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1.
Sci Total Environ ; 811: 152323, 2022 Mar 10.
Artigo em Inglês | MEDLINE | ID: mdl-34910946

RESUMO

Driving behavior and speed enforcement are both important to road safety and affect vehicle exhaust emissions. Relationships between driving characteristics and safety or emissions have been assessed in multiple studies. However, there is scant information on whether safe driving also reduces emissions and how this relationship changes across urban areas. This study makes use of two similar GPS datasets collected in the metropolitan areas of Toronto and Beijing to conduct a comparative analysis of driving characteristics, speed limit violations, and emissions. Emissions for all trips were computed using the same emission rate database derived from a Portable Emissions Monitoring System (PEMS). We observe that the average speeds in the two cities are close to 25 km/h. In Toronto, the fraction of time spent at speeds over 80 km/h on expressways is 40% higher than in Beijing. We also note a higher level of accelerations in Toronto. The trips in Beijing have approximately 14%, 57%, 14%, and 21% lower emissions of carbon dioxide (CO2), carbon monoxide (CO), nitrogen oxides (NOx), and particle number (PN), respectively. Drivers in Toronto violate speed limits in 93% of their trips for 21% of trip travel time while the numbers for Beijing are 43% and 4%. These differences are not necessarily due to driving behavior, but rather to driving characteristics, which encompass the effects of behavior, road network design, traffic congestion, trip patterns, and speed enforcement. A scenario was evaluated by reconstructing drive-cycles to assess the effects of speed limit enforcement for trips where violations were detected. In Toronto, if obeying the speed limit, the mean trip travel time was estimated to increase by 1.8 min. In contrast, trip emissions of CO2, CO, NOx, and PN were found to decrease, on average, by 5.2%, 19.1%, 5.2%, and 2.9%, respectively. Speed limit enforcement can result in lower emissions, by reducing aggressive accelerations.


Assuntos
Poluentes Atmosféricos , Poluentes Atmosféricos/análise , Pequim , Cidades , Óxidos de Nitrogênio/análise , Emissões de Veículos/análise
2.
Sci Total Environ ; 805: 150407, 2022 Jan 20.
Artigo em Inglês | MEDLINE | ID: mdl-34818772

RESUMO

In this study, driving trajectory data from private vehicles were collected in Toronto, Canada to construct representative local drive cycles. In addition, real-driving emission testing for four conventional gasoline vehicles (ICEV) and one hybrid electric vehicle (HEV) was conducted in the same region using a Portable Emissions Measurement System. Instantaneous fuel consumption and emissions of Carbon Monoxide (CO), Nitrogen Oxides (NOx), and Particle Number (PN) were measured. The results for all vehicles indicate that the acceleration state tends to generate the highest emissions and fuel consumption with the largest variation due to higher power demand. When accelerating, the HEV was observed to generate four times more CO emissions than some ICEVs. Instantaneous fuel consumption and emissions were analyzed as a function of operating modes to estimate the fuel efficiency (FE) and emission factors (EF) associated with six representative local drive cycles and four regulatory drive cycles. With most regulatory drive cycles, vehicles can reach the labeled FE and EPA emission limits, except under the New York City Cycle with frequent stop-and-go conditions. In contrast, except for highway cycles, the FE of Toronto-specific drive cycles can hardly meet the labeled values. CO EFs of the HEV can be higher than ICEVs, while it is lower than the emission limit by 42% on average. ICEVs may exceed the CO limit by 131% under local highway cycles, while they can violate NOx and PN limits under local arterial cycles. The result of this study emphasizes the importance of local drive cycles and real driving emission tests.


Assuntos
Poluentes Atmosféricos , Gasolina , Poluentes Atmosféricos/análise , Monóxido de Carbono/análise , Gasolina/análise , Veículos Automotores , Óxidos de Nitrogênio/análise , Emissões de Veículos/análise
3.
Environ Sci Technol ; 2021 Dec 29.
Artigo em Inglês | MEDLINE | ID: mdl-34965092

RESUMO

There is growing interest to move beyond fine particle mass concentrations (PM2.5) when evaluating the population health impacts of outdoor air pollution. However, few exposure models are currently available to support such analyses. In this study, we conducted large-scale monitoring campaigns across Montreal and Toronto, Canada during summer 2018 and winter 2019 and developed models to predict spatial variations in (1) the ability of PM2.5 to generate reactive oxygen species in the lung fluid (ROS), (2) PM2.5 oxidative potential based on the depletion of ascorbate (OPAA) and glutathione (OPGSH) in a cell-free assay, and (3) anhysteretic magnetic remanence (XARM) as an indicator of magnetite nanoparticles. We also examined how exposure to PM oxidative capacity metrics (ROS/OP) varied by socioeconomic status within each city. In Montreal, areas with higher material deprivation, indicating lower area-level average household income and employment, were exposed to PM2.5 characterized by higher ROS and OP. This relationship was not observed in Toronto. The developed models will be used in epidemiologic studies to assess the health effects of exposure to PM2.5 and iron-rich magnetic nanoparticles in Toronto and Montreal.

4.
Environ Health Perspect ; 129(10): 107005, 2021 10.
Artigo em Inglês | MEDLINE | ID: mdl-34644144

RESUMO

BACKGROUND: We do not currently understand how spatiotemporal variations in the composition of fine particulate air pollution [fine particulate matter with aerodynamic diameter ≤2.5µm (PM2.5)] affects population health risks. However, recent evidence suggests that joint concentrations of transition metals and sulfate may influence the oxidative potential (OP) of PM2.5 and associated health impacts. OBJECTIVES: The purpose of the study was to evaluate how combinations of transition metals/OP and sulfur content in outdoor PM2.5 influence associations with acute cardiovascular events. METHODS: We conducted a national case-crossover study of outdoor PM2.5 and acute cardiovascular events in Canada between 2016 and 2017 (93,344 adult cases). Monthly mean transition metal and sulfur (S) concentrations in PM2.5 were determined prospectively along with estimates of OP using acellular assays for glutathione (OPGSH), ascorbate (OPAA), and dithiothreitol depletion (OPDTT). Conditional logistic regression models were used to estimate odds ratios (OR) [95% confidence intervals (CI)] for PM2.5 across strata of transition metals/OP and sulfur. RESULTS: Among men, the magnitudes of observed associations were strongest when both transition metal and sulfur content were elevated. For example, an OR of 1.078 (95% CI: 1.049, 1.108) (per 10µg/m3) was observed for cardiovascular events in men when both copper and S were above the median, whereas a weaker association was observed when both elements were below median values (OR=1.019, 95% CI: 1.007, 1.031). A similar pattern was observed for OP metrics. PM2.5 was not associated with acute cardiovascular events in women. DISCUSSION: The combined transition metal and sulfur content of outdoor PM2.5 influences the strength of association with acute cardiovascular events in men. Regions with elevated concentrations of both sulfur and transition metals in PM2.5 should be examined as priority areas for regulatory interventions. https://doi.org/10.1289/EHP9449.


Assuntos
Poluentes Atmosféricos , Poluição do Ar , Doenças Cardiovasculares , Adulto , Poluentes Atmosféricos/análise , Poluição do Ar/análise , Canadá/epidemiologia , Doenças Cardiovasculares/epidemiologia , Estudos Cross-Over , Exposição Ambiental/análise , Monitoramento Ambiental , Feminino , Humanos , Masculino , Estresse Oxidativo , Material Particulado/análise , Enxofre
5.
Environ Monit Assess ; 193(10): 657, 2021 Sep 17.
Artigo em Inglês | MEDLINE | ID: mdl-34533645

RESUMO

High-resolution air quality maps are critical towards assessing and understanding exposures to elevated air pollution in dense urban areas. However, these surfaces are rarely available in low- and middle-income countries that suffer from some of the highest air pollution levels worldwide. In this study, we make use of land use regressions (LURs) to generate annual and seasonal, high-resolution nitrogen dioxide (NO2), nitrogen oxides (NOx), and ozone (O3) exposure surfaces for the Greater Beirut Area (GBA) in Lebanon. NO2, NOx and O3 concentrations were monitored using passive samplers that were deployed at 55 pre-defined monitoring locations. The average annual concentrations of NO2, NOx, and O3 across the GBA were 36.0, 89.7, and 26.9 ppb, respectively. Overall, the performance of the generated models was appropriate, with low biases, high model robustness, and acceptable R2 values that ranged between 0.66 and 0.73 for NO2, 0.56 and 0.60 for NOx, and 0.54 and 0.65 for O3. Traffic-related emissions as well as the operation of a fossil-fuel power plant were found to be the main contributors to the measured NO2 and NOx levels in the GBA, whereas they acted as sinks for O3 concentrations. No seasonally significant differences were found for the NO2 and NOx pollution surfaces; as their seasonal and annual models were largely similar (Pearson's r > 0.85 for both pollutants). On the other hand, seasonal O3 pollution surfaces were significantly different. The model results showed that around 99% of the population of the GBA were exposed to NO2 levels that exceeded the World Health Organization defined annual standard.


Assuntos
Poluentes Atmosféricos , Poluição do Ar , Ozônio , Poluentes Atmosféricos/análise , Poluição do Ar/análise , Monitoramento Ambiental , Óxidos de Nitrogênio/análise , Ozônio/análise
6.
Environ Monit Assess ; 193(9): 587, 2021 Aug 20.
Artigo em Inglês | MEDLINE | ID: mdl-34415446

RESUMO

This study harnesses the power of mobile data in developing a spatial model for predicting black carbon (BC) concentrations within one of the most heavily populated regions in the Middle East and North Africa MENA region, Greater Cairo Region (GCR) in Egypt. A mobile data collection campaign was conducted in GCR to collect BC measurements along specific travel routes. In total, 3,300 km were travelled across a widespread 525 km of routes. Reported average BC values were around 20 µg/m3, announcing an alarming order of magnitude value when compared to the maximum reported values in similar studies. A bi-directional stepwise land use regression (LUR) model was developed to select the best combination of explanatory variables and generate an exposure surface for BC, in addition to a number of machine learning models (random forest gradient boost, light gradient boost model (LightGBM), Keras neural network (NN)). Data from 7 air quality (AQ) stations were compared-in terms of mean square error (MSE) and mean absolute error (MAE)-with predictions from the LUR and the NN model. The NN model estimated higher BC concentrations in the downtown areas, while lower concentrations are estimated for the peripheral area at the east side of the city. Such results shed light on the credibility of the LUR models in generating a general spatial trend of BC concentrations while the superiority of NN in BC accuracy estimation (0.023 vs 0.241 in terms of MSE and 0.12 vs 0.389 in terms of MAE; of NN vs LUR respectively).


Assuntos
Poluentes Atmosféricos , Material Particulado , Poluentes Atmosféricos/análise , Carbono , Egito , Monitoramento Ambiental , Material Particulado/análise
7.
Environ Sci Technol ; 55(10): 6602-6612, 2021 05 18.
Artigo em Inglês | MEDLINE | ID: mdl-33929197

RESUMO

Reducing greenhouse gas (GHG) emissions of private passenger vehicles, transit buses, and commercial vehicles with newer technology can improve air quality, and, subsequently, population exposure and public health. For the Greater Toronto and Hamilton Area, we estimated the burden of each vehicle fleet on population health in the units of years of life lost and premature deaths. We then assessed the separate health benefits of electrifying private vehicles, transit buses, and replacing the oldest commercial vehicles with newer trucks. A complete deployment of electric passenger vehicles would lead to health benefits similar to replacing all trucks older than 8 years (i.e., about 300 premature deaths prevented) in the first year of implementation; however, GHG emissions would be mainly reduced with passenger fleet electrification. Transit bus electrification has similar health benefits as electrifying half of the passenger fleet (i.e., about 150 premature deaths prevented); however, the GHG emission reductions reached under the bus electrification scenario are lower by 90%. By accelerating policies to electrify cars and buses and renew older trucks, governments can save hundreds of lives per year and mitigate the impacts of climate change.


Assuntos
Poluentes Atmosféricos , Poluição do Ar , Poluentes Atmosféricos/análise , Poluição do Ar/análise , Poluição do Ar/prevenção & controle , Motivação , Veículos Automotores , Tecnologia , Emissões de Veículos/análise
8.
Environ Pollut ; 284: 117145, 2021 Sep 01.
Artigo em Inglês | MEDLINE | ID: mdl-33910134

RESUMO

Dispersion modelling is an effective tool to estimate traffic-related fine particulate matter (PM2.5) concentrations in near-road environments. However, many sources of uncertainty and variability are associated with the process of near-road dispersion modelling, which renders a single-number estimate of concentration a poor indicator of near-road air quality. In this study, we propose an integrated traffic-emission-dispersion modelling chain that incorporates several major sources of uncertainty. Our approach generates PM2.5 probability distributions capturing the uncertainty in emissions and meteorological conditions. Traffic PM2.5 emissions from 7 a.m. to 6 p.m. were estimated at 3400 ± 117 g. Modelled PM2.5 levels were validated against measurements along a major arterial road in Toronto, Canada. We observe large overlapping areas between modelled and measured PM2.5 distributions at all locations along the road, indicating a high likelihood that the model can reproduce measured concentrations. A policy scenario expressing the impact of reductions in truck emissions revealed that a 30% reduction in near-road PM2.5 concentrations can be achieved by upgrading close to 55% of the current trucks circulating along the corridor. A speed limit reduction of 10 km/h could lead to statistically significant increases in PM2.5 concentrations at twelve out of the eighteen locations.


Assuntos
Poluentes Atmosféricos , Poluição do Ar , Poluentes Atmosféricos/análise , Poluição do Ar/análise , Canadá , Monitoramento Ambiental , Material Particulado/análise , Incerteza , Emissões de Veículos/análise
9.
Am J Respir Crit Care Med ; 204(2): 168-177, 2021 07 15.
Artigo em Inglês | MEDLINE | ID: mdl-33798018

RESUMO

Rationale: Evidence linking outdoor air pollution with coronavirus disease (COVID-19) incidence and mortality is largely based on ecological comparisons between regions that may differ in factors such as access to testing and control measures that may not be independent of air pollution concentrations. Moreover, studies have yet to focus on key mechanisms of air pollution toxicity such as oxidative stress. Objectives: To conduct a within-city analysis of spatial variations in COVID-19 incidence and the estimated generation of reactive oxygen species (ROS) in lung lining fluid attributable to fine particulate matter (particulate matter with an aerodynamic diameter ⩽2.5 µm [PM2.5]). Methods: Sporadic and outbreak-related COVID-19 case counts, testing data, population data, and sociodemographic data for 140 neighborhoods were obtained from the City of Toronto. ROS estimates were based on a mathematical model of ROS generation in lung lining fluid in response to iron and copper in PM2.5. Spatial variations in long-term average ROS were predicted using a land-use regression model derived from measurements of iron and copper in PM2.5. Data were analyzed using negative binomial regression models adjusting for covariates identified using a directed acyclic graph and accounting for spatial autocorrelation. Measurements and Main Results: A significant positive association was observed between neighborhood-level ROS and COVID-19 incidence (incidence rate ratio = 1.07; 95% confidence interval, 1.01-1.15 per interquartile range ROS). Effect modification by neighborhood-level measures of racialized group membership and socioeconomic status was also identified. Conclusions: Examination of neighborhood characteristics associated with COVID-19 incidence can identify inequalities and generate hypotheses for future studies.


Assuntos
Poluição do Ar/análise , COVID-19/metabolismo , Modelos Estatísticos , Espécies Reativas de Oxigênio/análise , COVID-19/epidemiologia , Feminino , Humanos , Incidência , Masculino , Pessoa de Meia-Idade , Ontário/epidemiologia , SARS-CoV-2
10.
Environ Sci Technol ; 55(6): 3807-3818, 2021 03 16.
Artigo em Inglês | MEDLINE | ID: mdl-33666410

RESUMO

Metal components in fine particulate matter (PM2.5) from nontailpipe emissions may play an important role in underlying the adverse respiratory effects of PM2.5. We investigated the associations between long-term exposure to iron (Fe) and copper (Cu) in PM2.5 and their combined impact on reactive oxygen species (ROS) generation in human lungs, and the incidence of asthma, chronic obstructive pulmonary disease (COPD), COPD mortality, pneumonia mortality, and respiratory mortality. We conducted a population-based cohort study of ∼0.8 million adults in Toronto, Canada. Land-use regression models were used to estimate the concentrations of Fe, Cu, and ROS. Outcomes were ascertained using validated health administrative databases. We found positive associations between long-term exposure to Fe, Cu, and ROS and the risks of all five respiratory outcomes. The associations were more robust for COPD, pneumonia mortality, and respiratory mortality than for asthma incidence and COPD mortality. Stronger associations were observed for ROS than for either Fe or Cu. In two-pollutant models, adjustment for nitrogen dioxide somewhat attenuated the associations while adjustment for PM2.5 had little influence. Long-term exposure to Fe and Cu in PM2.5 and estimated ROS concentration in lung fluid was associated with increased incidence of respiratory diseases, suggesting the adverse respiratory effects of nontailpipe emissions.


Assuntos
Poluentes Atmosféricos , Poluição do Ar , Doenças Respiratórias , Adulto , Poluentes Atmosféricos/efeitos adversos , Poluentes Atmosféricos/análise , Poluição do Ar/análise , Canadá , Estudos de Coortes , Cobre/toxicidade , Exposição Ambiental/análise , Humanos , Ferro , Pulmão , Material Particulado/efeitos adversos , Material Particulado/análise , Espécies Reativas de Oxigênio
11.
Sci Total Environ ; 771: 144652, 2021 Jun 01.
Artigo em Inglês | MEDLINE | ID: mdl-33545464

RESUMO

It has been hypothesized that ultrafine particles (UFP) in air pollution may cause lung cancer. In preparation for an epidemiologic case-control study to assess this hypothesis in Montreal, Canada, we conducted a UFP measurement campaign in order to create an exposure surface with which we could assign UFP exposure to subjects corresponding to their residential addresses. The purpose of this paper is to describe the temporal and spatial variability that underlies the creation of an exposure surface in the Montreal area, and to consider the implications for epidemiological exposure assessment. We identified 249 fixed sampling sites, selected to provide a dense spatial representation of the areas of residence of Montreal residents. We conducted a winter campaign and a summer campaign, and each of the sites was visited three times during each seasonal campaign. Each visit entailed a 20-minute measurement period for UFPs with a separate measurement each second. This provided data for temporal comparisons at each site between seasons, between visits and between seconds. The median of UFP measurements was 16,593 particles/cm3 in winter and 8919 particles/cm3 in summer. Across the 249 sampling sites the Spearman correlation coefficient between the UFP measurements of winter and summer was 0.35. Within each visit, correlation was below 0.50 between pairs of UFP measurements taken more than 60 s apart, and there was hardly any correlation among measurements taken more than 300 s apart. When sites were grouped by proximity to certain types of pollution sources, and the seven resulting groups compared, there were modest, albeit statistically significant, differences in UFP levels. There was moderate positive spatial autocorrelation in UFPs over the study area. High temporal variability of UFPs from short-term measurements campaigns will likely compromise the predictive validity of the exposure surface, and will eventually attenuate the epidemiologic risk estimates.

12.
Environ Res ; 195: 110905, 2021 04.
Artigo em Inglês | MEDLINE | ID: mdl-33631139

RESUMO

The adverse effects of long-term exposure to environmental noise on human health are of increasing concern. Noise mapping methods such as spatial interpolation and land use regression cannot capture complex relationships between environmental conditions and noise propagation or attenuation in a three-dimension (3D) built environment. In this study, we developed a hybrid approach by combining a traffic propagation model and random forests (RF) machine learning algorithm to map the total environment noise levels for daily average, daytime, nighttime, and day-evening-nighttime at 30 m × 30 m resolution for the island of Montreal, Canada. The propagation model was used to predict traffic noise surfaces using road traffic flow, 3D building information, and a digital elevation model. The traffic noise estimates were compared with ground-based sound-level measurements at 87 points to extract residuals between total environmental noise and traffic noise. Residuals at these points were fit to RF models with multiple environmental and geographic predictor variables (e.g., vegetation index, population density, brightness of nighttime lights, land use types, and distances to noise contour around the airport, bus stops, and road intersections). Using the sound-level measurements as baseline data, the prediction errors, i.e., mean error, mean absolute error, and root mean squared error of daily average noise levels estimated by our hybrid approach was -0.03 dB(A), 2.67 dB(A), and 3.36 dB(A). Combining deterministic and stochastic models can provide accurate total environmental noise estimates for large geographic areas where sound-level measurements are available.


Assuntos
Monitoramento Ambiental , Ruído , Canadá , Exposição Ambiental , Humanos , Aprendizado de Máquina , Densidade Demográfica
13.
Sci Total Environ ; 760: 143402, 2021 Mar 15.
Artigo em Inglês | MEDLINE | ID: mdl-33221006

RESUMO

Studies have demonstrated that vehicles with gasoline direct injection (GDI) engines produce significantly higher emissions during a cold start than under hot-stabilized periods. A cold start is typically defined by the temperature of the engine or the catalytic converter; its extended effect on emissions, after the vehicle reaches the warm-up stage, has seldom been investigated. In this study, the influence of the post cold start period on nitrogen oxides (NOx) emissions was evaluated using real-world measurements. Vehicle on-board diagnostic data, fuel consumption, and emissions of multiple pollutants were collected on a 2020 GDI sports utility vehicle equipped with a Portable Emission Measurement System (PEMS). A total of 31 trips, with two drives per day, were conducted along arterial roads and highways in Toronto, Canada. The results indicate that during the first trip of the day after an overnight soak, the average NOx emission rate was 0.27 g/litre and 0.037 g/km, 384% and 299% higher than the emission rate on the second trip of the day. The amount of trip total NOx emissions is positively associated with the length of the catalytic converter warm-up period with correlation coefficient 0.67. We also observe that the catalyst warm-up time is negatively correlated with ambient temperature, and a negative relationship between ambient temperature and NOx emissions throughout the trip is depicted with correlation coefficient -0.44. The measured data reveal an extended effect of the cold start on NOx emissions even after the temperatures of the engine coolant and catalyst reach a stable level.

14.
Int J Epidemiol ; 50(2): 589-601, 2021 05 17.
Artigo em Inglês | MEDLINE | ID: mdl-33367589

RESUMO

BACKGROUND: Exposure to fine particulate (PM2.5) air pollution is associated with increased cardiovascular disease (CVD), but less is known about its specific components, such as metals originating from non-tailpipe emissions. We investigated the associations of long-term exposure to metal components [iron (Fe) and copper (Cu)] in PM2.5 with CVD incidence. METHODS: We conducted a population-based cohort study in Toronto, Canada. Exposures to Fe and Cu in PM2.5 and their combined impact on the concentration of reactive oxygen species (ROS) in lung fluid were estimated using land use regression models. Incidence of acute myocardial infarction (AMI), congestive heart failure (CHF) and CVD death was ascertained using health administrative datasets. We used mixed-effects Cox regression models to examine the associations between the exposures and health outcomes. A series of sensitivity analyses were conducted, including indirect adjustment for individual-level cardiovascular risk factors (e.g. smoking), and adjustment for PM2.5 and nitrogen dioxide (NO2). RESULTS: In single-pollutant models, we found positive associations between the three exposures and all three outcomes, with the strongest associations detected for the estimated ROS. The associations of AMI and CHF were sensitive to indirect adjustment, but remained robust for CVD death in all sensitivity analyses. In multi-pollutant models, the associations of the three exposures generally remained unaltered. Interestingly, adjustment for ROS did not substantially change the associations between PM2.5 and CVD, but attenuated the associations of NO2. CONCLUSIONS: Long-term exposure to Fe and Cu in PM2.5 and their combined impact on ROS were consistently associated with increased CVD death.


Assuntos
Poluentes Atmosféricos , Poluição do Ar , Doenças Cardiovasculares , Poluentes Atmosféricos/efeitos adversos , Poluentes Atmosféricos/análise , Poluição do Ar/efeitos adversos , Poluição do Ar/análise , Canadá/epidemiologia , Doenças Cardiovasculares/epidemiologia , Estudos de Coortes , Cobre , Exposição Ambiental/efeitos adversos , Exposição Ambiental/análise , Humanos , Incidência , Ferro , Pulmão , Material Particulado/efeitos adversos , Material Particulado/análise , Espécies Reativas de Oxigênio
15.
Int J Hyg Environ Health ; 232: 113666, 2021 03.
Artigo em Inglês | MEDLINE | ID: mdl-33296779

RESUMO

BACKGROUND: Cardiovascular effects of environmental noise are a growing concern. However, the evidence remains largely limited to the association between road traffic noise and hypertension and coronary heart diseases. OBJECTIVES: To investigate the association between long-term residential exposure to environmental/transportation noise and the incidence of myocardial infarction (MI) in the adult population living in Montreal. METHODS: An open cohort of adults aged 45 years old and over, living on the island of Montreal and free of MI before entering the cohort was created for the years 2000-2014 with the Quebec Integrated Chronic Disease Surveillance System; a systematic surveillance system from the Canadian province of Quebec starting in 1996. Residential noise exposure was calculated in three ways: 1) total ambient noise levels estimated by Land use regression (LUR) models; 2) road traffic noise estimated by a noise propagation model CadnaA and 3) distances to transportation sources (roads, airport, railways). Incident MI was based on diagnostic codes in hospital admission records. Cox models with time-varying exposures (age as the time axis) were used to estimate the associations with various adjustments (material deprivation indicator, calendar year, nitrogen dioxide, stratification for sex). Indirect adjustment based on ancillary data for smoking was performed. RESULTS: 1,065,414 individuals were followed (total of 9,000,443 person-years) and 40,718 (3.8%) developed MI. We found positive associations between total environmental noise, estimated by LUR models and the incidence of MI. Total noise LUR levels ranged from ~44 to ~79 dBA and varied slightly with the metric used. The adjusted hazard ratios (HRs) (also adjusted for smoking) were 1.12 (95% Confidence Intervals [CI]: 1.08-1.15), 1.11 (95%CI: 1.07-1.14) and 1.10 (95%CI: 1.06-1.14) per 10 dBA noise levels increase respectively in Level Accoustic equivalent 24 h (LAeq24 h), Level day-evening-night (Lden) and night level (Lnight). We found a borderline negative association between road noise levels estimated with CadnaA and MI (HR: 0.99 per 10 dBA; 95%CI: 0.98-1.00). Distances to major roads and highways were not associated with MI while the proximity to railways was positively associated with MI (HR for ≤100 vs > 1000 m: 1.07; 95%CI: 1.01-1.14). A negative association was found with the proximity to the airport noise exposure forecast (NEF25); HR (<1 vs >1000 m) = 0.88 (95%CI: 0.81-0.96). CONCLUSIONS: These associations suggest that exposure to total environmental noise at current urban levels may be related to the incidence of MI. Additional studies with more accurate road noise estimates are needed to explain the counterintuitive associations with road noise and specific transportation sources.


Assuntos
Infarto do Miocárdio , Ruído dos Transportes , Adulto , Canadá , Exposição Ambiental/efeitos adversos , Humanos , Incidência , Pessoa de Meia-Idade , Infarto do Miocárdio/epidemiologia , Infarto do Miocárdio/etiologia , Ruído dos Transportes/efeitos adversos
16.
Environ Pollut ; 267: 115695, 2020 Dec.
Artigo em Inglês | MEDLINE | ID: mdl-33254641

RESUMO

This study explores the generation of ultrafine particle emissions, measured in particle number (PN), based on a portable emissions measurement system (PEMS) in the City of Toronto between October and December 2019. Two driving routes were designed to include busy arterial roads and highways. All measurements were conducted between 10 a.m. and 4 p.m. Altogether, emissions from 31 drives were collected, leading to approximately 200,000 s of data. A spike detection algorithm was employed to isolate PN spikes in time series data. A sensitivity analysis was also conducted to identify the most optimum method for spike detection. The results indicate that the average emission rate during a PN spike is approximately 8 times the emission rate along the rest of the drive. In each test trip, about 25% of the duration was attributed to spike events, contributing 75% of total PN emissions. A Pearson correlation of 0.45 was estimated between the number of PN spikes and the number of sharp accelerations (above 8.5 km/h/s). The Pearson correlation between the occurrence of high engine torque (above 65.0 Nm) and the number of PN spikes was estimated at 0.80. The number of PN spikes was highest on arterial roads where the vehicle speed was relatively low, but with high variability, and including a high number of sharp accelerations. This pattern of UFP emissions leads to high UFP concentrations along arterial roads in the inner city core.


Assuntos
Poluentes Atmosféricos , Gasolina , Poluentes Atmosféricos/análise , Cidades , Monitoramento Ambiental , Gasolina/análise , Veículos Automotores , Tamanho da Partícula , Material Particulado/análise , Emissões de Veículos/análise
17.
Environ Health Perspect ; 128(10): 107006, 2020 10.
Artigo em Inglês | MEDLINE | ID: mdl-33074736

RESUMO

BACKGROUND: Environmental factors may contribute to the development of Kawasaki disease in children, but prenatal environmental exposures are understudied. OBJECTIVE: We used a population-based cohort to investigate whether prenatal exposure to outdoor air pollution is associated with the incidence of Kawasaki disease in childhood. METHODS: We performed a longitudinal cohort study of all children born in Quebec, Canada, between 2006 and 2012. Children were followed for Kawasaki disease from birth until 31 March 2018. We assigned prenatal air pollutant exposure according to the residential postal code at birth. The main exposure was annual average concentration of ambient fine particulate matter [PM ≤2.5µm in aerodynamic diameter (PM2.5) and nitrogen dioxide (NO2) from satellite-based estimates and land-use regression models. As secondary exposures, we considered industrial PM2.5, NO2, and sulfur dioxide (SO2) emissions estimated from dispersion models. We estimated hazard ratios (HRs) using Cox proportional hazards models, adjusted for maternal age, parity, sex, multiple birth, maternal smoking during pregnancy, socioeconomic status, birth year, and rural residence. We considered single and multipollutant models. We performed several sensitivity analyses, including assessing modifying effects of maternal comorbidities (e.g., diabetes, preeclampsia). RESULTS: The cohort comprised 505,336 children, including 539 with Kawasaki disease. HRs for each interquartile range increase in ambient air pollution were 1.16 (95% CI: 0.96, 1.39) for PM2.5 and 1.12 (95% CI: 0.96, 1.31) for NO2. For industrial air pollution, HRs were 1.07 (95% CI: 1.01, 1.13) for SO2, 1.09 (95% CI: 0.99, 1.20) for NO2, and 1.01 (95% CI: 0.97, 1.05) for PM2.5. In multipollutant models, associations for ambient PM2.5 and NO2 (i.e., from all sources) were robust to adjustment for industrial pollution, and vice versa. DISCUSSION: In this population-based cohort study, both prenatal exposure to ambient and industrial air pollution were associated with the incidence of Kawasaki disease in childhood. Further studies are needed to consolidate the observed associations. https://doi.org/10.1289/EHP6920.


Assuntos
Poluição do Ar/estatística & dados numéricos , Exposição Ambiental/estatística & dados numéricos , Síndrome de Linfonodos Mucocutâneos/epidemiologia , Efeitos Tardios da Exposição Pré-Natal/epidemiologia , Criança , Estudos de Coortes , Feminino , Humanos , Incidência , Indústrias , Estudos Longitudinais , Masculino , Material Particulado , Gravidez , Modelos de Riscos Proporcionais , Quebeque/epidemiologia , Fatores de Risco , Dióxido de Enxofre
18.
Sci Rep ; 10(1): 16703, 2020 10 07.
Artigo em Inglês | MEDLINE | ID: mdl-33028877

RESUMO

Urban populations are often simultaneously exposed to air pollution and environmental noise, which are independently associated with cardiovascular disease. Few studies have examined acute physiologic responses to both air and noise pollution using personal exposure measures. We conducted a repeated measures panel study of air pollution and noise in 46 non-smoking adults in Toronto, Canada. Data were analyzed using linear mixed-effects models and weighted cumulative exposure modeling of recent exposure. We examined acute changes in cardiovascular health effects of personal (ultrafine particles, black carbon) and regional (PM2.5, NO2, O3, Ox) measurements of air pollution and the role of personal noise exposure as a confounder of these associations. We observed adverse changes in subclinical cardiovascular outcomes in response to both air pollution and noise, including changes in endothelial function and heart rate variability (HRV). Our findings show that personal noise exposures can confound associations for air pollutants, particularly with HRV, and that impacts of air pollution and noise on HRV occur soon after exposure. Thus, both noise and air pollution have a measurable impact on cardiovascular physiology. Noise should be considered alongside air pollution in future studies to elucidate the combined impacts of these exposures in urban environments.


Assuntos
Poluentes Atmosféricos/efeitos adversos , Doenças Cardiovasculares/etiologia , Exposição Ambiental , Ruído/efeitos adversos , Poluição Relacionada com o Tráfego/efeitos adversos , Adolescente , Adulto , Poluição do Ar/efeitos adversos , Pressão Sanguínea/fisiologia , Canadá , Feminino , Frequência Cardíaca/fisiologia , Humanos , Masculino , População Urbana , Emissões de Veículos , Adulto Jovem
19.
Environ Int ; 145: 106135, 2020 12.
Artigo em Inglês | MEDLINE | ID: mdl-32979813

RESUMO

BACKGROUND: Ambient air pollution has been associated with childhood cancer. However, little is known about the possible impact of ambient ultrafine particles (<0.1 µm) (UFPs) on childhood cancer incidence. OBJECTIVE: This study aimed to evaluate the association between prenatal and childhood exposure to UFPs and development of childhood cancer. METHODS: We conducted a population-based cohort study of within-city spatiotemporal variations in ambient UFPs across the City of Toronto, Canada using 653,702 singleton live births occurring between April 1, 1998 and March 31, 2017. Incident cases of 13 subtypes of paediatric cancers among children up to age 14 were ascertained using a cancer registry. Associations between ambient air pollutant concentrations and childhood cancer incidence were estimated using random-effects Cox proportional hazards models. We investigated both single- and multi-pollutant models accounting for co-exposures to PM2.5 and NO2. RESULTS: A total of 1,066 childhood cancers were identified. We found that first trimester exposure to UFPs (Hazard Ratio (HR) per 10,000/cm3 increase = 1.13, 95% CI: 1.03-1.22) was associated with overall cancer incidence diagnosed before 6 years of age after adjusting for PM2.5, NO2, and for personal and neighborhood-level covariates. Association between UFPs and overall cancer incidence exhibited a linear shape. No statistically significant associations were found for specific cancer subtypes. CONCLUSION: Ambient UFPs may represent a previously unrecognized risk factor in the aetiology of cancers in children. Our findings reinforce the importance of conducting further research on the effects of UFPs given their high prevalence of exposure in urban areas.


Assuntos
Poluentes Atmosféricos , Poluição do Ar , Neoplasias , Adolescente , Poluentes Atmosféricos/análise , Canadá/epidemiologia , Criança , Estudos de Coortes , Exposição Ambiental/análise , Feminino , Humanos , Incidência , Neoplasias/induzido quimicamente , Neoplasias/epidemiologia , Dióxido de Nitrogênio/análise , Material Particulado/análise , Gravidez
20.
Environ Sci Technol ; 54(17): 10688-10699, 2020 09 01.
Artigo em Inglês | MEDLINE | ID: mdl-32786568

RESUMO

This study develops a set of algorithms to extract built environment features from Google aerial and street view images, reflecting the microcharacteristics of an urban location as well as the different functions of buildings. These features were used to train a Bayesian regularized artificial neural network (BRANN) model to predict near-road air quality based on measurements of ultrafine particles (UFPs) and black carbon (BC) in Toronto, Canada. The resulting models [adjusted R2 of 75.87 and 79.10% for UFP and BC and root mean squared error (RMSE) of 21,800 part/cm3 and 1300 ng/m3 for UFP and BC] were compared with similar ANN models developed using the same predictors, but extracted from traditional geographic information system (GIS) databases [adjusted R2 of 58.74 and 64.21% for UFP and BC and RMSE values of 23,000 part/cm3 and 1600 ng/m3 for UFP and BC]. The models based on feature extraction exhibited higher predictive power, thus highlighting the greater accuracy of the proposed methods compared to GIS layers that are solely based on aerial images. A comparison with other neural network approaches as well as with a traditional land-use regression model demonstrates the strength of the BRANN model for spatial interpolation of air quality.


Assuntos
Poluentes Atmosféricos , Poluição do Ar , Ambiente Construído , Poluentes Atmosféricos/análise , Poluição do Ar/análise , Teorema de Bayes , Canadá , Monitoramento Ambiental , Material Particulado/análise
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