ALBERT

Description: To comprehensively evaluate the effects of the recent “2+26” regional strategy for air quality improvement, we compared the variations in PM2.5 concentrations in Beijing during four pollution episodes with different emission-reduction strategies. The 2+26 strategy implemented in March 2018 led to a mean PM2.5 concentration 16.43 % lower than that during the pollution episode in March 2013, when no specific emission-reduction measures were in place. The same 2+26 strategy implemented in November 2017 led to a mean PM2.5 concentration 32.70 % lower than that during the pollution episode in November 2016, when local emission-reduction measures were implemented. The results suggested that the effects of the 2+26 regional emission-reduction measures on PM2.5 reductions were influenced by a diversity of factors and could differ significantly during specific pollution episodes. Furthermore, we found the proportions of sulfate ions decreased significantly, and nitrate ions were the dominant PM2.5 components during the two 2+26 orange alert periods. Meanwhile, the relative contribution of coal combustion to PM2.5 concentrations in Beijing during the pollution episodes in March 2013, November 2016, November 2017 and March 2018 was 40 %, 34 %, 28 % and 11 %, respectively, indicating that the recent “Coal to Gas” project and the contingent 2+26 strategy led to a dramatic decrease in coal combustion in the Beijing–Tianjin–Hebei region. On the other hand, the relative contribution of vehicle exhaust during the 2+26 orange alert periods in November 2017 and March 2018 reached 40 % and 54 %, respectively. The relative contribution of local emissions to PM2.5 concentrations in Beijing also varied significantly and ranged from 49.46 % to 89.35 % during the four pollution episodes. These results suggested that the 2+26 regional emission-reduction strategy should be implemented with red air pollution alerts during heavy pollution episodes to intentionally reduce the dominant contribution of vehicle exhausts to PM2.5 concentrations in Beijing, while specific emission-reduction measures should be implemented accordingly for different cities within the 2+26 framework.

Description: With frequent air pollution episodes in China, growing research emphasis has been put on quantifying meteorological influences on PM2.5 concentrations. However, these studies mainly focus on isolated cities, whilst meteorological influences on PM2.5 concentrations at the national scale have not yet been examined comprehensively. This research employs the CCM (convergent cross-mapping) method to understand the influence of individual meteorological factors on local PM2.5 concentrations in 188 monitoring cities across China. Results indicate that meteorological influences on PM2.5 concentrations have notable seasonal and regional variations. For the heavily polluted North China region, when PM2.5 concentrations are high, meteorological influences on PM2.5 concentrations are strong. The dominant meteorological influence for PM2.5 concentrations varies across locations and demonstrates regional similarities. For the most polluted winter, the dominant meteorological driver for local PM2.5 concentrations is mainly the wind within the North China region, whilst precipitation is the dominant meteorological influence for most coastal regions. At the national scale, the influence of temperature, humidity and wind on PM2.5 concentrations is much larger than that of other meteorological factors. Amongst eight factors, temperature exerts the strongest and most stable influence on national PM2.5 concentrations in all seasons. Due to notable temporal and spatial differences in meteorological influences on local PM2.5 concentrations, this research suggests pertinent environmental projects for air quality improvement should be designed accordingly for specific regions.

Description: With the completion of the Beijing Five-year Clean Air Action Plan by the end of 2017, the annual mean PM2.5 concentration in Beijing dropped dramatically to 58.0 µg m−3 in 2017 from 89.5 µg m−3 in 2013. However, controversies exist to argue that favourable meteorological conditions in 2017 were the major driver for such a rapid decrease in PM2.5 concentrations. To comprehensively evaluate this 5-year plan, we employed a Kolmogorov–Zurbenko (KZ) filter and WRF-CMAQ (Weather Research and Forecasting and the Community Multi-scale Air Quality) to quantify the relative contribution of meteorological conditions and the control of anthropogenic emissions to PM2.5 reduction in Beijing from 2013 to 2017. For these 5 years, the relative contribution of emission reduction to the decrease in PM2.5 concentrations calculated by KZ filtering and WRF-CMAQ was 80.6 % and 78.6 % respectively. KZ filtering suggested that short-term variations in meteorological and emission conditions contributed majorly to rapid changes in PM2.5 concentrations in Beijing. WRF-CMAQ revealed that the relative contribution of local and regional emission reduction to the PM2.5 decrease in Beijing was 53.7 % and 24.9 % respectively. For local emission-reduction measures, the regulation of coal boilers, increasing use of clean fuels for residential use and industrial restructuring contributed 20.1 %, 17.4 % and 10.8 % to PM2.5 reduction respectively. Both models suggested that the control of anthropogenic emissions accounted for around 80 % of the PM2.5 reduction in Beijing, indicating that emission reduction was crucial for air quality enhancement in Beijing from 2013 to 2017. Consequently, such a long-term air quality clean plan should be continued in the following years to further reduce PM2.5 concentrations in Beijing.

Description: With the completion of the Beijing Five-year Clean Air Action Plan by the end of 2017, the annual mean PM2.5 concentrations in Beijing dropped dramatically to 58.0 μg/m3 in 2017 from 89.5 μg/m3 in 2013. However, controversies exist to argue that favorable meteorological conditions in 2017 that helped pollution dispersion were the major factor for such rapid decrease in PM2.5 concentrations. To comprehensively evaluate this five-year plan, we employed Kolmogorov-Zurbenko (KZ) filtering and a WRF-CMAQ model to quantify the relative contribution of meteorological conditions and the control of anthropogenic emissions to PM2.5 reduction in Beijing from 2013 to 2017. For these five years, the relative contribution of emission-reduction measures to the decrease of PM2.5 concentrations in Beijing calculated by KZ filtering and the WRF-CMAQ model was 80.6 % and 78.6 % respectively. The WRF-CMAQ model further revealed that local and regional emission-reduction measures contributed to 53.7 % and 24.9 % of the PM2.5 reduction respectively. For local emission-reduction measures, the regulation of coal boilers, increasing clean fuels for residential use, industrial restructuring, the regulation of raise dust and vehicle emissions contributed to 20.1 %, 17.4 %, 10.8 %, 3.0 % and 2.4 % of PM2.5 reduction respectively. Both models suggested that the control of anthropogenic emissions contributed to around 80 % of the total decrease in PM2.5 concentrations in Beijing, indicating that emission control was crucial for the notable improvement in air quality in Beijing from 2013 to 2017. Therefore, such long-term air quality clean plan should be continued for the future years to further reduce PM2.5 concentrations in Beijing. Considering that different emission-reduction measures exert distinct effects on PM2.5 reduction and existing emission-reduction measures work poorly to reduce ozone concentrations, future strategies for emission-reduction should be designed and implemented accordingly.

Description: To comprehensively evaluate the effects of the recent 2+26 regional strategy for air quality improvement, we compared the variations in PM2.5 concentrations in Beijing during four pollution episodes with different emission-reduction strategies. The 2+26 strategy implemented in March 2018 led to a mean PM2.5 concentrations of 16.43 % lower than that during the pollution episode in March 2013, when no specific emission-reduction measures were in place. The same 2+26 strategy implemented in November 2017 led to a mean PM2.5 concentrations of 32.70 % lower than that during the pollution episode in November 2016, when local emission-reduction measures were implemented. The results suggested that the effects of the 2+26 regional emission-reduction measures on PM2.5 reductions were influenced by a diversity of factors and could differ significantly during specific pollution episodes. Furthermore, we found the proportions of sulfate ions decreased significantly and nitrate ions were the dominant PM2.5 components during the two 2+26 orange alert periods. Meanwhile, the relative contributions of coal combustion to PM2.5 concentrations in Beijing during the pollution episodes in March 2013, November 2016, November 2017 and March 2018 was 40 %, 34 %, 28 % and 11 % respectively, indicating that the recent Coal to Gas project and the contingent 2+26 strategy led to a dramatic decrease in coal combustion in the Beijing-Tianjin-Hebei Region. On the other hand, the relative contribution of vehicle exhaust during the 2+26 orange alert periods in November 2017 and March 2018 reached 40 % and 54 % respectively. The relative contribution of local emission to PM2.5 concentrations in Beijing also varied significantly and ranged from 49.46 % to 89.35 % during the four pollution episodes. These results suggested that the 2+26 regional emission-reduction strategy should be implemented with red air pollution alerts during heavy pollution episodes to intendedly reduce the dominant contribution of vehicle exhausts to PM2.5 concentrations in Beijing, while specific emission-reduction measures should be implemented accordingly for different cities within the 2+26 framework.

Description: With frequent haze events in China, growing research emphasis has been put on quantifying meteorological influences on PM2.5 concentrations. However, these studies mainly focus on isolated cities whilst meteorological influences on PM2.5 concentrations at the national scale have yet been examined comprehensively. This research employs the CCM (Cross Convergent Mapping) method to understand the causality influence of individual meteorological factors on local PM2.5 concentrations in 189 monitoring cities across China. Results indicate that meteorological influences on PM2.5 concentrations are of notable seasonal and regional variations. Generally, the higher PM2.5 concentrations, the larger influences meteorological factors exert on PM2.5 concentrations. The dominant meteorological influence for PM2.5 concentrations varies across locations and demonstrates regional similarities. For the most polluted winter, the dominant meteorological driver for local PM2.5 concentrations is mainly the wind within the North China region whilst precipitation is the dominant meteorological influence for most coastal regions. At the national scale, temperature, humidity, wind and air pressure exert stronger influences on PM2.5 concentrations than other meteorological factors. Due to notable temporal and spatial differences in meteorological influences on local PM2.5 concentrations, this research suggests pertinent environmental projects for air quality improvement should be designed accordingly for specific regions.

Description: In recent years, hydraulic quadruped robots have received increasing attention because of their strong environment adaptability and high load capacity. However, weight control is an important issue for mobile systems in consideration of limited onboard energy. Overweight will cause extra load on joints, reduce the flexibility of movement, and consume more power. Topology optimization is an effective tool to reduce volume and weight while maintaining enough strength. This article takes both optimal geometries and contained flow channels into consideration and gives solutions to structure design and good print quality in a manifold used on a robot. Using topology optimization, the volume of the manifold is further reduced by 50.7 %, while it can meet the mechanical requirement for actual application.