Comparisons of Meso-Scale Air Pollution Dispersion Modelling of S02, N02 and 03 Using Regional-Scale Monitoring Results

Results of a regional-scale monitoring campaign were compared with two meso-scale to sub-continental modelling studies, for S02 and N02 and 03 respectively (Fourie, 2006, Zunckel et al., 2006, van Tienhoven et al., 2006, Van Tienhoven and Zunckel, 2004). However, a direct validation of the monitored results with modelled results could not be carried out, as available modelling studies dealt with different periods from the monitoring study. For this study, three monitoring sites were selected for comparison with modelling results. These sites were strategically selected to be representative of the entire region. Site Elandsfontein in the centre of the industrial Highveld, site Amersfoort, downwind from the central pollution source region and site Louis Trichardt, a remote site. Sulphur, nitrogen and ozone species comparisons were considered in turn. The comparisons were carried out for equivalent annual (and seasonal) cycles. The compa risons produced mixed results. For sulphur and nitrogen species in most cases, depending on site and season, modelling results ranged between significant underestimates to overestimates. Ozone modelling almost always overestimated the concentrations compared to the measured results. Despite several limiting factors, constraining the reliability of the comparisons between the modelled and measured results, they were important as the distribution of the gases showed patterns that imply understanding of the source and fate of these pollutants. The uncertainty in the magnitude of the model inaccuracies as well as margin of error of the measured data remained. Thus a modelling validation is recommended using the concurrent period with fewer uncertainties

Ambient aromatic hydrocarbon measurements at Welgegund, South Africa

Aromatic hydrocarbons are associated with direct adverse human health effects and can have negative impacts on ecosystems due to their toxicity, as well as indirect negative effects through the formation of tropospheric ozone and secondary organic aerosol, which affect human health, crop production and regional climate. Measurements of aromatic hydrocarbons were conducted at the Welgegund measurement station (South Africa), which is considered to be a regionally representative background site. However, the site is occasionally impacted by plumes from major anthropogenic source regions in the interior of South Africa, which include the western Bushveld Igneous Complex (e.g. platinum, base metal and ferrochrome smelters), the eastern Bushveld Igneous Complex (platinum and ferrochrome smelters), the Johannesburg–Pretoria metropolitan conurbation (> 10 million people), the Vaal Triangle (e.g. petrochemical and pyrometallurgical industries), the Mpumalanga Highveld (e.g. coal-fired power plants and petrochemical industry) and also a region of anticyclonic recirculation of air mass over the interior of South Africa. The aromatic hydrocarbon measurements were conducted with an automated sampler on Tenax-TA and Carbopack-B adsorbent tubes with heated inlet for 1 year. Samples were collected twice a week for 2 h during daytime and 2 h during night-time. A thermal desorption unit, connected to a gas chromatograph and a mass selective detector was used for sample preparation and analysis. Results indicated that the monthly median (mean) total aromatic hydrocarbon concentrations ranged between 0.01 (0.011) and 3.1 (3.2) ppb. Benzene levels did not exceed the local air quality standard limit, i.e. annual mean of 1.6 ppb. Toluene was the most abundant compound, with an annual median (mean) concentration of 0.63 (0.89) ppb. No statistically significant differences in the concentrations measured during daytime and night-time were found, and no distinct seasonal patterns were observed. Air mass back trajectory analysis indicated that the lack of seasonal cycles could be attributed to patterns determining the origin of the air masses sampled. Aromatic hydrocarbon concentrations were in general significantly higher in air masses that passed over anthropogenically impacted regions. Inter-compound correlations and ratios gave some indications of the possible sources of the different aromatic hydrocarbons in the source regions defined in the paper. The highest contribution of aromatic hydrocarbon concentrations to ozone formation potential was also observed in plumes passing over anthropogenically impacted regions

Evaluating the Performance of a Regional-Scale Photochemical Modelling System: Part I Ozone Predictions

We present a detailed evaluation of the seasonal performance of the Community Multiscale Air Quality (CMAQ) modelling system and the PSU/NCAR meteorological model coupled to a new Numerical Emission Model for Air Quality (MNEQA). The combined system simulates air quality at a fine resolution (3 km as horizontal resolution and 1 h as temporal resolution) in north-eastern Spain, where problems of ozone pollution are frequent. An extensive database compiled over two periods, from May to September 2009 and 2010, is used to evaluate meteorological simulations and chemical outputs. Our results indicate that the model accurately reproduces hourly and 1-h and 8-h maximum ozone surface concentrations measured at the air quality stations, as statistical values fall within the EPA and EU recommendations. However, to further improve forecast accuracy, three simple bias-adjustment techniques mean subtraction (MS), ratio adjustment (RA), and hybrid forecast (HF) based on 10 days of available comparisons are applied. The results show that the MS technique performed better than RA or HF, although all the bias-adjustment techniques significantly reduce the systematic errors in ozone forecasts

Development of a Fast and Detailed Model of Urban-Scale Chemical and Physical Processing

Abstract and PDF report are also available on the MIT Joint Program on the Science and Policy of Global Change website (http://globalchange.mit.edu/).A reduced form metamodel has been produced to simulate the effects of physical, chemical, and meteorological processing of highly reactive trace species in hypothetical urban areas, which is capable of efficiently simulating the urban concentration, surface deposition, and net mass flux of these species. A polynomial chaos expansion and the probabilistic collocation method have been used for the metamodel, and its coefficients were fit so as to be applicable under a broad range of present-day and future conditions. The inputs upon which this metamodel have been formed are based on a combination of physical properties (average temperature, diurnal temperature range, date, and latitude), anthropogenic properties (patterns and amounts of emissions), and the surrounding environment (background concentrations of certain species). Probability Distribution Functions (PDFs) of the inputs were used to run a detailed parent chemical and physical model, the Comprehensive Air Quality Model with Extensions (CAMx), thousands of times. Outputs from these runs were used in turn to both determine the coefficients of and test the precision of the metamodel, as compared with the detailed parent model. The deviations between the metamodel and the parent mode for many important species (O3, CO, NOx, and BC) were found to have a weighted RMS error less than 10% in all cases, with many of the specific cases having a weighted RMS error less than 1%. Some of the other important species (VOCs, PAN, OC, and sulfate aerosol) usually have their weighted RMS error less than 10% as well, except for a small number of cases. These cases, in which the highly non-linear nature of the processing is too large for the third order metamodel to give an accurate fit, are explained in terms of the complexity and non-linearity of the physical, chemical, and meteorological processing. In addition, for those species in which good fits have not been obtained, the program has been designed in such a way that values which are not physically realistic are flagged. Sensitivity tests have been performed, to observe the response of the 16 metamodels (4 different meteorologies and 4 different urban types) to a broad set of potential inputs. These results were compared with observations of ozone, CO, formaldehyde, BC, and PM10 from a few well observed urban areas, and in most of the cases, the output distributions were found to be within ranges of the observations. Overall, a set of efficient and robust metamodels have been generated which are capable of simulating the effects of various physical, chemical, and meteorological processing, and capable of determining the urban concentrations, mole fractions, and fluxes of species, important to human health and the climate.Federal Agencies and industries that sponsor the MIT Joint Program on the Science and Policy of Global Change

Abstract Modelled surface ozone over southern Africa during the Cross Border Air Pollution Impact Assessment Project

Monitoring of surface ozone over southern Africa has shown that ambient concentrations often exceed a threshold of 40 ppb at which damage to vegetation by ozone could be expected. The Cross Border Air Pollution Assessment Project (CAPIA) was therefore established to assess the potential impacts of ozone on maize, a staple food crop, in five southern African countries. Measured surface ozone data are scare in the region so it was necessary to complement the monitoring with regional-scale photochemical modelling to achieve the objective. The Pennsylvania State and NCAR Mesoscale Model (MM5) is used to produce gridded meteorological data for 5 days in each month of the maize growing season, October to April, as input to the photochemical model, CAMx. Gridded anthropogenic emissions from industry, transport and domestic burning and gridded biogenic emissions from soils and vegetation are input to CAMx. The model estimations indicate large areas on the sub-continent where surface ozone concentrations exceed 40 ppb for up to 10 h per day. Maximum concentrations may exceed 80 ppb, particularly in the winter when mean ozone concentrations are higher. The areas where the 40 ppb threshold is exceeded coincide with maize growing areas in South Africa and Zimbabwe. It appears that neither anthropogenic emissions nor biogenic emissions are dominant in the production of surface ozone over southern Africa. Rather the formation of surface ozone over the region is attributed to the combine

Modelling SO2 emissions from Anglogold Ashanti's East Acid Plant: detemining impacts on ambient air quality

Since the promulgation of the new air quality legislation in South Africa, sulphur dioxide (SO2) has been a pollutant of concern especially in the heavily industrial South African regions. AngloGold Ashanti’s sulphuric acid (H2SO4) plant located in Klerksdorp, North West province is an important local source of SO2. Other important sources in the North West province include the platinum mine smelters which are responsible for elevated SO2 concentrations in the Rustenburg area. The impacts of these emissions are exacerbated by the poor atmospheric dispersion potential for a substantial portion of the year. An air dispersion modelling study undertaken by Scorgie and Venter (2004a) indicated that the AngloGold Ashanti’s East Acid Plant was likely not to comply with its Air Pollution Prevention Act (APPA) registration certificate (RC) conditions and the proposed South African ambient air quality standards. AngloGold Ashanti subsequently implemented emission reduction measures to minimise elevated SO2 levels and for the first time initiated continuous emission monitoring in the stack and the nearby village. This study aimed at determining the impacts from implementing emission control measures in 2007 whilst establishing the relationship between quantified stack emissions, modelled and monitored ambient air quality data. Other AngloGold Ashanti SO2 sources i.e. South Uranium Plant and Great Noligwa No. 8 Gold Plant were included in the model runs to assess their contribution to the cumulative SO2 concentrations. AERMOD was applied to examine the dispersion potential of stack and fugitive emissions. Modelled SO2 stack concentrations were within the current South African ambient air quality standards for all averaging periods prior and post East Acid Plant shutdown1. However, exceedances were noted for 1-hour and 24-hour averaging periods for modelled stack and volume sources combined i.e. East Acid Plant, South Uranium Plant and Great Noligwa No. 8 Gold Plant. The stack emissions and ambient data compared well with an exception of the fugitive emissions. The model demonstrated a satisfactory performance to calculate stack emissions from the East Acid Plant. However, the model compared poorly with the monitored ambient air quality data partly due to the lack of comprehensive emission factors for fugitive sources. Based on these results it can be concluded that the Acid Plant stack concentrations solely, do not pose significant health risk to the nearby receptors and that the implemented air pollution abatement measures are mostly effective. However, it is important to note that the model may have underestimated fugitive emissions which contribute to low-lying emissions thus impacting on sensitive receptors

Modelling isoprene emissions over Southern Africa based on climate change scenarios

M.Sc., Faculty of Science, University of the Witwatersrand, 2011Biogenic volatile organic compounds (BVOCs), in the presence of nitrogen oxide gases (NOx), play a role in the production of tropospheric ozone (O3) which is an effective greenhouse gas and is hazardous to human health (Haagen-Smit, 1952, Chameides et al, 1988, Atkinson, 2000, Kanakidou et al, 2004). Isoprene is a single BVOC that accounts for over 50% of all emitted BVOCs. Isoprene emissions are species specific and vary according to temperature, light and leaf area index. Climate change studies predict that the geographic distribution of species, temperature ranges, light intensity and leaf area index will shift, thus altering future isoprene emissions. Several attempts to model BVOC emissions have been undertaken in an effort to quantify BVOC emission rates and the impact on ozone formation. The most widely used and empirically tested emission algorithms to date were developed by Guenther et al (1993) and are incorporated into the emission model Model of Emissions of Gases and Aerosols from Nature (MEGAN). MEGAN is used in this study to model isoprene emission rates over southern Africa under current and future climate conditions. Current and future climate conditions are taken from the regional climate model, Conformal-Cubic Atmospheric Model (C-CAM), which has been shown to simulate current climate well for the region. Emissions were modelled for January and July only, to represent summer and winter conditions. January isoprene emission rates for the current climate range from 0 to 1.41 gm-2month-1 and total 0.938 Tg of isoprene for the study domain. The highest emission rates are caused by combinations of driving variables which are: high temperature only; high temperature and high leaf area index; high emission factor and high leaf area index. Emission rates effectively shut down in July due to low temperatures and low leaf area index. July emission rates range from 0 to 0.61 gm-2month-1 and total 0.208 Tg of isoprene. Temperature is shown to cause the greatest variation in isoprene emission rates, and thus future scenarios represent an increase in temperature only. The spatial distribution of future emission rates does not shift when compared to current emission rates, but does show an increase in magnitude. Future emission totals for January increase iv by 34% to 1.259 Tg of isoprene and the July emission total increases by 38% to 0.289 Tg of isoprene. Future emission rates responded to temperature as expected, increasing in magnitude, rate of change and range of temperature over which the greatest rate of change occurs. Three areas demonstrating the highest increase in emission rates and highest future emission rates were identified. As temperature was the only variable altered in future scenarios, these areas can be deemed as areas most sensitive to changes in temperature. These areas are situated near the Angola-Namibia border, the Northern Interior of South Africa and the low-lying areas of Mozambique

An assessment of the NAME III model capability in reproducing seasonal variation of SO₂ and O₃ pollutant concentrations : a focus on the Mpumalanga Highveld area.

Master of Science in Environmental Science. University of KwaZulu-Natal, Durban 2015.The South African Weather Service Air Quality Modelling programme initiative has a long term goal to develop a system capable of generating atmospheric air quality forecasts for a range of primary and secondary pollutants in order to advise and warn the public on possible high levels pollutant concentration in the air and also provide support in relevant policy development. In this study a pilot NAME III air quality modelling system was developed and tested for its performance in simulation of sulphur dioxide (SO₂) and ozone (O₃) concentrations over the Mpumalanga Highveld. The agreement of model predictions generated in this study with observations was evaluated using the statistical analysis of the monthly averages of SO₂ and O₃ concentrations based on the Bias, NMB, RMSE, NRMSE statistical measures. In addition, the seasonal distribution and variation of the modelled SO₂ and O₃ concentrations over the South African domain were assessed. The results demonstrate that the modelling system under-predicts SO₂ and O₃ concentrations. However, in most cases the modelled concentrations are in the same order of magnitudes with the measured data except for two incidences of very low modelled SO₂ in Middelburg during April and May months, which may be attributed to the poor initialisation of the model. For each season, the model was initialised for the first five days to allow for the pre calculation of the initial pollutant concentrations. This was not possible for the autumn season as no Numerical Weather Prediction (NWP) data were available for initialisation during this period. In general the overall results indicate that the NAME III modelling system is a promising and cost-effective tool for providing real time air quality forecasts, in particular, the ground level O₃ concentration in South Africa. The NAME III modelling system therefore has the potential to be used operationally as a national air quality forecasting system and, as a tool to conduct air quality modelling studies. Specifically the modelling system could assist in the amendment and development of relevant air quality policies that have a direct impact on the environment, health and other related sectors. However, it is suggested that while more evaluation exercises must be undertaken, advancements in term of a comprehensive emissions inventory and improved representation of meteorological information are needed