Economic Valuation of Health Impact of PM10 Pollution in Beijing from 2001 to 2006

In light of the practical need for research to inform policy in Beijing,this study evaluates the economic cost of the impact of PM10 pollution in Beijing from 2001 to 2006,taking health as the main impact,and mortality as the main outcome.Based on the literature review,this study adopts relatively conservative parameters as the basis for calculating the health impacts.It concludes that nearly 30% of mortality among registered residents above age 30 in Beijing can be attributed to PM10 pollution,and that the economic cost equals 0.8%-1.2% of the city's GDP over the same period.This is lower than the results of previous studies,but still high enough to warrant a commitment to solve the city's air pollution problem.     

High resolution exposure modelling of heat and air pollution and the impact on mortality

BackgroundElevated temperature and air pollution have been associated with increased mortality. Exposure to heat and air pollution, as well as the density of vulnerable groups varies within cities. The objective was to investigate the extent of neighbourhood differences in mortality risk due to heat and air pollution in a city with a temperate maritime climate.MethodsA case-crossover design was used to study associations between heat, air pollution and mortality. Different thermal indicators and air pollutants (PM₁₀, NO₂, O₃) were reconstructed at high spatial resolution to improve exposure classification. Daily exposures were linked to individual mortality cases over a 15 year period.ResultsSignificant interaction between maximum air temperature (Ta_max) and PM₁₀ was observed. During “summer smog” days (Ta_max > 25 °C and PM₁₀ > 50 μg/m³), the mortality risk at lag 2 was 7% higher compared to the reference (Ta_max 15 °C and PM₁₀ 15 μg/m³). Persons above age 85 living alone were at highest risk.ConclusionWe found significant synergistic effects of high temperatures and air pollution on mortality. Single living elderly were the most vulnerable group. Due to spatial differences in temperature and air pollution, mortality risks varied substantially between neighbourhoods, with a difference up to 7%.     

Health effects from Sahara dust episodes in Europe: Literature review and research gaps

The adverse consequences of particulate matter (PM) on human health have been well documented. Recently, special attention has been given to mineral dust particles, which may be a serious health threat. The main global source of atmospheric mineral dust is the Sahara desert, which produces about half of the annual mineral dust. Sahara dust transport can lead to PM levels that substantially exceed the established limit values. A review was undertaken using the ISI web of knowledge database with the objective to identify all studies presenting results on the potential health impact from Sahara dust particles. The review of the literature shows that the association of fine particles, PM_2.5, with total or cause‐specific daily mortality is not significant during Saharan dust intrusions. However, regarding coarser fractions PM₁₀ and PM_2.5–10 an explicit answer cannot be given. Some of the published studies state that they increase mortality during Sahara dust days while other studies find no association between mortality and PM₁₀ or PM_2.5–10. The main conclusion of this review is that health impact of Saharan dust outbreaks needs to be further explored. Considering the diverse outcomes for PM₁₀ and PM_2.5–10, future studies should focus on the chemical characterization and potential toxicity of coarse particles transported from Sahara desert mixed or not with anthropogenic pollutants. The results of this review may be considered to establish the objectives and strategies of a new European directive on ambient air quality. An implication for public policy in Europe is that to protect public health, anthropogenic sources of particulate pollution need to be more rigorously controlled in areas highly impacted by the Sahara dust.     

WATCH

Abstract

The characteristics of fine particulate pollution (PM₁₀ and PM_2.5) were measured at urban and suburban sites in Jinan during the 2008–2009 heating and non-heating seasons. The results showed that PM₁₀ and PM_2.5 pollution was quite serious, and PM mass concentration was higher during the heating season than the non-heating season. PM was the highest in the chemical factory and lowest in the development zone. The mass concentrations of PM₁₀ and PM_2.5 were linearly related, and the mass concentration ratio of PM_2.5/PM₁₀ was up to 0.59 in urban areas. PM pollution in Jinan was related to local meteorological factors: PM_2.5 mass concentration and humidity were positively correlated, and PM_2.5 mass concentration was negatively correlated with both click on the temperature and wind speed, although wind speed varied more.     

Association between long-term exposure to air pollution and mortality in France: A 25-year follow-up study

IntroductionLong-term exposure to air pollution (AP) has been shown to have an impact on mortality in numerous countries, but since 2005 no data exists for France.ObjectivesWe analyzed the association between long-term exposure to air pollution and mortality at the individual level in a large French cohort followed from 1989 to 2013.MethodsThe study sample consisted of 20,327 adults working at the French national electricity and gas company EDF-GDF. Annual exposure to PM₁₀, PM_10–2.5, PM_2.5, NO₂, O₃, SO₂, and benzene was assessed for the place of residence of participants using a chemistry-transport model and taking residential history into account. Hazard ratios were estimated using a Cox proportional-hazards regression model, adjusted for selected individual and contextual risk factors. Hazard ratios were computed for an interquartile range (IQR) increase in air pollutant concentrations.ResultsThe cohort recorded 1967 non-accidental deaths. Long-term exposures to baseline PM_2.5, PM_10-25, NO₂ and benzene were associated with an increase in non-accidental mortality (Hazard Ratio, HR = 1.09; 95% CI: 0.99, 1.20 per 5.9 μg/m³, PM_10-25; HR = 1.09;95% CI: 1.04, 1.15 per 2.2 μg/m³, NO₂: HR = 1.14; 95% CI: 0.99, 1.31 per 19.3 μg/m³ and benzene: HR = 1.10; 95% CI: 1.00, 1.22 per 1.7 μg/m³).The strongest association was found for PM₁₀: HR = 1.14; 95% CI: 1.05, 1.25 per 7.8 μg/m³. PM₁₀, PM_10-25 and SO₂ were associated with non-accidental mortality when using time varying exposure. No significant associations were observed between air pollution and cardiovascular and respiratory mortality.ConclusionLong-term exposure to fine particles, nitrogen dioxide, sulfur dioxide and benzene is associated with an increased risk of non-accidental mortality in France. Our results strengthen existing evidence that outdoor air pollution is a significant environmental risk factor for mortality. Due to the limited sample size and the nature of our study (occupational), further investigations are needed in France with a larger representative population sample.     

Long-term trend and spatial pattern of PM2.5 induced premature mortality in China

With rapid economic growth, China has witnessed increasingly frequent and severe haze and smog episodes over the past decade, posing serious health impacts to the Chinese population, especially those in densely populated city clusters. Quantification of the spatial and temporal variation of health impacts attributable to ambient fine particulate matter (PM_2.5) has important implications for China's policies on air pollution control. In this study, we evaluated the spatial distribution of premature deaths in China between 2000 and 2010 attributable to ambient PM_2.5 in accord with the Global Burden of Disease based on a high resolution population density map of China, satellite retrieved PM_2.5 concentrations, and provincial health data. Our results suggest that China's anthropogenic ambient PM_2.5 led to 1,255,400 premature deaths in 2010, 42% higher than the level in 2000. Besides increased PM_2.5 concentration, rapid urbanization has attracted large population migration into the more developed eastern coastal urban areas, intensifying the overall health impact. In addition, our analysis implies that health burdens were exacerbated in some developing inner provinces with high population density (e.g. Henan, Anhui, Sichuan) because of the relocation of more polluting and resource-intensive industries into these regions. In order to avoid such national level environmental inequities, China's regulations on PM_2.5 should not be loosened in inner provinces. Furthermore policies should create incentive mechanisms that can promote transfer of advanced production and emissions control technologies from the coastal regions to the interior regions.     

Effect of the shape of the exposure-response function on estimated hospital costs in a study on non-elective pneumonia hospitalizations related to particulate matter

ObjectiveWe used log-linear and log-log exposure-response (E-R) functions to model the association between PM_2.5 exposure and non-elective hospitalizations for pneumonia, and estimated the attributable hospital costs by using the effect estimates obtained from both functions.MethodsWe used hospital discharge data on 3519 non-elective pneumonia admissions from UZ Brussels between 2007 and 2012 and we combined a case-crossover design with distributed lag models. The annual averted pneumonia hospitalization costs for a reduction in PM_2.5 exposure from the mean (21.4 μg/m³) to the WHO guideline for annual mean PM_2.5 (10 μg/m³) were estimated and extrapolated for Belgium.ResultsNon-elective hospitalizations for pneumonia were significantly associated with PM_2.5 exposure in both models. Using a log-linear E-R function, the estimated risk reduction for pneumonia hospitalization associated with a decrease in mean PM_2.5 exposure to 10 μg/m³ was 4.9%. The corresponding estimate for the log-log model was 10.7%. These estimates translate to an annual pneumonia hospital cost saving in Belgium of €15.5 million and almost €34 million for the log-linear and log-log E-R function, respectively.DiscussionAlthough further research is required to assess the shape of the association between PM_2.5 exposure and pneumonia hospitalizations, we demonstrated that estimates for health effects and associated costs heavily depend on the assumed E-R function. These results are important for policy making, as supra-linear E-R associations imply that significant health benefits may still be obtained from additional pollution control measures in areas where PM levels have already been reduced.     

Associations between ultrafine and fine particles and mortality in five central European cities — Results from the UFIREG study

BackgroundEvidence on health effects of ultrafine particles (UFP) is still limited as they are usually not monitored routinely. The few epidemiological studies on UFP and (cause-specific) mortality so far have reported inconsistent results.ObjectivesThe main objective of the UFIREG project was to investigate the short-term associations between UFP and fine particulate matter (PM) < 2.5 μm (PM_2.5) and daily (cause-specific) mortality in five European Cities. We also examined the effects of PM < 10 μm (PM₁₀) and coarse particles (PM_2.5–10).MethodsUFP (20–100 nm), PM and meteorological data were measured in Dresden and Augsburg (Germany), Prague (Czech Republic), Ljubljana (Slovenia) and Chernivtsi (Ukraine). Daily counts of natural and cardio-respiratory mortality were collected for all five cities. Depending on data availability, the following study periods were chosen: Augsburg and Dresden 2011–2012, Ljubljana and Prague 2012–2013, Chernivtsi 2013–March 2014. The associations between air pollutants and health outcomes were assessed using confounder-adjusted Poisson regression models examining single (lag 0–lag 5) and cumulative lags (lag 0–1, lag 2–5, and lag 0–5). City-specific estimates were pooled using meta-analyses methods.ResultsResults indicated a delayed and prolonged association between UFP and respiratory mortality (9.9% [95%-confidence interval: − 6.3%; 28.8%] increase in association with a 6-day average increase of 2750 particles/cm³ (average interquartile range across all cities)). Cardiovascular mortality increased by 3.0% [− 2.7%; 9.1%] and 4.1% [0.4%; 8.0%] in association with a 12.4 μg/m³ and 4.7 μg/m³ increase in the PM_2.5- and PM_2.5–10-averages of lag 2–5.ConclusionsWe observed positive but not statistically significant associations between prolonged exposures to UFP and respiratory mortality, which were independent of particle mass exposures. Further multi-centre studies are needed investigating several years to produce more precise estimates on health effects of UFP.     

Levels and major sources of PM2.5 and PM10 in Bangkok Metropolitan Region

This research was the first long-term attempt to concurrently measure and identify major sources of both PM₁₀ and PM_2.5 in Bangkok Metropolitan Region (BMR). Ambient PM₁₀ and PM_2.5 were evaluated at four monitoring stations and analyzed for elemental compositions, water-soluble ions, and total carbon during February 2002–January 2003. Fifteen chemical elements, four water-soluble ions, and total carbon were analyzed to assist major source identification by a receptor model approach, known as chemical mass balance. PM₁₀ and PM_2.5 were significantly different (p < 0.05) at all sites and 24 h averages were high at traffic location while two separated residential sites were similar. Seasonal difference of PM₁₀ and PM_2.5 concentrations was distinct between dry and wet seasons. Major source of PM₁₀ at the traffic site indicated that automobile emissions and biomass burning-related sources contributed approximately 33% each. Automobiles contributed approximately 39 and 22% of PM₁₀ mass at two residential sites while biomass burning contributed about 36 and 28%. PM₁₀ from re-suspended soil and cooking sources accounted for 10 to 15% at a residential site. Major sources of PM_2.5 at traffic site were automobile and biomass burning, contributing approximately 32 and 26%, respectively. Biomass burning was the major source of PM_2.5 mass concentrations at residential sites. Meat cooking also accounted for 31% of PM_2.5 mass at a low impact site. Automobile, biomass burning, and road dust were less significant, contributed 10, 6, and 5%, respectively. Major sources identification at some location had difficulty to achieve performance criteria due to limited source profiles. Improved in characterize other sources profiles will help local authority to better air quality.     

Communicating air pollution-related health risks to the public: An application of the Air Quality Health Index in Shanghai,China

The Air Quality Health Index (AQHI) was originally developed in Canada. However, little is known about its validity in communicating morbidity risks. We aimed to establish the AQHI in Shanghai, China, and to compare the associations of AQHI and existing Air Pollution Index (API) with daily mortality and morbidity. We constructed the AQHI as the sum of excess total mortality associated with individual air pollutants, and then adjusted it to an arbitrary scale (0–10), according to a time-series analysis of air pollution and mortality in Shanghai from 2001 to 2008. We examined the associations of AQHI with daily mortality and morbidity, and compared these associations with API from 2005 to 2008. The coefficients of short-term associations of total mortality with particulate matter with an aerodynamic diameter less than 10 μm (PM₁₀), PM_2.5 and nitrogen dioxide (NO₂) were used in the establishment of AQHI. During 2005–2008, the AQHI showed linear non-threshold positive associations with daily mortality and morbidity. A unit increase of the PM₁₀-AQHI was associated with a 0.90% [95% (confidence interval, CI), 0.43 to 1.37], 1.04% (95%CI, 0.04 to 2.04), 1.62% (95%CI, 0.39 to 2.85) and 0.51% (95%CI, 0.09 to 0.93) increase of current-day total mortality, hospital admissions, outpatient visits and emergency room visits, respectively. The PM_2.5-AQHI showed quite similar effect estimates with the PM₁₀-AQHI. In contrast, the associations for API were much weaker and generally statistically insignificant. The AQHI, compared with the existing API, provided a more effective tool to communicate the air pollution-related health risks to the public.     

Acute health impacts of airborne particles estimated from satellite remote sensing

Satellite-based remote sensing provides a unique opportunity to monitor air quality from space at global, continental, national and regional scales. Most current research focused on developing empirical models using ground measurements of the ambient particulate. However, the application of satellite-based exposure assessment in environmental health is still limited, especially for acute effects, because the development of satellite PM_2.5 model depends on the availability of ground measurements. We tested the hypothesis that MODIS AOD (aerosol optical depth) exposure estimates, obtained from NASA satellites, are directly associated with daily health outcomes. Three independent healthcare databases were used: unscheduled outpatient visits, hospital admissions, and mortality collected in Beijing metropolitan area, China during 2006. We use generalized linear models to compare the short-term effects of air pollution assessed by ground monitoring (PM₁₀) with adjustment of absolute humidity (AH) and AH-calibrated AOD. Across all databases we found that both AH-calibrated AOD and PM₁₀ (adjusted by AH) were consistently associated with elevated daily events on the current day and/or lag days for cardiovascular diseases, ischemic heart diseases, and COPD. The relative risks estimated by AH-calibrated AOD and PM₁₀ (adjusted by AH) were similar. Additionally, compared to ground PM₁₀, we found that AH-calibrated AOD had narrower confidence intervals for all models and was more robust in estimating the current day and lag day effects. Our preliminary findings suggested that, with proper adjustment of meteorological factors, satellite AOD can be used directly to estimate the acute health impacts of ambient particles without prior calibrating to the sparse ground monitoring networks.     

Status and characteristics of ambient PM2.5 pollution in global megacities

Ambient PM_2.5 pollution is a substantial threat to public health in global megacities. This paper reviews the PM_2.5 pollution of 45 global megacities in 2013, based on mass concentration from official monitoring networks and composition data reported in the literature. The results showed that the five most polluted megacities were Delhi, Cairo, Xi'an, Tianjin and Chengdu, all of which had an annual average concentration of PM_2.5 greater than 89 μg/m³. The five cleanest megacities were Miami, Toronto, New York, Madrid and Philadelphia, the annual averages of which were less than 10 μg/m³. Spatial distribution indicated that the highly polluted megacities are concentrated in east-central China and the Indo-Gangetic Plain. Organic matter and SNA (sum of sulfate, nitrate and ammonium) contributed 30% and 36%, respectively, of the average PM_2.5 mass for all megacities. Notable seasonal variation of PM_2.5 polluted days was observed, especially for the polluted megacities of China and India, resulting in frequent heavy pollution episodes occurring during more polluted seasons such as winter. Marked differences in PM_2.5 pollution between developing and developed megacities require more effort on local emissions reduction as well as global cooperation to address the PM_2.5 pollution of those megacities mainly in Asia.     

Projecting future air pollution-related mortality under a changing climate: progress,uncertainties and research needs

BackgroundClimate change may affect mortality associated with air pollutants, especially for fine particulate matter (PM_2.5) and ozone (O₃). Projection studies of such kind involve complicated modelling approaches with uncertainties.ObjectivesWe conducted a systematic review of researches and methods for projecting future PM_2.5-/O₃-related mortality to identify the uncertainties and optimal approaches for handling uncertainty.MethodsA literature search was conducted in October 2013, using the electronic databases: PubMed, Scopus, ScienceDirect, ProQuest, and Web of Science. The search was limited to peer-reviewed journal articles published in English from January 1980 to September 2013.DiscussionFifteen studies fulfilled the inclusion criteria. Most studies reported that an increase of climate change-induced PM_2.5 and O₃ may result in an increase in mortality. However, little research has been conducted in developing countries with high emissions and dense populations. Additionally, health effects induced by PM_2.5 may dominate compared to those caused by O₃, but projection studies of PM_2.5-related mortality are fewer than those of O₃-related mortality.There is a considerable variation in approaches of scenario-based projection researches, which makes it difficult to compare results. Multiple scenarios, models and downscaling methods have been used to reduce uncertainties. However, few studies have discussed what the main source of uncertainties is and which uncertainty could be most effectively reduced.ConclusionsProjecting air pollution-related mortality requires a systematic consideration of assumptions and uncertainties, which will significantly aid policymakers in efforts to manage potential impacts of PM_2.5 and O₃ on mortality in the context of climate change.     

The relationship between population and the environment and its impact on sustainable development in Egypt using a multi-equation model

The relationship between population and the environment is a significant issue due to its impact on chances for achieving sustainable development, especially in developing countries. Previous studies on this relationship have primarily focused on the impact of population growth on the environment, while the impact of the environment on population has received less attention, where most of these studies have used single-equation models (SEM) in their analysis. In order to capture the interrelationship between population growth and the environment, and both its direct and indirect effects on the potential for achieving sustainable development, SEM may not be appropriate. This paper takes a step forward in providing such empirical evidence, by developing a multi-equation model based on the recursive equation system in order to empirically examine the relationship between population growth and the environment in terms of air pollution represented by increased CO₂ emissions, health level represented by the mortality and morbidity due to air pollution, and labour productivity represented by GDP per hour worked, and using a time series data set for Egypt during the period of 1950–2010. Quantitatively, the current study finds that (1) In Egypt, a 1% increase in population raises the CO₂ emissions by 2.4%. (2) An increase in CO₂ emissions by 1% is associated with an increase in deaths due to outdoor air pollution (respiratory and cardiovascular diseases) by 2.5%. (3) Poor health due to air pollution leads to a decrease in labour productivity by 1.58%. (4) The impact of population growth on chances for sustainable development depends on how much the rise in air pollution decreases labour productivity through raising the rate of morbidity. (5) Even when rapid population growth rate plays a minor role in creating a specific problem, such as its indirect negative impact on labour productivity and thus economic growth, population management policies may still constitute a viable measure for dealing with that problem, especially with respect to policy intervention cost. The study argues that population growth in Egypt negatively affects the state’s ability to achieve sustainable development via its negative impact on the environment. Environmental degradation in turn leads to adverse effects on population, particularly with regard to public health. These negative effects on health lead to lower labour productivity, and thus hinder the state’s ability to sustain development.     

CO2 emission driving forces and corresponding mitigation strategies under low-carbon economy mode: evidence from China’s Beijing–Tianjin–Hebei region

On account of the background of China’s “new normal” characterized by slower economic growth, this paper analyses the low-carbon economy status quo in the Beijing–Tianjin–Hebei region and empirically investigates the relationship between carbon dioxide (CO₂) emissions and its various factors for China’s Beijing–Tianjin–Hebei region using panel data econometric technique. We find evidence of existence of Environmental Kuznets Curve. Results also show that economic scale, industrial structure, and urbanization rate are crucial factors to promote CO₂ emissions. However, technological progress, especially the domestic independent research and development, plays a key role in CO₂ emissions abatement. Next, we further analyze the correlation between each subregion and various factors according to Grey Relation Analysis. Thereby, our findings provide important implications for policymakers in air pollution control and CO₂ emissions reduction for this region.     

Cost-Effective Control of Ground-Level Ozone Pollution in and around Beijing

Abstract

Ground level ozone pollution has become a significant air pollution problem in Beijing. Because of the complex way in which ozone is formed, it is difficult for policy makers to identify optimal control options on a cost-effective basis. This paper identifies and assesses a range of options for addressing this problem. We apply the Ambient Least Cost Model and compare the economic costs of control options, then recommend the most effective sequence to realize pollution control at the lowest cost. The study finds that installing of Stage II gasoline vapor recovery system at Beijing’s 1446 gasoline stations would be the most cost-effective option. Overall, options to reduce ozone pollution by cutting vehicular emissions are much more cost-effective than options to “clean up” coal-fired power plants.     

Ambient air pollution epidemiology systematic review and meta-analysis: A review of reporting and methods practice

BackgroundSystematic review and meta-analysis (SRMA) are increasingly employed in environmental health (EH) epidemiology and, provided methods and reporting are sound, contribute to translating science evidence to policy. Ambient air pollution (AAP) is both among the leading environmental causes of mortality and morbidity worldwide, and of growing policy relevance due to health co-benefits associated with greenhouse gas emissions reductions.ObjectivesWe reviewed the published AAP SRMA literature (2009 to mid-2015), and evaluated the consistency of methods, reporting and evidence evaluation using a 22-point questionnaire developed from available best-practice consensus guidelines and emerging recommendations for EH. Our goal was to contribute to enhancing the utility of AAP SRMAs to EH policy.Results and discussionWe identified 43 studies that used both SR and MA techniques to examine associations between the AAPs PM_2.5, PM_10, NO₂, SO₂, CO and O₃, and various health outcomes. On average AAP SRMAs partially or thoroughly addressed 16 of 22 questions (range 10–21), and thoroughly addressed 13 of 22 (range 5–19). We found evidence of an improving trend over the period. However, we observed some weaknesses, particularly infrequent formal reviews of underlying study quality and risk-of-bias that correlated with lower frequency of thorough evaluation for key study quality parameters. Several other areas for enhanced reporting are highlighted.ConclusionsThe AAP SRMA literature, in particular more recent studies, indicate broad concordance with current and emerging best practice guidance. Development of an EH-specific SRMA consensus statement including a risk-of-bias evaluation tool, would be a contribution to enhanced reliability and robustness as well as policy utility.     

Future climate and adverse health effects caused by fine particulate matter air pollution: case study for Poland

Ground level air pollution, especially fine particulate matter (PM_2.5), has been associated with a number of adverse health effects. The dispersion of PM_2.5 through the atmosphere depends on several mutually connected anthropogenic, geophysical and meteorological parameters, all of which are affected by climate change. This study examines how projected climate change would affect population exposure to PM_2.5 air pollution in Poland. Population exposure to PM_2.5 in Poland was estimated for three decades: the 1990s, 2040s and 2090s. Future climate conditions were projected by Regional Climate Model RegCM (Beta), forced by the general atmospheric circulation model ECHAM5. The dispersion of PM_2.5 was simulated with chemical transport model CAMx version 4.40. Population exposure estimates of PM_2.5 were 18.3, 17.2 and 17.1 μg/m³ for the 1990s, 2040s and 2090s, respectively. PM_2.5 air pollution was estimated to cause approximately 39,800 premature deaths in the population of Poland in the year 2000. Our results indicate that in Poland, climate change may reduce the levels of exposure to anthropogenic particulate air pollution in future decades and that this reduction will reduce adverse health effects caused by the air pollution.     

Using the Community Multiscale Air Quality (CMAQ) model to estimate public health impacts of PM2.5 from individual power plants

We estimated PM_2.5-related public health impacts/ton emitted of primary PM_2.5, SO₂, and NO_x for a set of power plants in the Mid-Atlantic and Lower Great Lakes regions of the United States, selected to include varying emission profiles and broad geographic representation. We then developed a regression model explaining variability in impacts per ton emitted using the population distributions around each plant. We linked outputs from the Community Multiscale Air Quality (CMAQ) model v 4.7.1 with census data and concentration–response functions for PM_2.5-related mortality, and monetized health estimates using the value-of-statistical-life. The median impacts for the final set of plants were $130,000/ton for primary PM_2.5 (range: $22,000–230,000), $28,000/ton for SO₂ (range: $19,000–33,000), and $16,000/ton for NOx (range: $7100–26,000). Impacts of NO_x were a median of 34% (range: 20%–75%) from ammonium nitrate and 66% (range: 25%–79%) from ammonium sulfate. The latter pathway is likely from NO_x enhancing atmospheric oxidative capacity and amplifying sulfate formation, and is often excluded. Our regression models explained most of the variation in impact/ton estimates using basic population covariates, and can aid in estimating impacts averted from interventions such as pollution controls, alternative energy installations, or demand-side management.     

Characteristics of PM10, PM2.5, CO2 and CO monitored in interiors and platforms of subway train in Seoul, Korea

This study was performed to investigate the concentration of PM₁₀ and PM_2.5 inside trains and platforms on subway lines 1, 2, 4 and 5 in Seoul, KOREA. PM₁₀, PM_2.5, carbon dioxide (CO₂) and carbon monoxide (CO) were monitored using real-time monitoring instruments in the afternoons (between 13:00 and 16:00). The concentrations of PM₁₀ and PM_2.5 inside trains were significantly higher than those measured on platforms and in ambient air reported by the Korea Ministry of Environment (Korea MOE). This study found that PM₁₀ levels inside subway lines 1, 2 and 4 exceeded the Korea indoor air quality (Korea IAQ) standard of 150 μg/m³. The average percentage that exceeded the PM₁₀ standard was 83.3% on line 1, 37.9% on line 2 and 63.1% on line 4, respectively. PM_2.5 concentration ranged from 77.7 μg/m³ to 158.2 μg/m³, which were found to be much higher than the ambient air PM_2.5 standard promulgated by United States Environmental Protection Agency (US-EPA) (24 h arithmetic mean: 65 μg/m³). The reason for interior PM₁₀ and PM_2.5 being higher than those on platforms is due to subway trains in Korea not having mechanical ventilation systems to supply fresh air inside the train. This assumption was supported by the CO₂ concentration results monitored in tube of subway that ranged from 1153 ppm to 3377 ppm. The percentage of PM_2.5 in PM₁₀ was 86.2% on platforms, 81.7% inside trains, 80.2% underground and 90.2% at ground track. These results indicated that fine particles (PM_2.5) accounted for most of PM₁₀ and polluted subway air. GLM statistical analysis indicated that two factors related to monitoring locations (underground and ground or inside trains and on platforms) significantly influence PM₁₀ (p < 0.001, R² = 0.230) and PM_2.5 concentrations (p < 0.001, R² = 0.172). Correlation analysis indicated that PM₁₀, PM_2.5, CO₂ and CO were significantly correlated at p < 0.01 although correlation coefficients were different. The highest coefficient was 0.884 for the relationship between PM₁₀ and PM_2.5.