scholarly journals The success of emissions control legislation in mitigating air pollution is higher than previously estimated

2016 ◽  
Author(s):  
Nikos Daskalakis ◽  
Kostas Tsigaridis ◽  
Stelios Myriokefalitakis ◽  
George S. Fanourgakis ◽  
Maria Kanakidou

Abstract. During the last 30 years significant effort has been made to improve air quality through legislation for emissions reduction. Global three-dimensional chemistry-transport simulations of atmospheric composition changes over the past three decades have been performed to assess the impact of these measures. The simulations are based on assimilated meteorology to account for the year-to-year observed climate variability and on different anthropogenic emissions scenarios of pollutants which may or may not account for air quality legislation application. The ACCMIP dataset historical emissions are used as the starting point. We show that air quality legislation has been more efficient than thought in limiting the rapid increase of air pollutants due to significant technology development. The achieved reductions in nitrogen oxides, carbon monoxide, black carbon and sulphate aerosols are found to be significant when comparing to simulations neglecting legislation for the protection of the environment. We also show the large tropospheric air-quality benefit from the development of cleaner technology. These 30-year hindcast simulations demonstrate that the actual benefit in air quality due to air pollution legislation and technological advances is higher than the gain calculated by a simple comparison against a constant anthropogenic emissions simulation, as is usually done. Our results also indicate that over China and India the beneficial technological advances for the air-quality have been masked by the explosive increase in local population and the disproportional increase in energy demand.

2016 ◽  
Vol 16 (15) ◽  
pp. 9771-9784 ◽  
Author(s):  
Nikos Daskalakis ◽  
Kostas Tsigaridis ◽  
Stelios Myriokefalitakis ◽  
George S. Fanourgakis ◽  
Maria Kanakidou

Abstract. During the last 30 years, significant effort has been made to improve air quality through legislation for emissions reduction. Global three-dimensional chemistry-transport simulations of atmospheric composition over the past 3 decades have been performed to estimate what the air quality levels would have been under a scenario of stagnation of anthropogenic emissions per capita as in 1980, accounting for the population increase (BA1980) or using the standard practice of neglecting it (AE1980), and how they compare to the historical changes in air quality levels. The simulations are based on assimilated meteorology to account for the year-to-year observed climate variability and on different scenarios of anthropogenic emissions of pollutants. The ACCMIP historical emissions dataset is used as the starting point. Our sensitivity simulations provide clear indications that air quality legislation and technology developments have limited the rapid increase of air pollutants. The achieved reductions in concentrations of nitrogen oxides, carbon monoxide, black carbon, and sulfate aerosols are found to be significant when comparing to both BA1980 and AE1980 simulations that neglect any measures applied for the protection of the environment. We also show the potentially large tropospheric air quality benefit from the development of cleaner technology used by the growing global population. These 30-year hindcast sensitivity simulations demonstrate that the actual benefit in air quality due to air pollution legislation and technological advances is higher than the gain calculated by a simple comparison against a constant anthropogenic emissions simulation, as is usually done. Our results also indicate that over China and India the beneficial technological advances for the air quality may have been masked by the explosive increase in local population and the disproportional increase in energy demand partially due to the globalization of the economy.


Author(s):  
Cheng Liu ◽  
Meng Gao ◽  
Qihou Hu ◽  
Guy P. Brasseur ◽  
Gregory R. Carmichael

AbstractMonitoring and modeling/predicting air pollution are crucial to understanding the links between emissions and air pollution levels, to supporting air quality management, and to reducing human exposure. Yet, current monitoring networks and modeling capabilities are unfortunately inadequate to understand the physical and chemical processes above ground, and to support attribution of sources. We highlight the need for the development of an international stereoscopic monitoring strategy that can depict three-dimensional (3D) distribution of atmospheric composition to reduce the uncertainties, and to advance diagnostic understanding and prediction of air pollution. There are three reasons for the implementation of stereoscopic monitoring: (1) current observation networks provide only partial view of air pollution, and this can lead to misleading air quality management actions; (2) satellite retrievals of air pollutants are widely used in air pollution studies, but too often users do not acknowledge that they have large uncertainties, which can be reduced with measurements of vertical profiles; (3) air quality modeling and forecasting require 3D observational constraints. We call on researchers and policymakers to establish stereoscopic monitoring networks and share monitoring data to better characterize the formation of air pollution, optimize air quality management and protect human health. Future directions for advancing monitoring and modeling/predicting air pollution are also discussed.


2020 ◽  
Author(s):  
Johannes Flemming ◽  
Okasna Tarasova ◽  
Lu Ren ◽  
Alexander Baklanov ◽  
Greg Carmichael

<p>Air pollution is the single largest environmental risk factor to health globally; it contributes to climate change, is detrimental for ecosystems, damages property, impacts visibility and can threaten food and water security. A wide variety of Air Quality (AQ) systems operate at different spatial and temporal scales to provide information required to mitigate the impact of or to reduce air pollution. </p><p>Recognising the importance to support the transition of scientific efforts into useful services, the Global Atmosphere Watch Programme (GAW) of the World Meteorological Organisation (WMO) has started an initiative on Global Air quality Forecast and Information Systems (GAFIS). GAFIS aims to become a network for the development of good practices for air quality forecasting and monitoring services using  diverse approaches. GAFIS will closely interact with existing GAW efforts on air pollution forecasting and dust strom prediction, and it intends to build strong links with the international health community. As a major first step, GAFIS will carry out and maintain a survey of AQ information systems and identify areas and regions with a lack of adequate AQ services. GAFIS aims to improve access to air quality observations and to encourage better quality control and meta-data provision.  GAFIS will initiate coordinated evaluation activities of air quality services using a harmonized evaluation protocol. Finally,  promoting operational applications of atmospheric composition feedbacks in Numerical Weather Prediction is a further objective of GAFIS.</p><p>In the presentation we will introduce GAFIS to the scientific community and invite collaboration within its framework. </p>


Energies ◽  
2021 ◽  
Vol 14 (8) ◽  
pp. 2033
Author(s):  
Rafał Blazy ◽  
Jakub Błachut ◽  
Agnieszka Ciepiela ◽  
Rita Łabuz ◽  
Renata Papież

Air pollution is one of the important environmental problems in Poland. The main cause of its occurrence is emissions associated with individual heating of buildings. The reduction of the primary energy demand in a building is influenced by its proper thermal modernization, including in particular insulating. In view of the above, this article presents the results of studies on the possible environmental benefits of thermal modernization of single-family houses for the area of Southern Poland. The analysis was limited to determining the impact of measures to reduce air pollution emissions by insulating the building envelope of single-family houses. The research was conducted for two voivodeships: Śląskie and Małopolskie. Its aim is to identify the financial costs and achievable ecological effects of the thermal modernization of single-family buildings. The geographical selection of the research area was based on the fact that it covers the most polluted region in Poland. This region is characterized by many features that influence poor air quality. Among these features, the most important are: diversified building structure, a diverse topography, and very high population density. To limit multiple variables, we have selected a scenario method that has already been used in similar research. Four scenarios were established to show the relationship between the value of emission reductions and the level of funding for thermal modernization. The analysis allows a comparison of the effectiveness of individual variants and the transposition of their results into the possibilities of action in the region. This research will help to supplement the knowledge of the impact of insulating building envelopes on reducing pollutant emissions by reducing the energy demand of a building. They also identify a possible link between the level of this reduction and the grant amount for thermal modernization. As a result, it was found that a high share of external funding—stimulating the tendency of the inhabitants of the analyzed voivodeships to effective thermal modernization, and thus reducing the buildings’ energy consumption—has a significant impact on the improvement of air quality.


2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Parichat Wetchayont

With the outbreak of the COVID-19 pandemic around the world, many countries announced lockdown measures, including Thailand. Several scientific studies have reported on improvements in air quality due to the impact of these COVID-19 lockdowns. This study aims to investigate the effects of the COVID-19 lockdown and its driving influencing factors on air pollution in Greater Bangkok, Thailand, using in situ measurements. Overall, PM2.5, PM10, O3, and CO concentrations presented a significant decreasing trend during the COVID-19 outbreak year based on three periods: the Before Lockdown, Lockdown, and After Lockdown periods, for PM2.5: −0.7%, −15.8%, and −20.7%; PM10: −4.1%, −31.7%, and −6.1%; and O3: −0.3%, −7.1%, and −4.7%, respectively, compared to the same periods in 2019. CO concentrations, especially which had increased by 14.7% Before Lockdown, decreased by −8.0% and −23.6% during the Lockdown and After Lockdown periods, respectively. Meanwhile, SO2 increased by 54.0%, 41.5%, and 84.6%, and NO2 increased by 20.1%, 3.2%, and 26.6%, respectively, for the Before Lockdown, Lockdown, and After Lockdown periods. PCA indicated a significant combination effect of atmospheric mechanisms that were strongly linked to emission sources such as traffic and biomass burning. It has been demonstrated that the COVID-19 lockdown did pause some of these anthropogenic emissions, i.e., traffic and commercial and industrial activities, but not all of them. Even low traffic emissions, on their own, did not cause an absolute reduction in air pollution since there are several primary emission sources that dominate the air quality over Greater Bangkok. Finally, these findings highlight the impact of COVID-19 lockdown measures not only on air pollution levels but on their effects on air pollution characteristics, as well.


Author(s):  
Farhang Tahmasebi ◽  
Yan Wang ◽  
Elizabeth Cooper ◽  
Daniel Godoy Shimizu ◽  
Samuel Stamp ◽  
...  

The Covid-19 outbreak has resulted in new patterns of home occupancy, the implications of which for indoor air quality (IAQ) and energy use are not well-known. In this context, the present study investigates 8 flats in London to uncover if during a lockdown, (a) IAQ in the monitored flats deteriorated, (b) the patterns of window operation by occupants changed, and (c) more effective ventilation patterns could enhance IAQ without significant increases in heating energy demand. To this end, one-year’s worth of monitored data on indoor and outdoor environment along with occupant use of windows has been used to analyse the impact of lockdown on IAQ and infer probabilistic models of window operation behaviour. Moreover, using on-site CO2 data, monitored occupancy and operation of windows, the team has calibrated a thermal performance model of one of the flats to investigate the implications of alternative ventilation strategies. The results suggest that despite the extended occupancy during lockdown, occupants relied less on natural ventilation, which led to an increase of median CO2 concentration by up to 300 ppm. However, simple natural ventilation patterns or use of mechanical ventilation with heat recovery proves to be very effective to maintain acceptable IAQ. Practical application: This study provides evidence on the deterioration of indoor air quality resulting from homeworking during imposed lockdowns. It also tests and recommends specific ventilation strategies to maintain acceptable indoor air quality at home despite the extended occupancy hours.


Author(s):  
Christian Acal ◽  
Ana M. Aguilera ◽  
Annalina Sarra ◽  
Adelia Evangelista ◽  
Tonio Di Battista ◽  
...  

AbstractFaced with novel coronavirus outbreak, the most hard-hit countries adopted a lockdown strategy to contrast the spread of virus. Many studies have already documented that the COVID-19 control actions have resulted in improved air quality locally and around the world. Following these lines of research, we focus on air quality changes in the urban territory of Chieti-Pescara (Central Italy), identified as an area of criticality in terms of air pollution. Concentrations of $$\hbox {NO}_{{2}}$$ NO 2 , $$\hbox {PM}_{{10}}$$ PM 10 , $$\hbox {PM}_{2.5}$$ PM 2.5 and benzene are used to evaluate air pollution changes in this Region. Data were measured by several monitoring stations over two specific periods: from 1st February to 10 th March 2020 (before lockdown period) and from 11st March 2020 to 18 th April 2020 (during lockdown period). The impact of lockdown on air quality is assessed through functional data analysis. Our work makes an important contribution to the analysis of variance for functional data (FANOVA). Specifically, a novel approach based on multivariate functional principal component analysis is introduced to tackle the multivariate FANOVA problem for independent measures, which is reduced to test multivariate homogeneity on the vectors of the most explicative principal components scores. Results of the present study suggest that the level of each pollutant changed during the confinement. Additionally, the differences in the mean functions of all pollutants according to the location and type of monitoring stations (background vs traffic), are ascribable to the $$\hbox {PM}_{{10}}$$ PM 10 and benzene concentrations for pre-lockdown and during-lockdown tenure, respectively. FANOVA has proven to be beneficial to monitoring the evolution of air quality in both periods of time. This can help environmental protection agencies in drawing a more holistic picture of air quality status in the area of interest.


2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Peter D. Sly ◽  
Brittany A. Trottier ◽  
Catherine M. Bulka ◽  
Stephania A. Cormier ◽  
Julius Fobil ◽  
...  

Abstract Background An unusual feature of SARS-Cov-2 infection and the COVID-19 pandemic is that children are less severely affected than adults. This is especially paradoxical given the epidemiological links between poor air quality and increased COVID-19 severity in adults and that children are generally more vulnerable than adults to the adverse consequences of air pollution. Objectives To identify gaps in knowledge about the factors that protect children from severe SARS-Cov-2 infection even in the face of air pollution, and to develop a transdisciplinary research strategy to address these gaps. Methods An international group of researchers interested in children’s environmental health was invited to identify knowledge gaps and to develop research questions to close these gaps. Discussion Key research questions identified include: what are the effects of SAR-Cov-2 infection during pregnancy on the developing fetus and child; what is the impact of age at infection and genetic susceptibility on disease severity; why do some children with COVID-19 infection develop toxic shock and Kawasaki-like symptoms; what are the impacts of toxic environmental exposures including poor air quality, chemical and metal exposures on innate immunity, especially in the respiratory epithelium; what is the possible role of a “dirty” environment in conveying protection – an example of the “hygiene hypothesis”; and what are the long term health effects of SARS-Cov-2 infection in early life. Conclusion A concerted research effort by a multidisciplinary team of scientists is needed to understand the links between environmental exposures, especially air pollution and COVID-19. We call for specific research funding to encourage basic and clinical research to understand if/why exposure to environmental factors is associated with more severe disease, why children appear to be protected, and how innate immune responses may be involved. Lessons learned about SARS-Cov-2 infection in our children will help us to understand and reduce disease severity in adults, the opposite of the usual scenario.


Author(s):  
Shwet Ketu ◽  
Pramod Kumar Mishra

AbstractIn the last decade, we have seen drastic changes in the air pollution level, which has become a critical environmental issue. It should be handled carefully towards making the solutions for proficient healthcare. Reducing the impact of air pollution on human health is possible only if the data is correctly classified. In numerous classification problems, we are facing the class imbalance issue. Learning from imbalanced data is always a challenging task for researchers, and from time to time, possible solutions have been developed by researchers. In this paper, we are focused on dealing with the imbalanced class distribution in a way that the classification algorithm will not compromise its performance. The proposed algorithm is based on the concept of the adjusting kernel scaling (AKS) method to deal with the multi-class imbalanced dataset. The kernel function's selection has been evaluated with the help of weighting criteria and the chi-square test. All the experimental evaluation has been performed on sensor-based Indian Central Pollution Control Board (CPCB) dataset. The proposed algorithm with the highest accuracy of 99.66% wins the race among all the classification algorithms i.e. Adaboost (59.72%), Multi-Layer Perceptron (95.71%), GaussianNB (80.87%), and SVM (96.92). The results of the proposed algorithm are also better than the existing literature methods. It is also clear from these results that our proposed algorithm is efficient for dealing with class imbalance problems along with enhanced performance. Thus, accurate classification of air quality through our proposed algorithm will be useful for improving the existing preventive policies and will also help in enhancing the capabilities of effective emergency response in the worst pollution situation.


2020 ◽  
Vol 9 (8) ◽  
pp. 2351
Author(s):  
Łukasz Kuźma ◽  
Krzysztof Struniawski ◽  
Szymon Pogorzelski ◽  
Hanna Bachórzewska-Gajewska ◽  
Sławomir Dobrzycki

(1) Introduction: air pollution is considered to be one of the main risk factors for public health. According to the European Environment Agency (EEA), air pollution contributes to the premature deaths of approximately 500,000 citizens of the European Union (EU), including almost 5000 inhabitants of Poland every year. (2) Purpose: to assess the gender differences in the impact of air pollution on the mortality in the population of the city of Bialystok—the capital of the Green Lungs of Poland. (3) Materials and Methods: based on the data from the Central Statistical Office, the number—and causes of death—of Białystok residents in the period 2008–2017 were analyzed. The study utilized the data recorded by the Provincial Inspectorate for Environmental Protection station and the Institute of Meteorology and Water Management during the analysis period. Time series regression with Poisson distribution was used in statistical analysis. (4) Results: A total of 34,005 deaths had been recorded, in which women accounted for 47.5%. The proportion of cardiovascular-related deaths was 48% (n = 16,370). An increase of SO2 concentration by 1-µg/m3 (relative risk (RR) 1.07, 95% confidence interval (CI) 1.02–1.12; p = 0.005) and a 10 °C decrease of temperature (RR 1.03, 95% CI 1.01–1.05; p = 0.005) were related to an increase in the number of daily deaths. No gender differences in the impact of air pollution on mortality were observed. In the analysis of the subgroup of cardiovascular deaths, the main pollutant that was found to have an effect on daily mortality was particulate matter with a diameter of 2.5 μm or less (PM2.5); the RR for 10-µg/m3 increase of PM2.5 was 1.07 (95% CI 1.02–1.12; p = 0.01), and this effect was noted only in the male population. (5) Conclusions: air quality and atmospheric conditions had an impact on the mortality of Bialystok residents. The main air pollutant that influenced the mortality rate was SO2, and there were no gender differences in the impact of this pollutant. In the male population, an increased exposure to PM2.5 concentration was associated with significantly higher cardiovascular mortality. These findings suggest that improving air quality, in particular, even with lower SO2 levels than currently allowed by the World Health Organization (WHO) guidelines, may benefit public health. Further studies on this topic are needed, but our results bring questions whether the recommendations concerning acceptable concentrations of air pollutants should be stricter, or is there a safe concentration of SO2 in the air at all.


Sign in / Sign up

Export Citation Format

Share Document