Research report (Health Effects Institute)最新文献

{"title":"Personal exposure to mixtures of volatile organic compounds: modeling and further analysis of the RIOPA data.","authors":"Stuart Batterman, Feng-Chiao Su, Shi Li, Bhramar Mukherjee, Chunrong Jia","doi":"","DOIUrl":"","url":null,"abstract":"<p><strong>Introduction: </strong>Emission sources of volatile organic compounds (VOCs*) are numerous and widespread in both indoor and outdoor environments. Concentrations of VOCs indoors typically exceed outdoor levels, and most people spend nearly 90% of their time indoors. Thus, indoor sources generally contribute the majority of VOC exposures for most people. VOC exposure has been associated with a wide range of acute and chronic health effects; for example, asthma, respiratory diseases, liver and kidney dysfunction, neurologic impairment, and cancer. Although exposures to most VOCs for most persons fall below health-based guidelines, and long-term trends show decreases in ambient emissions and concentrations, a subset of individuals experience much higher exposures that exceed guidelines. Thus, exposure to VOCs remains an important environmental health concern. The present understanding of VOC exposures is incomplete. With the exception of a few compounds, concentration and especially exposure data are limited; and like other environmental data, VOC exposure data can show multiple modes, low and high extreme values, and sometimes a large portion of data below method detection limits (MDLs). Field data also show considerable spatial or interpersonal variability, and although evidence is limited, temporal variability seems high. These characteristics can complicate modeling and other analyses aimed at risk assessment, policy actions, and exposure management. In addition to these analytic and statistical issues, exposure typically occurs as a mixture, and mixture components may interact or jointly contribute to adverse effects. However most pollutant regulations, guidelines, and studies remain focused on single compounds, and thus may underestimate cumulative exposures and risks arising from coexposures. In addition, the composition of VOC mixtures has not been thoroughly investigated, and mixture components show varying and complex dependencies. Finally, although many factors are known to affect VOC exposures, many personal, environmental, and socioeconomic determinants remain to be identified, and the significance and applicability of the determinants reported in the literature are uncertain. To help answer these unresolved questions and overcome limitations of previous analyses, this project used several novel and powerful statistical modeling and analysis techniques and two large data sets. The overall objectives of this project were (1) to identify and characterize exposure distributions (including extreme values), (2) evaluate mixtures (including dependencies), and (3) identify determinants of VOC exposure. METHODS VOC data were drawn from two large data sets: the Relationships of Indoor, Outdoor, and Personal Air (RIOPA) study (1999-2001) and the National Health and Nutrition Examination Survey (NHANES; 1999-2000). The RIOPA study used a convenience sample to collect outdoor, indoor, and personal exposure measurements in three cities (E","PeriodicalId":74687,"journal":{"name":"Research report (Health Effects Institute)","volume":" 181","pages":"3-63"},"PeriodicalIF":0.0,"publicationDate":"2014-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4577247/pdf/nihms706229.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"32603859","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Characterizing ultrafine particles and other air pollutants in and around school buses.","authors":"Yifang Zhu,&nbsp;Qunfang Zhang","doi":"","DOIUrl":"","url":null,"abstract":"<p><p>Increasing evidence has demonstrated toxic effects of ultrafine particles (UFP*, diameter < 100 nm). Children are particularly at risk because of their immature respiratory systems and higher breathing rates per body mass. This study aimed to characterize UFP, PM2.5 (particulate matter < or = 2.5 microm in aerodynamic diameter), and other vehicular-emitted pollutants in and around school buses. Four sub-studies were conducted, including: 1. On-road tests to measure in-cabin air pollutant levels while school buses were being driven; 2. Idling tests to determine the contributions of tailpipe emissions from idling school buses to air pollutant levels in and around school buses under different scenarios; 3. Retrofit tests to evaluate the performance of two retrofit systems, a diesel oxidation catalyst (DOC) muffler and a crankcase filtration system (CFS), on reducing tailpipe emissions and in-cabin air pollutant concentrations under idling and driving conditions; and 4. High efficiency particulate air (HEPA) filter air purifier tests to evaluate the effectiveness of in-cabin filtration. In total, 24 school buses were employed to cover a wide range of school buses commonly used in the United States. Real-time air quality measurements included particle number concentration (PNC), fine and UFP size distribution in the size range 7.6-289 nm, PM2.5 mass concentration, black carbon (BC) concentration, and carbon monoxide (CO) and carbon dioxide (CO2) concentrations. For in-cabin measurements, instruments were placed on a platform secured to the rear seats inside the school buses. For all other tests, a second set of instruments was deployed to simultaneously measure the ambient air pollutant levels. For tailpipe emission measurements, the exhaust was diluted and then measured by instruments identical to those used for the in-cabin measurements. The results show that when driving on roads, in-cabin PNC, fine and UFP size distribution, PM2.5, BC, and CO varied by engine age, window position, driving speed, driving route, and operating conditions. Emissions from idling school buses increased the PNC close to the tailpipe by a factor of up to 26.0. Under some circumstances, tailpipe emissions of idling school buses increased the in-cabin PNC by factors ranging from 1.2 to 5.8 in the 10-30 nm particle size range. Retrofit systems significantly reduced the tailpipe emissions of idling school buses. With both DOC and CFS installed, PNC in tailpipe emissions dropped by 20%-94%. No unequivocal decrease was observed for in-cabin air pollutants after retrofitting. The operation of the air conditioning (AC) unit and the pollutant concentrations in the surrounding ambient air played more important roles than retrofit technologies in determining in-cabin air quality. The use of a HEPA air purifier removed up to 50% of in-cabin particles. Because each sub-study tested only a subset of the 24 school buses, the results should be seen as more exploratory than definiti","PeriodicalId":74687,"journal":{"name":"Research report (Health Effects Institute)","volume":" 180","pages":"3-37"},"PeriodicalIF":0.0,"publicationDate":"2014-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"32348043","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"New statistical approaches to semiparametric regression with application to air pollution research.","authors":"James M Robins,&nbsp;Peng Zhang,&nbsp;Rajeev Ayyagari,&nbsp;Roger Logan,&nbsp;Eric Tchetgen Tchetgen,&nbsp;Lingling Li,&nbsp;Thomas Lumley,&nbsp;Aad van der Vaart","doi":"","DOIUrl":"","url":null,"abstract":"","PeriodicalId":74687,"journal":{"name":"Research report (Health Effects Institute)","volume":" 175","pages":"3-129"},"PeriodicalIF":0.0,"publicationDate":"2013-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"32009178","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"National Particle Component Toxicity (NPACT) Initiative: integrated epidemiologic and toxicologic studies of the health effects of particulate matter components.","authors":"Morton Lippmann,&nbsp;Lung-Chi Chen,&nbsp;Terry Gordon,&nbsp;Kazuhiko Ito,&nbsp;George D Thurston","doi":"","DOIUrl":"","url":null,"abstract":"<p><p>Particulate matter (PM*), an ambient air criteria pollutant, is a complex mixture of chemical components; particle sizes range from nanometer-sized molecular clusters to dust particles that are too large to be aspirated into the lungs. Although particle composition is believed to affect health risks from PM exposure, our current health-based air quality standards for PM are limited to (1) the mass concentrations of PM2.5 (particles 2.5 microm or smaller in aerodynamic diameter), which are largely attributable to combustion products; and (2) PM10 (10 microm or smaller), which includes larger-sized mechanically generated dusts. Both of these particle size fractions are regulated under the National Ambient Air Quality Standards (NAAQS) and both have been associated with excess mortality and morbidity. We conducted four studies as part of HEI's integrated National Particle Component Toxicity (NPACT) Initiative research program. Since 1999, the Chemical Speciation Network (CSN), managed by the U.S. Environmental Protection Agency (U.S; EPA), has routinely gathered air monitoring data every third or sixth day for the concentrations of numerous components of PM2.5. Data from the CSN enabled us to conduct a limited time-series epidemiologic study of short-term morbidity and mortality (Ito study); and a study of the associations between long-term average pollutant concentrations and annual mortality (Thurston study). Both have illuminated the roles of PM2.5 chemical components and source-related mixtures as potentially causal agents. We also conducted a series of 6-month subchronic inhalation exposure studies (6 hours/day, 5 days/week) of PM2.5 concentrated (nominally) 10 x from ambient air (CAPs) with apolipoprotein E-deficient (ApoE(-/-)) mice (a mouse model of atherosclerosis) (Chen study). The CAPs studies were conducted in five different U.S. airsheds; we measured the daily mass concentrations of PM2.5, black carbon (BC), and 16 elemental components in order to identify their sources and their roles in eliciting both short- and long-term health-related responses. In addition, from the same five air-sheds we collected samples of coarse (PM10-2.5), fine (PM2.5-0.2), and ultrafine (PM0.2) particles. Aliquots of these samples were administered to cells in vitro and to mouse lungs in vivo (by aspiration) in order to determine their comparative acute effects (Gordon Study). The results of these four complementary studies, and the overall integrative analyses, provide a basis for guiding future research and for helping to determine more targeted emission controls for the PM components most hazardous to acute and chronic health. Application of the knowledge gained in this work may therefore contribute to an optimization of the public health benefits of future PM emission controls. The design of each NPACT study conducted at NYU was guided by our scientific hypotheses, which were based on our reviews of the background literature and our experience in co","PeriodicalId":74687,"journal":{"name":"Research report (Health Effects Institute)","volume":" 177","pages":"5-13"},"PeriodicalIF":0.0,"publicationDate":"2013-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"31988052","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"National Particle Component Toxicity (NPACT) initiative report on cardiovascular effects.","authors":"Sverre Vedal,&nbsp;Matthew J Campen,&nbsp;Jacob D McDonald,&nbsp;Timothy V Larson,&nbsp;Paul D Sampson,&nbsp;Lianne Sheppard,&nbsp;Christopher D Simpson,&nbsp;Adam A Szpiro","doi":"","DOIUrl":"","url":null,"abstract":"<p><p>Epidemiologic and toxicologic studies were carried out in concert to provide complementary insights into the compositional features of ambient particulate matter (PM*) that produce cardiovascular effects. In the epidemiologic studies, we made use of cohort data from two ongoing studies--the Multi-Ethnic Study of Atherosclerosis (MESA) and the Women's Health Initiative--Observational Study (WHI-OS)--to investigate subclinical markers of atherosclerosis and clinical cardiovascular events. In the toxicologic study, we used the apolipoprotein E null (ApoE(-/-)) hypercholesterolemic mouse model to assess cardiovascular effects of inhalation exposure to various atmospheres containing laboratory-generated pollutants. In the epidemiologic studies, individual-level residential concentrations of fine PM, that is, PM with an aerodynamic diameter of 2.5 microm or smaller (PM2.5), PM2.5 components (primarily elemental carbon [EC] and organic carbon [OC], silicon, and sulfur but also sulfate, nitrate, nickel, vanadium, and copper), and the gaseous pollutants sulfur dioxide and nitrogen dioxide were estimated using spatiotemporal modeling and other exposure estimation approaches. In the MESA cohort data, evidence for associations with increased carotid intima-media thickness (CIMT) was found to be strongest for PM2.5, OC, and sulfur, as well as for copper in more limited analyses; the evidence for this was found to be weaker for silicon, EC, and the other components and gases. Similarly, in the WHI-OS cohort data, evidence for associations with incidence of cardiovascular mortality and cardiovascular events was found to be good for OC and sulfur, respectively, and for PM2.5; the evidence for this was found to be weaker for EC and silicon. Source apportionment based on extensive monitoring data in the six cities in the MESA analyses indicated that OC represented secondary formation processes as well as primary gasoline and biomass emissions, that sulfur represented largely secondary inorganic aerosols, and that copper represented brake dust and diesel emissions. In the toxicologic study, hypercholesterolemic mice were exposed for 50 days to atmospheres containing mixed vehicular engine emissions (MVE) consisting of mixed gasoline and diesel engine exhaust or to MVE-derived gases only (MVEG). Mice were also exposed to atmospheres containing sulfate, nitrate, or road dust, either alone or mixed with MVE or MVEG. Sulfate alone or in combination with MVE was associated with increased aortic reactivity. All exposures to atmospheres containing MVE (including a combination of MVE with other PM) were associated with increases in plasma and aortic oxidative stress; exposures to atmospheres containing only sulfate or nitrate were not. Exposure to MVE and to MVEG combinations except those containing road dust resulted in increased monocyte/macrophage sequestration in aortic plaque (a measure of plaque inflammation). Exposure to all atmospheres except those containing","PeriodicalId":74687,"journal":{"name":"Research report (Health Effects Institute)","volume":" 178","pages":"5-8"},"PeriodicalIF":0.0,"publicationDate":"2013-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"31988053","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effect of air pollution control on mortality and hospital admissions in Ireland.","authors":"Douglas W Dockery,&nbsp;David Q Rich,&nbsp;Patrick G Goodman,&nbsp;Luke Clancy,&nbsp;Pamela Ohman-Strickland,&nbsp;Prethibha George,&nbsp;Tania Kotlov","doi":"","DOIUrl":"","url":null,"abstract":"<p><p>During the 1980s the Republic of Ireland experienced repeated severe pollution episodes. Domestic coal burning was a major source of this pollution. In 1990 the Irish government introduced a ban on the marketing, sale, and distribution of coal in Dublin. The ban was extended to Cork in 1995 and to 10 other communities in 1998 and 2000. We previously reported decreases in particulate black smoke (BS*) and sulfur dioxide (SO2) concentrations, measured as total gaseous acidity, in Dublin after the 1990 coal ban (Clancy et al. 2002). In the current study we explored and compared the effectiveness of the sequential 1990, 1995, and 1998 bans in reducing community air pollution and in improving public health. We compiled records of daily BS, total gaseous acidity (SO2), and counts of cause-specific deaths from 1981 to 2004 for Dublin County Borough (1990 ban), county Cork (1995 ban), and counties Limerick, Louth, Wexford, and Wicklow (1998 ban). We also compiled daily counts of hospital admissions for cardiovascular, respiratory, and digestive diagnoses for Cork County Borough (1991 to 2004) and counties Limerick, Louth, Wexford, and Wicklow (1993 to 2004). We compared pre-ban and post-ban BS and SO2 concentrations for each city. Using interrupted time-series methods, we estimated the change in cause-specific, directly standardized mortality rates in each city or county after the corresponding local coal ban. We regressed weekly age- and sex-standardized mortality rates against an indicator of the post- versus pre-ban period, adjusting for influenza epidemics, weekly mean temperature, and a season smooth of the standardized mortality rates in Coastal counties presumably not affected by the bans. We compared these results with similar analyses in Midlands counties also presumably unaffected by the bans. We also estimated the change in cause-specific, directly standardized, weekly hospital admissions rates normalized for underreporting in each city or county after the 1995 and 1998 bans, adjusting for influenza epidemics, weekly mean temperature, and local admissions for digestive diagnoses. Mean BS concentrations fell in all affected population centers post-ban compared with the pre-ban period, with decreases ranging from 4 to 35 microg/m3 (corresponding to reductions of 45% to 70%, respectively), but we observed no clear pattern in SO2 measured as total gaseous acidity associated with the bans. In comparisons with the pre-ban periods, no significant reduction was found in total death rates associated with the 1990 (1% reduction), 1995 (4% reduction), or 1998 (0% reduction) bans, nor for cardiovascular mortality (0%, 4%, and 1% reductions for the 1990, 1995, and 1998 bans, respectively). Respiratory mortality was reduced in association with the bans (17%, 9%, and 3%, respectively). We found a 4% decrease in hospital admissions for cardiovascular disease associated with the 1995 ban and a 3% decrease with the 1998 ban. Admissions for respiratory dis","PeriodicalId":74687,"journal":{"name":"Research report (Health Effects Institute)","volume":" 176","pages":"3-109"},"PeriodicalIF":0.0,"publicationDate":"2013-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"31722795","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cardiorespiratory biomarker responses in healthy young adults to drastic air quality changes surrounding the 2008 Beijing Olympics.","authors":"Junfeng Zhang,&nbsp;Tong Zhu,&nbsp;Howard Kipen,&nbsp;Guangfa Wang,&nbsp;Wei Huang,&nbsp;David Rich,&nbsp;Ping Zhu,&nbsp;Yuedan Wang,&nbsp;Shou-En Lu,&nbsp;Pamela Ohman-Strickland,&nbsp;Scott Diehl,&nbsp;Min Hu,&nbsp;Jian Tong,&nbsp;Jicheng Gong,&nbsp;Duncan Thomas","doi":"","DOIUrl":"","url":null,"abstract":"<p><p>Associations between air pollution and cardiorespiratory mortality and morbidity have been well established, but data to support biologic mechanisms underlying these associations are limited. We designed this study to examine several prominently hypothesized mechanisms by assessing Beijing residents' biologic responses, at the biomarker level, to drastic changes in air quality brought about by unprecedented air pollution control measures implemented during the 2008 Beijing Olympics. To test the hypothesis that changes in air pollution levels are associated with changes in biomarker levels reflecting inflammation, hemostasis, oxidative stress, and autonomic tone, we recruited and retained 125 nonsmoking adults (19 to 33 years old) free of cardiorespiratory and other chronic diseases. Using the combination of a quasi-experimental design and a panel-study approach, we measured biomarkers of autonomic dysfunction (heart rate [HR*] and heart rate variability [HRV]), of systemic inflammation and oxidative stress (plasma C-reactive protein [CRP], fibrinogen, blood cell counts and differentials, and urinary 8-hydroxy-2'-deoxyguanosine [8-OHdG]), of pulmonary inflammation and oxidative stress (fractional exhaled nitric oxide [FeNO], exhaled breath condensate [EBC] pH, EBC nitrate, EBC nitrite, EBC nitrite+nitrate [sum of the concentrations of nitrite and nitrate], and EBC 8-isoprostane), of hemostasis (platelet activation [plasma sCD62P and sCD40L], platelet aggregation, and von Willebrand factor [vWF]), and of blood pressure (systolic blood pressure [SBP] and diastolic blood pressure [DBP]). These biomarkers were measured on each subject twice before, twice during, and twice after the Beijing Olympics. For each subject, repeated measurements were separated by at least one week to avoid potential residual effects from a prior measurement. We measured a large suite of air pollutants (PM2.5 [particulate matter < or = 2.5 microm in aerodynamic diameter] and constituents, sulfur dioxide [SO2], carbon monoxide [CO], nitrogen dioxide [NO2], and ozone [O3]) throughout the study at a central Beijing site near the residences and workplaces of the subjects on a daily basis. Total particle number (TPN) was also measured at a separate site. We used a time-series analysis to assess changes in pollutant concentration by period (pre-, during-, and post-Olympics periods). We used mixed-effects models to assess changes in biomarker levels by period and to estimate changes associated with increases in pollutant concentrations, controlling for ambient temperature, relative humidity (RH), sex, and the day of the week of the biomarker measurements. We conducted sensitivity analyses to assess the impact of potential temporal confounding and exposure misclassification. We observed reductions in mean concentrations for all measured pollutants except O3 from the pre-Olympics period to the during-Olympics period. On average, elemental carbon (EC) changed by -36%, TPN by -22%","PeriodicalId":74687,"journal":{"name":"Research report (Health Effects Institute)","volume":" 174","pages":"5-174"},"PeriodicalIF":0.0,"publicationDate":"2013-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4086245/pdf/nihms580799.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"31408707","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Selective detection and characterization of nanoparticles from motor vehicles.","authors":"Murray V Johnston,&nbsp;Joseph P Klems,&nbsp;Christopher A Zordan,&nbsp;M Ross Pennington,&nbsp;James N Smith","doi":"","DOIUrl":"","url":null,"abstract":"<p><p>Numerous studies have shown that exposure to motor vehicle emissions increases the probability of heart attacks, asthma attacks, and hospital visits among at-risk individuals. However, while many studies have focused on measurements of ambient nanoparticles near highways, they have not focused on specific road-level domains, such as intersections near population centers. At these locations, very intense spikes in particle number concentration have been observed. These spikes have been linked to motor vehicle activity and have the potential to increase exposure dramatically. Characterizing both the contribution and composition of these spikes is critical in developing exposure models and abatement strategies. To determine the contribution of the particle spikes to the ambient number concentration, we implemented wavelet-based algorithms to isolate the particle spikes from measurements taken during the summer and winter of 2009 in Wilmington, Delaware, adjacent to a roadway intersection that approximately 28,000 vehicles pass through daily. These measurements included both number concentration and size distributions recorded once every second by a condensation particle counter (CPC*; TSI, Inc., St. Paul, MN) and a fast mobility particle sizer (FMPS). The high-frequency portion of the signal, consisting of a series of abrupt spikes in number concentration that varied in length from a few seconds to tens of seconds, accounted for 3% to 35% of the daily ambient number concentration, with spike contributions sometimes greater than 50% of hourly number concentrations. When the data were weighted by particle volume, this portion of the signal contributed an average of 10% to 20% to the daily concentration of particulate matter (PM) < or = 0.1 microm in aerodynamic diameter (PM0.1). The preferred locations for observing particle concentration spikes were those surrounding the measurement site at which motor vehicles accelerated after a red traffic light turned green. As the distance or transit time from emission to sampling increased, the size distribution shifted to a larger particle size, which confirmed the source assignments. To determine the distribution of emissions from individual vehicles, we correlated camera images with the spike contribution to particle number concentration at each time point. A small percentage of motor vehicles were found to emit a disproportionally large concentration of nanoparticles, and these high emitters included both spark-ignition (SI) and heavy-duty diesel (HDD) vehicles. In addition to characterizing the contribution of the spikes (local sources) to the ambient number concentration, we developed a method to determine the net contribution of motor vehicles (all sources) to the total mass concentration of ambient nanoparticles. To do this, we correlated the concentration of spikes with measurements of fast changes in the chemical composition of nanoparticles measured with the nano aerosol mass spectrometer (NAMS","PeriodicalId":74687,"journal":{"name":"Research report (Health Effects Institute)","volume":" 173","pages":"3-45"},"PeriodicalIF":0.0,"publicationDate":"2013-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"31381458","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Potential air toxics hot spots in truck terminals and cabs.","authors":"Thomas J Smith,&nbsp;Mary E Davis,&nbsp;Jaime E Hart,&nbsp;Andrew Blicharz,&nbsp;Francine Laden,&nbsp;Eric Garshick","doi":"","DOIUrl":"","url":null,"abstract":"<p><strong>Introduction: </strong>Hot spots are areas where concentrations of one or more air toxics--organic vapors or particulate matter (PM)--are expected to be elevated. The U.S. Environmental Protection Agency's (EPA*) screening values for air toxics were used in our definition of hot spots. According to the EPA, a screening value \"is used to indicate a concentration of a chemical in the air to which a person could be continually exposed for a lifetime ... and which would be unlikely to result in a deleterious effect (either cancer or noncancer health effects)\" (U.S. EPA 2006). Our characterization of volatile organic compounds (VOCs; namely 18 hydrocarbons, methyl tert-butyl ether [MTBE], acetone, and aldehydes) was added onto our ongoing National Cancer Institute-funded study of lung cancer and particulate pollutant concentrations (PM with an aerodynamic diameter < or = 2.5 microm [PM2.5], elemental carbon [EC], and organic carbon [OC]) and source apportionment of the U.S. trucking industry. We focused on three possible hot spots within the trucking terminals: upwind background areas affected by nearby industrial parks; downwind areas affected by upwind and terminal sources; and the loading docks and mechanic shops within terminal as well as the interior of cabs of trucks being driven on city, suburban, and rural streets and on highways.</p><p><strong>Methods: </strong>In Phase 1 of our study, 15 truck terminals across the United States were each visited for five consecutive days. During these site visits, sorbent tubes were used to collect 12-hour integrated samples of hydrocarbons and aldehydes from upwind and downwind fence-line locations as well as inside truck cabs. Meteorologic data and extensive site information were collected with each sample. In Phase 2, repeat visits to six terminals were conducted to test the stability of concentrations across time and judge the representativeness of our previous measurements. During the repeat site visits, the sampling procedure was expanded to include real-time sampling for total hydrocarbon (HC) and PM2.5 at the terminal upwind and downwind sites and inside the truck cabs, two additional monitors in the yard for four-quadrant sampling to better characterize the influence of wind, and indoor sampling in the loading dock and mechanic shop work areas.</p><p><strong>Results: </strong>Mean and median concentrations of VOCs across the sampling locations in and around the truck terminals showed significant variability in the upwind concentrations as well as in the intensity of exposures for drivers, loading-dock workers, and mechanics. The area of highest concentrations varied, although the lowest concentrations were always found in the upwind background samples. However, the downwind samples, which included the terminal's contribution, were on average only modestly higher than the upwind samples. In the truck terminal, the mechanic-shop-area concentrations were consistently elevated for many of the","PeriodicalId":74687,"journal":{"name":"Research report (Health Effects Institute)","volume":" 172","pages":"5-82"},"PeriodicalIF":0.0,"publicationDate":"2012-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5116924/pdf/nihms828156.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"31330047","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Accountability analysis of title IV phase 2 of the 1990 Clean Air Act Amendments.","authors":"Richard D Morgenstern,&nbsp;Winston Harrington,&nbsp;Jhih-Shyang Shih,&nbsp;Michelle L Bell","doi":"","DOIUrl":"","url":null,"abstract":"<p><p>In this study, we sought to assess what portion, if any, of the reductions in ambient concentrations of particulate matter (PM*) < or = 2.5 microm in aerodynamic diameter (PM2.5) that occurred in the United States between the years 1999 and 2006 can be attributed to reductions in emissions of sulfur dioxide (SO2) and nitrogen oxides (NOx) resulting from implementation of Phase 2 of Title IV of the 1990 Clean Air Act Amendments. To this end, a detailed statistical model linking sources and monitors over time and space was used to estimate associations between the observed emissions reductions and improvements in air quality. Overall, it turned out to be quite feasible to use relatively transparent statistical methods to assess these outcomes of the Phase 2 program, which was designed to reduce long-range transport of emissions. Associations between changes in emissions from individual power plants and monitor-specific estimates of changes in concentrations of PM2.5, our indicator pollutant, were highly significant and were mostly of the expected relative magnitudes with respect to distances and directions from sources. Originally estimated on monthly data for a set of 193 monitors between 1999 and 2005, our preferred model performed equally well using data for the same 193 monitors for 2006 as well as for an additional 217 monitors not in the original set in 2006. Although substantial model uncertainty was observed, we were able to estimate that the Title IV Phase 2 emissions reduction program implemented between 1999 and 2005 reduced PM2.5 concentrations in the eastern United States by an average of 1.07 microg/m3 (standard deviation [SD] = 0.11 microg/m3) compared with a counterfactual case defined as there having been no change in emission rates per unit of energy input (1 million British thermal units [BTUs]). On a population-weighted basis, the comparable reduction in PM2.5 was 0.89 microg/m3. Compared with the air quality fate and transport models used by the U.S. Environmental Protection Agency (EPA) to estimate air quality improvements associated with the Clean Air Interstate Rule (CAIR) for 2010 and 2015, when baseline PM2.5 concentrations were expected to be about one-third lower, our statistical model yielded roughly similar results per ton of SO2 reduced, well within the estimated confidence intervals of the models. We have proposed a number of steps to advance air quality outcomes research using statistical methods. Specifically, we have emphasized the value of updating our analysis with post-2005 data to try to corroborate our findings. We have also recommended extending the work on air quality outcomes to include changes in health outcomes that might be associated with the implementation of Title IV Phase 2.</p>","PeriodicalId":74687,"journal":{"name":"Research report (Health Effects Institute)","volume":" 168","pages":"5-35"},"PeriodicalIF":0.0,"publicationDate":"2012-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"31330043","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}