The use of satellite images and dispersion models for mitigation of air pollution in Cairo city. ABSTRACT

Transcription

1 The use of satellite images and dispersion models for mitigation of air pollution in Cairo city. Mahmoud A.A Hussein and Usama A. Faramawi Egyptian Meteorological Authority ABSTRACT The severe air pollution episodes southern in Cairo and delta resulting from open burning of agriculture and domestic waste at a time when the surface atmospheric conditions is very stable. Severe air pollution episodes could therefore be avoided if industrial emissions were controlled. By using meteorological dispersion models of pollutants we can organize these operations. Verification of dispersion models is very useful tool for developing and refining the model results and for inter-comparisons among different models and to show the efficiencies of the system. Air pollution monitoring stations and Terra satellite images (Bands 1-4-3,i.e true color) are of great importance in verification of dispersion models for both shape and concentrations of the plume. In this research, CAMx and MM5 models have been used for the study of severe pollution episodes, which occurred in Cairo city. Cairo is affected by the unorganized burning of agricultural wastes in the North during the season of rice harvesting and also from industrial emission from steel and cement factories in the South. CAMx is used to forecast the potentiality of the atmosphere to carry and transport pollutants from different sources to certain area, consequently determine the suitable times and locations for open burning and control emissions from other sources. By determining the location, timing and quantity of emission, we can predict the concentration of the pollutants. This process will be difficult without accurate emission inventory. Another method is applied using the predicted hourly ventilation index, wind direction and backward trajectories reaching Cairo city, which is considered easier but relies on the experience of the forecaster. 1- Introduction The objective of this paper is to illustrate how satellite images could be used in the field of dispersion modeling. Both the shape of dispersed plume resulting from point or area sources and the accuracy of air trajectory could be verified subjectively then the meteorological and/or air quality dispersion model behavior would be tuned and refined accordingly. Due to the special topography of Cairo city, the meteorological conditions, high population density, industrial activity and agriculture waste burning inside and around the city, the frequency of occurrence of air pollution episodes especially during autumn, winter and spring increases.to avoid or mitigate man made pollution episodes a control technique for open burning and industrial emissions should be applied using meteorological models coupled with dispersion models. The accuracy of simulated episodes is strongly dependent on the availability of pollution sources (emission inventory). Detailed emission inventory for large city as Greater Cairo needs long time for preparation. Two methods for issuance of forecasts are used. The subjective method depends on the ventilation index Vi ( wind speed * mixing height V i = ), 10 backward trajectory and correct locations of important emission sources.the temporary sources locations such as open burning must be given in addition to the duration of burning before issuing the forecast. When issuing the forecast it must take into account the area between the forecasted trajectories and its neighborhood is a ban area for open burning.

2 PM10 µg/m^3 Pollutant status Normal Qulally Maadi <99 Clear Moderate Abbasya Giza a- The subjective method gives air quality rating as shown in table (1) >350 Warning El Sahel Table (1) Table (2) Table (3) For episodic day the Vi is less than 3 for duration greater than 8 hours. Also the subjective method depends on the experience gained by the forecaster and his interpretation to the meteorological output data and charts. Satellite images are very useful for this method. The accuracy of subjective method for forecasting episodes is about 70%, which is reasonable. b-the Objective method Air Quality Models are coupled with atmospheric models to simulate pollutant emission, transport, diffusion and deposition. It is useful tool for analyzing and understanding episodic case studies and air pollution forecasting to help decision makers in mitigation and avoiding severe episodes. Air pollution dispersion studies vary in complexity from emission from a single source to many complex sources over large areas. It is important to point out that Air Quality model needs good identification for particle size distribution, since smaller particles stay in the air longer and are carried farther from the emission source than larger particles. 2-Models description and numerical experiment design A dispersion model needs detailed meteorological data set to simulate pollutant cycle. Such data set can be provided by meteorological model, which has the ability to resolve the synoptic scale and mesoscale in addition to micro atmospheric physics. In this study Penn state NCAR Mesoscale Model version 3(MM5v3) is used. Details about MM5 model can be found in Grell, 1994 and which has proven to be powerful tool for the air quality modeling community due to its good accuracy and nesting capabilities. MM5 is coupled with Comprehensive Air quality dispersion Model with extension (CAMx) version 3. Details about CAMx model can be found in a- MM5 domain and resolution MM5 was run on 1-way nested meshes of horizontal resolutions, 30 km for regional area and 10km for local area. The regional area extends between longitudes and latitudes. The local area extends between longitudes and latitudes. The vertical resolution is 32 levels between ground surface and about 16km aloft. The 30km resolution used initial and boundary conditions derived from global National Center for Environmental Prediction NCEP data. The NCEP broadcasts global model outputs as girded data to be used for initial and boundary conditions by World Area Forecast centers WAFS. WAFS s horizontal resolution is 1.25 o in latitude and longitude on 12 standard vertical pressure levels. b- MM5 Physics - OSU/Eta Land-Surface Model, Chen and Dudhia (2001). - CCM2 radiation scheme, multiple spectral bands in short wave and long wave see Hack et al. (1993). - Dudhia Simple Ice microphysical scheme. - Cumulus parameterization, Grell et al. (1994). - Planetary boundary layer Mellor-Yamada scheme as used in the Eta model, Janjic (1994, MWR). c- CAMx design CAMx have vertical structure, 10 levels from ground level to about 700m and horizontal resolution 2km. The area extends between longitudes and latitudes. The initial and lateral boundary conditions are set to background concentration (70µg/m^3) for both PM10 and PM2.5. Plume in Grid (PiG) sub model that tracks individual puff segment is used during the early stages of emitted puffs. The calculation of the horizontal and vertical advection of the atmospheric constituents is performed using Bott, A (1989) algorithm. For the treatment of gas dry deposition, Wesely (1989) approach was used and Kumar (1996) for aerosol. Wet deposition is treated using simple scavenging coefficient based on Maul (1980).

3 3- Case studies 3-1 Northern episode A cloudless period 23 to 27 October 2002 has been chosen where satellite images illustrate the smoke plumes clearly. During this period intensive open burning of rice straw took place. Emission input The daily rice acreage burned is obtained from different Egyptian municipal and the locations of open burning area are obtained from consecutive satellite images from 23Oct-27Oct2002. The emission factor from open burning of rice straw is estimated using EPA-1995a, EPA-1996b (Environmental Protection Agency. In this study emission factor for PM10 is 38 pound/ton and 34.8 for PM2.5. Actually the emission factors are affected by combustion efficiency; consequently the emission factor could be changed slightly according to combustion processes. About acres are burned daily distributed over East Nile delta and represented by 20-point sources. Most of open burning locations marked as red rectangles on satellite images. When red marks appear without smoke plume it indicates dry and complete combustion. While wet or incomplete combustion due to less oxygen creates smoke plumes around the red rectangle in satellite image. Rice is the most widely planted crop in the Northeast of Nile delta with approximately 1.5 million acres is growing annually. Open field burning has been the traditional and most efficient method for disposing of rice straw for land clearing and controlling rice disease. This burning should occur right after harvest in the fall. Unfortunately, the fall is favorable season for stable meteorological conditions because of the length of night time and calm wind accompanies zonal high pressure area dominant over North west Egypt with weak pressure gradients. To improve air quality and smoke impacts, Air quality forecasting model is used to regulate agricultural burning. The results: a-subjective method Fig (1a,b, c, d) show ventilation index less than 4 for 9 hours starts at 23 Oct. 21Z, wind speed less than 3.5 m/s, wind direction is Northern for the same period and Northeast 12 hours before that period and wind trajectories, which is in agreement with the other figures. According to the experience gained during three years of forecasting smoke episodes the pollutant status warning could be expected from such case Discussion: Comparing the forecasted pollutant status and expected high concentration period with the available observed ambient PM10 from the regional network stations of the Egyptian Environmental Affairs Agency, EEAA, namely Abbasya, Fum-elkhlig and Qulally, we see that the forecast is in good agreement with the observations. b- Objective method (CAMx model): PM2.5 is simulated; because burning rice straw emits about 95% extremely fine PM2.5.Taking into account the acres are burned daily distributed over East Nile delta and represented by 20-point sources as shown in fig (2) and fig (4a,b), the hourly emission rate for PM2.5 point source is estimated as 900 kg. Model output showed by Fig (2a) represents PM2.5 night pattern where the smoke cloud stands near to its sources. While the early morning regime showed by Fig (2b) represents plumes move out of the emission areas and mixed within the planetary boundary layer downwind. Fig (2c) represents PM2.5 at noon (satellite time). It demonstrates that the plumes exhibit a more detail structure, where the area of NE Cairo is most affected by smoke. a) b)

4 c) d) Fig (1) Forecasted meteorological variables for the period 23-26Oct2002 at Cairo city (a) Ventilation index, (b) wind speed (m/sec), (c) wind direction ( o ), and back trajectory reached Cairo at 06:00Z Verification using monitoring station data As we know that the simulated sources are ranging from 50Km to 120Km far from Cairo, and, only PM2.5 reaches the observation stations, then, about 70 percent of observed average PM10 in this case is assumed PM2.5 as shown in table (2) taken from Cairo Air Improvement Project funded by USAID. Fig (3) shows a comparison between the results of the CAMx simulation model for PM2.5 and the observed data at three stations for PM10 from 23 to 25 October The figures indicate that the two major periods on NE flow from the high emission region near Cairo that coincides with the periods of high pollution: during this period very high concentrations of PM10 are observed. Between these events the concentrations are reduced to the local background. The predicted concentrations of PM2.5 show nearly the same pattern of maximum observed concentrations, but they show differences in values and timing. In general the simulated concentration of PM2.5 exhibit lower values and about 3-6 hours time lag between the maximum beaks of observed and forecasted concentrations The reason for that shift may be due to the incorrect locations of the emission point sources and missing source. a) b) c) d) Fig (2) shows open burning locations over Nile delta denoted by * and near surface PM2.5 concentrations (µg/m^3) (approximately 18 meter above the ground) during 24-25Oct2002:(a) show accumulations of pollutants around emission sources during nighttime stable condition, (b, d) show moving of the plume out of emission sources and mixed within the boundary layer in the early morning and (c) shows diffusion of the plume due to increasing mixing at noontime.

5 Ab Qa Fu OAb OQa OFu /10/02 23/10/02 23/10/02 18:00 23/10/02 21:00 03:00 06:00 09:00 18:00 21:00 03:00 06:00 09:00 Fig (3) Observed PM10 concentrations at stations Abbasya (Oab), Fum-elkhlig (Ofu) and Qulally (Oqa) and forecasted PM2.5 (Ab, Fu, Qa). The concentrations are in µg/m^3. Verification using Satellite images Comparing the forecasted trajectory with the dispersed plume tracks as shown in satellite image fig (4a), one-notice differences between the two tracks. This discrepancy results from the differences between the forecasted and actual winds during stable condition at night (Grell, G. A., Dudhai 1994). Fig (4a) shows two main plumes, the first one path through the central delta, while the second paths over the northern part of Cairo. Comparing the forecasted plume shape fig (2c) with the satellite images fig (4a), one note that the second plume has a slight difference in orientation, while the first plume has a remarkable difference in the orientation and the width due to wind speed and excessive numerical diffusion (Bott.,1989).Fig(2d)and fig(4b) shows the forecasted and observed plumes, a slight difference appear due to changes of burning locations and efficiency of burning process,also the figures shows a patch of smoke cloud cover El-Fayum Oasis. (a) Satellite image at 24Oct UTC (b) Satellite image at 25Oct UTC Fig (4a,b) show burning locations at delta (red rectangle). Two plumes appear over northeast delta in fig (5a) and scattered smoke clouds is represented by fig (5b)

6 3-2 Southern episode This southern episode resulting from blowing southwest low wind speed due to passage of traveling depression over central Mediterranean sea. This southern wind bringing most of emitted pollutants from south Cairo to populated area. Emission input The input emission database for southern case is provided by the Egyptian Pollution Abatement Project, EPAP, for PM10 and PM2.5.The annual emission rates for point source available only for about 60% highlevel sources; Most of them are located south of Cairo. Results: Fig (5a,b) shows transport of pollutants from area of greatest emission located south of Cairo to El-Fayum Oases. During this time the wind blowing from northeast. At later times about 6-8 hour the depression moved slowly eastward, due to this shift the wind direction changes to a southwestward as shown in fig (5c). Fig (5b) shows a plume of smoke covers the central part of Cairo; the plume is thin inside Cairo and more wide faraway. This change in the plume width is due to the surrounding hills. Again the figure shows a light smoke cloud covers El-Fayum resulting from cutoffs the old plume. Verification using monitoring station data Fig (5d) shows the observed PM10 and forecasted PM2.5.PM2.5 contribution to the measurements is expected to be about 50 percent of the average PM10 according to CAIP measurements shown in table (3) During the integration period, greater Cairo is affected by northern source of pollution except for 6 hours between 03 :00 and 09:00 Z 22 nd morning where southern winds carried pollution from south Cairo. This event is clearly simulated by model and showed low concentrations along the period except for the 6 hours mentioned above. The figure again showed that Abbasya is greatly affected by rice smoke. a) b) Ab Fu Qa Oba Ofu Oqa c) d) /11/02 21/11/02 21/11/02 18:00 21/11/02 21:00 03:00 06:00 09:00 Fig (5) as in fig (2) but shows :(a) transport of smoke plume by northeast wind from emission sources located south of Cairo towards El- Fayum Oases at 00Z22Nov2002, (b) splitting the plume due to south wind into two parts, the main plume cover the central and northeast area, the other plume appear as patched smoke cloud,( c) wind direction and (d) observed PM10 and forecasted PM2.5 as in fig 3

7 Verification using Satellite images The satellite image fig (6) shows two sources of pollution, the first located north of Cairo on the central of delta due to open burning rice straw and the second is located to the south of Cairo. Again the satellite image shows a patched cloud cover El-Fayum. Comparing the forecasted plume fig (5b) with the observed southern plume, one-notice slight differences in the orientations and width where the observed plume is narrow. Also the location of the forecasted patched smoke has slight deviation from the observed in the satellite picture and more diluted. Satellite image at 22Nov UTC Fig (6) show plume of smoke cover the central part of Cairo and patched cloud over El-Fayum Oasis. 3-3 Point source case This case provides an opportunity to study transport of pollutants emitted from point source (burning from open pit) with huge amount of pollutant for 6-8 hours duration. The input emission for the point source is estimated by equating it with similar point source (100kg/hour). Fum-elkhlig monitoring station was chosen to compare the forecasted PM2.5 and observed PM10 because it is closest to source (located to the south edge of Cairo) and significantly affected by southern sources, also it is not affected by local activates during southern wind times. Fig (7a,b) shows the forecasted PM2.5 and observed PM10 for Fum-elkhlig are increasing during the period of southern wind. Fig (8) show a plume emitted from open pit and elongated to the south west of Cairo and that has limited impact on the Fum-elkhlig area. Comparing the forecasted plume fig (6a) with the satellite image, we notice slight differences in the orientation and 2-hour lag. Fu Ofu a) b) 0 03:00 06:00 09:00 18:00 21:00 23/01/03 Fig (7) as in fig (2) but shows :(a) a plume of smoke emitted from burning in open pit at 07Z22Jan2003, (b) observed PM10 and forecasted PM2.5 as in fig 3

8 Satellite image at 22Jan UTC Fig (7) show smoke plume emitted from open pit 4-Conclusions: In this study satellite images are used to determine the locations of unknown pollutant sources such as open burning of agricultural waste. It is successfully used to estimate the emitted amount of pollutions and following up its transport and dispersion. Satellite images have proven to a powerful tool for model output verification and interpretation. Satellite images are now considered on of the most important wide world monitoring observation system for meteorology and environment specially where it is difficult to establish and maintain monitoring stations Acknowledgments. We gratefully acknowledge the Egyptian Meteorological Authority, Ministry of Environment for providing observed data, the National Center of Environmental Prediction (NCEP) for supporting WAFS data, NASA satellite, and University of Maryland and U.S Forest service for providing satellite images References Bott, A A Positive Definite Advection Scheme Obtained by Nonlinear Renormalization of the Advective Fluxes. Mon. Wea. Rev., 117, Chen, F., and J. Dudhia, 2001: Coupling an advanced land-surface/hydrology model with the Penn State/NCAR MM5 modeling system. Part I: Model implementation and sensitivity. Mon. Wea. Rev., 129, Dudhia, J., 1989: Numerical study of convection observed during winter monsoon experiment using a mesoscale two-dimensional model. J. Atmos. Sci., 46, Dudhia, J., 1996: A multi-layer soil temperature model for MM5. Preprints, The Sixth PSU/NCAR Mesoscale Model Users' Workshop, July 1996, Boulder, Colorado, Available from EPA. 1996b Evaluation of Emissions from the Open Burning of Land-Clearing Debris. EPA-600/R U.S Environmental Protection Agency, Control Technology Center. Research Triangle Park, North Carolina. EPA. 1995a Compilation of Air Pollution Emission Factors, Volume I: Stationary Point and Area Sources, Fifth Edition, AP-42(GPO ). U.S Environmental Protection Agency, Research Triangle Park, North Carolina. Grell, G. A., J. Dudhia and D. R. Stauffer, 1994: A description of the fifth-generation Penn State/NCAR mesoscale model (MM5). NCAR Technical Note, NCAR/TN-398+STR, 117 pp. Hack, J. J., B. A. Boville, B. P. Briegleb, J. T. Kiehl, P. J. Rasch, and D. L. Williamson, 1993: Description of the NCAR Community Climate Model (CCM2). NCAR Technical Note, NCAR/TN-382+STR, 120 pp. Janjic, Zavisa I., 1994: The step-mountain eta coordinate model: Further development of the convection, viscous sublayer, and turbulent closure schemes. Mon. Wea. Rev., 122, Kumar, N., F.W. Lurmann, A.S. Wexler, S. Pands, and J.H. Seinfeld Development and Applications of Three dimensional Aerosol Model. Presented at the A&WMA Specially Conference on Computing in Environmental Resources Management, Research Triangle Park, NC, December 2-4,1996. Wesely, M.L Parameterization of Surface Resistance to Gaseous Dry Deposition in Regional-Scale Numerical Models. Atmos. Environ., 23,