scholarly journals High Resolution Chemistry Transport Modeling with the On-Line CHIMERE-WRF Model over the French Alps—Analysis of a Feedback of Surface Particulate Matter Concentrations on Mountain Meteorology

Atmosphere ◽  
2020 ◽  
Vol 11 (6) ◽  
pp. 565 ◽  
Author(s):  
Bertrand Bessagnet ◽  
Laurent Menut ◽  
Rémy Lapere ◽  
Florian Couvidat ◽  
Jean-Luc Jaffrezo ◽  
...  

Air pollution is of major concern throughout the world and the use of modeling tools to analyze and forecast the pollutant concentrations in complex orographic areas remains challenging. This work proposes an exhaustive framework to analyze the ability of models to simulate the air quality over the French Alps up to 1.2 km resolution over Grenoble and the Arve Valley. The on-line coupled suite of models CHIMERE-WRF is used in its recent version to analyze a 1 month episode in November–December 2013. As expected, an improved resolution increases the concentrations close to the emission areas and reduced the negative bias for Particulate Matter that is the usual weakness of air quality models. However, the nitrate concentrations seem overestimated with at the same time an overestimation of surface temperature in the morning by WRF. Different WRF settings found in the literature are tested to improve the results, particularly the ability of the meteorological model to simulate the strong thermal inversions in the morning. Wood burning is one of the main contributor of air pollution during the period ranging from 80 to 90% of the Organic Matter. The activation of the on-line coupling has a moderate impact on the background concentrations but surprisingly a change of Particulate Matter (PM) concentrations in the valley will affect more the meteorology nearby high altitude areas than in the valley. This phenomenon is the result of a chain of processes involving the radiative effects and the water vapor column gradients in complex orographic areas. At last, the model confirms that the surrounding glaciers are largely impacted by long range transport of desert dust. However, in wintertime some outbreaks of anthropogenic pollution from the valley when the synoptic situation changes can be advected up to the nearby high altitude areas, then deposited.

2017 ◽  
Author(s):  
Luke D. Schiferl ◽  
Colette L. Heald

Abstract. Ensuring global food security requires a comprehensive understanding of environmental pressures on food production, including the impacts of air quality. Surface ozone damages plants and decreases crop production; this effect has been extensively studied. In contrast, the presence of particulate matter (PM) in the atmosphere can be beneficial to crops given that enhanced light scattering leads to a more even and efficient distribution of photons which can outweigh total incoming radiation loss. This study quantifies the impacts of ozone and PM on the global production of maize, rice, and wheat in 2010 and 2050. We show that accounting for the growing season of these crops is an important factor in determining their air pollution exposure. We find that the effect of PM can offset much, if not all, of the reduction in yield associated with ozone damage. Assuming maximum sensitivity to PM, the current (2010) global net impact of air quality on crop production is positive (+6.0 %, +0.5 %, and +4.9 % for maize, wheat, and rice, respectively). Future emissions scenarios indicate that attempts to improve air quality can result in a net negative effect on crop production in areas dominated by the PM effect. However, we caution that the uncertainty in this assessment is large due to the uncertainty associated with crop response to changes in diffuse radiation; this highlights that more detailed physiological study of this response for common cultivars is crucial.


Author(s):  
Eric S. Coker ◽  
Ssematimba Joel ◽  
Engineer Bainomugisha

Background: There are major air pollution monitoring gaps in sub-Saharan Africa. Developing capacity in the region to conduct air monitoring in the region can help estimate exposure to air pollution for epidemiology research. The purpose of our study is to develop a land use regression (LUR) model using low-cost air quality sensors developed by a research group in Uganda (AirQo). Methods: Using these low-cost sensors, we collected continuous measurements of fine particulate matter (PM2.5) between May 1, 2019 and February 29, 2020 at 22 monitoring sites across urban municipalities of Uganda. We compared average monthly PM2.5 concentrations from the AirQo sensors with measurements from a BAM-1020 reference monitor operated at the US Embassy in Kampala. Monthly PM2.5 concentrations were used for LUR modeling. We used eight Machine Learning (ML) algorithms and ensemble modeling; using 10-fold cross validation and root mean squared error (RMSE) to evaluate model performance. Results: Monthly PM2.5 concentration was 60.2 µg/m3 (IQR: 45.4-73.0 µg/m3; median= 57.5 µg/m3). For the ML LUR models, RMSE values ranged between 5.43 µg/m3 - 15.43 µg/m3 and explained between 28% and 92% of monthly PM2.5 variability. Generalized additive models explained the largest amount of PM2.5 variability (R2=0.92) and produced the lowest RMSE (5.43 µg/m3) in the held-out test set. The most important predictors of monthly PM2.5 concentrations included monthly precipitation, major roadway density, population density, latitude, greenness, and percentage of households using solid fuels. Conclusion: To our knowledge, ours is the first study to model the spatial distribution of urban air pollution in sub-Saharan Africa using air monitors developed from the region itself. Non-parametric ML for LUR modeling performed with high accuracy for prediction of monthly PM2.5 levels. Our analysis suggests that locally produced low-cost air quality sensors can help build capacity to conduct air pollution epidemiology research in the region.


Időjárás ◽  
2021 ◽  
Vol 125 (4) ◽  
pp. 625-646
Author(s):  
Zita Ferenczi ◽  
Emese Homolya ◽  
Krisztina Lázár ◽  
Anita Tóth

An operational air quality forecasting model system has been developed and provides daily forecasts of ozone, nitrogen oxides, and particulate matter for the area of Hungary and three big cites of the country (Budapest, Miskolc, and Pécs). The core of the model system is the CHIMERE off-line chemical transport model. The AROME numerical weather prediction model provides the gridded meteorological inputs for the chemical model calculations. The horizontal resolution of the AROME meteorological fields is consistent with the CHIMERE horizontal resolution. The individual forecasted concentrations for the following 2 days are displayed on a public website of the Hungarian Meteorological Service. It is essential to have a quantitative understanding of the uncertainty in model output arising from uncertainties in the input meteorological fields. The main aim of this research is to probe the response of an air quality model to its uncertain meteorological inputs. Ensembles are one method to explore how uncertainty in meteorology affects air pollution concentrations. During the past decades, meteorological ensemble modeling has received extensive research and operational interest because of its ability to better characterize forecast uncertainty. One such ensemble forecast system is the one of the AROME model, which has an 11-member ensemble where each member is perturbed by initial and lateral boundary conditions. In this work we focus on wintertime particulate matter concentrations, since this pollutant is extremely sensitive to near-surface mixing processes. Selecting a number of extreme air pollution situations we will show what the impact of the meteorological uncertainty is on the simulated concentration fields using AROME ensemble members.


2021 ◽  
Author(s):  
Rema Hanna ◽  
Bridget Hoffmann ◽  
Paulina Oliva ◽  
Jake Schneider

Male, younger, and higher-income respondents as well as those who perceived high pollution in recent days showed greater willingness to pay for SMS air quality alerts. Willingness to pay was uncorrelated with actual recent high pollution. Recipients of SMS alerts indicated having received air pollution information via SMS, along with reporting a high-pollution day in the past week and having stayed indoors on the most recent day they perceived pollution to be high. However, alert recipients were not more accurate in identifying which specific days had high pollution than other respondents. Households that received a free N95 mask were more likely to report utilizing a mask with a filter during the past two weeks but not more likely to report using a mask with a filter on the specific days with high particulate matter.


2016 ◽  
Author(s):  
Jianlin Hu ◽  
Jianjun Chen ◽  
Qi Ying ◽  
Hongliang Zhang

Abstract. China has been experiencing severe air pollution in recent decades. Although ambient air quality monitoring network for criteria pollutants has been constructed in over 100 cities since 2013 in China, the temporal and spatial characteristics of some important pollutants, such as particulate matter (PM) components, remain unknown, limiting further studies investigating potential air pollution control strategies to improve air quality and associating human health outcomes with air pollution exposure. In this study, a yearlong (2013) air quality simulation using the Weather Research & Forecasting model (WRF) and the Community Multi-scale Air Quality model (CMAQ) was conducted to provide detailed temporal and spatial information of ozone (O3), PM2.5 total and chemical components. Multi-resolution Emission Inventory for China (MEIC) was used for anthropogenic emissions and observation data obtained from the national air quality monitoring network were collected to validate model performance. The model successfully reproduces the O3 and PM2.5 concentrations at most cities for most months, with model performance statistics meeting the performance criteria. However, over-prediction of O3 generally occurs at low concentration range while under-prediction of PM2.5 happens at low concentration range in summer. Spatially, the model has better performance in Southern China than in Northern, Central and Sichuan basin. Strong seasonal variations of PM2.5 exist and wind speed and direction play important roles in high PM2.5 events. Secondary components have more boarder distribution than primary components. Sulfate (SO42−), nitrate (NO3−), ammonium (NH4+), and primary organic aerosol (POA) are the most important PM2.5 components. All components have the highest concentrations in winter except secondary organic aerosol (SOA). This study proves the ability of CMAQ model in reproducing severe air pollution in China, identifies the directions where improvements are needed, and provides information for human exposure to multiple pollutants for assessing health effects.


Energies ◽  
2020 ◽  
Vol 13 (15) ◽  
pp. 3876 ◽  
Author(s):  
Zhe Liu ◽  
Xueli Chen ◽  
Jinyang Cai ◽  
Tomas Baležentis ◽  
Yue Li

Air pollution has become an increasingly serious environmental problem in China. Especially in winter, the air pollution in northern China becomes even worse due to winter heating. The “coal to gas” policy, which uses natural gas to replace coal in the heating system in winter, was implemented in Beijing in the year 2013. However, the effects of this policy reform have not been examined. Using a panel dataset of 16 districts in Beijing, this paper employs a first difference model to examine the impact of the “coal to gas” policy on air quality. Strong evidence shows that the “coal to gas” policy has significantly improved the air quality in Beijing. On average, the “coal to gas” policy reduced sulfur dioxide (SO2), nitrogen dioxide (NO2), particulate matter smaller than 10 µm (PM10), particulate matter smaller than 2.5 µm (PM2.5) and carbon monoxide (CO) by 12.08%, 4.89%, 13.07%, 11.94% and 11.10% per year, respectively. We find that the “coal to gas” policy is more effective in areas with less energy use efficiency. The finding of this paper suggests that the government should continue to implement the “coal to gas” policy, so as to alleviate the air pollution in Beijing, China.


Author(s):  
Luisa T. Molina ◽  
Tong Zhu ◽  
Wei Wan ◽  
Bhola R. Gurjar

Megacities (metropolitan areas with populations over 10 million) and large urban centers present a major challenge for the global environment. Transportation, industrial activities, and energy demand have increased in megacities due to population growth and unsustainable urban development, leading to increasing levels of air pollution that subject the residents to the health risks associated with harmful pollutants, and impose heavy economic and social costs. Although much progress has been made in reducing air pollution in developed and some developing world megacities, there are many remaining challenges in achieving cleaner and breathable air for their residents. As centers of economic growth, scientific advancement, and technology innovation, however, these urban settings also offer unique opportunities to capitalize on the multiple benefits that can be achieved by optimizing energy use, reducing atmospheric pollution, minimizing greenhouse gas emissions, and bringing many social benefits. Realizing such benefits will, however, require strong and wide-ranging institutional cooperation, public awareness, and multi-stakeholder involvement. This is especially critical as the phenomenon of urbanization continues in virtually all countries of the world, and more megacities will be added to the world, with the majority of them located in developing countries. The air quality and emission mitigation strategies of eight megacities—Mexico City, Beijing, Shanghai, Shenzhen, Chengdu, Delhi, Kolkata, and Mumbai—are presented as examples of the environmental challenges experienced by large urban centers. While these megacities share common problems of air pollution due to the rapid growth in population and urbanization, each city has its own unique circumstances—geographical location, meteorology, sources of emissions, human and financial resources, and institutional capacity—to address them. Nevertheless, the need for an integrated multidisciplinary approach to air quality management is the same. Mexico City’s air pollution problem was considered among the worst in the world in the 1980s due to rapid population growth, uncontrolled urban development, and energy consumption. After three decades of implementing successive comprehensive air quality management programs that combined regulatory actions with technological change and were based on scientific, technical, social, and political considerations, Mexico City has made significant progress in improving its air quality; however, ozone and particulate matter are still at levels above the respective Mexican air quality standards. Beijing, Shanghai, Shenzhen, and Chengdu are microcosms of megacities in the People’s Republic of China, with rapid socioeconomic development, expanding urbanization, and swift industrialization since the era of reform and opening up began in the late 1970s, leading to severe air pollution. In 2013, the Chinese government issued the Action Plan for Air Pollution Prevention and Control. Through scientific research and regional coordinated air pollution control actions implemented by the Chinese government authority, the concentration of atmospheric pollutants in several major cities has decreased substantially. About 20% of total megacities’ populations in the world reside in Indian megacities; the population is projected to increase, with Delhi becoming the largest megacity by 2030. The increased demands of energy and transportation, as well as other sources such as biomass burning, have led to severe air pollution. The air quality trends for some pollutants have reduced as a result of emissions control measures implemented by the Indian government; however, the level of particulate matter is still higher than the national standards and is one of the leading causes of premature deaths. The examples of the eight cities illustrate that although most air pollution problems are caused by local or regional sources of emissions, air pollutants are transported from state to state and across international borders; therefore, international coordination and collaboration should be strongly encouraged. Based on the available technical-scientific information, the regulations, standards, and policies for the reduction of polluting emissions can be formulated and implemented, which combined with adequate surveillance, enforcement, and compliance, would lead to progressive air quality improvement that benefits the population and the environment. The experience and the lessons learned from the eight megacities can be valuable for other large urban centers confronting similar air pollution challenges.


2019 ◽  
Vol 11 (10) ◽  
pp. 2728 ◽  
Author(s):  
Shulin Wang ◽  
Yongtao Li ◽  
Mahfuzul Haque

Environmental pollution, especially air pollution, is an alarming issue for the public, which is extensively debated among academic scholars. During the winter heating season, “smog” has become somewhat a normal phenomenon to local residents’ livelihood in northern China. Based on the daily air pollution data of regional cities in China from 2014 to 2016, and using a regression discontinuity design (RDD), the study finds that winter heating makes the air quality worse in the northern part of China. With the start of the winter heating, it increases the Air Quality Index (AQI) by 10.4%, particulate matter smaller than 10 μm (PM10) by 9.77%, particulate matter smaller than 2.5 μm (PM2.5) by 17.25%, CO by 9.84%, NO2 by 5.23%, and SO2 by 17.1%. Furthermore, dynamic changes demonstrate that air quality has gradually improved due to a series of heating policy changes implemented by the central government in recent years. Specifically, from 2014 to 2016, major indicators measuring the air pollution decrease dramatically, such as AQI by 92.36%, PM10 by 91.24%, PM2.5 by 84.06%, CO by 70.97%, NO2 by 52.76%, and SO2 by 17.15%.


Author(s):  
Janis Kleperis ◽  
Gunars Bajars ◽  
Ingrida Bremere ◽  
Martins Menniks ◽  
Arturs Viksna ◽  
...  

Air Quality in Riga and Its Improvement Options Air quality in the city of Riga is evaluated from direct monitoring results and from accounting registered air pollutants in the city. It is concluded that from all air polluting substances listed in the European Commission directives, only nitrogen dioxide NO2 and particulate matter PM10 exceed the limits. In assessing the projected measures to improve air quality in Riga, it can be concluded that the implementation of cleaner fuels and improvements in energy efficiency of household and industrial sectors will decrease particle pollution, but measures in the transport sector will also contribute to reducing air pollution from nitrogen oxides.


2013 ◽  
Vol 173 ◽  
pp. 255-256 ◽  
Author(s):  
H. Bravo Alvarez ◽  
R. Sosa Echeverria ◽  
P. Sanchez Alvarez ◽  
S. Krupa

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