Formaldehyde (HCHO) columns measured from space by solar UV backscatter allow mapping of reactive hydrocarbon emissions. The principal contributor to these emissions during the growing season is the biogenic hydrocarbon isoprene, which is of great importance for driving regional and global tropospheric chemistry. We present seven years (1995-2001) of HCHO column data for North America from the Global Ozone Monitoring Experiment (GOME), and show that the general seasonal and interannual variability of these data is consistent with knowledge of isoprene emission. There are some significant regional discrepancies with the seasonal patterns predicted from current isoprene emission models, and we suggest that these may reflect flaws in the models. The interannual variability of HCHO columns observed by GOME appears to follow the interannual variability of surface temperature, as expected from current isoprene emission models.

We investigate how a recently suggested pathway for production of secondary organic aerosol (SOA) affects the consistency of simulated organic aerosol (OA) mass in a global three-dimensional model of oxidant-aerosol chemistry (GEOS-Chem) versus surface measurements from the interagency monitoring of protected visual environments (IMPROVE) network. Simulations in which isoprene oxidation products contribute to SOA formation, with a yield of 2.0% by mass reduce a model bias versus measured OA surface mass concentrations. The resultant increase in simulated OA mass concentrations during summer of 0.6-1.0 μg m-3 in the southeastern United States reduces the regional RMSE to 0.88 μg m-3 from 1.26 μg m-3. Spring and fall biases are also reduced, with little change in winter when isoprene emissions are negligible. © 2006 Elsevier Ltd. All rights reserved.

Background

Evidence suggests a link between air pollution and dementia. Cardiovascular disease (CVD) may be a potential determinant of dementia. This motivated us to quantify the contribution of CVD to the association between air pollution and dementia.

Methods

A cohort of Canadian-born residents of Ontario, who participated in the 1996-2003 Canadian Community Health Surveys, was followed through 2013 or until dementia diagnosis. Exposure to nitrogen dioxide (NO2) and fine particulate matter (PM2.5) was estimated with a 3-year average and 5-year lag before dementia diagnosis. Incident CVD was evaluated as a mediator. We used multi-level Cox proportional and Aalen additive hazard regression models, adjusting for individual- and neighbourhood-level risk factors to estimate associations with NO2 and PM2.5. We estimated the total, direct and indirect effects of air pollution on dementia through cardiovascular disease.

Results

This study included 34 391 older adults. At baseline, the mean age of this cohort was 59 years. The risk of dementia was moderately higher among those more exposed to NO2 (hazard ratio (HR) 1.10, 95% confidence interval (CI) 0.99-1.19; and 100 additional cases per 100 000 [standard error (SE) <100x10-5]) and PM2.5 [(HR 1.29, 95% CI 0.99-1.64; 200 additional cases per 100 000] [SE 100x10-5]) after adjusting for covariates; however, these estimates are imprecise. A greater proportion of the relationship between PM2.5 and dementia was mediated through CVD than NO2 for both scales.

Conclusions

These results suggest some of the association between air pollution and dementia is mediated through CVD, indicating that improving cardiovascular health may prevent dementia in areas with higher exposure to air pollution.

Ambient fine particulate matter (PM2.5) is the worlds leading environmental health risk factor. Quantification is needed of regional contributions to changes in global PM2.5 exposure. Here we interpret satellite-derived PM2.5 estimates over 1998-2019 and find a reversal of previous growth in global PM2.5 air pollution, which is quantitatively attributed to contributions from 13 regions. Global population-weighted (PW) PM2.5 exposure, related to both pollution levels and population size, increased from 1998 (28.3 μg/m3) to a peak in 2011 (38.9 μg/m3) and decreased steadily afterwards (34.7 μg/m3 in 2019). Post-2011 change was related to exposure reduction in China and slowed exposure growth in other regions (especially South Asia, the Middle East and Africa). The post-2011 exposure reduction contributes to stagnation of growth in global PM2.5-attributable mortality and increasing health benefits per µg/m3 marginal reduction in exposure, implying increasing urgency and benefits of PM2.5 mitigation with aging population and cleaner air.

Background Long-term exposure to outdoor fine particulate matter (PM_2.5) is the leading environmental risk factor for premature mortality worldwide. Characterizing important pathways through which PM_2.5 increases individuals' mortality risk can clarify the PM_2.5-mortality relationship and identify possible points of interventions. Recent evidence has linked PM_2.5 to the onset of diabetes and cardiovascular disease, but to what extent these associations contribute to the effect of PM_2.5 on mortality remains poorly understood. Methods and Results We conducted a population-based cohort study to investigate how the effect of PM_2.5 on nonaccidental mortality is mediated by its impacts on incident diabetes, acute myocardial infarction, and stroke. Our study population comprised ≈200 000 individuals aged 20 to 90 years who participated in population-based health surveys in Ontario, Canada, from 1996 to 2014. Follow-up extended until December 2017. Using causal mediation analyses with Aalen additive hazards models, we decomposed the total effect of PM_2.5 on mortality into a direct effect and several path-specific indirect effects mediated by diabetes, each cardiovascular event, or both combined. A series of sensitivity analyses were also conducted. After adjusting for various individual- and neighborhood-level covariates, we estimated that for every 1000 adults, each 10 μg/m³ increase in PM_2.5 was associated with ≈2 incident cases of diabetes, ≈1 major cardiovascular event (acute myocardial infarction and stroke combined), and ≈2 deaths annually. Among PM_2.5-related deaths, 31.7% (95% CI, 17.2%-53.2%) were attributable to diabetes and major cardiovascular events in relation to PM_2.5. Specifically, 4.5% were explained by PM_2.5-induced diabetes, 22.8% by PM_2.5-induced major cardiovascular events, and 4.5% through their interaction. Conclusions This study suggests that a significant portion of the estimated effect of long-term exposure to PM_2.5 on deaths can be attributed to its effect on diabetes and cardiovascular diseases, highlighting the significance of PM_2.5 on deteriorating cardiovascular health. Our findings should raise awareness among professionals that improving metabolic and cardiovascular health may reduce mortality burden in areas with higher exposure to air pollution.

We estimate isoprene emissions over tropical South America during 1997-2001 using column measurements of formaldehyde (HCHO) from the Global Ozone Monitoring Experiment (GOME) satellite instrument, the GEOS-Chem chemistry transport model, and the MEGAN (Model of Emissions of Gases and Aerosols from Nature) bottom-up isoprene inventory. GEOS-Chem is qualitatively consistent with in situ ground-based and aircraft concentration profiles of isoprene and HCHO, and GOME HCHO column data (r = 0.41; bias = +35%), but has less skill in reproducing wet season observations. Observed variability of GOME HCHO columns over South America is determined largely by isoprene and biomass burning. We find that the column contributions from other biogenic volatile organic compounds (VOC) are typically smaller than the column fitting uncertainty. HCHO columns influenced by biomass burning are removed using Along Track Scanning Radiometer (ATSR) firecounts and GOME NO2 columns. We find that South America can be split into eastern and western regions, with fires concentrated over the eastern region. A monthly mean linear transfer function, determined by GEOS-Chem, is used to infer isoprene emissions from observed HCHO columns. The seasonal variation of GOME isoprene emissions over the western region is broadly consistent with MEGAN (r = 0.41; bias = -256%), with largest isoprene emissions during the dry season when the observed variability is consistent with knowledge of temperature dependence. During the wet season other unknown factors play a significant role in determining observed variability. Copyright 2008 by the American Geophysical Union.

Background

Little is known about the long-term health effects of ambient ultrafine particles (<0.1 μm) (UFPs) including their association with respiratory disease incidence. In this study, we examined the relationship between long-term exposure to ambient UFPs and the incidence of lung cancer, adult-onset asthma, and chronic obstructive pulmonary disease (COPD).

Methods

Our study cohort included approximately 1.1 million adults who resided in Toronto, Canada and who were followed for disease incidence between 1996 and 2012. UFP exposures were assigned to residential locations using a land use regression model. Random-effect Cox proportional hazard models were used to estimate hazard ratios (HRs) describing the association between ambient UFPs and respiratory disease incidence adjusting for ambient fine particulate air pollution (PM_2.5), NO₂, and other individual/neighbourhood-level covariates.

Results

In total, 74,543 incident cases of COPD, 87,141 cases of asthma, and 12,908 cases of lung cancer were observed during follow-up period. In single pollutant models, each interquartile increase in ambient UFPs was associated with incident COPD (HR = 1.06, 95% CI: 1.05, 1.09) but not asthma (HR = 1.00, 95% CI: 1.00, 1.01) or lung cancer (HR = 1.00, 95% CI: 0.97, 1.03). Additional adjustment for NO₂ attenuated the association between UFPs and COPD and the HR was no longer elevated (HR = 1.01, 95% CI: 0.98, 1.03). PM_2.5 and NO₂ were each associated with increased incidence of all three outcomes but risk estimates for lung cancer were sensitive to indirect adjustment for smoking and body mass index.

Conclusions

In general, we did not observe clear evidence of positive associations between long-term exposure to ambient UFPs and respiratory disease incidence independent of other air pollutants. Further replication is required as few studies have evaluated these relationships.

Background

Numerous epidemiological studies have documented the adverse health impact of long-term exposure to fine particulate matter [particulate matter ≤2.5μm in aerodynamic diameter (PM2.5)] on mortality even at relatively low levels. However, methodological challenges remain to consider potential regulatory intervention's complexity and provide actionable evidence on the predicted benefits of interventions. We propose the parametric g-computation as an alternative analytical approach to such challenges.

Method

We applied the parametric g-computation to estimate the cumulative risks of nonaccidental death under different hypothetical intervention strategies targeting long-term exposure to PM2.5 in the Canadian Community Health Survey cohort from 2005 to 2015. On both relative and absolute scales, we explored the benefits of hypothetical intervention strategies compared with the natural course that a) set the simulated exposure value at each follow-up year to a threshold value if exposure was above the threshold (8.8 μg/m3, 7.04 μg/m3, 5 μg/m3, and 4 μg/m3), and b) reduced the simulated exposure value by a percentage (5% and 10%) at each follow-up year. We used the 3-y average PM2.5 concentration with 1-y lag at the postal code of respondents' annual mailing addresses as their long-term exposure to PM2.5. We considered baseline and time-varying confounders, including demographics, behavior characteristics, income level, and neighborhood socioeconomic status. We also included the R syntax for reproducibility and replication.

Results

All hypothetical intervention strategies explored led to lower 11-y cumulative mortality risks than the estimated value under the natural course without intervention, with the smallest reduction of 0.20 per 1,000 participants (95% CI: 0.06, 0.34) under the threshold of 8.8 μg/m3, and the largest reduction of 3.40 per 1,000 participants (95% CI: -0.23, 7.03) under the relative reduction of 10% per interval. The reductions in cumulative risk, or numbers of deaths that would have been prevented if the intervention was employed instead of maintaining the status quo, increased over time but flattened toward the end of the follow-up period. Estimates among those ≥65 years of age were greater with a similar pattern. Our estimates were robust to different model specifications.

Discussion

We found evidence that any intervention further reducing the long-term exposure to PM2.5 would reduce the cumulative mortality risk, with greater benefits in the older population, even in a population already exposed to low levels of ambient PM2.5. The parametric g-computation used in this study provides flexibilities in simulating real-world interventions, accommodates time-varying exposure and confounders, and estimates adjusted survival curves with clearer interpretation and more information than a single hazard ratio, making it a valuable analytical alternative in air pollution epidemiological research. https://doi.org/10.1289/EHP11095.

Epidemiologic studies have found associations between fine particulate matter (PM_2.5) exposure and adverse health effects using exposure models that incorporate monitoring data and other relevant information. Here, we use nine PM_2.5 concentration models (i.e., exposure models) that span a wide range of methods to investigate i) PM_2.5 concentrations in 2011, ii) potential changes in PM_2.5 concentrations between 2011 and 2028 due to on-the-books regulations, and iii) PM_2.5 exposure for the U.S. population and four racial/ethnic groups. The exposure models included two geophysical chemical transport models (CTMs), two interpolation methods, a satellite-derived aerosol optical depth-based method, a Bayesian statistical regression model, and three data-rich machine learning methods. We focused on annual predictions that were regridded to 12-km resolution over the conterminous U.S., but also considered 1-km predictions in sensitivity analyses. The exposure models predicted broadly consistent PM_2.5 concentrations, with relatively high concentrations on average over the eastern U.S. and greater variability in the western U.S. However, differences in national concentration distributions (median standard deviation: 1.00 μg m^-3) and spatial distributions over urban areas were evident. Further exploration of these differences and their implications for specific applications would be valuable. PM_2.5 concentrations were estimated to decrease by about 1 μg m^-3 on average due to modeled emission changes between 2011 and 2028, with decreases of more than 3 μg m^-3 in areas with relatively high 2011 concentrations that were projected to experience relatively large emission reductions. Agreement among models was closer for population-weighted than uniformly weighted averages across the domain. About 50% of the population was estimated to experience PM_2.5 concentrations less than 10 μg m^-3 in 2011 and PM_2.5 improvements of about 2 μg m^-3 due to modeled emission changes between 2011 and 2028. Two inequality metrics were used to characterize differences in exposure among the four racial/ethnic groups. The metrics generally yielded consistent information and suggest that the modeled emission reductions between 2011 and 2028 would reduce absolute exposure inequality on average.

BACKGROUND: Numerous studies have linked fine particulate matter (PM2.5) to increased cardiovascular mortality. Less is known how the PM2.5-cardiovascular mortality association varies by use of cardiovascular medications. This study sought to quantify effect modification by statin use status on the associations between long-term exposure to PM2.5 and mortality from any cardiovascular cause, coronary heart disease (CHD), and stroke. METHODS: In this nested case-control study, we followed 1.2 million community-dwelling adults aged ≥66 years who lived in Ontario, Canada from 2000 through 2018. Cases were patients who died from the three causes. Each case was individually matched to up to 30 randomly selected controls using incidence density sampling. Conditional logistic regression models were used to estimate odds ratios (ORs) for the associations between PM2.5 and mortality. We evaluated the presence of effect modification considering both multiplicative (ratio of ORs) and additive scales (the relative excess risk due to interaction, RERI). RESULTS: Exposure to PM2.5 increased the risks for cardiovascular, CHD, and stroke mortality. For all three causes of death, compared with statin users, stronger PM2.5-mortality associations were observed among non-users [e.g. for cardiovascular mortality corresponding to each interquartile range increase in PM2.5, OR = 1.042 (95% CI, 1.032-1.053) vs OR = 1.009 (95% CI, 0.996-1.022) in users, ratio of ORs = 1.033 (95% CI, 1.019-1.047), RERI = 0.039 (95% CI, 0.025-0.050)]. Among users, partially adherent users exhibited a higher risk of PM2.5-associated mortality than fully adherent users. CONCLUSIONS: The associations of chronic exposure to PM2.5 with cardiovascular and CHD mortality were stronger among statin non-users compared to users.