Simulated Sensitivity of Ozone Generation to Precursors in Beijing during a High O_(3) Episode

This study uses the WRF-Chem model combined with the empirical kinetic modeling method(EKMA curve)to study the compound pollution event in Beijing that happened in 13−23 May 2017.Sensitivity tests are conducted to analyze ozone sensitivity to its precursors,and to develop emission reduction measures.The results suggest that the model can accurately simulate the compound pollution process of photochemistry and haze.When VOCs and NOx were reduced by the same proportion,the effect of O_(3)reduction at peak time was more obvious,and the effect during daytime was more significant than at night.The degree of change in ozone was peak time>daytime average.When reducing or increasing the ratio of precursors by 25%at the same time,the effect of reducing 25%VOCs on the average ozone concentration reduction was most significant.The degree of change in ozone decreased with increasing altitude,the location of the ozone maximum change shifted westward,and its range narrowed.As the altitude increases,the VOCs-limited zone decreases,VOCs sensitivity decreases,NOx sensitivity increases.The controlled area changed from near-surface VOCs-limited to high-altitude NOx-limited.Upon examining the EKMA curve,we have found that suburban and urban are sensitive to VOCs.The sensitivity tests indicate that when VOCs in suburban are reduced about 60%,the O_(3)-1h concentration could reach the standard,and when VOCs of the urban decreased by about 50%,the O_(3)-1h concentration could reach the standard.Thus,these findings could provide references for the control of compound air pollution in Beijing.

Evolution of boundary layer ozone in Shijiazhuang,a suburban site on the North China Plain

The structure of the boundary layer affects the evolution of ozone(O3), and research into this structure will provide important insights for understanding photochemical pollution.In this study, we conducted a one-month observation(from June 15 to July 14, 2016) of the boundary layer meteorological factors as well as O3 and its precursors in Luancheng County,Shijiazhuang(37°53′N, 114°38′E). Our research showed that photochemical pollution in Shijiazhuang is serious, and the mean hourly maximum and mean 8-hr maximum O3 concentrations are 97.9 ± 26.1 and 84.4 ± 22.4 ppbV, respectively. Meteorological factors play a significant role in the formation of O3. High temperatures and southeasterly winds lead to elevated O3 values, and at moderate relative humidity(40%–50%) and medium boundary layer heights(1200–1500 m), O3 production sensitivity occurred in the transitional region between volatile organic compounds(VOC) and nitrogen oxides(NOx) limitations,and the O3 concentration was the highest. The vertical profiles of O3 were also measured by a tethered balloon. The results showed that a large amount of O3 was stored in the residual layer, and the concentration was positively correlated with the O3 concentration measured the previous day. During the daytime of the following day, the contribution of O3 stored in the residual layer to the boundary layer reached 27%± 7% on average.

Temporal Variation and Source Identification of Black Carbon at Lin'an and Longfengshan Regional Background Stations in China

Black carbon （BC） is a component of fine particulate matter （PM2.5）, associated with climate, weather, air quality, and people＇s health. However, studies on temporal variation of atmospheric BC concentration at background stations in China and its source area identification are lacking. In this paper, we use 2-yr BC observations from two background stations, Lin＇an （LAN） and Longfengshan （LFS）, to perform the investigation. The results show that the mean diurnal variation of BC has two significant peaks at LAN while different characteristics are found in the BC vari- ation at LFS, which are probably caused by the difference in emission source contributions. Seasonal variation of monthly BC shows double peaks at LAN but a single peak at LFS. The annual mean concentrations of BC at LAN and LFS decrease by 1.63 and 0.26 μg m 3 from 2009 to 2010, respectively. The annual background concentration of BC at LAN is twice higher than that at LFS. The major source of the LAN BC is industrial emission while the source of the LFS BC is residential emission. Based on transport climatology on a 7-day timescale, LAN and LFS stations are sensitive to surface emissions respectively in belt or approximately circular area, which are dominated by summer monsoon or colder land air flows in Northwest China. In addition, we statistically analyze the BC source regions by using BC observation and FLEXible PARTicle dispersion model （FLEXPART） simulation. In summer, the source regions of BC are distributed in the northwest and south of LAN and the southwest of LFS. Low BC concentration is closely related to air mass from the sea. In winter, the source regions of BC are concentrated in the west and south of LAN and the northeast of the threshold area of stot at LFS. The cold air mass in the northwest plays an important role in the purification of atmospheric BC. On a yearly scale, sources of BC are approximately from five provinces in the northwest/southeast of LAN and the west of LFS. These findings are helpful in reducing BC emission and con- trolling air pollution.

Influences of Meteorological Conditions on Interannual Variations of Particulate Matter Pollution during Winter in the Beijing–Tianjin–Hebei Area

To investigate the interannual variations of particulate matter （PM） pollution in winter, this paper examines the pollution characteristics of PM with aerodynamic diameters of less than 2.5 and 10 μm （i.e., PM2.5 and PM10）, and their relationship to meteorological conditions over the Beijing municipality, Tianjin municipality, and Hebei Province--an area called Jing-Jin-Ji （JJJ, hereinafter）-in December 2013-16. The meteorological conditions during this period are also analyzed. The regional average concentrations of PM2.5 （PM10） over the JJJ area during this period were 148.6 （236.4）, 100.1 （166.4）, 140.5 （204.5）, and 141.7 （203.1） μg m^-3, respectively. The high occurrence frequencies of cold air outbreaks, a strong Siberian high, high wind speeds and boundary layer height, and low temperature and relative humidity, were direct meteorological causes of the low PM concentration in December 2014. A combined analysis of PM pollution and meteorological conditions implied that control measures have resulted in an effective improvement in air quality. Using the same emissions inventory in December 2013-16, a modeling analysis showed emissions of PM2.5 to decrease by 12.7%, 8.6%, and 8.3% in December 2014, 2015, and 2016, respectively, each compared with the previous year, over the JJJ area.

Emission inventory evaluation using observations of regional atmospheric background stations of China

Any accurate simulation of regional air quality by numerical models entails accurate and up-to-date emissions data for that region.The INTEX-B2006 （I06）,one of the newest emission inventories recently popularly used in China and East Asia,has been assessed using the Community Multiscale Air Quality model and observations from regional atmospheric background stations of China.Comparisons of the model results with the observations for the species SO2,NO 2,O 3 and CO from the three regional atmospheric background stations of Shangdianzi,Longfengshan and Linan show that the model can basically capture the temporal characteristics of observations such as the monthly,seasonal and diurnal variance trends.Compared to the other three species,the simulated CO values were grossly underestimated by about two-third or one-half of the observed values,related to the uncertainty in CO emissions.Compared to the other two stations,Shangdianzi had poorer simulations,especially for SO2 and CO,which partly resulted from the site location close to local emission sources from the Beijing area;and the regional inventory used was not capable of capturing the influencing factors of strong regional sources on stations.Generally,the fact that summer gave poor simulation,especially for SO2 and O 3,might partly relate to poor simulations of meteorological fields such as temperature and wind.

Tracking a Severe Pollution Event in Beijing in December 2016 with the GRAPES–CUACE Adjoint Model

We traced the adjoint sensitivity of a severe pollution event in December 2016 in Beijing using the adjoint model of the GRAPES–CUACE（Global/Regional Assimilation and Prediction System coupled with the China Meteorological Administration Unified Atmospheric Chemistry Environmental Forecasting System）. The key emission sources and periods affecting this severe pollution event are analyzed. For comaprison, we define 2000 Beijing Time 3 December 2016 as the objective time when PM2.5 reached the maximum concentration in Beijing. It is found that the local hourly sensitivity coefficient amounts to a peak of 9.31 μg m^–3 just 1 h before the objective time, suggesting that PM2.5 concentration responds rapidly to local emissions. The accumulated sensitivity coefficient in Beijing is large during the 20-h period prior to the objective time, showing that local emissions are the most important in this period.The accumulated contribution rates of emissions from Beijing, Tianjin, Hebei, and Shanxi are 34.2%, 3.0%, 49.4%,and 13.4%, respectively, in the 72-h period before the objective time. The evolution of hourly sensitivity coefficient shows that the main contribution from the Tianjin source occurs 1–26 h before the objective time and its peak hourly contribution is 0.59 μg m^-3 at 4 h before the objective time. The main contributions of the Hebei and Shanxi emission sources occur 1–54 and 14–53 h, respectively, before the objective time and their hourly sensitivity coefficients both show periodic fluctuations. The Hebei source shows three sensitivity coefficient peaks of 3.45, 4.27, and 0.71 μg m^–3 at 4, 16, and 38 h before the objective time, respectively. The sensitivity coefficient of the Shanxi source peaks twice, with values of 1.41 and 0.64 μg m^–3 at 24 and 45 h before the objective time, respectively. Overall, the adjoint model is effective in tracking the crucial sources and key periods of emissions for the severe pollution event.