scholarly journals Sensitivity Analysis of the Surface Ozone and Fine Particulate Matter to Meteorological Parameters in China

2020 ◽  
Author(s):  
Zhihao Shi ◽  
Lin Huang ◽  
Jingyi Li ◽  
Qi Ying ◽  
Hongliang Zhang ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
Meteorological Parameters ◽  
Surface Ozone ◽  
Fine Particulate Matter ◽  
Absolute Humidity ◽  
Meteorological Conditions ◽  
Daily Maximum ◽  
Fine Particulate ◽  
Surface O3

Abstract. Meteorological conditions play important roles in the formation of ozone (O3) and fine particulate matter (PM2.5). China has been suffering from serious regional air pollution problems, characterized by high concentrations of surface O3 and PM2.5. In this study, the Community Multiscale Air Quality (CMAQ) model was used to quantify the sensitivity of surface O3 and PM2.5 to key meteorological parameters in different regions of China. Six meteorological parameters were perturbed to create different meteorological conditions, including temperature (T), wind speed (WS), absolute humidity (AH), planetary boundary layer height (PBLH), cloud liquid water content (CLW) and precipitation (PCP). Air quality simulations under the perturbed meteorological conditions were conducted in China in January and July of 2013. The changes in O3 and PM2.5 concentrations due to individual meteorological parameters were then quantified. T has the greatest impact on the daily maximum 8-h average O3 (O3-8 h) concentrations, which leads to O3-8 h increases by 1.7 ppb K−1 in January in Chongqing and 1.1 ppb K−1 in July in Beijing. WS, AH, and PBLH have a smaller but notable influence on O3-8 h with maximum change rates of 0.3, −0.15, and 0.14 ppb %−1, respectively. T, WS, AH, and PBLH have important effects on PM2.5 formation of in both January and July. In general, PM2.5 sensitivities are negative to T, WS, and PBLH and positive to AH in most regions of China. The sensitivities in January are much larger than in July. PM2.5 sensitivity to T, WS, PBLH, and AH in January can be up to −5 μg m−3 K−1, −3 μg m3 %−1, −1 g m−3, and +0.6 μg m−3 %−1, respectively, and in July can be up to −2 μg m−3 K−1, −0.4 μg m−3 %−1, −0.14 μg m−3 %−1, and +0.3 μg m−3 %−1, respectively. Other meteorological factors (CLW and PCP) have negligible effects on O3-8 h (less than 0.01 ppb %−1) and PM2.5 (less than 0.01 μg m−3 %−1). The results suggest that surface O3 and PM2.5 concentrations can change significantly due to changes in meteorological parameters and it is necessary to consider these effects when developing emission control strategies in different regions of China.

scholarly journals Sensitivity analysis of the surface ozone and fine particulate matter to meteorological parameters in China

2020 ◽  
Vol 20 (21) ◽  
pp. 13455-13466
Author(s):  
Zhihao Shi ◽  
Lin Huang ◽  
Jingyi Li ◽  
Qi Ying ◽  
Hongliang Zhang ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
Meteorological Parameters ◽  
Surface Ozone ◽  
Fine Particulate Matter ◽  
Great Influence ◽  
Meteorological Conditions ◽  
Daily Maximum ◽  
Fine Particulate ◽  
Surface O3

Abstract. Meteorological conditions play important roles in the formation of ozone (O3) and fine particulate matter (PM2.5). China has been suffering from serious regional air pollution problems, characterized by high concentrations of surface O3 and PM2.5. In this study, the Community Multiscale Air Quality (CMAQ) model was used to quantify the sensitivity of surface O3 and PM2.5 to key meteorological parameters in different regions of China. Six meteorological parameters were perturbed to create different meteorological conditions, including temperature (T), wind speed (WS), absolute humidity (AH), planetary boundary layer height (PBLH), cloud liquid water content (CLW) and precipitation (PCP). Air quality simulations under the perturbed meteorological conditions were conducted in China in January and July of 2013. The changes in O3 and PM2.5 concentrations due to individual meteorological parameters were then quantified. T has a great influence on the daily maximum 8 h average O3 (O3-8 h) concentrations, which leads to O3-8 h increases by 1.7 in January in Chongqing and 1.1 ppb K−1 in July in Beijing. WS, AH, and PBLH have a smaller but notable influence on O3-8 h with maximum change rates of 0.3 ppb %−1, −0.15 ppb %−1, and 0.14 ppb %−1, respectively. T, WS, AH, and PBLH have important effects on PM2.5 formation of both in January and July. In general, PM2.5 sensitivities are negative to T, WS, and PBLH and positive to AH in most regions of China. The sensitivities in January are much larger than in July. PM2.5 sensitivity to T, WS, PBLH, and AH in January can be up to −5 µg m−3 K−1, −3 µg m−3 %−1, −1 µg m−3 %−1, and +0.6 µg m−3 %−1, respectively, and in July it can be up to −2 µg m−3 K−1, −0.4 µg m−3 %−1, −0.14 µg m−3 %−1, and +0.3 µg m−3 %−1, respectively. Other meteorological factors (CLW and PCP) have negligible effects on O3-8 h (less than 0.01 ppb %−1) and PM2.5 (less than 0.01 µg m−3 %−1). The results suggest that surface O3 and PM2.5 concentrations can change significantly due to changes in meteorological parameters, and it is necessary to consider these effects when developing emission control strategies in different regions of China.

scholarly journals Impacts of East Mediterranean megacity emissions on air quality

2012 ◽  
Vol 12 (14) ◽  
pp. 6335-6355 ◽  
Author(s):  
U. Im ◽  
M. Kanakidou
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
Urban Areas ◽  
Surface Ozone ◽  
Fine Particulate Matter ◽  
Biogenic Emissions ◽  
Anthropogenic Emissions ◽  
East Mediterranean ◽  
Fine Particulate ◽  
Surface O3

Abstract. Megacities are large urban agglomerations with intensive anthropogenic emissions that have significant impacts on local and regional air quality. In the present mesoscale modeling study, the impacts of anthropogenic emissions from the Greater Istanbul Area (GIA) and the Greater Athens Area (GAA) on the air quality in GIA, GAA and the entire East Mediterranean are quantified for typical wintertime (December 2008) and summertime (July 2008) conditions. They are compared to those of the regional anthropogenic and biogenic emissions that are also calculated. Finally, the efficiency of potential country-based emissions mitigation in improving air quality is investigated. The results show that relative contributions from both cities to surface ozone (O3) and aerosol levels in the cities' extended areas are generally higher in winter than in summer. Anthropogenic emissions from GIA depress surface O3 in the GIA by ~ 60% in winter and ~ 20% in summer while those from GAA reduce the surface O3 in the GAA by 30% in winter and by 8% in summer. GIA and GAA anthropogenic emissions contribute to the fine particulate matter (PM2.5) levels inside the cities themselves by up to 75% in winter and by 50% (GIA) and ~ 40% (GAA), in summer. GIA anthropogenic emissions have larger impacts on the domain-mean surface O3 (up to 1%) and PM2.5 (4%) levels compared to GAA anthropogenic emissions (<1% for O3 and ≤2% for PM2.5) in both seasons. Impacts of regional anthropogenic emissions on the domain-mean surface pollutant levels (up to 17% for summertime O3 and 52% for wintertime fine particulate matter, PM2.5) are much higher than those from Istanbul and Athens together (~ 1% for O3 and ~ 6% for PM2.5, respectively). Regional biogenic emissions are found to limit the production of secondary inorganic aerosol species in summer up to 13% (non-sea-salt sulfate (nss-SO42−) in rural Athens) due to their impact on oxidant levels while they have negligible impact in winter. Finally, the responses to country-based anthropogenic emission mitigation scenarios inside the studied region show increases in O3 mixing ratios in the urban areas of GIA and GAA, higher in winter (~ 13% for GIA and 2% for GAA) than in summer (~ 7% for GIA and <1% for GAA). On the opposite PM2.5 concentrations decrease by up to 30% in GIA and by 20% in GAA with the highest improvements computed for winter. The emission reduction strategy also leads to domain-wide decreases in most primary pollutants like carbon monoxide (CO) or nitrogen oxides (NOx) for both seasons. The results show the importance of long range transport of pollutants for the air quality in the East Mediterranean. Thus, improvements of air quality in the East Mediterranean require coordinated efforts inside the region and beyond.

scholarly journals Meteorological controls on atmospheric particulate pollution during hazard reduction burns

2017 ◽  
Author(s):  
Giovanni Di Virgilio ◽  
Melissa Anne Hart ◽  
Ningbo Jiang
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
Fine Particulate Matter ◽  
Meteorological Conditions ◽  
Atmospheric Conditions ◽  
Hazard Reduction ◽  
Particulate Pollution ◽  
Fine Particulate ◽  
Projected Changes ◽  
Sydney Australia

Abstract. Internationally, severe wildfires are an escalating problem likely to worsen given projected changes to climate. Hazard reduction burns (HRB) are used to suppress wildfire occurrences, but they generate considerable emissions of atmospheric fine particulate matter, which depending upon prevailing atmospheric conditions, can degrade air quality. Our objectives are to improve understanding of the relationships between meteorological conditions and air quality during HRBs in Sydney, Australia. We identify the primary meteorological covariates linked to high PM2.5 pollution (particulates

scholarly journals Characteristics of Fine Particulate Matter (PM2.5) over Urban, Suburban, and Rural Areas of Hong Kong

Atmosphere ◽  
2019 ◽  
Vol 10 (9) ◽  
pp. 496 ◽  
Author(s):  
Muhammad Bilal ◽  
Janet E. Nichol ◽  
Majid Nazeer ◽  
Yuan Shi ◽  
Lunche Wang ◽  
...  
Keyword(s):  
Hong Kong ◽  
Particulate Matter ◽  
Air Quality ◽  
Rural Areas ◽  
Meteorological Parameters ◽  
Fine Particulate Matter ◽  
Residential Area ◽  
City Area ◽  
Fine Particulate ◽  
Commercial Area

In urban areas, fine particulate matter (PM2.5) associated with local vehicle emissions can cause respiratory and cardiorespiratory disease and increased mortality rates, but less so in rural areas. However, Hong Kong may be a special case, since the whole territory often suffers from regional haze from nearby mainland China, as well as local sources. Therefore, to understand which areas of Hong Kong may be affected by damaging levels of fine particulates, PM2.5 data were obtained from March 2005 to February 2009 for urban, suburban, and rural air quality monitoring stations; namely Central (city area, commercial area, and urban populated area), Tsuen Wan (city area, commercial area, urban populated, and residential area), Tung Chung (suburban and residential area), Yuen Long (urban and residential area), and Tap Mun (remote rural area). To evaluate the relative contributions of regional and local pollution sources, the study aimed to test the influence of weather conditions on PM2.5 concentrations. Thus, meteorological parameters including temperature, relative humidity, wind speed, and wind directions were obtained from the Hong Kong Observatory. The results showed that Hong Kong’s air quality is mainly affected by regional aerosol emissions, either transported from the land or ocean, as similar patterns of variations in PM2.5 concentrations were observed over urban, suburban, and rural areas of Hong Kong. Only slightly higher PM2.5 concentrations were observed over urban sites, such as Central, compared to suburban and rural sites, which could be attributed to local automobile emissions. Results showed that meteorological parameters have the potential to explain 80% of the variability in daily mean PM2.5 concentrations—at Yuen Long, 77% at Tung Chung, 72% at Central, 71% at Tsuen Wan, and 67% at Tap Mun, during the spring to summer part of the year. The results provide not only a better understanding of the impact of regional long-distance transport of air pollutants on Hong Kong’s air quality but also a reference for future regional-scale collaboration on air quality management.

scholarly journals Description and Evaluation of the Fine Particulate Matter Forecasts in the NCAR Regional Air Quality Forecasting System

Atmosphere ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 302
Author(s):  
Rajesh Kumar ◽  
Piyush Bhardwaj ◽  
Gabriele Pfister ◽  
Carl Drews ◽  
Shawn Honomichl ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
Information Dissemination ◽  
Fine Particulate Matter ◽  
Model Errors ◽  
Air Quality Forecast ◽  
Fine Particulate ◽  
Regional Air Quality ◽  
Forecasting System ◽  
Air Quality Forecasting

This paper describes a quasi-operational regional air quality forecasting system for the contiguous United States (CONUS) developed at the National Center for Atmospheric Research (NCAR) to support air quality decision-making, field campaign planning, early identification of model errors and biases, and support the atmospheric science community in their research. This system aims to complement the operational air quality forecasts produced by the National Oceanic and Atmospheric Administration (NOAA), not to replace them. A publicly available information dissemination system has been established that displays various air quality products, including a near-real-time evaluation of the model forecasts. Here, we report the performance of our air quality forecasting system in simulating meteorology and fine particulate matter (PM2.5) for the first year after our system started, i.e., 1 June 2019 to 31 May 2020. Our system shows excellent skill in capturing hourly to daily variations in temperature, surface pressure, relative humidity, water vapor mixing ratios, and wind direction but shows relatively larger errors in wind speed. The model also captures the seasonal cycle of surface PM2.5 very well in different regions and for different types of sites (urban, suburban, and rural) in the CONUS with a mean bias smaller than 1 µg m−3. The skill of the air quality forecasts remains fairly stable between the first and second days of the forecasts. Our air quality forecast products are publicly available at a NCAR webpage. We invite the community to use our forecasting products for their research, as input for urban scale (<4 km), air quality forecasts, or the co-development of customized products, just to name a few applications.

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