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.     

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.     

Chemical mass balance source apportionment for combined PM2.5 measurements from U.S. non-urban and urban long-term networks

The Minnesota Particulate Matter 2.5 (PM_2.5) Source Apportionment Study was undertaken to explore the utility of PM_2.5 mass, element, ion, and carbon measurements from long-term speciation networks for pollution source attribution. Ambient monitoring data at eight sites across the state were retrieved from the archives of the Interagency Monitoring of Protected Visual Environments (IMPROVE) and the Speciation Trends Network (STN; part of the Chemical Speciation Network [CSN]) and analyzed by an Effective Variance – Chemical Mass Balance (EV-CMB) receptor model with region-specific geological source profiles developed in this study. PM_2.5 was apportioned into contributions of fugitive soil dust, calcium-rich dust, taconite (low grade iron ore) dust, road salt, motor vehicle exhaust, biomass burning, coal-fired utility, and secondary aerosol. Secondary sulfate and nitrate contributed strongly (49–71% of PM_2.5) across all sites and was dominant (≥60%) at IMPROVE sites. Vehicle exhausts accounted for 20–70% of the primary PM_2.5 contribution, largely exceeding the proportion in the primary PM_2.5 emission inventory. The diesel exhaust contribution was separable from the gasoline engine exhaust contribution at the STN sites. Higher detection limits for several marker elements in the STN resulted in non-detectable coal-fired boiler contributions which were detected in the IMPROVE data. Despite the different measured variables, analytical methods, and detection limits, EV-CMB results from a nearby IMPROVE-STN non-urban/urban sites showed similar contributions from regional sources – including fugitive dust and secondary aerosol. Seasonal variations of source contributions were examined and extreme PM_2.5 episodes were explained by both local and regional pollution events.     

2-(4-Chlorophenyl)benzo-1,4-quinone induced ROS-signaling inhibits proliferation in human non-malignant prostate epithelial cells

Polychlorinated biphenyls (PCBs) and their metabolites are environmental chemical contaminants which can produce reactive oxygen species (ROS) by auto-oxidation of di-hydroxy PCBs as well as the reduction of quinones and redox-cycling. We investigate the hypothesis that 2-(4-chlorophenyl)benzo-1,4-quinone (4-Cl-BQ), a metabolite of 4-chlorobiphenyl (PCB3), induced ROS-signaling inhibits cellular proliferation. Monolayer cultures of exponentially growing asynchronous human non-malignant prostate epithelial cells (RWPE-1) were incubated with 0–6 μM of 4-Cl-BQ and harvested at the end of 72 h of incubation to assess antioxidant enzyme expression, cellular ROS levels, cell growth, and cell cycle phase distributions. 4-Cl-BQ decreased manganese superoxide dismutase (MnSOD) activity, protein, and mRNA levels. 4-Cl-BQ treatment increased dihydroethidium (DHE) fluorescence, which was suppressed in cells pretreated with polyethylene glycol conjugated superoxide dismutase (PEG-SOD). The increase in ROS levels was associated with a decrease in cell growth, and an increase in the percentage of S-phase cells. These effects were suppressed in cells pretreated with PEG-SOD. 4-Cl-BQ treatment did not change the protein levels of phosphorylated H2AX at the end of 72 h of incubation, suggesting that the inhibition in cell growth and accumulation of cells in S-phase at the end of the treatments were probably not due to 4-Cl-BQ induced DNA double strand break. These results demonstrate that MnSOD activity and ROS-signaling perturb proliferation in 4-Cl-BQ treated in vitro cultures of human prostate cells.     

Inferring coastal processes from regional-scale mapping of Radon and salinity: examples from the Great Barrier Reef, Australia

The radon isotope ²²²Rn and salinity in coastal surface water were mapped on regional scales, to improve the understanding of coastal processes and their spatial variability. Radon was measured with a surface-towed, continuously recording multi-detector setup on a moving vessel. Numerous processes and locations of land-ocean interaction along the Central Great Barrier Reef coastline were identified and interpreted based on the data collected. These included riverine fluxes, terrestrially-derived fresh submarine groundwater discharge (SGD) and the tidal pumping of seawater through mangrove forests. Based on variations in the relationship of the tracers radon and salinity, some aspects of regional freshwater inputs to the coastal zone and to estuaries could be assessed. Concurrent mapping of radon and salinity allowed an efficient qualitative assessment of land-ocean interaction on various spatial and temporal scales, indicating that such surveys on coastal scales can be a useful tool to obtain an overview of SGD locations and processes.     

Sustainable nations: what do aggregate indexes tell us?

What is a ‘sustainable nation’ and how can we identify and rank ‘sustainable nations?’ Are nations producing and consuming in a sustainable way? Although several aggregate indexes have been proposed to answer such questions, comprehensive and internationally comparable data are not available for most of these. This paper quantitatively compares three aggregate indexes of sustainability: the World Bank’s ‘Genuine Savings’ measure, the ‘Ecological Footprint,’ and the ‘Environmental Sustainability Index.’ These three indexes are available for a large number of countries and also seem to be the most influential among the aggregate indexes. This paper first discusses the main limitations and weaknesses of each of these indexes. Subsequently, it shows that rankings of sustainable nations and aggregate assessments of unsustainable world population and world GDP shares vary considerably among these indexes. This disagreement leads to suggestions for analysis and policy. One important insight is that climate change, arguable the most serious threat currently faced by humanity, is not or arbitrarily captured by the indexes.