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.     

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.     

Emission,speciation, and evaluation of impacts of non-methane volatile organic compounds from open dump site

Surface emission from Dhapa, the only garbage disposal ground in Kolkata, is a matter of concern to the local environment and also fuels the issues of occupational and environmental health. Surface emission of the Dhapa landfill site was studied using a flux chamber measurement for nonmethane volatile organic compounds (NMVOCs). Eighteen noncarbonyl volatile organic compounds (VOCs) and 14 carbonyl VOCs, including suspected and known carcinogens, were found in appreciable concentrations. The concentrations of the target species in the flux chamber were found to be significantly higher for most of the species in summer than winter. Surface emission rate of landfill gas was estimated by using two different approaches to assess the applicability for an open landfill site. It was found that the emissions predicted using the model Land GEM version 3.02 is one to two orders less than the emission rate calculated from flux chamber measurement for the target species. Tropospheric ozone formation has a serious impact for NMVOC emission. The total ozone-forming potential (OFP) of the Dhapa dumping ground considering all target NMVOCs was estimated to be 4.9E+04 and 1.2E+05 g/day in winter and summer, respectively. Also, it was found that carbonyl VOCs play a more important role than noncarbonyl VOCs for tropospheric ozone formation. Cumulative cancer risk estimated for all the carcinogenic species was found to be 2792 for 1 million population, while the total noncancer hazard index (HI) was estimated to be 246 for the occupational exposure to different compounds from surface emission to the dump-site workers at Dhapa.

Implications:This paper describes the real-time surface emission of NMVOCs from an open municipal solid waste (MSW) dump site studied using a flux chamber. Our study findings indicate that while planning for new landfill site in tropical meteorology, real-time emission data must be considered, rather than relying on modeled data. The formation of tropospheric ozone from emitted NMVOC has also been studied. Our result shows how an open landfill site acts as a source and adds to the tropospheric ozone for the airshed of a metropolitan city.     

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.     

Particulate matter speciation profiles for light-duty gasoline vehicles in the United States

Representative profiles for particulate matter particles less than or equal to 2.5 µm (PM_2.5) are developed from the Kansas City Light-Duty Vehicle Emissions Study for use in the U.S. Environmental Protection Agency (EPA) vehicle emission model, the Motor Vehicle Emission Simulator (MOVES), and for inclusion in the EPA SPECIATE database for speciation profiles. The profiles are compatible with the inputs of current photochemical air quality models, including the Community Multiscale Air Quality Aerosol Module Version 6 (AE6). The composition of light-duty gasoline PM_2.5 emissions differs significantly between cold start and hot stabilized running emissions, and between older and newer vehicles, reflecting both impacts of aging/deterioration and changes in vehicle technology. Fleet-average PM_2.5 profiles are estimated for cold start and hot stabilized running emission processes. Fleet-average profiles are calculated to include emissions from deteriorated high-emitting vehicles that are expected to continue to contribute disproportionately to the fleet-wide PM_2.5 emissions into the future. The profiles are calculated using a weighted average of the PM_2.5 composition according to the contribution of PM_2.5 emissions from each class of vehicles in the on-road gasoline fleet in the Kansas City Metropolitan Statistical Area. The paper introduces methods to exclude insignificant measurements, correct for organic carbon positive artifact, and control for contamination from the testing infrastructure in developing speciation profiles. The uncertainty of the PM_2.5 species fraction in each profile is quantified using sampling survey analysis methods. The primary use of the profiles is to develop PM_2.5 emissions inventories for the United States, but the profiles may also be used in source apportionment, atmospheric modeling, and exposure assessment, and as a basis for light-duty gasoline emission profiles for countries with limited data.

Implications: PM_2.5 speciation profiles were developed from a large sample of light-duty gasoline vehicles tested in the Kansas City area. Separate PM_2.5 profiles represent cold start and hot stabilized running emission processes to distinguish important differences in chemical composition. Statistical analysis was used to construct profiles that represent PM_2.5 emissions from the U.S. vehicle fleet based on vehicles tested from the 2005 calendar year Kansas City metropolitan area. The profiles have been incorporated into the EPA MOVES emissions model, as well as the EPA SPECIATE database, to improve emission inventories and provide the PM_2.5 chemical characterization needed by CMAQv5.0 for atmospheric chemistry modeling.     

Consequences of increased terrestrial dissolved organic matter and temperature on bacterioplankton community composition during a Baltic Sea mesocosm experiment

Predicted increases in runoff of terrestrial dissolved organic matter (DOM) and sea surface temperatures implicate substantial changes in energy fluxes of coastal marine ecosystems. Despite marine bacteria being critical drivers of marine carbon cycling, knowledge of compositional responses within bacterioplankton communities to such disturbances is strongly limited. Using 16S rRNA gene pyrosequencing, we examined bacterioplankton population dynamics in Baltic Sea mesocosms with treatments combining terrestrial DOM enrichment and increased temperature. Among the 200 most abundant taxa, 62 % either increased or decreased in relative abundance under changed environmental conditions. For example, SAR11 and SAR86 populations proliferated in combined increased terrestrial DOM/temperature mesocosms, while the hgcI and CL500-29 clades (Actinobacteria) decreased in the same mesocosms. Bacteroidetes increased in both control mesocosms and in the combined increased terrestrial DOM/temperature mesocosms. These results indicate considerable and differential responses among distinct bacterial populations to combined climate change effects, emphasizing the potential of such effects to induce shifts in ecosystem function and carbon cycling in the future Baltic Sea.     

Nitrogen fixation by cyanobacteria stimulates production in Baltic food webs

Filamentous, nitrogen-fixing cyanobacteria form extensive summer blooms in the Baltic Sea. Their ability to fix dissolved N₂ allows cyanobacteria to circumvent the general summer nitrogen limitation, while also generating a supply of novel bioavailable nitrogen for the food web. However, the fate of the nitrogen fixed by cyanobacteria remains unresolved, as does its importance for secondary production in the Baltic Sea. Here, we synthesize recent experimental and field studies providing strong empirical evidence that cyanobacterial nitrogen is efficiently assimilated and transferred in Baltic food webs via two major pathways: directly by grazing on fresh or decaying cyanobacteria and indirectly through the uptake by other phytoplankton and microbes of bioavailable nitrogen exuded from cyanobacterial cells. This information is an essential step toward guiding nutrient management to minimize noxious blooms without overly reducing secondary production, and ultimately most probably fish production in the Baltic Sea.     

Automated data analysis to rapidly derive and communicate ecological insights from satellite-tag data: A case study of reintroduced red kites

Analysis of satellite-telemetry data mostly occurs long after it has been collected, due to the time and effort needed to collate and interpret such material. Delayed reporting reduces the usefulness of such data for nature conservation where timely information about animal movements is required. To counter this problem, we present a novel approach which combines automated analysis of satellite-telemetry data with rapid communication of insights derived from such data. A relatively simple algorithm (based on radial and angular velocity calculated from fixes) allowed instantaneous detection of excursions away from settlement areas and automated calculation of home ranges on the remaining data. Automating the detection of both excursions and home-range calculations enabled us to disseminate ecological insights from satellite-tag data instantaneously through a dedicated web portal. The automated analysis, interpretation, and communication of satellite-tag and other ecological data offer clear benefits to nature conservation research and practice.     

Limitations of recreational camera traps for wildlife management and conservation research: A practitioner’s perspective

The availability of affordable ‘recreational’ camera traps has dramatically increased over the last decade. We present survey results which show that many conservation practitioners use cheaper ‘recreational’ units for research rather than more expensive ‘professional’ equipment. We present our perspective of using two popular models of ‘recreational’ camera trap for ecological field-based studies. The models used (for >2 years) presented us with a range of practical problems at all stages of their use including deployment, operation, and data management, which collectively crippled data collection and limited opportunities for quantification of key issues arising. Our experiences demonstrate that prospective users need to have a sufficient understanding of the limitations camera trap technology poses, dimensions we communicate here. While the merits of different camera traps will be study specific, the performance of more expensive ‘professional’ models may prove more cost-effective in the long-term when using camera traps for research.     

Ecological literacy and beyond: Problem-based learning for future professionals

Ecological science contributes to solving a broad range of environmental problems. However, lack of ecological literacy in practice often limits application of this knowledge. In this paper, we highlight a critical but often overlooked demand on ecological literacy: to enable professionals of various careers to apply scientific knowledge when faced with environmental problems. Current university courses on ecology often fail to persuade students that ecological science provides important tools for environmental problem solving. We propose problem-based learning to improve the understanding of ecological science and its usefulness for real-world environmental issues that professionals in careers as diverse as engineering, public health, architecture, social sciences, or management will address. Courses should set clear learning objectives for cognitive skills they expect students to acquire. Thus, professionals in different fields will be enabled to improve environmental decision-making processes and to participate effectively in multidisciplinary work groups charged with tackling environmental issues.