Improvements of Biogenic Emission Estimation in China by Using WRF-CLM4-MEGAN Model

2020 ◽  
Author(s):  
Lifei Yin ◽  
Yu Song ◽  
Hongsheng Zhang ◽  
Xuhui Cai ◽  
Zhenying Xu ◽  
...  
2016 ◽  
Vol 23 (1) ◽  
pp. 137-149 ◽  
Author(s):  
Chang-Yong YI ◽  
Han-Seong GWAK ◽  
Dong-Eun LEE

Low carbon construction is an important operation management goal because greenhouse gas (GHG) reduc­tion has become a global concern. Major construction resources that contribute GHG, such as equipment and labour, are being targeted to achieve this goal. The GHG emissions produced by the resources vary with their operating conditions. It is commendable to provide a statistical GHG emission estimation method that models the transitory nature of resource states at micro-scale of construction operations. This paper proposes a computational method called Stochastic Carbon Emission Estimation (SCE2) that measures the variability of GHG emissions. It creates construction operation models consisting of atomic work tasks, utilizes hourly equipment fuel consumption and hourly labourer respiratory rates that change according to their operating conditions classified into five categories, and identifies an optimal resource combi­nation by trading off eco-economic performance metrics such as the amount of GHG emissions, operation completion time, operation completion cost, and productivity. The study is of value to researchers because SCE2 fill in a gap to eco-economic operation modelling and analysis tool which considers operating conditions at micro-scale of construction operation having many stochastic work tasks. This study is also relevance to practitioners because it allows project man­agers to achieve eco-economic goals while honouring predefined constraints associated with time and cost.


2016 ◽  
Vol 94 (1) ◽  
pp. 91-113 ◽  
Author(s):  
Prabir K. PATRA ◽  
Tazu SAEKI ◽  
Edward J. DLUGOKENCKY ◽  
Kentaro ISHIJIMA ◽  
Taku UMEZAWA ◽  
...  

2016 ◽  
Author(s):  
Alexandra-Jane Henrot ◽  
Tanja Stanelle ◽  
Sabine Schröder ◽  
Colombe Siegenthaler ◽  
Domenico Taraborrelli ◽  
...  

Abstract. A biogenic emission scheme based on the Model of Emissions of Gases and Aerosols from Nature (MEGAN) version 2.1 (Guenther et al., 2012) has been integrated into the ECHAM6-HAMMOZ chemistry climate model in order to calculate the emissions from terrestrial vegetation of 32 compounds. The estimated annual global total for the simulation period (2000–2012) is 634 Tg C yr−1. Isoprene is the main contributor to the average emission total accounting for 66 % (417 Tg C yr−1), followed by several monoterpenes (12 %), methanol (7 %), acetone (3.6 %) and ethene (3.6 %). Regionally, most of the high annual emissions are found to be associated to tropical regions and tropical vegetation types. In order to evaluate the implementation of the biogenic model in ECHAM-HAMMOZ, global and regional BVOC emissions of the reference simulation were compared to previous published experiment results with the MEGAN model. Several sensitivity simulations were performed to study the impact of different model input and parameters related to the vegetation cover and the ECHAM6 climate. BVOC emissions obtained with the biogenic model are within the range of previous published estimates. The large range of emission estimates can be attributed to the use of different input data and empirical coefficients within different setups of the MEGAN model. The biogenic model shows a high sensitivity to the changes in plant functional type (PFT) distributions and associated emission factors for most of the compounds. The global emission impact for isoprene is about −9 %, but reaches +75 % for α-pinene when switching to PFT-dependent emission factor distributions. Isoprene emissions show the highest sensitivity to soil moisture impact, with a global decrease of 12.5 % when the soil moisture activity factor is included in the model parameterization. Nudging ECHAM6 climate towards ERA-Interim reanalysis has impact on the biogenic emissions, slightly lowering the global total emissions and their interannual variability.


2020 ◽  
Author(s):  
Yang Yang ◽  
Yu Zhao ◽  
Lei Zhang ◽  
Jie Zhang ◽  
Xin Huang ◽  
...  

Abstract. We developed a top-down methodology combining the inversed chemistry transport modeling and satellite-derived tropospheric vertical column of NO2, and estimated the NOx emissions of Yangtze River Delta (YRD) region at a horizontal resolution of 9 km for January, April, July and October 2016. The effect of the top-down emission estimation on air quality modeling, and the response of ambient ozone (O3) and secondary inorganic aerosols (SO42−, NO3−, and NH4+, SNA) to the changed precursor emissions were evaluated with the Community Multi-scale Air Quality (CMAQ) system. The top-down estimates of NOx emissions were smaller than those in a national emission inventory, MEIC (i.e., the bottom-up estimates), for all the four months, and the monthly mean was calculated at 260.0 Gg/month, 24 % less than the bottom-up one. The NO2 concentrations simulated with the bottom-up estimate of NOx emissions were clearly higher than the ground observation, indicating the possible overestimation in current emission inventory attributed to its insufficient consideration of recent emission control in the region. The model performance based on top-down estimate was much better, and the biggest change was found for July with the normalized mean bias (NMB) and normalized mean error (NME) reduced from 111 % to −0.4 % and from 111 % to 33 %, respectively. The results demonstrate the improvement of NOx emission estimation with the nonlinear inversed modeling and satellite observation constraint. With the smaller NOx emissions in the top-down estimate than the bottom-up one, the elevated concentrations of ambient O3 were simulated for most YRD and they were closer to observation except for July, implying the VOC (volatile organic compound)-limit regime of O3 formation. With available ground observations of SNA in the YRD, moreover, better model performance of NO3− and NH4+ were achieved for most seasons, implying the effectiveness of precursor emission estimation on the simulation of secondary inorganic aerosols. Through the sensitivity analysis of O3 formation for April 2016, the decreased O3 concentrations were found for most YRD region when only VOCs emissions were reduced or the reduced rate of VOCs emissions was two times of that of NOx, implying the crucial role of VOCs control on O3 pollution abatement. The SNA level for January 2016 was simulated to decline 12 % when 30 % of NH3 emissions were reduced, while the change was much smaller with the same reduced rate for SO2 or NOx. The result suggests that reducing NH3 emissions was the most effective way to alleviate SNA pollution for YRD in winter.


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