Application of an emission profile-based method to trace the sources of volatile organic compounds in a chemical industrial park

Cooperative and Bifunctional Adsorbent-Catalyst Materials for In-situ VOCs Capture-Conversion

Volatile organic compounds (VOCs) are gases that are emitted into the air from products or processes and are major components of air pollution that significantly deteriorate air quality and seriously affect human health. Different types of metals, metal oxides, mixed-metal oxides, polymers, activated carbons, zeolites, metal-organic frameworks (MOFs) and mixed-matrixed materials have been developed and used as adsorbent or catalyst for diversified VOCs detection, removal, and destruction. In this comprehensive review, we first discuss the general classification of VOCs removal materials and processes and outline the historical development of bifunctional and cooperative adsorbent-catalyst materials for the removal of VOCs from air. Subsequently, particular attention is devoted to design of strategies for cooperative adsorbent-catalyst materials, along with detailed discussions on the latest advances on these bifunctional materials, reaction mechanisms, long-term stability, and regeneration for VOCs removal processes. Finally, challenges and future opportunities for the environmental implementation of these bifunctional materials are identified and outlined with the intent of providing insightful guidance on the design and fabrication of more efficient materials and systems for VOCs removal in the future.

Novel approach for identifying VOC emission characteristics based on mobile monitoring platform data and deep learning: Application of source apportionment in a chemical industrial park

Refined volatile organic compound (VOC) emission characteristics are crucial for accurate source apportionment in chemical industrial parks. The data from mobile monitoring platforms in chemical industrial parks contain pollution information that is not intuitively displayed, requiring further excavation. A novel approach was proposed to identify VOC emission characteristics using the class activation map (CAM) technology of convolutional neural network (CNN), which was applied on the mobile monitoring platform data (MD) derived from a typical fine chemical industrial park. It converts a large amount of monitoring data with high spatiotemporal complexity into simple and interpretable characteristic maps, effectively improving the identification effect of VOC emission characteristics, supporting more accurate source apportionment of VOC pollution around the park. Using this method, the VOC emission characteristics of eight key factories were identified. VOC source apportionment in the park was conducted for one day using a positive matrix factorization (PMF) model and seven combined factor profiles (CFPs) were calculated. Based on the identified VOC emission characteristics, the main pollution sources and their contributions to surrounding schools and residential areas were determined, revealing that one pesticide factory (named LKA) had the highest contribution ratio. The source apportionment results indicated that the impact of the chemical industrial park on the surrounding areas varied from morning to afternoon, which to some extent reflected the intermittent production methods employed for fine chemicals.

Investigation of Plant-Level Volatile Organic Compound Emissions from Chemical Industry Highlights the Importance of Differentiated Control in China

The chemical industry is a significant source of nonmethane volatile organic compounds (NMVOCs), pivotal precursors to ambient ozone (O3), and secondary organic aerosol (SOA). Despite their importance, precise estimation of these emissions remains challenging, impeding the implementation of NMVOC controls. Here, we present the first comprehensive plant-level assessment of NMVOC emissions from the chemical industry in China, encompassing 3461 plants, 127 products, and 50 NMVOC compounds from 2010 to 2019. Our findings revealed that the chemical industry in China emitted a total of 3105 (interquartile range: 1179-8113) Gg of NMVOCs in 2019, with a few specific products accounting for the majority of the emissions. Generally, plants engaged in chemical fibers production or situated in eastern China pose a greater risk to public health due to their higher formation potentials of O3 and SOA or their proximity to residential areas or both. We demonstrated that targeting these high-risk plants for emission reduction could enhance health benefits by 7-37% per unit of emission reduction on average compared to the current situation. Consequently, this study provides essential insights for developing effective plant-specific NMVOC control strategies within China's chemical industry.

Integrating ambient carbonyl compounds provides insight into the constrained ozone formation chemistry in Zibo city of the North China Plain

Quantifying the impact of carbonyl compounds (carbonyls) on ozone (O₃) photochemical formation is crucial to formulating targeted O₃ mitigation strategies. To investigate the emission source of ambient carbonyls and their integrated observational constraint on the impact of O₃ formation chemistry, a field campaign was conducted in an industrial city (Zibo) of the North China Plain from August to September 2020. The site-to-site variations of OH reactivity for carbonyls were in accordance with the sequence of Beijiao (BJ, urban, 4.4 s^-1) > Xindian (XD, suburban, 4.2 s^-1) > Tianzhen (TZ, suburban, 1.6 s^-1). A 0-D box model (MCMv3.3.1) was applied to assess the O₃-precursor relationship influenced by measured carbonyls. It was found that without carbonyls constraint, the O₃ photochemical production of the three sites was underestimated to varying degrees, and the biases of overestimating the VOC-limited degree were also identified through a sensitivity test to NO_x emission changes, which may be associated with the reactivity of carbonyls. In addition, the results of the positive matrix factorization (PMF) model indicated that the main source of aldehydes and ketones was secondary formation and background (81.6% for aldehydes, 76.8% for ketones), followed by traffic emission (11.0% for aldehydes, 14.0% for ketones). Incorporated with the box model, we found that biogenic emission contributed the most to the O₃ production at the three sites, followed by traffic emission as well as industry and solvent usage. Meanwhile, the relative incremental reactivity (RIR) values of O₃ precursor groups from diverse VOC emission sources featured consistencies and differences at the three sites, which further highlights the importance of the synergetic mitigation of target O₃ precursors at regional and local scales. This study will help to provide targeted policy-guiding O₃ control strategies for other regions.

Emission factors and source profiles of volatile organic compounds from typical industrial sources in Guangzhou, China

Volatile organic compounds (VOCs) are important precursors of ozone (O₃) and fine particulate matter (PM_2.5). An accurate depiction of the emission characteristics of VOCs is the key to formulating VOC control strategies. In this study, the VOC emission factors and source profiles in five industrial sectors were developed using large-scale field measurements conducted in Guangzhou, China (100 samples for the emission factors and 434 samples for the source profile measurements). The emission factors based on the actual measurement method and the material balance method were 1.6-152.4 kg of VOCs per ton of raw materials (kg/t) and 3.1-242.2 kg/t, respectively. The similarities between the emission factors obtained using these two methods were examined, which showed a coefficient of divergence (CD) of 0.34-0.72. Among the 33 subdivided VOC source profiles developed in this study, sources including light guide plate (LGP), photoresist mask, and plastic products were the first time developed in China. Due to regional diversities in terms of production technologies, materials, and products, the emission characteristics of the VOCs varied, even in the same sector, thereby demonstrating the importance of developing localized source profiles of VOCs. The ozone formation potential (OFP) of the shipbuilding and repair sector from fugitive emissions was the highest value among all the industrial sectors. Controlling the emissions of aromatics and OVOCs was critical to reducing the O₃ growth momentum in industrial sectors. In addition, 1,2-dibromoethane showed high carcinogenic risk potentials (CRPs) during most of the industrial sectors and should be prioritized for controlling.

Mobile monitoring of VOCs and source identification using two direct-inlet MSs in a large fine and petroleum chemical industrial park

Mobile monitoring with direct-inlet MS (DI-MS), one of the most direct and effective ways to track emission sources, can effectively serve air quality management in chemical industrial parks (CIPs). Mobile monitoring using a high mass-resolution proton-transfer-reaction time-of-flight MS (HMR-PTR-TOFMS) and single-photon ionization time-of-flight MS (SPI-TOFMS) was conducted in a large fine and petroleum CIP in eastern China for three days. The high mixing ratios of aliphatic hydrocarbons (AHs), aromatics, oxygenated VOCs (OVOCs), and nitrogenous VOCs (NVOCs) were found in the northeast, middle, north, and northeast of the fine chemical industrial zone (FCIZ), respectively. OVOCs were the most abundant VOC group in this area. Abnormal emissions of aromatics were universal throughout the CIP. We discovered 38 characteristic VOCs by the HMR-PTR-TOFMS, mainly including C6-C10 aromatics, C2-C6 carbonyls, C2-C3 organic acids, and some NVOCs. The time series and spatial distribution of the TVOCs obtained by the two DI-MSs are generally consistent. A comparison of the speciated VOCs at the TVOC peak points illustrates that the characteristic VOCs obtained by different instruments differed significantly: PTR-TOFMS showed an advantage in measuring aromatics and OVOCs; SPI-TOFMS showed an advantage in measuring aromatics and some Ahs; offline GC-MS showed an advantage in measuring AHs, aromatics, some OVOCs, and halohydrocarbons. Similarities were compared between five positive matrix factorization (PMF) model-based fingerprints of VOCs in a previous study and observed profiles of VOCs from mobile monitoring. The emission sources of the five fingerprints were identified and validated: two were widely distributed, one was a chemical reagent production factory, one was an acrylic fiber production plant, and one was a pesticide factory. This study demonstrated methods for analyzing mobile monitoring data, characterizing the VOCs in the fine and petroleum CIP, correlating the results of stationary observation and mobile monitoring, and integrating the source tracing system with DI-MSs.

A Novel Method for Source Tracking of Chemical Gas Leakage: Outlier Mutation Optimization Algorithm

Chemical industrial parks, which act as critical infrastructures in many cities, need to be responsive to chemical gas leakage accidents. Once a chemical gas leakage accident occurs, risks of poisoning, fire, and explosion will follow. In order to meet the primary emergency response demands in chemical gas leakage accidents, source tracking technology of chemical gas leakage has been proposed and evolved. This paper proposes a novel method, Outlier Mutation Optimization (OMO) algorithm, aimed to quickly and accurately track the source of chemical gas leakage. The OMO algorithm introduces a random walk exploration mode and, based on Swarm Intelligence (SI), increases the probability of individual mutation. Compared with other optimization algorithms, the OMO algorithm has the advantages of a wider exploration range and more convergence modes. In the algorithm test session, a series of chemical gas leakage accident application examples with random parameters are first assumed based on the Gaussian plume model; next, the qualitative experiments and analysis of the OMO algorithm are conducted, based on the application example. The test results show that the OMO algorithm with default parameters has superior comprehensive performance, including the extremely high average calculation accuracy: the optimal value, which represents the error between the final objective function value obtained by the optimization algorithm and the ideal value, reaches 2.464e-15 when the number of sensors is 16; 2.356e-13 when the number of sensors is 9; and 5.694e-23 when the number of sensors is 4. There is a satisfactory calculation time: 12.743 s/50 times when the number of sensors is 16; 10.304 s/50 times when the number of sensors is 9; and 8.644 s/50 times when the number of sensors is 4. The analysis of the OMO algorithm's characteristic parameters proves the flexibility and robustness of this method. In addition, compared with other algorithms, the OMO algorithm can obtain an excellent leakage source tracing result in the application examples of 16, 9 and 4 sensors, and the accuracy exceeds the direct search algorithm, evolutionary algorithm, and other swarm intelligence algorithms.

Update on volatile organic compound (VOC) source profiles and ozone formation potential in synthetic resins industry in China

The synthetic resin industry plays an important role in Volatile organic compounds (VOCs) emissions from industrial sources. However, owing to various products and their different emission characteristics, it is extremely difficult to study the source profiles of synthetic resins. In this study, the product-based pollution characteristics of VOCs from eight synthetic resin enterprises were investigated in Shanghai, China. Up to 133 VOCs were identified, including 106 based on the Photochemical Assessment Monitoring Stations (PAMS) and the Toxic Organics (TO-15) methods, and the remaining 27 were identified based on the new mass spectrometry analysis method. Aromatics (39.7%) and oxygenated VOCs (29.9%) accounted for a relatively high proportion in the synthetic resin industry. The product-based source profiles of each process unit are compiled. Generally, 1,4-dioxane, methyl isobutyl ketone, toluene, benzene, styrene, propane, and dichloromethane are the most abundant species in synthetic resin. Furthermore, the product-based ozone formation potentials (OFPs) and sources reactivity (SR) were calculated, the synthetic resin industry SR range from 0.3 g g^-1 to 4.6 g g^-1. Results suggest that toluene, benzene, styrene, propylene, ethylene, and oxygenated VOCs (including 1,4-dioxane, methyl isobutyl ketone, and aldehyde) should be preferentially controlled to reduce the OFPs. A three-level classification was established to evaluate the degree of photochemical pollution in different industries. Emission factors were calculated and ranked for eight synthetic resins. A VOC emission inventory of Chinese synthetic resin from 2005 to 2018 was compiled. It is estimated that the Chinese synthetic resin emitted 23.96 Gg of VOCs in 2018. In this study, a product-based VOC source profile and emission inventory of the synthetic resin industry were established for the first time. Finally, combined with product types, processes, and processing equipment, feasible recommendations for reducing VOC emissions in the synthetic resin industry are proposed.

Uncovering the characteristics of air pollutants emission in industrial parks and analyzing emission reduction potential: case studies in Henan, China

Industrial parks contribute greatly to China’s economic development while emitting huge air pollutants. It is necessary to study the characteristics of air pollutant emissions in industrial parks. In this study, emission inventories for 11 industrial parks were established. Meanwhile, the source emission and spatial distribution characteristics of the industrial park were analyzed. The cluster analysis was used to classify these parks into “4Hs”, “Mixed” and “4Ls” parks. “4Hs”, “Mixed” and “4Ls” represent that the levels of energy intensity, economic proportion of energy-intensive industries, coal proportion and pollution performance value are high, medium and low in turn. Then three emission reduction measures were set up to estimate the emission reduction potential and environmental impacts. The results show that: (1) the emissions of SO₂, NO_x, CO, PM₁₀, PM_2.5, VOCs and NH₃ of 11 industrial parks in 2017 were 11.2, 23.1, 30.8, 8.3, 3.5, 5.1, and 1.1 kt, respectively. (2) Power plants were the largest source of SO₂ and NO_x emissions, and industrial processes were the largest emission source of CO, PM₁₀, PM_2.5, VOCs and NH₃. (3) “4Hs” parks with traditional energy-intensive industries as the leading industries should be the emphasis of air pollutant emission reduction. (4) Through the optimal emission reduction measures, SO₂, NO_x, PM₁₀, PM_2.5 and VOCs were reduced by 81, 46, 51, 46 and 77%, respectively. Environmental impact reductions include 1.6 kt SO₂eq acidified gas emissions, 1.4 kt PO₄³⁻eq eutrophication substances, 4.2 kt PM₁₀eq atmospheric particulate emissions, 7.0 kt 1,4-DCEeq human toxic substances, and 5.2 kt PM_2.5 eq breathing Inorganic. This study is helpful to understand the characteristics of air pollutants emissions in industrial parks and promotes the proposal and implementation of air pollutant emissions reduction strategies.

Occurrence and risk assessment of volatile organic compounds in multiple drinking water sources in the Yangtze River Delta region, China

Volatile organic compounds (VOCs) are widely present in water environment, which can threaten ecological sustainability and human health. The concentrations of VOCs and their ecological risks in drinking water are of great concern to human beings. Therefore, 54 kinds of VOCs were investigated from 58 locations of the Yangtze River Delta Region (Yangtze River, Qiantang River, Huangpu River, Taihu Lake and Jiaxing Urban River). Out of 54 target compounds, only 31 VOCs were detected, with total concentrations ranging from 0.570 to 46.820 μg/L from 58 locations of all drinking water sources. Among all detected VOCs compounds, only toluene and styrene can cause high-level ecological risk at location TH-2 of Taihu Lake. According to the carcinogenic and non-carcinogenic risk index, compounds such as 1,2-dichloroethane, bromodichloromethane and 1,1,2-trichloroethane posed a higher carcinogenic risk, and 1,2-dichloroethane, trichloroethylene and toluene posed a higher non-carcinogenic risk. Olfactory risks of water bodies in the Yangtze River Delta region are negligible. Although the concentrations of VOCs in the Yangtze River Delta region did not exceed national standards in China and guidelines of the World Health Organization (WHO) for drinking water, the presence of some ecological and health risks indicated that future monitoring studies and control practices are important to ensure ecological safety of drinking water sources.

Stationary monitoring and source apportionment of VOCs in a chemical industrial park by combining rapid direct-inlet MSs with a GC-FID/MS

Fast and comprehensive monitoring of VOCs, required for air quality management in large-scale chemical industrial parks in China, cannot be accomplished by stationary measurements using conventional GC-FID or GC-MS alone due to their low temporal resolutions and limited detectable ranges. Novel direct-inlet mass spectrometry (DI-MS) has been widely applied for real-time monitoring of VOCs. To verify its applicability in industrial settings, high mass-resolution proton-transfer-reaction time-of-flight MS (HMR-PTR-TOFMS), single-photon ionization time-of-flight MS (SPI-TOFMS), together with online GC-FID/MS were simultaneously deployed at the boundary of one of the largest chemical industrial parks in eastern China. Aromatics, acetonitrile, acetic acid, ethyl acetate, aliphatic hydrocarbons, 1,2-dichloroethane, and acetone were detected as the main pollutants. These three instruments detected 12 common species, among which ethyl acetate, toluene, C8-aromatics, and methyl ethyl ketone showed similar time series and levels. Acetone, benzene, chlorobenzene, styrene, and C9-aromatics showed only similar time series. The HMR-PTR-TOFMS uniquely detected 14 species, mainly oxidized VOCs, nitriles, and amines, which greatly helps acknowledge the pollutants in the chemical industrial area. Positive matrix factorization, using the HMR-PTR-TOFMS and GC-FID/MS datasets, was used to identify eight sources. Four of the identified sources were mainly detected by the HMR-PTR-TOFMS, with pollutants mainly comprised of nitriles, amines, carbonyls, and organic acids, most of which were hazardous and/or odorous. These four sources accounted for 41.5% and 33.2% of the total VOCs and ozone formation potential, respectively. The complementary nature of GC-FID/MS and HMR-PTR-TOFMS in VOC source apportionment in industrial settings is of great practical use for advanced VOCs abatement. Thus, the high mass resolution DI-MSs are suggested to be a supplementary measurement for fence-line monitoring. Although with a relatively short period attempt, this study has wide implications for the fence-line stationary observational modes and source apportion methods combining with traditional observations.