Modelling study of soil C, N and pH response to air pollution and climate change using European LTER site observations

A Modelling Study on PM2.5-Related Health Impacts from Climate Change and Air Pollution Emission Control — China, 2010s and 2040s

China CDC Weekly ◽

10.46234/ccdcw2021.128 ◽

2021 ◽

Vol 3 (23) ◽

pp. 500-506

Author(s):

Jing Huang ◽

◽

Heng Tian ◽

Jiawei Wang ◽

Teng Yang ◽

...

Keyword(s):

Climate Change ◽

Air Pollution ◽

Emission Control ◽

Health Impacts ◽

Pollution Emission ◽

Modelling Study

Download Full-text

CO2 emission and air pollution (volatile organic compounds, etc.)–related problems causing climate change

Current Trends and Future Developments on (Bio-) Membranes ◽

10.1016/b978-0-12-816778-6.00001-1 ◽

2020 ◽

pp. 1-30

Author(s):

Ali Sadatshojaie ◽

Mohammad Reza Rahimpour

Keyword(s):

Climate Change ◽

Air Pollution ◽

Volatile Organic Compounds ◽

Organic Compounds ◽

Co2 Emission ◽

Volatile Organic

Download Full-text

The Benefit of Focusing on Air Pollution Instead of Climate Change: How Discussing Power Plant Emissions in the Context of Air Pollution, Rather than Climate Change, Influences Perceived Benefits, Costs, and Political Action for Policies to Limit Emissions

Science Communication ◽

10.1177/1075547020980443 ◽

2020 ◽

pp. 107554702098044

Author(s):

P. Sol Hart ◽

Lauren Feldman

Keyword(s):

Climate Change ◽

Air Pollution ◽

Power Plant ◽

Environmental Impacts ◽

Political Ideology ◽

Political Action ◽

Perceived Benefits ◽

Power Plant Emissions ◽

Plant Emissions ◽

Benefits And Costs

This experiment examines how framing power plant emissions in terms of air pollution or climate change, and in terms of health or environmental impacts, influences perceived benefits and costs of policies to reduce emissions and intentions to take political action that supports such policies. A moderated-mediation model reveals that focusing on air pollution, instead of climate change, has a positive significant indirect influence on intended political action through the serial mediators of perceived benefits and costs. Political ideology moderates the association between perceived benefits and political action. No framing effects are observed in the comparison between health and environmental impacts.

Download Full-text

Abstract 36: Mapping and Multilevel Modeling of Climate Change and Air Pollution With Risk of Stroke in the United States and China: Findings From the Drexel-SARI Low Carbon and Healthy City Study

Stroke ◽

10.1161/str.47.suppl_1.36 ◽

2016 ◽

Vol 47 (suppl_1) ◽

Author(s):

Longjian Liu ◽

Hui Liu ◽

Xuan Yang ◽

Feng Jia ◽

Mingquan Wang

Keyword(s):

Climate Change ◽

Air Pollution ◽

Air Quality ◽

Pollution Index ◽

The United States ◽

Potential Interaction ◽

Low Carbon ◽

Multilevel Regression ◽

Healthy City ◽

Nationally Representative

Introduction and Hypothesis: Stroke is a leading cause of death and the major cause of disability in the world. However, few studies applied multilevel regression techniques to explore the association of stroke risk with climate change and air pollution. In the study, we aimed to test the hypothesis that the disproportionately distributed stroke rates across the counties and cities within a country are significantly associated with air pollution and temperature. Methods: We used data from U.S. 1118 counties in 49 states, which had estimated measures of particulate matter (PM)2.5 for the years 2010-2013, and data from China 120 cities in 32 provinces (including 4 municipalities), which had measures of Air Pollution Index (API) for the years 2012-2013. We assessed the association between air quality and prevalence of stroke using spatial mapping, autocorrelation and multilevel regression models. Results: Findings from the U.S. show that the highest average PM2.5 level was in July (10.2 μg/m3) and the lowest in October (7.63 μg/m3) for the years 2010-2013. Annual average PM2.5 levels were significantly different across the 1118 counties, and were significantly associated with stroke rates. Multilevel regression analysis indicated that the prevalence of stroke significantly increased by 1.19% for every 10 μg/m3 increase of PM2.5 (p<0.001). Significant variability in PM2.5 by states was observed (p=0.019). More than 70% of the variation in stroke rates existed across the counties (p=0.017) and 18.7% existed across the states (p=0.047). In China, the highest API was observed in the month of December, with a result of 75.76 in 2012 and 97.51 in 2013. The lowest API was observed in July, with a result of 51.21 in 2012, and 54.23 in 2013. Prevalence of stroke was significantly higher in cities with higher API concentrations. The associations between air quality and risk of stroke were significantly mediated by temperatures. Conclusions: The study, using nationally representative data, is one of the first studies to address a positive and complex association between air quality and prevalence of stroke, and a potential interaction effect of temperatures on the air - stroke association.

Download Full-text

Climate Change and Air Pollution: Translating Their Interplay into Present and Future Mortality Risk for Rome and Milan Municipalities

SSRN Electronic Journal ◽

10.2139/ssrn.3977590 ◽

2021 ◽

Author(s):

Melania Michetti ◽

Maurizio Gualtieri ◽

Alessandro Anav ◽

Mario Adani ◽

Barbara Benassi ◽

...

Keyword(s):

Climate Change ◽

Air Pollution ◽

Mortality Risk

Download Full-text

Effects of climate change on soil organic matter chemical composition and carbon content in different physical fractions

10.5194/egusphere-egu21-9216 ◽

2021 ◽

Author(s):

Moritz Mohrlok ◽

Victoria Martin ◽

Alberto Canarini ◽

Wolfgang Wanek ◽

Michael Bahn ◽

...

Keyword(s):

Climate Change ◽

Organic Matter ◽

Chemical Composition ◽

Soil Organic Matter ◽

Soil C ◽

Size Classes ◽

Soil Fractions ◽

Total Soil ◽

C And N ◽

Amp Clay

Soil organic matter (SOM) is composed of many pools with different properties (e.g. turnover times) which are generally used in biogeochemical models to predict carbon (C) dynamics. Physical fractionation methods are applied to isolate soil fractions that correspond to these pools. This allows the characterisation of chemical composition and C content of these fractions. There is still a lack of knowledge on how these individual fractions are affected by different climate change drivers, and therefore the fate of SOM remains elusive. We sampled soils from a multifactorial climate change experiment in a managed grassland in Austria four years after starting the experiment to investigate the response of SOM in physical soil fractions to temperature (eT: ambient and elevated by +3&#176;C), atmospheric CO2-concentration (eCO2: ambient and elevated by +300 ppm) and to a future climate treatment (eT x eCO2: +3&#176;C and + 300 ppm). A combination of slaking and wet sieving was used to obtain three size classes: macro-aggregates (maA, > 250 &#181;m), micro-aggregates (miA, 63 &#181;m &#8211; 250 &#181;m) and free silt & clay (sc, < 63 &#181;m). In both maA and miA, four different physical OM fractions were then isolated by density fractionation (using sodium polytungstate of &#961; = 1.6 g*cm-3, ultrasonication and sieving): Free POM (fPOM), intra-aggregate POM (iPOM), silt & clay associated OM (SCaOM) and sand-associated OM (SaOM). We measured C and N contents and isotopic composition by EA-IRMS in all fractions and size classes and used a Pyrolysis-GC/MS approach to assess their chemical composition. For eCO2 and eT x eCO2 plots, an isotope mixing-model was used to calculate the proportion of recent C derived from the elevated CO2 treatment. Total soil C and N did not significantly change with treatments.&#160; eCO2 decreased the relative proportion of maA-mineral-associated C and increased C in fPOM and iPOM. About 20% of bulk soil C was represented by the recent C derived from the CO2 fumigation treatment. This significantly differed between size classes and density fractions (p < 0.001), which indicates inherent differences in OM age and turnover. Warming reduced the amount of new C incorporated into size classes. We found that each size class and fraction possessed a unique chemical fingerprint, but this was not significantly changed by the treatments. Overall, our results show that while climate change effects on total soil C were not significant after 4 years, soil fractions showed specific effects. Chemical composition differed significantly between size classes and fractions but was unaffected by simulated climate change. This highlights the importance to separate SOM into differing pools, while including changes to the molecular composition might not be necessary for improving model predictions.&#160;&#160;&#160;&#160;

Download Full-text