2,348 research outputs found
Air pollution at Rochester, NY: Long-term trends and multivariate analysis of upwind SO2 source impacts
No full textThere have been many changes in the air pollutant sources in the northeastern United States since 2001. To assess the effect of these changes, trend analyses of the monthly average values were performed on PM2.5 and its components including major ions, elemental carbon (EC), organic carbon (OC), and gaseous pollutant concentrations measured between 2001 (in some cases 1999) and 2015 at the NYS Department of Environmental Conservation sites in Rochester, NY. Mann-Kendall regression with Sen's slope was applied to estimate the trends and seasonality. Using piecewise regression, significant reductions in the air pollution of Rochester area were observed between 2008 and 2010 when a 260 MW coal-fired power plant was decommissioned, new heavy-duty diesel trucks had to be equipped with catalytic regenerator traps, and the economic recession that began in 2008 reduced traffic and other activities. The monthly average PM2.5 mass showed a downward trend (− 5 μg/m3; − 41%) in Rochester between 2001 and 2015. This change is largely due to reductions in particulate sulfate that showed a 65% decrease. The sulfate concentrations were compared to changes in SO2 emissions in seventeen upwind source domains, and other systematic changes by multivariate linear regression. Selectivity ratio obtained from target projection discriminated the most important source domains that are SO2 emissions from Georgia for winter, North Carolina for transition (spring and fall) and Ohio along with other influences for summer. North Carolina and Michigan were identified as the main sources for entire period. These observations suggest that any further reductions in the specified regional SO2 emissions would result in a proportional decrease in sulfate in Rochester
Performance Enhancements to a High Efficiency Wood Pellet Boiler: A Modified Combustion System-Dome
No full textMultivariate analysis of upwind SO2 emission influences on air pollution in Rochester, NY
No full textA long-term source apportionment of PM2.5 in New York State during 2005–2016
No full textThe development and implementation of effective policies for controlling PM2.5 mass concentrations and protecting human health depend upon the identification and apportionment of its sources. In this study, the PM2.5 sources affecting 6 urban and 2 rural sites across New York State during the period 2005–2016 were determined. The extracted profiles were compared to identify state-wide common profiles. The source contributions provide detailed, long-term quantification of the emission sources across the state during the investigated period (2005–2016). Seven factors were common to all sites: secondary sulfate, secondary nitrate, spark-ignition emissions, diesel emissions, road dust, biomass burning, and pyrolyzed organic (OP) rich. The largest contributors were secondary sulfate, secondary nitrate, spark-ignition (gasoline), diesel, and OP-rich. Secondary sulfate concentrations ranged from 2.3 μg m−3 at Whiteface to 3.2 μg m−3 at Buffalo and the Bronx. The highest secondary sulfate fractional contributions were found at the rural sites (∼46% of PM2.5 mass) also showed the highest OP-rich contributions (∼19%). Secondary nitrate showed the highest concentrations at the urban sites representing ∼17% of PM2.5 mass (1.6 ± 0.3 μg m−3 on average). Urban sites also showed the highest average spark-ignition concentrations (1.7 ± 0.2 μg m−3, ∼18%) and diesel emissions (1.0 ± 0.2 μg m−3, ∼10%). During this period, secondary sulfate concentrations declined likely related to the implementation of mitigation strategies for controlling SO2 emissions and the changing economics of electricity generation. Similarly, diesel and secondary nitrate showed decreases in concentrations likely associated with the introduction of emissions controls and improved quality fuels for heavy-duty diesel on-road trucks and buses. Spark-ignition concentrations showed an increase across the state during 2014–2016 associated with the increase of registered vehicles in New York State
Boilers Emissions Under Different Stack Configurations at a School in Saranac Lake, NY
No full textA 1.7 MMBTU wood pellet boiler was installed in a container outside the Petrova Elementary School, Saranac Lake to provide heat to the building and reduce the dependence on fuel oil. The exhaust stack was initially 25’ high, i.e. less than the school building height and the effluent stream could then enter through the building air intakes. Computational fluid dynamics modeling was performed to assess the emission impacts for a taller stack. Results showed if the stack height was raised to 45’ (10’ above the roof), the plume would loft over the building and avoid the air intakes. However, the USEPA best practices guidelines suggested the stack should be 2.5 times the height of the structure.
From December 2015, a sampling campaign was conducted to evaluate if the increased stack height was sufficient to reduce the air pollutant concentrations at the roof top and, thus, if the stack configuration was sufficient to avoid boiler exhausts be drawn into the school. CO, black carbon and PM were measured on the roof of the school. Weather and wind parameters were also measured. Air pollution data were recorded in periods without boiler emissions and then with both the short and taller stacks in place. A series of chemometric tools were thus applied for: (i) comparing the levels of pollutants during different stack configurations; (ii) investigating the relationships among pollutants and boiler operation modes; (iii) detect possible effects of meteorology on the levels of air pollutants. The results of this evaluation will be presented
Long-term trends (2005–2016) of source apportioned PM2.5 across New York State
No full textThe United States has experienced substantial air pollutant emissions reductions in the last two decades. Among others, emissions produced by electricity generation plants and industries were significantly lowered. Ultralow (<15 ppm) sulfur fuels were introduced for road vehicles, nonroad, rail, and maritime transport. New heavy-duty diesel trucks have been equipped with particle traps and NOx controls. Residual oil (No. 6) for space heating and for any other purpose was replaced with cleaner No. 2 and No. 4 oils. Chemical speciation of PM2.5 has been measured since 2005 at eight sites across the New York State. A prior study has identified and apportioned the major sources of PM2.5 across the State using receptor modelling (positive matrix factorization). This present study aims to investigate the long-term trends of those source-apportioned PM2.5 mass contributions from 2005 to 2016 at the eight sites: two rural sites (Pinnacle and Whiteface), three medium sized cities (Buffalo, Albany, Rochester), and three sites in the New York City metropolitan area (Bronx, Manhattan and Queens). Negative trends from 2005 to 2016 were detected across the state for secondary sulfate (from −0.19 μg/m3/y in Rochester to −0.36 μg/m3/y at BRO and QUE) and secondary nitrate (from −0.02 μg/m3/y at the rural sites to approximately −0.2 μg/m3/y at BRO and MAN). Spark-ignition vehicles were the only source type experiencing upward annual trends at all urban sites with slopes ranging from 0.02 μg/m3/y (ROC, not statistically significant) to ∼0.2 μg/m3/y (Albany, Bronx, Manhattan). Other sources exhibited different trends among the sites. The relationships of source contributions with emissions inventories were explored with regression analysis. A new trajectory model, differential concentration-weighted trajectories (DCWT), was used to examine spatial changes in sources of secondary aerosol affecting the rural sites
Differential Probability Functions for Investigating Long-Term Changes in Local and Regional Air Pollution Sources
No full textConditional probability functions are commonly used for source identification purposes in air pollution studies. CBPF (conditional bivariate probability function) categorizes the probability of high concentrations being observed at a location by wind direction/speed and investigate the directionality of local sources. PSCF (potential source contribution function), a trajectory-ensemble method, identifies the source regions most likely to be associated with high measured concentrations. However, these techniques do not allow the direct identification of areas where changes in emissions have occurred. This study presents an extension of conditional probability methods in which the differences between conditional probability values for temporally different sets of data can be used to explore changes in emissions from source locations. The differential CBPF and differential PSCF were tested using a long-term series of air quality data (12 years; 2005/2016) collected in Rochester, NY. The probability functions were computed for each of 4 periods that represent known changes in emissions. Correlation analyses were also performed on the results to find pollutants undergoing similar changes in local and regional sources. The differential probability functions permitted the identification of major changes in local and regional emission location. In Rochester, changes in local air pollution were related to the shutdown of a large coal power plant (SO2) and to the abatement measures applied to road and off-road traffic (primary pollutants). The concurrent effects of these changes in local emissions were also linked to reduced concentrations of nucleation mode particles. Changes in regional source areas were related to the decreases in secondary inorganic aerosol and organic carbon. The differential probabilities for sulfate, nitrate, and organic aerosol were consistent with differences in the available National Emission Inventory annual emission values. Changes in the source areas of black carbon and PM2.5 mass concentrations were highly correlated
Spatial-temporal variations of summertime ozone concentrations across a metropolitan area using a network of low-cost monitors to develop 24 hourly land-use regression models
No full textTen relatively-low-cost ozone monitors (Aeroqual Series 500 with OZL ozone sensor) were deployed to assess the spatial and temporal variability of ambient ozone concentrations across residential areas in the Monroe County, New York from June to October 2017. The monitors were calibrated in the laboratory and then deployed to a local air quality monitoring site where they were compared to the federal equivalent method values. These correlations were used to correct the measured ozone concentrations. The values were also used to develop hourly land use regression models (LUR) based on the deletion/substitution/addition (D/S/A) algorithm that can be used to predict the spatial and temporal concentrations of ozone at any hour of a summertime day and given location in Monroe County. Adjusted R2 values were high (average 0.83) with the highest adjusted R2 for the model between 8 and 9 AM (i.e. 1–2 h after the peak of primary emissions during the morning rush hours). Spatial predictors with the highest positive effects on ozone estimates were high intensity developed areas, low and medium intensity developed areas, forests + shrubs, average elevation, Interstate + highways, and the annual average vehicular daily traffic counts. These predictors are associated with potential emissions of anthropogenic and biogenic precursors. Maps developed from the models exhibited reasonable spatial and temporal patterns, with low ozone concentrations overnight and the highest concentrations between 11 AM and 5 PM. The adjusted R2 between the model predictions and the measured values varied between 0.79 and 0.87 (mean = 0.83). The combined use of the network of low-cost monitors and LUR modeling provide useful estimates of intraurban ozone variability and exposure estimates that will be used in future epidemiological studies
Changes in PM2.5 Sources across New York State during 2005-2015
No full textThe highest mass concentrations of airborne fine particulate
matter (PM2.5) and PM-bound sulfate of North America are
recorded over the Eastern US, which also exhibits high
concentrations of ammonium and elemental carbon. However,
the emission scenario has significantly changed during the last
decades (e.g., US standards for vehicle emissions, the
implementation of the highway diesel fuel sulfur program, use
of heating oil containing less than 15 ppm sulfur).
This study aims to detect the trends of the most impacting
PM2.5 sources across the state of New York in the last decade
(2005-2015). PM2.5 chemical speciation data were retrieved
from the US-EPA Chemical Speciation Network (CSN,
https://aqs.epa.gov/api). PM2.5 samples were collected in 8 sites
scattered over the State and characterized by different emission
scenarios: 6 urban (Albany, Buffalo, Rochester, New York -
Bronx, New York-Division St, New York - Queens) and 2 rural
(Pinnacle and Whiteface) background sites.
Samples were analyzed for PM2.5 mass, water-soluble inorganic
ions (NH4
+, K+, Na+, NO3
-, SO4
2-), elemental (EC) and organic
(OC) carbon and elements with atomic number ≥1. The final
dataset was split in pre-IMPROVE and post-IMPROVE OC/EC
analysis.
EPA PMF 5.0 was applied to identify and apportion the most
impacting sources on PM2.5 over the sites. Subsequently, the
Theil-Sen method coupled with the non-parametric Mann-
Kendall approach has been used to analyze the inter-annual
trends of extracted PM sources.
For example, 9 PM2.5 sources were extracted for Queens all
over the period: ammonium sulfate (accounting for 34% of
PM2.5mass), ammonium nitrate (17%), gasoline (15%), diesel
(10%), biomass burning (6%), aged sea salt (5%), road dust
(4%), residual oil (3%) and fresh sea salt (2%). Among the
main PM2.5 contributors, a significant decrease was observed
for ammonium sulfate (-7% y-1) and ammonium nitrate (-6% y-
1) whereas the emissions associated with gasoline vehicles
increased (+6% y-1)
Regional Nucleation Events and Sources of Submicron Particles in Rochester (NY)
No full textExtensive measurements of particle number concentration (PNC) and particle size distribution (PNSD) have been performed in Rochester (NY) since 2001. These long-term data allow assessment of past and current mitigation strategies for air pollution in the Northeastern US. This study investigates the three most recent years of data (2014/16).
Results show an average of 4.3·103 particles/cm3, of which 1.4·103, 2.3·103, and 0.7·103 particles cm3 were classified as nucleation (14-30 nm), Aitken nuclei (30-100 nm) and accumulation (100-470 nm) ranges, respectively. Annually, total PNC show two maxima, one on February and one during summer (May to September), while the daily pattern of PNC show two peaks related to the traffic rush hours (one in the early morning, one in the late afternoon-evening). Nucleation sized particles also show an evident increase during daytime, which is broadly comparable with the nucleation events driven by photochemical transformations.
Positive matrix factorization (PMF) was applied to identify and quantify the major airborne particle sources. Data were separately analyzed for summer, winter, and transition periods. For each period, 5 to 7 factors were apportioned and identified (nucleation, traffic, domestic and residential heating, secondary aerosol and ozone-rich aerosol). The application of PMF post-processing tools was useful to: (i) study the patterns of sources; (ii) depict the role of atmospheric photochemical processes; (iii) examine the locations of potential local sources by mean of conditional bivariate probability function analysis and (iv) investigate the role of regional transport of air masses to the concentrations of resolved sources. Finally, the contour plots of SMPS data were examined: an algorithm was applied to identify potential nucleation events and distinguish them between traffic nucleation events and regional photochemical nucleation events
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