Agricultural insurance and green agriculture are strongly related. Agricultural insurance not only motivates farmers to adopt environmentally friendly production technology and enhances the effectiveness of production, but it also accomplishes the goal of lowering the number of chemicals that are put into the environment. This article investigates the dynamic relationship between agricultural insurance, air pollution, and agricultural green total factor productivity. To complete the aim, the authors used the panel auto-regressive distributed lags method (PMG method) and panel data from 50 states of the United States between 2005 and 2019. The empirical findings demonstrate a considerable co-integration and a cross-sectional reliance between agricultural insurance, air pollution, and agricultural green total factor production. Expanding agricultural insurance may boost agricultural green whole factor output but also exacerbate air pollution. However, significant air pollution does not increase agricultural production’s green total factor productivity. The panel Granger causality test shows a one-way causal relationship between agricultural insurance, green total factor productivity, and air pollution. A one-way causal relationship exists between air pollution and agricultural green total factor productivity. The author concluded that improving agricultural insurance coverage or cutting down on air pollution will boost agricultural green total factor output. These findings have long-term policy and management repercussions, particularly for those involved in agriculture policy and environmental management.

Access to energy, including electricity, determines countries’ socio-economic development. The growing demand for electricity translates into environmental problems. Energy is therefore a crucial element of the European Union’s sustainable development strategy. This article aims to present the changes taking place in the electricity market in Poland considering the goals of the energy policy until 2040. This is the basis for the determination of the scale of processes taking place in the Polish energy sector from two perspectives, i.e., the production of electricity considering its level and energy carriers used, and the consumption of electricity in households depending on their location (rural vs. urban areas). The research was conducted at the regional level (NUTS 2 until 2017) in Poland. Secondary data from the Central Statistical Office (GUS) contained in the Local Data Bank were used, along with information from the European Commission and Eurostat websites. Results of the study made it possible to identify areas in which a greater environmental load is observed due to increasing electricity consumption. The coefficient of localization and concentration (by Florence) and the rate of change were applied. These results indicate that, in Poland, it is now the rural areas that have a greater negative environmental impact than urban areas, resulting from differences in unit energy consumption. Compared to the other provinces, rural areas of Podlaskie province had the highest rate of growth in energy consumption in the years 2004–2019, with an annual average of almost 20%.

Several economies have acknowledged that environmental degradation poses a serious danger to worldwide sustainable production and consumption. Policy makers concur that the increased use and production of carbon-intensive technologies has intensified the detrimental consequences of carbon dioxide emissions. In response, a number of nations have reacted by enacting stringent regulations and encouraging green technology innovations across corporate and governmental organizations. Evidence that already exists suggests that research and development is a cyclical process; nevertheless, the non-linear influence of shocks in research and development and innovation in green technologies on CO2 emissions in the Nordic nations has not been well investigated. Using panel data from 1995 to 2019, this research explores the asymmetric link between innovation in green technologies and CO2 emissions. The cointegration link between the chosen variables was validated using the Westerlund cointegration test and the Johansen–Fisher panel cointegration test. The findings of both tests confirm the presence of cointegration association between dependent and independent variables. The outcomes of CS-ARDL revealed that negative shocks in creating green technologies contribute to carbon dioxide emissions during recessions. Second, the findings supported the notion that innovation in green technology may reduce carbon dioxide emissions during times of economic expansion. Thirdly, the GDP increases the CO2 emissions, but the usage of renewable energy decreases CO2 emissions. In addition, the robustness analysis validated the consistency and precision of the existing findings. In summary, the findings suggest that the link between advances in environmentally friendly technologies and levels of carbon dioxide emissions were inversely proportional.

The main aim of the paper was an analysis of the present status and changes of commercially grown genetically modified crops and food security from 2012 to 2018, based on the Global Food Security Index by countries. The work used a descriptive approach with elements of inductive reasoning and meta-analysis based on secondary data, derived from Briefs of The International Service for the Acquisition of Agri-biotech Applications, FAOSTAT and the GFSI, developed and calculated by The Economist Intelligence Unit. The study showed the highest increase in biotech crops was observed in Brazil and the USA, i.e. in countries with a relatively high level of GFSI. Accordingly, the highest positive change in GFSI was achieved in several countries both with quite a high level of GFSI (Chile, Uruguay and Argentina) and with a very low GFSI (Burkina Faso and Myanmar). A slightly positive Pearson correlation coefficient for the area of biotech crops and GFSI indicated that, in the analysed period, when an increase in GM crop area was observed, the value of the GFSI increased as well. However, the value of the Pearson correlation means that the biotech crop area can be considered one of the many factors influencing the food security of the studied countries. The results show that biotech crops cannot only be analysed in the context of food security at a country level, but also at a household level. GM crops could contribute to food production increases and higher food availability, however not necessarily to food security, especially at a country level.

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