Human travels are considered the biggest source of carbon dioxide emissions, and climate change is considered the most important part of this problem. On the other hand, the tourism sector is one of the sectors that facilitates intense human mobility and travel. The aim of this research is to estimate the carbon footprint of aircraft and road transportation due to international and domestic touristic trips to Marrakech/Morocco between 2010 and 2018. In this research, the preferred means of transportation and the distances traveled by the tourists who visited Marrakech/Morocco between 2010 and 2018 were used as a data set. Carbon footprint calculations were made according to each transportation vehicle preference. The total carbon footprint was calculated at the same time. In general, the average 9-year carbon footprint of touristic trips to Morocco from different parts of the world has been found to be 7148.90 tons in total. The per capita carbon footprint of all visitors from different countries of the world has been determined as 0.416 kg. However, tourism, due to its transport intensity, particularly air transport, is a growing source of greenhouse gas emissions. It should be taken into account in the definition of climate policies following the Paris Agreement.

Greenhouse gas (GHG) emissions from agriculture contribute to climate change. The consequences of unsustainable agricultural activity are polluted water, soil, air, and food. The agricultural sector has become one of the major contributors to global GHG emissions and is the world’s second largest emitter after the energy sector, which includes emissions from power generation and transport. Latvian and Lithuanian agriculture generates about one fifth of GHG emissions, while Estonia generates only about one tenth of the country’s GHG emissions. This paper investigates the GHG trends in agriculture from 1995 to 2019 and the driving forces of changes in GHG emissions from the agricultural sectors in the Baltic States (Lithuania, Latvia, and Estonia), which are helpful for formulating effective carbon reduction policies and strategies. The impact factors have on GHG emissions was analysed by using the Logarithmic Mean Divisia Index (LMDI) method based on Kaya identity. The aim of this study is to assess the dynamics of GHG emissions in agriculture and to identify the factors that have had the greatest impact on emissions. The analysis of the research data showed that in all three Baltic States GHG emissions from agriculture from 1995 to 2001–2002 decreased but later exceeded the level of 1995 (except for Lithuania). The analysis of the research data also revealed that the pollution caused by animal husbandry activities decreased. GHG intensity declined by 2–3% annually, but the structure of agriculture remained relatively stable. The decomposition of GHG emissions in agriculture showed very large temporary changes in the analysed factors and the agriculture of the Baltic States. GHG emissions are mainly increased by pollution due to the growing economy of the sector, and their decrease is mainly influenced by two factors—the decrease in the number of people employed in the agriculture sector and the decreasing intensity of GHGs in agriculture. The dependence of the result on the factors used for the decomposition analysis was investigated by the method of multivariate regression analysis. Regression analysis showed that the highest coefficient of determination (R² = 0.93) was obtained for Estonian data and the lowest (R² = 0.54) for Lithuanian data. In the case of Estonia, all factors were statistically significant; in the case of Latvia and Lithuania, one of the factors was statistically insignificant. The identified GHG emission factors allowed us to submit our insights for the reduction of emissions in the agriculture of the Baltic States.

The EU’s Common Agricultural Policy has for decades been geared towards sustainable agricultural development, not only to ensure a fair income for farmers but also to tackle climate change and environmental degradation, emphasizing the link between agricultural economic activity and the importance of greenhouse gas (GHG) emissions. The importance of research in this area is reinforced by the EU’s ever-increasing sustainability ambitions in recent years, as set out in the European Green Deal, which has found a place in the new 2023–2027 Common Agricultural Policy (CAP) policy to meet the EU’s 2050 target to achieve climate neutrality. The aim of this study is to assess the relationship between greenhouse gas emissions and economic performance for the agricultural sector in the Baltic States (Lithuania, Latvia, and Estonia) from 1998 to 2019. These three countries have similar agricultural structures and similar natural conditions, so the research provides comparable results. The relationship was analyzed by using the nonlinear autoregressive distributed lag (NARDL) model that allows the estimation of short-term dynamics using a distributed delay component and long-term dynamics using a single cointegrating vector. The analysis of the research data showed that gross value-added changes influence greenhouse gas emissions in all three countries. The results of the research, on the other hand, suggested that there is evidence supporting the reverse ‘U-shaped’ impact of the environmental Kuznets curve (ECK) when assessing data from Lithuania and Estonia, but not from Latvia. The study’s findings have significant policy consequences.

Ecosystems can provide a wide range of services that are critical to human well-being, health, subsistence, and survival. Examining the coherence between humans and ecosystems, ensuring the social and economic well-being of present and future generations in the context of ecosystem services (ES), this article seeks to present empirical research carried out on the possibilities of adapting human activities to ecosystem services in a specific area; namely, a coastal–rural area in the Lithuanian coastal zone, Nemunas Delta and Curonian Lagoon in Lithuania, seeking to offer opportunities with the rapidly declining population to operate services of ecosystems. Thus, elderships located near the Curonian Lagoon or within the protected area of the Nemunas Delta Regional Park were selected for the study. For this purpose, the empirical study involved representatives of different (public and private) sectors and stakeholders. The research was carried out in local tourism cultural centres and elderships with four group respondents (tourists, farmers, entrepreneurs, eldership employees). The research revealed that development of nature tourism could provide a lot of benefits for the region; after discovering the links between farming and nature tourism, possibilities would emerge to promote local farmers’ production by selling, not the raw materials, but already processed production, which has greater added value. The aforementioned tourist development ideas, especially in the ecologically vulnerable region, would enable the protected areas’ employees, local farmers, businesspeople, and municipal employees to seek new methods to adapt ecologically vulnerable areas for tourist needs without damaging the ecosystems.

The main aim of this article is to empirically examine the impact of economic growth and urbanisation on environmental degradation, as well as the existence of the environmental Kuznets curve (EKC) in three Baltic States (Lithuania, Latvia, and Estonia) from 2000 to 2020. The main Kaya identity and the extended urban Kaya identity models are applied within the analysis. The multiple regression analysis made it possible to assess the influence of urbanisation and other factors on greenhouse gas (GHG) emissions in the studied countries, as well as test the hypothesis of the inverted U-shaped EKC. The main finding reveals that GDP per capita growth has the largest and increasing effect on GHG emissions in all three countries. It was also found that changes in population in urban areas in Lithuania and Latvia reduced the amount of GHG until 2020, while in Estonia, the growing urban population greatly contributed to increasing GHG emissions. As a result, processes related to urbanisation have not yet had a significant impact on environmental quality in Lithuania and Latvia. Meanwhile, in Estonia, this is a significant factor that policymakers need to focus on when solving environmental pollution reduction problems. The hypothesis of the EKC was mostly supported when analysing GHG emissions in Lithuania and Estonia and using GDP per capita as an indicator for economic growth. On the other hand, it was found that the impact of the urbanisation rate on GHG emissions is not curved, yet there is some evidence that in Estonia, a growing urbanisation rate is related to diminishing GHG emissions, according to the multiple regression analysis. The results of the study showed that policymakers should consider economic growth and, especially in Estonia, urbanisation when solving problems related to environmental degradation.

The development of a country’s economy is directly related to the use of energy in that country’s economic sectors. Therefore, the energy–environmental Kuznets curve (EEKC) is often used when analysing a country’s potential and challenges in sustainable development, green economy, and green growth. This hypothesis tests whether there is an inverse “U”-shaped relationship between energy use and economic growth and is especially important when analysing developing countries to assess if, at a certain point, energy use begins to drop, resulting in fewer greenhouse gas emissions, environmental degradation, and the consumption of fossil-based fuels. This study aims to examine the relationship between energy consumption and economic growth in the Baltic States from 1995 to 2019, with a focus on the agriculture sector. The study uses the non-linear autoregressive distributed lag (NARDL) model for individual and panel time series. Total energy use, as well as electricity use, is included in the study, whereas gross value added is employed as a measure of economic growth. Research data analysis reveals that energy use in all three Baltic countries stabilises as gross value added increases. However, there is insufficient evidence to show that after a certain point, energy use begins to drop; thus, the hypothesis for the inverse “U”-shaped energy–environmental Kuznets curve (EEKC) is rejected. Research results have important practical implications regarding countries’ policies toward energy, including the use of electricity and sustainable development.