Arid soils where water and nutrients are scarce occupy over 30% of the Earth's total surface. However, the microbial autotrophy in the harsh environments remains largely unexplored. In this study, the abundance an...Arid soils where water and nutrients are scarce occupy over 30% of the Earth's total surface. However, the microbial autotrophy in the harsh environments remains largely unexplored. In this study, the abundance and diversity of autotrophic bacteria were investigated, by quantifying and profiling the large subunit genes of ribulose-1,5-bisphosphate carboxylase/oxygenase(Ru Bis CO) form I(cbb L) responsible for CO2 fixation, in the arid soils under three typical plant types(Haloxylon ammodendron, Cleistogenes chinensis,and Reaumuria soongorica) in Northwest China. The bacterial communities in the soils were also characterized using the 16 S r RNA gene. Abundance of red-like autotrophic bacteria ranged from 3.94 × 105 to 1.51 × 106 copies g-1dry soil and those of green-like autotrophic bacteria ranged from 1.15 × 106 to 2.08 × 106 copies g-1dry soil. Abundance of both red- and green-like autotrophic bacteria did not significantly differ among the soils under different plant types. The autotrophic bacteria identified with the cbb L gene primer were mainly affiliated with Alphaproteobacteria, Betaproteobacteria and an uncultured bacterial group, which were not detected in the 16 S r RNA library. In addition, 25.9% and 8.1% of the 16 S r RNA genes were affiliated with Cyanobacteria in the soils under H. ammodendron and R. soongorica, respectively. However, no Cyanobacteria-affiliated cbb L genes were detected in the same soils. The results suggested that microbial autotrophic CO2 fixation might be significant in the carbon cycling of arid soils, which warrants further exploration.展开更多
A smart grid power system for a small region consisting of 1,000 residential homes with electric heating appliances from the demand side,and a generic generation mix of nuclear,hydro,coal,gas and oil-based generators ...A smart grid power system for a small region consisting of 1,000 residential homes with electric heating appliances from the demand side,and a generic generation mix of nuclear,hydro,coal,gas and oil-based generators representing the supply side,is investigated using agent-based simulations.The simulation includes a transactive load control in a real-time pricing electricity market.The study investigates the impacts of adding wind power and demand response(DR)on both greenhouse gas(GHG)emissions and generator cycling requirements.The results demonstrate and quantify the effectiveness of DR in mitigating the variability of renewable generation.The extent to which greenhouse gas emissions can be mitigated is found to be highly dependent on the mix of generators and their operational capacity factors.It is expected that the effects of demand response on electricity use can reduce dependency on fossil fuel-based electricity generation.However,the anticipated mitigation of GHG emissions is found to dependent on the number and efficiency of fossil fuel generators,and especially on the capacity factor at which they operate.Therefore,if a generator(the marginal seller)is forced to use less efficient fossil fuel power generation schemes,it will result in higher GHG emissions.The simulations show that DR can yield a small reduction in GHG emissions,but also lead to a smaller increase in emissions in circumstances when,for example,a generator(the marginal seller)is forced to use less efficient fossil fuel power generation schemes.Nonetheless,DR is shown to enhance overall system operation,particularly by facilitating increased penetration of variable renewable electricity generation without jeopardizing grid operation reliability.DR reduces the amount of generator cycling by an increased order of magnitude,thereby reducing wear and tear,improving generator efficiency,and avoiding the need for additional operating reserves.The effectiveness of DR for these uses depends on the participation of responsive loads,and this study 展开更多
基金supported by the National Basic Research Program(973 Program)of China(No.2009-CB825103)the National Natural Science Foundation of China(No.40901119)
文摘Arid soils where water and nutrients are scarce occupy over 30% of the Earth's total surface. However, the microbial autotrophy in the harsh environments remains largely unexplored. In this study, the abundance and diversity of autotrophic bacteria were investigated, by quantifying and profiling the large subunit genes of ribulose-1,5-bisphosphate carboxylase/oxygenase(Ru Bis CO) form I(cbb L) responsible for CO2 fixation, in the arid soils under three typical plant types(Haloxylon ammodendron, Cleistogenes chinensis,and Reaumuria soongorica) in Northwest China. The bacterial communities in the soils were also characterized using the 16 S r RNA gene. Abundance of red-like autotrophic bacteria ranged from 3.94 × 105 to 1.51 × 106 copies g-1dry soil and those of green-like autotrophic bacteria ranged from 1.15 × 106 to 2.08 × 106 copies g-1dry soil. Abundance of both red- and green-like autotrophic bacteria did not significantly differ among the soils under different plant types. The autotrophic bacteria identified with the cbb L gene primer were mainly affiliated with Alphaproteobacteria, Betaproteobacteria and an uncultured bacterial group, which were not detected in the 16 S r RNA library. In addition, 25.9% and 8.1% of the 16 S r RNA genes were affiliated with Cyanobacteria in the soils under H. ammodendron and R. soongorica, respectively. However, no Cyanobacteria-affiliated cbb L genes were detected in the same soils. The results suggested that microbial autotrophic CO2 fixation might be significant in the carbon cycling of arid soils, which warrants further exploration.
基金This work was supported by Pacific Institute for Climate Solutions(PICS)the Wind Energy Strategic Network(WESNet)and the US Department of Energy(DOE),Office of Electricity Delivery and Energy Reliability.
文摘A smart grid power system for a small region consisting of 1,000 residential homes with electric heating appliances from the demand side,and a generic generation mix of nuclear,hydro,coal,gas and oil-based generators representing the supply side,is investigated using agent-based simulations.The simulation includes a transactive load control in a real-time pricing electricity market.The study investigates the impacts of adding wind power and demand response(DR)on both greenhouse gas(GHG)emissions and generator cycling requirements.The results demonstrate and quantify the effectiveness of DR in mitigating the variability of renewable generation.The extent to which greenhouse gas emissions can be mitigated is found to be highly dependent on the mix of generators and their operational capacity factors.It is expected that the effects of demand response on electricity use can reduce dependency on fossil fuel-based electricity generation.However,the anticipated mitigation of GHG emissions is found to dependent on the number and efficiency of fossil fuel generators,and especially on the capacity factor at which they operate.Therefore,if a generator(the marginal seller)is forced to use less efficient fossil fuel power generation schemes,it will result in higher GHG emissions.The simulations show that DR can yield a small reduction in GHG emissions,but also lead to a smaller increase in emissions in circumstances when,for example,a generator(the marginal seller)is forced to use less efficient fossil fuel power generation schemes.Nonetheless,DR is shown to enhance overall system operation,particularly by facilitating increased penetration of variable renewable electricity generation without jeopardizing grid operation reliability.DR reduces the amount of generator cycling by an increased order of magnitude,thereby reducing wear and tear,improving generator efficiency,and avoiding the need for additional operating reserves.The effectiveness of DR for these uses depends on the participation of responsive loads,and this study
