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.     

Minimizing the effect of automotive pollution in urban geometry using mathematical optimization

One of the factors that needs to be considered during the layout of new urban geometry (e.g. street direction, spacing and width, building height restrictions) is the effect of the air pollution associated with the automotive transport that would use routes in this urban area. Although the pollution is generated at street level, its effect can be widespread due to interaction of the pollutant dispersion and diffusion with the wind speed and direction. In order to study the effect of a new urban geometry on the pollutant levels and dispersion, a very time-consuming experimental or parametric numerical study would have to be performed. This paper proposes an alternative approach, that of combining mathematical optimization with the techniques of computational fluid dynamics (CFD). In essence, the meteorological information as represented by a wind rose (wind speed and direction), is used to calculate pollutant levels as a function of urban geometry variables: street canyon depth and street canyon width. The pollutant source specified in conjunction with a traffic scenario with CO is used as pollutant. The main aim of the study is to be able to suggest the most beneficial configuration of an idealized urban geometry that minimizes the peak pollutant levels due to assumed traffic distributions. This study uses two mathematical optimization methods. The first method is implemented through a successive maximization–minimization approach, while the second method determines the location of saddle points of the pollutant level, considered as a function of urban geometry and wind rose. Locally, a saddle point gives the best urban geometry for the worst meteorological scenario. The commercial CFD code, STAR-CD, is coupled with a version of the DYNAMIC-Q optimization algorithm of Snyman, first to successively locate maxima and minima in a min–max approach; and then to locate saddle points. It is shown that the saddle-point method is more cost-effective. The methodology presented in this paper can readily be extended to optimize traffic patterns for existing geometry or in the development of geometry modification for pollution control or toxic releases.     

An Air Quality Data Analysis System for Interrelating Effects,Standards, and Needed Source Reductions: Part 4. A Three-Parameter Averaging-Time Model

Urban air pollutant concentration data often tend to fit a two-parameter averaging-time model having three characteristics: (1) pollutant concentrations are (two-parameter) lognormally distributed for all averaging times; (2) median concentrations are proportional to averaging time raised to an exponent; and (3) maximum concentrations are approximately inversely proportional to averaging time raised to an exponent. Concentration data obtained near many isolated point sources and in some urban areas often do not fit a two-parameter lognormal distribution. An increment (either positive or negative) can be added to each such concentration in order to fit the data instead to a three-parameter lognormal distribution. This increment has been incorporated as the third parameter in a new three-parameter averaging-time model that can be used in both point-source and urban settings. Examples show how this new model can be used to analyze SO₂ concentration data obtained near a point source to determine the degree of emission reduction needed to achieve the national ambient air quality standards.     

An Atmospheric Diffusion Model for Metropolitan Areas

An urban diffusion model, which does not require the use of an electronic computer, is presented. The main simplifying assumptions are that continuous pollutant sources are uniformly distributed over the urban area and vertical diffusion occurs until the effluent from each line source reaches the top of the mixing layer, after which the effluent is uniformly distributed through the mixing layer. After the appropriate vertical diffusion coefficient is specified, the calculated concentration is a function of source strength, linear dimension of the metropolis, mixing depth, and wind speed. The calculated concentration is interpreted either as a representative maximum concentration or, through integration, as the average concentration over the metropolitan area. When a representative pollutant concentration is known, the model may be used to determine the apparent “uniform” source strength.     

Modeling distributions of air pollutant concentrations—III. The hybrid deterministic-statistical distribution approach

A general modeling approach is proposed to predict the distribution of air pollutant concentrations and in particular the upper percentiles. The approach is hybrid in that it combines features of both deterministic and statistical distribution models. These features include causality and the attempted quantification of stochastic variability and uncertainty. The properties of deterministic and statistical distribution models are discussed separately and this clarifies the contribution that can be made by hybrid modeling. In this way the underlying assumptions are clearly presented. The range of successful applications of the hybrid approach is briefly reviewed. These involve relatively inert pollutants from urban/industrial, point source, elevated point source and roadway emissions. Areas of further research are outlined which would enhance the routine use of the approach and extend its application. Sufficient development has been undertaken, however, that the present standard set of air pollutant dispersion models could be easily updated to provide hybrid models capable of predicting frequency distributions of air pollutant levels under stipulated assumptions.     

Evolution of air quality in the Sao Paulo metropolitan area and its relation with public policies

The Sao Paulo Metropolitan Area (SPMA) is one of the largest urban regions in the world, with more than 17 million inhabitants, about 2000 major industrial facilities, and more than 6 million vehicles based on diesel, gasoline, and ethanol. The area is thus a representative example of large urban region. The accumulated data collected by a network of air quality measuring stations, distributed throughout the SPMA, enables the monitoring of the air quality and is an adequate source of information for checking the effect of air quality control measures in the region. The present work shows that, although the levels of primary air pollutants have decreased over the last 20 years, events with high levels of NO₂, CO, particulate material and ozone still take place. In the last five years, ozone has become the most problematic pollutant, in view of the high frequency of peak events. Increased control of emission sources and adequate planning of the urban area, especially concerning the traffic system, are both necessary in order to keep pollution in the area under established levels.     

Assessment of traffic-related air pollution in two street canyons in Paris: implications for exposure studies

The small-scale spatial variability of air pollution observed in urban areas has created concern about the representativeness of measurements used in exposure studies. It is suspected that limit values for traffic-related pollutants may be exceeded near busy streets, although respected at urban background sites. In order to assess spatial concentration gradients and identify weather conditions that might induce air pollution episodes in urban areas, different sampling and modelling techniques were studied.Two intensive monitoring campaigns were carried out in typical street canyons in Paris during winter and summer. Steep cross-road and vertical concentration gradients were observed within the canyons, in addition to large differences between roadside and background levels. Low winds and winds parallel to the street axis were identified as the worst dispersion conditions. The correlation between the measured compounds gave an insight into their sources and fate. An empirical relationship between CO and benzene was established. Two relatively simple mathematical models and an algorithm describing vertical pollutant dispersion were used. The combination of monitoring and modelling techniques proposed in this study can be seen as a reliable and cost-effective method for assessing air quality in urban micro-environments. These findings may have important implications in designing monitoring studies to support investigation on the health effects of traffic-related air pollution.     

Inhalation transfer factors for air pollution health risk assessment

To facilitate routine health risk assessments, we develop the concept of an inhalation transfer factor (ITF). The ITF is defined as the pollutant mass inhaled by an exposed individual per unit pollutant mass emitted from an air pollution source. A cumulative population inhalation transfer factor (PITF) is also defined to describe the total fraction of an emitted pollutant inhaled by all members of the exposed population. In this paper, ITFs and PITFs are calculated for outdoor releases from area, point, and line sources, indoor releases in single zone and multizone indoor environments, and releases within motor vehicles. Typical PITFs for an urban area from emissions outdoors are approximately 10(-6)-10(-3). PITFs associated with emissions in buildings or in moving vehicles are typically much higher, approximately 10(-3)-10(-1).     

Self-organized criticality of air pollution

In this work, we investigate the frequency-size distribution of three pollution indexes (PM₁₀, NO₂ and SO₂) in Shanghai. They are well approximated by power-law distributions, which suggest that air pollution might be a manifestation of self-organized criticality. We introduce a new numerical sandpile model with decay coefficient to reveal inherent dynamic mechanism of air pollution. Only changing the number value of decay coefficient of pollutants, this model gives a good simulation of three pollutants' statistical characteristic. This work shows that it is the self-organized criticality of the air pollutants that results in the temporal variation of air pollutant indexes and the minor air pollution sources can trigger the occurrence of large pollutant events by SOC behavior.     

Rapid urban growth,land-use changes and air pollution in Santiago,Chile

This paper is a contribution to the understanding of the topoclimatic and environmental geography of the basin where Santiago — one of the most polluted Latin American city – is located. In the first part, land-use change is analysed looking at the climatic transformation caused by the rapid transit from natural semiarid surface to urban areas. In the second part, seasonal weather and daily cycles of slope winds and the available ventilation are described trying to relate those patterns with the spatial distribution of air pollution. A combination of meteorological, geographical and cultural factors explain extreme air pollution events: meteorologically, Santiago is under permanent subsidence inversion layers. Geographically, the city is located in a closed basin surrounded by mountains. Culturally, the urban area has the highest population concentration (40% of the national total), industries (near 70% of the total) and vehicles, which are the main sources of smog. The urban and suburban transport system is based on a large number of buses (diesel) and private cars, both experiencing a rapid growth from the past few years. The city and specially the transport system generates high emissions of pollutant, but the natural semiarid deforested soils and slopes are also important sources. The local wind system can explain the differential spatial distribution on the concentration of air pollutants in the city and its periphery. In winter (rain season) concentrations of particulate matter are higher at the centre and the SW part of the city. The andean piedmont area (E part of the city) shows minimum values, suggesting major ventilation effects of slope and valley winds. Ozone exceeds air quality standards in summer (dry season) at all sites in the centre and periphery. However, the O₃-concentrations are higher on preferred residential areas located at the piedmont area (E part of the city), suggesting air pollution transport effects. Currently, there is no consideration of these local climatic features in the process of urban planning.     

Inhalation Transfer Factors for Air Pollution Health Risk Assessment

ABSTRACT

To facilitate routine health risk assessments, we develop the concept of an inhalation transfer factor (ITF). The ITF is defined as the pollutant mass inhaled by an exposed individual per unit pollutant mass emitted from an air pollution source. A cumulative population inhalation transfer factor (PITF) is also defined to describe the total fraction of an emitted pollutant inhaled by all members of the exposed population. In this paper, ITFs and PITFs are calculated for outdoor releases from area, point, and line sources, indoor releases in single zone and multizone indoor environments, and releases within motor vehicles. Typical PITFs for an urban area from emissions outdoors are ~10^-6–10^-3. PITFs associated with emissions in buildings or in moving vehicles are typically much higher, ~10^-3–10^-1.     

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.     

Urban nonpoint source pollution buildup and washoff models for simulating storm runoff quality in the Los Angeles County

Many urban nonpoint source pollution models utilize pollutant buildup and washoff functions to simulate storm runoff quality of urban catchments. In this paper, two urban pollutant washoff load models are derived using pollutant buildup and washoff functions. The first model assumes that there is no residual pollutant after a storm event while the second one assumes that there is always residual pollutant after each storm event. The developed models are calibrated and verified with observed data from an urban catchment in the Los Angeles County. The application results show that the developed model with consideration of residual pollutant is more capable of simulating nonpoint source pollution from urban storm runoff than that without consideration of residual pollutant. For the study area, residual pollutant should be considered in pollutant buildup and washoff functions for simulating urban nonpoint source pollution when the total runoff volume is less than 30 mm.     

Air pollution dispersion within urban street canyons

A semi-empirical mathematical model, Urban Street Model (USM), is proposed to efficiently estimate the dispersion of vehicular air pollution in cities. This model describes urban building arrangements by combining building density, building heights and the permeability of building arrangements relative to wind flow. To estimate the level of air pollution in the city of Krasnoyarsk (in Eastern Siberia), the spatial distribution of pollutant concentrations off roadways is calculated using Markov's processes in USM. The USM-predicted numerical results were compared with field measurements and with results obtained from other frequently used models, CALINE-4 and OSPM. USM consistently yielded the best results. OSPM usually overestimated pollutant concentration values. CALINE-4 consistently underestimated these values. For OSPM, the maximum differences were 160% and for CALINE-4 about 400%. Permeability and building density are necessary parameters for accurately modeling urban air pollution and influencing regulatory requirements for building planning.     

The Transport of Suspended Particulates as a Function of Wind Direction and Atmospheric Conditions

Linear regression of high volume air sampler data and various meteorological parameters was used to determine a suspended particulate air pollution climatology for Albany, NY. A new method for exhibiting associations between wind direction and pollutant levels using correlation coefficients is presented. Correlations between wind direction distribution frequency and other meteorological parameters is employed to help explain differences in correlations for direction with suspended particulate levels. Results show that high particulate concentrations correlate well with southerly wind flow throughout the study area, regardless of relative location of receptor to local sources. This suggests that ambient background concentrations inherent in different air masses more consistently affected suspended particulate levels than did the diffusion from local sources during the study period. Maximum particulate advection occurs under conditions of good mixing of the boundary layer and moderate wind speeds and is enhanced further in the absence of removal processes such as rainout and washout. Trajectory analysis of selected days indicates a definite relationship between path and origin of the wind flow and regional average particulate concentration.     

Effects of Strength and Position of Pollutant Source on Pollutant Dispersion Within an Urban Street Canyon

A two-dimensional numerical model for simulating airflow and pollutant dispersion inside an urban street canyon was first developed using the FLUENT code, and then it was validated against a wind tunnel experiment. Then the effects of strength and position of pollutant sources on pollutant dispersion within an urban street canyon were investigated numerically. The numerical results showed that the dimensionless pollutant concentrations within the urban street canyon were independent from the source strength. The results also revealed that the pollutant distributions inside the urban street canyon with a two-lane road were influenced significantly by the positions of the two sources: 1) the closer the two sources were to the street center of the canyon, the lower the pollutant concentrations on the leeward wall and at the human respiration level in the leeward footpath became; 2) the pollutant concentrations on the windward wall and at the human respiration level in the windward footpath were not sensitive to the locations of the two sources as long as the source on the windward lane was situated outside the small recirculation zone at the bottom corner of the canyon windward wall; 3) the pollutant concentrations on the lower parts of the windward and leeward walls as well as in the two footpaths increased greatly when the two sources were moved from outside into the small recirculation zones.     

A new moss biomonitoring method for detecting sources of small scale pollution

A new simple method is proposed for identifying sources of small scale pollution, by determining the tissue concentrations of pollutants in terrestrial mosses. The method is based on spatial characterization of the processes that generate accumulation of pollutants in these organisms. The steps involved in implementing and applying the method are: (i) obtaining data on pollutants in moss samples collected at least at 35 pairs of sampling sites (SS) separated by 1 km distance; (ii) study of the distribution of the differences in concentration between the pairs of SS, eliminating pairs affected by foci that generate small scale processes; (iii) characterization of the resulting normal distributions and calculation, for different levels of significance, of the probability of a value lying within these distributions, and (iv) application of the calculated quantiles to data corresponding to the differences in concentrations between pairs of SS in the vicinities of foci of small scale pollution, to determine which elements can be considered as pollutants. Given the small number of data required once the distribution of the differences has been established, the method is an inexpensive, efficient way of establishing the probability that a pollutant is being emitted from a particular source. The method is very useful for verifying the results of pollution inventories, evaluating new technologies and improving the design of regional networks for biomonitoring of air quality with terrestrial mosses.     

工业点源大气污染扩散空间信息系统

开发了一个基于高斯扩散的大气污染扩散空间信息系统,用于模拟工业点源污染对区域大气质量的影响。该工业点源污染模型包括工业点源数据库、扩散参数、气象条件和大气质量评价4个主要数据库。用该模型计算上海市主要工业区的SO2排放,结果表明,该模型为模拟SO2污染扩散提供了一个有效便捷的方法。     

Numerical Modeling of the Transport Diffusion and Deposition of Pollutants For Regions and Extended Scales

There is an emerging need to develop understanding and predictive capability for the transport, diffusion, and deposition of pollutants on regional and extended spatial scales. Some recent developments in the numerical simulation of pollutant transport and diffusion are reviewed and summarized herein, including case studies of model validation whenever’available. The efforts reported include: (a) the development and verification of a Lagrangian large-cloud diffusion code for intermediate to extended scales; (b) a hybrid Lagrangian-Eulerian transport-diffusion code for simulating pollutant distributions in transient stratified shear flow; (c) a meteorological submodel for determining a mass-consistent wind field on a regional scale suitable as input to a regional air pollution model; and (d) the development and initial verification of a multi-box regional air pollution model for the San Francisco Bay Area utilizing a mass-consistent wind field submodel.