Coke Plant Research Articles

A novel integrated prediction method using adaptive mode decomposition, attention mechanism and deep learning for coking products prices

Accurate prediction of coking product prices is crucial for enhancing production efficiency, cost optimization, and profit maximization in smart coking facilities. To address the volatility caused by nonlinear factors such as raw material costs, substitutes, macroeconomic indicators, sudden events, policy changes, and market behaviors, we propose a novel integrated prediction method for coking product price prediction. This method combines Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) for signal decomposition, Bidirectional Encoder Representations from Transformers (BERT) for natural language processing, attention mechanisms (AT) to weigh feature importance, and an ensemble of Bidirectional Gated Recurrent Unit, Bidirectional Long Short-Term Memory, and Gated Recurrent Unit, abbreviated BBG, for robust feature extraction. We design a feature selection strategy to avoid data leakage and improve the predictive ability of the model, and describe a method to maintain textual data information integrity when combining data from different sources. Experimental results on coke and methanol datasets show that our approach retains multi-source text richness improves predictive capability, and outperforms other state-of-the-art methods, providing an effective tool for developing smart coke plants.

Ultrahigh-purity ammonia recovery from synthetic coke wastewater via membrane contactor: Overcoming phenolic interference and assessing cost efficiency

Ammonia recovery from industrial wastewater using membrane contactor processes is emerging as a promising method owing to the diverse applications of ammonia. This study uniquely addressed ammonia recovery from coke plant wastewater, which is challenging due to the presence of numerous toxic and volatile phenolic compounds. Experiments were conducted using a synthetic coke plant effluent to assess the effects of various pH levels and temperatures on ammonia recovery. Specifically, the aim was to achieve high-purity ammonia recovery while minimizing the permeation of phenolic compounds. The results demonstrate that ammonia recovery in the membrane contactor processes is highly efficient, even in the presence of phenolic compounds. During temperature variations at 25 °C and 40 °C, the recovery of ammonia increased from 42.36% to 52.97% at pH 11. Additionally, increasing the pH of a feed solution from 7 to 12 significantly increased the ammonia content to 58.3%. At this pH, the recovered ammonia was of exceptional purity (>99%), with phenol, p-Cresol, and 2,4-xylenol present at negligible concentrations (0.001%, 0.002%, and 0.004%, respectively). This was attributed to the ionization of phenolic compounds at higher pH levels, which prevents their permeation through the hydrophobic membrane. The estimated cost analysis revealed that the membrane contactor process at pH 12 was approximately 1.41 times more cost-effective than conventional air-stripping processes over eight years of operating period (pH-12 membrane contactor: $19.79; pH-12 air stripping: $23.75). This study provides a detailed analysis of the optimal conditions for selective ammonia recovery from complex wastewater, highlighting both effective treatment and sustainable resource recovery and offering a superior alternative to traditional methods.

Assessment of sewage sludge as a component for the tire char co-gasification process

The work aimed to assess various sewage sludge (from coking, refinery, and fat-processing plants) as components for tire char co-gasification. The sewage sludge were analysed (basic characteristics, thermal stability, ash characteristics). Then, CO2 gasification and co-gasification measurements of individual materials and their blends (ratio: 70:30, 40:60) were made using the TGA, based on which the process and synergy effect were assessed. Moreover, a detailed analysis of char gasification formed during the pyrolysis was performed (reactivity assessment, kinetic parameters determined using the n-order Coats and Redfern model, and correlation between the individual elements in materials and their reactivity). Co-gasification measurements proved that the addition and increasing sewage sludge share in blends enhanced the process (TG curves were shifted towards lower temperatures, reactivity indicators, and final conversion degrees were improved compared to tire char). The greatest impact on the pyrolysis stage had the sludge from the refinery, while on the gasification stage sewage sludge from coking and fat-processing plants (where the synergy was observed). Moreover, the addition of sewage sludge to tire char reduces the activation energy and, in most cases, the pre-exponential factor. Finally, the correlation between reactivity and the Na, Mg, and P amount in the samples has been proved.

Toxicity of soil leaching liquor from coking plant in developmental zebrafish embryos/larvae model.

The coking industry in China is the largest coke supplier in the world. Contaminated soil in industrial areas poses a serious threat to human and ecosystems. Most of the studies investigated the toxicity of soil from coking plant on soil microorganisms, while the toxic effects of soil leaching liquor on aquatics are limited. In this study, the composition of soil leaching liquor from a coking plant in Taiyuan (TY) was analyzed, and the developmental toxicity on zebrafish was evaluated. The results showed that a total of 91 polycyclic aromatic hydrocarbons were detected in the leaching liquor, followed by phenols and benzene series. The leaching liquor induced developmental impairment in zebrafish larvae, including delayed incubation, deficits in locomotor behavior, vascular and cardiac dysplasia, and impaired neurodevelopment. The results of metabolomics analysis showed that TY soil leaching liquor induced significant metabolic profile disturbances in zebrafish embryos/larvae. The developmental toxicity of the leaching liquor metabolic disorders may be associated with the leaching liquor-induced abnormalities in zebrafish embryonic development. Metabolic pathways were identified by arginine and proline metabolism, phosphotransferase system, starch and sucrose metabolism, steroid biosynthesis, beta-alanine metabolism, and nucleotide metabolism pathways.

The Effect of Coke Plant Shutdown on Air Pollution: An Interrupted Time Series Analysis of Source-Apportioned PM2.5

The Effect of Coke Plant Shutdown on Air Pollution: An Interrupted Time Series Analysis of Source-Apportioned PM2.5

Compound Castings for the Coke Industry.

In this paper, issues related to the technology of compound castings composed of two parts, i.e., the working layer and the supporting part, made of X46Cr13 high-chromium steel and EN-GJL-HB 255 grey cast iron, respectively, in a liquid-solid system by pre-installing a monolithic insert in the mould cavity are presented. As a part of the research, the mechanism of formation of transitional zones in the bonding area of the above-mentioned two alloys was identified and described. It was shown that the phenomenon that determines the formation of a permanent bond between the joined materials is the transport of C and heat from the "high-carbon and hot" material of the supporting part poured into the mould in the form of liquid cast iron to the "low-carbon and cold" material of the working layer placed in the form of a steel monolithic insert inside the mould cavity. In the paper, the suitability of the compound castings technology developed for use in the coke industry is also presented. Full-size high-chromium steel-grey cast iron compound casting plates designed for the coke quenching car lining were positively verified in real coke plant operating conditions.

Insight into interaction among soil microbial community, soil metabolomics and enzyme activity after long-term PAH stress

The problem of soil polycyclic aromatic hydrocarbon (PAH) pollution in coking plant sites has been widely studied in recent years, but there is a lack of research on the correlation between soil microorganisms, soil metabolomics, and soil properties. Thus, in this study, the long-term impact of coke combustion on soil microbial community structure, enzyme activities, and metabolic pathways within a former coking plant site was investigated. Soil samples were collected from both the coking production area (CA group) and office area (OLA group), approximately 0 to 20 cm in depth. Compared with OLA group, elevated levels of 16 PAHs in the list of USA EPA were detected by gas chromatography-mass spectrometry in the CA group. Several dominant microorganisms, such as Altererythrobacter, Lysobacter, and Sulfurifustis, were identified by 16 s ribosomal DNA sequencing in the CA group. The fatty acid biosynthesis pathway exhibited specific inhibition, while the phenylalanine metabolic pathway was promoted in response to PAH stress. Long-term PAH exposure led to the inhibition of soil urease activity. The co-occurrence network of microorganisms revealed intricate patterns of co-metabolism and co-adaptation within complex bacterial communities, facilitating their adaptation to and decomposition of soil-borne PAHs. This research could provide valuable insights into the community characteristics and metabolic mechanisms of microorganisms inhabiting PAH-polluted soil within coking plant sites. The findings enhance our understanding of the indigenous soil microbiome and its intricate network dynamics under the persistent stress of PAHs, contributing to a more comprehensive knowledge of soil ecosystems in such environments.

Sphingobium sp. SJ10-10 encodes a not-yet-reported chromate reductase and the classical Rieske dioxygenases to simultaneously degrade PAH and reduce chromate

Both polycyclic aromatic hydrocarbons (PAHs) and heavy metals persist in the environment and are toxic to organisms. Their co-occurrence makes any of them difficult to remove during bioremediation and poses challenges to environmental management and public health. Microorganisms capable of effectively degrading PAHs and detoxifying heavy metals concurrently are required to improve the bioremediation process. In this study, we isolated a new strain, Sphingobium sp. SJ10–10, from an abandoned coking plant and demonstrated its capability to simultaneously degrade 92.6 % of 75 mg/L phenanthrene and reduce 90 % of 3.5 mg/L hexavalent chromium [Cr(VI)] within 1.5 days. Strain SJ10–10 encodes Rieske non-heme iron ring-hydroxylating oxygenases (RHOs) to initiate PAH degradation. Additionally, a not-yet-reported protein referred to as Sphingobium chromate reductase (SchR), with low sequence identity to known chromate reductases, was identified to reduce Cr(VI). SchR is distributed across different genera and can be classified into two classes: one from Sphingobium members and the other from non-Sphingobium species. The widespread presence of SchR in those RHO-containing Sphingobium members suggests that they are excellent candidates for bioremediation. In summary, our study demonstrates the simultaneous removal of PAHs and Cr(VI) by strain SJ10–10 and provides valuable insights into microbial strategies for managing complex pollutant mixtures.

Particulate matter, polycyclic aromatic hydrocarbons and metals, platelet parameters and blood pressure alteration: Multi-pollutants study among population

Epidemiological findings have determined the linkage of fine particulate matter (PM2.5) and the morbidity of hypertension. However, the mode of action and specific contribution of PM2.5 component in the blood pressure elevation remain unclear. Platelets are critical for vascular homeostasis and thrombosis, which may be involved in the increase of blood pressure. Among 240 high-PM2.5 exposed, 318 low-PM2.5 exposed workers in a coking plant and 210 workers in the oxygen plant and cold-rolling mill enrolled in present study, both internal and external exposure characteristics were obtained, and we performed linear regression, adaptive elastic net regression, quantile g-computation and mediation analyses to analyze the relationship between urine metabolites of polycyclic aromatic hydrocarbons (PAHs) and metals fractions with platelets indices and blood pressure indicators. We found that PM2.5 exposure leads to increased systolic blood pressure (SBP) and pulse pressure (PP). Specifically, for every 10 μg/m3 increase in PM2.5, there was a 0.09 mmHg rise in PP. Additionally, one IQR increase in urinary 1-hydroxypyrene (1.06 μmol/mol creatinine) was associated with a 3.43 % elevation in PP. Similarly, an IQR increment of urine cobalt (2.31 μmol/mol creatinine) was associated with a separate 1.77 % and 4.71 % elevation of SBP and PP. Notably, platelet-to-lymphocyte ratio (PLR) played a mediating role in the elevation of SBP and PP induced by cobalt. Our multi-pollutants results showed that PAHs and cobalt were deleterious contributors to the elevated blood pressure. These findings deepen our understanding of the cardiovascular effects associated with PM2.5 constituents, highlighting the importance of increased vigilance in monitoring and controlling the harmful components in PM2.5.

Моделирование установки замедленного коксования в программе MatLab

In order to prevent the occurrence of an emergency situation in the oil and gas industry, it is necessary to use control, automation and alarm systems. In this regard, artificial intelligence technologies have recently become in-creasingly popular. Neural networks are of particular interest. To implement the task of regulating, automating and predicting technological processes in the oil industry, it is possible to use neural network modeling of chemical and technological processes. Examples of using neural network modeling in practice are given. The results of neural network modeling of a delayed coking plant of one of the operating enterprises are presented. A delayed coking installation was modeled in the UniSim Design software package, which allowed us to obtain an initial data array for a neural network. The neural network was built in the MatLab program, and the program code was created. Graphs of error and regression are presented. The analysis of the results presented on the regression and error graphs is given. As a result of testing the model, minimal discrepancies between experimental and predicted data were obtained, which indicates the adequacy of the neural network model. An additional test of the program was also performed. The results of training and testing of the model are presented. The results obtained can later be used to create programs at different levels of control, since the model allows you to estimate the amount of losses during the operation of the installation at a certain flow rate of feed water supplied to the installation as a turbocharger.

Optimizing industrial Energy: An Eco-Efficient system for integrated Power, Oxygen, and methanol production using coke plant waste heat and electrolysis

This research presents a novel, eco-efficient hybrid system designed for the simultaneous production of power, oxygen, and methanol. It utilizes energy from coke plants and incorporates state-of-the-art waste heat recovery processes (WHRPs). The system effectively merges electricity and methanol production with WHRPs, improving both environmental sustainability and economic feasibility in industrial energy transformation. It consists of a fuel reforming and combustion unit, a waste heat recovery unit, a unit for hydrogen gas production through water electrolysis, and a methanol synthesis module. This configuration enables the production of 12.72 MW of electricity, 0.51 kg/s of oxygen, and 0.53 kg/s of methanol, achieving an energy productivity of 46.8 % and an exergy efficiency of 85.13 %. The economic analysis indicates competitive costs of $0.099 per kWh for electricity and $0.56 per kg for methanol. The system surpasses current technologies in thermodynamic efficiency, operational and product costs, and reduced CO2 emissions, demonstrating its potential as a sustainable and economically sound solution for industrial energy challenges. It supports global sustainability initiatives and fits within the circular economy concept.

Arsenic effectively improves the degradation of fluorene by Rhodococcus sp. 2021 under the combined pollution of arsenic and fluorene

The performance of bacterial strains in executing degradative functions under the coexistence of heavy metals/heavy metal-like elements and organic contaminants is understudied. In this study, we isolated a fluorene-degrading bacterium, highly arsenic-resistant, designated as strain 2021, from contaminated soil at the abandoned site of an old coking plant. It was identified as a member of the genus Rhodococcus sp. strain 2021 exhibited efficient fluorene-degrading ability under optimal conditions of 400 mg/L fluorene, 30 °C, pH 7.0, and 250 mg/L trivalent arsenic. It was noted that the addition of arsenic could promote the growth of strain 2021 and improve the degradation of fluorene – a phenomenon that has not been described yet. The results further indicated that strain 2021 can oxidize As3+ to As5+; here, approximately 13.1% of As3+ was converted to As5+ after aerobic cultivation for 8 days at 30 °C. The addition of arsenic could greatly up-regulate the expression of arsR/A/B/C/D and pcaG/H gene clusters involved in arsenic resistance and aromatic hydrocarbon degradation; it also aided in maintaining the continuously high expression of cstA that codes for carbon starvation protein and prmA/B that codes for monooxygenase. These results suggest that strain 2021 holds great potential for the bioremediation of environments contaminated by a combination of arsenic and polycyclic aromatic hydrocarbons. This study provides new insights into the interactions among microbes, as well as inorganic and organic pollutants.

Process-based life cycle inventory framework for assessing the carbon footprint of products from complex production paths: Case of dual-phase automotive strip steel

The production paths of industrial products are usually complex, leading to difficulties and a large workload when conducting traditional process-based life cycle assessment (P-LCA). Existing studies on reducing LCA workload have focused mainly on simplifying the process or combining LCA with correlation methods. For complex production paths that cannot be simplified or changed, the methods have weak generality. To fill in these research gaps, a process-based life cycle inventory (P-LCI) framework for complex production paths is proposed. P-LCI contains accurate classification and definition methods for input, output and unit processes, and an interconnection model for calculating process coefficients according to the complexity of the linkages among processes is proposed. Based on the proposed framework, a case study of the dual-phase automotive strip steel (DP) production process is performed. The results show that the production of 1 kg of DP steel consumes 0.679 kg of molten steel from a basic oxygen furnace plant and 0.557 kg from the another. Coke plants produce the largest carbon footprint (CF) per unit of coke, which is 0.889–1.231 kgCO2e/kg-coke. For the cradle-to-gate lifecycle of DP steels, the BFP has the largest CF at 0.614 kgCO2e/kg-DP, accounting for 26.32%. Through the proposed P-LCI framework, unit processes can be clearly defined, and the interconnection model can be used as the basis for environmental impact analysis. When the production path changes, the model can be flexibly adjusted, and the workload of repeated model construction can be reduced.

Environmental and dietary exposure to 24 polycyclic aromatic hydrocarbons in a typical Chinese coking plant

Polycyclic aromatic hydrocarbons (PAHs), known for their health risks, are prevalent in the environment, with the coking industry being a major source of their emissions. To bridge the knowledge gap concerning the relationship between environmental and dietary PAH exposure, we explore this complex interplay by investigating the dietary exposure characteristics of 24 PAHs within a typical Chinese coking plant and their association with environmental pollution. Our research revealed Nap and Fle as primary dietary contaminants, emphasizing the significant influence of soil and atmospheric pollution on PAH exposure. We subjected our data to non-metric multidimensional scaling (NMDS), Spearman correlation analysis, Lasso regression, and Weighted Quantile Sum (WQS) regression to delve into this multifaceted phenomenon. NMDS reveals that dietary PAH exposure, especially within the high molecular weight (HMW) group, is common both within and around the coking plant. This suggests that meals prepared within the plant may be contaminated, posing health risks to coking plant workers. Furthermore, our assessment of dietary exposure risk highlights Nap and Fle as the primary dietary contaminants, with BaP and DahA raising concerns due to their higher carcinogenic potential. Our findings indicate that dietary exposure often exceeds acceptable limits, particularly for coking plant workers. Correlation analyses uncover the dominant roles of soil and atmospheric pollution in shaping dietary PAH exposure. Soil contamination significantly impacts specific PAHs, while atmospheric pollution contributes to others. Additionally, WQS regression emphasizes the substantial influence of soil and drinking water on dietary PAHs. In summary, our study sheds light on the dietary exposure characteristics of PAHs in a typical Chinese coking plant and their intricate interplay with environmental factors. These findings underscore the need for comprehensive strategies to mitigate PAH exposure so as to safeguard both human health and the environment in affected regions.

Pollution Characteristics and Health Risks of Polycyclic Aromatic Compounds (PACs) in Soils of a Coking Plant.

Coke production is an important source of environmental polycyclic aromatic compounds (PACs), including parent polycyclic aromatic hydrocarbons (PAHs) and their derivatives. The focus near coking plants has primarily been on parent-PAH contamination, with less attention given to highly toxic derivatives. In this study, soil samples were collected from both within and outside of a coking plant. The concentrations of parent-PAHs and their derivatives, including methylated-PAHs, oxygenated-PAHs, and nitrated-PAHs, were examined. Spatial interpolation was employed to determine their spatial distribution patterns. Methods for identifying potential sources and conducting incremental lifetime cancer risk analysis were used. This could achieve a comprehensive understanding of the status of PAC pollution and the associated health risks caused by coke production. The concentrations of total PACs inside the plant ranged from 7.4 to 115.8 mg/kg, higher than those outside (in the range of 0.2 to 65.7 mg/kg). The spatial distribution of parent-PAH concentration and their derivatives consistently decreased with increasing distance from the plant. A significant positive correlation (p < 0.05) among parent-PAHs and their derivatives was observed, indicating relatively consistent sources. Based on diagnostic ratios, the potential emission sources of soil PACs could be attributed to coal combustion and vehicle emissions, while principal component analysis-multiple linear regression further indicated that primary emissions and secondary formation jointly influenced the PAC content, accounting for 60.4% and 39.6%, respectively. The exposure risk of soil PACs was dominated by 16 priority control PAHs; the non-priority PAHs' contribution to the exposure risk was only 6.4%.

Construction of an effective method combining in situ capping with electric field-enhanced biodegradation for treating PAH-contaminated soil at abandoned coking sites

The simultaneous application of in situ capping and electro-enhanced biodegradation may be a suitable method for ensuring the feasibility and safety of reusing abandoned coking sites. However, the capping layer type and applied electric field pattern may affect the efficiency of sequestering and removing pollutants. This study investigated changes in electric current, soil moisture content and pH, polycyclic aromatic hydrocarbon (PAH) concentration, bacterial number, and microbial community structure and metabolic function during soil remediation at abandoned coking plant sites under different applied electric field patterns and barrier types. The results indicated that polarity-reversal electric field was more conducive to maintaining electric current, soil properties, resulting in higher microbial number, community diversity, and functional gene abundance. At 21d, the mean PAH concentrations in contaminated soil, the capping layer's clean soil and barrier were 78.79, 7.56, and 1.57 mg kg−1 lower than those with a unidirectional electric field, respectively. The mean degradation rate of PAHs in the bio-barrier was 10.12 % higher than that in the C-Fe barrier. In the experiment combining a polarity-reversal electric field and a bio-barrier, the mean PAH concentrations in contaminated soil and the capping layer were 706.68 and 27.15 mg kg−1 lower than those in other experiments, respectively, and no PAHs were detected in the clean soil, demonstrating that the combination of the polarity-reversal electric field and the bio-barrier was effective in treating soil at abandoned coking plant sites. The established method of combining in situ capping with electro-enhanced biodegradation will provide technical support for the treatment and reuse of heavily PAH-contaminated soil at abandoned coking plant sites.

Spatial distribution, environmental behavior, and health risk assessment of PAHs in soils at prototype coking plants in Shanxi, China: Stable carbon isotope and molecular composition analyses

To investigate the environmental behavior of and carcinogenic risk posed by 16 priority-controlled polycyclic aromatic hydrocarbons (PAHs), soil samples and air samples from the coke oven top were collected in two prototype coking plants (named PF and JD). The PF soils contained more PAHs than the JD soils because the PF plant employed the side-charging technique and had a lower coke oven height. The soils from both plants contained enough PAHs to pose a carcinogenic risk, and this risk was higher in the PF plant. Data were collected on the source characteristic spectrum of stable carbon isotopic composition (δ13C) of PAHs emitted from the coke oven top (δ13C values of −36.02‰ to −32.05‰ for gaseous PAHs and −34.09‰ to −25.28‰ for particulate PAHs), and these data fill a research gap and may be referenced for isotopic-technology-based source apportionment. Diagnostic ratios and isotopic technology revealed that the coking plant soils were mainly influenced by the coking process, followed by vehicle exhaust; the soils near the boundary of each plant were slightly affected by C3 plant burning. For most PAHs [excluding fluoranthene, benzo(k)fluoranthene, indeno(1,2,3-c,d)pyrene, and dibenzo(a,h)anthracene], the dominant migration process was the net volatilization of PAHs from soil to air. In the PF plant, 13C was depleted in gaseous PAHs during volatilization.

Some Features of Chinese Coke Plants: Report by a Delegation of VUKhIN Specialists

Some Features of Chinese Coke Plants: Report by a Delegation of VUKhIN Specialists

Occurrence of BTX and PAHs in underground drinking water of coking contaminated sites: Linkage with altitude and health risk assessment by boiling-modified models

The safety of underground drinking water has received widespread attention. However, few studies have focused on the occurrence and health risks of pollutants in underground drinking water of coking contaminated sites. In this study, the distribution characteristics, sources, and human health risks of benzene, toluene, xylene (BTX) and polycyclic aromatic hydrocarbons (PAHs) in underground drinking water from a typical coking contaminated site in Shanxi of China were investigated. The average concentrations of BTX and PAHs in coking plant (CP) were 5.1 and 4.8 times higher than those in residential area (RA), respectively. Toluene and Benzene were the main BTX, while Acenaphthene, Fluorene, and Pyrene were the main PAHs. Concentrations of BTX/PAHs were negatively correlated with altitude, revealing altitude might be an important geological factor influencing spatial distribution of BTX/PAHs. PMF model demonstrated that the BTX/PAHs pollution in RA mainly originated from coking industrial activities. Health risk assessments were conducted by a modified US EPA-based model, in which environmental concentrations were replaced by residual concentrations after boiling. Residual ratios of different BTX/PAHs were determined by boiling experiments to be 9.4–93.8 %. The average total carcinogenic risks after boiling were decreased from 2.6 × 10−6 to 1.4 × 10−6 for adults, and from 4.3 × 10−6 to 2.1 × 10−6 for children, suggesting boiling was an effective strategy to reduce the carcinogenic risks from BTX/PAHs, especially for ingestion pathway. Monte Carlo simulation results matched well with the calculated results, suggesting the uncertainty was acceptable and the risk assessment results were reliable. This study provided useful information for revealing the spatial distribution of BTX/PAHs in underground drinking water of coking contaminated sites, understanding their linkage with altitude, and also helped to more accurately evaluate the health risks by using the newly established boiling-modified models.

Development of a continuous UAV-mounted air sampler and application to the quantification of CO2 and CH4 emissions from a major coking plant

Abstract. The development in uncrewed aerial vehicle (UAV) technologies over the past decade has led to a plethora of platforms that can potentially enable greenhouse gas emission quantification. Here, we report the development of a new air sampler, consisting of a pumped stainless coiled tube of 150 m in length with controlled time stamping, and its deployment from an industrial UAV to quantify CO2 and CH4 emissions from the main coking plant stacks of a major steel maker in eastern China. Laboratory tests show that the time series of CO2 and CH4 measured using the sampling system is smoothed when compared to online measurement by the cavity ring-down spectrometer (CRDS) analyzer. Further analyses show that the smoothing is akin to a convolution of the true time series signals with a heavy-tailed digital filter. For field testing, the air sampler was mounted on the UAV and flown in virtual boxes around two stacks in the coking plant of the Shagang Group (steel producer). Mixing ratios of CO2 and CH4 in air and meteorological parameters were measured from the UAV during the test flight. A mass-balance computational algorithm was used on the data to estimate the CO2 and CH4 emission rates from the stacks. Using this algorithm, the emission rates for the two stacks from the coking plant were calculated to be 0.12±0.014 t h−1 for CH4 and 110±18 t h−1 for CO2, the latter being in excellent agreement with material-balance-based estimates. A Gaussian plume inversion approach was also used to derive the emission rates, and the results were compared with those derived using the mass-balance algorithm, showing a good agreement between the two methods.