Abstract. Extremely severe and persistent haze occurred in January 2013 over eastern and northern China. The record-breaking high concentrations of fine particulate matter (PM 2.5 ) of more than 700 µg m −3 on hourly average and the persistence of the episodes have raised widespread, considerable public concerns. During that period, 7 of the top 10 polluted cities in China were within the Hebei Province. The three cities in southern Hebei (Shijiazhuang, Xingtai, and Handan) have been listed as the top three polluted cities according to the statistics for the first half of the year 2013. In this study, the Mesoscale Modeling System Generation 5 (MM5) and the Models-3/Community Multiscale Air Quality (CMAQ) modeling system are applied to simulate the 2013 severe winter regional hazes in East Asia and northern China at horizontal grid resolutions of 36 and 12 km, respectively, using the Multi-resolution Emission Inventory for China (MEIC). The source contributions of major source regions and sectors to PM 2.5 concentrations in the three most polluted cities in southern Hebei are quantified by aiming at the understanding of the sources of the severe haze pollution in this region, and the results are compared with December 2007, the haziest month in the period 2001-2010. Model evaluation against meteorological and air quality observations indicates an overall acceptable performance and the model tends to underpredict PM 2.5 and coarse particulate matter (PM 10 ) concentrations during the extremely polluted episodes. The MEIC inventory is proven to be a good estimation in terms of total emissions of cities but uncertainties exist in the spatial allocations of emissions into fine grid resolutions within cities. The source apportionment shows that emissions from northern Hebei and the Beijing-Tianjin city cluster are two major regional contributors to the pollution in January 2013 in Shijiazhuang, compared with those from Shanxi and northern Hebei for December 2007. For Xingtai and Handan, the emissions from northern Hebei and Henan are important. The industrial and domestic sources are the most significant local contributors, and the domestic and agricultural emissions from Shandong and Henan are non-negligible regional sources, especially for Xingtai and Handan. Even in the top two haziest months (i.e., January 2013 and December 2007), a large fraction of PM 2.5 in the three cities may originate from quite different regional sources. These results indicate the importance of establishing a regional joint framework of policymaking and action system to effectively mitigate air pollution in this area, not only over the Beijing-Tianjin-Hebei area, but also surrounding provinces such as Henan, Shandong, and Shanxi.

Abstract. Aerosol acidity plays a key role in secondary aerosol formation. The high-temporal-resolution PM2.5 pH and size-resolved aerosol pH in Beijing were calculated with ISORROPIA II. In 2016–2017, the mean PM2.5 pH (at relative humidity (RH) > 30 %) over four seasons was 4.5±0.7 (winter) > 4.4±1.2 (spring) > 4.3±0.8 (autumn) > 3.8±1.2 (summer), showing moderate acidity. In coarse-mode aerosols, Ca2+ played an important role in aerosol pH. Under heavily polluted conditions, more secondary ions accumulated in the coarse mode, leading to the acidity of the coarse-mode aerosols shifting from neutral to weakly acidic. Sensitivity tests also demonstrated the significant contribution of crustal ions to PM2.5 pH. In the North China Plain (NCP), the common driving factors affecting PM2.5 pH variation in all four seasons were SO42-, TNH3 (total ammonium (gas + aerosol)), and temperature, while unique factors were Ca2+ in spring and RH in summer. The decreasing SO42- and increasing NO3- mass fractions in PM2.5 as well as excessive NH3 in the atmosphere in the NCP in recent years are the reasons why aerosol acidity in China is lower than that in Europe and the United States. The nonlinear relationship between PM2.5 pH and TNH3 indicated that although NH3 in the NCP was abundant, the PM2.5 pH was still acidic because of the thermodynamic equilibrium between NH4+ and NH3. To reduce nitrate by controlling ammonia, the amount of ammonia must be greatly reduced below excessive quantities.

Abstract. Extremely severe and persistent haze occurred in January 2013 over the eastern and northern China. The record-breaking high concentrations of fine particulate matter (PM2.5) of more than 700 μg m−3 on hourly average and the persistence of the episodes have raised widespread, considerable public concerns. During that period, seven of the top ten polluted cities in China were within Hebei Province. The three cities in southern Hebei, Shijiazhuang, Xingtai, and Handan, have been listed as the top three polluted cities according to the statistics for the first half year of 2013. In this study, the Mesoscale Modeling System Generation 5 (MM5) and the Models-3/Community Multiscale Air Quality (CMAQ) modeling system are applied to simulate the 2013 severe winter regional hazes in East Asia and the northern China at horizontal grid resolutions of 36 and 12 km, respectively, using the Multi-resolution Emission Inventory of China (MEIC). The source contributions of major source regions and sectors to PM2.5 concentrations in the three most-polluted cities in southern Hebei are quantified aiming at the understanding of the sources of the severe haze pollution in this region, and the results are compared with December 2007, the haziest month in 2001–2010. Model evaluation against meteorological and air quality observations indicates an overall acceptable performance and the model tends to underpredict PM2.5 and coarse particulate matter (PM10) concentrations during the extremely severe polluted episodes. The MEIC inventory is proved to be a good estimation in terms of total emissions of cities but uncertainties exist in the spatial allocations of emissions into fine grid resolutions within cities. The source apportionment shows that emissions from the northern Hebei and the Beijing–Tianjin city cluster are two major regional contributors to the pollution in January 2013 in Shijiazhuang, comparing with those from Shanxi and the northern Hebei for December 2007. For Xingtai and Handan, the emissions from the northern Hebei and Henan are important. The industrial and domestic sources are the most significant local contributors, and the domestic and agricultural emissions from Shandong and Henan are unnegligible regional sources, especially for Xingtai and Handan. Even in the top two haziest months (i.e., January 2013 and December 2007), a large fraction of PM2.5 in the three cities may originate from quite different regional sources. These results indicate the importance of establishing a regional joint framework of policymaking and action system to effectively mitigate air pollution in this area, not only over Beijing–Tianjin–Hebei area, but also surrounding provinces such as Henan, Shandong, and Shanxi.

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Machine Learning (ML) and Internet of Things (IoT) are complementary advances: ML techniques unlock the potential of IoT with intelligence, and IoT applications increasingly feed data collected by sensors into ML models, thereby employing results to improve their business processes and services. Hence, orchestrating ML pipelines that encompass model training and implication involved in the holistic development lifecycle of an IoT application often leads to complex system integration. This paper provides a comprehensive and systematic survey of the development lifecycle of ML-based IoT applications. We outline the core roadmap and taxonomy, and subsequently assess and compare existing standard techniques used at individual stages.