South Pole Antarctica observations and modeling results: New insights on HOx radical and sulfur chemistry

Measurements of OH, H₂SO₄, and MSA at South Pole (SP) Antarctica were recorded as a part of the 2003 Antarctic Chemistry Investigation (ANTCI 2003). The time period 22 November, 2003–2 January, 2004 provided a unique opportunity to observe atmospheric chemistry at SP under both natural conditions as well as those uniquely defined by a solar eclipse event. Results under natural solar conditions generally confirmed those reported previously in the year 2000. In both years the major chemical driver leading to large scale fluctuations in OH was shifts in the concentration levels of NO. Like in 2000, however, the 2003 observational data were systematically lower than model predictions. This can be interpreted as indicating that the model mechanism is still missing a significant HO_x sink reaction(s); or, alternatively, that the OH calibration source may have problems. Still a final possibility could involve the integrity of the OH sampling scheme which involved a fixed building site. As expected, during the peak in the solar eclipse both NO and OH showed large decreases in their respective concentrations. Interestingly, the observational OH profile could only be approximated by the model mechanism upon adding an additional HO_x radical source in the form of snow emissions of CH₂O and/or H₂O₂. This would lead one to think that either CH₂O and/or H₂O₂ snow emissions represent a significant HO_x radical source under summertime conditions at SP. Observations of H₂SO₄ and MSA revealed both species to be present at very low concentrations (e.g., 5 × 10⁵ and 1 × 10⁵ molec cm^?3, respectively), but similar to those reported in 2000. The first measurements of SO₂ at SP demonstrated a close coupling with the oxidation product H₂SO₄. The observed low concentrations of MSA appear to be counter to the most recent thinking by glacio-chemists who have suggested that the plateau's lower atmosphere should have elevated levels of MSA. We speculate here that the absence of MSA may reflect efficient atmospheric removal mechanisms for this species involving either dynamical and/or chemical processes.     

On-road traffic emissions in a megacity

A new annual bottom–up emission inventory of criteria pollutants and greenhouse gases from on-road mobile sources was developed for 2006 for the metropolitan area of Buenos Aires, Argentina, within a four-year regional project aimed at providing tools for chemical weather forecast in South America. Under the scarcity of local emission factors, we collected data from measuring campaigns performed in Argentina, Brazil, Chile and Colombia and compiled a data set of regional emission factors representative of Latin American fleets and driving conditions. The estimated emissions were validated with respect to downscaled national estimates and the EDGAR global emission database. Our results highlight the role of older technologies accounting in average for almost 80% of the emissions of all species. The area exhibits higher specific emissions than developed countries, with figures two times higher for criteria pollutants. We analyzed the effect on emissions of replacing gasoline by compressed natural gas, occurring in Argentina since 1995. We identified (i) a relationship between number of vehicles and a compound socioeconomic indicator, and (ii) time-lags in vehicle technologies between developed and developing countries, which can be respectively applied for spatial disaggregation and the development of projections for other Latin American cities. The results may also be employed to complement global emission inventories and by local policy makers as an environmental management tool.     

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.     

Air pollutants and health outcomes: Assessment of confounding by influenza

We assessed confounding of associations between short-term effects of air pollution and health outcomes by influenza using Hong Kong mortality and hospitalization data for 1996–2002.Three measures of influenza were defined: (i) intensity: weekly proportion of positive influenza viruses, (ii) epidemic: weekly number of positive influenza viruses ≥4% of the annual number for ≥2 consecutive weeks, and (iii) predominance: an epidemic period with co-circulation of respiratory syncytial virus <2% of the annual positive isolates for ≥2 consecutive weeks. We examined effects of influenza on associations between nitrogen dioxide (NO₂), sulfur dioxide (SO₂), particulate matter with aerodynamic diameter ≤10 μm (PM₁₀) and ozone (O₃) and health outcomes including all natural causes mortality, cardiorespiratory mortality and hospitalization. Generalized additive Poisson regression model with natural cubic splines was fitted to control for time-varying covariates to estimate air pollution health effects. Confounding with influenza was assessed using an absolute difference of >0.1% between unadjusted and adjusted excess risks (ER%).Without adjustment, pollutants were associated with positive ER% for all health outcomes except asthma and stroke hospitalization with SO₂ and stroke hospitalization with O₃. Following adjustment, changes in ER% for all pollutants were <0.1% for all natural causes mortality, but >0.1% for mortality from stroke with NO₂ and SO₂, cardiac or heart disease with NO₂, PM₁₀ and O₃, lower respiratory infections with NO₂ and O₃ and mortality from chronic obstructive pulmonary disease with all pollutants. Changes >0.1% were seen for acute respiratory disease hospitalization with NO₂, SO₂ and O₃ and acute lower respiratory infections hospitalization with PM₁₀. Generally, influenza does not confound the observed associations of air pollutants with all natural causes mortality and cardiovascular hospitalization, but for some pollutants and subgroups of cardiorespiratory mortality and respiratory hospitalization there was evidence to suggest confounding by influenza.     

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.     

The seasonal cycles and photochemistry of C2–C5 alkanes at Mace Head

Continuous in-situ measurements of NMHCs at Mace Head, Ireland during two full annual cycles from January 2005 to January 2007 were used to investigate NMHC emission sources and transport including dilution and photochemical oxidation. The Mace Head research station is ideally located to sample a wide range of air masses including polluted European transport, clean North Atlantic and Arctic air masses and the ultra-clean, Southern Atlantic air masses. The variety in air mass sampling is used to investigate interaction of emissions, transport, dilution and photochemistry. Variability of long-lived hydrocarbon ratios is used to assess and estimate typical transport times from emission source to the Mace Head receptor. Seasonality in the ratios of isomeric alkane pairs (for butane and pentanes) are used to assess the effects of atmospheric transport and photochemical ageing. Finally, the natural logarithms of NMHC ratios are used to assess photochemical oxidation.     

Urban tracer dispersion experiments during the second DAPPLE field campaign in London 2004

As part of the DAPPLE programme two large scale urban tracer experiments using multiple simultaneous releases of cyclic perfluoroalkanes from fixed location point sources was performed. The receptor concentrations along with relevant meteorological parameters measured are compared with a three screening dispersion models in order to best predict the decay of pollution sources with respect to distance. It is shown here that the simple dispersion models tested here can provide a reasonable upper bound estimate of the maximum concentrations measured with an empirical model derived from field observations and wind tunnel studies providing the best estimate. An indoor receptor was also used to assess indoor concentrations and their pertinence to commonly used evacuation procedures.     

A land use regression model for predicting ambient volatile organic compound concentrations in Toronto,Canada

More than 25 studies have employed land use regression (LUR) models to estimate nitrogen oxides and to a lesser extent particulate matter indicators, but these methods have been less commonly applied to ambient concentrations of volatile organic compounds (VOCs). Some VOCs have high plausibility as sources of health effects and others are specific indicators of motor vehicle exhaust. We used LUR models to estimate spatial variability of VOCs in Toronto, Canada. Benzene, n-hexane and total hydrocarbons (THC) were measured from July 25 to August 9, 2006 at 50 locations using the TraceAir organic vapor monitors. Nitrogen dioxide (NO₂) was also sampled to assess its spatial pattern agreement with VOC exposures. Buffers for land use, population density, traffic density, physical geography, and remote sensing measures of greenness and surface brightness were also tested. The remote sensing measures have the highest correlations with VOCs and NO₂ levels (i.e., explains >36% of the variance). Our regression models explain 66–68% of the variance in the spatial distribution of VOCs, compared to 81% for the NO₂ model. The ranks of agreement between various VOCs range from 48 to 63% and increases substantially – up to 75% – for the top and bottom quartile groups. Agreements between NO₂ and VOCs are much smaller with an average rank of 36%. Future epidemiologic studies may therefore benefit from using VOCs as potential toxic agents for traffic-related pollutants.