1,721,067 research outputs found
Estimation of the intra-urban variability of particulate matter concentrations using low-cost monitors and land use regression models
No full textUrban background air quality stations are representative of the city-wide pollution and are used (i) for
regulatory purposes and (ii) to estimate the average exposure for the population. However, just one or
a few urban sites are usually located within major cities in routine monitoring networks. This sparse
spatial coverage is insufficient to capture the spatial variability expected in urban areas. This serious
gap causes problems when performing human exposure studies: poor spatial resolution may mask the
exposure variability in the study population and may lead to potential exposure misclassifications that
reduces the power of the study.
Recent advance in micro-scale technology have made available low-cost sensors now that permit
continuous and simultaneous measurements to be made in multiple locations. However, low-cost
monitors do not meet rigid performance standards and produce data that need to be carefully evaluated
and unbiased before being used for scientific purposes [1].
Measurements of ambient PM concentrations were performed using 25 low-cost monitors from
October to April 2015–2016 and 2016–2017 to assess the spatial and temporal variability in PM and
the relative importance of traffic and wood smoke to outdoor PM concentrations in Rochester, NY,
USA [2]. In general, results showed a moderate spatial inhomogeneity. Pearson correlation
coefficients were often moderate (~50% of units showed correlations >0.5 during the first season),
indicating that there was some coherent variation across the urban area.
Land-use regression (LUR) models provide location and time specific estimates of exposure to air
pollution and thereby improve the sensitivity of health effects models. LUR models based on the
deletion/substitution/addition algorithm were built from the low-cost monitor data for each hour of
the day and weekdays/weekend days. Coefficients of determination for hourly PM predictions ranged
from 0.63 to 0.67.
The technology behind the current commercially available low-cost monitor still needs substantial
improvements to return devices able to approximate PM concentrations similarly to conventional
scientific-grade instruments. However, our results also show that the use of this new technology may
be useful in increasing the spatial resolution of regulatory air quality networks.
Bibliografia
[1] N. Zikova et al. (2017). J. Aerosol Sciences, 105, 24–34.
[2] N. Zikova et al. (2017). Sensors, 17, 192
Impact of environmental policies and the economy on changes in criteria air pollutants concentrations and particulate matter compositions in New York State during 2005-2016
Get PDFOver the past several decades, several mitigation strategies have been adopted by federal and state agencies in the United States to improve air quality. These strategies were mostly targeted to reduce SO2 and NOx emissions from light- and heavy-duty vehicles and electric power generation. Between 2007 and 2009, the financial/economic crisis also lowered activity and reduced emissions. Simultaneously, changes in the prices of coal and natural gas drove a shift in fuels used for electricity generation toward natural gas.
This study investigates the seasonal patterns, diel cycles, spatial gradients, and trends of gaseous and particulate pollutant concentrations and PM2.5 sources over New York State (NYS) between 2005 and 2016. Gaseous pollutants concentrations (SO2, O3, CO, and NOx) and PM2.5 mass and chemical speciation data (elements, major water soluble inorganic ions, EC, and OC) were retrieved from USEPA (https://aqs.epa.gov/api). The final dataset included 54 sites for PM2.5 mass and gases (26 for PM2.5, 37 for O3, 26 for SO2, 8 for NOx, 2 for NOy 11 for CO) and 6 urban sites (Albany, Bronx, Buffalo, Manhattan, Queens, and Rochester) and 2 rural sites (Pinnacle and Whiteface) for PM2.5 speciation data.
EPA PMF 5.0 was applied to the speciation data to identify and apportion the major sources of PM2.5 across these sites. The relationships between ambient concentrations, changes in emissions retrieved from the national emission inventory (NEI), and economic changes were studied.
Results show that the combined effects of the mitigation strategies, economic pressures, and the recession led to an overall decrease in PM2.5 and primary gaseous pollutants concentrations across New York State ultimately resulting in relatively homogeneous spatial distributions for PM2.5 and SO2. PM2.5 concentrations decreased significantly at all sites with slopes ranging from -8.6%/y and –2.2%/y. SO2 concentrations dropped significantly at all sites within this period, with the highest slopes observed at the urban sites (e.g., -8.5%/y at Queens, New York City).
The reduction of NOx emissions contributed to the reduction of high ozone episodes during summer, but there was no reduction in spring maxima. Increases in autumn and winter ozone concentrations were estimated (e.g., 6.6 ± 0.4% y-1 on average in New York City). Statistically significant relationships were observed between PM2.5, primary pollutants, and economic indicators. Overall, the decrease in electricity generation with coal, and the simultaneous increase in natural gas consumption for power generation, led to a decrease in PM2.5 and gaseous pollutants concentrations.
Seven main common sources of PM2.5 were identified across the state: (i) secondary sulfate; (ii) secondary nitrate; (iii) gasoline emissions; (iv) diesel emission; (v) road dust; (vi) biomass burning and (vii) OP-rich. A road salt source was identified at Albany, Buffalo, Rochester and Pinnacle and Whiteface. Additional sources at the New York City sites (Bronx, Manhattan, and Queens) were fresh sea salt, aged sea salt and residual oil combustion.
Among the main PM2.5 sources, decreases of secondary sulfate, secondary nitrate, and diesel emissions were observed (-6.7±1.1%/y, -5.3±1.2%/y, -5.3±1.9%/y, respectively) across the state. Decreases can be associated to the mitigation strategies aimed at reducing emissions from light- and heavy-duty vehicles and electric power generation and to the shift from high sulfur to ultralow sulfur fuels. Beginning on July 1, 2012, New York State required that all No. 2 oil sold within the state for any purpose to have ultralow sulfur content. Gasoline emissions increased in Albany, Buffalo, and New York City with slopes higher than 7%/y reflecting the increase of registered vehicles in the area (e.g., New York City +9%, Buffalo +5%, and Albany +6% during 2007-2016)
Characterizing indoor-outdoor PM relationships using low cost monitors during two heating seasons in Rochester, New York
No full textSUMMARY
The overall goal of this project is to obtain a better understanding of community-wide indi-vidual exposures to residential wood smoke such that the impacts of wood combustion emis-sions on human health and the environment can be more accurately assessed. The study confirmed that low cost PM sensors can be utilized to provide spatially and temporally re-solved PM data. The results showed increases in PM associated with indoor combustion sources as well as daily and weekly patterns of occupancy and typical activity patterns.
1 INTRODUCTION
During the last decade, there has been a substantial rise in the use of wood for space and water heating in North America. Wood combustion is a major source of airborne PM and related pollutants during the heating season in Rochester, NY (Wang et al., 2012). Since health outcomes may be triggered by hourly PM exposures (e.g., Gardner et al., 2014), tem-porally and spatially resolved estimates of wood smoke exposure are needed to assess whether health outcomes may be impacted by this source specific PM a few hours after ex-posure.
2 METHODS
Continuous 1-minute indoor and outdoor PM and indoor CO concentrations were measured from November through April of 2015/16 and 2016/17 at 50 residences across Monroe County, near Rochester, New York (25 residences per season). Inclusion criteria for the study were homes that had wood burning appliances or homes for which the residents smelled wood smoke in the vicinity of their homes. Low cost Speck monitors (Airviz Inc., Carnegie Mellon University, Pittsburgh, PA), which use an infra-red LED-based Samyoung (South Korea) DSM501A dust sensor (size range 0.5 to 3 μm), were deployed for PM moni-toring. CO was measured using data loggers with electrochemical sensors (EL-USB-CO, Lascar Electronics, Erie, PA). During the second season, a thermocouple with a datalogger was attached to the wood burning appliance to record when the appliance was in use.
3 RESULTS AND DISCUSSION
The results of this study confirmed that wood-burning appliances increased indoor expo-sures to airborne particles in homes. Increases in wood-burning appliance temperature and indoor CO concentrations were associated with significant increases in indoor PM2.5 concen-trations. Other indoor PM sources include other combustion sources (e.g., gas stoves, can-dles) as well as non-combustions sources (e.g., cleaning). The mean indoor/outdoor (I/O) PM ratio was 1.7 for all homes, which increased to 2.5 when a combustion source was pre-sent (Figure 1).
The link between human activity patterns and PM concentrations can be seen in the daily and weekly concentration cycles (Figure 2), with higher concentrations recorded during the weekends when people are expected to be home more. The daily pattern showed clear morn-ing and evening peaks. Hourly patterns on Saturdays and Sundays showed a peak that coin-cided with expected increased human activities in the home. Because concentrations meas-ured during the study were often lower than the nominal detection limit of the Speck PM monitors, and many combustion particles are in the size range below the nominal 0.5 μm sensor lower limit of detection, the estimated PM concentrations produced by wood combus-tion sources are likely to have been underestimated in this study.
5 CONCLUSIONS
The outcome of the study provides improved estimated exposures at any given time during the heating season for these individuals. Future studies may use this approach for exposure assessment in combination with health outcomes
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Differential probability functions for investigating long-term changes in local and regional air pollution sources
No full textVariations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Using Commercially Available Low‐Cost Monitors to Estimate the Hourly Spatial Variability of Particulate Matter Concentrations across a Metropolitan Area
Get PDFIn U.S., the National Ambient Air Quality Standards (NAAQS) set the limit values for six principal “criteria” air pollutants including PM2.5. Data are primarily collected to assess the citywide air pollution concentrations for regulatory purposes. PM2.5 is measured at one or a few urban stations within major cities or in rural locations. This sparse spatial resolution is insufficient to capture the intra-urban spatial variability of air pollution that is driven by the locations and strengths of local sources, the effect of street canyons and complex terrain, and urban heat island effects. Consequently, exposure misclassifications are likely to occur when using these data for epidemiological studies. In addition, NAAQS for PM2.5 requires the attainment of annual or daily limit values. However, recent studies have reported associations between high hourly PM2.5 peaks and mortality/morbidity, particularly cardiovascular events [1]. Consequently, it is important to increase the temporal resolution to capture air pollution peaks responsible of short-term health outcomes.
The accessibility of low-cost sensing for air pollution may be a valuable resource to improve the spatial and temporal resolution of current routine monitoring networks. Low-cost monitors (LCMs) are much less expensive than scientific-grade instruments, physically smaller and lighter (generally portable), collect data with high time resolutions (from few seconds to minutes), require less maintenance, and have low power demands. However, they are not designed to meet rigid performance standards, and they produce data with much less accuracy than scientific-grade instruments. Thus, LCMs require careful calibration and post-processing of data.
Recently, we have used data collected with commercially available LCMs at multiple locations across a metropolitan area of the eastern U.S. (Rochester, NY) during two consecutive winters (2015–2016 and 2016–2017). These monitors (Speck, Airviz Inc., Pittsburgh, PA) were tested under laboratory [2] and field [3] conditions. Data were also used to predict the hourly small-scale variability of PM using sophisticated land-use regression models [4].
The results of a summer/fall sampling campaign (June to October 2017) that essentially completes our dataset to cover all the seasons over three years (2015 to 2017) will be described. Forty-nine LCMs placed in weatherproof cases were deployed outdoors at residential locations in Rochester NY, while another unit was co-located to the NYS DEC air quality monitoring site. Raw data were originally collected at 1 min time resolution. Data were handled to return robust and reliable datasets at 1 h resolution time. Instrumental biases were assessed during 3 days of field co-location with a GRIMM 1.109 aerosol spectrometer pre and post-field deployment. Multiple pairwise analyses were used to investigate the collected data, including coefficient of divergence and signed rank tests of the value distributions.
The data were affected by a large but correctable bias that was caused by the low PM concentrations typically measured in Rochester. However, this main limitation was overcome by a careful instrument calibration and validation of data prior to and after the sampling campaigns to ensure unbiased datasets. Despite the lower accuracy of data, results show that the use of these monitors provides the opportunity for successfully improving the spatial resolution of particulate pollution.
[1] Gardner, B. et al., 2014. Ambient fine particulate air pollution triggers ST-elevation myocardial infarction, but not non-ST elevation myocardial infarction: a case-crossover study. Particle and Fibre Toxicology 11(1), 1.
[2] Zikova, N., et al. 2017. Evaluation of new low-cost particle monitors for PM2.5 concentrations measurements. J. Aerosol Sci. 105, 24–34.
[3] Zikova, N., et al., 2017. Estimating hourly concentrations of PM2.5 across a metropolitan area using low-cost particle monitors. Sensors 17, 1922.
[4] Masiol, M., et al., submitted. Hourly land use regression models based on low-cost PM monitor data
Dispelling the Myths Behind First-author Citation Counts
Get PDFWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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