Fine particulate air pollution and human mortality: 25+ years of cohort studies

Development of a Unified IoT Platform for Assessing Meteorological and Air Quality Data in a Tropical Environment

In developing nations, outdated technologies and sulfur-rich heavy fossil fuel usage are major contributors to air pollution, affecting urban air quality and public health. In addition, the limited resources hinder the adoption of advanced monitoring systems crucial for informed public health policies. This study addresses this challenge by introducing an affordable internet of things (IoT) monitoring system capable of tracking atmospheric pollutants and meteorological parameters. The IoT platform combines a Bresser 5-in-1 weather station with a previously developed air quality monitoring device equipped with Alphasense gas sensors. Utilizing MQTT, Node-RED, InfluxDB, and Grafana, a Raspberry Pi collects, processes, and visualizes the data it receives from the measuring device by LoRa. To validate system performance, a 15-day field campaign was conducted in Santa Clara, Cuba, using a Libelium Smart Environment Pro as a reference. The system, with a development cost several times lower than Libelium and measuring a greater number of variables, provided reliable data to address air quality issues and support health-related decision making, overcoming resource and budget constraints. The results showed that the IoT architecture has the capacity to process measurements in tropical conditions. The meteorological data provide deeper insights into events of poorer air quality.

Geospatial Science for the Environmental Epidemiology of Cancer in the Exposome Era

Geospatial science is the science of location or place that harnesses geospatial tools, such as geographic information systems (GIS), to understand the features of the environment according to their locations. Geospatial science has been transformative for cancer epidemiologic studies through enabling large-scale environmental exposure assessments. As the research paradigm for the exposome, or the totality of environmental exposures across the life course, continues to evolve, geospatial science will serve a critical role in determining optimal practices for how to measure the environment as part of the external exposome. The objectives of this article are to provide a summary of key concepts, present a conceptual framework that illustrates how geospatial science is applied to environmental epidemiology in practice and through the lens of the exposome, and discuss the following opportunities for advancing geospatial science in cancer epidemiologic research: enhancing spatial and temporal resolutions and extents for geospatial data; geospatial methodologies to measure climate change factors; approaches facilitating the use of patient addresses in epidemiologic studies; combining internal exposome data and geospatial exposure models of the external exposome to provide insights into biological pathways for environment-disease relationships; and incorporation of geospatial data into personalized cancer screening policies and clinical decision making.

Ambient particulate matter air pollution exposure and ovarian cancer incidence in the USA: An ecological study

OBJECTIVE

To investigate associations between air particulate matter of ≤2.5 μm in diameter (PM2.5 ) and ovarian cancer.

DESIGN

County-level ecological study.

SETTING

Surveillance, epidemiology, and end results from a collection of state-level cancer registries across 744 counties. Data from the Environmental Protection Agency's network for PM2.5 monitoring was used to calculate trailing 5- and 10-year PM2.5 county-level values. County-level data on demographic characteristics were obtained from the American Community Survey.

POPULATION

A total of 98 751 patients with histologically confirmed ovarian cancer as a primary malignancy from 2000 to 2016.

METHODS

Generalised linear regression models were developed to estimate the association between PM2.5 and PM10 levels, over 5- and 10-year periods of exposure, and ovarian cancer risk, after accounting for county-level covariates.

MAIN OUTCOME MEASURES

Risk ratios for associations between ovarian cancer (both overall and specifically epithelial ovarian cancer) and PM2.5 levels.

RESULTS

For the 744 counties included, the average PM2.5 level from 1990 through 2018 was 11.75 μg/m3 (SD = 3.7) and the average PM10 level was 22.7 μg/m3 (SD = 5.7). After adjusting for county-level covariates, the overall annualised ovarian cancer incidence was significantly associated with increases in 5-year PM2.5 (RR = 1.11 per 10 units (μg/m3 ) increase, 95% CI 1.06-1.16). Similarly, when the analysis was limited to epithelial cell tumours and adjusted for county-level covariates there was a significant association with trailing 5-year PM2.5 exposure models (RR = 1.12 per 10 units increase, 95% CI 1.08-1.17). Likewise, 10-year PM2.5 exposure was associated with ovarian cancer overall and with epithelial ovarian cancer.

CONCLUSIONS

Higher county-level ambient PM2.5 levels are associated with 5- and 10-year incidences of ovarian cancer, as measurable in an ecological study.

Health benefits of vehicle electrification through air pollution in Shanghai, China

Vehicle electrification has been recognized for its potential to reduce emissions of air pollutants and greenhouse gases in China. Several studies have estimated how national-level policies of electric vehicle (EV) adoption might bring very large environmental and public health benefits from improved air quality to China. However, large-scale adoption is very costly, some regions derive more benefits from large-scale EV adoption than others, and the benefits of replacing internal combustion engines in specific cities are less known. Therefore, it is important for policymakers to design incentives based on regional characteristics - especially for megacities like Shanghai - which typically suffer from worse air quality and where a larger population is exposed to emissions from vehicles. Over the past five years, Shanghai has offered substantial personal subsidies for passenger EVs to accelerate its electrification efforts. Still, it remains uncertain whether EV benefits justify the strength of incentives. The purpose of our study is to evaluate the health and climate benefits of replacing light-duty gasoline vehicles (ICEVs) with battery EVs in the city of Shanghai. We assess health impacts due to ICEV emissions of primary fine particulate matter, NOx, and volatile organic compounds, and to powerplant emissions of NOx and SO2 due to EV charging. We incorporate climate benefits from reduced greenhouse gas emissions based on existing research. We find that the benefit of replacing the average ICEV with an EV in Shanghai is US$6400 (2400-14,700), with health impacts of EVs about 20 times lower than the average ICEV. Larger benefits ensue if older ICEVs are replaced, but replacing newer China ICEVs also achieves positive health benefits. As Shanghai plans to stop providing personal subsidies for EV purchases in 2024, our results show that EVs achieve public health and climate benefits and can help inform policymaking strategies in Shanghai and other megacities.

Ambient dust pollution with all-cause, cardiovascular and respiratory mortality: A systematic review and meta-analysis

A severe health crisis has been well-documented regarding dust particle exposure. We aimed to present the risk of all-cause, cardiovascular, and respiratory mortality due to particulate matter (PM) exposure during non-dust and dust storm events by performing a meta-analysis. A systematic review of the literature was conducted by an online search of the databases (Google Scholar, Web of Science, Scopus, and PubMed) with no restrictions according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines until December 2022. We performed a random-effects model to compute the pooled rate ratio (RR) of mortality with 95 % confidence intervals (CI). The Office of Health Assessment and Translation (OHAT) risk of bias rating tool was prepared to assess the quality of the individual study. The registration number in PROSPERO was CRD42023423212. We found a 16 % (95 % CI: 0.7 %, 24 %) increase in all-cause, 25 % (95 % CI: 14 %, 37 %) increase in cardiovascular, and 18 % (95 % CI: 13 %, 22 %) increase in respiratory mortality per 10 μg/m3 increment in dust exposure. Furthermore, the RRs per 10 μg/m3 increment in PM10-2.5 were 1.046 (95 % CI: 1.019, 1.072)¸ 1.085 (95 % CI: 1.045, 1.0124), and 1.089 (95 % CI: 0.939, 1.24) for all-cause, cardiovascular, and respiratory mortality, respectively. PM10 during dust days significantly increased the all-cause (1.013, 95 % CI: 1.007, 1.018) cardiovascular mortality risk (1.014, 95 % CI: 1.009, 1.02). We also found significant evidence for all-cause, cardiovascular, and respiratory mortality among females and the elderly age group due to dust particle (PM10-2.5 and PM10) exposure. Our results provided significant evidence about high concentrations of PM10-2.5 and PM10 during dust storm events related to mortality risk.

Molecular mechanisms underlying NLRP3 inflammasome activation and IL-1β production in air pollution fine particulate matter (PM2.5)-primed macrophages

Exposure to air pollution fine particulate matter (PM2.5) aggravates respiratory and cardiovascular diseases. It has been proposed that PM2.5 uptake by alveolar macrophages promotes local inflammation that ignites a systemic response, but precise underlying mechanisms remain unclear. Here, we demonstrate that PM2.5 phagocytosis leads to NLRP3 inflammasome activation and subsequent release of the pro-inflammatory master cytokine IL-1β. Inflammasome priming and assembly was time- and dose-dependent in inflammasome-reporter THP-1-ASC-GFP cells, and consistent across PM2.5 samples of variable chemical composition. While inflammasome activation was promoted by different PM2.5 surrogates, significant IL-1β release could only be observed after stimulation with transition-metal rich Residual Oil Fly Ash (ROFA) particles. This effect was confirmed in primary human monocyte-derived macrophages and murine bone marrow-derived macrophages (BMDMs), and by confocal imaging of inflammasome-reporter ASC-Citrine BMDMs. IL-1β release by ROFA was dependent on the NLRP3 inflammasome, as indicated by lack of IL-1β production in ROFA-exposed NLRP3-deficient (Nlrp3-/-) BMDMs, and by specific NLRP3 inhibition with the pharmacological compound MCC950. In addition, while ROFA promoted the upregulation of pro-inflammatory gene expression and cytokines release, MCC950 reduced TNF-α, IL-6, and CCL2 production. Furthermore, inhibition of TNF-α with a neutralizing antibody decreased IL-1β release in ROFA-exposed BMDMs. Using electron tomography, ROFA particles were observed inside intracellular vesicles and mitochondria, which showed signs of ultrastructural damage. Mechanistically, we identified lysosomal rupture, K+ efflux, and impaired mitochondrial function as important prerequisites for ROFA-mediated IL-1β release. Interestingly, specific inhibition of superoxide anion production (O2•-) from mitochondrial respiratory Complex I, but not III, blunted IL-1β release in ROFA-exposed BMDMs. Our findings unravel the mechanism by which PM2.5 promotes IL-1β release in macrophages and provide a novel link between innate immune response and exposure to air pollution PM2.5.

Reconstructing individual-level exposures in cohort analyses of environmental risks: an example with the UK Biobank

Recent developments in linkage procedures and exposure modelling offer great prospects for cohort analyses on the health risks of environmental factors. However, assigning individual-level exposures to large population-based cohorts poses methodological and practical problems. In this contribution, we illustrate a linkage framework to reconstruct environmental exposures for individual-level epidemiological analyses, discussing methodological and practical issues such as residential mobility and privacy concerns. The framework outlined here requires the availability of individual residential histories with related time periods, as well as high-resolution spatio-temporal maps of environmental exposures. The linkage process is carried out in three steps: (1) spatial alignment of the exposure maps and residential locations to extract address-specific exposure series; (2) reconstruction of individual-level exposure histories accounting for residential changes during the follow-up; (3) flexible definition of exposure summaries consistent with alternative research questions and epidemiological designs. The procedure is exemplified by the linkage and processing of daily averages of air pollution for the UK Biobank cohort using gridded spatio-temporal maps across Great Britain. This results in the extraction of exposure summaries suitable for epidemiological analyses of both short and long-term risk associations and, in general, for the investigation of temporal dependencies. The linkage framework presented here is generally applicable to multiple environmental stressors and can be extended beyond the reconstruction of residential exposures. IMPACT: This contribution describes a linkage framework to assign individual-level environmental exposures to population-based cohorts using high-resolution spatio-temporal exposure. The framework can be used to address current limitations of exposure assessment for the analysis of health risks associated with environmental stressors. The linkage of detailed exposure information at the individual level offers the opportunity to define flexible exposure summaries tailored to specific study designs and research questions. The application of the framework is exemplified by the linkage of fine particulate matter (PM2.5) exposures to the UK Biobank cohort.

Measuring magnetic susceptibility of particulate matter collected on filters

The magnetic susceptibility (κ) of particulate matter (PM) is a useful tool in estimation concentration of iron-rich particles and provides useful information on the emission sources and pathways of spread of PM in the atmosphere. However, there is currently no established protocol for measuring the magnetic susceptibility of PM collected on filters used in standard monitoring of PM concentration. This paper presents a step-by-step process for collecting PM on filters in automatic samplers and measuring their κ. The procedure outlines requirements for data quality, measurement uncertainty, exposure time and conditions, and the amount of material collected on the filters. The study analyzed a 2-year dataset of magnetic susceptibility measurements by MFK-1 kappabridge (Agico, Czech Republic) for PM10 and PM2.5 collected at two locations, Warsaw and Cracow, in Poland using low-volume PM samplers. By strictly following the procedure for conditioning filters, measuring magnetic susceptibility and mass of PM, the study found that it is possible to obtain repeatable data with good measurement accuracy and acceptable errors. This makes magnetic susceptibility an additional reliable parameter for tracking of emission sources of iron-rich particles. Successful implementation of this magnetic method as a standard procedure for monitoring PM in addition to the PM mass collected on filters could be used to analyze sources of emission of Fe-particles and their contribution to the PM mass, especially in urban and industrial environments.

Hyper-local to regional exposure contrast of source-resolved PM2.5 components across the contiguous United States: implications for health assessment

BACKGROUND

Improved understanding of sources and processes that drive exposure contrast of fine particulate matter (PM2.5) is essential for designing and interpreting epidemiological study outcomes.

OBJECTIVE

We investigate the contribution of various sources and processes to PM2.5 exposure contrasts at different spatial scales across the continental United States.

METHODS

We consider three cases: exposure contrast within a metro area, nationwide exposure contrast with high spatial resolution, and nationwide exposure contrast with low spatial resolution. Using national empirical model estimates of source- and chemically specific PM2.5 concentration predictions, we quantified the contribution of various sources and processes to PM2.5 exposure contrasts in these three cases.

RESULTS

At the metro level (i.e., metropolitan statistical area; MSA), exposure contrasts of PM2.5 vary between -1.8 to 1.4 µg m-3 relative to the MSA-mean with about 50% of within-MSA exposure contrast of PM2.5 caused by cooking and mobile source primary PM2.5. For the national exposure contrast at low-resolution (i.e., using MSA-average mean concentrations), exposure contrasts (relative to the national mean: -3.9 to 3.2 µg m-3) are larger than within an MSA with ~80% of the variation due to secondary PM2.5. National exposure contrast at high resolution (census block) has the largest absolute range (relative to the national mean: -4.7 to 3.7 µg m-3) due to both regional and intra-urban contributions; on average, 65% of the national exposure contrast is due to secondary PM2.5 with the remaining from the primary PM2.5 (cooking and mobile source 26%, other 9%).

IMPACT

Our study provides a comprehensive analysis of the sources and processes that contribute to exposure contrasts of PM2.5 across different geographic areas in the US. For the first time on a national scale, we used high spatial resolution source-specific exposure estimates to identify the primary contributors to PM2.5 exposure contrasts. The study also highlights the advantages of different study designs for investigating the health impacts of specific PM2.5 components. The findings provide novel insights that can inform public health policies aimed at reducing PM2.5 exposure and advance the understanding of the epidemiological study outcomes.

Particulate matter 10 induces oxidative stress and apoptosis in rhesus macaques skin fibroblast

Background

Particulate matter (PM) is a major air pollutant that affects human health worldwide. PM can pass through the skin barrier, thus causing skin diseases such as heat rash, allergic reaction, infection, or inflammation. However, only a few studies have been conducted on the cytotoxic effects of PM exposure on large-scale animals. Therefore, herein, we investigated whether and how PM affects rhesus macaque skin fibroblasts.

Methods

Rhesus macaque skin fibroblasts were treated with various concentrations of PM10 (1, 5, 10, 50, and 100 μg/mL) and incubated for 24, 48, and 72 h. Then, cell viability assay, TUNEL assay, and qRT-PCR were performed on the treated cells. Further, the reactive oxygen species, glutathione, and cathepsin B levels were determined. The MTT assay revealed that PM10 (>50 μg/mL) proportionately reduced the cell proliferation rate.

Results

PM10 treatment increased TUNEL-positive cell numbers, following the pro-apoptosis-associated genes (CASP3 and BAX) and tumor suppressor gene TP53 were significantly upregulated. PM10 treatment induced reactive oxidative stress. Cathepsin B intensity was increased, whereas GSH intensity was decreased. The mRNA expression levels of antioxidant enzyme-related genes (CAT, GPX1 and GPX3) were significantly upregulated. Furthermore, PM10 reduced the mitochondrial membrane potential. The mRNA expression of mitochondrial complex genes, such as NDUFA1, NDUFA2, NDUFAC2, NDUFS4, and ATP5H were also significantly upregulated. In conclusion, these results showed that PM10 triggers apoptosis and mitochondrial damage, thus inducing ROS accumulation. These findings provide potential information on the cytotoxic effects of PM10 treatment and help to understand the mechanism of air pollution-induced skin diseases.

Long-term exposure to air pollution and mortality in Scotland: A register-based individual-level longitudinal study

BACKGROUND

Air pollution is associated with several adverse health outcomes. However, heterogeneity in the size of effect estimates between cohort studies for long-term exposures exist and pollutants like SO2 and mental/behavioural health outcomes are little studied. This study examines the association between long-term exposure to multiple ambient air pollutants and all-cause and cause-specific mortality from both physical and mental illnesses.

METHODS

We used individual-level administrative data from the Scottish-Longitudinal-Study (SLS) on 202,237 individuals aged 17 and older, followed between 2002 and 2017. The SLS dataset was linked to annual concentrations of NO2, SO2, and particulate-matter (PM10, PM2.5) pollution at 1 km2 spatial resolution using the individuals' residential postcode. We applied survival analysis to assess the association between air pollution and all-cause, cardiovascular, respiratory, cancer, mental/behavioural disorders/suicides, and other-causes mortality.

RESULTS

Higher all-cause mortality was associated with increasing concentrations of PM2.5, PM10, NO2, and SO2 pollutants. NO2, PM10, and PM2.5 were also associated with cardiovascular, respiratory, cancer and other-causes mortality. For example, the mortality hazard from respiratory diseases was 1.062 (95%CI = 1.028-1.096), 1.025 (95%CI = 1.005-1.045), and 1.013 (95%CI = 1.007-1.020) per 1 μg/m3 increase in PM2.5, PM10 and NO2 pollutants, respectively. In contrast, mortality from mental and behavioural disorders was associated with 1 μg/m3 higher exposure to SO2 pollutant (HR = 1.042; 95%CI = 1.015-1.069).

CONCLUSION

This study revealed an association between long-term (16-years) exposure to ambient air pollution and all-cause and cause-specific mortality. The results suggest that policies and interventions to enhance air quality would reduce the mortality hazard from cardio-respiratory, cancer, and mental/behavioural disorders in the long-term.

Early life PM2.5 exposure, childhood cognitive ability and mortality between age 11 and 86: A record-linkage life-course study from Scotland

BACKGROUND

Living in areas with high air pollution concentrations is associated with all-cause and cause-specific mortality. Exposure in sensitive developmental periods might be long-lasting but studies with very long follow-up are rare, and mediating pathways between early life exposure and life-course mortality are not fully understood.

METHODS

Data were drawn from the Scottish Longitudinal Study Birth Cohort of 1936, a representative record-linkage study comprising 5% of the Scottish population born in 1936. Participants had valid age 11 cognitive ability test scores along with linked mortality data until age 86. Fine particle (PM2.5) concentrations estimated with the EMEP4UK atmospheric chemistry transport model were linked to participants' residential address derived from the National Identity Register in 1939 (age 3). Confounder-adjusted Cox regression estimated associations between PM2.5 and mortality; regression-based causal mediation analysis explored mediation through childhood cognitive ability.

RESULTS

The final sample consisted of 2734 individuals with 1608 deaths registered during the 1,833,517 person-months at risk follow-up time. Higher early life PM2.5 exposure increased the risk of all-cause mortality (HR = 1.03, 95% CI: 1.01-1.04 per 10 μg m-3 increment), associations were stronger for mortality between age 65 and 86. PM2.5 increased the risk of cancer-related mortality (HR = 1.05, 95% CI: 1.02-1.08), especially for lung cancer among females (HR = 1.11, 95% CI: 1.02-1.21), but not for cardiovascular and respiratory diseases. Higher PM2.5 in early life (≥50 μg m-3) was associated with lower childhood cognitive ability, which, in turn, increased the risk of all-cause mortality and mediated 25% of the total associations.

CONCLUSIONS

In our life-course study with 75-year of continuous mortality records, we found that exposure to air pollution in early life was associated with higher mortality in late adulthood, and that childhood cognitive ability partly mediated this relationship. Findings suggest that past air pollution concentrations will likely impact health and longevity for decades to come.

Air pollution deaths attributable to fossil fuels: observational and modelling study

OBJECTIVES

To estimate all cause and cause specific deaths that are attributable to fossil fuel related air pollution and to assess potential health benefits from policies that replace fossil fuels with clean, renewable energy sources.

DESIGN

Observational and modelling study.

METHODS

An updated atmospheric composition model, a newly developed relative risk model, and satellite based data were used to determine exposure to ambient air pollution, estimate all cause and disease specific mortality, and attribute them to emission categories.

DATA SOURCES

Data from the global burden of disease 2019 study, observational fine particulate matter and population data from National Aeronautics and Space Administration (NASA) satellites, and atmospheric chemistry, aerosol, and relative risk modelling for 2019.

RESULTS

Globally, all cause excess deaths due to fine particulate and ozone air pollution are estimated at 8.34 million (95% confidence interval 5.63 to 11.19) deaths per year. Most (52%) of the mortality burden is related to cardiometabolic conditions, particularly ischaemic heart disease (30%). Stroke and chronic obstructive pulmonary disease both account for 16% of mortality burden. About 20% of all cause mortality is undefined, with arterial hypertension and neurodegenerative diseases possibly implicated. An estimated 5.13 million (3.63 to 6.32) excess deaths per year globally are attributable to ambient air pollution from fossil fuel use and therefore could potentially be avoided by phasing out fossil fuels. This figure corresponds to 82% of the maximum number of air pollution deaths that could be averted by controlling all anthropogenic emissions. Smaller reductions, rather than a complete phase-out, indicate that the responses are not strongly non-linear. Reductions in emission related to fossil fuels at all levels of air pollution can decrease the number of attributable deaths substantially. Estimates of avoidable excess deaths are markedly higher in this study than most previous studies for these reasons: the new relative risk model has implications for high income (largely fossil fuel intensive) countries and for low and middle income countries where the use of fossil fuels is increasing; this study accounts for all cause mortality in addition to disease specific mortality; and the large reduction in air pollution from a fossil fuel phase-out can greatly reduce exposure.

CONCLUSION

Phasing out fossil fuels is deemed to be an effective intervention to improve health and save lives as part the United Nations' goal of climate neutrality by 2050. Ambient air pollution would no longer be a leading, environmental health risk factor if the use of fossil fuels were superseded by equitable access to clean sources of renewable energy.

Redox and inflammatory mechanisms linking air pollution particulate matter with cardiometabolic derangements

Air pollution is the largest environmental risk factor for disease and premature death. Among the different components that are present in polluted air, fine particulate matter below 2.5 μm in diameter (PM2.5) has been identified as the main hazardous constituent. PM2.5 mainly arises from fossil fuel combustion during power generation, industrial processes, and transportation. Exposure to PM2.5 correlates with enhanced mortality risk from cardiovascular diseases (CVD), such as myocardial infarction and stroke. Over the last decade, it has been increasingly suggested that PM2.5 affects CVD already at the stage of risk factor development. Among the multiple biological mechanisms that have been described, the interplay between oxidative stress and inflammation has been consistently highlighted as one of the main drivers of pulmonary, systemic, and cardiovascular effects of PM2.5 exposure. In this context, PM2.5 uptake by tissue-resident immune cells in the lung promotes oxidative and inflammatory mediators release that alter tissue homeostasis at remote locations. This pathway is central for PM2.5 pathogenesis and might account for the accelerated development of risk factors for CVD, including obesity and diabetes. However, transmission and end-organ mechanisms that explain PM2.5-induced impaired function in metabolic active organs are not completely understood. In this review, the main features of PM2.5 physicochemical characteristics related to PM2.5 ability to induce oxidative stress and inflammation will be presented. Hallmark and recent epidemiological and interventional studies will be summarized and discussed in the context of current air quality guidelines and legislation, knowledge gaps, and inequities. Lastly, mechanistic studies at the intersection between redox metabolism, inflammation, and function will be discussed, with focus on heart and adipose tissue alterations. By offering an integrated analysis of PM2.5-induced effects on cardiometabolic derangements, this review aims to contribute to a better understanding of the pathogenesis and potential interventions of air pollution-related CVD.

High glucose enhances the activation of NLRP3 inflammasome by ambient fine particulate matter in alveolar macrophages

BACKGROUND

Epidemiological studies have demonstrated that individuals with preexisting conditions, including diabetes mellitus (DM), are more susceptible to air pollution. However, the underlying mechanisms remain unclear. In this study, we proposed that a high glucose setting enhances ambient fine particulate matter (PM2.5)-induced macrophage activation and secretion of the proinflammatory cytokine, IL-1β, through activation of the NLRP3 inflammasome, altering the balance between matrix metalloproteinases (MMPs) and tissue inhibitors of MMPs (TIMPs).

RESULTS

Exposure of mouse alveolar macrophages to non-cytotoxic doses of PM2.5 led to upregulation of IL-1β, activation of the NLRP3 inflammasome, increased nuclear translocation of the transcription factor NF-κB, increased generation of reactive oxygen species (ROS), and increased expression and enzymatic activity of MMP-9; these effects were enhanced when cells were pretreated with high glucose. However, pretreatment in a high glucose setting alone did not induce significant changes. ROS generation following PM2.5 exposure was abolished when cells were pretreated with ROS scavengers such as Trolox and superoxide dismutase (SOD), or with an NADPH oxidase inhibitor, DPI. Pretreatment of cells with DPI attenuated the effects of a high glucose setting on PM2.5-induced upregulation of IL-1β, activation of the NLRP3 inflammasome, and nuclear translocation of NF-κB. In addition, enhancement of PM2.5-induced expression and enzymatic activity of MMP-9 following high glucose pretreatment was not observed in primary alveolar macrophages obtained from NLRP3 or IL-1R1 knockout (KO) mice, where pro-IL-1β cannot be cleaved to IL-1β or cells are insensitive to IL-1β, respectively.

CONCLUSIONS

This study demonstrated that exposure of mouse alveolar macrophages to PM2.5 in a high glucose setting enhanced PM2.5-induced production of IL-1β through activation of the NLRP3 inflammasome and nuclear translocation of NF-κB due to PM2.5-induced oxidative stress, leading to MMP-9 upregulation. The key role of NADPH oxidase in PM2.5-induced ROS generation and activation of the IL-1β secretion pathway and the importance of IL-1β secretion and signaling in PM2.5-induced increases in MMP-9 enzymatic activity were also demonstrated. This study provides a further understanding of the potential mechanisms underlying the susceptibility of individuals with DM to air pollution and suggests potential therapeutic targets.

Long-term association of air pollution and incidence of lung cancer among older Americans: A national study in the Medicare cohort

BACKGROUND

Despite strong evidence of the association of fine particulate matter (PM2.5) exposure with an increased risk of lung cancer mortality, few studies had investigated associations of multiple pollutants simultaneously, or with incidence, or using causal methods. Disparities were also understudied.

OBJECTIVES

We investigated long-term effects of PM2.5, nitrogen dioxide (NO2), warm-season ozone, and particle radioactivity (PR) exposures on lung cancer incidence in a nationwide cohort.

METHODS

We conducted a cohort study with Medicare beneficiaries (aged ≥ 65 years) continuously enrolled in the fee-for-service program in the contiguous US from 2001 to 2016. Air pollution exposure was averaged across three years and assigned based on ZIP code of residence. We fitted Cox proportional hazards models to estimate the hazard ratio (HR) for lung cancer incidence, adjusted for individual- and neighborhood-level confounders. As a sensitivity analysis, we evaluated the causal relationships using inverse probability weights. We further assessed effect modifications by individual- and neighborhood-level covariates.

RESULTS

We identified 166,860 lung cancer cases of 12,429,951 studied beneficiaries. In the multi-pollutant model, PM2.5 and NO2 exposures were statistically significantly associated with increased lung cancer incidence, while PR was marginally significantly associated. Specifically, the HR was 1.008 (95% confidence interval [CI]: 1.005, 1.011) per 1-μg/m3 increase in PM2.5, 1.013 (95% CI: 1.012, 1.013) per 1-ppb increase in NO2, and 1.005 (0.999, 1.012) per 1-mBq/m3 increase in PR. At low exposure levels, all pollutants were associated with increased lung cancer incidence. Men, older individuals, Blacks, and residents of low-income neighborhoods experienced larger effects of PM2.5 and PR.

DISCUSSION

Long-term PM2.5, NO2, and PR exposures were independently associated with increased lung cancer incidence among the national elderly population. Low-exposure analysis indicated that current national standards for PM2.5 and NO2 were not restrictive enough to protect public health, underscoring the need for more stringent air quality regulations.

Health impact assessment for air pollution in the presence of regional variation in effect sizes: The implications of using different meta-analytic approaches

The estimated health effects of air pollution vary between studies, and this variation is caused by factors associated with the study location, hereafter termed regional heterogeneity. This heterogeneity raises a methodological question as to which studies should be used to estimate risks in a specific region in a health impact assessment. Should one use all studies across the world, or only those in the region of interest? The current study provides novel insight into this question in two ways. Firstly, it presents an up-to-date analysis examining the magnitude of continent-level regional heterogeneity in the short-term health effects of air pollution, using a database of studies collected by Orellano et al. (2020). Secondly, it provides in-depth simulation analyses examining whether existing meta-analyses are likely to be underpowered to identify statistically significant regional heterogeneity, as well as evaluating which meta-analytic technique is best for estimating region-specific estimates. The techniques considered include global and continent-specific (sub-group) random effects meta-analysis and meta-regression, with omnibus statistical tests used to quantify regional heterogeneity. We find statistically significant regional heterogeneity for 4 of the 8 pollutant-outcome pairs considered, comprising NO2, O3 and PM2.5 with all-cause mortality, and PM2.5 with cardiovascular mortality. From the simulation analysis statistically significant regional heterogeneity is more likely to be identified as the number of studies increases (between 3 and 30 in each region were considered), between region heterogeneity increases and within region heterogeneity decreases. Finally, while a sub-group analysis using Cochran's Q test has a higher median power (0.71) than a test based on the moderators' coefficients from meta-regression (0.59) to identify regional heterogeneity, it also has an inflated type-1 error leading to more false positives (median errors of 0.15 compared to 0.09).

Climate Change and Cancer Care-Feeling the Heat

This Viewpoint describes how climate change and air pollution markedly affect cancer incidence, care delivery, and patient outcomes.

Uncertainty Reduction and Environmental Justice in Air Pollution Epidemiology: The Importance of Minority Representation

Ambient air pollution is an increasing threat to society, with rising numbers of adverse outcomes and exposure inequalities worldwide. Reducing uncertainty in health outcomes models and exposure disparity studies is therefore essential to develop policies effective in protecting the most affected places and populations. This study uses the concept of information entropy to study tradeoffs in mortality uncertainty reduction from increasing input data of air pollution versus health outcomes. We study a case scenario for short-term mortality from particulate matter (PM2.5) in North Carolina for 2001-2016, employing a case-crossover design with inputs from an individual-level mortality data set and high-resolution gridded data sets of PM2.5 and weather covariates. We find a significant association between mortality and PM2.5, and the information tradeoffs indicate that a 10% increase in mortality information reduces model uncertainty three times more than increased resolution of the air pollution model from 12 to 1 km. We also find that Non-Hispanic Black (NHB) residents tend to live in relatively more polluted census tracts, and that the mean PM2.5 for NHB cases in the mortality model is significantly higher than that of Non-Hispanic White cases. The distinct distribution of PM2.5 for NHB cases results in a relatively higher information value, and therefore faster uncertainty reduction, for new NHB cases introduced into the mortality model. This newfound influence of exposure disparities in the rate of uncertainty reduction highlights the importance of minority representation in environmental research as a quantitative advantage to produce more confident estimates of the true effects of environmental pollution.

Managing nitrogen in maize production for societal gain

Highly productive agriculture is essential to feed humanity, but agricultural practices often harm human health and the environment. Using a nitrogen (N) mass-balance model to account for N inputs and losses to the environment, along with empirical based models of yield response, we estimate the potential gains to society from improvements in nitrogen management that could reduce health and environmental costs from maize grown in the US Midwest. We find that the monetized health and environmental costs to society of current maize nitrogen management practices are six times larger than the profits earned by farmers. Air emissions of ammonia from application of synthetic fertilizer and manure are the largest source of pollution costs. We show that it is possible to reduce these costs by 85% ($21.6 billion per year, 2020$) while simultaneously increasing farmer profits. These gains come from (i) managing fertilizer ammonia emissions by changing the mix of fertilizer and manure applied, (ii) improving production efficiency by reducing fertilization rates, and (iii) halting maize production on land where health and environmental costs exceed farmer profits, namely on low-productivity land and locations in which emissions are especially harmful. Reducing ammonia emissions from changing fertilizer types-in (i)-reduces health and environmental costs by 46% ($11.7 billion). Reducing fertilization rates-in (ii)-limits nitrous oxide emissions, further reducing health and environmental costs by $9.5 billion, and halting production on 16% of maize-growing land in the Midwest-in (iii)-reduces costs by an additional $0.4 billion.

Chronic exposure to fine particles (PM2.5) and mortality: Evidence from Chile

Many Chilean cities suffer from high air pollution from industrial, mobile, and residential wood-burning sources. Several studies have linked PM2.5 air pollution exposure to higher mortality risk from cardiovascular, pulmonary, and lung cancer causes. In recent years, Chile has developed an extensive air pollution monitoring network to enforce air quality standards for PM2.5, allowing the study of the medium-term association between PM2.5 and mortality.

Methods

A negative binomial regression model was used to study the association between 3-year average PM2.5 concentrations and age-adjusted mortality rates for 105 of the 345 municipalities in Chile. Models were fitted for all (ICD10 A to Q codes), cardiopulmonary (I and J), cardiovascular (I), pulmonary (J), cancer (C), and lung cancer (C33-C34) causes; controlling for meteorological, socioeconomic, and demographic characteristics.

Results

A significant association of PM2.5 exposure with cardiopulmonary (relative risk for 10 µg/m3 PM2.5: 1.06; 95% confidence interval = 1.00, 1.13) and pulmonary (1.11; 1.02, 1.20) age-adjusted mortality rates was found. Cardiovascular (1.06; 0.99, 1.13) and all causes (1.02; 0.98, 1.07) were positive, but not significant. No significant association was found between cancer and lung cancer. The positive associations remained even when controlling for multiple confounding factors, model specifications, and when considering different methods for exposure characterization. These estimates are in line with results from cohort studies from the United States and European studies.

Conclusion

Three-year average PM2.5 exposure is positively associated with the age-adjusted mortality rate for cardiopulmonary and cardiovascular causes in Chile. This provides evidence of the medium-term exposure effect of fine particles on long-term mortality rates.

Individual and joint associations of long-term exposure to air pollutants and cardiopulmonary mortality: a 22-year cohort study in Northern China

Background

Evidence on the associations between long-term exposure to multiple air pollutants and cardiopulmonary mortality is limited, especially for developing regions with higher pollutant levels. We aimed to characterise the individual and joint (multi-pollutant) associations of long-term exposure to air pollutants with cardiopulmonary mortality, and to identify air pollutant that primarily contributes to the mortality risk.

Methods

We followed 37,442 participants with a mean age of 43.5 years in four cities in northern China (Tianjin, Shenyang, Taiyuan, and Rizhao) from January 1998 to December 2019. Annual particulate matter (PM) with diameters ≤2.5 μm (PM2.5), ≤10 μm (PM10), sulfur dioxide (SO2) and nitrogen dioxide (NO2) were estimated using daily average values from satellite-derived machine learning models and monitoring stations. Time-varying Cox proportional hazards model was used to evaluate the individual association between air pollutants and mortality from non-accidental causes, cardiovascular diseases (CVDs), non-malignant respiratory diseases (RDs) and lung cancer, accounting for demographic and socioeconomic factors. Effect modifications by age, sex, income and education level were also examined. Quantile-based g-Computation integrated with time-to-event data was additionally applied to evaluate the co-effects and the relative weight of contributions for air pollutants.

Findings

During 785,807 person-years of follow-up, 5812 (15.5%) died from non-accidental causes, among which 2932 (7.8%) were from all CVDs, 479 (1.3%) from non-malignant RDs, and 552 (1.4%) from lung cancer. Long-term exposure to PM10 (mean [baseline]: 136.5 μg/m3), PM2.5 (mean [baseline]: 70.2 μg/m3), SO2 (mean [baseline]: 113.0 μg/m3) and NO2 (mean [baseline]: 39.2 μg/m3) were adversely and consistently associated with all mortality outcomes. A 10 μg/m3 increase in PM2.5 was associated with higher mortality from non-accidental causes (hazard ratio 1.20; 95% confidence interval 1.17-1.23), CVDs (1.23; 1.19-1.28), non-malignant RDs (1.37; 1.25-1.49) and lung cancer (1.14; 1.05-1.23). A monotonically increasing curve with linear or supra-linear shape with no evidence of a threshold was observed for the exposure-response relationship of mortality with individual or joint exposure to air pollutants. PM2.5 consistently contributed most to the elevated mortality risks related to air pollutant mixture, followed by SO2 or PM10.

Interpretation

There was a strong and positive association of long-term individual and joint exposure to PM10, PM2.5, SO2, and NO2 with mortalities from non-accidental causes, CVDs, non-malignant RDs and lung cancer in high-exposure settings, with PM2.5 potentially being the main contributor. The shapes of associations were consistent with a linear or supra-linear exposure-response relationship, with no lower threshold observed within the range of concentrations in this study.

Funding

National Key Research and Development Program of China, the China Scholarship Council, the National Natural Science Foundation of China, Natural Science Foundation of Guangdong Province.

Mortality attributable to ambient fine particulate matter and nitrogen dioxide in Switzerland in 2019: Use of two-pollutant effect estimates

INTRODUCTION

Air pollution health risk assessments have traditionally used single-pollutant effect estimates for one proxy ambient air pollutant such as PM_2.5. Two-pollutant effect estimates, i.e. adjusted for another correlated pollutant, theoretically enable the aggregation of pollutant-specific health effects minimizing double-counting. Our study aimed at estimating the adult mortality in Switzerland in 2019 attributable to PM_2.5 from a single-pollutant effect estimate and to the sum of PM_2.5 and NO₂ from two-pollutant estimates; comparing the results with those from alternative global, European and Swiss effect estimates.

METHODS

For the single-pollutant approach, we used a PM_2.5 summary estimate of European cohorts from the project ELAPSE, recommended by the European Respiratory Society and International Society for Environmental Epidemiology (ERS-ISEE). To derive the two-pollutant effect estimates, we applied ELAPSE-based conversion factors to ERS-ISEE PM_2.5 and NO₂ single-pollutant effect estimates. Additionally, we used World Health Organization 2021 Air Quality Guidelines as counterfactual scenario, exposure model data from 2019 and Swiss lifetables.

RESULTS

The single-pollutant effect estimate for PM_2.5 (1.118 [1.060; 1.179] per 10 μg/m³) resulted in 2240 deaths (21,593 years of life lost). Using our derived two-pollutant effect estimates (1.023 [1.012; 1.035] per 10 μg/m³ PM_2.5 adjusted for NO₂ and 1.040 [1.023; 1.058] per 10 μg/m³ NO₂ adjusted for PM_2.5), we found 1977 deaths (19,071 years of life lost) attributable to PM_2.5 and NO₂ together (23% from PM_2.5). Deaths using alternative effect estimates ranged from 1042 to 5059.

DISCUSSION

Estimated premature mortality attributable to PM_2.5 alone was higher than to both PM_2.5 and NO₂ combined. Furthermore, the proportion of deaths from PM_2.5 was lower than from NO₂ in the two-pollutant approach. These seemingly paradoxical results, also found in some alternative estimates, are due to statistical imprecisions of underlying correction methods. Therefore, using two-pollutant effect estimates can lead to interpretation challenges in terms of causality.

Health Risk Assessment of Exposure to Air Pollutants Exceeding the New WHO Air Quality Guidelines (AQGs) in São Paulo, Brazil

We applied the AirQ+ model to analyze the 2021 data within our study period (15 December 2020 to 17 June 2022) to quantitatively estimate the number of specific health outcomes from long- and short-term exposure to atmospheric pollutants that could be avoided by adopting the new World Health Organization Air Quality Guidelines (WHO AQGs) in São Paulo, Southeastern Brazil. Based on temporal variations, PM_2.5, PM₁₀, NO₂, and O₃ exceeded the 2021 WHO AQGs on up to 54.4% of the days during sampling, mainly in wintertime (June to September 2021). Reducing PM_2.5 values in São Paulo, as recommended by the WHO, could prevent 113 and 24 deaths from lung cancer (LC) and chronic obstructive pulmonary disease (COPD) annually, respectively. Moreover, it could avoid 258 and 163 hospitalizations caused by respiratory (RD) and cardiovascular diseases (CVD) due to PM_2.5 exposure. The results for excess deaths by RD and CVD due to O₃ were 443 and 228, respectively, and 90 RD hospitalizations due to NO₂. Therefore, AirQ+ is a useful tool that enables further elaboration and implementation of air pollution control strategies to reduce and prevent hospital admissions, mortality, and economic costs due to exposure to PM_2.5, O₃, and NO₂ in São Paulo.

The new WHO air quality guidelines for PM2.5: predicament for small/medium cities

The global burden of disease estimated that approximately 7.1 million deaths worldwide were related to air pollution in 2016. However, only a limited number of small- and middle-sized cities have air quality monitoring networks. To date, air quality in terms of particulate matter is still mainly focused on mass concentration, with limited compositional monitoring even in mega cities, despite evidence indicating differential toxicity of particulate matter. As this evidence is far from conclusive, we conducted PM_2.5 bioaccessibility studies of potentially harmful elements in a medium-sized city, Londrina, Brazil. The data was interpreted in terms of source apportionment, the health risk evaluation and the bioaccessibility of inorganic contents in an artificial lysosomal fluid. The daily average concentration of PM_2.5 was below the WHO guideline, however, the chemical health assessment indicated a considerable health risk. The in vitro evaluation showed different potential mobility when compared to previous studies in large-sized cities, those with 1 million inhabitants or more (Curitiba and Manaus). The new WHO guideline for PM_2.5 mass concentration puts additional pressure on cities where air pollution monitoring is limited and/or neglected, because decision making is mainly revenue-driven and not socioeconomic-driven. Given the further emerging evidence that PM chemical composition is as, or even more, important than mass concentration levels, the research reported in the paper could pave the way for the necessary inter- and intra-city collaborations that are needed to address this global health challenge.

The impacts of air pollution on immigrants' settlement intention in China

This paper investigates the impacts of air pollution on immigrants' willingness to settle in China. We construct a theoretical model that discusses how air pollution impacts immigrants' willingness to return home and move to other cities and illustrates how air pollution decreases the settlement intention of immigrants. The empirical results show that urban air pollution decreases immigrants' settlement intention. Robustness checks using multi-methods and multi-measures of settlement intention and air pollution support this conclusion. Air pollution has heterogeneous impacts on immigrants' settlement intentions. From the individual level, air pollution decreases the settlement intention for immigrants with 30-60 years old, middle-income migrants, and rural migrants. From the city level, air pollution decreases the settlement intention of immigrants in the eastern region, developed cities, and cities with high and low air pollution.

Effects of shared governance and cost redistribution on air pollution control: a study of game theory-based cooperation

This study seeks cost-effective strategies for PM2.5 reduction to generate insights into minimizing pollution abatement costs subject to different scenarios. This study theorizes that the cooperation of PM2.5 abatement has potential gains for participants and develop an empirical way to compare the costs and efficiency of PM2.5 abatement involving the variation of environmental conditions. This study revises the cooperative game model in the context of threshold effects using data obtained from the Beijing-Tianjin-Hebei metropolitan cluster in China. In general, the results support the key assertion that cooperation in the metropolitan cluster plays a vital role in optimizing the efficiency and costs of PM2.5 abatement. In addition to extending the application of the revised model, this study provides a way to estimate the costs and the mitigation benefits of meeting the pollution targets for each coparticipant and take the scenario of multiparty cooperation into account as well as the scenarios involving other types of pollutants. The empirical findings have important policy implications for regional shared governance, decentralization, and resource reallocation. Economic incentive-based shared governance and cost reallocation work better than traditional regulations.

Fine particulate matter induces adipose tissue expansion and weight gain: Pathophysiology

Dysregulations in energy balance represent a major driver of obesity. Recent evidence suggests that environmental factors also play a pivotal role in inducing weight gain. Chronic exposure to fine particulate matter (PM_2.5 ) is associated with white adipose tissue (WAT) expansion in animals and higher rates of obesity in humans. This review discusses metabolic adaptions in central and peripheral tissues that promote energy storage and WAT accumulation in PM_2.5 -exposed animals and humans. Chronic PM_2.5 exposure produces inflammation and leptin resistance in the hypothalamus, decreasing energy expenditure and increasing food intake. PM_2.5 promotes the conversion of brown adipocytes toward the white phenotype, resulting in decreased energy expenditure. The development of inflammation in WAT can stimulate adipogenesis and hampers catecholamine-induced lipolysis. PM_2.5 exposure affects the thyroid, reducing the release of thyroxine and tetraiodothyronine. In addition, PM_2.5 exposure compromises skeletal muscle fitness by inhibiting Nitric oxide (NO)-dependent microvessel dilation and impairing mitochondrial oxidative capacity, with negative effects on energy expenditure. This evidence suggests that pathological alterations in the hypothalamus, brown adipose tissue, WAT, thyroid, and skeletal muscle can alter energy homeostasis, increasing lipid storage and weight gain in PM_2.5 -exposed animals and humans. Further studies will enrich this pathophysiological model.

Long-term exposure to fine particulate matter and site-specific cancer mortality: A difference-in-differences analysis in Jiangsu province, China

BACKGROUND

Accumulating studies have reported that chronic exposure to ambient fine particulate matter (PM_2.5) can lead to adverse effects on lung cancer mortality; however, such chronic effects are less clear for mortality from other site-specific cancers.

OBJECTIVE

To explore the causal effect of long-term PM_2.5 exposure on mortality from all-site and a variety of site-specific cancers in Jiangsu province, China during 2015-2020 using a difference-in-differences analysis.

METHODS

For each of 53 county-based spatial units in Jiangsu province, we calculated annual death counts for all-site cancer and 23 site-specific cancers. Using a validated high-resolution PM_2.5 grid dataset, long-term PM_2.5 exposure of a spatial unit within a given year was evaluated as the average of population-weighted annual concentrations during recent 10 years. Conditional Poisson regression models were employed to evaluate exposure-response associations adjusting for spatial and temporal variables, seasonal temperatures, relative humidity, and gross domestic product (GDP).

RESULTS

During the study period, we identified 947,337 adult cancer deaths in Jiangsu province. Each 1 μg/m³ increment in PM_2.5 exposure was significantly associated with a 2.7% increase in the risk of all-site cancer mortality. PM_2.5-mortality associations were also observed in cancer of lip, oral cavity and pharynx, stomach, colorectum, pancreas, lung, bone and joints, ovary, prostate, and lymphoma (all adjusted P < 0.05), with the relative risks ranging from 1.028 (95% confidence interval [CI]: 1.011, 1.046) for stomach cancer to 1.201 (95% CI: 1.120, 1.308) for bone and joints cancers. Exposure-response curves showed that these associations were close to linearity, though most of them had increasing slopes at high exposure levels. Overall, women and subjects in low GDP regions were more vulnerable to PM_2.5 exposures.

CONCLUSIONS

Long-term exposure to ambient PM_2.5 contributes to a higher risk of mortality from multiple site-specific cancers.

Driving factors behind the continuous increase of long-term PM2.5-attributable health burden in India using the high-resolution global datasets from 2001 to 2020

Air pollution is the fourth leading global risk factor, whereas in India air pollution is reported as the highest risk factor with millions of premature deaths every year. Despite implementation of several air pollution control plans, PM_2.5 levels over India have not noticeably reduced. PM_2.5-associated health burdens in India have increased significantly in past decades. A fine resolution (0·01° × 0·01°) analysis of PM_2.5-attribulable premature deaths (rather than the coarse-level analysis) may elucidate the reason for this increase and inform and effective start-of-the-art state-level and national emission control strategies. This study quantified the spatiotemporal dynamics of PM_2.5-attributable premature deaths from 2001 to 2020 and applied a decomposition analysis to dissect the contribution of various associated parameters, such as PM_2.5 concentration, population distribution and disease-specific baseline death rate. Results show significant spatiotemporal variations of PM_2.5 and associated health burden in India. During the study period, population weighted PM_2.5 value increased from 46.0 to 59.5 μg/m³ and associated non-communicable death increased around 87.6 %, from 1050 [95 % (CI): 880-1210] thousand to 1970 (95 % CI: 1658-2259) thousand. The states of Uttar Pradesh, Bihar, West Bengal, Maharashtra, Rajasthan, and Madhya Pradesh had the highest PM_2.5-attributable deaths. In these states, non-accidental deaths increased from 232.1, 112.7, 81.4, 79.1, 66.3 and 58.5 thousand in 2001 to 424.1, 226.7, 156.2, 154.5, 123.3 and 119.7 thousand in 2020. In per capita population (/10⁵ population), the highest PM_2.5-attributable deaths were observed in Delhi, Uttar Pradesh, Bihar, Haryana and Punjab. Throughout the study period, demographic changes outweighed the health burden and were responsible for ~62.8 % increase of PM_2.5-related non-accidental deaths across India, whereas the change in PM_2.5 concentration influenced only 18.7 %. The change in baseline mortality rate impacts differently for the estimation of disease-specific mortality changes. Our findings suggest more dynamic and comprehensive policies at state-specific level, especially for North India is very indispensable for the overall decrease of PM_2.5-related deaths in India.

U.S. West Coast droughts and heat waves exacerbate pollution inequality and can evade emission control policies

Droughts reduce hydropower production and heatwaves increase electricity demand, forcing power system operators to rely more on fossil fuel power plants. However, less is known about how droughts and heat waves impact the county level distribution of health damages from power plant emissions. Using California as a case study, we simulate emissions from power plants under a 500-year synthetic weather ensemble. We find that human health damages are highest in hot, dry years. Counties with a majority of people of color and counties with high pollution burden (which are somewhat overlapping) are disproportionately impacted by increased emissions from power plants during droughts and heat waves. Taxing power plant operations based on each plant's contribution to health damages significantly reduces average exposure. However, emissions taxes do not reduce air pollution damages on the worst polluting days, because supply scarcity (caused by severe heat waves) forces system operators to use every power plant available to avoid causing a blackout.

Kinetics of autophagic activity in nanoparticle-exposed lung adenocarcinoma (A549) cells

Autophagy, a homeostatic mechanism, is crucial in maintaining normal cellular function. Although dysregulation of autophagic processes is recognized in certain diseases, it is unknown how maintenance of cellular homeostasis might be affected by the kinetics of autophagic activity in response to various stimuli. In this study, we assessed those kinetics in lung adenocarcinoma (A549) cells in response to exposure to nanoparticles (NP) and/or Rapamycin. Since NP are known to induce autophagy, we wished to determine if this phenomenon could be a driver of the harmful effects seen in lung tissues exposed to air pollution. A549 cells were loaded with a fluorescent marker (DAPRed) that labels autophagosomes and autolysosomes. Autophagic activity was assessed based on the fluorescence intensity of DAPRed measured over the entire cell volume of live single cells using confocal laser scanning microscopy (CLSM). Autophagic activity over time was determined during exposure of A549 cells to single agents (50 nM Rapamycin; 80 μg/mL, 20 nm carboxylated polystyrene NP (PNP); or, 1 μg/mL ambient ultrafine particles (UFP) (<180 nm)), or double agents (Rapamycin + PNP or Rapamycin + UFP; concomitant and sequential), known to stimulate autophagy. Autophagic activity increased in all experimental modalities, including both single agent and double agent exposures, and reached a steady state in all cases ~2 times control from ~8 to 24 hrs, suggesting the presence of an upper limit to autophagic capacity. These results are consistent with the hypothesis that environmental stressors might exert their harmful effects, at least in part, by limiting available autophagic response to additional stimulation, thereby making nanoparticle-exposed cells more susceptible to secondary injury due to autophagic overload.

Health benefits from the reduction of PM2.5 concentrations under carbon tax and emission trading scheme: a case study in China

Climate policies could improve air quality, thereby generating health benefits and thus increasing labour input for economic growth. Nevertheless, health benefits are usually overlooked in evaluation frameworks of climate policies. In this paper, a dynamic recursive computable general equilibrium (CGE) model is adopted to define how climate policies are related to air pollution, namely [Formula: see text] concentrations. Health benefits of climate policies are divided into reduction of [Formula: see text]-related morbidity and mortality. The CGE model results show that both carbon tax and emission trading scheme (ETS) decrease morbidity and mortality; therefore, under climate policies, [Formula: see text]-related labour loss decreases, and thus increasing labour input triggers an economic boom. Carbon tax generates more health benefits in short term, while health benefits of ETS policy will gradually increase in long term. Hence, we conclude that regarding health benefits, a long-term ETS policy is preferable to a long-term carbon tax. This finding implies that the recently established nationwide ETS market in China is meaningful, as it will generate more health benefits in future. Nevertheless, the quantified health benefits in this paper still cannot compensate GDP loss induced by climate policy implementations, implying that it is a challenging task to unbiasedly model health benefits of climate policies. Hence, we have recommended that the scopes and contents of health benefits should be expanded in evaluations of climate policies.

How does particulate air pollution affect barrier functions and inflammatory activity of lung vascular endothelium?

Both particulate matter and gaseous components of air pollution have already been shown to increase cardiovascular mortality in numerous studies. It is, however, important to note that on their way to the bloodstream the polluting agents pass the lung barrier. Inside the alveoli, particles of approximately 0.4-1 μm are most efficiently deposited and commonly undergo phagocytosis by lung macrophages. Not only the soluble agents, but also particles fine enough to leave the alveoli enter the bloodstream in this finite part of the endothelium, reaching thus higher concentrations in close proximity of the alveoli and endothelium. Additionally, deposits of particulate matter linger in direct proximity of the endothelial cells and may induce inflammation, immune responses, and influence endothelial barrier dysfunction thus increasing PM bioavailability in positive feedback. The presented discussion provides an overview of possible components of indoor PM and how endothelium is thus influenced, with emphasis on lung vascular endothelium and clinical perspectives.

Short-Term Exposure Effect of Ambient Fine Particulate Matter, Ozone and Cold Temperature on Emergency Room Visits for Asthma Patients

(1) Background: The acute effects of ozone, cold temperature and particulate matter less than 2.5 μm (PM_2.5) in size related to asthma attacks are well known worldwide. The adverse effects of ozone and cold temperature on asthma morbidity in Taiwan are still inconclusive. (2) Methods: This retrospective study included patients who had asthma emergency room visits (ERVs) from 1 January 2016 to 31 December 2019 in a regional hospital in Taiwan. The short-term negative effects were estimated using Distributed Lag Non-Linear Models (DLNMs) for the relative risks (RRs) of asthma ERVs associated with PM_2.5, ozone and cold temperature exposures within 5 days. (3) Results: There was a significant association between a 10 ppm increase in PM_2.5 exposure and asthma ERVs at a 2-day lag (RR 1.166, 95% confidence interval (C.I.): 1.051-1.294). There was a significant association between ozone and asthma ERVs at a 1-day lag (RR 1.179, 95% C.I.: 1.034-1.345). The ambient temperature in cold weather compared with the temperature of minimum asthma ERV showed an RR of 1.214, 95% C.I.: 1.009-1.252 at a 1-day lag. (4) Conclusions: This study provides evidence that short-term exposure to fine suspended particulates, ozone and inverse temperature is associated with asthma exacerbation.

Environmental Health, Racial/Ethnic Health Disparity, and Climate Impacts of Inter-Regional Freight Transport in the United States

We quantify and compare three environmental impacts from inter-regional freight transportation in the contiguous United States: total mortality attributable to PM2.5 air pollution, racial-ethnic disparities in PM2.5-attributable mortality, and CO2 emissions. We compare all major freight modes (truck, rail, barge, aircraft) and routes (∼30,000 routes). Our study is the first to comprehensively compare each route separately and the first to explore racial-ethnic exposure disparities by route and mode, nationally. Impacts (health, health disparity, climate) per tonne of freight are the largest for aircraft. Among nonaircraft modes, per tonne, rail has the largest health and health-disparity impacts and the lowest climate impacts, whereas truck transport has the lowest health impacts and greatest climate impacts─an important reminder that health and climate impacts are often but not always aligned. For aircraft and truck, average monetized damages per tonne are larger for climate impacts than those for PM2.5 air pollution; for rail and barge, the reverse holds. We find that average exposures from inter-regional truck and rail are the highest for White non-Hispanic people, those from barge are the highest for Black people, and those from aircraft are the highest for people who are mixed/other race. Level of exposure and disparity among racial-ethnic groups vary in urban versus rural areas.

Sources, transport, and visibility impact of ambient submicrometer particle number size distributions in an urban area of central Taiwan

This study applied positive matrix factorization (PMF) to identify the sources of size-resolved submicrometer (10-1000 nm) particles and quantify their contributions to impaired visibility based on the particle number size distributions (PNSDs), aerosol light extinction (b_p), air pollutants (PM₁₀, PM_2.5, SO₂, O₃, and NO), and meteorological parameters (temperature, relative humidity, wind speed, wind direction, and ultraviolet index) measured hourly over an urban basin in central Taiwan between 2017 and 2021. The transport of source-specific PNSDs was evaluated with wind and back trajectory analyses. The PMF revealed six sources to the total particle number (TPN), surface (TPS), volume (TPV), and b_p. Factor 1 (F1), the key contributor to TPN (35.0 %), represented nucleation (<25 nm) particles associated with fresh traffic emission and secondary new particle formation, which were transported from the west-southwest by stronger winds (>2.2 m s^-1). F2 represented the large Aitken (50-100 nm) particles transported regionally via northerly winds, whereas F3 represented large accumulation (300-1000 nm) particles, which showed elevated concentrations under stagnant conditions (<1.1 m s^-1). F4 represented small Aitken (25-50 nm) particles arising from the growth and transport of the nucleation particles (F1) via west-southwesterly winds. F5 represented large Aitken particles originating from combustion-related SO₂ sources and carried by west-northwesterly winds. F6 represented small accumulation (100-300 nm) particles emitted both by local sources and by the remote SO₂ sources found for F5. Overall, large accumulation particles (F3) played the greatest role in determining the TPV (66.4 %) and TPS (34.8 %), and their contribution to b_p increased markedly from 17.3 % to 40.7 % as visibility decreased, indicating that TPV and TPS are better metrics than TPN for estimating b_p. Furthermore, slow-moving air masses-and therefore stagnant conditions-facilitate the build-up of accumulation mode particles (F3 + F6), resulting in the poorest visibility.

Bibliometric Analysis Reveals the Progress of PM2.5 in Health Research, Especially in Cancer Research

PM_2.5 has an aerodynamic diameter of less than or equal to 2.5 microns due to its inherent physical and chemical properties so that it can enter the alveoli through the respiratory tract for blood gas exchange. Numerous studies have shown that PM_2.5 is a serious air pollutant that poses a wide range of health risks, especially for cancer. Bibliometric methods were employed to have comprehensively analyzed the research of PM_2.5 in cancer for about a decade in Web of Science to identify hotspots and trends using VOSviewer, CiteSpace, and R. The field has undergone overall growth in the past decade. As research on PM_2.5 in health deepens, cancer related to it expanded beyond the respiratory system to the digestive system, urinary system, female gonadal axis, breast cancer and other cancers. Another observation is that research on PM_2.5 in cancer has progressed in the mechanisms of deterioration, such as the role of matrix metalloproteinases in cancer. In addition, research on the risks of PM_2.5 in combination with polycyclic aromatic hydrocarbons and heavy metals has also emerged. Results showed that there are relatively more studies on PM_2.5 in high-latitude countries, which may be due to different national conditions, such as climate and coal combustion. Our research has combed through the progress of PM_2.5 in cancer research and provided a supplement for developing pollution prevention ideas with different national conditions in this field.

1,4-Naphthoquinone-coated black carbon nanoparticles up-regulation POR/FTL/IL-33 axis in THP1 cells

Black carbon (BC) is an important component of atmospheric PM 2.5 and the second largest contributor to global warming. 1,4-naphthoquinone-coated BC (1,4 NQ-BC) is a secondary particle with great research value, so we chose 1,4 NQ-BC as the research object. In our study, mitochondria and lysosomes were selected as targets to confirm whether they were impaired by 1,4 NQ-BC, label free proteomics technology, fluorescent probes, qRT-PCR and western blots were used to investigate the mechanism of 1,4 NQ-BC toxicity. We found 494 differentially expressed proteins (DEPs) in mitochondria and 86 DEPs in lysosomes using a proteomics analysis of THP1 cells after 1,4 NQ-BC exposure for 24 h. Through proteomics analysis and related experiments, we found that 1,4 NQ-BC can damage THP-1-M cells by obstructing autophagy, increasing lysosomal membrane permeability, disturbing the balance of ROS, and reducing the mitochondrial membrane potential. It is worth noting that 1,4 NQ-BC prevented the removal of FTL by inhibiting autophagy, and increased IL-33 level by POR/FTL/IL-33 axis. We first applied proteomics to study the damage mechanism of 1,4 NQ-BC on THP1 cells. Our research will enrich knowledge of the mechanism by which 1,4 NQ-BC damages human macrophages and identify important therapeutic targets and adverse outcome pathways for 1,4 NQ-BC-induced damage.

Avoidable mortality due to long-term exposure to PM2.5 in Colombia 2014-2019

OBJECTIVE

To compare estimates of spatiotemporal variations of surface PM_2.5 concentrations in Colombia from 2014 to 2019 derived from two global air quality models, as well as to quantify the avoidable deaths attributable to the long-term exposure to concentrations above the current and projected Colombian standard for PM_2.5 annual mean at municipality level.

METHODS

We retrieved PM_2.5 concentrations at the surface level from the ACAG and CAMSRA global air quality models for all 1,122 municipalities, and compare 28 of them with available concentrations from monitor stations. Annual mortality data 2014-2019 by municipality of residence and pooled effect measures for total, natural and specific causes of mortality were used to calculate the number of annual avoidable deaths and years of potential life lost (YPLL) related to the excess of PM_2.5 concentration over the current mean annual national standard of 25 µg/m³ and projected standard of 15 µg/m³.

RESULTS

Compared to surface data from 28 municipalities with monitoring stations in 2019, ACAG and CAMSRA models under or overestimated annual mean PM_2.5 concentrations. Estimations from ACAG model had a mean bias 1,7 µg/m³ compared to a mean bias of 4,7 µg/m³ from CAMSRA model. Using ACAG model, estimations of total nationally attributable deaths to PM_2.5 exposure over 25 and 15 µg/m³ were 142 and 34,341, respectively. Cardiopulmonary diseases accounted for most of the attributable deaths due to PM_2.5 excess of exposure (38%). Estimates of YPLL due to all-cause mortality for exceeding the national standard of 25 µg/m³ were 2,381 years.

CONCLUSION

Comparison of two global air quality models for estimating surface PM_2.5 concentrations during 2014-2019 at municipality scale in Colombia showed important differences. Avoidable deaths estimations represent the total number of deaths that could be avoided if the current and projected national standard for PM_2.5 annual mean have been met, and show the health-benefit of the implementation of more restrictive air quality standards.

Associations between short-term exposure of ambient particulate matter and hemodialysis patients death: A nationwide, longitudinal case-control study in China

BACKGROUND

Long-term exposure to particulate air pollutants can lead to an increase in mortality of hemodialysis patients, but evidence of mortality risk with short-term exposure to ambient particulate matter is lacking. This study aimed to estimate the association of short-term exposure to ambient particulate matter across a wide range of concentrations with hemodialysis patients mortality.

METHODS

We performed a time-stratified case-crossover study to estimate the association between short-term exposures to PM_2.5 and PM₁₀ and mortality of hemodialysis patients. The study included 18,114 hemodialysis death case from 279 hospitals in 41 cities since 2013. Daily particulate matter exposures were calculated by the inverse distance-weighted model based on each case's dialysis center address. Conditional logistic regression were implemented to quantify exposure-response associations. The sensitivity analysis mainly explored the lag effect of particulate matter.

RESULTS

During the study period, there were 18,114 case days and 61,726 control days. Of all case and control days, average PM_2.5 and PM₁₀ levels were 43.98 μg/m³ and 70.86 μg/m³, respectively. Each short-term increase of 10 μg/m³ in PM_2.5 and PM₁₀ were statistically significantly associated with a relative increase of 1.07 % (95 % confidence interval [CI]: 0.99 % - 1.15 %) and 0.89 % (95 % CI: 0.84 % - 0.94 %) in daily mortality rate of hemodialysis patients, respectively. There was no evidence of a threshold in the exposure-response relationship. The mean of daily exposure on the same day of death and one-day prior (Lag 01 Day) was the most plausible exposure time window.

CONCLUSIONS

This study confirms that short-term exposure to particulate matter leads to increased mortality in hemodialysis patients. Policy makers and public health practices have a clear and urgent opportunity to pass air quality control policies that care for hemodialysis populations and incorporate air quality into the daily medical management of hemodialysis patients.

Partitioning of reactive oxygen species from indoor surfaces to indoor aerosols

Reactive oxygen species (ROS) are among the species thought to be responsible for the adverse health effects of particulate matter (PM) inhalation. Field studies suggest that indoor sources of ROS contribute to measured ROS on PM in indoor air. We hypothesize that ozone reacts on indoor surfaces to form semi-volatile ROS, in particular organic peroxides (OPX), which partition to airborne particles. To test this hypothesis, we modeled ozone-induced formation of OPX, its decay and its partitioning to PM in a residential building and compared the results to field measurements. Simulations indicate that, while ROS of outdoor origin is the primary contributor to indoor ROS (in PM), a substantial fraction of ROS present in indoor PM is from ozone-surface chemistry. At an air change rate equal to 1/h, and an outdoor ozone mixing ratio of 35 ppb, 25% of the ROS concentration in air is due to indoor formation and partitioning of OPX to PM. For the same conditions, but with a modest indoor source of PM (1.5 mg h^-1), 44% of indoor ROS on PM is of indoor origin. An indoor source of ozone, such as an electrostatic air cleaner, also increases OPX present in indoor PM. The results of the simulations support the hypothesis that ozone-induced formation of OPX on indoor surfaces, and subsequent partitioning to aerosols, is sufficient to explain field observations. Therefore, indoor sourced ROS could contribute meaningfully to total inhaled PM-ROS.

Role of Secondary Organic Matter on Soot Particle Toxicity in Reconstituted Human Bronchial Epithelia Exposed at the Air-Liquid Interface

Secondary organic matter (SOM) formed from gaseous precursors constitutes a major mass fraction of fine particulate matter. However, there is only limited evidence on its toxicological impact. In this study, air-liquid interface cultures of human bronchial epithelia were exposed to different series of fresh and aged soot particles generated by a miniCAST burner combined with a micro smog chamber (MSC). Soot cores with geometric mean mobility diameters of 30 and 90 nm were coated with increasing amounts of SOM, generated from the photo-oxidation of mesitylene and ozonolysis of α-pinene. At 24 h after exposure, the release of lactate dehydrogenase (LDH), indicating cell membrane damage, was measured and proteome analysis, i.e. the release of 102 cytokines and chemokines to assess the inflammatory response, was performed. The data indicate that the presence of the SOM coating and its bioavailability play an important role in cytotoxicity. In particular, LDH release increased with increasing SOM mass/total particle mass ratio, but only when SOM had condensed on the outer surface of the soot cores. Proteome analysis provided further evidence for substantial interference of coated particles with essential properties of the respiratory epithelium as a barrier as well as affecting cell remodeling and inflammatory activity.

An enhanced loss function in deep learning model to predict PM2.5 in India

Fine particulate matter (PM2.5) is one of the major air pollutants and is an important parameter for measuring air quality levels. High concentrations of PM2.5 show its impact on human health, the environment, and climate change. An accurate prediction of fine particulate matter (PM2.5) is significant to air pollution detection, environmental management, human health, and social development. The primary approach is to boost the forecast performance by reducing the error in the deep learning model. So, there is a need to propose an enhanced loss function (ELF) to decrease the error and improve the accurate prediction of daily PM2.5 concentrations. This paper proposes the ELF in CTLSTM (Chi-Square test Long Short Term Memory) to improve the PM2.5 forecast. The ELF in the CTLSTM model gives more accurate results than the standard forecast models and other state-of-the-art deep learning techniques. The proposed ELFCTLSTM reduces the prediction error of by a maximum of 10 to 25 percent than the state-of-the-art deep learning models.

Indoor PM2.5 from occupied residences in Sweden caused higher inflammation in mice compared to outdoor PM2.5

We spend most of our time indoors; however, little is known about the effects of exposure to aerosol particles indoors. We aimed to determine differences in relative toxicity and physicochemical properties of PM_2.5 collected simultaneously indoors (PM_{2.5 INDOOR} ) and outdoors (PM_{2.5 OUTDOOR} ) in 15 occupied homes in southern Sweden. Collected particles were extracted from filters, pooled (indoor and outdoor separately), and characterized for chemical composition and endotoxins before being tested for toxicity in mice via intratracheal instillation. Various endpoints including lung inflammation, genotoxicity, and acute-phase response in lung and liver were assessed 1, 3, and 28 days post-exposure. Chemical composition of particles used in toxicological assessment was compared to particles analyzed without extraction. Time-resolved particle mass and number concentrations were monitored. PM_{2.5 INDOOR} showed higher relative concentrations (μg mg^-1 ) of metals, PAHs, and endotoxins compared to PM_{2.5 OUTDOOR} . These differences may be linked to PM_{2.5 INDOOR} causing significantly higher lung inflammation and lung acute-phase response 1 day post-exposure compared to PM_{2.5 OUTDOOR} and vehicle controls, respectively. None of the tested materials caused genotoxicity. PM_{2.5 INDOOR} displayed higher relative toxicity than PM_{2.5 OUTDOOR} under the studied conditions, that is, wintertime with reduced air exchange rates, high influence of indoor sources, and relatively low outdoor concentrations of PM. Reducing PM_{2.5 INDOOR} exposure requires reduction of both infiltration from outdoors and indoor-generated particles.

Exposure to fine particulate matter (PM2.5) from non-tobacco sources in homes within high-income countries: a systematic review

The health impacts associated with exposure to elevated concentrations of fine particulate matter (PM_2.5) are well recognised. There is a substantial number of studies characterising PM_2.5 concentrations outdoors, as well as in homes within low- and middle-income countries. In high-income countries (HICs), there is a sizeable literature on indoor PM_2.5 relating to smoking, but the evidence on exposure to PM_2.5 generated from non-tobacco sources in homes is sparse. This is especially relevant as people living in HICs spend the majority of their time at home, and in the northern hemisphere households often have low air exchange rates for energy efficiency. This review identified 49 studies that described indoor PM_2.5 concentrations generated from a variety of common household sources in real-life home settings in HICs. These included wood/solid fuel burning appliances, cooking, candles, incense, cleaning and humidifiers. The reported concentrations varied widely, both between sources and within groups of the same source. The burning of solid fuels was found to generate the highest indoor PM_2.5 concentrations. On occasion, other sources were also reported to be responsible for high PM_2.5 concentrations; however, this was only in a few select examples. This review also highlights the many inconsistencies in the ways data are collected and reported. The variable methods of measurement and reporting make comparison and interpretation of data difficult. There is a need for standardisation of methods and agreed contextual data to make household PM_2.5 data more useful in epidemiological studies and aid comparison of the impact of different interventions and policies.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s11869-022-01288-8.

Rnf20 inhibition enhances immunotherapy by improving regulatory T cell generation

BACKGROUND

Allergic disorders are common all over the world. The pathogenesis of allergy is unclear. Therapies for allergic disorders require improvement. Endoplasmic reticulum (ER) stress is one of the factors influencing immune response. The purpose of this study is to improve the effectiveness of immunotherapy for experimental respiratory allergy by targeting the ER stress signal pathway.

METHODS

Committed CD4⁺ T cells were isolated from blood samples collected from patients with allergic rhinitis (AR) and TCR ovalbumin transgenic mice. The effects of TCR engagement and 3-methyl-4-nitrophenol (MNP) on inducing ER stress in committed CD4⁺ T cells were evaluated.

RESULTS

ER stress was detected in antigen-specific CD4⁺ T cells (sCD4⁺ T cells) of AR patients. The environmental pollutant MNP increased the expression of the X-binding protein-1 (XBP1) in the committed CD4⁺ T cells during the TCR engagement. XBP1 mediated the effects of MNP on inhibiting regulatory T cell (Treg) generation. The effects of MNP on induction of protein 20 (Rnf20) in CD4⁺ T cells were mediated by XBP1. Inhibition of Rnf20 rescued the Treg development from MNP-primed sCD4⁺ T cells. The ablation of Rnf20 improved the immunotherapy of AR through the restoration of the Treg generation.

CONCLUSIONS

ER stress can be detected in CD4⁺ T cells in TCR engagement. Exposure to MNP exacerbates ER stress in committed CD4⁺ T cells. Regulation of the ER stress-related Rnf20 expression can restore the generation of Treg from CD4⁺ T cells of subjects with allergic diseases.

Insights to the 3D internal morphology and metal oxidation states of single atmospheric aerosol particles by synchrotron-based methodology

The morphology and metal oxidation states of atmospheric aerosols are pertinent to their formation processes and ensuing interactions with surrounding gases, vapors and other environments upon deposition, such as human respiratory tract, soil and water. Although much progress has been made in recent years through single-particle techniques, considerably less is known with respect to the three-dimensional (3D) internal morphology of single atmospheric aerosol particles due to the limited penetration depth of electron microscopy. In this study, for the first time, a novel synchrotron-based transmission X-ray microscopy (TXM) methodology has been developed to visualize the 3D internal chemical mixing state and structure of single particles. The results show that the TXM is more applicable to the imaging of solid particles containing high-density elements, e.g., iron (Fe), aluminum (Al), silicone (Si), carbon (C) and sulfur (S), and/or solid particles of sizes larger than about 100 nm. In addition, the TXM is capable to reveal the fine 3D topographic features of single particles. The derived 3D internal and external information would be difficult to discern in the 2D images from electron microscopy. The TXM 3D images illustrate that aerosol particles exhibit complex internal mixing state and structure, e.g., homogeneously-, heterogeneously-mixed, multiple inclusions, fibrous, porous, and core-shell configuration. When coupled with the synchrotron-based X-ray fluorescence spectrometry (XRF) and absorption near-edge spectroscopy (XANES) of an X-ray nanoprobe in the energy range of 4-15 keV, the 3D morphology of single particles is further supplemented with the spatial distribution and oxidation sates of selected elements, including Fe, vanadium (V), manganese (Mn), chromium (Cr) and arsenic (As). The presented cross-platform, synchrotron-based methodology shows promise in complementing existing single-particle techniques and providing new insights to the heterogeneity of single-particle micro-physicochemical states relevant to the aerosol chemistry, optical properties, and their environmental and health impacts.