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Aviation is responsible for at least 3.5% of global warming, and demand is predicted to rise rapidly over the next few decades. To reverse this trend, air travel demand will need to be managed. An important question is: ‘who would be affected by air travel demand reduction policies’? The answer to that question largely depends on who is participating in air travel, and how unequally it is distributed. Existing analysis suggests that participation in air travel in the UK is highly unequal and driven by richer, highly educated and urban households. However, so far little is known about how these patterns of inequality have changed over time – has air travel participation increased among low income households, e.g. due to the rise of low-cost carriers and ‘normalisation’ of air travel as a social practice? Would these groups therefore now be more affected by flight taxes or frequent flyer levies? To address these questions, this paper examines trends in air travel inequality between 2001 and 2018 in the UK based on two representative surveys, providing the first micro-level analysis of air travel inequality over time for this country. We find that while disadvantaged groups have contributed to the expansion of air travel over the past two decades, they remain far less likely to be affected by air travel demand management policies because air travel inequality is still at a very high level. These findings challenge common discourses that present air travel as a widespread norm, and demand management policies as socially unfair.

Demand for cage birds is highly prevalent and increasing across Indonesia, as wild bird populations across Asia decline. To find ways to reduce demand, it is important to understand the motivations and psychographic drivers to keep (or not keep) birds, and how demographic characteristics and public attitudes influence such decisions. Based on surveys with over 3,000 people, we found few people citing health, sanitary, or welfare concerns as reasons for not keeping birds, whereas most people started keeping birds to enjoy their beauty or song, or to keep up with peers. Pet‐keepers (“Hobbyists”) commonly started doing so opportunistically; song contest participants (“Contestants”) and breeders and trainers (“Breeders”) did so for financial gain. Bird‐keepers and non‐bird‐keepers disagreed on birds' environmental importance, longevity in captivity, and endangerment by trade. Older respondents were less concerned that keeping birds endangers them and few felt birds to be an important part of the environment. Hobbyists were least likely to consider wild bird population health a major concern. Efforts to dissuade potential bird‐keepers should focus on public concern for the environment and the threat bird‐keeping poses to wild populations. The importance of peer pressure among bird‐keepers presents an opportunity to promote sustainable bird‐keeping activities among key groups.

In assessing energy security, risk is recognised as being important. However, it is rarely assessed in a transparent quantitative way. To address this, we decompose the global energy system into 27 generic fuel supply chains and six sequential process stages. One of these fuels – ‘Demand Reduction’ – is conceived as ‘negative fuel’ to satisfy the supply/demand balance. We use 7 categories of risk and estimate the likelihood and impact for each cause of risk for each fuel and each process stage – demonstrating the tractability of creating a risk matrix for the whole energy system. Impacts of risk events are evaluated using the triple-bottom-line methodology, allowing for system resilience. This direct assessment of risk events is based on published data, interpretation and comment (with risk seldom directly articulated), and eliminates the need for arbitrary weighting of individual risks in the overall assessment. In a UK case study, 19 of the fuel categories were found to be relevant and those with the highest overall risk were a group of fossil fuels and nuclear fission. The least risky fuels were renewables, including solar (electric and thermal), wind, and hydro sources. Cost reduction alone was shown to be insufficient to deliver an efficient and more environmentally benign energy system. The UK case study demonstrates the need for governments to consider more closely policy relating to long-term energy security and identifies key elements of risk hindering the low-carbon transition.

Utility-implemented load-shedding aims to balance the supply and demand of a constrained power grid for a scheduled period of time by switching off supply to selected regions. The unintended consequence of this strategy occurs at the return of supply, where an instantaneous peak demand is experienced as an impulse at localised points of the power system. This results in frequent trips on medium voltage breakers that can damage infrastructure and result in delayed return of supply to end-users. The aim of this paper is to examine demand-side management interventions using intelligent control of electric water heaters (EWHs) to reduce the instantaneous peak demand at return of supply. Domestic water heating load was chosen as it is a deferrable, dispatchable, passive load with a high power requirement. The approach taken simulates the loading effect of 3 600 EWHs using three measured tank states and the combination of the Monte Carlo algorithm for probabilistic population behaviour. A typical 150-litre, 3 kW EWH in horizontal orientation is used, with a maximum draw volume of 50-litre per tank per day. It is shown that system changes to load-shedding schedules from a period of 4.5-hours to 2.5-hours beneficially reduces the instantaneous peak demand with the shorter period. For a 3 600 EWH-population, simulated results comparing uniformly distributed stochastic delays for activation time windows within 15, 30, 45, and 60 minutes show that a 15-minute activation time window could reduce the expected peak demand by a factor of two. This is important because intelligent controller retrofits onto EWHs is becoming more ubiquitous and if this simple sub-routine is built-in to produce a short delay after a period of no supply, it could result in significant passive impact on the power grid.

With the increase in Internet use across the world, there has also been an increase in the prevalence of problematic Internet use. There are various challenges in addressing the same – the addictive nature of Internet, lack of standard or uniform definition making its measurement or comparability across studies difficult, lack of national epidemiological studies that can help to direct resources based on the need, lack of awareness among the general public, challenges in restricting access of Internet to children and adolescents, and the commercial interests of gaming and gambling industries. The various initiatives to address problematic Internet use can be divided into supply reduction measures, demand reduction measures, and harm reduction measures, similar to that in the case of substance use disorders. Supply reduction measures focus on reduction in the availability or accessibility of Internet for children and adolescents. Harm reduction measures focus on regulating the age appropriateness of content of gaming or other Internet-related material provided to children, as well as restriction on the information that can be obtained from children. Demand reduction measures include promoting responsible use or healthy use of Internet as part of education for schoolchildren, and establishment of treatment centers for treatment of patients with problematic Internet use. India still has a long way to go in all these three arms of public health initiatives to curb the problem of Internet addiction.

Residential energy optimization provides economic and reliability benefits to the electric utility and consumers. Two major challenges in community energy optimization are: 1) to efficiently coordinate among a large number of residential consumers’ electric appliances and 2) to ensure participating consumers are comfortable and are rewarded with financial incentives during demand reduction. This paper proposes a hierarchical control framework with a novel bidding scheme that manages the use of consumers’ electric appliances while satisfying utility demand reduction requests. A new demand reduction bidding strategy is introduced for the efficient coordination among several local controllers (LCs) under a central controller (CC) in the proposed framework. Incentives are provided to the residential consumers for their participation, while considering their preferences, using a continuous reward structure. A simulation study on the 6-bus Roy Billinton test system with 1200 residential consumers demonstrates the financial benefits to the electric utility and consumers by performing a 6% demand reduction during peak times. The results show that the utility saves $28 217, and a residential consumer earns $9.37 on average for a one-hour demand reduction event (e.g., reducing 1.2 MW peak power). The reward scheme designed from this framework is more economical to utilities compared to existing utility reward schemes.

Demand response is considered as a valuable functionality of the power grid and its potential impacts continue expanding with grid modernization. Colocation data centers (simply called colocation) are recognized as a notably promising resource for demand response due to their high power demand and remarkable potential in demand management. A major challenge of colocation demand response is the split incentive, that is, colocation operators desire demand response for financial compensation while tenants may not embrace demand response due to lack of incentives. Another key challenge is caused by renewable energy co-located with data centers. Demand response mechanisms overlooking the uncertainty of renewable would cause much inefficiency in terms of energy saving and economic aspects. Existing work considers the two challenges separately in the context of data centers. By contrast, this work jointly addresses them and specially studies mechanism design for colocation data centers in presence of co-located renewable. We propose a hierarchical demand response scheme, which is based on a new two-level market mechanism that results in a win-win situation for both parties, i.e., tenants who choose to reduce power demand obtain financial rewards from the operator, while the operator receives financial compensation from the electric power company due to its tenants’ demand reduction. At each demand response period, the colocation operator solicits bids (amount of energy reduction) from tenants and tenants who choose to participate responds to the operator with their bids. The proposed mechanism provably converges to a unique equilibrium solution, and at the equilibrium, neither the operator or tenants can improve their individual economic performance by changing their own strategies. Further, we present a stochastic optimization based algorithm, which uses predictions of the co-located renewable to determine the colocation operator's best strategy. At the equilibrium, the algorithm has a provable economic performance guarantee in terms of the prediction error. We finally evaluate the designed mechanism via detailed simulations and the results show the efficacy and validate the theoretical analysis for the mechanism.

Essential resources, like electricity and water, can experience rapidly changing demand or supply while the other side of the market is unchanged. Short-run price variation could efficiently allocate resources at these critical times but only if consumers exhibit short-run demand elasticity. The question for firms in these markets has always been how to enable this response. Randomized control trials are increasingly used to test dynamic pricing and technologies that can assist in response by providing information and/or automated response. However, the trials typically do not randomize short-run prices. This paper illustrates how demand from a randomly assigned control group can be used to test the effectiveness of different technologies in increasing short-term price elasticity. To do so, we use a nonparametric control function approach that eliminates the bias inherent in estimating short-term price response using only household random assignment. We find that only automation technology leads to the short-term price elasticity needed to justify real-time pricing. This paper was accepted by Matthew Shum, marketing.

Incentive-based demand response (IDR) programs enable smart grid customers to participate in the demand reduction, triggered by system contingencies or peak load, to improve reliability, sustainability, security, and efficiency of the power grid. However, the deployment of smart meters and the increasing number of customers in IDR programs make the data generated in the smart grid at a large scale. Meanwhile, fine-grained data from smart meters can deluge customers’ lifestyle and usage pattern, posing threat to customer privacy. Therefore, privacy-preserving demand source management techniques that support increasingly large-scale datasets are in urgent need. In this paper, we propose an online privacy-preserving IDR management system, in which social welfare is maximized through recommending the optimal consumer to the utility company. Since the contexts of electricity curtailment offers from the utility company are different, an adaptive context partition method is proposed to enable the system context awareness. In addition, we cluster the customers in a tree structure to make the analyses of the customers in the cluster level and thus enable the algorithm to support the large-scale system. Furthermore, a tree-based noise aggregation method is applied to guarantee both the differential privacy of customers’ sensitive information and the utility of the data. Theoretical analysis shows that our proposal guarantees differential privacy of customers, while converging to the optimal policy in a long run. Numerical results validate that our proposed algorithm supports the large-scale dataset while striking a balance between the privacy-preserving level and social welfare.

India is a welfare-based nation; therefore, it has an embedded responsibility to protect the marginalized communities. However, drug dependency has always been a hidden phenomenon. Focusing on the Indian scenario, this research critically analyses the implementation of the demand reduction programme, i.e. the National Scheme of Assistance for Prevention of Alcoholism and Substance Abuse which emerged from Section 71 of Narcotic Drugs and Psychotropic Substances (NDPS) Act. Although the NDPS Act is prohibitionist in its approach and has criminalized the use of drugs, it has inculcated Section 71 of NDPS Act that stated the government can establish sufficient de-addiction centres for treatment and rehabilitation of drug dependents. In order to gain a broad understanding of the implementation the study covered a national perspective by including Chennai, Mumbai, New Delhi and Mizoram representing Southern, Western, Northern and North East regions of the country respectively. The treatment and rehabilitation services were analyzed categorically and thematically by posing specific standards such as availability, accessibility, quality and Protection of Human Rights. It was learnt that at the regional and community level, no autonomous body was set up for implementation of treatment and rehabilitation, treatment was envisaged through correctional angle, huge gaps in extension of financial support to existing de-addiction centres, weak preventive measures, ineffective training of staff, restricted admission for high risk drug dependents, diverse cases of human rights violation, mismanagement of withdrawal symptoms and prevalence of minimal harm reduction measures. However, on the positive side, the best practices are also being recorded with ongoing study such as positive impact of meditation, yoga therapy, life coaching based on emotional intelligence among other indigenous practices. The focus of this article is to provide a knowledge framework to enhance the quality of policy formulation and disseminate recommendations of the study with the hope that policy makers and practitioners and other concerned stakeholders are better informed of the situation so as to make a positive change in the lives of the users and the society at large.

The growing demand for energy and the increasing carbon footprint in the globe has made electricity utilities to move from nonrenewable energy to renewable energy. The integration of renewables into the electric grid is increasing day-by-day. The consumers’ energy consumption needs to be managed wisely and effectively. The Internet of Things has helped in connecting all homes and appliances to the Internet. With smart homes, it is possible to study consumer’s usage patterns and their demand for energy. During peak hours of the day, the demand for energy increases and have to be met by the utilities by starting up additional coal-fired generation. This makes peak hour usage of electricity costly. This paper studies the usage behavior of consumers from their historical data and predicts the demand for energy every hour for the individual consumer for the next 72 h using time series analysis. Also, the work statistically studies the usage pattern of appliances in every home thereby finding which appliances play a significant role during the peak hour usage. This paper will help utilities understand how their consumers use electricity and can encourage consumers to shift usage of peak hour appliances to nonpeak hours. Also, consumers can grant control of individual appliances to utilities, to curtail the load during peak hours to reduce the demand.

The complex nature of water resources and the related uncertainty cause decision making to be difficult in practice. In this study, two multi-criteria decision making (MCDM) methods, Analytic Hierarchy Process (AHP) and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), were applied to determine the best scenario adapting to climate change in agriculture for the Gharanghu basin in Northwest Iran for a 30-year period (2040-2069). Reservoir efficiency indexes were used as evaluation criteria. Specifically, the preference of each criterion relative to the other criteria was determined based on experts’ opinions. Five management scenarios were considered, involving reductions in agricultural water demand by 5, 10, 15, 20, and 25%, respectively. By applying the AHP approach, the consolidated weight of each criterion was calculated; the best adaptation scenario to climate change was determined; the inconsistency rate was calculated; and sensitivity analysis was also performed. The AHP results showed that the fifth scenario (25% demand reduction) with a weight of 33.5% was the best one for agricultural water demand management. The results obtained from the TOPSIS model indicated that the third scenario (15% demand reduction) with a weight of 20.8% was the best management scenario for agriculture in the period of climate change. Thus, estimation of uncertainty related to climate change is critical to choosing the best alternative using the MCDM models. Uncertainty analysis helps address the questions about whether the management scenarios are sustainable under unforeseen changes, and whether they are an ideal response to critical conditions of climate change.

The illegal trade in wildlife products is a major driver of the global biodiversity crisis. Trade in wildlife products is driven by consumer demand; however, consumer's motivations are often poorly understood. In this study, we use mixed social science approaches to understand the motivations driving consumers of bear products for medicine in Vietnam, and of traditional medicine practitioners who may be influencing consumers. In addition, we provide current information about the ways bear products are used in the two largest cities of Vietnam: Hanoi and Ho Chi Minh City. We found that bear products are still used widely in Vietnam, despite their use being prohibited since 2006. We directly estimated use at 45% of the sample of consumers for Hanoi, and 18% for consumers in Ho Chi Minh City. However, bear products are used differently between the two cities, with Hanoians more likely to take bear medicine products to treat an ailment, versus Ho Chi Minh City, where it is taken as a daily tonic. We also found that some traditional medicine practitioners in Vietnam are continuing to prescribe bear products, despite medicinal prescription of bear bile being made illegal, and availability of traditional medicine herbal alternatives. Generally, use of bear products appears to still be widely acceptable in the country, indicating a need for changing the social norms of bear product consumption. The insights gathered here will be beneficial to conservation managers working in Vietnam and throughout the Southeast Asia region, and will be particularly informative for developing and implementing demand reduction campaigns.

Demand management programs help utilities to reduce the load demand during high wholesale electricity price or system peak periods to maintain the system reliability and operational security. The challenge here is to properly address the customers’ inconvenience to encourage them to participate and meanwhile satisfy the required demand reduction efficiently. To this end, we propose a new incentive-based demand management scheme for schedulable appliances in a residential community. The proposed scheme is designed to provide scalability to the system. Different from existing literature, a new compensation scheme is adopted for the shifting of task-based appliances based on the level of inconvenience. The potentials of the schedulable appliances to contribute during the demand reduction event are assessed with a modified demand response potential. In this approach, the utility sends command and consumption limit to several controllers to perform the energy optimization. Participating customers are benefited with financial compensation along with minimized privacy concerns in the proposed centralized approach. Considering different demand reduction events within a month, the electricity bill with the proposed scheme is compared with the electricity bill from time-of-use (TOU) tariff-based optimization scheme and also with the base case (i.e., without any energy optimization scheme). Comparison of monthly electricity costs shows that the proposed scheme can save 11.3% on average more than the base case, and also the proposed scheme can save 6.2% on average more than the TOU tariff-based optimization.

Objective: While some countries of the WHO European Region are global leaders in tobacco control, the Newly Independent States (NIS) have the highest tobacco-smoking prevalence globally and a relatively low overall level of the WHO Framework Convention on Tobacco Control (WHO FCTC) implementation. An abridged version of the SimSmoke tobacco control policy simulation model has been developed to project the health impact of implementing tobacco-control policies in line with the WHO FCTC. Methods: Data on population size, smoking prevalence, policy-specific effect sizes and formulas were applied in 11 NIS - Armenia, Azerbaijan, Belarus, Georgia, Kazakhstan, Kyrgyzstan, the Russian Federation, Tajikistan, Turkmenistan, Ukraine, and Uzbekistan. The aim was to project the relative reduction in smoking prevalence, number of smokers and number of smoking-attributable deaths resulting from implementing six individual and/or combined WHO FCTC measures. Results: An increase in excise cigarette taxes to 75% of price yields the largest relative reduction in smoking prevalence (range 12.1-44%) for all countries. The projections show that when all six tobacco control measures are fully implemented in line with the WHO FCTC, smoking prevalence in each of the NIS countries can be reduced by at least 39% by the year 2033 (baseline 2015). Conclusion: The projections show that the NIS countries can expect a large number of smoking-attributable deaths just among those smokers alive today, but large reductions in smoking prevalence and smoking-attributable deaths can be achieved if the WHO FCTC demand reduction policies are implemented. The results can be used as an advocacy tool for accelerating enforcement of tobacco control laws in NIS.

Purpose The purpose of this paper is to critically reflect on the usefulness of quality standards aimed at prevention interventions for drug using young offenders. Design/methodology/approach This paper uses critical literature on quality standards, readings of quality standards and qualitative interviews as well as focus-group discussions with professionals working in services targeting drug use among young offenders. Findings The findings show discrepancies between the idea that quality standards provide a tool for supporting the implementation of more effective interventions and professionals’ experiences with quality standards as almost absent in their work. Originality/value This viewpoint highlights barriers to the implementation of quality standards that have to be overcome if quality standards are to be adopted and implemented in practice.

Demand response programs are becoming an integral part of the power system, helping create a closer alignment between the electrical service providers and customers. The research described in this paper uses the residential demand response (DR) program during a peak demand event to determine the demand reduction capacity as a virtual storage (VS). As in the marketing business, identifying target customers is vital in the DR program, thus making it more efficient and productive. Additionally, peak load events are very critical in the power system; therefore, it is essential to model an effective demand response program. This paper uses predictive analytics to estimate the level of residential participation in a DR program, and thus the load reduction capacity available, during peak load events. Also derives the mathematical modeling of the demand reduction capacity of a demand response program as a virtual storage system and optimizes it using genetic algorithm technique.

In its 2016 Heating and Cooling Strategy, the European Commission (EC) highlighted the strategic importance of heating demand for the energy demand reduction, and further noted that District Heat Networks (DHN) can play an important role in decarbonising this sector. This study applied a thermal atlas approach to map the potential for district heat networks in Switzerland. It extended existing methods with a novel approach to estimating linear thermal demand density in DHN at a national scale. DHN potential for current-generation high temperature networks as well as cutting-edge low temperature networks were compared for current building space heating and hot water demand as well as for two demand reduction scenarios. The method was tested by comparing its results to those of a local engineering study conducted for a Swiss municipality (Brig-Glis). The potential percentage of demand supplied by high temperature DHN was shown to decrease from 66% to 41% with energy saving while the potential for low temperature systems increased significantly from 2.1% to 42%. The percentage of heat demand covered by heat networks decreases less than the percentage of buildings covered, reflecting the strength of heat networks for supplying large fractions of thermal demand in geographically confined areas.

Recent and projected growth in global aeromobility is poised to substantially expand aviation’s contribution to anthropogenic climate change. With limited prospects for technical- or policy-based reductions in sectoral carbon emissions, behavioural shifts in the form of decreased demand for flying become increasingly important. This conceptual article introduces an innovative approach to aviation demand reduction in the form of a co-benefits approach, wherein conventional pro-environmental messaging is augmented by the articulation of the negative personal health impacts of flying. Using a critical review approach based on secondary literature, we examine frequent flying and theories of environmental behaviour change before examining how co-benefits approaches have been used in other domains. We then identify global and local environmental harms from aviation and synthesise these with the existing literature on the personal health impacts of frequent flying, which includes both physiological effects and psycho-social harms. We find that flying less would engender a much wider range of benefits for individual health, than for the environment, and that the health benefits would likely be more salient for frequent flyers than environmental benefits. We conclude that the personal nature of health impacts will add needed salience and urgency to efforts to reduce unsustainable aeromobility.

Automated blind control has been found to be more effective in controlling solar penetration than manual blind operation. Existing automated blind control methods mainly focus on improving indoor c...

Achieving further reductions in building electricity usage requires a detailed characterization of electricity consumption in homes. Understanding drivers of consumption can inform strategies for promoting conservation and efficiency. While there exist numerous approaches for modeling building energy demand, the use of regularization methods in statistical models can address challenges inherent to building energy modeling while also enabling more accurate predictions and better identification of variables that influence consumption. This paper applies five regularization techniques to regression models of original survey and electricity consumption data for more than one thousand households in California. It finds that of these, elastic net and two extensions of the lasso—group lasso and adaptive lasso—outperform other approaches in terms of prediction accuracy and model interpretability. These findings contribute to methodological approaches for modeling energy consumption in buildings as well as to our understanding of key drivers of consumption. The paper shows that while structural factors predominate in explaining annual electricity consumption patterns, habitual actions taken to save energy in the home are important for reducing consumption while pro-environmental attitudes and energy literacy are not. Implications for improving building energy modeling and for informing demand reduction strategies are discussed in the context of the low-carbon transition.

Although demand-side management (DSM) needs to be more customer centred, either with or without smart technologies (e.g. smart grid), less attention has been paid to the developing world in relation to DSM strategy development. The main reasons have been lack of appropriate technology and capital costs. Importantly, there are alternative DSM strategies that require minimum or no cost to implement and provide immediate results, of which energy-saving behaviour of the occupants at residences is one. This study explores the potentiality of this energy-saving behaviour as a DSM strategy for the least developed economies, focusing particularly on Bangladesh. The literature suggests that energy-saving behaviour could reduce energy demand by a maximum of 21.9%. However, this potential DSM scheme seems underestimated in the national DSM programme of Bangladesh. The Energy Efficiency and Conservation Master Plan (EECMP) of Bangladesh (a DSM program) shows that efficiency improvement in the use of home appliances could reduce electricity demand in the residential sector by about 28.8%, but this does require a long time to be implemented, whereas the inclusion of energy-saving behaviour as a demand response strategy in residences along with the EECMP might achieve demand reduction of up to 50.7%. Although the findings from this study are specific to Bangladesh, these could be useful guidelines for the policymakers of other developing nations where national DSM strategy development is underway.

The US switched its China and Taiwan anti-dumping duties to uniform tariffs on all imports of solar panels in January 2018. This research uses an Equilibrium Displacement Model (EDM) to determine the relative effects of these two tariffs on domestic consumer and producer welfare, employment, government revenue, and environmental costs. The results indicate that uniform tariffs are more effective than the specific-country tariffs because of higher welfare for domestic manufacturers and higher government revenue. However, the uniform tariffs hurt American consumers, employees, and the environment more than the other because of higher domestic price and larger domestic demand reduction. Therefore, if a policy aims to create more jobs and have less effect on consumers and the environment, a specific-country tariff might be preferable. However, uniform tariffs are better if the administration intends to support domestic manufacturers and increase government revenue.

Interventions targeting consumer behavior may help to reduce demand for bushmeat in urban areas. Understanding the drivers of urban bushmeat consumption is crucial to guide such interventions; however the cultural and socio-psychological factors driving consumer behavior remain understudied. Through qualitative interviews with urban bushmeat consumers in Pointe Noire, Republic of Congo, we investigated perceptions of bushmeat and other animal proteins, and social norms regulating urban demand for bushmeat. The perception of bushmeat as natural, tasty and healthy, and a rare luxury product functioning as a symbol of social status, underpins social norms to provide bushmeat. The main barriers to purchasing were cost and availability. Locally produced fish, meat, and poultry were positively perceived as organic and healthy, whereas frozen imported animal proteins were perceived negatively as transformed, of poor quality and taste, and unhealthy. Our findings provide an initial baseline understanding of social-psychological drivers shaping consumption that can inform the design of bushmeat demand reduction campaigns.

Greenhouse gas emission (GHGE) taxes on food products have recently been proposed as means to help reduce agricultural emissions. Numerous authors have calculated potential GHGE reductions in case such a tax was implemented in certain countries or regions. They did however assume a reduced production of GHGE-intense foods equal to the decline in demand induced by the tax. This omits however possible increases of net-exports that might offset such a demand reduction. Herein, the market dynamic behind this so-called “emission leakage” is explained and its effect quantified for a greenhouse gas tax in the European Union. We use the European Forest and Agricultural Sector Optimization Model for the quantitative analysis and simulate a greenhouse gas tax on all food products, based on their individual emission levels. The partial equilibrium model covers all world regions and hence the tax's effects on international trade of agricultural commodities can be examined. It was found that 43% of the greenhouse gas reduction indicted by a domestic consumption reduction is lost through emission leakage. This already includes the mitigating effects of a production shift from inefficient to efficient producers that is another consequence of increased exports from the European Union. A greenhouse gas emission tax on food products is hence much less efficient than previously proposed, if it is not introduced globally or trade is not restricted.

Demand response (DR) is a set of demand-side activities to reduce or shift electricity use to improve the electric grid efficiency and reliability. Shutting down part of operating chillers directly in central air-conditioning systems of buildings to meet the urgent demand reduction needs of power grids has received increasing attention recently. A model predictive control strategy is developed for optimizing the operation of a central air-conditioning system integrated with an active cold storage during such fast demand response events. The primary objective of the proposed control strategy is to maximize the power reduction with a profile pattern preferred by power grids as well as to maintain the indoor air temperature within an acceptable level during fast DR period. The MPC controller determines the control outputs of chiller power demand and active storage discharge rate based on the discrete-time state space building thermal response model. Test results show that expected profile pattern (i.e., maximum and stable) of power reduction was achieved by the proposed MPC strategy during fast DR events. Meanwhile, the indoor air temperature was maintained within the acceptable range.

Residential air-conditioner loads are known to be a key driver of summer demand peaks for some electricity industries. Such demand peaks occur infrequently but have potentially severe implications for network and peaking generation plant investment, and hence electricity prices for end users. Detailed assessments of air-conditioner peak demand have, however, been hampered by limited residential consumption data, and even when interval meter data is available, the complexities of other household loads and behavior. This study utilizes data from a significant appliance level consumption monitoring project in Sydney, Australia, to analyze the actual contribution of air-conditioners to regional summer demand peaks. K-means clustering is used to characterize air-conditioner load profiles across a large number of households at times of these overall demand peaks. These clustered air-conditioning load profiles, combined with a number of possible load control strategies, are then used to estimate possible peak load reductions from air-conditioner demand response across the Australian State of New South Wales. Our findings suggest that residential air-conditioning presents a significant demand response opportunity, approaching perhaps 9% of total peak demand in some circumstances.

Air-conditioning systems in commercial buildings play a vital role in the demand respond (DR) of cities. At present, many researches are focused on zone temperature reset strategies which are used frequently in the commercial buildings of the United States. However, this strategy requires the support of the energy management and control system (EMCS), which is not suitable for most commercial buildings in China. This paper focuses on the DR effect of the chiller-side control strategies in Chinese commercial buildings. Taking an office building as the research object, the coupling thermal inertial model of the building and the air conditioning system was built; based on the coupling model, the demand reduction effects of the typical chiller-side DR control strategies, including intermittent shutdown, chiller quantity reduction and chilled water temperature increase, were simulated; and the characteristics and applicability of these strategies were pointed out.

Japan’s mid-century strategy for reducing greenhouse gas emissions by 80% in 2050 would require large-scale energy system transformation and associated increases in mitigation costs. Nevertheless, the role of energy demand reduction, especially reductions related to energy services such as behavioral changes and material use efficiency improvements, have not been sufficiently evaluated. This study aims to identify key challenges and opportunities of the decarbonization goal when considering the role of energy service demand reduction. To this end, we used a detailed bottom-up energy system model in conjunction with an energy service demand model to explore energy system changes and their cost implications. The results indicate that final energy demand in 2050 can be cut by 37% relative to the no-policy case through energy service demand reduction measures. Although the lack of carbon capture and storage would cause mitigation costs to double or more, these economic impacts can be offset by energy service demand reduction. Among energy demand sectors, the impact of industrial service demand reduction is largest, as it contributes to reducing residual emissions from the industry sector. These findings highlight the importance of energy service demand reduction measures for meeting national climate goals in addition to technological options.

There is a growing academic interest on the dark side of engagement on social media and the role of user-generated content (UGC). The illicit trade of wildlife online is a major contributor to global species loss and, thus, strategies to reduce demand for wild species and consumer engagement in the market and are of paramount importance. We first conduct qualitative analyses on a large data set of UGC (n=14,729 words from 1060 comments from 12 Facebook groups) from a biodiversity hotspot, The Republic of Indonesia. We use automatic machine-learning lexical software to explore the discourse that occurs in comments of posts that promote behaviour change and demand reduction. Then, to examine the efficacy of these posts, we test an extended elaboration likelihood model to determine the nature of information processing that leads viewers to agree with wildlife conservation content. Our results show that motivation, opportunity and ability factors moderate the relationship between information processing and comment valence, as well as influencing whether comments indicate attitude change. This work extends the use of theory from information systems and marketing to conservation, and provides both conceptual and practical recommendations to encourage behaviour change and reduce the harmful effects of engagement.

Electric appliances for cooling and lighting are responsible for most of the increase in electricity consumption in Karachi, Pakistan. This study aims to investigate the impact of passive energy efficiency measures (PEEMs) on the potential reduction of indoor temperature and cooling energy demand of an architectural campus building (ACB) in Karachi, Pakistan. PEEMs focus on the building envelope’s design and construction, which is a key factor of influence on a building’s cooling energy demand. The existing architectural campus building was modeled using the building information modeling (BIM) software Autodesk Revit. Data related to the electricity consumption for cooling, building masses, occupancy conditions, utility bills, energy use intensity, as well as space types, were collected and analyzed to develop a virtual ACB model. The utility bill data were used to calibrate the DesignBuilder and EnergyPlus base case models of the existing ACB. The cooling energy demand was compared with different alternative building envelope compositions applied as PEEMs in the renovation of the existing exemplary ACB. Finally, cooling energy demand reduction potentials and the related potential electricity demand savings were determined. The quantification of the cooling energy demand facilitates the definition of the building’s electricity consumption benchmarks for cooling with specific technologies.

This thesis proposed a decision-making framework to consider multiple objectives in long-term planning situations, and asserts that planning for power generation systems should consider relevant environmental and/or social objectives at the same decision level as traditional economic or reliability objectives. The framework was applied to the case study of long-term planning for Ontario's power generation system. The framework integrates life-cycle based information and decision-maker preferences toward multiple objectives in the context of sustainable development. Six decision criteria evaluated as measures of the objectives include life-cycle cost of electricity, a system flexibility indicator, demand reduction, land use requirements, greenhouse gas emissions, and air emissions. Stakeholder values were derived through questionnaires. Three hypothetical electricity generation scenarios were compared to test the decision-making framework. The results of the application indicated that the scenario which included aggressive renewable energy development and demand reduction was favourable, even given the tradeoffs of reliability and costs.

Introduction The world’s first global health treaty, WHO Framework Convention on Tobacco Control (FCTC) aims to reduce tobacco product demand by focusing on tobacco taxes, smoking bans, health warning labels, and tobacco advertising bans. Previous studies almost unanimously suggest that FCTC has prompted countries to implement more effective tobacco demand reduction policies. Aims and Methods By taking into account the pre-FCTC status, country income level, and state capacity we studied if ratifying FCTC was associated with tobacco demand reduction measures in 2018/2019. We used logistic regression to assess the association of FCTC ratification with adoption demand reduction measures, accounting for years since ratification, baseline status, and other covariates. Results Except for taxes, state of tobacco policy implementation before FCTC ratification did not predict adoption of FCTC policies. Time since FCTC ratification was associated with implementing smoking bans and pictorial HWLs. In contrast, while the tax rate prior to FCTC ratification was positively associated with increased taxes after FCTC ratification, time since FCTC ratification was marginally negatively associated with increases in tobacco taxes. Conclusions While the FCTC was followed by implementation of compliant demand reduction policies, there are still many parties that have not implemented the FCTC, particularly increasing taxes and ending tobacco advertising and promotions. Implications We assessed changes in tobacco demand reductions measures over 22 years in 193 countries. By using internal tobacco industry documents, we were able establish a baseline before the FCTC negotiations. Unlike previous studies, we included four tobacco demand reductions measures: tobacco taxes, smoking bans, health warning labels, and tobacco advertising ban. The limitation of the study is that we do not have data to describe if demand reduction measures are actually enforced or what their effect on tobacco consumption is.

This work aims at developing a methodology for the assessment of district heating (DH) potential through the mapping of energy demand and waste heat sources. The presented method is then applied to the Metropolitan City of Milano as a case study in order to investigate the current and, especially, the future sustainability of DH with the foreseen building refurbishment and consequent heat demand reduction. The first step is the identification of the areas the most interesting from a heat density and an economic point of view through a clustering algorithm, in which lies the main novelty of the work. The potential is then assessed by investigating their synergy with the available heat sources, which are mapped and analyzed in terms of recoverable thermal energy and costs. In future scenarios with foreseen heat demand reduction, low-temperature networks and excess heat sources are considered, such as metro stations and datacenters, together with the conventional sources, such as thermoelectric plants. The outcomes prove that lower heat demand corresponds to higher network costs with consequently reduced district heating potential but also prove that the properties of low-temperature district heating can potentially compensate for the drop in its cost-effectiveness. Another interesting finding is that the renovation of buildings in an area should be not performed evenly but with criteria; for instance, in synergy with DH diffusion.

Shared autonomous vehicles (SAVs) can have significant impacts on the transport system and land use by replacing private vehicles. Sharing vehicles without drivers is expected to reduce parking demand, and as a side effect, increase congestion owing to the empty fleets made by SAVs picking up travelers and relocating. Although the impact may not be uniform over a region of interest owing to the heterogeneity of travel demand distribution and network configuration, few studies have debated such impact at a local scale, such as in transportation analysis zones (TAZs). To understand the impact in relation to geographical situations, this study aims to estimate the impacts of SAVs at the local scale by simulating their operation on a developed simulator. Using the mainland of Okinawa, Japan as a case study, it was found that parking demand was reduced the most in residence-dominant zones in terms of quantity and in office-dominant zones in terms of proportion. As a side effect of replacing private vehicles with SAVs, empty fleets increase congestion, particularly at the periphery of the city. Overall, the results show the heterogeneous impacts of the SAVs at the TAZ level on both land use and traffic, thus suggesting the importance of developing appropriate strategies for urban and transport planning when considering the characteristics of the zones., 27 pages, 9 figures, 4 tables

Cheetahs (Acinonyx jubatus) are a keystone predator of savanna systems in Africa, yet their populations have dramatically declined due to pressures such as human-wildlife conflict, loss of habitat, and most notably the illegal trade in live cheetah cubs as pets. We provide the most extensive dataset relevant to seized and non-intercepted illegal trade in live cheetahs and cheetah parts for the decade 2010-2019, spanning over 300 sources and 56 countries in Africa, the Middle East, Asia, Europe, Oceania and North America. It includes 1,884 individual incidents involving at least 4,000 cheetahs or cheetah parts or products likely or confirmed to breach national laws or CITES regulations. While the covert nature of illegal trade of any kind makes it extremely difficult to capture its true volume, we believe that the information contained in this dataset demonstrates the need for a more in-depth look into illegal cheetah trade, including sustainability assessments with emphasis in regions where cheetah populations are small and widely exploited, such as the Horn of Africa, as this dataset suggests. Ultimately, such actions could lead to improved enforcement and legal frameworks, and provide a guide for CITES actions involving international cooperation and demand reduction efforts.

Efforts to shift unsustainable human behaviour are at the crux of many conservation interventions, particularly when addressing illegal or unsustainable wildlife trade. These efforts, often in the form of behaviour change interventions, have proven largely unable to counteract this pervasive issue, however, leading to calls for more robust intervention designs. In behavioural science fields like public health, design processes that integrate human behaviour theory and evidence from data collection are often developed to ground behaviour change interventions within a strong understanding of the context, thus supporting interventions that are efficient and have a higher likelihood of success. Here we detail the foundational process of designing an intervention around the use of a wildlife product by a particular group: Singaporean consumers of saiga horn (from the Critically Endangered Saiga tatarica). We employ both qualitative and quantitative data, along with human behaviour theories and past literature on the study system, to develop a comprehensive understanding of the many influences driving this target audience to purchase saiga horn products. We use this insight to identify the key influences to leverage in a behaviour change intervention: those that are both the most powerful and the most amenable to change. This work provides a reproducible process which can be used by other intervention implementers, highlights the often complex intricacies of socially influenced behaviour, and demonstrates why a methodical understanding of these intricacies is invaluable when attempting to shift human behaviour for conservation goals. A free Plain Language Summary can be found within the Supporting Information of this article.

Bushmeat consumption remains significant in urban Central Africa. Increasing urbanization has fueled bushmeat trade and become a threat to endangered species like the pangolin. Behavioral change interventions may help reduce demand for pangolins in urban centers. However, there is still a lack of adequate locally‐specific research on consumer behavior and drivers of demand to effectively guide such interventions. Our study addressed this knowledge gap through semistructured interviews to investigate consumer preferences and bushmeat consumption habits and perceptions of 597 participants in Bertoua and Ebolowa, Cameroon. Bushmeat, in general, was positively perceived as a tasty, healthy, and luxurious item that meets cultural needs, while domestic meat was negatively perceived as an unhealthy and intensively processed product. The biggest barriers to bushmeat consumption were its illegality and high price. Pangolin was among the most desired types of bushmeat. Nearly half of pangolin consumers were willing to pay more for a pangolin meal. Despite being fully protected by national laws, pangolins were consistently found in local bushmeat markets and restaurants, suggesting the ineffectiveness in law enforcement and/or communication with the public about the legal protection and current status of pangolins. Our findings provide an understanding of sociocultural consumer behavior and drivers that can help guide bushmeat demand reduction interventions in urban centers of Cameroon.

Water and energy are two pivotal areas for future sustainable development, with complex linkages existing between the two sectors. These linkages require special attention in the context of the energy transition. Against this background, this paper analyses the role of water availability in the development of solar thermal and photovoltaic power plants for the case of the Drâa Valley in southern Morocco. Located in a semi-arid to arid mountainous area, the Drâa Valley faces high water stress – a situation expected to worsen due to climate change. At the same time, the region has one of the greatest potentials for solar energy in the world. To examine whether limited water availability could accelerate or delay the implementation of solar thermal and photovoltaic power plants, this paper compares regional water availability and demand in the Drâa Valley for different scenarios, paying particular attention to potential socio-economic development pathways. The Water Evaluation and Planning System software is applied to allocate the water resources in the study region. The water supply is modelled under the Representative Concentration Pathway 8.5 climate scenario, while the water demand for the Drâa Valley is modelled for a combination of three socio-economic and two energy scenarios. The climate scenario describes a significant decrease in water availability by 2050, while the socio-economic and energy scenarios show an increase in water demand. The results demonstrate that during a sequence of dry years the reservoirs water availability is reduced and shortages in water supply can result in high levels of unmet demand. If this situation occurs, oasis farming, water for drinking and energy production could compete directly with each other for water resources. The energy scenarios indicate that the use of dry cooling technologies in concentrated solar power and photovoltaic hybrid systems could be one option for reducing competition for the scarce water resources in the region. However, given that energy generation accounts for only a small share of the regional water demand, the results also suggest that socio-economic demand reduction, especially in the agricultural sector, for example by reducing the cultivated area, will most likely become necessary.

One way to deal with the future effects of climatic changes on the water resources and to cope with water shortages in basins is to have a clear understanding of the future climate change trends. To this end, this study proposes an integrated hydrological-water transfer and supply (HWTS) framework including a coupled SWAT-Bi level programming model to investigate future optimal water supply between different sectors with regard to transaction right. Indeed, Soil & Water Assessment Tool (SWAT) is applied to project the rate of streamflow under Representative Concentration Pathway scenarios of RCP2.6&RCP4.5 and future periods (2020–2040 & 204(Abbas et al. 2015)2060). In addition, a case study of the Hamoun wetland in southeastern of Iran is considered for calibration and validation of real historical data (2000–2016) and then simulation of future streamflow patterns (2020–2060). Next, simulated streamflow data extracted by SWAT is entered as the input of market based bi-level optimization model so that upper-level manager seeks optimization of the available water level in the reservoirs while the lower-level decision maker tries to minimize the economic loss due to water shortage between different sectors regarding transaction right. However, after solving the model with the Improved Particle Swarm Optimization (IBPSO) technique, the final results show that although not much economic profit will be made, but considering specific management strategies such as demand reduction schemes to conserve more water, the imbalance between supply and demand can be significantly improved.

Water scarcity poses a real crisis for decision makers of water supply system because satisfying growing demand and, as a result, achieving full consumer satisfaction in different sectors of the system remains a major problem. Therefore, this study develops a dynamic multi-objective model of water supply optimization under different scenarios to improve multisectoral consumer satisfaction. To diminish the negative effects of the water crisis on long-term consumer satisfaction, the performance of the dynamic water supply system is evaluated and optimized, which can change the situation from a state of dissatisfaction to satisfaction. In this regard, to analyze the developed model, a real case study of the Hamoun wetland in southeastern Iran is considered. According to the proposed model, various strategies are performed along with the analysis of two scenarios related to runoff uncertainty in order to investigate the consumer satisfaction status in detail. However, given to the final results, which show the greater impact of the two sensitive factors of reliability and vulnerability on consumer satisfaction, the highest level of dissatisfaction is related to the agricultural sector because it has less reliability and higher vulnerability compared to other sectors. In this regard, by proposing policies such as weight scenarios and demand reduction scheme, the situation of consumer satisfaction has improved much more desirable.

Simple Summary In response to the illegal wildlife trade, successful enforcement often involves the seizure, confiscation, and subsequent management of illegally traded wildlife. Unfortunately, confiscated live animals often experience substandard care. In this study, we investigate the barriers to the ‘disposal’ of confiscated live animals in Southeast Asia. ‘Disposal’ is the term used for what happens to illegally traded wildlife after confiscation. Guidelines for the ‘disposal’ of live specimens are provided by the Convention on the International Trade in Endangered Species of Wild Fauna and Flora (CITES), although individual nations must enforce this within their own legislation. We interviewed 18 experts from seven countries in Southeast Asia revealing eight categories of barriers to the disposal of confiscated live animals. We then propose seven recommendations to help reform the disposal of confiscated live animals, which would support the efficient and humane management of illegally traded wildlife in Southeast Asia and globally. Abstract Increased focus on the illegal global wildlife trade has resulted in greater numbers of live animals confiscated by authorities, increasing the need to manage these animals responsibly. Most wildlife seizures take place in Southeast Asia, with global demand for live animals fuelling much of the trafficking. Guidelines for the ‘disposal’ of live specimens are provided by the Convention on the International Trade in Endangered Species of Wild Fauna and Flora (CITES), although individual Parties must implement provisions through national laws and regulations. ‘Disposal’ is the term used for the management of illegally traded wildlife upon confiscation. Confiscated live animals can be euthanised (i.e., killed), repatriated to their native country and released, or kept in captivity. This study investigates barriers to proper care and disposal of confiscated live animals in Southeast Asia, where roughly one quarter of the global multibillion dollar illegal wildlife trade takes place. Interviews were conducted with 18 professionals working within conservation, wildlife crime, and confiscated live animal management. Eight limitations to the proper care and disposal of confiscated wildlife were identified: (1) political will, (2) policy, (3) funding, (4) capacity, (5) expertise (6) attitudes and behaviours, (7) exploitation, and (8) corruption. Based on interviews, we propose seven key reforms to support the efficient and humane management of illegally traded wildlife for national authorities and CITES parties. These are wildlife seizure management, legislative support, enhanced political will, demand reduction, global participation, registry of rescue centres, and terminology change. This research highlights major barriers to the proper care and disposal of live confiscated animals and proposes key reforms to improve the conservation of threatened species and the welfare of millions of illegally traded animals.

The rising load demands in industrial, commercial, and residential levels is the order of primary concern for Distribution System Operators (DSO). Therefore, advanced energy-efficient technologies such as Conservation Voltage Reduction (CVR) are considered to reduce the substation demand by regulating the voltage in a lower voltage regulation range (120-114)V. The ANSI voltage limits of end-user customer are maintained by incorporating PV's in the distribution network. This study aims to attain higher substation demand reduction. Therefore, smart PV inverter Volt- VAr control has been incorporated. Time series simulation has been performed in an OpenDSS environment for the daily load demands of various customers. IEEE-13 node three-phase radial unbalanced distribution network is taken for study purpose along with voltage-dependent load model. The significance of this work has been proved by a comparative analysis of various case studies to analyze the impact of CVR in combination with a smart PV inverter.