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Does attainment status for the PM10 National Air Ambient Quality Standard change the trend in ambient levels of particulate matter?
Abstract
Despite increasingly stringent and cost-demanding national, state, and local air quality regulations, adverse health effects
associated with ambient exposure to air pollution persist. Accountability research, aimed at evaluating the effects of air
quality regulation on health outcome, is increasingly viewed as an essential component of responsible government intervention.
In this paper, we focused on assessing the impact of air quality regulations on ambient levels of air pollution. We considered
two groups of counties: the first group (A) includes counties that in 1991 were designated as in attainment or unclassifiable
with respect to the 1987 National Ambient Air Quality Standards (NAAQS) and maintained their status through 2006; the second
group (Ā), includes counties that in 1991 were designated as nonattainment and were subsequently redesignated as in attainment.
We hypothesized that if air pollution control programs adopted to meet the NAAQS are effective in reducing air pollution levels,
counties in group Ā will experience a sharper decrease in PM10 levels than counties in group A. To provide evidence to support this hypothesis, Bayesian hierarchical models were developed
for estimating 1) the yearly percentage change in ambient PM10 levels for 100 counties and the entire USA during the period 1987–2007 and 2) the change in PM10 ambient levels in counties in group Ā compared with counties in group A. We found statistically significant evidence of variability
across counties in trends of PM10 concentrations. We also found strong evidence that counties transitioning from nonattainment to attainment status during
the period 1987–2007 experienced a sharper decline in PM10 when compared with counties that were always in attainment.
KeywordsParticulate matter–Bayesian methods–Hierarchical models–National Ambient Air Quality Standards–Accountability–Environmental epidemiology
... In the last years, environmental and public health scientists have conducted several accountability studies in Asia (Hedley et al. 2002;Lee et al. 2007; Wang and Xie 2009;Zhang et al. 2013), Europe (Cesaroni et al. 2012;Clancy et al. 2002;Ebelt et al. 2001;Heinrich et al. 2002;Kelly et al. 2011a, b;Mudway et al. 2018;Pitz et al. 2001;Wichmann et al. 2000), and the USA (Chay et al. 2003;Greenstone 2004;Rava et al. 2011;van Erp et al. 2012) in order to focus on the effectiveness of air quality regulations. Furthermore, a systematic review was being published, showing great heterogeneity across interventions, outcomes, and methods (Burns et al. 2019). ...
Public interventions to reduce industrial emissions and improve air quality are particularly necessary in areas that suffer an environmental and health emergency. Taranto (Apulia region, Southern Italy) is one of the most industrialized cities in Southern Italy due to the massive presence of industrial sites, including a huge steel plant. The latter hosts a large open-air mineral deposit, whose dust strongly impacts the Tamburi neighborhood, downwind of the plant when the wind blows north-wester. In order to reduce the PM10 (particulate matter) and B(a)P (Benzo(a)pirene) concentrations in this neighborhood, the Apulia Region enacted a law restricting some industrial activities during certain meteorological situations, called wind days, characterized by strong north-westerly winds. Connected to the regional law, there was a Local Health Unit warning to the Tamburi population to ventilate indoor environments during the central hours of the day. The aim of this work is to assess the effectiveness and the appropriateness of the intervention implemented and to evaluate whether it effectively improved the air quality in the neighborhood close to the mineral deposit. Time-space statistical analysis of PM data measured by the fixed monitoring network before and after the intervention period was carried out. The analysis was performed for different meteorological conditions, different wind days characteristics (long/short), time periods, and other pollutants such as PAH (polycyclic aromatic hydrocarbon), which includes B(a)P for which measurements were not available. In the area closest to the industrial area, there was a reduction in the difference between the concentration of PM10 on wind days and those in other weather conditions. The reduction was more consistent on long, persistent wind days, when the difference in concentrations reduced from 13.3 to 3.9 μg/m3. However, the uncertainties regarding the wind days predictions suggest that the PM reduction may only partially be attributed to the regional law. Furthermore, the analysis of the PAH showed that there are weather conditions other than wind days that lead to a deterioration in the air quality in the neighborhood. Regarding the warning given by local health authorities to protect the population from dust injuries, the wind days daily PM10 profiles do not evidence a sharp reduction during the selected time slot, while other industrial pollutants clearly increase in the same time slot. Overall, results evidence the partiality of the intervention and call for a more comprehensive emissions plan to reduce their impact on air quality. In general, the study shows the need to periodically evaluate the effectiveness of any intervention and to take the consequent decisions to adapt them.
Background:
Ambient air pollution is associated with a large burden of disease in both high-income countries (HICs) and low- and middle-income countries (LMICs). To date, no systematic review has assessed the effectiveness of interventions aiming to reduce ambient air pollution.
Objectives:
To assess the effectiveness of interventions to reduce ambient particulate matter air pollution in reducing pollutant concentrations and improving associated health outcomes.
Search methods:
We searched a range of electronic databases with diverse focuses, including health and biomedical research (CENTRAL, Cochrane Public Health Group Specialised Register, MEDLINE, Embase, PsycINFO), multidisciplinary research (Scopus, Science Citation Index), social sciences (Social Science Citation Index), urban planning and environment (Greenfile), and LMICs (Global Health Library regional indexes, WHOLIS). Additionally, we searched grey literature databases, multiple online trial registries, references of included studies and the contents of relevant journals in an attempt to identify unpublished and ongoing studies, and studies not identified by our search strategy. The final search date for all databases was 31 August 2016.
Selection criteria:
Eligible for inclusion were randomized and cluster randomized controlled trials, as well as several non-randomized study designs, including controlled interrupted time-series studies (cITS-EPOC), interrupted time-series studies adhering to EPOC standards (ITS-EPOC), interrupted time-series studies not adhering to EPOC standards (ITS), controlled before-after studies adhering to EPOC standards (CBA-EPOC), and controlled before-after studies not adhering to EPOC standards (CBA); these were classified as main studies. Additionally, we included uncontrolled before-after studies (UBA) as supporting studies. We included studies that evaluated interventions to reduce ambient air pollution from industrial, residential, vehicular and multiple sources, with respect to their effect on mortality, morbidity and several air pollutant concentrations. We did not restrict studies based on the population, setting or comparison.
Data collection and analysis:
After a calibration exercise among the author team, two authors independently assessed studies for inclusion, extracted data and assessed risk of bias. We conducted data extraction, risk of bias assessment and evidence synthesis only for main studies; we mapped supporting studies with regard to the types of intervention and setting. To assess risk of bias, we used the Graphic Appraisal Tool for Epidemiological studies (GATE) for correlation studies, as modified and employed by the Centre for Public Health Excellence at the UK National Institute for Health and Care Excellence (NICE). For each intervention category, i.e. those targeting industrial, residential, vehicular and multiple sources, we synthesized evidence narratively, as well as graphically using harvest plots.
Main results:
We included 42 main studies assessing 38 unique interventions. These were heterogeneous with respect to setting; interventions were implemented in countries across the world, but most (79%) were implemented in HICs, with the remaining scattered across LMICs. Most interventions (76%) were implemented in urban or community settings.We identified a heterogeneous mix of interventions, including those aiming to address industrial (n = 5), residential (n = 7), vehicular (n = 22), and multiple sources (n = 4). Some specific interventions, such as low emission zones and stove exchanges, were assessed by several studies, whereas others, such as a wood burning ban, were only assessed by a single study.Most studies assessing health and air quality outcomes used routine monitoring data. Studies assessing health outcomes mostly investigated effects in the general population, while few studies assessed specific subgroups such as infants, children and the elderly. No identified studies assessed unintended or adverse effects.The judgements regarding the risk of bias of studies were mixed. Regarding health outcomes, we appraised eight studies (47%) as having no substantial risk of bias concerns, five studies (29%) as having some risk of bias concerns, and four studies (24%) as having serious risk of bias concerns. Regarding air quality outcomes, we judged 11 studies (31%) as having no substantial risk of bias concerns, 16 studies (46%) as having some risk of bias concerns, and eight studies (23%) as having serious risk of bias concerns.The evidence base, comprising non-randomized studies only, was of low or very low certainty for all intervention categories and primary outcomes. The narrative and graphical synthesis showed that evidence for effectiveness was mixed across the four intervention categories. For interventions targeting industrial, residential and multiple sources, a similar pattern emerged for both health and air quality outcomes, with essentially all studies observing either no clear association in either direction or a significant association favouring the intervention. The evidence base for interventions targeting vehicular sources was more heterogeneous, as a small number of studies did observe a significant association favouring the control. Overall, however, the evidence suggests that the assessed interventions do not worsen air quality or health.
Authors' conclusions:
Given the heterogeneity across interventions, outcomes, and methods, it was difficult to derive overall conclusions regarding the effectiveness of interventions in terms of improved air quality or health. Most included studies observed either no significant association in either direction or an association favouring the intervention, with little evidence that the assessed interventions might be harmful. The evidence base highlights the challenges related to establishing a causal relationship between specific air pollution interventions and outcomes. In light of these challenges, the results on effectiveness should be interpreted with caution; it is important to emphasize that lack of evidence of an association is not equivalent to evidence of no association.We identified limited evidence for several world regions, notably Africa, the Middle East, Eastern Europe, Central Asia and Southeast Asia; decision-makers should prioritize the development and implementation of interventions in these settings. In the future, as new policies are introduced, decision-makers should consider a built-in evaluation component, which could facilitate more systematic and comprehensive evaluations. These could assess effectiveness, but also aspects of feasibility, fidelity and acceptability.The production of higher quality and more uniform evidence would be helpful in informing decisions. Researchers should strive to sufficiently account for confounding, assess the impact of methodological decisions through the conduct and communication of sensitivity analyses, and improve the reporting of methods, and other aspects of the study, most importantly the description of the intervention and the context in which it is implemented.
The main purpose of this paper is to present the evolution of the concentration for four main air pollutants in Craiova city, during twelve month (i.e., by any kind of weather). The selected period was between July 1st 2010 and June 30th 2011, and the pollutants submitted to the investigation were: nitrogen oxides NOx, sulfur dioxide SO2, carbon monoxide CO and suspended particulate matter, PM10. Within the paper, two purposes are achieved. The most important one is presenting the data about the evolution of the concentration of the four pollutants taken into study, graphics being used to show the situation of air quality in Craiova during the selected period. Another purpose was to find a statistical model to fit the recorded data for PM10, which is the log-normal distribution (the paper also presents some theoretical features of the model).
This paper provides a brief overview of recent EPA forecasts of air quality and emissions related to ozone and particle pollution.
It is intended to supplement conference papers on air quality (White 2007) and benefits estimates by highlighting the potential utility of national, regional, and local forecasts in developing and
implementing health and environmental quality tracking programs. As Hubbell and Fann (2007) note, such forecasts are of particular importance in evaluating the feasibility and design of programs intended to assess
the benefits of air-related control or mitigation programs. Tracking programs may focus on overall air quality improvements
or on reductions from particular source categories of interest.
Accountability of air quality management is often measured by tracking ambient pollution concentrations over time. These changes
in ambient air quality are rarely linked to changes in public health, a major driver for such programs. We propose a method
to assess the accountability of air quality management programs with respect to improvements in public health by estimating
national temporal trends in health risk attributable to air pollution. The air health indicator (AHI) is a function of two
temporal functions, annual air pollutant concentrations and annual estimates of health risk obtained by time series statistical
methods, to indicate the trend in annual percent attributable risk (the product of concentration and risk times 100). Random
effects models are used to obtain a distribution of risk over space. The model is illustrated by examining the association
between daily nonaccidental deaths in 24 of Canada’s largest cities and daily concentrations of ozone and nitrogen dioxide
over the 17-year period 1984–2000. Our analysis demonstrates that examining trends in exposure alone, which has typically
been the approach to air quality indicators, provides an incomplete picture of trends in the impact of air pollution. The
AHI appears to provide a more informative measure of the population burden of illness associated with air pollution over time.
Exposure to fine-particulate air pollution has been associated with increased morbidity and mortality, suggesting that sustained reductions in pollution exposure should result in improved life expectancy. This study directly evaluated the changes in life expectancy associated with differential changes in fine particulate air pollution that occurred in the United States during the 1980s and 1990s.
We compiled data on life expectancy, socioeconomic status, and demographic characteristics for 211 county units in the 51 U.S. metropolitan areas with matching data on fine-particulate air pollution for the late 1970s and early 1980s and the late 1990s and early 2000s. Regression models were used to estimate the association between reductions in pollution and changes in life expectancy, with adjustment for changes in socioeconomic and demographic variables and in proxy indicators for the prevalence of cigarette smoking.
A decrease of 10 microg per cubic meter in the concentration of fine particulate matter was associated with an estimated increase in mean (+/-SE) life expectancy of 0.61+/-0.20 year (P=0.004). The estimated effect of reduced exposure to pollution on life expectancy was not highly sensitive to adjustment for changes in socioeconomic, demographic, or proxy variables for the prevalence of smoking or to the restriction of observations to relatively large counties. Reductions in air pollution accounted for as much as 15% of the overall increase in life expectancy in the study areas.
A reduction in exposure to ambient fine-particulate air pollution contributed to significant and measurable improvements in life expectancy in the United States.
Ten years of public health interventions on industrial emissions to clean air were monitored for the Mediterranean city of Cartagena. During the 1960s, a number of large chemical and non-ferrous metallurgical factories were established that significantly deteriorated the city's air quality. By the 1970s, the average annual air concentration of sulfur dioxide (SO2) ranged from 200 to 300 microg/m3 (standard conditions units). In 1979, the Spanish government implemented an industrial intervention plan to improve the performance of factories and industrial air pollution surveillance. Unplanned urban development led to residential housing being located adjacent to three major factories. Factory A produced lead, factory B processed zinc from ore concentrates, and factory C produced sulfuric acid and phosphates. This, in combination with the particular abrupt topography and frequent atmospheric thermal inversions, resulted in the worsening of air quality and heightening concern for public health. In 1990, the City Council authorized the immediate intervention at these factories to reduce or shut down production if ambient levels of SO2 or total suspended particles (TSP) exceeded a time-emission threshold in pre-established meteorological contexts. The aim of this research was to assess the appropriateness and effectiveness of the intervention plan implemented from 1992 to 2001 to abate industrial air pollution.
The maximum daily 1-h ambient air level of SO2, NO2, and TSP pollutants was selected from one of the three urban automatic stations, designed to monitor ambient air quality around industrial emissions sources. The day on which an intervention took place to reduce and/or interrupt industrial production by factory and pollutant was defined as a control day, and the day after an intervention as a post-control day. To assess the short-term intervention effect on air quality, an ecological time series design was applied, using regression analysis in generalized additive models, focusing on day-to-day variations of ambient air pollutants levels. Two indicators were estimated: (a) appropriateness, the ratio between mean levels of the pollutant for control days versus the other days, and (b) effectiveness, the ratio between mean levels of the pollutant for post-control days versus the other days. Ratios in regression analyses were adjusted for trend, seasonality, temperature, humidity and atmospheric pressure, calendar day, and special events as well as the other pollutants.
A total of 702 control days were made on the factories' industrial production during the 10-year period. Fifteen reductions and five shutdown control days took place at factory A for ambient air SO2. At factory B, more controls were carried out for the SO2 pollutant in the years 1992-1993 and 1997. At factory C, the control days for SO2 decreased from 59 reductions and 14 shutdowns to a minimum from 1995 onwards, whereas the controls on TSP were more frequent, reaching a maximum of 99 reductions and 47 shutdowns in the last year. SO2 ambient air mean levels ranged from 456 to 699 microg/m(3) among factories on reduction control days and between 624 and 1,010 microg/m(3) on shutdown days. The TSP ambient air mean levels were 428 and 506 microg/m(3) on reduction and shutdown days, respectively. For all types of control days and factories, a mean ratio of 104% (95% confidence interval [CI] 88 to 121) in SO(2) levels was obtained and a mean ratio of 67% (95% CI 59 to 75) in TSP levels. Post-control days at all factories showed a mean ratio of -16% (95% CI -7 to -24) in SO(2) levels and a mean ratio of -13% (95% CI -7 to -19) in TSP levels.
Interventions on industrial production based on the urban SO(2) and TSP ambient air levels were justified by the high concentrations detected. The best assessment of the interventions' effectiveness would have been to utilize the ambient air pollutant concentration readings from the entire time of the production shutdowns or reductions; however, the daily hourly maximum turned out to be a useful indicator because of meteorological factors influencing the diurnal concentration profile. A substantial number of interventions were carried out from 1 to 3 AM: , when vehicular traffic was minimum. On the other hand, atmospheric stability undergoes diurnal cycling in the autumn-winter period due to thermal inversion, which reaches maximum levels around daybreak. Therefore, this increases the ambient air levels and justified the interventions carried out at daybreak in spite of the traffic influence.
All the interventions for SO(2) and TSP were carried out when the measured ambient air levels of pollutants were exceeded, which shows the appropriateness of the intervention program. This excess was greater when intervening on SO(2) than on the TSP levels. For both ambient air levels of SO(2) and TSP, significant drops in air pollution were achieved from all three factories following activity reductions. The production shutdown controls were very effective, because they returned excess levels, higher than in the reduction controls, to everyday mean values.
The Cartagena City observational system of intermittent control has proven to effectively reduce industrial emissions' impact on ambient air quality. This experienced model approach could serve well in highly polluted industrial settings. From a public health perspective, studies are needed to assess that the industrial interventions to control air pollution were related to healthier human populations. Legislation was needed to allow the public administration to take direct actions upon the polluting industries.
A large body of epidemiologic literature has found an association of increased fine particulate air pollution (PM2.5) with acute and chronic mortality. The effect of improvements in particle exposure is less clear.
Earlier analysis of the Harvard Six Cities adult cohort study showed an association between long-term ambient PM2.5 and mortality between enrollment in the mid-1970s and follow-up until 1990. We extended mortality follow-up for 8 yr in a period of reduced air pollution concentrations.
Annual city-specific PM2.5 concentrations were measured between 1979 and 1988, and estimated for later years from publicly available data. Exposure was defined as (1) city-specific mean PM2.5 during the two follow-up periods, (2) mean PM2.5 in the first period and change between these periods, (3) overall mean PM2.5 across the entire follow-up, and (4) year-specific mean PM2.5. Mortality rate ratios were estimated with Cox proportional hazards regression controlling for individual risk factors.
We found an increase in overall mortality associated with each 10 microg/m3 increase in PM2.5 modeled either as the overall mean (rate ratio [RR], 1.16; 95% confidence interval [CI], 1.07-1.26) or as exposure in the year of death (RR, 1.14; 95% CI, 1.06-1.22). PM2.5 exposure was associated with lung cancer (RR, 1.27; 95% CI, 0.96-1.69) and cardiovascular deaths (RR, 1.28; 95% CI, 1.13-1.44). Improved overall mortality was associated with decreased mean PM2.5 (10 microg/m3) between periods (RR, 0.73; 95% CI, 0.57-0.95).
Total, cardiovascular, and lung cancer mortality were each positively associated with ambient PM2.5 concentrations. Reduced PM2.5 concentrations were associated with reduced mortality risk.
Evidence on the health risks associated with short-term exposure to fine particles (particulate matter < or =2.5 microm in aerodynamic diameter [PM2.5]) is limited. Results from the new national monitoring network for PM2.5 make possible systematic research on health risks at national and regional scales.
To estimate risks of cardiovascular and respiratory hospital admissions associated with short-term exposure to PM2.5 for Medicare enrollees and to explore heterogeneity of the variation of risks across regions.
A national database comprising daily time-series data daily for 1999 through 2002 on hospital admission rates (constructed from the Medicare National Claims History Files) for cardiovascular and respiratory outcomes and injuries, ambient PM2.5 levels, and temperature and dew-point temperature for 204 US urban counties (population >200,000) with 11.5 million Medicare enrollees (aged >65 years) living an average of 5.9 miles from a PM2.5 monitor.
Daily counts of county-wide hospital admissions for primary diagnosis of cerebrovascular, peripheral, and ischemic heart diseases, heart rhythm, heart failure, chronic obstructive pulmonary disease, and respiratory infection, and injuries as a control outcome.
There was a short-term increase in hospital admission rates associated with PM2.5 for all of the health outcomes except injuries. The largest association was for heart failure, which had a 1.28% (95% confidence interval, 0.78%-1.78%) increase in risk per 10-microg/m3 increase in same-day PM2.5. Cardiovascular risks tended to be higher in counties located in the Eastern region of the United States, which included the Northeast, the Southeast, the Midwest, and the South.
Short-term exposure to PM2.5 increases the risk for hospital admission for cardiovascular and respiratory diseases.
To alleviate traffic congestion in Central London, the Mayor introduced the Congestion Charging Scheme (CCS) in February 2003. We modelled the impact of the CCS on levels of traffic pollutants, life expectancy and socioeconomic inequalities.
Annual average NO(2) and PM(10) were modelled using an emission-dispersion model. We assumed the meteorology and vehicle fleet remained constant during the pre- and post-CCS periods to isolate changes due to traffic flow. Air pollution concentrations were linked to small area socioeconomic, population and mortality data. Associated changes in life expectancy were predicted using life table analysis and exposure-response coefficients from the literature.
Before the introduction of the CCS, annual average NO(2) was 39.9 microg/m(3) and PM(10) was 26.2 microg/m(3) across Greater London. Concentrations were 54.7 microg/m(3) for NO(2) and 30.3 microg/m(3) for PM(10) among census wards within or adjacent to the charging zone. Absolute and relative reductions in concentrations following the introduction of the CCS were greater among charging zone wards compared to remaining wards. Predicted benefits in the charging zone wards were 183 years of life per 100,000 population compared to 18 years among the remaining wards. In London overall, 1888 years of life were gained. More deprived areas had higher air pollution concentrations; these areas also experienced greater air pollution reductions and mortality benefits compared to the least deprived areas.
The CCS, a localised scheme targeting traffic congestion, appears to have modest benefit on air pollution levels and associated life expectancy. Greater reductions in air pollution in more deprived areas are likely to make a small contribution to reducing socioeconomic inequalities in air pollution impacts.
Health risks of fine particulate matter of 2.5 microm or less in aerodynamic diameter (PM2.5) have been studied extensively over the last decade. Evidence concerning the health risks of the coarse fraction of greater than 2.5 microm and 10 microm or less in aerodynamic diameter (PM10-2.5) is limited.
To estimate risk of hospital admissions for cardiovascular and respiratory diseases associated with PM10-2.5 exposure, controlling for PM2.5.
Using a database assembled for 108 US counties with daily cardiovascular and respiratory disease admission rates, temperature and dew-point temperature, and PM10-2.5 and PM2.5 concentrations were calculated with monitoring data as an exposure surrogate from January 1, 1999, through December 31, 2005. Admission rates were constructed from the Medicare National Claims History Files, for a study population of approximately 12 million Medicare enrollees living on average 9 miles (14.4 km) from collocated pairs of PM10 and PM2.5 monitors.
Daily counts of county-wide emergency hospital admissions for primary diagnoses of cardiovascular or respiratory disease.
There were 3.7 million cardiovascular disease and 1.4 million respiratory disease admissions. A 10-microg/m3 increase in PM10-2.5 was associated with a 0.36% (95% posterior interval [PI], 0.05% to 0.68%) increase in cardiovascular disease admissions on the same day. However, when adjusted for PM2.5, the association was no longer statistically significant (0.25%; 95% PI, -0.11% to 0.60%). A 10-microg/m3 increase in PM10-2.5 was associated with a nonstatistically significant unadjusted 0.33% (95% PI, -0.21% to 0.86%) increase in respiratory disease admissions and with a 0.26% (95% PI, -0.32% to 0.84%) increase in respiratory disease admissions when adjusted for PM2.5. The unadjusted associations of PM2.5 with cardiovascular and respiratory disease admissions were 0.71% (95% PI, 0.45%-0.96%) for same-day exposure and 0.44% (95% PI, 0.06% to 0.82%) for exposure 2 days before hospital admission.
After adjustment for PM2.5, there were no statistically significant associations between coarse particulates and hospital admissions for cardiovascular and respiratory diseases.
During the 1980s Ireland experienced severe pollution episodes, principally because of domestic coal burning. In 1990, the Irish government introduced a ban on the marketing, sale, and distribution of coal in Dublin. They extended the ban to Cork in 1995 and to ten other communities in 1998 and 2000. We previously reported declines in particulate (black smoke [BS]) and sulfur dioxide (SO2) concentrations in Dublin following the 1990 coal ban. We now explore and compare the effectiveness of these sequential bans in 1990, 1995, 1998, and 2000. Daily BS and total gaseous acidity (SO2) measurements were compiled between 1980 and 2004. We calculated descriptive statistics for the pre-ban (5 yr before ban) and post-ban (5 yr after ban) periods for BS and SO2 concentrations and for season-specific periods. Mean BS levels fell in all centers post-ban compared with the pre-ban period, with decreases ranging from 4 to 35 μg∙m (–45 to –70%). These reductions were smallest in the summer and largest in the winter. These BS reductions were sustained in all centers until the end of the study period. We observed no clear pattern in SO2 changes associated with the coal bans. The 1990, 1995, 1998, and 2000 Irish coal sale bans resulted in immediate and sustained decreases in particulate levels in centers, with the largest declines in the winter. In contrast, we did not observe consistent declines in total acidity as a measure of SO2. It may be that coal was not the major source of SO2. Simple legislation was very effective at improving ambient air quality in Irish cities with varying populations, geography/topography, and meteorological conditions.
Estimation of the effects of environmental impacts is a major focus of current theoretical and policy research in environmental economics. Such estimates are used to set regulatory standards for pollution exposure; design appropriate environmental protection and damage mitigation strategies; guide the assessment of environmental impacts; and measure public willingness to pay for environmental amenities. It is a truism that the effectiveness of such strategies depends crucially on the quality of the estimates used to inform them. However, this paper argues that in respect to at least one area of the empirical literature—the estimation of the health impacts of air pollution using daily time series data—existing estimates are questionable and thus have limited relevance for environmental decision-making. By neglecting the issue of model uncertainty—or which models, among the myriad of possible models researchers should choose from to estimate health effects—most studies overstate confidence in their chosen model and underestimate the evidence from other models, thereby greatly enhancing the risk of obtaining uncertain and inaccurate results. This paper discusses the importance of model uncertainty for accurate estimation of the health effects of air pollution and demonstrates its implications in an exercise that models pollution-mortality impacts using a new and comprehensive data set for Toronto, Canada. The main empirical finding of the paper is that standard deviations for air pollution-mortality impacts become very large when model uncertainty is incorporated into the analysis. Indeed they become so large as to question the plausibility of previously measured links between air pollution and mortality. Although applied to the estimation of the effects of air pollution, the general message of this paper—that proper treatment of model uncertainty critically determines the accuracy of the resulting estimates—applies to many studies that seek to estimate environmental effects.
Around the world, daily variations in ambient air pollution have been consistently associated with variations in daily mortality. The aim of the study presented here was to assess the effects of ambient air pollution on daily mortality during a period of tremendous changes in air quality in the city of Erfurt, in eastern Germany, from October 1991 to March 2002. Data on particle size distributions were obtained from September 1995 to March 2002 at a research monitoring station. For particles from 0.01 microm to 2.5 microm in diameter, number concentrations (NCs)* and mass concentrations (MCs) were calculated. Particles with diameters less than or equal to 0.10 microm are defined as ultrafine particles (UFP). Data on the gaseous pollutants NO2, CO, SO2, and O3 and on PM10 (particulate matter [PM] with aerodynamic diameter less than or equal to 10 microm) were obtained from a government air-monitoring station. Data on changes in energy consumption, car fleet composition, and population were collected from local authorities. Death certificates of persons living in and dying in Erfurt were abstracted, and daily mortality counts were calculated. Poisson regression models were used to analyze the data, applying penalized splines (also known as P-splines) to model nonlinear relationships in the confounders. Model selection was done without air pollutants in the models, based on a combination of goodness-of-fit criteria and avoidance of autocorrelation in error terms. Final models included P-splines of time trend, meteorologic data, and influenza epidemics as well as day of the week with an indicator variable. Results are presented as change per interquartile range (IQR), i.e., change in the relative risk of mortality associated with a change in the concentration from the 25th to the 75th percentile of a given pollutant. Air pollutants were considered both as linear terms and as P-splines to assess the exposure-response functions. Changes in effect estimates over time were calculated using fully Bayesian time-varying coefficient models. This method was selected over four other approaches tested in simulation studies. Air-pollution concentrations decreased substantially in Erfurt during the decade under observation. The strongest changes were observed for SO2, for which annual concentrations decreased from 64 microg/m3 in 1992 to 4 microg/m3 in 2001. Concentrations of PM10, PM2.5 (particulate matter with aerodynamic diameter less than or equal to 2.5 microm), and CO decreased by more than 50%. NO2, O3, and ultrafine particles also decreased, though to a lesser extent. Based on visual inspection of the data on the changes in ambient air-pollution concentrations during the study period, we defined three study subperiods: A first subperiod from 1991 to 1995; a second, transitional subperiod from 1995 to 1998; and a third subperiod from 1998 to 2002. Generally, air-pollution concentrations decreased substantially from the first subperiod to the second, and some additional decreases occurred from the second subperiod to the third. During the second, transitional subperiod, natural gas replaced coal as the main energy source in Erfurt. In addition, the number of cars with catalytic converters increased over time, as did the number of cars in general. To facilitate the interpretation of the results, we organized the air pollutants into four groups: (1) NO2, CO, and ultrafine particles, (2) PM10 and PM2.5, (3) SO2, and (4) O3. We observed a 1.6% increased risk for daily mortality (CI, -0.4% to 3.5%) for an increase of 19.7 microg/m3 in NO2 (lag day 3), a 1.9% increased risk (CI, 0.2%-3.6%) for an increase of 0.48 mg/m3 in CO (lag day 4), and a 2.9% increased risk (CI, 0.3%-5.5%) for an increase of 9743/cm3 in ultrafine particles (lag day 4). No consistent associations were observed for PM10, PM2.5, or SO2. For O3, a 4.6% increased risk for daily mortality (CI, 1.1%-8.3%) was associated with a 43.8 microg/m3 maximum 8-hr concentration of O3 per day (lag day 2). For all four pollutants, exposure-response functions suggested no deviation from linearity. However, in time-varying models the strongest associations were observed for NO2, CO, and ultrafine particles during the transition subperiod, from 1995 to 1998, when O3 concentrations were lowest. Changes in source characteristics or ambient air-pollution concentrations were not able to explain these observations in a straightforward manner. However, the observations suggested that changes such as the introduction of three-way catalytic converters in cars and the substitution natural gas for coal might have been beneficial. Overall we concluded that: 1. Economic and political changes and the adoption of new technologies in eastern Germany resulted in distinct improvements in ambient air quality; 2. Urban air pollution in Erfurt changed within one decade from the eastern mixture toward that of western Europe ("western mixture"), which is dominated by concentrations of NOx, O3, fine particles, and ultrafine particles with low concentrations of SO2; 3. There was an association between daily mortality and ultrafine particles and combustion-related gases (lag days 3 or 4); 4. Ultrafine particles seemed to be the best pollution indicator and to point to the role of local combustion in the pollution mixture; 5. Regression coefficients showed variation over time for NO2, CO, ultrafine particles, and O3 that could not be explained by nonlinearity in the exposure-response functions; 6. Mortality associated with pollution was lower at the end of the 1990s than during the 1990s, except for mortality associated with O3; and 7. Mortality associated with pollution was strongest in the second, transitional subperiod, from 1995 to 1998, when changes in source characteristics had taken place but the benefits of improved ambient air quality had not yet been completely achieved.
The 1981–1982 recession induced substantial variation across sites in air pollution reductions. This is used to estimate the
impact of total suspended particulates (TSPs) on infant mortality. We find that a 1-percent reduction in TSPs results in a
0.35 percent decline in the infant mortality rate at the county level, implying that 2500 fewer infants died from 1980–1982
than would have in the absence of the TSPs reductions. Most of these effects are driven by fewer deaths occurring within one
month of birth, suggesting that fetal exposure is a potential pathophysiologic mechanism. The analysis also reveals nonlinear
effects of TSPs pollution and greater sensitivity of black infant mortality at the county level. Importantly, the estimates
are stable across a variety of specifications.
Abstract
Abstract During 2005–2007, a woodstove changeout program was conducted in a Rocky Mountain valley community in an effort to reduce ambient levels of PM2.5. In addition to changes in ambient PM2.5, an opportunity was provided to evaluate the changes in indoor air quality when old stoves were replaced with US Environmental Protection Agency (EPA)-certified woodstoves. PM2.5 samples were measured in 16 homes prior to and following the changeout. For each sampling event, PM2.5 mass was continuously measured throughout the 24-h sampling periods, and organic/elemental carbon (OC/EC) and associated chemical markers of woodsmoke were measured from quartz filters. Results showed that average PM2.5 concentrations and maximum PM2.5 concentrations were reduced by 71% and 76%, respectively (as measured by TSI DustTraks). Levoglucosan was reduced by 45% following the introduction of the new woodstove. However, the concentrations of resin acids, natural chemicals found in the bark of wood, were increased following the introduction of the new woodstove. There were no discernible trends in methoxphenol levels, likely due to the semi-volatile nature of the species that were measured. Although there is some uncertainty in this study regarding the amount of ambient PM infiltration to the indoor environment, these findings demonstrated a large impact on indoor air quality following this intervention.
Previous research on air pollution effects has found associations with chronic adverse health effects even at the relatively low levels of ambient particulates currently measured in most urban areas.
We assessed the impact of declines of total suspended particulates and sulfur dioxide in eastern Germany after reunification on the prevalence of nonallergic respiratory disorders in children. In the 1990s, particle mass (total suspended particulates) and sulfur dioxide declined, whereas number concentrations of nucleation-mode particles (10-30 nm) increased. In three study areas, questionnaires for 7,632 children between 5 and 14 years of age were collected in three phases: 1992-1993, 1995-1996, and 1998-1999.
Adjusted odds ratios (ORs) and 95% confidence intervals (CIs) for a 50-microg/m3 increment in total suspended particulates were 3.0 (CI = 1.7-5.3) for bronchitis, 2.6 (CI = 1.0-6.6) for sinusitis, and 1.9 (CI = 1.2-3.1) for frequent colds. The effect sizes for a 100-microg/m3 increment in sulfur dioxide were similar. The effect estimates for ambient total suspended particulates and sulfur dioxide were stronger among children not exposed to gas stove emissions, visible molds or dampness, cats, or environmental tobacco smoke.
The decreasing prevalence of nonallergic respiratory symptoms, along with improvements in ambient particle mass and sulfur dioxide (but not in nucleation-mode particles), indicates the reversibility of adverse health effects in children. This adds further evidence of a causal association between combustion-related air pollutants and childhood respiratory symptoms.
Particulate air pollution episodes have been associated with increased daily death. However, there is little direct evidence that diminished particulate air pollution concentrations would lead to reductions in death rates. We assessed the effect of air pollution controls--ie, the ban on coal sales--on particulate air pollution and death rates in Dublin.
Concentrations of air pollution and directly-standardised non-trauma, respiratory, and cardiovascular death rates were compared for 72 months before and after the ban of coal sales in Dublin. The effect of the ban on age-standardised death rates was estimated with an interrupted time-series analysis, adjusting for weather, respiratory epidemics, and death rates in the rest of Ireland.
Average black smoke concentrations in Dublin declined by 35.6 mg/m(3) (70%) after the ban on coal sales. Adjusted non-trauma death rates decreased by 5.7% (95% CI 4-7, p<0.0001), respiratory deaths by 15.5% (12-19, p<0.0001), and cardiovascular deaths by 10.3% (8-13, p<0.0001). Respiratory and cardiovascular standardised death rates fell coincident with the ban on coal sales. About 116 fewer respiratory deaths and 243 fewer cardiovascular deaths were seen per year in Dublin after the ban.
Reductions in respiratory and cardiovascular death rates in Dublin suggest that control of particulate air pollution could substantially diminish daily death. The net benefit of the reduced death rate was greater than predicted from results of previous time-series studies.
In July, 1990, a restriction was introduced over one weekend that required all power plants and road vehicles in Hong Kong to use fuel oil with a sulphur content of not more than 0.5% by weight. This intervention led to an immediate fall in ambient sulphur dioxide (SO2). We assessed the effect of this intervention on mortality over the next 5 years.
Changes in trends in deaths were estimated by a Poisson regression model of deaths each month between 1985 and 1995. Changes in seasonal deaths immediately after the intervention were measured by the increase in deaths from warm to cool season. We also estimated the annual proportional change in number of deaths before and after the intervention. We used age-specific death rates to estimate person-years of life gained.
In the first 12 months after introduction of the restriction, a substantial reduction in seasonal deaths was noted, followed by a peak in the cool-season death rate between 13 and 24 months, returning to the expected pattern during years 3-5. Compared with predictions, the intervention led to a significant decline in the average annual trend in deaths from all causes (2.1%; p=0.001), respiratory (3.9%; p=0.0014) and cardiovascular (2.0%; p=0.0214) diseases, but not from other causes. The average gain in life expectancy per year of exposure to the lower pollutant concentration was 20 days (females) to 41 days (males).
Pollution resulting from sulphur-rich fuels has an effect on death rates, especially respiratory and cardiovascular deaths. The outcome of the Hong Kong intervention provides direct evidence that control of this pollution has immediate and long-term health benefits.
We propose a method for diagnosing confounding bias under a model that links a spatially and temporally varying exposure and health outcome. We decompose the association into orthogonal components, corresponding to distinct spatial and temporal scales of variation. If the model fully controls for confounding, the exposure effect estimates should be equal at the different temporal and spatial scales. We show that the overall exposure effect estimate is a weighted average of the scale-specific exposure effect estimates. We use this approach to estimate the association between monthly averages of fine particles (PM2.5) over the preceding 12 months and monthly mortality rates in 113 US counties from 2000 to 2002. We decompose the association between PM2.5 and mortality into 2 components: (1) the association between "national trends" in PM2.5 and mortality; and (2) the association between "local trends," defined as county-specific deviations from national trends. This second component provides evidence as to whether counties having steeper declines in PM2.5 also have steeper declines in mortality relative to their national trends. We find that the exposure effect estimates are different at these 2 spatiotemporal scales, which raises concerns about confounding bias. We believe that the association between trends in PM2.5 and mortality at the national scale is more likely to be confounded than is the association between trends in PM2.5 and mortality at the local scale. If the association at the national scale is set aside, there is little evidence of an association between 12-month exposure to PM2.5 and mortality.
Previous research has established an association between air pollution and adult mortality. However, studies utilizing short-term fluctuations in pollution may detect mortality changes among the already ill or dying, while prospective cohort studies, which utilize geographic differences in long-run pollution levels, may suffer from severe omitted variables bias. This study utilizes the long-run reduction in total suspended particulates (TSPs) pollution induced by the Clean Air Act of 1970, which mandated aggressive regulation of local polluters in heavily polluted counties. We find that regulatory status is associated with large reductions in TSPs pollution but has little association with reductions in either adult or elderly mortality. These findings are interpreted with caution due to several caveats. Copyright 2003 by Kluwer Academic Publishers
Reports over the last decade of association between levels of particles in outdoor air and daily mortality counts have raised concern that air pollution shortens life, even at concentrations within current regulatory limits. Criticisms of these reports have focused on the statistical techniques that are used to estimate the pollution–mortality relationship and the inconsistency in findings between cities. We have developed analytical methods that address these concerns and combine evidence from multiple locations to gain a unified analysis of the data. The paper presents log-linear regression analyses of daily time series data from the largest 20 US cities and introduces hierarchical regression models for combining estimates of the pollution–mortality relationship across cities. We illustrate this method by focusing on mortality effects of PM10 (particulate matter less than 10 m in aerodynamic diameter) and by performing univariate and bivariate analyses with PM10 and ozone (O3) level. In the first stage of the hierarchical model, we estimate the relative mortality rate associated with PM10 for each of the 20 cities by using semiparametric log-linear models. The second stage of the model describes between-city variation in the true relative rates as a function of selected city-specific covariates. We also fit two variations of a spatial model with the goal of exploring the spatial correlation of the pollutant-specific coefficients among cities. Finally, to explore the results of considering the two pollutants jointly, we fit and compare univariate and bivariate models. All posterior distributions from the second stage are estimated by using Markov chain Monte Carlo techniques. In univariate analyses using concurrent day pollution values to predict mortality, we find that an increase of 10 g m-3 in PM10 on average in the USA is associated with a 0.48% increase in mortality (95% interval: 0.05, 0.92). With adjustment for the O3 level the PM10-coefficient is slightly higher. The results are largely insensitive to the specific choice of vague but proper prior distribution. The models and estimation methods are general and can be used for any number of locations and pollutant measurements and have potential applications to other environmental agents.
Trends in air pollution and mortality: an approach to the assessment of unmeasured confounding Measuring the health effects of air pollu-tion: to what extent can we really say that people are dying from bad air?
- H F Dominici
- Zeger
- Sl
H, Dominici F, Zeger SL (2007) Trends in air pollution and mortality: an approach to the assessment of unmeasured confounding. Epidemiology 18(4):416–423. doi:10.1097/ EDE.0b013e31806462e9 Koop G, Tole L (2004) Measuring the health effects of air pollu-tion: to what extent can we really say that people are dying from bad air? J Environ Econ Manage 47(1):30–54
Fine-particulate air pollution and life expectancy in the United States Measuring public health accountability of air quality management
- Ca Pope
- M Ezzati
- Dockery
Pope CA, Ezzati M, Dockery DW (2009) Fine-particulate air pollution and life expectancy in the United States. N Engl J Med 360(4):376–386. doi:10.1056/NEJMsa0805646 Shin H, Burnett R, Stieb D, Jessiman B (2009) Measuring public health accountability of air quality management. Air Qual Atmos Health 2(1):11–20
JAGS version 1.0.3 manual
- M Plummer