The effects of air pollution on work loss and morbidity

The pending revision of U.S. air standards and the analytic requirements of Executive Order 12291 will force regulators to examine closely the data showing possible human health effects from air pollution. A number of studies have investigated the relationship between air pollution and human mortality using an epidemiological approach. This study uses a data set on individuals, the Health Interview Survey, conducted by the National Center for Health Statistics, to examine the relationship between air pollution and various measures of morbidity. Regressions run with the total sample and a subsample of male nonsmokers indicate a statistically significant relationship between particulates and both work loss and restricted activity days. Further analysis considering alternative functional forms also indicates that the ambient level of particulates is still significantly related to the measure of morbidity.     

Air pollution effects on hospital admissions: a statistical analysis of parallel time series

A statistical model for longitudinal count data is used to examine the potential adverse health effects of ambient air pollution. Daily respiratory admissions to 164 acute care hospitals in Ontario are obtained for the period 1983 to 1988. Estimates of ozone levels in the vicinity of each hospital are determined from air pollution monitoring stations maintained by the Ontario Ministry of the Environment. Generalized estimating equation methods are used to make inferences about the regression and overdispersion parameters. The admission data display little evidence of serial correlation and extra Poisson variation. However, admission rates vary considerably among hospitals. This latter source of variation needs to be taken into account in examining the effects of air pollution on respiratory health status.     

Investigating the impact of air pollution on AMI and COPD hospital admissions in the coastal city of Qingdao,China

• The impact of air pollution on AMI/COPD hospital admissions were examined. • Significant connection was found between air pollutants and AMI/COPD in Qingdao. • Nonlinearity exists between air pollution and AMI/COPD hospital admissions. Air pollution has been widely associated with adverse effects on the respiratory and cardiovascular systems. We investigated the relationship between acute myocardial infarction (AMI), chronic obstructive pulmonary disease (COPD) and air pollution exposure in the coastal city of Qingdao, China. Air pollution in this region is characterized by inland and oceanic transportation sources in addition to local emission. We examined the influence of PM_2.5, PM₁₀, NO₂, SO₂, CO and O₃ concentrations on hospital admissions for AMI and COPD from October 1, 2014, to September 30, 2018, in Qingdao using a Poisson generalized additive model (GAM). We found that PM_2.5, PM₁₀, NO₂, SO₂ and CO exhibited a significant short-term (lag 1 day) association with AMI in the single-pollutant model among older adults (>65 years old) and females, especially during the cold season (October to March). In contrast, only NO₂ and SO₂ had clear cumulative lag associations with COPD admission for females and those over 65 years old at lag 01 and lag 03, respectively. In the two-pollutant model, the exposure-response relationship fitted by the two-pollutant model did not change significantly. Our findings indicated that there is an inflection point between the concentration of certain air pollutants and the hospital admissions of AMI and COPD even under the linear assumption, indicative of the benefits of reducing air pollution vary with pollution levels. This study has important implications for the development of policy for air pollution control in Qingdao and the public health benefits of reducing air pollution levels.     

Do new health conditions support mortality–air pollution effects?

Epidemiological research underlying US air quality regulations documents significant associations between measures of fine particles and premature mortality. Recent studies examine potential mechanistic pathways, related to heart and lung functioning, that may contribute to the observed deaths. Our results support these pathophysiological analyses. We examine whether the onset of serious health conditions, consistent with disease pathways, is related to current and long-term exposure to particulate matter and ozone. Associations between air pollution and alternative indicators of health status are also evaluated. The 1996 wave of the Health and Retirement Study is used with a two-step estimator acknowledging limitations in our ability to measure individual exposures. The findings suggest significant current and long-term effects of particulates on new cases of heart attacks and angina, reinforcing the disease pathways identified in epidemiological studies. Long-term air pollution exposure is also a determinant of recently diagnosed chronic lung conditions and reports of shortness of breath.     

A factor analysis study: Air pollution,meteorology, and hospital admissions for respiratory diseases

It is well known that air pollution exerts adverse effects on health and environment. Bal?kesir located in the Marmara region (Turkey) has serious air pollution problems produced by heating in the months of winter. In this study, the effect of exposure to air pollution on hospital admission for respiratory illnesses among children and adults was examined. Epidemiological data from records of hospitals, air pollutants and meteorological data were used. During July 2005–July 2007 period, there was a total of 280,426 hospital admissions for respiratory diseases. In a population-based analysis, 9 children were admitted for asthma, 17 children for acute bronchitis, and 20 children for lower respiratory diseases out of 100 children. There was a significant increase in the hospital admissions for respiratory diseases and air pollutants from October to March. It was concluded that children living in the city suffer from respiratory diseases such as asthma, pneumonia, and lower respiratory diseases. Three factors that account for approximately 90% of total variance of hospital admissions, air pollution, and meteorology were identified by means of principal component factor analysis.     

Air pollution and morbidity revisited: A specification test

Since little is known about the correct specification of the relationship of air pollution and morbidity, it is difficult to draw any solid inferences from any set of regressions based on one single data set. It is important, therefore, to replicate whenever possible the regression results for other similar data sets. In this light, this paper replicates earlier analysis using the 1976 Health Interview Survey to relate morbidity—measured as either days of work loss, restricted activity or respiratory-related restricted activity—to particulate matter. The analysis, which uses 6 years of the annual Health Interview Survey, also uses data on fine particulates, a more relevant measure of exposure to particulate matter than total suspended particulates, which is traditionally used.     

The effect of pollution on crime: Evidence from data on particulate matter and ozone

We estimate the effect of short-term air pollution exposure (PM_2.5 and ozone) on several categories of crime, with a particular emphasis on aggressive behavior. To identify this relationship, we combine detailed daily data on crime, air pollution, and weather for an eight-year period across the United States. Our primary identification strategy employs extremely high dimensional fixed effects and we perform a series of robustness checks to address confounding variation between temperature and air pollution. We find a robust positive effect of increased air pollution on violent crimes, and specifically assaults, but no relationship between increases in air pollution and property crimes. The effects are present in and out of the home, at levels well below Ambient Air Pollution Standards, and PM_2.5 effects are strongest at lower temperatures. The results suggest that a 10% reduction in daily PM_2.5 and ozone could save $1.4 billion in crime costs per year, a previously overlooked cost associated with pollution.     

Health externalities of India's expansion of coal plants: Evidence from a national panel of 40,000 households

Coal power generation is expanding rapidly in India and other developing countries. In addition to consequences for climate change, present-day health externalities may also substantially increase the social cost of coal. Health consequences of air pollution have proven important in studies of developed countries, but, despite clear importance, similarly well-identified estimates are less available for developing countries, and no estimates exist for the important case of coal in India. We exploit panel data on Indian households, matched to local changes in exposure to coal plants. Increased exposure to coal plants is associated with worse respiratory health. Consistent with a causal mechanism, the effect is specific: no effect is seen on diarrhea or fever, and no effect on respiratory health is seen of new non-coal plants. Our result is not due to endogenous avoidance behavior, or to differential trends in determinants of respiratory health, either before the period studied or simultaneously.     

The effect of outdoor air pollutants and greenness on allergic rhinitis incidence rates: a cross-sectional study in Seoul,Korea

Air pollution poses a serious threat to human health in Asia. This study analyzes the association of air pollutants and greenness with incidence rates of allergic rhinitis in Seoul at the administrative district level to gain insight into district-level urban policies to improve public health. A spatial regression model is constructed to investigate the correlation between allergic rhinitis incidence rates and five air pollutants measured at 128 air pollution monitoring stations around Seoul: sulfur dioxide (SO₂), particulate matter less than 10 μm (PM₁₀), ozone (O₃), nitrogen dioxide (NO₂), and carbon monoxide (CO). The allergic rhinitis incidence data are derived from the National Health Insurance Service’s database that includes the number of allergic rhinitis-related clinic visits by the patients over 20 years of age and living in Seoul. A kriging geostatistical interpolation was used to estimate average air pollution level of 423 administrative districts. To assess pollen concentrations that can affect allergic rhinitis, the average normalized difference vegetation index (NDVI) is measured based on the urban greenness. The model, controlling for built environment and socio-economic attributes, identifies the possibility of a weak association between allergic rhinitis incidence rates and carbon monoxide levels. The NDVI value is negatively correlated with allergic rhinitis incidence rates, implying a complicated aspect in relation to the effect of urban greenness.     

An initial assessment of spatial relationships between respiratory cases,soil metal content,air quality and deprivation indicators in Glasgow,Scotland, UK: relevance to the environmental justice agenda

There is growing interest in links between poor health and socio-environmental inequalities (e.g. inferior housing, crime and industrial emissions) under the environmental justice agenda. The current project assessed associations between soil metal content, air pollution (NO₂/PM₁₀) and deprivation and health (respiratory case incidence) across Glasgow. This is the first time that both chemical land quality and air pollution have been assessed citywide in the context of deprivation and health for a major UK conurbation. Based on the dataset ‘averages’ for intermediate geography areas, generalised linear modelling of respiratory cases showed significant associations with overall soil metal concentration (p = 0.0367) and with deprivation (p < 0.0448). Of the individual soil metals, only nickel showed a significant relationship with respiratory cases (p = 0.0056). Whilst these associations could simply represent concordant lower soil metal concentrations and fewer respiratory cases in the rural versus the urban environment, they are interesting given (1) possible contributions from soil to air particulate loading and (2) known associations between airborne metals like nickel and health. This study also demonstrated a statistically significant correlation (?0.213; p < 0.05) between soil metal concentration and deprivation across Glasgow. This highlights the fact that despite numerous regeneration programmes, the legacy of environmental pollution remains in post-industrial areas of Glasgow many decades after heavy industry has declined. Further epidemiological investigations would be required to determine whether there are any causal links between soil quality and population health/well-being. However, the results of this study suggest that poor soil quality warrants greater consideration in future health and socio-environmental inequality assessments.     

Air pollution and children's respiratory health: A cohort analysis

This paper uses a large database of multiple birth cohorts to study relationships between air pollution exposure and non-infant children's respiratory health outcomes. We observe several years of early-life health treatments for hundreds of thousands of English children. Three distinct research designs account for potential socioeconomic, behavioral, seasonal, and economic confounders. We find that marginal increases in carbon monoxide and ground-level ozone are associated with statistically significant increases in children's contemporaneous respiratory treatments. We also find that carbon monoxide exposure over the previous year has an effect on children's health that goes above and beyond contemporaneous exposure alone.     

Does subway expansion improve air quality?

Major cities in China and many other fast-growing economies are expanding their subway systems in order to address worsening air pollution and traffic congestion. This paper quantifies the impact of subway expansion on air quality by leveraging fine-scale air quality data and the rapid build-out of 14 new subway lines and 252 stations in Beijing from 2008 to 2016. Our main empirical framework examines how the density of the subway network affects air quality across different locations in the city during this period. To address the potential endogenous location of subway stations, we construct an instrument based on historical subway planning, long before air pollution and traffic congestion were of concern. Our analysis shows that an increase in subway density by one standard deviation improves air quality by two percent and the result is robust to a variety of alternative specifications including the distance-based difference-in-differences method. The total discounted health benefit during a 20-year period from reduced mortality and morbidity as a result of 14 new subway lines amounts to $1.0–3.1 billion, or only 1.4–4.4 percent of the total construction and operating cost.     

Imputing Unmeasured Explanatory Variables in Environmental Epidemiology With Application to Health Impact Analysis of Air Pollution

This paper presents the results of a reconsideration of earlier work that finds an association between daily hospital admissions for respiratory distress and daily concentrations of sulphate (lag 1) as well as daily maximum concentrations of ozone (lags 1 and 3). These associations are found even after clustering the data by hospital of admission and accounting for the effects of temperature. We use an adaptation of their generalized estimating equation technique for clustered data, that daily data being for southern Ontario summers from 1983 to 1988. Like them, we adjust for daily maximum temperatures. However, unlike the earlier work returned to ours includes daily average humidity as a potential explanatory variable in our model. Our analysis also differs from theirs in that we cluster the data by census subdivision to reduce the risk of confounding pollutant levels with population size within regions. Moreover, we log-transform the explanatory variables and then high-pass filter the resulting data. We also deviate from the earlier analysis by taking account of measurement error incurred in using surrogate measures of the explanatory variables. To do so we use new methodology designed for our study but of potential value in other applications. That methodology requires a spatial predictive distribution for the unmeasured explanatory variables. Each day about 700 missing measurements for each of these variables can then be imputed over the geographical domain of the study. With these imputations we get a measure of imputation error through the covariance of the predictive distribution. Along with the predictive distribution we require an impact model to link-up with the predictive distribution. We describe that model and show how it uses the imputed measurements of the missing values of the explanatory variables. We also show how through that model, uncertainty about these values is reflected in our analysis and in commensurate uncertainties in the inferences made. Apart from its substantive objectives, our analysis serves to test the new methods with the earlier results serving as a foil. The reassuring qualitative agreement between our findings and the earlier results seems encouraging.     

A building-based data capture and data mining technique for air quality assessment

Recently, a building-based air quality model system which can predict air quality in front of individual buildings along both sides of a road has been developed. Using the Macau Peninsula as a case study, this paper shows the advantages of building-based model system in data capture and data mining. Compared with the traditional grid-based model systems with input/output spatial resolutions of 1–2 km, the building-based approach can extract the street configuration and traffic data building by building and therefore, can capture the complex spatial variation of traffic emission, urban geometry, and air pollution. The non-homogeneous distribution of air pollution in the Macau Peninsula was modeled in a high-spatial resolution of 319 receptors·km^-2. The spatial relationship among air quality, traffic flow, and urban geometry in the historic urban area is investigated. The study shows that the building-based approach may open an innovative methodology in data mining of urban spatial data for environmental assessment. The results are particularly useful to urban planners when they need to consider the influences of urban form on street environment.     

SARS-CoV-2 variants and environmental effects of lockdowns,masks and vaccination: a review

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is continuously evolving and four variants of concern have been identified so far, including Alpha, Beta, Gamma and Delta variants. Here we review the indirect effect of preventive measures such as the implementation of lockdowns, mandatory face masks, and vaccination programs, to control the spread of the different variants of this infectious virus on the environment. We found that all these measures have a considerable environmental impact, notably on waste generation and air pollution. Waste generation is increased due to the implementation of all these preventive measures. While lockdowns decrease air pollution, unsustainable management of face mask waste and temperature-controlled supply chains of vaccination potentially increases air pollution.

     

Willingness to pay for clean air in China

We use a residential sorting model incorporating migration disutility to recover the implicit value of clean air in China. The model is estimated using China Population Census Data along with PM2.5 satellite data. Our study provides new evidence on the willingness to pay for air quality improvements in developing countries and is the first application of an equilibrium sorting model to the valuation of non-market amenities in China. We employ two instrumental variables based on coal-fired electricity generation and wind direction to address the endogeneity of local air pollution. Results suggest important differences between the residential sorting model and a conventional hedonic model, highlighting the role of moving costs and the discreteness of the choice set. Our sorting results indicate that the economic value of air quality improvement associated with a one-unit decline in PM2.5 concentration is up to $8.83 billion for all Chinese households in 2005.     

Health impacts of air pollution in China

•Impacts of air pollution on various body systems health in China were highlighted. •China’s actions to control air pollution and their effects were briefly introduced. •Challenges and perspectives of the health effects of air pollution are provided. The health effects of air pollution have attracted considerable attention in China. In this review, the status of air pollution in China is briefly presented. The impacts of air pollution on the health of the respiratory system, the circulatory system, the nervous system, the digestive system, the urinary system, pregnancy and life expectancy are highlighted. Additionally, China’s actions to control air pollution and their effects are briefly introduced. Finally, the challenges and perspectives of the health effects of air pollution are provided. We believe that this review will provide a promising perspective on the health impacts of air pollution in China, and further elicit more attention from governments and researchers worldwide.     

Air pollution and mortality rates: A note on Lave and Seskin's pooling of cross-section and time-series data

In “Air Pollution and Human Health” (Johns Hopkins University Press, Baltimore, 1977) Lester Lave and Eugene Seskin report the results of regressions which suggest a strong association between air pollution and mortality rates. This note questions assumptions made by Lave and Seskin which underlie their -estimation of a single-equation model using pooled cross-section and time-series data. If, in fact, these assumptions cannot be made, the association between air pollution and mortality rates appears considerably weakened, but it still appears to be significant.     

A flexible spatio-temporal model for air pollution with spatial and spatio-temporal covariates

The development of models that provide accurate spatio-temporal predictions of ambient air pollution at small spatial scales is of great importance for the assessment of potential health effects of air pollution. Here we present a spatio-temporal framework that predicts ambient air pollution by combining data from several different monitoring networks and deterministic air pollution model(s) with geographic information system covariates. The model presented in this paper has been implemented in an R package, SpatioTemporal, available on CRAN. The model is used by the EPA funded Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air) to produce estimates of ambient air pollution; MESA Air uses the estimates to investigate the relationship between chronic exposure to air pollution and cardiovascular disease. In this paper we use the model to predict long-term average concentrations of \(\text {NO}_{x}\) in the Los Angeles area during a 10 year period. Predictions are based on measurements from the EPA Air Quality System, MESA Air specific monitoring, and output from a source dispersion model for traffic related air pollution (Caline3QHCR). Accuracy in predicting long-term average concentrations is evaluated using an elaborate cross-validation setup that accounts for a sparse spatio-temporal sampling pattern in the data, and adjusts for temporal effects. The predictive ability of the model is good with cross-validated \(R^2\) of approximately \(0.7\) at subject sites. Replacing four geographic covariate indicators of traffic density with the Caline3QHCR dispersion model output resulted in very similar prediction accuracy from a more parsimonious and more interpretable model. Adding traffic-related geographic covariates to the model that included Caline3QHCR did not further improve the prediction accuracy.