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Land use regression (LUR) has evolved as a standard tool for estimating intra-urban variation in long-term air pollution exposures. LUR, however, generally relies on observed spatial relationships between distributed sources and pollution measures, rather than meteorological or physio-chemical information. Incorporating traffic-meteorological interaction information into LURs via dispersion models may improve accuracy and physical interpretability. To examine whether deterministic dispersion output improves LUR predictions for nitrogen dioxide (NO2), we incorporated hourly Caline3QHCR dispersion information into existing winter-time regression models originally designed to disentangle effects of multiple sources (e.g., legacy industry, vehicle traffic) and concentration modifiers (e.g., elevation) across Pittsburgh, PA. Caline3QHCR output improved overall cross-validated R2 values by 0.10, 0.03, and 0.05 for the weekday, full-week, and merged years models, respectively. The addition of Caline3 output as an independent covariate effectively displaced two road-specific predictors, one built environment predictor and one meteorological predictor across two winter-season models. The incorporation of study-specific dispersion principles may corroborate overall LUR model interpretability and could be applied similarly to preexisting LUR models that lack strong source-concentration relationships. Model improvements were observed at sites with relatively higher NO2 concentrations that exhibited higher traffic volumes and were in closer proximity to roadways (

Impacts of industrial emissions on outdoor air pollution in nearby communities are well-documented. Fewer studies, however, have explored impacts on indoor air quality in these communities. Because persons in northern climates spend a majority of their time indoors, understanding indoor exposures, and the role of outdoor air pollution in shaping such exposures, is a priority issue. Braddock and Clairton, Pennsylvania, industrial communities near Pittsburgh, are home to an active steel mill and coke works, respectively, and the population experiences elevated rates of childhood asthma. Twenty-one homes were selected for 1-week indoor sampling for fine particulate matter (PM2.5) and black carbon (BC) during summer 2011 and winter 2012. Multivariate linear regression models were used to examine contributions from both outdoor concentrations and indoor sources. In the models, an outdoor infiltration component explained 10 to 39% of variability in indoor air pollution for PM2.5, and 33 to 42% for BC. For both PM2.5 models and the summer BC model, smoking was a stronger predictor than outdoor pollution, as greater pollutant concentration increases were identified. For winter BC, the model was explained by outdoor pollution and an open windows modifier. In both seasons, indoor concentrations for both PM2.5 and BC were consistently higher than residence-specific outdoor concentration estimates. Mean indoor PM2.5 was higher, on average, during summer (25.8±22.7μg/m3) than winter (18.9±13.2μg/m3). Contrary to the study's hypothesis, outdoor concentrations accounted for only little to moderate variability (10 to 42%) in indoor concentrations; a much greater proportion of PM2.5 was explained by cigarette smoking. Outdoor infiltration was a stronger predictor for BC compared to PM2.5, especially in winter. Our results suggest that, even in industrial communities of high outdoor pollution concentrations, indoor activities – particularly cigarette smoking – may play a larger role in shaping indoor exposures.

FracTracker is a participatory geographic information system (PGIS) and website that was designed to address concerns surrounding the process of unconventional natural gas development (UNGD) by ena...

The UC Berkeley Time-Activity Monitoring System (UCB-TAMS) was developed to measure time-activity in exposure studies. The system consists of small, light, inexpensive battery-operated 40-kHz ultrasound transmitters (tags) worn by participants and an ultrasound receiver (locator) attached to a datalogger fixed in an indoor location. Presence or absence of participants is monitored by distinguishing the unique ultrasound ID of each tag. Efficacy tests in rural households of highland Guatemala showed the system to be comparable to the gold-standard time-activity measure of direct observation by researchers, with an accuracy of predicting time-weighted averages of 90-95%, minute-by-minute accuracy of 80-85%, and sensitivity/specificity values of 86-89%/71-74% for one-minute readings on children 3-8 years-old. Additional controlled tests in modern buildings and in rural Guatemalan homes confirmed the performance of the system with the presence of other ultrasound sources, with multiple tags, covered by clothing, and in other non-ideal circumstances.

In society's effort to address and prepare for climate change, the health community itself must ensure that it is prepared. Health personnel will require flexible and iterative action plans to address climate change at the individual, hospital, local health department, state, and national levels. This requires that health workers analyze the impact of climate change with a view to human health, and then formulate robust policy and demonstrate authentic leadership. In this review, we summarize the status of the health community's preparation for climate change and provide specific recommendations for action at each level. Although preparation status and recommendations vary, our observation is that it is not enough for public health and medical care agencies and departments to develop policies and advocate change. They have a direct responsibility to demonstrate substantive leadership.

Standardized techniques for monitoring and evaluating (M&E) changes in indoor air quality and stove fuel performance were developed and deployed in two NGO-led programs to disseminate improved cookstoves (ICSs) in India and one in Mexico. This paper describes the objectives and characteristics of these monitoring and evaluation methods and how they were deployed. The results showed major and mostly statistically significant improvements in 48-hour indoor air pollution concentrations in those households using the stoves one year after introduction. Kitchen levels of carbon monoxide reduced 30-70 % and concentrations of small particles reduced 25-65 %. Results for stove performance were mixed, with some stoves achieving improvement in one or another of the short-term metrics that are part of the water boiling test (WBT) used to evaluate stoves in laboratory (controlled) settings. The kitchen performance test, which measures fuel use in households under actual use, was less easily conducted because of high variation and difficult field logistics. The results are more promising, however, with statistically significant reductions in fuel use per person ranging from about 20 to 67 %. From the results, it also seems clear that several indicators of stove performance derived from the WBT are not good predictors of actual fuel use and thus should be confined to evaluations during the design stage of stove development. In two of the sites, the reductions in pollution roughly matched those in fuel use, although in the third, indoor air pollution may have reduced a bit more. This indicates perhaps that for all the monitored stoves, much or all of the benefits of each type came from improving the heat transfer into the pots and not from either increased combustion efficiency of the fires or stove-venting

Despite the reach of India's National Program on Improved Chulhas, little quantitative monitoring and evaluation of improved stove projects in India has previously been undertaken by non-governmental organizations. Development Alternatives (DA) recently distributed 980 improved chimney cookstoves (Sukhad stoves) in the Bundelkhand region of India. In a subset of these households (n = 60), DA undertook a comprehensive assessment of the impact of the improved Sukhad stove on indoor air quality. Measurements of carbon monoxide (CO) and fine particulate matter (PM 2.5 ) were conducted for a 48-hour period in 60 rural kitchens in Bundelkhand before and after installation of the Sukhad stove. One year after the installation of the of the Sukhad, 48-hour average CO concentrations were reduced, on average, by 70% (p 2.5 concentrations were reduced, on average, by 44% (p

To reduce the impact of indoor air pollution and improve fuel efficiency, the Appropriate Rural Technology Institute (ARTI), in conjunction with ten non-governmental organizations, helped establish rural enterprises that subsequently distributed 30,000 improved cement cookstoves in Maharashtra, India, between August 2004 and December 2005. In a subset of these households (n = 110), ARTI undertook a comprehensive assessment of the impact of the improved Laxmi (vented) and Bhagyalaxmi (unvented) stoves on indoor air quality. Measurements of carbon monoxide (CO) and fine particulate matter (PM 2.5 ) were taken for a 48-hour period in kitchens before and after installation of improved stoves. One year after the installation of the improved stoves, the 48-hr mean CO concentration was reduced, on average, by 39% for the Laxmi and 38% for the Bhagyalaxmi. Similarly, the 48-hr mean PM 2.5 concentration was reduced, on average, by 24% for the Laxmi and 49% for the Bhagyalaxmi. Key challenges during the monitoring were: (1) motivating household members to purchase the improved cookstoves (ICSs); (2) ensuring that the households made the transition to using the ICSs; and (3) maintaining high standards of data quality as a field team. Despite the challenges, the importance of monitoring and evaluation remains critical in verifying the benefits of improved stove designs. Building on the lessons that we have learned, future efforts will focus on monitoring and evaluating fewer villages to concentrate resources, establishing a stronger rapport with study participants, and better understanding the dynamics of stove adoption in each home. Our hope is that this experience will aid other organizations in the design of their own ICS monitoring and evaluation programs.

Fine particulate matter (PM2.5) air pollution, varying in concentration and composition, has been shown to cause or exacerbate adverse effects on both human and ecological health. The concept of biomonitoring using deciduous tree leaves as a proxy for intraurban PM air pollution in different areas has previously been explored using a variety of study designs (e.g., systematic coverage of an area, source-specific focus), deciduous tree species, sampling strategies (e.g., single day, multi-season), and analytical methods (e.g., chemical, magnetic) across multiple geographies and climates. Biomonitoring is a low-cost sampling method and may potentially fill an important gap in current air monitoring methods by providing low-cost, longer-term urban air pollution measures. As such, better understanding of the range of methods, and their corresponding strengths and limitations, is critical for employing the use of tree leaves as biomonitors for pollution to improve spatially resolved exposure assessments for epidemiological studies and urban planning strategies.

Background Characterizing intra-urban variation in air quality is important for epidemiological investigation of health outcomes and disparities. To date, however, few studies have been designed to capture spatial variation during select hours of the day, or to examine the roles of meteorology and complex terrain in shaping intra-urban exposure gradients. Methods We designed a spatial saturation monitoring study to target local air pollution sources, and to understand the role of topography and temperature inversions on fine-scale pollution variation by systematically allocating sampling locations across gradients in key local emissions sources (vehicle traffic, industrial facilities) and topography (elevation) in the Pittsburgh area. Street-level integrated samples of fine particulate matter (PM2.5), black carbon (BC), nitrogen dioxide (NO2), sulfur dioxide (SO2), and ozone (O3) were collected during morning rush and probable inversion hours (6-11 AM), during summer and winter. We hypothesized that pollution concentrations would be: 1) higher under inversion conditions, 2) exacerbated in lower-elevation areas, and 3) vary by season. Results During July - August 2011 and January - March 2012, we observed wide spatial and seasonal variability in pollution concentrations, exceeding the range measured at regulatory monitors. We identified elevated concentrations of multiple pollutants at lower-elevation sites, and a positive association between inversion frequency and NO2 concentration. We examined temporal adjustment methods for deriving seasonal concentration estimates, and found that the appropriate reference temporal trend differs between pollutants. Conclusions Our time-stratified spatial saturation approach found some evidence for modification of inversion-concentration relationships by topography, and provided useful insights for refining and interpreting GIS-based pollution source indicators for Land Use Regression modeling.

Background: Land use regression (LUR) models describe spatial relationships between distributed pollutant concentration measures and geographic information systems (GIS)-based indicators of source ...

Background: Land use regression (LUR) models describe spatial relationships between distributed pollutant concentration measures and geographic information systems (GIS)-based indicators of source ...

Background While air pollution exposures have been linked to cardiovascular outcomes, the contribution from acute gas and particle traffic-related pollutants remains unclear. Using a panel study design with repeated measures, we examined associations between personal exposures to traffic-related air pollutants in Mexico City and changes in heart rate variability (HRV) in a population of researchers aged 22 to 56 years. Methods Participants were monitored for approximately 9.5 hours for eight days while operating a mobile laboratory van designed to characterize traffic pollutants while driving in traffic and “chasing” diesel buses. We examined the association between HRV parameters (standard deviation of normal-to-normal intervals (SDNN), power in high frequency (HF) and low frequency (LF), and the LF/HF ratio) and the 5-minute maximum (or average in the case of PM2.5) and 30-, 60-, and 90-minute moving averages of air pollutants (PM2.5, O3, CO, CO2, NO2, NOx, and formaldehyde) using single- and two-pollutant linear mixed-effects models. Results Short-term exposure to traffic-related emissions was associated with statistically significant acute changes in HRV. Gaseous pollutants – particularly ozone – were associated with reductions in time and frequency domain components (α = 0.05), while significant positive associations were observed between PM2.5 and SDNN, HF, and LF. For ozone and formaldehyde, negative associations typically increased in magnitude and significance with increasing averaging periods. The associations for CO, CO2, NO2, and NOx were similar with statistically significant associations observed for SDNN, but not HF or LF. In contrast, PM2.5 increased these HRV parameters. Conclusions Results revealed an association between traffic-related PM exposures and acute changes in HRV in a middle-aged population when PM exposures were relatively low (14 μg/m3) and demonstrate heterogeneity in the effects of different pollutants, with declines in HRV – especially HF – with ozone and formaldehyde exposures, and increases in HRV with PM2.5 exposure. Given that exposure to traffic-related emissions is associated with increased risk of cardiovascular morbidity and mortality, understanding the mechanisms by which traffic-related emissions can cause cardiovascular disease has significant public health relevance., Massachusetts Institute of Technology. Mexico City Project

During the first randomized intervention trial (RESPIRE: Randomized Exposure Study of Pollution Indoors and Respiratory Effects) in air pollution epidemiology, we pioneered application of passive carbon monoxide (CO) diffusion tubes to measure long-term personal exposures to woodsmoke. Here we report on the protocols and validations of the method, trends in personal exposure for mothers and their young children, and the efficacy of the introduced improved chimney stove in reducing personal exposures and kitchen concentrations. Passive diffusion tubes originally developed for industrial hygiene applications were deployed on a quarterly basis to measure 48-hour integrated personal carbon monoxide exposures among 515 children 0-18 months of age and 532 mothers aged 15-55 years and area samples in a subsample of 77 kitchens, in households randomized into control and intervention groups. Instrument comparisons among types of passive diffusion tubes and against a continuous electrochemical CO monitor indicated that tubes responded nonlinearly to CO, and regression calibration was used to reduce this bias. Before stove introduction, the baseline arithmetic (geometric) mean 48-h child (n ¼ 270), mother (n ¼ 529) and kitchen (n ¼ 65) levels were, respectively, 3.4 (2.8), 3.4 (2.8) and 10.2 (8.4) p.p.m. The between-group analysis of the 3355 post-baseline measurements found CO levels to be significantly lower among the intervention group during the trial period: kitchen levels: � 90%; mothers: � 61%; and children: � 52% in geometric means. No significant deterioration in stove effect was observed over the 18 months of surveillance. The reliability of these findings is strengthened by the large sample size made feasible by these unobtrusive and inexpensive tubes, measurement error reduction through instrument calibration, and a randomized, longitudinal study design. These results from the first randomized trial of improved household energy technology in a developing country and demonstrate that a simple chimney stove can substantially reduce chronic exposures to harmful indoor air pollutants among women and infants.

Background Braddock, Pennsylvania is home to the Edgar Thomson Steel Works (ETSW), one of the few remaining active steel mills in the Pittsburgh region. An economically distressed area, Braddock exceeds average annual (>15 μg/m3) and daily (>35 μg/m3) National Ambient Air Quality Standards (NAAQS) for particulate matter (PM2.5). Methods A mobile air monitoring study was designed and implemented in morning and afternoon hours in the summer and winter (2010–2011) to explore the within-neighborhood spatial and temporal (within-day and between-day) variability in PM2.5 and PM10. Results Both pollutants displayed spatial variation between stops, and substantial temporal variation within and across study days. For summer morning sampling runs, site-specific mean PM2.5 ranged from 30.0 (SD = 3.3) to 55.1 (SD = 13.0) μg/m3. Mean PM10 ranged from 30.4 (SD = 2.5) to 69.7 (SD = 51.2) μg/m3, respectively. During summer months, afternoon concentrations were significantly lower than morning for both PM2.5 and PM10, potentially owing to morning subsidence inversions. Winter concentrations were lower than summer, on average, and showed lesser diurnal variation. Temperature, wind speed, and wind direction predicted significant variability in PM2.5 and PM10 in multiple linear regression models. Conclusions Data reveals significant morning versus afternoon variability and spatial variability in both PM2.5 and PM10 concentrations within Braddock. Information obtained on peak concentration periods, and the combined effects of industry, traffic, and elevation in this region informed the design of a larger stationary monitoring network.