Research

21 pages, 8614 KiB

Open AccessArticle

Interpolation-Based Fusion of Sentinel-5P, SRTM, and Regulatory-Grade Ground Stations Data for Producing Spatially Continuous Maps of PM_2.5 Concentrations Nationwide over Thailand

by Shinhye Han, Worasom Kundhikanjana, Peeranan Towashiraporn and Dimitris Stratoulias

Atmosphere 2022, 13(2), 161; https://doi.org/10.3390/atmos13020161 - 20 Jan 2022

Cited by 13 | Viewed by 2908 | Correction

Abstract

Atmospheric pollution has recently drawn significant attention due to its proven adverse effects on public health and the environment. This concern has been aggravated specifically in Southeast Asia due to increasing vehicular use, industrial activity, and agricultural burning practices. Consequently, elevated PM_2.5 [...] Read more.

Atmospheric pollution has recently drawn significant attention due to its proven adverse effects on public health and the environment. This concern has been aggravated specifically in Southeast Asia due to increasing vehicular use, industrial activity, and agricultural burning practices. Consequently, elevated PM_2.5 concentrations have become a matter of intervention for national authorities who have addressed the needs of monitoring air pollution by operating ground stations. However, their spatial coverage is limited and the installation and maintenance are costly. Therefore, alternative approaches are necessary at national and regional scales. In the current paper, we investigated interpolation models to fuse PM_2.5 measurements from ground stations and satellite data in an attempt to produce spatially continuous maps of PM_2.5 nationwide over Thailand. Four approaches are compared, namely the inverse distance weighted (IDW), ordinary kriging (OK), random forest (RF), and random forest combined with OK (RFK) leveraging on the NO₂, SO₂, CO, HCHO, AI, and O₃ products from the Sentinel-5P satellite, regulatory-grade ground PM_2.5 measurements, and topographic parameters. The results suggest that RFK is the most robust, especially when the pollution levels are moderate or extreme, achieving an RMSE value of 7.11 μg/m³ and an R² value of 0.77 during a 10-day long period in February, and an RMSE of 10.77 μg/m³ and R² and 0.91 during the entire month of March. The proposed approach can be adopted operationally and expanded by leveraging regulatory-grade stations, low-cost sensors, as well as upcoming satellite missions such as the GEMS and the Sentinel-5. Full article

(This article belongs to the Special Issue Air Quality Management)

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23 pages, 4493 KiB

Open AccessArticle

Spatio-Temporal Characteristics and Variation Pattern of the Atmospheric Particulate Matter Concentration: A Case Study of the Beijing–Tianjin–Hebei Region, China

by Haoran Zhai, Jiaqi Yao, Guanghui Wang and Xinming Tang

Atmosphere 2022, 13(1), 120; https://doi.org/10.3390/atmos13010120 - 12 Jan 2022

Cited by 4 | Viewed by 1802

Abstract

Based on measurement data from air quality monitoring stations, the spatio-temporal characteristics of the concentrations of particles with aerodynamic equivalent diameters smaller than 2.5 and 10 μm (PM_2.5 and PM₁₀, respectively) in the Beijing–Tianjin–Hebei (BTH) region from 2015 to 2018 [...] Read more.

Based on measurement data from air quality monitoring stations, the spatio-temporal characteristics of the concentrations of particles with aerodynamic equivalent diameters smaller than 2.5 and 10 μm (PM_2.5 and PM₁₀, respectively) in the Beijing–Tianjin–Hebei (BTH) region from 2015 to 2018 were analysed at yearly, seasonal, monthly, daily and hourly scales. The results indicated that (1) from 2015 to 2018, the annual average values of PM_2.5 and PM₁₀ concentrations and the PM_2.5/PM₁₀ ratio in the study area decreased each year; (2) the particulate matter (PM) concentration in winter was significantly higher than that in summer, and the PM_2.5/PM₁₀ ratio was highest in winter and lowest in spring; (3) the PM_2.5 and PM₁₀ concentrations exhibited a pattern of double peaks and valleys throughout the day, reaching peak values at night and in the morning and valleys in the morning and afternoon; and (4) with the use of an improved sine function to simulate the change trend of the monthly mean PM concentration, the fitting R² values for PM_2.5 and PM₁₀ in the whole study area were 0.74 and 0.58, respectively. Moreover, the high-value duration was shorter, the low-value duration was longer, and the concentration decrease rate was slower than the increase rate. Full article

(This article belongs to the Special Issue Air Quality Management)

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15 pages, 4825 KiB

Open AccessArticle

Study on the Effect of an Intermittent Ventilation Strategy on Controlling Formaldehyde Concentrations in Office Rooms

by Baoping Xu, Yuekang Liu, Yanzhe Dou, Ling Hao, Xi Wang and Jianyin Xiong

Atmosphere 2022, 13(1), 102; https://doi.org/10.3390/atmos13010102 - 09 Jan 2022

Cited by 3 | Viewed by 1566

Abstract

Material emission and ventilation are two aspects influencing indoor air quality. In this study, a model predictive control (MPC) strategy is proposed for intermittent ventilation system in office buildings, to achieve a healthy indoor environment. The strategy is based on a dynamic model [...] Read more.

Material emission and ventilation are two aspects influencing indoor air quality. In this study, a model predictive control (MPC) strategy is proposed for intermittent ventilation system in office buildings, to achieve a healthy indoor environment. The strategy is based on a dynamic model for predicting emissions of volatile organic compounds (VOCs) from materials. The key parameters of formaldehyde from panel furniture in the model are obtained by an improved C-history method and large-scale chamber experiments. The effectiveness of the determined key parameters is validated, which are then used to predict the formaldehyde concentration variation and the pre-ventilation time in a typical office room. In addition, the influence of some main factors (i.e., vacant time, loading ratio, air change rate) on the pre-ventilation time is analyzed. Results indicate that the pre-ventilation time of the intermittent ventilation system ranges from several minutes to several hours. The pre-ventilation time decreases exponentially with the increase in the vacant time, the air change rate, and with the decrease in the loading ratio. When the loading ratio of the furniture is 0.30 m²/m³ and the vacant time is 100 days, the required pre-ventilation time approaches zero. Results further reveal that an air change rate of 2 h⁻¹ is the most effective means for rapid removal of indoor formaldehyde for the cases studied. The proposed strategy should be helpful for achieving effective indoor pollution control. Full article

(This article belongs to the Special Issue Air Quality Management)

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18 pages, 6631 KiB

Open AccessArticle

Emissions and Air Quality Implications of Upstream and Midstream Oil and Gas Operations in Mexico

by Elena McDonald-Buller, Gary McGaughey, John Grant, Tejas Shah, Yosuke Kimura and Greg Yarwood

Atmosphere 2021, 12(12), 1696; https://doi.org/10.3390/atmos12121696 - 17 Dec 2021

Cited by 4 | Viewed by 2903

Abstract

Mexico approved amendments to its constitution in December 2013 that initiated transformational changes to its energy sector. This study developed a 2016 bottom-up emissions inventory for volatile organic compounds (VOCs), nitrogen oxides (NO_x), sulfur dioxide (SO₂), carbon monoxide (CO), [...] Read more.

Mexico approved amendments to its constitution in December 2013 that initiated transformational changes to its energy sector. This study developed a 2016 bottom-up emissions inventory for volatile organic compounds (VOCs), nitrogen oxides (NO_x), sulfur dioxide (SO₂), carbon monoxide (CO), and fine particulate matter (PM_2.5) from upstream and midstream sector sources, including onshore and offshore well sites, gas flaring, natural gas processing facilities, and natural gas compressor stations, throughout Mexican basins. Crude oil storage tanks at onshore oil well sites and venting and fugitive sources at offshore oil production sites were the primary sources of VOC emissions. Key contributions to NO_x, CO, and PM_2.5 emissions were from internal combustion engines at offshore oil well sites and midstream operations. SO₂ emissions were associated with onshore and offshore gas flaring and boilers and process heaters at natural gas processing facilities. Application of the inventory with the Comprehensive Air Quality Model with Extensions (CAMx) indicated that oil and gas production operations could contribute to ozone and PM_2.5 concentrations in Mexican and U.S. states under favorable transport patterns. This study provides a foundation for assessing the implications of Mexico’s future energy policies on emissions and domestic and cross-border air quality and public health. Full article

(This article belongs to the Special Issue Air Quality Management)

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21 pages, 1008 KiB

Open AccessArticle

Security Challenges and Air Quality Management in India: Emissions Inventory and Forecasting Estimates

by Haroon ur Rashid Khan, Shujaat Abbas, Muhammad Khalid Anser, Abdelmohsen A. Nassani, Mohamed Haffar and Khalid Zaman

Atmosphere 2021, 12(12), 1644; https://doi.org/10.3390/atmos12121644 - 08 Dec 2021

Cited by 3 | Viewed by 2043

Abstract

The defense and peace literature have focused mainly on the military-growth nexus, with little attention paid to the environmental sustainability agenda, which is impacted by increased global arms transfers. The supply of lead-containing ammunition generates complex gas mixtures (including CO₂ emissions) and [...] Read more.

The defense and peace literature have focused mainly on the military-growth nexus, with little attention paid to the environmental sustainability agenda, which is impacted by increased global arms transfers. The supply of lead-containing ammunition generates complex gas mixtures (including CO₂ emissions) and particulates that harm the healthcare sustainability agenda. Based on the significance of the subject matter, the study uses the Indian economy as a case study, with a significant rate of arms transfers associated with higher carbon emissions. The study analyzed data from more than four decades, from 1975 to 2020. Data on arms imports, military personnel, and military expenditures are used to evaluate the ‘ammunition emissions function’. It corresponds to the three research hypotheses, namely, the ‘emissions-defense burden hypothesis’ (arms transfers increase carbon emissions), the ‘emissions-cleaner hypothesis’ (arms transfers reduce carbon emissions), and the ‘emissions-asymmetric hypothesis’ (positive and negative shocks of arms transfers either support the ‘defense burden hypothesis’ or ‘cleaner hypothesis’). The non-linear autoregressive distributed lag (NARDL) results confirmed the ’emissions-defense burden hypothesis‘ in the long run, as positive and negative shocks from arms imports increase carbon emissions. However, in the short run, positive arms imports increase carbon emissions while negative arms imports decrease carbon emissions. Furthermore, the findings supported the ’emissions-cleaner hypothesis‘ in the relationship between armed forces personnel and carbon emissions. The findings imply that the positive and negative shocks experienced by armed forces personnel reduce carbon emissions in the short and long run. Positive shocks to military spending support the ’emissions-defense burden hypothesis‘ in the short run; however, the results vanished when negative shocks to military spending supported the ’emissions-spillover hypothesis‘ (lowering military spending reduces carbon emissions and increases economic productivity) in the short and long run. The country’s unsustainable economic activities are viewed as a negative factor contributing to long-term carbon emissions increases. The negative shocks of armed forces personnel and positive arms imports would almost certainly have a significant long-term impact on carbon emissions. As a result, the ‘treadmill theory of destruction’ has been confirmed in a country. The study concludes that lead-free ammunition and managing ammunition safety are beneficial to a country’s environmental sustainability agenda. Full article

(This article belongs to the Special Issue Air Quality Management)

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19 pages, 3658 KiB

Open AccessArticle

Operational Analysis and Medium-Term Forecasting of the Greenhouse Gas Generation Intensity in the Cryolithozone

by Andrey V. Timofeev, Viktor Y. Piirainen, Vladimir Y. Bazhin and Aleksander B. Titov

Atmosphere 2021, 12(11), 1466; https://doi.org/10.3390/atmos12111466 - 05 Nov 2021

Cited by 7 | Viewed by 1432

Abstract

We proposed a new approach to solving the problem of operational analysis and medium-term forecasting of the greenhouse gas generation (CO₂, CH₄) intensity in a certain area of the cryolithozone using data from a geographically distributed network of multimodal [...] Read more.

We proposed a new approach to solving the problem of operational analysis and medium-term forecasting of the greenhouse gas generation (CO₂, CH₄) intensity in a certain area of the cryolithozone using data from a geographically distributed network of multimodal measuring stations. A network of measuring stations, capable of functioning autonomously for long periods of time, continuously generated a data flow of the CO₂, CH₄ concentration, soil moisture, and temperature, as well as a number of other parameters. These data, taking into account the type of soil, were used to build a spatially distributed dynamic model of greenhouse gas emission intensity of the permafrost area depending on the temperature and moisture of the soil. This article presented models for estimating and medium-term predicting ground greenhouse gases emission intensity, which are based on artificial intelligence methods. The results of the numerical simulations were also presented, which showed the adequacy of the proposed approach for predicting the intensity of greenhouse gas emissions. Full article

(This article belongs to the Special Issue Air Quality Management)

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10 pages, 2832 KiB

Open AccessEditor’s ChoiceArticle

Sulfur and Nitrogen Oxides in the Atmosphere of Lake Baikal: Sources, Automatic Monitoring, and Environmental Risks

by Vladimir Obolkin, Elena Molozhnikova, Maxim Shikhovtsev, Olga Netsvetaeva and Tamara Khodzher

Atmosphere 2021, 12(10), 1348; https://doi.org/10.3390/atmos12101348 - 15 Oct 2021

Cited by 14 | Viewed by 1907

Abstract

This paper analyzes the results of the automatic (in situ) recording of the regional transport of pollutants from the large regional coal-fired thermal power plants in the atmospheric boundary layer above the southern basin of Lake Baikal. Due to high stacks (about 200 [...] Read more.

This paper analyzes the results of the automatic (in situ) recording of the regional transport of pollutants from the large regional coal-fired thermal power plants in the atmospheric boundary layer above the southern basin of Lake Baikal. Due to high stacks (about 200 m), emissions from large thermal power plants rise to the altitudes of several hundreds of meters and spread over long distances from their source by tens and hundreds of kilometers. The continuous automatic monitoring of the atmosphere in the southern basin of Lake Baikal on top of the coastal hill (200 m above the lake) revealed the transport of a large number of sulfur oxides and nitrogen oxides in the form of high-altitude plumes from thermal power plants of the large cities located 70 to 100 km to the northwest of the lake (Irkutsk and Angarsk). The consequence of such transport is the increased acidity of precipitation in the southern basin of Lake Baikal and the additional influx of biogenic nitrogen compounds to the lake ecosystem. The spatial scale and possible risks of such regional transport of air pollution for the lake ecosystem require further closer study. Full article

(This article belongs to the Special Issue Air Quality Management)

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11 pages, 4503 KiB

Open AccessArticle

Air Quality in Windsor (Canada) and Impact of Regional Scale Transport

by Tianchu Zhang, Yangfan Chen, Rongtai Tan and Xiaohong Xu

Atmosphere 2021, 12(10), 1300; https://doi.org/10.3390/atmos12101300 - 06 Oct 2021

Cited by 2 | Viewed by 2362

Abstract

Air Quality Health Index (AQHI) is a scale designed in Canada to help residences understand the impact of air quality on health. This study investigated temporal variability of daily AQHI and impact of regional transport on AQHI in Windsor, Ontario, Canada from 2016 [...] Read more.

Air Quality Health Index (AQHI) is a scale designed in Canada to help residences understand the impact of air quality on health. This study investigated temporal variability of daily AQHI and impact of regional transport on AQHI in Windsor, Ontario, Canada from 2016 to 2019. The four-year average daily AQHI was 2.9, slightly below the upper limit of the low health risk level of 3. AQHI value decreased from 2.95 to 2.81 during the study period, indicating the improvement of air quality. Half of the days, AQHI were 3 regardless of season. AQHI was higher in the warm season (3.1) than in the cold season (2.6) due to more frequent moderate risk days (27%, AQHI = 4) in warm season and more frequent low risk days (42%, AQHI = 2) in the cold season. Among the three pollutants considered, O₃ was the most frequently reported dominant contributor to daily AQHI (88% of days), followed by NO₂ (12%), especially in the cold season, with small contribution from PM_2.5 (<1%). Trajectory analysis found that AQHI ≤ 3 days were closely associated with air masses from the north and northwest, whereas AQHI > 3 days were closely associated with air masses from the west and southwest. This is because northerly flows brought in clear air mass owing to less industrial facilities. Polluted air masses were transported from the south of Windsor, where several industrial states of the US were located. Directional AQHI resembles O₃ more than NO₂ or PM_2.5 concentrations do. Further improvement of AQHI in Windsor could be challenging because O₃ concentrations have continued to increase in recent years. Thus, more effective control measures to mitigate O₃ pollution are warranted to reduce its impact on human health and the environment. Full article

(This article belongs to the Special Issue Air Quality Management)

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17 pages, 5389 KiB

Open AccessArticle

Extreme Aerosol Events at Mesa Verde, Colorado: Implications for Air Quality Management

by Marisa E. Gonzalez, Jeri G. Garfield, Andrea F. Corral, Eva-Lou Edwards, Kira Zeider and Armin Sorooshian

Atmosphere 2021, 12(9), 1140; https://doi.org/10.3390/atmos12091140 - 04 Sep 2021

Cited by 3 | Viewed by 2660

Abstract

A significant concern for public health and visibility is airborne particulate matter, especially during extreme events. Of most relevance for health, air quality, and climate is the role of fine aerosol particles, specifically particulate matter with aerodynamic diameters less than or equal to [...] Read more.

A significant concern for public health and visibility is airborne particulate matter, especially during extreme events. Of most relevance for health, air quality, and climate is the role of fine aerosol particles, specifically particulate matter with aerodynamic diameters less than or equal to 2.5 micrometers (PM_2.5). The purpose of this study was to examine PM_2.5 extreme events between 1989 and 2018 at Mesa Verde, Colorado using Interagency Monitoring of Protected Visual Environments (IMPROVE) monitoring data. Extreme events were identified as those with PM_2.5 on a given day exceeding the 90th percentile value for that given month. We examine the weekly, monthly, and interannual trends in the number of extreme events at Mesa Verde, in addition to identifying the sources of the extreme events with the aid of the Navy Aerosol Analysis and Prediction (NAAPS) aerosol model. Four sources were used in the classification scheme: Asian dust, non-Asian dust, smoke, and “other”. Our results show that extreme PM_2.5 events in the spring are driven mostly by the dust categories, whereas summertime events are influenced largely by smoke. The colder winter months have more influence from “other” sources that are thought to be largely anthropogenic in nature. No weekly cycle was observed for the number of events due to each source; however, interannual analysis shows that the relative amount of dust and smoke events compared to “other” events have increased in the last decade, especially smoke since 2008. The results of this work indicate that, to minimize and mitigate the effects of extreme PM_2.5 events in the southwestern Colorado area, it is important to focus mainly on smoke and dust forecasting in the spring and summer months. Wintertime extreme events may be easier to regulate as they derive more from anthropogenic pollutants accumulating in shallow boundary layers in stagnant conditions. Full article

(This article belongs to the Special Issue Air Quality Management)

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15 pages, 4709 KiB

Open AccessArticle

Office Indoor PM and BC Level in Lithuania: The Role of a Long-Range Smoke Transport Event

by Julija Pauraite, Gediminas Mainelis, Simonas Kecorius, Agnė Minderytė, Vadimas Dudoitis, Inga Garbarienė, Kristina Plauškaitė, Jurgita Ovadnevaite and Steigvilė Byčenkienė

Atmosphere 2021, 12(8), 1047; https://doi.org/10.3390/atmos12081047 - 15 Aug 2021

Cited by 6 | Viewed by 2167

Abstract

While the impacts of climate change on wildfires and resulting air pollution levels have been observed, little is known about how indoor air filtering systems are performing under intensive smoke conditions. For this aim, particle number size distribution and concentration in a size [...] Read more.

While the impacts of climate change on wildfires and resulting air pollution levels have been observed, little is known about how indoor air filtering systems are performing under intensive smoke conditions. For this aim, particle number size distribution and concentration in a size range 0.5–18 µm and equivalent black carbon (eBC) mass concentration were measured in a modern office with a mechanical ventilation system. Measurements took place from 30 September to 6 October 2020 in the Center for Physical Sciences and Technology (FTMC) campus located in the urban background environment in Lithuania. During the measurement campaign, an intensive pollution episode, related to long-range transport wildfire smoke, was observed. The results indicated that the smoke event increased both indoor and outdoor eBC mass concentrations twice. Filters were non-selective for different eBC sources (biomass burning versus traffic) or chemical composition of carbonaceous aerosol particles (eBC versus brown carbon (BrC)). Air filtering efficiency was found to be highly dependent on particle size. During the smoke event the highest particle number concentration was observed at 2.1 µm and 1.0 µm size particles in outdoor and indoor air, respectively. Differences of indoor to outdoor ratio between event and non-event days were not significant. Because of lower removal rate for small particles, eBC had higher contribution to total PM_2.5 mass concentration in indoor air than in outdoor air. The results gained are crucial for decision-making bodies in order to implement higher-quality air-filtering systems in office buildings and, as a result, minimize potential health impacts. Full article

(This article belongs to the Special Issue Air Quality Management)

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15 pages, 4266 KiB

Open AccessArticle

Predicting the Nonlinear Response of PM_2.5 and Ozone to Precursor Emission Changes with a Response Surface Model

by James T. Kelly, Carey Jang, Yun Zhu, Shicheng Long, Jia Xing, Shuxiao Wang, Benjamin N. Murphy and Havala O. T. Pye

Atmosphere 2021, 12(8), 1044; https://doi.org/10.3390/atmos12081044 - 14 Aug 2021

Cited by 9 | Viewed by 2678

Abstract

Reducing PM_2.5 and ozone concentrations is important to protect human health and the environment. Chemical transport models, such as the Community Multiscale Air Quality (CMAQ) model, are valuable tools for exploring policy options for improving air quality but are computationally expensive. Here, [...] Read more.

Reducing PM_2.5 and ozone concentrations is important to protect human health and the environment. Chemical transport models, such as the Community Multiscale Air Quality (CMAQ) model, are valuable tools for exploring policy options for improving air quality but are computationally expensive. Here, we statistically fit an efficient polynomial function in a response surface model (pf-RSM) to CMAQ simulations over the eastern U.S. for January and July 2016. The pf-RSM predictions were evaluated using out-of-sample CMAQ simulations and used to examine the nonlinear response of air quality to emission changes. Predictions of the pf-RSM are in good agreement with the out-of-sample CMAQ simulations, with some exceptions for cases with anthropogenic emission reductions approaching 100%. NO_x emission reductions were more effective for reducing PM_2.5 and ozone concentrations than SO₂, NH₃, or traditional VOC emission reductions. NH₃ emission reductions effectively reduced nitrate concentrations in January but increased secondary organic aerosol (SOA) concentrations in July. More work is needed on SOA formation under conditions of low NH₃ emissions to verify the responses of SOA to NH₃ emission changes predicted here. Overall, the pf-RSM performs well in the eastern U.S., but next-generation RSMs based on deep learning may be needed to meet the computational requirements of typical regulatory applications. Full article

(This article belongs to the Special Issue Air Quality Management)

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15 pages, 2257 KiB

Open AccessArticle

Comparative Analysis of Three Methods for HYSPLIT Atmospheric Trajectories Clustering

by Likai Cui, Xiaoquan Song and Guoqiang Zhong

Atmosphere 2021, 12(6), 698; https://doi.org/10.3390/atmos12060698 - 30 May 2021

Cited by 21 | Viewed by 4490

Abstract

Using the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model to obtain backward trajectories and then conduct clustering analysis is a common method to analyze potential sources and transmission paths of atmospheric particulate pollutants. Taking Qingdao (N36 E120) as an example, the global data [...] Read more.

Using the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model to obtain backward trajectories and then conduct clustering analysis is a common method to analyze potential sources and transmission paths of atmospheric particulate pollutants. Taking Qingdao (N36 E120) as an example, the global data assimilation system (GDAS 1°) of days from 2015 to 2018 provided by National Centers for Environmental Prediction (NCEP) is used to process the backward 72 h trajectory data of 3 arrival heights (10 m, 100 m, 500 m) through the HYSPLIT model with a data interval of 6 h (UTC 0:00, 6:00, 12:00, and 18:00 per day). Three common clustering methods of trajectory data, i.e., K-means, Hierarchical clustering (Hier), and Self-organizing maps (SOM), are used to conduct clustering analysis of trajectory data, and the results are compared with those of the HYSPLIT model released by National Oceanic and Atmospheric Administration (NOAA). Principal Component Analysis (PCA) is used to analyze the original trajectory data. The internal evaluation indexes of Davies–Bouldin Index (DBI), Silhouette Coefficient (SC), Calinski Harabasz Index (CH), and I index are used to quantitatively evaluate the three clustering algorithms. The results show that there is little information in the height data, and thus only two-dimensional plane data are used for clustering. From the results of clustering indexes, the clustering results of SOM and K-means are better than the Hier and HYSPLIT model. In addition, it is found that DBI and I index can help to select the number of clusters, of which DBI is preferred for cluster analysis. Full article

(This article belongs to the Special Issue Air Quality Management)

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13 pages, 2309 KiB

Open AccessArticle

The Role of Physical Parameterizations on the Numerical Weather Prediction: Impact of Different Cumulus Schemes on Weather Forecasting on Complex Orographic Areas

by Giuseppe Castorina, Maria Teresa Caccamo, Franco Colombo and Salvatore Magazù

Atmosphere 2021, 12(5), 616; https://doi.org/10.3390/atmos12050616 - 11 May 2021

Cited by 7 | Viewed by 2215

Abstract

Numerical weather predictions (NWP) play a fundamental role in air quality management. The transport and deposition of all the pollutants (natural and/or anthropogenic) present in the atmosphere are strongly influenced by meteorological conditions such as, for example, precipitation and winds. Furthermore, the presence [...] Read more.

Numerical weather predictions (NWP) play a fundamental role in air quality management. The transport and deposition of all the pollutants (natural and/or anthropogenic) present in the atmosphere are strongly influenced by meteorological conditions such as, for example, precipitation and winds. Furthermore, the presence of particulate matter in the atmosphere favors the physical processes of nucleation of the hydrometeors, thus increasing the risk of even extreme weather events. In this framework of reference, the present work aimed to improve the quality of weather forecasts related to extreme events through the optimization of the weather research and forecasting (WRF) model. For this purpose, the simulation results obtained using the WRF model, where physical parametrizations of the cumulus scheme can be optimized, are reported. As a case study, we considered the extreme meteorological event recorded on 25 November 2016, which affected the whole territory of Sicily and, in particular, the area of Sciacca (Agrigento). In order, to evaluate the performance of the proposed approach, we compared the WRF model outputs with data obtained by a network of radar and weather stations. The comparison was performed through statistical methods on the basis of a “contingency table”, which allowed for ascertaining the best suited physical parametrizations able to reproduce this event. Full article

(This article belongs to the Special Issue Air Quality Management)

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15 pages, 4320 KiB

Open AccessArticle

Impact of Encouraging Vehicles to Refuel at Night on Ozone and Non-Methane Hydrocarbons (NMHCs): A Case Study in Ji’nan, China

by Wenxuan Chai, Yaolong Shi, Kun Hu, Yujing Hou, Siyuan Liang, Wentai Chen, Ming Wang and Guigang Tang

Atmosphere 2021, 12(5), 555; https://doi.org/10.3390/atmos12050555 - 26 Apr 2021

Cited by 1 | Viewed by 1615

Abstract

Gasoline evaporation is a potential source of ambient non-methane hydrocarbons (NMHCs) during summer, and thus the policy of encouraging vehicles to refuel at night has been implemented to control ground-level ozone (O₃) and NMHCs. In this study, NMHCs and trace gases [...] Read more.

Gasoline evaporation is a potential source of ambient non-methane hydrocarbons (NMHCs) during summer, and thus the policy of encouraging vehicles to refuel at night has been implemented to control ground-level ozone (O₃) and NMHCs. In this study, NMHCs and trace gases were observed online at an urban site of Ji’nan during May–July in 2019 and 2020 to assess the impact of this policy. After the implementation of this policy, the average concentration of daily maximum 8 h moving average O₃ decreased from 198 μg/m³ to 181 μg/m³. Meanwhile, the average mixing ratio of NMHCs decreased from 19.89 ppbv to 18.02 ppbv. Sources of NMHCs were then apportioned using the positive matrix factorization model. Four factors were resolved and identified, including vehicle exhaust, paint and solvents usage, gasoline evaporation, and biogenic emission. Relative contributions of these four sources were 52.5%, 20.6%, 18.3%, and 8.6%, respectively. After the implementation of this policy, relative contributions of gasoline evaporation in 1:00–4:00 increased from 20.2–22.7% to 25.4–28.2%, while those for 16:00–18:00 decreased from 16.8–18.7% to 13.9–15.7%. The non-linear relationship of O₃ with NMHCs and NO_x was investigated using a box model based on observations. Results suggest that O₃ production was mainly controlled by NMHCs. Aromatics and alkenes were the key NMHC species in O₃ formation. Furthermore, two scenarios of encouraging vehicles to refuel at night were designed to evaluate their impact on O₃. The relative decreases of O₃ peak concentrations were lower than 1%, indicating that this policy had a limited impact on O₃ during the observation period. Full article

(This article belongs to the Special Issue Air Quality Management)

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11 pages, 1538 KiB

Open AccessArticle

Quantifying Air Pollutant Emission from Agricultural Machinery Using Surveys—A Case Study in Anhui, China

by Yi Ai, Yunshan Ge, Zheng Ran, Xueyao Li, Zhibing Xu, Yangfan Chen, Xifeng Miao, Xiaohong Xu, Hongjun Mao, Zongbo Shi and Taosheng Jin

Atmosphere 2021, 12(4), 440; https://doi.org/10.3390/atmos12040440 - 29 Mar 2021

Cited by 9 | Viewed by 2290

Abstract

Diesel-powered agricultural machinery (AM) is a significant contributor to air pollutant emissions, including nitrogen oxides (NO_x) and particulate matter (PM). However, the fuel consumption and pollutant emissions from AM remain poorly quantified in many countries due to a lack of accurate [...] Read more.

Diesel-powered agricultural machinery (AM) is a significant contributor to air pollutant emissions, including nitrogen oxides (NO_x) and particulate matter (PM). However, the fuel consumption and pollutant emissions from AM remain poorly quantified in many countries due to a lack of accurate activity data and emissions factors. In this study, the fuel consumption and air pollutant emission from AM were estimated using a survey and emission factors from the literature. A case study was conducted using data collected in Anhui, one of the agricultural provinces of China. The annual active hours of AM in Anhui ranged 130 to 175 h. The estimated diesel fuel consumption by AM was 1.45 Tg in 2013, approximately 25% of the total diesel consumption in the province. The air pollutants emitted by AM were 57 Gg of carbon monoxide, 14 Gg of hydrocarbon, 74 Gg of NO_x and 5.7 Gg of PM in 2013. The NO_x and PM emissions from AM were equivalent to 17% and 22% of total on-road traffic emissions in Anhui. Among nine types of AM considered, rural vehicles are the largest contributors to fuel consumption (31%) and air emissions (33–45%). Full article

(This article belongs to the Special Issue Air Quality Management)

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16 pages, 7948 KiB

Open AccessArticle

Volatile Organic Compounds Monitored Online at Three Photochemical Assessment Monitoring Stations in the Pearl River Delta (PRD) Region during Summer 2016: Sources and Emission Areas

by Tao Zhang, Shaoxuan Xiao, Xinming Wang, Yanli Zhang, Chenglei Pei, Duohong Chen, Ming Jiang and Tong Liao

Atmosphere 2021, 12(3), 327; https://doi.org/10.3390/atmos12030327 - 04 Mar 2021

Cited by 15 | Viewed by 2242

Abstract

Volatile organic compounds (VOCs) were monitored online at three photochemical assessment monitoring stations (MDS, WQS and HGS) in the Pearl River Delta region during the summer of 2016. Measured levels of VOCs at the MDS, WQS and HGS sites were 34.78, 8.54 and [...] Read more.

Volatile organic compounds (VOCs) were monitored online at three photochemical assessment monitoring stations (MDS, WQS and HGS) in the Pearl River Delta region during the summer of 2016. Measured levels of VOCs at the MDS, WQS and HGS sites were 34.78, 8.54 and 8.47 ppbv, respectively, with aromatics and alkenes as major ozone precursors and aromatics as major precursors to secondary organic aerosol (SOA). The positive matrix factorization (PMF) model revealed that VOCs at the sites mainly came from vehicle exhaust, petrochemical industry, and solvent use. Vehicle exhaust and industrial processes losses contributed most to ozone formation potentials (OFP) of VOCs, while industrial processes losses contributed most to SOA formation potentials of VOCs. Potential source contribution function (PSCF) analysis revealed a north-south distribution for source regions of aromatics occurring at MDS with emission sources in Guangzhou mainly centered in the Guangzhou central districts, and source regions of aromatics at WQS showed an east-west distribution across Huizhou, Dongguan and east of Guangzhou, while that at HGS showed a south-north distribution across Guangzhou, Foshan, Zhaoqing and Yangjiang. This study demonstrates that multi-point high time resolution data can help resolve emission sources and locate emission areas of important ozone and SOA precursors. Full article

(This article belongs to the Special Issue Air Quality Management)

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15 pages, 4085 KiB

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Quantification of Regional Ozone Pollution Characteristics and Its Temporal Evolution: Insights from Identification of the Impacts of Meteorological Conditions and Emissions

by Leifeng Yang, Danping Xie, Zibing Yuan, Zhijiong Huang, Haibo Wu, Jinglei Han, Lijun Liu and Wenchao Jia

Atmosphere 2021, 12(2), 279; https://doi.org/10.3390/atmos12020279 - 20 Feb 2021

Cited by 11 | Viewed by 2417

Abstract

Ozone (O₃) pollution has become the major new challenge after the suppression of PM_2.5 to levels below the standard for the Pearl River Delta (PRD). O₃ can be transported between nearby stations due to its longevity, leading stations with [...] Read more.

Ozone (O₃) pollution has become the major new challenge after the suppression of PM_2.5 to levels below the standard for the Pearl River Delta (PRD). O₃ can be transported between nearby stations due to its longevity, leading stations with a similar concentration in a state of aggregation, which is an alleged regional issue. Investigations in such regional characteristics were rarely involved ever. In this study, the aggregation (reflected by the global Moran’s I index, GM), its temporal evolution, and the impacts from meteorological conditions and both local (i.e., produced within the PRD) and non-local (i.e., transported from outside the PRD) contributions were explored by spatial analysis and statistical modeling based on observation data. The results from 2007 to 2018 showed that the GM was positive overall, implying that the monitoring stations were surrounded by stations with similar ozone levels, especially during ozone seasons. State of aggregation was reinforced from 2007 to 2012, and remained stable thereafter. Further investigations revealed that GM values were independent of meteorological conditions, while closely related to local and non-local contributions, and its temporal variations were driven only by local contributions. Then, the correlation (R²) between O₃ and meteorology was identified. Result demonstrated that the westerly belonged to temperature (T) and surface solar radiation (SSR) sensitive regions and the correlation between ozone and the two became intense with time. Relative humidity (RH) showed a negative correlation with ozone in most areas and periods, whereas correlations with u and v were positive for northerly winds and negative for southerly winds. Two important key points of such investigation are that, firstly, we defined the features of ozone pollution by characterizing the temporal variations in spatial discrepancies among all stations, secondly, we highlighted the significance of subregional cooperation within the PRD and regional cooperation with external environmental organizations. Full article

(This article belongs to the Special Issue Air Quality Management)

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19 pages, 4638 KiB

Open AccessArticle

Trends and Source Contribution Characteristics of SO₂, NO_X, PM₁₀ and PM_2.5 Emissions in Sichuan Province from 2013 to 2017

by Min He, Junhui Chen, Yuming He, Yuan Li, Qichao Long, Yuhong Qiao and Kaishan Zhang

Atmosphere 2021, 12(2), 189; https://doi.org/10.3390/atmos12020189 - 30 Jan 2021

Cited by 4 | Viewed by 1785

Abstract

As one of the most populated regions in China, Sichuan province had been suffering from deteriorated air quality due to the dramatic growth of economy and vehicles in recent years. To deal with the increasingly serious air quality problem, Sichuan government agencies had [...] Read more.

As one of the most populated regions in China, Sichuan province had been suffering from deteriorated air quality due to the dramatic growth of economy and vehicles in recent years. To deal with the increasingly serious air quality problem, Sichuan government agencies had made great efforts to formulate various control measures and policies during the past decade. In order to better understand the emission control progress in recent years and to guide further control policy formulation, the emission trends and source contribution characteristics of SO₂, NO_X, PM₁₀ and PM_2.5 from 2013 to 2017 were characterized by using emission factor approach in this study. The results indicated that SO₂ emission decreased rapidly during 2013–2017 with total emission decreased by 52%. NO_X emission decreased during 2013–2015 but started to increase slightly afterward. PM₁₀ and PM_2.5 emissions went down consistently during the study period, decreased by 26% and 25%, respectively. In summary, the contribution of power plants kept decreasing, while contribution of industrial combustion remained steady in the past 5 years. The contribution of industrial processes increased for SO₂ emission, and decreased slightly for NO_X, PM₁₀ and PM_2.5 emissions. The on-road mobile sources were the largest emission contributor for NO_X, accounting for about 32–40%, and its contribution increased during 2013–2015 and then decreased. It was worth mentioning that nonroad mobile sources and natural gas fired boilers were becoming important NO_X contributors in Sichuan. Fugitive dust were the key emission sources for PM₁₀ and PM_2.5, and the contribution kept increasing in the study period. Comparison results with other inventories, satellite data and ground observations indicated that emission trends developed in this research were relatively credible. Full article

(This article belongs to the Special Issue Air Quality Management)

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15 pages, 15248 KiB

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Variations in Levels and Sources of Atmospheric VOCs during the Continuous Haze and Non-Haze Episodes in the Urban Area of Beijing: A Case Study in Spring of 2019

by Lihui Zhang, Xuezhong Wang, Hong Li, Nianliang Cheng, Yujie Zhang, Kai Zhang and Lei Li

Atmosphere 2021, 12(2), 171; https://doi.org/10.3390/atmos12020171 - 28 Jan 2021

Cited by 14 | Viewed by 2200

Abstract

To better evaluate the variations in concentration characteristics and source contributions of atmospheric volatile organic compounds (VOCs) during continuous haze days and non-haze days, hourly observations of atmospheric VOCs were conducted using a continuous on-line GC-FID (Airmo VOC GC-866) monitoring system during 1–15 [...] Read more.

To better evaluate the variations in concentration characteristics and source contributions of atmospheric volatile organic compounds (VOCs) during continuous haze days and non-haze days, hourly observations of atmospheric VOCs were conducted using a continuous on-line GC-FID (Airmo VOC GC-866) monitoring system during 1–15 March 2019, in urban areas of Beijing, China. The results showed that the total VOC concentrations during haze days and non-haze days were 59.13 ± 31.08 μg/m³ and 16.91 ± 7.19 μg/m³, respectively. However, the average O₃ concentrations during the two haze days were lower than those of non-haze days due to the extremely low concentrations at night instead of the reported lower photochemical reaction in daytime. The ratio of OH radical concentration during haze and non-haze days indicating that the rate of photochemical reaction during haze days was higher than those of non-haze days from 13:00–19:00. The stable air conditions and the local diesel emission at night were the main reasons for the decreased O₃ concentrations during haze days. Six major sources were identified by positive matrix factorization (PMF), namely, diesel exhaust, combustion, gasoline evaporation, solvent usage, gasoline exhaust, and the petrochemical industry, contributing 9.93%, 25.29%, 3.90%, 16.88%, 35.59% and 8.41%, respectively, during the whole observation period. The contributions of diesel exhaust and the petrochemical industry emissions decreased from 26.14% and 6.43% during non-haze days to 13.70% and 2.57%, respectively, during haze days. These reductions were mainly ascribed to the emergency measures that the government implemented during haze days. In contrast, the contributions of gasoline exhaust increased from 34.92% during non-haze days to 48.77% during haze days. The ratio of specific VOC species and PMF both showed that the contributions of gasoline exhaust emission increased during haze days. The backward trajectories, potential source contribution function (PSCF) and concentration weighted trajectory (CWT) showed that the air mass of VOCs during haze days was mainly affected by the short-distance transportation from the southwestern of Hebei province. However, the air mass of VOCs during non-haze days was mainly affected by the long-distance transportation from the northwest. Full article

(This article belongs to the Special Issue Air Quality Management)

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13 pages, 4611 KiB

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A Novel Hybrid Machine Learning Method (OR-ELM-AR) Used in Forecast of PM_2.5 Concentrations and Its Forecast Performance Evaluation

by Guibin Lu, Enping Yu, Yangjun Wang, Hongli Li, Dongpo Cheng, Ling Huang, Ziyi Liu, Kasemsan Manomaiphiboon and Li Li

Atmosphere 2021, 12(1), 78; https://doi.org/10.3390/atmos12010078 - 06 Jan 2021

Cited by 11 | Viewed by 2079

Abstract

Accurate forecast of PM_2.5 pollution is highly needed for the timely prevention of haze pollution in many cities suffered from frequent haze pollution. In this work, an online recurrent extreme learning machine (OR-ELM) technique with online data update was used in the [...] Read more.

Accurate forecast of PM_2.5 pollution is highly needed for the timely prevention of haze pollution in many cities suffered from frequent haze pollution. In this work, an online recurrent extreme learning machine (OR-ELM) technique with online data update was used in the forecast of PM_2.5 pollution for the first time, and a hybrid model (OR-ELM-AR) by combining autoregressive (AR) model was proposed to enhance its forecast ability to capture the variations of hourly PM_2.5 concentration. Evaluation of forecast performances in terms of pollution levels, forecast times, spatial distributions were conducted over the Yangtze River Delta (YRD) region, China. Results indicated that the OR-ELM-AR model could quickly respond to short-term changes and had better forecast performance. Therefore, the OR-ELM-AR model is a promising tool for air pollution forecast of supporting the government to take urgent actions to reduce the frequency and severity of haze pollution in cities or regions. Full article

(This article belongs to the Special Issue Air Quality Management)

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17 pages, 6448 KiB

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Spatial Characteristics of PM_2.5 Pollution among Cities and Policy Implication in the Northern Part of the North China Plain

by Yangjun Wang, Hongli Li, Jin Feng, Wu Wang, Ziyi Liu, Ling Huang, Elly Yaluk, Guibin Lu, Kasemsan Manomaiphiboon, Youguo Gong, Dramane Traore and Li Li

Atmosphere 2021, 12(1), 77; https://doi.org/10.3390/atmos12010077 - 06 Jan 2021

Cited by 5 | Viewed by 2739

Abstract

In the recent decade, the North China Plain (NCP) has been among the region’s most heavily polluted by PM_2.5 in China. For the nonattainment cities in the NCP, joint pollution control with related cities is highly needed in addition to the emission [...] Read more.

In the recent decade, the North China Plain (NCP) has been among the region’s most heavily polluted by PM_2.5 in China. For the nonattainment cities in the NCP, joint pollution control with related cities is highly needed in addition to the emission controls in their own cities. However, as the basis of decision-making, the spatial characteristics of PM_2.5 among these cities are still insufficiently revealed. In this work, the spatial characteristics among all nonattainment cities in the northern part of the North China Plain (NNCP) region were revealed based on data mining technologies including clustering, coefficient of divergence (COD), network correlation model, and terrain and meteorology analysis. The results indicate that PM_2.5 pollution of cities with a distance of less than 180 km exhibits homogeneity in the NCP region. Especially, the sub-region, composed of Xinxiang, Hebi, Kaifeng, Zhengzhou, and Jiaozuo, was strongly homogeneous and a strong correlation exists among them. Compared with spring and summer, much stronger correlations of PM_2.5 between cities were found in autumn and winter, indicating a strong need for joint prevention and control during these periods. All nonattainment cities in this region were divided into city-clusters, depending on the seasons and pollution levels to further helping to reduce their PM_2.5 concentrations effectively. Air stagnation index (ASI) analysis indicates that the strong correlations between cities in autumn were more attributed to the transport impacts than those in winter, even though there were higher PM_2.5 concentrations in winter. These results provided an insight into joint prevention and control of pollution in the NCP region. Full article

(This article belongs to the Special Issue Air Quality Management)

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17 pages, 5329 KiB

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Observation-Based Summer O₃ Control Effect Evaluation: A Case Study in Chengdu, a Megacity in Sichuan Basin, China

by Qinwen Tan, Li Zhou, Hefan Liu, Miao Feng, Yang Qiu, Fumo Yang, Wenju Jiang and Fusheng Wei

Atmosphere 2020, 11(12), 1278; https://doi.org/10.3390/atmos11121278 - 26 Nov 2020

Cited by 16 | Viewed by 2091

Abstract

Ground-level ozone (O₃), which is mainly from the photochemical reactions of NO_x and volatile organic compounds (VOCs), has become a crucial pollutant obstructing air quality improvement in China. Understanding the composition, temporal variability and source apportionment of VOCs is necessary [...] Read more.

Ground-level ozone (O₃), which is mainly from the photochemical reactions of NO_x and volatile organic compounds (VOCs), has become a crucial pollutant obstructing air quality improvement in China. Understanding the composition, temporal variability and source apportionment of VOCs is necessary for determining effective control measures to minimize VOCs and their related photochemical pollution. To provide a comprehensive analysis of VOC sources and their contributions to ozone formation in the city of Chengdu—a megacity with the highest rates of industrial and economic development in southwest China—we conducted a one-month monitoring project at three urban sites (Shuangliu, Xindu, Junpingjie; SL, XD and JPJ, respectively) along the main north–south meteorological transport channel before and during the implemented control measures. Alkanes were the dominant group at each site, contributing to around 50% of the observed total VOCs, followed by oxygen-containing VOCs (OVOCs), aromatics, halohydrocarbons and alkenes. During the control period, the mixing ratios of most measured VOC species decreased, and O₃ concentrations were down by at least 20%. VOC species experiencing the most effect from control were aromatics and OVOCs, which had higher O₃ formation reactivity. This indicated that the control policies had significant influence on reductions of reactive VOC species. We also identified VOC sources at SL and XD using positive matrix factorization (PMF) and assessed their contributions to photochemical O₃ formation by calculating the O₃ formation potential (OFP) based on mass concentrations and maximum incremental reactivity of related VOCs. Five dominant VOC sources were identified, with the highest contributions from vehicular exhaust and fuel evaporation before control, followed by solvent utilization, biogenic background and secondary formation, and industrial emissions. Contribution from vehicular exhaust was reduced the most at SL, while at XD, secondary formation VOCs decreased significantly. VOCs from vehicular and industrial emissions and solvent utilization were found to be the dominant precursors for OFPs, particularly the species of xylenes, toluene and propene. Our results therefore suggest that priority should be given to the alleviation of photochemical pollutants for effective control of O₃ formation in Chengdu. The findings from this work have important implications for formulating effective emission control policies in Chengdu. Full article

(This article belongs to the Special Issue Air Quality Management)

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