Dataset Information

Disproportionality in Power Plants' Carbon Emissions: A Cross-National Study.

ABSTRACT: Past research on the disproportionality of pollution suggests a small subset of a sector's facilities often produces the lion's share of toxic emissions. Here we extend this idea to the world's electricity sectors by calculating national-level disproportionality Gini coefficients for plant-level carbon emissions in 161 nations based on data from 19,941 fossil-fuel burning power plants. We also evaluate if disproportionalities in plant-level emissions are associated with increased national carbon emissions from fossil-fuel based electricity production, while accounting for other well-established human drivers of greenhouse gas emissions. Results suggest that one potential pathway to decreasing nations' greenhouse gas emissions could involve reducing disproportionality among fossil-fuel power plants by targeting those plants in the upper end of the distribution that burn fuels more inefficiently to produce electricity.

SUBMITTER: Jorgenson A

PROVIDER: S-EPMC4929454 | biostudies-literature | 2016 Jul

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Disproportionality in Power Plants' Carbon Emissions: A Cross-National Study.

Jorgenson Andrew A Longhofer Wesley W Grant Don D

Scientific reports 20160701

Past research on the disproportionality of pollution suggests a small subset of a sector's facilities often produces the lion's share of toxic emissions. Here we extend this idea to the world's electricity sectors by calculating national-level disproportionality Gini coefficients for plant-level carbon emissions in 161 nations based on data from 19,941 fossil-fuel burning power plants. We also evaluate if disproportionalities in plant-level emissions are associated with increased national carbon ...[more]

PMID: 27363677

Similar Datasets

Project description:Background:Compared to 10 years ago, the ambient particulate matter 10 (PM10) and carbon monoxide (CO) levels in South Korea have decreased. However, compared to many other OECD countries, these levels are still too high. Concentration of air pollutants such as PM10 is especially higher during winter than during summer. The first step to rationally solving the air pollution problem in Korea is to identify the key air pollution sources during each season. This ecological study was performed to assess the association between the number of days the accepted PM10 and CO thresholds were exceeded and the concentration of potential emission sources in winter season 2015. Methods:An emission inventory of the PM10 and CO emissions in the 232 administrative South Korean districts in January, 2015, and February, 2015 and December, 2015, and the population density, number of car registrations, number of car accidents, industrial power usage, and presence of a fossil-fuel power plant in each district was established on the basis of official web-page data from the government. For all emission source variables except power plants, the administrative districts were grouped into quartiles. Districts were also divided according to whether a power plant was present or not. Negative binomial regression was performed to assess the associations between the PM10 and CO air pollution (defined as ?100 g/m3 and???9 ppm, respectively) and the concentration of each emission source. Results:Compared to the districts with the lowest population density, the districts with the third highest population density associated most strongly with air pollution. This was also observed for industrial power usage. Car accident number and car registration numbers showed a linear relationship with air pollution. Districts with power plants were significantly more likely to have air pollution than districts that lacked a plant. Conclusions:Greater car numbers, industrial activity, and population density, and the presence of fossil-fuel plants associated with air pollution in the 2015 winter in South Korea. These data highlight the contaminant sources that could be targeted by interventions that aim to reduce air pollution, decrease the incidence of exposure, and limit the impact of pollution on human health.

Project description:BackgroundMotorised travel and associated carbon dioxide (CO?) emissions generate substantial health costs; in the case of motorised travel, this may include contributing to rising obesity levels. Obesity has in turn been hypothesised to increase motorised travel and/or CO? emissions, both because heavier people may use motorised travel more and because heavier people may choose larger and less fuel-efficient cars. These hypothesised associations have not been examined empirically, however, nor has previous research examined associations with other health characteristics. Our aim was therefore to examine how and why weight status, health, and physical activity are associated with transport CO? emissions.Methods3463 adults completed questionnaires in the baseline iConnect survey at three study sites in the UK, reporting their health, weight, height and past-week physical activity. Seven-day recall instruments were used to assess travel behaviour and, together with data on car characteristics, were used to estimate CO2 emissions. We used path analysis to examine the extent to which active travel, motorised travel and car engine size explained associations between health characteristics and CO? emissions.ResultsCO? emissions were higher in overweight or obese participants (multivariable standardized probit coefficients 0.16, 95% CI 0.08 to 0.25 for overweight vs. normal weight; 0.16, 95% CI 0.04 to 0.28 for obese vs. normal weight). Lower active travel and, particularly for obesity, larger car engine size explained 19-31% of this effect, but most of the effect was directly explained by greater distance travelled by motor vehicles. Walking for recreation and leisure-time physical activity were associated with higher motorised travel distance and therefore higher CO? emissions, while active travel was associated with lower CO? emissions. Poor health and illness were not independently associated with CO? emissions.ConclusionsEstablishing the direction of causality between weight status and travel behaviour requires longitudinal data, but the association with engine size suggests that there may be at least some causal effect of obesity on CO? emissions. More generally, transport CO? emissions are associated in different ways with different health-related characteristics. These include associations between health goods and environmental harms (recreational physical activity and high emissions), indicating that environment-health 'co-benefits' cannot be assumed. Instead, attention should also be paid to identifying and mitigating potential areas of tension, for example by promoting low-carbon recreational physical activity.

Dataset Information

Disproportionality in Power Plants' Carbon Emissions: A Cross-National Study.

Publications

Disproportionality in Power Plants' Carbon Emissions: A Cross-National Study.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure