Using a photochemical air quality model to evaluate emissions and simulate concentrations

The air-quality modelling system was conducted to evaluate emissions inventory and simulate air concentration over Thailand. The coupling model of the Regional Atmospheric Modelling System (RAMS) and the models-3 Community Multi-scale Air Quality (CMAQ) was applied to simulate the concentration distributions of gaseous pollutants (i.e., NO_x, SO₂ and CO) over the Central and Eastern regions of Thailand. CMAQ was run for a summertime episode in a sub-grid scale. Simulated air concentrations were then compared with monitoring data. The evaluating results between modelling simulation and monitoring observation show a good agreement within a factor of 2.0 and relevant trend line, representing the acceptable level of emissions and concentration. This coupling model can be applied to support emission control strategies and clean air acts.     

Process analysis of a regional air pollution episode over Pearl River Delta Region,China, using the MM5-CMAQ model

This study focuses on the influences of a warm high-pressure meteorological system on aerosol pollutants, employing the simulations by the Models-3/CMAQ system and the observations collected during October 10–12, 2004, over the Pearl River Delta (PRD) region. The results show that the spatial distributions of air pollutants are generally circular near Guangzhou and Foshan, which are cities with high emissions rates. The primary pollutant is particulate matter (PM) over the PRD. MM5 shows reasonable performance for major meteorological variables (i.e., temperature, relative humidity, wind direction) with normalized mean biases (NMB) of 4.5–38.8% and for their time series. CMAQ can capture one peak of all air pollutant concentrations on October 11, but misses other peaks. The CMAQ model systematically underpredicts the mass concentrations of all air pollutants. Compared with chemical observations, SO₂ and O₃ are predicted well with a correlation coefficient of 0.70 and 0.65. PM_2.5 and NO are significantly underpredicted with an NMB of 43% and 90%, respectively. The process analysis results show that the emission, dry deposition, horizontal transport, and vertical transport are four main processes affecting air pollutants. The contributions of each physical process are different for the various pollutants. The most important process for PM₁₀ is dry deposition, and for NO_x it is transport. The contributions of horizontal and vertical transport processes vary during the period, but these two processes mostly contribute to the removal of air pollutants at Guangzhou city, whose emissions are high. For this high-pressure case, the contributions of the various processes show high correlations in cities with the similar geographical attributes. According to the statistical results, cities in the PRD region are divided into four groups with different features. The contributions from local and nonlocal emission sources are discussed in different groups.

Implications: The characteristics of aerosol pollution episodes are intensively studied in this work using the high-resolution modeling system MM5/SMOKE/CMAQ, with special efforts on examining the contributions of different physical and chemical processes to air concentrations for each city over the PRD region by a process analysis method, so as to provide a scientific basis for understanding the formation mechanism of regional aerosol pollution under the high-pressure system over PRD.     

Predictions of U.K. regulated power station contributions to regional air pollution and deposition: a model comparison exercise

Contributions of the emissions from a U.K. regulated fossil-fuel power station to regional air pollution and deposition are estimated using four air quality modeling systems for the year 2003. The modeling systems vary in complexity and emphasis in the way they treat atmospheric and chemical processes, and include the Community Multiscale Air Quality (CMAQ) modeling system in its versions 4.6 and 4.7, a nested modeling system that combines long- and short-range impacts (referred to as TRACK-ADMS [Trajectory Model with Atmospheric Chemical Kinetics-Atmospheric Dispersion Modelling System]), and the Fine Resolution Atmospheric Multi-pollutant Exchange (FRAME) model. An evaluation of the baseline calculations against U.K. monitoring network data is performed. The CMAQ modeling system version 4.6 data set is selected as the reference data set for the model footprint comparison. The annual mean air concentration and total deposition footprints are summarized for each modeling system. The footprints of the power station emissions can account for a significant fraction of the local impacts for some species (e.g., more than 50% for SO2 air concentration and non-sea-salt sulfur deposition close to the source) for 2003. The spatial correlation and the coefficient of variation of the root mean square error (CVRMSE) are calculated between each model footprint and that calculated by the CMAQ modeling system version 4.6. The correlation coefficient quantifies model agreement in terms of spatial patterns, and the CVRMSE measures the magnitude of the difference between model footprints. Possible reasons for the differences between model results are discussed. Finally, implications and recommendations for the regulatory assessment of the impact of major industrial sources using regional air quality modeling systems are discussed in the light of results from this case study.     

Dynamic evaluation of a regional air quality model: Assessing the emissions-induced weekly ozone cycle

Air quality models are used to predict changes in pollutant concentrations resulting from envisioned emission control policies. Recognizing the need to assess the credibility of air quality models in a policy-relevant context, we perform a dynamic evaluation of the Community Multiscale Air Quality (CMAQ) modeling system for the “weekend ozone effect” to determine if observed changes in ozone due to weekday-to-weekend (WDWE) reductions in precursor emissions can be accurately simulated. The weekend ozone effect offers a unique opportunity for dynamic evaluation, as it is a widely documented phenomenon that has persisted since the 1970s. In many urban areas of the Unites States, higher ozone has been observed on weekends than weekdays, despite dramatically reduced emissions of ozone precursors (nitrogen oxides [NO_x] and volatile organic compounds [VOCs]) on weekends. More recent measurements, however, suggest shifts in the spatial extent or reductions in WDWE ozone differences. Using 18 years (1988–2005) of observed and modeled ozone and temperature data across the northeastern United States, we re-examine the long-term trends in the weekend effect and confounding factors that may be complicating the interpretation of this trend and explore whether CMAQ can replicate the temporal features of the observed weekend effect. The amplitudes of the weekly ozone cycle have decreased during the 18-year period in our study domain, but the year-to-year variability in weekend minus weekday (WEWD) ozone amplitudes is quite large. Inter-annual variability in meteorology appears to influence WEWD differences in ozone, as well as WEWD differences in VOC and NO_x emissions. Because of the large inter-annual variability, modeling strategies using a single episode lasting a few days or a few episodes in a given year may not capture the WEWD signal that exists over longer time periods. The CMAQ model showed skill in predicting the absolute values of ozone concentrations during the daytime. However, early morning NO_x concentrations were underestimated and ozone levels were overestimated. Also, the modeled response of ozone to WEWD differences in emissions was somewhat less than that observed. This study reveals that model performance may be improved by (1) properly estimating mobile source NO_x emissions and their temporal distributions, especially for diesel vehicles; (2) reducing the grid cell size in the lowest layer of CMAQ; and, (3) using time-dependent and more realistic boundary conditions for the CMAQ simulations.     

Plot-scale spatiotemporal variations of CO2 concentration and flux across water–air interfaces at aquaculture shrimp ponds in a subtropical estuary

Human activities have increased anthropogenic CO₂ emissions, which are believed to play important roles in global warming. The spatiotemporal variations of CO₂ concentration and flux at fine spatial scales in aquaculture ponds remain unclear, particularly in China, the country with the largest aquaculture. In this study, the plot-scale spatiotemporal variations of water CO₂ concentration and flux, both within and among ponds, were researched in shrimp ponds in Shanyutan Wetland, Min River Estuary, Southeast China. The average water CO₂ concentration and flux across the water–air interface in the shrimp ponds over the shrimp farming period varied from 22.79?±?0.54 to 186.66?±?8.71 μmol L^?1 and from ??0.50?±?0.04 to 2.87?±?0.78 mol m^?2 day^?1, respectively. There was no remarkable difference in CO₂ concentration and flux within the ponds, but significantly spatiotemporal differences in CO₂ flux were observed between shrimp ponds. Chlorophyll a, pH, salinity, air temperature, and morphometry were the important factors driving the spatiotemporal patterns of CO₂ flux in the shrimp ponds. Our findings highlighted the importance and spatiotemporal variations of CO₂ flux in the important coastal ecosystems.

     

The growth response of Alternanthera philoxeroides in a simulated post-combustion emission with ultrahigh [CO2] and acidic pollutants

Although post-combustion emissions from power plants are a major source of air pollution, they contain excess CO₂ that could be used to fertilize commercial greenhouses and stimulate plant growth. We addressed the combined effects of ultrahigh [CO₂] and acidic pollutants in flue gas on the growth of Alternanthera philoxeroides. When acidic pollutants were excluded, the biomass yield of A. philoxeroides saturated near 2000 μmol mol⁻¹ [CO₂] with doubled biomass accumulation relative to the ambient control. The growth enhancement was maintained at 5000 μmol mol⁻¹ [CO₂], but declined when [CO₂] rose above 1%, in association with a strong photosynthetic inhibition. Although acidic components (SO₂ and NO₂) significantly offset the CO₂ enhancement, the aboveground yield increased considerably when the concentration of pollutants was moderate (200 times dilution). Our results indicate that using excess CO₂ from the power plant emissions to optimize growth in commercial green house could be viable.     

Emissions and risks associated with oxyfuel combustion: State of the science and critical data gaps

Oxyfuel combustion is a promising technology that may greatly facilitate carbon capture and sequestration by increasing the relative CO₂ content of the combustion emission stream. However, the potential effect of enhanced oxygen combustion conditions on emissions of criteria and hazardous air pollutants (e.g., acid gases, particulates, metals and organics) is not well studied. It is possible that combustion under oxyfuel conditions could produce emissions posing different risks than those currently being managed by the power industry (e.g., by changing the valence state of metals). The data available for addressing these concerns are quite limited and are typically derived from laboratory-scale or pilot-scale tests. A review of the available data does suggest that oxyfuel combustion may decrease the air emissions of some pollutants (e.g., SO₂, NOx, particulates) whereas data for other pollutants are too limited to draw any conclusions. The oxy-combustion systems that have been proposed to date do not have a conventional “stack” and combustion flue gas is treated in such a way that solid or liquid waste streams are the major outputs. Use of this technology will therefore shift emissions from air to solid or liquid waste streams, but the risk management implications of this potential change have yet to be assessed. Truly useful studies of the potential effects of oxyfuel combustion on power plant emissions will require construction of integrated systems containing a combustion system coupled to a CO₂ processing unit. Sampling and analysis to assess potential emission effects should be an essential part of integrated system tests.

Implications: Oxyfuel combustion may facilitate carbon capture and sequestration by increasing the relative CO₂ content of the combustion emission stream. However, the potential effect of enhanced oxygen combustion conditions on emissions of criteria and hazardous air pollutants has not been well studied. Combustion under oxyfuel conditions could produce emissions posing different risks than those currently being managed by the power industry. Therefore, before moving further with oxyfuel combustion as a new technology, it is appropriate to summarize the current understanding of potential emissions risk and to identify data gaps as priorities for future research.     

Influence of model grid resolution on NO2 vertical column densities over East Asia

NO₂ vertical column densities (VCDs) over East Asia in June and December 2007 were simulated by the Community Multi-scale Air Quality (CMAQ) version 4.7.1 using an updated and more elaborate version of the Regional Emission Inventory in Asia (REAS) version 2. The modeling system could reasonably capture observed spatiotemporal changes of NO₂ VCDs by satellite sensors, the Global Ozone Monitoring Experiment-2 (GOME-2), the Scanning Imaging Absorption Spectrometer for Atmospheric Cartography (SCIAMACHY), and the Ozone Monitoring Instrument (OMI), even at the coarsest horizontal resolution of 80 km. The CMAQ simulations were performed in a sequence of three horizontal resolutions (80 km, 40 km, and 20 km) for June and December 2007 to investigate the influence of changes of horizontal resolution on the obtained NO₂ VCDs. CMAQ-simulated NO₂ VCDs generally increased with improvements in resolution from 80 km to 40 km and then to 20 km. Increases in the CMAQ-simulated NO₂ VCDs were greater for the change from 80 km to 40 km than for those from 40 km and 20 km, in which the increases of NO₂ VCDs due to the improvement of horizontal resolution were approached convergence at the horizontal resolution of approximately 20 km. Conversely, no clear convergences in NO₂ VCDs changes were found at near Tokyo and over the East China Sea. The biases of the NO₂ VCDs simulated at a resolution of 20 km against the satellite retrievals were ～36% near Beijing (CHN1) and ～78% near Shanghai (CHN2) in summer; these errors were found to be comparable to the horizontal resolution-dependent errors, which were 18–25% at CHN1 and 44–58% at CHN2 from 80 km to 40 km. Conversely, the influence of changes of horizontal resolution in winter was relatively less compared to that in summer.

Implications: NO₂ VCDs over East Asia in June and December 2007 were simulated using CMAQ version 4.7.1 and REAS version 2. The modeling system could reasonably capture observed spatiotemporal changes of NO₂ VCDs by satellite sensors. The CMAQ simulations were performed in a sequence of three horizontal resolutions, 80, 40, and 20 km, to investigate the influence of changes of horizontal resolution on the obtained NO₂ VCDs. The results suggested that the influence of changes of horizontal resolution was larger in summer compared to that in winter. The magnitude of the influence was comparable to the biases of the NO₂ VCDs simulated at a resolution of 20 km against the satellite retrievals.     

The impact of CO2 capture in the power and heat sector on the emission of SO2, NOx,particulate matter,volatile organic compounds and NH3 in the European Union

This study quantifies the trade-offs and synergies between climate and air quality policy objectives for the European power and heat (P&H) sector. An overview is presented of the expected performance data of CO₂ capture systems implemented at P&H plants, and the expected emission of key air pollutants, being: SO₂, NO_X, NH₃, volatile organic compounds (VOCs) and particulate matter (PM). The CO₂ capture systems investigated include: post-combustion, oxyfuel combustion and pre-combustion capture.For all capture systems it was found that SO₂, NO_x and PM emissions are expected to be reduced or remain equal per unit of primary energy input compared to power plants without CO₂ capture. Increase in primary energy input as a result of the energy penalty for CO₂ capture may for some technologies and substances result in a net increase of emissions per kWh output. The emission of ammonia may increase by a factor of up to 45 per unit of primary energy input for post-combustion technologies. No data are available about the emission of VOCs from CO₂ capture technologies.A simple model was developed and applied to analyse the impact of CO₂ capture in the European P&H sector on the emission level of key air pollutants in 2030. Four scenarios were developed: one without CO₂ capture and three with one dominantly implemented CO₂ capture system, varying between: post-combustion, oxyfuel combustion and pre-combustion.The results showed a reduction in GHG emissions for the scenarios with CO₂ capture compared to the baseline scenario between 12% and 20% in the EU 27 region in 2030. NO_x emissions were 15% higher in the P&H sector in a scenario with predominantly post-combustion and lower when oxyfuel combustion (?16%) or pre-combustion (?20%) were implemented on a large scale. Large scale implementation of the post-combustion technology in 2030 may also result in significantly higher, i.e. increase by a factor of 28, NH₃ emissions compared to scenarios with other CO₂ capture options or without capture. SO₂ emissions were very low for all scenarios that include large scale implementation of CO₂ capture in 2030, i.e. a reduction varying between 27% and 41%. Particulate Matter emissions were found to be lower in the scenarios with CO₂ capture. The scenario with implementation of the oxyfuel technology showed the lowest PM emissions followed by the scenario with a significant share allocated to pre-combustion, respectively ?59% and ?31%. The scenario with post-combustion capture resulted in PM emissions varying between 35% reduction and 26% increase.     

Carbon dioxide and methane emissions from the scale model of open dairy lots

To investigate the impacts of major factors on carbon loss via gaseous emissions, carbon dioxide (CO₂) and methane (CH₄) emissions from the ground of open dairy lots were tested by a scale model experiment at various air temperatures (15, 25, and 35 °C), surface velocities (0.4, 0.7, 1.0, and 1.2 m sec^?1), and floor types (unpaved soil floor and brick-paved floor) in controlled laboratory conditions using the wind tunnel method. Generally, CO₂ and CH₄ emissions were significantly enhanced with the increase of air temperature and velocity (P < 0.05). Floor type had different effects on the CO₂ and CH₄ emissions, which were also affected by air temperature and soil characteristics of the floor. Although different patterns were observed on CH₄ emission from the soil and brick floors at different air temperature-velocity combinations, statistical analysis showed no significant difference in CH₄ emissions from different floors (P > 0.05). For CO₂, similar emissions were found from the soil and brick floors at 15 and 25 °C, whereas higher rates were detected from the brick floor at 35 °C (P < 0.05). Results showed that CH₄ emission from the scale model was exponentially related to CO₂ flux, which might be helpful in CH₄ emission estimation from manure management.

Implications: Gaseous emissions from the open lots are largely dependent on outdoor climate, floor systems, and management practices, which are quite different from those indoors. This study assessed the effects of floor types and air velocities on CO₂ and CH₄ emissions from the open dairy lots at various temperatures by a wind tunnel. It provided some valuable information for decision-making and further studies on gaseous emissions from open lots.     

Development of an individual exposure model for application to the Southern California children's health study

The Southern California Children's Health Study (CHS) investigated the relationship between air pollution and children's chronic respiratory health outcomes. Ambient air pollutant measurements from a single CHS monitoring station in each community were used as surrogates for personal exposures of all children in that community. To improve exposure estimates for the CHS children, we developed an Individual Exposure Model (IEM) to retrospectively estimate the long-term average exposure of the individual CHS children to CO, NO₂, PM₁₀, PM_2.5, and elemental carbon (EC) of ambient origin. In the IEM, pollutant concentrations due to both local mobile source emissions (LMSE) and meteorologically transported pollutants were taken into account by combining a line source model (CALINE4) with a regional air quality model (SMOG). To avoid double counting, local mobile sources were removed from SMOG and added back by CALINE4. Limited information from the CHS survey was used to group each child into a specific time-activity category, for which corresponding Consolidated Human Activity Database (CHAD) time-activity profiles were sampled. We found local traffic significantly increased within-community variability of exposure to vehicle-related pollutants. PM-associated exposures were influenced more by meteorologically transported pollutants and local non-mobile source emissions than by LMSE. The overall within-community variability of personal exposures was highest for NO₂ (±20–40%), followed by EC (±17–27%), PM₁₀ (±15–25%), PM_2.5 (±15–20%), and CO (±9–14%). Between-community exposure differences were affected by community location, traffic density, and locations of residences and schools in each community. Proper siting of air monitoring stations relative to emission sources is important to capture community mean exposures.     

Transport impacts on atmosphere and climate: Shipping

Emissions of exhaust gases and particles from oceangoing ships are a significant and growing contributor to the total emissions from the transportation sector. We present an assessment of the contribution of gaseous and particulate emissions from oceangoing shipping to anthropogenic emissions and air quality. We also assess the degradation in human health and climate change created by these emissions. Regulating ship emissions requires comprehensive knowledge of current fuel consumption and emissions, understanding of their impact on atmospheric composition and climate, and projections of potential future evolutions and mitigation options. Nearly 70% of ship emissions occur within 400 km of coastlines, causing air quality problems through the formation of ground-level ozone, sulphur emissions and particulate matter in coastal areas and harbours with heavy traffic. Furthermore, ozone and aerosol precursor emissions as well as their derivative species from ships may be transported in the atmosphere over several hundreds of kilometres, and thus contribute to air quality problems further inland, even though they are emitted at sea. In addition, ship emissions impact climate. Recent studies indicate that the cooling due to altered clouds far outweighs the warming effects from greenhouse gases such as carbon dioxide (CO₂) or ozone from shipping, overall causing a negative present-day radiative forcing (RF). Current efforts to reduce sulphur and other pollutants from shipping may modify this. However, given the short residence time of sulphate compared to CO₂, the climate response from sulphate is of the order decades while that of CO₂ is centuries. The climatic trade-off between positive and negative radiative forcing is still a topic of scientific research, but from what is currently known, a simple cancellation of global mean forcing components is potentially inappropriate and a more comprehensive assessment metric is required. The CO₂ equivalent emissions using the global temperature change potential (GTP) metric indicate that after 50 years the net global mean effect of current emissions is close to zero through cancellation of warming by CO₂ and cooling by sulphate and nitrogen oxides.     

Current and future emission estimates of exhaust gases and particles from shipping at the largest port in Korea

The emissions of exhaust gases (NO _x , SO₂, VOCs, and CO₂) and particles (e.g., PM) from ships traversing Busan Port in Korea were estimated over three different years (the years 2006, 2008, and 2009). This analysis was performed according to the ship operational modes (“at sea,” “maneuvering,” and “in port”) and ship types based on an activity-based method. The ship emissions for current (base year 2009) and future scenarios (years 2020 and 2050) were also compared. The annual emissions of SO₂, VOCs, PM, and CO₂ were highest (9.6?×?10³, 374, 1.2?×?10³, and 5.6?×?10⁵ ton year^?1, respectively) in 2008. In contrast, the annual NO _x emissions were highest (11.7?×?10³ ton year^?1) in 2006 due mainly to the high NO _x emission factor. The emissions of air pollutants for each ship operational mode differed considerably, with the largest emission observed in “in port” mode. In addition, the largest fraction (approximately 45–67 %) of the emissions of all air pollutants during the study period was emitted from container ships. The future ship emissions of most pollutants (except for SO₂ and PM) in 2020 and 2050 are estimated to be 1.4–1.8 and 4.7–6.1 times higher than those in 2009 (base year), respectively.     

Autonomous mobile platform for monitoring air emissions from industrial and municipal wastewater ponds

Significant amounts of volatile organic compounds and greenhouse gases are generated from wastewater lagoons and tailings ponds in Alberta, Canada. Accurate measurements of these air pollutants and greenhouse gases are needed to support management and regulatory decisions. A mobile platform was developed to measure air emissions from tailings pond in the oil sands region of Alberta. The mobile platform was tested in 2015 in a municipal wastewater treatment lagoon. With a flux chamber and a CO₂/CH₄ sensor on board, the mobile platform was able to measure CO₂ and CH₄ emissions over two days at two different locations in the pond. Flux emission rates of CO₂ and CH₄ that were measured over the study period suggest the presence of aerobic and anaerobic zones in the wastewater treatment lagoon. The study demonstrated the capabilities of the mobile platform in measuring fugitive air emissions and identified the potential for the applications in air and water quality monitoring programs.

Implications: The Mobile Platform demonstrated in this study has the ability to measure greenhouse gas (GHG) emissions from fugitive sources such as municipal wastewater lagoons. This technology can be used to measure emission fluxes from tailings ponds with better detection of spatial and temporal variations of fugitive emissions. Additional air and water sampling equipment could be added to the mobile platform for a broad range of air and water quality studies in the oil sands region of Alberta.     

Traffic pollution in a downtown site of Buenos Aires City

It has recently been recognized that air and noise pollution constitutes an extended problem over the densely populated city of Buenos Aires. Traffic emissions are of paramount concern, especially along narrow and main traffic arteries. In spite of these considerations, few systematic studies have been undertaken to evaluate the air quality in the metropolitan area of the city. In 1996, concentrations of carbon monoxide (CO), nitric oxide (NO), nitrogen dioxide (NO₂) and ozone (O₃) were simultaneously measured for the first time using a continuous monitoring station. This station was placed in a building at Belgrano Avenue, which is a heavy traffic street in the downtown area of the city (Bogo et al., Atmospheric Environment 33 (1999) 2587. In this work, we analyze the dependence of the measured primary pollutants, CO and the mixture of nitrogen oxides (NO_x), with meteorological conditions, traffic emissions and monitoring location. We compare the registered values with the results obtained from modeling the dispersion of the pollutants emitted from mobile and area sources. We also discuss the relevance of street canyon effects compared with background concentrations of these pollutants.     

Development of the high spatial resolution EMICAT2000 emission model for air pollutants from the north-eastern Iberian Peninsula (Catalonia, Spain)

Ozone (O(3)) pollution episodes take place in Catalonia (NE of the Iberian Peninsula), mainly during summertime. The complex O(3) behaviour could be understood by using a Chemical Transport Model (CTM). Emission inventories provide the spatial and temporal emissions distribution of the O(3) precursors and other pollutants required by this approach. We developed the EMICAT2000 model with high spatial (cells of 1 km(2)) and temporal (1h) resolutions, to estimate the emissions during the year 2000 from Catalonia. Total annual emissions were 107 kt yr(-1) of NO(x), 137 kt yr(-1) of NMVOC, 267 kt yr(-1) of CO, 65 kt yr(-1) of SO(2), 24 kt yr(-1) of TSP and 32,175 kt yr(-1) of equivalent CO(2). Main NO(x) sources are on-road traffic (58%) and industries (38%). Main NMVOC sources are on-road traffic (36%), vegetation (34%) and use of solvents (13%). Speciation was established according to the Carbon Bond IV mechanism. EMICAT2000 generates directly the data files required for the third generation CTM Models-3/CMAQ.     

Uncertainty Analysis of Ozone Formation and Response to Emission Controls Using Higher-Order Sensitivities

Abstract

Understanding ozone response to its precursor emissions is crucial for effective air quality management practices. This nonlinear response is usually simulated using chemical transport models, and the modeling results are affected by uncertainties in emissions inputs. In this study, a high ozone episode in the southeastern United States is simulated using the Community Multiscale Air Quality (CMAQ) model. Uncertainties in ozone formation and response to emissions controls due to uncertainties in emission rates are quantified using the Monte Carlo method. Instead of propagating emissions uncertainties through the original CMAQ, a reduced form of CMAQ is formulated using directly calculated first- and second-order sensitivities that capture the nonlinear ozone concentration-emission responses. This modification greatly reduces the associated computational cost. Quantified uncertainties in modeled ozone concentrations and responses to various emissions controls are much less than the uncertainties in emissions inputs. Average uncertainties in modeled ozone concentrations for the Atlanta area are less than 10% (as measured by the inferred coefficient of variance [ICOV]) even when emissions uncertainties are assumed to vary between a factor of 1.5 and 2. Uncertainties in the ozone responses generally decrease with increased emission controls. Average uncertainties (ICOV) in emission-normalized ozone responses range from 4 to 22%, with the smaller being associated with controlling of the relatively certain point nitrogen oxide (NO_x) emissions and the larger resulting from controlling of the less certain mobile NO_x emissions. These small uncertainties provide confidence in the model applications, such as in performance evaluation, attainment demonstration, and control strategy development.     

Assessment of air quality benefits from national air pollution control policies in China. Part I: Background,emission scenarios and evaluation of meteorological predictions

Under the 11th Five Year Plan (FYP, 2006–2010) for national environmental protection by the Chinese government, the overarching goal for sulfur dioxide (SO₂) controls is to achieve a total national emissions level of SO₂ in 2010 10% lower than the level in 2005. A similar nitrogen oxides (NO_x) emissions control plan is currently under development and could be enforced during the 12th FYP (2011–2015). In this study, the U.S. Environmental Protection Agency (U.S.EPA)’s Community Multi-Scale Air Quality (Models-3/CMAQ) modeling system was applied to assess the air quality improvement that would result from the targeted SO₂ and NO_x emission controls in China. Four emission scenarios — the base year 2005, the 2010 Business-As-Usual (BAU) scenario, the 2010 SO₂ control scenario, and the 2010 NO_x control scenario—were constructed and simulated to assess the air quality change from the national control plan. The Fifth-Generation NCAR/Penn State Mesoscale Model (MM5) was applied to generate the meteorological fields for the CMAQ simulations. In this Part I paper, the model performance for the simulated meteorology was evaluated against observations for the base case in terms of temperature, wind speed, wind direction, and precipitation. It is shown that MM5 model gives an overall good performance for these meteorological variables. The generated meteorological fields are acceptable for using in the CMAQ modeling.     

Emissions Variability Processor (EMVAP): Design,evaluation, and application

Emissions of pollutants such as SO₂ and NOx from external combustion sources can vary widely depending on fuel sulfur content, load, and transient conditions such as startup, shutdown, and maintenance/malfunction. While monitoring will automatically reflect variability from both emissions and meteorological influences, dispersion modeling has been typically conducted with a single constant peak emission rate. To respond to the need to account for emissions variability in addressing probabilistic 1-hr ambient air quality standards for SO₂ and NO₂, we have developed a statistical technique, the Emissions Variability Processor (EMVAP), which can account for emissions variability in dispersion modeling through Monte Carlo sampling from a specified frequency distribution of emission rates. Based upon initial AERMOD modeling of from 1 to 5 years of actual meteorological conditions, EMVAP is used as a postprocessor to AERMOD to simulate hundreds or even thousands of years of concentration predictions. This procedure uses emissions varied hourly with a Monte Carlo sampling process that is based upon the user-specified emissions distribution, from which a probabilistic estimate can be obtained of the controlling concentration. EMVAP can also accommodate an advanced Tier 2 NO₂ modeling technique that uses a varying ambient ratio method approach to determine the fraction of total oxides of nitrogen that are in the form of nitrogen dioxide. For the case of the 1-hr National Ambient Air Quality Standards (NAAQS, established for SO₂ and NO₂), a “critical value” can be defined as the highest hourly emission rate that would be simulated to satisfy the standard using air dispersion models assuming constant emissions throughout the simulation. The critical value can be used as the starting point for a procedure like EMVAP that evaluates the impact of emissions variability and uses this information to determine an appropriate value to use for a longer term (e.g., 30-day) average emission rate that would still provide protection for the NAAQS under consideration. This paper reports on the design of EMVAP and its evaluation on several field databases that demonstrate that EMVAP produces a suitably modest overestimation of design concentrations. We also provide an example of an EMVAP application that involves a case in which a new emission limitation needs to be considered for a hypothetical emission unit that has infrequent higher-than-normal SO₂ emissions.

ImplicationsEmissions of pollutants from combustion sources can vary widely depending on fuel sulfur content, load, and transient conditions such as startup and shutdown. While monitoring will automatically reflect this variability on measured concentrations, dispersion modeling is typically conducted with a single peak emission rate assumed to occur continuously. To realistically account for emissions variability in addressing probabilistic 1-hr ambient air quality standards for SO₂ and NO₂, the authors have developed a statistical technique, the Emissions Variability Processor (EMVAP), which can account for emissions variability in dispersion modeling through Monte Carlo sampling from a specified frequency distribution of emission rates.     

Assessment of the emissions and air quality impacts of biomass and biogas use in California

It is estimated that there is sufficient in-state “technically” recoverable biomass to support nearly 4000 MW of bioelectricity generation capacity. This study assesses the emissions of greenhouse gases and air pollutants and resulting air quality impacts of new and existing bioenergy capacity throughout the state of California, focusing on feedstocks and advanced technologies utilizing biomass resources predominant in each region. The options for bioresources include the production of bioelectricity and renewable natural gas (NG). Emissions of criteria pollutants and greenhouse gases are quantified for a set of scenarios that span the emission factors for power generation and the use of renewable natural gas for vehicle fueling. Emissions are input to the Community Multiscale Air Quality (CMAQ) model to predict regional and statewide temporal air quality impacts from the biopower scenarios. With current technology and at the emission levels of current installations, maximum bioelectricity production could increase nitrogen oxide (NO_x) emissions by 10% in 2020, which would cause increases in ozone and particulate matter concentrations in large areas of California. Technology upgrades would achieve the lowest criteria pollutant emissions. Conversion of biomass to compressed NG (CNG) for vehicles would achieve comparable emission reductions of criteria pollutants and minimize emissions of greenhouse gases (GHG). Air quality modeling of biomass scenarios suggest that applying technological changes and emission controls would minimize the air quality impacts of bioelectricity generation. And a shift from bioelectricity production to CNG production for vehicles would reduce air quality impacts further. From a co-benefits standpoint, CNG production for vehicles appears to provide the best benefits in terms of GHG emissions and air quality.

Implications:?This investigation provides a consistent analysis of air quality impacts and greenhouse gas emissions for scenarios examining increased biomass use. Further work involving economic assessment, seasonal or annual emissions and air quality modeling, and potential exposure analysis would help inform policy makers and industry with respect to further development and direction of biomass policy and bioenergy technology alternatives needed to meet energy and environmental goals in California.