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.     

Kinetic study of the OH reaction with some hydrochloroethers under simulated atmospheric conditions

Using the relative rate technique, rate constants for the gas-phase reactions of hydroxyl radicals with 2-chloroethyl methyl ether (k₁), 2-chloroethyl ethyl ether (k₂) and bis(2-chloroethyl) ether (k₃) have been measured. Experiments were carried out at (298 ± 2) K and atmospheric pressure using synthetic air as bath gas. Using n-pentane and n-heptane as reference compounds, the following rate constants were derived: k₁ = (5.2 ± 1.2) × 10^?12, k₂ = (8.3 ± 1.9) × 10^?12 and k₃ = (7.6 ± 1.9) × 10^?12, in units of cm³ molecule^?1 s^?1. This is the first experimental determination of k₂ and k₃ under atmospheric pressure. The rate constants obtained are compared with previous literature data and the observed trends in the relative rates of reaction of hydroxyl radicals with the ethers studied are discussed. The atmospheric implications of the results are considered in terms of lifetimes and fates of the hydrochloroethers studied.     

Using a reduced Common Representative Intermediates (CRIv2-R5) mechanism to simulate tropospheric ozone in a 3-D Lagrangian chemistry transport model

A reduced chemical scheme (CRIv2-R5) which describes ozone formation from the tropospheric degradation of methane and 22 emitted non-methane hydrocarbons and oxygenated volatile organic compounds has been applied in a global-3D chemistry transport model (STOCHEM). The scheme, which contains 220 species in 609 reactions, has been used to simulate ozone and its precursors for the meteorological year of 1998 and the results have been compared with those from STOCHEM runs with its original chemistry. Compared with the original chemistry scheme, the degradation of a larger number of more reactive VOCs in the CRI scheme results in the formation (and their consequent transportation) of more NO_x active reservoirs thus leading to formation of more ozone away from land-based sources. Conversely, the more reactive VOCs also lead to greater removal of OH in continental areas and greater formation of OH in marine environments. STOCHEM run with the CRI scheme simulates more ozone (by up to 10 ppb), which results in better agreement with observed vertical ozone profiles. The CRI scheme transforms the globally and annually integrated ozone budget for the considered year in STOCHEM from a net loss of ?55 Tg yr^?1 to a net gain of +50 Tg yr^?1.     

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.     

The application of profluorescent nitroxides to detect reactive oxygen species derived from combustion-generated particulate matter: Cigarette smoke – A case study

Reactive oxygen species (ROS) and related free radicals are considered to be key factors underpinning the various adverse health effects associated with exposure to ambient particulate matter. Therefore, measurement of ROS is a crucial factor for assessing the potential toxicity of particles. In this work, a novel profluorescent nitroxide, BPEAnit, was investigated as a probe for detecting particle-derived ROS. BPEAnit has a very low fluorescence emission due to inherent quenching by the nitroxide group, but upon radical trapping or redox activity, a strong fluorescence is observed. BPEAnit was tested for detection of ROS present in mainstream and sidestream cigarette smoke. In the case of mainstream cigarette smoke, there was a linear increase in fluorescence intensity with an increasing number of cigarette puffs, equivalent to an average of 101 nmol ROS per cigarette based on the number of moles of the probe reacted. Sidestream cigarette smoke sampled from an environmental chamber exposed BPEAnit to much lower concentrations of particles, but still resulted in a clearly detectible increase in fluorescence intensity with sampling time. It was calculated that the amount of ROS was equivalent to 50 ± 2 nmol per mg of particulate matter; however, this value decreased with ageing of the particles in the chamber. Overall, BPEAnit was shown to provide a sensitive response related to the oxidative capacity of the particulate matter. These findings present a good basis for employing the new BPEAnit probe for the investigation of particle-related ROS generated from cigarette smoke as well as from other combustion sources.     

Association of size-resolved airborne particles with foot traffic inside a carpeted hallway

The effect of foot traffic on indoor particle resuspension was evaluated by associating non-prescribed foot traffic with simultaneous size-resolved airborne particulate matter (PM) concentrations in a northern California hospital. Foot traffic and PM were measured every 15 min in a carpeted hallway over two 27-h periods. The PM concentration in the hallway was modeled based on the foot traffic intensity, including the previous PM concentration via an autocorrelation regression method based on the well-mixed box model. All 5 size ranges of PM, ranging from 0.75–1 μm to 5–7.5 μm, were highly correlated with foot traffic measurements for both monitoring periods (p < 0.001, R² = 0.87–0.90). However, correlations during daytime hours were less significant than nighttime. Coefficients found via this autoregressive analysis can be interpreted to reveal (i) time-independent contributions of walking activities on PM levels for a specific location; and (ii) size-specific characteristics of the resuspended PM.     

Carbon Storage in Soil Size Fractions Under Two Cacao Agroforestry Systems in Bahia, Brazil

Shaded perennial agroforestry systems contain relatively high quantities of soil carbon (C) resulting from continuous deposition of plant residues; however, the extent to which the C is sequestered in soil will depend on the extent of physical protection of soil organic C (SOC). The main objective of this study was to characterize SOC storage in relation to soil fraction-size classes in cacao (Theobroma cacao L.) agroforestry systems (AFSs). Two shaded cacao systems and an adjacent natural forest in reddish-yellow Oxisols in Bahia, Brazil were selected. Soil samples were collected from four depth classes to 1 m depth and separated by wet-sieving into three fraction-size classes (>250 μm, 250–53 μm, and <53 μm)—corresponding to macroaggregate, microaggregate, and silt-and-clay size fractions—and analyzed for C content. The total SOC stock did not vary among systems (mean: 302 Mg/ha). On average, 72% of SOC was in macroaggregate-size, 20% in microaggregate-size, and 8% in silt-and-clay size fractions in soil. Sonication of aggregates showed that occlusion of C in soil aggregates could be a major mechanism of C protection in these soils. Considering the low level of soil disturbances in cacao AFSs, the C contained in the macroaggregate fraction might become stabilized in the soil. The study shows the role of cacao AFSs in mitigating greenhouse gas (GHG) emission through accumulation and retention of high amounts of organic C in the soils and suggests the potential benefit of this environmental service to the nearly 6 million cacao farmers worldwide.     

Anticipating Forest and Range Land Development in Central Oregon (USA) for Landscape Analysis, with an Example Application Involving Mule Deer

Forest policymakers, public lands managers, and scientists in the Pacific Northwest (USA) seek ways to evaluate the landscape-level effects of policies and management through the multidisciplinary development and application of spatially explicit methods and models. The Interagency Mapping and Analysis Project (IMAP) is an ongoing effort to generate landscape-wide vegetation data and models to evaluate the integrated effects of disturbances and management activities on natural resource conditions in Oregon and Washington (USA). In this initial analysis, we characterized the spatial distribution of forest and range land development in a four-county pilot study region in central Oregon. The empirical model describes the spatial distribution of buildings and new building construction as a function of population growth, existing development, topography, land-use zoning, and other factors. We used the model to create geographic information system maps of likely future development based on human population projections to inform complementary landscape analyses underway involving vegetation, habitat, and wildfire interactions. In an example application, we use the model and resulting maps to show the potential impacts of future forest and range land development on mule deer (Odocoileus hemionus) winter range. Results indicate significant development encroachment and habitat loss already in 2000 with development located along key migration routes and increasing through the projection period to 2040. The example application illustrates a simple way for policymakers and public lands managers to combine existing data and preliminary model outputs to begin to consider the potential effects of development on future landscape conditions.     

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.