Impact of Crop Straw Burning on Urban Air Quality Based on WRF-Chem Simulations
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摘要: 利用融合火点排放源、人为源和生物源的WRF-Chem(Weather Research and Forecasting Model coupled with Chemistry)模式,模拟2015年9月30日08:00(北京时间)起的72 h发生在淮河流域的一次农作物秸秆大面积露天焚烧过程,研究了农作物秸秆焚烧释放的气态污染物和颗粒物对区域城市空气质量的影响。通过有无火点两组试验分析了此次秸秆焚烧对流域内河南、山东、江苏和安徽四省83座城市CO、PM10(空气动力学当量直径小于等于10 μm的颗粒物,即可吸入颗粒物)、PM2.5(空气动力学当量直径小于等于2.5 μm的颗粒物,即细颗粒物)和O3浓度的定量影响,结果表明:(1)融合NCAR-FINN(Fire Inventory from NCAR)火点排放资料的WRF-Chem模式较好地再现了此次秸秆焚烧及火点烟羽扩散过程。同时结合EDGAR-HTAP(Emission Database for Global Atmospheric Research on Hemispheric Transport of Air Pollution)人为源和MEGAN(Model of Emission of Gases and Aerosols from Nature)生物源的WRF-FIRE(考虑火点排放试验)对流域内城市大气污染物的模拟效果较为理想,尤其对秸秆焚烧释放的污染物CO、PM10和PM2.5和产生的二次污染物O3浓度的模拟。(2)秸秆焚烧所释放的污染物造成流域内城市一次污染物CO、PM10和PM2.5浓度的增加,火点中心和下风向城市增幅最为明显,最大小时浓度增幅达到3倍标准差。气态污染物CO和相比PM10粒径更小的PM2.5可随风扩散至更远的地区,对城市浓度影响更大。(3)此外,秸秆焚烧也使得火点中心城市和下风向城市二次污染物O3浓度增加,但小时浓度增幅极值区分布在火点下风向烟羽末端太阳光照充足的地区,最大小时浓度增幅接近3倍标准差。秸秆焚烧对区域城市空气质量的影响存在明显的空间分布差异且对城市各大气污染成分的影响也不相同。
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关键词:
- 焚烧 /
- 城市空气质量 /
- WRF-Chem模式 /
- FINN (Fire Inventory from NCAR) 火点排放清单
Abstract: Smoke from open crop straw burning has a notable impact on ambient, regional, and global air quality. The crop straw burning smoke event of 1 October 2015 in Huaihe River basin of China has been simulated using the WRF-Chem (Weather Research and Forecasting Model coupled with Chemistry). This study focused on the evolution of the fire plume composition and its impact on urban air quality in 83 cities in Henan, Shangdong, Jiangsu, and Anhui provinces. Two simulations were conducted in this study. The first simulation referred to as WRF-FIRE included the FINN (Fire Inventory from NCAR) fire emission dataset, EDGAR-HTAP (Emission Database for Global Atmospheric Research on Hemispheric Transport of Air Pollution) anthropogenic emissions and MEGAN (Model of Emission of Gases and Aerosols from Nature) while the other referred to as WRF-NOFIRE, which was conducted without the FINN fire emission. The results show that WRF-FIRE simulation could reveal most of the locations of fires and the spreading of the fire plume was properly captured. WRF-FIRE simulation agreed well with ground-based measurements of O3, CO, PM2.5, and PM10. The total correlation coefficient between simulation and observations was up to 0.50. Based on the difference between simulations with and without fire emission, the concentrations of O3, CO, PM2.5, and PM10 increased differently in different cities. The maximum hourly biases (MHB) of CO, PM2.5, and PM10 were up to triple standard deviations of simulations without fire emission near the source. Emissions of nitrogen oxides (NOx) and volatile organic compounds (VOCs) from fire tended to increase modeled O3 concentrations downwind of the fire location, and MHB was almost triple standard deviations of simulation without fire emission. Meanwhile, the impacts of fires were different for individual components of urban air pollutants. The basic concentrations of NO2 and SO2 probably decreased due to the high level surface O3 far downwind of the fire location. -
图 2 2001~2010年MODIS 500 m土地利用气候分布(Broxton et al., 2014)、淮河流域(蓝色实线区域)、WRF模式区域(蓝色点线区域)和2015年10月1日MODIS火点信息(红色十字)
Figure 2. MODIS-based land cover climatology at 0.5-km resolution for the 10-year period (2001-2010) (Broxton et al., 2014), Huaihe River basin is denoted by the blue solid line, WRF domain is indicated by the blue dotted line, and MODIS active fire map (red crosses) on 1 October 2015
图 3 2015年10月1日(a)12:45的Terra卫星和(b)14:30的Auqa卫星MODIS可见光拼图和火点信息(红色圆点);当日(c)13:00和(d)15:00近地面CO浓度(填色),用以表征火点烟羽]和地面10 m风场的WRF-Chem模拟结果
Figure 3. Comparison of fire smoke between MODIS (a) on NASA's Terra satellite at 1245 LST 1 October 2015 and (b) on NASA's Aqua at 1430 LST 1 October 2015, and MODIS active fire map (ned dots); FINN fire emissions at (c) 1300 LST and (d) 1500 LST on the same day represented by CO content (colored) from WRF-Chem simulation with wind map at 10-m height
图 4 地面(a)O3和CO、(b)PM10和PM2.5、(c)SO2和NO2小时实测与WRF-FIRE模拟序列的Taylor图
Figure 4. Taylor diagrams for observations of (a) O3 and CO, (b) PM2.5 and PM10, and (c) SO2 and NO2 from Ministry of Environmental Protection of the People's Republic of China and WRF-FIRE simulations from 0000 LST 1 October 2015 to 0800 LST 3 October 2015 at 83 cities in Huaihe River basin
图 5 秸秆焚烧对城市空气质量(a)CO、(b)PM10、(c)PM2.5、(d)O3、(e)NO2和(f)SO2的最大小时浓度影响(蓝色表示负影响,红色代表正影响)
Figure 5. Normalized maximum hourly biases of (a) CO, (b) PM10, (c) PM2.5, (d) O3, (e) NO2, and (f) SO2 between the WRF-FIRE and WRF-NOFIRE simulations from 0000 LST 1 October 2015 to 0800 LST 3 October 2015 at 83 cities in Huaihe River basin, blue means it's decreased, red means it's increased
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