Characterizing the unknown contribution of iron industries in atmospheric iron emissions using sensitivity analysis
Introduction
Iron ores, mainly contain iron-rich minerals, such as hematite (Fe2O3) and magnetite (Fe3O4), are mined and beneficiated to make concentrates. Concentrated minerals need to be further processed to be used directly in most iron-making furnaces, thereby, they are pelletized with binders and additives in iron processing plants. Iron industries just like oil industries (Amoatey et al., 2019) and sewage treatment plants (Baawain et al., 2017 and 2019) are recognized for their atmospheric emission potential (Mohiuddin et al., 2014; Omidvarborna, Baawain, Al-Mamun, et al., 2018). Fine (aerodynamic diameter less than 2.5 μm; PM2.5) and coarse (aerodynamic diameter between 2.5 and 10 μm; PM2.5-10) iron particles, contained abundant iron element, are released from the main operations, such as induration, blending, and mechanical (transportation, loading/unloading activities, etc.) processes. For example, a rotary Kiln, as the main part of the induration process could be as dusty as a fine crushing process, because the iron pellets are relatively weak and they abrade as they tumble (Jonsson et al., 2013).
The generation of these fine and coarse particles has significant effects on human health and the environment (Amoatey et al., 2018 and 2020). Iron particles could be contaminated with the iron ore impurities, such as Al, Si, Ca, and Mg and priority toxic heavy metals, such as Cr (VI), Cd, Ni and Pb (Bollati et al., 2010; Hu et al., 2006; Lau et al., 2016; Machemer, 2004). Due to high density of coarse iron particles (5.3 g cm−3), only fine iron particles can be transferred and routed to long distances, generally where residential areas are located (Omidvarborna, Baawain, Al-Mamun, et al., 2018). Hence, proper management plans have to be taken into consideration for sustainable development and to protect the surrounding environment near iron industries.
Literature review revealed that the physicochemical properties of atmospheric iron articles are related to feeding and processes of nearby iron industries (Galvão et al., 2018; Garimella & Deo, 2008; Querol et al., 2004). Previous studies reported that iron particles in the surrounding atmosphere of iron industries are among the major fractions of PM2.5 and PM10 emissions (Chang et al., 2005; Dai et al., 2015; Prati et al., 2000). Pope (1996) described how the closure of a steel mill resulted in an overall decrease in the concentration of associated Fe, Cu and Zn content particles. In addition, the Fe-bearing particles in total suspended particles and PM10 were found in higher concentrations nearby steel plants (Choël et al., 2007; Ledoux et al., 2006). Mohiuddin et al. (2014) found that PM2.5 and PM1 fractions in the PM10 particles, ranged from 35 to 62% and 20–46%, respectively, indicating the contribution of fine iron particles at the sampling sites. The iron emission of iron-based industries is complex because (Almeida et al., 2015): i) the major iron industries are located in very close proximity to each other making it difficult to distinguish between the iron emission sources; ii) there are different iron emission sources that produce a high amount of particles with various characteristics; and iii) the situation to distinguish the right source is complicated because some processes operate continuously, while others are not. Additionally, the influence of other external sources like road traffic, ships in case of ports, and resuspension of previously deposited particles make the case even more complicated.
Some studies predicted the dispersion of iron particles via air quality models due to the importance of iron concentration levels in the nearby iron industries. Singh and Perwez (2015) modeled total suspended PMs and PM10 concentration levels using the Industrial Source Complex and U.S. Environmental Protection Agency (EPA) Regulatory Model (ISC-AERMOD) for mining complexes. The study revealed that with the increasing distance from the site, the concentration decreases exponentially. This finding might be attributed to the high specific gravity of the ore, meteorological status and undulating terrain, which assists the dry deposition process. Omidvarborna, Baawain, Al-Mamun, et al. (2018) studied dispersion and deposition of atmospheric iron particles released from the processing plant in both industrial and residential areas. This is the first study in the region aimed to develop a simple model based on the available dataset to identify the possible sources of atmospheric iron particles in some residential areas. To do so, the study included PM10 as the only size of all particles from the plant, however, the contribution of other iron industries were remained untouched.
With reference to Almeida et al. (2015), where major iron industries are located in very close proximity to other iron industries, it is very difficult to distinguish among the contributions of each specific source on the formation of fine iron particles. Additionally, identifying real emission sources is always a challenging question to be answered in case of any legal litigations, especially when the industry sectors did not reveal their emissions data for investigations. The study aims to address the unknown contribution of iron sources in atmospheric iron emissions in the industrial port and nearby residential areas. For this purpose, various analytical and modeling approaches were followed to utilize the known contribution of an iron plant (hereafter named “plant”) to understand unknown contribution of two iron plants (hereafter named “other iron industries”) in atmospheric iron emissions. In order to characterize fine iron particles, physicochemical characteristics of iron particles generated by the plant (process, stacks, in the plant atmospheric environment, and dustfall) were studied and categorized according to their specifications. In comparison, atmospheric iron particles close to other iron industries and dust particles in nearby residential areas were collected and analyzed. The gathered data were used to develop and validate the dispersion/deposition model. Different scenarios were defined and sensitivity analysis was implemented to estimate the contribution of other iron industries in the atmospheric iron emissions.
Section snippets
Study area
The plant is located in Sohar Industrial Port (SIP) in the Liwa region, Oman (Fig. 1). SIP covers approximately 2 km of coastline and it was established as the third major industrial area in the country. SIP is highly affected by land-sea breeze circulation (Charabi et al., 2013) and emissions from different industries (Omidvarborna, Baawain, & Al-Mamun, 2018). The region's topography is characterized by a relatively flat area at sea level bordered by a region of high mountains.
Plant process description
Similar to other
Analysis of the process samples
The selected process sites inside the plant (raw feed, before furnace (rotary Kiln), and after rotary Kiln (final product)) were sampled to assess the potential generation of fine iron particles. The characterization results allowed us to classify the observed particles into fine and coarse size fractions, whose morphology and compositions were broadly associated with the structure of single sharp-edged, single soft-edged, agglomerated soft-edged, and agglomerated sharp-edged particles. The
Conclusion and recommendations
The proposed study is an attempt towards a better understanding of the nature of fine iron emissions from anthropogenic sources within a developing region. This study tried to identify the possible sources of atmospheric iron pollution in residential area by characterizing and estimating the spatial distribution of fine iron particles from the plant and other iron industries. Among the shapes and structures, single and agglomerated sharp-/soft-edged iron particles were the main structures
Declaration of competing interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Acknowledgement
Authors acknowledge the support provided by Sultan Qaboos University, Oman under the Grant No. CR/ENG/CAED/17/05.
References (36)
- et al.
Chemical characterization of atmospheric particles and source apportionment in the vicinity of a steelmaking industry
The Science of the Total Environment
(2015) - et al.
Indoor air pollution and exposure assessment of the gulf cooperation council countries: A critical review
Environment International
(2018) - et al.
Emissions and exposure assessments of SOx, NOx, PM10/2.5 and trace metals from oil industries: A review study (2000–2018)
Process Safety and Environmental Protection
(2019) - et al.
Characterization of atmospheric aerosols by SEM in a rural area in the western part of México and its relation with different pollution sources
Atmospheric Environment
(2009) - et al.
Single-particle analysis of atmospheric aerosols at Cape Gris-Nez, English Channel: Influence of steel works on iron apportionment
Atmospheric Environment
(2007) - et al.
Environmental factors controlling the seasonal variability in particle size distribution of modern Saharan dust deposited off Cape Blanc
Aeolian Research
(2016) - et al.
Resonant Synchrotron X-ray Diffraction determines markers for iron-rich atmospheric particulate matter in urban region
Chemosphere
(2018) - et al.
Emission mitigation of CO2 in steel industry: Current status and future scenarios
Journal of Iron and Steel Research, International
(2006) - et al.
Characterization and mass balance of trace elements in an iron ore sinter plant
Journal of Materials Research and Technology
(2016) - et al.
Characterization of iron and manganese species in atmospheric aerosols from anthropogenic sources
Atmospheric Research
(2006)
The 23rd october 2002 dust storm in eastern Australia: Characteristics and meteorological conditions
Atmospheric Environment
Characterisation of trace metals in atmospheric particles in the vicinity of iron and steelmaking industries in Australia
Atmospheric Environment
Ambient air quality and exposure assessment study of the gulf cooperation council countries: A critical review
The Science of the Total Environment
Source apportionment near a steel plant in Genoa (Italy) by continuous aerosol sampling and PIXE analysis
Atmospheric Environment
Speciation and origin of PM10 and PM2. 5 in Spain
Journal of Aerosol Science
New approaches to in situ characterization of ultrafine agglomerates
Journal of Aerosol Science
Association between human health and indoor air pollution in the gulf cooperation council (GCC) countries: A review
Reviews on Environmental Health
Assessment of hydrogen sulfide emission from a sewage treatment plant using AERMOD
Environmental Monitoring and Assessment
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