Are Green Buildings an Indicator of Sustainable Development?

Abstract

The world’s population keeps growing together with the construction rate of buildings that need to reduce their environmental footprint in order to mitigate global warming. This paper analyses if the spread of green buildings can be used as an indicator of broader sustainable development. The study is carried out with data taken from Eurostat Database and green buildings directories for 27 EU countries in the 10-year period spanning from 2010 to 2019. The relationship between the indicators is examined through simple linear regressions, and the results confirm the Environmental Kuznets Curve hypothesis: in developed countries, a growing economy (more GDP) is related to an environmental improvement (fewer GHG emissions). In addition, this study proves that the variance of green buildings expresses with a consistent probability the variance of GDP per capita (p-value = 0.0004 and R2 = 0.8475) and the variance of GHG emissions (p-value = 0.0002 and R2 = 0.8825), meaning that green buildings are indeed an indicator of sustainable development. This is due to the upfront cost required to implement advanced construction technologies that ultimately cut GHG emissions during the building lifecycle. This also points out that policy makers should encourage green building implementation through tax relieves and grants.

The Importance of Clean Energy and Technology in the Development of Smart Cities

“…Figure 1 Relevant components of smart city areas [22] The concept of smart cities has emerged globally in response to increasing urbanization and environmental problems faced by cities. The United Nations estimates that by 2050, 68% of the world's population will live in urban areas, up from 55% in 2018 [23]- [25] .This rapid growth puts pressure on urban infrastructure and services, leading to density, pollution, and resource depletion. Smart cities offer a solution to these problems by optimizing urban systems using technology and increasing resource efficiency.…”

Greenhouse Gas Emissions Forecasts in Countries of the European Union by Means of a Multifactor Algorithm

“…During the preliminary analysis required for the development of the algorithm, several metrics have been analysed: gross domestic product (GDP), country surface area, population, construction activity, energy consumption, renewable energy share (RES), employment in construction, number of green buildings certifications, GHG emissions and heating degree days. However, the variables that appear to influence the most GHG emissions are three, as highlighted in the literature review [20][21][22][23][24][25][26][27][28]: GDP, population and RES. For this, data of GDP (in million euros), population (in million people) and RES (in % of renewables over total energy use) of each of the analysed years are collected from Eurostat.…”

“…Recently, Marotta et al analysed various factors that influence GHGs emissions. For example, a study on the built environment [20] correlates GDP growth (economic dimension) with GHG emissions and renewable energy use (environmental dimension), based on the concept of the environmental Kuznets curve (EKC) hypothesis about the nonlinear relationship between economic growth and environmental degradation as shown in Figure 1.…”