Short-Term Impact of Traffic-Related Particulate Matter and Noise Exposure on Cardiac Function

Cyclists' exposure to air pollution, noise, and greenery: a population-level spatial analysis approach

Urban travel exposes people to a range of environmental qualities with significant health and wellbeing impacts. Nevertheless, the understanding of travel-related environmental exposure has remained limited. Here, we present a novel approach for population-level assessment of multiple environmental exposure for active travel. It enables analyses of (1) urban scale exposure variation, (2) alternative routes' potential to improve exposure levels per exposure type, and (3) by combining multiple exposures. We demonstrate the approach's feasibility by analysing cyclists' air pollution, noise, and greenery exposure in Helsinki, Finland. We apply an in-house developed route-planning and exposure assessment software and integrate to the analysis 3.1 million cycling trips from the local bike-sharing system. We show that especially noise exposure from cycling exceeds healthy thresholds, but that cyclists can influence their exposure by route choice. The proposed approach enables planners and individual citizens to identify (un)healthy travel environments from the exposure perspective, and to compare areas in respect to how well their environmental quality supports active travel. Transferable open tools and data further support the implementation of the approach in other cities.

Noise Disturbance and Well-Being in the North of Spain

Environmental noise is considered one of the main risks for physical and mental health and well-being, with a significant associated burden of disease in Europe. This work aims to explore the main sources of noise exposure at home and its effect on well-being in northern Spain. A transversal opinion study has been performed through a closed questionnaire. The questionnaire included three different parts: sociodemographic data, noise disturbance, and the 5-item World Health Organization Well-Being Index (WHO-5). A Binary Logistics Regression model was performed to analyze the relationship between noise exposure and well-being. Overall, 16.6% of the participants consider that the noise isolation of their homes is bad or very bad. The noise generated by the neighbors (air and impact noise) is considered the most disturbing indoor noise source, while street works are the most disturbing outdoor noise source in urban areas and road traffic is the most disturbing in rural areas. People who indicate that noise interferes with their life at home have a worse score on the WHO-5 (decreased perception of well-being). The exposure to outdoor noise (specifically the noise coming from the street and trains), internal impact noise produced by neighbors, and in general, the noise that wakes you up, is related to receiving a worse score in the WHO-5 (p < 0.05). Administrative bodies must ensure that laws regulating at-home noise levels, which are continually being updated with stricter restrictions, are enforced.

Associations between personal noise exposure and heart rate variability were modified by obesity and PM2.5: The study among obese and normal-weight adults (SONA)

Noise pollution has been documented to increase the risks of cardiovascular disorders, which can be predicted by heart rate variability (HRV), nevertheless, there has been limited evidence on the modifiers of noise pollution. Environmental fine particulate matter (PM_2.5) and obesity status are both growing major concerns of cardiovascular disease burden. Our study aims to investigate whether these two factors may modify the associations between noise exposure and HRV indices. An investigation was performed on 97 (53 normal-weight and 44 obese) participants aged 18-26 years, with continuous 5-min personal exposure assessment and ambulatory electrocardiogram monitoring for 24 h. This study found that personal exposure to noise was associated with decreased HRV level and imbalanced cardiac autonomic function, as indicated by decreases in standard deviation of normal-to-normal intervals (SDNN), square root of the mean squared differences of successive intervals (rMSSD), the percentage of R-R intervals that differ from each other by more than 50 ms (pNN50), low-frequency (LF) power, high-frequency (HF) power, and increases in LF-HF-Ratio. Stronger associations between personal noise exposure and HRV indices were observed among obese participants and participants with higher PM_2.5 exposure levels compared to their counterparts. For SDNN, a 1 dB(A) increment in personal noise exposure at 3h-average was associated with a 1.25% (95%CI: -1.64%, -0.86%) decrease among obese participants, and a 0.11% (95%CI: -0.38%, 0.16%) decrease among normal-weight participants (P for subgroup difference<0.001); and a 0.87% (95%CI: -1.20%, -0.54%) decrease among participants with higher PM_2.5 exposure levels, and a 0.22% (95%CI: -0.58%, 0.14%) decrease among participants with lower PM_2.5 exposure levels (P for subgroup difference = 0.008). Obesity and PM_2.5 may aggravate the adverse effects of noise on HRV, which has implications for targeted prevention of cardiovascular disease burden associated with noise pollution.

A controlled chamber study of effects of exposure to diesel exhaust particles and noise on heart rate variability and endothelial function

BACKGROUND

Adverse cardiovascular effects are associated with both diesel exhaust and road traffic noise, but these exposures are hard to disentangle epidemiologically. We used an experimental setup to evaluate the impact of diesel exhaust particles and traffic noise, alone and combined, on intermediary outcomes related to the autonomic nervous system and increased cardiovascular risk.

METHODS

In a controlled chamber 18 healthy adults were exposed to four scenarios in a randomized cross-over fashion. Each exposure scenario consisted of either filtered (clean) air or diesel engine exhaust (particle mass concentrations around 300 µg/m³), and either low (46 dB(A)) or high (75 dB(A)) levels of traffic noise for 3 h at rest. ECG was recorded for 10-min periods before and during each exposure type, and frequency-domain heart rate variability (HRV) computed. Endothelial dysfunction and arterial stiffness were assessed after each exposure using EndoPAT 2000.

RESULTS

Compared to control exposure, HRV in the high frequency band decreased during exposure to diesel exhaust, both alone and combined with noise, but not during noise exposure only. These differences were more pronounced in women. We observed no synergistic effects of combined exposure, and no significant differences between exposure scenarios for other HRV indices, endothelial function or arterial stiffness.

CONCLUSION

Three-hour exposure to diesel exhaust, but not noise, was associated with decreased HRV in the high frequency band. This indicates activation of irritant receptor-mediated autonomic reflexes, a possible mechanism for the cardiovascular risks of diesel exposure. There was no effect on endothelial dysfunction or arterial stiffness after exposure.

Acute cardiovascular effects of traffic-related air pollution (TRAP) exposure in healthy adults: A randomized, blinded, crossover intervention study

Exposure to traffic-related air pollution (TRAP) may enhance the risk of cardiovascular disease. However, the short-term effects of TRAP components on the cardiovascular system are not well understood. We conducted a randomized, double-blinded, crossover intervention study in which 39 healthy university students spent 2 h next to a busy road. Participants wore a powered air-purifying respirator (PAPR) or an N95 mask. PAPRs were equipped with a filter for particulate matter (PM), a PM and volatile organic compounds (VOCs) filter or a sham filter. Participants were blinded to PAPR filter type and underwent randomized exposures four times, once for each intervention mode. Blood pressure (BP), heart rate (HR) and heart rate variability (HRV) were measured before, during and for 6 h after the roadside exposure. Linear mixed-effect models were used to evaluate the effects of the interventions relative to baseline controlling for other covariates. All HRV measures increased during and following exposure for all intervention modes. Some HRV measures (SDNN and rMSSD during exposure and SDNN after exposure) were marginally affected by PM filtration. Wearing the N95 mask affected VLF power and rMSSD responses to traffic exposure differently than the PAPR interventions. Both systolic and diastolic BP increased slightly during exposure, but then were generally lower than baseline after exposure for the sham and filter interventions. HR, which fell during exposure and mostly remained lower than baseline after exposure, was lower yet with all filter interventions compared to the sham mode following exposure. Therefore, short-term exposure to traffic acutely affects HRV, BP and HR, but N95 mask and PAPR interventions generally show little efficacy in reducing these effects. Removing the PM component of TRAP has some limited effects on HRV responses to exposure but exaggerates the traffic-related decrease in HR. HRV findings from N95 mask interventions need to be interpreted cautiously.

Demonstrating the Applicability of Smartwatches in PM2.5 Health Impact Assessment

Smartwatches are being increasingly used in research to monitor heart rate (HR). However, it is debatable whether the data from smartwatches are of high enough quality to be applied in assessing the health impacts of air pollutants. The objective of this study was to assess whether smartwatches are useful complements to certified medical devices for assessing PM_2.5 health impacts. Smartwatches and medical devices were used to measure HR for 7 and 2 days consecutively, respectively, for 49 subjects in 2020 in Taiwan. Their associations with PM_2.5 from low-cost sensing devices were assessed. Good correlations in HR were found between smartwatches and certified medical devices (r_s > 0.6, except for exercise, commuting, and worshipping). The health damage coefficients obtained from smartwatches (0.282% increase per 10 μg/m³ increase in PM_2.5) showed the same direction, with a difference of only 8.74% in magnitude compared to those obtained from certified medical devices. Additionally, with large sample sizes, the health impacts during high-intensity activities were assessed. Our work demonstrates that smartwatches are useful complements to certified medical devices in PM_2.5 health assessment, which can be replicated in developing countries.

Ambient air PM2.5 exposure induces heart injury and cardiac hypertrophy in rats through regulation of miR-208a/b, α/β-MHC, and GATA4

Ambient air fine particulate matter (PM2.5) may increase cardiovascular disease risks. In this study, we investigated the miR-208/GATA4/myosin heavy chain (MHC) regulation mechanisms on cardiac injury in rats after PM2.5 exposure via an animal inhalation device. The results showed that PM2.5 exposure for 2 months caused pathological heart injury, reduced nucleus-cytoplasm ratio, and increased the levels of CK-MB and cTnI, showing cardiac hypertrophy. Oxidative stress and inflammatory responses were also observed in rats' hearts exposed to PM2.5. Of note, PM2.5 exposure for 2-month significantly elevated GATA4 and β-MHC mRNA and protein expression compared with the corresponding controls, along with the high-expression of miR-208b. The ratios of β-MHC/α-MHC expression induced by PM2.5 were remarkably raised in comparison to their controls. It suggested that the up-regulation of miR-208b/β-MHC and GATA4 and the conversion from α-MHC to β-MHC may be the important causes of cardiac hypertrophy in rats incurred by PM2.5.

Estimation of the Inhaled Dose of Pollutants in Different Micro-Environments: A Systematic Review of the Literature

Recently, the need to assess personal exposure in different micro-environments has been highlighted. Further, estimating the inhaled dose of pollutants is considerably one of the most interesting parameters to be explored to complete the fundamental information obtained through exposure assessment, especially if associated with a dose-response approach. To analyze the main results obtained from the studies related to the estimation of the inhaled dose of pollutants in different micro-environments (environments in which an individual spends a part of his day), and to identify the influence of different parameters on it, a systematic review of the literature was performed. The principal outcomes from the considered studies outlined that (i) exposure concentration and residence time are among the most important parameters to be evaluated in the estimation of the inhaled dose, especially in transport environments. Further, (ii) the pulmonary ventilation rate can be of particular interest during active commuting because of its increase, which increases the inhalation of pollutants. From a methodological point of view, the advent of increasingly miniaturized, portable and low-cost technologies could favor these kinds of studies, both for the measurement of atmospheric pollutants and the real-time evaluation of physiological parameters used for estimation of the inhaled dose. The main results of this review also show some knowledge gaps. In particular, numerous studies have been conducted for the evaluation (in terms of personal exposure and estimation of the inhaled dose) of different PM fractions: other airborne pollutants, although harmful to human health, are less represented in studies of this type: for this reason, future studies should be conducted, also considering other air pollutants, not neglecting the assessment of exposure to PM. Moreover, many studies have been conducted indoors, where the population spends most of their daily time. However, it has been highlighted how particular environments, even if characterized by a shorter residence time, can contribute significantly to the dose of inhaled pollutants. These environments are, therefore, of particular importance and should be better evaluated in future studies, as well as occupational environments, where the work results in a high pulmonary ventilation rate. The attention of future studies should also be focused on these categories of subjects and occupational studies.

Cycling in one of the most polluted cities in the world: Exposure to noise and air pollution and potential adverse health impacts in Delhi

Background

In India, many cities struggle with extreme levels of air pollution and noise. Delhi, in particular, has the notorious reputation of being one of the most polluted cities in the world. Cyclists constitute a particularly exposed population, since they cycle among motor vehicles without any protection. This paper modeled the cyclists’ exposure to nitrogen dioxide (NO₂) and noise in Delhi, India.

Methods

Using primary data collected on 1,229 kms of roads in Delhi, Generalized Additive Mixed Models with Auto-Regressive terms (GAMMAR) are constructed for noise exposure, NO₂ exposure and NO₂ inhalation doses.

Results

Results show that cyclists are exposed to 47 µg/m³ of NO₂ and 3.3 dB(A) more when cycling on a primary road than on a residential street. Using WHO guideline values for noise and air pollution, we assessed how many minutes of inhaling doses and noise doses become potentially harmful to cyclists’ health in Delhi. Such thresholds are quickly exceeded: after cycling one hour in an area with moderate predicted values of noise and air pollution, the noise dose and inhaled dose of NO₂ will reach 212% and 403 µg on residential streets, and 459% and 482 µg on primary roads, respectively.

Conclusion

Policy makers should take these results into account to minimize cyclists’ exposure, especially for the most deprived people.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12942-021-00272-2.

Research on Energy Management of Hybrid Unmanned Aerial Vehicles to Improve Energy-Saving and Emission Reduction Performance

The rapid development of industry results in large energy consumption and a negative impact on the environment. Pollution of the environment caused by conventional energy sources such as petrol leads to increased demand for propulsion systems with higher efficiency and capable of energy-saving and emission reduction. The usage of hybrid technology is expected to improve energy conversion efficiency, reduce energy consumption and environmental pollution. In this paper, the simulation platform for the hybrid unmanned aerial vehicle (UAV) has been built by establishing the subsystem models of the UAV power system. Under the two chosen working conditions, the conventional cruise flight mission and the terrain tracking mission, the power tracking control and Q-Learning method have been used to design the energy management controller for the hybrid UAV. The fuel consumption and pollutant emissions under each working condition were calculated. The results show that the hybrid system can improve the efficiency of the UAV system, reduce the fuel consumption of the UAV, and so reduce the emissions of CO₂, NO_x, and other pollutants. This contributes to improving of environmental quality, energy-saving, and emission reduction, thereby contributing to the sustainable development of aviation.

Meteorological Variables and Synoptic Patterns Associated with Air Pollutions in Eastern China during 2013-2018

Steady meteorological conditions are important external factors affecting air pollution. In order to analyze how adverse meteorological variables affect air pollution, surface synoptic situation patterns and meteorological conditions during heavy pollution episodes are discussed. The results showed that there were 78 RPHPDs (regional PM_2.5 pollution days) in Jiangsu, with a decreasing trend year by year. Winter had the most stable meteorological conditions, thus most RPHPDs appeared in winter, followed by autumn and summer, with the least days in spring. RPHPDs were classified into three patterns, respectively, as equalized pressure (EQP), advancing edge of a cold front (ACF) and inverted trough of low pressure (INT) according to the SLP (sea level pressure). RPHPDs under EQP were the most (51%), followed by ACF (37%); INT was the minimum (12%). Using statistical methods and meteorological condition data on RPHPDs from 2013 to 2017 to deduce the thresholds and 2018 as an independent dataset to validate the proposed thresholds, the threshold values of meteorological elements are summarized as follows. The probability of RPHPDs without rain was above 92% with the daily and hourly precipitation of all RPHPDs below 2.1 mm and 0.8 mm. Wind speed, RHs, inversion intensity(ITI), height difference in the temperature inversion(ITK), the lower height of temperature inversion (LHTI) and mixed-layer height (MLH) in terms of 25%–75% high probability range were respectively within 0.5–3.6 m s⁻¹, 55%–92%, 0.7–4.0 °C 100 m ⁻¹, 42–576 m, 3–570 m, 200–1200 m. Two conditions should be considered: whether the pattern was EQP, ACF or INT and whether the eight meteorological elements are within the thresholds. If both criteria are met, PM_2.5 particles tend to accumulate and air pollution diffusion conditions are poor. Unfavorable meteorological conditions are the necessary, but not sufficient condition for RPHPDs.