Comparative statistical study of hourly precipitation determined by radar-based Stage IV and ground-based methods in the North Central United States

Detailed hourly precipitation data are required for long-range modeling of dispersion and wet deposition of particulate matter and water-soluble pollutants using the CALPUFF model. In sparsely populated areas such as the north central United States, ground-based precipitation measurement stations may be too widely spaced to offer a complete and accurate spatial representation of hourly precipitation within a modeling domain. The availability of remotely sensed precipitation data by satellite and the National Weather Service array of next-generation radars (NEXRAD) deployed nationally provide an opportunity to improve on the paucity of data for these areas. Before adopting a new method of precipitation estimation in a modeling protocol, it should be compared with the ground-based precipitation measurements, which are currently relied upon for modeling purposes. This paper presents a statistical comparison between hourly precipitation measurements for the years 2006 through 2008 at 25 ground-based stations in the north central United States and radar-based precipitation measurements available from the National Center for Environmental Predictions (NCEP) as Stage IV data at the nearest grid cell to each selected precipitation station. It was found that the statistical agreement between the two methods depends strongly on whether the ground-based hourly precipitation is measured to within 0.1 in/hr or to within 0.01 in/hr. The results of the statistical comparison indicate that it would be more accurate to use gridded Stage IV precipitation data in a gridded dispersion model for a long-range simulation, than to rely on precipitation data interpolated between widely scattered rain gauges.

Implications:

The current reliance on ground-based rain gauges for precipitation events and hourly data for modeling of dispersion and wet deposition of particulate matter and water-soluble pollutants results in potentially large discontinuity in data coverage and the need to extrapolate data between monitoring stations. The use of radar-based precipitation data, which is available for the entire continental United States and nearby areas, would resolve these data gaps and provide a complete and accurate spatial representation of hourly precipitation within a large modeling domain.     

The flux of radionuclides in flowback fluid from shale gas exploitation

This study considers the flux of radioactivity in flowback fluid from shale gas development in three areas: the Carboniferous, Bowland Shale, UK; the Silurian Shale, Poland; and the Carboniferous Barnett Shale, USA. The radioactive flux from these basins was estimated, given estimates of the number of wells developed or to be developed, the flowback volume per well and the concentration of K (potassium) and Ra (radium) in the flowback water. For comparative purposes, the range of concentration was itself considered within four scenarios for the concentration range of radioactive measured in each shale gas basin, the groundwater of the each shale gas basin, global groundwater and local surface water. The study found that (i) for the Barnett Shale and the Silurian Shale, Poland, the 1 % exceedance flux in flowback water was between seven and eight times that would be expected from local groundwater. However, for the Bowland Shale, UK, the 1 % exceedance flux (the flux that would only be expected to be exceeded 1 % of the time, i.e. a reasonable worst case scenario) in flowback water was 500 times that expected from local groundwater. (ii) In no scenario was the 1 % exceedance exposure greater than 1 mSv—the allowable annual exposure allowed for in the UK. (iii) The radioactive flux of per energy produced was lower for shale gas than for conventional oil and gas production, nuclear power production and electricity generated through burning coal.     

Indoor air quality (IAQ) assessment in a multistorey shopping mall by high-spatial-resolution monitoring of volatile organic compounds (VOC)

In order to assess indoor air quality (IAQ), two 1-week monitoring campaigns of volatile organic compounds (VOC) were performed in different areas of a multistorey shopping mall. High-spatial-resolution monitoring was conducted at 32 indoor sites located in two storehouses and in different departments of a supermarket. At the same time, VOC concentrations were monitored in the mall and parking lot area as well as outdoors. VOC were sampled at 48-h periods using diffusive samplers suitable for thermal desorption. The samples were then analyzed with gas chromatography–mass spectrometry (GC–MS). The data analysis and chromatic maps indicated that the two storehouses had the highest VOC concentrations consisting principally of terpenes. These higher TVOC concentrations could be a result of the low efficiency of the air exchange and intake systems, as well as the large quantity of articles stored in these small spaces. Instead, inside the supermarket, the food department was the most critical area for VOC concentrations. To identify potential emission sources in this department, a continuous VOC analyzer was used. The findings indicated that the highest total VOC concentrations were present during cleaning activities and that these activities were carried out frequently in the food department. The study highlights the importance of conducting both high-spatial-resolution monitoring and high-temporal-resolution monitoring. The former was able to identify critical issues in environments with a complex emission scenario while the latter was useful in interpreting the dynamics of each emission source.     

Major ionic compositions of fine particulate matter in an animal feeding operation facility and its vicinity

Animal feeding operations (AFOs) produce particulate matter (PM) and gaseous pollutants. Investigation of the chemical composition of PM_2.5 inside and in the local vicinity of AFOs can help to understand the impact of the AFO emissions on ambient secondary PM formation. This study was conducted on a commercial egg production farm in North Carolina. Samples of PM_2.5 were collected from five stations, with one located in an egg production house and the other four located in the vicinity of the farm along four wind directions. The major ions of NH₄⁺, Na⁺, K⁺, SO₄^2?, Cl^?, and NO₃^? were analyzed using ion chromatography (IC). In the house, the mostly abundant ions were SO₄^2?, Cl^?, and K⁺. At ambient stations, SO₄^2?, and NH₄⁺ were the two most abundant ions. In the house, NH₄⁺, SO₄^2?, and NO₃^? accounted for only 10% of the PM_2.5 mass; at ambient locations, NH₄⁺, SO₄^2?, and NO₃^? accounted for 36–41% of the PM_2.5 mass. In the house, NH₄⁺ had small seasonal variations indicating that gas-phase NH₃ was not the only major force driving its gas–particle partitioning. At the ambient stations, NH₄⁺ had the highest concentrations in summer. In the house, K⁺, Na⁺, and Cl^? were highly correlated with each other. In ambient locations, SO₄^2? and NH₄⁺ had a strong correlation, whereas in the house, SO₄^2? and NH₄⁺ had a very weak correlation. Ambient temperature and solar radiation were positively correlated with NH₄⁺ and SO₄^2?. This study suggests that secondary PM formation inside the animal house was not an important source of PM_2.5. In the vicinity, NH₃ emissions had greater impact on PM_2.5 formation.

ImplicationsThe chemical composition of PM_2.5 inside and in the local vicinity of AFOs showed the impact of the AFO emissions on ambient secondary PM_2.5 formation, and the fate and transport of air pollutants associated with AFOs. The results may help to manage in-house animal facility air quality, and to develop regional air quality control strategies and policies, especially in animal agriculture-concentrated areas.     

U.S. National PM2.5 Chemical Speciation Monitoring Networks—CSN and IMPROVE: Description of networks

The U.S. Environmental Protection Agency (EPA) initiated the national PM_2.5 Chemical Speciation Monitoring Network (CSN) in 2000 to support evaluation of long-term trends and to better quantify the impact of sources on particulate matter (PM) concentrations in the size range below 2.5 μm aerodynamic diameter (PM_2.5; fine particles). The network peaked at more than 260 sites in 2005. In response to the 1999 Regional Haze Rule and the need to better understand the regional transport of PM, EPA also augmented the long-existing Interagency Monitoring of Protected Visual Environments (IMPROVE) visibility monitoring network in 2000, adding nearly 100 additional IMPROVE sites in rural Class 1 Areas across the country. Both networks measure the major chemical components of PM_2.5 using historically accepted filter-based methods. Components measured by both networks include major anions, carbonaceous material, and a series of trace elements. CSN also measures ammonium and other cations directly, whereas IMPROVE estimates ammonium assuming complete neutralization of the measured sulfate and nitrate. IMPROVE also measures chloride and nitrite. In general, the field and laboratory approaches used in the two networks are similar; however, there are numerous, often subtle differences in sampling and chemical analysis methods, shipping, and quality control practices. These could potentially affect merging the two data sets when used to understand better the impact of sources on PM concentrations and the regional nature and long-range transport of PM_2.5. This paper describes, for the first time in the peer-reviewed literature, these networks as they have existed since 2000, outlines differences in field and laboratory approaches, provides a summary of the analytical parameters that address data uncertainty, and summarizes major network changes since the inception of CSN.

ImplicationsTwo long-term chemical speciation particle monitoring networks have operated simultaneously in the United States since 2001, when the EPA began regular operations of its PM_2.5 Chemical Speciation Monitoring Network (IMPROVE began in 1988). These networks use similar field sampling and analytical methods, but there are numerous, often subtle differences in equipment and methodologies that can affect the results. This paper describes these networks since 2000 (inception of CSN) and their differences, and summarizes the analytical parameters that address data uncertainty, providing researchers and policymakers with background information they may need (e.g., for 2018 PM_2.5 designation and State Implementation Plan process; McCarthy, 2013) to assess results from each network and decide how these data sets can be mutually employed for enhanced analyses. Changes in CSN and IMPROVE that have occurred over the years also are described.     

Optimization-Based Atmospheric Plume Source Identification

This work applies optimization and an Eulerian inversion approach presented by Bagtzoglou and Baun in 2005 in order to reconstruct contaminant plume time histories and to identify the likely source of atmospheric contamination using data from a real test site for the first time. Present-day distribution of an atmospheric contaminant plume as well as data points reflecting the plume history allow the reconstruction and provide the plume velocity, distribution, and probable source. The method was tested to a hypothetical case and with data from the Forest Atmosphere Transfer and Storage (FACTS) experiment in the Duke experimental forest site. In the scenarios presented herein, as well as in numerous cases tested for verification purposes, the model conserved mass, successfully located the peak of the plume, and managed to capture the motion of the plume well but underestimated the contaminant peak.     

Volatile Organic Compounds from Coal Tar and Soil Vapor Samples at MGP Sites

This study characterized organic compounds found in New York State manufactured gas plant (MGP) coal tar vapors using controlled laboratory experiments from four separate MGP sites. In addition, a limited number of deep (0.3–1.2 m above coal tar) and shallow (1.2–2.4 m above coal tar) soil vapor samples were collected above the in situ coal tar source at three of these sites. A total of 29 compounds were consistently detected in the laboratory-generated coal tar vapors at 50°C, whereas 24 compounds were detected at 10°C. The compounds detected in the field sample results were inconsistent with the compounds found in the laboratory-generated samples. Concentrations of compounds in the shallow soil vapor sample were either non-detectable or substantially lower than those found in deeper samples, suggesting attenuation in the vadose zone. Laboratory-generated data at 50°C compared the (% non-aromatic)/(% aromatic) ratio and indicated that this ratio may provide good discrimination between coal tar vapor and common petroleum distillates.