Air Pollution Risk Assessment Research Articles

The last decade of air pollution epidemiology and the challenges of quantitative risk assessment.

Epidemiologic research and quantitative risk assessment play a crucial role in transferring fundamental scientific knowledge to policymakers so they can take action to reduce the burden of ambient air pollution. This commentary addresses several challenges in quantitative risk assessment of air pollution that require close attention. The background to this discussion provides a summary of and conclusions from the epidemiological evidence on ambient air pollution and health outcomes accumulated since the 1990s. We focus on identifying relevant exposure-health outcome pairs, the associated concentration-response functions to be applied in a risk assessment, and several caveats in their application. We propose a structured and comprehensive framework for assessing the evidence levels associated with each exposure-health outcome pair within a health impact assessment context. Specific issues regarding the use of global or regional concentration-response functions, their shape, and the range of applicability are discussed.

Using EEA data to calculate health impacts of air pollution via the AirQ+ model: a practical example

Abstract The AirQ+ software tool for health risk assessment of air pollution, developed by the World Health Organization, helps quantify the effects of exposure to air pollution. Specifically, AirQ+ can estimate the effects of short-term changes in air pollution (based on risk estimates from time-series studies) and the effects of long-term exposures (using life-tables approach and based on risk estimates from cohort studies). AirQ+ is available in English, French, German and Russian. In this presentation, AirQ+ will be loaded with air pollution data from the European Environment Agency datasets for a quick evaluation of health effects from air pollution in an European city.

Advances and future directions of environmental risk research: A bibliometric review

Environmental risk is one of the world’s most significant threats, projected to be the leading risk over the next decade. It has garnered global attention due to increasingly severe environmental issues, such as climate change and ecosystem degradation. Research and technology on environmental risks are gradually developing, and the scope of environmental risk study is also expanding. Here, we developed a tailored bibliometric method, incorporating co-occurrence network analysis, cluster analysis, trend factor analysis, patent primary path analysis, and patent map methods, to explore the status, hotspots, and trends of environment risk research over the past three decades. According to the bibliometric results, the publications and patents related to environmental risk have reached explosive growth since 2018. The primary topics in environmental risk research mainly involve (a) ecotoxicology risk of emerging contaminants (ECs), (b) environmental risk induced by climate change, (c) air pollution and health risk assessment, (d) soil contamination and risk prevention, and (e) environmental risk of heavy metal. Recently, the hotspots of this field have shifted into artificial intelligence (AI) based techniques and environmental risk of climate change and ECs. More research is needed to assess ecological and health risk of ECs, to formulize mitigation and adaptation strategies for climate change risks, and to develop AI-based environmental risk assessment and control technology. This study provides the first comprehensive overview of recent advances in environmental risk research, suggesting future research directions based on current understanding and limitations.

Toward cleaner air and better health: Current state, challenges, and priorities.

The most up-to-date estimate of the global burden of disease indicates that ambient air pollution, including fine particulate matter and ozone, contributes to an estimated 5.2 million deaths each year. In this review, we highlight the challenges in estimating population exposure to air pollution and attributable health risks, particularly in low- and middle-income countries and among vulnerable populations. To protect public health, the evidence so far confirms urgent needs to prioritize interdisciplinary research on air pollution exposure and risk assessment and to develop evidence-based intervention policies and risk communication strategies. Here, we synthesize the emerging evidence supporting the monitoring and evaluation of the progress in implementation of the Global Air Quality Guidelines prepared by the World Health Organization.

Effect of the Method Detection Limit on the Health Risk Assessment of Ambient Hazardous Air Pollutants in an Urban Industrial Complex Area

Hazardous air pollutants (HAPs) significantly impacted environmental air quality and were widely studied to determine human health risks. Kaohsiung is Taiwan’s second-largest city, known for its heavily industrialized and densely populated development. The Linhai industrial park, located in this region, contains roughly 500 industrial facilities that contributed to the emission of HAPs. The purpose of this study was to identify the volatile organic compound (VOCs) and particulate matter (PM)-bounded heavy metals and to examine the effects of the method detection limit (MDL) for analyzed species and the sampling program on health risk assessments. This study identified formaldehyde, 1,2-dichloroethane, acetaldehyde, benzene, and vinyl chloride. As, ethylbenzene, Ni, Cr(VI), Cd, Pb, and 1,3-butadiene were defined as high-risk species and VOCs accounted for more than 95% of respiratory-related health risks, this study proposes that the MDL for analysis methods and the sampling frequency for different species (and the species of interest) would eventually affect the results of health risk assessments. In other words, the current control strategies for reducing health risks may be ineffective. This research output can be used to comprehend the effects of MDL on the health risk assessments of HAPs better while also providing a reliable method to determine the major sources of air pollutants in urban industrial areas.

Air Pollution Risk Assessment Using GIS and Remotely Sensed Data in Kirkuk City, Iraq

According to World Health Organization (WHO) estimates and based on a world population review, Iraq ranks tenth among the most air-polluted countries in the world. In this study, the authors tried to evaluate the outdoor air of Kirkuk City north of Iraq. The authors relied on two types of data: field measurements and remotely sensed data. Fifteen air quality points were determined in the study region representing the monthly average measurements implemented for the one-year dataset. Geographic information systems (GIS) based geo-statistic and geo-processing techniques have been applied to collected data. Spatial distribution data related to Air Quality Index (AQI), and Particulate Matter (PM10 and PM2.5) were obtained by mapping collected records. Remotely sensed data of PM2.5 were analyzed and compared with the collected data. Health impacts were assessed per each air pollutant determined in the study. Spatial distribution maps revealed the hazardous air type in the study area. Overall AQI ranged between 300 and 472 µg/m3 referring to unhealthy, very unhealthy, and hazardous classes of pollution. Also, PM10 ranged between 300 and 570 µg/m3 indicating the same class of air pollution from unhealthy to hazardous. While PM2.5 ranged between 40 and 60 µg/m3 which represents unhealthy air for sensitive persons and unhealthy air. The remotely sensed data revealed different air types for the study period ranging from 14.5 to 52.5 µg/m3 represented in moderate and unhealthy air for sensitive persons. Significant correlations were obtained where the mean local R2 (coefficient of determination) was obtained as 0.83. The assessed data were within high air pollution that requires immediate intervention for controlling causes and eliminating their effects.

Human health risk assessment of air pollutants in the largest coal mining area in Brazil.

The Candiota region, located in the extreme south of Brazil, has the largest mineral coal deposit in the country, and this activity is capable of releasing pollutants in which they are associated with the contamination of different matrices (soil, water, and air). The present study aimed to carry out a risk assessment to human health of atmospheric pollutants NO2 and SO2 and PM10-bound metal(loid)s in the municipality of Candiota, in addition to evaluating the correlation of meteorological parameters for the dynamics and potential risk of these pollutants. Pollutants were sampled from stations located almost 4km from coal exploration activities, and the trace elements As, Cd, Se, Pb, and Ni, in addition to NO2 and SO2, were evaluated. Risk assessment was conducted taking into account the risk to adults via the inhalation route. During the sampling period, all pollutants presented values lower than national legislation or internationally accepted values, and Pb was the element that presented the highest values throughout the sampled period. The risk assessment showed no carcinogenic and non-carcinogenic risks, even when considering the sum of the risk of all analyzed pollutants. It can be observed that the highest levels of Pb, As, and Se occurred in the winter season, while the levels of Ni and Cd were higher in the spring, and the meteorological parameters were correlated with the pollutants, even using a temporal lag of 5days. Although the air pollutants evaluated did not present a risk to human health, continuous monitoring of regions with strong mineral exploration activity must be carried out with a view to maintaining the well-being of exposed populations, mainly because there are people living in areas closer to sources of coal pollution than distance to air quality monitoring stations.

Health effects of air pollutant mixtures (volatile organic compounds, particulate matter, sulfur and nitrogen oxides)- a review of the literature.

The health risks associated with individual air pollutant exposures have been studied and documented, but in real-life, the population is exposed to a multitude of different substances, designated as mixtures. A body of literature on air pollutants indicated that the next step in air pollution research is investigating pollutant mixtures and their potential impacts on health, as a risk assessment of individual air pollutants may actually underestimate the overall risks. This review aims to synthesize the health effects related to air pollutant mixtures containing selected pollutants such as: volatile organic compounds, particulate matter, sulfur and nitrogen oxides. For this review, the PubMed database was used to search for articles published within the last decade, and we included studies assessing the associations between air pollutant mixtures and health effects. The literature search was conducted according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. A number of 110 studies were included in the review from which data on pollutant mixtures, health effects, methods used, and primary results were extracted. Our review emphasized that there are a relatively small number of studies addressing the health effects of air pollutants as mixtures and there is a gap in knowledge regarding the health effects associated with these mixtures. Studying the health effects of air pollutant mixtures is challenging due to the complexity of components that mixtures may contain, and the possible interactions these different components may have.

A novel FMEA approach for risk assessment of air pollution from ships

Port State Control (PSC) is the inspection mechanism that ensures commercial vessels comply with internationally binding rules and regulations. During the PSC inspections, non-compliances with international maritime conventions may result in deficiencies or even the detention of the vessel. On the other side, deficiencies identified during PSC inspections are significant for the safe, secure, clean seas and sustainable marine environment. In this line, International Maritime Organization (IMO) aims to reduce ship-related pollution within the scope of the International Convention for the Prevention of Pollution from Ships (MARPOL). Specifically, Annex-VI is the most recently ratified regulation of MARPOL covering air pollution. Although Annex-VI deficiencies pose significant risks to maritime stakeholders and the natural environment, this topic has been broadly neglected by researchers. For this reason, a detailed risk analysis for the MARPOL Annex-VI deficiencies was carried out to demonstrate a prioritization concerning the marine environment and maritime stakeholders in this study. An improved Failure Mode and Effects Analysis (FMEA) approach is employed in the computation of risk priority numbers (RPN) by taking O, S, and D inputs from two different expert groups and the Paris MoU database. According to the results, the riskiest MARPOL Annex-VI failure modes are identified as 14615-Fuel change-over procedure (RPN: 235.71), 14608-Incinerator operations and operating manual (RPN: 232.65), and 14601-Technical files and if applicable, monitoring manual (RPN: 219.86). Consequently, the presented risk analysis and findings are intended to be a reference for maritime stakeholders to prevent harmful scenarios involving ship-related air pollution.

Assessment of the burden of disease due to PM2.5 air pollution for the Belgrade district

The health effects attributed to exposure to ambient PM2.5 concentrations above 10 ?g/m3 by using the AirQ+ modeling software were assessed. The hourly concentrations of PM2.5 were collected from 13 air pollution monitoring stations in the Belgrade district during June and July 2021., which were further used as input data for the AirQ+ software. The average concentration of PM2.5 for two-month monitoring from all sampling sites in the city was 14.8 ?g/m3, the maximum daily concentration was 55.7 ?g/m3, while the maximum concentration per hour was 365 mg/m3. The spatial distribution of concentrations was mapped using geostatistical interpolation, revealing hotspots within the city center and industrial area of the district. The burden of disease, such as stroke, ischemic heart disease (IHD), chronic obstructive pulmonary disease (COPD), and lung cancer, due to the ambient PM2.5 pollution was evaluated according to the WHO method-ology for health risk assessment of air pollution. The model used for this assessment is based on the attributable proportion defined as the section of the health effect related to exposure to air pollution in an at-risk population. The estimated attributable proportion was 19.4% for stroke, 27.2% for IHD, 15.3% for COPD and 9.0% for lung cancer. The estimated number of attributable cases per 100000 population at risk, due to PM2.5 air pollution, for stroke, IHD, COPD, and lung cancer, was 28, 34, 15, and 8, respectively.

Species differences in activation of TRPA1 by resin additive-related chemicals relevant to indoor air quality.

Transient Receptor Potential Ankyrin 1 (TRPA1), which is expressed in the airways, has causative and exacerbating roles in respiratory diseases. TRPA1 is known as a target of sick building syndrome-related air pollutants, such as formaldehyde. Thus, an in vitro TRPA1 activation assay would be useful for predicting the potential risk of air pollution. In this study, we used human TRPA1 (hTRPA1)- and mouse TRPA1 (mTRPA1)-expressing cell lines to measure TRPA1 activation by the emerging indoor air pollutants 2-ethyl-1-hexanol (2-EH), a mixture of 2,2,4-trimethyl-1,3-pentanediol 1- and 3-monoisobutyrate (Texanol), and 2,2,4-trimethyl-1,3-pentanediol diisobutyrate (TXIB). The results indicated that 2-EH activated both hTRPA1 and mTRPA1 in a concentration-dependent manner, whereas TXIB did not activate hTRPA1 or mTRPA1. Texanol also activated hTRPA1 in a concentration-dependent manner. In contrast, a bell-shaped concentration-dependent curve was observed for mouse TRPA1 activation by Texanol, indicating inhibitory effects at a higher concentration range, which was also reported for menthol, a typical TRPA1 modulator. To further elucidate the mechanism underlying the species difference in TRPA1 activation by Texanol, V875G and G878V mutations were introduced into hTRPA1 and mTRPA1, respectively, which were reported to be key mutations for the inhibitory effect of menthol. These mutations switched the inhibitory effects of Texanol; thus, hTRPA1/V875G, but not mTRPA1/G878V, was inhibited at higher concentrations of Texanol. These results indicate that Texanol shares an interaction site with menthol. Overall, these findings suggest that careful interpretation is necessary when extrapolating rodent TRPA1-dependent toxicological effects to humans, especially with respect to the risk assessment of indoor air pollutants.

A Nested Monte Carlo Simulation Model for Enhancing Dynamic Air Pollution Risk Assessment

The risk assessment of air pollution is an essential matter in the area of air quality computing. It provides useful information supporting air quality (AQ) measurement and pollution control. The outcomes of the evaluation have societal and technical influences on people and decision-makers. The existing air pollution risk assessment employs different qualitative and quantitative methods. This study aims to develop an AQ-risk model based on the Nested Monte Carlo Simulation (NMCS) and concentrations of several air pollutant parameters for forecasting daily AQ in the atmosphere. The main idea of NMCS lies in two main parts, which are the Outer and Inner parts. The Outer part interacts with the data sources and extracts a proper sampling from vast data. It then generates a scenario based on the data samples. On the other hand, the Inner part handles the assessment of the processed risk from each scenario and estimates future risk. The AQ-risk model is tested and evaluated using real data sources representing crucial pollution. The data is collected from an Italian city over a period of one year. The performance of the proposed model is evaluated based on statistical indices, coefficient of determination (R2), and mean square error (MSE). R2 measures the prediction ability in the testing stage for both parameters, resulting in 0.9462 and 0.9073 prediction accuracy. Meanwhile, MSE produced average results of 9.7 and 10.3, denoting that the AQ-risk model provides a considerably high prediction accuracy.

Air pollution risk assessment related to fossil fuel-driven vehicles in megacities in China by employing the Bayesian network coupled with the Fault Tree method

Vehicle emissions have become one of the key pollution sources affecting air quality and human health in China's megacities. How to curb excess vehicle emissions has become a key pain point of urban air pollution prevention and control. This work tries to explore an effective integrated approach/framework to quantitatively assess the risk factors of excess vehicle emissions (EVE) and their impact on air quality for China's typical megacities. Bayesian Network is employed as the assessment tool by coupling with the Fault Tree method to curb the above problem for the first time. Four megacities (Beijing, Tianjin, Hangzhou, and Guangzhou) in China are selected as case studies, and the risk factors leading to EVE are identified to construct the Bayesian Network model. At the same time, some accurate quantisation algorithms of the occurrence probability of root nodes were proposed for the target megacities from 2014 to 2019. The analysis results show that the variation trend of the probability of EVE has a good positive correlation with the variation trend of air quality in some megacities. From 2014 to 2019, the no-occurrence probability of EVE in Beijing, Tianjin, and Hangzhou increased from 0.4972, 0.4973, and 0.6314 to 0.6491, 0.6846, and 0.7564; the good air quality rate increased from 47.1%, 47.9%, and 59.2%–65.8%, 60%, and 78.6%. Based on the developing trend of the historical data/information and considering the impact of new energy vehicles, the no-occurrence probability of EVE in Beijing and Tianjin is predicted to be increased from 0.6888 to 0.7929 in 2020 to 0.8561 and 0.8645 in 2025. This work may provide a novel approach and perspective that can realise accurate traceability of key risk factors, quantitative risk assessment and prediction function of urban vehicle emissions for sustainable development of China's megacities.

Environmental Health Risk Assessment of Air Pollutants in Online Motorcycle Taxi Drivers in the Special Capital Region of Jakarta

Introduction: Online motorcycle taxi drivers spend most of their time outside as either driving or waiting for their customers. Therefore, chances of exposure to various air pollutants are higher and may cause various health problems, especially the respiratory problems. Methods: This is a descriptive study that used the Environmental Health Risk Analysis method to estimate the Risk Quotient (RQ) from exposure to PM10, SO2, CO, O3, and NO2 in drivers. The RQ was calculated based on exposure concentrations from the Special Capital Region of Jakarta Environment Agency; daily working hours, working days in a year, and working period obtained from interviews; additionally, body weight measurement, reference concentration (RfC), and the default value of inhalation intake were also collected. The population of this study was adult online motorcycle taxi drivers who operate around areas which become the air quality measurement stations in the Special Capital Region of Jakarta with a total sample of 81 people. Results and Discussion: The RQ for all minimum, average, and maximum concentrations of SO2, CO, and NO2 were <1. While for the average and maximum concentrations of PM10 and the maximum concentration of O3, the RQ was >1. The safe concentrations, work duration, and the number of working days also surpassed the maximum safety limit levels. Conclusion: PM10 and O3 ambient exposures are categorized unsafe for drivers. Environmental health efforts are necessary to reduce the concentration of air pollutants, and the guidelines to reduce pollutants exposure should be provided for drivers.

Toxicological Mechanism of Individual Susceptibility to Formaldehyde-Induced Respiratory Effects.

Understanding the mechanisms of individual susceptibility to exposure to environmental pollutants has been a challenge in health risk assessment. Here, an integrated approach combining a CRISPR screen in human cells and epidemiological analysis was developed to identify the individual susceptibility to the adverse health effects of air pollutants by taking formaldehyde (FA) and the associated chronic obstructive pulmonary disease (COPD) as a case study. Among the primary hits of CRISPR screening of FA in human A549 cells, HTR4 was the only gene genetically associated with COPD susceptibility in global populations. However, the association between HTR4 and FA-induced respiratory toxicity is unknown in the literature. Adverse outcome pathway (AOP) network analysis of CRISPR screen hits provided a potential mechanistic link between activation of HTR4 (molecular initiating event) and FA-induced lung injury (adverse outcome). Systematic toxicology tests (in vitro and animal experiments) were conducted to reveal the HTR4-involved biological mechanisms underlying the susceptibility to adverse health effects of FA. Functionality and enhanced expression of HTR4 were required for susceptibility to FA-induced lung injury, and FA-induced epigenetic changes could result in enhanced expression of HTR4. Specific epigenetic and genetic characteristics of HTR4 were associated with the progression and prevalence of COPD, respectively, and these genetic risk factors for COPD could be potential biomarkers of individual susceptibility to adverse respiratory effects of FA. These biomarkers could be of great significance for defining subpopulations susceptible to exposure to FA and reducing uncertainty in the next-generation health risk assessment of air pollutants. Our study delineated a novel toxicological pathway mediated by HTR4 in FA-induced lung injury, which could provide a mechanistic understanding of the potential biomarkers of individual susceptibility to adverse respiratory effects of FA.

DNA damage, serum metabolomic alteration and carcinogenic risk associated with low-level air pollution

Outdoor air pollution has been classified as carcinogenic to humans (Group 1) for lung cancer, but the underlying mechanism and key toxic components remain incompletely understood. Since DNA damage and metabolite alterations are associated with cancer progression, exploring potential mechanisms linking air pollution and cancer might be meaningful. In this study, a real-time ambient air exposure system was established to simulate the real-world environment of adult male SD rats in Beijing from June 13th, 2018, to October 8th, 2018. 8-OHdG in the urine, γ-H2AX in the lungs and mtDNA copy number in the peripheral blood were analyzed to explore DNA damage at different levels. Serum non-targeted metabolomics analysis was performed. Pair-wise spearman was used to explore the correlation between DNA damage biomarkers and serum differential metabolites. Carcinogenic risks of heavy metals and PAHs via inhalation were assessed according to US EPA guidelines. Results showed that PM2.5 and O3 were the major air pollutants in the exposure group and not detected in the control group. Compared with control group, higher levels of 8-OHdG, mtDNA copy number, γ-H2AX and PCNA-positive nuclei cells were observed in the exposure group. Histopathological evaluation suggested ambient air induced alveolar wall thickening and inflammatory cell infiltration in lungs. Perturbed metabolic pathways identified included glycolysis/gluconeogenesis metabolism, purine and pyrimidine metabolism, etc. γ-H2AX was positively correlated with serum ADP, 3-phospho-D-glyceroyl phosphate and N-acetyl-D-glucosamine. The BaPeq was 0.120 ng/m3. Risks of Cr(VI), As, V, BaP, BaA and BbF were above 1 × 10−6. We concluded that low-level air pollution was associated with DNA damage and serum metabolomic alterations in rats. Cr(VI) and BaP were identified as key carcinogenic components in PM2.5. Our results provided experimental evidence for hazard identification and risk assessment of low-level air pollution.

A New Collaborative Multi-Agent Monte Carlo Simulation Model for Spatial Correlation of Air Pollution Global Risk Assessment

Air pollution risk assessment is complex due to dynamic data change and pollution source distribution. Air quality index concentration level prediction is an effective method of protecting public health by providing the means for an early warning against harmful air pollution. However, air quality index-based prediction is challenging as it depends on several complicated factors resulting from dynamic nonlinear air quality time-series data, such as dynamic weather patterns and the verity and distribution of air pollution sources. Subsequently, some minimal models have incorporated a time series-based predicting air quality index at a global level (for a particular city or various cities). These models require interaction between the multiple air pollution sensing sources and additional parameters like wind direction and wind speed. The existing methods in predicting air quality index cannot handle short-term dependencies. These methods also mostly neglect the spatial correlations between the different parameters. Moreover, the assumption of selecting the most recent part of the air quality time series is not valid considering that pollution is cyclic behavior according to various events and conditions due to the high possibility of falling into the trap of local minimum and poor generalization. Therefore, this paper proposes a new air pollution global risk assessment (APGRA) prediction model for an air quality index of spatial correlations to address these issues. The APGRA model incorporates an autoregressive integrated moving average (ARIMA), a Monte Carlo simulation, a collaborative multi-agent system, and a prediction algorithm for reducing air quality index prediction error and processing time. The proposed APGRA model is evaluated based on Malaysia and China real-world air quality datasets. The proposed APGRA model improves the average root mean squared error by 41%, mean and absolute error by 47.10% compared with the conventional ARIMA and ANFIS models.

The human health risk assessment of particulate air pollution (PM2.5 and PM10) in Romania

Air pollution, especially the concentration of particulate matter (PM2.5, PM10) is a major issue and is the biggest environmental risk for early death. In the present study, we aimed to estimate the human health risk and to describe the spatial and temporal variation of particulate matter in Romania between 2009 and 2018. The average concentration of PM2.5 and PM10 particulate matter in the eight studied regions varied between 17.01 and 22.91 µg m−3 and 23.02–33.29 µg m−3, while the PM2.5/PM10 ratio varied between 0.52 and 0.76, respectively. The relative risk generated by PM10 in all-cause mortality had a significant variation between the regions, a relative risk of 1.017 in case of Bucharest and1.025 for western regions, with an average of 1.020 ( ± 0.002). According to our observations, a positive relative risk was identified in the case of cardiopulmonary and lung cancer morbidity mainly attributed to PM2.5 exposure, hence the resulted risk for the country average values was 1.26 ( ± 0.023) and 1.42 ( ± 0.037), respectively. The results revealed that the excess risk and attributable fraction for cardiopulmonary mortality can be reduced by 26.7% and 21.0%. Analyzing the evolution of particulate matters and the possible health impacts of PM2.5 and PM10 in all region of Romania a strong positive correlation was observed. Since the distributions of PM in different region had significant variation, more investigation is required to understand and decipher the most important regional emission sources for each region. In order to address this issue an in-depth investigation should separately analyze the regional characteristics of air pollution.

A New Strategic Air Pollution Risk Assessment by Considering the Influence of Wind Regimes

A New Strategic Air Pollution Risk Assessment by Considering the Influence of Wind Regimes

Health Risk Assessment of Toxic and Harmful Air Pollutants Discharged by a Petrochemical Company in the Beijing-Tianjin-Hebei Region of China

Monitoring of toxic and hazardous air pollutants (HAPs) in a petrochemical company in the Beijing-Tianjin-Hebei region of China to assess the impact of HAPs on the health risks of workers in the petrochemical company. The samples were tested by solid-phase adsorption thermal desorption/gas chromatography-mass spectrometry (HJ734-2014), and the pollutant emission list was obtained. According to the pollutant emission inventory, it can be seen that benzene, toluene and xylene are the main components of toxic and harmful air pollutants emitted by the petrochemical enterprise. The method of combining actual monitoring and CALPUFF model prediction was used to evaluate the impact of the toxic and harmful air pollutants emitted by the enterprise on the health of workers. The risk characterization results show that when benzene is the maximum concentration value predicted by the model, it will pose a carcinogenic risk to the factory workers. Therefore, based on the results of this study, it is recommended not to allow residents to live within the predicted concentration range of the model. The results of this study can enable China’s oil refining industry to better understand the characteristics of pollutant emissions from petrochemical companies in the Beijing-Tianjin-Hebei region. Moreover, the results of this study can be used as a policy basis for improving the health of workers in petrochemical enterprises, and are of great significance to the protection of public health.