Ozone and haze pollution weakens net primary productivity in China

Atmospheric pollutants have both beneficial and detrimental effects on carbon uptake by land ecosystems. Surface ozone (O3) damages leaf photosynthesis by oxidizing plant cells, while aerosols promote carbon uptake by increasing diffuse radiation and exert additional influences through concomitant perturbations to meteorology and hydrology. China is currently the world’s largest emitter of both carbon dioxide and short-lived air pollutants. The land ecosystems of China are estimated to provide a carbon sink, but it remains unclear whether air pollution acts to inhibit or promote carbon uptake. Here, we employ Earth system modeling and multiple measurement datasets to assess the separate and combined effects of anthropogenic O3 and aerosol pollution on net primary productivity (NPP) in China. In the present day, O3 reduces annual NPP by 0.6 Pg C (14 %) with a range from 0.4 Pg C (low O3 sensitivity) to 0.8 Pg C (high O3 sensitivity). In contrast, aerosol direct effects increase NPP by 0.2 Pg C (5 %) through the combination of diffuse radiation fertilization, reduced canopy temperatures, and reduced evaporation leading to higher soil moisture. Consequently, the net effects of O3 and aerosols decrease NPP by 0.4 Pg C (9 %) with a range from 0.2 Pg C (low O3 sensitivity) to 0.6 Pg C (high O3 sensitivity). However, precipitation inhibition from combined aerosol direct and indirect effects reduces annual NPP by 0.2 Pg C (4 %), leading to a net air pollution suppression of 0.8 Pg C (16 %) with a range from 0.6 Pg C (low O3 sensitivity) to 1.0 Pg C (high O3 sensitivity). Our results reveal strong dampening effects of air pollution on the land carbon uptake in China today. Following the current legislation emission scenario, this suppression will be further increased by the year 2030, mainly due to a continuing increase in surface O3. However, the maximum technically feasible reduction scenario could drastically relieve the current level of NPP damage by 70 % in 2030, offering protection of this critical ecosystem service and the mitigation of long-term global warming

Aerosol Optical Properties Over Mount Song, a Rural Site in Central China

Seasonal variations of aerosol optical depth (AOD), Ångström exponent (α), single scattering albedo (SSA), water vapor content (WVC), aerosol size distribution and refractive index at Mount Song, a rural site in Central China are analyzed using ground-based sunphotometer data for the period April 2012 to May 2014 for the first time. The results show that the area is highly polluted even the major anthropogenic emission sources are far away. Seasonal mean AOD is high (0.72 ± 0.52) during summer (June–August) season and low (0.51 ± 0.38) during autumn (September–November) season. The monthly mean α is very low (0.81 ± 0.30) in the month of April and very high (1.32 ± 0.23) in the month of September with annual average value 1.1. Analysis of the frequency distributions of AOD and α in each season indicates presence of fine-mode particles. Strong seasonal variations in SSA is likely due to local biomass burning and regional transport of anthropogenic aerosol particles, Seasonal mean SSA at 440 nm wavelength are 0.89 ± 0.04, 0.91 ± 0.06, 0.89 ± 0.07 and 0.92 ± 0.05, respectively during spring, summer, autumn and winter seasons. It is also shown that the scattering capacity of the fine-mode particles is relatively higher during summer compared to other seasons. The aerosol volume size distributions show pronounced seasonal variations in volume concentration, peak radius and the fine-mode particles are evidently dominant during summer season due to the hygroscopic growth. A distinct seasonal variations in aerosol parameters confirm the transport of polluted air mass at Mount Song

Evaluation of Aerosol Optical Depth and Aerosol Models from VIIRS Retrieval Algorithms over North China Plain

The first Visible Infrared Imaging Radiometer Suite (VIIRS) was launched on Suomi National Polar-orbiting Partnership (S-NPP) satellite in late 2011. Similar to the Moderate resolution Imaging Spectroradiometer (MODIS), VIIRS observes top-of-atmosphere spectral reflectance and is potentially suitable for retrieval of the aerosol optical depth (AOD). The VIIRS Environmental Data Record data (VIIRS_EDR) is produced operationally by NOAA, and is based on the MODIS atmospheric correction algorithm. The MODIS-like VIIRS data (VIIRS_ML) are being produced experimentally at NASA, from a version of the dark-target algorithm that is applied to MODIS. In this study, the AOD and aerosol model types from these two VIIRS retrieval algorithms over the North China Plain (NCP) are evaluated using the ground-based CE318 Sunphotometer (CE318) measurements during 2 May 2012-31 March 2014 at three sites. These sites represent three different surface types: urban (Beijing), suburban (XiangHe) and rural (Xinglong). Firstly, we evaluate the retrieved spectral AOD. For the three sites, VIIRS_EDR AOD at 550 nm shows a positive mean bias (MB) of 0.04-0.06 and the correlation of 0.83-0.86, with the largest MB (0.10-0.15) observed in Beijing. In contrast, VIIRS_ML AOD at 550 nm has overall higher positive MB of 0.13-0.14 and a higher correlation (0.93-0.94) with CE318 AOD. Secondly, we evaluate the aerosol model types assumed by each algorithm, as well as the aerosol optical properties used in the AOD retrievals. The aerosol model used in VIIRS_EDR algorithm shows that dust and clean urban models were the dominant model types during the evaluation period. The overall accuracy rate of the aerosol model used in VIIRS_ML over NCP three sites (0.48) is higher than that of VIIRS_EDR (0.27). The differences in Single Scattering Albedo (SSA) at 670 nm between VIIRS_ML and CE318 are mostly less than 0.015, but high seasonal differences are found especially over the Xinglong site. The values of SSA from VIIRS_EDR are higher than that observed by CE318 over all sites and all assumed aerosol modes, with a positive bias of 0.02-0.04 for fine mode, 0.06-0.12 for coarse mode and 0.03-0.05 for bi-mode at 440nm. The overestimation of SSA but positive AOD MB of VIIRS_EDR indicate that other factors (e.g. surface reflectance characterization or cloud contamination) are important sources of error in the VIIRS_EDR algorithm, and their effects on aerosol retrievals may override the effects from non-ideality in these aerosol models

Evaluation of aerosol optical depth and aerosol models from VIIRS retrieval algorithms over North China Plain

The first Visible Infrared Imaging Radiometer Suite (VIIRS) was launched on Suomi National Polar-orbiting Partnership (S-NPP) satellite in late 2011. Similar to the Moderate resolution Imaging Spectroradiometer (MODIS), VIIRS observes top-of-atmosphere spectral reflectance and is potentially suitable for retrieval of the aerosol optical depth (AOD). The VIIRS Environmental Data Record data (VIIRS_EDR) is produced operationally by NOAA, and is based on the MODIS atmospheric correction algorithm. The “MODIS-like” VIIRS data (VIIRS_ML) are being produced experimentally at NASA, from a version of the “dark-target” algorithm that is applied to MODIS. In this study, the AOD and aerosol model types from these two VIIRS retrieval algorithms over the North China Plain (NCP) are evaluated using the ground-based CE318 Sunphotometer (CE318) measurements during 2 May 2012 – 31 March 2014 at three sites. These sites represent three different surface types: urban (Beijing), suburban (XiangHe) and rural (Xinglong). Firstly, we evaluate the retrieved spectral AOD. For the three sites, VIIRS_EDR AOD at 550 nm shows a positive mean bias (MB) of 0.04-0.06 and the correlation of 0.83-0.86, with the largest MB (0.10-0.15) observed in Beijing. In contrast, VIIRS_ML AOD at 550 nm has overall higher positive MB of 0.13-0.14 and a higher correlation (0.93-0.94) with CE318 AOD. Secondly, we evaluate the aerosol model types assumed by each algorithm, as well as the aerosol optical properties used in the AOD retrievals. The aerosol model used in VIIRS_EDR algorithm shows that dust and clean urban models were the dominant model types during the evaluation period. The overall accuracy rate of the aerosol model used in VIIRS_ML over NCP three sites (0.48) is higher than that of VIIRS_EDR (0.27). The differences in Single Scattering Albedo (SSA) at 670 nm between VIIRS_ML and CE318 are mostly less than 0.015, but high seasonal differences are found especially over the Xinglong site. The values of SSA from VIIRS_EDR are higher than that observed by CE318 over all sites and all assumed aerosol modes, with a positive bias of 0.02-0.04 for fine mode, 0.06-0.12 for coarse mode and 0.03-0.05 for bi-mode at 440nm. The overestimation of SSA but positive AOD MB of VIIRS_EDR indicate that other factors (e.g. surface reflectance characterization or cloud contamination) are important sources of error in the VIIRS_EDR algorithm, and their effects on aerosol retrievals may override the effects from non-ideality in these aerosol models

Large contribution of meteorological factors to inter-decadal changes in regional aerosol optical depth

Aerosol optical depth (AOD) has become a crucial metric for assessing global climate change. Although global and regional AOD trends have been studied extensively, it remains unclear what factors are driving the inter-decadal variations in regional AOD and how to quantify the relative contribution of each dominant factor. This study used a long-term (1980–2016) aerosol dataset from the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2) reanalysis, along with two satellite-based AOD datasets (MODIS/Terra and MISR) from 2001 to 2016, to investigate the long-term trends in global and regional aerosol loading. Statistical models based on emission factors and meteorological parameters were developed to identify the main factors driving the inter-decadal changes of regional AOD and to quantify their contribution. Evaluation of the MERRA-2 AOD with the ground-based measurements of AERONET indicated significant spatial agreement on the global scale (r= 0.85, root-mean-square error = 0.12, mean fractional error = 38.7 %, fractional gross error = 9.86 % and index of agreement = 0.94). However, when AOD observations from the China Aerosol Remote Sensing Network (CARSNET) were employed for independent verification, the results showed that MERRA-2 AODs generally underestimated CARSNET AODs in China (relative mean bias = 0.72 and fractional gross error =−34.3 %). In general, MERRA-2 was able to quantitatively reproduce the annual and seasonal AOD trends on both regional and global scales, as observed by MODIS/Terra, although some differences were found when compared to MISR. Over the 37-year period in this study, significant decreasing trends were observed over Europe and the eastern United States. In contrast, eastern China and southern Asia showed AOD increases, but the increasing trend of the former reversed sharply in the most recent decade. The statistical analyses suggested that the meteorological parameters explained a larger proportion of the AOD variability (20.4 %–72.8 %) over almost all regions of interest (ROIs) during 1980–2014 when compared with emission factors (0 %–56 %). Further analysis also showed that SO2 was the dominant emission factor, explaining 12.7 %–32.6 % of the variation in AOD over anthropogenic-aerosol-dominant regions, while black carbon or organic carbon was the leading factor over the biomass-burning-dominant (BBD) regions, contributing 24.0 %–27.7 % of the variation. Additionally, wind speed was found to be the leading meteorological parameter, explaining 11.8 %–30.3 % of the variance over the mineral-dust-dominant regions, while ambient humidity (including soil moisture and relative humidity) was the top meteorological parameter over the BBD regions, accounting for 11.7 %–35.5 % of the variation. The results of this study indicate that the variation in meteorological parameters is a key factor in determining the inter-decadal change in regional AOD.This research has been supported by the National Science Fund for Distinguished Young Scholars (grant no. 41825011), the National Key R & D Program Pilot Projects of China (grant nos. 2016YFA0601901 and 2016YFC0203304), the National Natural Science Foundation of China (grant no. 41590874), the CAMS Basis Research Project (grant no. 2017Z011), the European Union Seventh Framework Programme(FP7/2007-2013) (grant no. 262254), and the AERONET-Europe ACTRIS-2 program, European Union's Horizon 2020 research and innovation programme (grant no. 654109)

A comparative analysis of aerosol microphysical, optical and radiative properties during the Spring Festival holiday over Beijing and surrounding regions

Using ground-based data, meteorological observations, and atmospheric environmental monitoring data, a comparative analysis of the microphysical and optical properties, and radiative forcing of aerosols was conducted between three stations in different developed environments during a severe air pollution episode during the Spring Festival over Beijing. During the most polluted period, the daily peak values of the aerosol optical depth were ~1.62, ~1.73, and ~0.74, which were about 2.6, 2.9, and 2.1 times higher than the background levels at the CAMS, Xianghe, and Shangdianzi sites, respectively. The daily peak values of the single scattering albedo were ~0.95, ~0.96, and ~0.87. The volume of fine-mode particles varied from 0.04 to 0.21 µm3 µm-2, 0.06 to 0.17 µm3 µm-2, and 0.01 to 0.10 µm3 µm-2, which were about 0.3 to 5.8, 1.1 to 4.7, and 1.2 to 8.9 times greater than the background values, respectively. The daily absorption aerosol optical depth was ~0.01 to ~0.13 at CAMS, ~0.03 to ~0.14 at Xianghe, and ~0.01 to ~0.09 at Shangdianzi, and the absorption Ångström exponents reflected a significant increase in organic aerosols over CAMS and Xianghe and in black carbon over Shangdianzi. Aerosol radiative forcing at the bottom of the atmosphere varied from -20 to -130, -40 to -150, and -10 to -110 W m-2 for the whole holiday period, indicating the cooling effect. The potential source contribution function and concentration-weighted trajectory analysis showed that Beijing, the southern parts of Hebei and Shanxi, and the central northern part of Shandong contributed greatly to the pollution

Column aerosol optical properties and aerosol radiative forcing during a serious haze-fog month over North China Plain in 2013 based on ground-based sunphotometer measurements

In January 2013, North China Plain experienced several serious haze events. Cimel sunphotometer measurements at seven sites over rural, suburban and urban regions of North China Plain from 1 to 30 January 2013 were used to further our understanding of spatial-temporal variation of aerosol optical parameters and aerosol radiative forcing (ARF). It was found that Aerosol Optical Depth at 500 nm (AOD500 nm) during non-pollution periods at all stations was lower than 0.30 and increased significantly to greater than 1.00 as pollution events developed. The Angstrom exponent (Alpha) was larger than 0.80 for all stations most of the time. AOD500 nm averages increased from north to south during both polluted and non-polluted periods on the three urban sites in Beijing. The fine mode AOD during pollution periods is about a factor of 2.5 times larger than that during the non-pollution period at urban sites but a factor of 5.0 at suburban and rural sites. The fine mode fraction of AOD675 nm was higher than 80% for all sites during January 2013. The absorption AOD675 nm at rural sites was only about 0.01 during pollution periods, while ~0.03–0.07 and 0.01–0.03 during pollution and non-pollution periods at other sites, respectively.This work is financially supported by grants from the National Key Project of Basic Research (2011CB403401 and 2014CB441201), the Project (41005086, 41275167 and 41130104) supported by NSFC, the Strategic Priority Research Programme of the Chinese Academy of Sciences (Grant no. XDA05100301), CAMS Basis Research Project (2012Y02 and 2013Z007). Cimel master calibration of CARSNET was performed at the AERONET-EUROPE calibration center (LOA and AEMET-Tenerife), supported by ACTRIS (European Union Seventh Framework Programme (FP7/2007-2013) under grant agreement no. 262254