Risk, Responsibility, and Blame: An Analysis of Vocabularies of Motive in Air-Pollution(ing) Discourses

10.1068/a3521 ◽  
2002 ◽  
Vol 34 (12) ◽  
pp. 2175-2192 ◽  
Author(s):  
Karen Bickerstaff ◽  
Gordon Walker
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Empirical Study ◽  
Health Risk ◽  
Public Perceptions ◽  
Policy Implications ◽  
Urban Air ◽  
Collective Risk ◽  
The Individual ◽  
Academic Debate

In this paper we analyse the reasonings that people deploy in explaining and rationalising their behaviour in relation to the collective environmental and health-risk problem of urban air quality. We draw on an empirical study of public perceptions of air pollution to identify a range of ‘vocabularies of motive’ or discourses that serve to move responsibility to act away from the individual and onto other groups. We consider how far each of these ‘vocabularies' can be interpreted as a mode of blaming, and draw conclusions linking our analysis to wider relational and moral tensions. Our analysis suggests that blame, although conceptually powerful, falters under empirical scrutiny. On this basis we argue for a more sensitive reading of responsibility discourses in academic debate and enquiry. Conclusions and policy implications are developed, linking our interpretation to the (confrontation of) wider relational and moral tensions, which characterise collective-risk situations.

Assessing the impact of the New Athens airport to urban air quality with contemporary air pollution models

1997 ◽  
Vol 31 (10) ◽  
pp. 1497-1511 ◽  
Author(s):  
N. Moussiopoulos ◽  
P. Sahm ◽  
K. Karatzas ◽  
S. Papalexiou ◽  
A. Karagiannidis
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Urban Air Quality ◽  
Urban Air ◽  
The Impact ◽  
Air Pollution Models

Residents’ preferred measures and willingness-to-pay for improving urban air quality: A case study of Hanoi city, Vietnam

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Thanh Cong Nguyen ◽  
Hang Dieu Nguyen ◽  
Hoa Thu Le ◽  
Shinji Kaneko
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Willingness To Pay ◽  
Public Transportation ◽  
Online Survey ◽  
Urban Air Quality ◽  
Multivariate Probit ◽  
Urban Air ◽  
Content Type ◽  
Public Opinions

PurposeThis purpose of this paper is to understand residents’ choice of preferred measures and their willingness-to-pay (WTP) for the measures to improve the air quality of Hanoi city.Design/methodology/approachQuestionnaire surveys were conducted to collect the opinions of 212 household representatives living in Hanoi City. The survey tools were tested and adjusted through an online survey with 191 responses. Multivariate probit and linear regression models were used to identify determinants of respondents’ choices of measures and their WTP.FindingsRespondents expressed their strong preferences for three measures for air quality improvements, including: (1) increase of green spaces; (2) use of less polluting fuels; (3) expansion of public transportation. The mean WTP for the implementation of those measures was estimated at about 148,000–282,000 Vietnamese dong, equivalent to 0.09–0.16% of household income. The respondents’ choices appear to be consistent with their characteristics and needs, such as financial affordability, time on roads and their perceived impacts of air pollution. The WTP estimates increase with perception of air pollution impacts, time on roads, education and income; but are lower for older people.Originality/valueTo gain a better understanding of public opinions, we applied multivariate probit models to check whether respondents’ choices were consistent with their characteristics and perceptions. This appears to be the first attempt to test the validity of public opinions on choices of measures for improving urban air quality in Vietnam. Our WTP estimates also contribute to the database on the values of improved air quality in the developing world.

An assessment of ambient air quality using AQI and exceedance factor for Udaipur City, Rajasthan (India)

2021 ◽  
pp. 94-106
Author(s):  
Porush Kumar ◽  
Kuldeep ◽  
Nilima Gautam
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Pollution Control ◽  
Urban Air Pollution ◽  
Ambient Air ◽  
Quality Monitoring ◽  
Urban Air ◽  
Air Quality Monitoring ◽  
Ambient Air Quality ◽  
Control Board

Air pollution is a severe issue of concern worldwide due to its most significant environmental risk to human health today. All substances that appear in excessive amounts in the environment, such as PM10, NO2, or SO2, may be associated with severe health problems. Anthropogenic sources of these pollutants are mainly responsible for the deterioration of urban air quality. These sources include stationary point sources, mobile sources, waste disposal landfills, open burning, and similar others. Due to these pollutants, people are at increased risk of various serious diseases like breathing problems and heart disease, and the death rate due to these diseases can also increase. Hence, air quality monitoring is essential in urban areas to control and regulate the emission of these pollutants to reduce the health impacts on human beings. Udaipur has been selected for the assessment of air quality with monitored air quality data. Air quality monitoring stations in Udaipur city are operated by the CPCB (Central Pollution Control Board) and RSPCB (Rajasthan State Pollution Control Board). The purpose of this study is to characterize the level of urban air pollution through the measurement of PM10, NO2, or SO2 in Udaipur city, Rajasthan (India). Four sampling locations were selected for Udaipur city to assess the effect of urban air pollution and ambient air quality, and it was monitored for a year from 1st January 2019 to 31st December 2019. The air quality index has been calculated with measured values of PM10, NO2, and SO2. The concentration of PM10 is at a critical level of pollution and primarily responsible for bad air quality and high air quality Index in Udaipur city.

scholarly journals Healthier breath for all and everywhere – Urban air quality monitoring experience

2019 ◽  
Vol 29 (Supplement_4) ◽  
Author(s):  
J Gajic ◽  
D Dimovski ◽  
B Vukajlovic ◽  
M Jevtic
Keyword(s):  
Public Health ◽  
Air Pollution ◽  
Air Quality ◽  
Health Risk ◽  
Urban Health ◽  
Urban Areas ◽  
Danube River ◽  
Quality Monitoring ◽  
Air Quality Monitoring ◽  
Residential Areas

Abstract Issue/problem Increasing attention is being paid to air pollution as one of the greatest threats to public and urban health. The WHO’s Urban Health Initiative points out the importance of collecting data and mapping the present state of air quality in urban areas. For citizens, such engagement is enabled by the appearance of personal air quality measurement devices that use crowd-sourcing to make measurement results publicly accessible in real time. Description of the problem As a way of contributing to air pollution monitoring in their town, three PhD Public health students conducted over 40 measurements between the start of June and end of August 2018 on various locations in the city of Novi Sad, Serbia. Measurements were performed using AirBeam personal air quality monitoring devices and their results presented as μg/m3 of Particulate Matter 2.5 (PM2.5) and automatically uploaded to the internet using the Air-casting app. Results Measurements conducted in public transportation vehicles returned the rather high average value of 40 μg/m3, where coffee shops and restaurants scored an even higher value of 48,67 μg/m3. The lowest average air pollution levels were registered near the Danube river bank (5.67) and in the parks (6), while the sites near crossroads or in the street showed average air pollution of 8.33 μg/m3. Residential areas where smoking is present during the day reported 2.5 times higher PM2.5 values than those without smokers (33.8 and 12.78 μg/m3). Lessons Bearing in mind that the air quality is considered as a serious health risk in urban areas, results of this pilot investigation suggest potential health risk for citizens living in urban areas. The negative effects of combustion and smoking on air quality are strongly highlighted, as well as the positive impact of green areas and parks near residential areas. Key messages Air pollution exposure as a serious health risk in urban areas. Crowdsourcing as a way of air quality monitoring has great potential for contributing to public health.

scholarly journals Ensemble Forecasts of Air Quality in Eastern China – Part 2. Evaluation of the MarcoPolo-Panda Prediction System, Version 1

2018 ◽  
Author(s):  
Anna Katinka Petersen ◽  
Guy P. Brasseur ◽  
Idir Bouarar ◽  
Johannes Flemming ◽  
Michael Gauss ◽  
...  
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Observational Data ◽  
Prediction System ◽  
Model Ensemble ◽  
Individual Model ◽  
Forecasting System ◽  
The Individual ◽  
Pollution Events ◽  
Statistical Indicators

Abstract. An operational multi-model forecasting system for air quality has been developed to provide air quality services for urban areas of China. The initial forecasting system included seven state-of-the-art computational models developed and executed in Europe and China (CHIMERE, IFS, EMEP MSC-W, WRF-Chem-MPIM, WRF-Chem-SMS, LOTOS-EUROS and SILAMtest). Several other models joined the prediction system recently, but are not considered in the present analysis. In addition to the individual models, a simple multi-model ensemble was constructed by deriving statistical quantities such as the median and the mean of the predicted concentrations. The prediction system provides daily forecasts and observational data of surface ozone, nitrogen dioxides and particulate matter for the 37 largest urban agglomerations in China (population higher than 3 million in 2010). These individual forecasts as well as the multi-model ensemble predictions for the next 72 hours are displayed as hourly outputs on a publicly accessible web site (www.marcopolo-panda.eu). In this paper, the performance of the predictions system (individual models and the multi-model ensemble) for the first operational year (April 2016 until June 2017) has been analysed through statistical indicators using the surface observational data reported at Chinese national monitoring stations. This evaluation aims to investigate a) the seasonal behavior, b) the geographical distribution and c) diurnal variations of the ensemble and model skills. Statistical indicators show that the ensemble product usually provides the best performance compared to the individual model forecasts. The ensemble product is robust even if occasionally some individual model results are missing. Overall and in spite of some discrepancies, the air quality forecasting system is well suited for the prediction of air pollution events and has the ability to provide alert warning (binary prediction) of air pollution events if bias corrections are applied to improve the ozone predictions.

scholarly journals Investigation of the Impact of Land-Use Distribution on PM2.5 in Weifang: Seasonal Variations

2020 ◽  
Vol 17 (14) ◽  
pp. 5135
Author(s):  
Chengming Li ◽  
Kuo Zhang ◽  
Zhaoxin Dai ◽  
Zhaoting Ma ◽  
Xiaoli Liu
Keyword(s):  
Land Use ◽  
Air Pollution ◽  
Air Quality ◽  
Nonlinear Effects ◽  
Policy Implications ◽  
Effective Control ◽  
Boosted Regression Tree ◽  
Construction Land ◽  
The Impact ◽  
Effects Of Land Use

As air pollution becomes highly focused in China, the accurate identification of its influencing factors is critical for achieving effective control and targeted environmental governance. Land-use distribution is one of the key factors affecting air quality, and research on the impact of land-use distribution on air pollution has drawn wide attention. However, considerable studies have mostly used linear regression models, which fail to capture the nonlinear effects of land-use distribution on PM2.5 (fine particulate matter with a diameter less than or equal to 2.5 microns) and to show how impacts on PM2.5 vary with land-use magnitudes. In addition, related studies have generally focused on annual analyses, ignoring the seasonal variability of the impact of land-use distribution on PM2.5, thus leading to possible estimation biases for PM2.5. This study was designed to address these issues and assess the impacts of land-use distribution on PM2.5 in Weifang, China. A machine learning statistical model, the boosted regression tree (BRT), was applied to measure nonlinear effects of land-use distribution on PM2.5, capture how land-use magnitude impacts PM2.5 across different seasons, and explore the policy implications for urban planning. The main conclusions are that the air quality will significantly improve with an increase in grassland and forest area, especially below 8% and 20%, respectively. When the distribution of construction land is greater than around 10%, the PM2.5 pollution can be seriously substantially increased with the increment of their areas. The impact of gardens and farmland presents seasonal characteristics. It is noted that as the weather becomes colder, the inhibitory effect of vegetation distribution on the PM2.5 concentration gradually decreases, while the positive impacts of artificial surface distributions, such as construction land and roads, are aggravated because leaves drop off in autumn (September–November) and winter (December–February). According to the findings of this study, it is recommended that Weifang should strengthen pollution control in winter, for instance, expand the coverage areas of evergreen vegetation like Pinus bungeana Zucc. and Euonymus japonicus Thunb, and increase the width and numbers of branches connecting different main roads. The findings also provide quantitative and optimal land-use planning and strategies to minimize PM2.5 pollution, referring to the status of regional urbanization and greening construction.

scholarly journals Effects of meteorology and emissions on urban air quality: a quantitative statistical approach to long-term records (1999–2016) in Seoul, South Korea

2018 ◽  
Vol 18 (21) ◽  
pp. 16121-16137 ◽  
Author(s):  
Jihoon Seo ◽  
Doo-Sun R. Park ◽  
Jin Young Kim ◽  
Daeok Youn ◽  
Yong Bin Lim ◽  
...  
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
South Korea ◽  
Meteorological Conditions ◽  
Meteorological Variables ◽  
Urban Air ◽  
Short Term ◽  
Long Term Trends ◽  
Local Emissions

Abstract. Together with emissions of air pollutants and precursors, meteorological conditions play important roles in local air quality through accumulation or ventilation, regional transport, and atmospheric chemistry. In this study, we extensively investigated multi-timescale meteorological effects on the urban air pollution using the long-term measurements data of PM10, SO2, NO2, CO, and O3 and meteorological variables over the period of 1999–2016 in Seoul, South Korea. The long-term air quality data were decomposed into trend-free short-term components and long-term trends by the Kolmogorov–Zurbenko filter, and the effects of meteorology and emissions were quantitatively isolated using a multiple linear regression with meteorological variables. In terms of short-term variability, intercorrelations among the pollutants and meteorological variables and composite analysis of synoptic meteorological fields exhibited that the warm and stagnant conditions in the migratory high-pressure system are related to the high PM10 and primary pollutant, while the strong irradiance and low NO2 by high winds at the rear of a cyclone are related to the high O3. In terms of long-term trends, decrease in PM10 (−1.75 µg m−3 yr−1) and increase in O3 (+0.88 ppb yr−1) in Seoul were largely contributed by the meteorology-related trends (−0.94 µg m−3 yr−1 for PM10 and +0.47 ppb yr−1 for O3), which were attributable to the subregional-scale wind speed increase. Comparisons with estimated local emissions and socioeconomic indices like gross domestic product (GDP) growth and fuel consumptions indicate probable influences of the 2008 global economic recession as well as the enforced regulations from the mid-2000s on the emission-related trends of PM10 and other primary pollutants. Change rates of local emissions and the transport term of long-term components calculated by the tracer continuity equation revealed a decrease in contributions of local emissions to the primary pollutants including PM10 and an increase in contributions of local secondary productions to O3. The present results not only reveal an important role of synoptic meteorological conditions on the episodic air pollution events but also give insights into the practical effects of environmental policies and regulations on the long-term air pollution trends. As a complementary approach to the chemical transport modeling, this study will provide a scientific background for developing and improving effective air quality management strategy in Seoul and its metropolitan area.

ACROSS: An Observational Campaign to Improve Understanding of Photochemistry of Mixed Urban and Biogenic Air Masses

2020 ◽  
Author(s):  
Christopher Cantrell ◽  
Vincent Michoud ◽  
Paola Formenti ◽  
Jean-Francois Doussin ◽  
Aline Gratien ◽  
...  
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Field Study ◽  
Organic Compounds ◽  
Numerical Models ◽  
Urban Air Pollution ◽  
Central Component ◽  
Urban Air ◽  
Oxides Of Nitrogen ◽  
Chemical Structures

<p>In recent decades, significant progress has been made in understanding the causes and impacts of urban air pollution, generally leading to improved air quality through enhanced knowledge and regulatory action. While a significant number of people still die prematurely each year from air pollution, progress continues to be made. Scientific investigation has exposed the processes by which primary pollutants, such as oxides of nitrogen and volatile organic compounds, are processed in the atmosphere, leading to their oxidation and ultimate removal, while at the same time producing secondary species such as ozone and organic aerosols.</p><p>Research has uncovered the complex chemistry of natural organic compounds released from trees and other plants. Because of the chemical structures of these compounds, they react somewhat differently than organic substances typically found in urban environments. The ACROSS (<strong>A</strong>tmospheric <strong>C</strong>hemist<strong>R</strong>y <strong>O</strong>f the <strong>S</strong>uburban fore<strong>S</strong>t) project focuses on scientific research to understand the detailed chemistry and physics of urban air mixed with biogenic emissions with the goals to increase detailed understanding of the chemical processes and to use this knowledge to improve the performance of air quality models. Enhanced knowledge and improved models will allow society to develop better strategies to improve air quality and save lives.</p><p>The central component of ACROSS is a comprehensive summertime field study with many instruments for the measurement of primary and secondary constituents. Measurements will be made from research aircraft, a tower located in a forest, tethered balloons and/or drones, and mobile platforms. Observations from the field study will be analyzed in a variety of ways involving statistical approaches and comparisons with different types of numerical models.</p><p>This presentation describes activities in preparation of the ACROSS measurement campaign and provides information for interested parties to become involved.</p>

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