Modeling traffic air pollution in street canyons in New York City for intra-urban exposure assessment in the US Multi-Ethnic Study of atherosclerosis and air pollution

We evaluated the Danish AirGIS air quality and exposure model system using air quality measurement data from New York City in the Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air). Measurements were used from three US EPA Air Quality System (AQS) monitoring stations and a comprehensive MESA Air measurement campaign including about 150 different locations and about 650 samples of about 2 week measurements of NO_x, NO₂ and PM_2.5. AirGIS is a deterministic exposure model system based on the dispersion models Operational Street Pollution Model (OSPM) and the Urban Background Model (UBM). The UBM model reproduced the annual levels within 1–26% depending on station and pollutant at the three urban background EPA monitor stations, and generally reproduced well the seasonal and diurnal variation. The full model with OSPM and UBM reproduced the MESA Air measurements with a correlation coefficient of r² = 0.51 for NO_x, r² = 0.28 for NO₂ and r² = 0.73 for PM_2.5.     

Ultrafine particle fluxes above four major European cities

Little information is known about the behaviour of ultrafine particles (UFP) on a citywide scale. Total particle number flux, dominated by UFP, and other meteorological parameters were collected from tower sites in Manchester, London, Edinburgh and Gothenburg between 1999 and 2006 using the eddy covariance technique. Averaged diurnal cycles were produced for particle number flux, concentration, sensible heat flux, emission velocity, friction velocity, wind speed and temperature. UFP flux cycles showed clear diurnal trends which were linked to traffic activity and local sources. Wind sector analysis showed contributions to flux from local heavily urbanised areas. A simple parameterised model linking UFP flux to traffic activity, sensible heat and friction velocity above the city was produced.     

A study of the total atmospheric sulfur dioxide load using ground-based measurements and the satellite derived Sulfur Dioxide Index

We present characteristics of the sulfur dioxide (SO₂) loading over Thessaloniki, Greece, and seven other selected sites around the world using SO₂ total column measurements from Brewer spectrophotometers together with satellite estimates of the Version 8 TOMS Sulfur Dioxide Index (SOI) over the same locations, retrieved from Nimbus 7 TOMS (1979–1993), Earth Probe TOMS (1996–2003) and OMI/Aura (2004–2006). Traditionally, the SOI has been used to quantify the SO₂ quantities emitted during great volcanic eruptions. Here, we investigate whether the SOI can give an indication of the total SO₂ load for areas and periods away from eruptive volcanic activity by studying its relative changes as a correlative measure to the SO₂ total column. We examined time series from Thessaloniki and another seven urban and non-urban stations, five in the European Union (Arosa, De Bilt, Hohenpeissenberg, Madrid, Rome) and two in India (Kodaikanal, New Delhi). Based on the Brewer data, Thessaloniki shows high SO₂ total columns for a European Union city but values are still low if compared to highly affected regions like those in India. For the time period 1983–2006 the SO₂ levels above Thessaloniki have generally decreased with a rate of 0.028 Dobson Units (DU) per annum, presumably due to the European Union's strict sulfur control policies. The seasonal variability of the SO₂ total column exhibits a double peak structure with two maxima, one during winter and the second during summer. The winter peak can be attributed to central heating while the summer peak is due to synoptic transport from sources west of the city and sources in the north of Greece. A moderate correlation was found between the seasonal levels of Brewer total SO₂ and SOI for Thessaloniki, Greece (R = 0.710–0.763) and Madrid, Spain (R = 0.691) which shows that under specific conditions the SOI might act as an indicator of the SO₂ total load.     

Surface ozone background in the United States: Canadian and Mexican pollution influences

We use a global chemical transport model (GEOS-Chem) with 1° × 1° horizontal resolution to quantify the effects of anthropogenic emissions from Canada, Mexico, and outside North America on daily maximum 8-hour average ozone concentrations in US surface air. Simulations for summer 2001 indicate mean North American and US background concentrations of 26 ± 8 ppb and 30 ± 8 ppb, as obtained by eliminating anthropogenic emissions in North America vs. in the US only. The US background never exceeds 60 ppb in the model. The Canadian and Mexican pollution enhancement averages 3 ± 4 ppb in the US in summer but can be occasionally much higher in downwind regions of the northeast and southwest, peaking at 33 ppb in upstate New York (on a day with 75 ppb total ozone) and 18 ppb in southern California (on a day with 68 ppb total ozone). The model is successful in reproducing the observed variability of ozone in these regions, including the occurrence and magnitude of high-ozone episodes influenced by transboundary pollution. We find that exceedances of the 75 ppb US air quality standard in eastern Michigan, western New York, New Jersey, and southern California are often associated with Canadian and Mexican pollution enhancements in excess of 10 ppb. Sensitivity simulations with 2020 emission projections suggest that Canadian pollution influence in the Northeast US will become comparable in magnitude to that from domestic power plants.     

Ultrafine particles near a major roadway in Raleigh,North Carolina: Downwind attenuation and correlation with traffic-related pollutants

Ultrafine particles (UFPs, diameter < 100 nm) and co-emitted pollutants from traffic are a potential health threat to nearby populations. During summertime in Raleigh, North Carolina, UFPs were simultaneously measured upwind and downwind of a major roadway using a spatial matrix of five portable industrial hygiene samplers (measuring total counts of 20–1000 nm particles). While the upper sampling range of the portable samplers extends past the defined “ultrafine” upper limit (100 nm), the 20–1000 nm number counts had high correlation (Pearson R = 0.7–0.9) with UFPs (10–70 nm) measured by a co-located research-grade analyzer and thus appear to be driven by the ultrafine range. Highest UFP concentrations were observed during weekday morning work commutes, with levels at 20 m downwind from the road nearly fivefold higher than at an upwind station. A strong downwind spatial gradient was observed, linearly approximated over the first 100 m as an 8% drop in UFP counts per 10 m distance. This result agreed well with UFP spatial gradients estimated from past studies (ranging 5–12% drop per 10 m). Linear regression of other vehicle-related air pollutants measured in near real-time (10-min averages) against UFPs yielded moderate to high correlation with benzene (R² = 0.76), toluene (R² = 0.49), carbon monoxide (R² = 0.74), nitric oxide (R² = 0.80), and black carbon (R² = 0.65). Overall, these results support the notion that near-road levels of UFPs are heavily influenced by traffic emissions and correlate with other vehicle-produced pollutants, including certain air toxics.     

A validated 2-D diffusion–advection model for prediction of drift from ground boom sprayers

Correct field drift prediction is a key element in environmental risk assessment of spraying applications. A reduced order drift prediction model based on the diffusion–advection equation is presented. It allows fast assessment of the drift potential of specific ground boom applications under specific environmental wind conditions that obey the logarithmic wind profile. The model was calibrated based on simulations with a validated Computational Fluid Dynamics (CFD) model. Validation of both models against 38 carefully conducted field experiments is successfully performed for distances up to 20 m from the field edge, for spraying on flat pasture land. The reduced order model succeeded in correct drift predictions for different nozzle types, wind velocities, boom heights and spray pressures. It used 4 parameters representing the physical aspects of the drift cloud; the height of the cloud at the field edge, the mass flux crossing the field edge, the settling velocity of the droplets and the turbulence. For the parameter set and range considered, it is demonstrated for the first time that the effect of the droplet diameter distribution of the different nozzle types on the amount of deposition spray drift can be evaluated by a single parameter, i.e., the volume fraction of droplets with a diameter smaller than 191 μm. The reduced order model can be solved more than 4 orders of magnitude faster than the comprehensive CFD model.     

Evaluation and application of biomagnetic monitoring of traffic-derived particulate pollution

Inhalation of particulate pollutants below 10 μm in size (PM₁₀) is associated with adverse health effects. Here we use magnetic remanence measurements of roadside tree leaves to examine levels of vehicle-derived PM around Lancaster, UK. Leaf saturation remanence (SIRM) values exhibit strong correlation with both the SIRM and particulate mass of co-located, pumped-air samples, indicating that these leaf magnetic values are an effective proxy for ambient PM₁₀ concentrations. Biomagnetic monitoring using tree leaves can thus provide high spatial resolution data sets for assessment of particulate pollution levels at pedestrian-relevant heights. Leaf SIRM values not only increase with proximity to roads with higher traffic volumes, but are also ～100% higher at 0.3 m than at ～1.5–2 m height. Magnetic and SEM data indicate that the particle populations are dominated by spherical, iron-rich particles ～0.1–1 μm in diameter, with fewer larger, more angular, silica-rich particles. Comparison of the roadside leaf-calculated PM₁₀ concentrations with PM₁₀ concentrations predicted by a widely-used atmospheric dispersion model indicates some agreement between them. However, the model under-predicts PM₁₀ concentrations at ‘urban hotspots’ such as major–minor road junctions and traffic lights. Conversely, the model over-predicts PM₁₀ concentrations with distance from the road wherever one tree is screened by another, indicating the filtering/protective effect of roadside trees in leaf.     

Tethered balloon-based soundings of ozone,aerosols, and solar radiation near Mexico City during MIRAGE-MEX

A tethered balloon sampling system was used to measure vertical profiles of ozone, particles, and solar radiation in the atmospheric boundary layer on the northern edge of Mexico City, in March 2006 as part of the Megacity Impact on Regional and Global Environment-Mexico experiment. Several commercial sensors, designed for surface applications, were deployed on a tethered balloon platform.Profiles indicate that for these 3 scalars the boundary layer (surface up to 700 m) was well mixed in the period 10:00–16:00 LST. Good agreement was observed for median surface and balloon ozone and particle number concentrations. For most profiles, the surface deposition of ozone was not significant compared to median profile concentrations. Particle number concentration (0.3, 0.5, 1.0 and 5.0 μm) also showed little variation with attitude. Radiatprofiles showed a monotonic increase in diffuse radiation from the maximum altitude of profiles to the surface. Consequently, it was inferred that surface measurements of these likely were representative of lower boundary layer values during this time period.     

Influence of air mass source region on nanoparticle events and hygroscopicity in central Virginia,U.S.

During autumn, 2006, variation in the frequency of aerosol nucleation events, as inferred from nanoparticle growth events, and associated hygroscopicity were investigated as a function of air mass transport history at a mixed deciduous forest in central Virginia, U.S. Above-canopy size distributions of aerosols between 0.012 and 0.700 μm diameter, size-resolved particle hygroscopicity at eight dry diameters between 0.012 and 0.400 μm, and cloud condensation nuclei (CCN) activity were characterized. Air mass back trajectories were clustered to identify source regions. Growth events were most frequent in fast-moving air masses (mean = 9 m s^?1) that originated over the north central U.S. Under these flow regimes, mean values for preexisting sub-μm aerosol number concentrations (4700 cm^?3), corresponding surface area (142 μm² cm^?3), air temperature (6.2 °C), and relative humidity (RH, 49.4%) were relatively low compared to other regimes. Under stagnant flow conditions (mean = 3 m s^?1), mean number concentrations were higher (>6000 cm^?3) and size fractions <0.1 μm diameter exhibited enhanced hygroscopicity compared to other source regions. These results indicate that precursors emitted into relatively clean, cold, and dry air transported over the southeastern U.S. reacted to form condensable intermediates that subsequently produced new aerosols via nucleation and growth. This pathway was an important source for CCN. During events in October, nanoparticles were produced in greater numbers and grew more rapidly compared to November and December.     

Assessing spatial variability of SO2 field as detected by an air quality network using Self-Organizing Maps,cluster, and Principal Component Analysis

In Bilbao (Spain), an air quality network measures sulphur dioxide levels at 4 locations. The objective of this paper is to develop a practical methodology to identify redundant sensors and evaluate a network's capability to correctly follow and represent SO₂ fields in Bilbao, in the frame of a continuous network optimization process.The methodology is developed and tested at this particular location, but it is general enough to be useable at other places as well, since it is not tied neither to the particular geographical characteristics of the place nor to the phenomenology of the air quality over the area.To assess the spatial variability of SO₂ measured at 4 locations in the area, three different techniques have been used: Self-Organizing Maps (SOMs), cluster analysis (CA) and Principal Component Analysis (PCA). The results show that the three techniques yield the same results, but the information obtained via PCA can be helpful not only for that purpose but also to throw light on the major mechanisms involved. This might be used in future network optimization stages. The main advantage of cluster analysis and SOMs is that they provide readily interpretable results. All the calculations have been carried out using the freely available software R.