scholarly journals Studies on Photochemical Reactions of Air Pollutants. XII. Photochemical Epoxidation of Aldrin with Suspended Particulates in Air.

1994 ◽  
Vol 17 (6) ◽  
pp. 815-818 ◽  
Author(s):  
Kazuhiro NOJIMA ◽  
Chiho ISOGAMI ◽  
Hisaaki ITOH ◽  
Akihiro KAWAGUCHI
Keyword(s):  
Air Pollutants ◽  
Photochemical Reactions ◽  
Suspended Particulates

scholarly journals Observations of air composition in Brazil between the Equator and 20°s during the dry season.

1985 ◽  
Vol 15 (1-2) ◽  
pp. 77-120 ◽  
Author(s):  
P.J. Crutzen ◽  
M.T. Coffey ◽  
A.C. Delany ◽  
J. Greenberg ◽  
P. Haagenson ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Carbon Monoxide ◽  
Tropical Forests ◽  
Air Pollutants ◽  
Trace Gases ◽  
Dry Season ◽  
Photochemical Reactions ◽  
Ozone Concentrations ◽  
Air Chemistry ◽  
High Concentrations

Field measurement programs in Brazil during the dry season months of August and September in 1979 and 1980 have demonstrated the great importance of the continental tropics in global air chemistry. Especially in the mixed layer, the air composition over land is much different from that over the ocean and the land areas are clearly longe scale sources of many inportant trace gases. During the dry season much biomass, burning takes place especially in the cerrado regions leading to substantial emission of air pollutants, such as CO, NOx, N2O, CH4 and other hydrocarbons. Ozone concentrations are alsoenhanced due to photochemical reactions. Biogenic organic emissions from tropical forests play likewise an important role in the photochemistry of the atmosphere. Carbon monoxide was found to be present in high concentrations in the boundary layer of the tropical forest, but ozone concentrations were much lower than in the cerrado.

scholarly journals Pollutants and climatic conditions related to the formation of photochemical oxidants

2021 ◽  
Vol 5 (2) ◽  
pp. 001-005
Author(s):  
Shigeru Suna
Keyword(s):  
Economic Activity ◽  
Air Pollutants ◽  
Photochemical Reaction ◽  
Linear Regression Analysis ◽  
Climatic Conditions ◽  
Photochemical Reactions ◽  
Stepwise Linear Regression Analysis ◽  
Independent Variables ◽  
Hourly Data ◽  
Photochemical Oxidants

Solar radiation produces harmful compounds such as atmospheric oxidants and pharmaceutical intermediates through photochemical reactions. To clarify the variables related to the formation of photochemical oxidants, hourly data of air pollutants and climatic conditions in the Tokyo region of Japan from late May to early June 2020 were analyzed. Air pollutants, NO, NO2, CO, SO2, NMHCs and CH4, were significantly lower in 2020 than those in 2019. It seems to indicate that Japan's economic activity was suppressed by the COVID-19 emergency. Photochemical oxidants and NO were significantly higher during the day than at night. It shows the photochemical reaction is progressing during the day. Stepwise linear regression analysis revealed that relative humidity, ambient temperature, NO, CO, wind speed and NMHCs (non-methane hydrocarbons) were significant independent variables for photochemical oxidants formation.

scholarly journals Development and intercity transferability of land-use regression models for predicting ambient PM<sub>10</sub>, PM<sub>2.5</sub>, NO<sub>2</sub> and O<sub>3</sub> concentrations in northern Taiwan

2021 ◽  
Vol 21 (6) ◽  
pp. 5063-5078
Author(s):  
Zhiyuan Li ◽  
Kin-Fai Ho ◽  
Hsiao-Chi Chuang ◽  
Steve Hung Lam Yim
Keyword(s):  
Land Use ◽  
Air Pollution ◽  
Air Pollutants ◽  
Measurement Data ◽  
Air Pollutant ◽  
Population Exposure ◽  
Land Use Regression ◽  
Suspended Particulates ◽  
Model Based ◽  
Northern Taiwan

Abstract. To provide long-term air pollutant exposure estimates for epidemiological studies, it is essential to test the feasibility of developing land-use regression (LUR) models using only routine air quality measurement data and to evaluate the transferability of LUR models between nearby cities. In this study, we developed and evaluated the intercity transferability of annual-average LUR models for ambient respirable suspended particulates (PM10), fine suspended particulates (PM2.5), nitrogen dioxide (NO2) and ozone (O3) in the Taipei–Keelung metropolitan area of northern Taiwan in 2019. Ambient PM10, PM2.5, NO2 and O3 measurements at 30 fixed-site stations were used as the dependent variables, and a total of 156 potential predictor variables in six categories (i.e., population density, road network, land-use type, normalized difference vegetation index, meteorology and elevation) were extracted using buffer spatial analysis. The LUR models were developed using the supervised forward linear regression approach. The LUR models for ambient PM10, PM2.5, NO2 and O3 achieved relatively high prediction performance, with R2 values of > 0.72 and leave-one-out cross-validation (LOOCV) R2 values of > 0.53. The intercity transferability of LUR models varied among the air pollutants, with transfer-predictive R2 values of > 0.62 for NO2 and < 0.56 for the other three pollutants. The LUR-model-based 500 m × 500 m spatial-distribution maps of these air pollutants illustrated pollution hot spots and the heterogeneity of population exposure, which provide valuable information for policymakers in designing effective air pollution control strategies. The LUR-model-based air pollution exposure estimates captured the spatial variability in exposure for participants in a cohort study. This study highlights that LUR models can be reasonably established upon a routine monitoring network, but there exist uncertainties when transferring LUR models between nearby cities. To the best of our knowledge, this study is the first to evaluate the intercity transferability of LUR models in Asia.

scholarly journals 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

Atmosphere ◽  
2021 ◽  
Vol 12 (11) ◽  
pp. 1490
Author(s):  
Zhihua Su ◽  
Xin Li ◽  
Yunlong Liu ◽  
Bing Deng
Keyword(s):  
Air Pollution ◽  
Time Scale ◽  
Air Pollutants ◽  
Photochemical Reactions ◽  
Air Pollutant ◽  
Guizhou Province ◽  
Air Pollution Control ◽  
Pollutant Concentrations ◽  
Air Pollutant Concentrations ◽  
The Impact

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.

scholarly journals Studies on photochemical reaction of air pollutants. X. Identification of nitrophenols in suspended particulates.

1983 ◽  
Vol 31 (3) ◽  
pp. 1047-1051 ◽  
Author(s):  
KAZUHIRO NOJIMA ◽  
AKIHIRO KAWAGUCHI ◽  
TAKESHI OHYA ◽  
SABURO KANNO ◽  
MASAAKI HIROBE
Keyword(s):  
Air Pollutants ◽  
Photochemical Reaction ◽  
Suspended Particulates
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