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China is the most important steel producer in the world, and its steel industry is one of the most carbon-intensive industries in China. Consequently, research on carbon emissions from the steel industry is crucial for China to achieve carbon neutrality and meet its sustainable global development goals. We constructed a carbon dioxide (CO2) emission model for China's iron and steel industry from a life cycle perspective, conducted an empirical analysis based on data from 2019, and calculated the CO2 emissions of the industry throughout its life cycle. Key emission reduction factors were identified using sensitivity analysis. The results demonstrated that the CO2 emission intensity of the steel industry was 2.33 ton CO2/ton, and the production and manufacturing stages were the main sources of CO2 emissions, accounting for 89.84% of the total steel life-cycle emissions. Notably, fossil fuel combustion had the highest sensitivity to steel CO2 emissions, with a sensitivity coefficient of 0.68, reducing the amount of fossil fuel combustion by 20% and carbon emissions by 13.60%. The sensitivities of power structure optimization and scrap consumption were similar, while that of the transportation structure adjustment was the lowest, with a sensitivity coefficient of less than 0.1. Given the current strategic goals of peak carbon and carbon neutrality, it is in the best interest of the Chinese government to actively promote energy-saving and low-carbon technologies, increase the ratio of scrap steel to steelmaking, and build a new power system.

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Assessing the iron and steel industry's (ISI) impact on climate change and environmental health is vital, particularly in China, where this sector significantly influences air quality and CO2 emissions. There is a lack of comprehensive analyses that consider the environmental and health burdens of manufacturing processes for ISI enterprises. Here, we present an integrated emission inventory that encompasses air pollutants and CO2 emissions from 811 ISI enterprises and five key manufacturing processes in 2020. Our analysis shows that sintering is the primary source of air pollution in the ISI. It contributes 71% of SO2, 73% of NO x , and 54% of PM2.5 emissions. On the other hand, 81% of total CO2 emissions come from blast furnaces. Significantly, the contributions of ISI have resulted in an increase of 3.6 µg m-3 in national population-weighted PM2.5 concentration, causing approximately 59,035 premature deaths in 2020. Emissions from Hebei, Jiangsu, Shandong, Shanxi, and Inner Mongolia provinces contributed to 48% of PM2.5-related deaths in China. Moreover, the transportation of air pollutants across provincial borders highlights a concerning trend of environmental health inequality. Based on the research findings, it is crucial for ISI manufacturers to prioritize the removal of outdated production capacities and adopt energy-efficient and advanced techniques, along with ultra-low emission technologies. This is particularly important for those manufacturers with substantial environmental footprints. These transformative actions are essential in mitigating the environmental and health impacts in the affected regions.

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The iron and steel industry (ISI) is a significant source of sulfur dioxide and particulate matter pollution in China. Existing research on regional environmental regulation or ISI emission reduction strategies tends to overlook spillover effects and the enterprise perspective. During the heating season, production limitations in ISI are potential policy measures for achieving structural emission reductions in heavily polluted cities in China's Jing-Jin-Ji and surrounding regions. We adopt a bottom-up modeling approach, incorporating effective production time to describe enterprise behavior and establishing a quantitative trade model based on trade theory. By modeling three types of production restriction policies outlined in policy documents, we evaluate the emission reduction effects of structure-adjustment measures using the example of reduced effective production time for steel-producing enterprises in the air pollution transmission channel in the Beijing-Tianjin-Hebei area. The results indicate the following: (1) Reducing the effective production time of ISI enterprises can help decrease domestic production value and total factor productivity in pollution-intensive industries, including but not limited to ISI. It also leads to reduced emissions of various pollutants in the implementation regions. (2) Due to interprovincial trade and input-output linkages, structural reduction measures in certain regions have implications for almost all other provinces' industrial structures. Differences in initial industrial structures, factor endowments, and geographical locations contribute to varying directions and magnitudes of industrial structural changes. Pollution-intensive industries' share tends to increase higher in less developed regions. (3) Our estimated pollution reduction is smaller compared to the literature evaluating clean air policies in similar regions using top-down strategies. This discrepancy arises because we analyze a single policy tool rather than modeling industry-wide emission fluctuations from the top down. Additionally, our modeling approach allows us to examine dynamic changes in comparative advantages. The increase in production scale for certain industries in policy-affected regions partially offsets the decline in pollution emissions. These findings enhance our understanding of structure-adjustment reduction measures' role and highlight their potential advantages and limitations.

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Electric Arc Furnaces (EAFs) play a pivotal part in the steel industry, offering a versatile of producing high-quality steel. This paper conducts an in-depth examination of the EAF, along with exploring mathematical modeling and optimization techniques pertinent to this furnace. Additionally, it delves into the global steel production capacity employing this technology, introduces different processes associated with EAF, scrutinizes the energy balance of EAFs, and provides an overview of numerical and simulation modeling in this context. The core focus of this extensive review is the diverse landscape of EAF simulation methods. It places particular emphasis on understanding the key components and stages of the EAF process, including charging, melting, refining, tapping, and slag removal. The review delves into the wide array of approaches and methodologies employed in EAF modeling, spanning from innovative computational fluid dynamics (CFD) and finite element analysis to the intricacies of mathematical and thermodynamic models. Furthermore, the paper underscores the importance of simulation in predicting and enhancing crucial aspects such as heat transfer, chemical reactions, and fluid dynamics within the EAF. By doing so, it contributes to the optimization of energy efficacy and the ultimate quality of steel produced in these furnaces. In conclusion, this review identifies gaps in existing knowledge and offers valuable recommendations for improving mathematical process models, underscoring the continuous efforts to enhance the efficiency, sustainability, and environmental impact of steel production processes. In conclusion, several techniques aimed at enhancing both production rates and the quality of the melting process in EAF have been put forward.

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The steel industry, crucial to the global economy, grapples with critical sustainable challenges, including high energy consumption, greenhouse gas emissions, and non-renewable resource utilization, making sustainability imperative for upholding its economic role without compromising the planet or societal well-being. This study proposes a framework aimed at advancing sustainability in the steel industry through the articulation of the triple helix sectors (university, industry, and government). Based on the integrative review scientific method, systematic selection, interpretation, and synthesis of information from various sources were carried out to map a technical-scientific scenario of sustainability in the steel industry. This scenario informed benchmarking which, in light of the scientific theory and the authors' expertise, enabled the proposition of customized actions aimed at the triple helix actors. The main theoretical-scientific contribution lies in deepening and expanding the knowledge that connects sustainability to the steel industry, thus reinforcing the basis for future research and empirical studies. As for the managerial-applied contribution, this work can guide universities in developing sustainable projects and establishing industrial partnerships; steel companies benefit from the best practices and technologies, while also achieving regulatory compliance; and governments can promote public policies that boost sustainability in the steel sector.

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With its high energy consumption and pollutant emissions, the iron and steel industry is a significant source of air pollution and carbon emissions in the Beijing-Tianjin-Hebei (BTH) region. To improve air quality and reduce greenhouse gas emissions, a series of policies involving ultra-low emission, synergistic reduction of pollution, and carbon application have been implemented in the region. This study has assessed air pollutant and CO2 emission patterns in the iron and steel industry of the region by employing co-control effects coordinate system, marginal abatement cost curve, and numerical modeling, along with the synergistic benefits of typical technologies. The results have demonstrated that: (1) the intensive production activities pertinent to iron and steel enterprises has contributed greatly to the emission in Tangshan and Handan, where the sintering process is the main source of SO2, NOx, PM2.5, and CO, accounting for 64.86%, 55.15%, 29.98%, and 46.43% of the total emissions, respectively. (2) Among the typical pollution control and reduction measures, industrial restructuring and adjustment of the energy-resource structure have led to the greatest effects on emission reduction. Technologies exhibiting great potential in emission reduction and high-cost efficiency such as Blast Furnace Top Gas Recovery Turbine Unit (TRT) need to be promoted. (3) In Tangshan city with the highest level of steel production, the iron and steel production activities contributed to the concentration of 30.51% of PM2.5, 50.67% of SO2, and 42.54% of NO2 during the non-heating period. During the heating period, pollutants pertinent to the combustion of fossil energy for heating have increased, while iron and steel induced emissions have decreased to 23.7%, 34.32%, and 29.13%, respectively. By 2030, it is speculated that the contribution of the iron and steel industry to air quality will be significantly decreased as result of successful implementation of ultra-low emission policies and typical synergistic reduction technologies.

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Air pollution is recognized as a risk factor for cardiovascular diseases; however, the precise underlying mechanisms remain unclear. This study investigated the impact of occupational air pollution exposure on endothelial function in workers within the steel industry. Specifically, we examined male employees in the coke-making division of the Isfahan Steel Company in Iran, as well as those in administrative roles with no known history of cardiovascular risk. Data on age, body mass index, duration of employment, blood pressure, fasting blood sugar, and lipid profile were collected. To assess endothelial function, flow-mediated dilation (FMD) was measured. The baseline brachial artery diameter was greater (mean difference [95% CI] = 0.068 mm [0.008 to 0.128]), while the FMD was lower (mean difference [95% CI] = -0.908 % [-1.740 to -0.075]) in the coke-making group than in the control group. After controlling for potential confounding variables, it was observed that working in the coke-making sector of the industry was associated with lower FMD (F = 3.954, p = .049). These findings indicated that occupational air pollution exposure among workers in the steel industry is linked to impaired endothelium-dependent vasodilation.

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The steel industry is a significant worldwide source of atmospheric particulate matter (PM). Part of PM may settle (SePM) and deposit metal/metalloid and metallic nanoparticles in aquatic ecosystems. However, such an air-to-water cross-contamination is not observed by most monitoring agencies. The region of Vitoria City is the main location of iron processing for exports in Brazil, and it has rivers, estuaries, and coastal areas affected by SePM. We have evaluated the effects of SePM on a local representative fish species, the fat snook, Centropomus parallelus. After acclimation, 48 fishes (61.67 ± 27.83 g) were individually exposed for 96 h to diverse levels of SePM (0.0, 0.01, 0.1 and 1 g/L-1). The presence of metals in the blood and several blood biomarkers were analyzed to evaluate the impact of SePM on stress signaling, blood oxygen transport capacity, and innate immune activity. Metal bioaccumulation was measured from blood in two separately analyzed compartments: intracellular (erythrocytes plus white blood cells) and extracellular (plasma). The major metals present at all contamination levels in both compartments were Fe and Zn, followed by Al and Cu, plus traces of 'Emerging metals': Ba, Ce, La, Rb, Se, Sr, and Ti. Emerging metals refer to those that have recently been identified in water as contaminants, encompassing rare earth elements and critical technology elements, as documented in previous studies (See REEs and TCEs in Cobelo-García et al., 2015; Batley et al., 2022). Multivariate analysis revealed that SePM had strong, dose-dependent correlations with all biomarker groups and indicated that blood oxygen-carrying capacity had the highest contamination responsiveness. Metal contamination also increased cortisol and blood glucose levels, attesting to increased stress signaling, and had a negative effect on innate immune activity. Knowledge of the risks related to SePM contamination remains rudimentary. However, the fact that there was metal bioaccumulation, causing impairment of fundamental physiological and cellular processes in this ecologically relevant fish species, consumed by the local human population, highlights the pressing need for further monitoring and eventual control of SePM contamination.

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The goal of the current study is to evaluate the heavy metal rainfall contamination in the vicinity brought on by the Erbil Steel Factory in Iraq during the study period. The study's findings revealed the concentration of all studied heavy metals in the precipitation near and around the factory is significantly higher than that of the rural area of Barzan village which is used as a control site. The average concentration of the metals is in descending order manganese (Mn) > lead (Pb) > iron (Fe) > arsenic (As) > cobalt (Co) > selenium (Se) > mercury (Hg) > and cadmium (Cd) for the polluted site. The geo-accumulation index (I-geo) of the heavy metal Mn in the rainfall around the steel factory site is 6.28 > 5 which indicates extreme contamination. While the Igeo values of Cd, As, and Fe are 4.87, 4.54, and 4.04 > 4 that indicate heavy to extreme contamination, for Pb, 3.80 > 3 indicates moderate to heavy contamination, Cd 1.68 > 1 indicates moderate contamination, Hg 0.46 > 0 indicates uncontaminated to moderate contamination, and Se - 0.36 < 0 indicates uncontaminated. The pollution load index (PLI) of the rainwater around the steel factory site is 13.46 > 1, demonstrating that the area is highly metal-contaminated.

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Identifying the key factors influencing energy consumption and CO2 emissions is necessary for developing effective energy conservation and emission mitigation policies. Previous studies have focused mainly on decomposing changes in energy consumption and CO2 emissions at the national, regional, or sectoral levels, while the perspective of site-level decomposition has been neglected. To narrow this gap in research, a site-level decomposition of energy- and carbon-intensive iron and steel sites is discussed. In this work, the logarithmic mean Divisia index (LMDI) method is used to decompose the changes in the energy consumption and CO2 emissions of iron and steel sites. The results show that the production scale significantly contributes to the increase in both energy consumption and CO2 emissions, with cumulative contributions of 229.63 and 255.36%, respectively. Energy recovery and credit emissions are two key factors decreasing site-level energy consumption and CO2 emissions, with cumulative contributions to the changes in energy consumption and CO2 emissions of -158.30 and -160.45%, respectively. A decrease in energy, flux, and carbon-containing material consumption per ton of steel promotes direct emission reduction, and purchased electricity savings greatly contribute to indirect emission reduction. In addition, site products and byproducts promote an increase in credit emissions and ultimately inhibit an increase in the total CO2 emissions of iron and steel sites.

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The steel industry is one of the most carbon-intensive industries in China. To analyze the carbon emission and carbon reduction potential of the steel industry in the life cycle, a carbon emission accounting model was built from the perspective of the life cycle. Taking the year 2020 as an example, an empirical analysis was carried out to predict and evaluate the carbon reduction potential of the steel industry in the life cycle by optimizing four variables, namely, scrap usage, fossil fuel combustion, electric power carbon footprint factor, and clean transportation proportion. At the same time, sensitivity analysis was used to determine the key degree of factors affecting carbon emission reduction in the life cycle of steel. The results showed that in 2020, the total life cycle CO2 emissions of the steel industry in China was approximately 2.404 billion tons, of which the acquisition and processing of raw materials were the key links in the carbon emissions of the steel industry, accounting for more than 98% of the total life cycle CO2 emissions of the steel industry. From the analysis of CO2 emission source categories, fossil fuel savings and outsourcing power cleaning were the top priorities of carbon reduction in the steel industry. By 2025, the steel industry could achieve 20%, 6%, 5%, and 1% carbon emission reduction potential by respectively promoting low-carbon technology, optimizing the power structure, increasing the number of steel scraps, and increasing the proportion of clean transportation. The fossil fuel combustion had the most significant impact on the life cycle CO2 emissions of the steel industry, followed by the electric power carbon footprint factor and scrap steelmaking usage. With regard to low-carbon technologies in the steel industry, in the short term, the promotion of low-carbon technologies in the steel rolling process and blast furnace ironmaking process should be the main focus. Later, with the gradual increase in the proportion of electric furnace steelmaking, the promotion of low-carbon technologies in the electric furnace steelmaking process will significantly improve the carbon emission reduction potential of the steel industry throughout its life cycle.

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The iron and steel industry (ISI) is important for socio-economic progress but emits greenhouse gases and air pollutants detrimental to climate and human health. Understanding its historical emission trends and drivers is crucial for future warming and pollution interventions. Here, we offer an exhaustive analysis of global ISI emissions over the past 60 years, forecasting up to 2050. We evaluate emissions of carbon dioxide and conventional and unconventional air pollutants, including heavy metals and polychlorinated dibenzodioxins and dibenzofurans. Based on this newly established inventory, we dissect the determinants of past emission trends and future trajectories. Results show varied trends for different pollutants. Specifically, PM2.5 emissions decreased consistently during the period 1970 to 2000, attributed to adoption of advanced production technologies. Conversely, NOx and SO2 began declining recently due to stringent controls in major contributors such as China, a trend expected to persist. Currently, end-of-pipe abatement technologies are key to PM2.5 reduction, whereas process modifications are central to CO2 mitigation. Projections suggest that by 2050, developing nations (excluding China) will contribute 52-54% of global ISI PM2.5 emissions, a rise from 29% in 2019. Long-term emission curtailment will necessitate the innovation and widespread adoption of new production and abatement technologies in emerging economies worldwide.

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OBJECTIVES: to quantify the temperature-related global health impacts of the Taranto steel plant CO2e emissions. DESIGN: using the risk functions available in the literature, a prospective global health impact assessment of the marginal CO2e emissions declared by the steel plant for 2020 was conducted. SETTING AND PARTICIPANTS: world population in the period 2020-2100. MAIN OUTCOMES MEASURES: deaths in the period 2020-2100 attributable to the marginal CO2e emitted by the Taranto steel plant in 2020. RESULTS: considering the central estimates in the baseline emission scenario (4.1°C warming by 2100), the Taranto steel plant 2020 CO2e emissions will cause 1,876 deaths worldwide between 2020 and 2100. The largest part will be attributable to steelmaking processes, accounting for 1,093 deaths. The same emissions will cause 5.56 × 10-4 deaths worldwide between 2020 and 2100 per tonne of steel produced in 2020, i.e. one death for every 1,799 tonnes of steel. If the 2020 CO2e emissions of the steel plant had been reduced by 25%, 50% or 75%, the deaths avoided in the world in the period 2020-2100 would have been 469, 938 and 1,407 respectively. CONCLUSIONS: estimates predict a probably significant mortality impact worldwide by the end of the century associated with the greenhouse gases emissions of the Taranto steel plant. Just reducing emissions by 50% in a single year could maybe avoid over 900 deaths worldwide by the end of the century. This confirms the importance of implementing incisive policies to reduce greenhouse gases emissions in all sectors.

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Emissions from the iron and steel industry are a major source of air pollution. To investigate the composition characteristics, estimate the secondary transformation potential, and assess the ecological risk and human health risks of air pollutants from iron and steel industry, field measurements of volatile organic compounds (VOCs) and trace metals (TMs) were conducted simultaneously from 2020 to 2022 in the Yangtze River Delta (YRD) region, China. The average mixing concentration of VOCs (Σ64VOCs) was 58.2 ppbv. Alkanes, alkenes and aromatics were the major components. Benzene and ethylene were the most abundant VOC species. In the O3 season, the calculated OH loss rates (LOH) and ozone formation potential (OFP) were 10.87 S-1 and 181.74 ppbv, respectively, which increased 39.54% and 21.51% compared to the non-O3 season. Furthermore, the O3-VOCs-NOx sensitivity indicated that O3 formation was under the VOCs-limited regime. The average concentration of total 10 trace metals (Σ10TMs) was 226.8 ng m-3, Zn, Pb and Mn were the top abundant TM species. The results also found that Se was extremely contaminated; Pb and Zn was heavily to extremely contaminated; Cu, As and Ni were moderately to heavily contaminated. For lifetime cancer risk, the cumulative carcinogenic risks were 1.84E-5 for children, 6.14E-5 for adults and 1.83E-5 for workers. The carcinogenic risks of individual chemicals cannot be ignored, especially for Cr, Ni, benzene and 1,3-butadiene. The hazard index values for workers and residents were 0.53 and 2.23, respectively, suggesting a high non-carcinogenic risks to the exposed population. These findings deepen the understanding of the pollutant character of the iron and steel industry, and provide theoretical support for policy development on O3 pollution treatment and human health in the YRD region, China. For the study area, we recommend utilizing high-quality raw coal, reducing the volatile hydrocarbon content in the sinter feed, and installing absorption device for highly reactive VOC components at the exhaust outlet.

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Conversion of steel industry off-gases to value-added chemicals enabled by renewable electricity can significantly reduce the environmental burden of the steelmaking process. Herein, we demonstrate that CO2 reduction by H2, both contained in steel mill off-gases, to form syngas via the reverse water-gas-shift reaction is effectively performed by nanosecond pulsed discharges at atmospheric pressure. The experimental results suggest the following: (i) An optimum interelectrode distance exists, maximizing CO2 conversion. (ii) CO2 conversion at constant SEI follows a nonmonotonic trend with H2 excess. CO2 conversion increases with H2 excess up to H2:CO2 = 3:1 upon shifting the chemical equilibrium. At larger H2:CO2, both gas cooling, promoted by the high H2 content, and hindered CO2 collisions in a highly diluted stream hamper CO2 conversion. (iii) SEI enhances CO2 conversion, but the effect decreases with increasing SEI due to equilibrium limitations. A stoichiometric H2:CO2 feed ratio in the plasma reactor is recommended for higher energy efficiency. Intensifying MeOH productivity via SEI elevation is not advised as a 2-fold SEI increase results only in 17% higher MeOH throughput.

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Given the urgency of addressing climate change and the declining demand for steel, it is imperative that China's iron and steel industry begin phasing out its primary production facility, the blast furnace. While there are various studies examining the decarbonization pathways for this sector and the resulting impacts, research exploring how to design decarbonization pathways that consider economic, environmental, and regional aspects equally is lacking. Moreover, it remains unclear how the individual heterogeneity of facilities affects the effectiveness of climate policies. In this study, we address the aforementioned research gaps by proposing a novel strategy that takes into account economic, carbon, water, and health factors in determining the priority for the closure of China's blast furnaces. We developed a bottom-up framework that incorporates a facility-level data set, a stock-driven dynamic material analysis, and retirement metrics with uncertain parameters to measure the multidimensional impacts of various phaseout pathways for China's blast furnaces. We have identified potential pathways that can improve environmental efficiency in multiple aspects compared with the cost-minimization pathway without impeding regional equality.

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In this paper, a unified level 2 Advanced Process Control system for steel billets reheating furnaces is proposed. The system is capable of managing all process conditions that can occur in different types of furnaces, e.g., walking beam and pusher type. A multi-mode Model Predictive Control approach is proposed together with a virtual sensor and a control mode selector. The virtual sensor provides billet tracking, together with updated process and billet information; the control mode selector module defines online the best control mode to be applied. The control mode selector uses a tailored activation matrix and, in each control mode, a different subset of controlled variables and specifications are considered. All furnace conditions (production, planned/unplanned shutdowns/downtimes, and restarts) are managed and optimized. The reliability of the proposed approach is proven by the different installations in various European steel industries. Significant energy efficiency and process control results were obtained after the commissioning of the designed system on the real plants, replacing operators' manual conduction and/or previous level 2 systems control.

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OBJECTIVE: To evaluate the association between environmental exposure to the following chemical substances: cadmium (Cd), lead (Pb), nickel (Ni), manganese (Mn), benzene (BZN), and toluene (TLN), and Period Circadian Regulator 3 (PER3) gene variable number of tandem repeats (VNTR) polymorphisms, according to chronotype in a population living in a steel residue-contaminated area. METHODS: This assessment comprises a study conducted from 2017 to 2019 with 159 participants who completed health, work, and Pittsburgh sleep scale questionnaires. Cd, Pb, Ni, Mn, BZN, and TLN concentrations in blood and urine were determined by Graphite Furnace Atomic Absorption Spectrometry (GFAAS) and Headspace Gas Chromatography (GC), and genotyping was carried out using Polymerase Chain Reaction (PCR). RESULTS: A total of 47% of the participants were afternoon chronotype, 42% were indifferent, and 11% were morning chronotype. Insomnia and excessive sleepiness were associated with the indifferent chronotype, while higher urinary manganese levels were associated with the morning chronotype (Kruskal-Wallis chi-square = 9.16; p < 0.01). In turn, the evening chronotype was associated with poorer sleep quality, higher lead levels in blood, and BZN and TLN levels in urine (χ2 = 11.20; p < 0.01) in non-occupationally exposed individuals (χ2 = 6.98; p < 0.01) as well as the highest BZN (χ2 = 9.66; p < 0.01) and TLN (χ2 = 5.71; p < 0.01) levels detected in residents from the influence zone 2 (far from the slag). CONCLUSION: Mn, Pb, benzene, and toluene contaminants may have influenced the different chronotypes found in the steel residue-exposed population.

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Background: The steel factory work environment contains various chemical exposures that can affect indoor air quality and have impact on respiratory health of the workers. Aims: The objective of this study was to assess potential effects of occupational exposures in steel factory workers in Iran on the respiratory symptoms, occurrence and the lung function levels. Method: This was a cross-sectional study of 133 men working in a steel factory forming the exposed group and 133 male office workers forming the reference group from a steel company in Iran. The participants filled in a questionnaire and underwent spirometry. Work history was used both as dichotomous (exposed/reference) and a quantitative measure of exposure, the latter measured as duration of exposure in the specified work (in years) for the exposed group and zero for the reference group. Results: Multiple linear regression and Poisson regression were used to adjust for confounding. In Poisson regression analyses, an increased prevalence ratio (PR) of all respiratory symptoms was observed in the exposed group. Lung function parameters were significantly reduced in the exposed group (p < 0.001). There was a dose-response relation between duration of occupational exposures and reduction in the predicted value of FEV1/FVC level (0.177, 95% CI -0.198 to -0.156) in all models. Conclusion: The results of these analyses showed that occupational exposures in steel factory work increase the prevalence of respiratory symptoms and reduce lung function. Safety training and workplace conditions were found to need improvement. In addition, use of proper personal protective equipment is recommended.

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Recent years have witnessed significant improvement in China's air quality. Strict environmental protection measures have led to significant decreases in sulfur dioxide (SO2), nitrogen oxides (NO x ), and particulate matter (PM) emissions since 2013. But there is no denying that the air quality in 135 cities is inferior to reaching the Ambient Air Quality Standards (GB 3095-2012) in 2020. In terms of temporal, geographic, and historical aspects, we have analyzed the potential connections between China's air quality and the iron and steel industry. The non-target volatile organic compounds (VOCs) emissions from iron and steel industry, especially from the iron ore sinter process, may be an underappreciated index imposing a negative effect on the surrounding areas of China. Therefore, we appeal the authorities to pay more attention on VOCs emission from the iron and steel industry and establish new environmental standards. And different iron steel flue gas pollutants will be eliminated concurrently with the promotion and application of new technology.