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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)
Differential probability functions for investigating long-term changes in local and regional air pollution sources
No full textUsing 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
Long-term trends of ultrafine and fine particle number concentrations in New York State: Apportioning between emissions and dispersion
No full textIn the past several decades, a variety of efforts have been made in the United States to improve air quality, and ambient particulate matter (PM) concentrations have been used as a metric to evaluate the efficacy of environmental policies. However, ambient PM concentrations result from a combination of source emission rates and meteorological conditions, which also change over time. Dispersion normalization was recently developed to reduce the influence of atmospheric dispersion and proved an effective approach that enhanced diel/seasonal patterns and thus provides improved source apportionment results for speciated PM mass and particle number concentration (PNC) measurements. In this work, dispersion normalization was incorporated in long-term trend analysis of 11–500 nm PNCs derived from particle number size distributions (PNSDs) measured in Rochester, NY from 2005 to 2019. Before dispersion normalization, a consistent reduction was observed across the measured size range during 2005–2012, while after 2012, the decreasing trends slowed down for accumulation mode PNCs (100–500 nm) and reversed for ultrafine particles (UFPs, 11–100 nm). Through dispersion normalization, we showed that these changes were driven by both emission rates and dispersion. Thus, it is important for future studies to assess the effects of the changing meteorological conditions when evaluating policy effectiveness on controlling PM concentrations. Before and after dispersion normalization, an evident increase in nucleation mode particles was observed during 2015–2019. This increase was possibly enabled by a cleaner atmosphere and will pose new challenges for future source apportionment and accountability studies
Estimating hourly exposure to residential wood combustion for human health
No full textDuring the last decade, there has been a substantial rise in the use of wood for space and water heating in North America, in addition to recreational burning. While there are national, state and regional programs to improve efficiency and reduce emissions from wood burning appliances, wood combustion remains a major source of airborne particulate matter (PM) and related pollutants during the heating season. While current regulatory air monitoring for PM2.5 provides daily measurements, with one monitoring site representing a relatively large area, health outcomes may be triggered by hourly pollutant exposures. For example, acute myocardial infarctions (MI), were found to be triggered within hours of short term increases in ambient PM2.5 concentrations (Gardner et al., 2014). Thus, more temporally 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 exposure, rather than after a few days or weeks.
For this study, continuous 1-minute indoor and outdoor PM and indoor carbon monoxide (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 that homes had wood burning appliances or were located in ‘high wood smoke’ areas of Monroe County. Although wood combustion in most Monroe County residences is recreational only, we found that wood smoke can represent up to 30% of the winter-time PM2.5 concentrations there (Wang et al., 2012a,b).
Results from the first heating season validate the importance of including indoor exposure to combustion appliance emissions when assessing cumulative inhalation exposure to wood smoke. A regular daily cycle of PM was observed at all homes, with peaks associated with human activity, cooking, and wood burning appliance use. Indoor/outdoor PM concentration ratios were significantly higher when the carbon monoxide measurement indicated the presence of a combustion source. Most of the sites showed clear diurnal patterns with higher PM concentrations and indoor/outdoor PM concentration ratios in the late afternoon and evening hours.
Monitoring data were used as input for a land use regression model to predict hourly ambient PM2.5 concentrations across the region. Raster surfaces (spatial resolution 10 x 10 m) were developed for a series of predictors, including the number of bedrooms, fireplaces, and kitchens, as well as the property value, year the property was built, nearby road type and road traffic densities, railways, elevation, and density of various land cover data features. In general, the relationships between PM concentrations and the predictors were moderate and results were similar to a previous study predicting 24-h concentrations (Su et al., 2015).
References:
Gardner B, Ling F, Hopke PK, Frampton MW, Utell MJ, Zareba W, Cameron SJ, Chalupa D, Kane C, Ku-landhaisamy S, Topf M, Rich DQ. 2014. Ambient fine particulate air pollution triggers ST-elevation myocardial infarction, but not non-ST-elevation myocardial infarction. Particle & Fibre Toxicology, 11, pp. 1.
Su JG, Hopke PK, Tian Y, Baldwin N, Thurston SW, Evans K and Rich DQ. 2015. Modeling particulate matter concentrations measured through mobile monitoring in a deletion/substitution/addition approach. Atmospheric Environment, 122, pp.477-483.
Wang Y, Hopke PK, Rattigan OV, Chalupa DC and Utell MJ. (2012a) Multiple-year black carbon measurements and source apportionment using delta-C in Rochester, New York. J Air Waste Manag Assoc. 62:880-887.
Wang Y, Hopke PK, Xia X, Rattigan OV, Chalupa DC and Utell MJ. (2012b) Source apportionment of airborne particulate matter using inorganic and organic species as tracers. Atmospheric Environment. 55:525-532.
Acknowledgements:
This work was supported by the New York State Energy Research and Development Authority (NYSERDA) under agreement 63040
Residential PM Measured in 50 Homes Using Low‐cost Monitors over Two Heating Seasons in Rochester, NY
No full textHeating appliances using wood and wood products for combustion are a major source of airborne PM and related pollutants during the heating season in Rochester, NY (Wang et al., 2012). Although most regulatory short-term PM monitoring is based on 24-h integrated measurements in relatively few locations, health outcomes may be triggered by increases in PM concentrations in the previous few hours (e.g., Gardner et al., 2014), and PM concentrations can vary greatly across an urban area (Zikova et al., 2017a). Temporally and spatially resolved estimates of PM exposure to wood smoke and other sources are needed to understand how health outcomes are associated with increases in PM concentration a few hours later
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
Variations 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
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