Transient risk of ambient fine particulate matter on hourly cardiovascular events in Tainan City, Taiwan

Health impact assessment of PM2.5 from uncovered coal trains in the San Francisco Bay Area: Implications for global exposures

Coal generates almost 40% of the world's electricity with 80 countries throughout the world using coal power. An inherent part of this generation is the rail transport of coal in uncovered cars, often up to a mile long. Existing studies document the subsequent increments of PM2.5 to the near-rail populations, which typically include a large number of economically disadvantaged residents and/or people of color. However, to date there is no assessment of the health implications of this stage in the use of coal. The present study quantifies such impacts on a region in the San Francisco Bay Area. The analysis shows important effects on mortality, hospitalization for cardiovascular and respiratory disease, asthma exacerbation, work loss, and days of restricted activity. Several of these outcomes exhibited a one to six percent increase over baseline. As such, it delineates the implications for the global effects of the transport of coal.

Sequence-oriented sensitive analysis for PM2.5 exposure and risk assessment using interactive process mining

The World Health Organization has estimated that air pollution will be one of the most significant challenges related to the environment in the following years, and air quality monitoring and climate change mitigation actions have been promoted due to the Paris Agreement because of their impact on mortality risk. Thus, generating a methodology that supports experts in making decisions based on exposure data, identifying exposure-related activities, and proposing mitigation scenarios is essential. In this context, the emergence of Interactive Process Mining-a discipline that has progressed in the last years in healthcare-could help to develop a methodology based on human knowledge. For this reason, we propose a new methodology for a sequence-oriented sensitive analysis to identify the best activities and parameters to offer a mitigation policy. This methodology is innovative in the following points: i) we present in this paper the first application of Interactive Process Mining pollution personal exposure mitigation; ii) our solution reduces the computation cost and time of the traditional sensitive analysis; iii) the methodology is human-oriented in the sense that the process should be done with the environmental expert; and iv) our solution has been tested with synthetic data to explore the viability before the move to physical exposure measurements, taking the city of Valencia as the use case, and overcoming the difficulty of performing exposure measurements. This dataset has been generated with a model that considers the city of Valencia's demographic and epidemiological statistics. We have demonstrated that the assessments done using sequence-oriented sensitive analysis can identify target activities. The proposed scenarios can improve the initial KPIs-in the best scenario; we reduce the population exposure by 18% and the relative risk by 12%. Consequently, our proposal could be used with real data in future steps, becoming an innovative point for air pollution mitigation and environmental improvement.

The impact of coal trains on PM2.5 in the San Francisco Bay area

Exposure to fine particulate matter (PM2.5) is associated with adverse health effects, including mortality, even at low concentrations. Rail conveyance of coal, accounting for one-third of American rail freight tonnage, is a source of PM2.5. However, there are limited studies of its contribution to PM2.5, especially in urban settings where residents experience higher exposure and vulnerability to air pollution. We developed a novel artificial intelligence-driven monitoring system to quantify average and maximum PM2.5 concentrations of full and empty (unloaded) coal trains compared to freight and passenger trains. The monitor was close to the train tracks in Richmond, California, a city with a racially diverse population of 115,000 and high rates of asthma and heart disease. We used multiple linear regression models controlling for diurnal patterns and meteorology. The results indicate coal trains add on average 8.32 µg/m3 (95% CI = 6.37, 10.28; p < 0.01) to ambient PM2.5, while sensitivity analysis produced midpoints ranging from 5 to 12 µg/m3. Coal trains contributed 2 to 3 µg/m3 more of PM2.5 than freight trains, and 7 µg/m3 more under calm wind conditions, suggesting our study underestimates emissions and subsequent concentrations of coal train dust. Empty coal cars tended to add 2 µg/m3. Regarding peak concentrations of PM2.5, our models suggest an increase of 17.4 µg/m3 (95% CI = 6.2, 28.5; p < 0.01) from coal trains, about 3 µg/m3 more than freight trains. Given rail shipment of coal occurs globally, including in populous areas, it is likely to have adverse effects on health and environmental justice.

High levels of indoor fine particulate matter during the cold season in Almaty prompt urgent public health action

INTRODUCTION

Almaty is the largest city of Kazakhstan with extreme air pollution, mostly in the cold season, but little is known whether staying indoors could lessen the exposure. The aim was to quantitatively characterize indoor fine PM levels and to verify the contribution of ambient pollution to it in a polluted city like Almaty.

METHODS

We collected forty-six 24-hour 15-min average samples of the ambient air and a similar number of paired indoor samples (total 92 samples). Predictors of both ambient and indoor PM2.5 mass concentrations in mg/m3, including ambient concentration, precipitation, minimal daily temperature and humidity, along with the indoor/outdoor (I/O) ratio were tested in the adjusted regression models at eight 15-min lags.

RESULTS

Ambient air PM2.5 15-min average mass concentrations were highly variable and ranged from 0.001 to 0.694 mg/m3 (geometric mean (GM) 0.090, geometric standard deviation (GSD) 2.285). Snowing was the strongest predictor of lower ambient PM2.5 24-hour mass concentrations (median 0.053 vs 0.135 mg/m3 (p<0.001)). Indoor mean 15-min PM2.5 concentrations ranged from 0.002 to 0.228 mg/m3 (GM 0.034, GSD 2.254). In adjusted models, outdoor PM2.5 concentration explained 0.58 of all variability of the indoor concentration with a 75-min delay (R2 0.67 at lag8 on snowing days). Median I/O ranged from 0.386 (IQR 0.264 to 0.532) at lag0 to 0.442 (IQR 0.339 to 0.584) at lag8.

CONCLUSION

During the cold season when fossil fuel is burnt for heating, the population in Almaty is exposed to very high fine PM levels even indoors. Urgent public health action is needed.

A systematic review and meta-analysis of intraday effects of ambient air pollution and temperature on cardiorespiratory morbidities: First few hours of exposure matters to life

BACKGROUND

A growing number of studies have reported an increased risk of cardiovascular disease (CVD) and respiratory disease (RD) within hours after exposure to ambient air pollution or temperature. We assemble published evidence on the sub-daily associations of CVD and RD with ambient air pollution and temperature.

METHODS

Databases of PubMed and Web of Science were searched for original case-crossover and time-series designs of English articles examining the intra-day effects of ambient air pollution [particulate matter with aerodynamic diameter ≤2.5 μm (PM_2.5), ≤10 μm (PM₁₀), 2.5-10μm (PM_10-2.5), and < 7 μm (SPM), O₃, SO₂, NO₂, CO, and NO] and temperatures (heat and cold) on cardiorespiratory diseases within 24 h after exposure in the general population by comparing with exposure at different exposure levels or periods. Meta-analyses were conducted to pool excess risks (ERs, absolute percentage increase in risk) of CVD and RD morbidities associated with an increase of 10 μg/m³ in particulate matters, 0.1 ppm in CO, and 10 ppb in other gaseous pollutants.

FINDINGS

Final analysis included thirty-three papers from North America, Europe, Oceania, and Asia. Meta-analysis found an increased risk of total CVD morbidity within 3 h after exposure to PM_2.5 [ER%: 2.65% (95% CI: 1.00% to 4.34%)], PM_10-2.5 [0.31% (0.02% to 0.59%)], O₃ [1.42% (0.14% to 2.73%)], and CO [0.41% (0.01% to 0.81%)]. The risk of total RD morbidity elevated at lag 7-12 h after exposure to PM_2.5 [0.69% (0.14% to 1.24%)] and PM₁₀ [0.38% (0.02% to 0.73%)] and at lag 12-24 h after exposure to SO₂ [2.68% (0.94% to 4.44%)]. Cause-specific CVD analysis observed an increased risk of myocardial infarction morbidity within 6 h after exposure to PM_2.5, PM₁₀, and NO₂, and an increased risk of out-of-hospital cardiac arrest morbidity within 12 h after exposure to CO. Risk of total CVD also increased within 24 h after exposure to heat.

INTERPRETATION

This study supports a sudden risk increase of cardiorespiratory diseases within a few hours after exposure to air pollution or heat, and some acute and highly lethal diseases such as myocardial infarction and cardiac arrest could be affected within a shorter time.

FUNDING

The National Natural Science Foundation of China (Grant No. 42105165; 81773518), the High-level Scientific Research Foundation of Anhui Medical University (Grant No. 0305044201), and the Discipline Construction of Anhui Medical University (Grant No. 0301001836).

Tussilagone protects acute lung injury from PM2.5 via alleviating Hif-1α/NF-κB-mediated inflammatory response

Environmental pollution, especially particulate matter in the air, is a serious threat to human health. Long-term inhalation of particulate matter with a diameter < 2.5 μm (PM2.5) induced irreversible respiratory and lung injury. However, it is not clear whether temporary exposure to massive PM2.5 would result in epithelial damage and lung injury. More importantly, it is urgent to clarify the mechanisms of PM2.5 cytotoxicity and develop a defensive and therapeutic approach. In this study, we demonstrated that temporary exposure with PM2.5 induced lung epithelial cell apoptosis via promoting cytokines expression and inflammatory factors secretion. The cytotoxicity of PM2.5 could be alleviated by tussilagone (TSL), which is a natural compound isolated from the flower buds of Tussilago farfara. The mechanism study indicated that PM2.5 promoted the protein level of Hif-1α by reducing its degradation mediated by PHD2 binding, which furtherly activated NF-κB signaling and inflammatory response. Meanwhile, TSL administration facilitated the interaction of the Hif-1α/PHD2 complex and restored the Hif-1α protein level increased by PM2.5. When PHD2 was inhibited in epithelial cells, the protective function of TSL on PM2.5 cytotoxicity was attenuated and the expression of cytokines was retrieved. Expectedly, the in vivo study also suggested that temporary PM2.5 exposure led to acute lung injury. TSL treatment could effectively relieve the damage and decrease the expression of inflammatory cytokines by repressing Hif-1α level and NF-κB activation. Our findings provide a new therapeutic strategy for air pollution-related respiratory diseases, and TSL would be a potential preventive medicine for PM2.5 cytotoxicity.