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Accompanied by the continuous declines of PM2.5, O3 pollution has become increasingly prominent and has been targeted by the Government of China to protect climate, ecosystem, and human health. Although satellite retrievals of column O3 have been operated for decades and nationwide monitoring of ground-level O3 has been offered since 2013 in China, climatological variability of ground-level O3 remains unknown, which impedes understanding of the long-term driver and impacts of O3 pollution in China. Here we develop an eXtreme Gradient Boosting (XGBoost) model integrating high-resolution meteorological data, satellite retrievals of trace gases, etc. to provide reconstructed daily ground-level O3 over 2005–2021 in China. Model validation confirms the robustness of this dataset, with R2 of 0.89 for sample-based cross-validation. The accuracy of the long-term variations has also been confirmed with independent historical observations covering the same period from urban, rural and background sites. Our dataset covers the long time period of 2005–2021 with 0.1°×0.1° gap-free grids, which can facilitate climatological, ecological, and health research. The dataset is freely available at Zenodo (https://zenodo.org/record/6507706#.Yo8hKujP13g; Zhou, 2022).

Despite the significant progress in improving chemical transport models (CTMs), applications of these modeling endeavors are still subject to large and complex model uncertainty. The Model Inter-Comparison Study for Asia III (MICS-Asia III) has provided the opportunity to assess the capability and uncertainty of current CTMs in East Asian applications. In this study, we have evaluated the multi-model simulations of nitrogen dioxide (NO2), carbon monoxide (CO) and ammonia (NH3) over China under the framework of MICS-Asia III. A total of 13 modeling results, provided by several independent groups from different countries and regions, were used in this study. Most of these models used the same modeling domain with a horizontal resolution of 45 km and were driven by common emission inventories and meteorological inputs. New observations over the North China Plain (NCP) and Pearl River Delta (PRD) regions were also available in MICS-Asia III, allowing the model evaluations over highly industrialized regions. The evaluation results show that most models captured the monthly and spatial patterns of NO2 concentrations in the NCP region well, though NO2 levels were slightly underestimated. Relatively poor performance in NO2 simulations was found in the PRD region, with larger root-mean-square error and lower spatial correlation coefficients, which may be related to the coarse resolution or inappropriate spatial allocations of the emission inventories in the PRD region. All models significantly underpredicted CO concentrations in both the NCP and PRD regions, with annual mean concentrations that were 65.4 % and 61.4 % underestimated by the ensemble mean. Such large underestimations suggest that CO emissions might be underestimated in the current emission inventory. In contrast to the good skills for simulating the monthly variations in NO2 and CO concentrations, all models failed to reproduce the observed monthly variations in NH3 concentrations in the NCP region. Most models mismatched the observed peak in July and showed negative correlation coefficients with the observations, which may be closely related to the uncertainty in the monthly variations in NH3 emissions and the NH3 gas-aerosol partitioning. Finally, model intercomparisons have been conducted to quantify the impacts of model uncertainty on the simulations of these gases, which are shown to increase with the reactivity of species. Models contained more uncertainty in the NH3 simulations. This suggests that for some highly active and/or short-lived primary pollutants, like NH3, model uncertainty can also take a great part in the forecast uncertainty in addition to the emission uncertainty. Based on these results, some recommendations are made for future studies.

Recently, there has been increasing interest in the relation between particulate matter (PM) pollution and atmospheric boundary layer (ABL) structure. However, this has yet to be fully understood because most studies have been superficial. This study aimed to qualitatively assess the interaction between PM and ABL structure in essence, and to further quantitatively estimate the effects of aerosol radiative forcing (ARF) on the ABL structure. Multi-episode contrastive analysis stated the key to determining whether haze outbreak or dissipation was the ABL structure (i.e., stability and turbulence kinetic energy (TKE)) satisfied relevant conditions. However, it seemed that the ABL structure change was in turn highly related to the PM level and ARF. |SFC-ATM| (SFC and ATM is respectively the ARF at the surface and interior of the atmospheric column) is the absolute difference between ground and atmosphere layer ARFs, and the change in |SFC-ATM| is linearly related to the PM mass concentration. However, the influence of ARF on the boundary layer structure is nonlinear. With increasing |SFC-ATM|, the TKE level exponentially decreased, which was notable in the lower layers/ABL but disappeared above the ABL. Moreover, the threshold of the ARF effects on the ABL structure was determined for the first time, namely, once |SFC-ATM| exceeded ~ 55 W m−2, the ABL structure would quickly stabilize and would thereafter change little with increasing ARF. The threshold of the ARF effects on the boundary layer structure could provide useful information for relevant atmospheric environment improvement measures and policies, such as formulating the objectives of phased air pollution control.

The Chinese government has exerted strict emission controls to mitigate air pollution since 2013, which has resulted in significant decreases in the concentrations of air pollutants such as SO2. Strict pollution control actions also reduced the average PM2.5 concentration to the low level of 39.7 µg m−3 in urban Beijing during the winter of 2017. To investigate the impact of such changes on the physiochemical properties of atmospheric aerosols in China, we conducted a comprehensive observation focusing on PM2.5 in Beijing during the winter of 2017. Compared with the historical record (2014–2017), SO2 decreased to the low level of 3.2 ppbv in the winter of 2017, but the NO2 level was still high (21.4 ppbv in the winter of 2017). Accordingly, the contribution of nitrate (23.0 µg m−3) to PM2.5 far exceeded that of sulfate (13.1 µg m−3) during the pollution episodes, resulting in a significant increase in the nitrate-to-sulfate molar ratio. The thermodynamic model (ISORROPIA II) calculation results showed that during the PM2.5 pollution episodes particle pH increased from 4.4 (moderate acidic) to 5.4 (more neutralized) when the molar ratio of nitrate to sulfate increased from 1 to 5, indicating that aerosols were more neutralized as the nitrate content elevated. Controlled variable tests showed that the pH elevation should be attributed to nitrate fraction increase other than crustal ion and ammonia concentration increases. Based on the results of sensitivity tests, future prediction for the particle acidity change was discussed. We found that nitrate-rich particles in Beijing at low and moderate humid conditions (RH: 20 %–50 %) can absorb twice the amount of water that sulfate-rich particles can, and the nitrate and ammonia with higher levels have synergetic effects, rapidly elevating particle pH to merely neutral (above 5.6). As moderate haze events might occur more frequently under abundant ammonia and nitrate-dominated PM2.5 conditions, the major chemical processes during haze events and the control target should be re-evaluated to obtain the most effective control strategy.

Despite the significant progress in improving chemical transport models (CTMs), applications of these modeling endeavors are still subject to large and complex model uncertainty. The Model Inter-Comparison Study for Asia III (MICS-Asia III) has provided the opportunity to assess the capability and uncertainty of current CTMs in East Asian applications. In this study, we have evaluated the multi-model simulations of nitrogen dioxide (NO2), carbon monoxide (CO) and ammonia (NH3) over China under the framework of MICS-Asia III. A total of 13 modeling results, provided by several independent groups from different countries and regions, were used in this study. Most of these models used the same modeling domain with a horizontal resolution of 45 km and were driven by common emission inventories and meteorological inputs. New observations over the North China Plain (NCP) and Pearl River Delta (PRD) regions were also available in MICS-Asia III, allowing the model evaluations over highly industrialized regions. The evaluation results show that most models captured the monthly and spatial patterns of NO2 concentrations in the NCP region well, though NO2 levels were slightly underestimated. Relatively poor performance in NO2 simulations was found in the PRD region, with larger root-mean-square error and lower spatial correlation coefficients, which may be related to the coarse resolution or inappropriate spatial allocations of the emission inventories in the PRD region. All models significantly underpredicted CO concentrations in both the NCP and PRD regions, with annual mean concentrations that were 65.4 % and 61.4 % underestimated by the ensemble mean. Such large underestimations suggest that CO emissions might be underestimated in the current emission inventory. In contrast to the good skills for simulating the monthly variations in NO2 and CO concentrations, all models failed to reproduce the observed monthly variations in NH3 concentrations in the NCP region. Most models mismatched the observed peak in July and showed negative correlation coefficients with the observations, which may be closely related to the uncertainty in the monthly variations in NH3 emissions and the NH3 gas–aerosol partitioning. Finally, model intercomparisons have been conducted to quantify the impacts of model uncertainty on the simulations of these gases, which are shown to increase with the reactivity of species. Models contained more uncertainty in the NH3 simulations. This suggests that for some highly active and/or short-lived primary pollutants, like NH3, model uncertainty can also take a great part in the forecast uncertainty in addition to the emission uncertainty. Based on these results, some recommendations are made for future studies.

Despite significant progress in improving chemical transport models (CTMs), applications of these modeling endeavours are still subject to the large and complex model uncertainty. Model Inter-Comparison Study for Asia III (MICS-Asia III) provides the opportunity to assess the capability and uncertainty of current CTMs in East Asia applications. In this study, we evaluated the multi-model simulations of nitrogen dioxide (NO2), carbon monoxide (CO) and ammonia (NH3) over China under the framework of MICS-Asia III. Compared with MICS-Asia II, modeling results were provided by a larger number of independent groups from different countries/regions and covered a longer period of time (one-full year). Furthermore, most of these groups used a common emission inventory, common meteorological inputs, and the same modeling domain and horizontal resolutions. New observations over North China Plain (NCP) and Peral River Delta (PRD) were also available in MICS-Asia III, allowing model evaluations over highly industrialized regions. The results show that most models well captured the monthly and spatial patterns of NO2 in NCP though NO2 levels were slightly underestimated. Relatively poor performance in NO2 simulations was found in PRD with larger root mean square error and lower spatial correlation coefficients, possibly due to the relative coarse model resolutions. All models significantly underpredicted CO concentrations both in NCP and PRD, with annual mean concentrations 65.4 % and 61.4 % underestimated by the ensemble mean respectively. Such large underestimations suggest that CO emissions might be underestimated in current emission inventory. In contrast to the good skills in simulating the monthly variations of NO2 and CO concentrations, all models failed to reproduce the observed monthly variations of NH3 concentrations in NCP. Most models mismatched the observed peak in July and showed negative correlation coefficients with observations, which may be closely related to the uncertainty in the monthly variations of NH3 emissions and the NH3 gas-aerosol partitioning. Finally, inter-comparisons of these model results were conducted to quantify the impacts of model uncertainty on the simulations of these gases, which are shown increase with the reactivity of species. Models contained more uncertainty in the NH3 simulations. This suggests that for some highly active and/or short-lived primary pollutants, like NH3, model uncertainty can also take a great part in the forecast uncertainty in addition to the emission uncertainty. Based on these results, some recommendations are made for future studies.

The “Campaign on Atmospheric Aerosol Research” network of China (CARE-China) is a long-term project for the study of the spatio-temporal distributions of physical aerosol characteristics as well as the chemical components and optical properties of aerosols over China. This study presents the first long-term data sets from this project, including 3 years of observations of online PM2.5 mass concentrations (2012–2014) and 1 year of observations of PM2.5 compositions (2012–2013) from the CARE-China network. The average PM2.5 concentration at 20 urban sites is 73.2µgm−3 (16.8–126.9µgm−3), which was 3 times higher than the average value from the 12 background sites (11.2–46.5µgm−3). The PM2.5 concentrations are generally higher in east-central China than in the other parts of the country due to their relatively large particulate matter (PM) emissions and the unfavourable meteorological conditions for pollution dispersion. A distinct seasonal variability in PM2.5 is observed, with highs in the winter and lows during the summer at urban sites. Inconsistent seasonal trends were observed at the background sites. Bimodal and unimodal diurnal variation patterns were identified at both urban and background sites. The chemical compositions of PM2.5 were analysed at six paired urban and background sites located within the most polluted urban agglomerations – North China Plain (NCP), Yangtze River delta (YRD), Pearl River delta (PRD), North-east China region (NECR), South-west China region (SWCR) – and the cleanest region of China – the Tibetan Autonomous Region (TAR). The major PM2.5 constituents across all the urban sites are organic matter (OM, 26.0%), SO42− (17.7%), mineral dust (11.8%), NO3− (9.8%), NH4+ (6.6%), elemental carbon (EC) (6.0%), Cl− (1.2%) at 45% RH and unaccounted matter (20.7%). Similar chemical compositions of PM2.5 were observed at background sites but were associated with higher fractions of OM (33.2%) and lower fractions of NO3− (8.6%) and EC (4.1%). Significant variations of the chemical species were observed among the sites. At the urban sites, the OM ranged from 12.6µgm−3 (Lhasa) to 23.3µgm−3 (Shenyang), the SO42− ranged from 0.8µgm−3 (Lhasa) to 19.7µgm−3 (Chongqing), the NO3− ranged from 0.5µgm−3 (Lhasa) to 11.9µgm−3 (Shanghai) and the EC ranged from 1.4µgm−3 (Lhasa) to 7.1µgm−3 (Guangzhou). The PM2.5 chemical species at the background sites exhibited larger spatial heterogeneities than those at urban sites, suggesting different contributions from regional anthropogenic or natural emissions and from long-range transport to background areas. Notable seasonal variations of PM2.5-polluted days were observed, especially for the megacities in east-central China, resulting in frequent heavy pollution episodes occurring during the winter. The evolution of the PM2.5 chemical compositions on polluted days was consistent for the urban and nearby background sites, where the sum of sulfate, nitrate and ammonia typically constituted much higher fractions (31–57%) of PM2.5 mass, suggesting fine-particle pollution in the most polluted areas of China assumes a regional tendency, and the importance of addressing the emission reduction of secondary aerosol precursors including SO2 and NOx. Furthermore, distinct differences in the evolution of [NO3−]∕[SO42−] ratio and OC∕EC ratio on polluted days imply that mobile sources and stationary (coal combustion) sources are likely more important in Guangzhou and Shenyang, respectively, whereas in Beijing it is mobile emission and residential sources. As for Chongqing, the higher oxidation capacity than the other three cities suggested it should pay more attention to the emission reduction of secondary aerosol precursors. This analysis reveals the spatial and seasonal variabilities of the urban and background aerosol concentrations on a national scale and provides insights into their sources, processes and lifetimes.

In January 2013, a long-lasting episode of severe haze occurred in central and eastern China, and it attracted attention from all sectors of society. The process and evolution of haze pollution episodes were observed by the "Forming Mechanism and Control Strategies of Haze in China" group using an intensive aerosol and trace gases campaign that simultaneously obtained data at 11 ground-based observing sites in the CARE-China network. The characteristics and formation mechanism of haze pollution episodes were discussed. Five haze pollution episodes were identified in the Beijing-Tianjin-Hebei (Jing-Jin-Ji) area; the two most severe episodes occurred during 9-15 January and 25-31 January. During these two haze pollution episodes, the maximum hourly PM2.5 mass concentrations in Beijing were 680 and 530 μg m-3, respectively. The process and evolution of haze pollution episodes in other major cities in the Jing-Jin-Ji area, such as Shijiazhuang and Tianjin were almost the same as those observed in Beijing. The external cause of the severe haze episodes was the unusual atmospheric circulation, the depression of strong cold air activities and the very unfavorable dispersion due to geographical and meteorological conditions. However, the internal cause was the quick secondary transformation of primary gaseous pollutants to secondary aerosols, which contributed to the "explosive growth" and "sustained growth" of PM2.5. Particularly, the abnormally high amount of nitric oxide (NO x ) in the haze episodes, produced by fossil fuel combustion and vehicle emissions, played a direct or indirect role in the quick secondary transformation of coal-burning sulphur dioxide (SO2) to sulphate aerosols. Furthermore, gaseous pollutants were transformed into secondary aerosols through heterogeneous reactions on the surface of fine particles, which can change the particles size and chemical composition. Consequently, the proportion of secondary inorganic ions, such as sulphate and nitrate, gradually increased, which enhances particle hygroscopicity and thereby accelerating formation of the haze pollution.

Two years of measurements of ultraviolet radiation (UV), broadband solar (Rs) radiation and aerosol optical depth (AOD at 500 nm) at 19 stations belonging to six climate zones in China were analyzed in this study. The highest value of UV appeared in the summer, while minimum values appeared in January or December. There was a sharp increase in UV radiation from winter to spring, especially in March. The monthly average hourly ratio of UV radiation to Rs (UV fraction) varied from 2.9% to 4.6%, it increased from November to August, and then gradually decreased. The ratio of UV radiation to its extraterrestrial value is defined as Ktuv, and the clearness index (Ks) is the ratio of Rs to its extraterrestrial value. There was a good linear relationship between Ktuv and Ks, and the ratio of Ktuv to Ks was about 70%. There was a negative linear correlation between UV radiation and AOD. The correlation between the UV fraction and AOD was also negatively linear and stronger than that between UV radiation and AOD. An empirical equation was developed to describe UV radiation from measured Rs under cloudless conditions. This model estimated UV radiation with high accuracy at the site where the model was developed. The mean bias error was close to zero, and the relative error was less than 2%. The application of the model to other locations showed that this model could provide reasonable estimates of UV values from broadband radiation measurements within a relative error of 6%.

An automated procedure employing principal-component analysis and a two-stage cluster analysis was developed to classify the synoptic meteorological conditions prevailing over Urumqi, one of the mo...

in order to investigate the chemical characteristics of atmospheric aerosols in a regional background site, PM2.5 and PM10 were collected at Mount Gongga Station once a week in 2006. The concentrations of fifteen elements including Na, Mg, Al, K, Ca, V, Fe, Ni, Cu, Zn, As, Ag, Ba, Tl, and Pb were detected by Inductively Coupled Plasma Mass Spectrometer (ICP-MS). The results showed that Na, Mg, Al, K, Ca, Fe were the major components of elements detected in PM2.5 and PM10, occupied 89.5% and 91.3% of all the elements. Crustal enrichment factor (EF) Calculation indicated that several anthropogenic heavy metals (Ni, Cu, Zn, As, Ag,Tl, Pb) were transported long distances atmospherically. The concentrations of all elements (except Na) measured in PM2.5 and PM10 in spring and winter were higher than those in summer and autumn. The backward air mass trajectory analysis suggests that northeast India may be the source region of those pollutants. (C) 2009 Published by Elsevier B.V.

Intensive field investigations were conducted at the summit of Mount Tai in June 2006 to understand the effects of the local and regional sources on atmospheric volatile organic compounds (VOCs) distributions. A total of 60 samples were collected and determined by quantitative analytical methods. The concentrations of the total VOCs (TVOCs) observed in the air of Mount Tai were 6.95 ± 5.71 ppb. Aromatic hydrocarbons provided the largest contribution to TVOCs, followed by alkanes and halocarbons. High levels of halocarbons accounted for 20% of TVOCs due to emission from a PVC plant located at the foot of Mount Tai. Alkenes and cycloalkanes contributed little to the total VOCs. The day-and-night differences and day-to-day variations in the concentrations of four selected species were investigated and the effects of several factors such as meteorological parameters, sources and transport characteristics on them were discussed in details. A back trajectory analysis showed that relatively higher levels of VOCs were related to long-range transport of pollutants from polluted areas. The vertical motions of air masses also had a large impact on the variations of the levels of VOCs. The result of the variability–lifetime relationships of VOCs, which is used to estimate the remoteness of the sampling location, showed that Mount Tai represents intermediate conditions between remote sites and sites in the vicinity of sources.

Climatic characteristics of broadband solar radiation (Rs) in Chinese arid and semi-arid areas are reported in this study. The annual average daily Rs in the arid and semi-arid areas is 16.3±5.77 a...

This paper reports altitude-resolved concentrations of sulfur dioxide (SO2) and particulate matter up to 10 microns in diameter (PM10) in the planetary boundary layer of major urban centers during extreme pollution episodes. The concentration of SO2 was observed continuously from November 24, 2004, to December 4, 2004, in Beijing during the heating period. Fluorescence SO2 analyzers were used to measure the atmospheric SO2 concentrations. Four SO2 analyzers were placed at 4 different levels (8 m, 47 m, 120 m, and 280 m) of the 325-m high meteorological observation tower of the Institute of Atmospheric Physics (IAP). Chinese Academy of Sciences. A maximal SO2 concentration of 172.3 ppb was measured during this pollution episode, and SO2 concentration increased with altitude and reached its maximal value at similar to 50 m. The study also analyzed the meteorological situation before, during, and after the pollution episode. (C) 2008 Elsevier Ltd. All rights reserved.

An automated cumulative sampling system and a method that combines a two-step cryo-concentrated system and gas chromatography/mass spectrometry (CCS-GC/MS) are introduced. The method is evaluated by a set of special experiments and the results are presented. The lowest measurement detection limit was expanded from 10−6 nmol mol−1 to 10−12 nmol mol−1 by using CCS-GC/MS instead of the simpler method of gas chromatography/mass spectrometry (GC/MS), with the average responsible factor of 39 object compounds being 2.9×10−12. When the volume of air sample reached 1000 cm3, the lowest detection limit reached up to 7 × 10−12−40 × 10−12 nmol mol−1. The CCS-GC/MS method can potentially identify all objective chemical species in an atmospheric sample, with an average 2.5 s bias error of retention time for 39 gas chromatography (GC) peaks. Within the range 0–400 × 10−9 nmol mol−1, the concentration of 39 kinds of objective compounds can be individually calculated very accurately by a standard curve [average r2 (coefficient of determination) value of above 0.99]. The recovery efficiency was 88%–111%, with an average of 100.8% ±5.6%. The bias error of precision was 2%–14%, with an average of 6.6%.

To gain an understanding of the characteristics of nitrate, sulfate and ammonium in the urban atmosphere of Beijing, an experiment was conducted in October 2004, using a method involving the rapid collection of particles and analysis using an ion chromatography system. The study shows that the mean concentration of water soluble ions (WSI) increased during heavily polluted weather, and this change in the concentration of pollutants was related to the meteorological background. The concentration of nitrate, sulfate and ammonium increased 7.9, 4.1 and 5.4 times, respectively, during heavily polluted periods. The concentration of nitrate increased most among the WSI in PM 10. The diurnal variations of nitrate, sulfate and ammonium in more polluted periods were different from those in less polluted periods. The highest concentration of nitrate (NO 3 -), sulfate (SO 4 2-), and ammonium (NH 4 +) appeared at 19:00 during more polluted periods. In contrast, the highest concentrations of these compounds occurred at noon during less polluted periods. A correlation analysis showed that NO 3 -, SO 4 2-, NH 4 +, nitrogen oxides (NO x) and sulfur dioxide (SO 2) had significant positive correlations in more polluted periods. The transformation ratio from SO 2 and NO x to SO 4 2- and NO 3 - was higher in more polluted than that in less polluted periods.

To understand methane (CH4) and nitrous oxide (N2O) emissions from permanently flooded rice paddy fields and to develop mitigation options, a field experiment was conducted in situ for two years (from late 2002 to early 2005) in three rice-based cultivation systems, which are a permanently flooded rice field cultivated with a single time and followed by a, non-rice season (PF), a rice-wheat rotation system (RW) and a rice-rapeseed rotation system (RR) in a hilly area in Southwest China. The results showed that the total CH4 emissions from PF were 646.3+/-52.1 and 215.0+/-45.4 kg CH4 hm(-2) during the rice-growing period and non-rice period, respectively. Both values were much lower than many previous reports from similar regions in Southwest China. The CH4 emissions in the rice-growing season were more intensive in PF, as compared to RW and RR. Only 33% of the total annual CH4 emission in PF occurred in the non-rice season, though the duration of this season is two times longer than the rice season. The annual mean N2O flux in PF was 4.5+/-0.6 kg N2O hm(-2) yr(-1). The N2O emission in the rice-growing season was also more intensive than in the non-rice season, with only 16% of the total annual emission occurring in the non-rice season. The amounts of N2O emission in PF were ignorable compared to the CH4 emission in terms of the global warming potential (GWP). Changing PF to RW or RR not only eliminated CH4 emissions in the non-rice season, but also substantially reduced the CH4 emission during the following rice-growing period (ca. 58%, P >RR approximate to RW. The GWP of PF is higher than that of RW and RR by a factor of 2.6 and 2.7, respectively. Of the total GWP of CH4 and N2O emissions, CH4 emission contributed to 93%, 65% and 59% in PF, RW and RR, respectively. These results suggest that changing PF to RW and RR can substantially reduce not only CH4 emission but also the total GWP of the CH4 and N2O emissions.

The Beijing 325-m Meteorological Tower (325MT) is used to observe the vertical variation of solar radiation. Results of the experiments indicate that the automatic radiation monitoring system, including a sun tracker and data collection system, works well and all the specifications meet WMO observation standards. The measurement data show that there is a significant radiation decrease from 320 m to the surface, where the difference is only about 30 W m−2 on light air-pollution days, while the maximum reaches about 110 W m−2 when heavy pollution appears near the ground. The global UV radiation decreases on heavy air-pollution days and under poor visibility conditions, and the difference between 300 m and 8 m is larger than on clear days.

[ABSTRACT] The data, measured by using global photosynthetically active radiometer (LI-COR quantum sensor) and global solar radiometer in Beijing, has been analyzed, for investigating the relationship of these two radiant fluxes in Beijing. The data is used to determining timescale variability of the ratio of Photosynthetically active radiation (PAR) to global solar radiation (Rs). The seasonal variation of the ratio ranges from 1.713 to 1.990μmol J^-1,monthly from 1.626 to 2.039μmol J^-1, and daily from 1.42 to 2.57μmol J^-1, with annual mean value 1.841μmol J^-1.

Field measurements were made from June 2001 to May 2002 to evaluate the effect of crop residue application and temperature on CO2, CH4, and N2O emissions within an entire rice-wheat rotation season. Rapeseed cake and wheat straw were incorporated into the soil at a rate of 2.25 t hm−2 when the rice crop was transplanted in June 2001. Compared with the control, the incorporation of rapeseed cake enhanced the emissions of CO2, CH4, and N2O in the rice-growing season by 12.3%, 252.3%, and 17.5%, respectively, while no further effect was held on the emissions of CO2 and N2O in the following wheatgrowing season. The incorporation of wheat straw enhanced the emissions of CO2 and CH4 by 7.1% and 249.6%, respectively, but reduced the N2O emission by 18.8% in the rice-growing season. Significant reductions of 17.8% for the CO2 and of 12.9% for the N2O emission were observed in the following wheatgrowing season. A positive correlation existed between the emissions of N2O and CO2 (R 2 = 0.445,n = 73,p < 0.001) from the rice-growing season when N2O was emitted. A trade-off relationship between the emissions of CH4 and N2O was found in the rice-growing season. The CH4 emission was significantly correlated with the CO2 emission for the period from rice transplantation to field drainage, but not for the entire rice-growing season. In addition, air temperature was found to regulate the CO2 emissions from the non-waterlogged period over the entire rice-wheat rotation season and the N2O emissions from the nonwaterlogged period of the rice-growing season, which can be quantitatively described by an exponential function. The temperature coefficient (Q 10) was then evaluated to be 2.3±0.2 for the CO2 emission and 3.9±0.4 for the N2O emission, respectively.

To understand influence of litters on the emission/absorption of CO2, N2O and CH4 in broadleaved/Korean pine forest in Changbai Mountain, fluxes of soil CO2, N2O and CH4 were measured by closed static chamber technique, from Sept 3, 2002 to Oct 30, 2003 in two types of soil ecosystems, of which one was covered with litters on the surface soil, and the other had no litters. The results showed that litters had significant influences on CO2, N2O and CH4 fluxes (p

Potentilla fruticosa scrub,Kobresia humilis meadow andKobresia tibetica meadow are widely distributed on the Qinghai-Tibet Plateau. During the grass exuberance period from 3 July to 4 September, based on close chamber-GC method, a study on CO2 emissions from different treatments was conducted in these meadows at Haibei research station, CAS. Results indicated that mean CO2 emission rates from various treatments were 672.09±152.37 mgm-2h-1 for FC (grass treatment); 425.41± 191.99 mgm-2h-1 for FJ (grass exclusion treatment); 280.36±174.83 mgm-2h-1 for FL (grass and roots exclusion treatment); 838.95±237.02 mgm-2h-1 for GG (scrub+grass treatment); 528.48±205.67 mgm-2h-1 for GC (grass treatment); 268.97±99.72 mgm-2h-1 for GL (grass and roots exclusion treatment); and 659.20±94.83 mgm-2h-1 for LC (grass treatment), respectively (FC, FJ, FL, GG, GC, GL, LC were the Chinese abbreviation for various treatments). Furthermore,Kobresia humilis meadow,Potentilla fruticosa scrub meadow andKobresia tibetica meadow differed greatly in average CO2 emission rate of soil-plant system, in the order of GG>FC>LC>GC. Moreover, inKobresia humilis meadow, heterotrophic and autotrophic respiration accounted for 42% and 58% of the total respiration of soil-plant system respectively, whereas, inPotentilla fruticosa scrub meadow, heterotrophic and autotrophic respiration accounted for 32% and 68% of total system respiration from GG; 49% and 51% from GC. In addition, root respiration fromKobresia humilis meadow approximated 145 mgCO2m-2h-1, contributed 34% to soil respiration. During the experiment period,Kobresia humilis meadow andPotentilla fruticosa scrub meadow had a net carbon fixation of 111.11 gm-2 and 243.89 gm-2, respectively. Results also showed that soil temperature was the main factor which influenced CO2 emission from alpine meadow ecosystem, significant correlations were found between soil temperature at 5 cm depth and emission from GG, GC, FC and FJ treatments. In addition, soil moisture may be the inhibitory factor of CO2 emission fromKobresia tibetica meadow, and more detailed analyses should be done in further research.

Methane (CH4) and carbon dioxide (CO2) emission was measured from mires in the Sanjiang Plain, Northeast China, by using a static chamber technique during free snow-covered periods. The seasonal mean emission of CH4 was 12.4mg/(m2·h) and the emission range of CO2 was 8.7–16.6g/(m2·d) (gross CO2 flux) during plant growth period. CO2 emission rate in the day was stronger than that at night, and the daily peak appears at 19:00. The mire plants in the Sanjiang Plain begin to sprout at the end of April. The aboveground biomass of the mire plants increased from zero to the peak from July to September and showed single peak form. The aboveground biomass of Carex lasiocarpa (464.8g/m2) was lower than that of Deyeuxia platyphylla (530.8g/m2), but the underground biomass was higher than that of Deyeuxia platyphylla. Gross CO2 flux showed the significance positive correlation relationship with plant biomass. Gross CO2 flux and CH4 emission were also correlated with soil temperature (0–5cm) and water temperature. However, the highest CH4 emission rate lagged behind the highest soil temperature in the root area during plant growth period. The data also indicated that wet and warm conditions during the early spring led to greater value of CH4 emission flux. Inundation is the necessary condition for the existence of methane bacteria, but there is no significant positive correlation between the inundation depth and CH4 emission rate in this region. Within the same growing season and under the same inundation condition, the variations of CH4 emission rate could be markedly different.

In this paper, a new method had been developed, which is suitable to estimate methane emissions from rice fields in China at present. The method is developed based upon the methane models developed in China, different from those recommended by OECD/IPCC. The influences of climate conditions, field water management, organic fertilizers and soil types on methane emission from rice fields are considered. The methane model has been tested with field measurement data. Methane emissions from Chinese rice fields are estimated to be 9.67–12.66 Tg/yr in 1990. These values are lower than previous estimates and are more nearly to the measured data, because of the improved method extrapolations of field measurements.

An experimental study on mitigation of greenhouse gas (CH4, N2O and NO) emission has been conducted in a typical cropping system of Southeast China for 4 years. By simultaneous measurement, the CH4, N2O and NO emission fluxes from rice-wheat rotation fields, effects of fertilization, water management, temperature and soil moisture were investigated. Temperature, fertilization and water status were found to be the key factors to regulate CH4, N2O and NO emis-sions. Based on the experimental results, some agricultural measures were recommended as techni-cal options to mitigate greenhouse gas emissions from rice-wheat rotation ecosystems. These miti-gation measures are reducing mineral N input, coupling organic manure with chemical fertilizers, applying fertilizers which release available N slowly during periods with intensive plant activity, and applying dry fermented organic manure and well management of water and fertilizer.

The methane emission flux from rice paddies was simultaneously measured with automatic and manual methods in the suburban of Suzhou. Both methods were based on the static chamber / GC-FID techniques. Detail analysis of the experimental results indicates: a) The data of methane emission measured with the automatic method is reliable, b) About 11 or 19 o'clock of local time is recommended as the optimum sampling time for the manual spot measurement of methane emission from rice paddies. The methane emission fluxes measured by manual sampling at local time other than the optimum time have to be corrected. The correction coefficient may be determined by automatic and continuous measurement, c) In order to get a more accurate result, an empirical correction factor, such as 18%, is recommended to correct the seasonally total amount of measured methane emission by enlarging the automatically measured data or reducing the manually measured ones.

Combining improved injector, gas line and valve-driving models, a gas chromatograph (GC) equipped with Hydrogen Flame Ionization Detector (FID) and Electron Capture Detector (ECD), can measure CH4, CO2, and N2O simultaneously in an air sample in four minutes. Test results show that the system has high sensitivity, resolution, and precision; the linear response range of the system meets the requirement of flux measurements in situ. The system is suitable for monitoring fluxes of the main greenhouse gases in a short-plant field since it is easy to use, efficacious, and constant and reliable in collecting data.

The variation characteristics of Ultraviolet-B (UVB; 280-315 nm) radiation over Beijing were explored using measured data that were collected in Beijing from November 2010 to October 2011. Seasonal variations in UVB radiation and influence of ozone and clearness index on the ratio of UVB to broadband solar radiation (G) were investigated. The annual value of UVB radiation in Beijing is 6.37 MJ m(-2), and monthly average value ranges from 4.96 to 28.37 kJ m(-2) d(-1). The maximum daily total UVB radiation ranges from 6.55 kJ m(-2) d(-1) in November to 54.22 kJ m(-2) d(-1) in July. The monthly minimum of daily total UVB radiation varies from 0.5 kJ m(-2) d(-1) in February to 11.52 kJ m(-2) d(-1) in July. The monthly average of the ratio of UVB radiation to G ranges from 0.007 to 0.017%, with an annual average value of 0.012%. The variation in slant ozone column causes annual cycle of the ratio UVB radiation to G, with maximum value in summer. In addition, clouds have a greater effect on G than UVB radiation. Thus, the ratio increases by more than 17% when the atmospheric conditions change from clear to cloudy.

Air samples were collected in Beijing from June through August 2008, and concentrations of volatile organic compounds (VOCs) in those samples are here discussed. This sampling was performed to increase understanding of the distributions of their compositions, illustrate the overall characteristics of different classes of VOCs, assess the ages of air masses, and apportion sources of VOCs using principal compound analysis/absolute principal component scores (PCA/APCS). During the sampling periods, the relative abundance of the four classes of VOCs as determined by the concentration-based method was different from that determined by the reactivity approach. Alkanes were found to be most abundant (44.3–50.1%) by the concentration-based method, but aromatic compounds were most abundant (38.2–44.5%) by the reactivity approach. Aromatics and alkenes contributed most (73–84%) to the ozone formation potential. Toluene was the most abundant compound (11.8–12.7%) during every sampling period. When the maximum incremental reactivity approach was used, propene, toluene, m,p-xylene, 1-butene, and 1,2,4-trimethylbenzene were the five most abundant compounds during two sampling periods. X/B, T/B, and E/B ratios in this study were lower than those found in other cities, possibly due to the aging of the air mass at this site. Four components were extracted from application of PCA to the data. It was found that the contribution of vehicle exhaust to total VOCs accounted for 53% of VOCs, while emissions due to the solvent use contributed 33% of the total VOCs. Industrial sources contributed 3% and biogenic sources contributed 11%. The results showed that vehicle exhausts (i.e., unburned vehicle emissions + vehicle internal engine combustion) were dominant in VOC emissions during the experimental period. The solvent use made the second most significant contribution to ambient VOCs.

Volatile organic compounds (VOCs) in the air of Beijing City were measured at the heights of 8, 32, 140 and 280 m on the Beijing 325 m meteorological tower in autumn 2005. Concentrations of fifty-five compounds were determined by quantitative analytical methods. Our study utilized GC/MS analysis of 0.5 l air sample that were cryo-concentrated prior to analysis. The vertical distributions of VOCs were also investigated using 1-butene, isopentane, dichloromethane and toluene as representative compounds of several different categories. It is shown that 1-butene followed by 2-butene, isopentane followed by n-pentane, dichloromethane followed by chloroform and toluene followed by benzene are the most abundant compounds in the categories of alkene, alkane, halocarbon and aromatic hydrocarbon, respectively. The concentrations of TVOCs range from 51.2+/-39.7 ppb to 83.6+/-44.4 ppb on clear days, but from 62.9+/-19.0 ppb to 105.0+/-59.2 ppb on haze days. While alkenes and halocarbons contribute little to TVOCs, alkanes provide the largest percentage, ranging from about 46% to 63% at four different heights, which are followed by aromatic hydrocarbons ranging from about 15% to 27%. The vertical distributions of VOCs are complex. On clear days most distribution profiles show a decreasing trend with increasing height. On haze days, however, they exhibit first a decrease with increasing altitude from 8 m to 140 m and then a significant increase at 280 m. These results are understood by analyzing how the vertical distributions of VOCs are affected jointly by several factors such as meteorological parameters and transport property. In addition, principal components analysis (PCA) and cluster analysis show that VOCs have different origins at different heights.