Modeling effects of traffic and landscape characteristics on ambient nitrogen dioxide levels in Connecticut

An integrated exposure model was developed that estimates nitrogen dioxide (NO(2)) concentration at residences using geographic information systems (GIS) and variables derived within residential buffers representing traffic volume and landscape characteristics including land use, population density and elevation. Multiple measurements of NO(2) taken outside of 985 residences in Connecticut were used to develop the model. A second set of 120 outdoor NO(2) measurements as well as cross-validation were used to validate the model. The model suggests that approximately 67% of the variation in NO(2) levels can be explained by: traffic and land use primarily within 2 km of a residence; population density; elevation; and time of year. Potential benefits of this model for health effects research include improved spatial estimations of traffic-related pollutant exposure and reduced need for extensive pollutant measurements. The model, which could be calibrated and applied in areas other than Connecticut, has importance as a tool for exposure estimation in epidemiological studies of traffic-related air pollution.     

Comparison of land-use regression models between Great Britain and the Netherlands

Land-use regression models have increasingly been applied for air pollution mapping at typically the city level. Though models generally predict spatial variability well, the structure of models differs widely between studies. The observed differences in the models may be due to artefacts of data and methodology or underlying differences in source or dispersion characteristics. If the former, more standardised methods using common data sets could be beneficial. We compared land-use regression models for NO₂ and PM_10, developed with a consistent protocol in Great Britain (GB) and the Netherlands (NL).Models were constructed on the basis of 2001 annual mean concentrations from the national air quality networks. Predictor variables used for modelling related to traffic, population, land use and topography. Four sets of models were developed for each country. First, predictor variables derived from data sets common to both countries were used in a pooled analysis, including an indicator for country and interaction terms between country and the identified predictor variables. Second, the common data sets were used to develop individual baseline models for each country. Third, the country-specific baseline models were applied after calibration in the other country to explore transferability. The fourth model was developed using the best possible predictor variables for each country.A common model for GB and NL explained NO₂ concentrations well (adjusted R² 0.64), with no significant differences in intercept and slopes between the two countries. The country-specific model developed on common variables for NL but not GB improved the prediction.The performance of models based upon common data was only slightly worse than models optimised with local data. Models transferred to the other country performed substantially worse than the country-specific models. In conclusion, care is needed both in transferring models across different study areas, and in developing large inter-regional LUR models.     

Simulating the fine and coarse inorganic particulate matter concentrations in a polluted megacity

A three dimensional chemical transport model (PMCAMx) is applied to the Mexico City Metropolitan Area (MCMA) in order to simulate the chemical composition and mass of the major PM₁ (fine) and PM_1–10 (coarse) inorganic components and determine the effect of mineral dust on their formation. The aerosol thermodynamic model ISORROPIA-II is used to explicitly simulate the effect of Ca, Mg, and K from dust on semi-volatile partitioning and water uptake. The hybrid approach is applied to simulate the inorganic components, assuming that the smallest particles are in thermodynamic equilibrium, while describing the mass transfer to and from the larger ones. The official MCMA 2004 emissions inventory with improved dust and NaCl emissions is used. The comparison between the model predictions and measurements during a week of April of 2003 at Centro Nacional de Investigacion y Capacitacion Ambiental (CENICA) “Supersite” shows that the model reproduces reasonably well the fine mode composition and its diurnal variation. Sulfate predicted levels are relatively uniform in the area (approximately 3 μg m^?3), while ammonium nitrate peaks in Mexico City (approximately 7 μg m^?3) and its concentration rapidly decreases due to dilution and evaporation away from the urban area. In areas of high dust concentrations, the associated alkalinity is predicted to increase the concentration of nitrate, chloride and ammonium in the coarse mode by up to 2 μg m^?3 (a factor of 10), 0.4 μg m^?3, and 0.6 μg m^?3 (75%), respectively. The predicted ammonium nitrate levels inside Mexico City for this period are sensitive to the physical state (solid versus liquid) of the particles during periods with RH less than 50%.     

A new condensed toluene mechanism for Carbon Bond: CB05-TU

Toluene is ubiquitous in urban atmospheres and is a precursor to tropospheric ozone and aerosol (smog). An important characteristic of toluene chemistry is the tendency of some degradation products (e.g., cresols and methyl-catechols) to form organic nitro and nitrate compounds that sequester NOx (NO and NO₂) from active participation in smog formation. Explaining the NOx sinks in toluene degradation has made mechanism development more difficult for toluene than for many other organic compounds. Another challenge for toluene is explaining sources of radicals early in the degradation process. This paper describes the development of a new condensed toluene mechanism consisting of 26 reactions, and evaluates the performance of CB05 with this new toluene scheme (Toluene Update, TU) against 38 chamber experiments at 7 different environmental chambers, and provides recommendations for future developments. CB05 with the current toluene mechanism (CB05-Base) under-predicted the maximum O₃ and O₃ production rate for many of these toluene–NOx chamber experiments, especially under low-NOx conditions ([NOx]_t=0 < 100 ppb). CB05 with the new toluene mechanism (CB05-TU) includes changes to the yields and reactions of cresols and ring-opening products, and showed better performance than CB05-Base in predicting the maximum O₃, O₃ formation rate, NOx removal rate and cresol concentration. Additional environmental chamber simulations with xylene–NOx experiments showed that the TU mechanism updates tended to improve mechanism performance for xylene.     

Improved land cover and emission factors for modeling biogenic volatile organic compounds emissions from Hong Kong

This paper describes a study of local biogenic volatile organic compounds (BVOC) emissions from the Hong Kong Special Administrative Region (HKSAR). An improved land cover and emission factor database was developed to estimate Hong Kong emissions using MEGAN, a BVOC emission model developed by Guenther et al. (2006). Field surveys of plant species composition and laboratory measurements of emission factors were combined with other data to improve existing land cover and emission factor data. The BVOC emissions from Hong Kong were calculated for 12 consecutive years from 1995 to 2006. For the year 2006, the total annual BVOC emissions were determined to be 12,400 metric tons or 9.82 × 10⁹ g C (BVOC carbon). Isoprene emission accounts for 72%, monoterpene emissions account for 8%, and other VOCs emissions account for the remaining 20%. As expected, seasonal variation results in a higher emission in the summer and a lower emission in the winter, with emission predominantly in day time. A high emission of isoprene occurs for regions, such as Lowest Forest-NT North, dominated by broadleaf trees. The spatial variation of total BVOC is similar to the isoprene spatial variation due to its high contribution. The year to year variability in emissions due to weather was small over the twelve-year period (?1.4%, 2006 to 1995 trendline), but an increasing trend in the annual variation due to an increase in forest land cover can be observed (+7%, 2006 to 1995 trendline). The results of this study demonstrate the importance of accurate land cover inputs for biogenic emission models and indicate that land cover change should be considered for these models.     

Ambient TSP concentration and dustfall in major cities of China: Spatial distribution and temporal variability

Based on environmental monitoring data in 93 major cities and meteorological records at 398 weather stations in China from 1981 to 2007, total suspended particle (TSP) concentration, the intensity of dustfall, and sand and dust storm frequency (F_d) were analysed. During the past 27 years, the annual average TSP concentration (C_TSP) in 93 cities was 402 μg m^?3. Annual average C_TSP decreased from the north to the south and from inland to the coast areas with a peak value of 628.8 μg m^?3 in Lanzhou. In the 1980s, 1990s and 2000s, annual average C_TSP was 628.7, 319.2, and 250.1 μg m^?3, respectively. Annual average intensity of dustfall (I_d) was 240.5 t km^?2 a^?1, decreased from northern to southern China and from inland to the coast areas with the maximum value of 717.2 t km^?2 a^?1 in Baotou. In the 1980s, 1990s and 2000s, annual average I_d was 334.8, 220.9, 146 t km^?2 a^?1 respectively. Annual average I_d in the Loess Plateau region was commonly higher than 200 t km^?2 a^?1. The annual average F_d decreased from arid regions in northwestern China to humid areas in southeastern China with two sand and sand storm centers existing in Xinjiang Taklamakan Desert and western Inner Mongolia. The annual average F_d in the 1980s, 1990s, 2000s was 16, 8, 6 days respectively, decreased steadily from 18 days in 1981–5 days in 2007. Annual average I_d had a positive linear relation to annual average C_TSP (R² = 0.96). Annual average F_d had a positive relation with annual average C_TSP (R² = 0.97) as well as annual average I_d (R² = 0.94). TSP was the chief pollutant influencing Air Pollution Index (API) in northern China in spring and winter seasons. Sand and dust storm might be a major factor affecting the temporal variability and spatial distribution of TSP and dustfall in China.     

Spatial variability of carbonaceous aerosols and associated source tracers in two cites in the Midwestern United States

Semi-continuous and 24-h averaged measurements of fine carbonaceous aerosols were made concurrently at three sites within each of two U.S. Midwestern Cities; Detroit, Michigan and Cleveland, Ohio; during two, one-month intensive campaigns conducted in July of 2007 and January & February of 2008. A comparison of 24-h measurements revealed substantial intra-urban variability in carbonaceous aerosols consistent with the influence of local sources, and excesses in both PM_2.5 organic carbon (OC) and elemental carbon (EC) were identified at individual sites within each city. High time-resolved black carbon (BC) measurements indicated that elemental carbon concentrations were higher at sites adjacent to freeways and busy surface streets, and temporal patterns suggested that excess EC at sites adjacent to freeways was dominated by mobile source emissions while excesses in EC away from traffic corridors was dominated by point/area source emissions. The site-to-site variability in OC concentrations was approximately 7% within the neighborhood scale (0.5–4 km) and between 4 and 27% at the urban scale (4–100 km). In contrast, measurements of organic source tracers, in conjunction with a Chemical Mass Balance (CMB) source-apportionment model, indicated that the spatial variation in the contribution of both mobile and stationary sources to PM_2.5 OC often exceeded the variation in OC mass concentration by a factor of 3 or more. Markers for mobile sources, biomass smoke, natural gas, and coal combustion differed by as much as 60% within the neighborhood scale and by greater than 200% within the urban scale. The observations made during this study suggest that the urban excess of carbonaceous aerosols is much more complex than has been previously reported and that a more rigorous, source-oriented approach should be taken in order to assess the risk associated with exposure to carbonaceous aerosols within the industrialized environments of the Midwestern United States.     

Uncertainty in health risks due to anthropogenic primary fine particulate matter from different source types in Finland

The emission-exposure and exposure-response (toxicity) relationships are different for different emission source categories of anthropogenic primary fine particulate matter (PM_2.5). These variations have a potentially crucial importance in the integrated assessment, when determining cost-effective abatement strategies. We studied the importance of these variations by conducting a sensitivity analysis for an integrated assessment model. The model was developed to estimate the adverse health effects to the Finnish population attributable to primary PM_2.5 emissions from the whole of Europe. The primary PM_2.5 emissions in the whole of Europe and in more detail in Finland were evaluated using the inventory of the European Monitoring and Evaluation Programme (EMEP) and the Finnish Regional Emission Scenario model (FRES), respectively. The emission-exposure relationships for different primary PM_2.5 emission source categories in Finland have been previously evaluated and these values incorporated as intake fractions into the integrated assessment model. The primary PM_2.5 exposure-response functions and toxicity differences for the pollution originating from different source categories were estimated in an expert elicitation study performed by six European experts on air pollution health effects. The primary PM_2.5 emissions from Finnish and other European sources were estimated for the population of Finland in 2000 to be responsible for 209 (mean, 95% confidence interval 6–739) and 357 (mean, 95% CI 8–1482) premature deaths, respectively. The inclusion of emission-exposure and toxicity variation into the model increased the predicted relative importance of traffic related primary PM_2.5 emissions and correspondingly, decreased the predicted relative importance of other emission source categories. We conclude that the variations of emission-exposure relationship and toxicity between various source categories had significant impacts for the assessment on premature deaths caused by primary PM_2.5.     

Assimilation of conventional and satellite wind observations in a mesoscale atmospheric model for studying atmospheric dispersion

A mesoscale atmospheric model PSU/NCAR MM5 is used to provide operational weather forecasts for a nuclear emergency response decision support system on the southeast coast of India. In this study the performance of the MM5 model with assimilation of conventional surface and upper-air observations along with satellite derived 2-d surface wind data from QuickSCAT sources is examined. Two numerical experiments with MM5 are conducted: one with static initialization using NCEP FNL data and second with dynamic initialization by assimilation of observations using four dimensional data assimilation (FDDA) analysis nudging for a pre-forecast period of 12 h. Dispersion simulations are conducted for a hypothetical source at Kalpakkam location with the HYSPLIT Lagrangian particle model using simulated wind field from the above experiments. The present paper brings out the differences in the atmospheric model predictions and the differences in dispersion model results from control and assimilation runs. An improvement is noted in the atmospheric fields from the assimilation experiment which has led to significant alteration in the trajectory positions, plume orientation and its distribution pattern. Sensitivity tests using different PBL and surface parameterizations indicated the simple first order closure schemes (Blackadar, MRF) coupled with the simple soil model have given better results for various atmospheric fields. The study illustrates the impact of the assimilation of the scatterometer wind and automated weather stations (AWS) observations on the meteorological model predictions and the dispersion results.     

Verification of diffusive and pumped samplers for volatile organic compounds using a controlled atmosphere test facility

There is a requirement to verify the performance of sorbent-based passive or active samplers and to extend their use, where possible, to monitor volatile organic compounds (VOCs) that are known to be photochemical ozone pre-cursors or are relevant to the activities of the petrochemical industry. We report measurements of the 14-day diffusive uptake rates for the VOCs: i-butane (2-methyl propane), n-butane, i-pentane (2-methyl butane), n-pentane, n-hexane, benzene, toluene, and m-xylene (at environmental level concentrations) for industry standard axial samplers (Perkin–Elmer-type samplers) containing the sorbents Carbopack-X, -Z, -B or Tenax-TA. We also present data on back-diffusion, blank levels, and storage for the above sorbents, and describe the simultaneous use of the sorbent Carbopack-X for pumped sampling of certain VOCs. The results were obtained by dosing samplers in a controlled atmosphere test facility (CATFAC) operating under well-defined conditions of concentration, nominal temperature of 20 °C, wind speed of 0.5 m s^?1, and relative humidities of 0% and 80%. Field measurements were also obtained to provide supplementary data to support the laboratory study. Results are compared to existing published data, where these are available.