Qing Hou's research while affiliated with Chinese Academy of Meteorological Sciences and other places

After the Chinese government introduced a series of policies to strengthen the control of air pollution, the concentration of particulate matter has decreased, but the concentration of ozone has increased, and the problem of complex air pollution still exists, posing a serious threat to public health. Therefore, disentangling the health effect of multi-pollutants has been a long-discussed challenge in China. To evaluate the adverse effects of complex air pollution, a generalized additive model was used to assess the health risks of different pollution types in eight metropolises in different climates in China from 2013 to 2016. Instead of directly introducing multiple pollutant concentrations, we integrated the concentration levels of PM2.5, NO2, and O3 into a set of predictors by grouping methods and divided air pollution into three high single-pollutant types and four high multi-pollutant types to calculate mortality risk in different types. The comprehensive results showed that the impact of high multi-pollutant types on mortality risk was greater than that of high single-pollutant types. Throughout the study period, the high multi-pollutant type with high PM2.5, NO2, and O3 and the high multi-pollutant type with high PM2.5 and NO2 were more associated with death, and the highest RRs were 1.129 (1.080, 1.181) and 1.089 (1.066, 1.113), respectively. In addition, the pollution types that most threaten people are different in different cities. These differences may be related to different pollution conditions, pollutant composition, and indoor–outdoor activity patterns in different cities. Seasonally, the risk of complex air pollution is greater in most cities in the warm season than in the cold season. This may be caused by the modifying effects of high temperature on pollutants in addition to different indoor–outdoor activity patterns in different seasons. The results also show that calculating the effect of individual air pollutants separately and adding them together may lead to an overestimation of the combined effect. It further highlights the urgency and need for air pollution health research to move towards a multi-pollutant approach that considers air pollution as a whole in the context of atmospheric abatement and global warming.

Black carbon (BC) may have more adverse effects on human health than other constituents of PM2.5. The daily mean concentrations of BC in China are much higher than those in developed countries and are estimated to account for more than a quarter of global anthropogenic BC emissions. However, reports on the health effects of BC in China have been limited. Thus, a time-stratified case-crossover study was conducted to evaluate the impacts of BC on daily mortality risk in nine Chinese megacities from 2008-2016. Our results show that for all-cause mortality, when compared to the interquartile range (IQR) of BC concentration increased, odds ratios (ORs) were in the range of 1.01-1.06 (95% CIs: 0.99-1.10). For cardiovascular mortality, ORs were in the range of 1.02-1.07 (95% CIs: 1.003-1.12), and for respiratory mortality, ORs were in the range of 1.01-1.15 (95% CIs: 1.00-1.18). The effects of BC in the nine cities were robust after adjusting for PM2.5, or even became more prominent. Furthermore, BC had stronger effects in spring and winter in northern cities, whereas in mid-latitude cities, BC had stronger effects in the warm seasons. In southern cities, BC had stronger effects in the cool and dry seasons. Our findings support an association between residential exposure to BC and mortality and thus provide further evidence that BC negatively impacts human health and is helpful for decision-making.

Based on the geographic information system (GIS) software and the application of the black carbon (BC) and fine particulate matter ([Formula: see text]) ratio method, this paper analyzed and calculated the national BC distribution from 2015 to 2017 and evaluated the national human exposure to BC. The results showed that from 2015 to 2017, 2/3 of the national land area and nearly half of the population were exposed to 1-3 [Formula: see text], and the area and population exposed to a concentration less than 2 [Formula: see text] increased yearly, while the area and population exposed to a concentration higher than 9 [Formula: see text] decreased yearly. The estimated economic loss showed that 77.3% of the targeted districts or counties claimed a loss per square kilometer of 50 million Chinese Yuan (CNY) or less from the perspective of annual changes, and districts and counties in Beijing-Tianjin-Hebei and Hunan with annual losses between 50 and 500 million CNY showed an increasing trend. The BC ratio (the proportion of BC economic loss to GDP) of Beijing-Tianjin-Hebei and Hunan also showed an increasing trend yearly.

With the progress of air pollution control in China, the concentration of particulate matter has decreased, but the concentration of ozone has increased, the problem of complex air pollution has become more severe, posing a serious threat to public health. However, there is less study on the health effects of complex air pollution in China. Instead of introducing pollutant concentrations directly, we converted them into a set of predictors to prevent collinearity and other problems will occur when the concentrations of multiple correlated pollutants are introduced in general multi-pollution models. Based on different combinations of PM 2.5 , NO 2, and O 3 concentration levels, air pollutant constituent condition is divided into eight types, including three single-pollutant types and four multi-pollutant types. The health effects of different pollution types on mortality in eight typical Chinese cities from 2013 to 2016 were evaluated using a generalized additive model. The results from eight cities collectively indicate that multi-pollutant type leads to a higher impact on mortality risk than single-pollutant type. Type 7 with higher PM 2.5 , O 3 , and NO 2 and type 4 with higher PM 2.5 and NO 2 have a greater relative risk among them. In most northern cities, the multi-pollutant type has a higher mortality effect in the warm season, but the single-pollutant type with high PM 2.5 has a higher effect in the cold season. In southeastern cities, the multi-pollutant type had a higher mortality effect in both seasons. The results also showed that the excess risk of multi-pollutants was less than the simple sum of individual air pollutants effects, partially false conclusions would have been reached by ignoring the presence of interactions between air pollutants. The result further highlights the urgency and necessity of moving towards a multi-pollutant approach in air pollution health research under the background of atmospheric emission reduction and global warming.

We presented the development of the gaseous chemistry adjoint module of the meteorological-chemical model system GRAPES-CUACE (Global/Regional Assimilation and PrEdiction System coupled with CMA Unified Atmospheric Chemistry Environmental Forecasting System) on the basis of the previously constructed aerosol adjoint module. The latest version of the GRAPES-CUACE adjoint model mainly includes the adjoint of the physical and chemical processes, the adjoint of the transport processes, and the adjoint of interface programs, of both gas and aerosol. The adjoint implementation was validated for the full model, and adjoint results showed good agreement with brute force sensitivities. We also applied the newly developed adjoint model to the sensitivity analysis of an ozone episode occurred in Beijing on July 2, 2017, as well as the design of emission-reduction strategies for this episode. The relationships between the ozone concentration and precursor emissions were well captured by the adjoint model. It is indicated that for a case used here, the Beijing peak ozone concentration was influenced mostly by local emissions (6.2-24.3%), as well as by surrounding emissions, including Hebei (4.4-16.8%), Tianjin (1.8-6.6%), Shandong (1.8-2.6%), and Shanxi (<1%). In addition, reduction of NOx, VOCs, and CO emissions in these regions would effectively decrease the Beijing peak ozone concentration. This study highlights the capability of GRAPES-CUACE adjoint model in quantifying "emission-concentration" relationship and in providing guidance for environmental control policy.

Based on GIS (Geographic Information System) software, applied the black carbon (BC)and fine particulate matter ( PM 2.5 )concentration ratio method, this paper analyzed and calculated the national BC concentration distribution from 2015 to 2017, and evaluated the national human exposure of BC. The results show that from 2015 to 2017, 2/3 of the national land and nearly half of the population were exposed to the concentration range of 1-3 ug/m 3 , and the area and population exposed to the concentration below 2 ug/m 3 increased year by year, while the area and population exposed to the concentration above 9 ug/m 3 decreased year by year. The estimated results of economic loss show that 77.3% of the targeted districts or counties claimed a loss per square kilometer of 50 million RMB or less From the perspective of annual changes, districts and counties in Beijing-Tianjin-Hebei and Hunan with annual losses between 50 and 500 million RMB show an increasing trend. Meanwhile, the BC ratio (the proportion of black carbon economic loss to GDP) of Beijing-Tianjin-Hebei and Hunan also shows an increasing trend year by year.

In this study, a four-dimensional variational (4D-Var) data assimilation system was developed based on the GRAPES–CUACE (Global/Regional Assimilation and PrEdiction System – CMA Unified Atmospheric Chemistry Environmental Forecasting System) atmospheric chemistry model, GRAPES–CUACE adjoint model and L-BFGS-B (extended limited-memory Broyden–Fletcher–Goldfarb–Shanno) algorithm (GRAPES–CUACE-4D-Var) and was applied to optimize black carbon (BC) daily emissions in northern China on 4 July 2016, when a pollution event occurred in Beijing. The results show that the newly constructed GRAPES–CUACE-4D-Var assimilation system is feasible and can be applied to perform BC emission inversion in northern China. The BC concentrations simulated with optimized emissions show improved agreement with the observations over northern China with lower root-mean-square errors and higher correlation coefficients. The model biases are reduced by 20 %–46 %. The validation with observations that were not utilized in the assimilation shows that assimilation makes notable improvements, with values of the model biases reduced by 1 %–36 %. Compared with the prior BC emissions, which are based on statistical data of anthropogenic emissions for 2007, the optimized emissions are considerably reduced. Especially for Beijing, Tianjin, Hebei, Shandong, Shanxi and Henan, the ratios of the optimized emissions to prior emissions are 0.4–0.8, indicating that the BC emissions in these highly industrialized regions have greatly reduced from 2007 to 2016. In the future, further studies on improving the performance of the GRAPES–CUACE-4D-Var assimilation system are still needed and are important for air pollution research in China.

Abstract. The adjoint method is known for its efficient calculation of sensitive information. After decades of development, assimilation technology based on adjoint method has gradually become an important tool for emission inversion. On the basis of GRAPES-CUACE aerosol adjoint model, and combined with the optimization algorithm and pollutants observations, the GRAPES-CUACE 3D variational (GRAPES-CUACE-3D-Var) assimilation system was further developed, and was used in the inversion of BC emissions in Beijing-Tianjin-Hebei region. The results show that the newly constructed GRAPES-CUACE-3D-Var assimilation system is reasonable and reliable, and can be applied to the emission inversion in Beijing-Tianjin-Hebei region. Compared to the simulations using the a priori BC emissions, the model simulations driven by the a posterior BC emissions in two inversion schemes are in better agreement with measurements. The correlation coefficient between the simulations and the observations is increased from 0.2 before the inversion to 0.7 and 0.64, respectively, and the NMSE is reduced from 0.38 to 0.22 and 0.24, respectively, and the NMB is decreased from 51.53 % to 43.37 % and 40.90 %, respectively, in the two inversion schemes. The spatial distributions of the a posterior BC emissions in the two inversion schemes are consistent with the distributions of the a priori BC emissions. The high-value areas are mainly located in the south of Beijing, Tianjin, central and southern Hebei, and northern Shandong. On the whole, the inversion scheme with a large observation ratio has better optimization effect. The observation information of the target time has a great influence on the a posterior BC emissions in a short period before the target time, and the influence decreases with the reverse time sequence.

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 PM2.5 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 PM2.5 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 PM2.5 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 PM2.5 concentration peaks, and the contribution of emissions from Hebei province to the first PM2.5 concentration peak (43.6 %) is greater than that to the second PM2.5 concentration peak (41.5 %). The second most influential province for the 05:00 LT PM2.5 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 PM2.5 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 PM2.5 air quality.