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Considering the dearth of industry-specific empirical research exploring sustainability reporting in the context of developing countries, this chapter aims to critically examine the extent and the nature of sustainability information disclosure of environmentally polluting industries in India.

Data are collected from business responsibility reports (BRRs), sustainability reports, Corporate Social Responsibility (CSR) reports and integrated reports of all 57 energy and mining companies included in NIFTY500 Index at National Stock Exchange of India for the year 2017–2018 and 2018–2019. Content analysis is used to examine the sustainability disclosure practices and one-way analysis of variance (ANOVA) statistical analysis is performed to test the difference across various dimensions of sustainability reporting of companies.

The results indicate low environmental reporting of the key indicators by energy and mining companies in India. It is found that state-owned companies have better social reporting practices against private sector companies. The findings also indicate that Global reporting initiative (GRI) based reporting have better sustainability disclosure practices and companies reporting based on BRR lack quantitative information disclosure.

The findings of the present chapter have several implications for policymakers, investors, regulators and management of these high environmental and social impact companies in India. The findings which coincide with the key areas of sustainability disclosure can be used for improving sustainability disclosure practices by the various stakeholders.

This is one of the first studies to investigate the nature and extent of sustainability performance disclosure of the companies from polluting industries in India. This chapter also contributes to the existing sustainability reporting literature by providing evidence on industry-specific disclosure in the context of a developing country.

This study attempts to analyze energy intensity, capacity utilization (CU), output and productivity growth of aggregate manufacturing sector in India during the period 1980–1981 to 2016–2017. A decadal analysis as well as a comparison between pre- and post-liberalization period of productivity growth is also made. Total factor productivity growth (TFPG) is also adjusted with CU to obtain adjusted TFPG. The trend in energy intensity is also analyzed to answer the question of sustainability. Results shows that TFPG declined in the post-reform period, highlighting the fact that liberalization process has its adverse impact on productivity growth. From the study it is observed that a declining trend in adjusted TFPG in the post-reform period, but the rate of decline is higher. Energy intensity and CU of the Indian manufacturing industries is found to be increasing over the study period. Increasing energy intensity, quite significantly, would increase the level of pollution generated by the manufacturing industries. So, interestingly enough, this may lead to conclude that the growth of the manufacturing industries is not in line with the basic essence of sustainable development.

The unorganised manufacturing sector contributes one third share of overall manufacturing employment and one fifth share of gross value added of the manufacturing sector. Despite its important role in large-scale employment generation, this sector is neglected by the researchers as well as by the policy makers as compared to the focus given on the organised manufacturing sector. The issues of energy intensity, environment emissions and growth of unorganised manufacturing enterprises (UMEs) remain unexplored. The present chapter attempts to estimate the CO₂ emission and emission intensity (EI) across UMEs on the basis of NSSO Unit Level data of 62nd, 67th and 73rd rounds. It also analyses the growth of UMEs in relation to CO₂ emission and EI. The nature of the sector is very much dispersed. Our study reveals that a portion of unorganised enterprises did not use any energy in their production activities and used manually operated instruments like – handlooms, weaving machines, hand-operated oil and rice mills, etc. The main energy inputs of UMEs are electricity and fuel & lubricants. The CO₂ emission is relatively less in UMEs compared to organised manufacturing enterprises. Across the unorganised manufacturing industries, the higher CO₂ emission are observed in manufacturing of food product industry and other non-metallic mineral industry. The study found that CO₂ EI of UMEs depends on firm-level characteristics like perennial nature, establishment type, urban location and expanding growth status. However, capital intensive UMEs are more polluting.

In this chapter, characteristic of the fuel and energy sector of Republic of Belarus; its organizational structure; the current state of development of power, gas, peat, and oil industries are given. The energy balance of the country and the main power streams is analyzed. Characteristic of key indicators of energy security is presented. The main threats connected with ensuring energy security of Republic of Belarus are allocated. In particular, the characteristic of the directions of reducing the energy dependence of the Republic of Belarus on the supply of natural gas from the Russian Federation is presented. Dynamics of power consumption of GDP is analyzed. Potential of use of renewable and local energy resources, complexity and prospect of their further integration into the Belarusian power system are considered. The prospects of development of nuclear power of Republic of Belarus are described. The advantages and disadvantages connected with input of the Belarusian nuclear power plant in operation are designated. The perspective directions of sustainable power development of Republic of Belarus till 2035 are revealed.

In this study, the authors have tried to estimate and examine the relationship between energy intensity (EI), capacity utilisation (CU) and total factor productivity (TFP) of Indian Iron and steel industry for the time period 1980–1981 to 2016–2017. The estimation of TFP and its growth is based on three inputs capital (K), labour (L) and energy (E) using transcendental logarithmic cost function. Besides, capital and labour factor inputs, the estimation of CU also take into account the input, energy. It also considers the variable, price of energy and uses a variable cost (VC) function. This study also takes into account the concept of adjusting total factor productivity growth (TFPG) by CU. From our result, this study observes that CU increased over time. Again, Iron and Steel industry has become energy intensive (increasing EI) over the time period taken up for the study. On the other hand, TFPG has declined in the liberalised era. The preliminary idea that we get from our result is that TFPG is negatively related to the extent of pollution generated by energy intensive nature of the Indian Iron and Steel industry, which is in line with reality. To come out of this situation, we may prescribe the use of green technology and green energy sources for this industry.

There is a long-going discussion in Russia focusing on finding new stimulus for economic growth. Being very rich with natural recourses, Russia has enjoyed extensive economic growth model for many centuries. The world is changing. Russia as any country which is to keep up with the dynamics and the quality of the world economic growth must find some new technologies and economic triggers. Green investment can be regarded as the key instrument to achieve faster economic growth and to make technological gap narrower. The chapter focuses on state policy and business practice in green investment in Russia.