Air Carbon Monoxide Research Articles

Carbon Monoxide Emission and Air Quality Analysis Based on an Improved Double-Weight Fuzzy Comprehensive Evaluation.

In this article, we adopt an improved double-weighted fuzzy comprehensive evaluation method to investigate the air condition of Hefei City from July 2016 to July 2021. We focus on the impact of the toxicity index, especially the impact of carbon monoxide, which is also considered in some other kinds of quality evaluation, such as water classification. Firstly, we found that with the increasing awareness of environmental protection and with the attention of the government to the quality of air in recent years, the air conditions have become better (the grades become lower). Secondly, the value of the factors, PM2.5, PM10, SO2, CO, NO2, and O3 periodically fluctuate from year to year; and the periodicity of O3 is reversed with the other factors. Finally, the monthly average analysis shows that the overall air quality is good; all the grades are I-II, except for December 2017 which has a grade III. Furthermore, the air quality in the winter (especially in December and January) is not always good.

Hemolysis contributes to anemia during long-duration space flight

Anemia in astronauts has been noted since the first space missions, but the mechanisms contributing to anemia in space flight have remained unclear. Here, we show that space flight is associated with persistently increased levels of products of hemoglobin degradation, carbon monoxide in alveolar air and iron in serum, in 14 astronauts throughout their 6-month missions onboard the International Space Station. One year after landing, erythrocytic effects persisted, including increased levels of hemolysis, reticulocytosis and hemoglobin. These findings suggest that the destruction of red blood cells, termed hemolysis, is a primary effect of microgravity in space flight and support the hypothesis that the anemia associated with space flight is a hemolytic condition that should be considered in the screening and monitoring of both astronauts and space tourists.

Design of a Low-Cost Air Quality Monitoring System Using Arduino and ThingSpeak

The impact of daily emissions of gaseous and particulate pollutants of machines and industries on human health and the environment has attracted increasing concerns. This impact has significantly led to a notable increase in mortality in the highly industrialized zones. Therefore, monitoring air quality and creating public awareness are important for a safer future, which led the governments globally to invest multi-billion in policymaking and solution stratification to address the problem. This study aims to design a real-time Internet of Things low-cost air quality monitoring system. The system utilizes air quality and carbon monoxide sensors for monitoring gaseous pollutants. Moreover, the system utilizes an Arduino Nano development board equipped with a WiFi module to effectively send readings to a ThingSpeak online channel platform for instantaneous and real-time display of air quality. The ThingSpeak uses HTTP protocols to send emails in raising awareness of poor air quality. The level of concentration is monitored graphically through channels with the help of ThingSpeak to aid remote communication. A threshold value is set. Thus, when pollutants have become unhealthy and harmful, the system trips off an alarm, and e-mail notifications are sent to the officials. The results have shown that the work was successfully implemented a design of a low-cost air quality monitoring system using Arduino and ThingSpeak, showing that an air quality system can be implemented using a low-cost technology, Arduino and ThingSpeak.

Adverse synergies between inhaled carbon monoxide and tricresyl phosphate in aircraft cabin air

Adverse synergies between inhaled carbon monoxide and tricresyl phosphate in aircraft cabin air

Tobacco-use behavior and toxicant exposure among current dual users of electronic cigarettes and tobacco cigarettes.

Electronic cigarette (e-cigarette) use continues to grow with most users reporting concurrent cigarette smoking, but few studies have focused on tobacco use and toxicant exposure among naturalistic dual-using populations. This controlled clinical laboratory study examined how dual versus exclusive use of e-cigarettes and cigarettes and no tobacco/nicotine affected behavioral, physiological, and subjective measures among current dual users. Twenty-two participants identifying as cigarette (≥ 10 cigarettes per day [CPD]) and e-cigarette (≥ 3 days/week) users of "cig-a-like" e-cigarettes completed four 5-day outpatient conditions, which differed by their own brand of products used ad libitum: (a) cigarette and e-cigarette (dual), (b) cigarette-only, (c) e-cigarette-only, and (d) no tobacco/nicotine. Primary outcomes included daily tobacco use, expired air carbon monoxide (CO), and urinary cotinine and NNAL. Linear mixed models with pairwise comparisons (Bonferroni corrected) were performed (p < .05). CPD did not differ significantly between dual and cigarette-only use, but e-cigarette use and liquid consumed increased significantly during e-cigarette-only relative to dual use. Relative to dual use, expired air CO did not differ during cigarette-only and was significantly lower during e-cigarette-only use. Urinary cotinine was significantly lower during e-cigarette-only use relative to dual and cigarette-only use, while urinary NNAL did not differ between the nicotine-containing conditions. In summary, among current dual users, e-cigarettes in combination with cigarettes did not reduce CPD relative to exclusive cigarette use or toxicant exposure relative to exclusive use of either product. However, exclusive e-cigarette use did reduce CO and cotinine, highlighting the benefits of cigarette cessation. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Engineering macromolecular nanocarriers for local delivery of gaseous signaling molecules.

In addition to being notorious air pollutants, nitric oxide (NO), carbon monoxide (CO), and hydrogen sulfide (H2S) have also been known as endogenous gaseous signaling molecules (GSMs). These GSMs play critical roles in maintaining the homeostasis of living organisms. Importantly, the occurrence and development of many diseases such as inflammation and cancer are highly associated with the concentration changes of GSMs. As such, GSMs could also be used as new therapeutic agents, showing great potential in the treatment of many formidable diseases. Although clinically it is possible to directly inhale GSMs, the precise control of the dose and concentration for local delivery of GSMs remains a substantial challenge. The development of gaseous signaling molecule-releasing molecules provides a great tool for the safe and convenient delivery of GSMs. In this review article, we primarily focus on the recent development of macromolecular nanocarriers for the local delivery of various GSMs. Learning from the chemistry of small molecule-based donors, the integration of these gaseous signaling molecule-releasing molecules into polymeric matrices through physical encapsulation, post-modification, or direct polymerization approach renders it possible to fabricate numerous macromolecular nanocarriers with optimized pharmacokinetics and pharmacodynamics, revealing improved therapeutic performance than the small molecule analogs. The development of GSMs represents a new means for many disease treatments with unique therapeutic outcomes.

The Multi-Time Scale Changes in Air Pollutant Concentrations and Its Mechanism before and during the COVID-19 Periods: A Case Study from Guiyang, Guizhou Province

The lockdown during the coronavirus disease 2019 (COVID-19) pandemic provides a scarce opportunity to assess the efficiency of air pollution mitigation. Herein, the monitoring data of air pollutants were thoroughly analyzed together with meteorological parameters to explore the impact of human activity on the multi-time scale changes of air pollutant concentrations in Guiyang city, located in Southwest China. The results show that the COVID-19 lockdown had different effects on the criteria air pollutants, i.e., PM2.5 (diameter ≤ 2.5 μm), PM10 (diameter ≤ 10 μm), sulfur dioxide (SO2), nitrogen dioxide (NO2), carbon monoxide (CO), and ozone (O3) concentrations. The lockdown caused a significant drop in NO2 concentration. During the first-level lockdown period, the NO2 concentration declined sharply by 8.41 μg·m−3 (45.68%). The decrease in NO concentration caused the “titration effect” to weaken, leading to a sharp increase in O3 concentration. Although human activities resumed partially and the “titration effect” enhanced certainly during the second-level lockdown period, the meteorological conditions became more conducive to the formation of O3 by photochemical reactions. Atmosphere oxidation was enhanced to promote the generation of secondary aerosols through gas–particle transitions, thus compensating for the reduced primary emission of PM2.5. The implication of this study is that the appropriate air pollution control policies must be initiated to suppress the secondary generation of both PM2.5 and O3.

A chemiluminescent probe for highly sensitive detection of carbon monoxide in aqueous solution and air

Carbon monoxide (CO) is a colorless and odorless gas often used as a fuel and as an important raw material for the synthesis of basic organic compounds in the chemical industry. CO affects respiration and organ coordination in organisms, and is fatal at high concentration. Due to the wide range of industrial applications and biological effects of CO, its research has received considerable attention from researchers. In this study, we designed and synthesized a chemiluminescent sensor CL-CO, which can recognize CO in the presence of palladium chloride (PdCl2), based on the Schaap’s adamantylidene-dioxetane system and allyl ether as the recognition site. In both liquid and solid states, CL-CO can recognize CO gas with high sensitivity and selectivity. This work provides a convenient tool for studying CO gas, and a new application for exploring the adamantylidene-dioxetane system.

A Dynamic Analysis of Air Pollution: Implications of Economic Growth and Renewable Energy Consumption.

This paper examines how economic growth and renewable energy consumption are associated with air pollution using a dynamic panel approach. Focusing on several major air pollutants, namely, particulate matter, sulfur dioxide, nitrogen oxide, and carbon monoxide, this paper tests the environmental Kuznets hypothesis and determines whether the use of renewable energy sources contributes to a reduction in air pollution. Data from a balanced panel of 145 countries for the period between 2000 and 2014 was used for the estimation of the dynamic panel model. The results of the dynamic panel model showed inverted U-shaped curves for the relationship between economic development and particulate matter and sulfur dioxide emissions. The results also revealed that increasing renewable energy consumption contributes to an improvement in air quality. Moreover, it was found that urbanization tends to decrease sulfur dioxide and nitrogen oxide emissions, while trade openness reduces particulate matter and carbon monoxide emissions but increases sulfur dioxide emissions.

Long-term air pollution exposure and decreased kidney function: A longitudinal cohort study in Bangkok Metropolitan Region, Thailand from 2002 to 2012

BackgroundKidney dysfunction is considered a cardiovascular risk factor. However, few longitudinal studies have examined the effects of air pollution on kidney function. We evaluated associations between long-term air pollution exposure and estimated glomerular filtration rate (eGFR) using data from a cohort of the Electricity Generating Authority of Thailand (EGAT) study in Bangkok Metropolitan Region, Thailand. MethodsThis longitudinal study included 1839 subjects (aged 52–71 years in 2002) from the EGAT1 cohort study during 2002–2012. eGFR, based on creatinine, was measured in 2002, 2007, and 2012. Annual mean concentrations of air pollutants (i.e., particulate matter with an aerodynamic diameter ≤10 μm (PM10), ozone (O3), nitrogen dioxide (NO2), sulfur dioxide (SO2), and carbon monoxide (CO)) prior to a measurement of creatinine were assessed with the ordinary kriging method. Mixed-effect linear regression models were used to assess associations between air pollutants and eGFR, while controlling for potential covariates. eGFR values are expressed as percent change per interquartile range (IQR) increments of each pollutant. ResultsLower eGFR was associated with higher concentrations of PM10 (−1.99%, 95% confidence interval (CI): −3.33, −0.63), SO2 (−4.89%, 95%CI: −6.69, −3.07), and CO (−0.97%, 95%CI: −1.96, 0.03). However, after adjusting for temperature, relative humidity, PM10, and SO2, no significant association was observed between CO and eGFR. ConclusionsOur findings support the hypothesis that long-term exposure to high concentrations of PM10 and SO2 is associated with the progression of kidney dysfunction in subjects of the EGAT cohort study.

Sandstorm and its effect on particulate matter PM 2.5, carbon monoxide, nitrogen dioxide, ozone pollutants and SARS-CoV-2 cases and deaths

Sandstorms are a natural metrological phenomenon, frequently occurring in many arid and semi-arid regions of the world. The sandstorm dust contains environmental pollutants, microorganisms including bacteria, fungi, and viruses. These events are the primary sources of air pollution and its long-distance transport. Thus, sandstorms are becoming a greater concern during the COVID-19 pandemic. Therefore, this novel study aimed to investigate the effect of a sandstorm on “environmental pollutants particulate matter (PM2.5), carbon monoxide (CO), ozone (O3), nitrogen dioxide (NO2), and day-to-day new cases and deaths due to Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection” in Riyadh, Saudi Arabia. On March 12, 2021, a sandstorm occurred in the Riyadh region, the capital city of Saudi Arabia. The data on PM 2.5, CO, NO2, and O3 were recorded three weeks before and three weeks after the onset of the sandstorm, from February 20, 2021, to March 12, 2021, and from March 13 to April 2, 2021. The daily PM2.5, CO, NO2, and O3 levels were documented from the metrological websites, and Air Quality Index-AQI, COVID-19 daily cases, and deaths were obtained from Saudi Arabia's official coronavirus website. After sandstorm, the air pollutants, CO level increased by 84.25%; PM2.5: 76.71%; O3: 40.41%; NO2: 12.03%; and SARS-CoV-2 cases increased by 33.87%. However, the number of deaths decreased by 22.39%. The sandstorm event significantly increased the air pollutants, PM2.5, CO, and O3, which were temporally associated with increased SARS-COV-2 cases. However, no significant difference was noticed in NO2 and the number of deaths after the sandstorm. The findings have an important message to health authorities to timely provide information to the public about the sandstorm and its associated health problems, including SARS-CoV-2 cases and deaths.

Association between Meniere\u2019s disease and air pollution in South Korea

Meniere’s disease is thought to be a disorder of the inner ear function, affected by genetic and environmental factors. Several recent studies have shown that air pollution could affect middle and inner ear diseases. The purpose of this study was to investigate the relationship between the Meniere’s disease occurrence and air pollution status in Korea. This study used a time-stratified case-crossover design. Hospital visit data by Meniere’s disease were collected from the Korea National Health Insurance Service-National Sample Cohort (NHIS-NSC) database. Daily air pollution data for sulfur dioxide (SO2), nitrogen dioxide (NO2), carbon monoxide (CO), ozone (O3), and particulate matter (PM10: ≤ 10 μm in diameter, and PM2.5: ≤ 2.5 μm in diameter) were collected from the National Ambient air quality Monitoring Information System (NAMIS) database. We used two-stage analysis to assess the association between degree of air pollution and the occurrence of Meniere’s disease. In the first stage, region-specific analysis was conducted to estimate the odds ratios (ORs) of Meniere’s disease risk associated with each air pollutant exposure by using conditional logistic regression for matched case–control sets in 16 regions. In the second stage, region-specific ORs from the first stage were combined and the pooled effect estimates were derived through fixed and random effect meta-analysis. Subgroup analysis was conducted for age, sex, seasonality, and urbanization of residence. In total, 29,646 (32.1% males and 67.9% females) Meniere’s disease cases were identified from Korea NHIS-NSC database between 2008 and 2015. Overall, SO2, NO2, CO, and PM10 showed significant correlation with Meniere’s disease risk at immediate lags, and weaker correlation at delayed lags, whereas O3 showed slightly negative correlation at the immediate lag (lag0) and PM2.5 did not show strong correlation (SO2: 1.04 [95% confidence interval: 1.01, 1.06]; NO2: 1.08 [1.06, 1.11]; CO: 1.04 [1.02, 1.06]; O3: 0.96 [0.93, 0.99]: statistically significant ORs at lag0 are listed). These positive and negative associations between Meniere’s disease and each air pollutant were generally stronger in the age of 40–64, female, summer (June–August) season, and urban subgroups. Our results showed that hospital visits for Meniere’s disease were associated with the measured concentrations of ambient air pollutants SO2, NO2, CO, and PM10. Further studies are required to confirm these associations and find their mechanisms.

Association of sociodemographic and environmental factors with spatial distribution of tuberculosis cases in Gombak, Selangor, Malaysia.

Tuberculosis (TB) cases have increased drastically over the last two decades and it remains as one of the deadliest infectious diseases in Malaysia. This cross-sectional study aimed to establish the spatial distribution of TB cases and its association with the sociodemographic and environmental factors in the Gombak district. The sociodemographic data of 3325 TB cases such as age, gender, race, nationality, country of origin, educational level, employment status, health care worker status, income status, residency, and smoking status from 1st January 2013 to 31st December 2017 in Gombak district were collected from the MyTB web and Tuberculosis Information System (TBIS) database at the Gombak District Health Office and Rawang Health Clinic. Environmental data consisting of air pollution such as air quality index (AQI), carbon monoxide (CO), nitrogen dioxide (NO2), sulphur dioxide (SO2), and particulate matter 10 (PM10,) were obtained from the Department of Environment Malaysia from 1st July 2012 to 31st December 2017; whereas weather data such as rainfall were obtained from the Department of Irrigation and Drainage Malaysia and relative humidity, temperature, wind speed, and atmospheric pressure were obtained from the Malaysia Meteorological Department in the same period. Global Moran’s I, kernel density estimation, Getis-Ord Gi* statistics, and heat maps were applied to identify the spatial pattern of TB cases. Ordinary least squares (OLS) and geographically weighted regression (GWR) models were used to determine the spatial association of sociodemographic and environmental factors with the TB cases. Spatial autocorrelation analysis indicated that the cases was clustered (p<0.05) over the five-year period and year 2016 and 2017 while random pattern (p>0.05) was observed from year 2013 to 2015. Kernel density estimation identified the high-density regions while Getis-Ord Gi* statistics observed hotspot locations, whereby consistently located in the southwestern part of the study area. This could be attributed to the overcrowding of inmates in the Sungai Buloh prison located there. Sociodemographic factors such as gender, nationality, employment status, health care worker status, income status, residency, and smoking status as well as; environmental factors such as AQI (lag 1), CO (lag 2), NO2 (lag 2), SO2 (lag 1), PM10 (lag 5), rainfall (lag 2), relative humidity (lag 4), temperature (lag 2), wind speed (lag 4), and atmospheric pressure (lag 6) were associated with TB cases (p<0.05). The GWR model based on the environmental factors i.e. GWR2 was the best model to determine the spatial distribution of TB cases based on the highest R2 value i.e. 0.98. The maps of estimated local coefficients in GWR models confirmed that the effects of sociodemographic and environmental factors on TB cases spatially varied. This study highlighted the importance of spatial analysis to identify areas with a high TB burden based on its associated factors, which further helps in improving targeted surveillance.

Synthesis of CuMnOx catalysts by using various precipitants for oxidation of carbon monoxide

Hopcalite (CuMnOx) is one of the best catalysts for carbon monoxide (CO) oxidation at ambient conditions. In present research work we measured the performances of various precipitants (KMnO 4 , Na 2 CO 3 and KOH) used in the CuMnOx catalysts synthesis by the co-precipitation method and calcined at 300°C temperature. The KMnO 4 precipitant used in CuMnOx catalyst has shown that the best catalytic activity, which completely oxidized CO at the lower temperature (T 100 = 83°C). The other precipitants used in CuMnOx catalyst synthesis by Na 2 CO 3 as precipitant for CO oxidation was done at (T 100 =105°C) and KOH used as precipitant in CuMnOx catalyst, which completely oxidized CO (T 100 =115°C). The calcinations conditions of precursors have huge impact on the performances of resulting catalysts for CO oxidation. The reactive calcinations (RC) conditions (1.5% CO in air) prepared CuMnOx catalysts have shown that the best catalytic activity as compared to the tradition calcinations conditions. The RC route is one of the best calcinations strategies for preparation of highly active CuMnO x catalyst for CO oxidation. • The choice of precipitant in precursor has significant effect in the designing of most suitable catalyst. • The KMnO 4 is one of the best precipitant for synthesis of highly active CuMnOx catalyst. • The reactive calcinations condition is produced highly active CuMnOx catalyst for CO oxidation.

Effect of meteorological factors and air pollutants on fractures: a nationwide population-based ecological study

ObjectiveTo determine the association of meteorological factors and air pollutants (MFAPs) with fracture and to estimate the effect size/time lag.DesignThis is a nationwide population-based ecological study from 2008 to 2017.SettingEight...

Air Quality Assessment in the State of Kuwait during 2012 to 2017

This study aimed to examine the trend of ambient air pollution (i.e., ozone (O3), nitrogen monoxide (NO), nitrogen dioxide (NO2), nitrogen oxides (NOx), sulfur dioxide (SO2), carbon monoxide (CO), benzene (C6H6) and particulate matter with an aerodynamic diameter smaller than 10 microns (PM10), and non-methane hydrocarbons (NMHCs) at 10 monitoring stations located in the main residential and industrial areas in the State of Kuwait over 6 years (2012–2017). We found that the SO2 level in industrial areas (0.065 ppm) exceeded the allowable range of SO2 in residential areas (0.030 ppm). Air pollution variables were defined by the Environmental Public Authority of Kuwait (K-EPA). In this study, integrated statistical analysis was performed to compare an established air pollution database to Kuwait Ambient Air Quality Guidelines and to determine the association between pollutants and meteorological factors. All pollutants were positively correlated, with the exception of most pollutants and PM10 and O3. Meteorological factors, i.e., the ambient temperature, wind speed and humidity, were also significantly associated with the above pollutants. Spatial distribution mapping indicated that the PM10 level remained high during the southwest monsoon (the hot and dry season), while the CO level was high during the northeast monsoon (the wet season). The NO2 and O3 levels were high during the first intermonsoon season.

Selective gas detection of H2 and CO by a single MOX-sensor

Abstract The temperature modulation of the SnO 2 -based metal oxide sensor with the addition of PdO x opened up the possibility of selective analysis of both conventionally one-component systems “hydrogen in air”, “carbon monoxide in air” and conditionally two-component system “hydrogen and carbon monoxide in air”. The aim of this work was the quantitative and qualitative analysis of gases using a single MOX sensor based on a small number of training sample concentrations in the range from 1 to 100 ppm. Gas concentrations in test experiments differed from gas concentrations in the training sample. We also studied the effect of air humidity on the error of the selective determination of gas concentrations in conventionally one- and two-component systems. To reduce multidimensional data in determining analyte concentrations, we used a specific combination of PCA regression analysis algorithms. The temperature modulation of the SnO 2 -sensor with the addition of PdO x allowed us to increase the sensor responses for concentrations from 10 to 100 ppm by about two orders of magnitude compared to the stationary temperature regime.

Air Pollution Monitoring based Fuzzy Controller with Embedded System

Air pollution has a wide and great influence on the concentration of constituents of the atmosphere, which leads to many effects such as acid rains and global warming. In order to avoid such unwanted adverse imbalances in the nature, designing an air pollution monitoring system (APMS) is very important. This paper discussed the development of an effective solution for monitoring the air pollution by making an Arduino-Based Air Pollution Monitoring System (APMS). Carbon monoxide and Carbon Dioxide concentration levels in air were measured and monitored using MQ4 and MQ7 gas sensors and Arduino atmega microcontroller. These sensors can detect many harmful gases and can be used for measuring their amount very accurately. The concentrations of CO and CO2 in particle per million (PPM) will be monitored and displayed on the LCD very easily. Based on these measurements the pollution level could be monitored, determined, and displayed. The experiments were carried out using the developed wireless APMS under various physical conditions. The results showed that the designed system collects reliable and reasonable real time pollution data. Three hour sampling time was executed in each location. One of the logical functions that are widely used is fuzzy logic. A fuzzy logic artificial intelligence for gas sensors is used which clarifies the presence as well as the concentration of CO and CO2 efficiently. Fuzzy logic will gives the decision about whether the air is polluted or unpolluted. This logic function we can process some existing data into a form of output which can be in the form of a status or state of action that will be performed by a tool. This proposed system will contribute in the construction of an APMS in the outdoor or even in the indoor environment.

Elegant cooperation of AIE, ESIPT and ICT effects into tetraarylimidazole-based fluorophore and its tuning for ratiometric detection of carbon monoxide

Carbon monoxide (CO) is an important gasotransmitter to regulate various physiological processes. Visualization of CO in situ would be conducive to uncover its physiological/pathological role. Unfortunately, most current CO fluorescent probes display aggregation-caused quenching (ACQ) characters. Herein, we reported a new fluorophore (MTPIM-HBT) coupling with aggregation-induced emission (AIE), excited-state intramolecular proton transfer (ESIPT), and intramolecular charge transfer (ICT) characteristics by attaching 2-(2′-hydroxyphenyl)benzothiazole (HBT) on methoxyl-substituted tetraarylimidazole derivative. Because of the synergistic effects, this fluorophore presented an all-purpose platform for developing ratiometric fluorescent probes with promising optimized properties. Hence, two reaction-based fluorescent probes (MTIPIM-AF-CO and MTPIM-AE-CO) for ratiometric detection and imaging of CO were rationally designed based on these unique scaffolds via one-step facilely synthesis. These probes have the merits of superior selectivity and excellent sensitivity with detection limit 47.5 nM and 32.2 nM, respectively. Significantly, the practicability of probes for visual detection of CO in air and ratiometric detection of exogenous and endogenous CO in living cells were successfully elucidated as well.

Spatial-temporal heterogeneity of air pollution and its relationship with meteorological factors in the Pearl River Delta, China

Analyzing the distribution of air pollution and its influencing factors is critical for regional air pollution prevention and control. This study takes the Pearl River Delta (PRD) as a study area, analyzes the spatial-temporal changes in air pollution (including sulfur dioxide (SO2), nitrogen dioxide (NO2), ozone (O3), carbon monoxide (CO), and particles with an aerodynamic diameter less than 10 μm (PM10) and less than 2.5 μm (PM2.5)) from 2006 to 2019, and explores the relationship between air pollution and meteorological factors. The results showed that (1) most air pollutant concentrations decreased from 2006 to 2019, with the most obvious change being the decrease in the SO2 concentration from 52.4 μg/m3 to 7.8 μg/m3. The O3 concentration increased, with a Sen's slope of 0.649 μg m−3·year−1. Air pollution was lower in coastal areas (Shenzhen and Huizhou) than in inland areas (Foshan and Zhaoqing), affected by ocean atmospheric transmission, and coastal areas had the cleanest air quality. (2) Air pollutants had high correlations with air pressure, relative humidity, precipitation, and temperature. The most serious air pollution was found in winter, which was partially due to the meteorological conditions in winter that were more unfavorable for pollutant dispersion and dilution than were the conditions in other seasons. (3) Through the wavelet coherence method, an interesting finding revealed that other air pollution and meteorological factors exhibited complex period-dependent characteristics that were significantly related to PM2.5. Areas with less air pollution were more susceptible to meteorological factors. (4) The overlapping area of the PM2.5 distribution hotspot and nighttime light hotspot was mainly in Foshan and Guangzhou, representing approximately 12.1% of the study area. Our work contributes to the literature by considering seasonal and timescale-dependent characteristics of meteorological factors affecting air pollutant emissions, and it provides new insights into recognizing regions that need to prioritize urban air pollution control based on hotspot analysis.