Long-run dynamics of renewable energy consumption on carbon emissions and economic growth in the European union

This paper examines long-run and short-run dynamics of renewable energy consumption on carbon dioxide (CO₂) emissions and economic growth in the European Union. This study employs cointegration tests, Granger causality tests and vector error correction estimates to examine the direction of Granger causality, the long-run dynamics of economic growth and energy variables on carbon emissions. This study analyses time series data from the World Development Indicators over the period from1961 to 2012. The results of this study support a link between renewable energy consumption, economic growth, industrialization, exports and CO₂ emissions in the long-run and short-run. The results support that the sign of the long-run dynamics from the endogenous variables to the CO₂ emissions variable is negative and significant, which implies that the energy and environmental policies of the European Union aimed at curbing CO₂ emissions must have been effective in the long-term. Furthermore, renewable energy consumption and exports have significant negative impact on CO₂ emissions in the short-run. However, industrialization and economic growth have positive impact on CO₂ emissions in the short-run. The results suggest that both economic growth and industrialization must have been achieved at the cost of harming the environment. The finding suggests that the increasing consumption of renewable energy tends to play an important role in curbing carbon emissions in the region.     

Economic growth,international trade,and the depletion or conservation of renewable natural resources

Conservation of renewable natural resources and promotion of economic growth are both sustainable development goals. Here, we study the interdependency between economic growth, international trade, and the use of renewable natural resources—under alternative institutional settings of either open access or full property rights—in an endogenous growth model. We find that if the resource is depleted over time, consumption growth is reduced. Economic growth and international trade only impact resource use when the resource is harvested under full property rights. Then, widening international trade can lead countries to shift from conservation to depletion. Changes in the institutional setting of resource use in one country may have repercussions on trading partners. Our results indicate potential trade-offs between the sustainable development goals and imply that policies focusing on resource use or trade (e.g., international trade bans or certified trade) are not sufficient to prevent resource depletion.     

Temporal trends in agricultural water use and the relationships to hydroclimatic factors in the High Plains aquifer region

The High Plains aquifer (HPA) is the primary water source for agricultural irrigation in the US Great Plains. The water levels in many locations of the aquifer have declined steadily over the past several decades because the rate of water withdrawals exceeds recharge, which has been a serious concern to the water resources management in the region. We evaluated temporal trends and variations in agricultural water use and hydroclimatic variables including precipitation, air temperature, reference evapotranspiration, runoff, groundwater level, and terrestrial water storage across the HPA region for different periods from 1985 to 2020 at the grid, county, or region scale. The results showed that water withdrawals decreased from 21.3 km³/year in 1985 to 18.2 km³/year in 2015, while irrigated croplands increased from 71,928 km² in 1985 to 78,464 km² in 2015 in the entire HPA. The hydroclimatic time-series showed wetting trends in most of the northern HPA, but drying and warming trends in the southern region from 1985 to 2020. The groundwater level time-series indicated flat trends in the north, but significant declining in the central and southern HPA. Trends in irrigation water withdrawals and irrigation area across the HPA were controlled by the advancement of irrigation systems and technologies and the management of sustainable water use, but also were affected by dynamical changes in the hydroclimatic conditions.     

A framework for allocating conservation resources among multiple threats and actions

Land managers decide how to allocate resources among multiple threats that can be addressed through multiple possible actions. Additionally, these actions vary in feasibility, effectiveness, and cost. We sought to provide a way to optimize resource allocation to address multiple threats when multiple management options are available, including mutually exclusive options. Formulating the decision as a combinatorial optimization problem, our framework takes as inputs the expected impact and cost of each threat for each action (including do nothing) and for each overall budget identifies the optimal action to take for each threat. We compared the optimal solution to an easy to calculate greedy algorithm approximation and a variety of plausible ranking schemes. We applied the framework to management of multiple introduced plant species in Australian alpine areas. We developed a model of invasion to predict the expected impact in 50 years for each species-action combination that accounted for each species’ current invasion state (absent, localized, widespread); arrival probability; spread rate; impact, if present, of each species; and management effectiveness of each species-action combination. We found that the recommended action for a threat changed with budget; there was no single optimal management action for each species; and considering more than one candidate action can substantially increase the management plan's overall efficiency. The approximate solution (solution ranked by marginal cost-effectiveness) performed well when the budget matched the cost of the prioritized actions, indicating that this approach would be effective if the budget was set as part of the prioritization process. The ranking schemes varied in performance, and achieving a close to optimal solution was not guaranteed. Global sensitivity analysis revealed a threat's expected impact and, to a lesser extent, management effectiveness were the most influential parameters, emphasizing the need to focus research and monitoring efforts on their quantification.     

Can climate mitigation help the poor? Measuring impacts of the CDM in rural China

This study examines whether investment in climate change mitigation contributes to poverty alleviation. We investigate the impacts of the renewable energy-based clean development mechanism (RE-CDM) projects on rural communities in China. The impacts of RE-CDM projects are estimated by combining propensity score matching with the difference-in-differences approach. We found that the biomass-based CDM projects significantly contribute to income improvement and employment generation in rural communities in China. Our estimation results also reveal that wind energy-based CDM projects have the potential to increase income and the share of labor force in the primary industry in rural areas. These results suggest different channels through which renewable energy sources affect income.     

Microtargeting for conservation

Widespread human action and behavior change is needed to achieve many conservation goals. Doing so at the requisite scale and pace will require the efficient delivery of outreach campaigns. Conservation gains will be greatest when efforts are directed toward places of high conservation value (or need) and tailored to critical actors. Recent strategic conservation planning has relied primarily on spatial assessments of biophysical attributes, largely ignoring the human dimensions. Elsewhere, marketers, political campaigns, and others use microtargeting—predictive analytics of big data—to identify people most likely to respond positively to particular messages or interventions. Conservationists have not yet widely capitalized on these techniques. To investigate the effectiveness of microtargeting to improve conservation, we developed a propensity model to predict restoration behavior among 203,645 private landowners in a 5,200,000 ha study area in the Chesapeake Bay Watershed (U.S.A.). To isolate the additional value microtargeting may offer beyond geospatial prioritization, we analyzed a new high-resolution land-cover data set and cadastral data to identify private owners of riparian areas needing restoration. Subsequently, we developed and evaluated a restoration propensity model based on a database of landowners who had conducted restoration in the past and those who had not (n = 4978). Model validation in a parallel database (n = 4989) showed owners with the highest scorers for propensity to conduct restoration (i.e., top decile) were over twice as likely as average landowners to have conducted restoration (135%). These results demonstrate that microtargeting techniques can dramatically increase the efficiency and efficacy of conservation programs, above and beyond the advances offered by biophysical prioritizations alone, as well as facilitate more robust research of many social–ecological systems.     

The impact of coal and non-coal consumption on China's energy performance improvement

China is the world's largest energy consumer, and coal accounts for a higher proportion of the country's total energy consumption, yet during its 12th five-year plan (2011–2015), the coal share among total energy consumption significantly decreased. Previous studies exploring energy performance typically used energy consumption as an input, but this lacks the analytical capacity for the structure of energy consumption. Thus, this study splits energy input into two different inputs, coal consumption and non-coal energy consumption, and based on their differences with other variables, uses the hybrid dynamic data envelopment analysis model to assess the energy performance of China's provincial industrial sector during the period 2011 to 2015. We then compare coal consumption's and non-coal consumption's rooms for improvement and conclude that provinces in eastern and central China should reduce the amount of coal consumption, thereby improving energy performance. Conversely, provinces in the western region should target a balance between energy utilization efficiency and coal consumption.     

HUD状态下飞行员视觉注意资源分配机制研究

为了解决平视显示器（Head Up Display,HUD）飞行中的注意资源分配问题，基于飞行模拟器，设计双作业飞行任务开展相关研究。基于事件相关电位（Event Related Potential，ERP）技术，选取行为绩效和P300成分为评价指标，采用oddball模式，在双作业飞行任务条件下开展实验研究。结果表明:随主任务难度的增加，主、辅任务的作业绩效均显著下降，被试者对HUD上异常信息的正确操作率降低，且反应时间延长；随主任务难度的增加，由辅任务所诱发的P300的波幅显著降低。在实验结果的基础上，最终提出了HUD状态下飞行员视觉注意资源分配机制。     

瓦斯压力对卸荷原煤力学特性及能量特征的影响

运用自主研制的含瓦斯煤热流固耦合三轴伺服渗流试验装置,以原煤煤样作为研究对象,进行了含瓦斯煤固定轴向压力、卸围压的渗流试验,研究了卸围压过程中瓦斯压力对煤样力学特性和能量特征的影响。结果表明:在轴压加载阶段,煤样的变形模量基本不变,泊松比逐渐减小;在定轴压卸围压阶段,煤样的变形模量先小幅度增加,然后逐渐减小,泊松比则逐渐增大。瓦斯压力越高,煤样的承载能力越低,煤样发生破坏时相应的轴向应变和围压卸荷量百分比越小,而煤样破坏时的径向变形和扩容量越大。各应变围压柔量Δεi与瓦斯压力呈线性关系且线性相关性良好。随瓦斯压力升高,轴向应变的围压敏感性降低,径向应变和体积应变的围压敏感性显著升高。随瓦斯压力升高,煤样发生破坏时存储的弹性应变能Ue减小,而总能量U、耗散能Ud和耗散能比例Ud/U都增大。     

惰性粉体对蔗糖粉尘最小点火能的影响研究

为了预防蔗糖粉尘爆炸,利用1.2 L哈特曼管研究了NH₄H₂PO₄与Al(OH₄对蔗糖粉尘爆炸的抑制作用。在蔗糖粉尘质量分数一定的条件下,通过改变 NH₄H₂PO₄与Al(OH)₄的粒径和质量分数,测定其对蔗糖粉尘爆炸的抑制效果。结果表明:随着NH₄H₂PO₄和Al(OH)₄质量分数的增加,粒径的减小,蔗糖粉尘的最小点火能均逐渐增大,当惰性粉体增加到一定质量时,蔗糖粉尘被完全惰化,在蔗糖粉尘中分别加入粒径为48~74,38~47,25~37 μm的NH₄H₂PO₄和Al(OH)₄,3种粒径的NH₄H₂PO₄使蔗糖粉尘完全惰化的质量分数分别为40%,35%,30%,3种粒径的Al(OH)₃使蔗糖粉尘惰化的质量分数均为60%。因此(NH₄)H₂PO₄抑制蔗糖粉尘爆炸的效果比Al(OH)₃更显著。