Modeling study of PM&amp;lt;sub&amp;gt;2.5&amp;lt;/sub&amp;gt; pollutant transport across cities in China's Jing–Jin–Ji region during a severe haze episode in December 2013

Jiang, Chao; Wang, H.; Zhao, Tianliang; Li, T.; Che, Huizheng

doi:10.5194/acp-15-5803-2015

Cited by 102 publications

(66 citation statements)

References 46 publications

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“…The large amount of PM 2.5 inflows can only be efficiently blown out to the northeast direction (Chengde, Langfang (N) and Tianjin (N)). These results are consistent with Jiang et al (2015), who also found a strong southerly input at a high level during a haze episode in winter.…”

Section: The Daily Characteristics Of Pm 25 Transport In Beijingsupporting

confidence: 82%

Assessment of inter-city transport of particulate matter in the Beijing–Tianjin–Hebei region

et al. 2018

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Abstract. The regional transport of particulate matter with diameter less than 2.5 µm (PM 2.5 ) plays an important role in the air pollution of the Beijing-Tianjin-Hebei (BTH) region in China. However, previous studies on regional transport of PM 2.5 mainly aim at province level, which is insufficient for the development of an optimal joint PM 2.5 control strategy. In this study, we calculate PM 2.5 inflows and outflows through the administrative boundaries of three major cities in the BTH region, i.e., Beijing, Tianjin and Shijiazhuang, using the WRF (Weather Research and Forecasting model)-CMAQ (Community Multiscale Air Quality) modeling system. The monthly average inflow fluxes indicate the major directions of PM 2.5 transport. For Beijing, the PM 2.5 inflow fluxes from Zhangjiakou (in the northwest) and Baoding (in the southwest) constitute 57 % of the total in winter, and Langfang (in the southeast) and Baoding constitute 73 % in summer. Based on the net PM 2.5 fluxes and their vertical distributions, we find there are three major transport pathways in the BTH region: the northwest-southeast pathway in winter (at all levels below 1000 m), the northwestsoutheast pathway in summer (at all levels below 1000 m), and the southwest-northeast pathway in both winter and in summer (mainly at 300-1000 m). In winter, even if surface wind speeds are low, the transport at above 300 m can still be strong. Among the three pathways, the southwest-northeast happens along with PM 2.5 concentrations 30 and 55 % higher than the monthly average in winter and summer, respectively. Analysis of two heavy pollution episodes in January and July in Beijing show a much (8-16 times) stronger transport than the monthly average, emphasizing the joint air pollution control of the cities located on the transport pathways, especially during heavy pollution episodes.

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Section: The Daily Characteristics Of Pm 25 Transport In Beijingsupporting

confidence: 82%

Assessment of inter-city transport of particulate matter in the Beijing–Tianjin–Hebei region

et al. 2018

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“…In an urban and industrialized region, anthropogenic emissions from traffic, domestic heating, factories, power plants and biomass burning significantly elevate the concentrations of these (and other) trace gases (TGs) in the boundary layer (Environmental Protection Agency, 1998;Seinfeld and Pandis, 1998). There is strong evidence that aerosol particles formed through photochemistry of NO x , SO 2 and VOCs significantly contribute to haze pollution events occurring frequently around megacities and urban agglomerations in China, like the Jing-Jin-Ji region and the Yangtze River delta region Huang et al, 2014;Jiang et al, 2015;Fu et al, 2014). The aerosols also impact the local radiative forcing through direct (e.g.…”

Section: Introductionmentioning

confidence: 99%

Validation of OMI, GOME-2A and GOME-2B tropospheric NO2, SO2 and HCHO products using MAX-DOAS observations from 2011 to 2014 in Wuxi, China: investigation of the effects of priori profiles and aerosols on the satellite products

et al. 2017

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Abstract. Tropospheric vertical column densities (VCDs) of NO 2 , SO 2 and HCHO derived from the Ozone Monitoring Instrument (OMI) on AURA and the Global Ozone Monitoring Experiment 2 aboard METOP-A (GOME-2A) and METOP-B (GOME-2B) are widely used to characterize the global distributions, trends and dominating sources of these trace gases. They are also useful for the comparison with chemical transport models (CTMs). We use tropospheric VCDs and vertical profiles of NO 2 , SO 2 and HCHO derived from MAX-DOAS measurements from 2011 to 2014 in Wuxi, China, to validate the corresponding products (daily and bi-monthly-averaged data) derived from OMI and GOME-2A/B by different scientific teams. Prior to the comparison, the spatial and temporal coincidence criteria for MAX-DOAS and satellite data are determined by a sensitivity study using different spatial and temporal averaging conditions. Cloud effects on both MAX-DOAS and satellite observations are also investigated. Our results indicate that the discrepancies between satellite and MAX-DOAS results increase with increasing effective cloud fraction and are dominated by the effects of clouds on the satellite products. In comparison with MAX-DOAS, we found a systematic underestimation of all SO 2 (40 to 57 %) and HCHO products (about 20 %), and an overestimation of the GOME-2A/B NO 2 products (about 30 %), but good consistency with the DOMINO version 2 NO 2 product. To better understand the reasons for these differences, we evaluated the a priori profile shapes used in the OMI retrievals (derived from CTM) by comparison with those derived from the MAX-DOAS observations. Significant differences are found for the SO 2 and HCHO profile shapes derived from the IMAGES model, whereas on average good agreement is found for the NO 2 profile shapes derived from the TM4 model. We also applied the MAX-DOAS profile shapes to the satellite rePublished by Copernicus Publications on behalf of the European Geosciences Union. 5008 Y. Wang et al.: Validation of OMI, GOME-2A and GOME-2B tropospheric NO 2 , SO 2 and HCHO products trievals and found that these modified satellite VCDs agree better with the MAX-DOAS VCDs than the VCDs from the original data sets by up to 10, 47 and 35 % for NO 2 , SO 2 and HCHO, respectively. Furthermore, we investigated the effect of aerosols on the satellite retrievals. For OMI observations of NO 2 , a systematic underestimation is found for large AOD, which is mainly attributed to effect of the aerosols on the cloud retrieval and the subsequent application of a cloud correction scheme (implicit aerosol correction). In contrast, the effect of aerosols on the clear-sky air mass factor (explicit aerosol correction) has a smaller effect. For SO 2 and HCHO observations selected in the same way, no clear aerosol effect is found, probably because for the considered data sets no cloud correction is applied (and also because of the larger scatter). From our findings we conclude that for satellite observations with cloud top pressure (CTP) > 900 hPa and effective ...

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“…The overestimation of PM 2.5 in this study might be attributed to the uncertainties of these three factors in the model. Prior studies (Zhou et al, 2012;Wang et al, 2015a, b;Jiang et al, 2015) have demonstrated the stable simulation performance of the GRAPES-CUACE modeling system in reproducing air pollution levels and variation trends over northeast China. Above all, the following analysis mainly focuses on the variations and the contributing proportions of emission sources over different regions.…”

Section: Model Setup Data and Validationmentioning

confidence: 99%

“…The GRAPES-CUACE is an online coupled atmospheric chemistry modeling system (Wang et al, 2009;Zhou et al, 2012;Jiang et al, 2015) developed by the China Meteorological Administration (CMA). GRAPES-Meso is a regional meteorological model (Xue et al, 2008) within GRAPES-CUACE, and CUACE is an atmospheric chemistry modeling system independent of meteorological and climate models.…”

Section: Model Descriptionmentioning

confidence: 99%

“…Research using approaches such as the flux calculation method , the back-trajectory model , and observation analysis , have revealed that southerly winds almost always promote high PM 2.5 conditions in Beijing. Studies have also indicated that more than 50 % of PM 2.5 pollutants originate in surrounding provinces and cities, including southern Hebei, Tianjin, eastern Shanxi, and Shandong provinces (Jiang et al, 2015;Gao et al, 2016). Studies have also shown that joint regional air pollution management control can be more costeffective and that joint control schemes in critical source zones (detected by a back-trajectory model) prior to unfavorable meteorological conditions can help reduce costs and improve efficiency .…”

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confidence: 99%

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Detection of critical PM2.5 emission sources and their contributions to a heavy haze episode in Beijing, China, using an adjoint model

Zhai¹,

Xu²,

Zhao³

et al. 2018

Atmos. Chem. Phys.

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Abstract. Air pollution sources and their regional transport are important issues for air quality control. The Global-Regional Assimilation and Prediction System coupled with the China Meteorological Administration Unified Atmospheric Chemistry Environment (GRAPES-CUACE) aerosol adjoint model was applied to detect the sensitive primary emission sources of a haze episode in Beijing occurring between 19 and 21 November 2012. The high PM 2.5 concentration peaks occurring at 05:00 and 23:00 LT (GMT+8) over Beijing on 21 November 2012 were set as the cost functions for the aerosol adjoint model. The critical emission regions of the first PM 2.5 concentration peak were tracked to the west and south of Beijing, with 2 to 3 days of cumulative transport of air pollutants to Beijing. The critical emission regions of the second peak were mainly located to the south of Beijing, where southeasterly moist air transport led to the hygroscopic growth of particles and pollutant convergence in front of the Taihang Mountains during the daytime on 21 November. The temporal variations in the sensitivity coefficients for the two PM 2.5 concentration peaks revealed that the response time of the onset of Beijing haze pollution from the local primary emissions is approximately 1-2 h and that from the surrounding primary emissions it is approximately 7-12 h. The upstream Hebei province has the largest impact on the two PM 2.5 concentration peaks, and the contribution of emissions from Hebei province to the first PM 2.5 concentration peak (43.6 %) is greater than that to the second PM 2.5 concentration peak (41.5 %). The second most influential province for the 05:00 LT PM 2.5 concentration peak is Beijing (31.2 %), followed by Shanxi (9.8 %), Tianjin (9.8 %), and Shandong (5.7 %). The second most influential province for the 23:00 LT PM 2.5 concentration peak is Beijing (35.7 %), followed by Shanxi (8.1 %), Shandong (8.0 %), and Tianjin (6.7 %). The adjoint model results were compared with the forward sensitivity simulations of the Models-3/CMAQ system. The two modeling approaches are highly comparable in their assessments of atmospheric pollution control schemes for critical emission regions, but the adjoint method has higher computational efficiency than the forward sensitivity method. The results also imply that critical regional emission reduction could be more efficient than individual peak emission control for improving regional PM 2.5 air quality.

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Modeling study of PM<sub>2.5</sub> pollutant transport across cities in China's Jing–Jin–Ji region during a severe haze episode in December 2013

Cited by 102 publications

References 46 publications

Assessment of inter-city transport of particulate matter in the Beijing–Tianjin–Hebei region

Assessment of inter-city transport of particulate matter in the Beijing–Tianjin–Hebei region

Validation of OMI, GOME-2A and GOME-2B tropospheric NO<sub>2</sub>, SO<sub>2</sub> and HCHO products using MAX-DOAS observations from 2011 to 2014 in Wuxi, China: investigation of the effects of priori profiles and aerosols on the satellite products

Detection of critical PM<sub>2.5</sub> emission sources and their contributions to a heavy haze episode in Beijing, China, using an adjoint model

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Modeling study of PM&lt;sub&gt;2.5&lt;/sub&gt; pollutant transport across cities in China's Jing–Jin–Ji region during a severe haze episode in December 2013

Cited by 102 publications

References 46 publications

Assessment of inter-city transport of particulate matter in the Beijing–Tianjin–Hebei region

Assessment of inter-city transport of particulate matter in the Beijing–Tianjin–Hebei region

Validation of OMI, GOME-2A and GOME-2B tropospheric NO&lt;sub&gt;2&lt;/sub&gt;, SO&lt;sub&gt;2&lt;/sub&gt; and HCHO products using MAX-DOAS observations from 2011 to 2014 in Wuxi, China: investigation of the effects of priori profiles and aerosols on the satellite products

Detection of critical PM&lt;sub&gt;2.5&lt;/sub&gt; emission sources and their contributions to a heavy haze episode in Beijing, China, using an adjoint model

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Modeling study of PM<sub>2.5</sub> pollutant transport across cities in China's Jing–Jin–Ji region during a severe haze episode in December 2013

Validation of OMI, GOME-2A and GOME-2B tropospheric NO<sub>2</sub>, SO<sub>2</sub> and HCHO products using MAX-DOAS observations from 2011 to 2014 in Wuxi, China: investigation of the effects of priori profiles and aerosols on the satellite products

Detection of critical PM<sub>2.5</sub> emission sources and their contributions to a heavy haze episode in Beijing, China, using an adjoint model