Five tips for China to realize its co-targets of climate mitigation and Sustainable Development Goals(SDGs)

In 2018,a total of US$166 billion global economic losses and a new high of 55.3 Gt of CO_(2)equivalent emission were generated by 831 climate-related extreme events.As the world’s largest CO_(2)emitter,we reported China’s recent progresses and pitfalls in climate actions to achieve climate mitigation targets(i.e.,limit warming to 1.5-2°C above the pre-industrial level).We first summarized China’s integrated actions(2015 onwards)that benefit both climate change mitigation and Sustainable Development Goals(SDGs).These projects include re-structuring organizations,establishing working goals and actions,amending laws and regulations at national level,as well as increasing social awareness at community level.We then pointed out the shortcomings in different regions and sectors.Based on these analyses,we proposed five recommendations to help China improving its climate policy strategies,which include:1)restructuring the economy to balance short-term and long-term conflicts;2)developing circular economy with recycling mechanism and infrastructure;3)building up unified national standards and more accurate indicators;4)completing market mechanism for green economy and encouraging green consumption;and 5)enhancing technology innovations and local incentives via bottom-up actions.

Enhancing the sustainability and energy conservation in heritage buildings:The case of Nottingham Playhouse

Today,there is a growing interest in developing energy efficient buildings since it is estimated that buildings account for about 40%of the total primary energy consumption in the world.In relation to existing buildings,energy efficiency retrofits have become an important opportunity to upgrade the energy performance of commercial,public and residential buildings that may reduce the energy consumption,demand and cost.In this paper we cover the energy efficiency deep retrofit process that has been carried out for Nottingham Playhouse theatre building for the aim of enhancing its environmental performance and analysing the energy efficiency gained after implementing certain proposed modifications.It is a nationally protected historic building,listed as Grade II*on The National Heritage List for England(NHLE).The building has had insulation enhancement,doors modifications,solar energy installations,energy-saving lights,in addition to improved heating and air conditioning system.The paper presents a novel methodology;and its results indicate significant improvements in the building’s energy performance which is demonstrated using infrared thermographic images and data logger sensors where significant energy savings to the building’s thermal performance are obtained.The energy saving measures have been completed while maintaining the heritage building’s general appearance and architectural features,which have received a Commendation Certificate from The Nottingham Civic Society for this achievement.

A data-driven approach for predicting long-term degradation of a fleet of micro gas turbines

Predictive health monitoring of micro gas turbines can significantly increase the availability and reduce the operating and maintenance costs.Methods for predictive health monitoring are typically developed for large-scale gas turbines and have often focused on single systems.In an effort to enable fleet-level health monitoring of micro gas turbines,this work presents a novel data-driven approach for predicting system degradation over time.The approach utilises operational data from real installations and is not dependent on data from a reference system.The problem was solved in two steps by:1)estimating the degradation from time-dependent variables and 2)forecasting into the future using only running hours.Linear regression technique is employed both for the estimation and forecasting of degradation.The method was evaluated on five different systems and it is shown that the result is consistent(r>0.8)with an existing method that computes corrected values based on data from a reference system,and the forecasting had a similar performance as the estimation model using only running hours as an input.

Applications of AI in advanced energy storage technologies

The prompt development of renewable energies necessitates advanced energy storage technologies,which can alleviate the intermittency of renewable energy.In this regard,artificial intelligence(AI)is a promising tool that provides new opportunities for advancing innovations in advanced energy storage technologies(AEST).Given this,Energy and AI organizes a special issue entitled“Applications of AI in Advanced Energy Storage Technologies(AEST)”.

Methane mitigation: Learning from the natural marine environment

During the past decades,public attention regarding global warming has mainly focused on CO_(2) reduction;however,CH4,another important greenhouse gas,has a global warming potential that is 84 times higher than that of CO_(2) on a 20-year basis.The annual atmospheric amount of CH4 in 2020 reached its highest level since systematic monitoring began in 1983(Figure 1A).To date,despite coronavirus 2019 shutdowns,methane has contributed approximately 30%to global warming.Recently,a series of timely appeals,such as“The Global Methane Pledge”signed at the United Nations Climate Change Conference(COP26)and the“Global Methane Assessment”from the United Nations Environment Program,have called on global methane reduction and mitigation.

Key technologies for electric vehicles

1.Introduction Electric vehicles(EVs)are playing an increasingly important role in decarbonizing the transportation sector.They constitute a promising solution to a set of global challenges such as climate change and air pollution.EVs are an integration of a wide spectrum of techniques,such as battery monitoring,battery safety and vehicle energy management.In this regard,the EV development still faces significant challenges,which necessitate innovations in EV technologies.Given this,Green Energy and Intelligent Transportation(GEITS)organizes a special issue of“Key Technologies for Electric Vehicles”that attempts to advance knowledge in the area of EVs and provides a platform for researchers and engineers to share recent research results and discuss critical challenges in this field.A wide spectrum of topics are discussed,including but not limited to the following.

An innovative approach towards enhancing energy conservation in buildings via public engagement using DIY infrared thermography surveys

Energy consumption in urban environment in the EU accounts for about 40%of the total energy consumption,and the majority of this energy is utilised for heating and air conditioning of buildings.Hence the process of insulating and retrofitting of relatively old buildings is essential to enhance the thermal performance and hence contribute to energy and carbon emission reduction.There is a need to enhance people’s engagement and education in relation to such issues to inspire and encourage positive actions and investment from the public.This paper presents an approach of combining a novel training process using a low-cost infrared thermal camera with small scale building model to promote DIY(Do-It-Yourself)infrared survey for the public to evaluate the performance of their own homes in order to identify any issues related to insulation or air leaks from the building envelop to encourage them to take corrective actions.The work included the engagement of 50 people to survey their own homes to capture the technical findings as well as their personal reaction and feedback.The results show that 88%of participants have found the educational session helpful to understand the infrared thermography;and 92%have considered the infrared camera to be an effective tool to indicate location of heat losses.Additionally,90%of participants trust that the thermal camera has helped them to identify insulation defects that cause heat losses in their homes.Moreover,84%believe that the thermal imaging has convinced them to think more seriously about the heat losses of their homes and what they could do to improve that.The experimental thermography surveys have shown that many houses have limitations in terms of thermal insulation which have been identified by the participants.This DIY interaction has provided enhanced public engagement and energy awareness via the use of the technology.The financial issues are also found to be critical,as none of the participants would have done the survey if they had to pay for it.Hence,this paper provides a solution for households with limited budgets.

An explainable AI model for power plant NOx emission control

In recent years,developing Artificial Intelligence(AI)models for complex system has become a popular research area.There have been several successful AI models for predicting the Selective Non-Catalytic Reduction(SNCR)system in power plants and large boilers.However,all these models are in essence black box models and lack of explainability,which are not able to give new knowledge.In this study,a novel explainable AI(XAI)model that combines the polynomial kernel method with Sparse Identification of Nonlinear Dynamics(SINDy)model is proposed to find the governing equation of SNCR system based on 5-year operation data from a power plant.This proposed model identifies the system’s governing equation in a simple polynomial format with polynomial order of 1 and only 1 independent variable among original 68 input variables.In addition,the explainable AI model achieves a considerable accuracy with less than 21%deviation from base-line models of partial least squares model and artificial neural network model.