WRF/Chem simulated springtime impact of rising Asian emissions on air quality over the U.S.

This paper examines the impact of tripled anthropogenic emissions from China and India over the base level (gaseous species and carbonaceous aerosols for 2000) on air quality over the U.S. using the WRF/Chem (Weather Research and Forecasting – Chemistry) model at 1° resolution. WRF/Chem is a state-of-the-science, fully coupled chemistry and meteorology system suitable for simulating the transport and dispersion of pollutants and their impacts. The analyses in this work were focused on MAM (March, April and May). The simulations indicate an extensive area of elevated pollutant concentrations spanning from the Arabian Sea to the Northern Pacific and to the Northern Atlantic. MAM mean contributions from the tripled Asian emissions over the U.S. are found to be: 6–12 ppbv for CO, 1.0–2.5 ppbv for O₃, and 0.6–1.6 μg m^?3 for PM_2.5 on a daily basis.     

Influence of ship emissions on ozone concentrations around coastal areas during summer season

The influence of ship emissions on ozone (O₃) concentrations in a coastal area (CA) including Busan port, Korea was examined based on a numerical modeling approach during a high O₃ episode. The analysis was performed by two sets of simulation scenarios: (1) with ship emissions (e.g., TOTAL case) and (2) without ship emissions (e.g., BASE case). A process analysis (PA) (the integrated processes rate (IPR) and integrated reaction rate (IRR) analyses) was used to evaluate the relative contributions of individual physical and chemical processes in O₃ production in and around the CA (e.g., sites of Dong Sam (DS) and Dae Yeon (DY)). The model study suggested the possibility that pollutant gases emitted from the ships traversing Busan port can exert a direct impact on the O₃ concentration levels in the CA. Largest impacts of ship emissions on the O₃ concentrations were predicted at the coast (up to 15 ppb) and at inland locations (about 5 ppb) due to both the photochemical production of pollutant gases emitted from the ships and meteorological conditions. From the PA, the photochemical production of O₃ (P(O₃)) due to ship emissions in the CA was found to increase by a mean of 1.5 ppb h^?1 (especially by ≥10 ppb h^?1 at the DS site) during the day.     

Application of a Lagrangian particle model to assess the impact of harbour,industrial and urban activities on air quality in the Taranto area,Italy

This paper evaluates the relative impact on air quality of harbour emissions, with respect to other emission sources located in the same area. The impact assessment study was conducted in the city of Taranto, Italy. This area was considered as representative of a typical Mediterranean harbour region, where shipping, industries and urban activities co-exist at a short distance, producing an ideal case to study the interaction among these different sources. Chemical and meteorological field campaigns were carried out to provide data to this study. An emission inventory has been developed taking into account industrial sources, traffic, domestic heating, fugitive and harbour emissions. A 3D Lagrangian particle dispersion model (SPRAY) has then been applied to the study area using reconstructed meteorological fields calculated by the diagnostic meteorological model MINERVE. 3D short term hourly concentrations have been computed for both all and specific sources. Industrial activities are found to be the main contributor to SO₂. Industry and traffic emissions are mainly responsible for NO_x simulated concentrations. CO concentrations are found to be mainly related to traffic emissions, while primary PM₁₀ simulated concentrations tend to be linked to industrial and fugitive emissions. Contributions of harbour activities to the seasonal average concentrations of SO₂ and NO_x are predicted to be up to 5 and 30 μg m⁻³, respectively to be compared to a overall peak values of 60 μg m⁻³ for SO₂ and 70 μg m⁻³ for NO_x. At selected urban monitoring stations, SO₂ and NO_x average source contributions are predicted to be both of about 9% from harbour activities, while 87% and 41% respectively of total concentrations are predicted to be of industrial origin.     

Identification and assessment of ship emissions and their effects in the harbour of Göteborg,Sweden

The effect of ship emissions in the urban environment of Göteborg has been studied by multivariate analysis. The simultaneous measurements of relevant gases and sub-micron particles make identification of ship plumes possible. Increased concentrations of these species due to ship emissions are quantified for ships entering the inner part of the harbour. Annual depositions of SO₂ and NO₂ are estimated to be 220 and 115 kg km⁻² yr⁻¹, respectively. Exposure of transient particles (less than 0.1 μm in diameter) to this part of the harbour increased by a factor of 3 in number concentration when a ship plume was recorded. Ni, Pb, V and Zn are shown to have positive correlation with NO emissions from ships.     

Sensitivity of ozone concentrations to diurnal variations of surface emissions in Mexico City: A WRF/Chem modeling study

Sensitivity of ozone (O₃) concentrations in the Mexico City area to diurnal variations of surface air pollutant emissions is investigated using the WRF/Chem model. Our analysis shows that diurnal variations of nitrogen oxides (NO_x = NO + NO₂) and volatile organic compound (VOC) emissions play an important role in controlling the O₃ concentrations in the Mexico City area. The contributions of NO_x and VOC emissions to daytime O₃ concentrations are very sensitive to the morning emissions of NO_x and VOCs. Increase in morning NO_x emissions leads to decrease in daytime O₃ concentrations as well as the afternoon O₃ maximum, while increase in morning VOC emissions tends to increase in O₃ concentrations in late morning and early afternoon, indicating that O₃ production in Mexico City is under VOC-limited regime. It is also found that the nighttime O₃ is independent of VOCs, but is sensitive to NO_x. The emissions of VOCs during other periods (early morning, evening, and night) have only small impacts on O₃ concentrations, while the emissions of NO_x have important impacts on O₃ concentrations in the evening and the early morning.This study suggests that shifting emission pattern, while keeping the total emissions unchanged, has important impacts on air quality. For example, delaying the morning emission peak from 8 am to 10 am significantly reduced the morning peaks of NO_x and VOCs, as well as the afternoon O₃ maxima. It suggests that without reduction of total emission, the daytime O₃ concentrations can be significantly reduced by changing the diurnal variations of the emissions of O₃ precursors.     

C1–C8 volatile organic compounds in the atmosphere of Hong Kong: Overview of atmospheric processing and source apportionment

We present measurements of C₁–C₈ volatile organic compounds (VOCs) at four sites ranging from urban to rural areas in Hong Kong from September 2002 to August 2003. A total of 248 ambient VOC samples were collected. As expected, the urban and sub-urban sites generally gave relatively high VOC levels. In contrast, the average VOC levels were the lowest in the rural area. In general, higher mixing ratios were observed during winter/spring and lower levels during summer/fall because of seasonal variations of meteorological conditions. A variation of the air mass composition from urban to rural sites was observed. High ratios of ethyne/CO (5.6 pptv/ppbv) and propane/ethane (0.50 pptv/pptv) at the rural site suggested that the air masses over the territory were relatively fresh as compared to other remote regions. The principal component analysis (PCA) with absolute principal component scores (APCS) technique was applied to the VOC data in order to identify and quantify pollution sources at different sites. These results indicated that vehicular emissions made a significant contribution to ambient non-methane VOCs (NMVOCs) levels in urban areas (65±36%) and in sub-urban areas (50±28% and 53±41%). Other sources such as petrol evaporation, industrial emissions and solvent usage also played important roles in the VOC emissions. At the rural site, almost half of the measured total NMVOCs were due to combustion sources (vehicular and/or biomass/biofuel burning). Petrol evaporation, solvent usage, industrial and biogenic emissions also contributed to the atmospheric NMVOCs. The source apportionment results revealed a strong impact of anthropogenic VOCs to the atmosphere of Hong Kong in both urban/sub-urban and rural areas.     

Source characterization of ambient fine particles at multiple sites in the Seattle area

To identify major PM_2.5 (particulate matter ≤2.5 μm in aerodynamic diameter) sources with a particular emphasis on the ship engine emissions from a major port, integrated 24 h PM_2.5 speciation data collected between 2000 and 2005 at five United State Environmental Protection Agency's Speciation Trends Network monitoring sites in Seattle, WA were analyzed. Seven to ten PM_2.5 sources were identified through the application of positive matrix factorization (PMF). Secondary particles (12–26% for secondary nitrate; 17–20% for secondary sulfate) and gasoline vehicle emissions (13–31%) made the largest contributions to the PM_2.5 mass concentrations at all of the monitoring sites except for the residential Lake Forest site, where wood smoke contributed the most PM_2.5 mass (31%). Other identified sources include diesel vehicle emissions, airborne soil, residual oil combustion, sea salt, aged sea salt, metal processing, and cement kiln. Residual oil combustion sources identified at multiple monitoring sites point clearly to the Port of Seattle suggesting ship emissions as the source of oil combustion particles. In addition, the relationship between sulfate concentrations and the oil combustion emissions indicated contributions of ship emissions to the local sulfate concentrations. The analysis of spatial variability of PM_2.5 sources shows that the spatial distributions of several PM_2.5 sources were heterogeneous within a given air shed.     

Modelling NOx from lightning and its impact on global chemical fields

We have used a three-dimensional off-line chemical transport model (CTM) to assess the impact of lightning emissions in the free troposphere both on NO_x itself and on other chemical species such as O₃ and OH. We have investigated these effects using two lightning emission scenarios. In the first, lightning emissions are coupled in space and time to the convective cloud top height calculated every 6 h by the CTM's moist convection scheme. In the second, lightning emissions are calculated as a constant, monthly mean field. The model's performance against observed profiles of NO_x and O₃ in the Atlantic and Pacific ocean improves significantly when lightning emissions are included. With the inclusion of these emissions, the CTM produces a significant increase in the NO_x concentrations in the upper troposphere, where the NO_x lifetime is long, and a smaller increase in the lower free troposphere, where the surface NO_x sources dominate. These changes cause a significant increase in the O₃ production in the upper troposphere and hence higher calculated O₃ there. The model indicates that lightning emissions cause local increases of over 50 parts per 10¹² by volume (pptv) in NO_x, 200 pptv in HNO₃ and 20 parts per 10⁹ by volume (ppbv) (>40%) in O₃. In addition, a smaller increase of O₃ in the lower troposphere occurs due to an increase in the downward transport of O₃. The O₃ change is accompanied by an increase in OH which is more pronounced in the upper troposphere with a corresponding reduction in CO. The method of emission employed in the model does not appear to have a significant effect globally. In the upper troposphere (above about 300 hPa) NO_x concentrations are generally lower with monthly mean emissions, because of the de-coupling of emissions from the model's convection scheme, which vents NO_x aloft more efficiently in the coupled scheme. Below the local convective outflow altitude, NO_x concentrations are larger when using the monthly mean emissions than when coupled to the convection scheme, because the more dilute emissions, and nighttime emissions, lead to a slower NO_x destruction rate. Only minor changes are predicted in the monthly average fields of O₃ if we emit lightning as a monthly constant field. However, the method of emission becomes important when we make a direct comparison of model results with time varying data. These differences should be taken into account when a direct comparison of O₃ with measurements collected at particular times and locations is attempted.     

Fully coupled “online” chemistry within the WRF model

A fully coupled “online” Weather Research and Forecasting/Chemistry (WRF/Chem) model has been developed. The air quality component of the model is fully consistent with the meteorological component; both components use the same transport scheme (mass and scalar preserving), the same grid (horizontal and vertical components), and the same physics schemes for subgrid-scale transport. The components also use the same timestep, hence no temporal interpolation is needed. The chemistry package consists of dry deposition (“flux-resistance” method), biogenic emission as in [Simpson et al., 1995. Journal of Geophysical Research 100D, 22875–22890; Guenther et al., 1994. Atmospheric Environment 28, 1197–1210], the chemical mechanism from RADM2, a complex photolysis scheme (Madronich scheme coupled with hydrometeors), and a state of the art aerosol module (MADE/SORGAM aerosol parameterization).The WRF/Chem model is statistically evaluated and compared to MM5/Chem and to detailed photochemical data collected during the summer 2002 NEAQS field study. It is shown that the WRF/Chem model is statistically better skilled in forecasting O₃ than MM5/Chem, with no appreciable differences between models in terms of bias with the observations. Furthermore, the WRF/Chem model consistently exhibits better skill at forecasting the O₃ precursors CO and NO_y at all of the surface sites. However, the WRF/Chem model biases of these precursors and of other gas-phase species are persistently higher than for MM5/Chem, and are most often biased high compared to observations. Finally, we show that the impact of other basic model assumptions on these same statistics can be much larger than the differences caused by model differences. An example showing the sensitivity of various statistical measures with respect to the treatment of biogenic volatile organic compounds emissions illustrates this impact.     

Measurements and modelling of PM2.5 concentrations near a major road in Kuopio,Finland

A particle measurement campaign was conducted in a suburban environment near a major road in Kuopio, Central Finland from 3 August to 9 September 1999. The mass concentrations of fine particles (PM_2.5) were measured simultaneously at distances of 12, 25, 52 and 87 m from the centre of a major road at a height of 1.8 m, using identical samplers. The concentration measurements were conducted during 16 daytime hours (from 6.00 a.m. to 10.00 p.m.) for 27 days. Traffic flows and relevant meteorological parameters were measured on-site; meteorological measurements from a nearby synoptic weather station were also utilised. We also suggest a preliminary model for predicting the concentrations of PM_2.5 and apply this model in order to analyse the measured data. The regionally and long-range transported contribution was evaluated on the basis of a semi-empirical mathematical model utilising as input values the daily sulphate, nitrate and ammonium measurements at the EMEP stations (Co-operative programme for monitoring and evaluation of the long-range transmission of air pollutants in Europe). The influence of primary vehicular emissions from the nearest roads was evaluated using a roadside emission and dispersion model, CAR-FMI, in combination with a meteorological pre-processing model, MPP-FMI. The contribution of non-exhaust particulate matter emissions (including resuspension of particulate matter from road surfaces) was estimated simply to be directly proportional to the concentrations originating from primary vehicular emissions. Comparison of the predicted results and measurements yields information on the relative importance of various source categories of the measured concentrations of PM_2.5. The regionally and long-range transported contribution, the primary and non-exhaust vehicular emissions, and other sources were estimated to contribute on average 41±6%, 33±6% and 26±7% of the observed PM_2.5 concentrations, respectively. The model presented could also be applied in other European cities for analysing the source contributions to measured fine particulate matter concentrations.     

Comparisons of WRF/Chem simulated O3 concentrations in Mexico City with ground-based RAMA measurements during the MILAGRO period

This work compares the WRF/Chem (Weather Research and Forecasting – Chemistry) simulated O₃ concentrations in the Mexico City Metropolitan Area (MCMA) with measurements from the ground-based RAMA network during the MILAGRO (Megacity Initiative: Local and Global Research Observations) period. The model resolves the observations reasonably well in terms of diurnal cycle and mean magnitude as reflected by high correlation coefficients and low root-mean-square errors. Stations located in the center of the MCMA generally exhibit higher correlation coefficients and lower model biases than those stations located in the peripheral of the MCMA. Large temporal variations in the observed and simulated O₃ concentrations are noted from station to station during the MILAGRO period. Sensitivity analyses of O₃ concentrations to changes in NO_x and VOC emissions rates suggest that O₃ production in the MCMA is VOC-sensitive, and VOC-emissions reduction appears to be an effective strategy for reducing high surface O₃ concentrations in the MCMA.     

The use of receptor modelling and emission inventory data to explain the downward trend in UK PM10 concentrations

Statistically significant downward trends in measured UK annual mean PM₁₀ concentrations have been observed at eight out of the nine urban background monitoring sites between the start of monitoring in 1992 or 1993 and 2000.Site-specific projections of the individual components of measured PM₁₀ concentrations have been derived for the period 1992–2000 at three monitoring sites from receptor modelling results for 1999 monitoring data. Measured annual average PM₁₀ concentrations declined to between 71% and 66% of the 1992 values during this period at the sites studied. The largest contributions to the decline in total PM₁₀ are from secondary particles at London Bloomsbury (40%, 3.4 μg m⁻³, tapered element oscillating microbalance (TEOM)), stationary sources at Belfast Centre (53%, 4.6 μg m⁻³, TEOM) and roadside traffic emissions at Bury Roadside (49%, 5.0 μg m⁻³, TEOM). The good agreement between the projected total PM₁₀ concentrations and measured values for the years 1992–2000 indicate that the combination of the receptor model and the site-specific projections provide a suitably robust method for predicting future PM₁₀ concentrations and the quantification of the impact of possible future policy measures to reduce PM₁₀ concentrations. The good agreement between the projections and measured concentration also provides a useful verification of the trends in emissions inventory estimates for the 1990s.Projections of estimated PM₁₀ concentrations have also been calculated for the London Bloomsbury site for the period from 1970 to 1991. Annual mean concentrations are predicted to have been in the range from 30 to 35 μg m⁻³, TEOM from 1977 to 1991 but much higher at values between 39 and 46 μg m⁻³, TEOM in the early 1970s.     

Meteorological variability in NO2 and PM10 concentrations in the Netherlands and its relation with EU limit values

The extent of the exceedance of the EU limit values for nitrogen dioxide (NO₂) and particulate matter (PM₁₀) concentrations within the Netherlands is expected to decrease significantly, in the coming years. Whether limit values will actually be exceeded, in the next decade, depends not only on European, national and local policies, but also on the effects of inevitable interannual meteorological fluctuations. An analysis of model calculations and measurements yields variations (1 sigma) in the annual average concentration of about 5% for NO₂ and 9% for PM₁₀, due to meteorological fluctuations. These deviations from long-term average concentrations affect assessments of future levels, set against limit values. For instance, an NO₂ concentration of 39 μg m^?3, estimated for a given year with long-term average meteorology, indicates that it is likely (chance >66%) that the limit value of 40 μg m^?3 will not be exceeded in that particular year. At the same time, the estimation also indicates, for example, that this situation is unlikely (change <33%) to continue for three years in a row. However, with an estimated concentration of 38 μg m^?3, it is likely that the limit value will not be exceeded for three years in a row. The limit value for the daily average PM₁₀ concentration is equivalent to an annual average of about 32 μg m^?3. This threshold is unlikely to be exceeded for three years in a row, when an annual average concentration of 29 μg m^?3 is estimated. Interannual variations in concentrations of NO₂ and PM₁₀ are linked to large-scale meteorological fluctuations. Therefore, similar results can be expected for other European countries.     

An examination of oxidant amounts on secondary organic aerosol formation and aging

The effect of HO_x radicals (OH and HO₂) and ozone (O₃) on aerosol formation and aging has been studied. Experiments were performed in presence as well as in absence of oxygen in a flow-through chamber at 299 K for three organic precursor gases, isoprene, α-pinene and m-xylene. The HO_x source was the UV photolysis of humidified air or nitrogen and was measured with a GTHOS (Ground-based Tropospheric Hydrogen Oxides Sensor). The precursor gases concentration was monitored with an online GC-FID. The aerosol mass was then quantified by a Tapered Element Oscillating Microbalance (TEOM). Typical oxidant mixing ratios were (0–4.5) ppm for O₃, 200 pptv for OH and 3 ppbv for HO₂. A simple kinetics model is used to infer the aerosol production mechanism. In the present of O₃ (or O₂), the SOA yields were 0.46, 0.036 and 0.12 for α-pinene with an initial concentration of 100 ppbv (RH = 37%), isoprene with an initial concentration of 177 ppbv (RH = 50%) and m-xylene with an initial concentration of 100 ppbv (RH = 37%), respectively. When the chosen precursor gases reacted with HO_x in the absence of O₃, the maximum SOA yields were significantly increased by factors of 1.6 for isoprene 1.1 for α-pinene, and 3 for m-xylene respectively. The comparison of the calculated and measured potential aerosol mass concentrations as function of time shows that presence of ozone or oxygen can influence the aerosol yield and the absence of ozone or oxygen in the system resulted in high concentrations of its organic aerosol products.     

The effect of variability in industrial emissions on ozone formation in Houston, Texas

Ambient observations have indicated that high concentrations of ozone observed in the Houston/Galveston area are associated with plumes of highly reactive hydrocarbons, mixed with NO_x, from industrial facilities. Ambient observations and industrial process data, such as mass flow rates for industrial flares, indicate that the VOCs associated with these industrial emissions can have significant temporal variability. To characterize the effect of this variability in emissions on ozone formation in Houston, data were collected on the temporal variability of industrial emissions or emission surrogates (e.g., mass flow rates to flares). The observed emissions variability was then used to construct regionwide emission inventories with variable industrial emissions, and the impacts of the variability on ozone formation were examined for two types of meteorological conditions, both of which lead to high ozone concentrations in Houston. The air quality simulations indicate that variability in industrial emissions has the potential to cause increases and decreases of 10–52 ppb (13–316%), or more, in ozone concentration. The largest of these differences are restricted to regions of 10–20 km², but the variability also has the potential to increase regionwide maxima in ozone concentrations by up to 12 ppb.     

Estimating the effects of increased urbanization on surface meteorology and ozone concentrations in the New York City metropolitan region

Land use and pollutant emission changes can have significant impacts on air quality, regional climate, and human health. Here we describe a modeling study aimed at quantifying the potential effects of extensive changes in urban land cover in the New York City (NYC), USA metropolitan region on surface meteorology and ozone (O₃) concentrations. The SLEUTH land-use change model was used to extrapolate urban land cover over this region from “present-day” (ca. 1990) conditions to a future year (ca. 2050), and these projections were subsequently integrated into meteorological and air quality simulations. The development of the future-year land-use scenario followed the narrative of the “A2” scenario described by the Intergovernmental Panel on Climate Change (IPCC), but was restricted to the greater NYC area. The modeling system consists of the Penn State/NCAR MM5 mesoscale meteorological model; the Sparse Matrix Operator Kernal Emissions processing system; and the US EPA Community Multiscale Air Quality model, and simulations were performed for two 18-day episodes, one near-past and one future. Our results suggest that extensive urban growth in the NYC metropolitan area has the potential to increase afternoon near-surface temperatures by more than 0.6 °C and planetary boundary layer (PBL) heights by more than 150 m, as well as decrease water vapor mixing ratio by more than 0.6 g kg⁻¹, across the NYC metropolitan area, with the areal extent of all of these changes generally coinciding with the area of increased urbanization. On the other hand, the impacts of these land use changes on ozone concentrations are more complex. Simulation results indicate that future changes in urbanization, with emissions held constant, may lead to increases in episode-average O₃ levels by about 1–5 ppb, and episode-maximum 8 h O₃ levels by more than 6 ppb across much of the NYC area. However, spatial patterns of ozone changes are heterogeneous and also indicate the presence of areas with decreasing ozone concentrations. When anthropogenic emissions were increased to be consistent with the extensive urbanization in the greater NYC area, the O₃ levels increased in outer counties of the metropolitan region but decreased in others, including coastal Connecticut and the Long Island Sound area.     

Temporal,spatial characteristics and uncertainty of biogenic VOC emissions in the Pearl River Delta region,China

Using the Global Biosphere Emissions and Interactions System model (GloBEIS), 3 × 3 km gridded and hourly biogenic volatile organic compound (BVOC) emissions in the Pearl River Delta (PRD) were estimated for the year 2006. The study used newly available land cover database, observed meteorological data, and recent measurements of emission rates for tree species in China. The results show that the total BVOC emission in the PRD region in 2006 was 296 kt (2.2 × 10¹¹ gC), of which isoprene contributes about 25% (73 kt, 6.4 × 10¹⁰ gC), monoterpenes about 34% (102 kt, 8.9 × 10¹⁰ gC), and other VOCs (OVOC) about 41% (121 kt, 6.8 × 10¹⁰ gC). BVOC emissions in the PRD region exhibit a marked seasonal pattern with the peak emission in July and the lowest emission in January, and are mainly distributed over the outlying areas of the PRD region, where the economy and land use are less developed. The uncertainties in BVOC emission estimates were quantified using Monte Carlo simulation; the results indicate high uncertainties in isoprene emission estimates, with a relative error of ?82 to +177%, ranging from 12.4 to 186.4 kt; ?41 to +58% uncertainty for monoterpenes emissions, ranging from 67.7 to 181.9 kt; and ?26 to +30% uncertainty in OVOC emissions, ranging from 88.8 to 156.2 kt on the 95% confidence intervals. The key uncertainty sources include emission factors and the model empirical coefficients α, C_T1, C_L, and E_opt for estimating isoprene emission, and emission factors and foliar density for estimating monoterpenes and OVOC emissions. This implies that determining these empirical coefficient values properly and conducting more field measurements of emission rates of tree species are key approaches for reducing uncertainties in BVOC emission estimates. Improving future BVOC emission inventory work in the PRD region requires giving priority to research on shrub land, coniferous forests, and irrigated cropland and pasture.     

Three-dimensional characterization of the ammonia plume from a beef cattle feedlot

In Canada approximately 45% of ammonia (NH₃) emissions are attributed to dairy and beef cattle industries. The present study focused on NH₃ emissions from a beef feedlot with a one-time capacity of 17,220 head. The aim was to improve the Canadian NH₃ emission inventories and air quality forecasting capabilities. A Cessna 207, equipped with a fast-response NH₃/NO_y detector and a quadrupole aerosol mass spectrometer, was flown in a grid pattern covering an area of 8 × 8 km centered on a feedlot (800 × 800 m) at altitudes ranging from 30 to 300 m above ground. Stationary ground measurements of NH₃ concentration and turbulence parameters were made downwind of the feedlot. Three flights were conducted under varying meteorological conditions, ranging from very calm to windy with near-neutral stratification. NH₃ mixing ratios up to 100 ppbv were recorded on the calm day, up to 300 m above ground. An average feedlot NH₃ emission rate of 76 ± 4 μg m^?2 s^?1 (equivalent to 10.2 g head^?1 h^?1) was estimated. Characteristics of the measured NH₃ plume were compared to those predicted by a Lagrangian dispersion model. The spatially integrated pattern of NH₃ concentrations predicted and measured agreed but the measured was often more complex than the predicted spatial distribution. The study suggests that the export of NH₃ through advection accounted for about 90% of the emissions from the feedlot, chemical transformation was insignificant, and dry deposition accounted for the remaining 10%.     

Analysis of ozone and VOCs measured in Shanghai: A case study

Shanghai Meteorological Administration has established a volatile organic compounds (VOCs) laboratory and an observational network for VOCs and ozone (O₃) measurements in the city of Shanghai. In this study, the measured VOCs and O₃ concentrations from 15 November (15-Nov) to 26 November (26-Nov) of 2005 in Shanghai show that there are strong day-to-day and diurnal variations. The measured O₃ and VOCs concentrations have very different characterizations between the two periods. During 15-Nov to 21-Nov (defined as the first period), VOCs and O₃ concentrations are lower than the values during 22-Nov to 28-Nov (defined as the second period). There is a strong diurnal variation of O₃ during the second period with maximum concentrations of 40–80 ppbv at noontime, and minimum concentrations at nighttime. By contrast, during the first period, the diurnal variation of O₃ is in an irregular pattern with maximum concentrations of only 20–30 ppbv. The VOC concentrations change rapidly from 30–50 ppbv during the first period to 80–100 ppbv during the second period. Two chemical models are applied to interpret the measurements. One model is a regional chemical/dynamical model (WRF-Chem) and another is a detailed chemical mechanism model (NCAR MM). Model analysis shows that the meteorological conditions are very different between the two periods, and are mainly responsible for the different chemical characterizations of O₃ and VOCs between the two periods. During the first period, meteorological conditions are characterized by cloudy sky and high-surface winds in Shanghai, resulting in a higher nighttime planetary boundary layer (PBL) and faster transport of air pollutants. By contrast, during the second period, the meteorological conditions are characterized by clear sky and weak surface winds, resulting in a lower nighttime PBL and slower transport of air pollutants. The chemical mechanism model calculation shows that different VOC species has very different contributions to the high-ozone concentrations during the second period. Alkane (40 ppbv) and aromatic (30 ppbv) are among the highest VOC concentrations observed in Shanghai. The analysis suggests that the aromatic is a main contributor for the O₃ chemical production in Shanghai, with approximately 79% of the O₃ being produced by aromatic. This analysis implies that future increase in VOC (especially aromatic) emissions could lead to significant increase in O₃ concentrations in Shanghai.     

Current and future emission estimates of exhaust gases and particles from shipping at the largest port in Korea

The emissions of exhaust gases (NO _x , SO₂, VOCs, and CO₂) and particles (e.g., PM) from ships traversing Busan Port in Korea were estimated over three different years (the years 2006, 2008, and 2009). This analysis was performed according to the ship operational modes (“at sea,” “maneuvering,” and “in port”) and ship types based on an activity-based method. The ship emissions for current (base year 2009) and future scenarios (years 2020 and 2050) were also compared. The annual emissions of SO₂, VOCs, PM, and CO₂ were highest (9.6?×?10³, 374, 1.2?×?10³, and 5.6?×?10⁵ ton year^?1, respectively) in 2008. In contrast, the annual NO _x emissions were highest (11.7?×?10³ ton year^?1) in 2006 due mainly to the high NO _x emission factor. The emissions of air pollutants for each ship operational mode differed considerably, with the largest emission observed in “in port” mode. In addition, the largest fraction (approximately 45–67 %) of the emissions of all air pollutants during the study period was emitted from container ships. The future ship emissions of most pollutants (except for SO₂ and PM) in 2020 and 2050 are estimated to be 1.4–1.8 and 4.7–6.1 times higher than those in 2009 (base year), respectively.