Municipal solid waste (MSW) landfills are among the major sources of greenhouse gas (GHG) emissions affecting global warming and the Earth’s climate. In Bulgaria, 53 regional non-hazardous waste landfills (RNHWL) are in operation, which necessitates conducting studies to determine the environmental risk from the emitted GHGs. This study attempted to assess the CH₄ and CO₂ emissions from three gas wells of a cell (in active and closed phases, each of 2.5 years duration) in an RNHWL, Harmanli (41°54′24.29″ N; 25°53′45.17″ E), based on monthly in situ measurements by portable equipment, using the Interrupted Time Series (ITS) ARMA model. The obtained results showed a significant variation of the CH₄ and CO₂ concentrations (2.06–15.1% v/v) and of the CH₄ and CO₂ emission rates (172.81–1762.76 kg/y) by gas wells (GWs), months and years, indicating the dynamics of the biodegradation of the deposited waste in the areas of the three GWs. Throughout most of the monitoring period (2018–2022), the CH₄ concentrations were higher than the CO₂ concentrations (% v/v), while CO₂ emissions were lower than CH₄ emissions (kg/y), a fact that could be explained by the differences in the mass of the two gases. The emissions rates of both gases from GW2 dominated over those from GW1 and GW3, giving a reason to determine the zone of GW2 as a hotspot of Cell-1. On the whole, CH₄ and CO₂ emission rates were higher in the winter (December–February) and partly in the spring (March–May) compared to summer–autumn (June–November). However, the CH₄ and CO₂ concentrations and emissions decreased drastically after the Cell-1 closure. The CH₄/CO₂ ratio (0.68–2.01) by months and gas wells demonstrated a great sensitivity, making it a suitable indicator for the assessment of organic waste biodegradation level in the landfills. The ITS ARMA model confirmed the negative and significant effect of the cell closure on CH₄ and CO₂ emissions; the correlations found between predicted and observed values were strong and positive (0.739–0.896).

The aim of this article is to supply the first empirical research inspecting how changes in diesel prices influence the prices of four agricultural commodities in Bulgaria. For this purpose, using a VECM and monthly agricultural commodity prices between January 2011 and July 2022, we estimated short-run and long-run changes in producer and retail prices of cow’s milk, chicken eggs, greenhouse tomatoes and cucumbers due to the change in average monthly diesel prices. The Granger causality test indicates that diesel prices cannot be used to forecast the behavior of producer and retail prices in the four markets considered. Diesel prices can be used to forecast the behavior of producer prices in only the cow’s milk market, and the diesel price predicts retail prices in the chicken egg and greenhouse cucumber markets. The results of the response of the researched prices of agricultural commodities to diesel price shocks indicate a positive response of both upstream and downstream prices of cow’s milk and chicken egg markets and upstream prices of the greenhouse tomato market despite the initial negative shock.

The purpose of this paper is to provide the first empirical research analysing the effects of the COVID-19 pandemic on the Bulgarian stock market before its onset and in the four pandemic waves. For this purpose, we used a fixed effect panel data regression model for the stock returns of 23 companies listed on the Bulgarian Stock Exchange from 2 January 2020 to 16 November 2021. The study showed that the growth rate of COVID-19 deaths per day in Bulgaria had a negative effect on the stock returns and had the strongest influence on them in the fourth pandemic wave. In addition, our results showed that stock returns in healthcare, IT, utilities, and real estate sectors were negatively affected before the COVID-19 pandemic while the first COVID-19 pandemic wave had a positive effect on healthcare and consumer staples sectors. During the second COVID-19 wave, the stock returns of the IT sector had a positive effect, while Utilities sector had a negative effect. The third COVID-19 wave had a positive effect on industrials and consumer staples sectors, while healthcare, real estate, and IT sectors showed a negative effect. During the fourth COVID-19 wave, the stock returns of the IT sector had a positive effect and consumer staples sector had a negative effect.

Geometric characteristics and properties of a two-parametric family of Lie groups with almost contact B-metric structure of the smallest dimension