Search

This paper contributes to the debate surrounding the impact of adaptation to climate change on the incentives to abate greenhouse gases emissions. Using data from the World Development Indicators and various adaptation funds under the UNFCCC framework, this paper provides an empirical analysis of the relation between adaptation and emissions. We specifically test whether adaptation measures to climate change affect emissions of greenhouse gases in a world where adaptation funds are available. Using a staggered difference-in-differences approach and an event study analysis, we find that receiving adaptation funding significantly and negatively affects several CO2 emissions measures, providing preliminary evidence of the presence of a halo effect of adaptation funding. We do not find evidence of a significant change in the emissions of methane, nitrous dioxide and other greenhouse gases. [ABSTRACT FROM AUTHOR]

The excessive carbon emissions not only intensify the global climate change, but also seriously restrict the sustainable development of social economy. However, improving industrial carbon emissions efficiency is the most directly effective way to reduce emissions. Therefore, accurate measurement and analysis of carbon emissions efficiency and evolution characteristics of China's industrial system is the basis for China to improve carbon emissions efficiency. Based on this, we adopted energy consumption method and input-output method to calculate and analyze the industrial carbon emissions efficiency and evolution characteristics of China from 2002 to 2015. The results show that (1) If carbon emissions from cement production are ignored and only energy-related carbon emissions are considered, the calculation results of carbon emissions efficiency of heavy industry will be overestimated about 30%. (2) Compared with 2002, China's industrial carbon emissions efficiency increased by about twice in 2015. Specifically, the optimization of carbon emissions efficiency in agriculture, construction, light industry and service industry is very obvious, which has increased by 5.65, 5.00, 4.69 and 4.68 times respectively; The optimization of carbon emissions efficiency in power sector, heavy industry, transportation and chemical industry was obvious, which increased by 2.55, 2.01, 1.86 and 1.47 times respectively; The carbon emissions efficiency of the fossil energy sector has decreased by 0.36 times. (3) The carbon emissions efficiency of various industries has significant differences. Among them, agriculture, service industry, light industry and construction industry are generally industries with higher carbon emissions efficiency, while power sector, fossil energy sector, transportation industry, chemical industry and heavy industry are generally industries with lower carbon emissions efficiency, especially power and fossil energy sectors. Based on these, this paper provides policy implications and scientific evidence for accurately improving carbon emissions efficiency from the perspective of carbon emissions efficiency. [ABSTRACT FROM AUTHOR]

It is crucial for the development of carbon reduction strategies to accurately examine the spatial distribution of carbon emissions. Limited by data availability and lack of industry segmentation, previous studies attempting to model spatial carbon emissions still suffer from significant uncertainty. Taking Pudong New Area as an example, with the help of multi-source data, this paper proposed a research framework for the amount calculation and spatial distribution simulation of its CO2 emissions at the scale of urban functional zones (UFZs). The methods used in this study were based on mapping relations among the locations of geographic entities and data of multiple sources, using the coefficient method recommended by the Intergovernmental Panel on Climate Change (IPCC) to calculate emissions. The results showed that the emission intensity of industrial zones and transport zones was much higher than that of other UFZs. In addition, Moran's I test indicated that there was a positive spatial autocorrelation in high emission zones, especially located in industrial zones. The spatial analysis of CO2 emissions at the UFZ scale deepened the consideration of spatial heterogeneity, which could contribute to the management of low carbon city and the optimal implementation of energy allocation. [ABSTRACT FROM AUTHOR]

Government policies during the COVID-19 pandemic have drastically altered patterns of energy demand around the world. Many international borders have been closed and populations have been confined to their homes, which has reduced transport and changed consumption patterns. A decrease in CO2 emissions and pollution has thus been recorded during forced confinements. This has offered a glimpse of how the world might look like with a drastic reduction of human impact. The present paper explores how facts are framed in news discourse and investigates the recontextualization of the environmental issue in news media. The study analyses a collection of news articles about the consequences of coronavirus on the environment published on the websites of the major news channels in the UK, namely BBC News and Sky News. This CDA investigation studies how the UK news outlets re-mediated scientific knowledge about climate change to emphasise or minimise the positive consequences of confinement on the planet. [ABSTRACT FROM AUTHOR]

The study estimates the amount of emissions resulting from linear sources. There were calculations for a model rural municipality, composed of national, provincial, country, and municipal roads that run through the area. In this study, the following categories of vehicles were assumed to travel along this route: motorcycles, passenger cars, light trucks (vans), heavy trucks without trailers, trucks with trailers, and buses. The analysis used data on the average volume of traffic (SDR) on selected roads on the territory of the sample municipality, based on the frequency of participation in traffic by each mode of transportation on selected road sections. To estimate the emission rates of each pollutant, for each vehicle category separately, the calculations were made based on the emission factor rates for each type of fuel. According to the adopted methodology and based on the adopted assumptions scenarios, pollutants' emissions were estimated. The implementation of the scenarios offered for reducing CO2 emissions has been proposed, and it is estimated that, depending on the variant adopted, the reductions will be between 13 and 21% in variant I, between 3 and 8% in variant II, and between 18 and 34% in combining these variants. The variant with a reduction in private car transportation in favor of bicycle transportation in combination with public transportation showed the most favorable effects on the environment. [ABSTRACT FROM AUTHOR]

The landfill is an inexpensive way of municipal solid waste (MSW) management and contributes extensively to the total carbon budget and global climate change. Three landfills from two geographically distinct metro- cities of India were taken as model systems to create microcosms and study their physiochemistry, microbiology, and carbon emission. The microcosm experiments revealed that facultative anaerobic bacterial community showing the dominance in the beginning but with the progression of anoxia and anaerobic conditions, methanogenesis prevailed, resulting in a clear shift towards the abundance of methanogens especially the members of Methanosarcina, Methanocorpusculum, and Methanoculleus (70–90% of the total microbial population). Geochemical data showed a wide range of heterogeneity in landfills' composition located even in the same city. In past, greenhouse gas emission from landfills is mainly estimated using different models which lack accuracy. As limited information is available as of now, this study can elicit researcher interest for in-depth characterization of microbial diversity and carbon emission from landfills. The microcosm model presented in the current study is a robust and straightforward method of accurate estimation of amounts of different types of gases release from landfill. It can also be extrapolate for estimation of different gases release from actual landfill sites by setting the on-site experiments. [ABSTRACT FROM AUTHOR]

COVID-19, declared by the World Health Organization (WHO) to be a pandemic, has affected greenhouse gas emissions and contributed to the uncertainty of environmental activities. This study demonstrates the effect of lockdowns, the number of new confirmed cases, and the number of newly confirmed deaths due to COVID-19 on CO2 emissions. The data series used are for the UK from 23 March 2020 to 31 December 2020 and for Spain from 14 March 2020 to 31 December 2020. This research adopted the Augmented Dickey–Fuller (ADF) test for a stationarity check of the data series, the Johansen cointegration test for determining cointegration among variables, and the vector error correction model (VEC) Granger causality test for directional cause and effect between exogenous and endogenous variables. The VEC model shows a bidirectional relationship between CO2 emissions and lockdown and a unidirectional relationship with newly confirmed cases and deaths for the UK. The results of Spain confirmed the unidirectional relationship of CO2 emissions, lockdown, new confirmed cases, and deaths. The Granger causality test reconfirms the relationship of variables except for newly confirmed deaths for the UK and newly confirmed cases for Spain. Conclusively, the pandemic breakout reduced the emission of CO2. The directional relation of variables supported the short-run relationship of CO2 emissions with newly confirmed cases and deaths, while a long- and short-run relationship was shown with lockdown. The directional and relational behavior of lockdown potentially linked the CO2 emissions with daily life activities. [ABSTRACT FROM AUTHOR]

Climate change and farmland environmental pollution have put greater pressure on the sustainability of agricultural production. Based on the provincial panel data of mainland China from 1978 to 2018, climate variables such as precipitation, temperature, and sunshine hours are included into the input indicators, and agricultural non-point source pollution and carbon emissions are taken as undesirable outputs, the agricultural production efficiency (APE) under the dual constraints of climate change and the resource environment was estimated by the super slacks-based measure (SBM)-undesirable model. On the basis of the trajectory of the imbalanced spatiotemporal evolution of APE shown by Kernel density estimation and the standard deviational ellipse (SDE)–center of gravity (COG) transfer model, the spatial convergence model was used to test the convergence and differentiation characteristics of APE. Under the dual constraints, APE presents a "bimodal" distribution with a stable increase in fluctuation, but it is still at a generally low level and does not show polarization, among which the APE in the northeast region is the highest. The COG of APE tends to transfer towards the northeast, and the coverage of the SDE is shrinking, so the overall spatial pattern is characterized by a tendency of clustering towards the north in the north-south direction and a tendency of imbalance in the east-west direction. APE has significant spatial convergence, and there is a trend of "latecomer catching-up" in low-efficiency regions. The introduction of spatial correlation accelerates the convergence rate and shortens the convergence period. The convergence rate is the highest in the central and western regions, followed by that in the northeastern region, and the convergence rate is the lowest in the eastern region. In addition, the convergence rate in different time periods has a phase change. The process of improving the quality and efficiency of agricultural production requires enhancing the adaptability of climate change, balancing the carrying capacity of the resource environment, and strengthening inter-regional cooperation and linkage in the field of agriculture. [ABSTRACT FROM AUTHOR]