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The use of economic instruments within environmental policy has become a challenging topic for policymakers, governments and scholars. Environmental taxes have emerged as a prevailing preference in developed countries to promote sustainability. Recently, a particular focus has been given to waste generation and disposal, shifting the attention from greenhouse gases to another important source of environmental pollution. This paper investigates the effect of national environmental taxes and policies on industrial waste. A fixed effects model is used for 34 countries across Europe from 2004 to 2022. The results suggest that environmental taxes and energy policies reduce industrial (hazardous and non-hazardous) waste. However, environmental tax reforms should take into consideration the deterioration in environmental quality, the increase in economic costs and undesirable social consequences.

The simulation of the energy consumptions in an hourly regime is necessary in order to perform calculations on residential buildings of particular relevance for volume or for architectural features. In such cases, the simplified methodology provided by the regulations may be inadequate, and the use of software like EnergyPlus is needed. To obtain reliable results, usually, significant time is spent on the meticulous insertion of the geometrical inputs of the building, together with the properties of the envelope materials and systems. Less attention is paid to the climate database. The databases available on the EnergyPlus website refer to airports located in rural areas near major cities. If the building to be simulated is located in a metropolitan area, it may be affected by the local heat island, and the database used as input to the software should take this phenomenon into account. To this end, it is useful to use a meteorological model such as the Weather Research and Forecasting (WRF) model to construct an appropriate input climate file. A case study based on a building located in the city center of Rome (Italy) shows that, if the climatic forcing linked to the heat island is not considered, the estimated consumption due to the cooling is underestimated by 35–50%. In particular, the analysis and the seasonal comparison between the energy needs of the building simulated by EnergyPlus, with the climatic inputs related to two airports in the rural area of Rome and with the inputs provided by the WRF model related to the center of Rome, show discrepancies of about (i) WRF vs. Fiumicino (FCO): Δ = −3.48% for heating, Δ = 49.25% for cooling; (ii) WRF vs. Ciampino (CIA): Δ = −7.38% for heating, Δ = +35.52% for cooling.

This study explores the critical notion of how feasible it is to achieve long-term mitigation goals to limit global temperature change. It uses a model inter-comparison of three integrated assessment models (TIAM-Grantham, MESSAGE-GLOBIOM and WITCH) harmonized for socio-economic growth drivers using one of the new shared socio-economic pathways (SSP2), to analyse multiple mitigation scenarios aimed at different temperature changes in 2100, in order to assess the model outputs against a range of indicators developed so as to systematically compare the feasibility across scenarios. These indicators include mitigation costs and carbon prices, rates of emissions reductions and energy efficiency improvements, rates of deployment of key low-carbon technologies, reliance on negative emissions, and stranding of power generation assets. The results highlight how much more challenging the 2 °C goal is, when compared to the 2.5–4 °C goals, across virtually all measures of feasibility. Any delay in mitigation or limitation in technology options also renders the 2 °C goal much less feasible across the economic and technical dimensions explored. Finally, a sensitivity analysis indicates that aiming for less than 2 °C is even less plausible, with significantly higher mitigation costs and faster carbon price increases, significantly faster decarbonization and zero-carbon technology deployment rates, earlier occurrence of very significant carbon capture and earlier onset of global net negative emissions. Such a systematic analysis allows a more in-depth consideration of what realistic level of long-term temperature changes can be achieved and what adaptation strategies are therefore required.

One of the key challenges of developing countries is to tackle the mitigation of the impacts of rapid and uncontrolled urbanization. Assessing this phenomenon is crucial to lessen the consequences for the environment and society. ‘Literature has been concentrated in planning strategies for the cities’ adaptation and engagements to the principles of green development ensuring a long-term quality of life for their citizens. Hereby, smart technologies and applications consist of two of the most encouraging concepts for solutions for achieving the 2030 and 2050 horizon targets towards clean energy transition and carbon neutrality. In academia, scholars have already raised the importance of ‘smartness’ to define the adaptative patterns for the global pressures of climate change and uncontrolled urban growth. The mitigation of these phenomena is crucial to ensure the cities’ future and lessen their impacts. This study seeks a strategic and smart-driven vision to leverage smartness on the phenomenon of rapid urbanization that occurred in the case of Beijing, China. Defining and evaluating the environmental impacts in line with the RIAM approach as one of its main targets. Future works can be focused on addressing solutions in similar cases in further developing countries to not only overcome environmental, but also economic, social, and digital complications.

The Climate Change scenario projected by the IPCC for the year 2050 predicts noticeable increases in temperature. In severe summer climates, such as the Mediterranean area, this would have very negative effects on thermal comfort in the existing housing stock, given the current high percentage of dwellings which are obsolete in energy terms and house a population at serious risk of energy poverty. The main aim of this paper is to generate a predictive model in order to assess the impact of this future climate scenario on thermal comfort conditions in an entire building category. To do so, calibrated models representing linear-type social multi-family buildings, dating from the post-war period and located in southern Spain, will be simulated extensively using transient energy analyses performed by EnergyPlus. In addition, a sensitivity analysis will be performed to identify the most influential parameters on thermal discomfort. The main results predict a generalized deterioration in indoor thermal comfort conditions due to global warming, increasing the average percentage of discomfort hours during the summer by more than 35%. This characterization of the future thermal behaviour of the residential stock in southern Spain could be a trustworthy tool for decision-making in energy retrofitting projects which are so badly needed. To do so, further work is required on some limitations of this model so that different user profiles and typologies can be represented in detail and an economic assessment can be included.

This article provides an agent-based model of a hypothetical standalone electricity network to identify how the feed-in tariffs and the installed capacity of wind power, calculated in percentage of total system demand, affect the electricity consumption from renewables. It includes the mechanism of electricity pricing on the Day Ahead Market (DAM) and the Imbalance Market (IM). The extra production volumes of Electricity from Renewable Energy Sources (RES-E) and the flexibility of electrical consumption of industries is provided as reserves on the IM. Five thousand simulations were run by using the agent-based model to gather data that were then fit in linear regression models. This helped to quantify the effect of feed-in tariffs and installed capacity of wind power on the consumption from renewable energy and market prices. The consumption from renewable sources, expressed as percentage of total system consumption, increased by 8.17% for every 10% increase in installed capacity of wind power. The sharpest increase in renewable energy consumption is observed when a feed-in tariff of 0.04 €/kWh is provided to the wind farm owners, resulting in an average increase of 9.1% and 5.1% in the consumption from renewable sources while the maximum installed capacity of wind power is 35% and 100%, respectively. The regression model for the annualized DAM prices showed an increase by 0.01 €cents/kWh in the DAM prices for every 10% increase in the installed wind power capacity. With every increase of 0.01 €/kWh in the value of feed-in tariffs, the mean DAM price is lowered as compared to the previous value of the feed-in tariff. DAM prices only decrease with increasing installed wind capacity when a feed-in tariff of 0.04 €/kWh is provided. This is observed because all wind power being traded on DAM at a very cheap price. Hence, no volume of electricity is being stored for availability on IM. The regression models for predicting IM prices show that, with every 10% increase in installed capacity of wind power, the annualized IM price decreases by 0.031 and 0.34 €cents/kWh, when installed capacity of wind power is between 0 and 25%, and between 25 and 100%, respectively. The models also showed that, until the maximum installed capacity of wind power is less than 25%, the IM prices increase when the value of feed-in tariff is 0.01 and 0.04 €/kWh, but decrease for a feed-in tariff of 0.02 and 0.03 €/kWh. When installed capacity of wind power is between 25 and 100%, increasing feed-in tariffs to the value of 0.03 €/kWh result in lowering the mean IM price. However, at 0.04 €/kWh, the mean IM price is higher, showing the effect of no storage reserves being available on IM and more expensive reserves being engaged on the IM. The study concludes that the effect of increasing installed capacity of wind power is more significant on increasing consumption of renewable energy and decreasing the DAM and IM prices than the effect of feed-in tariffs. However, the effect of increasing values of both factors on the profit of RES-E producers with storage facilities is not positive, pointing to the need for customized rules and incentives to encourage their market participation and investment in storage facilities.