scholarly journals Atmospheric Pollution Impact Assessment of Brick and Tile Industry: A Case Study of Xinmi City in Zhengzhou, China

2021 ◽  
Vol 13 (4) ◽  
pp. 2414
Author(s):  
Liuzhen Xie ◽  
Qixiang Xu ◽  
Ruidong He
Keyword(s):  
Air Quality ◽  
Emission Inventory ◽  
Census Data ◽  
Emission Control ◽  
Temporal Distribution ◽  
Point Sources ◽  
Control Measures ◽  
Pollutant Emissions ◽  
Brick And Tile ◽  
The Impact

The brick and tile industry was selected to investigate the impact of pollutants emitted from such industry on air quality. Based on the 2018 Zhengzhou City Census data and combined with field sampling and research visits, an emission inventory of the brick and tile industry in Xinmi City was established using the emission factor method. Based on the established emission inventory, the concentrations of SO2, NOX, and PM2.5 emitted by 31 brick and tile enterprises were then predicted using the CALPUFF model (California puff model, USEPA), which had been evaluated for accuracy, and the simulation results were compared with the observed results to obtain the impact of pollutant emissions from the brick and tile industry on air pollution in the simulated region. Results show that SO2, NOX, and PM2.5 emissions from the brick and tile industry in the study area in 2018 were 564.86 tons, 513.16 tons, and 41.01 tons, respectively. The CALPUFF model can simulate the characteristics of meteorological changes and pollutant concentration trends, and the correlation coefficient of the fit curve between the pollutant observed data and the simulated data was higher than 0.8, which can reproduce the impact of key industrial point sources on air quality well. The simulated concentration values and spatial and temporal distribution characteristics of SO2, NOX, PM2.5 in spring, summer, autumn, and winter were obtained from the model simulations. The contribution of pollutant emissions from the brick and tile industry to the monthly average concentrations of SO2, NOX, and PM2.5 in the simulated region were 6.58%, 5.38%, and 1.42%, respectively, with the Housing Administration monitoring station as the receptor point. The brick and tile industry should increase the emission control measures of SO2 and NOX, and at the same time, the emission control of PM2.5 cannot be slackened.

scholarly journals Dominant role of emission reduction in PM<sub>2.5</sub> air quality improvement in Beijing during 2013–2017: a model-based decomposition analysis

2019 ◽  
Vol 19 (9) ◽  
pp. 6125-6146 ◽  
Author(s):  
Jing Cheng ◽  
Jingping Su ◽  
Tong Cui ◽  
Xiang Li ◽  
Xin Dong ◽  
...  
Keyword(s):  
Air Quality ◽  
Emission Inventory ◽  
Industrial Structure ◽  
Emission Control ◽  
Meteorological Conditions ◽  
Control Measures ◽  
Emission Reductions ◽  
Air Quality Improvement ◽  
Clean Air ◽  
Emission Control Measures

Abstract. In 2013, China's government published the Air Pollution Prevention and Control Action Plan (APPCAP) with a specific target for Beijing, which aims to reduce annual mean PM2.5 concentrations in Beijing to 60 µg m−3 in 2017. During 2013–2017, the air quality in Beijing was significantly improved following the implementation of various emission control measures locally and regionally, with the annual mean PM2.5 concentration decreasing from 89.5 µg m−3 in 2013 to 58 µg m−3 in 2017. As meteorological conditions were more favourable to the reduction of air pollution in 2017 than in 2013 and 2016, the real effectiveness of emission control measures on the improvement of air quality in Beijing has frequently been questioned. In this work, by combining a detailed bottom-up emission inventory over Beijing, the MEIC regional emission inventory and the WRF-CMAQ (Weather Research and Forecasting Model and Community Multiscale Air Quality) model, we attribute the improvement in Beijing's PM2.5 air quality in 2017 (compared to 2013 and 2016) to the following factors: changes in meteorological conditions, reduction of emissions from surrounding regions, and seven specific categories of local emission control measures in Beijing. We collect and summarize data related to 32 detailed control measures implemented during 2013–2017, quantify the emission reductions associated with each measure using the bottom-up local emission inventory in 2013, aggregate the measures into seven categories, and conduct a series of CMAQ simulations to quantify the contribution of different factors to the PM2.5 changes. We found that, although changes in meteorological conditions partly explain the improved PM2.5 air quality in Beijing in 2017 compared to 2013 (3.8 µg m−3, 12.1 % of total), the rapid decrease in PM2.5 concentrations in Beijing during 2013–2017 was dominated by local (20.6 µg m−3, 65.4 %) and regional (7.1 µg m−3, 22.5 %) emission reductions. The seven categories of emission control measures, i.e. coal-fired boiler control, clean fuels in the residential sector, optimize industrial structure, fugitive dust control, vehicle emission control, improved end-of-pipe control, and integrated treatment of VOCs, reduced the PM2.5 concentrations in Beijing by 5.9, 5.3, 3.2, 2.3, 1.9, 1.8, and 0.2 µg m−3, respectively, during 2013–2017. We also found that changes in meteorological conditions could explain roughly 30 % of total reduction in PM2.5 concentration during 2016–2017 with more prominent contribution in winter months (November and December). If the meteorological conditions in 2017 had remained the same as those in 2016, the annual mean PM2.5 concentrations would have increased from 58 to 63 µg m−3, exceeding the target established in the APPCAP. Despite the remarkable impacts from meteorological condition changes, local and regional emission reductions still played major roles in the PM2.5 decrease in Beijing during 2016–2017, and clean fuels in the residential sector, coal-fired boiler control, and optimize industrial structure were the three most effective local measures (contributing reductions of 2.1, 1.9, and 1.5 µg m−3, respectively). Our study confirms the effectiveness of clean air actions in Beijing and its surrounding regions and reveals that a new generation of control measures and strengthened regional joint emission control measures should be implemented for continued air quality improvement in Beijing because the major emitting sources have changed since the implementation of the clean air actions.

scholarly journals A high-resolution emission inventory of primary pollutants for the Huabei region, China

2012 ◽  
Vol 12 (1) ◽  
pp. 481-501 ◽  
Author(s):  
B. Zhao ◽  
P. Wang ◽  
J. Z. Ma ◽  
S. Zhu ◽  
A. Pozzer ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Air Quality ◽  
Emission Inventory ◽  
Emission Factors ◽  
Cloud Microphysics ◽  
Point Sources ◽  
Air Pollutant ◽  
Pollutant Emissions ◽  
Environmental Research ◽  
Straw Burning

Abstract. Huabei, located between 32° N and 42° N, is part of eastern China and includes administratively the Beijing and Tianjin Municipalities, Hebei and Shanxi Provinces, and Inner-Mongolia Autonomous Region. Over the past decades, the region has experienced dramatic changes in air quality and climate, and has become a major focus of environmental research in China. Here we present a new inventory of air pollutant emissions in Huabei for the year 2003 developed as part of the project Influence of Pollution on Aerosols and Cloud Microphysics in North China (IPAC-NC). Our estimates are based on data from the statistical yearbooks of the state, provinces and local districts, including major sectors and activities of power generation, industrial energy consumption, industrial processing, civil energy consumption, crop straw burning, oil and solvent evaporation, manure, and motor vehicles. The emission factors are selected from a variety of literature and those from local measurements in China are used whenever available. The estimated total emissions in the Huabei administrative region in 2003 are 4.73 Tg SO2, 2.72 Tg NOx (in equivalent NO2), 1.77 Tg VOC, 24.14 Tg CO, 2.03 Tg NH3, 4.57 Tg PM10, 2.42 Tg PM2.5, 0.21 Tg EC, and 0.46 Tg OC. For model convenience, we consider a larger Huabei region with Shandong, Henan and Liaoning Provinces included in our inventory. The estimated total emissions in the larger Huabei region in 2003 are: 9.55 Tg SO2, 5.27 Tg NOx (in equivalent NO2), 3.82 Tg VOC, 46.59 Tg CO, 5.36 Tg NH3, 10.74 Tg PM10, 5.62 Tg PM2.5, 0.41 Tg EC, and 0.99 Tg OC. The estimated emission rates are projected into grid cells at a horizontal resolution of 0.1° latitude by 0.1° longitude. Our gridded emission inventory consists of area sources, which are classified into industrial, civil, traffic, and straw burning sectors, and large industrial point sources, which include 345 sets of power plants, iron and steel plants, cement plants, and chemical plants. The estimated regional NO2 emissions are about 2–3% (administrative Huabei region) or 5% (larger Huabei region) of the global anthropogenic NO2 emissions. We compare our inventory (IPAC-NC) with the global emission inventory EDGAR-CIRCE and the Asian emission inventory INTEX-B. Except for a factor of 3 lower EC emission rate in comparison with INTEX-B, the biases of the total emissions of most primary air pollutants in Huabei estimated in our inventory, with respect to EDGAR-CIRCE and INTEX-B, generally range from −30% to +40%. Large differences up to a factor of 2–3 for local emissions in some areas (e.g. Beijing and Tianjin) are found. It is recommended that the inventories based on the activity rates and emission factors for each specific year should be applied in future modeling work related to the changes in air quality and atmospheric chemistry over this region.

scholarly journals Dominant role of emission reduction in PM<sub>2.5</sub> air quality improvement in Beijing during 2013–2017: a model-based decomposition analysis

2018 ◽  
Author(s):  
Jing Cheng ◽  
Jingping Su ◽  
Tong Cui ◽  
Xiang Li ◽  
Xin Dong ◽  
...  
Keyword(s):  
Air Quality ◽  
Emission Inventory ◽  
Industrial Structure ◽  
Emission Control ◽  
Meteorological Conditions ◽  
Control Measures ◽  
Emission Reductions ◽  
Air Quality Improvement ◽  
Clean Air ◽  
Emission Control Measures

Abstract. In 2013, China's government published the Air Pollution Prevention and Control Action Plan (APPCAP) with a specific target for Beijing, which aims to reduce annual mean PM2.5 concentrations in Beijing to 60  m−3 in 2017. During 2013–2017, the air quality in Beijing was significantly improved following the implementation of various emission control measures locally and regionally, with the annual mean PM2.5 concentration decreasing from 89.5  m−3 in 2013 to 58  m−3 in 2017. As meteorological conditions were more favourable to the reduction of air pollution in 2017 than in 2013 and 2016, the real effectiveness of emission control measures on the improvement of air quality in Beijing has frequently been questioned. In this work, by combining a detailed bottom-up emission inventory over Beijing, the MEIC regional emission inventory, and the WRF-CMAQ model, we attribute the improvement in Beijing's PM2.5 air quality in 2017 (compared to 2013 and 2016) to the following factors: changes in meteorological conditions, reduction of emissions from surrounding regions, and seven specific categories of local emission control measures in Beijing. We collect and summarize data related to 32 detailed control measures implemented during 2013–2017, quantify the emission reductions associated with each measure using the bottom-up local emission inventory in 2013, aggregate the measures into seven categories, and conduct a series of CMAQ simulations to quantify the contribution of different factors to the PM2.5 changes. We found that, although changes in meteorological conditions partly explain the improved PM2.5 air quality in Beijing in 2017 compared to 2013 (3.8  m−3, 12.1 % of total), the rapid decrease in PM2.5 concentrations in Beijing during 2013–2017 was dominated by local (20.6  m−3, 65.4 %) and regional (7.1  m−3, 22.5 %) emission reductions. The seven categories of emission control measures, i.e., Coal-fired boiler control, Clean fuels in the residential sector, Optimized industrial structure, Fugitive dust control, Vehicle emission control, Improved end-of-pipe control, and Integrated treatment of VOCs, reduced the PM2.5 concentrations in Beijing by 5.9, 5.3, 3.2, 2.3, 1.9, 1.8, and 0.2  m−3, respectively, during 2013–2017. We also found that if the meteorological conditions in 2017 had remained the same as those in 2016, the annual mean PM2.5 concentrations would have increased from 58  m−3 to 63  m−3, exceeding the target established in the APPCAP. Despite the remarkable impacts from meteorological condition changes, local and regional emission reductions still played dominant roles in the PM2.5 decrease in Beijing during 2016–2017, and Clean fuels in the residential sector, Coal-fired boiler control, and Optimized industrial structure were the three most effective local measures (contributing reductions of 2.1, 1.9 and 1.5  m−3, respectively). Our study confirms the effectiveness of clean air actions in Beijing and its surrounding regions and reveals that a new generation of control measures and strengthened regional joint emission control measures should be implemented for continued air quality improvement in Beijing because the major emitting sources have changed since the implementation of the clean air actions.

scholarly journals Development of a vehicle emission inventory with high temporal–spatial resolution based on NRT traffic data and its impact on air pollution in Beijing – Part 2: Impact of vehicle emission on urban air quality

2016 ◽  
Vol 16 (5) ◽  
pp. 3171-3184 ◽  
Author(s):  
Jianjun He ◽  
Lin Wu ◽  
Hongjun Mao ◽  
Hongli Liu ◽  
Boyu Jing ◽  
...  
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Spatial Resolution ◽  
Emission Inventory ◽  
Emission Factors ◽  
Pollutant Emissions ◽  
Vehicle Emission ◽  
Traffic Data ◽  
Near Surface ◽  
The Impact

Abstract. A companion paper developed a vehicle emission inventory with high temporal–spatial resolution (HTSVE) with a bottom-up methodology based on local emission factors, complemented with the widely used emission factors of COPERT model and near-real-time (NRT) traffic data on a specific road segment for 2013 in urban Beijing (Jing et al., 2016), which is used to investigate the impact of vehicle pollution on air pollution in this study. Based on the sensitivity analysis method of switching on/off pollutant emissions in the Chinese air quality forecasting model CUACE, a modelling study was carried out to evaluate the contributions of vehicle emission to the air pollution in Beijing's main urban areas in the periods of summer (July) and winter (December) 2013. Generally, the CUACE model had good performance of the concentration simulation of pollutants. The model simulation has been improved by using HTSVE. The vehicle emission contribution (VEC) to ambient pollutant concentrations not only changes with seasons but also changes with time. The mean VEC, affected by regional pollutant transports significantly, is 55.4 and 48.5 % for NO2 and 5.4 and 10.5 % for PM2.5 in July and December 2013 respectively. Regardless of regional transports, relative vehicle emission contribution (RVEC) to NO2 is 59.2 and 57.8 % in July and December 2013, while it is 8.7 and 13.9 % for PM2.5. The RVEC to PM2.5 is lower than the PM2.5 contribution rate for vehicle emission in total emission, which may be due to dry deposition of PM2.5 from vehicle emission in the near-surface layer occuring more easily than from elevated source emission.

scholarly journals Impact of Short-Term Emission Control Measures on Air Quality in Nanjing During the Jiangsu Development Summit

2021 ◽  
Vol 9 ◽  
Author(s):  
Haoran Zhang ◽  
Keqin Tang ◽  
Weihang Feng ◽  
Xintian Yan ◽  
Hong Liao ◽  
...  
Keyword(s):  
Air Quality ◽  
Emission Control ◽  
Sulfur Oxidation ◽  
Air Pollutant ◽  
Control Measures ◽  
Pollutant Emissions ◽  
Short Term ◽  
Production Regime ◽  
Oxidation Ratio ◽  
Emission Control Measures

This study analyzed the effectiveness of temporary emission control measures on air quality of Nanjing, China during the Jiangsu Development Summit (JDS). We employed a regional chemistry model WRF-Chem to simulate air pollutants in Nanjing and compared the results to surface observations and satellite retrievals. During the JDS, air pollutant emissions from industry and transportation sectors largely decreased by 50–67% due to the short-term emission control measures such as reducing coal combustions, shutting down factories, and partially limiting traffic. Benefiting from the emission control, the simulated concentrations of PM2.5, NO2, SO2, CO and VOCs in Nanjing decreased by 17%, 20%, 20%, 19%, and 15% respectively, consistent with the surface and satellite observations. However, both the observed and simulated O3 increased by 3–48% during the JDS, which was mainly due to the remarkable NOx emission reduction (26%) in the downtown of Nanjing where the O3 production regime was mainly VOC-controlled. In addition, the atmospheric oxidation capacity and further the sulfur oxidation ratio, were facilitated by the elevated O3, which led to variable mitigation efficiencies of different secondary PM2.5 compositions. Our study offers an opportunity for understanding the coordinated control of PM2.5 and O3 in typical city clusters, and can provide implications for future mitigation actions.

scholarly journals Bottom-Up Emission Inventory and Its Spatio-Temporal Distribution from Paved Road Dust Based on Field Investigation: A Case Study of Harbin, Northeast China

Atmosphere ◽  
2021 ◽  
Vol 12 (4) ◽  
pp. 449
Author(s):  
Lili Li ◽  
Kun Wang ◽  
Zhijian Sun ◽  
Weiye Wang ◽  
Qingliang Zhao ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
Emission Inventory ◽  
Road Dust ◽  
Field Investigation ◽  
Pollutant Emissions ◽  
County Level ◽  
Bottom Up ◽  
Spatial Allocation ◽  
Paved Road

Road dust is one of the primary sources of particulate matter which has implications for air quality, climate and health. With the aim of characterizing the emissions, in this study, a bottom-up approach of county level emission inventory from paved road dust based on field investigation was developed. An inventory of high-resolution paved road dust (PRD) emissions by monthly and spatial allocation at 1 km × 1 km resolution in Harbin in 2016 was compiled using accessible county level, seasonal data and local parameters based on field investigation to increase temporal-spatial resolution. The results demonstrated the total PRD emissions of TSP, PM10, and PM2.5 in Harbin were 270,207 t, 54,597 t, 14,059 t, respectively. The temporal variation trends of pollutant emissions from PRD was consistent with the characteristics of precipitation, with lower emissions in winter and summer, and higher emissions in spring and autumn. The spatial allocation of emissions has a strong association with Harbin’s road network, mainly concentrating in the central urban area compared to the surrounding counties. Through scenario analysis, positive control measures were essential and effective for PRD pollution. The inventory developed in this study reflected the level of fugitive dust on paved road in Harbin, and it could reduce particulate matter pollution with the development of mitigation strategies and could comply with air quality modelling requirements, especially in the frigid region of northeastern China.

scholarly journals Air quality improvement in a megacity: implications from 2015 Beijing Parade Blue pollution control actions

2017 ◽  
Vol 17 (1) ◽  
pp. 31-46 ◽  
Author(s):  
Wen Xu ◽  
Wei Song ◽  
Yangyang Zhang ◽  
Xuejun Liu ◽  
Lin Zhang ◽  
...  
Keyword(s):  
Quality Improvement ◽  
Air Quality ◽  
Control Period ◽  
Emission Control ◽  
Monitoring Network ◽  
Control Measures ◽  
Integrated Analysis ◽  
Air Quality Improvement ◽  
Emission Control Measures ◽  
Control Regions

Abstract. The implementation of strict emission control measures in Beijing and surrounding regions during the 2015 China Victory Day Parade provided a valuable opportunity to investigate related air quality improvements in a megacity. We measured NH3, NO2 and PM2.5 at multiple sites in and outside Beijing and summarized concentrations of PM2.5, PM10, NO2, SO2 and CO in 291 cities across China from a national urban air quality monitoring network between August and September 2015. Consistently significant reductions of 12–35 % for NH3 and 33–59 % for NO2 in different areas of Beijing during the emission control period (referred to as the Parade Blue period) were observed compared with measurements in the pre- and post-Parade Blue periods without emission controls. Average NH3 and NO2 concentrations at sites near traffic were strongly correlated and showed positive and significant responses to traffic reduction measures, suggesting that traffic is an important source of both NH3 and NOx in urban Beijing. Daily concentrations of PM2.5 and secondary inorganic aerosol (sulfate, ammonium and nitrate) at the urban and rural sites both decreased during the Parade Blue period. During (after) the emission control period, concentrations of PM2.5, PM10, NO2, SO2 and CO from the national city-monitoring network showed the largest decrease (increase) of 34–72 % (50–214 %) in Beijing, a smaller decrease (a moderate increase) of 1–32 % (16–44 %) in emission control regions outside Beijing and an increase (decrease) of 6–16 % (−2–7 %) in non-emission-control regions of China. Integrated analysis of modelling and monitoring results demonstrated that emission control measures made a major contribution to air quality improvement in Beijing compared with a minor contribution from favourable meteorological conditions during the Parade Blue period. These results show that controls of secondary aerosol precursors (NH3, SO2 and NOx) locally and regionally are key to curbing air pollution in Beijing and probably in other mega cities worldwide.

scholarly journals TNO-MACC_II emission inventory; a multi-year (2003–2009) consistent high-resolution European emission inventory for air quality modelling

2014 ◽  
Vol 14 (20) ◽  
pp. 10963-10976 ◽  
Author(s):  
J. J. P. Kuenen ◽  
A. J. H. Visschedijk ◽  
M. Jozwicka ◽  
H. A. C. Denier van der Gon
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
High Resolution ◽  
Emission Inventory ◽  
Point Sources ◽  
Air Quality Modelling ◽  
Emission Data ◽  
Data Set ◽  
Spatially Distributed ◽  
Reported Data

Abstract. Emissions to air are reported by countries to EMEP. The emissions data are used for country compliance checking with EU emission ceilings and associated emission reductions. The emissions data are also necessary as input for air quality modelling. The quality of these "official" emissions varies across Europe. As alternative to these official emissions, a spatially explicit high-resolution emission inventory (7 × 7 km) for UNECE-Europe for all years between 2003 and 2009 for the main air pollutants was made. The primary goal was to supply air quality modellers with the input they need. The inventory was constructed by using the reported emission national totals by sector where the quality is sufficient. The reported data were analysed by sector in detail, and completed with alternative emission estimates as needed. This resulted in a complete emission inventory for all countries. For particulate matter, for each source emissions have been split in coarse and fine particulate matter, and further disaggregated to EC, OC, SO4, Na and other minerals using fractions based on the literature. Doing this at the most detailed sectoral level in the database implies that a consistent set was obtained across Europe. This allows better comparisons with observational data which can, through feedback, help to further identify uncertain sources and/or support emission inventory improvements for this highly uncertain pollutant. The resulting emission data set was spatially distributed consistently across all countries by using proxy parameters. Point sources were spatially distributed using the specific location of the point source. The spatial distribution for the point sources was made year-specific. The TNO-MACC_II is an update of the TNO-MACC emission data set. Major updates included the time extension towards 2009, use of the latest available reported data (including updates and corrections made until early 2012) and updates in distribution maps.

scholarly journals Air Quality Improvement in a Megacity: Implications from 2015 Beijing Parade Blue Pollution-Control Actions

2016 ◽  
Author(s):  
Wen Xu ◽  
Wei Song ◽  
Yangyang Zhang ◽  
Xuejun Liu ◽  
Lin Zhang ◽  
...  
Keyword(s):  
Quality Improvement ◽  
Air Quality ◽  
Control Period ◽  
Emission Control ◽  
Monitoring Network ◽  
Control Measures ◽  
Integrated Analysis ◽  
Beijing City ◽  
Air Quality Improvement ◽  
Emission Control Measures

Abstract. The implementation of strict emission control measures in Beijing and surrounding regions during the 2015 China Victory Day Parade provided a valuable opportunity to investigate related air quality improvements in a megacity. We measured NH3, NO2 and PM2.5 at multiple sites in and outside Beijing and summarized concentrations of PM2.5, PM10, NO2, SO2 and CO in 291 cities across China from a national urban air quality monitoring network between August and September 2015. Consistently significant reductions of 12–35 % for NH3 and 33–59 % for NO2 in different areas of Beijing city during the emission control period (referred to as the Parade Blue period) were observed compared with measurements in the pre- and post-Parade Blue periods without emission controls. Average NH3 and NO2 concentrations at sites near traffic were strongly correlated and showed positive and significant responses to traffic reduction measures, suggesting that traffic is an important source of both NH3 and NOx in urban Beijing. Daily concentrations of PM2.5 and secondary inorganic aerosol (sulfate, ammonium, and nitrate) at the urban and rural sites both decreased during the Parade Blue period. Concentrations of PM2.5, PM10, NO2, SO2 and CO from the national city-monitoring network showed the largest decrease (34–72 %) in Beijing, a smaller decrease (1–32 %) in North China (excluding Beijing), and an increase (6–16 %) in other regions of China during the emission control period. Integrated analysis of modeling and monitoring results demonstrated that emission control measures made a major contribution to air quality improvement in Beijing compared with a minor contribution from favorable meteorological conditions during the Parade Blue period. These results show that controls of secondary aerosol precursors (NH3, SO2 and NOx) locally and regionally are key to curbing air pollution in Beijing and probably in other mega cities worldwide.

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