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.     

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.     

Trace metals in soil and leaves of Jacaranda mimosifolia in Tshwane area,South Africa

Plant and soil have been identified as major sink of pollutants in the environment. We evaluated the reliability of biomonitoring of heavy metals in Tshwane area with the use of leaves of Jacaranda mimosifolia. The concentrations of heavy metals such as Ca, Mg, Fe, Pb, Zn, Cu, Sb were measured in leaves of J. mimosifolia and soils collected from 10 sites in the city of Tshwane during two sampling periods. The metals were analyzed with the use of ICP-MS. The result shows significant differences in the concentration of trace metals in all the sites (p < 0.01). The differences between the two sampling periods were statistically significant (p < 0.01). Concentration of metals from high traffic and industrial sites were significantly higher than in the residential areas (p < 0.01). Concentration factor suggests that translocation of metals from roots to leaves could be relevant only for some metals such as Ca, Mg and Sb. The study reveals an anthropogenic source for the trace metals. Leaves of J. mimosifolia were found to be a useful biomonitor of the determined trace metals.     

Use of Calluna vulgaris to detect signals of nitrogen deposition across an urban–rural gradient

Densely populated cities can experience high concentrations of traffic-derived pollutants, with oxides of nitrogen and ammonia contributing significantly to the overall nitrogen (N) budget of urban ecosystems. This study investigated changes in the biochemistry of in situ Calluna vulgaris plants to detect signals of N deposition across an urban–rural gradient from central London to rural Surrey, UK. Foliar N concentrations and δ¹⁵N signatures were higher, and C/N ratios lower, in urban areas receiving the highest rates of N deposition. Plant phosphorus (P) concentrations were also highest in these areas, suggesting that elevated rates of N deposition are unlikely to result in progressive P-limitation in urban habitats. Free amino acid concentrations were positively related to N deposition for asparagine, glutamine, glycine, phenylalanine, isoleucine, leucine and lysine. Overall, relationships between tissue chemistry and N deposition were similar for oxidised, reduced and total N, although the strength of relationships varied with the different biochemical indicators. The results of this study indicate that current rates of N deposition are having substantial effects on plant biochemistry in urban areas, with likely implications for the biodiversity and functioning of urban ecosystems.     

Comprehensive analysis of the carbon impacts of vehicle intelligent speed control

In recent years sophisticated technologies have been developed to control vehicle speed based on the type of road the vehicle is driven on using Global Positioning Systems and in-car technology that can alter the speed of the vehicle. While reducing the speed of road vehicles is primarily of interest from a safety perspective, vehicle speed is also an important determinant of vehicle emissions and thus these technologies can be expected to have impacts on a range of exhaust emissions. This work analyses the results from a very large, comprehensive field trial that used 20 instrumented vehicles with and without speed control driven almost 500,000 km measuring vehicle speed at 10 Hz. We develop individual vehicle modal emissions models for CO₂ for 30 Euro III and Euro IV cars at a 1-Hz time resolution. Generalized Additive Models were used to describe how emissions from individual vehicles vary depending on their driving conditions, taking account of variable interactions and time-lag effects. We quantify the impact that vehicle speed control has on-vehicle emissions of CO₂ by road type, fuel type and driver behaviour. Savings in CO₂ of ≈6% were found on average for motorway-type roads when mandatory speed control was used compared with base case conditions. For most other types of road, speed control has very little effect on emissions of CO₂ and in some cases can result in increased emissions for low-speed limit urban roads. We also find that there is on average a 20% difference in CO₂ emission between the lowest and highest emitting driver, which highlights the importance of driver behaviour in general as a means of reducing emissions of CO₂.     

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.     

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.     

Chemical speciation,transport and contribution of biomass burning smoke to ambient aerosol in Guangzhou,a mega city of China

Intensive measurements of aerosol (PM₁₀) and associated water-soluble ionic and carbonaceous species were conducted in Guangzhou, a mega city of China, during summer 2006. Elevated levels of most chemical species were observed especially at nighttime during two episodes, characterized by dramatic build-up of the biomass burning tracers levoglucosan and non-sea-salt potassium, when the prevailing wind direction had changed due to two approaching tropical cyclones. High-resolution air mass back trajectories based on the MM5 model revealed that air masses with high concentrations of levoglucosan (43–473 ng m^?3) and non-sea-salt potassium (0.83–3.2 μg m^?3) had passed over rural regions of the Pearl River Delta and Guangdong Province, where agricultural activities and field burning of crop residues are common practices. The relative contributions of biomass burning smoke to organic carbon in PM₁₀ were estimated from levoglucosan data to be on average 7.0 and 14% at daytime and nighttime, respectively, with maxima of 9.7 and 32% during the episodic transport events, indicating that biomass and biofuel burning activities in the rural parts of the Pearl River Delta and neighboring regions could have a significant impact on ambient urban aerosol levels.     

Simulating chemistry–aerosol–cloud–radiation–climate feedbacks over the continental U.S. using the online-coupled Weather Research Forecasting Model with chemistry (WRF/Chem)

The chemistry–aerosol–cloud–radiation–climate feedbacks are simulated using WRF/Chem over the continental U.S. in January and July 2001. Aerosols can reduce incoming solar radiation by up to ?9% in January and ?16% in July and 2-m temperatures by up to 0.16 °C in January and 0.37 °C in July over most of the continental U.S. The NO₂ photolysis rates decrease in July by up to ?8% over the central and eastern U.S. where aerosol concentrations are high but increase by up to 7% over the western U.S. in July and up to 13% over the entire domain in January. Planetary boundary layer (PBL) height reduces by up to ?23% in January and ?24% in July. Temperatures and wind speeds in July in big cities such as Atlanta and New York City reduce at/near surface but increase at higher altitudes. The changes in PBL height, temperatures, and wind speed indicate a more stable atmospheric stability of the PBL and further exacerbate air pollution over areas where air pollution is already severe. Aerosols can increase cloud optical depths in big cities in July, and can lead to 500–5000 cm^?3 cloud condensation nuclei (CCN) at a supersaturation of 1% over most land areas and 10–500 cm^?3 CCN over ocean in both months with higher values over most areas in July than in January, particularly in the eastern U.S. The total column cloud droplet number concentrations are up to 4.9 × 10⁶ cm^?2 in January and up to 11.8 × 10⁶ cm^?2 in July, with higher values over regions with high CCN concentrations and sufficient cloud coverage. Aerosols can reduce daily precipitation by up to 1.1 mm day^?1 in January and 19.4 mm day^?1 in July thus the wet removal rates over most of the land areas due to the formation of small CCNs, but they can increase precipitation over regions with the formation of large/giant CCN. These results indicate potential importance of the aerosol feedbacks and an urgent need for their accurate representations in current atmospheric models to reduce uncertainties associated with climate change predictions.     

Influence of roads and inhabited areas on metal concentrations in terrestrial mosses

The guidelines regarding sampling terrestrial mosses for biomonitoring the atmospheric contamination in a region specifically recommend that sampling close to focal points of contamination (i.e. roads, populated areas, etc.) should be avoided for satisfactory characterization of general patterns of contamination. However, these recommendations cannot always be followed in many parts of the world with dense, highly dispersed populations. The aim of the present study was to determine how the distances between sampling sites (SS) and contamination foci such as roads, isolated houses and urban nuclei affect regular, large-scale sampling networks. Metal concentrations obtained in biennial sampling surveys carried out between 2000 and 2006 in Galicia (NW Spain) were used, and the relative proportions of the concentrations corresponding to small-scale and large-scale processes were calculated. The possible relationship between the mean concentrations corresponding to small-scale processes in the different sampling surveys and the distances from SS to roads, buildings and urban nuclei was established by a GIS. Outliers in the data were identified at many of the SS and frequency statistics revealed the absence of any relationship between the distance to these foci and the concentrations of metals in the moss. The method also revealed many instances of the influence of one or more small-scale contamination foci such as airports and railways (often not considered in the sampling recommendations) on SS. Relocation of such SS would improve the representativeness of the sampling grid.