A summary of some of the scientific sources used in the compilation of this article is presented below.
by Chengliang Zhang et al, studied a petroleum refinery for Reduction of fugitive VOC emissions by using leak detection and repair (LDAR). this investigation carried out at the China on 2022, Result showed the LDAR was effectiveness to decrees VOC emissions of petroleum refinery (Zhang et al., 2022).
Arkadiusz Kamiński et al. investigated in Poland in 2019 entitled “The Use of Dedicated System Tools in Integrated Management in Environmental Protection on the Example of LDAR Program”. The findings of this study showed that LDAR is one of the tools that reduce VOCs emissions into the atmosphere, lower fuel consumption and prevent product loss. It also improves workplace safety risks and lowers environmental costs (Kamiński et al., 2019).
The paper entitled “Optical Gas Imaging (OGI) as a Moderator for Interdisciplinary Cooperation, Reduced Emissions and Increased Safety", published by Log et al. in 2019, shows that the OGI camera is a very valuable tool for detecting probable emissions of volatile compounds. It is also a valuable tool for fire and explosion safety management, which can reduce damage after a leak (Log et al., 2019).
The article entitled "Leak Detection and Repair (LDAR) Standard Review for Self-Inspection and Management for VOC Emission in China’s Traditional Energy Chemical Industry", published by Jinbo Zhao et al. (2018), demonstrated that hydrocarbon emissions from energy chemical industries in China comprise 20% of the total abnormal VOCs emissions. The coal and petrochemical industries are the most important sources of VOCs emissions. This study showed that careful implementation of emission source inspection and management projects not only results in reduced VOCs but also leads to lower costs, cleaner production, and more economic efficiency (Li et al., 2019).
The LDAR program at the Qatar LNG refinery is the focus of an article published by Khan et al. (2014). In this study, it was determined that volatile organic compounds (VOCs) in the atmosphere as a result of photochemical reactions lead to the formation of ground-level ozone. The implementation of the LDAR program has also reduced the leakage rate at Qatar gas facilities and has reduced the VOCs emissions by approximately 97% since the implementation of the LDAR program.
Apart from VOCs, due to the high fuel consumption in the petrochemical industry especially in furnaces, the release of other pollutants such as NOx is of great importance, too. Various activities have been carried out to estimate the emission of this pollutant in various oil industries, some of which are discussed below.
The emission of gaseous pollutants from the flared exhaust is more than from turbines and boilers. Also, the CO2 emission factor is more influenced by the type of fuel consumed than it is by the type of device (Kahforoshan et al., 2014).
NOx, CO, and CO2 gases can have harmful environmental effects. It is necessary to determine their emission rates to estimate and control the emission of these gases. Also, the amount of vapor and excess air present in the gases has a significant impact on their emissions (Talebi et al., 2014).
Theory/calculation
This research is an applied one and was carried out on a case-by-case basis in the olefin unit of the petrochemical industry. Petrochemical complex is located in the Pars Special Energy Economy Zone (PSEEZ) in south of Iran. The new technology of volatile gas leak detection i.e. "FLIR Gas FindIR HSX" equipment has been used to conduct research and for quantifying leakages, the "Ultraprobe 10,000" device was utilized. The infrared camera is specialized for thermal imaging to detect leakage of volatile gases in the Leak Detection and Repair Program (LDAR). Before the site visit, an engineering review was conducted considering P&ID maps and the number of hydrocarbon-containing equipment was determined in each section of the olefin unit. Then the number of potential leak sources (PLS) per equipment was calculated based on the number of components. Valves and other equipment, shown as individual items in P&ID, have several potential leak sources. The number of potential leak sources per device will always be greater than the number of its components. During this study, several types of tools approved by the EPA were used to determine the leakage of process equipment. During this study, a variety of tools approved by the EPA were used to determine the leakage of process equipment. Their names are given in Table 1 with the abbreviation. After determining the process equipment leak locations, environmental flow diagrams (EFDs) were plotted based on PFD and P&ID maps using Ms-Visio software. A list of process equipment that was inspected for leak detection using a Gas FindIR HSX camera is given in Table 2. Flowchart 1 shows the structural outline of the LDAR implementation.
Table 1
List of leak detection tools
Abbreviation: | Survey Equipment Name: | Used to: |
OGI | Optical Gas Imaging | Identify VOC/Hydrocarbon Leaks |
UP | Ultraprobe | Identify & Quantify Compressed Gas Leakages |
Table 2
Names of process equipment for leak detection
Valves | Blind Spades |
Pumps | Spectacle Blinds |
Open Ended Lines | Pipe Caps |
Instruments | Pipe/Threaded Caps |
Safety Valves | Y-Type Strainer |
Vents | I-Type Strainer |
Seals | Vessel Manways |
Liquid Drainage Points | Pumps |
Well Heads | Flow Meters |
Pig Launcher/Receiver | |
Flanges (Pipe & Blind) | |
The mean concentration of each pollutant at each time was measured and calculated to evaluate the status of the unit air pollution throughout the year. For this purpose, the cell size and geographical scope of the raster layers of the pollutants concentrations were aligned at each measurement turn. Then, using the Raster Calculator, the annual mean concentrations of the pollutants were calculated and the related maps were prepared. Subsequently, the results of the interpolation of the pollutants concentrations at the olefin unit boundary are presented. In these maps, there are 2 plans for each pollutant. The first plan shows the pollutant concentration continuously and the second one shows the concentration levels rather than the relevant standards. IDW route in ArcGIS 10.2 software was used for zoning of benzene and ethyl benzene pollutants emissions in ambient air. The position of the environmental pollutants measurement points is presented in Fig. 1.
Emission modeling
The fuel consumed in the burner of olefin furnaces is Fuel Gas, which is one of the clean fuels. Based on the monitoring and measurement of chimney exhaust gases, NOx was identified as the most important pollutant. In this study, the concentration and distribution mode of NOx emitted from 9 chimneys of the olefin unit in different seasons as well as annual averages of meteorological data in 2021 were simulated by the AERMOD model over an area of 50×50 km2. To model the distribution of pollutants from the olefin unit chimneys of the petrochemical complex using AERMOD, three-hour meteorological data from the nearest weather station were used for over a year. The station is approximately 7 km from the site under study. The dominant wind direction in this region is northwest to southeast. (Moradzadeh,and et al. 2018)
After processing the meteorological data by AERMET and providing the required information, the up-and-down situation of the region of the study was determined using the AERMAP core. The heights are located to the north of the complex. In the modeling scope, the highest altitude is 1537 m and the lowest one is the sea level. (Alhamdani, Y. A., and et al, 2017)
The emission rate of NOx was calculated based on the measurements taken from each emission source of the complex and the discharge of gas from each chimney. To determine the emission rate of this pollutant, the amount of pollutants emitted from all the chimneys studied was measured in each season. Then, through Eq. 1, the emission rate of each pollutant was calculated.
\(E=\frac{C\text{*}MW\text{*}P\text{*}V\text{*}\pi {d}^{2}\text{*}273.15}{\left(T+273.15\right)\text{*}68137344}\) (Eq. 1)
E = pollutant emission rate\(\left(\frac{gr}{S}\right)\)
C = pollutant concentration\(\left(PPM\right)\)
MW = pollutant molecular weight
P = atmospheric pressure\(\left(mm Hg\right)\)
V = output gas velocity\(\left(\frac{m}{S}\right)\)
d = internal diameter at chimney outlet\(\left(m\right)\)
T = output gas temperature\(\left(C\right)\)
The relevant information and the emission rates calculated using the discharge are presented in Table 5.