Use of CALPUFF for exposure assessment in a near-field,complex terrain setting

CALPUFF is an atmospheric source-receptor model recommended by the U.S. Environmental Protection Agency for use on a case-by-case basis in complex terrain and wind conditions. The ability of the model to provide useful information for exposure assessments in areas with those topographical and meteorological conditions has received little attention. This is an important knowledge gap for use of CALPUFF outside of regulatory applications, such as exposure analyses conducted in support of risk assessments and health studies. We compared deposition of cadmium (Cd), lead (Pb), and zinc (Zn) calculated with CALPUFF as a result of emissions from a zinc smelter with corresponding concentrations of the metals measured in attic dust and soil samples obtained from the surrounding area. On a point-by-point analysis, predictions from CALPUFF explained 11% (lead) to 53% (zinc) of the variability in concentrations measured in attic dust. Levels of heavy metals in soil interpolated to 100 residential addresses from the distribution of concentrations measured in soil samples also agreed well with deposition predicted with CALPUFF: R² of 0.46, 0.76, and 079 for Pb, Cd, and Zn, respectively. Community-average concentrations of Cd, Pb, and Zn measured in soil were significantly (p < 0.0001) and strongly correlated (R² ranged from 0.77 to 0.98) with predicted deposition rates. These findings demonstrate that CALPUFF can provide reasonably accurate predictions of the patterns of long-term air pollutant deposition in the near-field associated with emissions from a discrete source in complex terrain. Because deposition estimates are calculated as a linear function of air concentrations, CALPUFF is expected to be reliable model for prediction of long-term average, near-field ambient air concentrations in complex terrain as well.     

Nocturnal boundary layer characteristics and land breeze development in Houston,Texas during TexAQS II

The nocturnal boundary layer in Houston, Texas was studied using a high temporal and vertical resolution tethersonde system on four nights during the Texas Air Quality Study II (TexAQS II) in August and September 2006. The launch site was on the University of Houston campus located approximately 4 km from downtown Houston. Of particular interest was the evolution of the nocturnal surface inversion and the wind flows within the boundary layer. The land–sea breeze oscillation in Houston has important implications for air quality as the cycle can impact ozone concentrations through pollutant advection and recirculation. The results showed that a weakly stable surface inversion averaging in depth between 145 and 200 m AGL formed on each of the experiment nights, typically within 2–3 h after sunset. Tethersonde vertical winds were compared with two other Houston data sets (High Resolution Doppler Lidar and radar wind profiler) from locations near the coastline and good agreement was found, albeit with a temporal lag at the tethersonde site. This comparison revealed development of a land breeze on three nights which began near the coastline and propagated inland both horizontally and vertically with time. The vertical temperature structure was significantly modified on one night at the tethersonde site after the land breeze wind shift, exhibiting near-adiabatic profiles below 100 m AGL.     

Ground-level ozone in the Pearl River Delta region: Analysis of data from a recently established regional air quality monitoring network

The ambient air quality monitoring data of 2006 and 2007 from a recently established Pearl River Delta (PRD) regional air quality monitoring network are analyzed to investigate the characteristics of ground-level ozone in the region. Four sites covering urban, suburban, rural and coastal areas are selected as representatives for detailed analysis in this paper. The results show that there are distinct seasonal and diurnal cycles in ground-level ozone across the PRD region. Low ozone concentrations are generally observed in summer, while high O₃ levels are typically found in autumn. The O₃ diurnal variations in the urban areas are larger than those at the rural sites. The O₃ concentrations showed no statistically significant difference between weekend and weekdays in contrast to the findings in many other urban areas in the world. The average ozone concentrations are lower in urban areas compared to the sites outside urban centers. Back trajectories are used to show the major air-mass transport patterns and to examine the changes in ozone from the respective upwind sites to a site in the center of the PRD (Wanqingsha). The results show higher average ozone concentrations at the upwind sites in the continental and coastal air masses, but higher 1 h-max O₃ concentrations (by 8–16 ppbv) at the center PRD site under each of air-mass category, suggesting that the ozone pollution in the PRD region exhibits both regional and super-regional characteristics.     

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.     

Modeling the surface–atmosphere exchange of ammonia

New parameterizations for surface–atmosphere exchange of ammonia are presented for application in atmospheric transport models and compared with parameterizations of the literature. The new parameterizations are based on a combination of the results of three years of ammonia flux measurements over a grassland canopy (dominated by Lolium perenne and Poa trivialis) near Wageningen, the Netherlands and existing parameterizations from literature. First, a model for the surface–atmosphere exchange of ammonia that includes the concentration at the external leaf surface is derived and validated. Second, a parameterization for the stomatal compensation point (expressed as Γ_s, the ratio of [NH₄⁺]/[H⁺] in the leaf apoplast) that accounts for the observed seasonal variation is derived from the measurements. The new, temperature-dependent Γ_s describes the observed seasonal behavior very well. It is noted, however, that senescence of plants and field management practices will also influence the seasonal variation of Γ_s on a shorter timescale. Finally, a relation that links Γ_s to the atmospheric pollution level of the location through the ‘long-term’ NH₃ concentration in the air is proposed.     

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.     

Long-Term Community Dynamics of Small Landbirds with and Without Exposure to Extensive Disturbance from Military Training Activities

Military training activities are known to impact individual species, yet our understanding of how such activities influence animal communities is limited. In this study, we used long-term data in a case study approach to examine the extent to which the local small landbird community differed between a site in northeast Kansas that experienced intensive disturbance from military training activities (Ft. Riley Military Installation) and a similar, nearby site that experienced minimal human disturbance (Konza Prairie Biological Station). In addition, we characterized how the regional pool of potential colonizers influenced local community dynamics using Breeding Bird Survey data. From 1991 to 2001, most species of small terrestrial landbirds (73%) recorded during breeding surveys were found at both sites and the mean annual richness at Ft. Riley (39.0 ± 2.86 [SD]) was very similar to that of Konza Prairie (39.4 ± 2.01). Richness was maintained at relatively constant levels despite compositional changes because colonizations compensated local extinctions at both sites. These dynamics were driven primarily by woodland species that exhibited stochastic losses and gains and were present at a low local and regional abundance. Our results suggest that military training activities may mimic natural disturbances for some species in this area because the small landbird community did not differ markedly between sites with and sites without extensive human disturbance. Although our results suggest that military training is not associated with large changes in the avian community, additional studies are needed to determine if this pattern is found in other ecological communities.     

A Generic Bio-Economic Farm Model for Environmental and Economic Assessment of Agricultural Systems

Bio-economic farm models are tools to evaluate ex-post or to assess ex-ante the impact of policy and technology change on agriculture, economics and environment. Recently, various BEFMs have been developed, often for one purpose or location, but hardly any of these models are re-used later for other purposes or locations. The Farm System Simulator (FSSIM) provides a generic framework enabling the application of BEFMs under various situations and for different purposes (generating supply response functions and detailed regional or farm type assessments). FSSIM is set up as a component-based framework with components representing farmer objectives, risk, calibration, policies, current activities, alternative activities and different types of activities (e.g., annual and perennial cropping and livestock). The generic nature of FSSIM is evaluated using five criteria by examining its applications. FSSIM has been applied for different climate zones and soil types (criterion 1) and to a range of different farm types (criterion 2) with different specializations, intensities and sizes. In most applications FSSIM has been used to assess the effects of policy changes and in two applications to assess the impact of technological innovations (criterion 3). In the various applications, different data sources, level of detail (e.g., criterion 4) and model configurations have been used. FSSIM has been linked to an economic and several biophysical models (criterion 5). The model is available for applications to other conditions and research issues, and it is open to be further tested and to be extended with new components, indicators or linkages to other models.     

Integrating Environmental and Socio-Economic Indicators of a Linked Catchment–Coastal System Using Variable Environmental Intensity

Can we develop land use policy that balances the conflicting views of stakeholders in a catchment while moving toward long term sustainability? Adaptive management provides a strategy for this whereby measures of catchment performance are compared against performance goals in order to progressively improve policy. However, the feedback loop of adaptive management is often slow and irreversible impacts may result before policy has been adapted. In contrast, integrated modelling of future land use policy provides rapid feedback and potentially improves the chance of avoiding unwanted collapse events. Replacing measures of catchment performance with modelled catchment performance has usually required the dynamic linking of many models, both biophysical and socio-economic—and this requires much effort in software development. As an alternative, we propose the use of variable environmental intensity (defined as the ratio of environmental impact over economic output) in a loose coupling of models to provide a sufficient level of integration while avoiding significant effort required for software development. This model construct was applied to the Motueka Catchment of New Zealand where several biophysical (riverine water quantity, sediment, E. coli faecal bacteria, trout numbers, nitrogen transport, marine productivity) models, a socio-economic (gross output, gross margin, job numbers) model, and an agent-based model were linked. An extreme set of land use scenarios (historic, present, and intensive) were applied to this modelling framework. Results suggest that the catchment is presently in a near optimal land use configuration that is unlikely to benefit from further intensification. This would quickly put stress on water quantity (at low flow) and water quality (E. coli). To date, this model evaluation is based on a theoretical test that explores the logical implications of intensification at an unlikely extreme in order to assess the implications of likely growth trajectories from present use. While this has largely been a desktop exercise, it would also be possible to use this framework to model and explore the biophysical and economic impacts of individual or collective catchment visions. We are currently investigating the use of the model in this type of application.