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Open AccessArticle

Deep Sequence Learning for Prediction of Daily NO₂ Concentration in Coastal Cities of Northern China

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Atmosphere 2023, 14(3), 467; https://doi.org/10.3390/atmos14030467 - 27 Feb 2023

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Abstract

Nitrogen dioxide (NO₂) is an important precursor of atmospheric aerosol. Forecasting urban NO₂ concentration is vital for effective control of air pollution. This paper proposes a hybrid deep learning model for predicting daily average NO₂ concentrations on the next [...] Read more.

Nitrogen dioxide (NO₂) is an important precursor of atmospheric aerosol. Forecasting urban NO₂ concentration is vital for effective control of air pollution. This paper proposes a hybrid deep learning model for predicting daily average NO₂ concentrations on the next day, based on atmospheric pollutants, meteorological data, and historical data during 2014 to 2020 in five coastal cities of Shandong peninsula, northern China. A random Forest (RF) algorithm was used to select input variables to reduce data dimensionality trained by the sequence to sequence (Seq2Seq) the model and describe how the Seq2Seq model understands each predictor variable. The hybrid model combining an RF with Seq2Seq network (RF-S2S) was evaluated and achieved a Pearson’s correlation coefficient of 0.93, a Nash–Sutcliffe coefficient (NS) of 0.79, a Root Mean Square Error (RMSE) of 5.85 µg/m³, a Mean Absolute Error (MAE) of 4.50 µg/m³, and a Mean Absolute Percentage Error (MAPE) of 20.86%. Feature selection by an RF model improves the performance of the Seq2Seq model, reducing errors by 19.7% (RMSE), 20.3% (MAE), and 29.3% (MAPE), respectively. Carbon monoxide (CO) and PM10 are two common, important features influencing the prediction of NO₂ concentrations in coastal areas of northern China. The results of RF-S2S models can capture general trends and disruptions more accurately than can long-short term memory (LSTM) models with and without feature selection. The decreasing tendency of NO₂ from 2014 to 2020 illustrated by the empirical mode decomposition (EMD) method is one important obstacle to improving the RF-S2S prediction accuracy. An EMD-based RF-S2S model could help to perform the short-term forecast of NO₂ concentrations efficiently. Full article

(This article belongs to the Special Issue Air Pollution and Climate Issues in the Coastal Atmosphere of China)

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Open AccessArticle

Impact Analysis of Super Typhoon 2114 ‘Chanthu’ on the Air Quality of Coastal Cities in Southeast China Based on Multi-Source Measurements

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Atmosphere 2023, 14(2), 380; https://doi.org/10.3390/atmos14020380 - 15 Feb 2023

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Abstract

The northward typhoon configuration along the southeast coast of China (TC_N-SEC) is one of the key circulation patterns influencing the coastal cities in southeast China (CCSE). Here, we analyzed the air quality in CCSE during the high-incidence typhoon period from 2019 [...] Read more.

The northward typhoon configuration along the southeast coast of China (TC_N-SEC) is one of the key circulation patterns influencing the coastal cities in southeast China (CCSE). Here, we analyzed the air quality in CCSE during the high-incidence typhoon period from 2019 to 2021. Multi-source measurements were carried out to explore the impact of super typhoon 2114 ‘Chanthu’ on the air quality in CCSE. The results showed that the TC_N-SEC and its surrounding weather situation had a favorable impact on the increase in pollutant concentration in CCSE, especially on the increase in O₃ concentration. From 13 September to 17 September 2021, affected by the cyclonic shear in the south of super typhoon 2114 ‘Chanthu,’ the strong wind near the ground, stable relative humidity, strong precipitation, and the significantly reduced wind speed had a substantial effect on PM₁₀, PM_2.5, SO₂, and NO₂ concentrations. Calm and light air near the ground, weak precipitation, high daily maximum temperatures, and minimum relative humidity may provide favorable meteorological conditions for the accumulation of O₃ precursors and photochemical reactions during the day, resulting in the daily peak values of O₃ exceeding 160 μg/m³. The evolution of wind, relative humidity, and boundary layer height could play an important role in the variations in PM₁₀ and PM_2.5 concentrations by influencing pollutant accumulation or diffusion. It was suggested that the atmospheric structure of horizontal stability and vertical mixing below 1500 m could play a significant role in the accumulation and vertical distribution of ozone. The results highlight the important role of typhoons in the regional environment and provide a scientific basis for further application of multi-source observation data, as well as air pollution control. Full article

(This article belongs to the Special Issue Air Pollution and Climate Issues in the Coastal Atmosphere of China)

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Open AccessArticle

Insight into Source and Evolution of Oxalic Acid: Characterization of Particulate Organic Diacids in a Mega-City, Shanghai from 2008 to 2020

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Atmosphere 2022, 13(9), 1347; https://doi.org/10.3390/atmos13091347 - 24 Aug 2022

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Abstract

Organic acids are important aerosol compositions with significant implications on particle formation, growth, acidity, phase state, and environmental impacts. Oxalic acid was found to be the most abundant particulate organic diacid in Shanghai during the study period, accounting for ~58% of the total [...] Read more.

Organic acids are important aerosol compositions with significant implications on particle formation, growth, acidity, phase state, and environmental impacts. Oxalic acid was found to be the most abundant particulate organic diacid in Shanghai during the study period, accounting for ~58% of the total dicarboxylic acids (C2–C10). Biomass burning (BB) explained a small but non-negligible fraction (less than 10%) of oxalate. Significant correlations between oxalate and sulfate indicated a potentially synergistic formation mechanism of oxalate and sulfate. In addition, meteorological factors such as ambient temperature and relative humidity were found to influence the formation of oxalate. Higher oxalate relative to inorganic particulate content was found in summer. Potential source contribution function analysis suggested that most of the oxalate observed in Shanghai was produced locally. The formation of oxalate was largely impacted by atmospheric oxidation capacity as indicated by its significant correlations with both secondary organic carbon (SOC) and sulfur oxidation ratio (SOR). The evolution of oxalate, oxalate/sulfate, oxalate/organic carbon were consistent with the emission trend of volatile organic carbons (VOCs) in recent years, indicating that oxalate may be derived from secondary oxidation of VOCs, which is further confirmed by a positive relationship between O_x and oxalate/VOCs over the study period. With a detailed characterization of oxalate in Shanghai, our study highlights the importance of regulating primary emissions, such as VOCs, as well as mitigation of atmospheric oxidation capacity in controlling air pollution in a coastal megacity. Full article

(This article belongs to the Special Issue Air Pollution and Climate Issues in the Coastal Atmosphere of China)

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Open AccessArticle

Impact of the ‘Coal-to-Natural Gas’ Policy on Criteria Air Pollutants in Northern China

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Atmosphere 2022, 13(6), 945; https://doi.org/10.3390/atmos13060945 - 10 Jun 2022

Cited by 1 | Viewed by 782

Abstract

During the last decades, China had issued a series of stringent control measures, resulting in a large decline in air pollutant concentrations. To quantify the net change in air pollutant concentrations driven by emissions, we developed an approach of determining the closed interval [...] Read more.

During the last decades, China had issued a series of stringent control measures, resulting in a large decline in air pollutant concentrations. To quantify the net change in air pollutant concentrations driven by emissions, we developed an approach of determining the closed interval of the deweathered percentage change (DPC) in the concentration of air pollutants on an annual scale, as well as the closed intervals of cumulative DPC in a year compared with that in the base year. Thus, the hourly mean mass concentrations of criteria air pollutants to determine their interannual variations and the closed intervals of their DPCs during the heating seasons from 2013 to 2019 in Qingdao (a coastal megacity) were analyzed. The seasonal mean SO₂ concentration decreased from 2013 to 2019. The seasonal mean CO, NO₂, and PM_2.5 concentrations also generally decreased from 2013 to 2017, but increased unexpectedly in 2018 (from 0.9 mg m⁻³ (CO), 42 µg m⁻³ (NO₂), and 51 µg m⁻³ (PM_2.5) in 2017 to 1.1 mg m⁻³, 48 µg m⁻³, and 64 µg m⁻³ in 2018, respectively). The closed intervals of DPC in concentrations of CO, NO₂, and PM_2.5 from the 2017 heating season (2017/2018) to the 2018 heating season (2018/2019) were obtained at (27%, 30%), (15%, 18%), and (30%, 33%), respectively. Such high positive endpoint values of the closed intervals, in contrast to their small interval lengths, indicate increased emissions of these pollutants and/or their precursors in 2018/2019 compared with 2017/2018, by minimizing the meteorological influences. The rebounds of CO, NO₂, and PM_2.5 in 2018/2019 were likely associated with a doubled increase in natural gas (NG) consumption implemented by the “coal-to-NG” project, as the total energy consumption showed little difference. Our results suggested an important role of the “coal-to-NG” project in driving concentrations of air pollutant increases in China in 2018/2019, which need integrated assessments. Full article

(This article belongs to the Special Issue Air Pollution and Climate Issues in the Coastal Atmosphere of China)

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Open AccessArticle

Investigation of Policy Relevant Background (PRB) Ozone in East Asia

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Yun Fat Lam

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Hung Ming Cheung

Atmosphere 2022, 13(5), 723; https://doi.org/10.3390/atmos13050723 - 01 May 2022

Viewed by 1150

Abstract

The concept of Policy Relevant Background (PRB) ozone has emerged in recent years to address the air quality baseline on the theoretical limits of air pollution controls. In this study, the influence of Long-range Transport (LRT) of air pollutants from North America and [...] Read more.

The concept of Policy Relevant Background (PRB) ozone has emerged in recent years to address the air quality baseline on the theoretical limits of air pollution controls. In this study, the influence of Long-range Transport (LRT) of air pollutants from North America and the effect of Stratosphere-Troposphere Transport (STT) on PRB ozone was investigated using GEOS-Chem coupled WRF-CMAQ modelling system. Four distinct seasons in 2006 were simulated to understand better the seasonal and geographical impacts of these externalities on PRB ozone over East Asia (EA). Overall, the LRT impact from North America has been found to be ~0.54 ppbv, while the maximum impacts were found at the mountain stations with values of 2.3 ppbv, 3.3 ppbv, 2.3 ppbv, and 3.0 ppbv for January, April, July, and October, respectively. In terms of PRB ozone, the effect of STT has enhanced the surface background ozone by ~3.0 ppbv, with a maximum impact of 7.8 ppbv found in the northeastern part of East Asia (near Korea and Japan). Springtime (i.e., April) has the most vital STT signals caused by relatively cold weather and unstable atmospheric condition resulting from the transition of the monsoon season. The simulated PRB ozone based on the mean values of the maximum daily 8-h average (MDA8) is 53 ppbv for spring (April) and 22 ppbv for summer (July). Up to ~1.0 ppbv and ~2.2 ppbv of MDA8 ozone were attributed to LRT and STT, respectively. Among the selected cities, Beijing and Guangzhou have received the most substantial anthropogenic enhancement in MDA8 ozone in summer, ranging from 40.0 ppbv to 56.0 ppbv. Full article

(This article belongs to the Special Issue Air Pollution and Climate Issues in the Coastal Atmosphere of China)

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Open AccessArticle

Does Ambient Secondary Conversion or the Prolonged Fast Conversion in Combustion Plumes Cause Severe PM_2.5 Air Pollution in China?

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Atmosphere 2022, 13(5), 673; https://doi.org/10.3390/atmos13050673 - 22 Apr 2022

Cited by 2 | Viewed by 1118

Abstract

The ambient formation of secondary particulate matter (ambient FSPM) is commonly recognized as the major cause of severe PM_2.5 air pollution in China. We present observational evidence showing that the ambient FSPM was too weak to yield a detectable contribution to extreme [...] Read more.

The ambient formation of secondary particulate matter (ambient FSPM) is commonly recognized as the major cause of severe PM_2.5 air pollution in China. We present observational evidence showing that the ambient FSPM was too weak to yield a detectable contribution to extreme PM_2.5 pollution events that swept northern China between 11 and 14 January 2019. Although the Community Multiscale Air Quality (CMAQ) model (v5.2) reasonably reproduced the observations in January 2019, it largely underestimated the concentrations of the PM_2.5 during the episode. We propose a novel mechanism, called the “in-fresh-stack-plume non-precipitation-cloud processing of aerosols” followed by the evaporation of semi-volatile components from the aerosols, to generate PM_2.5 at extremely high concentrations because of highly concentrated gaseous precursors and large amounts of water droplets in fresh cooling combustion plumes under poor dispersion conditions, low ambient temperature, and high relative humidity. The recorded non-precipitation-cloud processing of the aerosols in fresh stack combustion plumes normally lasts 20–30 s, but it prolongs as long as 2–5 min under cold, humid, and stagnant meteorological conditions and expectedly causes severe PM_2.5 pollution events. Regardless of the presence of the natural cloud in the planetary boundary layer during the extreme events, the fast conversion of air pollutants in water droplets and the generation of the PM_2.5 through the non-precipitation-cloud processing of aerosols always occur in fresh combustion plumes. The processing of aerosols is detectable using a nano-scan particle sizer assembled on an unmanned aerial vehicle to monitor the particle formation in stack plumes. In-fresh-stack-plume processed aerosols under varying meteorological conditions need to be studied urgently. Full article

(This article belongs to the Special Issue Air Pollution and Climate Issues in the Coastal Atmosphere of China)

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Open AccessArticle

Influence of Ambient Atmospheric Environments on the Mixing State and Source of Oxalate-Containing Particles at Coastal and Suburban Sites in North China

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Atmosphere 2022, 13(5), 647; https://doi.org/10.3390/atmos13050647 - 20 Apr 2022

Viewed by 973

Abstract

Photodegradation is a key process impacting the lifetime of oxalate in the atmosphere, but few studies investigated this process in the field due to the complex mixing and sources of oxalate. Oxalate-containing particles were measured via single-particle aerosol mass spectrometry at coastal and [...] Read more.

Photodegradation is a key process impacting the lifetime of oxalate in the atmosphere, but few studies investigated this process in the field due to the complex mixing and sources of oxalate. Oxalate-containing particles were measured via single-particle aerosol mass spectrometry at coastal and suburban sites in Qingdao, a coastal city in North China in the summer of 2016. The mixing state and influence of different ambient conditions on the source and photodegradation of oxalate were investigated. Generally, 6.3% and 12.3% of the total particles (by number) contained oxalate at coastal and suburban sites, respectively. Twelve major types of oxalate-containing particles were identified, and they were classified into three groups. Biomass burning (BB)-related oxalate–K and oxalate–carbonaceous particles were the dominant groups, respectively, accounting for 68.9% and 13.6% at the coastal site and 72.0% and 16.8% at the suburban site. Oxalate–Heavy metals (HM)-related particles represented 14.6% and 9.3% of the oxalate particles at coastal and suburban sites, respectively, which were mainly from industrial emissions (Cu-rich, Fe-rich, Pb-rich), BB (Zn-rich), and residual fuel oil combustion (V-rich). The peak area of oxalate at the coastal site decreased immediately after sunrise, while it increased during the daytime at the suburban site. However, the oxalate peak area of Fe-rich particles at both sites decreased after sunrise, indicating that iron plays an important role in oxalate degradation in both environments. The decay rates (k) of Fe-rich and BB-Fe particles at the coastal site (−0.978 and −0.859 h⁻¹, respectively), were greater than those at the suburban site (−0.512 and −0.178 h⁻¹, respectively), owing to the high-water content of particles and fewer oxalate precursors. The estimated k values of oxalate peak area for different ambient conditions were in the same order of magnitude, which can help establish or validate the future atmospheric models. Full article

(This article belongs to the Special Issue Air Pollution and Climate Issues in the Coastal Atmosphere of China)

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Open AccessArticle

Exploring the Sensitivity of Visibility to PM_2.5 Mass Concentration and Relative Humidity for Different Aerosol Types

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Atmosphere 2022, 13(3), 471; https://doi.org/10.3390/atmos13030471 - 14 Mar 2022

Cited by 2 | Viewed by 1386

Abstract

Fine particle (PM_2.5) mass concentration and relative humidity (RH) are the primary factors influencing atmospheric visibility. There are some studies focused on the complex, nonlinear relationships among visibility, PM_2.5 concentration, and RH. However, the relative contribution of the two factors [...] Read more.

Fine particle (PM_2.5) mass concentration and relative humidity (RH) are the primary factors influencing atmospheric visibility. There are some studies focused on the complex, nonlinear relationships among visibility, PM_2.5 concentration, and RH. However, the relative contribution of the two factors to visibility degradation, especially for different aerosol types, is difficult to quantify. In this study, the normalized forward sensitivity index method for identifying the dominant factors of visibility was used on the basis of the sensitivity of visibility to PM_2.5 and RH changes. The visibility variation per unit of PM_2.5 or RH was parameterized by derivation of the visibility multivariate function. The method was verified and evaluated based on 4453 valid hour data records in Tianjin, and visibility was identified as being in the RH-sensitive regime when RH was above 75%. In addition, the influence of aerosol chemical compositions on sensitivity of visibility to PM_2.5 and RH changes was discussed by analyzing the characteristics of extinction components ((NH₄)₂SO₄, NH₄NO₃, organic matter, and elemental carbon) measured in Tianjin, 2015. The result showed that the fitting equation of visibility, PM_2.5, and RH, separately for different aerosol types, further improved the accuracy of the parameterization scheme for visibility in most cases. Full article

(This article belongs to the Special Issue Air Pollution and Climate Issues in the Coastal Atmosphere of China)

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