Contributing to WUDAPT: A Local Climate Zone Classification of Two Cities in Ukraine

Local climate zones (LCZs) divide the urban landscape into homogeneous types based on urban structure (i.e.,morphology of streets and buildings), urban cover (i.e., permeability of surfaces), construction materials, and human activities (i.e., anthropogenic heat). This classification scheme represents a standardized way of capturing the basic urban form of cities and is currently being applied globally as part of the world urban database and portal tools (WUDAPT) initiative. This paper assesses the transferability of the LCZ concept to two Ukrainian cities, i.e., Kyiv and Lviv, which differ in urban form and topography, and considers three ways to validate and verify this classification scheme. An accuracy of 64% was achieved for Kyiv using an independent validation dataset while a comparison of the LCZ maps with the GlobeLand30 land cover map resulted in a match that was greater than 75% for both cities. There was also good correspondence between the urban classes in the LCZ maps and the urban points of interest in OpenStreetMap (OSM). However, further research is still required to produce a standardized validation protocol that could be used on a regular basis by contributors to WUDAPT to help produce more accurate LCZ maps in the future

Methodology and Assessment of Labor Remuneration in Terms of Implementing the Principles of Decent Work in Ukraine

The aim of the work is to highlight the methodological and methodical aspects, and the results of studying labor remuneration in terms of implementing the principles of decent work in Ukraine. The necessity of implementing the concept of decent work and its payment into the practice of social and labor relations is substantiated. The methodological basis for developing tools to assess wages in terms of implementing the principles of decent work is formulated. Indicators and standards of decent wages for the macro level are proposed. Based on the results of the expert survey, the reliability of the formed indicators and their weights are determined. Various methodological approaches to calculating single indices of decent wages are proposed depending on the specifics of the indicators, units of measurement, established standards, and the availability of a basis for comparison. The article contains the methodology for determining a composite indicator of decent wages, which can be used to carry out a comparative analysis of the wage policy of various countries and their ranking. Ranges of values for the composite indicator of decent wages are developed to determine its level and trends in labor remuneration. The results of assessing wages in terms of implementing the principles of decent work in Ukraine showed that single indices have zero values for most indicators. The composite indicator of decent wages at the macro level corresponds to the level “below average”, which indicates a number of shortcomings in the wage policy in Ukraine. The results of the study indicate a lack of attention of government bodies, enterprise managers, and social partnership parties to wage management issues, which requires developing innovative mechanisms for the formation of wage policy based on decent work

МОДЕЛЮВАННЯ ЕМІСІЇ ПАРНИКОВИХ ГАЗІВ У ЖИТЛОВОМУ СЕКТОРІ ЗАХІДНОЇ УКРАЇНИ З ВИКОРИСТАННЯМ ГЕОІНФОРМАЦІЙНИХ ТЕХНОЛОГІЙ

A mathematical model for territorial inventory and spatial analysis of greenhouse gas emission processes in the residential sector is developed. The model is based on the assessment of energy demand, methods of inventory recommended by Intergovernmental Panel on Climate Change, and reflects the accessibility of energy sources for the population. As an example, using statistical information the spatial inventory of greenhouse gas emissions in the residential sector in Western Ukraine was conducted. Emission processes analysis is carried out at the level of settlements.Розроблено математичну модель для територіальної інвентаризації та просторового аналізу процесів емісії парникових газів у житловому секторі. Модель базується на оцінюванні енергетичних потреб населення, методиках інвентаризації Міжурядової групи експертів зі зміни клімату і враховує рівень доступності джерел енергії для населення. Як приклад, на основі статистичних даних здійснено просторову інвентаризацію емісій парникових газів у житловому секторі областей Західної України. Дослідження емісійних процесів проведено на рівні населених пунктів

High-resolution spatial distribution of greenhouse gas emissions in the residential sector

The development of high-resolution greenhouse gas (GHG) inventories is an important step towards emission reduction in different sectors. However, most of the spatially explicit approaches that have been developed to date produce outputs at a coarse resolution or do not disaggregate the data by sector. In this study, we present a methodology for assessing GHG emissions from the residential sector by settlements at a fine spatial resolution. In many countries, statistical data about fossil fuel consumption is only available at the regional or country levels. For this reason, we assess energy demand for cooking and water and space heating for each settlement, which we use as a proxy to disaggregate regional fossil fuel consumption data. As energy demand for space heating depends heavily on climatic conditions, we use the heating degree day method to account for this phenomenon. We also take the availability of energy sources and differences in consumption patterns between urban and rural areas into account. Based on the disaggregated data, we assess GHG emissions at the settlement level using country and regional specific coefficients for Poland and Ukraine, two neighboring countries with different energy usage patterns. In addition, we estimate uncertainties in the results using a Monte Carlo method, which takes uncertainties in the statistical data, calorific values, and emission factors into account. We use detailed data on natural gas consumption in Poland and biomass consumption for several regions in Ukraine to validate our approach. We also compare our results to data from the EDGAR (Emissions Database for Global Atmospheric Research), which shows high agreement in places but also demonstrates the advantage of a higher resolution GHG inventory. Overall, the results show that the approach developed here is universal and can be applied to other countries using their statistical information

Determination of CO2 solubility in Perna perna mussel and analysis of the suitability of the ideal and non-ideal gas models

In SGS (Soluble Gas Stabilization) processes, the carbon dioxide (CO2 ) is dissolved into the food product under controlled temperature, pressure, and gas/product ratio. The prediction of CO2 solubility can be achieved using a computational code using equations of state from experimental data on CO2 concentration in food. In this work, the solubility of CO2 in Perna perna mussels was obtained using Ideal Gas law and Virial, Van der Waals, Soave-Redlich-Kwong, and Peng-Robinson equations. The SGS process was performed at varying system pressure (200–600 kPa), temperature (0–6 °C), and gas/product (g/p) (mussels) ratio (1:1–5:1) in the cooked and shucked mussels for 65 h. A total of 11 experiments, arranged in a 23 experimental design, with triplicate runs at the central point, were performed. The compressibility factor indicated that the Ideal Gas state is a good approximation only for experiments 1, 2, 5, and 6. It was observed that the pressure and the gas/product ratio exert a more significant influence on the CO2 solubilization process in the mussel. Visual Basic for Applications (VBA) to perform thermodynamic calculations showed to be a great resource regarding complex calculations

МОДЕЛЮВАННЯ ЕМІСІЙ ПАРНИКОВИХ ГАЗІВ ВІД СПАЛЮВАННЯ ПРИРОДНОГО ТА СКРАПЛЕНОГО ГАЗУ В ЖИТЛОВОМУ СЕКТОРІ РІВНЕНСЬКОЇ ОБЛАСТІ

Based on the analysis of natural and liquefied gases used in residential sector in Rivne region an approach to inventory and spatial analysis of greenhouse gas emissions caused by burning these fossil fuels is presented. The mathematical model and the algorithms for spatial inventory of greenhouse gases, based on territorial disaggregation of burned fuels, which gives possibility to create georeferenced cadastres of emissions in the residential sector, are developed. Based on performed numerical experiments the digital map and database of greenhouse gas emissions in Rivne region are obtained. Analysis of emission processes is conducted for elementary areas 2 km × 2 km in size.На основі аналізу цільового використання природного та скрапленого газу у житловому секторі Рівненської області представлено загальний підхід до процесу інвентаризації та просторового аналізу емісій парникових газів від спалювання цих видів палива. Розроблено математичну модель та алгоритми дослідження процесів емісії парникових газів у житловому секторі, що ґрунтуються на територіальному розподілі спаленого населенням палива з врахуванням показників густоти населення, питомої житлової площі, обладнаної газом та опаленням, і дають можливість формувати георозподілені кадастри емісій парникових газів. На підставі здійснених числових експериментів отримано цифрову карту та відповідну георозподілену базу даних, які містять інформацію про джерела та кількісні оцінки емісії в розрізі окремих елементарних об’єктів розміром 2 х 2 км

Satellite Observations Reveal Inequalities in the Progress and Effectiveness of Recent Electrification in Sub-Saharan Africa

Ending energy poverty is a necessary condition for achieving the Sustainable Development Goals (SDGs). Boosting electricity access levels is, how- ever, insufficient if consumption and reliability in- dicators stagnate. Previous research has shown that satellite-derived data can complement field surveys in tracking energy poverty but with little consideration for the multi-dimensionality of en- ergy access and the role of demographic dy- namics. Here, we process 6 years of high-resolu- tion population, nighttime light, and settlement data for sub-Saharan Africa to derive multi- dimensional estimates of electricity access. Our results, validated against a range of sources, confirm a recent surge in electrification such that >115 million people gained access over the 2014–2019 period. Yet, they reveal wide inequal- ities in the quality of electrification, which cannot be observed in the existing statistics. The pace of electrification must more than triple to fulfill SDG 7.1.1 by 2030. Efforts could fall short if aimed solely at boosting numbers of national electricity connections

Spatial GHG inventory in the agriculture sector and uncertainty analysis: A case study for Poland

Estimation of uncertainties is an important part of complete inventory of greenhouse gas (GHG) emissions. Information on uncertainty is intended not only to question the reliability of inventory estimates, but to assist in the identifying priority measures to improve the quality of future inventories. This article discusses bottom-up inventory from the agricultural sector in Poland. Accordingly to the developed geoinformation approach area-type sources of emission (arable lands, rural localities) were investigated. In implemented mathematical models for the estimation of GHG emissions from agricultural activity the statistical data on animal and crop production, as well as specific emission factors were used. Methods for the spatial inventory of GHG emissions from agricultural sources, taking into account the specifics of animal nutrition, are described. Monte-Carlo method was applied for a detailed estimation of uncertainty "from category to category," because uncertainties of input parameters (CH4 and N2O emission factors) are large and non-normally distributed (95% confidence interval). The land use map is used to calculate the territorial distribution of GHG emissions. The structure of total GHG emissions on different categories of animal sector and agricultural soils sector by type of GHG is presented and visualised as digital maps. Analysis of uncertainty of GHG inventory results were carried out for voivodeships. Results are presented as sets of numerical values of the bounds of confidence intervals for the main GHGs and at different levels of spatial disaggregation. The improving of knowledge on territories, where emissions took places, enables us to better inventory process and reduce the overall uncertainty

Conditionally autoregressive model for spatial disaggregation of activity data in GHG inventory: Application for agriculture sector in Poland

This report presents a novel approach for allocation of spatially correlated data, such as emission inventories, into finer spatial scales conditional on covariate information observable in a fine grid. Spatial dependence is modelled with the conditional autoregressive structure introduced into a linear model as a random effect. The maximum likelihood approach to inference is employed, and the optimal predictors are developed to assess missing values in a fine grid. The usefulness of the proposed technique is shown for agricultural sector of GHG inventory in Poland. An example of allocation of livestock data (a number of horses) from district to municipality level is analysed. The results indicate that the proposed method outperforms a naive and commonly used approach of proportional distribution