scholarly journals Climate Change and Human Health Impacts in the United States: An Update on the Results of the U.S. National Assessment

2006 ◽  
Vol 114 (9) ◽  
pp. 1318-1324 ◽  
Author(s):  
Kristie L. Ebi ◽  
David M. Mills ◽  
Joel B. Smith ◽  
Anne Grambsch
Keyword(s):  
Climate Change ◽  
United States ◽  
Human Health ◽  
The United States ◽  
Health Impacts ◽  
National Assessment ◽  
Human Health Impacts ◽  
The U.S

scholarly journals Air quality and human health impacts of grasslands and shrublands in the United States

2018 ◽  
Vol 182 ◽  
pp. 193-199 ◽  
Author(s):  
Varsha Gopalakrishnan ◽  
Satoshi Hirabayashi ◽  
Guy Ziv ◽  
Bhavik R. Bakshi
Keyword(s):  
United States ◽  
Air Quality ◽  
Human Health ◽  
The United States ◽  
Health Impacts ◽  
Human Health Impacts

scholarly journals Magnitude, Trends, and Impacts of Ambient Long-Term Ozone Exposure in the United States from 2000–2015

2019 ◽  
Author(s):  
Karl M. Seltzer ◽  
Drew T. Shindell ◽  
Prasad Kasibhatla ◽  
Christopher S. Malley
Keyword(s):  
United States ◽  
Human Health ◽  
Crop Yields ◽  
Relative Yield ◽  
The United States ◽  
Average Concentration ◽  
Ozone Exposure ◽  
Health Impacts ◽  
Human Health Impacts

Abstract. Long-term exposure to ambient ozone (O3) is associated with a variety of impacts, including adverse human-health effects and reduced yields in commercial crops. Ground-level O3 concentrations for assessments are typically predicted using chemical transport models, however such methods often feature biases that can influence impact estimates. Here, we develop and apply artificial neural networks to empirically model long-term O3 exposure over the continental United States from 2000–2015, and generate a measurement-based assessment of impacts on human-health and crop yields. Notably, we find that two commonly-used human-health averaging metrics, based on separate epidemiological studies, differ in their trends over the study period. The population-weighted, April–September average of the daily 1-hour maximum concentration peaked in 2002 at 55.9 ppb and decreased by −0.43 [95 % CI: −0.28, −0.57] ppb/yr between 2000–2015, yielding a ~ 18 % decrease in normalized human-health impacts. In contrast, there was little change in the population-weighted, annual average of the maximum daily 8-hour average concentration between 2000–2015, which resulted in a ~ 5 % increase in normalized human-health impacts. In both cases, an aging population structure played a substantial role in modulating these trends. By contrast, all agriculture-weighted crop-loss metrics featured decreasing trends, leading to reductions in the estimated national relative yield loss ranging from 1.7–1.9 % for maize, 5.1–7.1 % for soybeans, and 2.7 % for wheat. Overall, these results provide a measurement-based estimate of long-term O3 exposure over the United States, quantify the historical magnitude, trends, and impacts of such exposure, and illustrate how different conclusions regarding historical impacts can be made through the use of varying metrics.

scholarly journals Magnitude, trends, and impacts of ambient long-term ozone exposure in the United States from 2000 to 2015

2020 ◽  
Vol 20 (3) ◽  
pp. 1757-1775 ◽  
Author(s):  
Karl M. Seltzer ◽  
Drew T. Shindell ◽  
Prasad Kasibhatla ◽  
Christopher S. Malley
Keyword(s):  
United States ◽  
Human Health ◽  
Crop Yields ◽  
Relative Yield ◽  
The United States ◽  
Average Concentration ◽  
Ozone Exposure ◽  
Health Impacts ◽  
Human Health Impacts

Abstract. Long-term exposure to ambient ozone (O3) is associated with a variety of impacts, including adverse human-health effects and reduced yields in commercial crops. Ground-level O3 concentrations for assessments are typically predicted using chemical transport models; however such methods often feature biases that can influence impact estimates. Here, we develop and apply artificial neural networks to empirically model long-term O3 exposure over the continental United States from 2000 to 2015, and we generate a measurement-based assessment of impacts on human-health and crop yields. Notably, we found that two commonly used human-health averaging metrics, based on separate epidemiological studies, differ in their trends over the study period. The population-weighted, April–September average of the daily 1 h maximum concentration peaked in 2002 at 55.9 ppb and decreased by 0.43 [95 % CI: 0.28, 0.57] ppb yr−1 between 2000 and 2015, yielding an ∼18 % decrease in normalized human-health impacts. In contrast, there was little change in the population-weighted, annual average of the maximum daily 8 h average concentration between 2000 and 2015, which resulted in a ∼5 % increase in normalized human-health impacts. In both cases, an aging population structure played a substantial role in modulating these trends. Trends of all agriculture-weighted crop-loss metrics indicated yield improvements, with reductions in the estimated national relative yield loss ranging from 1.7 % to 1.9 % for maize, 5.1 % to 7.1 % for soybeans, and 2.7 % for wheat. Overall, these results provide a measurement-based estimate of long-term O3 exposure over the United States, quantify the historical trends of such exposure, and illustrate how different conclusions regarding historical impacts can be made through the use of varying metrics.

Nutrients Pollution in Water Bodies

2017 ◽  
pp. 21-42
Author(s):  
Ángeles Val del Río ◽  
Paula Carrera Fernández ◽  
José Luis Campos Gómez ◽  
Anuska Mosquera-Corral
Keyword(s):  
Climate Change ◽  
United States ◽  
Human Health ◽  
The United States ◽  
Water Bodies ◽  
Nitrogen And Phosphorus ◽  
International Conventions ◽  
Laws And Regulations

The pollution of water bodies by an excess of nutrients (N and P) is a worldwide problem with effects on the human health, ecosystems status, climate change, etc. To face with this important issue different regulations were promulgated by the countries, sometimes based on the results from international conventions and programmes. In this chapter, a review of the laws and regulations that affect the discharge of nitrogen and phosphorus is addressed, focused in the case of Europe and the United States. Finally, a brief explanation about international initiatives was performed to understand the global framework concerning nutrients pollution.

scholarly journals Catastrophic Health Impacts of Spiraling Climate Change: How Certain Can We Be About Their Magnitudes?

2020 ◽  
Vol 8 ◽  
Author(s):  
Zaid Chalabi ◽  
Anna M. Foss
Keyword(s):  
Climate Change ◽  
Human Health ◽  
Climate Model ◽  
Environmental Exposures ◽  
Building Blocks ◽  
Health Impacts ◽  
Model Parameters ◽  
Policy Makers ◽  
Total Uncertainty ◽  
Human Health Impacts

Recently, there has been a strong interest in the climate emergency and the human health impacts of climate change. Although estimates have been quoted, the modeling methods used have either been simplistic or opaque, making it difficult for policy makers to have confidence in these estimates. Providing central estimates of health impacts, without any quantification of their uncertainty, is deficient because such an approach does not acknowledge the inherent uncertainty in extreme environmental exposures associated with spiraling climate change and related health impacts. Furthermore, presenting only the uncertainty bounds around central estimates, without information on how the uncertainty in each of the model parameters and assumptions contribute to the total uncertainty, is insufficient because this approach hides those parameters and assumptions which contribute most to the total uncertainty. We propose a framework for calculating the catastrophic human health impacts of spiraling climate change and the associated uncertainties. Our framework comprises three building blocks: (A) a climate model to simulate the environmental exposure extremes of spiraling climate change; (B) a health impact model which estimates the health burdens of the extremes of environmental exposures; and (C) an analytical mathematical method which characterizes the uncertainty in (A) and (B), propagates the uncertainty in-between and through these models, and attributes the proportion of uncertainty in the health outcomes to model assumptions and parameter values. Once applied, our framework can be of significant value to policy makers because it handles uncertainty transparently while taking into account the complex interactions between climate and human health.

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