Aspects and prospects of algal carbon capture and sequestration in ecosystems: a review

Long-term storage of carbon dioxide (CO₂) and other forms of carbon in non-atmospheric reservoirs is called carbon sequestration. Selective anthropogenic enrichment of the atmospheric carbon pool is causing dire environmental problems, thereby necessitating remediation by mitigation. Algae possess efficient carbon concentrating mechanisms and consequently high photosynthetic rates which make them suitable candidates for biosequestration of CO₂. Globally, nearly half of the atmospheric oxygen is generated by algal photosynthesis despite the fact that algae account for less than 1% of photosynthetic biomass. In water bodies, algae are responsible for creating the ‘biological pump’ that transports carbon from the upper sunlit waters to the depth below. A diverse array of photoautotrophs ranging from prokaryotic cyanobacteria to eukaryotic algae such as Chlorophytes, and even protists like euglenoids, contribute to this ‘biological pump’. It operates in a variety of aquatic ecosystems ranging from small freshwater ponds to the oceans where it has been most extensively studied. Two separate but intricately linked processes constitute this ‘biological pump’, viz. the ‘organic carbon pump’ and the ‘calcium carbonate pump’. The present review discusses the natural CO₂ sequestration processes carried out by algae and cyanobacteria in their native ecosystems.     

Future year ozone source attribution modeling studies for the eastern and western United States

Three modeling approaches, the U.S. Environmental Protection Agency’s (EPA) Community Multiscale Air Quality (CMAQ) zero-out, the Comprehensive Air quality Model with extensions (CAMx) zero-out, and the CAMx probing tools ozone source apportionment tool (OSAT), were used to project the contributions of various source categories to future year design values for summer 8-hr average ozone concentrations at selected U.S. monitors. The CMAQ and CAMx zero-out or brute-force approaches predicted generally similar contributions for most of the source categories, with some small differences. One of the important findings from this study was that both the CMAQ and CAMx zero-out approaches tended to apportion a larger contribution to the “other” category than the OSAT approach. For the OSAT approach, this category is the difference between the total emissions and the sum of the tracked emissions and consists of non-U.S. emissions. For the zero-out approach, it also includes the effects of nonlinearities in the system because the sum of the sensitivities of all sources is not necessarily equal to the sum of their contributions in a nonperturbed environment. The study illustrates the strengths and weaknesses of source apportionment approaches, such as OSAT, and source sensitivity approaches, such as zero-out. The OSAT approach is suitable for studying source contributions, whereas the zero-out approach is suitable for studying response to emission changes. Future year design values of summer 8-hr average ozone concentrations were projected to decrease at all the selected monitors for all the simulations in each city, except at the downtown Los Angeles monitor. Both the CMAQ and CAMx results showed all modeled locations project attainment in 2018 and 2030 to the current National Ambient Air Quality Standards (NAAQS) level of 75 ppb, except the selected Los Angeles monitor in 2018 and the selected San Bernardino monitor in 2018 and 2030.

Implications:This study illustrates the strengths and weaknesses of three modeling approaches, CMAQ zero-out, CAMx zero-out, and OSAT to project contributions of various source categories to future year design values for summer 8-hr average ozone concentrations at selected U.S. monitors. The OSAT approach is suitable for studying source contributions, whereas the zero-out approach is suitable for studying response to emission changes. Future year design values of summer 8-hr average ozone concentrations were projected to decrease, except at the downtown Los Angeles monitor. Comparing projections with the current NAAQS (75 ppb) show attainment everywhere, except two locations in 2018 and one location in 2030.     

Implementation and application of sub-grid-scale plume treatment in the latest version of EPA’s third-generation air quality model,CMAQ 5.01

The Community Multiscale Air Quality (CMAQ) modeling system Version 5.0 (CMAQv5.0) was released by the U.S. Environmental Protection Agency (EPA) in February 2012, with an interim release (v5.01) in July 2012. Because CMAQ is a community model, the EPA encourages the development of proven alternative science treatments by external scientists and developers that can be incorporated as part of an official CMAQ release. This paper describes the implementation, evaluation, and testing of a plume-in-grid (PinG) module in CMAQ 5.01. The PinG module, also referred to as Advanced Plume Treatment (APT), provides the capability of resolving sub-grid-scale processes, such as the transport and chemistry of point-source plumes, in a grid model. The new PinG module in CMAQ 5.01 is applied and evaluated for two 15-day summer and winter periods in 2005 to the eastern United States, and the results are compared with those from the base CMAQ 5.01. Eighteen large point sources of NOx in the eastern United States were selected for explicit plume treatment with APT in the PinG simulation. The results show that overall model performance is negligibly affected when PinG treatment is included. However, the PinG model predicts significantly different contributions of the 18 sources to pollutant concentrations and deposition downwind of the point sources compared to the base model.

Implications: This study describes the incorporation of a plume-in-grid (PinG) capability within the latest version of the EPA grid model, CMAQ. The capability addresses the inherent limitation of the grid model to resolve processes, such as the evolution of point-source plumes, which occur at scales much smaller than the grid resolution. The base grid model and the PinG version predict different source contributions to ozone and PM_2.5 concentrations that need to be considered when source attribution studies are conducted to determine the impacts of large point sources on downwind concentrations and deposition of primary and secondary pollutants.     

Simulation of Stack Plume Opacity

ABSTRACT

The visual impact of primary particles emitted from stacks is regulated according to stack opacity criteria. In-stack monitoring of the flue gas opacity allows plant operators to ensure that the plant meets U.S. Environmental Protection Agency opacity regulations. However, the emission of condensable gases such as SO₃ (that hydrolyzes to H₂SO₄), HCl, and NH₃, which may lead to particle formation after their release from the stack, makes the prediction of stack plume opacity more difficult.

We present here a computer simulation model that calculates the opacity due to both primary particles emitted from the stack and secondary particles formed in the atmosphere after the release of condensable gases from the stack. A comprehensive treatment of the plume rise due to buoyancy and momentum is used to calculate the location at which the condensed water plume has evaporated (i.e., where opacity regulations apply).

Conversion of H₂SO₄ to particulate sulfate occurs through nucleation and condensation on primary particles. A thermodynamic aerosol equilibrium model is used to calculate the amount of ammonium, chloride, and water present in the particulate phase with the condensed sulfate. The model calculates the stack plume opacity due to both primary and secondary particles. Examples of model simulations are presented for three scenarios that differ by the emission control equipment installed at the power plant: (1) electrostatic precipitators (ESP), (2) ESP and flue gas desulfurization, and (3) ESP and selective catalytic reduction. The calculated opacity is most sensitive to the primary particulate emissions. For the conditions considered here, SO₃ emissions showed only a small effect, except if one assumes that most H₂SO₄ condenses on primary particles. Condensation of NH₄Cl occurs only at high NH₃ emission rates (about 25 ppm stack concentration).     

Hg Vapor Emission from Broken Compact Fluorescent Lamps (CFLs) in an Acrylic Chamber

The United States Environmental Protection Agency/Environmental Response Team (US EPA/ERT), in collaboration with St. John's College, Dr. B. R. Ambedkar University, Agra, India, is conducting a study to determine Hg vapor emission rates resulting from broken compact fluorescent lamps (CFLs) in a residential setting. The overall objectives of the study are to determine Hg vapor emission data and provide homeowners with cleanup procedures and disposal options for broken CFLs. Most of the currently available CFLs in the US market are manufactured in China for US companies. Several different types of CFLs were purchased from local stores and their Hg content was determined. Based on previous studies, such as the 2011 study by Singhvi and colleagues, five popular spiral CFLs were selected for emission studies in an acrylic chamber. This study found that Hg vapor emissions from CFLs may be significantly greater than those from beads of liquid Hg with weights comparable to the Hg content of the CFLs. The average 24-hour Hg loss into the atmosphere from CFLs broken on a plastic surface ranged from 0.6% to 22% of the bulb content, while that for CFLs broken on carpet ranged from 2.6% to 28%. Projections for a 12 foot × 9.33 foot × 8 foot (25.4 m³) room based on the chamber measurements in this study indicate that CFL breakage in some household settings may produce 24-hour Hg concentrations above the 2000 Agency for Toxic Substances and Disease Registry (ATSDR) minimum risk level (MRL) of 0.2 μg/m³, for typical air exchange rates. This study also indicates that Hg emission may not be proportional to exposed surface area based on experiments using liquid Hg with different surface areas.     

Source apportionment: findings from the U.S. Supersites Program

Receptor models are used to identify and quantify source contributions to particulate matter and volatile organic compounds based on measurements of many chemical components at receptor sites. These components are selected based on their consistent appearance in some source types and their absence in others. UNMIX, positive matrix factorization (PMF), and effective variance are different solutions to the chemical mass balance (CMB) receptor model equations and are implemented on available software. In their more general form, the CMB equations allow spatial, temporal, transport, and particle size profiles to be combined with chemical source profiles for improved source resolution. Although UNMIX and PMF do not use source profiles explicitly as input data, they still require measured profiles to justify their derived source factors. The U.S. Supersites Program provided advanced datasets to apply these CMB solutions in different urban areas. Still lacking are better characterization of source emissions, new methods to estimate profile changes between source and receptor, and systematic sensitivity tests of deviations from receptor model assumptions.     

Evaluation of the community multiscale air quality (CMAQ) model version 4.5: Sensitivities impacting model performance; Part II—particulate matter

This paper is Part II in a pair of papers that examines the results of the Community Multiscale Air Quality (CMAQ) model version 4.5 (v4.5) and discusses the potential explanations for the model performance characteristics seen. The focus of this paper is on fine particulate matter (PM_2.5) and its chemical composition. Improvements made to the dry deposition velocity and cloud treatment in CMAQ v4.5 addressing compensating errors in 36-km simulations improved particulate sulfate (SO₄²⁻) predictions. Large overpredictions of particulate nitrate (NO₃⁻) and ammonium (NH₄⁺) in the fall are likely due to a gross overestimation of seasonal ammonia (NH₃) emissions. Carbonaceous aerosol concentrations are substantially underpredicted during the late spring and summer months, most likely due, in part, to a lack of some secondary organic aerosol (SOA) formation pathways in the model. Comparisons of CMAQ PM_2.5 predictions with observed PM_2.5 mass show mixed seasonal performance. Spring and summer show the best overall performance, while performance in the winter and fall is relatively poor, with significant overpredictions of total PM_2.5 mass in those seasons. The model biases in PM_2.5 mass cannot be explained by summing the model biases for the major inorganic ions plus carbon. Errors in the prediction of other unspeciated PM_2.5 (PM_Other) are largely to blame for the errors in total PM_2.5 mass predictions, and efforts are underway to identify the cause of these errors.     

Multi-drug resistance,integron and transposon-mediated gene transfer in heterotrophic bacteria from Penaeus vannamei and its culture environment

Environmental Science and Pollution Research - Multi-drug resistance (MDR) in bacteria is regarded as an emerging pollutant in different food production avenues including aquaculture. One hundred...