Regional inequalities in benzene exposures across the European petrochemical industry: A Bayesian multilevel modelling approach

What is the spatiotemporal pattern of benzene concentration spread over susceptible area surrounding the Hartman Park community, Houston, Texas?

The Hartman Park community in Houston, Texas-USA, is in a highly polluted area which poses significant risks to its predominantly Hispanic and lower-income residents. Surrounded by dense clustering of industrial facilities compounds health and safety hazards, exacerbating environmental and social inequalities. Such conditions emphasize the urgent need for environmental measures that focus on investigating ambient air quality. This study estimated benzene, one of the most reported pollutants in Hartman Park, using machine learning-based approaches. Benzene data was collected in residential areas in the neighborhood and analyzed using a combination of five machine-learning algorithms (i.e., XGBR, GBR, LGBMR, CBR, RFR) through a newly developed ensemble learning model. Evaluations on model robustness, overfitting tests, 10-fold cross-validation, internal and stratified validation were performed. We found that the ensemble model depicted about 98.7% spatial variability of benzene (Adj. R2 =0.987). Through rigorous validations, stability of model performance was confirmed. Several predictors that contribute to benzene were identified, including temperature, developed intensity areas, leaking petroleum storage tank, and traffic-related factors. Analyzing spatial patterns, we found high benzene spread over areas near industrial zones as well as in residential areas. Overall, our study area was exposed to high benzene levels and requires extra attention from relevant authorities.

Development and demonstration of a data visualization platform of short-term guidelines for ambient air levels of benzene during disaster response in Houston, Texas

Industrial disasters have caused hazardous air pollution and public health impacts. Response officials have developed limited exposure guidelines to direct them during the event; often, guidelines are outdated and may not represent relevant elevated-exposure periods. The 2019 Intercontinental Terminals Company (ITC) fire in Houston, Texas led to large-scale releases of benzene and presented a public health threat. This incident highlights the need for effective response and nimble, rapid public health communication. We developed a data-driven visualization tool to store, display, and interpret ambient benzene concentrations to assist health officials during environmental emergencies. Guidance values to interpret risk from acute exposure to benzene were updated using recent literature that also considers exposure periodicity. The visualization platform can process data from different sampling instruments and air monitors automatically, and displays information publicly in real time, along with the associated risk information and action recommendations. The protocol was validated by applying it retrospectively to the ITC event. The new guidance values are 6-30 times lower than those derived by the Texas regulatory agency. Fixed-site monitoring data, assessed using the protocol and revised thresholds, indicated that eight shelter-in-place and 17 air-quality alerts may have been considered. At least one of these shelter-in-place alerts corresponded to prolonged, elevated benzene concentrations (~1000 ppb). This new tool addresses essential gaps in the timely communication of air pollution measurements, provides context to understand potential health risks from exposure to benzene, and provides a clear protocol for local officials in responding to industrial air releases of benzene. Integr Environ Assess Manag 2024;20:533-546. © 2023 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

Improving the adsorption performance of non-polar benzene vapor by using lignin-based activated carbon

Both indoor and outdoor contamination continually contain benzene vapor. It has primary concerns about long-term health risks to the living environment. Benzene is a crucial airborne pollutant in the environment due to its apparent acute toxicity, high volatility, and poor degradability. It is especially urgent to restrain benzene emissions due to the persistent concentration increase and stringent processes. Benzene adsorption is a highly efficient mechanism with low cost, low energy consumption, and a simple process. In this study, biomass-derived porous carbon materials (TCACs) were synthesized by pyrolysis activation combined with H3PO4, HNO3, and HCl. TCAC44 has the best activation conclusion, showing that surface area and pore volume were 1107 m2/g and 0.58 cm3/g treated with H3PO4 and so was chosen for subsequent benzene adsorption/desorption tests. The adsorption capacities of benzene for TCAC44 were increased from 58 mg/g for 35 °C + 95% RH to 121 mg/g for 25 °C + 15% RH and presented a higher adsorption capacity of benzene than TCAC101 and TCAC133. Otherwise, well recyclability of TCAC44 was revealed as the benzene adsorption capacity reductions were 22.49% after five adsorption-desorption cycles. Furthermore, the present study established the property-application relationships to promote and encourage future research on the newly synthesized innovative TCAC44 for benzene removal.

Long-term exposure to air pollution and COVID-19 severity: A cohort study in Greater Manchester, United Kingdom

Exposure to outdoor air pollution may affect incidence and severity of coronavirus disease 2019 (COVID-19). In this retrospective cohort based on patient records from the Greater Manchester Care Records, all first COVID-19 cases diagnosed between March 1, 2020 and May 31, 2022 were followed until COVID-19 related hospitalization or death within 28 days. Long-term exposure was estimated using mean annual concentrations of particulate matter with diameter ≤2.5 μm (PM_2.5), ≤10 μm (PM₁₀), nitrogen dioxide (NO₂), ozone (O₃), sulphur dioxide (SO₂) and benzene (C₆H₆) in 2019 using a validated air pollution model developed by the Department for Environment, Food and Rural Affairs (DEFRA). The association of long-term exposure to air pollution with COVID-19 hospitalization and mortality were estimated using multivariate logistic regression models after adjusting for potential individual, temporal and spatial confounders. Significant positive associations were observed between PM_2.5, PM_10, NO_2, SO_2, benzene and COVID-19 hospital admissions with odds ratios (95% Confidence Intervals [CI]) of 1.27 (1.25-1.30), 1.15 (1.13-1.17), 1.12 (1.10-1.14), 1.16 (1.14-1.18), and 1.39 (1.36-1.42), (per interquartile range [IQR]), respectively. Significant positive associations were also observed between PM_2.5, PM₁₀, SO₂, or benzene and COVID-19 mortality with odds ratios (95% CI) of 1.39 (1.31-1.48), 1.23 (1.17-1.30), 1.18 (1.12-1.24), and 1.62 (1.52-1.72), per IQR, respectively. Individuals who were older, overweight or obese, current smokers, or had underlying comorbidities showed greater associations between all pollutants of interest and hospital admission, compared to the corresponding groups. Long-term exposure to air pollution is associated with developing severe COVID-19 after a positive SARS-CoV-2 infection, resulting in hospitalization or death.

Examining the risk factors for overweight and obesity among women in Ghana: A multilevel perspective

Overweight/obesity prevalence is on the increase in epidemic proportions across Low- and Middle-Income countries (LMICs). The public health burden associated with obesity/overweight cannot be underestimated due to its association with chronic health outcomes. This study investigated the individual- and community level risk factors for obesity/overweight among reproductive women. The data used consist of 4393 reproductive women and form part of the 2014 Ghana Demographic and Health Survey (GDHS). Information on these women are clustered within 427 communities. A 2-tier random intercept multilevel logistic model was used to assess the effect of individual- and community level factors on the likelihood of a woman to be obese/overweight. The obesity/overweight prevalence among reproductive women was estimated to be 35.5% (95% CI: 34.04, 36.90%), which significantly differed across clusters. Most at risk were women from middle-income households (aOR = 2.85; 95% CI: 2.28, 3.56), upper-income households (aOR = 5.019, 95% CI: 3.85, 6.55), attaining secondary education (aOR = 1.74; 95% CI: 1.41, 2.16), and higher (aOR = 1.63; 95% CI: 1.14, 2.33), old age (20-29 years (aOR = 4.26; 95% CI: 3.142,5.78); 30-39 years (aOR = 8.59; 95% CI: 6.15, 12.00); 40-49 years (aOR = 12.81; 95% CI: 9.10, 18.16)). Significant differences in the probability of being overweight/obese between different communities were observed (MOR = 1.39). The high prevalence of overweight/obesity requires urgent public health interventions to prevent future public health crises. Efforts to strengthen the healthcare system, encourage lifestyle modification, and public health education are needed to solidify the gains of ensuring a healthy population by 2030 (SDG 3).

Characterizing vulnerabilities to climate change across the United States

Climate change will cause a range of related risks, including increases in infectious and chronic disease, intensified social and economic stresses, and more frequent extreme weather events. Vulnerable groups will be disproportionately affected due to greater exposure to climate risks and lower ability to prepare, adapt, and recover from their effects. Better understanding of the intersection of vulnerability and climate change risks is required to identify the most important drivers of future climate risks and effectively build resilience and deploy targeted adaptation efforts. Incorporating community stakeholder input, we identified and integrated available public health, social, economic, environmental, and climate data in the United States (U.S.), comprising 184 indicators, to develop a Climate Vulnerability Index (CVI) composed of four baseline vulnerabilities (health, social/economic, infrastructure, and environment) and three climate change risks (health, social/economic, extreme events). We find that the vulnerability to and risks from climate change are highly heterogeneous across the U.S. at the census tract scale, and geospatially cluster into complementary areas with similar climate risks but differing baseline vulnerabilities. Our results therefore demonstrate that not only are climate change risks both broadly and variably distributed across the U.S., but also that existing disparities are often further exacerbated by climate change. The CVI thus lays a data-driven, scientific foundation for future research on the intersection of climate change risks with health and other inequalities, while also identifying health impacts of climate change as the greatest research gap. Moreover, given U.S. government initiatives surrounding climate and equity, the CVI can be instrumental in empowering communities and policymakers to better prioritize resources and target interventions, providing a template for addressing local-scale climate and environmental justice globally.

Living proximity to petrochemical industries and the risk of attention-deficit/hyperactivity disorder in children

Evidence regarding the negative neurodevelopmental effects of compound exposure to petrochemicals remains limited. We aimed to evaluate the association between exposure to petrochemical facilities and generated emissions during early life and the risk of attention-deficit/hyperactivity disorder (ADHD) development in children. We conducted a population-based birth cohort study using the 2004 to 2014 Taiwanese Birth Certificate Database and verified diagnoses of ADHD using the National Health Insurance Database. The level of petrochemical exposure in each participant's residential township was evaluated using the following 3 measurements: distance to the nearest petrochemical industrial plant (PIP), petrochemical exposure probability (accounting for monthly prevailing wind measurements), and monthly benzene concentrations estimated using kriging-based land-use regression models. We applied Cox proportional hazard models to evaluate the association. During the study period, 48,854 out of 1,863,963 children were diagnosed as having ADHD. The results revealed that residents of townships in close proximity to PIPs (hazard ratio [HR] = 1.20, 95% confidence interval [CI]: 1.16-1.23, <3 vs. ≥10 km), highly affected by petrochemical-containing prevailing winds (HR = 1.12, 95% CI: 1.08-1.16, ≥40% vs. <10%), and with high benzene concentrations (HR = 1.26, 95% CI: 1.23-1.29, ≥0.75 vs. <0.55 ppb) were consistently associated with the increased risk of ADHD development in children. The findings of the sensitivity analysis remained robust, particularly for the 2004 to 2009 birth cohort and for models accounting for a longer duration of postnatal exposure. This work provided clear evidence that living near petrochemical plants increases the risk of ADHD development in children. Further studies are warranted to confirm our findings.

Distributive justice in environmental health hazards from industrial contamination: A systematic review of national and near-national assessments of social inequalities

Communities where polluting human activities are sited often show disadvantage in terms of social and economic variables. Environmental distributive justice studies seek to identify common characteristics in exposed populations and highlight the presence of environmental inequalities. We have conducted a review of the existing literature about justice in the distribution of health hazards from industrial pollution. We included papers investigating associations between social disadvantage and contamination through assessments at national or macro-area level. From each study we extracted: indicators for the social determinants of exposed communities (classified according to PROGRESS-plus categories); definition and measurement of environmental hazard (as either proximity to contamination sources, exposure to emissions or health impacts from pollutants); study design and methods; significant results. We retrieved 45 eligible articles. Most publications were from USA and had a nationwide scope with data at municipal/sub-municipal scale. Socioeconomic position and race/ethnicity were the social determinants most often explored, followed by occupation and education; air pollution was the commonest sort of contamination, while proximity prevailed as measurement of hazard. All papers found significant associations between social dimensions and health hazard from industrial contamination: the majority of associations supported an increased burden on vulnerable categories, especially ethnic minorities and unemployed - however, several relationships were found in the opposite direction or in both ways, particularly with wealth and education, reflecting a mixed reality where potential discrimination in siting decisions coexists with socioeconomic benefits for nearby communities due to industrial development. Assessments of environmental distributive justice are lacking in most countries and those that are conducted show vast methodological heterogeneity. We recommend consistency in models and indicators, the inclusion of female-led households among indicators of social disadvantage, and the adoption of a small scale to elicit significant findings and provide meaningful policy action.

The presence of Superfund sites as a determinant of life expectancy in the United States

Superfund sites could affect life expectancy (LE) via increasing the likelihood of exposure to toxic chemicals. Here, we assess to what extent such presence could alter the LE independently and in the context of sociodemographic determinants. A nationwide geocoded statistical modeling at the census tract level was undertaken to estimate the magnitude of impact. Results showed a significant difference in LE among census tracts with at least one Superfund site and their neighboring tracts with no sites. The presence of a Superfund site could cause a decrease of -0.186 ± 0.027 years in LE. This adverse effect could be as high as -1.22 years in tracts with Superfund sites and high sociodemographic disadvantage. Specific characteristics of Superfund sites such as being prone to flooding and the absence of a cleanup strategy could amplify the adverse effect. Furthermore, the presence of Superfund sites amplifies the negative influence of sociodemographic factors at lower LEs.

Does living close to a petrochemical complex increase the adverse psychological effects of the COVID-19 lockdown?

The petrochemical industry has made the economic development of many local communities possible, increasing employment opportunities and generating a complex network of closely-related secondary industries. However, it is known that petrochemical industries emit air pollutants, which have been related to different negative effects on mental health. In addition, many people around the world are being exposed to highly stressful situations deriving from the COVID-19 pandemic and the lockdowns adopted by national and regional governments. The present study aims to analyse the possible differential effects on various psychological outcomes (stress, anxiety, depression and emotional regulation strategies) stemming from the COVID-19 pandemic and consequent lockdown experienced by individuals living near an important petrochemical complex and subjects living in other areas, nonexposed to the characteristic environmental pollutants emitted by these kinds of complex. The sample consisted of 1607 subjects who answered an ad hoc questionnaire on lockdown conditions, the Perceived Stress Scale (PSS), the Hospital Anxiety and Depression Scale (HADS), the Barratt Impulsivity Scale (BIS) and the Emotional Regulation Questionnaire (ERQ). The results indicate that people living closer to petrochemical complexes reported greater risk perception [K = 73.42, p < 0.001, with a medium size effect (η2 = 0.061)]. However, no significant relationship between psychological variables and proximity to the focus was detected when comparing people living near to or far away from a chemical/petrochemical complex. Regarding the adverse psychological effects of the first lockdown due to COVID-19 on the general population in Catalonia, we can conclude that the conditions included in this survey were mainly related to changes in the participants' impulsivity levels, with different total impulsivity scores being obtained if they had minors in their care (p<0.001), if they had lost their jobs, if they were working (p<0.001), if they were not telecommuting (p<0.001), if they went out to work (p<0.001) or if they established routines (p = 0.009). However, we can also be fairly certain that the economic effects are going to be worse than those initially detected in this study. More research will be necessary to corroborate our results.

Evaluation of the physico-chemical properties of hydrocarbons-exposed bacterial biomass

In the efforts for the removal of hazardous materials from the environment biological processes are a valuable tool. Although much attention has been paid to the changes in bacteria at the omics level, another, physical-chemical perspective on the issue is essential, as little is known of microbial response to continuous exposition on harmful substances. This study provides in-depth characterization of the physical-chemical parameters of bacterial biomass after hydrocarbons exposure. To provide comparability of the harmful effects of chlorotoluenes and xylenes non-exposed and 12-months hydrocarbons exposed cells were analyzed, using the advanced spectrometric methods, inverse gas chromatography and low-temperature N2 sorption to evaluate acid-base as well as dispersive properties of the studied biomass. Presented results indicate P. fluorescens B01 cells strategy aimed at protecting the cell, thus lowering its' biodegradation efficiency as a result of metabolic stress. The outcome of the study was that prolonged exposure to pollutants might reduce the bioavailability of hydrocarbons to bacteria cells, and consequently decrease the effectiveness of decontamination of polluted sites by indigenous microorganisms.