Modeling Environmental Impacts of Urban Expansion: A Systematic Method for Dealing with Uncertainties

In a rapidly transitioning China, urban land use has changed dramatically, both spatially and in terms of magnitude; these changes have significantly affected the natural environment. This paper reports the development of an Integrated Environmental Assessment of Urban Land Use Change (IEA-ULUC) model, which combines cellular automata, scenario analysis, and stochastic spatial sampling with the goal of exploring urban land-use change, related environmental impacts, and various uncertainties. By applying the IEA-ULUC model to a new urban development area in Dalian in northeastern China, the evolution of spatial patterns from 1986 to 2005 was examined to identify key driving forces affecting the changing trajectories of local land use. Using these results, future urban land use in the period 2005–2020 was projected for four scenarios of economic development and land-use planning regulation. A stochastic sampling process was implemented to generate industrial land distributions for each land expansion scenario. Finally, domestic and industrial water pollution loads to the ocean were estimated, and the environmental impacts of each scenario are discussed. The results showed that the four urban expansion scenarios could lead to considerable differences in environmental responses. In principle, urban expansion scenarios along the intercity transportation rail/roadways could have higher negative environmental impacts than cluster-developing scenarios, while faster economic growth could more intensely aggravate the environment than in the moderate growth scenarios

Quantifying Baseline Emission Factors of Air Pollutants in China’s Regional Power Grids

Drawing lessons from the clean development mechanism (CDM), this paper developed a combined margin methodology to quantify baseline emission factors of air pollutants in China’s regional power grids. The simple average of baseline emission factors of SO₂, NO_<i>X</i>, and PM_2.5 in China’s six power grids in 2010 were respectively 1.91 kg/MWh, 1.83 kg/MWh and 0.32 kg/MWh. Several low-efficient mitigation technologies, such as low nitrogen oxide burner (LNB), were suggested to be replaced or used together with other technologies in order to virtually decrease the grid’s emission factor. The synergies between GHG and air pollution mitigation in China’s power sector was also notable. It is estimated that in 2010, that every 1% CO₂ reduction in China’s power generation sector resulted in the respective coreduction of 1.1%, 0.5%, and 0.8% of SO₂, NO_<i>X</i>, and PM_2.5. Wind is the best technology to achieve the largest amount of coabatement in most parts of China. This methodology is recommended to be used in making comprehensive air pollution control strategies and in cobenefits analysis in future CDM approval processes

Targeted Discovery and Combinatorial Biosynthesis of Polycyclic Tetramate Macrolactam Combamides A–E

Polycyclic tetramate macrolactams (PoTeMs) are a growing class of natural products with distinct structure and diverse biological activities. By promoter engineering and heterologous expression of the cryptic <i>cbm</i> gene cluster, four new PoTeMs, combamides A–E (<b>1</b>–<b>4</b>), were identified. Additionally, two new derivatives, combamides E (<b>5</b>) and F (<b>6</b>), were generated via combinatorial biosynthesis. Together, our findings provide a sound base for expanding the structure diversities of PoTeMs through genome mining and combinatorial biosynthesis