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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 in 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.

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.

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.

China has pledged reduction of carbon dioxide (CO2) emissions per unit of gross domestic product (GDP) by 60 %–65 % relative to 2005 levels, and to peak carbon emissions overall by 2030. However, the lack of observational data and disagreement among the many available inventories makes it difficult for China to track progress toward these goals and evaluate the efficacy of control measures. To demonstrate the value of atmospheric observations for constraining CO2 inventories we track the ability of CO2 concentrations predicted from three different CO2 inventories to match a unique multi-year continuous record of atmospheric CO2. Our analysis time window includes the key commitment period for the Paris Agreement (2005) and the Beijing Olympics (2008). One inventory is China-specific and two are spatial subsets of global inventories. The inventories differ in spatial resolution, basis in national or subnational statistics, and reliance on global or China-specific emission factors. We use a unique set of historical atmospheric observations from 2005 to 2009 to evaluate the three CO2 emissions inventories within China's heavily industrialized and populated northern region accounting for ∼33 %–41 % of national emissions. Each anthropogenic inventory is combined with estimates of biogenic CO2 within a high-resolution atmospheric transport framework to model the time series of CO2 observations. To convert the model–observation mismatch from mixing ratio to mass emission rates we distribute it over a region encompassing 90 % of the total surface influence in seasonal (annual) averaged back-trajectory footprints (L_0.90 region). The L_0.90 region roughly corresponds to northern China. Except for the peak growing season, where assessment of anthropogenic emissions is entangled with the strong vegetation signal, we find the China-specific inventory based on subnational data and domestic field studies agrees significantly better with observations than the global inventories at all timescales. Averaged over the study time period, the unscaled China-specific inventory reports substantially larger annual emissions for northern China (30 %) and China as a whole (20 %) than the two unscaled global inventories. Our results, exploiting a robust time series of continuous observations, lend support to the rates and geographic distribution in the China-specific inventory Though even long-term observations at a single site reveal differences among inventories, exploring inventory discrepancy over all of China requires a denser observational network in future efforts to measure and verify CO2 emissions for China both regionally and nationally. We find that carbon intensity in the northern China region has decreased by 47 % from 2005 to 2009, from approximately 4 kg of CO2 per USD (note that all references to USD in this paper refer to USD adjusted for purchasing power parity, PPP) in 2005 to about 2 kg of CO2 per USD in 2009 (Fig. 9c). However, the corresponding 18 % increase in absolute emissions over the same time period affirms a critical point that carbon intensity targets in emerging economies can be at odds with making real climate progress. Our results provide an important quantification of model–observation mismatch, supporting the increased use and development of China-specific inventories in tracking China's progress as a whole towards reducing emissions. We emphasize that this work presents a methodology for extending the analysis to other inventories and is intended to be a comparison of a subset of anthropogenic CO2 emissions rates from inventories that were readily available at the time this research began. For this study's analysis time period, there was not enough spatially distinct observational data to conduct an optimization of the inventories. The primary intent of the comparisons presented here is not to judge specific inventories, but to demonstrate that even a single site with a long record of high-time-resolution observations can identify major differences among inventories that manifest as biases in the model–data comparison. This study provides a baseline analysis for evaluating emissions from a small but important region within China, as well a guide for determining optimal locations for future ground-based measurement sites.

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.

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.

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° 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.

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 northern 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, depending on whether anions or cations are in excess. Calculations using total (gas plus aerosol phase) measurements as inputs (i.e., forward mode) are affected much less by these measurement errors. In future studies, the reverse mode should be avoided whereas the forward mode should be used. 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 northern China winter haze, indicating further that ammonia plays an important role in determining this property. The assumed particle phase state, either stable (solid plus liquid) or metastable (only liquid), does not significantly impact pH predictions. The unrealistic pH values of about 7 in a few previous studies (using the standard ISORROPIA model and stable state assumption) resulted from coding errors in the model, which have been identified and fixed in this study.

Rapid economic and industrial development in China and relatively weak emission controls have resulted in significant increases in emissions of nitrogen oxides (NOx) in recent years, with the exception of late 2008 to mid 2009 when the economic downturn led to emission reductions detectable from space. Here vertical column densities (VCDs) of tropospheric NO2 retrieved from satellite observations by SCIAMACHY, GOME-2 and OMI (both by KNMI and by NASA) are used to evaluate changes in emissions of NOx from October 2004 to February 2010 identifying impacts of the economic downturn. Data over polluted regions of Northern East China suggest an increase of 27–33 % in 12-month mean VCD of NO2 prior to the downturn, consistent with an increase of 49 % in thermal power generation (TPG) reflecting the economic growth. More detailed analysis is used to quantify changes in emissions of NOx in January over the period 2005–2010 when the effect of the downturn was most evident. The GEOS-Chem model is employed to evaluate the effect of changes in chemistry and meteorology on VCD of NO2. This analysis indicates that emissions decreased by 20 % from January 2008 to January 2009, close to the reduction of 18 % in TPG that occurred over the same interval. A combination of three independent approaches indicates that the economic downturn was responsible for a reduction in emissions by 9–11 % in January 2009 with an additional decrease of 10 % attributed to the slow-down in industrial activity associated with the coincident celebration of the Chinese New Year; errors in the estimate are most likely less than 3.4 %.

The uncertainties of a national, bottom-up inventory of Chinese emissions of anthropogenic SO2, NOx, and particulate matter (PM) of different size classes and carbonaceous species are comprehensively quantified, for the first time, using Monte Carlo simulation. The inventory is structured by seven dominant sectors: coal-fired electric power, cement, iron and steel, other industry (boiler combustion), other industry (non-combustion processes), transportation, and residential. For each parameter related to emission factors or activity-level calculations, the uncertainties, represented as probability distributions, are either statistically fitted using results of domestic field tests or, when these are lacking, estimated based on foreign or other domestic data. The uncertainties (i.e., 95% confidence intervals around the central estimates) of Chinese emissions of SO2, NOx, total PM, PM10, PM2.5, black carbon (BC), and organic carbon (OC) in 2005 are estimated to be −14%~13%, −13%~37%, −11%~38%, −14%~45%, −17%~54%, −25%~136%, and −40%~121%, respectively. Variations at activity levels (e.g., energy consumption or industrial production) are not the main source of emission uncertainties. Due to narrow classification of source types, large sample sizes, and relatively high data quality, the coal-fired power sector is estimated to have the smallest emission uncertainties for all species except BC and OC. Due to poorer source classifications and a wider range of estimated emission factors, considerable uncertainties of NOx and PM emissions from cement production and boiler combustion in other industries are found. The probability distributions of emission factors for biomass burning, the largest source of BC and OC, are fitted based on very limited domestic field measurements, and special caution should thus be taken interpreting these emission uncertainties. Although Monte Carlo simulation yields narrowed estimates of uncertainties compared to previous bottom-up emission studies, the results are not always consistent with those derived from satellite observations. The results thus represent an incremental research advance; while the analysis provides current estimates of uncertainty to researchers investigating Chinese and global atmospheric transport and chemistry, it also identifies specific needs in data collection and analysis to improve on them. Strengthened quantification of emissions of the included species and other, closely associated ones – notably CO2, generated largely by the same processes and thus subject to many of the same parameter uncertainties – is essential not only for science but for the design of policies to redress critical atmospheric environmental hazards at local, regional, and global scales.

Although China has surpassed the United States as the world's largest carbon dioxide emitter, in situ measurements of atmospheric CO2 have been sparse in China. This paper analyzes hourly CO2 and its correlation with CO at Miyun, a rural site near Beijing, over a period of 51 months (Dec 2004 through Feb 2009). The CO2-CO correlation analysis evaluated separately for each hour of the day provides useful information with statistical significance even in the growing season. We found that the intercept, representing the initial condition imposed by global distribution of CO2 with influence of photosynthesis and respiration, exhibits diurnal cycles differing by season. The background CO2 (CO2,b) derived from Miyun observations is comparable to CO2 observed at a Mongolian background station to the northwest. Annual growth of overall mean CO2 at Miyun is estimated at 2.7 ppm yr−1 while that of CO2,b is only 1.7 ppm yr−1 similar to the mean growth rate at northern mid-latitude background stations. This suggests a relatively faster increase in the regional CO2 sources in China than the global average, consistent with bottom-up studies of CO2 emissions. For air masses with trajectories through the northern China boundary layer, mean winter CO2/CO correlation slopes (dCO2/dCO) increased by 2.8 ± 0.9 ppmv/ppmv or 11% from 2005–2006 to 2007–2008, with CO2 increasing by 1.8 ppmv. The increase in dCO2/dCO indicates improvement in overall combustion efficiency over northern China after winter 2007, attributed to pollution reduction measures associated with the 2008 Beijing Olympics. The observed CO2/CO ratio at Miyun is 25% higher than the bottom-up CO2/CO emission ratio, suggesting a contribution of respired CO2 from urban residents as well as agricultural soils and livestock in the observations and uncertainty in the emission estimates.

A new methodology is developed to constrain Chinese anthropogenic emissions of nitrogen oxides (NOx) from four major sectors (industry, power plants, mobile and residential) in July 2008. It combines tropospheric NO2 column retrievals from GOME-2 and OMI, taking advantage of their different passing time over China (~10:00 a.m. LT (local time) versus ~02:00 p.m.) and consistent retrieval algorithms. The approach is based on the difference of NOx columns at the overpass times of the two instruments; it thus is less susceptible to the likely systematic errors embedded in individual retrievals that are consistent with each other. Also, it explicitly accounts for diurnal variations and uncertainties of NOx emissions for individual sources. Our best top-down estimate suggests a national budget of 6.8 TgN/yr (5.5 TgN/yr for East China), close to the a priori bottom-up emission estimate from the INTEX-B mission for the year of 2006. The top-down emissions are lower than the a priori near Beijing, in the northeastern provinces and along the east coast; yet they exceed the a priori over many inland regions. Systematic errors in satellite retrievals are estimated to lead to underestimation of top-down emissions by at most 17% (most likely 10%). Effects of other factors on the top-down estimate are typically less than 15% each, including lightning, soil emissions, mixing in planetary boundary layer, anthropogenic emissions of carbon monoxide and volatile organic compounds, magnitude of a priori emissions, assumptions on emission diurnal variations, and uncertainties in the four sectors. The a posteriori emission budget is 5.7 TgN/yr for East China.

A series of aggressive measures was launched by the Chinese government to reduce pollutant emissions from Beijing and surrounding areas during the Olympic Games. Observations at Miyun, a rural site 100 km downwind of the Beijing urban center, show significant decreases in concentrations of O3, CO, NOy, and SO2 during August 2008, relative to August 2006–2007. The mean daytime mixing ratio of O3 was lower by about 15 ppbv, reduced to 50 ppbv, in August 2008. The relative reductions in daytime SO2, CO, and NOy were 61%, 25%, and 21%, respectively. Changes in SO2 and in species correlations from 2007 to 2008 indicate that emissions of SO2, CO, and NOx were reduced at least by 60%, 32%, and 36%, respectively, during the Olympics. Analysis of meteorological conditions and interpretation of observations using a chemical transport model suggest that although the day-to-day variability in ozone is driven mostly by meteorology, the reduction in emissions of ozone precursors associated with the Olympic Games had a significant contribution to the observed decrease in O3 during August 2008, accounting for 80% of the O3 reduction for the month as a whole and 45% during the Olympics Period (8–24 August). The model predicts that emission restrictions such as those implemented during the Olympics can affect O3 far beyond the Beijing urban area, resulting in reductions in boundary layer O3 of 2–10 ppbv over a large region of the North China Plain and Northeastern China.

An updated version of the nested-grid GEOS-Chem model is developed allowing for higher horizontal (0.5°×0.667°) resolution as compared to global models. CO transport over a heavily polluted region, the Beijing-Tianjin-Hebei (BTH) city cluster in China, and the pattern of outflow from East China in summertime are investigated. Comparison of the nested-grid with global models indicates that the fine-resolution nested-grid model is capable of resolving individual cities with high associated emission intensities. The nested-grid model indicates the presence of a high CO column density over the Sichuan Basin in summer, attributable to the low-level stationary vortex associated with the Basin's topographical features. The nested-grid model provides good agreement also with measurements from a suburban monitoring site in Beijing during summer 2005. Tagged CO simulation results suggest that regional emissions make significant contributions to elevated CO levels over Beijing on polluted days and that the southeastward moving cyclones bringing northwest winds to Beijing are the key meteorological mechanisms responsible for dispersion of pollution over Beijing in summer. Overall CO fluxes to the NW Pacific from Asia are found to decrease by a factor of 3–4 from spring to summer. Much of the seasonal change is driven by decreasing fluxes from India and Southeast Asia in summer, while fluxes from East China are only 30% lower in summer than in spring. Compared to spring, summertime outflow from Chinese source regions is strongest at higher latitudes (north of 35° N). The deeper convection in summer transporting CO to higher altitudes where export is more efficient is largely responsible for enhanced export in summer.

Large intra-season differences in mixing ratios of CO and O3 were detected at Miyun, a rural site north of Beijing, in summer 2006. Despite an increase in mean daytime mixing ratio of CO from 500 ppbv in June to 700 ppbv in July, mean daytime O3 dropped from 67 ppbv in June to 50 ppbv in July and August. The observed changes in CO and O3 are attributed to the influence of the summer monsoonal circulation that develops over the North China Plain in July. Photochemical production of O3 is reduced as a consequence of increased cloudiness during July and August, as indicated by the strong negative correlation observed between O3 and satellite observations of cloud optical depth, with cloudiness having little effect on CO. The analysis suggests a strategy for emission controls that could be implemented in an economically efficient manner to minimize the frequency of high levels of O3 during summer in Beijing.