scholarly journals Effects of meteorological variables and holidays on the concentrations of PM10, PM2.5, O3, NO2, SO2, and CO in Tehran (2014-2018)

2019 ◽  
Author(s):  
Mostafa Hadei ◽  
Maryam Yarahmadi ◽  
Ahmad Jonidi Jafari ◽  
Mohsen Farhadi ◽  
Seyed Saeed Hashemi Nazari ◽  
...  
Keyword(s):  
Air Pollution ◽  
Particulate Matter ◽  
Air Quality ◽  
Pollution Control ◽  
Meteorological Parameters ◽  
Air Pollution Control ◽  
Pollution Levels ◽  
Criteria Air Pollutants ◽  
High Concentrations ◽  
Autumn And Winter

Introduction: The aim of this study was to investigate the concentrations   of PM10, PM2.5, O3, NO2, SO2, and CO in Tehran during March 2014-March 2018, and evaluate the effects of holidays and meteorological parameters on   the air pollution levels.   Materials and methods: Hourly concentrations of PM10, PM2.5, O3, NO2, SO2, and CO in different air quality monitors of Tehran were acquired. The data from each air quality monitored were validated, and only high-quality monitors were included in this study.   Results: The 4-year averages of PM10, PM2.5, O3, NO2, SO2, and CO concen-trations were 88.74 (µg/m3), 31.02 (µg/m3), 34.87 (ppb), 71.01 (ppb), 20.04   (ppb), and 3.78 (ppm), respectively. Higher concentrations of PM10 and O3 were observed during summer. In case of PM2.5 and CO, autumn and winter concentrations were higher than those in springer and summer. Lower concen-trations of PM10 and NO2 in Fridays were observed comparing to other days of week. Ozone had high concentrations in Fridays as the weekend in Iran. Except for O3, all of the pollutants had higher concentrations in the working days, comparing to those in any type of vacation days. Concentrations of all pollutants rather that SO2 and O3 in Nowruz holidays were statistically lower than those in the working days. By controlling for the effects of meteorologi-cal variables, our results showed that the air pollution control policies and ac-tions have been not effective for particulate matter.   Conclusion: These results determines the time periods in which the concen-trations of criteria air pollutants are high. This can be very useful for an-nouncing alarms for citizens, and designing the air pollution control plans. In addition, more effective actions should be designed and implemented for reducing ambient levels of particulate matter.

scholarly journals Impact of air pollution control measures and regional transport on carbonaceous aerosols in fine particulate matter in urban Beijing, China: insights gained from long-term measurement

2019 ◽  
Vol 19 (13) ◽  
pp. 8569-8590 ◽  
Author(s):  
Dongsheng Ji ◽  
Wenkang Gao ◽  
Willy Maenhaut ◽  
Jun He ◽  
Zhe Wang ◽  
...  
Keyword(s):  
Air Pollution ◽  
Particulate Matter ◽  
Air Quality ◽  
Pollution Control ◽  
Fine Particulate Matter ◽  
Control Measures ◽  
Air Pollution Control ◽  
Heavy Duty ◽  
Potential Source ◽  
Fine Particulate

Abstract. As major chemical components of airborne fine particulate matter (PM2.5), organic carbon (OC) and elemental carbon (EC) have vital impacts on air quality, climate change, and human health. Because OC and EC are closely associated with fuel combustion, it is helpful for the scientific community and policymakers assessing the efficacy of air pollution control measures to study the impact of control measures and regional transport on OC and EC levels. In this study, hourly mass concentrations of OC and EC associated with PM2.5 were semi-continuously measured from March 2013 to February 2018. The results showed that annual mean OC and EC concentrations declined from 14.0 to 7.7 µg m−3 and from 4.0 to 2.6 µg m−3, respectively, from March 2013 to February 2018. In combination with the data of OC and EC in previous studies, an obvious decreasing trend in OC and EC concentrations was found, which was caused by clean energy policies and effective air pollution control measures. However, no obvious change in the ratios of OC and EC to the PM2.5 mass (on average, 0.164 and 0.049, respectively) was recorded, suggesting that inorganic ions still contributed a lot to PM2.5. Based on the seasonal variations in OC and EC, it appeared that higher OC and EC concentrations were still observed in the winter months, with the exception of winter of 2017–2018. Traffic policies executed in Beijing resulted in nighttime peaks of OC and EC, caused by heavy-duty vehicles and heavy-duty diesel vehicles being permitted to operate from 00:00 to 06:00 (China standard time, UTC+8, for all times throughout the paper). In addition, the fact that there was no traffic restriction in weekends led to higher concentrations on weekends compared to weekdays. Significant correlations between OC and EC were observed throughout the study period, suggesting that OC and EC originated from common emission sources, such as exhaust of vehicles and fuel combustion. OC and EC levels increased with enhanced SO2, CO, and NOx concentrations while the O3 and OC levels were enhanced simultaneously when O3 concentrations were higher than 50 µg m−3. Non-parametric wind regression analysis was performed to examine the sources of OC and EC in the Beijing area. It was found that there were distinct hot spots in the northeast wind sector at wind speeds of approximately 0–6 km h−1, as well as diffuse signals in the southwestern wind sectors. Source areas further away from Beijing were assessed by potential source contribution function (PSCF) analysis. A high-potential source area was precisely pinpointed, which was located in the northwestern and southern areas of Beijing in 2017 instead of solely in the southern areas of Beijing in 2013. This work shows that improvement of the air quality in Beijing benefits from strict control measures; however, joint prevention and control of regional air pollution in the regions is needed for further improving the air quality. The results provide a reference for controlling air pollution caused by rapid economic development in developing countries.

scholarly journals Impact of air pollution control measures and regional transport on carbonaceous aerosols in fine particulate matter in urban Beijing, China: Insights gained from long-term measurement

2019 ◽  
Author(s):  
Dongsheng Ji ◽  
Wenkang Gao ◽  
Willy Maenhaut ◽  
Jun He ◽  
Zhe Wang ◽  
...  
Keyword(s):  
Air Pollution ◽  
Particulate Matter ◽  
Air Quality ◽  
Pollution Control ◽  
Fine Particulate Matter ◽  
Control Measures ◽  
Air Pollution Control ◽  
Heavy Duty ◽  
Potential Source ◽  
Fine Particulate

Abstract. As major chemical components of airborne fine particulate matter (PM2.5), organic carbon (OC) and elemental carbon (EC) have vital impacts on air quality, climate change, and human health. Because OC and EC are closely associated with fuel combustion, it is helpful for the scientific community and policymakers assessing the efficacy of air pollution control measures to study on the impact of the control measures and regional transport on the OC and EC levels. In this study, hourly mass concentrations of OC and EC associated with PM2.5 were semi-continuously measured from March 2013 to February 2018. The results showed that annual mean OC and EC concentrations declined from 14.0 to 7.7 μg/m3 and from 4.0 to 2.6 μg/m3, respectively, from March 2013 to February 2018. In combination with the data of OC and EC in previous studies, an obvious decreasing trend in OC and EC concentrations was found, which was caused by clean energy policies and effective air pollution control measures. However, no obvious change in the ratios of OC and EC to the PM2.5 mass (on average, 0.164 and 0.049, respectively) was recorded, suggesting that inorganic ions still contributed a lot to PM2.5. Based on the seasonal variations of OC and EC, it appeared that higher OC and EC concentrations were still observed in the winter months, with the exception of winter of 2017–2018. Traffic policies executed in Beijing resulted in nighttime peaks of OC and EC, caused by heavy-duty vehicles and heavy-duty diesel vehicles being permitted to operate from 0:00 to 6:00. In addition, the fact that there was no traffic restriction in weekends led to higher concentrations in weekends compared to weekdays. Significant correlations between OC and EC were observed throughout the study period, suggesting that OC and EC originated from common emission sources, such as exhaust of vehicles and fuel combustion. OC and EC levels increased with enhanced SO2, CO and NOx concentrations while the O3 and OC levels enhanced simultaneously when O3 concentrations were higher than 50 μg/m3. Nonparametric wind regression analysis was performed to examine the sources of OC and EC in the Beijing area. It was found that there were distinct hot spots in the northeast wind sector at wind speeds of approximately 5 km/h, as well as diffuse signals in the southwestern wind sectors, highlighting probable trans-boundary transport from highly industrialized regions upwind of the Hebei province, such as Baoding, Shijiazhuang and Handan, which were the most polluted cities in China. This was consistent with their higher potential as source areas, as determined by the potential source contribution function (PSCF) analysis. A high-potential source area was precisely pinpointed, which was located in the northwestern and southern areas of Beijing in 2017 instead of solely in the southern areas of Beijing in 2013. This work shows that improvement of the air quality in Beijing benefits from strict control measures; however, joint prevention and control of regional air pollution in the regions is needed for further improving the air quality. The results provide a reference for controlling air pollution caused by rapid economic development in developing countries.

scholarly journals Using Costs and Health Benefits to Estimate the Priority of Air Pollution Control Action Plan: A Case Study in Taiwan

2020 ◽  
Vol 10 (17) ◽  
pp. 5970
Author(s):  
Hsin-Chih Lai ◽  
Min-Chuan Hsiao ◽  
Je-Liang Liou ◽  
Li-Wei Lai ◽  
Pei-Chih Wu ◽  
...  
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Pollution Control ◽  
Action Plan ◽  
Health Benefits ◽  
Control Measures ◽  
Cost Ratio ◽  
Air Pollution Control ◽  
Kriging Method ◽  
Quality Modeling

A comparative analysis was conducted between the costs and health benefits of the Air Pollution Control Action Plan (APCAP), which can be implemented in any country to improve air quality and human health. In this study, air quality modeling was used to simulate several scenarios and implement the Kriging method to describe the PM2.5 reduction concentration instantly. Then, health benefits were estimated using the environmental benefit mapping and analysis program (BenMAP) with results from the air quality modeling and Kriging method. To estimate the priority of APCAP, 14 pollution control measures that cover point, mobile, and area sources of air pollution in Taiwan were analyzed. The results indicate that the health benefits of the Taiwan APCAP (TAPCAP) are generally greater than the technical costs. Thus, the implementation of this strategy may result in net benefits. In addition, the benefit-to-control cost ratio for health for the 14 pollution control measures was calculated. The results provide evidence to prioritize the implementation of air quality policies with a higher benefit-cost ratio.

scholarly journals Effects of air pollution control measures on air quality improvement in Guangzhou, China

2019 ◽  
Vol 244 ◽  
pp. 127-137 ◽  
Author(s):  
Meifang Yu ◽  
Yun Zhu ◽  
Che-Jen Lin ◽  
Shuxiao Wang ◽  
Jia Xing ◽  
...  
Keyword(s):  
Air Pollution ◽  
Quality Improvement ◽  
Air Quality ◽  
Pollution Control ◽  
Control Measures ◽  
Air Pollution Control ◽  
Air Quality Improvement

scholarly journals Evaluation and Treatment Analysis of Air Quality Including Particulate Pollutants: A Case Study of Shandong Province, China

2020 ◽  
Vol 17 (24) ◽  
pp. 9476
Author(s):  
Bowen Jiang ◽  
Yuangang Li ◽  
Weixin Yang
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Pollution Control ◽  
Forecast Model ◽  
Maximum Error ◽  
Shandong Province ◽  
Air Pollution Control ◽  
Control Policies ◽  
Pm2.5 And Pm10

At present, China’s air pollution and its treatment effect are issues of general concern in the academic circles. Based on the analysis of the development stages of air pollution in China and the development history of China’s air quality standards, we selected 17 cities of Shandong Province, China as the research objects. By expanding China’s existing Air Quality Index System, the air quality of six major pollutants including PM2.5 and PM10 in 17 cities from February 2017 to January 2020 is comprehensively evaluated. Then, with a forecast model, the air quality of the above cities in the absence of air pollution control policies since June 2018 was simulated. The results of the error test show that the model has a maximum error of 4.67% when simulating monthly assessment scores, and the maximum mean error of the four months is 3.17%. Through the comparison between the simulation results and the real evaluation results of air quality, we found that since June 2018, the air pollution control policies of six cities have achieved more than 10% improvement, while the air quality of the other 11 cities declined. The different characteristics of pollutants and the implementation of governance policies are perhaps the main reasons for the above differences. Finally, policy recommendations for the future air pollution control in Shandong and China were provided.

A Discussion on recent research in air pollution - The application of air pollution research to power station design

1969 ◽  
Vol 265 (1161) ◽  
pp. 269-272
Keyword(s):  
Air Pollution ◽  
Pollution Control ◽  
Research Work ◽  
Control Measures ◽  
Air Pollution Control ◽  
Plant Design ◽  
Power Stations ◽  
Other Substances ◽  
High Concentrations ◽  
Definition Of

The aim of this contribution to the Meeting is to describe how the results of research work have been applied to the design of power stations in Britain. Before doing so, however, it is perhaps worth while giving an outline of the fundamental principles involved in the selection of air pollution control measures as they are seen by the engineers who must make practical decisions on plant design, and in this way define the specific objectives for the research work being undertaken. First, it must be appreciated that unless one accepts an exceedingly narrow definition of what constitutes air pollution, then clean air must be regarded as a matter of degree and not of kind. All sorts of naturally occurring gases and particulates pollute the atmosphere, even in places remote from mankind’s industrial and domestic activities. Volcanic dust and ashes, sulphur dioxide and other gases of geophysical origin, wind-blown dust, residues of sea-spray, pollen, spores, ozone, ammonia and many other substances exist quite naturally in the air we breathe. What constitutes an air pollution problem is the occurrence of pollutants in unduly high concentrations in a particular place or at a particular time. As a corollary of this, the aim of air pollution control measures is to prevent such high concentrations from occurring. This principle is fundamental to the whole concept of air pollution control, since once it is accepted then practical control measures need not necessarily be restricted to the prevention of the emission of pollutants, but can include also the manner of emission, in so far as this can influence subsequent concentrations of pollutants in the atmosphere

scholarly journals Assessment of the Effect of the Three-Year Action Plan to Fight Air Pollution on Air Quality and Associated Health Benefits in Sichuan Basin, China

2021 ◽  
Vol 13 (19) ◽  
pp. 10968
Author(s):  
Juihui Chen ◽  
Xiaoqiong Feng ◽  
Yonghui Zhu ◽  
Ling Huang ◽  
Min He ◽  
...  
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Pollution Control ◽  
Emission Reduction ◽  
Sichuan Basin ◽  
Action Plan ◽  
Control Measures ◽  
Air Pollution Control ◽  
Premature Deaths ◽  
Pm2.5 Concentration

To continuously improve air quality, after implementation of the “Clean Air Action Plan, 2013–2017” (CAAP), the “Three-year Action Plan to Fight Air Pollution” (TYP) was further conducted from 2018 to 2020. However, the effectiveness of the TYP remains unclear in one of the major city-clusters of China, the Sichuan Basin. In this study, the bottom-up method was used to quantify the emission reduction during TYP based on the emissions inventory in Sichuan Basin in 2017 and the air pollution control measures adopted from 2018 to 2020 in each city. The reduction of PM2.5 concentration and the avoided premature deaths due to implementation of air pollution control measures were assessed by using an integrated meteorology and air quality modeling system and a concentration-response algorithm. Emissions of SO2, NOx, PM2.5, and VOCs in the Sichuan Basin have been reduced by 42.6, 105.2, 40.2, and 136.6 Gg, respectively. The control of non-electricity industry contributed significantly to the emission reduction of all pollutants, accounting for 26–49%. In addition, the control of mobile sources contributes the most to NOx reductions, accounting for 57%. The results illustrate that the focus of air pollution control in Sichuan Basin is still industrial sources. We also found that the emission reduction of NOx, PM2.5, and VOCs in Chengdu is significantly higher than that of other cities, which were about 3.4~15.4 times, 2.2~40.1 times, and 4.3~24.4 times that of other cities, respectively. In Sichuan Basin, the average reduction rate of PM2.5 concentration due to air pollution control measures was 5% on average, with the highest contributions from industry, mobile source, and dust emission control. The decrease rate in each city ranges between 1~10%, and the decreasing ratios in Dazhou (10%), Chengdu (8%), and Zigong (7%) are relatively higher. The number of premature deaths avoided due to air pollution control measures in Sichuan Basin is estimated to be 22,934. Chengdu and Dazhou have benefitted most from the air pollution control measures, with 6043 and 2713 premature deaths avoided, respectively. Our results indicate that the implementation of TYP has achieved remarkable environmental and health benefits.

Sign in / Sign up

Export Citation Format

Share Document