Study on a new correlation between diffusion coefficient and temperature in porous building materials

The diffusion coefficient (D) and partition coefficient (K_ma) are the two important parameters used to predict the volatile organic compound (VOC) emission or sorption characteristics in porous building materials. D and K_ma may be strongly affected by temperature (T). In this study, we derived a new correlation between D and T based on the assumption that molecular diffusion is dominant, and evaluated this correlation using a series of existing experimental data. The modeling results using the new correlation agree well with the experimental data. The correlation would be useful for assessment of indoor air quality under different environmental (temperature) conditions.     

A performance evaluation of the National Air Quality Forecast Capability for the summer of 2007

This paper provides a performance evaluation of the real-time, CONUS-scale National Air Quality Forecast Capability (NAQFC) that supported, in part, its transition into operational status. This evaluation focuses primarily on discrete forecasts for the maximum 8-h O₃ concentrations covering the 4-month period, June through September, 2007, using measurements obtained from EPA's AIRNow network. Results indicate that the 2007 NAQFC performed as well or better than previous configurations, despite the expansion of the forecast domain into the western half of the nation that is dominated by complex terrain. The mean, domain-wide, season-long correlation was 0.70. When examined over time, the domain-wide correlations exhibit a fairly consistent nature, with values exceeding 0.60 (0.70) over 90% (55%) of the days. The NAQFC systematically over-predicted the 8-h O₃ concentrations, continuing a trend established by earlier NAQFC configurations, though to a lesser degree. The summer-long mean forecast value of 53.2 ppb was 4.2 ppb higher than the observed value, resulting in a domain-wide Normalized Mean Bias (NMB) of 8.7%. Most of the over-prediction is associated with observed concentrations less than 50 ppb. In fact the model tends to under-predict when concentrations exceed 70 ppb. As with the bias, the error associated with the latest configuration was also lower. The summer-long Root Mean Square Error of 13.0 ppb (Normalized Mean Error (NME) = 20.4%) represented marked improvements over earlier forecasts. Examination of the spatial distribution of both the NMB and NME reveals that the NAQFC was generally within 25% for the NME and 25% for the NMB over a majority of the domain. Several areas of poorer performance, where the NMB and NME often exceed 25% and in some cases 50%, were noted. These areas include southern California, where the NAQFC tended to under-predict concentrations (especially on weekends) and the southeast Atlantic and Gulf coasts regions, where the model over-predicted. Subsequent analysis revealed that the incorrect temporal allocation of precursor emissions was likely the source of the under-prediction in southern California, while inaccurate simulation of PBL heights likely contributed to the over-prediction in the coastal regions.     

Impact of dry deposition of semi-volatile organic compounds on secondary organic aerosols

Dry deposition of semi-volatile organic compounds (SVOC) is not currently treated in most chemical transport models of air quality and this omission has been identified as a possible major source of uncertainty. The effect of dry deposition of SVOC on the concentration of secondary organic aerosols (SOA) is investigated in summertime with the chemical transport model CHIMERE that simulates SOA concentrations by means of molecular SOA surrogate species. Omitting dry deposition could overestimate SOA concentrations by as much as 50%. This overestimation is larger during nighttime due to higher relative humidity.     

Natural emissions for regional modeling of background ozone and particulate matter and impacts on emissions control strategies

Natural emissions adopted in current regional air quality modeling are updated to better describe natural background ozone and PM concentrations for North America. The revised natural emissions include organosulfur from the ocean, NO from lightning, sea salt, biogenic secondary organic aerosol (SOA) precursors, and pre-industrial levels of background methane. The model algorithm for SOA formation was also revised. Natural background ozone concentrations increase by up to 4 ppb in annual average over the southeastern US and Gulf of Mexico due to added NO from lightning while the revised biogenic emissions produced less ozone in the central and western US. Natural PM_2.5 concentrations generally increased with the revised natural emissions. Future year (2018) simulations were conducted for several anthropogenic emission reduction scenarios to assess the impact of the revised natural emissions on anthropogenic emission control strategies. Overall, the revised natural emissions did not significantly alter the ozone responses to the emissions reductions in 2018. With revised natural emissions, ozone concentrations were slightly less sensitive to reducing NOx in the southeastern US than with the current natural emissions due to higher NO from lightning. The revised natural emissions have little impact on modeled PM_2.5 responses to anthropogenic emission reductions. However, there are substantial uncertainties in current representations of natural sources in air quality models and we recommend that further study is needed to refine these representations.     

Measured reduction of kerbside ultrafine particle number concentrations in Copenhagen

The average particle number concentration kerbside at a busy street in Copenhagen has been reduced by 27% from the period 2002–2004 to the period 2005–2007. The reduction is in the ultrafine particle range (<100 nm). Strong evidence indicates that a significant part of the reduction, especially in the size range <30 nm, is due to the transition to sulphur-free (<10 ppm) diesel fuel and petrol in Denmark at New Year 2005.     

A preliminary examination of the translocation of microencapsulated cyfluthrin following applications to the perimeter of residential dwellings

Abstract

Methods have been developed to monitor the translocation of microencapsulated cyfluthrin following perimeter applications to residential dwellings. A pilot study was implemented to determine both the potential for application spray to drift away from dwellings and the intrusion of residues into homes following perimeter treatments. Residential monitoring included measuring spray drift using cellulose filter paper and the collection of soil samples from within the spray zone. In addition, interior air was monitored using fiberglass filter paper as a sorbent medium and cotton ball swabs were used to collect surface wipes.

Fortification of matrixes resulted in recoveries of >90%. Spray drift was highest at the point of application and declined to low but measurable levels 9.1m from the foundations of dwellings. Soil residues declined to low, but measurable levels by 45 days post‐application. No cyfluthrin was measured from indoor air; however, some interior surfaces had detectable levels of cyfluthrin until three days post‐application.

Findings indicate that spray drift resulting from perimeter applications might contaminate non‐target surfaces outside the spray zone. Soil borne residues may serve as persistent sources for human exposure and potentially intrude into dwellings through the activities of occupants and pets. Residues do not appreciably translocate through air and consequently inhalation is not a likely route for human exposure. Surface residues detected indoors suggest that the physical movement of residues from the exterior to the interior might be a viable route of movement of residues following this type of application.     

Influence of boundary conditions on CMAQ simulations over the Iberian Peninsula

The influence of chemical boundary conditions (BC) on the response of the Community Multiscale Air Quality (CMAQ) model over the Iberian Peninsula was investigated in this study. Three strategies to supply boundary conditions in the context of the Integrated Assessment Modelling System for the Iberian Peninsula (SIMCA) were tested. Alternative methods consist in providing BC from (1) fixed, time-independent, concentration profiles, (2) concentrations predicted in a CMAQ mother domain (48 km, 1 h resolution) and (3) concentration values from the GEOS-Chem chemical-transport global model (2 × 2.5°, 3 h resolution). High resolution (3 km) simulated concentrations of the main pollutants (NO₂, NO, SO₂, O₃, PM₁₀ and PM_2.5) were compared through a comprehensive statistical analysis including observational data from 165 monitoring stations all over the Iberian Peninsula. It was found that model sensitivity to BC for nitrogen and sulphur oxides was limited, being restricted to the vicinity of model boundaries. However, significant domain-wide differences were found when modelling ozone and PM depending on the BC provided to run the tests. Although model performance was affected by spatial and seasonal factors, the results indicate that model-derived, dynamic BC improved CMAQ predictions when compared to those based on static concentrations prescribed in the boundaries. Aggregated statistics suggest that the GEOS-Chem produced the best results for O₃ and PM_2.5 while NO₂ and PM₁₀ were slightly better predicted under the CMAQ nesting approach. Besides the statistical evaluation some other relevant issues in the context of Integrated Assessment Modelling (IAM) are discussed to gain a better insight into the suitability of the methods analyzed and limitations of downscaling methods. Despite being useful to get a better understanding of the role of BC in SIMCA, this study contributed to highlight model deficiencies and therefore to point out future research needs to improve IAM activities in the Iberian Peninsula.     

Development of a composite line source emission model for traffic interrupted microenvironments and its application in particle number emissions at a bus station

A composite line source emission (CLSE) model was developed to specifically quantify exposure levels and describe the spatial variability of vehicle emissions in traffic interrupted microenvironments. This model took into account the complexity of vehicle movements in the queue, as well as different emission rates relevant to various driving conditions (cruise, decelerate, idle and accelerate), and it utilised multi-representative segments to capture the accurate emission distribution for real vehicle flow. Hence, this model was able to quickly quantify the time spent in each segment within the considered zone, as well as the composition and position of the requisite segments based on the vehicle fleet information, which not only helped to quantify the enhanced emissions at critical locations, but it also helped to define the emission source distribution of the disrupted steady flow for further dispersion modelling. The model then was applied to estimate particle number emissions at a bi-directional bus station used by diesel and compressed natural gas fuelled buses. It was found that the acceleration distance was of critical importance when estimating particle number emission, since the highest emissions occurred in sections where most of the buses were accelerating and no significant increases were observed at locations where they idled. It was also shown that emissions at the front end of the platform were 43 times greater than at the rear of the platform. Although the CLSE model is intended to be applied in traffic management and transport analysis systems for the evaluation of exposure, as well as the simulation of vehicle emissions in traffic interrupted microenvironments, the bus station model can also be used for the input of initial source definitions in future dispersion models.     

Potential Impact of Clean Air Act Regulations on Nitrogen Fate and Transport in the Neuse River Basin: a Modeling Investigation Using CMAQ and SWAT

There has been extensive analysis of Clean Air Act Amendment (CAAA) regulation impacts to changes in atmospheric nitrogen deposition; however, few studies have focused on watershed nitrogen transfer particularly regarding long-term predictions. In this study, we investigated impacts of CAAA NOx emissions on the fate and transport of nitrogen for two watersheds in the Neuse River Basin. We applied the Soil and Water Assessment Tool (SWAT) using simulated deposition rates from the Community Multiscale Air Quality (CMAQ) model. Two scenarios were investigated: one that considered CAAA emission controls in CMAQ simulation (with) and a second that did not (without). By 2020, results showed a 70 % drop in nitrogen discharge for the Little River watershed and a 50 % drop for the Nahunta watershed from 1990 levels under the with-CAAA scenario. Denitrification and plant nitrogen uptake played important roles in nitrogen discharge from each watershed. Nitrogen watershed response time to a change in atmospheric nitrogen deposition was 4 years for Nahunta and 2 years for Little River. We attribute these differences in nitrogen response time to contrasts in agricultural land use and diversity of crop types. Soybean, hay, and corn land covers had comparatively longer response times to changes in atmospheric deposition. The studied watersheds demonstrate relatively large nitrogen retention: ≥80 % of all delivered nitrogen.