According to the United Nations Environment Program (UNEP) annual Emissions Gap Report 2019, further reductions in greenhouse gas (GHG) emissions are needed to reduce climate change impacts. In Japan, the 2030 Intended Nationally Determined Contribution (INDC) target is an emissions reduction of 26% compared to 2013. The World Health Organization (WHO) declared that the coronavirus (COVID-19) outbreak has led to 43,341,451 confirmed cases and 1,157,509 confirmed deaths globally and affected 218 countries (as of 27 October 2020). In Japan, as of the same date, 96,948 infectious cases and 1724 deaths related to the new coronavirus had been recorded. These numbers continue to increase. In Japan, in March 2020, the number of international tourist arrivals decreased by about 93% compared to last year at the same period. The World Tourism Organization (UNWTO) reported several significant scenarios for the tourism industry. COVID-19 is the greatest shock to international tourism since 1950 and represents an abrupt end to the 10-year period of sustained growth that followed the 2009 financial crisis. It was thought that it would be possible to analyze the economic, environmental, and social impacts of rapid social changes. Thus, this study estimates changes in Japan’s tourist consumption, the carbon footprint (CFP), and employment due to the influence of the COVID-19 pandemic. The calculations in this study adopt a lifecycle approach using input–output tables. Based on these observations, this study uses four scenarios (SR 1, no recovery until December; SR 2, recovery from October; SR 3, recovery from July or September; and SR 0, same growth rate as 2018–2019) for Japan to calculate the CFP and employment change using input–output table analysis based on tourist consumption, which is a tourism metric. According to our results (2019 vs. SR 1 and 3), the consumption loss is between 20,540 billion yen (−65.1%) and 12,704 billion yen (−39.1%), the CFP reduction is between 89,488 kt-CO₂eq (−64.2%) and 54,030 kt-CO₂eq (−37.5%), and the employment loss is between 2,677,000 people (−64.2%) and 1,678,000 people (−37.5%). As of November 2020, the tourism industry continues to be affected by the COVID-19 pandemic. In the post-COVID-19 society, it will be necessary to maintain the GHG emissions reductions achieved in this short period and realize economic recovery. This recovery must also be sustainable for tourism stakeholders and society.

Weighting is one of the steps involved in LCIA. This enables us to integrate various environmental impacts and facilitates the interpretation of environmental information. Many different weighting methodologies have already been proposed, and the results of many case studies with a single index have been published. LIME2 (Itsubo et al. Int J Life Cycle Assess 17(4):488-498, 2012) developed weighting factors for four different areas of protection that reflect environmental awareness among the Japanese public. This method has already been widely used in Japan, but difficulties exist universally using the Japanese weighting factors around the world. It is presumed that the weighting varies depending on economic, cultural, and social conditions, and there are still few cases in which weighting factors have been specifically invented or studied in consideration of variance in these elements. This study attempted to develop weighting factors applicable to the Group of Twenty (G20) countries with a view toward developing those that could be used in different countries. In the study, a survey was conducted with a uniform questionnaire in G20 countries to compare the weighting factors calculated for different countries, along with an investigation on development and utilization of global weighting factors. A conjoint analysis was conducted to give a weighting between the four areas of protection defined by LIME: human health, social assets, biodiversity, and primary production. The analysis is suitable for measuring the value of each of the multiple attributes of the environment. This study conducted a questionnaire in all the G20 member states. The survey puts priority on making the questions understood by the respondents and minimizing bias, adopting interviews, visiting surveys, and surveys in venues in the 11 emerging countries. In the developed countries, Internet surveys were conducted after confirming that their results are statistically significant from the pretest results in these states. In both surveys, random sampling was performed to take 200–250 samples (households) in each of the emerging countries and 500–600 samples in each of the developed countries. The surveys collected a total of 6400 responses. Statistical values based on this model can be considered to reflect the variability between each individual’s environmental thoughts. The calculated results can then be used to compare the variety of environmental thoughts in developed and emerging countries. The study was able to obtain two different kinds of results: dimensionless weighting factors and economic indicators using the amount of willingness to pay. This paper solely presents the former. The weighting factors in the entire G20 community, in the group of developed countries (G8) and in the group of emerging countries (G20 states excluding the G8) and those in the individual G20 countries, were estimated. The calculated values were significant statistically at the 1 % level (all p values for the safeguard subject coefficients were less than 0.0001), with the exception of monetary attributes for several emerging countries. Converted into dimensionless values, so that the total sum for the four subjects equals 1, the weighting factor was the highest for human health in the entire G20 circles, at 0.34, followed by biodiversity at 0.29, and primary production at 0.23. The weighting for social assets was relatively poor, at 0.13. In the G8 developed states, the figures of biodiversity and primary production were relatively higher than those of the same two subjects in the full G20. Biodiversity had the highest value, at 0.34, and was followed by human health at 0.30. On the other hand, in emerging countries, the weighting of health impacts was particularly significant, at 0.44, whereas the three other subjects had almost equivalent weightings—biodiversity at 0.19, social assets at 0.18, and primary product at 0.18. The weighting factors by country and the variance of preference intensities by country showed minor differences among developed countries while they reflected considerable differences among emerging countries. Accurate weighting factors representing the environmental attitudes of the world and national public are needed in order to conduct general purpose LCA. This study is the world’s first to conduct surveys with the use of the same questionnaire not only in developed countries but also in emerging countries, and to compare the findings. A total of 6400 responses were obtained via interviews and Internet surveys. The survey thus gained a statistically significant result on all the environmental attributes including the weighting factors for the G20 circles, G8 states, emerging countries exclusive of the G8 states, and individual countries in which surveys took place. The results have revealed a relatively minor difference in weighting factors and variation coefficients between the areas of protection in the developed countries whereas a considerable difference was observed between those subjects in emerging countries.

The importance of the contribution of tourism to climate change has been noted by the United Nations World Tourism Organization (UNWTO). By combining a process-based life cycle assessment (LCA) and input–output analysis, several researchers have attempted to evaluate the impacts of the tourism industry, as well as its products and services. Indeed, the tourism sector has a wide range of industries, including travel and tours, transportation, accommodation, food and beverage, amusement, souvenirs, etc. However, the existing cases do not show a breakdown of the impact on climate change. In this paper, the carbon footprint (CFP) of the Japanese tourism industry was calculated based on tourist consumption, using the Japanese input–output table and the Japanese tourism industry. We demonstrate that the total emissions were approximately 136 million t-CO2 per year. The contribution ratio of each stage is as follows: Transport 56.3%, Souvenirs 23.2%, Petrol (direct emissions) 16.9%, Accommodation 9.8%, Food and Beverage 7.5%, and Activities 3.0%. Then, in the breakdown, the impacts are in the following order: Air transport 24.7%, Petrol (direct emissions) 16.9%, Accommodation 9.8%, Food and Beverage 7.5%, Petrol 6.1%, Textile products 5.3%, Food items 4.9%, Confectionery 4.8%, Rail transport 3.9%, Cosmetics 1.9%, and Footwear 1.8%. In addition to transportation, this research also highlights the contribution from souvenirs, accommodation, and food and beverages.

Life cycle assessment (LCA) has received attention as a tool to evaluate the environmental impacts of products and services. In the last 20 years, research on the topic has increased, and now more than 25,000 articles are related to LCA in scientific journals databases such as the Scopus database; however, the concept is relatively new in Africa, where the number of networks has been highlighted to be very low when compared to the other regions. This paper focuses on a review of life cycle assessments conducted in Africa over the last 20 years. It aims at highlighting the current research gap for African LCA. A total of 199 papers were found for the whole continent; this number is lower than that for both Japan and Germany (more than 400 articles each) and nearly equal to developing countries such as Thailand. Agriculture is the sector which received the most attention, representing 53 articles, followed by electricity and energy (60 articles for the two sectors). South Africa (43), Egypt (23), and Tunisia (19) were the countries where most of the research was conducted. Even if the number of articles related to LCA have increased in recent years, many steps still remain. For example, establishing a specific life cycle inventory (LCI) database for African countries or a targeted ideal life cycle impact assessment (LCIA) method. Several African key sectors could also be assessed further.

The external costs derived from the environmental impacts of electricity generation can be significant and should not be underrated, as their consideration can be useful to establish a ranking between different electricity generation sources to inform decision-makers. The aim of this research is to transparently evaluate the recent external cost of electricity generation in G20 countries using a global life-cycle impact-assessment (LCIA) method: life cycle impact assessment method based on endpoint modeling (LIME3). The weighting factors developed in the LIME3 method for each G20 country enable one to convert the different environmental impacts (not only climate change and air pollution) resulting from the emissions and resources consumption during the full lifecycle of electricity generation—from resource extraction to electricity generation—into a monetary value. Moreover, in LIME3, not only the weighting factors are developed for each G20 country but also all the impact categories. Using this method, it was possible to determine accurately which resources or emission had an environmental impact in each country. This study shows that the countries relying heavily on coal, such as India (0.172 $/kWh) or Indonesia (0.135 $/kWh) have the highest external costs inside the G20, with air pollution and climate accounting together for more than 80% of the costs. In these two countries, the ratio of the external cost/market price was the highest in the G20, at 2.3 and 1.7, respectively. On the other hand, countries with a higher reliance on renewable energies, such as Canada (0.008 $/kWh) or Brazil (0.012 $/kWh) have lower induced costs. When comparing with the market price, it has to be noted also that for instance Canada is able to generate cheap electricity with a low-external cost. For most of the other G20 countries, this cost was estimated at between about 0.020$ and 0.040 $/kWh. By estimating the external cost of each electricity generation technology available in each G20 country, this study also highlighted that sometimes the external cost of the electricity generated from one specific technology can be significant even when using renewables due to resource scarcity—for example, the 0.068 $/kWh of electricity generated from hydropower in India. This information, missing from most previous studies, should not be omitted by decision makers when considering which type of electricity generation source to prioritize.