Can biomass energy be an efficient policy tool for sustainable development?

WOS: 000394920600065This paper first reviews the potential causality from biomass energy to CO2 emissions and economic development within relevant literature. Later, the paper examines statistically the impacts of biomass energy consumption on CO2 emissions and GDP in the US. To this end, paper observes environmental and economic implications of biomass fuel usage throughout energy literature and launches asymmetric causality test to confirm/disconfirm the literature output. The findings of the tests indicate that biomass energy consumption per capita mitigates CO2 emissions per capita and increases GDP per capita. Eventually, upon its output, this research asserts that biomass energy consumption can be an efficient policy tool for environmentally sustainable development in the US, and, that, hence, biomass production technologies and biomass consumption need to be promoted in other countries as well as in the US. On the other hand, analyses underline the fact that policy makers should consider as well some potential constraints of biomass energy usage such as land use constraints and carbon leakage from biomass production. Therefore, although this paper explores the remedial impact of biomass on environment and growth, one may suggest also that further possible works consider the effects of biomass sources in detail to minimize the some worsening influence of biomass usage on climate change

A revisited renewable consumption-growth nexus: A continuous wavelet approach through disaggregated data

WOS: 000463342600001In this research, we aim at exploring the influence of renewables on industrial production (Ip) in the US by following continuous wavelet coherence and partial continuous wavelet coherence analyses. To this end, we observed the co-movements between, biofuels and Ip, solar and Ip, wind and Ip, geothermal and Ip, wood and Ip, and, waste and Ip in the US for the monthly period from January 1989 to November 2016. The primary motivations behind this research are twofold. Firstly, it attempts to reach the co-movements, if exists, between renewables' consumption and industrial production by following time domain and frequency domain analyses. Secondly, it aims at observing the potential co-movements between renewable energy sources (geothermal, solar, wind, biofuels, wood, and, waste) and Ip by adding some control variables (fossil fuels, total biomass etc.) into the wavelet models to understand clearly the responses of the industrial production to the impulses in renewables in both short term and long term periods. The paper hence eventually reveals significant effects of geothermal, wind, solar, biofuels, wood, and, waste on US industrial production in short term cycles and long term cycles. Thereby, following this paper's results of continuous wavelet analyses which depict the impact of renewables on US economy at 1-3-year frequency and 3-8-year frequency for the time period from January 1989 to November 2016, one might provide policy makers with relevant current and future efficient renewables' energy policy for the US and other countries which have similar structures with the US

The mutual effects of residential energy demand and climate change in the United States: A wavelet analysis

This study examines the complex and time-varying relationship between residential energy demand (including electricity, geothermal, and solar energy) and climate change using wavelet analyses with monthly USA data from January 1990 to March 2023. The results show that residential energy demand and climate change indicators exhibit a time-varying interrelationship with cyclical and lag effects. Specifically, before 2021, a positive correlation between residential electricity demand and carbon dioxide (CO2) emissions in short-term frequencies was found, but the relationship reversed thereafter, with an increase in CO2 levels influencing and decreasing residential electricity demand. In the long run frequencies, the link between residential power consumption and CO2 emissions shifted over time, exhibiting inconsistent co-movement. The co-movements between residential geothermal and CO2 show predominantly positive correlations, with CO2 leading the relationship in the short run, while geothermal leads the co-movements in the long run. In both short and long-term frequencies, the dependency and co-movement between residential solar and CO2 are mixed, with residential solar leading to positive correlations and CO2 leading to negative correlations. Therefore, improved insulation, energy-efficient windows, and high-efficiency heating systems can all assist in reducing heat loss and the total energy demand for domestic heating and subsequently low CO2 emissions