Demonstrating Attainment of the Air Quality Standards: Integration of Observations and Model Predictions into the Probabilistic Framework

ABSTRACT

This paper introduces an integrated observational-modeling approach to transform the deterministic nature of attainment demonstrations of the National Ambient Air Quality Standard (NAAQS) into the probabilistic framework. While the methods presented here can be used to address any air quality standard that is based on extreme values, this paper focuses on the application to the 1-hr and 8-hr NAAQS for ozone. Extreme value statistics and resampling techniques are applied to estimate the probability of exceeding the NAAQS for both 1-hr and 8-hr ozone concentrations. Within the integrated observation-modeling analysis approach, we show that the model-to-model differences in the predicted responses to emission reductions are smaller than the model-to-model differences in predicted absolute ozone concentrations. We illustrate that the emission reductions stemming from a real-world emission control strategy would substantially reduce the probability of exceeding the NAAQS over a large portion of the eastern United States, especially for the 8-hr average ozone concentrations.     

Current Status of Air Quality Models for Particulate Matter

ABSTRACT

The current status of the mathematical modeling of atmospheric particulate matter (PM) is reviewed in this paper. Simulating PM requires treating various processes, including the formation of condensable species, the gas/ particle partitioning of condensable compounds, and in some cases, the evolution of the particle size distribution. The algorithms available to simulate these processes are reviewed and discussed. Eleven 3-dimensional (3-D) Eulerian air quality models for PM are reviewed in terms of their formulation and past applications. Results of past performance evaluations of 3-D Eulerian PM models are presented. Currently, 24-hr average PM_2.5 concentrations appear to be predicted within 50% for urban-scale domains. However, there are compensating errors among individual particulate species. The lowest errors tend to be associated with SO₄ ^2-, while NO₃ ^-, black carbon (BC), and organic carbon (OC) typically show larger errors due to uncertainties in emissions inventories and the prediction of the secondary OC fraction. Further improvements and performance evaluations are recommended.     

Application and Evaluation of Two Air Quality Models for Particulate Matter for a Southeastern U.S. Episode

Abstract

The Models-3 Community Multiscale Air Quality (CMAQ) Modeling System and the Particulate Matter Comprehensive Air Quality Model with extensions (PMCAMx) were applied to simulate the period June 29–July 10, 1999, of the Southern Oxidants Study episode with two nested horizontal grid sizes: a coarse resolution of 32 km and a fine resolution of 8 km. The predicted spatial variations of ozone (O₃), particulate matter with an aerodynamic diameter less than or equal to 2.5 μm (PM_2.5), and particulate matter with an aerodynamic diameter less than or equal to 10 μm (PM₁₀) by both models are similar in rural areas but differ from one another significantly over some urban/suburban areas in the eastern and southern United States, where PMCAMx tends to predict higher values of O₃ and PM than CMAQ. Both models tend to predict O₃ values that are higher than those observed. For observed O₃ values above 60 ppb, O₃ performance meets the U.S. Environmental Protection Agency's criteria for CMAQ with both grids and for PMCAMx with the fine grid only. It becomes unsatisfactory for PMCAMx and marginally satisfactory for CMAQ for observed O₃ values above 40 ppb.

Both models predict similar amounts of sulfate (SO₄ ^2?) and organic matter, and both predict SO₄ ^2? to be the largest contributor to PM_2.5. PMCAMx generally predicts higher amounts of ammonium (NH₄ ⁺), nitrate (NO₃ ^?), and black carbon (BC) than does CMAQ. PM performance for CMAQ is generally consistent with that of other PM models, whereas PMCAMx predicts higher concentrations of NO₃ ^?,NH₄ ⁺, and BC than observed, which degrades its performance. For PM₁₀ and PM_2.5 predictions over the southeastern U.S. domain, the ranges of mean normalized gross errors (MNGEs) and mean normalized bias are 37–43% and –33–4% for CMAQ and 50–59% and 7–30% for PMCAMx. Both models predict the largest MNGEs for NO₃ ^? (98–104% for CMAQ, 138–338% for PMCAMx). The inaccurate NO₃ ^? predictions by both models may be caused by the inaccuracies in the ammonia emission inventory and the uncertainties in the gas/particle partitioning under some conditions. In addition to these uncertainties, the significant PM overpredictions by PMCAMx may be attributed to the lack of wet removal for PM and a likely underprediction in the vertical mixing during the daytime.     

Modeling Atmospheric Mercury Deposition in the Vicinity of Power Plants

Abstract

Two mathematical models of the atmospheric fate and transport of mercury (Hg), an Eulerian grid–based model and a Gaussian plume model, are used to calculate the atmospheric deposition of Hg in the vicinity (i.e., within 50 km) of five coal–fired power plants. The former is applied using two different horizontal resolutions: coarse (84 km) and fine (16.7 km). More than 96% of the power plant Hg emissions are calculated with the plume model to be transported beyond 50 km from the plants. The grid–based model predicts a lower fraction to be transported beyond 50 km: >91% with a coarse resolution and >95% with a fine resolution. The contribution of the power plant emissions to total Hg deposition within a radius of 50 km from the plants is calculated to be <8% with the plume model, <14% with the Eulerian model with a coarse resolution, and <10% with the Eulerian model with a fine resolution. The Eulerian grid–based model predicts greater local impacts than the plume model because of artificially enhanced vertical dispersion; the former predicts about twice as much Hg deposition as the latter when the area considered is commensurate with the resolution of the grid–based model. If one compares the local impacts for an area that is significantly less than the grid–based model resolution, then the grid–based model may predict lower local deposition than the plume model, because two compensating errors affect the results obtained with the grid–based model: initial dilution of the power plant emissions within one or more grid cells and enhanced vertical mixing to the ground.     

Crushed concrete as a phosphate binding material: a potential new management tool

To avoid eutrophication of receiving waters, effective methods to remove P in urban and agricultural runoff are needed. Crushed concrete may be an effective filter material to remove dissolved and particulate P. Five types of crushed concrete were tested in the laboratory to evaluate the retention capacity of dissolved P. All types removed P very effectively (5.1-19.6 g P kg(-1) concrete), while the possible release of bound P varied between 0.4 and 4.6%. The retention rate was positively related to a decreasing concrete grain size due to an increasing surface area for binding. The P retention was also related to a marked increase in pH (up to pH 12), and the highest retention was observed when pH was high. Under these circumstances, column experiments showed outlet P concentrations <0.0075 mg P L(-1). Furthermore, experiments revealed that release of heavy metals is of no importance for the treated water. We demonstrate that crushed concrete can be an effective tool to remove P in urban and agricultural runoff as filter material in sedimentation/infiltration ponds provided that pH in the treated water is neutralized or the water is diluted before outlet to avoid undesired effects caused by the high pH.     

Vivianite precipitation and phosphate sorption following iron reduction in anoxic soils

Phosphorus retention in lowland soils depends on redox conditions. The aim of this study was to evaluate how the Fe(III) reduction degree affects phosphate adsorption and precipitation. Two similarly P-saturated, ferric Fe-rich lowland soils, a sandy and a peat soil, were incubated under anaerobic conditions. M?ssbauer spectroscopy demonstrated that Fe(III) in the sandy soil was present as goethite and phyllosilicates, whereas Fe(III) in the peat soil was mainly present as polynuclear, Fe-humic complexes. Following anoxic incubation, extensive formation of Fe(II) in the solids occurred. After 100 d, the Fe(II) production reached its maximum and 34% of the citrate-bicarbonate-dithionite extractable Fe (Fe(CBD)) was reduced to Fe(II) in the sandy soil. The peat soil showed a much faster reduction of Fe(III) and the maximum reduction of 89% of Fe(CBD) was reached after 200 d. Neoformation of a metavivianite/vivianite phase under anoxic conditions was identified by X-ray diffraction in the peat. The sandy soil exhibited small changes in the point of zero net sorption (EPC?) and P(i) desorption with increasing Fe(III) reduction, whereas in the peat soil P desorption increased from 80 to 3100 μmol kg?1 and EPC? increased from 1.7 to 83 μM, after 322 d of anoxic incubation. The fast Fe(III) reduction made the peat soils particularly vulnerable to changes in redox conditions. However, the precipitation of vivianite/metavivianite minerals may control soluble P(i) concentrations to between 2 and 3 μM in the long term if the soil is not disturbed.     

The Effects of Hypoxia on Sediment Nitrogen Cycling in the Baltic Sea

Primary production in the eutrophic Baltic Sea is limited by nitrogen availability; hence denitrification (natural transformation of nitrate to gaseous N₂) in the sediments is crucial in mitigating the effects of eutrophication. This study shows that dissimilatory nitrate reduction to ammonium (DNRA) process, where nitrogen is not removed but instead recycled in the system, dominates nitrate reduction in low oxygen conditions (O₂ <110 μM), which have been persistent in the central Gulf of Finland during the past decade. The nitrogen removal rates measured in this study show that nitrogen removal has decreased in the Gulf of Finland compared to rates measured in mid-1990s and the decrease is most likely caused by the increased bottom water hypoxia.     

Arctic Tipping Points: Governance in Turbulent Times

Interacting forces of climate change and globalization are transforming the Arctic. Triggered by a non-linear shift in sea ice, this transformation has unleashed mounting interest in opportunities to exploit the region’s natural resources as well as growing concern about environmental, economic, and political issues associated with such efforts. This article addresses the implications of this transformation for governance, identifies limitations of existing arrangements, and explores changes needed to meet new demands. It advocates the development of an Arctic regime complex featuring flexibility across issues and adaptability over time along with an enhanced role for the Arctic Council both in conducting policy-relevant assessments and in promoting synergy in interactions among the elements of the emerging Arctic regime complex. The emphasis throughout is on maximizing the fit between the socioecological features of the Arctic and the character of the governance arrangements needed to steer the Arctic toward a sustainable future.     

Bio-Ethanol Production from Non-Food Parts of Cassava (<Emphasis Type="Italic">Manihot esculenta</Emphasis> Crantz)

Global climate issues and a looming energy crisis put agriculture under pressure in Sub-Saharan Africa. Climate adaptation measures must entail sustainable development benefits, and growing crops for food as well as energy may be a solution, removing people from hunger and poverty without compromising the environment. The present study investigated the feasibility of using non-food parts of cassava for energy production and the promising results revealed that at least 28% of peels and stems comprise dry matter, and 10 g feedstock yields >8.5 g sugar, which in turn produced >60% ethanol, with pH ≈ 2.85, 74-84% light transmittance and a conductivity of 368 mV, indicating a potential use of cassava feedstock for ethanol production. Thus, harnessing cassava for food as well as ethanol production is deemed feasible. Such a system would, however, require supportive policies to acquire a balance between food security and fuel.