Gao, Meng

2021
Yan Zhang, Yu Zhao, Meng Gao, Xin Bo, and Chris P. Nielsen. 2021. “Air quality and health benefits from ultra-low emission control policy indicated by continuous emission monitoring: a case study in the Yangtze River Delta region, China.” Atmospheric Chemistry and Physics, 21, Pp. 6411–6430. Publisher's VersionAbstract
To evaluate the improved emission estimates from online monitoring, we applied the Models-3/CMAQ (Community Multiscale Air Quality) system to simulate the air quality of the Yangtze River Delta (YRD) region using two emission inventories with and without incorporated data from continuous emission monitoring systems (CEMSs) at coal-fired power plants (cases 1 and 2, respectively). The normalized mean biases (NMBs) between the observed and simulated hourly concentrations of SO2, NO2, O3, and PM2.5 in case 2 were −3.1 %, 56.3 %, −19.5 %, and −1.4 %, all smaller in absolute value than those in case 1 at 8.2 %, 68.9 %, −24.6 %, and 7.6 %, respectively. The results indicate that incorporation of CEMS data in the emission inventory reduced the biases between simulation and observation and could better reflect the actual sources of regional air pollution. Based on the CEMS data, the air quality changes and corresponding health impacts were quantified for different implementation levels of China's recent “ultra-low” emission policy. If the coal-fired power sector met the requirement alone (case 3), the differences in the simulated monthly SO2, NO2, O3, and PM2.5 concentrations compared to those of case 2, our base case for policy comparisons, would be less than 7 % for all pollutants. The result implies a minor benefit of ultra-low emission control if implemented in the power sector alone, which is attributed to its limited contribution to the total emissions in the YRD after years of pollution control (11 %, 7 %, and 2 % of SO2, NOX, and primary particle matter (PM) in case 2, respectively). If the ultra-low emission policy was enacted at both power plants and selected industrial sources including boilers, cement, and iron and steel factories (case 4), the simulated SO2, NO2, and PM2.5concentrations compared to the base case would be 33 %–64 %, 16 %–23 %, and 6 %–22 % lower, respectively, depending on the month (January, April, July, and October 2015). Combining CMAQ and the Integrated Exposure Response (IER) model, we further estimated that 305 deaths and 8744 years of life loss (YLL) attributable to PM2.5 exposure could be avoided with the implementation of the ultra-low emission policy in the power sector in the YRD region. The analogous values would be much higher, at 10 651 deaths and 316 562 YLL avoided, if both power and industrial sectors met the ultra-low emission limits. In order to improve regional air quality and to reduce human health risk effectively, coordinated control of multiple sources should be implemented, and the ultra-low emission policy should be substantially expanded to major emission sources in industries other than the power industry.
Shaojie Song, Tao Ma, Yuzhong Zhang, Lu Shen, Pengfei Liu, Ke Li, Shixian Zhai, Haotian Zheng, Meng Gao, Jonathan M. Moch, Fengkui Duan, Kebin He, and Michael B. McElroy. 2021. “Global modeling of heterogeneous hydroxymethanesulfonate chemistry.” Atmospheric Chemistry and Physics, 21, 1, Pp. 457–481. Publisher's VersionAbstract
Hydroxymethanesulfonate (HMS) has recently been identified as an abundant organosulfur compound in aerosols during winter haze episodes in northern China. It has also been detected in other regions although the concentrations are low. Because of the sparse field measurements, the global significance of HMS and its spatial and seasonal patterns remain unclear. Here, we modify and add to the implementation of HMS chemistry in the GEOS-Chem chemical transport model and conduct multiple global simulations. The model accounts for cloud entrainment and gas–aqueous mass transfer within the rate expressions for heterogeneous sulfur chemistry. Our simulations can generally reproduce quantitative HMS observations from Beijing and show that East Asia has the highest HMS concentration, followed by Europe and North America. The simulated HMS shows a seasonal pattern with higher values in the colder period. Photochemical oxidizing capacity affects the competition of formaldehyde with oxidants (such as ozone and hydrogen peroxide) for sulfur dioxide and is a key factor influencing the seasonality of HMS. The highest average HMS concentration (1–3 µg m−3) and HMS ∕ sulfate molar ratio (0.1–0.2) are found in northern China in winter. The simulations suggest that aqueous clouds act as the major medium for HMS chemistry while aerosol liquid water may play a role if its rate constant for HMS formation is greatly enhanced compared to cloud water.
Peter Sherman, Meng Gao, Shaojie Song, Alex T. Archibald, Nathan Luke Abraham, Jean-François Lamarque, Drew Shindell, Gregory Faluvegi, and Michael B. McElroy. 2021. “Sensitivity of modeled Indian Monsoon to Chinese and Indian aerosol emissions.” Atmospheric Chemistry and Physics, 21, Pp. 3593–3605. Publisher's VersionAbstract
The South Asian summer monsoon supplies over 80 % of India's precipitation. Industrialization over the past few decades has resulted in severe aerosol pollution in India. Understanding monsoonal sensitivity to aerosol emissions in general circulation models (GCMs) could improve predictability of observed future precipitation changes. The aims here are (1) to assess the role of aerosols on India's monsoon precipitation and (2) to determine the roles of local and regional emissions. For (1), we study the Precipitation Driver Response Model Intercomparison Project experiments. We find that the precipitation response to changes in black carbon is highly uncertain with a large intermodel spread due in part to model differences in simulating changes in cloud vertical profiles. Effects from sulfate are clearer; increased sulfate reduces Indian precipitation, a consistency through all of the models studied here. For (2), we study bespoke simulations, with reduced Chinese and/or Indian emissions in three GCMs. A significant increase in precipitation (up to ~ 20 %) is found only when both countries' sulfur emissions are regulated, which has been driven in large part by dynamic shifts in the location of convective regions in India. These changes have the potential to restore a portion of the precipitation losses induced by sulfate forcing over the last few decades.
2020
Meng Gao, Zirui Liu, Bo Zheng, Dongsheng Ji, Peter Sherman, Shaojie Song, Jinyuan Xin, Cheng Liu, Yuesi Wang, Qiang Zhang, Jia Xing, Jingkun Jiang, Zifa Wang, Gregory R. Carmichael, and Michael B. McElroy. 2020. “China's emission control strategies have suppressed unfavorable influences of climate on wintertime PM2.5 concentrations in Beijing since 2002.” Atmospheric Chemistry and Physics, 20, 3, Pp. 1497-1505. Publisher's VersionAbstract
Severe wintertime PM2.5 pollution in Beijing has been receiving increasing worldwide attention, yet the decadal variations remain relatively unexplored. Combining field measurements and model simulations, we quantified the relative influences of anthropogenic emissions and meteorological conditions on PM2.5 concentrations in Beijing over the winters of 2002–2016. Between the winters of 2011 and 2016, stringent emission control measures resulted in a 21 % decrease in mean mass concentrations of PM2.5 in Beijing, with 7 fewer haze days per winter on average. Given the overestimation of PM2.5 by the model, the effectiveness of stringent emission control measures might have been slightly overstated. With fixed emissions, meteorological conditions over the study period would have led to an increase in haze in Beijing, but the strict emission control measures have suppressed the unfavorable influences of the recent climate. The unfavorable meteorological conditions are attributed to the weakening of the East Asia winter monsoon associated particularly with an increase in pressure associated with the Aleutian Low.
ACP_Full_Text
Meng Gao, Jinhui Gao, Bin Zhu, Rajesh Kumar, Xiao Lu, Shaojie Song, Yuzhong Zhang, Beixi Jia, Peng Wang, Gufran Beig, Jianlin Hu, Qi Ying, Hongliang Zhang, Peter Sherman, and Michael B. McElroy. 2020. “Ozone pollution over China and India: seasonality and sources.” Atmospheric Chemistry and Physics, 20, 7, Pp. 4399-4414. Publisher's VersionAbstract
A regional fully coupled meteorology–chemistry model, Weather Research and Forecasting model with Chemistry (WRF-Chem), was employed to study the seasonality of ozone (O3) pollution and its sources in both China and India. Observations and model results suggest that O3 in the North China Plain (NCP), Yangtze River Delta (YRD), Pearl River Delta (PRD), and India exhibit distinctive seasonal features, which are linked to the influence of summer monsoons. Through a factor separation approach, we examined the sensitivity of O3 to individual anthropogenic, biogenic, and biomass burning emissions. We found that summer O3 formation in China is more sensitive to industrial and biogenic sources than to other source sectors, while the transportation and biogenic sources are more important in all seasons for India. Tagged simulations suggest that local sources play an important role in the formation of the summer O3 peak in the NCP, but sources from Northwest China should not be neglected to control summer O3 in the NCP. For the YRD region, prevailing winds and cleaner air from the ocean in summer lead to reduced transport from polluted regions, and the major source region in addition to local sources is Southeast China. For the PRD region, the upwind region is replaced by contributions from polluted PRD as autumn approaches, leading to an autumn peak. The major upwind regions in autumn for the PRD are YRD (11 %) and Southeast China (10 %). For India, sources in North India are more important than sources in the south. These analyses emphasize the relative importance of source sectors and regions as they change with seasons, providing important implications for O3 control strategies.
ACP_Full_Text
2019
Peter Sherman, Meng Gao, Shaojie Song, Patrick Ohiomoba, Alex Archibald, and Michael B. McElroy. 2019. “The influence of dynamics and emissions changes on China’s wintertime haze.” Journal of Applied Meteorology and Climatology, 58, Pp. 1603-1611. Publisher's VersionAbstract

Haze days induced by aerosol pollution in North and East China have posed a persistent and growing problem over the past few decades. These events are particularly threatening to densely-populated cities such as Beijing. While the sources of this pollution are predominantly anthropogenic, natural climate variations may also play a role in allowing for atmospheric conditions conducive to formation of severe haze episodes over populated areas. Here, an investigation is conducted into the effects of changes in global dynamics and emissions on air quality in China’s polluted regions using 35 simulations developed from the Community Earth Systems Model Large Ensemble (CESM LENS) run over the period 1920-2100. It is shown that internal variability significantly modulates aerosol optical depth (AOD) over China; it takes roughly a decade for the forced response to balance the effects from internal variability even in China’s most polluted regions. Random forest regressions are used to accurately model (R2 > 0.9) wintertime AOD using just climate oscillations, the month of the year and emissions. How different phases of each oscillation affect aerosol loading are projected using these regressions. AOD responses are identified for each oscillation, with particularly strong responses from El Niño-Southern Oscillation (ENSO) and the Pacific Decadal Oscillation (PDO). As ENSO can be projected a few months in advance and improvements in linear inverse modelling (LIM) may yield a similar predictability for the PDO, results of this study offer opportunities to improve the predictability of China’s severe wintertime haze events, and to inform policy options that could mitigate subsequent health impacts.

JAMC paper
S.J. Song, M. Gao, W.Q. Xu, Y.L. Sun, D.R. Worsnop, J.T. Jayne, Y.Z. Zhang, L. Zhu, M. Li, Z. Zhou, C.L. Cheng, Y.B. Lv, Y. Wang, W. Peng, X.B. Xu, N. Lin, Y.X. Wang, S.X. Wang, J. W. Munger, D. Jacob, and M.B. McElroy. 2019. “Possible heterogeneous hydroxymethanesulfonate (HMS) chemistry in northern China winter haze and implications for rapid sulfate formation.” Atmospheric Chemistry and Physics, 19, Pp. 1357-1371. Publisher's VersionAbstract
The chemical mechanisms responsible for rapid sulfate production, an important driver of winter haze formation in northern China, remain unclear. Here, we propose a potentially important heterogeneous hydroxymethanesulfonate (HMS) chemical mechanism. Through analyzing field measurements with aerosol mass spectrometry, we show evidence for a possible significant existence in haze aerosols of organosulfur primarily as HMS, misidentified as sulfate in previous observations. We estimate that HMS can account for up to about one-third of the sulfate concentrations unexplained by current air quality models. Heterogeneous production of HMS by SO2 and formaldehyde is favored under northern China winter haze conditions due to high aerosol water content, moderately acidic pH values, high gaseous precursor levels, and low temperature. These analyses identify an unappreciated importance of formaldehyde in secondary aerosol formation and call for more research on sources and on the chemistry of formaldehyde in northern China winter.
ACP paper
Meng Gao, Peter Sherman, Shaojie Song, Yueyue Yu, Zhiwei Wu, and Michael B. McElroy. 2019. “Seasonal prediction of Indian wintertime aerosol pollution using the Ocean Memory Effect.” Science Advances, 5, 7. Publisher's VersionAbstract
As China makes every effort to control air pollution, India emerges as the world’s most polluted country, receiving worldwide attention with frequent winter (boreal) haze extremes. In this study, we found that the interannual variability of wintertime aerosol pollution over northern India is regulated mainly by a combination of El Niño and the Antarctic Oscillation (AAO). Both El Niño sea surface temperature (SST) anomalies and AAO-induced Indian Ocean Meridional Dipole SST anomalies can persist from autumn to winter, offering prospects for a prewinter forecast of wintertime aerosol pollution over northern India. We constructed a multivariable regression model incorporating El Niño and AAO indices for autumn to predict wintertime AOD. The prediction exhibits a high degree of consistency with observation, with a correlation coefficient of 0.78 (P < 0.01). This statistical model could allow the Indian government to forecast aerosol pollution conditions in winter and accordingly improve plans for pollution control.
Science_Advances_Paper.pdf
Shaojie Song, Athanasios Nenes, Meng Gao, Yuzhong Zhang, Pengfei Liu, Jingyuan Shao, Dechao Ye, Weiqi Xu, Lu Lei, Yele Sun, Baoxian Liu, Shuxiao Wang, and Michael B. McElroy. 2019. “Thermodynamic modeling suggests declines in water uptake and acidity of inorganic aerosols in Beijing winter haze events during 2014/2015–2018/2019.” Environmental Science & Technology Letters, 6, Pp. 752-760. Publisher's VersionAbstract
During recent years, aggressive air pollution mitigation measures in northern China have resulted in considerable changes in gas and aerosol chemical composition. But it is unclear whether aerosol water content and acidity respond to these changes. The two parameters have been shown to affect heterogeneous production of winter haze aerosols. Here, we performed thermodynamic equilibrium modeling using chemical and meteorological data observed in urban Beijing for four recent winter seasons and quantified the changes in the mass growth factor and pH of inorganic aerosols. We focused on high relative humidity (>60%) conditions when submicron particles have been shown to be in the liquid state. From 2014/2015 to 2018/2019, the modeled mass growth factor decreased by about 9%–17% due to changes in aerosol compositions (more nitrate and less sulfate and chloride), and the modeled pH increased by about 0.3–0.4 unit mainly due to rising ammonia. A buffer equation is derived from semivolatile ammonia partitioning, which helps understand the sensitivity of pH to meteorological and chemical variables. The findings provide implications for evaluating the potential chemical feedback in secondary aerosol production and the effectiveness of ammonia control as a measure to alleviate winter haze.
2018
Shaojie Song, Meng Gao, Weiqi Xu, Jingyuan Shao, Guoliang Shi, Shuxiao Wang, Yuxuan Wang, Yele Sun, and Michael McElroy. 2018. “Fine particle pH for Beijing winter haze as inferred from different thermodynamic equilibrium models.” Atmospheric Chemistry and Physics, 18, Pp. 7423-7438. Publisher's VersionAbstract
pH is an important property of aerosol particles but is difficult to measure directly. Several studies have estimated the pH values for fine particles in North China winter haze using thermodynamic models (i.e., E-AIM and ISORROPIA) and ambient measurements. The reported pH values differ widely, ranging from close to 0 (highly acidic) to as high as 7 (neutral). In order to understand the reason for this discrepancy, we calculated pH values using these models with different assumptions with regard to model inputs and particle phase states. We find that the large discrepancy is due primarily to differences in the model assumptions adopted in previous studies. Calculations using only aerosol phase composition as inputs (i.e., reverse mode) are sensitive to the measurement errors of ionic species and inferred pH values exhibit a bimodal distribution with peaks between −2 and 2 and between 7 and 10. Calculations using total (gas plus aerosol phase) measurements as inputs (i.e., forward mode) are affected much less by the measurement errors, and results are thus superior to those obtained from the reverse mode calculations. Forward mode calculations in this and previous studies collectively indicate a moderately acidic condition (pH from about 4 to about 5) for fine particles in North China winter haze, indicating further that ammonia plays an important role in determining this property. The differences in pH predicted by the forward mode E-AIM and ISORROPIA calculations may be attributed mainly to differences in estimates of activity coefficients for hydrogen ions. The phase state assumed, which can be either stable (solid plus liquid) or metastable (only liquid), does not significantly impact pH predictions of ISORROPIA.
ACP paper.pdf
Meng Gao, Gufran Beig, Shaojie Song, Hongliang Zhang, Jianlin Hu, Qi Ying, Fengchao Liang, Yang Liu, Haikun Wang, Xiao Lu, Tong Zhu, Gregory Carmichael, Chris P. Nielsen, and Michael B. McElroy. 2018. “The impact of power generation emissions on ambient PM2.5 pollution and human health in China and India.” Environment International, 121, Part 1, Pp. 250-259. Publisher's VersionAbstract

Emissions from power plants in China and India contain a myriad of fine particulate matter (PM2.5, PM≤2.5 micrometers in diameter) precursors, posing significant health risks among large, densely settled populations. Studies isolating the contributions of various source classes and geographic regions are limited in China and India, but such information could be helpful for policy makers attempting to identify efficient mitigation strategies. We quantified the impact of power generation emissions on annual mean PM2.5 concentrations using the state-of-the-art atmospheric chemistry model WRF-Chem (Weather Research Forecasting model coupled with Chemistry) in China and India. Evaluations using nationwide surface measurements show the model performs reasonably well. We calculated province-specific annual changes in mortality and life expectancy due to power generation emissions generated PM2.5 using the Integrated Exposure Response (IER) model, recently updated IER parameters from Global Burden of Disease (GBD) 2015, population data, and the World Health Organization (WHO) life tables for China and India. We estimate that 15 million (95% Confidence Interval (CI): 10 to 21 million) years of life lost can be avoided in China each year and 11 million (95% CI: 7 to 15 million) in India by eliminating power generation emissions. Priorities in upgrading existing power generating technologies should be given to Shandong, Henan, and Sichuan provinces in China, and Uttar Pradesh state in India due to their dominant contributions to the current health risks.

 

Meng Gao, Yihui Ding, Shaojie Song, Xiao Lu, Xinyu Chen, and Michael B. McElroy. 2018. “Secular decrease of wind power potential in India associated with warming Indian Ocean.” Science Advances, 4, 12. Publisher's VersionAbstract
The Indian government has set an ambitious target for future renewable power generation, including 60 GW of cumulative wind power capacity by 2022. However, the benefits of these substantial investments are vulnerable to the changing climate. On the basis of hourly wind data from an assimilated meteorology reanalysis dataset covering the 1980–2016 period, we show that wind power potential may have declined secularly over this interval, particularly in western India. Surface temperature data confirm that significant warming occurred in the Indian Ocean over the study period, leading to modulation of high pressure over the ocean. A multivariable linear regression model incorporating the pressure gradient between the Indian Ocean and the Indian subcontinent can account for the interannual variability of wind power. A series of numerical sensitivity experiments confirm that warming in the Indian Ocean contributes to subsidence and dampening of upward motion over the Indian continent, resulting potentially in weakening of the monsoonal circulation and wind speeds over India.
Science Advances paper.pdf