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Full length article

Identification of atmospheric emerging contaminants from industrial emissions: A case study of halogenated hydrocarbons emitted by the pharmaceutical industry

Lingning Meng

^a

, Song Gao

^a,*

, Shuwei Zhang

^a

, Xiang Che

^b

, Zheng Jiao

^a,*

, Yong Ren

^a

, Chunguang Wang

^c

aSchool of Environmental and Chemical Engineering, Shanghai University, Shanghai 200444, PR China

bState Ecologic Environmental Scientific Observation and Research Station at Dianshan Lake, Shanghai Environmental Monitoring Center, Shanghai 200235, PR China

cBeijing Police College, Beijing 102202, PR China

A R T I C L E I N F O Handling Editor: Xavier Querol Keywords:

Pharmaceutical industry Halogenated hydrocarbons Atmospheric emerging contaminants Volatile Organic Compounds Health assessment Persistence

A B S T R A C T

With the development of the pharmaceutical industry, halogenated hydrocarbons, which are the main raw materials and emissions of the pharmaceutical industry, may be defined as atmospheric emerging contaminants due to toxicity and low oxidation of the atmosphere. This study analyzed the volatile organic compounds (VOCs) emissions from four pharmaceutical companies located in the Yangtze River Delta. Samples were taken three times at each of the selected fixed and fugitive sampling sites in each company. Through testing, 141 VOCs were identified. The mean concentration and proportion of halogenated hydrocarbons from the four pharmaceutical companies were the highest of all the industries in the industrial park. They reached 18.9 ppm and 28.8 %, respectively. Fixed emissions of the companies exhibited the mean maximum concentration of dichloromethane and chlorobenzene, which are 11.4 ppm and 250.67 ppb. The mean concentration of fugitive emission of dichloromethane from the four companies in this study is lower than that of pharmaceutical companies in other studies. Newly detected halogenated hydrocarbons, such as 1,1-dichloropropanone and dichloronitromethane, present potential non-cancer and cancer risks to workers. Chlorobenzene was identified as a key potential cancer risk halogenated hydrocarbon the value of which reaches 0.00965. 2,6-dichloropyridine could be a potential emerging contaminant due to its lower MIR value and higher potential cancer risk. The study suggests that relevant pharmaceutical companies focus on the emissions of chlorobenzene and dichloromethane, which may be the atmospheric emerging contaminants for the pharmaceutical industry and focus on improve the treatment of waste gases in workshops and sewage stations.

1. Introduction

Volatile Organic Compounds (VOCs) are a diverse group of chemicals, including non-methane hydrocarbons, oxygenated organics, halogenated hydrocarbons, and nitrogen- and sulfur-containing organic compounds. Most of the halogenated hydrocarbons in the air are of much concern due to their toxicity and low oxidation. Carbon tetrachloride and 1,1,1-trichloroethane possess atmospheric lifetimes reaching up to 100 years and 6 years, respectively, which allows for their long-distance transport in various environmental media once released (Huang et al., 2014). They are widely used in producing pharmaceuticals, pesticides, adhesives, and refrigerants (Huang et al., 2014). Recent

studies indicate that halogenated hydrocarbons pose significant health risks. For example, (Zeng et al., 2013) found that increased levels of exposure to trihalomethanes (THMs) may lead to a decrease in sperm concentration and serum total testosterone. The research team observed a suggestive dose–response relationship between the elevated blood concentrations of chloroform (TCM) or total THMs and the reduced sperm concentration (both with a trend p-value of 0.07), as well as a suggestive relationship between the increased blood concentration of dibromochloromethane (DBCM) and the decrease in serum total testosterone (with a trend p-value of 0.07); (Scott & Jinot, 2011)found that overall trichloroethylene exposure increased the risk of kidney cancer by 27 % (summary relative risk RRm of 1.27, 95 % confidence

* Corresponding authors.

E-mail addresses: [email protected](S. Gao), [email protected](Z. Jiao).

Contents lists available at ScienceDirect

Environment International

journal homepage: www.elsevier.com/locate/envint

https://doi.org/10.1016/j.envint.2024.109027

Received 19 July 2024; Received in revised form 18 September 2024; Accepted 19 September 2024 Environment International 192 (2024) 109027

Available online 21 September 2024

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interval CI: 1.13, 1.43), and in the highest exposure group, the risk increased significantly to 58 % (RRm of 1.58, 95 % CI: 1.28, 1.96).

The pharmaceutical industry is a major contributor to VOC emissions, with China alone seeing an increase from 0.26 to 0.43 teragrams between 2010 and 2015 (Lin et al., 2023). The complexity of the industry’s production processes and the variety of raw materials lead to a diverse composition of VOCs, including significant proportions of halogenated hydrocarbons, which are particularly the focus of the public due to their environmental persistence and potential health im- pacts. Studies have consistently highlighted the dominance of halogenated hydrocarbons in emissions from pharmaceutical facilities, with Shao Yixin et al. (Yixin et al., 2020) reporting that these compounds accounted for over half of the VOC emissions in a chemical synthetic pharmaceutical company in East China. Further analysis by Nana Cheng et al. (Cheng et al., 2021) revealed that the production processes of erythromycin A oxime and azithromycin were particularly high in halogenated hydrocarbon emissions, at 63.2 % and 54.6 % respectively.

Specific halogenated compounds such as dichloromethane, chloroform, and 1,2-dichloropropane have been identified in stack emissions by Qinhao Lin et al. (Lin et al., 2023). The contribution of halogenated hydrocarbons extends beyond Western medicine, as evidenced by Hai- mei Huang et al. (Huang et al., 2024) who found that traditional Chinese medicine processing also emitted these compounds, exceeding 20 % of the total VOCs. The findings underscore the need for targeted strategies to address the substantial and varied emissions of halogenated hydrocarbons from the pharmaceutical sector.

In recent years, there’s been growing concern about emerging contaminants due to their toxicity, persistence, and bioaccumulation potential. Most current research on emerging contaminants focuses on water, soil, and the accumulation in organisms (Knudtzon et al., 2021).

Studies on emerging contaminants in the air concentrate on atmospheric particulate matter, such as research on halogenated flame retardants (Wang et al., 2017) and on OPEs (Organophosphate Esters) (Saini et al., 2020); as well as research on high molecular weight semi-volatile organic compounds in the atmosphere (Anh et al., 2020). With the rise of the pharmaceutical industry, research on atmospheric emerging contaminants emitted by the industry is relatively scarce, and there is less study on emerging contaminants in the halogenated hydrocarbons, which are major raw materials and major waste gas components in the pharmaceutical industry. The reason is the current lack of clear criteria for determining atmospheric emerging pollutants, especially those around industrial areas. And one of the reasons for the absence of clear criteria is the incomplete judgment of inhalation toxicity for all halogenated hydrocarbons and unclear classification of persistence.

In terms of inhalation toxicity research of VOCs, animal-based tests have produced extensive data (Luch, 2010). However, the available toxicity data for industrial chemicals and emerging contaminants are limited. Therefore, seeking a more efficient and cost-effective method to fill these data gaps is crucial. Compared with complex animal tests, the use of model prediction methods is much faster and less costly, significantly contributing to filling the data gap of compounds. In modern toxicology and environmental risk assessment, the realization of quantitative-structure–activity/property/toxicity relationships (QSAR/

QSPR/QSTR) is widely used method in computer technology to predict the biological activity/properties/toxicity of newly produced untested chemicals (Nath et al., 2022). Barun Bhhatarai and Paola Gramatica developed multivariate linear QSAR models to predict the LC50 data for rats and mice inhaling a large number of perfluorinated and poly- fluorinated chemicals (Gramatica, 2009). Additionally, there are quantitative structure–activity relationship (QSAR) models developed to estimate the inhalation toxicity of various organic chemicals in daily life based on the no-observed-adverse-effect concentration (NOAEC) (Nath et al., 2022). However, these methods are inherently complex and resource-intensive, making them difficult to replicate. Moreover, studies directly estimating the reference concentration (RfC) and inhalation unit risk (IUR) values for inhalation toxicity are sparse. Therefore,

developing a simplified quantitative structure–activity relationship method to estimate RfC and IUR values is significant in promoting the research on inhalation toxicity of halogenated hydrocarbons in the pharmaceutical industry.

Another key area requiring attention is the persistence of halogenated hydrocarbons in the troposphere, particularly around pharmaceutical industries(Montzka et al.), which may effect the analysis of atmospheric emerging contaminants emitted by pharmaceutical company. Therefore, it is meaningful to find a value to quantify the persistence of halogenated hydrocarbons in the troposphere and the area of pharmaceutical industries. The lifetime of most trace gases in the troposphere mainly depends on their reaction with hydroxyl radicals (Montzka et al.), which is similar to the ozone accumulation process.

The Maximum Incremental Reactivity (MIR) reflects how VOCs cause the maximum increase in ozone levels (Carter, 2012), and it indicates the reactivity of different volatile organic compounds in the lower troposphere. The study indicates that low MIR value halogenated hydrocarbons are more persistent. For instance, the Maximum Incremental Reactivity (MIR) value for perchloroethylene (PCE) is 0.2, and PCE is highly volatile and persistent in the atmosphere (Huang et al., 2014);

polychloromethane (carbon tetrachloride: 0; chloroform: 0.022;

chloromethane: 0.038; methylene chloride: 0.041) share high stability, volatility, low flammability, and solvent capacity (Huang et al., 2014).

This study selected four typical pharmaceutical companies in the Yangtze River Delta as case studies. Sampling and testing were conducted on the chimney and fugitive VOCs emission sources there, and a total of 141 VOCs were detected. The pollution characteristics of halogenated hydrocarbons were studied, and a simplified quantitative structure–activity relationship method was used to calculate the Refer- ence Concentration (RfC) and Inhalation Unit Risk (IUR) values, assessing the cancer and non-cancer risks of halogenated hydrocarbons emitted by the four companies. The persistence of halogenated hydrocarbon species in these companies was estimated using machine learning methods. A new systematic approach was developed by using the entropy weight method, pollution characteristics, health assessment, and persistence to identify atmospheric emerging contaminants in the multi-media environment emitted by the pharmaceutical industry.

2. Methods 2.1. Sampling sites

The four selected pharmaceutical companies are located in the Yangtze River Delta, which are among the largest fine chemical manufacturing bases in the country. Company A mainly manufactures chemical raw materials; Company B primarily focuses on the production of tablets (including hormone class, anti-tumor drugs), hard capsules (hormone class), and raw materials; Company C is responsible for producing various pharmaceutical-grade and food-grade vitamin mono- mers, compound vitamins, and feed-grade premix; The raw materials produced by Company D primarily focus on the areas of psycho- neurological, anti-rheumatic immune, and anti-tumor treatment.

These four companies are typical of the companies in the categories of chemical raw material production and chemical synthetic pharmaceuticals. Sampling was conducted at the flue sampling points in the workshop and the sewage treatment station. To ensure representative- ness, samples were taken in each functional area of the company, such as the storage tank area and the production workshop. When the production conditions of each company exceed 80 %, three samples are collected. Table S1summarizes the sampling points, treatment tech- nologies, and the number of samples for the four pharmaceutical companies.

2.2. VOCs sampling and analysis

Sample according to the Ozone Precursor Pollutants (PAMS) and TO-

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15 standard sample analysis methods recommended by the U.S. Envi- ronmental Protection Agency (EPA). Before sampling, clean the sampling port, and measure the temperature and humidity inside the flue.

For fixed sampling, use an automatic smoke and gas tester (3012H) used for measuring the exhaust flow rate and wind volume, followed by connecting the SUMMA can (6L) to the vacuum pump through a quick sampling head equipped with a particulate matter filter for sampling.

During the sampling process, the vacuum degree of the SUMMA can is checked and recorded to ensure the accuracy of the sampling. For fugitive waste gas or environmental air sampling, sampling is done continuously for 1 h or 24 h, calibrating the flow before sampling and recording meteorological parameters. After the sampling is completed, the pressure inside the SUMMA can is recorded, and the valve is closed to complete the sampling. After all samples are collected, the sampling equipment is cleaned for subsequent use.

The sample analysis mainly used a three-stage cold trap pre- concentration system (Entech 7100) coupled with a gas chromatography-mass spectrometry system (Agilent 7890A-5975C) to determine in detail the collected VOCs samples, encompassing 106 types of VOC substances. Other equipment models used an automatic sampler (Entech 7016) and a dynamic diluter (Entech 4600). During the analysis process, a 50 mL internal standard gas is first used for instrument calibration to ensure proper mass spectrometer functioning. Subsequently, under specific gas chromatography and mass spectrometry analysis conditions, the samples are analyzed. These conditions encompass the selection of the chromatographic column (DB-1, 60 m ×0.32 mm ×1.0 μm), carrier gas flow rate (He, 1.89 ml/min), injection port temperature (200 ^◦C), temperature programming strategy, interface temperature (250 ^◦C), and ion source temperature etc. Qualitative analysis is conducted by comparing the relative retention times and mass spectra of the target compounds, while quantitative analysis uses specific calculation formulas, and semi-quantitative analysis is performed for non-target compounds(Gao et al., 2022), as shown in the analysis flowchart S1.

Furthermore, to ensure the accuracy and reliability of the analytical results, a series of quality control measures were adopted, including laboratory blanks, field blanks, SUMMA can clean blanks, sample analysis timeliness requirements, instrument maintenance and adjust- ment, initial calibration, continuous calibration, internal standard response and retention time checks, laboratory duplicate sample determination, and surrogate recovery determination. Both TO-15 and PAMS calibration curves, each containing at least 5 points, a relative standard deviation (RSD) of the response factor for each compound is 15

%(RSD≤30 %). The deviation of the back-calculated concentration at each point of the standard curve is 20 %(<30 %). An injection analysis at one point on the curve validates the calibration curve, with each compound’s response factor deviation from the initial calibration is 18 % (≤30 %). The sensitivity of the internal standard in the method blank and samples differ by 10 % (no more than ± 20 %) from that in continuous calibration, and the retention time of each internal standard in the method blank and samples must differ by 0.2 min (no more than

±0.50 min) from the corresponding standard in continuous calibration.

The same sample is duplicated for approximately every 20 samples. The relative deviation of the determination results for each target compound is 10 %(≤20 %). A surrogate is added to each sample for recovery rate determination, with the recovery rate of the surrogate ranging from 70

% to 130 %.

2.3. The determination method for atmospheric emerging contaminants in halogenated hydrocarbons

A new systematic approach integrates the entropy weight method, pollution characteristics, health assessment, and persistence, which of- fers a method for the identification, source tracing, and health risk control of atmospheric halogenated hydrocarbon emerging contaminants in the multi-medium environment of pharmaceutical emissions.

Based on the availability of analytical data, the method is divided into

two main routes: one with detailed concentration data and the other with only the main VOCs proportion. Subsequently, according to the specific data provided by the enterprise, the comprehensive coefficient of halogenated hydrocarbons at the outlet or throughout the enterprise is calculated using the entropy weight method. The halogenated hydrocarbons with the highest comprehensive coefficient indicate the representative halogenated hydrocarbon species of the outlet or throughout the company. In the case of multiple outlets, it is essential to compile the representative halogenated hydrocarbons of all outlets of the enterprise, count the number of occurrences of the same halogenated hydrocarbons, and determine the representative halogenated hydrocarbon species of the enterprise. The specific framework and flowchart are shown in Figures S4 and S5. The following sections describe the calculation methods used.

2.3.1. Estimation methods for RfC and IUR values

This study utilizes molecular descriptors referenced in the literature (Nath et al., 2022), including Extended Topological Chemical Atoms (ETA), connectivity, configuration, functionality, two-dimensional atomic pairs, rings, atomic-centered fragments, molecular properties, and topological descriptors. The approach to estimating RfC and IUR values is illustrated in Figure S2(supplementary file), which first or- ganizes the concentration data of halogenated hydrocarbons with unknown RfC and IUR values from four companies. Known RfC and IUR values for species such as alkanes, alkenes, aromatic hydrocarbons, and halogenated hydrocarbons are collected and organized using the CompTox Chemicals Dashboard. Then, the 3D structure files of these species are obtained from PubChem. The ETA descriptors, connectivity, and structural data are computed via the PaDEL-Descriptor software. If the structure and ETA data of the halogenated hydrocarbons with unknown RfC and IUR values closely match those of a known RfC and IUR value halogenated hydrocarbons, the RfC and IUR of the target halogenated hydrocarbons are calculated using the known RfC and IUR values of halogenated hydrocarbons. The calculation formula is as follows.

ai=

⃒⃒

(M− Mknowi

Mknowi +1

)

*aknowi

⃒⃒

⃒⃒ (1)

a= (∑_n

iai)/n (2)

M is the molecular weight of the species with unknown RfC or IUR.

Mknowi is the molecular weight of a related species with known RfC or IUR

for the species with unknown RfC or IUR. aknowi is the RfC or IUR value of a related species with known RfC or IUR. ai is the RfC or IUR of the species with unknown RfC or IUR. nis the number of related species for the substances with known RfC or IUR in the data table. To assess the accuracy of the method, the method was used to calculate the RfC and IUR for all known inhalation toxicity parameter species collected and organized using the CompTox Chemicals Dashboard. 68.8 % of the predicted RfC values are within 0.2 to 5 times the true values, with 50 % within 0.5 to 2 times the true values; 69.6 % of the predicted IUR values are within 0.2 to 5 times the true values, with 41.3 % within 0.5 to 2 times the true values, akin to the predicted-to-true value ratios in the study by Lihao Pang et al. (Pang et al., 2024).

2.3.2. Estimation method for MIR values

The steps for establishing a machine learning model are as follows:

(1) model design; (2) data collection; (3) training of machine learning algorithms; (4) model validation. The roadmap is shown in Figure S3 (supplementary file). The known MIR value species are classified as alkanes, alkenes, alkynes, aromatic hydrocarbons, oxygenated organic compounds, halogenated hydrocarbons, and other compounds. Then, each species is arranged into a dataset based on different characteristic values, including the molecular weight of VOCs Mi, the number of elements (nci,nHi,nOi,nNi,nCIi,nSi,nBri,nIi,nFi,nPi)and the species category xi

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(alkanes − 1, alkenes − 2, aromatic hydrocarbons − 3, oxygen-containing compounds − 4, other compounds − 5). The calculation formula is as follows:

MIRi=f(Mi,nci,nHi,nOi,nNi,nCIi,nSi,nBri,nIi,nFi,nPi,xi (3) Support Vector Machine (SVM), Random Forest (RF), Extreme Gradient Boosting (XGBoost), Ridge Regression, and Multi-Layer Per- ceptron (MLP) models are commonly used and effective machine learning algorithms in atmospheric pollutant concentration prediction models. These models were trained, using 90 % of the dataset used as training set and 10 % of the dataset used as validation set. The Root Mean Square Error (RMSE) and the Coefficient of Determination R²were used to evaluate accuracy (Ye et al., 2022). RMSE is the square root of the mean squared differences between predicted and actual values. The smaller the RMSE, the smaller the difference between the model’s predicted values and the actual values, indicating better model perfor- mance. R²indicates the proportion of variance explained by the model relative to the total variance. The value of R²varies from 0 to 1. The closer R²is to 1, the stronger the model’s explanatory power and the better the fit. The parameters used in this study excluded complex chemical reaction mechanisms. After model validation, the Random Forest (RF) model with the best training results was chosen, with a Root Mean Square Error (RMSE) of 1.422905 and a Coefficient of Determi- nation R²of 0.776476.

2.3.3. Exposure risk assessment

Inhalation of VOCs is a major pathway for human health hazards. To accurately quantify the health risks of harmful VOCs from four pharmaceutical companies, this study assessed the cancer and non-cancer risks of inhaling VOCs in the outdoor environment. Since the concentration of toxic and harmful VOCs in ambient air directly indicates the level of human exposure to VOCs, the health risk assessment is based on the measured concentrations of VOCs in ambient air. The average daily dose (ADD) of pollutants in the air breathed by each specific VOC species is calculated as follows(Duan, 2014).

ADD=C×IR×ET×EF×ED

BW×AT (4)

ADD represents the average daily dose of pollutants inhaled from the air, measured in milligrams per kilogram per day (mg/(kg⋅d)), C represents the concentration of the pollutant in the air (mg/ m³), IR is the inhalation rate (m³/d), ET is the exposure time, taken as 8 h per day (h/

d), EF is the exposure frequency, taken as 250 days per year (d/a), ED is the exposure duration, taken as 30 years (a), BW is the body weight, measured in kilograms (kg), AT is the average exposure time. For cancer risk assessment, AT is taken as 365 ×70 ×24 (d), and for non-cancer risk assessment, AT is taken as 365 × 30 × 24 (d). The formula for calculating the inhalation rate is as follows.

IR=E×H×VQ

1440 (5)

H represents the oxygen consumption per unit of energy expenditure, typically taken as 0.05 L per kilojoule (L/kJ), VQ represents the venti- latory equivalent, which is typically 27, E represents the energy expenditure per unit of time (kJ/d). The formula for calculating E rate is as follows.

E=BMR×N (6)

BMR represents Basal Metabolic Rate (BMR) (kJ/d) or (MJ/d). The specific calculation method for BMR is detailed in the supplementary document. N represents the energy expenditure at various levels of activity intensity, which is a multiple of the basal metabolic rate and is dimensionless. The value of N varies with changes in activity intensity, and the respective values for resting, sitting, light activity, moderate physical activity, heavy physical activity, and very heavy physical activity are 1, 1.2, 1.5, 4, 6, and 10 (USEPA, 2011). The inhalation non-

cancer hazard ratio (HQ) calculation formula is as follows.

HQ=ADD

RfC (7)

The RfC represents Reference Concentration, with the unit of milligrams per cubic meter (mg/m³). If the HQ is ≤1, it indicates that the exposure level has not exceeded the threshold for adverse effects, and the non-cancer risk is relatively low. If the HQ is >1, it indicates that the exposure level has exceeded the threshold, and the non-cancer risk is relatively high, warranting attention. The inhalation cancer risk (CR) calculation formula is as follows.

CR=ADD×IUR×CF (8)

The IUR represents Inhalation Unit Risk, with the unit of cubic me- ters per microgram (m³/μg). The CF represents Conversion Factor, with a value of 1000, and the unit is micrograms per milligram (μg/mg).

2.3.4. The entropy weight method

The entropy weight method assigns weights to indicators based on the size of the information load of each indicator. Entropy is a measure of the disorder of a system, and the entropy weight indicates the information value of each indicator. By analyzing the correlation between indicators and the information provided by each indicator, the weight of the indicators is calculated, which to some extent avoids the bias caused by subjective factors. In the entropy weight method, the smaller the entropy value of a variable, the greater its impact. This study utilizes emission concentrations, cancer risk, non-cancer risk, and persistence (MIR value) data from four pharmaceutical companies. To consider the relatively high and low concentrations of halogenated hydrocarbons, a parameter is also introduced, with the specific explanation of the parameter in the supplementary document. For data from other provinces, this parameter is not included in the entropy weight calculation.

Since a smaller MIR value indicates lower reactivity and higher persistence, which is the opposite of the trend of other parameters’ values, the MIR value was adjusted. After processing, the larger the MIR value, the higher the persistence. The entropy weight method was used to evaluate the weights of five indicators of VOCs in the four pharmaceutical companies, and the halogenated hydrocarbon species that should be given priority in control were determined. The specific method is described as following (Li et al., 2023).

Due to the different attributes and magnitudes of each indicator, to eliminate dimensions and units, each factor was normalized according to the range of quantities for each option. Adding 0.001 is to prevent the normalized result from being zero. The formula is as follows.

x^ʹij= xij− xmin

xmax− xmin+0.001 (9)

x^ʹij represents the normalized value of the ith species for the jth parameter. Calculate the proportion of each x^ʹ_ijin the total values under the jth parameter, the formula is as following.

pij= x^ʹʹ_ij

∑_n

i=1x^ʹʹ_ij (10)

Calculate the entropy of the jth indicator, the formula is as following.

ej= − 1 ln(n)

∑_n

i=1pijln(pij (11)

Calculate the difference coefficient and the weight of the jth indicator, the formula is as following.

gj=1− ej (12)

wj=∑gj

jgj (13)

Finally, using the normalized data x^ʹ_ijand the entropy weight Wj,

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calculate the weight indicator for the specific VOC species i, which is defined as the comprehensive control index Mi, the formula is as following.

Mi=∑

jwjx^ʹ_ij (14)

3. Results

3.1. Comparison with halogenated hydrocarbons emissions of other industries

Figs. 1 and 2 provide a comprehensive overview of halogenated

hydrocarbon emissions across various industries in adjacent industrial parks, focusing on both fixed and fugitive sources. Fig. 1illustrates that among the industries studied, the four pharmaceutical companies exhibit the highest mean concentration (18.9 ppm) and proportion (28.8 %) of halogenated hydrocarbons from fixed emissions, with Company A standing out as the most significant contributor. Fig. 2shifts focus to fugitive emissions, revealing that the chemical raw materials and chemical products manufacturing industry leads in both mean concentration and proportion of halogenated hydrocarbons. The pharmaceutical industry follows closely behind, with a mean concentration of 54.8 ppb and a proportion of 13 % for fugitive emissions.

This study compared the total concentration of halogenated hydrocarbons from fixed and fugitive emission of the four companies with the total concentrations from other studies. Nana Cheng et al. (Cheng et al., 2021) investigated pharmaceutical companies that produce antimicrobials and antibiotics, reporting a mean concentration of 979.2 ppb for halogenated hydrocarbons from fugitive emissions with a proportion of 16.5 %, and fixed emissions via RTO (Regenerative Thermal Oxidizer) of 11.7 ppm, accounting for 35 %. Qinhao Lin et al.(Lin et al., 2023) conducted a study on the emissions of volatile organic compounds (VOCs) from three pharmaceutical companies in a chemical industrial zone in a southwestern province. They reported a mean concentration of 4.9 ppm for fugitive emissions of halogenated hydrocarbons with a proportion of 45.1 %, and a mean concentration of 20.6 ppm for fixed emissions, accounting for 36.8 %. Wang Chen et al. (Chen et al., 2024) focused on three pharmaceutical companies in a pharmaceutical industrial park in Shandong Province, conducting both fixed and fugitive VOCs monitoring based on production processes. They found that the mean concentration of halogenated hydrocarbons from fixed emissions of was 4484.3 ppb, with a proportion of 50.7 %. It can be seen that the mean concentration (18.9 ppm) and proportion (28.8 %) of halogenated hydrocarbons from fixed emissions obtained in this study are similar to those of other studies. However, our fugitive emission results (54.8 ppb, 13 %) are notably lower. This discrepancy may be attributed to our sampling methodology, which primarily utilized environmental sampling points within factory areas.

3.2. Halogenated hydrocarbon emissions in pharmaceutical API companies

Fig. 3a illustrates the proportion of halogenated hydrocarbon concentrations at various sampling points in Company A, encompassing both fixed emission points (TEV, WSVO, EEGOI, EEGOO, SSGOI, and SSGOO) and one fugitive emission point within the company area (PWSDW). Among all sampling points, the mean concentration of halogenated hydrocarbons ranges from 4.5 ppb to 12.5 ppm, and the mean concentration of total VOCs ranges from 18.1 ppb to 6.4 ppm, reflecting a significant difference in the mean concentrations of species at each sampling point. Dichloromethane is the main halogenated hydrocarbon species at all sampling points. Among them, the highest concentration of dichloromethane is observed at the tank field exhaust vent (TEV) at 49.8 ppm, followed by the workshop ventilation outlet (WSVO) at 10.6 ppm, and the influent of the sewage station at 5.6 ppm.

In addition to dichloromethane, chloroform and tetrachloroethylene concentrations are relatively high at the tank area waste gas outlet, and chlorobenzene concentrations are high at the equipment exhaust gas outlet- inlet/outlet (EEGOI/EEGOO) and at the sewage station exhaust gas-inlet/outlet (SSGOI/SSGOO).

Fig. 3b, 3c, and Table S2reveal relatively high mean relative concentrations of halogenated hydrocarbons at TEV and WSVO, which are related to the company’s higher usage of dichloromethane and the lower efficiency of the waste gas treatment devices. The waste gas treatment device at TEV uses activated carbon, while the one at WSVO uses an alkaline spray +activated carbon +bag filter. As can be seen from the figs. 3b and c,the mean relative concentrations of halogenated hydrocarbons at EEGOO and SSGOO are higher than at the inlets. Further Fig. 1. The concentration and proportion of halogenated hydrocarbons from

fixed emissions of companies in different industries within adjacent industrial parks. The pie chart named “concentration mean” means the mean concentration of halogenated hydrocarbons emitted by different industries. These pharmaceutical companies are listed from highest to lowest concentration and proportion as A, C, D, and B. PI: Pharmaceutical Industry; CC: Chemical Raw Materials and Chemical Products Manufacturing; RP: Rubber and Plastics In- dustry; CCO: Computer, Communication, and Other Electronic Equipment Manufacturing; OCO: Petroleum, Coal, and Other Fuel Processing; O:

Other Industries.

Fig. 2. The concentration and proportion of halogenated hydrocarbons from fugitive emission of companies in different industries within adjacent areas. The pharmaceutical companies, from left to right, are A, C, B, and D.

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analysis is needed on the efficiency of the waste gas treatment devices for halogenated hydrocarbons. EEGOI/EEGOO uses a three-stage alkaline wash +activated carbon +UV photocatalyst, while SSGOI/SSGOO employs an alkaline spray +activated carbon. Analysis of the efficiency of these purification devices reveals that the purification efficiency of the three-stage alkaline wash +activated carbon +UV photocatalyst for halogenated hydrocarbons is lower than that of the alkaline spray + activated carbon, at 60.5 % and 82.6 % respectively. Compared to the purification efficiency of other species at the same outlet (EEGOI/

EEGOO other species purification efficiency: 96.4 %, SSGOI/SSGOO aromatic hydrocarbons purification efficiency: 99.2 %), the purification efficiency for halogenated hydrocarbons is relatively lower. The reason could be due to the environmental conditions during UV photolysis. As Fares Almomani et al. (Almomani et al., 2021)pointed out, different free radicals are produced under UV irradiation that attack dichloromethane, leading to its degradation. The low dichloromethane removal ratio observed during the photolysis process indicates that the reactivity between UV light and air flow is low, resulting in a smaller number of free radicals produced, and thus failing to achieve a significant dichloromethane removal effect.

Figs. 4a and b illustrate the proportion of halogenated hydrocarbon concentrations at various sampling points within Company D. These include two fixed emission points (the Incinerator and Min le Road sewage station) and seven fugitive emission points within the company area (NMRSS, NBRSS, SECF, SWCF, RSG, NSNo.3WS, and DNo.3WS).

Across all sampling points, the mean concentration range of halogenated hydrocarbons ranges from 1.8 ppb to 29.8 ppb, and the mean total VOC concentration ranges from 2.2 ppb to 23 ppb, showing no significant variation in mean species concentrations compared to the other three companies’ sampling points. The exhaust from the incinerator contains notably high hydrogen chloride at 263.3 ppb, and the Min le Road sewage station has relatively high dichloromethane at 146 ppb.

Analysis of Figs. 4c, d, e, and Table S3reveals that both the Incin- erator and Min le Road sewage station exhibit higher average values for halogenated hydrocarbons and total VOCs compared to other sampling points. The Incinerator also detects newer halogenated hydrocarbons, such as hydrogen chloride, hydrogen bromide, 1,1-dichloropropanone, and dichloronitromethane, related to raw material production requirements and exhaust treatment devices. The raw materials used by the company include dichloroquinoline, a highly reactive substance containing both chlorine and nitrogen elements. Acetone can react with chlorine under light exposure to form 1,1-dichloropropanone. The production of dichloroacetonitrile may also relate to its cyano group (–CN) precursors and photocatalytic exhaust treatment (Lyon et al., 2014). The Min le Road sewage station is mainly responsible for treating rainwater, hence the main species of halogenated hydrocarbons differ from those at the Incinerator. The fugitive sampling point next to Min le Road sewage station (NMRSS) shows similar relative mean concentrations of various species to the Min le Road sewage station.

Fig. 3.(a) shows the proportion of halogenated hydrocarbon concentrations at various sampling points of Company A, (b) and (c) Show the mean relative concentrations of each VOC species at various sampling points of Company A. The mean relative concentration is the mean of each species (such as alkanes, halogenated hydrocarbons, etc.) divided by the mean of all VOCs.

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3.3. Halogenated hydrocarbon emissions in chemically synthesized pharmaceuticals companies

Fig. 5a is a chart showing the proportion of halogenated hydrocarbon concentrations at various sampling points of Company B, including one fixed emission sampling point for the east production workshop exhaust gas outlet (EPWEGO) and five fugitive emission sampling points in the company area (NB, ETWTS, No.2WMA, WB, and WTWTS). Among all sampling points, the mean concentration range of halogenated hydrocarbons ranges from 2 ppb to 83.2 ppb, and the mean total VOC concentration ranges from 2.2 ppb to 583.6 ppb, reflecting a significant difference in the mean concentrations of species at each sampling point.

Dichloromethane is the main species of halogenated hydrocarbons at the sampling points. The highest concentration of dichloromethane, reaching 298 ppb, is observed near the east three waste treatment station (ETWTS); the main species of halogenated hydrocarbons at the east production workshop exhaust gas outlet (EPWEGO) are dichloromethane and bromobenzene, with a high concentration of dichloromethane at 240 ppb. In the No.2 workshop middle area (No.2WMA), the main species of halogenated hydrocarbons also is dichloromethane with a concentration of 115 ppb, and at the west three waste treatment station (WTWTS), the main species are dichloromethane and chloroform.

From Figs. 5b and c and Table S4, it can be concluded that the mean value of halogenated hydrocarbons at EPWEGO is the highest among all outlets and sampling points. The relative mean value of halogenated hydrocarbons at ETWTS is the highest, while the relative mean value of OVOCs has decreased significantly compared to EPWEGO, because the role of the waste treatment station is to further treat the waste gas from

the production workshop, hence proportion of halogenated hydrocarbons increase, especially the highest concentration of dichloromethane, which may be due to some OVOCs reacting with chlorine to form dichloromethane.

Figs. 6a and c present the proportion of halogenated hydrocarbons concentrations at various sampling points of Company C, including four fixed emission sampling points (DFSRTO, VANo.243EF, Ino.743EF, and SSNo.751EF) and five fugitive emission sampling points in the company area (M243244, 732TF, M741742, 751SSDW, and NDNo.5G). Among all sampling points, the mean concentration range of halogenated hydrocarbons ranges from 0.8 ppb to 2.6 ppm, and the mean total VOC concentration ranges from 3.5 ppb to 5.3 ppm, reflecting significant differences in the mean concentrations of species at different sampling points. The majority of halogenated hydrocarbons emitted from the fixed outlets and fugitive sampling points of Company C is dichloromethane. Notably, the highest concentration of dichloromethane was 5.3 ppm at the vitamin B6 sewage station No.751 Exhaust Funnel (SSNo.751EF), with chloroethane concentration also reaching 4.9 ppm at this point.

From Figs. 6b, d, and Table S5, it can be concluded that the relative mean concentrations of halogenated hydrocarbons and alkanes at the vitamin A oil No.243 exhaust funnel (VANo.243EF) are relatively high, which is related to the production requirements of raw materials such as dichloromethane and n-hexane, and also related to the low efficiency of the purification device’s activated carbon adsorption treatment for waste gas at this outlet. SSNo.751EF shows the highest average values for total VOCs and halogenated hydrocarbons, with relative mean concentrations of aromatics, halogenated hydrocarbons, and oxygen- Fig. 4. (a) and (b) show the proportion of halogenated hydrocarbon concentrations at various sampling points of Company D.4(c), 4(d), and 4(e) display the mean relative concentrations of various VOCs species at various sampling points of Company D.

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containing hydrocarbons also being relatively high. The outlet of the workshop producing food additives emits fewer halogenated hydrocarbons and the total VOC concentration at this outlet is also lower, accounting for 0.36 % of Company C’s total fixed VOC concentration. This phenomenon is related to the high purification efficiency of the purification device RTO adopted by this outlet. The relative mean concentrations of various species at fugitive sampling points near the production workshops are similar to their corresponding fixed sampling points, such as the main species concentration relative average values at SSNo.751EF and its downwind fugitive emission sampling point (751SSDW) are similar.

3.4. Comparison with halogenated hydrocarbons species of pharmaceutical companies in other studies

From Fig. 7, it can be seen that in this study, main halogenated hydrocarbon species from the fixed emissions of the four pharmaceutical companies include dichloromethane, chloroform, chlorobenzene, and tetrachloroethylene. However, an examination of mean concentration proportions reveals no consistent patterns in fixed halogenated hydrocarbon emissions among these four companies or in comparison with other studies on pharmaceutical companies. Among them, company A has the highest mean concentrations of fixed emission for dichloromethane and chlorobenzene, which are 11.4 ppm and 250.7 ppb, respectively, accounting for 47 % and 52 % of the total. Company D has the lowest mean concentration of fixed emission for dichloromethane among all studies presented in Fig. 7(Chen et al., 2024; Cheng et al., 2021), accounting for about 1 %; the mean concentration of fixed emission for chlorobenzene in Company D is also relatively low, accounting for about 3 %. However, the company shows a relatively high

mean concentration of fixed chloroform emissions at 49.2 ppb, accounting for 52 %. Compared with other studies, Company D also detects more new halogenated hydrocarbons types, related to the raw materials used and the exhaust treatment devices adopted.

From Fig. 8, fugitive emissions of halogenated hydrocarbons in the four pharmaceutical companies in this study are more diverse than fixed emissions. In terms of the halogenated hydrocarbons species, similar halogenated hydrocarbons species are found among the fugitive emission of pharmaceutical companies in the same region (the four companies in this study and those in the Yangtze River Delta study) (Cheng et al., 2021). From the perspective of mean concentration proportions, Companies B and D in this study share more similar species in mean concentration proportions of halogenated hydrocarbons from fugitive emissions, although the main products of these two companies differ.

They share similar mean concentration proportions of halogenated hydrocarbons from fugitive emissions, such as chloroform, dichlorodiflu- oromethane, trichlorotrifluoroethane, and 1,2-dichloropropane.

Company C exhibits a higher mean concentration proportion of fugitive chlorobenzene emissions than the other three companies in this study, similar to the mean concentration proportion of fugitive chlorobenzene emissions in pharmaceutical companies in the Yangtze River Delta study, accounting for about 50 %. (Chen et al., 2024; Li, 2022; Wang et al., 2023).

The mean concentration of fugitive emission of dichloromethane from the four companies in this study is lower than that of pharmaceutical companies in other studies, accounting for 1 %. For example, a veterinary antibiotic pharmaceutical company in a northern city shows a mean concentration of fugitive dichloromethane emissions of 24.4 ppm, accounting for 96 %.

Fig. 5.(a) Proportion of halogenated hydrocarbons concentrations at various sampling points of Company B.(b) and (c) Mean relative concentrations of various VOCs species at various sampling points of Company B.

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4. Discussion

4.1. Potential toxic halogenated hydrocarbons analysis

The present study used a simplified quantitative structure–activity relationship model for RfC and IUR estimation methodologies and conducted a comprehensive risk assessment of halogenated hydrocarbon pollutants from four pharmaceutical companies, which has delin- eated previously unappreciated risks associated with halogenated hydrocarbon emissions from pharmaceutical manufacturing processes.

As depicted in Fig. 9, the HQ values for halogenated hydrocarbons from both fixed and fugitive emissions underscore the non-cancer risk levels, with Company D’s incinerator chimney exhibiting the most pronounced values. Specifically, 1,1-dichloropropanone demonstrated an HQ value of 71.956, surpassing the benchmark for non-cancer risk. Furthermore, emissions from Company A, particularly dichloromethane and chlorobenzene, indicated elevated HQ values, suggesting significant non- cancer risk potential. Our findings diverge from prior research, which

predominantly identified risks for select halogenated hydrocarbons such as dichloromethane and chlorobenzene (Lin et al., 2023; Ma & Li, 2024).

The discrepancy may be attributed to the more comprehensive toxicity assessment method and the new qualitative and quantitative methods employed in this study, as well as the diverse processing methods applied to various pharmaceutical raw materials. Fig. 10elucidates the CR values, with those exceeding 1 ×10^-4warranting heightened vigi- lance. Notably, chloroform emissions from Company B’s ETWTS and chlorobenzene from Company D’s incinerator and Company A’s SSGOI are of particular concern, with CR values 0.00965 that surpass the established threshold. It’s worth noting that chlorobenzene concentrations in our study exceed those reported elsewhere, with Company A’s fixed emissions concentration outstripping that of a Shandong company by 1.3 times. Just like in the non-cancer risk assessment, for the cancer risk assessment, this study has adopted new toxicity assessment methods. This study’s results contrast with existing literature (Cheng et al., 2021; Lin et al., 2023), the inhalation toxicity of chlorobenzene, though less studied, is a burgeoning area of concern. (Wu et al., 2020) Fig. 6. (a) and (c) show the proportion of halogenated hydrocarbons concentrations at various sampling points of Company C.(b) and (d) display the mean relative concentrations of various VOCs species at various sampling points of Company C.

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reported that certain chlorobenzene derivatives can release reactive species at elevated temperatures, potentially exacerbating respiratory conditions such as asthma. Additionally, the potential cancer risk posed by newly detected halogenated hydrocarbons, including hydrogen cya- nide and 1,1-dichloropropanone, cannot be overlooked. In the broader

context of fugitive emissions, chloroform, 1,2-dichloroethane, 1,2- dichloropropane, and chlorobenzene are identified as the primary car- cinogens, albeit with CR values an order of magnitude lower than those from fixed emissions. In conclusion, this study has bridged gaps in the understanding of non-cancer and cancer risks associated with Fig. 7. Mean concentration proportion of halogenated hydrocarbons from fixed emission.

Fig. 8.Mean concentration proportion of halogenated hydrocarbons from fugitive emission.

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halogenated hydrocarbons in the pharmaceutical industry. The findings underscore the need for targeted risk management strategies, particularly at fixed discharge points in sewage stations. Future research should focus on refining risk assessment models and exploring mitigation strategies to safeguard worker health and environmental integrity.

4.2. Potential persistent halogenated hydrocarbons analysis

While international standards classify the halogenated hydrocarbons

in this study as short-lived, with atmospheric lifetimes under six months, their impact on nearby residential areas shouldn’t be underestimated.

Even brief transport periods can significantly affect the health of resi- dents living in proximity to pharmaceutical or chemical companies (Wang et al., 2023). Therefore, reclassifying the persistence of halogenated hydrocarbons in the near-surface troposphere is necessary. This study integrates all halogenated hydrocarbons from four companies and, based on their Maximum Incremental Reactivity (MIR) values, uses hi- erarchical cluster analysis to categorize them into three classes. Values Fig. 9. Non-cancer risk HQ heatmap for halogenated hydrocarbons in four pharmaceutical companies.

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of 0–1 indicate high persistence, 1–2.5 indicate medium persistence, and 2.5–3 indicate low persistence, as detailed in Table S6. To verify the accuracy of the classification, literature on the persistence of these classes of halogenated hydrocarbons was reviewed, detailed in Table S6.

Carbon tetrachloride, bromoform, methyl bromide, and chloroform all have MIR values between 0 and 1, with carbon tetrachloride having an MIR value of 0, indicating significant persistence. Bromine-containing halogenated hydrocarbons generally exhibit lower MIR values, with

studies indicating a longer local lifetime for CH2Br2 in Southeast Asia, with τlocal at 120 days (Wisher et al., 2014). Therefore, brominated halogenated hydrocarbons may be potential persistent pollutants. In Company D, newly detected halogenated hydrocarbons containing oxygen and nitrogen elements are mostly highly reactive and have low persistence, such as dichloronitromethane with an MIR value of 2.89, cyanogen chloride with an MIR value of 2.27, bromoacetonitrile with an MIR value of 1.22, and 1,1-dichloropropanone with an MIR value of Fig. 10.Cancer risk CR heatmap for halogenated hydrocarbons in four pharmaceutical companies.

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2.76. While these compounds pose higher potential cancer or non- cancer risks, their low persistence may disqualify them as long-term pollutants of concern. However, this conclusion warrants further investigation. Among the newly detected halogenated hydrocarbons, 2,6-dichloropyridine exhibits a low MIR, indicating some persistence, and poses a higher potential cancer risk, making it a potential emerging contaminant of concern in the pharmaceutical industry.

4.3. Analyzing the atmospheric halogenated hydrocarbons emerging contaminants

Before delving into the specifics of atmospheric halogenated hydrocarbons emerging contaminants within the pharmaceutical industry, it is essential to recognize the broader context of these contaminants in the environment. Halogenated hydrocarbons, due to their inherent stability and resistance to degradation, have been identified as a class of compounds with significant potential to impact both human health and the environment. The pharmaceutical industry, with its extensive use of such compounds in various stages of drug production, inadvertently contributes to the atmospheric burden of these contaminants. The analysis presented in this section aims to evaluate the implications of our findings on the current understanding of atmospheric pollution, identify potential atmospheric emerging contaminants, and propose avenues for future research that can aid in mitigating the emission of these emerging contaminants.

4.3.1. The atmospheric halogenated hydrocarbons emerging contaminants in four pharmaceutical companies

This study combined the entropy weight method, pollution characteristics, health assessment, and persistence to provide a methodological reference for identifying, source tracking, and managing health risks associated with atmospheric halogenated hydrocarbons emerging contaminants in the multi-media environment of pharmaceutical industry emissions. Table 1and Table S7provide a detailed breakdown of index weights for five key parameters and a comprehensive index for all halogenated hydrocarbons emitted by the four pharmaceutical companies under study. Based on the comprehensive index of halogenated hydrocarbons, the emitted halogenated hydrocarbons at each sampling point are classified into five control levels. Species with a comprehensive index > 0.3 are classified as control level one, and those with a

comprehensive index of 0.2–0.3 are listed as level two. Both levels are identified as key species urgently needing concern (Li et al., 2023). From Table 2, the halogenated hydrocarbons emerging contaminants mainly appear in fixed emissions: (1) Company D should prioritize monitoring and control of 1,1-dichloropropanone, cyanogen chloride, bromoform, chlorobenzene, and 1,2-dichloroethane, particularly those emitted from the incinerator. Due to the high concentrations of 1,1-dichloropropanone and cyanogen chloride, the comprehensive index increases, but their MIR values are greater than 1.2, which does not meet the persistence requirements for emerging contaminants; (2) Company C needs to focus on halogenated hydrocarbons such as chlorobenzene, 1,2-dichloropropane, dichloromethane, and chloroethane, particularly those found in the exhaust stack of the sewage station in the vitamin B6 production area; (3) The main halogenated hydrocarbon species of Company B are chloroform and bromobenzene, detected in EPWEGO and WTWTS; (4) Company A should monitor chloroform, chlorobenzene, and dichloromethane, particularly at their TEV, WSVO, and SSGOI points. Among the four companies, Companies D and A both produce pharmaceutical chemical API, while Companies C and B are chemical synthetic pharmaceutical companies. A comprehensive analysis indicates that chlorobenzene is potential atmospheric emerging contaminants in fixed emissions by three pharmaceutical companies. From the perspective of sampling points, all four pharmaceutical companies should focus on fixed emission outlets of workshop and sewage station.

Table 1

Weights for five parameters.

Company Cancer

risk Non-

cancer risk Persistence Concentration Rank Company

A 30.14 % 18.39 % 6.02 % 25.31 % 20.14 %

Company

B 17.08 % 30.00 % 3.25 % 20.35 % 29.32 %

Company

C 22.57 % 25.16 % 2.39 % 31.06 % 18.82 %

Company

D 14.42 % 38.18 % 1.92 % 22.44 % 23.04 %

Table 2

The halogenated hydrocarbons that are potential atmospheric emerging contaminants for four pharmaceutical companies.

Company D fixed emission Company C fixed emission Company B fixed emission Company B fugitive emission Company A fixed emission 1,2-dichloroethane

Min le Road sewage station 0.19 Chlorobenzene

SSNo.751EF 0.20 Chloroform

EPWEGO 0.27 Chloroform

WTWTS 0.41 Chloroform

TEV 0.20

Chlorobenzene

Incinerator 0.23 1,2-dichloropropane

SSNo.751EF 0.33 Bromobenzene

EPWEGO 0.92 Dichloromethane

WSVO 0.33

Bromoform

Incinerator 0.24 Dichloromethane

SSNo.751EF 0.60 Chlorobenzene

SSGOI 0.37

Cyanogen chloride

Incinerator 0.48 Chloroethane

SSNo.751EF 0.70 Dichloromethane

TEV 0.70

1,1-dichloropropanone

Incinerator 0.56

Table 3

Information about pharmaceutical companies.

Region Type Sampling points

Company B Chemically synthesized

pharmaceuticals fixed emission, fugitive emission A company in Jiangsu Province Chemically synthesized

pharmaceuticals fixed emission A company in Yuncheng Chemically synthesized

pharmaceuticals

1 company in a pharmaceutical

park in Shandong Chemically synthesized

pharmaceuticals fixed emission, fugitive emission

Company C Chemically synthesized

pharmaceuticals fixed emission, fugitive emission A company in the Yangtze River

Delta Chemically synthesized

pharmaceuticals fixed emission, fugitive emission Company A in East China Chemically synthesized

pharmaceuticals fixed emission, fugitive emission Company B in East China Chemical API

manufacturing fixed emission, fugitive emission

Company D Chemical API

manufacturing fixed emission, fugitive emission

Company A Chemical API

manufacturing fixed emission, fugitive emission 2,3 companies in a

pharmaceutical park in Shandong

Chemical API

manufacturing fixed emission, fugitive emission A company in a central city in

northern China Biological fermentation fugitive emission A company in the Ningxia

region Biological fermentation fugitive emission

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4.3.2. The atmospheric halogenated hydrocarbons emerging contaminants in pharmaceutical companies across multiple provinces

This study focuses on atmospheric halogenated hydrocarbons emerging contaminants in four companies and collects VOC emission concentration data from several other pharmaceutical companies in different regions. Table 3 provides a comprehensive overview of the pharmaceutical companies analyzed across various locations. The collected data was analyzed by the steps shown in Figure S5to find the halogenated hydrocarbons emerging contaminants. From Fig. 11a, fixed emissions of these pharmaceutical companies can be categorized into two types: those focusing on dichloromethane and those that do not.

Both categories include companies in the chemically synthesized pharmaceuticals and chemical API, making it challenging to identify commonalities from this perspective. From the perspective of the types of drugs produced, summarizing commonalities of halogenated hydrocarbons emerging contaminants for chemical synthesis companies is difficult, possibly due to the various units involved in chemical synthesis technology, such as the synthesis of intermediates from raw materials, modification of intermediate structures, purification of products, and drying of final products (Zhou et al., 2020). The VOCs produced by this process, including solvents and unreacted intermediates, are more complex than those produced by biological fermentation (Zhou et al., 2020). Therefore, further subdivision of these chemical synthesis companies reveals that companies producing antimicrobials (Company A in East China and a company in the Yangtze River Delta) mainly focus on dichloromethane in their fixed emissions. This species is included in China’s key controlled new pollutants list. The potential halogenated hydrocarbons emerging contaminants for several chemical API manufacturing companies are mainly chlorobenzene. As can be seen from Fig. 11b, fugitive emissions of these pharmaceutical companies can be categorized into three types: those primarily emitting carbon tetrachloride, those primarily emitting methyl chloride and carbon tetrachloride, and those primarily emitting dichloromethane.

Dichloromethane is the halogenated hydrocarbons emerging contaminants from the fugitive emission of company producing antimicrobials

(Company A in a chemical industrial park in the East China region and the Yangtze River Delta). It is difficult to identify commonalities from other perspectives.

In summary, due to the complexity of raw materials, production processes and a scarcity of VOCs source profile data in the pharmaceutical industry, the fugitive emission of halogenated hydrocarbons from chemical synthetic pharmaceutical enterprises needs further study in future. For companies producing chemical API, the potential halogenated hydrocarbon emerging contaminants from fixed emissions is chlorobenzene, while for those producing antimicrobial drugs, both fixed and fugitive emissions should pay attention to dichloromethane, a new type of pollutant.

5. Conclusion

This study examined the emissions, health risks, and persistence of halogenated hydrocarbons from four major pharmaceutical companies.

By employing a systematic approach, the research team identified key atmospheric emerging contaminants across multiple media in the pharmaceutical industry’s emissions. The study went a step further, comparing these findings with data from other regions to pinpoint common atmospheric emerging contaminants industry-wide.

The four pharmaceutical companies had the highest levels of halogenated hydrocarbons from fixed emissions in their industrial park.

Company A had the highest levels of dichloromethane and chlorobenzene. Company D detected more new halogenated hydrocarbons, despite lower concentration. The Concentration of dichloromethane from fugitive emissions of company D were lower than in other studies, at just 1

%.The study identified health risks from dichloromethane and 1,2- dichloropropane, and new pollutants like 1,1-dichloropropanone and dichloronitromethane posed significant non-cancer risks. Chloroben- zene has major potential cancer risk, highlighting the need to monitor wastewater treatment emissions.

In terms of persistence, certain bromine-containing compounds, Fig. 11. (a) Number of occurrences of fixed emission potential halogenated hydrocarbons emerging contaminants in multiple provinces, (b) Number of occurrences of fugitive emission potential halogenated hydrocarbons emerging contaminants in multiple provinces.