CO2 emission accounting and emission reduction analysis of the steel production process based on the material-energy-carbon correlation effect.

This paper develops a process-level carbon emission calculation model for iron and steel enterprises through the carbon emission mechanism of the whole production process. The relationship between material, energy and carbon flows is considered and combined. The carbon emissions of enterprises are divided into industrial emissions and combustion emissions, and the indirect emissions of purchased intermediate products and electricity purchased from the grid are also considered. Carbon emission targets and corresponding emission reduction strategies are formulated at the enterprise and process levels. For example, consider an iron and steel enterprise. The different types of carbon emissions are accounted for, with their reduction potential analysed based on the carbon material flow analysis method. The results show that the carbon emission of this enterprise is 1930.87 kgCO2/t (CS), and the combustion emission caused by energy flow is the main contributor to the enterprise's carbon emission, accounting for 57.02% of the total emission. The carbon emission during iron-making accounts for 69.06% of the entire process and is critical in any carbon emission reduction of the enterprise. Among them, process emissions from the blast furnace process account for 81.79% of industrial emissions of the whole process, which is 356.51 kgCO2/t (CS), and is the main challenge of low carbon transformation in this extensive process. This study highlights that increasing the integrated steel-making scrap ratio and electric furnace steel production can break through the existing emission reduction limits. A 65.02% carbon emission reduction can be achieved, and using green electricity can reduce emissions by 24.15%. Reasonably determining the amount of purchased coke and paying attention to the high-value recycling of byproduct gas resources in the plant are essential to achieve low-carbon economic development of steel.

Accumulation degree and risk assessment of metals in street dust from a developing city in Central Taiwan.

Due to the numerous industrial parks and high traffic density in Miaoli, Taiwan, large amounts of metals may be released into the atmosphere, accumulating in street dust. Therefore, this study aimed to collect street dust in Miaoli to quantify the metals and assess the accumulation degree, sources, and potential risks. The enrichment factor (EF), geological accumulation index (Igeo), ecological risk, and non-carcinogenic and lifetime carcinogenic risk were estimated to assess the accumulation degree and the potential environmental and health risks. Pearson correlation analysis, principal component analysis, and positive matrix factor model were used to clarify the relationship between levels of metals and identify possible sources. The levels of metals in street dust in order were Fe > Zn > Mn > Cu > Cr > Ni > Pb > Sr > Co > Sb. According to Igeo, the level of Ni indicated moderately polluted. The levels of Zn, Cu, and Pb showed moderate to strong pollution, strong pollution, and very strong pollution, respectively. Results of average ecological risk analysis pointed out that Pb and Cu represent a very high risk, while other metals posed low-to moderate-level ecological risks. Excluding the Steel Enterprise area, based on the EF value and source identification, it might be concluded that Co, Sr, Fe, Mn, and Sb were mainly from natural sources, while Cu, Pb, and Zn come from anthropogenic pollution sources. Based on the results of the risk assessments, most metals pose no serious adverse health risk to humans. But, in comparison to Miaoli townships, the health risks of residents living in the Steel Enterprise area were higher. However, given that children and adolescents exposure to Co, Cr, Pb, and Ni together constitute a relatively higher carcinogenic risk (CR > 10-6), more attention needs to be paid to the populations most susceptible.

Impacts of the steel industry on sediment pollution by heavy metals in urban water system.

The impact of the steel industry on sediment heavy metal (HM) pollution in urban aquatic environments was investigated in a major iron ore-producing area (Ma'anshan) in China. The concentrations of Cd, Cr, Cu, Ni, Pb, and Zn were 9.68 ± 3.56, 170.31 ± 82.40, 90.62 ± 19.54, 30.61 ± 6.72, 125.43 ± 63.60, and 1276.59 ± 701.90 mg/kg in the steel industry intruded upon sediments and 4.63 ± 1.41, 87.60 ± 10.96, 52.67 ± 19.99, 37.49 ± 6.17, 35.84 ± 11.41, and 189.02 ± 95.57 mg/kg in the control area, respectively. Comparing with the local soil background (0.08 mg/kg for Cd, 62.6 mg/kg for Cr, 19.3 mg/kg for Cu, 28.1 mg/kg for Ni, 26.0 mg/kg for Pb, and 58.0 mg/kg for Zn), significantly higher levels of Cd, Cr, Cu, Pb, and Zn were detected in the steel industry affected sediments. The enrichment factor and principal component analysis indicated that the heavy metals (HMs), except for Ni, were primarily derived from anthropogenic inputs, particularly from steel industrial activities. Multiple risk assessment models suggested that the sediments affected by industrial activities showed significant toxic effects for Cd, Cr, Pb, and Zn, with Cd being the main contributor to sediment toxicity. However, the alkaline nature of the sediments (pH = 7.85 ± 0.57) and the high proportion of residual fraction Cd (61.09% ± 26.64%) may help to reduce the toxic risks in the sediments. Effective measures to eliminate tinuous thethe continous input of Cd and Zn via surface runoff are crucial.

Pollution evaluation and source identification of heavy metals in soil around steel factories located in Lanshan District, Rizhao City, eastern China.

More than 40 enterprises have settled in the constructed steel-supporting industrial park adjacent to the Yellow Sea in Lanshan District, Rizhao City, eastern China. The concentration of heavy metals in the soil around steel factories often exceeds the limit specified by the national environmental agency. In this study, nine metals (Cu, Zn, Pb, Cd, Cr, Ni, Mn, Fe, and Mg) in the soil around the steel-supporting industrial park were examined, and 100 soil samples were analyzed. The pollution characteristics and sources of these heavy metals were obtained via pollution index analysis, potential ecological risk evaluation, geostatistical analysis, and multivariate statistical analysis combined with a positive matrix factorization (PMF) model. The results indicated that the heavy metals showed varying accumulation levels, among which Cd, Ni, and Pb were the major heavy metals greatly influencing the soil quality. The area around the steel factories exhibited heavy pollution and a high ecological risk, and Ni and Cd were the main risk factors. The soil at the steel factories and that in the southeastern and southwestern parts of the study area attained higher heavy metal element contents than those in the soil in other parts. PMF analysis confirmed that Cu, Pb, and Cd originated from mixed agricultural and traffic sources. Mn was related to natural sources. Cr and Ni likely resulted from atmospheric deposition, and Zn, Cd, Fe, and Mg were mainly associated with industrial materials, with these four sources accounting for 32.68%, 12.2%, 27.57%, and 27.54%, respectively, of the total metal content. This study could facilitate the investigation, evaluation, and source identification of soil heavy metal pollution in industrial regions and surrounding areas of Lanshan District, Rizhao City.

Distribution of heavy metals in coastal sediments under the influence of multiple factors: A case study from the south coast of an industrialized harbor city (Tangshan, China).

This research investigated the spatial distribution of heavy metals, including mercury (Hg), cadmium (Cd), copper (Cu), arsenic (As), nickel (Ni), lead (Pb), chromium (Cr), and zinc (Zn), in surface sediments from a coastal area near to an industrial harbor (Tangshan Harbor, China) using 161 sediment samples. According to the geo-accumulation index (Igeo), 11 samples were classified as unpolluted (Igeo≤0). Notably, 41.0 % of the research samples were moderately or strongly polluted (2 < Igeo≤3) with Hg and 60.2 % of the samples were moderately polluted (1 < Igeo≤2) in Cd. The ecological effect evaluation showed that the metals Zn, Cd, and Pb were at the effect range low level, and 51.6 % of the samples for Cu, 60.9 % for Cr, 90.7 % for As, 41.0 % for Hg, and 64.0 % for Ni fell in the range between the effect range-low and the effect range-mean levels, respectively. The correlation analysis showed that the distribution patterns of Cr, Cu, Zn, Ni, and Pb were similar to each other, high in the northwest, southeast, and southwest regions of the study area and low in the northeast region, which corresponded well with sediment size components. Based on principal component analysis (PCA) and positive matrix factorization (PMF), four distinct sources of pollution were quantitatively attributed, including agricultural activities (22.08 %), fossil fuel consumption (24.14 %), steel production (29.78 %), and natural sources (24.00 %). Hg (80.29 %), Cd (82.31 %) and As (65.33 %) in the region's coastal sediments were predominantly contributed by fossil fuel, steel production and agricultural sources, respectively. Cr (40.00 %), Cu (43.63 %), Ni (47.54 %), and Zn (38.98 %) were primarily of natural lithogenic origin, while Pb mainly came from the mixed sources of agricultural activities (36.63 %), fossil fuel (36.86 %), and steel production (34.35 %). Multiple factors played important roles in the selective transportation of sedimentary heavy metals, particularly sediment properties, and hydrodynamic sorting processes in the study area.

Human exposure to dust and heavy metals in industrial regions and its relationship with the prevalence of multiple sclerosis disease.

In recent decades, multiple sclerosis (MS) diseases have been significantly prevalent in some industrial areas of Iran, such as steel industrial areas in Isfahan province (central Iran). In this study, the environmental impacts of two steel mill factories in Isfahan province and their effects on the spread of MS in the region were investigated. To examine the extent of exposure, seasonal dust samples were collected from 15 sites around the two investigated factories. The annual dust deposition rate (DDR) was then determined and the concentrations of lead (Pb), cadmium (Cd), nickel (Ni), cobalt (Co), and manganese (Mn) in the dust samples were measured. Furthermore, the concentration of the mentioned elements was determined in the nail samples taken from 40 MS patients and 40 healthy people (control) living in the study region. The interpolated map extracted from the DDR values showed the highest dust deposition around the two studied steel factories, which decreases with increasing distance from them. The enrichment factor (EF) of heavy metals was the highest at the distance between the two steel factories, decreasing by moving away from them which indicate that these two steel factories are the source of investigated heavy metals in the region. The statistical analysis also revealed significant differences (P < 0.01) between the concentration of heavy metals measured in nail samples taken from MS patients and healthy people. The mean Pb concentration measured in the nail sample taken from MS patients was more than 18 times that of healthy people (93.45 and 5.02 mg/kg, respectively). These results revealed a buildup of heavy metals in the body of MS patients much more than usual, originating from the activities of two investigated steel companies in the region.

Evaluation of Corrosion Mitigation Behaviour of Bombax ceiba Leaves Extract.

In this research investigation, conventional weight loss method, electrochemical measurements of potentiodynamic polarization and AC impedance spectroscopy were applied to inspect the Bombax ceiba leaves extract mitigation efficiency in 1.0 M H2SO4 medium at different temperatures. Behaviour of adsorption, parameters of thermodynamical and kinetic were intended in this study. Adsorption behaviour revealed that the phyto-organic constituents existing in the mitigator adsorbed on the metal exterior. The spectral studies then topographical experiments confirm the creation of insoluble film on mild steel in destructive medium. The contact angle method predicts the wettability character of the mild steel in the occurrence of mitigator. This research work exhibited that Bombax ceiba leaves extract act as a best low-cost, bio-friendly mitigator on mild steel in destructive medium.

Composition and Origin of Surface Casing Fluids in a Major US Oil- and Gas-Producing Region.

Fluids leaked from oil and gas wells often originate from their surface casing─a steel pipe installed beneath the deepest underlying source of potable groundwater that serves as the final barrier around the well system. In this study, we analyze a regulatory dataset of surface casing geochemical samples collected from 2573 wells in northeastern Colorado─the only known publicly available dataset of its kind. Thermogenic gas was present in the surface casings of 96.2% of wells with gas samples. Regulatory records indicate that 73.3% of these wells were constructed to isolate the formation from which the gas originated with cement. This suggests that gas migration into the surface casing annulus predominantly occurs through compromised barriers (e.g., steel casings or cement seals), indicative of extensive integrity issues in the region. Water was collected from 22.6% of sampled surface casings. Benzene, toluene, ethylbenzene, and xylenes were detected in 99.7% of surface casing water samples tested for these compounds, which may be due to the presence of leaked oil, natural gas condensate, or oil-based drilling mud. Our findings demonstrate the value of incorporating surface casing geochemical analysis in well integrity monitoring programs to identify integrity issues and focus leak mitigation efforts.

Phytoremediation of toxic heavy metals in polluted soils and water of Dargai District Malakand Khyber Pakhtunkhwa, Pakistan.

The contamination of natural resources with heavy metals released from steel mills is the primary cause of soil and water pollution in the Dargai Malakand, located on the northern side of Pakistan. Therefore, the present study was aimed to determine the level of heavy metals in soil and water samples of this area. The wild plant growing (nine native plants: Pteris vittata, Populus nigra, Eucalyptus camaldulensis, Persicaria maculosa, Arundo donax, Xanthium strumarium, Verbascum thapsus, Ricinus communis and Parthenium hysterophorus) there were then tested for their phytoremediation capabilities which is an environmentally friendly, generally utilized, and low-cost approach to eliminate heavy metals from polluted soils and water. Soil, water, and effluent samples were taken from the contaminated sites of seven steel mills in Dargai District Malakand and subjected to heavy metals analysis. Based on bioconcentration factor (BCF) and translocation factor (TF) calculated, The highest BCF for zinc was recorded for Pteris vittata roots (3.93), while the lowest value was observed for Verbascum thapsus leaves (0.306). Pteris vittata root showed the highest BCF for iron (1.618), while Ricinus communis leaves showed the lowest (0.023). The highest BCF value for chromium was highest for Populus nigra roots (0.717), while the lowest value was recorded for Persicaria maculosa leaves (0.031). For the selected metals; Fe, Zn and Cr the highest TF were recorded for Pteris vittata (0.988), Verbascum thapsus (0.944) and Xanthium strumairum (0.968) respectively. Therefore, it is recommended that these plants should be grown near to steel mills to reclaim heavy metals from industrial effluent, polluted soil as well as from polluted water.

Hydrophilic Covalent Organic Frameworks Coated Steel Sheet As a Mass Spectrometric Ionization Source for the Direct Determination of Zearalenone and Its Derivatives.

Zearalenone has attracted worldwide attention due to its toxic properties and threat to public health. A rapid determination method for zearalenone and its derivatives by hydrophilic covalent organic frameworks coated steel sheet (HCOFCS) combined with ambient mass spectrometry (AMS) was developed. The HCOFCS behaved as both a tip for solid-phase microextraction and a solid substrate for electrospray ionization mass spectrometry (ESI-MS). To evaluate the HCOFCS-ESI-MS method, five zearalenone and its derivatives in milk samples were determined, including zearalenone (ZEA), α-zearalenol (α-ZEL), ß-zearalenol (ß-ZEL), α-zearalanol (α-ZAL), and ß-zearalanol (ß-ZAL). After the extraction procedure, the HCOFCS was directly added with a high voltage for ESI-MS, and the analysis could be completed within 1 min. The developed method showed good linearity in the range 0.1-100 µg/L with a coefficient of determination (R2) > 0.9991. The limits of detection (LODs) and limits of quantitation (LOQs) ranged from 0.05 to 0.1 and 0.2 to 0.3 µg/L, respectively. The results demonstrated that the HCOFCS combined with ESI-MS can be used for the rapid and sensitive determination of trace ZEA and its derivatives in milk samples with satisfactory recoveries from 80.58% to 109.98% and reproducibility with relative standard deviations (RSDs) no more than 11.18%. Furthermore, HCOFCS showed good reusability, which could reuse at least 10 extraction cycles with satisfactory adsorption performance.

[Pollution Characteristics and Emission Factors of PCDD/Fs from Iron and Steel Industry].

The pollution level, emission characteristics, and emission factors of PCDD/Fs from a number of steel plants were investigated in a particular province of China. The results showed that the concentration of PCDD/Fs was at a low level and decreased by 1-2 orders of magnitude compared with that in 2005-2019. In detail, the concentrations of PCDD/Fs ranged from 0.003-0.557 ng·m-3(I-TEQ), and the mean value was 0.165 ng·m-3 for the sintering process. Moreover, the concentrations of PCDD/Fs ranged from 0.006 to 0.057 ng·m-3, and the mean value was 0.025 ng·m-3 for the electric furnace process. In addition, the concentration of PCDD/Fs in the iron and steel industry from 2005 to 2020 increased first and then decreased, especially after the implementation of the new emission standard and the ultra-low emission control of conventional pollutants such as smoke, showing a significant decline. The results of fingerprint analysis showed that 2,3,7,8-TCDF was the largest congener contributing to the mass concentration, and lower chlorinated PCDFs were increased. This result differed from those of previous studies in which highly chlorinated PCDFs and PCDDs dominated, indicating that the generation source of PCDD/Fs had changed. The congener and isomer profiles of PCDD/Fs in flue gas from the sintering process were similar to those in the flue gas from the electric furnace process. Additionally, showing the characteristics of the typical high-temperature thermal process, the de novo synthesis may be the dominant mechanism of formation of PCDD/Fs in the sintering process and electric furnace process. The emission factor was 0.003-0.5 µg·t-1 (I-TEQ), and the average emission factor was (0.18±0.22) µg·t-1 for the sintering process. The emission factor was 0.04-0.5 µg·t-1, and the average emission factor was (0.27±0.23) µg·t-1 for the electric furnace process. These values were far lower than those of the standard toolkit for identification and quantification of dioxin and furan emissions released by UNEP in 2013 and the emission factors in the dioxin emission inventory of China in 2004. It is suggested that the emission factors of PCDD/Fs in the iron and steel industry of China should be studied and updated.

Source apportionment of ambient PM10 collected at three sites in an urban-industrial area with multi-time resolution factor analyses.

Chemical speciation data for PM10, collected for annual trend analyses of health-relevant species, at three receptor sites in a highly industrialized area (IJmond) in the Netherlands were used in a multi-time resolution receptor model (ME-2) to identify the PM10 sources in this area. Despite the available data not being optimized for receptor modelling, five-factor solutions were obtained for all sites based on independent PMF analysis on PM10 data from the three sites (IJM, WAZ and BEV). Four factors were common to all three sites: nitrate-sulphate (average percentage contributions to PM10: IJM: 35.3 %, WAZ: 37.7 %, and BEV: 36.3 %); sea salt (20.2 %, 23.7 %, 15.2 %); industrial (8.1 %, 11.0 %, 18.1 %) and brake wear/traffic (31.4 %, 21.2 %, 20.6 %). At WAZ, a local/site-specific factor containing most of the PAH measurements was found (6.4 %) while a crustal matter factor was resolved at IJM (7.6 %) and BEV (9.8 %). Additionally, sludge-drying was a potential source of the marker species in the industrial factor at WAZ. Bootstrapping (BS) and factor displacement (DISP) were applied to the factor profiles in this work for error estimation. In general, the factor profiles at all three sites had very small intervals from both BS and DISP methods. To our knowledge, this is the first time DISP was applied in a complex model such as the multi-time resolution model. Most of the measured metal and PAH concentrations found in the IJmond area during the 2017-2019 period had local sources, with significant contributions from several processes related to the steel industry. This study shows that available detailed PM10 chemical speciation data, although primarily collected for annual trend analyses of health-relevant species, could also be used in receptor modelling by applying a multi-time framework. We propose general recommendations for the optimization of the measurement strategy for source apportionment of PM in areas with similar urban-industrial land use.

Innovative experimental approach for spatial mapping of source-specific risk contributions of potentially toxic trace elements in PM10.

Exposure to potentially toxic trace elements (PTTEs) in inhalable particulate matter (PM10) is associated with an increased risk of developing cardiorespiratory diseases. Therefore, in multi-source polluted urban contexts, a spatially-resolved evaluation of health risks associated with exposure to PTTEs in PM is essential to identify critical risk areas. In this study, a very-low volume device for high spatial resolution sampling and analysis of PM10 was employed in Terni (Central Italy) in a wide and dense network (23 sampling sites, about 1 km between each other) during a 15-month monitoring campaign. The soluble and insoluble fraction of 33 elements in PM10 was analysed through a chemical fractionation procedure that increased the selectivity of the elements as source tracers. Total carcinogenic risk (CR) and non-carcinogenic risk (NCR) for adults and children due to concentrations of PTTEs in PM10 were calculated and quantitative source-specific risk apportionment was carried out by applying Positive Matrix Factorization (PMF) to the spatially-resolved concentrations of the chemically fractionated elements. PMF analysis identified 5 factors: steel plant, biomass burning, brake dust, soil dust and road dust. Steel plant showed the greatest risk contribution. Total CR and NCR, and source-specific risk contributions at the 23 sites were interpolated using the ordinary kriging (OK) method and mapped to geo-reference the health risks of the identified sources in the whole study area. This also allowed risk estimation in areas not directly measured and the assessment of the risk contribution of individual sources at each point of the study area. This innovative experimental approach is an effective tool to localize the health risks of spatially disaggregated sources of PTTEs and it may allow for better planning of control strategies and mitigation measures to reduce airborne pollutant concentrations in urban settings polluted by multiple sources.

Spatial and seasonal variation and sources of deposition fluxes of polycyclic aromatic hydrocarbons (PAHs) in Shanghai.

Spatial and temporal variations of polycyclic aromatic hydrocarbons (PAHs) deposition fluxes and sources may significantly facilitate risk evaluation and pollution control of super megacity in China. A study on PAHs of wet and dry deposition in Shanghai was conducted from January to December of 2019. Seventeen sampling sites located in four functional areas were set, including the Baoshan iron and steel industry area (BS), Jinshan petrochemical industry area (JS), city center (CC), and Chongming agricultural area (CM). A total of 15 PAHs were determined by gas chromatography-mass spectrometry (GC-MS, Agilent 7890A/5975C). PAHs atmospheric deposition flux in winter was highest (3.12 ± 1.98 µg/(m2·day), mostly attributed to local emissions accumulation under adverse meteorological diffusion conditions, as well as pollutants transport from northern China during heating season. PAHs deposition fluxes in industrial area (BS and JS) were 3.75 ± 4.08 µg/(m2·day) and 3.18 ± 3.62 µg/(m2·day) respectively, which were greater than those in CC and CM, accounting for 1.91 ± 1.06 µg/(m2·day) and 1.41 ± 0.61 µg/(m2·day) respectively. Proportional composition and isomer ratios of PAHs indicated that the PAHs deposition in winter and spring samples were more homogeneous, whereas those of summer and autumn seemed to be more variable and dispersed. Positive matrix factorization model were employed to identify the potential sources of PAHs in specific functional areas. A dominance of contribution was attributed to coal combustion (46%) at BS, petroleum volatilization (48%) at JS, biomass burning (55%) at CM, and vehicle emission (49%) at CC. This study highlighted that local urbanization and industrialization have a significant contribution to PAHs deposition to specific functional regions in Shanghai.

Microbial diversity and geochemistry of groundwater impacted by steel slag leachates.

To understand long-term impacts of steel slag material on aquifer geochemistry and microbial communities, we conducted four sampling campaigns in the Gier alluvial groundwater (Loire, France). In its northern part, the aquifer flows under a 200,000 m3 steel slag exhibiting high levels of chromium and molybdenum. Geochemical analyses of the water table revealed the existence of water masses with different chemical signatures. They allowed us to identify an area particularly contaminated by leachates from the slag heap, whatever the sampling period. Water samples from this area were compared to non-contaminated samples, with geochemical characteristics similar to the river samples. To follow changes in microbial communities, the V3-V4 region of 16 s rRNA gene was sequenced. Overall, we observed lower diversity indices in contaminated areas, with higher relative abundances of Verrucomicrobiota and Myxococcota phyla, while several Proteobacteria orders exhibited lower relative abundances. In particular, one single genus among the Verrucomicrobiota, Candidatus Omnitrophus, represented up to 36 % of total taxon abundance in areas affected by steel slag leachates. A large proportion of taxa identified in groundwater were also detected in the upstream river, indicating strong river-groundwater interactions. Our findings pave the way for future research work on C. Omnitrophus remediation capacities.

Improvements in SO2 pollution in India: role of technology and environmental regulations.

India relies heavily on coal-based thermal power plants to meet its energy demands. Sulphur dioxide (SO2) emitted from these plants and industries is a major air pollutant. Analysis of spatial and temporal changes in SO2 using accurate and continuous observations is required to formulate mitigation strategies to curb the increasing air pollution in India. Here, we present the temporal changes in SO2 concentrations over India in the past four decades (1980-2020). Our analysis shows that the Central and East India, and Indo-Gangetic Plain (IGP) are the hotspots of SO2, as these regions house a cluster of thermal power plants, petroleum refineries, steel manufacturing units, and cement Industries. Thermal power plants (51%), and manufacturing and construction industries (29%) are the main sources of anthropogenic SO2 in India. Its concentration over India is higher in winter (December-February) and lower in pre-monsoon (March-May) seasons. The temporal analyses reveal that SO2 concentrations in India increased between 1980 and 2010 due to high coal burning and lack of novel technology to contain the emissions during the period. However, SO2 shows a decreasing trend in recent decade (2010-2020) because of the environmental regulations and implementation of effective control technologies such as the flue gas desulphurisation (FGD) and scrubber. Since 2010, India's renewable energy production has also been increased substantially when India adopted a sustainable development policy. Therefore, the shift in energy production from conventional coal to renewable sources, solid environmental regulation, better inventory, and effective technology would help to curb SO2 pollution in India. Both economic growth and air pollution control can be performed hand-in-hand by adopting new technology to reduce SO2 and GHG emissions.

Chemical fingerprinting of organic micropollutants in different industrial treated wastewater effluents and their effluent-receiving river.

Industry wastewater is considered one of the worst polluters of our precious water ecologies. However, the types of pollutants present in wastewater from industrial wastewater treatment plants (IWTPs) are still unclear. In this study, a simple and effective chemical fingerprinting method for checking the source-sink relationships among different industrial wastewaters and their effluent-receiving river was established. 107, 228, 155, and 337 chemicals were screened out in wastewater from electronics, steel, textile, and printing and dyeing plants, respectively. Chemical fingerprinting of the detected chemicals was performed, and results showed that aromatic compounds were the most prevalent among the pollutant categories (i.e., 56, 189, and 168 in electronics, iron and steel, and printing and dyeing plants, respectively). The traceability analysis of the chemicals selected in the effluent determined the characteristic pollutants of different industrial enterprises. Sixty-eight compounds were identified as the characteristic pollutants in the different process stages of wastewater of the four IWTPs. Of the 84 effluent-receiving river water signature pollutants, 47.6% (n = 40) were also detected in the effluent from the four IWTPs. Effective screening of organic pollutants in industrial wastewater and determining their sources will help accelerate the improvement of industrial wastewater treatment technology.

Metagenomic analysis for taxonomic and functional potential of Polyaromatic hydrocarbons (PAHs) and Polychlorinated biphenyl (PCB) degrading bacterial communities in steel industrial soil.

Iron and steel industries are the major contributors to persistent organic pollutants (POPs). The microbial community present at such sites has the potential to remediate these contaminants. The present study highlights the metabolic potential of the resident bacterial community of PAHs and PCB contaminated soil nearby Bhilai steel plant, Chhattisgarh (India). The GC-MS/MS analysis of soil samples MGB-2 (sludge) and MGB-3 (dry soil) resulted in identification of different classes of POPs including PAHs {benzo[a]anthracene (nd; 17.69%), fluorene (15.89%, nd), pyrene (nd; 18.7%), benzo(b)fluoranthene (3.03%, nd), benzo(k)fluoranthene (11.29%; nd), perylene (5.23%; nd)} and PCBs (PCB-15, PCB-95, and PCB-136). Whole-genome metagenomic analysis by Oxford Nanopore GridION Technology revealed predominance of domain bacteria (97.4%; 97.5%) followed by eukaryote (1.4%; 1.5%), archaea (1.2%; 0.9%) and virus (0.02%; 0.04%) in MGB-2 and MGB-3 respectively. Proteobacteria (44.3%; 50.0%) to be the prominent phylum followed by Actinobacteria (22.1%; 19.5%) in MBG-2 and MBG-3, respectively. However, Eukaryota microbial communities showed a predominance of phylum Ascomycota (20.5%; 23.6%), Streptophyta (18.5%, 17.0%) and unclassified (derived from Eukaryota) (12.1%; 12.2%) in MGB-2 and MGB-3. The sample MGB-3 was richer in macronutrients (C, N, P), supporting high microbial diversity than MGB-2. The presence of reads for biphenyl degradation, dioxin degradation, PAH degradation pathways can be further correlated with the presence of PCB and PAH as detected in the MGB-2 and MGB-3 samples. Further, taxonomic vis-à-vis functional analysis identified Burkholderia, Bradyrhizobium, Mycobacterium, and Rhodopseudomonas as the keystone degrader of PAH and PCB. Overall, our results revealed the importance of metagenomic and physicochemical analysis of the contaminated site, which improves the understanding of metabolic potential and adaptation of bacteria growing under POP contaminated environments.

Comparative water footprint assessment of fuel cell electric vehicles and compressed natural gas vehicles.

Utilization of renewable energy has become a current energy development trend. In this study, the water footprints of a fuel cell electric vehicle (FCEV) and a compressed natural gas vehicle (CNG) under different fuel scenarios were evaluated. The FCEV exhibits a low water footprint of 27.2 L/100 km under steam methane reforming hydrogen production technology. Hydrogen production using steam methane reforming and water electrolysis via wind can enable the FCEV industry to save more water resources. The percentage difference between different metallic materials in automobiles was analyzed. The water consumption by steel accounted for 73.6% and 80.5%, respectively. The fluctuation law of the water footprint was analyzed based on different power structures and steel water consumption coefficients. It was found that for low steel water consumption coefficient, wind power generation is conducive to slowing down the water consumption during the entire life cycle. In addition, a sensitivity analysis was performed for the FCEV and CNG under different fuel scenarios. Fuel technology and material structure have a significant impact on the total water footprint. The results of this study can provide guidance for the layout of the automobile industry and for water-saving measures in the future.

The impact of financial development on CO2 emissions of global iron and steel industry.

As carbon peaking and carbon neutrality have become a global consensus, more and more countries have introduced relevant policies to adapt to their own countries and formulated corresponding time roadmap. The industrial sector, especially the steel sector, which produces high levels of pollution and carbon emissions, is facing significant pressure to transform its operations to reduce CO2 emissions. Previous studies have shown the importance of financial development (FD) in environmental protection; however, the impact of FD on the CO2 emissions of the steel sector is ignored. This paper examines the impact of FD on the CO2 emissions of the iron and steel industry from a global perspective using comprehensive panel data from a total of 30 countries during the period from 1990 to 2018. Empirical results show that an improved level of FD in a given country reduces the CO2 emissions of the iron and steel industry. The mechanism analysis indicates that FD promotes the upgrading of the structure of the iron and steel industry and the reduction of the CO2 emissions by means of the three-stage least square method. Our results also show that the effect of FD on reducing the CO2 emissions of the iron and steel industry in developing countries is less than its effect in developed countries. Estimation results also show the existence of the environmental Kuznets curve hypothesis in the iron and steel industry. Finally, we discuss the policy implications of achieving carbon neutrality in the steel sector.