Atmospheric Emissions

2021
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. 2021. “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.
Peter Sherman, Shaojie Song, Xinyu Chen, and Michael B. McElroy. 2021. “Projected changes in wind power potential over China and India in high resolution climate models.” Environmental Research Letters, 16, 3. Publisher's VersionAbstract
As more countries commit to emissions reductions by midcentury to curb anthropogenic climate change, decarbonization of the electricity sector becomes a first-order task in reaching this goal. Renewables, particularly wind and solar power, will be predominant components of this transition. How availability of the wind and solar resource will change in the future in response to regional climate changes is an important and underdiscussed topic of the decarbonization process. Here, we study changes in potential for wind power in China and India, evaluating prospectively until the year 2060. To do this, we study a downscaled, high-resolution multimodel ensemble of CMIP5 models under high and low emissions scenarios. While there is some intermodel variability, we find that spatial changes are generally consistent across models, with decreases of up to 965 (a 1% change) and 186 TWh (a 2% change) in annual electricity generation potential for China and India, respectively. Compensating for the declining resource are weakened seasonal and diurnal variabilities, allowing for easier large-scale wind power integration. We conclude that while the ensemble indicates available wind resource over China and India will decline slightly in the future, there remains enormous potential for significant wind power expansion, which must play a major role in carbon neutral aspirations.
Qing Yang, Hewen Zhou, Pietro Bartocci, Francesco Fantozzi, Ondřej Mašek, Foster Agblevor, Zhiyu Wei, Haiping Yang, Hanping Chen, Xi Lu, Guoqing Chen, Chuguang Zheng, Chris P. Nielsen, and Michael B. McElroy. 2021. “Prospective contributions of biomass pyrolysis to China’s 2050 carbon reduction and renewable energy goals.” Nature Communications. Publisher's VersionAbstract
Deployment of negative emission technologies needs to start immediately if we are to avoid overshooting international carbon targets, reduce negative climate impacts, and minimize costs of emission mitigation. Actions in China, given its importance for the global anthropogenic carbon budget, can be decisive. While bioenergy with carbon capture and storage (BECCS) may need years to mature, this study focuses on developing a ready-to-implement biomass intermediate pyrolysis poly-generation (BIPP) technology to produce a potentially stable form of biochar, a medium for carbon storage, and to provide a significant source of valuable biofuels, especially pyrolysis gas. Combining the experimental data with hybrid models, the results show that a BIPP system can be profitable without subsidies: its national deployment could contribute to a 68% reduction of carbon emissions per unit of GDP in 2030 compared to 2005 and could result additionally in a reduction in air pollutant emissions. With 73% of national crop residues converted to biochar and other biofuels in the near term (2020 to 2030), the cumulative greenhouse gas (GHG) reduction could reach up to 5653 Mt CO2-eq by 2050, which could contribute 9-20% of the global GHG emission reduction goal for BECCS (28-65 Gt CO2-eq in IPCC’s 1.5 °C pathway), and nearly 2633 Mt more than that projected for BECCS alone. The national BIPP development strategy is developed on a provincial scale based on a regional economic and life-cycle analysis. 
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
X. Lu, L. Zhang, T. Wu, M. S. Long, J. Wang, D.J. Jacob, F. Zhang, J. Zhang, S. D. Eastham, L. Hu, L. Zhu, X. Liu, and M Wei. 2020. “Development of the global atmospheric general circulation-chemistry model BCC-GEOS-Chem v1.0: model description and evaluation.” Geoscientific Model Development, 13, 9, Pp. 3817–3838. Publisher's VersionAbstract
Chemistry plays an indispensable role in investigations of the atmosphere; however, many climate models either ignore or greatly simplify atmospheric chemistry, limiting both their accuracy and their scope. We present the development and evaluation of the online global atmospheric chemical model BCC-GEOS-Chem v1.0, coupling the GEOS-Chem chemical transport model (CTM) as an atmospheric chemistry component in the Beijing Climate Center atmospheric general circulation model (BCC-AGCM). The GEOS-Chem atmospheric chemistry component includes detailed troposphericHOx–NOx–volatile organic compounds–ozone–bromine–aerosol chemistry and online dry and wet deposition schemes. We then demonstrate the new capabilities of BCC-GEOS-Chem v1.0 relative to the base BCC-AGCM model through a 3-year (2012–2014) simulation with anthropogenic emissions from the Community Emissions Data System (CEDS) used in the Coupled Model Intercomparison Project Phase 6 (CMIP6). The model captures well the spatial distributions and seasonal variations in tropospheric ozone, with seasonal mean biases of 0.4–2.2 ppbv at 700–400 hPa compared to satellite observations and within 10 ppbv at the surface to 500 hPa compared to global ozonesonde observations. The model has larger high-ozone biases over the tropics which we attribute to an overestimate of ozone chemical production. It underestimates ozone in the upper troposphere which is likely due either to the use of a simplified stratospheric ozone scheme or to biases in estimated stratosphere–troposphere exchange dynamics. The model diagnoses the global tropospheric ozone burden, OH concentration, and methane chemical lifetime to be 336 Tg, 1.16×106 molecule cm−3, and 8.3 years, respectively, which is consistent with recent multimodel assessments. The spatiotemporal distributions of NO2, CO, SO2, CH2O, and aerosol optical depth are generally in agreement with satellite observations. The development of BCC-GEOS-Chem v1.0 represents an important step for the development of fully coupled earth system models (ESMs) in China.
Haikun Wang, Xiaojing He, Xinyu Liang, Ernani F. Choma, Yifan Liu, Li Shan, Haotian Zheng, Shaojun Zhang, Chris P. Nielsen, Shuxiao Wang, Ye Wu, and John S. Evans. 2020. “Health benefits of on-road transportation pollution control programs in China.” Proceedings of the National Academy of Sciences, Sept 2020, 201921271. Publisher's VersionAbstract
China started to implement comprehensive measures to mitigate traffic pollution at the end of 1990s, but the comprehensive effects, especially on ambient air quality and public health, have not yet been systematically evaluated. In this study, we analyze the effects of vehicle emission control measures on ambient air pollution and associated deaths attributable to long-term exposures of fine particulate matter (PM2.5) and O3 based on an integrated research framework that combines scenario analysis, air quality modeling, and population health risk assessment. We find that the total impact of these control measures was substantial. Vehicular emissions during 1998–2015 would have been 2–3 times as large as they actually were, had those measures not been implemented. The national population-weighted annual average concentrations of PM2.5 and O3 in 2015 would have been higher by 11.7 μg/m3 and 8.3 parts per billion, respectively, and the number of deaths attributable to 2015 air pollution would have been higher by 510 thousand (95% confidence interval: 360 thousand to 730 thousand) without these controls. Our analysis shows a concentration of mortality impacts in densely populated urban areas, motivating local policymakers to design stringent vehicle emission control policies. The results imply that vehicle emission control will require policy designs that are more multifaceted than traditional controls, primarily represented by the strict emission standards, with careful consideration of the challenges in coordinated mitigation of both PM2.5 and O3 in different regions, to sustain improvement in air quality and public health given continuing swift growth in China’s vehicle population.
Xueli Zhao, Xiaofang Wu, Chenghe Guan, Rong Ma, Chris P. Nielsen, and Bo Zhang. 2020. “Linking agricultural GHG emissions to global trade network.” Earth's Future, 8, 3. Publisher's VersionAbstract
As part of the climate policy to meet the 2‐degrees Celsius (2 °C) target, actions in all economic sectors, including agriculture, are required to mitigate global greenhouse gas (GHG) emissions. While there has been an ever‐increasing focus on agricultural greenhouse gas (AGHG) emissions, limited attention has been paid to their economic drivers in the globalized world economy and related mitigation potentials. This paper makes a first attempt to trace AGHG emissions via global trade networks using a multi‐regional input‐output model and a complex network model. Over one third of global AGHG emissions in 2012 can be linked with products traded internationally, of which intermediate trade and final trade contribute 64.2% and 35.8%, respectively. Japan, the USA, Germany, the UK, and Hong Kong are the world's five largest net importers of embodied emissions, while Ethiopia, Australia, Pakistan, India and Argentina are the five largest net exporters. Some hunger‐afflicted developing countries in Asia and Africa are important embodied emission exporters, due to their large‐scale exports of agricultural products. Trade‐related virtual AGHG emission transfers shape a highly heterogenous network, due to the coexistence of numerous peripheral economies and a few highly‐connected hub economies. The network clustering structure is revealed by the regional integration of several trading communities, while hub economies are collectors and distributors in the global trade network, with important implications for emission mitigation. Achieving AGHG emission reduction calls for a combination of supply‐ and demand‐side policies covering the global trade network.
AGU_Full_Text
2019
Yan Zhang, Xin Bo, Yu Zhao, and Chris P. Nielsen. 2019. “Benefits of current and future policies on emissions of China's coal-fired power sector indicated by continuous emission monitoring.” Environmental Pollution, 251, Pp. 415-424. Publisher's VersionAbstract
Emission inventories are critical to understanding the sources of air pollutants, but have high uncertainties in China due in part to insufficient on-site measurements. In this study, we developed a method of examining, screening and applying online data from the country's improving continuous emission monitoring systems (CEMS) to reevaluate a “bottom-up” emission inventory of China's coal-fired power sector. The benefits of China's current national emission standards and ultra-low emission policy for the sector were quantified assuming their full implementation. The derived national average emission factors of SO2, NOx and particulate matter (PM) were 1.00, 1.00 and 0.25 kg/t-coal respectively for 2015 based on CEMS data, smaller than those of previous studies that may not fully recognize improved emission controls in recent years. The annual emissions of SO2, NOx and PM from the sector were recalculated at 1321, 1430 and 334 Gg respectively, 75%, 63% and 76% smaller than our estimates based on a previous approach without the benefit of CEMS data. The results imply that online measurement with proper data screening can better track the recent progress of emission controls. The emission intensity (the ratio of emissions to economic output) of Northwest China was larger than that of other regions, attributed mainly to its less intensive economy and industry. Transmission of electricity to more-developed eastern provinces raised the energy consumption and emissions of less-developed regions. Judged by 95 percentiles of flue-gas concentrations measured by CEMS, most power plants met the current national emission standards in 2015 except for those in Northwest and Northeast China, while plants that met the ultra-low emission policy were much scarcer. National SO2, NOx and PM emissions would further decline by 68%, 55% and 81% respectively if the ultra-low emission policy can be strictly implemented, implying the great potential of the policy for emission abatement.
Jianxiong Sheng, Shaojie Song, Yuzhong Zhang, Ronald G. Prinn, and Greet Janssens-Maenhout. 2019. “Bottom-up estimates of coal mine methane emissions in China: A gridded inventory, emission factors, and trends.” Environmental Science and Technology Letters. Publisher's VersionAbstract
China has large but uncertain coal mine methane (CMM) emissions. Inverse modeling (top-down) analyses of atmospheric methane observations can help improve the emission estimates but require reliable emission patterns as prior information. To serve this urgent need, we developed a high-resolution (0.25° × 0.25°) methane emission inventory for China’s coal mining using a recent publicly available database of more than 10000 coal mines in China for 2011. This number of coal mines is 25 and 2.5 times, respectively, more than the number available in the EDGAR v4.2 and EDGAR v4.3.2 gridded global inventories, which have been extensively used in past inverse analyses. Our inventory shows large differences with the EDGAR v4.2 as well as its more recent version, EDGAR v4.3.2. Our results suggest that China’s CMM emissions have been decreasing since 2012 on the basis of coal mining activities and assuming time-invariant emission factors but that regional trends differ greatly. Use of our inventory as prior information in future inverse modeling analyses can help better quantify CMM emissions as well as more confidently guide the future mitigation of coal to gas in China.
ESTLett paper.pdf
China’s CO2 peak before 2030 implied from diverse characteristics and growth of cities
Haikun Wang, Xi Lu, Yu Deng, Yaoguang Sun, Chris P. Nielsen, Yifan Liu, Ge Zhu, Maoliang Bu, Jun Bi, and Michael B. McElroy. 2019. “China’s CO2 peak before 2030 implied from diverse characteristics and growth of cities.” Nature Sustainability, 2, Pp. 748–754. Publisher's VersionAbstract
China pledges to peak CO2 emissions by 2030 or sooner under the Paris Agreement to limit global warming to 2 °C or less by the end of the century. By examining CO2 emissions from 50 Chinese cities over the period 2000–2016, we found a close relationship between per capita emissions and per capita gross domestic product (GDP) for individual cities, following the environmental Kuznets curve, despite diverse trajectories for CO2 emissions across the cities. Results show that carbon emissions peak for most cities at a per capita GDP (in 2011 purchasing power parity) of around US$21,000 (80% confidence interval: US$19,000 to 22,000). Applying a Monte Carlo approach to simulate the peak of per capita emissions using a Kuznets function based on China’s historical emissions, we project that emissions for China should peak at 13–16 GtCO2 yr−1 between 2021 and 2025, approximately 5–10 yr ahead of the current Paris target of 2030. We show that the challenges faced by individual types of Chinese cities in realizing low-carbon development differ significantly depending on economic structure, urban form and geographical location.
Peng Jiang, Hongyan Liu, Shilong Piao, Philippe Ciais, Xiuchen Wu, Yi Yin, and Hongya Wang. 2019. “Enhanced growth after extreme wetness compensates for post-drought carbon loss in dry forests.” Nature Communications, 10, 195. Publisher's VersionAbstract
While many studies have reported that drought events have substantial negative legacy effects on forest growth, it remains unclear whether wetness events conversely have positive growth legacy effects. Here, we report pervasive and substantial growth enhancement after extreme wetness by examining tree radial growth at 1929 forest sites, satellite-derived vegetation greenness, and land surface model simulations. Enhanced growth after extreme wetness lasts for 1 to 5 years and compensates for 93 ± 8% of the growth deficit after extreme drought across global water-limited regions. Remarkable wetness-enhanced growths are observed in dry forests and gymnosperms, whereas the enhanced growths after extreme wetness are much smaller in wet forests and angiosperms. Limited or no enhanced growths are simulated by the land surface models after extreme wetness. These findings provide new evidence for improving climate-vegetation models to include the legacy effects of both drought and wet climate extremes.
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 full 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. Science_Advances_Paper.pdf
2018
Archana Dayalu, William Munger, Steven Wofsy, Yuxuan Wang, Thomas Nehrkorn, Yu Zhao, Michael McElroy, Chris Nielsen, and Kristina Luus. 2018. “Assessing biotic contributions to CO2 fluxes in northern China using the Vegetation, Photosynthesis and Respiration Model (VPRM-CHINA) and observations from 2005 to 2009.” Biogeosciences, 15, Pp. 6713-6729. Publisher's VersionAbstract
Accurately quantifying the spatiotemporal distribution of the biological component of CO2 surface–atmosphere exchange is necessary to improve top-down constraints on China's anthropogenic CO2 emissions. We provide hourly fluxes of CO2 as net ecosystem exchange (NEE; µmol CO2 m−2 s−1) on a 0.25∘×0.25∘" id="MathJax-Element-1-Frame" role="presentation" style="position: relative;" tabindex="0">0.25×0.25 grid by adapting the Vegetation, Photosynthesis, and Respiration Model (VPRM) to the eastern half of China for the time period from 2005 to 2009; the minimal empirical parameterization of the VPRM-CHINA makes it well suited for inverse modeling approaches. This study diverges from previous VPRM applications in that it is applied at a large scale to China's ecosystems for the first time, incorporating a novel processing framework not previously applied to existing VPRM versions. In addition, the VPRM-CHINA model prescribes methods for addressing dual-cropping regions that have two separate growing-season modes applied to the same model grid cell. We evaluate the VPRM-CHINA performance during the growing season and compare to other biospheric models. We calibrate the VPRM-CHINA with ChinaFlux and FluxNet data and scale up regionally using Weather Research and Forecasting (WRF) Model v3.6.1 meteorology and MODIS surface reflectances. When combined with an anthropogenic emissions model in a Lagrangian particle transport framework, we compare the ability of VPRM-CHINA relative to an ensemble mean of global hourly flux models (NASA CMS – Carbon Monitoring System) to reproduce observations made at a site in northern China. The measurements are heavily influenced by the northern China administrative region. Modeled hourly time series using vegetation fluxes prescribed by VPRM-CHINA exhibit low bias relative to measurements during the May–September growing season. Compared to NASA CMS subset over the study region, VPRM-CHINA agrees significantly better with measurements. NASA CMS consistently underestimates regional uptake in the growing season. We find that during the peak growing season, when the heavily cropped North China Plain significantly influences measurements, VPRM-CHINA models a CO2 uptake signal comparable in magnitude to the modeled anthropogenic signal. In addition to demonstrating efficacy as a low-bias prior for top-down CO2 inventory optimization studies using ground-based measurements, high spatiotemporal resolution models such as the VPRM are critical for interpreting retrievals from global CO2 remote-sensing platforms such as OCO-2 and OCO-3 (planned). Depending on the satellite time of day and season of crossover, efforts to interpret the relative contribution of the vegetation and anthropogenic components to the measured signal are critical in key emitting regions such as northern China – where the magnitude of the vegetation CO2 signal is shown to be equivalent to the anthropogenic signal.
BG paper
Bo Zhang, Xueli Zhao, Xiaofang Wu, Mengyao Han, Chenghe Guan, and Shaojie Song. 2018. “Consumption‐based accounting of global anthropogenic CH4 emissions.” Earth's Future, 6, 9, Pp. 1349-1363. Publisher's VersionAbstract

Global anthropogenic CH4 emissions have witnessed a rapid increase in the last decade. However, how this increase is connected with its socioeconomic drivers has not yet been explored. In this paper, we highlight the impacts of final demand and international trade on global anthropogenic CH4 emissions based on the consumption‐based accounting principle. We find that household consumption was the largest final demand category, followed by fixed capital formation and government consumption. The position and function of nations and major economies to act on the structure and spatial patterns of global CH4 emissions were systematically clarified. Substantial geographic shifts of CH4emissions during 2000‐2012 revealed the prominent impact of international trade. In 2012, about half of global CH4 emissions were embodied in international trade, of which 77.8% were from intermediate trade and 22.2% from final trade. Mainland China was the largest exporter of embodied CH4 emissions, while the USA was the largest importer. Developed economies such as Western Europe, the USA and Japan were major net receivers of embodied emission transfer, mainly from developing countries. CH4emission footprints of nations were closely related to their human development indexes (HDIs) and per capita gross domestic products (GDPs). Our findings could help to improve current understanding of global anthropogenic CH4 emission increases, and to pinpoint regional and sectoral hotspots for possible emission mitigation in the entire supply chains from production to consumption.

 

zhang_et_al-2018-earth27s_future.pdf
Jonathan M. Moch, Eleni Dovrou, Loretta J. Mickley, Frank N. Keutsch, Yuan Cheng, Daniel J. Jacob, Jingkun Jiang, Meng Li, J. William Munger, Xiaohui Qiao, and Qiang Zhang. 2018. “Contribution of hydroxymethane sulfonate to ambient particulate matter: A potential explanation for high particulate sulfur during severe winter haze in Beijing.” Geophysical Research Letters, 45, Pp. 11969-11979. Publisher's VersionAbstract
PM 2.5 during severe winter haze in Beijing, China, has reached levels as high as 880μg/m3, with sulfur compounds contributing significantly to PM 2.5 composition. This sulfur has been traditionally assumed to be sulfate, although atmospheric chemistry models are unable to account for such large sulfate enhancements under dim winter conditions. Using a 1-D model, we show that well-characterized but previously overlooked chemistry of aqueous-phase HCHO and S(IV) in cloud droplets to form a S(IV)-HCHO adduct, hydroxymethane sulfonate, may explain high particulate sulfur in wintertime Beijing. We also demonstrate in the laboratory that methods of ion chromatography typically used to measure ambient particulates easily misinterpret hydroxymethane sulfonate as sulfate. Our findings suggest that HCHO and not SO2 has been the limiting factor in many haze events in Beijing and that to reduce severe winter pollution in this region, policymakers may need to address HCHO sources such as transportation.
GRL paper
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
Qing Yang, Hewen Zhou, Xiaoyan Zhang, Chris P. Nielsen, Jiashuo Li, Xi Lu, Haiping Yang, and Hanping Chen. 2018. “Hybrid life-cycle assessment for energy consumption and greenhouse gas emissions of a typical biomass gasification power plant in China.” Journal of Cleaner Production, 205, Pp. 661-671. Publisher's VersionAbstract

Among biomass energy technologies which are treated as the promising way to mitigate critical energy crisis and global climate change, biomass gasification plays a key role given to its gaseous fuels especially syngas for distributed power plant. However, a system analysis for the energy saving and greenhouse gas emissions abatement potentials of gasification system has been directed few attentions. This study presents a system analysis that combines process and input-output analyses of GHG emissions and energy costs throughout the full chain of activities associated with biomass gasification. Incorporating agricultural production, industrial process and wastewater treatment which is always ignored, the energy inputs in life cycle are accounted for the first commercial biomass gasification power plant in China. Results show that the non-renewable energy cost and GHG emission intensity of the biomass gasification system are 0.163 MJ/MJ and 0.137 kg CO2-eq/MJ respectively, which reaffirm its advantages over coal-fired power plants in clean energy and environmental terms. Compared with other biomass energy processes, gasification performs well as its non-renewable energy cost and CO2 intensity are in the central ranges of those for all of these technologies. Construction of the plant is an important factor in the process’s non-renewable energy consumption, contributing about 44.48% of total energy use. Wastewater treatment is the main contributor to GHG emissions. The biomass gasification and associated wastewater treatment technologies have critical influence on the sustainability and renewability of biomass gasification. The results provide comprehensive analysis for biomass gasification performance and technology improvement potential in regulating biomass development policies for aiming to achieve sustainability globally.

 

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.

 

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