCST3) Model (used by ISC-AERMOD software) that is based on Gaussian plume dispersion and suitable for single or multiple emission sources, was applied for predicting average 24-hourly ground-level concentration (GLC) as influenced by stationary source emissions (Cimorelli et al., 1998). Earlier ISC3 model has been used in several studies to predict concentration of pollutants (Bhanarkar et al., 2010; Bhanarkar et al., 2005; Bhanarkar et al., 2003; Abdul-Wahab et al., 2002). Windspeed and directions, two critical model input parameters, were recorded and processed according to the model requirement. The atmospheric stability classes were computed by using Turner’s classification (Hanna et al., 1982). By incorporating physical characteristics of emission source, emission rates, wind speed, wind direction, ambient temperature, stability classes and mixing height as inputs, dispersion modelling was carried out for predicting GLCs of pollutants within 5-km radius around the plant in winter. GLCs of SO2 and NO2 were modeled from their respective emissions from stacks by using ISC3 model and concentration contours over the study area were generated in order to identify the areas of concern. We have undertaken dispersion modeling by considering PM emissions from stacks, but in principle, we could consider PM primarily as PM10, as refinery units are run on oil/ gas that are known to produce fine particles (Sánchez de la Campa et al., 2011; Kulkarni et al., 2007).

3. 1 Stationary Source Emission Assessment

In Refinery 1, the total emission load of PM, SO2 and NOx were found to range from 87.9-221.2 MT y-1 (UB and HRSG), 1.2-111.4 MT y-1 (H2U and SRU) and 14.3-2033.9 MT y-1 (SRU and HRSG), respectively. PM concentration in flue gas ranged from 48.4 to 144.9 mg Nm-3, the highest being from the utility boiler, but the emission load was highest (221.2 MT y-1) in HRSG, followed by CCU (156.1 MT y-1) and the lowest load was obtained from UB (87.9 MT y-1) (Table 2). SO2 was detected in the stack gas from all units, sulphur being a constituent in major raw materials. Highest SO2 concentration and emission load were detected in SRU (646 mg Nm-3 and 111.4 MT y-1, respectively) followed by UB (83.8 mg Nm-3 and 50.9 MT y-1, respectively). Concentration of NO2 was substantial in stack gas from all units, ranging from 57.8 to 445 mg Nm-3 corresponding to emissions of 24.3 and 2,034 MT y-1, respectively. In CDU, concentration and emissions of CO were 6.07 mg Nm-3 and 5 MT y-1, respectively. Concentration of PM, SO2, NO2 were well within the emission standards of MoEFCC in India.

Table 2. 
Emissions of particulates and gases from stationary sources in Refinery 1.
Process/Unit Fuel type Fuel quantity (MT h-1) Concentration (mg Nm-3) Emission load (MT y-1)
CDU FO+FG 5.65 (including VDU) ND 59 249 - 48.6 206.6
DCU FO+FG 2.4 ND 45 227 ND 33.5 170.4
H2U Naphtha 3.6 ND 3 58 ND 1.2 24.3
HCU1 FO+FG 2.2 (including HCU2) ND 3 303 ND 2.9 322.3
HCU2 FG ND 14 235 ND 15.1 252.4
HCU3 FO+FG 0.06 ND 50 217 ND 45.2 194.7
SRU - -- ND 646 83 ND 111.4 14.3
CCU FO+FG 8.6 75.9 6 209 156.1 12.5 430.6
UB FO+Naphtha 1.07 144.9 84 321 87.9 50.9 194.9
HRSG Naphtha 48.4 7 445 221.2 31.9 2033.9
NHDT+CRU FG ND 6 105 ND 4.6 86.8
ND: Not determined (In many units, PM is not generated and hence not measured)
FO: Fuel Oil; FG: Fuel gas
Crude Distillation Unit (CDU); Delayed Coking Unit (DCU); Coke Calcination Unit (CCU); Hydrogen Generation Unit (H2U); Hydrocracker Unit (HCU); Naphtha Hydrotreater/Hydro Desulphurisation Unit (NHDT/NHDS); Catalytic Reforming Unit (CRU); Sulphur Recovery Unit (SRU); Heat Recovery Steam Generator (HRSG)

In Refinery 2, the total emission load of PM, SO2 and NOx were found to range from 2.61-119.8 MT y-1 (DHX 11 and COB), 9.65-656.3 MT y-1 (DHX 11 and UB7) and 3.39-146.5 MT y-1 (DHX 11 and CPP), respectively. The concentration of particulate matter in the stack gas was in the range of 8-99 mg Nm-3 and the emission load ranged from 2.6 to 119 MT y-1 (Table 3). SO2 emission was highest in UB 8/9 (935 mg Nm-3) and lowest in DHX11 (37 mg Nm-3) while NOx concentration in stack gas ranged from 13 mg Nm-3 in DHX 11 to 235 mg Nm-3 in UB6, respectively. CO concentration was 1-46 mg Nm-3. Concentration of PM, SO2 and NOx were also well within the emission standards of MoEFCC. An overview of emissions from refineries around the world indicated that emission loads of most of the air pollutants observed in this work were comparable or lower than that found in some other European, Canadian and Asian refineries (Table 4). High SO2 emissions in Refinery 2 as compared to Refinery 1 might be due to use of high sulphur fuel oil as well as high amount of crude processing/ higher production capacity of Refinery 2 as compared to Refinery 1. High emissions levels of SO2 have been reported by Rao et al. (2006) in 2004 at Gujarat Refinery in India with crude oil processing capacity of 13.5 MMTPA. Karbassi et al. (2008) also reported high SO2 emissions at Tabriz oil refinery which used liquid fuels containing high sulphur.

Table 3. 
Emissions of particulates and gases from stationary sources in Refinery 2.
Process/Unit Fuel type Fuel quantity (MT h-1) Concentration (mg Nm-3) Emission load (MT y-1)
RH1 FO and FG 1.6 14 315 71 5.36 120.66 27.19
HH2 -do- 0.3 16 139 28 3.37 29.29 5.90
HH1 -do- 1.2 17 388 32 3.11 70.96 5.85
KH1 -do- 0.85 95 545 90 16.48 94.57 15.61
CH1 -do- 6.2 22 361 86 27.24 447.03 106.49
CH22 -do- 2.5 47 180 66 7.65 29.29 10.74
CH21 -do- 4.05 23 297 90 30.95 399.64 121.10
CH223 -do- 1.9 99 316 73 39.29 125.40 28.97
UB 8/9 -do- 6.0 43 935 199 12.55 272.91 58.08
DHX 11 -do- 5.0 10 37 13 2.61 9.65 3.39
SRU -do- 0.13 42 734 86 4.74 82.84 9.71
CPP -do- 5.8 8 173 70 16.74 362.08 146.51
UB 10 -do- 5.0 52 681 186 25.40 332.68 90.86
UB6 -do- 2.0 18 655 235 8.23 299.49 107.45
COB -do- 2.55 93 121 62 119.80 155.87 79.87
UB7 -do- 4.8 72 563 70 83.94 656.33 81.60
UB 4/5 -do- 3.5 13 905 58 4.69 326.52 20.93
DDH1 -do- 0.85 22 285 85 5.32 68.93 20.56
RH1: Reformer charge heater (CDU1); HH1: Naptha splitter 2 heater/NHDS charge heater (NHDS); HH2: NHDS Stripper Reboiler (NHDS); KH1: Kerosene Unit Charge heater (KHDS); CH1, CH21, CH22: Crude charge heaters (CDU1, CDU2, CDU2); CH223: Vacuum heater (CDU); UB4/5, UB6, UB7, UB8/9: Utility boiler; DHX11: DHDS Unit (DHDS); CPP: PIB Heater; SRU: Sulphur Recovery Unit (SRU); UB10: HRSG; COB: FCC Charge heater (FCC); DDH1: Reformer charge heater (DHDS)

Table 4. 
Review of particulate and gaseous emissions and ambient air quality near refineries around the globe.
Refinery-City Country Year of study Production/crude processed (MT y-1) Emissions (MT y-1, unless specified) Ambient air quality (μg m-3, unless specified) Ref
Gela Refinery-Sicily Italy 1996 5320000 610 68000 7200 850 2050* - - - - - Bevilacqua and Braglia (2002)
Livorno Refinery Italy 1996 4500000 155 13000 2000 152 170* - - - - - -do-
Priolo Refinery-Augusta Italy 1996 8350000 480 17500 6400 380 2390* - - - - - -do-
Sannazzano Refinery-Padania Italy 1996 8180000 440 4850 5200 430 2200* - - - - - -do-
Taranto Refinery Italy 1996 3970000 440 8000 2250 305 1000* - - - - - -do-
Kaohsiung Refinery, Kaohsiung Taiwan 2001 - - - - - - - 77# 53# - 79+# (benzene) Chiu et al. (2005)
North Atlantic Refinery, Newfoundland Canada 1998 - - 23680 - - - - 4.2-8.8 - - - Fisher et al. (2003)
Corinth Refinery, Agioi Theodori, Corinthia Greece - 4750000 - - - - - - - - - 0.81+ (benzene) Kalabokas et al. (2001)
Tabriz oil refinery-Tabriz Iran 2004 408192 - 10963 6150 - - - - - - - [62] Karbassi et al. (2008)
Mina Al-Fahal Refinery Oman - 39836289 315.0* - - - - 64.49 - - - Abdul-Wahab et al. (2002)
Gujarat Refinery India 2003 13500000 - 8203.7* - - - 45-91 4-28 - - - Rao et al. (2006), Rao et al. (2008)
Digboi Refinery India 2003 650000 - - - - - - - - - 13.6-159.2 (benzene) Pandya et al. (2006), Rao et al. (2007)
Chevron Burnaby Refinery British Columbia 1998-2000 - 10.3-13.5 0.0021-0.0052+ + 0.012-0.028+ + - - 10.3-13.5 0.029-0.288 0.073-0.081 0.71-1.17$ - Kennedy et al. (2002)
Naphtha Cracking Complex Taiwan 2009 450000 barrels day-1 - 6216 - - - - 0.226-0.849 - - - Shie et al. (2013)
Refinery, Montreal Canada - - - - - - - - 4.4-6.9 - - - Smargiassi et al. (2009)
Falconara Italy - 3900000 - - - - - - 17.0 38.7 - 1.7 (benzene) De Santis et al. (2004)
Refinery 1 India 2007 2568000 465.2 357.8 3931.2 5.0 0.0 38-65 3-8 3-9 0-525 - This study
Refinery2 India 2009 7680000 417.5 3884.2 940.8 88.1 0.0 46-79 3 4-7 130-501 - This study
#day time concentration; + +ppm; +ppb; $avg. of 8-hourly maximum values in ppm; *estimated value considering 24×7×365 operation

3. 2 Ambient Air Quality

The windrose diagram prepared for Refinery 1 indicated that prevailing wind direction was from North and Northeast direction, with the wind speed prevailing within a range of 2-5 m s-1 (Fig. 1). Winds from other directions were also observed on a few occasions with a predominance of North-Western direction. Calm condition was significantly prevalent, in 44% cases. The 24- hourly average levels of SO2, NO2, CO, benzene and PM10 around the Refinery 1 prevailed within the limits promulgated in National Ambient Air Quality Standards (NAAQS) (CPCB, 2018a). Due to wind effect, higher concentration of pollutants are observed at sites located in downwind directions. SO2 levels were always found to be low, while very low concentrations of NO2 were found at one station (Table 5). On the other hand, CO was detected at all the locations. Benzene was detected at a few locations but was persistently low in concentration, ranging from 0.17 to 0.31 μg m-3. Maximum PM10 concentration was 65 μg m-3 at location N1 followed by 53 μg m-3 at N4.

Table 5. 
Concentration of select criteria pollutants in ambient air.
Site code PM10 (μg m-3) SO2 (μg m-3) NO2 (μg m-3) CO (μg m-3) Benzene (μg m-3)
Refinery 1
N1 65 5.0 9.0 171 NDa
N2 38 3.0 5.0 170 ND
N3 53 5.0 3.0 525 0.31
N4 53 8.0 5.0 430 0.17
Refinery 2
K1 61 3.0 6.0 256 0.9
K2 52 3.4 5.2 388 1.2
K3 69 3.2 4.4 246 2.8
K4 51 3.4 4.0 380 4.4
K5 54 5.0 4.0 250 6.4
K6 46 3.0 4.0 501 1.6
ND: Not detected [aLDL for Benzene=0.05 μg m-3 benzene]
All the values are averages of 5 days.

As per the windrose diagram for Refinery 2, the prevailing wind direction was from West-South West with wind speed mostly falling in the range of 0.5-2.1 m s-1 (Fig. 1). Wind from the North-Western direction was also conspicuous. Higher wind speed of 2.1-3.6 m s-1 were observed on a few occasions. Weather Conditions prevailing near the refineries during the month of monitoring showed substantial day-to-day variability in relative humidity, especially in the minima, while temperature and pressure variability were comparatively lower. As the monitoring exercises were undertaken during February in Refinery 1 and September in Refinery 2, average temperature difference between the refineries was about 4-5°C while temperature in Refinery 1 showed a slightly increasing trend due to approaching summer. In general, slightly higher concentration of pollutants are observed at sites located in downwind directions. Around Refinery 2 also, 24-hourly average levels of SO2, NO2, CO, benzene and PM10 prevailed within the limits prescribed as NAAQS. In general, higher concentration of pollutants are observed at sites located in downwind directions. SO2 levels were persistently low, while very low concentrations of NO2 were found at a few stations (Table 5). Low ambient concentrations of SO2 and NO2 could be due to the location of refineries in open land with almost no blockade that promoted good dispersion and dilution of pollutants. Also, negligible presence of polluting industries in the vicinity and low vehicular traffic ensured low levels of ambient SO2 and NO2. Low ambient levels of SO2 and NO2 have been reported by Central Pollution Control Board (CPCB) in 2008 and 2010 at a few cities and towns of India (;; both accessed on 22.2.2019). CO and benzene were detected at all the locations but were low in concentration. However, benezene concentrations were found to be generally higher in this refinery than Refinery 1. Maximum PM10 concentration was to the tune of 69 μg m-3 at site K3 followed by 61 μg m-3 in site K1. Observed ambient air quality in our study and ambient air quality around other petroleum refineries in several other countries was found to be comparable (Table 4).

Ambient concentration of PM10, SO2 and CO were converted to respective air quality indices (AQI) as per USEPA’s concentration-AQI conversion principles and formulae (AirNow, 2018). It was noted that while AQI of CO never entered the zones of concern at any site and were always good, AQI of PM10 were moderate at two sites, the rest being good (Table 6). In case of SO2, no AQI could be calculated as SO2 concentration values were outside the calculable range. AQI for NO2 could not be calculated as the required 1-h average NO2 concentration data needed for AQI calculation were not available. Further, AQI was also developed as per the formula AQI used by Central Pollution Control Board (CPCB) of India (CPCB, 2018b) (Table 6). Since all the eight pollutants included in AQI calculation was not monitored, AQI was calculated based on concentration of minimum necessary three pollutants amongst which one should be either PM2.5 or PM10. Sub-indices were also generated for each pollutant to evaluate air quality status for that particular pollutant. The pollutant-wise calculated sub-index values for PM10 ranged from 38- 65 and 38-69 for refinery 1 and refinery 2 respectively. However, CO showed sub-index values varying between 9-26 and 9-25, respectively, for refinery 1 and refinery 2. Similarly, the sub-index values for NO2 ranged from 6-11 and from 5-8, respectively, for refinery 1 and refinery 2, whereas for SO2, it ranged from 4-6 for both the refineries. From the above calculations, it became apparent that AQI had never been poor under any circumstances at the selected sites, indicating no risk of significant health impacts to inhabitants residing near these refineries. Considering that clean burning fuels were used in these refineries and low PM concentration were obtained in stack gas from various units, AQI of all air quality monitoring stations in both the refineries were found to be satisfactory. Analysis of particulate-bound SO4= and NO3- in filters containing either ambient particulates or stack gas particulates was not deemed crucial for drawing important conclusions. Hence, this aspect was kept out of scope of this work.

Table 6. 
Conversion of ambient concentration to Air Quality Index (AQI).
Site code USEPAa CPCBb
AQI (PM10) AQI (SO2) AQI (CO) AQI Sub-index
Refinery 1
N1 56 (moderate) - 2 (good) 65 (satisfactory) 65 (PM10), 6 (SO2), 11 (NO2), 9 (CO)
N2 35 (good) - 2 (good) 38 (satisfactory) 38 (PM10), 4 (SO2), 6 (NO2), 9 (CO)
N3 49 (good) - 5 (good) 53 (satisfactory) 53 (PM10), 6 (SO2), 4 (NO2), 26 (CO)
N4 49 (good) - 4 (good) 53 (satisfactory) 53 (PM10), 6 (SO2), 10 (NO2), 22 (CO)
Refinery 2
K1 53 (moderate) - 2 (good) 61 (satisfactory) 61 (PM10), 4 (SO2), 8 (NO2), 13 (CO)
K2 47 (good) - 4 (good) 52 (satisfactory) 38 (PM10), 4 (SO2), 6 (NO2), 9 (CO)
K3 57 (moderate) - 2 (good) 69 (satisfactory) 69 (PM10), 4 (SO2), 6 (NO2), 12 (CO)
K4 46 (good) - 4 (good) 51 (satisfactory) 51 (PM10), 4 (SO2), 5 (NO2), 19 (CO)
K5 49 (good) - 2 (good) 54 (satisfactory) 54 (PM10), 6 (SO2), 5 (NO2), 13 (CO)
K6 42 (good) - 5 (good) 46 (satisfactory) 46 (PM10), 4 (SO2), 5 (NO2), 25 (CO)
N.B.: Missing values indicate ‘out of range’ returned by the calculator.

3. 3 Dispersion Modeling

Air quality modeling exercise undertaken by ISCST 3 Model (used by ISC-AERMOD software) with the stationary source emission data of Refinery 1 revealed that major dispersion of PM, SO2 and NO2 occurred in southwest and northeast directions due to predominant winds patterns. However, the impact of refinery emissions was not significant and ambient air quality levels of these pollutants did not exceed NAAQS. The maximum modeled GLC of PM, SO2 and NO2 were 2.4, 2.6 and 14.9 μg m-3, respectively (Table 7). The isopleths of predicted concentrations for SO2 in Refinery 1 are presented in Fig. 2a. In Refinery 2, predicted air quality generated by the model indicates that the maximum GLCs of PM, SO2 and NO2 were 2.1, 17.1 and 4.9 μg m-3, respectively (Table 6), which are lower than NAAQS and occurred primarily in the eastern direction. The isopleths of predicted concentrations for SO2 in Refinery 2 are presented in Fig. 2b. Maximum GLCs of these pollutants was observed within 3-4 km in eastern direction.

Table 7. 
Summary of actual and predicted 24-hrly concentration of select criteria ambient air pollutants vis a vis regulatory standards.
24-hrly concentration PM10 (μg m-3) SO2 (μg m-3) NO2 (μg m-3) CO (μg m-3) Benzene (μg m-3)
Refinery 1
Observed value 38-65 3-8 3-9 170-525 0-0.31
Modelled value 2.4* 2.6 14.9 NC NC
CPCB standard 100 80 80 2# 5$
Refinery 2
Observed value 46-69 3-5 4-6 246-501 0.9-6.4
Modelled value 2.1* 17.1 4.9 NC NC
CPCB standard 100 80 80 2# 5$
*Particulate Matter (PM) concentration
#8-hourly avg. in mg m-3
**24-hourly avg.
$Annual avg.
NC - Modeling not conducted

Fig. 2. 
Isopleths and windroses superimposed on maps showing predicted GLCs (μg m-3) of SO2 in (a) Refinery 1 (b) Refinery 2 and wind patterns, respectively [circles are of 5 km radius around the centres of refineries].

Low to moderate difference was observed between observed and modeled GLCs of the air pollutants which has been earlier reported by other researchers also (Abdul- Wahab et al., 2002). The observed concentration of PM10 in ambient air was found to be similar (Table 7) in both refineries as the total emission of PM from all stacks were similar in both. The concentrations for PM10 in ambient air are higher than predicted values due to presence of other sources of particulates like vehicular emissions in nearby roads, fugitive dust emissions from nearby agricultural fields and road construction activities, emissions from other stationary sources that included small workshops and emissions from household biomass burning which were not considered by the model. The modelled values of PM by ISCST3 was also similar (2 and 3 μg m-3, respectively), that depended on the stack PM emissions and hence validated. Though the emission of SO2 was much more in Refinery 2 than Refinery 1, the ambient concentration of SO2 was similar in both, probably because of higher conversion of SO2 into sulphate in the ambient air of Refinery 2, which is situated near sea shore. Conversion of SO2 to sulphate on sea salt in atmosphere is reported (Alexander et al., 2005) and hence, a predominance of this reaction might have played an active role in high conversion of emitted SO2 near Refinery 2.


The results indicated that though SO2 and NOx were the major air pollutants released by the stationary sources in the refineries, ground level concentrations of SO2, NO2 and PM did not exceed NAAQS followed in India. Air quality in terms of AQI values was never poor under any circumstances at the selected sites. These refineries are located in non-industrial zones and hence no other industrial emission was present to further deteriorate ambient air quality. Observed GLCs of SO2, NO2 and PM were predicted to a reasonable degree of accuracy from the stack emissions by the model ISCST3 (used by ISC-AERMOD software), which was authenticated by the measured levels in ambient air.

Refineries are major sources of SO2 and PM (Yateem et al., 2011) that includes fine, deeply inhalable metalliferous atmospheric PM with high degree of chemical and size variation, along with hydrocarbons, VOCs, CO2 etc. causing proximal and distal contamination in the long run and posing health risk to the inhabitants (Sánchez de la Campa, 2011; Holmgren and Sternhufvu, 2008; Karabassi et al., 2008; Lin et al., 2004; Cetin et al., 2003). Considering these, further study is needed to focus on size distribution and chemical composition of particulate- bound metals and VOCs emanating from stationary sources in refineries to assess human health risk.

Although air quality in terms of SO2, NO2 and PM in the surrounding area of both the refineries did not exceed NAAQS and the AQI had never been poor, in order to maintain better air quality, low-sulphur fuels should be used in heaters and boilers of these refineries. Efficiency of SRU system should be monitored regularly to control SO2 emissions to meet Indian emission standards specified by MOEF. Low NOx burners should be used in all heaters and boilers to control emissions of NOx from these refineries.


The continuous guidance and support of Director, CSIR-NEERI is gratefully acknowledged. The KRC (Knowledge Resource Centre of CSIR-National Environmental Engineering Research Institute) number for the manuscript is CSIR-NEERI/KRC/2018/AUG/APC-KZC/1.

1. Abdul-Wahab, S.-A., Al-Alawi, S.-M., El-Zawahry, A., (2002), Patterns of SO2 emissions: A refinery case study, Environmental Modelling and Software, 17, p563-570.
2. Aggarwal, S.-G., Kumar, S., Mandal, P., Sarangi, B., Singh, K., Pokhariyal, J., Mishra, S.-K., Agarwal, S., Sinha, D., Singh, S., Sharma, C., Gupta, P.-K., (2013), Traceability issue in PM2.5 and PM10 measurements, MAPAN-Journal of Metrology Society of India, 28(3), p153-166.
3. AirNow, (2018), AQI Calculator,, 29 June 2018.
4. Alexander, B., Savarino, J., Lee, C.-C.-W., Thiemens, M.-H., (2005), Sulfate formation in sea-salt aerosols: Constraints from oxygen isotopes, Journal of Geophysical Research, 110(D10), p307.
5. Al-Hamad, K.-K., Khan, A.-R., (2008), Total emission from flaring in Kuwait Oil fields, American Journal of Environmental Science, 4, p31-38.
6. Al-Jahdali, M.-O., Bin Bisher, A.-S., (2008), Sulfur dioxide (SO2) accumulation in soil and plant’s leaves around an oil refinery: A case study from Saudi Arabia, American Journal of Environmental Science, 4, p84-88.
7. ASTM, (2005), Standard practice for planning the sampling of ambient atmosphere, D1357-95, ASTM International, PA, USA.
8. Barberino, J.-L., Carvalho, F.-M., Silvany, A.-M., Coes, R., Rosa, H., Gidi, J., Valladares, C., Guedes, J., (2005), Liver changes in workers at an oil refinery in a reference population in state of Bahia, Brazil, Pan American Journal of Public Health, 17, p30-37.
9. Bertazzi, P.-A., Pesatori, A.-C., Zocchetti, C., Latocca, R., (1989), Mortality study of cancer risk among oil refinery workers, International Archives of Occupational and Environmental Health, 61, p261-270.
10. Bevilacqua, M., Braglia, M., (2002), Environmental efficiency analysis for ENI oil refineries, Journal of Cleaner Production, 10, p85-92.
11. Bhanarkar, A.-D., Gajghate, D.-G., Hasan, M.-Z., (2003), Assessment of impacts of a fossil fuel based power plant, International Journal of Environmental Studies, 60, p325-333.
12. Bhanarkar, A.-D., Majumdar, D., Nema, P., George, K.-V., (2010), Emissions of SO2, NOx and particulates from a pipe manufacturing plant and prediction of impact on air quality, Environmental Monitoring and Assessment, 169, p677-685.
13. Bhanarkar, A.-D., Rao, C.-V.-C., Pandit, V.-I., (2005), Air pollution modeling for power plant site selection, International Journal of Environmental Studies, 62, p527-534.
14. BIS, (1985), Indian standard: Methods for Measurement of Emission from Stationary Sources, Part 1: Particulate Matter (First Reprint APRIL 1998), Bureau of Indian Standards, New Delhi, India, IS 11255 (Part 2: 1985)) (Reaffirmed 2003).
15. BIS, (2001), Indian standard: Methods for measurement of air pollution, Part 2: Sulphur Dioxide (First Revision), Bureau of Indian Standards, New Delhi, India, IS 5182 (Part 2: 2001).
16. BIS, (2006), Indian Standard: Method for Measurement of Air Pollution, Part 6: Oxides of Nitrogen (First Revision), Bureau of Indian Standards, New Delhi, India, IS 5182 (Part 6: 2006).
17. Cetin, E., Odabasi, M., Seyfioglu, R., (2003), Ambient volatile organic compound (VOC) concentrations around a petrochemical complex and a petroleum refinery, Science of Total Environment, 312, p103-112.
18. Chiu, K.-W., Usha Sree, , Tseng, S.-H., Wu, C.-H., Lo, J.-G., (2005), Differential optical absorption spectrometer measurement of NO2, SO2, O3, HCHO and aromatic volatile organics in ambient air of Kaohsiung Petroleum Refinery in Taiwan, Atmospheric Environment, 39, p941-955.
19. Chudchawal, J., Halet, G.-P., Roy, J.-R., (2000), Determination of carbon monoxide with a modified zeolite sorbent and methanization-gas chromatography, AIHAJ-American Industrial Hygiene Association, 61, p410-414.
20. Cimorelli, A.-J., Wilson, R.-B., Perry, S.-G., Venkatram, A., Weil, J.-C., Paine, R.-J., Lee, R.-F., Peters, W.-D., (1998), Minimum meteorological data requirements for AERMOD-study and recommendations, USEPA Version 98314 (AERMOD and AERMET), 98022 (AERMAP) (; accessed on 11. 11.2018).
21. Coyne, L., Kuhlman, C., Zovack, N., (2011), The stability of sulfur compounds, low molecular weight gases, and VOCs in five air sample bag materials, SKC Inc., Eighty Four, PA 15330, USA,; accessed on 1.12.2018.
22. CPCB, (1981a), Comprehensive industry document oil refineries, COINDS/3/1980-81, Central Pollution Control Board, New Delhi, India.
23. CPCB, (1981b), Minimal national standards: oil refineries, COINDS/4/1980-81, Central Pollution Control Board, New Delhi, India.
24. CPCB, (1985), Comprehensive industry document series, emission regulations Part II, COINDS/18/1984-85, Central Pollution Control Board, New Delhi, India.
25. CPCB, (2018a), Air Quality Standards,; accessed 10 January 2018.
26. CPCB, (2018b), National Air Quality Index,; acecessed 26 June 2018.
27. De Santis, F., Fino, A., Menichelli, S., Vazzana, C., Allegrini, I., (2004), Monitoring the air quality around an oil refinery through the use of diffusive sampling, Analytical and Bioanalytical Chemistry, 378, p782-788.
28. Fisher, A.-L., Parsons, M.-C., Roberts, S.-E., Shea, P.-J., Khan, F.-I., Husain, T., (2003), Long term SO2 dispersion modeling over a coastal region, Environmental Technology, 24(4), p399-409.
29. Hanna, S.-R., Briggs, G.-A., Hosker, R.-P.-Jr., (1982), Handbook of atmospheric diffusion, Washington, DC, Technical Information Center, US Department of Energy, DOE/TIC-11223.
30. Holmgren, K., Sternhufvud, C., (2008), CO2-emission reduction costs for petroleum refineries in Sweden, Journal of Cleaner Production, 16, p385-394.
31. IBEF, (2017), Sectoral Report, Oil & Gas industry in India, India Brand Equity Foundation, New Delhi, India, p1-15.
32. Johnson, M., Edwards, R., Ghilardi, A., Berrueta, V., Gillen, D., Alatorrefrenk, C., Masera, O., (2009), Quantification of carbon savings from improved biomass cookstove projects, Environmental Science and Technology, 43, p2456-2462.
33. Kalabokas, P.-D., Hatzianestis, J., Bartzis, J.-G., Papagiannakopoulos, P., (2001), Atmospheric concentrations of saturated and aromatic hydrocarbons around a Greek oil refinery, Atmospheric Environment, 35, p2545-2555.
34. Karabassi, A.-R., Abbasspour, M., Sekhavatjou, M.-S., Ziviyar, F., Saeedi, M., (2008), Potential for reducing air pollution from oil refineries, Environmental Monitoring and Assessment, 145, p159-166.
35. Karras, G., (2010), Combustion emissions from refining lower quality oil, what is the global warming potential?, Environmental Science and Technology, 44, p9584-9589.
36. Kennedy, S.-M., Copes, R., Henderson, S., Na, S., MacKay, C., (2002), Air Emissions from the Chevron North Burnaby Refinery: Human Health Impact Assessment, UBC School of Occupational and Environmental Hygiene, University of British Columbia, Canada.
37. Korte, F., Boedefeld, E., (1978), Ecotoxicological review of global impact of petroleum industry and its products, Ecotoxicology and Environmental Safety, 2, p55-103.
38. Kulkarni, P., Chellam, S., Fraser, M.-P., (2007), Tracking petroleum refinery emission events using lanthanum and lanthanides as elemental markers for PM2.5, Environmental Science and Technology, 41, p6748-6754.
39. Lin, T.-S., Usha Sree, , Tseng, S.-H., Chiu, K.-H., Wu, C.-H., Lo, J.-G., (2004), Volatile organic compound concentrations in ambient air of Kaohsiung petroleum refinery in Taiwan, Atmospheric Environment, 38, p4111-4122.
40. Luginaah, I.-N., Taylor, S.-M., Elliott, S.-J., Eyles, J.-D., (2000), A longitudinal study of the health impacts of a petroleum refinery, Social Science and Medicine, 50, p1155-1166.
41. MoEF, (2008), Environmental Standards: G.S.R. 186 (E), [18/03/2008] - Environmental Standards for Petroleum Oil Refinery,; accessed on 1.10.2018.
42. Pandya, G.-H., Gavane, A.-G., Bhanarkar, A.-D., Kondawar, V.-K., (2006), Concentrations of volatile organic compounds (VOCs) at an oil refinery, International Journal of Environmental Studies, 63, p337-351.
43. Pimpisut, D., Jinsart, W., Hooper, M., (2003), Ambient air Levels and Sources of BTEX at a Petrochemical Complex in Thailand, Presented at 2nd Regional Conference on Energy Technology Towards a Clean Environment, February 12-14, Phuket, Thailand.
44. PPAC, (2018), Map of Refineries in India,
45. Rao, P.-S., Ansari, M.-F., Gajrani, C.-P., Kumar, A., Nema, P., Devotta, S., (2006), Atmospheric concentrations of sulphur dioxide in and around a typical Indian petroleum refinery, Bulletin of Environmental Contamination and Toxicology, 77, p274-281.
46. Rao, P.-S., Ansari, M.-F., Gavane, A.-G., Pandit, V.-I., Nema, P., Devotta, S., (2007), Seasonal variation of toxic benzene emissions in petroleum refinery, Environmental Monitoring and Assessment, 28, p323-328.
47. Rao, P.-S., Ansari, M.-F., Pipalatkar, P., Kumar, A., Nema, P., Devotta, S., (2008), Measurement of particulate phase polycyclic aromatic hydrocarbon (PAHs) around a petroleum refinery, Environmental Monitoring and Assessment, 137, p387-392.
48. Rao, P.-S., Chauhan, C., Mhaisalkar, V.-A., Kumar, A., Devotta, S., Wate, S.-R., (2012), Factor analysis for estimating source contribution to ambient airborne particles in and around a petroleum refinery in India, Indian Chemical Engineer, 54, p12-21.
49. Sánchez de la Campa, A.-M., Moreno, T., de la Rosa, J., Alastuey, A., Querol, X., (2011), Size distribution and chemical composition of metalliferous stack emissions in the San Roque petroleum refinery complex, southern Spain, Journal of Hazardous Materials, 90, p713-722.
50. Shie, R.-H., Yuan, T.-H., Chan, C.-C., (2013), Using pollution roses to assess sulfur dioxide impacts in a township downwind of a petrochemical complex, Journal of Air and Waste Management Association, 63, p702-711.
51. Simonsen, N., Scribner, R., Su, L.-J., Williams, D., Luckett, B., Yang, T., Fontham, E.-T.-H., (2010), Environmental exposure to emissions from petrochemical sites and lung cancer: the lower Mississippi Interagency Cancer Study, Journal of Environmental and Public Health, Article ID 759645.
52. Smargiassi, A., Kosatsky, T., Hicks, J., Plante, C., Armstrong, B., Villeneuve, P.-J., Goudreau, S., (2009), Risk of asthmatic episodes in children exposed to sulfur dioxide stack emissions from a refinery point source in Montreal, Canada, Environmental Health Perspectives, 117, p653-659.
53. Srivastava, S., Gargava, P., Ansari, P.M., (2010), New Approaches for Environmental Management in Indian Petroleum Refineries, Paper presented at 97th Indian Science Congress, ISC-2010, January 3-7, Thiruvananthapuram, India.
54. Tasi, S.-P., Wendt, J.-K., Cardarelli, K.-M., Fraser, A.-E., (2003), A mortality and morbidity study of refinery and oil employees in Louisiana, Journal of Occupational and Environmental Medicine, 60, p627-633.
55. TÜV, (2008), Summary of the report on the suitability test of the ambient air quality measuring system CO12M of the company Environnement S.A. for the measured component CO according to EN 14626, TÜV-Report 936/21206773/D, TÜV Rheinland Immissionsschutz und Energiesysteme GmbH, TÜV Rheinland Group, Cologne, US.
56. USEIA, (2013), Full report, Country India, U.S. Energy Information Administration, Washington, p1-19.
57. USEPA, (1995), Profile of the petroleum refining industry, Office of compliance sector notebook project, EPA 310-R-95-013, U.S. Environmental Protection Agency, Washington.
58. USEPA, (1997), Code of federal regulations, 40 CFR Part 60, Standards of performance for new stationary sources, U.S. Environmental Protection Agency, New York.
59. World Bank, (1998), Pollution prevention and abatement handbook, Petroleum refining, Environment Department, Washington.
60. Yang, C.-Y., Chang, C.-C., Chuang, H.-Y., Ho, C.-K., Wu, T.-N., Chang, P.-Y., (2004), Increased risk of preterm delivery among people living near the three oil refineries in Taiwan, Environment International, 30, p337-342.
61. Yang, C.-Y., Chen, B.-H., Hsu, T.-Y., Tsai, S.-S., Hung, C.-F., Wu, T.-N., (2000), Female lung cancer mortality and sex ratios at birth near a petroleum refinery plant, Environmental Research, 83, p33-40.
62. Yateem, W., Nassehi, V., Khan, A.-R., (2011), Inventories of SO2 and particulate matter emissions from fluid catalytic cracking units in petroleum refineries, Water Air Soil Pollution, 214, p287-295.