The Impact of Migration on Air Quality Dose-Response Functions: A Case Study of Jacksonville, Florida

Based on a case study in Rennes, the article presents how a group of urban public actors re-uses methods and technology from citizen sciences to raise the urban air quality issue in the public debate. The project gives a group of inhabitants the opportunity to follow air quality training and proceed PM2.5µm measurements. The authors question the impact of the ongoing hybridisation between citizen science and urban public action on participants' commitment. The authors present how the use of PM2.5-sensors during 11 weeks led to a disengagement phenomenon, even if the authors observe a strong participation to workshops. These results come from an interdisciplinary methodology using observations, interviews, and data analyses.

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Assessment of the Impact of CO, NOx and PM10 on Air Quality during Road Construction and Operation Phases

Sustainability ◽

10.3390/su122410549 ◽

2020 ◽

Vol 12 (24) ◽

pp. 10549

Author(s):

Marinella Giunta

Keyword(s):

Air Quality ◽

Comprehensive Evaluation ◽

Dispersion Model ◽

Road Construction ◽

Air Emissions ◽

Unpaved Road ◽

The Road ◽

The Impact ◽

Co Concentrations

The road sector is one of the main sources of air emissions in the atmosphere during both construction and operation. The objective of the present paper is a comprehensive evaluation of the impact on air quality during the two main phases of life cycle of roads. In this case study of a motorway project, the emissions of the primary pollutants, CO, NOx, and PM10 are estimated, and the results showed that (i) CO and NOx pollutants released during both phases are comparable, while the emissions of PM10 are more significant in the construction phase; (ii) 85% of PM10 in construction is due to storage, transit on unpaved road, and crushing; (iii) the portals of the tunnel are the sites where there are higher concentrations of pollutants in operation; and (iv) the CO concentrations estimated by the dispersion model are strongly influenced by the topography.

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Approaches for Health Effect Characterization in Risk-Benefit Assessment of Foods: A Comparative Case Study

Frontiers in Nutrition ◽

10.3389/fnut.2021.607929 ◽

2021 ◽

Vol 8 ◽

Author(s):

Sofie Theresa Thomsen ◽

Maarten Nauta ◽

Lea Sletting Jakobsen ◽

Marianne Uhre Jakobsen ◽

Heddie Mejborn ◽

...

Keyword(s):

Dose Response ◽

Health Effect ◽

Brown Rice ◽

Health Impact ◽

Benefit Assessment ◽

Comparative Case Study ◽

Food Component ◽

Risk Benefit Assessment ◽

The Impact

One of the challenges in quantitative risk-benefit assessment (RBA) of foods is the choice of approach for health effect characterization to estimate the health impact of dietary changes. The purpose of health effect characterization is to describe an association between intake of a food or food component and a health effect in terms of a dose-response relationship. We assessed the impact of the choice of approach for health effect characterization in RBA in two case studies based on substitution of (i) white rice by brown rice and (ii) unprocessed red meat by vegetables. We explored this by comparing the dose-response relations linking a health effect with (i) a food component present in the food, (ii) a food based on non-specified substitution analyses, and (iii) a food based on specified substitution analyses. We found that the choice of approach for health effect characterization in RBA may largely impact the results of the health impact estimates. Conducting the calculations only for a food component may neglect potential effects of the food matrix and of the whole food on the diet-disease association. Furthermore, calculations based on associations for non-specified substitutions include underlying food substitutions without specifying these. Data on relevant specified substitutions, which could reduce this type of bias, are unfortunately rarely available. Assumptions and limitations of the health effect characterization approaches taken in RBA should be documented and discussed, and scenario analysis is encouraged when multiple options are available.

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Air Quality Planning and the Minimization of Negative Externalities

Resources ◽

10.3390/resources8010015 ◽

2019 ◽

Vol 8 (1) ◽

pp. 15 ◽

Cited By ~ 2

Author(s):

Marco Ravina ◽

Deborah Panepinto ◽

Mariachiara Zanetti

Keyword(s):

Air Quality ◽

Urban Areas ◽

District Heating ◽

Heating System ◽

Negative Externalities ◽

District Heating System ◽

Quality Planning ◽

Air Quality Planning ◽

The Impact

The minimization of negative externalities is a key aspect in the development of a circular and sustainable economic model. At the local scale, especially in urban areas, externalities are generated by the adverse impacts of air pollution on human health. Local air quality policies and plans often lack of considerations and instruments for the quantification and evaluation of external health costs. Support for decision-makers is needed, in particular during the implementation stage of air quality plans. Modelling tools based on the impact pathway approach can provide such support. In this paper, the implementation of health impacts and externalities analysis in air quality planning is evaluated. The state of the art in European member states is reported, considering whether and how health effects have been included in the planning schemes. The air quality plan of the Piemonte region in Italy is then considered. A case study is analyzed to evaluate a plan action, i.e., the development of the district heating system in the city of Turin. The DIATI (Dipartimento di Ingegneria dell’Ambiente, del Territorio e delle Infrastrutture) Dispersion and Externalities Model (DIDEM model) is applied to detect the scenario with the highest external cost reduction. This methodology results are extensible and adaptable to other actions and measures, as well as other local policies in Europe. The use of health externalities should be encouraged and integrated into the present methodology supporting air quality planning. Efforts should be addressed to quantify and minimize the overall uncertainty of the process.

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Nottingham Express Transit

The International Journal of Entrepreneurship and Innovation ◽

10.1177/1465750317750323 ◽

2018 ◽

Vol 19 (1) ◽

pp. 56-68 ◽

Cited By ~ 2

Author(s):

John Disney ◽

Will Rossiter ◽

David J Smith

Keyword(s):

United Kingdom ◽

Air Quality ◽

Carbon Emissions ◽

Traffic Congestion ◽

New Technologies ◽

Detailed Examination ◽

Light Rail ◽

The United Kingdom ◽

The Impact

Traffic congestion at peak times has long been a problem facing cities in the United Kingdom.1 Latterly concern about combating congestion has been hightened by worries over carbon emissions and poor air quality. In tackling these problems, green innovations incorporating new technologies appear to have much to offer, although progress in implementing these sorts of innovation appears to have been slow. This case study analyses the efforts of one city to tackle these problems by pioneering a number of green innovations including the introduction of a light rail system employing trams known as Nottingham Express Transit as well as electric and gas-powered buses. The nature of these innovations is explored together with a detailed examination of how they came to be implemented and the impact they have had.

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Economic and environmental benefits of 3-wheeler electric vehicles during covid-19: A case study of Rajshahi, Bangladesh

Sukatha procedia ◽

10.32438/sa.120.3008 ◽

2021 ◽

pp. 38-44

Author(s):

Md. Raquibul Hasan

Keyword(s):

Air Quality ◽

Labour Market ◽

Electric Vehicles ◽

Vital Role ◽

Google Earth ◽

Environmental Benefits ◽

Industrial Emissions ◽

Market Impacts ◽

The Impact

This paper provides an insight into the labour market impacts of the COVID-19 crisis in Bangladesh, focusing on Rajshahi City Corporation. A survey was built to collect data about job switching nature before and during the crisis to shed light on the implications of COVID-19 on employment and earnings. The findings presented here indicate substantial labour market impacts both at the extensive and intensive margin, mainly due to the nature of the crisis's occupations. And the sufferers switch their jobs to 3-wheeler EVs industry as a driver or mechanic. Bus helper job was the most susceptible job during the pandemic, followed by garments. Due to the countrywide lockdown, emissions from vehicles were restricted, it was found that the air quality has been improved throughout the country during the lockdown. And 3-wheeler electric vehicles play a vital role to ease this issue. The study also assesses the impact of lockdown measures on air quality in Rajshahi. Four different air pollutants data from the google earth engine (NO2, SO2, CO, and O3) were analyzed. The study evaluated that the lockdown measures significantly reduced air pollution because of reduced vehicular and industrial emissions in Bangladesh.

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Establishment of Regional Concentration–Duration–Frequency Relationships of Air Pollution: A Case Study for PM2.5

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph17041419 ◽

2020 ◽

Vol 17 (4) ◽

pp. 1419 ◽

Cited By ~ 1

Author(s):

Hone-Jay Chu ◽

Muhammad Zeeshan Ali

Keyword(s):

Air Pollution ◽

Air Quality ◽

Spatial Pattern ◽

Frequency Of Occurrence ◽

Efficient Design ◽

Annual Frequency ◽

And Control ◽

Relationship Of ◽

The Impact

Poor air quality usually leads to PM2.5 warnings and affects human health. The impact of frequency and duration of extreme air quality has received considerable attention. The extreme concentration of air pollution is related to its duration and annual frequency of occurrence known as concentration–duration–frequency (CDF) relationships. However, the CDF formulas are empirical equations representing the relationship between the maximum concentration as a dependent variable and other parameters of interest, i.e., duration and annual frequency of occurrence. As a basis for deducing the extreme CDF relationship of PM2.5, the function assumes that the extreme concentration is related to the duration and frequency. In addition, the spatial pattern estimation of extreme PM2.5 is identified. The regional CDF identifies the regional extreme concentration with a specified duration and return period. The spatial pattern of extreme air pollution over 8 h duration shows the hotspots of air quality in the central and southwestern areas. Central and southwestern Taiwan is at high risk of exposure to air pollution. Use of the regional CDF analysis is highly recommended for efficient design of air quality management and control.

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Implementing a Framework to Evaluate the Impact of Food Intake Shifts on Risk of Illness Using a Case Study with Infant Cereal (P11-118-19)

Current Developments in Nutrition ◽

10.1093/cdn/nzz048.p11-118-19 ◽

2019 ◽

Vol 3 (Supplement_1) ◽

Author(s):

Sofia Santillana Farakos ◽

Regis Pouillot ◽

Judith Spungen ◽

Brenna Flannery ◽

Laurie Dolan ◽

...

Keyword(s):

Public Health ◽

Dose Response ◽

Inorganic Arsenic ◽

Decision Makers ◽

Response Models ◽

Wide Range ◽

Shiny App ◽

The Impact ◽

The U.S

Abstract Objectives We developed a framework to provide decision makers with a multi-faceted evaluation of the impact of dietary shifts on risk of illness in the U.S. population. Methods We collected representative data on prevalence and concentration of inorganic arsenic and aflatoxin in infant rice and oat cereal. Exposure to these contaminants through consumption and risk of illness from cancer were assessed per consumer based on data from the National Health and Nutrition Examination Survey and published dose-response and related data. The expected number of additional cases of illness and disability-adjusted life years (DALYs) for the U.S. population were estimated. The public health impact of shifts in consumption from one product to the other considered marginal and joint consumption and characterized uncertainty arising from estimates of contaminant concentrations, bioavailability and dose-response models. Monte Carlo simulations were developed in R and a Shiny app was created. Results Based on current consumption of infant rice and oat cereal, the estimated additional DALY for the total US population from inorganic arsenic and aflatoxin is 4,600 (CI 90% [370; 8,400]). If all consumers shift their consumption (maintaining equivalent servings) to only infant rice or only infant oat cereal, the estimated DALY increases to 1.4 and decreases to 0.4 relative to the baseline, respectively. Changes in contaminant concentrations or % consumers also significantly impact risk. Uncertainty in risk estimates is primarily driven by the dose-response models for this case study. The case study showcases applicability of the framework for a wide range of food safety and nutrition questions. Results support previous advice on varying grain intake in children. Conclusions The current risk-risk framework can provide decision makers with a nuanced understanding of the impact of consumption shifts on public health and reveal parameters that drive predicted changes in public health. The Shiny app provides a real-time visualization tool to facilitate understanding and allow direct query by decision makers. Funding Sources This work was carried out under official duties or contract with U.S. FDA.

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Influence of air quality model resolution on uncertainty associated with health impacts

Atmospheric Chemistry and Physics Discussions ◽

10.5194/acpd-12-14525-2012 ◽

2012 ◽

Vol 12 (6) ◽

pp. 14525-14549

Author(s):

T. M. Thompson ◽

N. E. Selin

Keyword(s):

Air Quality ◽

Confidence Interval ◽

Human Health ◽

Confidence Intervals ◽

Health Impacts ◽

Base Case ◽

Response Functions ◽

Model Resolution ◽

Ozone Concentrations ◽

The Impact

Abstract. We use regional air quality modeling to evaluate the impact of model resolution on uncertainty associated with the human health benefits resulting from proposed air quality regulations. Using a regional photochemical model (CAMx), we ran a modeling episode with meteorological inputs representing conditions as they occurred during August through September 2006, and two emissions inventories (a 2006 base case and a 2018 proposed control scenario, both for Houston, Texas) at 36, 12, 4 and 2 km resolution. The base case model performance was evaluated for each resolution against daily maximum 8-h averaged ozone measured at monitoring stations. Results from each resolution were more similar to each other than they were to measured values. Population-weighted ozone concentrations were calculated for each resolution and applied to concentration response functions (with 95% confidence intervals) to estimate the health impacts of modeled ozone reduction from the base case to the control scenario. We found that estimated avoided mortalities were not significantly different between 2, 4 and 12 km resolution runs, but 36 km resolution may over-predict some potential health impacts. Given the cost/benefit analysis requirements of the Clean Air Act, the uncertainty associated with human health impacts and therefore the results reported in this study, we conclude that health impacts calculated from population weighted ozone concentrations obtained using regional photochemical models at 36 km resolution fall within the range of values obtained using fine (12 km or finer) resolution modeling. However, in some cases, 36 km resolution may not be fine enough to statistically replicate the results achieved using 2 and 4 km resolution. On average, when modeling at 36 km resolution, 7 deaths per ozone month were avoided because of ozone reductions resulting from the proposed emissions reductions (95% confidence interval was 2–9). When modeling at 2, 4 or 12 km finer scale resolution, on average 5 deaths were avoided due to the same reductions (95% confidence interval was 2–7). Initial results for this specific region show that modeling at a resolution finer than 12 km is unlikely to improve uncertainty in benefits analysis. We suggest that 12 km resolution may be appropriate for uncertainty analyses in areas with similar chemistry, but that resolution requirements should be assessed on a case-by-case basis and revised as confidence intervals for concentration-response functions are updated.

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