Ultrafine particle fluxes above four major European cities

Little information is known about the behaviour of ultrafine particles (UFP) on a citywide scale. Total particle number flux, dominated by UFP, and other meteorological parameters were collected from tower sites in Manchester, London, Edinburgh and Gothenburg between 1999 and 2006 using the eddy covariance technique. Averaged diurnal cycles were produced for particle number flux, concentration, sensible heat flux, emission velocity, friction velocity, wind speed and temperature. UFP flux cycles showed clear diurnal trends which were linked to traffic activity and local sources. Wind sector analysis showed contributions to flux from local heavily urbanised areas. A simple parameterised model linking UFP flux to traffic activity, sensible heat and friction velocity above the city was produced.     

Modeling air/sea flux parameters in a coastal area: A comparative study of results from the TOGA COARE model and the NOAA Buoy model

Because estuaries and coastal regions are particularly susceptible to nutrient over-enrichment due to their close proximity to source-rich regions, a goal of the BRACE study was to improve estimates of nitrogen air/sea transfer rates in the Tampa Bay Estuary. Our objective was to critically evaluate two air/sea gas exchange models to determine their efficacy for use in a coastal region, with the ultimate goal of improving nitrogen exchange estimates in Tampa Bay. We used meteorological data and oceanographic parameters collected hourly at an instrumented tower located in Middle Tampa Bay, Florida. The data was used to determine the friction velocity and the turbulent flux of heat and moisture across the air/sea interface and then compared with modeled parameters at the same offshore site. On average both models underpredicted sensible heat flux and there was considerable scatter in the data during stable conditions, indicating that nitrogen gas exchange rates may also be underestimated. Model improvement, however, was observed with friction velocity comparisons. Model inter-comparisons of sensible heat flux and friction velocity suggest excellent agreement between the TOGA COARE and the NOAA Buoy models, but model estimated heat transfer coefficients and latent heat fluxes did not agree as well. Based on our analysis, we conclude that both models are suitable for use in a coastal environment to estimate nitrogen air/sea gas exchange, although the NOAA Buoy model requires fewer meteorological inputs. However, if the purpose is to conduct more sophisticated microscale modeling of air/sea interactions, we recommend the TOGA COARE model.     

A Multivariable Model for Atmospheric Dispersion Predictions

In conjunction with a 15-month air quality survey of Jacksonville, Fia., a mathematical model has been developed to describe the dispersion of atmospheric pollutants. The source inventory used with the model was compiled, in part, from the data obtained from the sampling of all major sources within the area. The major sources were considered separately from the one-mile square area sources which accounted for the remainder of the emissions. Meteorological data was recorded continuously in the city including vertical temperature observations to 750 ft. The model was compiled in FORTRAN and can be used for both gaseous and particulate pollutants, by utilizing proper decay rates. The variant nature of meteorological parameters and emission rates are considered. The ground level concentrations of several pollutants which were determined for 24 hr periods at 11 sites and continuously at two other sites were used to check the model. A limited tracer study was carried out in conjunction with the project.     

Comparison between the atmospheric boundary layer in Paris and its rural suburbs during the ECLAP experiment

The ECLAP experiment has been performed during the winter of 1995 in order to study the influence of the urban area of Paris on the vertical structure and diurnal evolution of the atmospheric boundary layer, in situations favourable to intense urban heat island and pollution increase. One urban site and one rural site have been instrumented with sodars, lidars and surface measurements. Additional radiosondes, 100 m masts and Eiffel Tower data were also collected. This paper gives a general overview of this experiment, and presents results of the analysis of four selected days, characterized by various wind directions and temperature inversion strengths. This analysis, which consists in a comparison between data obtained in the two sites, has been focused on three parameters of importance to the ABL dynamics: the standard deviation of vertical velocity, the surface sensible heat flux, and the boundary layer height. The vertical component of turbulence is shown to be enhanced by the urban area, the amplitude of this effect strongly depending on the meteorological situation. The sensible heat flux in Paris is generally found larger than in the rural suburbs. The most frequent differences range from 25–65 W m^-2, corresponding to relative differences of 20–60%. The difference of unstable boundary layer height between both sites are most of the time less than 100 m. However, sodar and temperature data show that the urban influence is enhanced during night-time and transitions between stable and unstable regimes.     

Pseudo-source parameters for flares: Derivation,implementation, and comparison

The United States Environmental Protection Agency (US EPA) flare pseudo-source parameters are over 30 years old and few dispersion modellers understand their basis and underlying assumptions. The calculation of plume rise from the user inputs of pseudo-stack diameter, temperature and velocity have the most influence on air dispersion model predictions of ground-level concentrations. Regulatory jurisdictions across Canada, the United States and around the world have adopted their own approach to pseudo-source parameters for flares; all relate buoyancy flux to the heat release rate, none consider momentum flux and flare tip downwash as adopted by the Alberta Energy Regulator (AER). This paper derives the plume buoyancy flux for flares burning a gas in terms of combustion variables readily known or calculated without simplifying assumptions. Dispersion model prediction sensitivity to flared gas composition, temperature and velocity, and ambient conditions are now correctly handled by the AER approach. The AER flare pseudo-source parameters are based on both the buoyancy and momentum flux, thus conserving energy and momentum. The AER approach to calculate the effective source height for flares during varying wind speeds is compared to the US EPA approach. Instead of a constant source for all meteorological conditions, multiple co-located sources with varying effective stack height and diameter are used. AERMOD is run with the no stack tip downwash option as flare stack tip downwash is accounted for in the effective stack height rather than the AERMOD model calculating the downwash incorrectly using the pseudo-source parameters. The modelling approaches are compared for an example flare. Maximum ground level predictions change, generally increasing near the source and decreasing further away, with the AER flare pseudo-source parameters. It's time to update how we model flares.

Implications: What are the implications of continuing to model flare source parameters using the overly simplified US EPA approach? First, the regulators perpetuate the myths that the flare source height, temperature, diameter and velocity are constant for all wind speeds and ambient temperatures. Second, that it is acceptable to make simplifying assumptions that violate the conservation of momentum and energy principles for the sake of convenience. Finally, regulatory decisions based on simplified source modelling result in predictions that are not conservative (or realistic). The AER regulatory approach for flare source parameters overcomes all of these shortcomings. AERflare is a publicly available spreadsheet that provides the “correct” inputs to AERMOD.     

The Use of Artificial Activable Trace Elements to Monitor Pollutant Source Strengths and Dispersal Patterns

A tracer technique using certain of the rare earth elements which are easily activated by neutrons has been developed for the analysis of air pollution problems. Studies employing these tracers were made to determine whether the available meteorological dispersion models can be used effectively to describe pollution emissions from selected industries in the vicinity of Albany, Oregon. The Gaussian plume model was found to be satisfactory for the moderately intense turbulence fields which characterize Stability Types B, C, and D, including cases in which the pollution was trapped by an inversion layer aloft. For sources near ground level, however, it was necessary to make allowance for urban influences on plume dispersion. A box model best described the observed dispersal pattern when the upward penetration of the very intense turbulence of Stability Type A was limited by an inversion layer aloft. These meteorological models were applied using a “blind” experimental procedure to predict the emission rates of the effluent from multiple sources of air pollution in the Albany area. It was found that these techniques can be used to predict the rate of emission within a factor of two for multiple sources consisting of three stacks.     

Development of a nonlocal convective mixing scheme with varying upward mixing rates for use in air quality and chemical transport models

BACKGROUND, AIM, AND SCOPE: Asymmetrical convective non-local scheme (CON) with varying upward mixing rates is developed for simulation of vertical turbulent mixing in the convective boundary layer in air quality and chemical transport models. MATERIALS AND METHODS: The upward mixing rate form the surface layer is parameterized using the sensible heat flux and the friction and convective velocities. Upward mixing rates varying with height are scaled with an amount of turbulent kinetic energy in layer, while the downward mixing rates are derived from mass conservation. RESULTS: This scheme provides a less rapid mass transport out of surface layer into other layers than other asymmetrical convective mixing schemes. DISCUSSION: In this paper, we studied the performance of a nonlocal convective mixing scheme with varying upward mixing in the atmospheric boundary layer and its impact on the concentration of pollutants calculated with chemical and air-quality models. This scheme was additionally compared versus a local eddy-diffusivity scheme (KSC). Simulated concentrations of NO(2) and the nitrate wet deposition by the CON scheme are closer to the observations when compared to those obtained from using the KSC scheme. CONCLUSIONS: Concentrations calculated with the CON scheme are in general higher and closer to the observations than those obtained by the KSC scheme (of the order of 15-20%). Nitrate wet deposition calculated with the CON scheme are in general higher and closer to the observations than those obtained by the KSC scheme. RECOMMENDATIONS AND PERSPECTIVES: To examine the performance of the scheme, simulated and measured concentrations of a pollutant (NO(2)) and nitrate wet deposition was compared for the year 2002. The comparison was made for the whole domain used in simulations performed by the chemical European Monitoring and Evaluation Programme Unified model (version UNI-ACID, rv2.0) where schemes were incorporated.     

高架连续点源落地浓度预测中风速的确定

高架连续点源污染物排放落地浓度是大气环境影响预测的主要内容。由于大气污染物扩散明显受气象条件尤其是风速的影响,而现有预测模型中对于风速的取值都是按经验值来确定的。通过分析在不同气象和烟源条件下,平均风速的计算方法对烟羽抬升高度以及最大落地浓度产生的影响,与实测值相比较确定了风速取值的合理方法,缩小了预测偏差。     

Air Quality Screening Model with Long-Term Averaging

A simple screening model is presented for estimating maximum ground level concentrations of air pollutants from single elevated buoyant sources of emissions. The model, which incorporates plausible error margins, is based on the Gaussian dispersion formula. Maximum longer-term (3, 8, 24 h) concentrations are estimated using a joint probability analysis of the persistence of meteorological worst case events.     

Analysis of an anomalous case of high air pollution concentration in Turin after a foehn event

A case of unusually high concentrations of some urban air pollutants (CO, NO, SO₂) in Turin (Northwestern Italy) is presented. This episode occurred during the late afternoon of 7 November 1995. This day was characterised by a strong northern foehn event in the morning, which followed the passage of a cold front. The analysis has been carried out by means of data derived from the urban and suburban air quality monitoring networks, of meteorological data (wind velocity, temperature and relative humidity) from the same network and from other networks in the region, and of the output of the numerical model LAMBO (operatively used by the Regional Meteorological Service of Emilia Romagna). The analysis of meteorological data appears to be in good correlation with the distribution of the air pollutant concentrations; in particular, the high concentrations observed in the late afternoon are due to a strong thin inversion layer near the ground, developing immediately after the sudden end of the foehn episode.     

Chemical transport models

Background, aim, and scope  Improving the parameterization of processes in the atmospheric boundary layer (ABL) and surface layer, in air quality and chemical transport models. To do so, an asymmetrical, convective, non-local scheme, with varying upward mixing rates is combined with the non-local, turbulent, kinetic energy scheme for vertical diffusion (COM). For designing it, a function depending on the dimensionless height to the power four in the ABL is suggested, which is empirically derived. Also, we suggested a new method for calculating the in-canopy resistance for dry deposition over a vegetated surface. Materials and methods  The upward mixing rate forming the surface layer is parameterized using the sensible heat flux and the friction and convective velocities. Upward mixing rates varying with height are scaled with an amount of turbulent kinetic energy in layer, while the downward mixing rates are derived from mass conservation. The vertical eddy diffusivity is parameterized using the mean turbulent velocity scale that is obtained by the vertical integration within the ABL. In-canopy resistance is calculated by integration of inverse turbulent transfer coefficient inside the canopy from the effective ground roughness length to the canopy source height and, further, from its the canopy height. Results  This combination of schemes provides a less rapid mass transport out of surface layer into other layers, during convective and non-convective periods, than other local and non-local schemes parameterizing mixing processes in the ABL. The suggested method for calculating the in-canopy resistance for calculating the dry deposition over a vegetated surface differs remarkably from the commonly used one, particularly over forest vegetation. Discussion  In this paper, we studied the performance of a non-local, turbulent, kinetic energy scheme for vertical diffusion combined with a non-local, convective mixing scheme with varying upward mixing in the atmospheric boundary layer (COM) and its impact on the concentration of pollutants calculated with chemical and air-quality models. In addition, this scheme was also compared with a commonly used, local, eddy-diffusivity scheme. Simulated concentrations of NO₂ by the COM scheme and new parameterization of the in-canopy resistance are closer to the observations when compared to those obtained from using the local eddy-diffusivity scheme. Conclusions  Concentrations calculated with the COM scheme and new parameterization of in-canopy resistance, are in general higher and closer to the observations than those obtained by the local, eddy-diffusivity scheme (on the order of 15–22%). Recommendations and perspectives  To examine the performance of the scheme, simulated and measured concentrations of a pollutant (NO₂) were compared for the years 1999 and 2002. The comparison was made for the entire domain used in simulations performed by the chemical European Monitoring and Evaluation Program Unified model (version UNI-ACID, rv2.0) where schemes were incorporated.     

Coupling of the Weather Research and Forecasting Model with AERMOD for pollutant dispersion modeling. A case study for PM10 dispersion over Pune,India

The prediction of spatial variation of the concentration of a pollutant governed by various sources and sinks is a complex problem. Gaussian air pollutant dispersion models such as AERMOD of the United States Environmental Protection Agency (USEPA) can be used for this purpose. AERMOD requires steady and horizontally homogeneous hourly surface and upper air meteorological observations. However, observations with such frequency are not easily available for most locations in India. To overcome this limitation, the planetary boundary layer and surface layer parameters required by AERMOD were computed using the Weather Research and Forecasting (WRF) Model (version 2.1.1) developed by the National Center for Atmospheric Research (NCAR). We have developed a preprocessor for offline coupling of WRF with AERMOD. Using this system, the dispersion of respirable particulate matter (RSPM/PM10) over Pune, India has been simulated. Data from the emissions inventory development and field-monitoring campaign (13–17 April 2005) conducted under the Pune Air Quality Management Program of the Ministry of Environment and Forests (MoEF), India and USEPA, have been used to drive and validate AERMOD. Comparison between the simulated and observed temperature and wind fields shows that WRF is capable of generating reliable meteorological inputs for AERMOD. The comparison of observed and simulated concentrations of PM10 shows that the model generally underestimates the concentrations over the city. However, data from this single case study would not be sufficient to conclude on suitability of regionally averaged meteorological parameters for driving Gaussian models like AERMOD and additional simulations with different WRF parameterizations along with an improved pollutant source data will be required for enhancing the reliability of the WRF–AERMOD modeling system.     

Estimating PM10 air concentrations from dust storms in Iraq,Kuwait and Saudi Arabia

A model for the emission of PM₁₀ dust has been constructed using the concept of a threshold friction velocity which is dependent on surface roughness. Surface roughness in turn was correlated with geomorphology or soil properties for Kuwait, Iraq, part of Syria, Saudi Arabia, the United Arab Emirates and Oman. The PM₁₀ emission algorithm was incorporated into a Lagrangian transport and dispersion model. PM₁₀ air concentrations were computed from August 1990 through August 1991. The model predicted about the right number of dust events over Kuwait (events occur 18% of the time). The model results agreed quantitatively with measurements at four locations in Saudi Arabia and one in Kuwait for one major dust event (>1000 μg/m³). However, for smaller scale dust events (200–1000 μg/m³), especially at the coastal sampling locations, the model substantially over-predicted the air concentrations. Part of the over-prediction was attributed to the entrainment of dust-free air by the sea breeze, a flow feature not represented by the large-scale gridded meteorological data fields used in the model computation. Another part of the over-prediction was the model's strong sensitivity to threshold friction velocity and the surface soil texture coefficient (the soil emission factor), and the difficulty in accurately representing these parameters in the model. A comparison of the model predicted PM₁₀ spatial pattern with the TOMS satellite aerosol index (AI) yielded a spatial pattern covering a major portion of Saudi Arabia that was quite similar to the observed AI pattern.     

Simulation of short-range diffusion experiment in low-wind convective conditions

A previously obtained analytical solution to model the short-range dispersion of pollutants in low winds from surface releases has been used to simulate diffusion tests conducted during winter in weakly convective conditions at the Indian Institute of Technology (IIT) Delhi. The turbulence parameterization based on friction velocity has been tested to simulate diffusion experiment. Such a parameterization in this study is considered justifiable on two counts: (1) prevailing meteorological and dispersion conditions have been generally of weakly unstable type as indicated by values of Monin–Obukhov length and bulk Richardson number, (2) uncertainties associated with the application of convective velocity based similarity parameterization to simulation of diffusion experiment at IIT Delhi, resulting in significant underprediction in most of the cases (Atmos. Environ. 30 (1996a) 1137). With this parameterization, the model simulations have improved considerably and compare reasonably well with the observations. Further, the results from a simple Gaussian model have been included for comparison. This study is in continuation of the work done earlier to simulate near-source dispersion in weak winds.     

Spatiotemporal Features of Severe Air Pollution in Northern Taiwan (8 pp)

Background, Aims and Scope This research attempted to identify the dominant factors simultaneously affecting the airborne concentrations of five air pollutants with principal component analysis and to determine the meteorologically related parameters that cause severe air-pollution events. According to the definition of subPSI and PSI values through the U.S. EPA, the historical raw data of five criteria air pollutants, SO2, CO, O3, PM10 and NO2, were calculated as daily subPSI values. In addition to the airborne concentrations, this study simultaneous collected the surface meteorological parameters of the Taipei meteorological station, established by the Central Weather Bureau. Methods Principal component analysis was conducted to screen severe air pollution scenarios for five air pollutants: SO2, CO, O3, PM10 and NO2. The concentrations of various air pollutants measured at 17 air-quality stations in northern Taiwan from 1995 to 2001 were transformed into daily subPSI values. The correlation analysis of the five air pollutants and four meteorological parameters (wind speed, temperature, mixing height and ventilation rate) were included in this research. After screening severe air pollution scenarios, this study recognized the synoptic patterns easily causing the severe air-pollution events. Results and Discussion Analytical results showed that the eigenvalues of the first two principal components for SO2, CO, O3, PM10 and NO2 were greater than 1. The first component of five air pollutants explained 64, 64, 67, 76 and 63% of subPSI variance for SO2, CO, O3, PM10 and NO2, respectively. Only the correlation coefficient of NO2 and CO had statistically significant positive values (0.82); other pollutant pairs presented medium (0.4 to 0.7) or low (0 to 0.4) positive values. The correlation coefficients for air pollutants and three meteorological parameters (wind speed, mixing height and ventilation index) were medium or low negative values. In northern Taiwan, spring was most likely induced high concentrations and the component scores of the first component for SO2, CO, PM10 and NO2; summer was the worst season that caused high O3 episodes. Consequently, the analytical results of factor loadings for the first principal component and emission inventory of various sources revealed that mobile sources were dominant factors affecting ambient air quality in northern Taiwan. Conclusion According to the results of principal component analysis for the five air pollutants, the first two of 17 components were cited as major factors and explained 71% of subPSI variance. Based on the inventory of NOx emissions and the isopleth diagram of factor loading for the first component, mobile sources in the southwest Taipei City accounted for the highest factor loading values and emission inventory values. Synoptic analysis and principal component analysis demonstrated that three types of weather patterns (high-pressure recirculation, prefrontal warm sector and the southwesterly wind system) easily caused the severe air-pollution scenarios. In summary, if severe air-pollution days occurred, the average meteorological parameters experienced adverse conditions for diffusing air pollutants; that is, the average values of wind speed, mixing height and ventilation index were lower than 2.1 ms-1, 360 m and 800 m2s-1, respectively. If one of the three synoptic patterns were to occur in combination with adverse meteorological conditions, severe air-pollution events would be developed. Recommendation and Outlook By utilizing synoptic patterns, this work found three weather systems easily caused severe air-pollution events over northern Taiwan. Analytical results showed, respectively, the wind speed and mixing height were less than 2.1 m/s and 360 m during severe air-pollution events.     

Testing the importance of accurate meteorological input fields and parameterizations in atmospheric transport modelling using dream - validation against ETEX-1

A tracer model, the DREAM, which is based on a combination of a near-range Lagrangian model and a long-range Eulerian model, has been developed. The meteorological meso-scale model, MM5V1, is implemented as a meteorological driver for the tracer model. The model system is used for studying transport and dispersion of air pollutants caused by a single but strong source as, e.g. an accidental release from a nuclear power plant. The model system including the coupling of the Lagrangian model with the Eulerian model are described. Various simple and comprehensive parameterizations of the mixing height, the vertical dispersion, and different meterological input data have been implemented in the combined tracer model, and the model results have been validated against measurements from the ETEX-1 release. Several different statistical parameters have been used to estimate the differences between the parameterizations and meterological input data in order to find the best performing solution.     

Effect of shoreline meteorological measurements on NOAA Buoy model prediction of coastal air–sea gas transfer

The NOAA Buoy model is currently used to estimate the air–sea transfer rates of highly soluble gases over coastal water bodies, such as Tampa Bay, using offshore meteorological measurements. Since a goal of the BRACE study was to improve estimates of nitrogen deposition over Tampa Bay, our objective was to investigate if the model accurately predicts gas transfer when shoreline input data are used in lieu of offshore measurements. To accomplish this objective, we compared over-water measurements of sensible heat with NOAA Buoy model predictions using both offshore and shoreline meteorology. In the summer months, the apparent daytime influence of land surface heating on air temperature produces a higher air than water temperature at the shoreline. For the NOAA Buoy model, this yields stable atmospheric conditions and thus under-predicts the over-water exchange rates for a shallow estuary. If the data records are removed from the model for periods when air temperature is 4.8 K greater than the water temperature, the shoreline and over-water transfer rates are in reasonable agreement.     

Analysis of air quality observations with the aid of the source-receptor relationship approach

In this study, an attempt was made to analyze time series of air quality measurements (O3, SO2, SO4(2-), NOx) conducted at a remote place in the eastern Mediterranean (Finokalia at Crete Island in 1999) to obtain concrete information on potential contributions from emission sources. For the definition of a source-receptor relationship, advanced meteorological and dispersion models appropriate to identify "areas of influence" have been used. The model tools used are the Regional Atmospheric Modeling System and the Lagrangian-type particle dispersion model (forward and backward in time), with capabilities to derive influence functions and definition of "areas of influence." When high levels of pollutants have been measured at the remote location of Finokalia, particles are released from this location (receptor) and traced backward in time. The influence function derived from particle distributions characterizes dispersion conditions in the atmosphere and also provides information on potential contributions from emission sources within the modeling domain to this high concentration. As was shown in the simulation results, the experimental site of Finokalia in Crete is influenced during the selected case studies, primarily by pollutants emitted from the urban conglomerate of Athens. Secondarily, it is influenced by polluted air masses arriving from Italy and/or the Black Sea Region. For some specific cases, air pollutants monitored at Finokalia were possibly related to war activities in the West Balkan Region (Kosovo).     

Determination of the latent heat flux in fog

The latent heat flux has been determined during a fog situation by using a method based on the surface heat balance equation and a parameterization of the sensible heat flux. The computed values of the latent heat flux show that it is connected with changes in fog density.     

An assessment of the impact of climate change on air quality at two UK sites

Possible effects of climate change on air quality are studied for two urban sites in the UK, London and Glasgow. Hourly meteorological data were obtained from climate simulations for two periods representing the current climate and a plausible late 21st century climate. Of the meteorological quantities relevant to air quality, significant changes were found in temperature, specific humidity, wind speed, wind direction, cloud cover, solar radiation, surface sensible heat flux and precipitation. Using these data, dispersion estimates were made for a variety of single sources and some significant changes in environmental impact were found in the future climate. In addition, estimates for future background concentrations of NO_x, NO₂, ozone and PM₁₀ upwind of London and Glasgow were made using the meteorological data in a statistical model. These showed falls in NO_x and increases in ozone for London, while a fall in NO₂ was the largest percentage change for Glasgow. Other changes were small. With these background estimates, annual-average concentrations of NO_x, NO₂, ozone and PM₁₀ were estimated within the two urban areas. For London, results averaged over a number of sites showed a fall in NO_x and a rise in ozone, but only small changes in NO₂ and PM₁₀. For Glasgow, the changes in all four chemical species were small. Large-scale background ozone values from a global chemical transport model are also presented. These show a decrease in background ozone due to climate change. To assess the net impact of both large scale and local processes will require models which treat all relevant scales.