Dynamic Trends of Carbon Intensities among 127 Countries

Chang, Yu Sang; Choi, Dong Gyu; Kim, Hann Earl

doi:10.3390/su9122268

Cited by 5 publications

(4 citation statements)

References 33 publications

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“…Using the slacks-based measure (SBM) approach, Wang et al (2017a) found a lower performance in Asia than in Europe and the Americas, yet the Asian countries had the greatest potential in performance improvement. Chang et al (2017) studied dynamic trends of carbon intensity of 127 countries from 1980-2011. Their findings indicated a decreasing trend of carbon intensity in general, yet the decreasing rates for individual countries were divergent to a great extent and most middle-and low-income economies experienced a growing trend of CIs.…”

Section: Cross-country Comparison Of Carbon Emission Performancementioning

confidence: 99%

Measuring wellbeing performance of carbon emissions using hybrid measure and meta-frontier techniques: Empirical tests for G20 countries and implications for China

Wang

Shao

Nathwani

et al. 2019

Journal of Cleaner Production

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Section: Cross-country Comparison Of Carbon Emission Performancementioning

confidence: 99%

Measuring wellbeing performance of carbon emissions using hybrid measure and meta-frontier techniques: Empirical tests for G20 countries and implications for China

Wang

Shao

Nathwani

et al. 2019

Journal of Cleaner Production

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“…Another type of EC-known as kinked EC-can detect whether a statistically-significant shift in a slope may have occurred during the sample period. For example, in a recent study on the dynamic slopes of carbon intensities [47], a majority of 73 out of 127 countries displayed kinked slopes during the 1980-2012 period. In these two EC models, the dependent variable is PME measured in µg/m 3 per person for a given country that can be viewed as the unit penalty or unit cost derived from PM 2.5 concentration experienced per person.…”

Section: Methodsmentioning

confidence: 99%

“…More recently, EC has been used to project CO 2 emissions until 2040 for seven major emitting countries and three regions of the world [46]. Further, EC has been used to estimate the dynamic trends of CIs for 127 countries [47]. As for the application of EC in energy technologies, a review article by Weiss et al [48] presented the PR for 75 energy demand technologies with an average PR of 82%.…”

Section: Experience Curve Applications In Energy and Air Pollutionmentioning

confidence: 99%

Dynamic Trends of Fine Particulate Matter Exposure across 190 Countries: Analysis and Key Insights

2020

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Despite the fact that fine particulate matter (PM2.5) causes serious health issues, few studies have investigated the level and annual rate of PM2.5 change across a large number of countries. For a better understanding of the global trend of PM2.5, this study classified 190 countries into groups showing different trends of PM2.5 change during the 2000–2014 period by estimating the progress ratio (PR) from the experience curve (EC), with PM2.5 exposure (PME)–the population-weighted average annual concentration of PM2.5 to which a person is exposed—as the dependent variable and the cumulative energy consumption as the independent variable. The results showed a wide variation of PRs across countries: While the average PR for 190 countries was 96.5%, indicating only a moderate decreasing PME trend of 3.5% for each doubling of the cumulative energy consumption, a majority of 118 countries experienced a decreasing trend of PME with an average PR of 88.1%, and the remaining 72 countries displayed an increasing trend with an average PR of 110.4%. When two different types of EC, classical and kinked, were applied, the chances of possible improvement in the future PME could be suggested in the descending order as follows: (1) the 60 countries with an increasing classical slope; (2) the 12 countries with an increasing kinked slope; (3) the 75 countries with a decreasing classical slope; and (4) the 43 countries with a decreasing kinked slope. The reason is that both increasing classical and kinked slopes are more likely to be replaced by decreasing kinked slopes, while decreasing classical and kinked slopes are less likely to change in the future. Population size seems to play a role: A majority of 52%, or 38 out of the 72 countries with an increasing slope, had a population size of bigger than 10 million inhabitants. Many of these countries came from SSA, EAP, and LAC regions. By identifying different patterns of past trends based on the analysis of PME for individual countries, this study suggests a possible change of the future slope for different groups of countries.

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“…Thus, numerous mitigation strategies have been proposed to mitigate GHG emissions. A total of 127 countries have already announced their carbon emission reduction timetables [3]. As the largest emitter, China has set its goals for carbon peak and carbon neutralization by 2030 and 2060, respectively.…”

Section: Introductionmentioning

confidence: 99%

Mapping Grassland Based on Bio-Climate Probability and Intra-Annual Time-Series Abundance Data of Vegetation Habitats

Sun,

Ji,

Jiao

et al. 2023

Remote Sensing

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Accurate inventories of grasslands are important for studies of greenhouse gas (GHG) dynamics, as grasslands store about one-third of the global terrestrial carbon stocks. This paper develops a framework for large-area grassland mapping based on the probability of grassland occurrence and the interactive pathways of fractional vegetation and soil-related endmember nexuses. In this study, grassland occurrence probability maps were produced based on data on bio-climate factors obtained from MODIS/Terra Land Surface Temperature (MOD11A2), MODIS/Terra Vegetation Indices (MOD13A3), and Tropical Rainfall Measuring Mission (TRMM 3B43) using the random forests (RF) method. Time series of 8-day fractional vegetation-related endmembers (green vegetation, non-photosynthetic vegetation, sand land, saline land, and dark surfaces) were generated using linear spectral mixture analysis (LSMA) based on MODIS/Terra Surface Reflectance data (MOD09A1). Time-series endmember fraction maps and grassland occurrence probabilities were employed to map grassland distribution using an RF model. This approach improved the accuracy by 5% compared to using endmember fractions alone. Additionally, based on the grassland occurrence probability maps, we identified extensive ecologically sensitive regions, encompassing 1.54 (104 km2) of desert-to-steppe (D-S) and 2.34 (104 km2) of steppe-to-meadow (S-M) transition regions. Among these, the D-S area is located near the threshold of 310 mm/yr in precipitation, an annual temperature of 10.16 °C, and a surface comprehensive drought index (TVPDI) of 0.59. The S-M area is situated close to the line of 437 mm/yr in precipitation, an annual temperature of 5.49 °C, and a TVPDI of 0.83.

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Dynamic Trends of Carbon Intensities among 127 Countries

Cited by 5 publications

References 33 publications

Measuring wellbeing performance of carbon emissions using hybrid measure and meta-frontier techniques: Empirical tests for G20 countries and implications for China

Measuring wellbeing performance of carbon emissions using hybrid measure and meta-frontier techniques: Empirical tests for G20 countries and implications for China

Dynamic Trends of Fine Particulate Matter Exposure across 190 Countries: Analysis and Key Insights

Mapping Grassland Based on Bio-Climate Probability and Intra-Annual Time-Series Abundance Data of Vegetation Habitats

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