How safe is Beijing s Air Quality for Human Health? Naresh Kumar Θ

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1 How safe is Beijing s Air Quality for Human Health? Naresh Kumar Θ Abstract: The success of the 2008 Olympics will be largely impacted by the level of air pollution in Beijing. The World Health Organization (WHO) has established air quality standards to protect human health. Using satellite remote sensing, we evaluated spatialtemporal distributions of air quality, measured by airborne particles 2.5μm and 10μm in aerodynamic diameter (PM 2.5 and PM 10, respectively) in Beijing with reference to air quality standards established by WHO. The long-term averages of PM 10 and PM 2.5 were significantly higher than the standards recommended by WHO. In the first half of July 2008, however, the levels of PM 2.5 and PM 10 were within the WHO recommended limits in the City. This improvement in air quality can be attributed to air quality controls adopted in the first week of July 2008, which included bans on the entry of nearly 300,000 vehicles and reduced number of cars entering the city. Despite these measures, the concentrations of PM 2.5 and PM 10 increased significantly during July 16-24, Since meteorological conditions, particularly wind direction and wind velocity, can transport air pollutants greater distances, it will be necessary to extend air quality control measures to the areas surrounding the city. Beijing must continue to enforce air quality control measures in the weeks leading up to and during the games if the city aims to achieve the acceptable standards of air quality. Otherwise, the current air pollution levels in the city could have catastrophic health consequences on visitors and athletes who are not used to elevated concentrations of fine and coarse particulates or who suffer from respiratory and cardiovascular problems. A map presented in this report could serve as a guide for visitors to avoid areas with elevated concentration of air pollution. Introduction - The 2008 Beijing Olympics begin in week s time, but the air quality in the city continues to be a major health concern despite several measures that have been put in place. These include bans on 300,000 pollution causing vehicles and a reduction in the number of cars entering the city since July 1, In this report, we evaluate shortand long-term spatial-temporal trends of PM 2.5 and PM 10, and examine whether the measures adopted to improve the Beijing s air quality have begun to work. While there is an increasing interest in measurement and monitoring of air quality of Beijing, we lack access to air pollution data monitored in and around the City. Nonetheless, satellite remote sensing provides a unique opportunity to estimate air quality at unprecedented spatial-temporal resolutions. Using the empirical association between aerosol optical depth (AOD) from satellite data and ground measurements of PM 2.5 and PM 10 observed in Delhi Metropolitan, daily, weekly, monthly and yearly concentrations of PM 2.5 and PM 10 at different distance intervals from the city center were computed. A brief description of data, methods, and results are presented in the remainder of this report, and methodological details are available in the online supporting material. Θ Assistant Professor, Dept of Geography, University of Iowa, Iowa City, IA nareshkumar@uiowa.edu

2 Data and Methods Air quality of a given place can be measured by the concentration of gaseous and particulate pollutants. In this report, however, we largely rely on PM 2.5 and PM 10, widely accepted measures of air quality worldwide. 1 Since data on ground measurement were not available, satellite data were used to convert aerosol loading into indirect estimates of PM 2.5 and PM 10 using the methodology presented in Kumar et al. 2 Aerosols are airborne suspended solid and liquid particles. By using the radiative transfer model, aerosol optical depth (AOD) can be extracted from satellite data. 3 Terra and Aqua Satellites have daily repetitive global coverage, and Moderate Resolution Imaging Spectroradiometer (MODIS) onboard these satellites record data every day for almost every part of the world. A number of studies suggest that AOD is a good predictor of 2, 4, 5 PM 2.5 and PM 10 after controlling for meteorological conditions. Using the empirical relationship between MODIS AOD and airborne particulates (observed in Delhi, a city with almost similar air pollution situation prior to air quality interventions in 2002) reported in Kumar et al. 2, PM 2.5 and PM 10 estimates were derived for Beijing from Feb 2000 until the third week of July These estimates were aggregated at different spatial-temporal scales. The analysis included yearly, monthly, weekly and daily estimates at different distance intervals from the city center. These estimates were mapped (Figure 1a & 1b) and aggregated statistics were produced for different distance intervals from the city center (Table 1a & 1b). Results According to the WHO guidelines, the yearly average of PM 10 should not exceed 50µg/m 3 (and 150µg/m 3 for more polluted cities). In the city of Beijing, however, the average concentration of PM 10 during January 2000 to June 2008 within 24km radius of the city center was as high as 268.6±1.9µg/m 3, five times greater than the recommended levels. The concentration of fine particulates for the same duration within the city (<24km radius) was estimated as high as 96.2µg/m 3, which was roughly six times higher than the annual average recommended by the United States Environmental Protection Agency (USEPA). Although elevated concentration of PM 10 and PM 2.5 were observed during Feb 2000 to July 2008, striking changes were observed during the month of July 2008 alone. For example, the weekly average of PM 2.5 during Jul 1-23, 2008 was recorded as 42.1±3.3µg/m 3 as against 87.2±3.3µg/m 3 from Dec 28, 2007 to July 24, Likewise, the weekly average of PM 10 for the same duration was 132.6±18.0µg/m 3 versus 269.5±33.6µg/m 3 from Dec 28, 2007 to July 24, From July 1 to July 21 the PM 10 concentrations ranged from 50 to 150µg/m 3 within 24km radius from the city center. The concentration of PM 2.5 was within 50µg/m 3 until July 17. The improvement in air quality during the first half of July 2008 can be attributed to the pollution reduction measures implemented in the city, including the ban on polluting vehicles and the reduction in the number of cars entering the city. A sharp contrast is visible in the concentration of PM 10 with reference to distance from the city center. But such contrast is not very prominent for fine particulates (PM 2.5 ). Coarse particles (such as PM 10 ) settle quicker with gravity as distance from their sources increases. Fine particulates (PM 2.5 ), however, stay aloft and can travel greater distances.

3 As evident from figure 2a and 2b and table 1a and 1b, the concentrations of PM 10 are relatively high within a 24km radius from the city center, and they gradually decline with the increase in distance, which means traffic and other activities are the main sources of coarse particulates and that these activities gradually decline with the increasing distance from the city. The concentration of fine particulates was highest within 48km distance from the city center, which means particulates generated in the city are transported to the neighboring areas through wind. Conclusion The overall air pollution situation in Beijing has been grim as the longterm averages of PM 2.5 and PM 10 were five-six times higher than that recommended by WHO and USEPA. However, a significant improvement in air quality was observed during the first half of July But the levels of PM 2.5 and PM 10 began to rise beyond the recommended standards in the third week of July, If Beijing intends to achieve acceptable air quality standards, the city will need to enforce air quality control measures vigorously not only in the city, but in the areas surrounding the city. These areas must be enforced in the weeks leading up to and during the games. If these improvements are not made, short-term exposure to the current levels of PM 2.5 and PM 10 could have catastrophic health consequences for sensitive populations, such as visitors and athletes who suffer from respiratory and cardiovascular diseases or who are not normally exposed to the high levels of air pollution as observed in Beijing. The air quality situation in the city varies by geographic space. The maps presented in the report could help visitors avoid the most hazardous areas. For example, areas around Beijing International Security Circuit, Peking University and Beijing Corp Flower Tea showed elevated concentration of PM 2.5 and PM 10. The spatial distribution of air quality during the games (and most recent one) will be made available at the url link

4 Reference 1. WHO, WHO Air quality guidelines for particulate matter, ozone, nitrogen dioxide and sulfur dioxide - Global update Summary of risk assessment 2006, Geneva: World Health Organization. 2. Kumar, N., A. Chu, and A. Foster, Remote sensing of ambient particles in Delhi and its environs: estimation and validation. International Journal of Remote Sensing, (12): p Chinnam, N., et al., Dust events in Kanpur, northern India: Chemical evidence for source and implications to radiative forcing. Geophysical Research Letters, (8): p Kumar, N., A. Chu, and A. Foster, An Empirical Relationship between PM 2.5 and Aerosol Optical Depth in Delhi Metropolitan. Atmospheric Environment, (21): p Chu, D.A., et al., Global Monitoring of Air Pollution over Land from EOS-Terra MODIS. J. Geophys. Res., (D21): p

5 Table 1a: Weekly estimates of PM 2.5 at different distance intervals from the City Center, From To Date <24km <48km 48-72km 72-96km 48-96km 96+km 28-Dec-07 3-Jan ± ± ± ± ± ± ±4.1 4-Jan Jan-08 NA 101.1± ± ± ± ± ± Jan Jan ± ± ± ± ± ± ± Jan Jan-08 NA 203.9± ± ± ± ± ± Jan Jan ± ± ± ± ± ± ±7.8 1-Feb-08 7-Feb ± ± ± ± ± ± ±3.8 8-Feb Feb ± ± ± ± ± ± ± Feb Feb ± ± ± ± ± ± ± Feb Feb ± ± ± ± ± ± ± Feb-08 6-Mar ± ± ± ± ± ± ±2.6 7-Mar Mar ± ± ± ± ± ± ± Mar Mar ± ± ± ± ± ± ± Mar Mar ± ± ± ± ± ± ± Mar-08 3-Apr ± ± ± ± ± ± ±5.9 4-Apr Apr ± ± ± ± ± ± ± Apr Apr ± ± ± ± ± ± ± Apr Apr ± ± ± ± ± ± ± Apr-08 1-May ± ± ± ± ± ± ±1.3 2-May-08 8-May ± ± ± ± ± ± ±1.3 9-May May ± ± ± ± ± ± ± May May ± ± ± ± ± ± ± May May ± ± ± ± ± ± ± May-08 5-Jun ± ± ± ± ± ± ±2.7 6-Jun Jun ± ± ± ± ± ± ± Jun Jun-08 NA 158.0± ± ± ± ± ± Jun Jun ± ± ± ± ± ± ± Jun-08 3-Jul ± ± ± ± ± ± ±3.0 July 2008 Analysis 1-Jul-08 5-Jul ± ± ± ± ± ± ±1.2 6-Jul Jul ± ± ± ± ± ± ± Jul Jul ± ± ± ± ± ± ± Jul Jul ± ± ± ± ± ± ±0.7 1-Jul Jul ± ± ± ± ± ± ± Dec Jul ± ± ± ± ± ± ±0.9

6 Table 1b: Weekly estimates of PM 10 at different distance intervals from the City Center, From To Date <24km <48km 48-72km 72-96km 48-96km 96+km 28-Dec-07 3-Jan ± ± ± ± ± ± ± Jan Jan-08 NA 237.5± ± ± ± ± ± Jan Jan ± ± ± ± ± ± ± Jan Jan-08 NA 282.0± ± ± ± ± ± Jan Jan ± ± ± ± ± ± ± Feb-08 7-Feb ± ± ± ± ± ± ± Feb Feb ± ± ± ± ± ± ± Feb Feb ± ± ± ± ± ± ± Feb Feb ± ± ± ± ± ± ± Feb-08 6-Mar ± ± ± ± ± ± ±8.0 7-Mar Mar ± ± ± ± ± ± ± Mar Mar ± ± ± ± ± ± ± Mar Mar ± ± ± ± ± ± ± Mar-08 3-Apr ± ± ± ± ± ± ± Apr Apr ± ± ± ± ± ± ± Apr Apr ± ± ± ± ± ± ± Apr Apr ± ± ± ± ± ± ± Apr-08 1-May ± ± ± ± ± ± ±6.2 2-May-08 8-May ± ± ± ± ± ± ±9.4 9-May May ± ± ± ± ± ± ± May May ± ± ± ± ± ± ± May May ± ± ± ± ± ± ± May-08 5-Jun ± ± ± ± ± ± ± Jun Jun ± ± ± ± ± ± ± Jun Jun-08 NA 385.4± ± ± ± ± ± Jun Jun ± ± ± ± ± ± ± Jun-08 3-Jul ± ± ± ± ± ± ±11.0 July 2008 Analysis 1-Jul-08 5-Jul ± ± ± ± ± ± ± Jul Jul ± ± ± ± ± ± ± Jul Jul ± ± ± ± ± ± ± Jul Jul ± ± ± ± ± ± ±5.4 1-Jul Jul ± ± ± ± ± ± ±3.6 Total 28-Dec Jul ± ± ± ± ± ± ±

7 day since July 2008 < 24km 48-72km >72km Fig 1b: PM 2.5 during the month of July, day since July 2008 < 24km 48-72km >72km Fig 1a: PM 10 during the month of July, 2008

8 Distance to City Center 24km microgram/cubic m 89 Distance to City Center 24km microgram/cubic m Forbidden City Shejangsang Stadium Peking University Olyumpic National Statidium Forbidden City Shejangsang Stadium Peking University Olyumpic National Statidium Beijing Crop Flower Tea Beijing International Security Circuit Beijing Crop Flower Tea Beijing International Security Circuit Kilometers Fig 2a: PM 2.5 distribution, July 1-8, 2008 Fig 2b: PM 2.5 distribution, June, 2008 Kilometers Distance to City Center 24km microgram/cubic m 376 Distance to City Center 24km microgram/cubic m Peking University Olyumpic National Statidium Peking University Olyumpic National Statidium Forbidden City Shejangsang Stadium Forbidden City Shejangsang Stadium Beijing Crop Flower Tea Beijing International Security Circuit Beijing Crop Flower Tea Beijing International Security Circuit Kilometers Fig 2c: PM 10 distribution, July 1-8, 2008 Fig 2d: PM 10 distribution, June, 2008 Kilometers

9 Short- and long-term trends of PM 2.5 and PM 10 in Beijing, China Year <24km 48-72km >72km Year <24km 48-72km >72km Fig 3a: Yearly estimates of PM 2.5 in Beijing, China Fig 3b: Yearly estimates of PM 2.5 in Beijing, China month since Jan, month since Jan, 2007 <24km 48-72km >72km <24km 48-72km >72km Fig 4a: Monthly estimates of PM 2.5 in Beijing, China since January 2007 Fig 4b: Monthly estimates of PM 2.5 in Beijing, China since January 2007

10 Table 2: Yearly trends of Aerosol optical depth, PM 2.5 and PM 10 in Beijing, China Year < 24km 48-72km 72+km Average±95% confidence Interval (# of observations) Aerosol Optical Depth ±0.03 (161) 0.46±0.01 (621) 0.38±0.01 (1062) 0.34±0.00 (2667) ±0.03 (164) 0.50±0.01 (644) 0.43±0.01 (1079) 0.38±0.01 (2770) ±0.03 (166) 0.53±0.01 (686) 0.43±0.01 (1136) 0.39±0.01 (2938) ±0.04 (148) 0.57±0.02 (666) 0.52±0.01 (1099) 0.49±0.01 (2743) ±0.02 (174) 0.41±0.01 (689) 0.36±0.01 (1155) 0.32±0.00 (3019) ±0.03 (166) 0.47±0.01 (678) 0.41±0.01 (1110) 0.38±0.01 (2883) ±0.03 (169) 0.55±0.01 (673) 0.46±0.01 (1154) 0.41±0.01 (2979) ±0.03 (163) 0.54±0.01 (693) 0.45±0.01 (1164) 0.40±0.01 (3066) ±0.04 (91) 0.65±0.02 (395) 0.57±0.02 (680) 0.49±0.01 (1751) PM 2.5 (µg/m 3 ) ±4.92 (55) 60.11±2.73 (215) 55.93±1.98 (374) 48.42±1.03 (1078) ±2.88 (65) 66.65±3.00 (246) 63.38±2.22 (419) 55.90±1.15 (1178) ±3.35 (91) 71.41±1.93 (398) 67.38±1.52 (651) 57.72±0.77 (1695) ±1.73 (137) 70.78±1.24 (607) 70.27±1.15 (1034) 63.54±0.65 (2535) ±3.52 (106) 70.26±1.58 (502) 66.53±1.24 (813) 59.45±0.70 (2130) ±1.99 (154) 68.28±1.22 (652) 62.97±0.97 (1081) 58.23±0.60 (2755) ±2.84 (117) 73.20±1.50 (495) 68.87±1.24 (871) 62.77±0.77 (2171) ±3.00 (104) 65.83±1.34 (508) 63.23±1.07 (880) 59.48±0.69 (2224) ±4.60 (85) ±2.39 (371) 98.26±1.76 (656) 88.03±1.08 (1737) PM 10 (µg/m 3 ) ±10.81 (54) ±5.60 (209) ±5.28 (332) ±3.25 (868) ±8.70 (65) ±5.35 (238) ±4.58 (366) ±3.03 (1006) ±6.53 (91) ±4.10 (393) ±3.76 (595) ±2.49 (1400) ±6.32 (137) ±3.97 (586) ±3.24 (930) ±2.16 (2113) ±9.44 (105) ±4.36 (465) ±3.72 (717) ±2.48 (1729) ±5.59 (154) ±3.37 (626) ±3.25 (947) ±2.12 (2246) ±6.79 (117) ±4.12 (488) ±3.75 (791) ±2.53 (1831) ±7.11 (104) ±3.85 (501) ±3.42 (815) ±2.35 (1969) ±10.08 (80) ±4.37 (346) ±4.13 (596) ±2.67 (1496)

11 Table 3: Monthly estimates of AOD, January 2007 to June 2008 Year Month <24km 48-72km > 72 Average±95% confidence Interval (# of observations) Aerosol Optical Depth (AOD) Jan 0.28±0.01 (3) 0.21±0.01 (52) 0.20±0.01 (93) 0.17±0.01 (227) Feb 0.42±0.09 (5) 0.32±0.01 (50) 0.30±0.01 (97) 0.25±0.01 (249) March 0.47±0.03 (6) 0.49±0.02 (60) 0.43±0.02 (101) 0.38±0.01 (252) April 0.89±0.02 (17) 0.76±0.03 (61) 0.57±0.03 (100) 0.47±0.02 (256) May 0.86±0.05 (18) 0.63±0.03 (59) 0.52±0.02 (98) 0.45±0.01 (264) 2007 June 1.44±0.03 (18) 1.17±0.02 (60) 1.05±0.03 (94) 0.94±0.02 (267) July 1.06±0.06 (17) 0.76±0.05 (63) 0.64±0.03 (100) 0.58±0.02 (258) Aug 1.05±0.06 (19) 0.71±0.03 (59) 0.55±0.02 (97) 0.54±0.02 (264) Sept 0.81±0.02 (17) 0.54±0.02 (63) 0.43±0.01 (94) 0.38±0.01 (266) Oct 0.47±0.02 (20) 0.38±0.02 (58) 0.30±0.01 (99) 0.26±0.01 (261) Nov 0.28±0.01 (17) 0.22±0.01 (58) 0.20±0.01 (99) 0.19±0.01 (259) Dec 0.20±0.02 (6) 0.19±0.01 (50) 0.17±0.01 (92) 0.14±0.00 (243) Jan 0.24±0.01 (3) 0.20±0.01 (51) 0.19±0.01 (86) 0.16±0.00 (217) Feb 0.37±0.03 (4) 0.27±0.01 (53) 0.22±0.01 (100) 0.21±0.01 (241) 2008 March 0.50±0.04 (9) 0.36±0.02 (60) 0.31±0.01 (103) 0.25±0.01 (254) April 1.12±0.03 (18) 0.96±0.03 (60) 0.82±0.04 (100) 0.65±0.02 (257) May 1.06±0.03 (20) 0.94±0.04 (58) 0.80±0.04 (97) 0.66±0.02 (262) June 1.47±0.04 (20) 1.30±0.04 (59) 1.14±0.04 (97) 0.92±0.03 (260)

12 PM 2.5 (µg/m 3 ) Jan 128.5±35.1 (2) 102.2±4.3 (41) 96.2±3.7 (76) 92.1±2.9 (172) Feb 67.0±. (1) 61.1±2.1 (44) 65.8±2.2 (88) 65.8±1.6 (212) March 36.0±2.9 (2) 34.6±1.1 (19) 45.7±4.6 (52) 46.2±4.2 (141) April 87.1±13.7 (10) 78.0±6.4 (41) 64.2±4.5 (71) 56.6±2.5 (156) May 36.8±1.7 (15) 30.2±1.1 (52) 28.3±0.8 (83) 25.9±0.5 (217) 2007 June 66.0±2.5 (15) 54.4±1.3 (49) 49.3±1.3 (76) 46.5±0.8 (212) July 42.0±2.7 (7) 34.3±1.4 (38) 34.5±1.5 (43) 33.7±1.2 (131) Aug 58.9±5.0 (14) 51.6±1.9 (49) 48.5±1.4 (83) 49.6±1.1 (212) Sept 86.2±4.8 (10) 70.4±2.5 (41) 57.0±1.6 (64) 54.8±1.0 (176) Oct 87.8±5.9 (15) 83.3±4.1 (44) 75.3±2.9 (75) 71.9±1.8 (198) Nov 102.7±4.8 (12) 91.0±2.6 (58) 88.2±2.9 (97) 86.8±1.9 (237) Dec 110.8±. (1) 87.7±3.1 (32) 85.4±3.7 (72) 76.8±2.4 (160) Jan 172.4±20.9 (3) 153.6±5.4 (51) 153.0±3.6 (86) 142.4±3.0 (217) Feb 168.2±33.7 (4) 162.6±4.7 (53) 139.9±4.0 (99) 136.4±2.6 (240) March 108.6±13.6 (7) 98.8±3.7 (59) 88.2±2.8 (103) 80.8±1.4 (254) 2008 April 131.0±5.3 (18) 117.1±2.9 (60) 105.7±2.7 (100) 93.4±1.6 (257) May 76.8±1.7 (20) 71.6±2.6 (58) 64.7±2.2 (97) 55.8±1.2 (262) June 97.9±2.9 (20) 95.9±2.3 (59) 88.3±2.0 (97) 75.6±1.5 (260) July 38.5±3.6 (13) 34.9±2.8 (31) 39.9±2.0 (74) 42.4±1.2 (247)

13 PM 10 (µg/m 3 ) Jan 312.2±22.6 (2) 244.5±12.2 (41) 239.9±11.7 (69) 211.1±9.2 (155) Feb 282.4±. (1) 233.5±8.8 (44) 220.2±10.8 (88) 179.4±8.1 (205) March 197.7±1.7 (2) 193.3±12.5 (19) 185.9±13.6 (52) 154.6±8.7 (138) April 385.2±20.1 (10) 337.2±13.2 (41) 272.8±12.5 (71) 233.0±8.4 (154) May 293.7±13.7 (15) 216.5±10.2 (52) 191.9±8.7 (82) 160.6±6.4 (207) 2007 June 351.4±5.4 (15) 298.0±5.6 (49) 260.4±8.1 (76) 232.9±5.9 (211) July 184.8±16.9 (7) 116.0±10.9 (34) 123.7±11.6 (30) 129.2±10.2 (71) Aug 225.0±16.5 (14) 161.9±8.9 (48) 133.1±7.7 (76) 132.8±6.0 (177) Sept 279.9±9.9 (10) 188.0±9.1 (41) 135.5±8.5 (59) 125.8±6.2 (146) Oct 257.2±12.9 (15) 205.2±12.0 (44) 171.4±10.6 (70) 138.8±7.5 (175) Nov 242.6±11.2 (12) 197.0±10.3 (57) 197.1±10.8 (81) 172.8±7.9 (203) Dec 272.2±. (1) 209.6±7.5 (31) 201.9±10.8 (61) 162.7±8.0 (127) Jan 230.8±31.2 (3) 193.8±9.5 (50) 174.1±9.5 (82) 161.0±7.8 (181) Feb 332.0±27.5 (4) 283.8±9.3 (52) 225.5±10.7 (94) 208.4±6.7 (236) March 319.1±24.5 (7) 242.4±11.0 (59) 197.5±9.9 (100) 157.6±5.6 (251) 2008 April 359.5±5.8 (18) 305.0±7.3 (60) 259.6±9.1 (100) 207.7±6.9 (257) May 288.6±5.6 (20) 245.9±9.6 (58) 203.8±10.6 (96) 173.7±6.8 (239) June 309.2±6.8 (20) 283.2±6.5 (59) 244.6±8.2 (97) 189.3±6.5 (243) July 56.2±11.4 (8) 60.9±22.0 (8) 96.6±14.9 (27) 124.2±8.1 (89)

14 Table 4a: Weekly estimates of PM 2.5, Jan-July 2008 From To Date <24km <48km 48-72km 72-96km 48-96km 96+km 28-Dec-07 3-Jan ± ± ± ± ± ± ±4.1 4-Jan Jan-08 NA 101.1± ± ± ± ± ± Jan Jan ± ± ± ± ± ± ± Jan Jan-08 NA 203.9± ± ± ± ± ± Jan Jan ± ± ± ± ± ± ±7.8 1-Feb-08 7-Feb ± ± ± ± ± ± ±3.8 8-Feb Feb ± ± ± ± ± ± ± Feb Feb ± ± ± ± ± ± ± Feb Feb ± ± ± ± ± ± ± Feb-08 6-Mar ± ± ± ± ± ± ±2.6 7-Mar Mar ± ± ± ± ± ± ± Mar Mar ± ± ± ± ± ± ± Mar Mar ± ± ± ± ± ± ± Mar-08 3-Apr ± ± ± ± ± ± ±5.9 4-Apr Apr ± ± ± ± ± ± ± Apr Apr ± ± ± ± ± ± ± Apr Apr ± ± ± ± ± ± ± Apr-08 1-May ± ± ± ± ± ± ±1.3 2-May-08 8-May ± ± ± ± ± ± ±1.3 9-May May ± ± ± ± ± ± ± May May ± ± ± ± ± ± ± May May ± ± ± ± ± ± ± May-08 5-Jun ± ± ± ± ± ± ±2.7 6-Jun Jun ± ± ± ± ± ± ± Jun Jun-08 NA 158.0± ± ± ± ± ± Jun Jun ± ± ± ± ± ± ± Jun-08 3-Jul ± ± ± ± ± ± ±3.0 July 2008 Analysis 1-Jul-08 5-Jul ± ± ± ± ± ± ±1.2 6-Jul Jul ± ± ± ± ± ± ± Jul Jul ± ± ± ± ± ± ± Jul Jul ± ± ± ± ± ± ±0.7 1-Jul Jul ± ± ± ± ± ± ± Dec Jul ± ± ± ± ± ± ±0.9

15 Table 4b: Weekly estimates of PM 10, Jan-July 2008 From To Date <24km <48km 48-72km 72-96km 48-96km 96+km 28-Dec-07 3-Jan ± ± ± ± ± ± ± Jan Jan-08 NA 237.5± ± ± ± ± ± Jan Jan ± ± ± ± ± ± ± Jan Jan-08 NA 282.0± ± ± ± ± ± Jan Jan ± ± ± ± ± ± ± Feb-08 7-Feb ± ± ± ± ± ± ± Feb Feb ± ± ± ± ± ± ± Feb Feb ± ± ± ± ± ± ± Feb Feb ± ± ± ± ± ± ± Feb-08 6-Mar ± ± ± ± ± ± ±8.0 7-Mar Mar ± ± ± ± ± ± ± Mar Mar ± ± ± ± ± ± ± Mar Mar ± ± ± ± ± ± ± Mar-08 3-Apr ± ± ± ± ± ± ± Apr Apr ± ± ± ± ± ± ± Apr Apr ± ± ± ± ± ± ± Apr Apr ± ± ± ± ± ± ± Apr-08 1-May ± ± ± ± ± ± ±6.2 2-May-08 8-May ± ± ± ± ± ± ±9.4 9-May May ± ± ± ± ± ± ± May May ± ± ± ± ± ± ± May May ± ± ± ± ± ± ± May-08 5-Jun ± ± ± ± ± ± ± Jun Jun ± ± ± ± ± ± ± Jun Jun-08 NA 385.4± ± ± ± ± ± Jun Jun ± ± ± ± ± ± ± Jun-08 3-Jul ± ± ± ± ± ± ±11.0 July 2008 Analysis 1-Jul-08 5-Jul ± ± ± ± ± ± ± Jul Jul ± ± ± ± ± ± ± Jul Jul ± ± ± ± ± ± ± Jul Jul ± ± ± ± ± ± ±5.4 1-Jul Jul ± ± ± ± ± ± ±3.6 Total 28-Dec Jul ± ± ± ± ± ± ±10.6

J. Vira, E. Rodriguez, G. de Leeuw, M. Sofiev International Workshop on Air Quality Forecasting Research December 2012 Geneve Switzerland

Regional-scale particulate matter emission estimates using satellite observations and variational inversion J. Vira, E. Rodriguez, G. de Leeuw, M. Sofiev International Workshop on Air Quality Forecasting