Impacts on human mortality due to reductions in PM10 concentrations through different traffic scenarios in Paris, France

Electric vehicles and health: A scoping review

BACKGROUND

The health impacts of the rapid transition to the use of electric vehicles are largely unexplored. We completed a scoping review to assess the state of the evidence on use of battery electric and hybrid electric vehicles and health.

METHODS

We conducted a literature search of MEDLINE, Embase, Global Health, CINAHL, Scopus, and Environmental Science Collection databases for articles published January 1990 to January 2024. We included articles if they presented observed or modeled data on the association between battery electric or hybrid electric cars, trucks, or buses and health-related outcomes. We abstracted data and summarized results.

RESULTS

Out of 897 reviewed articles, 52 met our inclusion criteria. The majority of included articles examined transitions to the use of electric vehicles (n = 49, 94%), with fewer studies examining hybrid electric vehicles (n = 11, 21%) or plug-in hybrid electric vehicles (n = 8, 15%). The most common outcomes examined were premature death (n = 41, 79%) and monetized health outcomes such as medical expenditures (n = 33, 63%). We identified only one observational study on the impact of electric vehicles on health; all other studies reported modeled data. Almost every study (n = 51, 98%) reported some evidence of a positive health impact of transitioning to electric or hybrid electric vehicles, although magnitudes of association varied. There was a paucity of information on the environmental justice implications of vehicle transitions.

CONCLUSIONS

The results of the current literature on electric vehicles and health suggest an overall positive health impact of transitioning to electric vehicles. Additional observational studies would help expand our understanding of the real-world health effects of electric vehicles. Future research focused on the environmental justice implications of vehicle fleet transitions could provide additional information about the extent to which the health benefits occur equitably across populations.

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.

Spatial Distribution of PM2.5 Mass and Number Concentrations in Paris (France) from the Pollutrack Network of Mobile Sensors during 2018-2022

The presence of particulate matter smaller than 2.5 µm in diameter (PM2.5) in ambient air has a direct pejorative effect on human health. It is thus necessary to monitor the urban PM2.5 values with high spatial resolution to better evaluate the different exposure levels that the population encounters daily. The Pollutrack network of optical mobile particle counters on the roofs of hundreds of vehicles in Paris was used to produce maps with a 1 km2 resolution (108 squares to cover the Paris surface). The study was conducted during the 2018-2022 period, showing temporal variability due to different weather conditions. When averaging all the data, the highest air pollution was found along the Paris motorway ring. Also, the mean mass concentrations of PM2.5 pollution increased from southwest to northeast, due to the typology of the city, with the presence of canyon streets, and perhaps due to the production of secondary aerosols during the transport of airborne pollutants by the dominant winds. The number of days above the new daily threshold of 15 µg.m-3 recommended by the WHO in September 2021 varies from 3.5 to 7 months per year depending on the location in Paris. Pollutrack sensors also provide the number concentrations for particles greater than 0.5 µm. Using number concentrations of very fine particles instead of mass concentrations corresponding to the dry residue of PM2.5 is more representative of the pollutants citizens actually inhale. Some recommendations for the calibration of the sensors used to provide such number concentrations are given. Finally, the consequences of such pollution on human health are discussed.

Sports Utility Vehicles: A Public Health Model of Their Climate and Air Pollution Impacts in the United Kingdom

The emission benefits of shifting towards battery electric vehicles have so far been hampered by a trend towards sports utility vehicles (SUVs). This study assesses the current and future emissions from SUVs and their potential impact on public health and climate targets. We modelled five scenarios of varying SUV sales and electrification rates, and projected associated carbon dioxide (CO2) and nitrogen oxide (NOx) emissions. Multiple linear regression was used to determine the relationship between vehicle characteristics and emissions. Cumulative CO2 emissions were valued using the social cost of carbon approach. Life table analyses were used to project and value life years saved from NOx emission reductions. Larger SUVs were disproportionately high emitters of CO2 and NOx. Replacing these with small SUVs achieved significant benefits, saving 702 MtCO2e by 2050 and 1.8 million life years from NO2 reductions. The largest benefits were achieved when combined with electrification, saving 1181 MtCO2e and gaining 3.7 million life years, with a societal value in the range of GBP 10-100s billion(s). Downsizing SUVs could be associated with major public health benefits from reduced CO2 and NOx emissions, in addition to the benefits of electrification. This could be achieved by demand-side mass-based vehicle taxation and supply-side changes to regulations, by tying emission limits to a vehicle's footprint rather than its mass.

California's early transition to electric vehicles: Observed health and air quality co-benefits

The transition to electric vehicles is projected to have considerable public health co-benefits, but most evidence regarding air quality and health impacts comes from projections rather than real-world data. We evaluated whether population-level respiratory health and air quality co-benefits were already detectable at the relatively low levels of zero-emissions vehicles (ZEVs: battery electric, plug-in hybrid, hydrogen fuel cell vehicle) adoption in California, and evaluated the ZEV adoption gap in underserved communities. We conducted a zip code-level ecologic study relating changes in annual number of ZEVs (nZEV) per 1000 population from 2013 to 2019 to: (i) annual average monitored nitrogen dioxide (NO2) concentrations and (ii) annual age-adjusted asthma-related emergency department (ED) visit rates, while considering educational attainment. The average nZEV increased from 1.4 per 1000 population in 2013 (standard deviation [SD]: 2.1) to 14.7 per 1000 in 2019 (SD: 14.7). ZEV adoption was considerably slower in zip codes with lower educational attainment (p < 0.0001). A within-zip code increase of 20 ZEVs per 1000 was associated with a - 0.41 ppb change in annual average NO2 (95 % confidence interval [CI]:-1.12, 0.29) in an adjusted model. A within-zip code increase of 20 ZEVs per 1000 population was associated with a 3.2 % decrease in annual age-adjusted rate of asthma-related ED visits (95 % CI:-5.4, -0.9). Findings were supported by a variety of sensitivity analyses. Observational data on the early phase ZEV transition in California provided a natural experiment, enabling us to document the first real-world associations between increasing nZEV and changes in air quality and health. Results suggest co-benefits of the early-phase transition to ZEVs but with an adoption gap among populations with lower socioeconomic status which threatens the equitable distribution of possible co-benefits.

Spatio-temporal visualization and forecasting of [Formula: see text] in the Brazilian state of Minas Gerais

Air pollution due to air contamination by gases, liquids, and solid particles in suspension, is a great environmental and public health concern nowadays. An important type of air pollution is particulate matter with a diameter of 10 microns or less ([Formula: see text]) because one of the determining factors that affect human health is the size of particles in the atmosphere due to the degree of permanence and penetration they have in the respiratory system. Therefore, it is extremely interesting to monitor and understand the behavior of [Formula: see text] concentrations so that they do not exceed the established critical levels. In this work, we will study the [Formula: see text] concentrations in all available monitoring stations in the Brazilian state of Minas Gerais. To better understand its behavior, we will provide a spatio-temporal visualization of the [Formula: see text] concentrations. Besides the descriptive and visualization analysis, we consider six standard and advanced time series models that will be used to fit and forecast [Formula: see text] concentrations, with application to three locations, one in Belo Horizonte, the Minas Gerais state capital, and the monitoring stations with the lowest and highest average [Formula: see text] concentration levels.

Statistical modeling approach for PM10 prediction before and during confinement by COVID-19 in South Lima, Perú

A total of 188,859 meteorological-PM$$_{10}$$ 10 data validated before (2019) and during the COVID-19 pandemic (2020) were used. In order to predict PM$$_{10}$$ 10 in two districts of South Lima in Peru, hourly, daily, monthly and seasonal variations of the data were analyzed. Principal Component Analysis (PCA) and linear/nonlinear modeling were applied. The results showed the highest annual average PM$$_{10}$$ 10 for San Juan de Miraflores (SJM) (PM$$_{10}$$ 10 -SJM: 78.7 $$\upmu$$ μ g/m$$^{3}$$ 3 ) and the lowest in Santiago de Surco (SS) (PM$$_{10}$$ 10 -SS: 40.2 $$\upmu$$ μ g/m$$^{3}$$ 3 ). The PCA showed the influence of relative humidity (RH)-atmospheric pressure (AP)-temperature (T)/dew point (DP)-wind speed (WS)-wind direction (WD) combinations. Cool months with higher humidity and atmospheric instability decreased PM$$_{10}$$ 10 values in SJM and warm months increased it, favored by thermal inversion (TI). Dust resuspension, vehicular transport and stationary sources contributed more PM$$_{10}$$ 10 at peak times in the morning and evening. The Multiple linear regression (MLR) showed the best correlation (r = 0.6166), followed by the three-dimensional model LogAP-LogWD-LogPM$$_{10}$$ 10 (r = 0.5753); the RMSE-MLR (12.92) exceeded that found in the 3D models (RMSE $$<0.3$$ < 0.3 ) and the NSE-MLR criterion (0.3804) was acceptable. PM$$_{10}$$ 10 prediction was modeled using the algorithmic approach in any scenario to optimize urban management decisions in times of pandemic.

Lowering mortality risks in urban areas by containing atmospheric pollution

OBJECTIVES

Although studies collectively examining the traffic and residential heat pollutant emissions are abundant, research investigations dedicated to Cyprus are scarce. This investigation has simulated the levels of air pollutants, namely, CO, NO_x, PM_2.5, and PM₁₀ and reconciled them with actual air quality measurements in Nicosia, Cyprus, during a 9-month period at an hourly resolution. To this end, several scenarios and cases were formulated to tackle emissions and minimise human mortality risks in the city.

METHODS

The GRAL dispersion model was used to project pollution levels. Nine different traffic scenarios were devised to estimate variations in concentration of PM_2.5 and NO_x under various policies, such as banning diesel passenger vehicles (PV), light duty vehicles (LDV), non-Euro 6 standards vehicles, stringent speed limits and a ubiquitous roll-out of electric passenger vehicles. Moreover, 4 distinct cases were analysed to year 2030 considering a fluctuation in traffic of ±20% whereas all vehicles conform to Euro 6 standards. Three additional policies examined the prohibition of diesel PV and LDV, 80% electric PV and outlawing fireplaces. Drawing on the findings of these scenarios and cases, the total cardiovascular and respiratory mortality rates at the capital of Cyprus, Nicosia, were deduced.

RESULTS

The most promising scenario in terms of curbing emissions was to ban non-Euro 6 vehicles and diesel PV and LDV which could contain average NO_x concentration, in Nicosia, from 52.9 μg/m³ to 15.0 μg/m³. If this policy were to be implemented, it could have saved 70% of the premature deaths tied to NO_x emissions. For particulate matter, banning fireplaces and abandoning non-Euro 6 vehicles could lower average concentrations from 18.3 μg/m³ to 13.1 μg/m³, saving at least 30% of the people poised to lose their lives from particulate matter risks.

CONCLUSION

Traffic and residential heat policies are not easy to implement. However, our study has demonstrated that the most effective policies for curbing NO_x emissions would be to ensure that all vehicles abide with the Euro 6 standards and, concurrently, ban diesel passenger and light duty vehicles. Lastly, phasing out domestic fireplaces appears to be the most promising solution for containing particulate matter, in 2030.

Particle formation due to brake wear, influence on the people health and measures for their reduction: a review

For achieving the desired vehicle speed, the IC engine is very important, while for further vehicle speed maintaining and adaptation to road conditions, the braking system is important. With each brake's activation, wear products are forming, which are very harmful to the environment, because they can contain heavy metals. The braking working parameters (initial speed and braking pressure) are beside the achieved temperature in contact par, the most responsible, for particle formation and their release into the air. The particles forming can be divided by size on coarse, fine, and ultrafine particles, and which were observed in the paper. However, the greatest accent was placed on coarse and fine particles. For the determination of the composition of wear products, most often, laboratory tests were used. Particle composition greatly depends on the composition of brake pads, which can consist of about 30 components, and where some of these components have very unfavourable effects on people's health. So today, many researches are focused on finding such composition for brake pads, which will wear as less as possible, without disturbing the basic tribological properties. The conclusion of this paper shows that the applied materials for manufacturing the braking system are very important, as well as the construction, for the reduction of particle emission.

Near-Source Risk Functions for Particulate Matter Are Critical When Assessing the Health Benefits of Local Abatement Strategies

When mortality or other health outcomes attributable to fine particulate matter (PM2.5) are estimated, the same exposure-response function (ERF) is usually assumed regardless of the source and composition of the particles, and independently of the spatial resolution applied in the exposure model. While several recent publications indicate that ERFs based on exposure models resolving within-city gradients are steeper per concentration unit (μgm-3), the ERF for PM2.5 recommended by the World Health Organization does not reflect this observation and is heavily influenced by studies based on between-city exposure estimates. We evaluated the potential health benefits of three air pollution abatement strategies: electrification of light vehicles, reduced use of studded tires, and introduction of congestion charges in Stockholm and Gothenburg, using different ERFs. We demonstrated that using a single ERF for PM2.5 likely results in an underestimation of the effect of local measures and may be misleading when evaluating abatement strategies. We also suggest applying ERFs that distinguish between near-source and regional contributions of exposure to PM2.5. If separate ERFs are applied for near-source and regional PM2.5, congestion charges as well as a reduction of studded tire use are estimated to be associated with a significant reduction in the mortality burden in both Gothenburg and Stockholm. In some scenarios the number of premature deaths is more than 10 times higher using separate ERFs in comparison to using a single ERF irrespective of sources as recommended by the WHO. For electrification, the net change in attributable deaths is small or within the uncertainty range depending on the choice of ERF.

The Influence of Air Pollutants and Meteorological Conditions on the Hospitalization for Respiratory Diseases in Shenzhen City, China

Air pollutants have significant direct and indirect adverse effects on public health. To explore the relationship between air pollutants and meteorological conditions on the hospitalization for respiratory diseases, we collected a whole year of daily major air pollutants’ concentrations from Shenzhen city in 2013, including Particulate Matter (PM₁₀, PM_2.5), Nitrogen dioxide (NO₂), Ozone (O₃), Sulphur dioxide (SO₂), and Carbon monoxide (CO). Meanwhile, we also gained meteorological data. This study collected 109,927 patients cases with diseases of the respiratory system from 98 hospitals. We investigated the influence of meteorological factors on air pollution by Spearman correlation analysis. Then, we tested the short-term correlation between significant air pollutants and respiratory diseases’ hospitalization by Distributed Lag Non-linear Model (DLNM). There was a significant negative correlation between the north wind and NO₂ and a significant negative correlation between the south wind and six pollutants. Except for CO, other air pollutants were significantly correlated with the number of hospitalized patients during the lag period. Most of the pollutants reached maximum Relative Risk (RR) with a lag of five days. When the time lag was five days, the annual average of PM₁₀, PM_2.5, SO₂, NO₂, and O₃ increased by 10%, and the risk of hospitalization for the respiratory system increased by 0.29%, 0.23%, 0.22%, 0.25%, and 0.22%, respectively. All the pollutants except CO impact the respiratory system’s hospitalization in a short period, and PM10 has the most significant impact. The results are helpful for pollution control from a public health perspective.

High Resolution Mapping of PM2.5 Concentrations in Paris (France) Using Mobile Pollutrack Sensors Network in 2020

There is a need for accurate monitoring of PM2.5 that adversely affects human health. Consequently, in addition to the monitoring performed by fixed microbalance instruments installed under legal obligation, we are proposing to deploy the Pollutrack network of mobile sensors within the city of Paris (France). The measurements are performed by mobile aerosol counters mounted on the roof of cars, providing a constant series of readings in the 0.3–10 µm size range that are then aggregated to identify areas of mass concentrations of pollution. The performance of the Pollutrack sensors has been established in ambient air in comparison with the microbalance measurement devices and with the Light Optical Aerosols Counter (LOAC) aerosol counter. A measurement uncertainty of about 5 µg. m−3 is obtained with absolute values from the Pollutrack measurements made at a given location. Instead of the current modelizations based on very few PM2.5 values, maps built from real measurements with a spatial resolution down to 100 m can now be produced each day for Paris, and potentially for specific times of the day, thanks to the high number of measurements achievable with the Pollutrack system (over 70,000 on weekdays). Interestingly, the global trend of PM2.5 content shows several significant pollution events in 2020 despite the COVID-19 crisis and the lockdown. The Pollutrack pollution maps recorded during different PM2.5 pollution conditions in the city frequently identified a strong spatial heterogeneity where the North and the East of Paris were more polluted than the west. These “hot spots” could be due to the city topology and its sensitivity to wind direction and intensity. These high-resolution maps will be crucial in creating evidence for the relevant authorities to respond appropriately to local sources of pollution and to improve the understanding of transportation of urban PM.

Simulation of primary and secondary particles in the streets of Paris using MUNICH

High particle concentrations are observed in the streets. Regional-scale chemistry-transport models are not able to reproduce these high concentrations, because their spatial resolution is not fine enough. Local-scale models are usually employed to simulate the high concentrations in street networks, but they often adopt substantial simplifications to determine background concentrations and use simplified chemistry. This study presents the new version of the local-scale Model of Urban Network of Intersecting Canyons and Highways (MUNICH) that integrates background concentrations simulated by the regional-scale chemistry-transport model Polair3D, and uses the same complex chemistry module as Polair3D, SSH-aerosol, to represent secondary aerosol formation. Gas and aerosol concentrations in Paris streets are simulated with MUNICH, considering a street-network with more than 3800 street segments, between 3 May and 30 June. Comparisons with PM₁₀ and PM_2.5 measurements at several locations of Paris show that the high PM₁₀ and PM_2.5 concentrations are well represented. Furthermore, the simulated chemical composition of fine particles corresponds well to a yearly measured composition. To understand the influence of the secondary pollutant formation, several sensitivity simulations are conducted. Simulations with and without gas-phase chemistry show that the influence of gas-phase chemistry on the formation of NO₂ is large (37% on average over May and across all modelled streets), but the influence on condensables is lower (less than 2% to 3% on average at noon for inorganics and organics), but may reach more than 20% depending on the street. The assumption used to compute gas/particle mass transfer by condensation/evaporation is important for inorganic and organic compounds of particles, as using the thermodynamic equilibrium assumption leads to an overestimation of the organic concentrations by 4.7% on average (up to 31% at noon depending on the streets). Ammonia emissions from traffic lead to an increase in inorganic concentrations by 3% on average, reaching 26% depending on the street segments. Not taking into account gas-phase chemistry and aerosol dynamics in the modelling leads to an underestimation of organic concentrations by about 11% on average over the streets and time, but this underestimation may reach 51% depending on the streets and the time of the day.

Public Health Considerations for PM10 in a High-Pollution Megacity: Influences of Atmospheric Condition and Land Coverage

This paper analyzes the PM10 concentrations and influences of atmospheric condition (AC) and land coverage (LC) on a high-pollution megacity (Bogota, Colombia) from a public health viewpoint. Information of monitoring stations equipped with measuring devices for PM10/temperature/solar-radiation/wind-speed were used. The research period lasted eight years (2007–2014). AC and LC were determined after comparing daily PM10 concentrations (DPM10) to reference limits published by the World Health Organization (WHO). ARIMA models for DPM10 were also developed. The results indicated that urban sectors with lower atmospheric instability (AI) had a 2.85% increase in daily mortality (DM) in relation to sectors with greater AI. In these sectors of lower AI, impervious LC predominated, instead of vegetated LC. An ARIMA analysis revealed that a greater extent of impervious LC around a station led to a greater effect on previous days’ DPM10 concentrations. Extreme PM10 episodes persisted for up to two days. Extreme pollution episodes were probably also preceded by low mixing-layer heights (between 722–1085 m). The findings showed a 13.0% increase in WHO standard excesses (PE) for each 10 µg/m3 increase in DPM10, and a 0.313% increase in DM for each 10% increase in PE. The observed average reduction of 14.8% in DPM10 (−0.79% in DM) was probably due to 40% restriction of the traffic at peak hours.

Vertical Profiles of Pollution Particle Concentrations in the Boundary Layer above Paris (France) from the Optical Aerosol Counter LOAC Onboard a Touristic Balloon

Atmospheric pollution by particulate matter represents a significant health risk and needs continuous monitoring by air quality networks that provide mass concentrations for PM10 and PM2.5 (particles with diameter smaller than 10 μm and 2.5 μm, respectively). We present here a new approach to monitor the urban particles content, using six years of aerosols number concentration measurements for particles in the 0.2−50 μm size range. These measurements are performed by the Light Optical Aerosols Counter (LOAC) instrument onboard the tethered touristic balloon “Ballon de Paris Generali”, in Paris, France. Such measurements have allowed us first to detect at ground a seasonal variability in the particulate matter content, due to the origin of the particles (anthropogenic pollution, pollens), and secondly, to retrieve the mean evolution of particles concentrations with height above ground up to 150 m. Measurements were also conducted up to 300 m above ground during major pollution events. The vertical evolution of concentrations varies from one event to another, depending on the origin of the pollution and on the meteorological conditions. These measurements have shown the interest of performing particle number concentrations measurements for the air pollution monitoring in complement with regulatory mass concentrations measurement, to better evaluate the intensity of the pollution event and to better consider the effect of smallest particles, which are more dangerous for human health.

Car Wake Flows and Ultrafine Particle Dispersion: From Experiments to Modelling

Improving air quality in urban environments and transportation systems is crucial. Concerns are related to health and environmental issues associated with huge costs. Car cabin is a microenvironment where pollutants can accumulate with possible risks for occupants. In automotive engineering, it has then become mandatory to study the path and dispersion of such pollutants emitted from the tailpipe of a car. In the present paper, the relation between the flow topology and the dispersion of ultrafine particles (UFP) in the wake of a vehicle is discussed. Experiments were undertaken at a reduced scale using simplified car models. Experimental conditions were defined to be representative of a vehicle in an urban environment. Based on experimental data, a simplified analytical model is developed, which aims at describing the concentration fields of UFP in the wake of a single vehicle for different rear slant angles. The strengths and limits of the present model are discussed and ways of improvements are suggested. Additional experiments are presented to assess the influence of the inter-vehicle distance on this recirculation region. Critical inter-vehicle distances were determined based on defined criteria for different rear slant angles of the leading vehicle and compared to safety clearances.