ALBERT

Description: The Beijing area has suffered from severe air pollution in recent years, including ozone pollution in the summer. In addition to the anthropogenic emissions inventory, understanding local ozone pollution requires a reliable biogenic volatile organic compound (BVOC) emission inventory. Forest coverage rose from 20.6 to 35.8 % from 1998 to 2013 in Beijing according to the National Forest Resource Survey (NFRS), and accurate representations of land cover for recent years is crucial for estimating BVOC emissions and their impacts on air quality. In this study, we established a high-resolution BVOC emission inventory in Beijing using the Model of Emissions of Gases and Aerosols from Nature (MEGAN) v2.1 with three independent leaf area index (LAI) products and three independent land cover products. Various combinations of the Global LAnd Surface Satellite (GLASS), Moderate-Resolution Imaging Spectroradiometer (MODIS) MCD15, and GEOland (GEO) v2 LAI datasets and the Finer Resolution Observation and Monitoring of Global Land Cover (FROM-GLC), MODIS MCD12Q1 plant functional type (PFT) products, and Climate Change Initiative Land Cover (CCI LC) products are used in five model sensitivity experiments (E1–E5), and the experiment using the FROM-GLC with the highest spatial resolution of 30 m and GLASS LAI products was treated as the baseline. These sensitivity calculations were driven by hourly, 3 km meteorological fields from the Weather Research and Forecasting (WRF) model. The following results were obtained: (1) according to the baseline estimate, the total amount of BVOC emissions is 75.9 Gg for the Beijing area, and isoprene, monoterpenes, sesquiterpenes and other VOCs account for 37.6, 14.6, 1.8 and 46 % of the total, respectively. Approximately three-quarters of BVOC emissions occur in the summer. (2) According to the sensitivity experiments, the LAI input does not significantly affect the BVOC emissions. Using MODIS MCD15Q1 and GEO v2 LAI led to slight declines of 2.6 and 1.4 %, respectively, of BVOC emissions in the same area. (3) The spatial distribution of PFTs from different inputs strongly influenced the spatial distribution of BVOC emissions. Furthermore, the cross-walking table for converting land cover classes to PFTs also has a strong impact on BVOC emissions; the sensitivity experiments showed that the estimate of BVOC emissions by CCI LC ranged from 42.1 to 70.2 Gg depending on the cross-walking table used.

Description: To analyze the middle-to-lower-troposphere atmospheric thermal contrast between the middle latitude over the Asian continent and over its eastern adjacent ocean near Japan, an empirical orthogonal function (EOF) analysis of the 40-yr ECMWF Re-Analysis (ERA-40) data of the June–August (JJA) 500-hPa geopotential height over the Asia–Pacific area (10°–80°N, 60°–180°E) during 1958–2000 was done. It shows that the dominating pattern of the thermal contrast may well be represented by a “seesaw” of 500-hPa geopotential height anomalies between a land area (40°–55°N, 75°–90°E) and an oceanic area (35°–42.5°N, 140°– 150°E). An index showing the difference between the two areas is defined as the middle-latitude land–sea thermal contrast index (LSI). The LSI has significant interannual and interdecadal variability. Its interannual variation is mainly attributed to the atmospheric thermal condition over the ocean, which has a remarkably regional unique feature, while the interdecadal variability is greatly attributed to that over the land. The LSI has a close connection to the East Asian summer precipitation. The results show that large (small) LSI is related to high (low) summer precipitation in the middle to lower reaches of the Yangtze River, Korea, Japan, and its eastern adjacent ocean at the same latitude, and low (high) precipitation in the South China Sea and tropical western Pacific, as well as low (high) precipitation in north China and high-latitude northeast Asia. The pattern of correlation between LSI and precipitation resembles the spatial distribution of the principle EOF mode of year-to-year precipitation variations. Furthermore, the variation of LSI is highly correlated to the time series of the first EOF mode of summer precipitation anomalies. This suggests that the middle-latitude land–sea thermal contrast is one of important factors to influence on the summer precipitation variations over the area from the whole East Asia to the western Pacific. The possible physical mechanisms of the land–sea thermal contrast impacting the East Asian summer monsoon precipitation are also investigated.

Description: The Beijing area has suffered from severe air quality pollution in recent years, including ozone pollution in the summer. Except for the anthropogenic emissions inventory, understanding the local ozone pollution still requires the reliable biogenic emission inventory. The forest coverage rate rose from 20.6 % to 35.8 % during 1998–2013 in Beijing according to the National Forest Resource Survey (NFRS). In this study, we established a new high resolution biogenic volatile organic compounds (BVOCs) emission inventory in Beijing based on Model of Emission of Gases and Aerosols from Nature (MEGAN) v2.1 model with three independent leaf area index (LAI) products and three independent land cover products. The Global LAnd Surface Satellite (GLASS) LAI, Moderate-Resolution Imaging Spectroradiometer (MODIS) MCD15 LAI, GEOland (GEO) v2 LAI datasets, and the Finer Resolution Observation and Monitoring of Global Land Cover (FROM-GLC), MODIS MCD12Q1 PFT products and Climate Change Initiative Land Cover (CCI-LC) products are used to design five experiments, as E1-E5, to calculate and test the sensitivity of the model. Based on the meteorological conditions from Weather Forecasting and Research (WRF) model, this inventory is an hourly inventory with 3-km spatial resolution. The result shows: (1) According to the baseline estimation, the total amount of BVOCs emissions are 99.9 Gg for Beijing area. The estimated annual emissions of isoprene, monoterpenes, sesquiterpenes and other VOCs are 52.5 Gg, 11.1 Gg, 1.4 Gg and 34.9 Gg, respectively. (2) The BVOCs emissions have the significant seasonal variability, which the summer season contributes 76.6 % of the total BVOCs emissions in Beijing, and the winter season only contributes 0.3 % emissions due to the low temperature and near-zero biomass of deciduous trees. (3) The broadleaf tree, as the dominant contributor to the BVOCs emissions, accounts for 94.5 % isoprene, 53.3 % monoterpenes, 53.8 % sesquiterpenes and 34.1 % other VOCs. (4) The MODIS LAI lead to a 17.4 % decline in BVOCs emissions because of the large mask area near the urban and water area. However, the GEO and GLASS LAI only led to a 1.0 % difference of total BVOCs emissions even with different temporal updating frequency of LAI. (5) The difference of PFTs have an obvious effect on the spatial distribution and density of BVOCs emissions. The MODIS and CCI-LC land cover led to an approximate 5.0 % and 26.0 % decline in BVOCs emissions compared with the baseline estimation. (6) The estimation of local BVOCs emissions in this study is much higher than the previous studies, and the development of local forest is main reason led to such the difference, thus implying that previous estimation of BVOCs in Beijing is underestimated and is not suitable for the current scene. In addition, further study will investigate and evaluate the effect of BVOCs on the local atmospheric environment through the regional chemistry transport model.

Description: Precise and rapid air quality simulations and forecasting are limited by the computational performance of the air quality model used, and the gas-phase chemistry module is the most time-consuming function in the air quality model. In this study, we designed a new framework for the widely used the Carbon Bond Mechanism Z (CBM-Z) gas-phase chemical kinetics kernel to adapt the single-instruction, multiple-data (SIMD) technology in next-generation processors to improve its calculation performance. The optimization implements the fine-grain level parallelization of CBM-Z by improving its vectorization ability. Through constructing loops and integrating the main branches, e.g., diverse chemistry sub-schemes, multiple spatial points in the model can be operated simultaneously on vector processing units (VPUs). Two generation CPUs – Intel Xeon E5-2680 V4 CPU and Intel Xeon Gold 6132 – and Intel Xeon Phi 7250 Knights Landing (KNL) are used as the benchmark processors. The validation of the CBM-Z module outputs indicates that the relative bias reaches a maximum of 0.025 % after 10 h integration with -fp-model fast =1 compile flag. The results of the module test show that the Multiple-Points CBM-Z (MP CBM-Z) resulted in 5.16× and 8.97× speedup on a single core of Intel Xeon E5-2680 V4 and Intel Xeon Gold 6132 CPUs, respectively, and KNL had a speedup of 3.69× compared with the performance of CBM-Z on the Intel Xeon E5-2680 V4 platform. For the single-node tests, the speedup on the two generation CPUs can reach 104.63× and 198.50× using message passing interface (MPI) and 101.02× and 194.60× using OpenMP, and the speedup on the KNL node can reach 175.23× using MPI and 167.45× using OpenMP. The speedup of the optimized CBM-Z is approximately 40 % higher on a one-socket KNL platform than on a two-socket Broadwell platform and about 13 %–16 % lower than on a two-socket Skylake platform. We also tested a three-dimensional chemistry transport model (CTM) named Nested Air Quality Prediction Model System (NAQPMS) equipped with the MP CBM-Z. The tests illustrate an obvious improvement on the performance for the CTM after adopting the MP CBM-Z. The results show that the MP CBM-Z leads to a speedup of 3.32 and 1.96 for the gas-phase chemistry module and the CTM on the Intel Xeon E5-2680 platform. Moreover, on the new Intel Xeon Gold 6132 platform, the MP CBM-Z gains 4.90× and 2.22× speedups for the gas-phase chemistry module and the whole CTM. For the KNL, the MP CBM-Z enables a 3.52× speedup for the gas-phase chemistry module, but the whole model lost 24.10 % performance compared to the CPU platform due to the poor performance of other modules. In addition, since this optimization seeks to improve the utilization of the VPU, the model is more suitable for the new generation processors adopting the more advanced SIMD technology. The results of our tests already show that the benefit of updating CPU improved by about 47 % by using the MP CBM-Z since the optimized code has better adaptability for the new hardware. This work improves the performance of the CBM-Z chemical kinetics kernel as well as the calculation efficiency of the air quality model, which can directly improve the practical value of the air quality model in scientific simulations and routine forecasting.

Description: Precise and rapid air quality simulation and forecasting are limited by the computation performance of the air quality model, and the gas-phase chemistry module is the most time-consuming function in the air quality model. In this study, we designed a new framework for the widely used Carbon Bond Mechanism Z (CBM-Z) gas-phase chemical kinetics kernel to adapt the Single Instruction Multiple Data (SIMD) technology in the next-generation processors for improving its calculation performance. The optimization implements the fine-grain level parallelization of CBM-Z by improving its vectorization ability. Through constructing loops and integrating the main branches, e.g. diverse chemistry sub-schemes, multiple spatial points in the model can be operated simultaneously on vector processing units (VPU). The Intel Xeon E5-2697 V4 CPU and Intel Xeon Phi 7250 Knight Landing (KNL) are used as the benchmark processors. The validation of the model outputs indicates that the relative errors are in an acceptable range (

Description: Satellite observations reveal that China has been leading the global greening trend in the past 2 decades. We assessed the impact of land cover change as well as climate variability on total biogenic volatile organic compound (BVOC) emission in China from 2001–2016. We found the greening trend in China is leading a national-scale increase in BVOC emission. The BVOC emission level in 2016 could be 11.7 % higher than that in 2001 because of higher tree cover fraction and vegetation biomass. On the regional scale, the BVOC emission level from 2013–2016 could be 8.6 %–19.3 % higher than that from 2001–2004 in hotspots including (1) northeastern China, (2) Beijing and its surrounding areas, (3) the Qin Mountains, (4) Yunnan Province, (5) Guangxi–Guangdong provinces, and (6) Hainan island because of the land cover change without considering the impact of climate variability. The comparison among different scenarios showed that vegetation changes resulting from land cover management are the main driver of BVOC emission change in China. Climate variability contributed significantly to interannual variations but not much to the changing trend during the study period. In the standard scenario, which considers both land cover change and climate variability, a statistically significant increasing trend can still be found in regions including Beijing and its surroundings, Yunnan Province, and Hainan island, and BVOC emission total amount in these regions from 2013–2016 is 11.0 %–17.2 % higher that from 2001–2004. We compared the long-term HCHO vertical columns (VC) from the satellite-based Ozone Monitoring Instrument (OMI) with the estimation of isoprene emission in summer. The results showed statistically significant positive correlation coefficients over the regions with high vegetation cover fractions. In addition, the isoprene emission and HCHO VC both showed statistically significant increasing trends in the south of China where these two variables have high positive correlation coefficients. This result may support our estimation of the variability and trends of BVOC emission in this region; however, the comparison still has large uncertainties since the chemical and physical processes, including transportation, diffusion and chemical reactions, were not considered. Our results suggest that the continued increase in BVOC will enhance the importance of considering BVOC when making policies for controlling ozone pollution in China along with ongoing efforts to increase the forest cover fraction.