Simulating Urban-Scale Air Pollutants and Their Predicting Capabilities over the Seoul Metropolitan Area

Abstract

Urban-scale air pollutants for sulfur dioxide, nitrogen dioxide, particulate matter with aerodynamic diameter >10 μm, and ozone (O₃) were simulated over the Seoul metropolitan area, Korea, during the period of July 2-11, 2002, and their predicting capabilities were discussed. The Air Pollution Model (TAPM) and the highly disaggregated anthropogenic and the biogenic gridded emissions (1 km × 1 km) recently prepared by the Korean Ministry of Environment were applied. Wind fields with observational nudging in the prognostic meteorological model TAPM are optionally adopted to comparatively examine the meteorological impact on the prediction capabilities of urban-scale air pollutants. The result shows that the simulated concentrations of secondary air pollutant largely agree with observed levels with an index of agreement (IOA) of >0.6, whereas IOAs of ～0.4 are found for most primary pollutants in the major cities, reflecting the quality of emission data in the urban area. The observationally nudged wind fields with higher IOAs have little effect on the prediction for both primary and secondary air pollutants, implying that the detailed wind field does not consistently improve the urban air pollution model performance if emissions are not well specified. However, the robust highest concentrations are better described toward observations by imposing observational nudging, suggesting the importance of wind fields for the predictions of extreme concentrations such as robust highest concentrations, maximum levels, and >90th percentiles of concentrations for both primary and secondary urban-scale air pollutants.     

The use of wind fields in a land use regression model to predict air pollution concentrations for health exposure studies

A methodology is developed to include wind flow effects in land use regression (LUR) models for predicting nitrogen dioxide (NO₂) concentrations for health exposure studies. NO₂ is widely used in health studies as an indicator of traffic-generated air pollution in urban areas. Incorporation of high-resolution interpolated observed wind direction from a network of 38 weather stations in a LUR model improved NO₂ concentration estimates in densely populated, high traffic and industrial/business areas in Toronto-Hamilton urban airshed (THUA) of Ontario, Canada. These small-area variations in air pollution concentrations that are probably more important for health exposure studies may not be detected by sparse continuous air pollution monitoring network or conventional interpolation methods. Observed wind fields were also compared with wind fields generated by Global Environmental Multiscale-High resolution Model Application Project (GEM-HiMAP) to explore the feasibility of using regional weather forecasting model simulated wind fields in LUR models when observed data are either sparse or not available. While GEM-HiMAP predicted wind fields well at large scales, it was unable to resolve wind flow patterns at smaller scales. These results suggest caution and careful evaluation of regional weather forecasting model simulated wind fields before incorporating into human exposure models for health studies. This study has demonstrated that wind fields may be integrated into the land use regression framework. Such integration has a discernable influence on both the overall model prediction and perhaps more importantly for health effects assessment on the relative spatial distribution of traffic pollution throughout the THUA. Methodology developed in this study may be applied in other large urban areas across the world.     

Assessment of ambient air quality in the port of Naples

Two experimental monitoring campaigns were carried out in 2012 to investigate the air quality in the port of Naples, the most important in southern Italy for traffic of passengers and one of the most important for goods. Therefore, it represents an important air pollution source located close to the city of Naples. The concentrations of sulfur dioxide (SO₂), nitrogen dioxide (NO₂), and BTEX (benzene, toluene, ethylbenzene, and xylenes) in the air were measured at 15 points inside the Naples port area through the use of passive samplers. In addition, a mobile laboratory was positioned in a fixed point inside the port area to measure continuous concentration of pollutants together with particulate matter, ambient parameters, and wind direction and intensity. The pollution levels monitored were compared with those observed in the urban area of Naples and in other Mediterranean ports. Even though the observation time was limited, measured concentrations were also compared with limit values established by European legislation. All the measured pollutants were below the limits with the exception of nitrogen dioxide: its average concentration during the exposition time exceeded the yearly limit value. A spatial analysis of data, according to the measured wind direction and intensity, provided information about the effects that ship emissions have on ambient air quality in the port area. The main evidence indicates that ship emissions influence sulfur dioxide concentration more than any other pollutants analyzed.

Implications: Two monitoring campaigns were carried out to measure BTEX, SO₂, NO₂, and PM₁₀ (particulate matter with an aerodynamic diameter <10 μm) air concentrations in the port of Naples. NO₂ hourly average and PM₁₀ daily average comply with European legislative standards. Spatial variation of pollutants long the axis corresponding to the prevailing wind direction seems to indicate a certain influence of ship emissions for SO₂. For NO₂ and PM₁₀, a correlation between concentrations in the harbor and those measured by the air quality monitoring stations sited in the urban area of Naples was observed, indicating a possible contribution of the near road traffic to the air pollution in the port of Naples.     

Application of an integrated Weather Research and Forecasting (WRF)/CALPUFF modeling tool for source apportionment of atmospheric pollutants for air quality management: A case study in the urban area of Benxi,China

In this study, the authors endeavored to develop an effective framework for improving local urban air quality on meso-micro scales in cities in China that are experiencing rapid urbanization. Within this framework, the integrated Weather Research and Forecasting (WRF)/CALPUFF modeling system was applied to simulate the concentration distributions of typical pollutants (particulate matter with an aerodynamic diameter <10 μm [PM₁₀], sulfur dioxide [SO₂], and nitrogen oxides [NO_x]) in the urban area of Benxi. Statistical analyses were performed to verify the credibility of this simulation, including the meteorological fields and concentration fields. The sources were then categorized using two different classification methods (the district-based and type-based methods), and the contributions to the pollutant concentrations from each source category were computed to provide a basis for appropriate control measures. The statistical indexes showed that CALMET had sufficient ability to predict the meteorological conditions, such as the wind fields and temperatures, which provided meteorological data for the subsequent CALPUFF run. The simulated concentrations from CALPUFF showed considerable agreement with the observed values but were generally underestimated. The spatial-temporal concentration pattern revealed that the maximum concentrations tended to appear in the urban centers and during the winter. In terms of their contributions to pollutant concentrations, the districts of Xihu, Pingshan, and Mingshan all affected the urban air quality to different degrees. According to the type-based classification, which categorized the pollution sources as belonging to the Bengang Group, large point sources, small point sources, and area sources, the source apportionment showed that the Bengang Group, the large point sources, and the area sources had considerable impacts on urban air quality. Finally, combined with the industrial characteristics, detailed control measures were proposed with which local policy makers could improve the urban air quality in Benxi. In summary, the results of this study showed that this framework has credibility for effectively improving urban air quality, based on the source apportionment of atmospheric pollutants.

Implications: The authors endeavored to build up an effective framework based on the integrated WRF/CALPUFF to improve the air quality in many cities on meso-micro scales in China. Via this framework, the integrated modeling tool is accurately used to study the characteristics of meteorological fields, concentration fields, and source apportionments of pollutants in target area. The impacts of classified sources on air quality together with the industrial characteristics can provide more effective control measures for improving air quality.

Through the case study, the technical framework developed in this study, particularly the source apportionment, could provide important data and technical support for policy makers to assess air pollution on the scale of a city in China or even the world.     

Behavior of particulate matter during high concentration episodes in Seoul

The behavior of particulate matter (PM) during high-concentration episodes was investigated using monitoring data from Guui station, a comprehensive air monitoring station in Seoul, Korea, from January 2008 to March 2010. Five non-Asian dust (ND) episodes and two Asian dust (AD) episodes of high PM concentrations were selected for the study. During the ND episode, primary air pollutants accumulated due to low wind speeds, and PM_2.5 increased along with most other air pollutants. Particles larger than PM_2.5 were also high since these particles were generated by vehicular traffic rather than wind erosion. During strong AD episodes, PM_10–2.5 primarily increased and gaseous primary air pollutants decreased under high wind speeds. However, even during the AD episode, PM_2.5 and gaseous primary air pollutants increased when the effects of AD were weak and wind speeds were low. This study corroborates that accumulation of air pollutants due to a drop in surface wind speed plays an important role in short-term high-concentration occurrences. However, low wind speeds could not be directly linked to local emissions because a significant portion of accumulated air pollutants resulted from long-range transport.     

New indicator approaches for effective urban air quality management

Measurements of urban air quality at monitoring stations in developed countries have frequently involved the criteria gaseous pollutants, particulates, hazardous air pollutants, perceived air quality and relevant meteorological conditions. Large numbers of indicators have therefore been established to quantify emissions, concentrations and environmental and human health impacts of each of these groups of substances. To simplify the data for management, several indicators have been grouped together to form urban air quality indices but the weightings of individual variables is contentious. In industrialising and developing countries, data may be limited and traditional air pollutant indicators cannot often be constructed. The emphasis therefore has to be placed on the development of policy-relevant indicators, such as Response Indicators that reflect different policy principles for regulating air pollutant emissions. Indices that quantify the air quality management capabilities and capacities at the city level provide further useful decision-relevant tools. Four sets of indices, namely, 1. air quality measurement capacity, 2. data assessment and availability, 3. emissions estimates, and 4. management enabling capabilities, and a composite index to evaluate air quality management capability, were constructed and applied to 80 cities. The indices revealed that management capability varied widely between the cities. In some of the cities, existing national knowledge on urban air quality could have been more effectively used for management. It was concluded that for effective urban air quality management, a greater emphasis should be given, not just to monitoring and data capture programmes, but to the development of indicators and indices that empower decision-makers to initiate management response strategies. Over-reliance on restricted, predetermined sets of traditional air quality indicators should be avoided.     

Effects of the density of meteorological observations on the diagnostic wind fields and the performance of photochemical modeling in the greater Seoul area

The high ozone episode in the greater Seoul area (GSA) for the period of 27 July–1 August 1997 was modeled by the California Institute of Technology (CIT) three-dimensional photochemical model. During the period, ozone concentrations around 140 ppb were observed for 2 days. Two sets of diagnostic wind fields were constructed by using observations from the weather stations operated by the Korea Meteorological Administration. One set of wind fields utilized only observations from the surface weather stations (SWS) and the other set also utilized observations from the automatic weather stations (AWS) that were more densely distributed than the SWS. The results showed that utilizing observations from the AWS could represent fine variations in the wind field such as those caused by topography. A better wind field gave a more reasonable spatial distribution of ozone concentrations. The model performance of ozone prediction was also improved to some extent, but only marginally acceptable owing to large day-to-day variations. Overshoots of primary pollutants particularly for NO₂ were observed as pollutants were accumulated where low wind speeds were maintained. More precise information on diurnal and daily variations in emissions was warranted in order to better model the photochemical phenomena over the GSA.     

Development of a speciated, hourly, and gridded air pollutants emission modeling system--a case study on the precursors of photochemical smog in the Seoul metropolitan area, Korea

A speciated, hourly, and gridded air pollutants emission modeling system (SHEMS) was developed and applied in predicting hourly nitrogen dioxide (NO2) and ozone (O3) levels in the Seoul Metropolitan Area (SMA). The primary goal of the SHEMS was to produce a systemized emission inventory for air pollutants including ozone precursors for modeling air quality in urban areas. The SHEMS is principally composed of three parts: (1) a pre-processor to process emission factors, activity levels, and spatial and temporal information using a geographical information system; (2) an emission model for each source type; and (3) a post-processor to produce report and input data for air quality models through database modeling. The source categories in SHEMS are point, area, mobile, natural, and other sources such as fugitive emissions. The emission database produced by SHEMS contains 22 inventoried compounds: sulfur dioxide, NO2, carbon monoxide, and 19 speciated volatile organic compounds. To validate SHEMS, the emission data were tested with the Urban Airshed Model to predict NO2 and O3 concentrations in the SMA during selected episode days in 1994. The results turned out to be reliable in describing temporal variation and spatial distribution of those pollutants.     

Measurement, analysis, and modeling of fine particulate matter in eastern North Carolina

An analysis of fine particulate data in eastern North Carolina was conducted to investigate the impact of the hog industry and its emissions of ammonia into the atmosphere. The fine particulate data are simulated using ISORROPIA, an equilibrium thermodynamic model that simulates the gas and aerosol equilibrium of inorganic atmospheric species. The observational data analyses show that the major constituents of fine particulate matter (PM2.5) are organic carbon, elemental carbon, sulfate, nitrate, and ammonium. The observed PM2.5 concentration is positively correlated with temperature but anticorrelated with wind speed. The correlation between PM2.5 and wind direction at some locations suggests an impact of ammonia emissions from hog facilities on PM2.5 formation. The modeled results are in good agreement with observations, with slightly better agreement at urban sites than at rural sites. The predicted total inorganic particulate matter (PM) concentrations are within 5% of the observed values under conditions with median initial total PM species concentrations, median relative humidity (RH), and median temperature. Ambient conditions with high PM precursor concentrations, low temperature, and high RH appear to favor the formation of secondary PM.     

The sensitivity of modeled ozone to the temporal distribution of point, area, and mobile source emissions in the eastern United States

Ozone remains one of the most recalcitrant air pollution problems in the US. Hourly emissions fields used in air quality models (AQMs) generally show less temporal variability than corresponding measurements from continuous emissions monitors (CEM) and field campaigns would imply. If emissions control scenarios to reduce emissions at peak ozone forming hours are to be assessed with AQMs, the effect of emissions' daily variability on modeled ozone must be understood. We analyzed the effects of altering all anthropogenic emissions' temporal distributions by source group on 2002 summer-long simulations of ozone using the Community Multiscale Air Quality Model (CMAQ) v4.5 and the Carbon Bond IV (CBIV) chemical mechanism with 12 km resolution. We find that when mobile source emissions were made constant over the course of a day, 8-h maximum ozone predictions changed by ±7 parts per billion by volume (ppbv) in many urban areas on days when ozone concentrations greater than 80 ppbv were simulated in the base case. Increasing the temporal variation of point sources resulted in ozone changes of +6 and −6 ppbv, but only for small areas near sources. Changing the daily cycle of mobile source emissions produces substantial changes in simulated ozone, especially in urban areas at night; results suggest that shifting the emissions of NO_x from day to night, for example in electric powered vehicles recharged at night, could have beneficial impacts on air quality.     

High time-resolved measurements of organic air toxics in different source regimes

High time-resolved (HTR) measurements can provide significant insight into sources and exposures of air pollution. In this study, an automated instrument was developed and deployed to measure hourly concentrations of 18 gas-phase organic air toxics and 6 volatile organic compounds (VOCs) at three sites in and around Pittsburgh, Pennsylvania. The sites represent different source regimes: a site with substantial mobile-source emissions; a residential site adjacent to a heavily industrialized zone; and an urban background site. Despite the close proximity of the sites (less than 13 km apart), the temporal characteristic of outdoor concentrations varied widely. Most of the compounds measured were characterized by short periods of elevated concentrations or plume events, but the duration, magnitude and composition of these events varied from site to site. The HTR data underscored the strong role of emissions from local sources on exposure to most air toxics. Plume events contributed more than 50% of the study average concentrations for all pollutants except chloroform, 1,2-dichloroethane, and carbon tetrachloride. Wind directional dependence of air toxic concentrations revealed that emissions from large industrial facilities affected concentrations at all of the sites. Diurnal patterns and weekend/weekday variations indicated the effects of the mixing layer, point source emissions patterns, and mobile source air toxics (MSATs) on concentrations. Concentrations of many air toxics were temporally correlated, especially MSATs, indicating that they are likely co-emitted. It was also shown that correlations of the HTR data were greater than lower time resolution data (24-h measurements). This difference was most pronounced for the chlorinated pollutants. The stronger correlations in HTR measurements underscore their value for source apportionment studies.     

Impact of using prognostic and objective wind fields on the photochemical modeling of Athens, Greece

A three-dimensional Eulerian photochemical model is used to follow the dynamics of ozone, NO_x, and CO over the Athens area, for 25 May 1990, the day considered in the APSIS project. A unique aspect of this work lies in the study of the impacts of the wind field preparation methods on the concentrations predicted by the model. Three sets of wind fields are developed. The first one used is derived from a prognostic meteorological model. The second one is calculated from available wind observations using objective: methods. For these two cases, a previous day is simulated, using the same conditions, to develop preconditioned initial conditions for the following day. For the third simulation, again two days are simulated, this time using the observed winds for each of the two days modeled. The predictions using the prognostically derived and the objective analysis wind fields are significantly different, particularly for the primary pollutants. Comparing predictions to the observations did not favor any particular method of wind field preparation. In this case, when using the prognostically derived field, the simulations are very sensitive to boundary conditions. In contrast, when using the wind fields constructed by objective methods, the simulations became most sensitive to emissions and initial conditions. This comes directly from the different residence times in the domain, which are governed by the wind speed.     

Modeling urban air pollution in São Paulo,Brazil: sensitivity of model predicted concentrations to different turbulence parameterizations

Production and transport of urban air pollution were studied at São Paulo, Brazil, due to the importance of the megacity as source of pollutants and the flow pattern and topography of the region. An Eulerian air quality model was applied. An improved method for calculating vertical diffusivities was introduced in the model and the impact on the behavior of pollutants was analyzed. The approach includes both shear generated and buoyancy-driven turbulence in a continuous formulation that adequately represents turbulence evolution in the atmospheric boundary layer. Dispersion and transformation processes are well described by model simulations. The application of the proposed parameterization leads to increased predicted concentrations. Relative changes range from 1.2 to 2. Uncertainties in the emissions result in some disagreement between measured and simulated concentrations.     

Chemical characteristics of long-range transport aerosol at background sites in Korea

In this study, background concentration sites of Deokjeok and Gosan, which were deemed suitable for monitoring the impact of long-range transported air pollutants, were selected. An investigation of the source types of pollutants, their locations, and relative quantitative contributions to the particulate concentrations at both sites using appropriate methodologies to make initial estimations was conducted. Episodic measurements of PM_2.5, PM₁₀, and size distribution, along with its ion and carbon components were performed from 2005 to 2007, and a comprehensive analysis of the results was conducted utilizing back trajectory analysis. As for frequency of wind direction, it was quite apparent that the two sites are heavily influenced by air masses originating from the eastern and northern regions of China. For PM_2.5 and PM₁₀, the mass concentrations from north and east China were higher than other cases, originating from the ocean. In the northerly-wind case, meteorological properties for Deokjeok and Gosan and the influence of carbon emissions from northwest Korea resulted in a changing of air mass properties during transport. As was the case with mass concentration, the highest contribution for ionic and carbon components of PM_2.5 and PM₁₀ for both sites appeared for the westerly wind case. A specially high relative contribution, greater than 1.4 times, was apparent in the secondary aerosol case because of a large influence of long-range transported pollutants from east China. Carbon components exhibited different behaviors for the northerly and westerly wind cases compared with secondary aerosol. The major reason for this discrepancy appears to be the carbon emissions from northwest Korea.     

Source apportionment of PM<Subscript>10</Subscript> and PM<Subscript>2.5</Subscript> at multiple sites in the strait of Gibraltar by PMF: impact of shipping emissions

Background  

The impact of shipping emissions on urban agglomerations close to major ports and vessel routes is probably one of the lesser understood aspects of anthropogenic air pollution. Little research has been done providing a satisfactory comprehension of the relationship between primary pollutant emissions, secondary aerosols formation and resulting air quality.     

Development of a Speciated,Hourly, and Gridded Air Pollutants Emission Modeling System—A Case Study on the Precursors of Photochemical Smog in the Seoul Metropolitan Area,Korea

ABSTRACT

A speciated, hourly, and gridded air pollutants emission modeling system (SHEMS) was developed and applied in predicting hourly nitrogen dioxide (NO₂) and ozone (O₃) levels in the Seoul Metropolitan Area (SMA). The primary goal of the SHEMS was to produce a systemized emission inventory for air pollutants including ozone precursors for modeling air quality in urban areas.

The SHEMS is principally composed of three parts: (1) a pre-processor to process emission factors, activity levels, and spatial and temporal information using a geographical information system; (2) an emission model for each source type; and (3) a post-processor to produce report and input data for air quality models through database modeling. The source categories in SHEMS are point, area, mobile, natural, and other sources such as fugitive emissions. The emission database produced by SHEMS contains 22 inventoried compounds: sulfur dioxide, NO₂, carbon monoxide, and 19 speciated volatile organic compounds. To validate SHEMS, the emission data were tested with the Urban Airshed Model to predict NO₂ and O₃ concentrations in the SMA during selected episode days in 1994. The results turned out to be reliable in describing temporal variation and spatial distribution of those pollutants.     

Modeling mobile source emissions during traffic jams in a micro urban environment

Urbanization typically involves a continuous increase in motor vehicle use, resulting in congestion known as traffic jams. Idling emissions due to traffic jams combine with the complex terrain created by buildings to concentrate atmospheric pollutants in localized areas. This research simulates emissions concentrations and distributions for a congested street in Minsk, Belarus. Ground-level (up to 50-meters above the street's surface) pollutant concentrations were calculated using STAR (version 3.10) with emission factors obtained from the U.S. Environmental Protection Agency, wind speed and direction, and building location and size. Relative emissions concentrations and distributions were simulated at 1-meter and 10-meters above street level. The findings demonstrate the importance of wind speed and direction, and building size and location on emissions concentrations and distributions, with the leeward sides of buildings retaining up to 99 percent of the emitted pollutants within 1-meter of street level, and up to 77 percent 10-meters above the street.