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Abstract Kenya has made considerable policy efforts to expand its renewable energy portfolio to meet energy demand and mitigate greenhouse gas (GHG) emissions. Development of proper policies requires a robust framework for analyzing the benefits of renewable energy investments. Towards this end, this study applied a choice experiment analysis to determine how attributes (type of energy, ownership, impact on environment, distance and visibility, community job creation, and yearly renewable energy tax) impact the public willingness to pay for renewable energy development in Kenya. A nationwide survey of 1020 households was conducted in nine counties using conditional logit (MNL) and random parameter logit (RPL) frameworks. The results reveal that the Kenyan public places a high value on environmental impact, followed by type of renewable energy and community job creation, respectively. On the other hand, respondents do not place much emphasis on ownership or distance and visibility. Policy simulation suggests that while renewable energy adoption is highly valued by households, the total willingness to pay is not enough to cover the higher capital cost for the development of various renewable energy technologies.

Integrated assessment models (IAMs) are playing an increasingly important role in long-run sustainability analysis. At their core is a set of global economic and environmental accounts which capture a complete set of inter-industry and inter-regional relationships in the global economy in a consistent manner. While much attention is focused on the raw data and parameterization required to expand or add sectoral detail to IAMs, only rarely is there discussion of how different matrix balancing methods (i.e. translating disparate raw data sources into the consistent database) affect modeling results. This article offers an in-depth look into the database–modeling nexus in IAMs, focusing on the electric power sector which is both a major source of CO2 emissions and a critical vehicle for climate change mitigation. Comparisons of the prevailing matrix balancing algorithms show how the choice of database reconciliation methodology affects modeling results using policy-relevant simulations in the context of the electric power sector. The resulting insights can be applied to the disaggregation of other, technology rich sectors in the economy. We conclude that appropriate selection of database reconciliation methodologies can reduce the deviation between bottom-up and top-down modeling.

Abstract Real-world vehicle operating mode data (2.5 million 1 Hz records), collected by instrumenting the vehicles of 82 volunteer drivers with OBD datalogger and GPS while they drove their routine travel routes, were analyzed to quantify vehicle emissions estimate errors due to road grade and driving style in rural, hilly Vermont. Data were collected in winter and summer for MY 1996 and newer passenger cars and trucks only. EPA MOVES2010b was used to estimate running exhaust emissions associated with measured vehicle activity. Changes in vehicle specific power (VSP) and MOVES operating mode (OpMode) due to proper accounting for real-world road grade indicated emission rate errors between 10% and 48%, depending on pollutant, chiefly because grade-related changes in VSP could shift activity by as many as six OpModes, depending on road type. The correct MOVES OpMode assignment was made only 33–55% of the time when road grade was not included in the VSP calculation. Driving style of individual drivers was difficult to assess due to unknown traffic operations data, but the largest differences between individual drivers were observed on rural restricted roads, where traffic conditions and control have minimal impact. The results suggest the importance of (1) measuring and incorporating real-world road grade in order to correctly assign MOVES emission rates; and (2) developing a driving style typology to account for differences in the MOVES emissions estimates due to driver variability.

Abstract Hydrothermal treatment (HT) is one of the efficient approaches for upgrading municipal solid waste (MSW). In the present study, emission characteristics of polycyclic aromatic hydrocarbons (PAHs) from hydrothermally treated municipal solid waste (H-MSW) combustion alone and H-MSW/coal co-combustion were investigated at different temperatures. The results showed that for all fuel combustion, the majority of PAHs were 3- or 4-ring PAHs. In addition, flue gas had the highest yields of PAHs followed by fly ash and bottom ash, while the ring number of dominated PAHs in fly ash was higher than those in flue gas and bottom ash. Compared to MSW, H-MSW combustion generated less PAHs at the value of 1131.95–7649.24 μg/g. The blending of H-MSW and coal reduced total PAH emissions and positive interactions were observed between H-MSW and coal during co-combustion. The toxicity equivalent quantity (TEQ) values of the PAHs from combustion were in the order MSW > H-MSW > H-MSW/coal, which was consistent with the total PAH emissions. The present study illustrated that significant reduction of PAH emissions and toxicity from combustion could be achieved by HT and the blending of H-MSW and coal.

China’s steel industry is an energy-intensive sector. Synergistic reduction of emissions of CO2 and air pollutants (SO2, NOx, and PM2.5) in the steel industry has an important practical significance for climate change and air pollution control. According to the CO2 emission reduction intensity targets (CERO) and air pollutant emission targets (PERO) for 2020 and 2030, 28 types of energy-saving and emission reduction technologies (20 types of carbon reduction technology and eight types of air pollution end-of-pipe technology) were selected for examination, and a two-stage dynamic optimization model with collaborative implementation of PERO and CERO was built to assess the near future (2015–2020) and long-term (2020–2030) implementation plans for synergistic emissions reduction of CO2 and air pollutants. The results show that in the near future, the implementation of PERO will have a greater synergistic effect on CO2 emission reduction. CO2 emission reduction under PERO in 2020 will be 97 million tons (Mt) higher than that of CERO, an increase of nearly 26%. However, the effects of implementing CERO are better in the long run. Under CERO, the emission reductions of SO2, NOx, and PM2.5 in 2030 are 2.44 Mt, 1.47 Mt, and 0.86 Mt, respectively, and 7%, 4%, and 5% higher than the implementation of PERO. As far as marginal abatement cost is concerned, in the near future, the marginal abatement costs of CO2 and air pollutant equivalents are 1.06 yuan/kgCO2 and 133 yuan/kg pollution equivalent (pe) under PERO, which are 23% and 11% lower than that of CERO, while in the long run, the marginal abatement costs of CO2 and pollutant equivalents under CERO are 0.025 yuan/kgCO2 and 2.73 yuan/kgpe, about 96% and 95% lower than that of PERO.

Along with the arrival of the Internet era, all walks of life are beginning to promote the wisdom of the process. As the concept of "smarter planet" and "wisdom city" is put forward, the school as the frontier of knowledge and information service, as a new talent incubator should seize the opportunity and apply the advanced information technology to promote the construction of smart campus. Wisdom campus applies in many aspects of the school, such as campus unified call center, intelligent transportation, energy saving, safe campus, mobile application service system construction, campus comprehensive information system, public housing resources comprehensive management, the foundation of the campus design regulation, etc. This paper makes the planning of the implementation and method technology of the intelligent transportation system in the construction of smart campus.

The influence of climate change on the regional hydrological cycle has been an international scientific issue that has attracted more attention in recent decades due to its huge effects on drought and flood. It is essential to investigate the change of regional hydrological characteristics in the context of global warming for developing flood mitigation and water utilization strategies in the future. The purpose of this study is to carry out a comprehensive analysis of changes in future runoff and flood for the upper Huai River basin by combining future climate scenarios, hydrological model, and flood frequency analysis. The daily bias correction (DBC) statistical downscaling method is used to downscale the global climate model (GCM) outputs from the sixth phase of the Coupled Model Intercomparison Project (CMIP6) and to generate future daily temperature and precipitation series. The Xinanjiang (XAJ) hydrological model is driven to project changes in future seasonal runoff under SSP245 and SSP585 scenarios for two future periods: 2050s (2031–2060) and 2080s (2071–2100) based on model calibration and validation. Finally, the peaks over threshold (POT) method and generalized Pareto (GP) distribution are combined to evaluate the changes of flood frequency for the upper Huai River basin. The results show that 1) GCMs project that there has been an insignificant increasing trend in future precipitation series, while an obvious increasing trend is detected in future temperature series; 2) average monthly runoffs in low-flow season have seen decreasing trends under SSP245 and SSP585 scenarios during the 2050s, while there has been an obvious increasing trend of average monthly runoff in high-flow season during the 2080s; 3) there is a decreasing trend in design floods below the 50-year return period under two future scenarios during the 2050s, while there has been an significant increasing trend in design flood during the 2080s in most cases and the amplitude of increase becomes larger for a larger return period. The study suggests that future flood will probably occur more frequently and an urgent need to develop appropriate adaptation measures to increase social resilience to warming climate over the upper Huai River basin.

Based on an extensive literature review and research interviews of energy experts, this article asks: what are the remaining impediments to clean energy systems and how can a Post-Kyoto Protocol climate framework be designed to overcome them? The article begins by exploring commercially available 'clean' energy systems and practices relating to energy end-use and infrastructure, energy supply, carbon capture and storage, and non-CO2 related greenhouse gas emissions. The article then examines a selection of persistent financial, market, information and intellectual property barriers. Lastly, it articulates the implication of these barriers for the design of future national and international climate change policies.

In an era of environmental crisis, the world is at a perilous moment. The fight between sustainability and economical choice has been a contentious matter and the world is facing environmental uncertainties today. The main purpose of the present study is to prepare an integrated exploration of the development of consciousness in all business categories. This study also focuses on the indispensable roles and impact of top management in merging the commitment and abilities to environmental leadership and thus, adds a contemporary insight into how businesses, economic stakeholders, government authorities, and the general human sphere can mitigate the runaway menace of environmental issues. Finally, the current authors conclude that the environment is the supernatural force that is making life a possibility on the planet. Therefore, every human operation should be regulated by the approaches mentioned in this study and efforts made through the strategic principles and theories of leadership.