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Four Years of National Clean Air Programme (NCAP) in Indian cities: Assessment of the impact on surface ozone during the period 2018–2022
Abstract
There is a significant increase in ozone at the surface and troposphere due to growing population, industrialization and urbanization. The initiation of National Clean Air Programme (NCAP) in 2019 marked a turning point in addressing air pollution in Indian cities. The Central Pollution Control Board (CPCB) ground-based measurements show a reduction in number of days with continuous exposure to 8 h surface ozone (MDA-8) exceeding 100 ppb since the implementation of NCAP. For instance, cities such as Visakhapatnam and Tirupati reported zero days of MDA-8 ozone surpassing 100 ppb in 2022. Also, a substantial reduction is observed in the frequency of MDA-8 ozone exceeding the 100 ppb threshold at other stations. The NO2 and PM2.5 measurements from CPCB show a decreasing trend at most stations, whereas satellite-based HCHO and NO2 measurements show negative (0–0.004 mol m−2 month−1) and positive (0–0.02 m−2 month−1) trends, respectively, during the period of 2019–2022. Therefore, although the implementation of NCAP is oriented towards reducing PM10 concentrations, it is also proven to be effective in curbing ozone pollution in most cities of India. This study, therefore, suggests to continue the efforts of NCAP and to implement tailored regulations for reducing ozone pollution in cities with high pollution.
... Cities like Noida, Ghaziabad and Moradabad situated in western UP are also grappling with serious environmental issues. However, significant PM 10 reductions are forecasted for cities like Bareilly (70%), Raebareli (58%), and Moradabad (55%), with Gorakhpur and Prayagraj expected to see increases of 50% and 32%, respectively. 7 Further analysis of air quality management in Uttar Pradesh highlighted that action plans prioritize road dust and construction activities (24% weightage). ...
... 9 Central Pollution Control Board (CPCB) data indicates a reduction in NO 2 and PM 2.5 levels at several locations, and satellite data for Visakhapatnam and Tirupati from 2019 to 2022. 10 A study in Kota city from January to March 2020 measured respirable suspended particulate matter, revealing that SO 2 and NO 2 levels remained within AQI limits (80 μg/m³), though PM 10 concentrations exceeded the safe limit of 100 μg/m³, underscoring the need for continued regulatory action and monitoring. 11 The selection of Kota city for this study underscores its importance as a major educational hub, drawing students from across India. ...
... [18][19][20] This study focuses on assessing the effectiveness of NCAP in Kota, Rajasthan, particularly in minimizing the air pollution and its associated health impacts. It aims to analyze trends in key pollutants, including PM 10 A limitation of this study is that its relatively short duration may not capture the full, long-term effectiveness of NCAP measures. Additionally, external factors, including the COVID-19 pandemic, could introduce variability by impacting pollution levels and health outcomes. ...
The clean air plan in India involves a set of rules, policies, and initiatives targeted at improving the air quality and public health by way of decreasing emissions from various sources. The study aims to evaluate the impact of National Clean Air Program (NCAP) on lowering air pollution levels and improving public health outcomes in Kota city, Rajasthan, highlighting progress, challenges, and the need for sustained emission control efforts. Kota's selection for this study highlights its significance as an educational hub, attracting students from all over India. The rapid population growth and increased vehicle emissions in the city cause adverse impacts on air quality. Improving air quality will not only enhance the health of residents and students but also contribute to a more conducive learning environment. The action plan of NCAP involves enforcing the construction and demolition waste management rules 2016, implementing emission control measures like water sprinkling and covered transport for construction activities, and extensive campaigns against open burning of biomass and waste. It also includes regular checks on industrial emissions, proper waste collection and disposal, and mandatory green belt development in residential areas. It employs a mixed-method approach, combining air quality monitoring data collected from the Central and State Pollution Control Boards from 2014 to 2023. It also examines trends in key pollutants, including NO2, SO2, and PM10, and analyzes the effect of regulatory measures such as emission controls and waste management rules. The study reveals a decreasing trend in NO2 (nitrogen dioxide) levels in Kota city, Rajasthan from 35.35 µg/m³ to 29.90 µg/m³ during 2014 to 2023, showing a significant drop during the COVID-19 lockdown. Similarly, PM10 (particulate matter) levels peaked at 153.28 µg/m³ in 2018 but saw a significant reduction to104.80 µg/m³ by 2020, indicating an improvement in air quality. However, SO2 (sulfur dioxide) concentrations slightly increased in 2019-2023 compared to 2014-2018. The air quality index (AQI) improved modestly but frequently surpassed 100, indicating hazardous air quality for vulnerable populations. The study concludes that while the NCAP in India has significantly improved air quality, challenges remain, with NO2 levels rebounding post-COVID-19 lockdown and persistent high particulate matter levels. It is recommended to ensure stricter enforcement of emission control measures, enhanced monitoring systems, and public awareness campaigns. Future work should focus on the long-term health impacts of particulate matter and strategies to achieve sustained air quality improvements in high-risk regions.
... According to previously published studies [99,100], the daily mean ground-level ozone concentrations were negatively correlated with the daily average concentrations of particulate matter PM2.5 and PM10 for all of the investigated cities, namely PM2. The risk of infection from pathogen-bearing particulate matter and other aerosols is very high in urban agglomerated regions. ...
... Temporal distribution of the daily mean ground level of ozone concentrations in the investigated metropolises during 1 January 2020-15 June 2020.According to previously published studies[99,100], the daily mean ground-level ozone concentrations were negatively correlated with the daily average concentrations of particulate matter PM2.5 and PM10 for all of the investigated cities, namely PM2.5 [(r = −0.64 with p < 0.01) for Milan; (r = −0.38 with p < 0.01) for Madrid; (r = −0.28 with p < 0.01) for London; (r = −0.48 with p < 0.01) for Wuhan] and PM10 [(r = −0.65 with p < 0.01) for Milan; r = (−0.48 with p < 0.01,) for Madrid; r = (−0.28 with p < 0.01) for London; (r = −0.37 with p < 0.01) for Bucharest; and (r = −0.29 with p < 0.01} for Wuhan]. ...
This paper investigates the impact of air quality and climate variability during the first wave of COVID-19 associated with accelerated transmission and lethality in Wuhan in China and four European metropolises (Milan, Madrid, London, and Bucharest). For the period 1 January–15 June 2020, including the COVID-19 pre-lockdown, lockdown, and beyond periods, this study used a synergy of in situ and derived satellite time-series data analyses, investigating the daily average inhalable gaseous pollutants ozone (O3), nitrogen dioxide (NO2), and particulate matter in two size fractions (PM2.5 and PM10) together with the Air Quality Index (AQI), total Aerosol Optical Depth (AOD) at 550 nm, and climate variables (air temperature at 2 m height, relative humidity, wind speed, and Planetary Boundary Layer height). Applied statistical methods and cross-correlation tests involving multiple datasets of the main air pollutants (inhalable PM2.5 and PM10 and NO2), AQI, and aerosol loading AOD revealed a direct positive correlation with the spread and severity of COVID-19. Like in other cities worldwide, during the first-wave COVID-19 lockdown, due to the implemented restrictions on human-related emissions, there was a significant decrease in most air pollutant concentrations (PM2.5, PM10, and NO2), AQI, and AOD but a high increase in ground-level O3 in all selected metropolises. Also, this study found negative correlations of daily new COVID-19 cases (DNCs) with surface ozone level, air temperature at 2 m height, Planetary Boundary PBL heights, and wind speed intensity and positive correlations with relative humidity. The findings highlight the differential impacts of pandemic lockdowns on air quality in the investigated metropolises.
... Our study highlighted the need for the involvement of grassroots/frontline-level workers. In India, the NCAP was launched in 2019 with the aim to reduce the concentration of PM2.5 and PM10 by 20-30% by 2024 taking 2017 as the base year [17]. A study by Kumari mentions the need to decentralize the said NCAP and strengthen grassroots-level workers and frontline workers for more effective implementation [18]. ...
Background: Air pollution poses a significant threat to global public health, contributing to high rates of mortality and morbidity. India, home to the world's largest population of children, is particularly affected. This study aims to identify effective strategies to mitigate the adverse health impacts of air pollution on this
vulnerable group.
Material and methods: The study utilized directed content analysis using a deductive approach and purposeful sampling to carry out in-depth interviews with researchers, academicians, paediatricians, public health experts, and climate change experts from different organizations in India. In total, 17 interviews were conducted over two months in March and April 2024 until data saturation was reached.
Results: A total of 29 subcategories were extracted. The main sub-categories include strategies for reducing indoor emissions and multisectoral emission reduction, strategies to reduce exposure at home, schools and transit, strategies for public awareness, effective communication, health sector communication and
awareness, and raising awareness by frontline workers and educational institutions, strategies for capacity building of health sector and frontline stakeholders, strategies for building research and knowledge translation, strategies for vertical and horizontal collaboration, strategies for child-centric policies, school closure policies, fiscal policies, comprehensive policymaking, sectoral policymaking, advocacy in policymaking, strategies for monitoring, and strategies for mother and child health.
Conclusions: The results of this study indicate that mitigating the adverse health impacts of pollution for children would entail a multi-pronged approach encompassing effective communication and education strategies and awareness raising of important stakeholders such as health professionals, community,
grassroots-level workers, parents, teachers and children. Such strategies could be useful to trigger the desired change in behaviour of all concerned. Also, there is a need for collaboration and partnership between various stakeholders and ministries as policy-making bodies. There is a need to build on the research and strengthen the monitoring and surveillance
The increasing population and its associated amenities demand innovative devices, infrastructure, methods, plans and policies. Regional climate has a great role in deciding the air quality and energy demand, and therefore, weather and climate have an indisputable role in its consumption and storage. Here, we present the changes in trace gases and associated regional weather in India during lockdown and unlock periods of COVID-19. We observe a reduction of about 30% in sulphur dioxide (SO2) and 10–20% in aerosols in the Indo-Gangetic Plain (IGP), large cities, industrial sites, mining areas and thermal power plants during lockdown as compared to the same period in the previous year and with respect to its climatology. However, a considerable increase in aerosols is found, particularly over IGP during Unlock 1.0 (1–30 June 2020), because of the relaxation of lockdown restrictions. The analyses also show a decrease in temperature by 1–3 °C during lockdown compared to its climatology for the same period, mainly in IGP and Central India, possibly due to the significant reduction in absorbing aerosols such as black carbon and decrease in humidity during the period. The west coast, northwest and central India show reduced wind speed when compared to its previous year and climatological values, suggesting that there was a change in regional weather due to the lockdown. Energy demand in India decreased by about 25–30% during the first phase of lockdown and about 20% during the complete lockdown period. This study thus suggests that the reduction of pollution could also modify local weather, and these results would be useful for drafting policy decisions on air pollution reduction, urban development, the energy sector, agriculture and water resources.
The Third Pole, Hindu Kush Himalaya (HKH) and Tien Shan mountains, has been closely monitored for the past few decades because of its deteriorating environmental condition. Here, we analyse the spatio-temporal changes in tropospheric NO2 over TP using satellite observations from 2005 to 2020. The highest NO¬2 concentrations (i.e. ≥ 1 × 1015 molec. cm-2) are found in the boundaries close to Indo-Gangetic Plain (IGP), and Yellow and Yangtze River basins (YYRB). The analysis of Emissions Database for Global Atmospheric Research (EDGAR v6.1) shows that the main contribution to NO2 in the region is from the road transport (81%) and then power sector (7%). The Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) analyses illustrate that the major regions from which air mass reach TP is from IGP, Southeast Asia, YYRB, Central Asia and Middle East. Our analysis reveals a positive trend in NO2 over most regions of TP (up to 0.05 ± 0.01 × 1015 molec. cm-2 year-1) in the yearly averaged data for the period 2005–2020, which suggest that the pollution is spreading even to the inner regions of TP. Therefore, this study reveals that the inner TP, one of the most pristine regions on the earth, is getting polluted because of high anthropogenic activities within and nearby areas/cities; indicating the impact of regional development activities and socioeconomic changes in recent years.
The Hindu Kush Himalaya and Tien Shan Mountain regions together are called the Third Pole (TP) of Earth, which encompasses ecologically fragile regions of 12 Asian countries. It is the highest mountain chain with the largest reserve of fresh ice mass on the planet outside the northern and southern polar regions. The TP region is experiencing high rate of glacier melting due to climate change for the past few decades, and is a great concern for water security of South Asia. Since changes in ozone concentrations in the atmosphere affect public health, ecosystem dynamics and climate, it is imperative to monitor its temporal evolution in an ecologically sensitive region such as TP. Here, the spatiotemporal characteristics of total column ozone (TCO) in TP and 20 selected cities in and around TP are investigated using a combined long-term data made from the satellite measurements of Ozone Monitoring Instrument (OMI) and Global Ozone Monitoring Experiment (GOME)-2B for the period 2005–2020. The spatial trends in TCO over TP are mostly negative in summer and autumn (from -0.2 DU/yr to -0.6 DU/yr), but positive in winter (up to +0.2 DU/yr). Among the selected 20 urban regions, the highest annual trend -0.42±0.3 DU/yr and the lowest -0.01±0.2 DU/yr are estimated in Xining and Chittagong, respectively. Analysis using a multiple regression model reveals that the ozone variability in TP is mostly driven by tropopause height with a contribution of 24.92%, Quasi-Biennial Oscillation (23.42%), aerosols (16.12%) and solar flux (15.34%). Our study suggests that the observed negative trend is mainly associated with human activities and climate change in TP, which would likely to enhance the surface temperature and thus, melting of glaciers in the region.
India is a country with more than 67% of its population (947 million) residing in rural areas and 33% in urban areas (472 million) as of 2020. Therefore, health of the people living in rural India is very important for its future development plans, economy and growth. Here, we analyse the rural air quality using satellite measurements of NO2 in India, as the sources of NO2 are well connected to the industrial and economic uplift of a nation. Our analyses for the rural regions show distinct seasonal changes with the highest value (2.0 × 1015 molecules per cm2) in winter and the lowest in monsoon (1.5 × 1015 molecules per cm2) seasons. About 41% of the total NO2 pollution in India is from its rural sources, but 59% of the urban sources were focused in the past studies. In addition, around 45% of the rural NO2 pollution is due to road transport, whereas more than 90% of it in urban India comes from the power sector. Our assessment shows that the NO2 exposure in rural regions is as serious as that in urban areas, indicating the need for more effective reduction of population exposure and protection of public health. Henceforth, this study reveals that rural India is gradually getting polluted from its nearby regions as well as from the new sources within. This is a big concern for the public health of the large rural population of India.
We performed a comprehensive and intensive field experiment including ground-based multi-axis differential optical absorption spectroscopy (MAX-DOAS) measurement at Raoyang (115°44′ E, 38°14′ N; 20 m altitude) in summer (13 June–20 August) 2014. The NO2 and HCHO profiles retrieved by MAX-DOAS take on different vertical distribution shapes, with the former declining with the increasing altitude and the latter having an elevated layer. The average levels of vertical column densities (VCDs) and near-surface volume mixing ratios (VMRs) were 1.02 ± 0.51 × 1016 molec·cm−2 and 3.23 ± 2.70 ppb for NO2 and 2.32 ± 0.56 × 1016 molec·cm−2 and 5.62 ± 2.11 ppb for HCHO, respectively. The NO2 and HCHO levels are closely connected with meteorological conditions, with the larger NO2 VCDs being associated with lower temperature, higher relative humidity (RH) and lower planetary boundary layer height (PBLH). With respect to the diurnal variations of vertical distribution, the NO2 in the residual layer gradually disappeared from 1.2 km height to the surface during the period of 7:00–11:00 Beijing time (BJ), and the near-surface NO2 had larger VMRs in the early morning and evening than in the later morning and afternoon. An elevated HCHO layer was observed to occur persistently with the lifted layer height rising from ~0.5 km to ~1.0 km before 10:00 BJ; the near-surface HCHO VMRs gradually increased and peaked around 10:00 BJ. The ratios of HCHO to NO2 (RHCHO-NO2) were generally larger than two in the boundary layer from 11:00 BJ until 19:00 BJ, the time period when ozone photochemistry was most active. Thus, ozone (O3) production was mainly in the NOx-limited regime during the observation campaign, which was closely related to relatively high temperatures and low RH. The O3 production regimes also changed with the wind’s direction. These results are significant to reveal the formation mechanism of O3 pollution and develop strategies for controlling the O3 photochemical pollution over the North China Plain.
A nationwide lockdown was imposed in India from 24 March 2020 to 31 May 2020 to contain the spread of COVID-19. The lockdown has changed the atmospheric pollution across the continents. Here, we analyze the changes in two most important air quality related trace gases, nitrogen dioxide (NO2) and tropospheric ozone (O3) from satellite and surface observations, during the lockdown (April–May 2020) and unlock periods (June–September 2020) in India, to examine the baseline emissions when anthropogenic sources were significantly reduced. We use the Bayesian statistics to find the changes in these trace gas concentrations in different time periods. There is a strong reduction in NO2 during the lockdown as public transport and industries were shut during that period. The largest changes are found in IGP (Indo-Gangetic Plain), and industrial and mining areas in Eastern India. The changes are small in the hilly regions, where the concentrations of these trace gases are also very small (0–1 × 10¹⁵ molec./cm²). In addition, a corresponding increase in the concentrations of tropospheric O3 is observed during the period. The analyses over cities show that there is a large decrease in NO2 in Delhi (36%), Bangalore (21%) and Ahmedabad (21%). As the lockdown restrictions were eased during the unlock period, the concentrations of NO2 gradually increased and ozone deceased in most regions. Therefore, this study suggests that pollution control measures should be prioritized, ensuring strict regulations to control the source of anthropogenic pollutants, particularly from the transport and industrial sectors.
Highlights
• Most cities show a reduction up to 15% of NO2 during the lockdown
• The unlock periods show again an increase of about 40–50% in NO2
• An increase in tropospheric O3 is observed together with the decrease in NO2
Atmospheric formaldehyde (HCHO) has significant adverse health effects at higher concentrations. It is an unstable and inflammable organic compound, and is an index for atmospheric pollution. Although the ambient HCHO is due to methane oxidation, the localised enhancement in HCHO is mostly from the emissions of non-methane volatile organic compounds (NMVOCs). Therefore, assessment of spatial and temporal changes in NMVOCs are key for monitoring air quality and climate change. Here, we analyze two decades of atmospheric HCHO measurements and investigate the HCHO sources in India using satellite observations in 1997–2020. The measurements show very high HCHO concentrations in the Indo-Gangetic Plain (IGP), and south and east India, about 8–12 × 10 15 molec. cm − 2 . The northwest region shows moderate concentrations, but Kashmir and northern regions of northeast show very small values of about 1–2 × 10 15 molec. cm − 2 . Our analyses reveal significant increase in HCHO over India in all seasons, with the highest trends during March–May, about 0.3–0.5 × 10 15 molec. cm − 2 yr − 1 ; suggesting the spread of pollution even to rural regions. Many ports and mining areas exhibit high positive HCHO trends, which also show new source regions and transport pathways of pollution. Furthermore, the analyses for the COVID-19 lockdown period expose significant contributions from sources other than anthropogenic origin (e.g. biogenic and pyrogenic). Therefore, this study indicates the need of new policy interventions for controlling Volatile Organic Compound (VOC) pollution in rural and urban India, and at the international seaports of Indian Ocean.
Actions in cities shape the outcome of greenhouse gas (GHG) emission mitigation and our climate change response. Accurate and consistent carbon inventories are essential for identifying the main sources of emissions and global comparison of carbon reduction progress and would help inform targeted policies for low-carbon transition. To identify the effectiveness of historical carbon reduction policies, our study conducted energy-related GHG emission inventories for 167 globally distributed cities with information from different sectors, and assessed the city-scale near-term, mid-term, and long-term goals carbon mitigation targets from 2020 to 2050. On this basis, we propose mitigation strategies to achieve local and global climate targets. We found that, although Asian cities are the biggest carbon emitters in totals, the per capita GHG emissions of cities in developed countries are still generally higher than that in developing countries. In terms of sectors, the GHG emissions from the stationary energy uses (such as residential, commercial, and industrial buildings) and transportation sector contributed the most. However, cities in more developed nations have been inclined to set absolute carbon reduction targets before 2050, while intensity reduction target has been largely set for cities at the stage of rapid economic growth and accelerated industrialization. More ambitious and easily-tracked climate targets should be proposed by cities and more effective measures of reducing GHG emissions are required to stay consistent with the global ambition of climate change mitigation.
The transport sector emerged as one of the largest contributors to atmospheric warming. In India, the transport sector consumes ~17% of total energy and produces about 60% of total greenhouse gases (GHG) during various activities. Particularly in Delhi, the rising ambient concentrations of particulate matter (PM) lead to thousands of premature deaths and several million asthma attacks every year. The outdoor exposure of high PM2.5 concentration in Delhi causes lung impairment to human beings. Several policy measures have been implemented from time to time by the Indian Government to control vehicular pollution, such as unleaded fuel implement in 1996 (0.15 g/l) and further reduction of lead (0.25%) and sulfur (0.5%) in fuel in 1998 and 1996, respectively. Besides the improvement of fuel quality, scrapping of 8-year-old buses and all other vehicles which were forced to meet Euro-1 norms except passenger cars was implemented in 2000. However, to reduce PM load in Delhi, the Indian Government implemented several policies like the Green Tribunal Act 2015; as per this act, 10-year-old diesel vehicles were banned in Delhi. The deployment of BS-VI vehicle and electric vehicles in the country is also proposed by the government up to 2020. These policies indicate the severity of transport sector emission and its adverse impacts on the environment and health. Hence, the chapter is focused on the roadway transport adverse effects and possible mitigation measures.
The National Clean Air Programme 2019 (NCAP 2019) addresses India's air pollution problem systematically and systemically. Its 198 action points comprehensively encapsulate the recommended pathways of the programme. We present an ontological analysis of these action points and highlight the pathways they emphasize frequently, infrequently and overlook. Subsequently, we discuss the selectivity and segmentation of the pathways in the action points, the gaps in them and the potential gaps in the effectiveness of NCAP 2019. Last, we present recommendations to discover and design novel pathways to bridge the gaps and improve the effectiveness of the programme.
The Indo-Gangetic Plain (IGP) experienced an intensive air pollution episode during November 2017. Weather Research and Forecasting model coupled to Chemistry (WRF-Chem), a coupled meteorology–chemistry model, was used to simulate this episode. In order to capture PM2.5 peaks, we modified input chemical boundary conditions and biomass burning emissions. The Community Atmosphere Model with Chemistry (CAM-chem) and Modern-Era Retrospective analysis for Research and Applications Version 2 (MERRA-2) global models provided gaseous and aerosol chemical boundary conditions, respectively. We also incorporated Visible Infrared Imaging Radiometer Suite (VIIRS) active fire points to fill in missing fire emissions in the Fire INventory from NCAR (FINN) and scaled by a factor of 7 for an 8 d period. Evaluations against various observations indicated the model captured the temporal trend very well although missed the peaks on 7, 8, and 10 November. Modeled aerosol composition in Delhi showed secondary inorganic aerosols (SIAs) and secondary organic aerosols (SOAs) comprised 30 % and 27 % of total PM2.5 concentration, respectively, during November, with a modeled OC/BC ratio of 2.72. Back trajectories showed agricultural fires in Punjab were the major source for extremely polluted days in Delhi. Furthermore, high concentrations above the boundary layers in vertical profiles suggested either the plume rise in the model released the emissions too high or the model did not mix the smoke down fast enough. Results also showed long-range-transported dust did not affect Delhi's air quality during the episode. Spatial plots showed averaged aerosol optical depth (AOD) of 0.58 (±0.4) over November. The model AODs were biased high over central India and low over the eastern IGP, indicating improving emissions in the eastern IGP can significantly improve the air quality predictions. We also found high ozone concentrations over the domain, which indicates ozone should be considered in future air quality management strategies alongside particulate matter.
National Clean Air Programme (NCAP), launched in 2019, is India's flagship program for better air quality in 122 cities. This review evaluates the scientific, legislative, financial, and institutional framework of the 102 publicly available clean air action plans submitted under NCAP. We assessed the robustness of the plans using the background information on pollution sources and their contribution; legal backing for the clean air action plan; cost of measures; and existing institutional accountability regime. We used the tally chart method for estimating city-specific and sector-specific mitigation measures, the number of actions under the purview of various implementation agencies, and the number of institutional, physical, and promotional interventions in the plans. Transport and road dust together cover 50% of action points, followed by interventions for the industries. Domestic cooking and heating is mentioned as a source only in 42 plans for a total of 2% of the action points. Institutional nature of the interventions was observed in 74% of the action points, using the language “overseeing, planning, proposing, preparing, investigating, identifying, ensuring, strengthening, training, studying, and engaging”. We also identified the plans that contained information on source contributions, an outline of financial requirements for executing the plans and measures for mitigating pollution from regional sources. Only 25% of the plans integrated information on the relative source contributions to formulate control strategies. Even fewer plans outlined the financial requirements for executing the plans. The institutional and administrative arrangements for ensuring inter-departmental and regional alignment in air pollution mitigation strategies are absent. We close the review with recommendations which include mandating regular updates for emission and pollution loads, granting greater fiscal autonomy for Urban Local Bodies to maintain the infrastructure necessary for sustaining air quality benefits, and moving from city-centric to airshed-centric air quality management.
Within the Copernicus Climate Change Service (C3S), ECMWF is producing the ERA5 reanalysis which, once completed, will embody a detailed record of the global atmosphere, land surface and ocean waves from 1950 onwards. This new reanalysis replaces the ERA‐Interim reanalysis (spanning 1979 onwards) which was started in 2006. ERA5 is based on the Integrated Forecasting System (IFS) Cy41r2 which was operational in 2016. ERA5 thus benefits from a decade of developments in model physics, core dynamics and data assimilation. In addition to a significantly enhanced horizontal resolution of 31 km, compared to 80 km for ERA‐Interim, ERA5 has hourly output throughout, and an uncertainty estimate from an ensemble (3‐hourly at half the horizontal resolution). This paper describes the general set‐up of ERA5, as well as a basic evaluation of characteristics and performance, with a focus on the dataset from 1979 onwards which is currently publicly available. Re‐forecasts from ERA5 analyses show a gain of up to one day in skill with respect to ERA‐Interim. Comparison with radiosonde and PILOT data prior to assimilation shows an improved fit for temperature, wind and humidity in the troposphere, but not the stratosphere. A comparison with independent buoy data shows a much improved fit for ocean wave height. The uncertainty estimate reflects the evolution of the observing systems used in ERA5. The enhanced temporal and spatial resolution allows for a detailed evolution of weather systems. For precipitation, global‐mean correlation with monthly‐mean GPCP data is increased from 67% to 77%. In general, low‐frequency variability is found to be well represented and from 10 hPa downwards general patterns of anomalies in temperature match those from the ERA‐Interim, MERRA‐2 and JRA‐55 reanalyses.
Fine particulate matter (PM2.5 , aerodynamic diameter ≤2.5 µm) impacts the climate, reduces visibility and severely influences human health. The Indo-Gangetic Plain (IGP), home to about one-seventh of the world’s total population and a hotspot of aerosol loading, observes strong enhancements in the pM concentrations towards winter. We performed high-resolution (12 km × 12 km) atmospheric chemical transport modeling (WRF-Chem) for the post-monsoon to winter transition to unravel the underlying dynamics and influences of regional emissions over the region. Model, capturing the observed variations to an extent, reveals that the spatial distribution of PM 2.5 having patches of enhanced concentrations (≥100 µgm−3 ) during post-monsoon, evolves dramatically into a widespread enhancement across the IGP region during winter. A sensitivity simulation, supported by satellite observations of fires, shows that biomass-burning emissions over the northwest IGP play a crucial role during post-monsoon. Whereas, in contrast, towards winter, a large-scale decline in the air temperature, significantly shallower atmospheric boundary layer, and weaker winds lead to stagnant conditions (ventilation coefficient lower by a factor of ~4) thereby confining the anthropogenic influences closer to the surface. Such changes in the controlling processes from post-monsoon to winter transition profoundly affect the composition of the fine aerosols over the IGP region. The study highlights the need to critically consider the distinct meteorological processes of west-to-east IGP and changes in dominant sources from post-monsoon to winter in the formulation of future pollution mitigation policies.
Ozone pollution in China is influenced by meteorological processes on multiple scales. Using regression analysis and weather classification, we statistically assess the impacts of local and synoptic meteorology on daily variability in surface ozone in eastern China in summer during 2013–2018. In this period, summertime surface ozone in eastern China (20–42∘ N, 110–130∘ E) is among the highest in the world, with regional means of 73.1 and 114.7 µg m-3, respectively, in daily mean and daily maximum 8 h average. Through developing a multiple linear regression (MLR) model driven by local and synoptic weather factors, we establish a quantitative linkage between the daily mean ozone concentrations and meteorology in the study region. The meteorology described by the MLR can explain ∼43 % of the daily variability in summertime surface ozone across eastern China. Among local meteorological factors, relative humidity is the most influential variable in the center and south of eastern China, including the Yangtze River Delta and the Pearl River Delta regions, while temperature is the most influential variable in the north, covering the Beijing–Tianjin–Hebei region. To further examine the synoptic influence of weather conditions explicitly, six predominant synoptic weather patterns (SWPs) over eastern China in summer are objectively identified using the self-organizing map clustering technique. The six SWPs are formed under the integral influence of the East Asian summer monsoon, the western Pacific subtropical high, the Meiyu front, and the typhoon activities. On average, regionally, two SWPs bring about positive ozone anomalies (1.1 µg m-3 or 1.7 % and 2.7 µg m-3 or 4.6 %), when eastern China is under a weak cyclone system or under the prevailing southerly wind. The impact of SWPs on the daily variability in surface ozone varies largely within eastern China. The maximum impact can reach ±8 µg m-3 or ±16 % of the daily mean in some areas. A combination of the regression and the clustering approaches suggests a strong performance of the MLR in predicting the sensitivity of surface ozone in eastern China to the variation of synoptic weather. Our assessment highlights the importance of meteorology in modulating ozone pollution over China.
From 2013 to 2017, with the implementation of the toughest-ever clean air policy in China, significant declines in fine particle (PM 2.5 ) concentrations occurred nationwide. Here we estimate the drivers of the improved PM 2.5 air quality and the associated health benefits in China from 2013 to 2017 based on a measure-specific integrated evaluation approach, which combines a bottom-up emission inventory, a chemical transport model, and epidemiological exposure-response functions. The estimated national population–weighted annual mean PM 2.5 concentrations decreased from 61.8 (95%CI: 53.3–70.0) to 42.0 µg/m ³ (95% CI: 35.7–48.6) in 5 y, with dominant contributions from anthropogenic emission abatements. Although interannual meteorological variations could significantly alter PM 2.5 concentrations, the corresponding effects on the 5-y trends were relatively small. The measure-by-measure evaluation indicated that strengthening industrial emission standards (power plants and emission-intensive industrial sectors), upgrades on industrial boilers, phasing out outdated industrial capacities, and promoting clean fuels in the residential sector were major effective measures in reducing PM 2.5 pollution and health burdens. These measures were estimated to contribute to 6.6- (95% CI: 5.9–7.1), 4.4- (95% CI: 3.8–4.9), 2.8- (95% CI: 2.5–3.0), and 2.2- (95% CI: 2.0–2.5) µg/m ³ declines in the national PM 2.5 concentration in 2017, respectively, and further reduced PM 2.5 -attributable excess deaths by 0.37 million (95% CI: 0.35–0.39), or 92% of the total avoided deaths. Our study confirms the effectiveness of China’s recent clean air actions, and the measure-by-measure evaluation provides insights into future clean air policy making in China and in other developing and polluting countries.
Plant and animal phenology is shifting in response to urbanization, with most hypotheses focusing on the ‘urban heat island’ (UHI) effect as the driver. However, generalities regarding the direction and magnitude of phenological response to urbanization have not yet emerged because most studies have focused on remote-sensed vegetative phenologies or at local scales with relatively few species. Furthermore, how urbanization interacts with broad-scale climate gradients remains an unknown but important component of anthropogenically driven phenological change. Here, we used a database with >22 million in situ plant phenological observations from the United States and Europe to study the joint influence of varying human population density, which serves as an urbanization measure, and of regional temperature on median flowering and leaf-out dates across a wide plant phylogenetic spectrum. Separately, increasing population density and warmer regional temperature both advanced plant flowering and leaf-out. However, the influence of human population density on plant flowering and leaf-out depends on the regional temperature: high population density advanced plant phenology in cold areas but this effect disappeared or even reversed in warm areas. UHI effects (as measured by daily land surface temperature) alone cannot explain the overall influence of urbanization on plant phenology, suggesting that urbanization also affects plant phenology via other mechanisms. Shorter plants with large specific leaf areas and early flower or leaf-out dates were most affected by urbanization and temperature changes. Our study provides strong empirical evidence that the influence of urbanization on plant phenology varies with regional temperature. Therefore, robust understanding and accurate prediction of phenological changes must take this interaction into account.
Oxides of nitrogen (NOx) and volatile organic compounds (VOCs) released into the atmosphere can react in the presence of solar irradiation, leading to ozone formation in the troposphere. Historically, before clean air regulations were implemented to control NOx and VOCs, ozone concentrations were high enough to exert acute effects such as eye and nose irritation, respiratory disease emergencies, and lung function impairment. At or above current regulatory standards, day-to-day variations in ozone concentrations have been positively associated with asthma incidence and daily non-accidental mortality rate. Emerging evidence has shown that both short-term and long-term exposures to ozone, at concentrations below the current regulatory standards, were associated with increased mortality due to respiratory and cardiovascular diseases. The pathophysiology to support the epidemiologic associations between mortality and morbidity and ozone centers at the chemical and toxicological property of ozone as a strong oxidant, being able to induce oxidative damages to cells and the lining fluids of the airways, and immune-inflammatory responses within and beyond the lung. These new findings add substantially to the existing challenges in controlling ozone pollution. For example, in the United States in 2016, 90% of non-compliance to the national ambient air quality standards was due to ozone whereas only 10% was due to particulate matter and other regulated pollutants. Climate change, through creating atmospheric conditions favoring ozone formation, has been and will continue to increase ozone concentrations in many parts of world. Worldwide, ozone is responsible for several hundreds of thousands of premature deaths and tens of millions of asthma-related emergency room visits annually. To combat ozone pollution globally, more aggressive reductions in fossil fuel consumption are needed to cut NOx and VOCs as well as greenhouse gas emissions. Meanwhile, preventive and therapeutic strategies are needed to alleviate the detrimental effects of ozone especially in more susceptible individuals. Interventional trials in humans are needed to evaluate the efficacy of antioxidants and ozone-scavenging compounds that have shown promising results in animal studies.
China faces severe air pollution issues due to the rapid growth of the economy, causing concerns for human physical and mental health as well as behavioral changes. Such adverse impacts can be mediated by individual avoidance behaviors such as traveling from polluted cities to cleaner ones. This study utilizes smartphone-based location data and instrumental variable regression to try and find out how air quality affects population mobility. Our results confirm that air quality does affect the population outflows of cities. An increase of 100 points in the air quality index will cause a 49.60% increase in population outflow, and a rise of 1 μg m−3 in PM2.5 may cause a 0.47% rise in population outflow. Air pollution incidents can drive people to leave their cities 3 days or a week later by railway or road. The effect is heterogeneous among workdays, weekends and holidays. Our results imply that air quality management can be critical for urban tourism and environmental competitiveness.
Significance
Drastic air pollution control in China since 2013 has achieved sharp decreases in fine particulate matter (PM 2.5 ), but ozone pollution has not improved. After removing the effect of meteorological variability, we find that surface ozone has increased in megacity clusters of China, notably Beijing and Shanghai. The increasing trend cannot be simply explained by changes in anthropogenic precursor [NO x and volatile organic compound (VOC)] emissions, particularly in North China Plain (NCP). The most important cause of the increasing ozone in NCP appears to be the decrease in PM 2.5 , slowing down the sink of hydroperoxy radicals and thus speeding up ozone production. Decreasing ozone in the future will require a combination of NO x and VOC emission controls to overcome the effect of decreasing PM 2.5 .
The objective of this research is to explore the diverse challenges faced by the customer as well transport providers through the selected modes of transportation of the second most populous country in the world - India. Two separate well-structured questionnaires administered to garner the opinions on different challenges. A random sample of 100 equally selected from the customers of 3 modes of transportation along with 30 transport providers. The collected data was analyzed in Microsoft Excel and R Studio platforms using Percentile Rank Tool and R Programming Language for Chi-square test respectively. Traffic congestion coupled with parking is the major problem in case of roadways while Safety and cleanliness in railways are the first amongst the problems to reckon with. High fares and lack of trained employees are the biggest challenges faced by aviation industry. The research is concentrated only in the states of Andhra Pradesh and Telangana in India with most widely used three modes of transportation viz., Road, Rail and Airways. This research paper is first of its kind which has collected the opinions of both customers as well transport providers on the problems faced. This research proffers information about the challenges faced by the customers which there will be an enormous possibility to review their strategies and plans.
Scientists use Essential Climate Variables to understand and model the Earth’s climate. Complementary to the Climate Variables this paper introduces global built-up area and population density, referred to as Essential Societal Variables, that can be used to model human activities and the impact of climate induced hazards on society. Climate impact scenarios inform policy makers on current and future risk and on the cost for mitigation and adaptation measures. The global built-up area and global population densities are generated from Earth observation image archives and from national population census data in the framework of the Global Human Settlement Layer (GHSL) project. The layers are produced with fine granularity for four epochs: 1975, 1990, 2000 and 2015, and will be updated on a regular basis with open satellite imagery. The paper discusses the relevance of global built-up area and population density for a number of policy areas, in particular to understand regional and global urbanization processes and for use in operational crisis management and risk assessment. The paper also provides examples of global statistics on exposure to natural hazards based on the two ESVs and their use in policy making. Finally, the paper discusses the potential of using population and built-up area for developing indicators to monitor the progress in Agenda 2030 including the Sustainable Development Goals (SDGs).
In the last two decades, air pollution has increased throughout India resulting in the deterioration of air quality. This paper estimates the prevalence of self-reported asthma in women aged 15-49 years and examines the link between outdoor air pollution and disease prevalence in India by combining satellite data on particulate matter (PM2.5) and the National Family Health Survey (NFHS-4), 2015-16. The results indicate that both indoor pollution as well as outdoor air pollution are important risk factors for asthma in women as both independently increase the probability of asthma among this group. Strategies around the prevention of asthma need to recognize the role of both indoor as well as outdoor air pollution. The other significant risk factors for asthma are smoking, second-hand smoking, type of diet and obesity.
At higher concentrations, tropospheric ozone can cause respiratory difficulties, premature human mortality and can harm vegetation by reducing photosynthesis and its growth. It is an oxidant and also an important green- house gas with positive feedback to temperature. It is produced as a byproduct of chemical reactions involving nitrogen oxides (NO ) and volatile organic compounds (VOCs) in the presence of sunlight, rather than being emitted directly to the atmosphere. Here, we analyse the seasonal and inter-annual variability, long-term trends and radiative forcing of the tropospheric column ozone (TPO) in India for the period of 2005–2020 using satellite and ground-based data. The analysis shows very high annual averaged TPO in the Indo-Gangetic Plain (IGP) and North West India, about 45–50 DU. Our findings reveal a significant increase of TPO in India, with the highest trend in the peninsular region (0.295 ± 0.0617 DU/year) and the lowest in North West (0.179 ± 0.048 DU/ year). The increase in tropospheric ozone reveals a warming of about 0.5 °C in the troposphere as there is an as- sociated radiative forcing of about 0.2–0.5 W/m 2 at the tropopause (125 hPa); indicating that the increasing tropospheric ozone is a great concern for regional warming, public health and ecosystem dynamics.
Hourly ground-level ozone (O3) data from 52 monitoring stations in Poland were analyzed over a ten-year pre-COVID19 period (2010–2019) to map and define areas at risk for human health and vegetation, and to calculate trends over the study period. Annual O3 metrics (24-h average concentrations, 50th percentiles, and hourly maxima), human health metrics (Sum Of daily maximum 8-h Means Over 35 ppb, SOMO35, summertime average of the daily 8-h maximum O3 concentrations, O3 MDA8, and number of daily maximum 8-h values above 60 ppb, EU60) and vegetation exposure metrics (AOT40, i.e., accumulation of hourly O3 concentrations exceeding 40 ppb during the growing season for agricultural crops AOT40c and forests AOT40f) were investigated. Higher O3 levels occurred in rural areas than in cities. Between 2010 and 2019, the O3 levels were rising in both urban and rural areas. Despite the reduction of nitrogen oxides (NOx: - 2.33% year-1) and volatile organic compounds emissions (VOCs: - 0.95% year-1), annual O3 mean levels (+0.81 and +0.12% year-1), 50th percentiles (+1.06 and ∼0% year-1), hourly maxima (- 0.10 and +0.23% year-1), SOMO35 (+2.86 and +1.50% year-1), summertime O3 MDA8 (+0.49 and +0.48% year-1), EU60 (+0.09 and +0.15 days year-1), AOT40c (+3.79 and +3.29% year-1) and AOT40f (+4.47 and +4.34% year-1) commonly increased in urban and rural stations. The O3 levels increased at 75% of urban stations and 62.5% of rural stations. A slight decline of the number of O3 peaks occurred in cities, likely driven by the recent reductions in NOx emissions by on-road transport. For all metrics, the increase can be attributed to higher regional photochemical O3 formation and rising background O3 levels likely driven by imported O3 and its precursors by long-range transport, climate change, and lower O3 titration by NOx emissions decline. The failure to attain the target value for O3 for protecting vegetation and human health and vegetation persists. Southeastern Poland, where coal stoves are still used for residential heating, faces the highest O3 risk. This study reports new information on surface O3 levels, exceedances, and trends in Poland to develop effective policies to mitigate O3 effects.
Carbon Monoxide (CO) is not a greenhouse gas (GHG), but has the capacity to change atmospheric chemistry of other GHGs such as methane and ozone, and therefore indirectly affects Earth's radiative forcing of the GHGs and surface temperature. Here, we use the CO mixing ratio at 850 hPa from the Tropospheric Emission Spectrometer (TES) reanalysis and the Measurement of Pollution in the Troposphere (MOPITT) satellite measurements for the period 2005-2019 to examine the spatio-temporal changes in CO across the latitudes. We find a substantial decrease in global CO, about 0.21 ± 0.09 ppb/yr (0.23 ± 0.12%/yr) with the TES data and about 0.36 ± 0.07 ppb/yr (0.45 ± 0.08%/yr) with the MOPITT satellite measurements during the study period. The highest CO decreasing trend is observed in Eastern China (2.7 ± 0.37 ppb/yr) followed by Myanmar (2.142 ± 0.59 ppb/yr) and South America (1.08 ± 0.82 ppb/yr). This negative trend in CO is primarily due to the decrease in biomass burning and stringent environmental regulations in the respective regions and countries. The sources including road transport that account for about 33.6% of CO emissions, followed by industries (18.3%) and agricultural waste burning (8.8%), might also be responsible for the reduction in CO due to adaptation of improved emission control technology and regulations in the past decade from 2005 to 2019. Therefore, the study provides new insights on the current trends of global CO distribution and reasons for recent reduction in global CO emissions, which would be useful for future decision-making process to control air pollution.
As the hydroxyl radical (OH) is the cleansing agent of the atmosphere, reduction in its concentration is a great concern for air quality and transport of trace gases across the latitudes and altitudes. In addition, OH determines the lifetime of most trace gases and non-CO2 greenhouse gases in the atmosphere. Since many pollutants have adverse health effects and are greenhouse gases, the changes in OH concentrations directly or indirectly affect public health and climate. Our analysis with OH data (from Tropospheric Emission Spectrometer and Copernicus Atmosphere Monitoring Service reanalyses) for the past 14 (2005–2018) years finds an OH minimum region over Indian Ocean, in the eastern Bay of Bengal at 6°–14° N and 92°–95° E. The Indian Ocean OH minimum reaches to 15 × 104 molec.cm−3 in April, and a secondary minimum of 18 × 104 molec.cm−3 in September–November. This seasonal minimum found around the Andaman and Nicobar Islands also hosts an active volcano, which releases noticeable amount of SO2 (OH sink) throughout the year. In addition, the biomass burning in spring and thus, the distribution of CO has a profound influence on the OH distribution in this region as Southeast Asia is one of the global hotspots of biomass burning, and the Indian Ocean OH minimum is located near that region. The El Niño and La Niño events also control the tropospheric ozone and CO distribution, and thus the interannual variability of OH minimum there. The WACCM model simulations reproduce the general latitudinal distribution and average seasonal cycle of OH, but not the extreme minimum OH values, although the simulations show the annual minimum in winter (December–January) in both ocean regions, which demands dedicated studies using chemical transport models. Therefore, this study reveals a seasonal OH minimum over Indian Ocean, which is very likely to influence the regional air quality and trace gas transport in the tropics.
The lockdown measures enacted to control the COVID-19 pandemic in Wuhan, China, resulted in a suspension of nearly all non-essential human activities on January 23, 2020. Nevertheless, the lockdown provided a natural experiment to understand the consistency of the relationship between the urban form and air pollution with different compositions of locally or regionally transported sources. This study investigated the variations in six air pollutants (PM2.5, PM10, NO2, CO, O3, and SO2) in Wuhan before and during the lockdown and in the two same time spans in 2021. Moreover, a hierarchical agglomerative cluster analysis was conducted to differentiate the relative levels of pollutants and to detect the relationships between the air pollutants and the urban form during these four periods. Several features depicting the urban physical structures delivered consistent impacts. A lower building density and plot ratio, and a higher porosity always mitigated the concentrations of NO2 and PM2.5. However, they had inverse effects on O3 during the non-lockdown periods. PM10, CO, and SO2 concentrations have little correlation with the urban form. This study improves the comprehensive understanding of the effect of the urban form on ambient air pollution and suggests practical strategies for mitigating air pollution in Wuhan.
Evaluating ozone levels at high resolutions and accuracy is crucial for understanding the spatiotemporal characteristics of ozone distribution and assessing ozone exposure levels in epidemiological studies. The national models with high spatiotemporal resolutions to predict ground ozone concentrations are limited in China so far. In this study, we aimed to develop a random forest model by combining ground ozone measurements from fixed stations, ozone simulations from the Community Multiscale Air Quality (CMAQ) modeling system, meteorological parameters, population density, road length, and elevation to predict ground maximum daily 8-h average (MDA8) ozone concentrations at a daily level and 1 km × 1 km spatial resolution. The model cross-validation R² and root mean squared error (RMSE) were 0.80 and 20.93 μg/m³ at daily level in 2013–2019, respectively. CMAQ ozone simulations and near-surface temperature played vital roles in predicting ozone concentrations among all predictors. The population-weighted median concentrations of predicted MDA8 ozone were 89.34 μg/m³ in mainland China in 2013, and reached 100.96 μg/m³ in 2019. However, the long-term temporal variations among regions were heterogeneous. Central and Eastern China, as well as the Southeast Coastal Area, suffered higher ozone pollution and higher increased rates of ozone concentrations from 2013 to 2019. The seasonal pattern of ozone pollution varied spatially. The peak-season ozone pollution with the highest 6-month ozone concentrations occurred in different months among regions, with more than half domain in April–September. The predictions showed that not only the annual mean concentrations but also the percentages of grid-days with MDA8 ozone concentrations higher than 100/160 μg/m³ have been increasing in the past few years in China; meanwhile, majority areas in mainland China suffered peak-season ozone concentrations higher than the air quality guidelines launched by the World Health Organization in September 2021. The proposed model and ozone predictions with high spatiotemporal resolution and full coverage could provide health studies with flexible choices to evaluate ozone exposure levels at multiple spatiotemporal scales in the future.
In summer, Ozone (O3) pollution and urban heat island (UHI) pose serious health risks to humans. To obtain the spatial distributions of ozone and urban heat island in Xi'an in summer and develop a simultaneous control strategy of ozone and urban heat island, the land use regression model is modified and improved using the machine learning random forest algorithm. The LUR-Kriging-RF integrated prediction model is then established. The land use regression and kriging are used to extract the feature variables, while random forest is used to establish a regression model. The spatial distribution maps of ozone and urban heat island in Xi'an are obtained by regression mapping of the prediction model, and the spatial relationships between them are analyzed. The SHapley Additive explanation (SHAP) and partial dependence plot (PDP) are adopted to explain the way feature variables act on ozone and urban heat island. Based on the spatial distribution and interaction mode, a simultaneous control strategy of ozone and urban heat island in Xi'an is put forward. For ozone, the R² of the integrated prediction model (0.65) is higher than that of land use regression (0.4), while the RMSE (28.18) of the integrated model is lower than that of land use regression (35.66). For temperature, the R² of the integrated model (0.93) is higher than that of land use regression (0.8), while its RMSE (0.92) is lower than that of land use regression (1.52). The performance of the LUR-Kriging-RF integrated prediction model is better than that of land use regression. This study reveals the spatial interactions between ozone and land use regression in the central urban areas. The suitable strategies for mapping ozone pollution and urban heat island control include reducing VOCs emissions from industrial sources and agricultural sources, increasing plants with low VOCs emissions, and spray humidification. This study can be used to evaluate ozone exposure and thermal exposure, provide scientific support for environmental protection and urban heat island control policies, contribute to reducing public health threats, promote the sustainability of urban environments, and promote the practical application of machine learning in this field.
Northwest India, known as the breadbasket of the country, is extremely vulnerable to ramifications of extreme rainfall events (EREs) such as flash floods, landslides, agricultural and infrastructural damages. Nevertheless, the characteristics of EREs are less explored over Northwest India compared to other parts of the country. Hence, this study investigates the spatiotemporal variability of EREs using India's first highest resolution regional atmospheric reanalysis, Indian Monsoon Data Assimilation and Analysis (IMDAA) during Indian Summer Monsoon (ISM) for the period 1979–2018. Prior to understanding the EREs, we evaluated IMDAA's ability to represent general ISM characteristics using reanalysis and observations. Our analysis reveals that IMDAA realistically represents the ISM salient features along with a more accurate spatial distribution of summer precipitation compared to India Meteorological Department (IMD) observations, albeit with some overestimations. The mean ISM precipitation over Northwest India is found to be increasing significantly at 95% confidence level. Furthermore, EREs from IMD and TRMM exhibit increasing trends over Northwest India, which also conforms with IMDAA results (one event every two years). The rising (declining) trend in convective available potential energy (convective inhibition energy) signifies that the atmosphere over Northwest India is becoming more unstable during ISM. This enables it to hold more moisture, which is transported to the region from Bay of Bengal through cyclonic vorticity over Central India. Finally, the inter-parameter correlation analysis reveals that IMDAA reanalysis has succeeded in better representation of the physical linkages among moisture availability, instability, and convective precipitation formation over Northwest India compared to the global reanalysis products such as ERA5.
Green technology innovations are deemed as effective channels through which economic growth and environmental governance are balanced. However, empirical research on the nexus between green technology innovations and CO2 emissions, especially in developing countries, remains scant. Employing panel data on 264 prefecture-level cities from 2006 to 2017 in China, we explore the impact of the urban innovation environment on the effect of green technological innovations on CO2 emissions. The empirical results indicate that green technology innovations have a heterogeneous impact in different types of cities. Meanwhile, green technological innovations can contribute to CO2 emission mitigation after 2010, while the effect is not significant in Chinese cities before 2010. Secondly, green technology innovations can reduce CO2 emissions indirectly through industrial structure upgrading. Thirdly, when the urban innovation environment is considered, government fiscal expenditure cannot significantly impact the marginal effect of green technologies. Meanwhile, the marginal mitigation effect of green technology innovations on CO2 emissions is only significant when the human capital level of a city has reached a certain level. There is a better carbon emission reduction effect in cities with higher human capital levels. The results provide important enlightenment to realize the coordination and unity of economic transition to innovation-driven and green and low-carbon development.
Air pollution has become one of the most severe and prevalent environmental issues worldwide because millions of deaths are caused by air pollution per year. Air pollution adversely affects emotions, physical health, mental health, and ultimately human well-being. However, it is difficult to quantify the relationships between human well-being and air pollutants, including sulfur dioxide (SO2), nitrogen oxide (NOX), and fine particulate matter (PM2.5). Furthermore, whether the current concentrations of air pollution affect humans’ attitudes toward air pollution remains unclear. Here, we show SO2, NOx, and PM2.5 are negatively associated with human well-being, based on the analyses with 246,782, 334,065, and 300,796 observations, respectively. On average, a 1-unit reduction of SO2, NOX, and PM2.5 are worth 1,510 USD, 1217 USD, 7,111 USD per capita, respectively. Additionally, humans perceive the air pollution severity to some degree, rather than accurately and absolutely, proved by the correlations between the concentrations of air pollutants and their effects estimated by geographically weighted regression. Our study illustrates the impacts of air pollution on human well-being, their spatial variability, and their monetary value to arouse the attention of governments and society.
Previous studies on long-term ozone (O3) variations in China have reported inconsistent conclusions on the role of meteorological factors in controlling said variations. In this study, we used an observation-based decomposition model to conduct an up-to-date investigation of the effects of meteorological factors on the variations in nitrogen dioxide (NO2) and O3 concentrations in China in the summer from 2013 to 2020. The variations in NO2 and O3 concentrations after removing the major meteorological effects were then analyzed to improve our understanding of O3 formation regimes. Ground measurements show that both NO2 and O3 concentrations decreased in eastern, central, and southeastern China (e.g., NO2 and O3 concentrations in Wuhan reduced by 4.3 and 6.2 ppb, respectively), which was not anticipated. Analyses of meteorological effects showed that reduced wind strength, decreased temperature, and increased relative humidity significantly reduced O3 concentrations in eastern and central China (e.g., by 10.5 ppb in Wuhan). After removing the major meteorological effects, the O3 trends were reversed in eastern and central China (e.g., increased by 4.9 ppb in Wuhan). The contrasting trends in NO2 and O3 concentrations suggest that their O3 formations were sensitive to volatile organic compounds (VOC-limited regime). In southeastern China, both NO2 and O3 concentrations decreased, implying that the O3 formation regimes changed to mixed sensitive or nitrogen oxide-limited (NOx-limited) regimes. The meteorological effects varied by region and may play a dominant role in controlling the long-term O3 variation. Our results indicate that the attribution of O3 variation to emission control without accounting for meteorological effects can be misleading.
The surface ozone (O3) spatiotemporal distribution, variations and its causes in Beijing in 2014−2020 are revealed by quantitative estimates of the trends of 12 ozone metrics relevant to human health and tropospheric NO2 and formaldehyde (HCHO) column concentration, based on the air quality monitoring network data and satellite retrievals from the Ozone Monitoring Instrument (OMI). Results showed that the maximum O3 concentrations decreased slightly since 2014. The annual 90th percentile of the daily maximum eight-hour average (MDA8) O3 and the “ozone-season” (April–September) MDA8 decreased by 0.32 and 0.19 μg m⁻³ year⁻¹, respectively. The changes in Beijing contrast the widespread and significant O3 increases in the Beijing–Tianjin–Hebei region in recent years. However, significant positive trends in MDA8-90th and ozone-season MDA8 were observed in 7% and 14% of monitoring sites in Beijing (p < 0.05), most of which are located in urban areas and suburbs close to urban areas. The spatial distribution of high O3 values in Beijing has changed significantly. The areas with high O3 concentrations shifted from the northern suburbs (Changping and Miyun districts) to the northeastern and southwestern suburbs and the east of the central urban area. The ozone-season NO2 and HCHO tropospheric columns showed reductions of 4.2% and 0.4% year⁻¹, respectively, from 2014 to 2019 in Beijing, which suggested that the decrease in NOX emissions was much greater than the decrease in volatile organic compound (VOC) emissions. Such an extremely inappropriate control ratio of ozone precursor NOX/VOCs led to an overall trend of slow declining fluctuations of O3 and an increasing trend of individual sites in Beijing. Obviously, the reduction of VOCs in Beijing is far from sufficient, and the significant decrease of Beijing’s O3 concentration can only be achieved by a drastically reduction in VOC emissions.
China is faced with increasing ozone pollution due to rapid economic development and urbanization. Although the ground monitoring network provides continuous real-time ozone measurements, its practical applications are limited due to sparse spatial distribution. The monitoring network coupling with various data and the machine learning algorithm is a promising approach to estimate surface ozone concentrations. However, previous studies on ozone estimation in China are restricted to small study scale, low spatial resolution and low predictive ability. The study aims to 1) improve the accuracy of surface ozone estimates across China using an iterative random forest (RF) model, more recent ground monitoring data and high-resolution grid meteorological data, and 2) estimate the daily max 8-h average ozone concentrations across China during 2008–2019 at a spatial resolution of 0.0625°. The iterative RF model showed that the sample-based and site-based cross-validation (CV) R² were 0.84 and 0.79, respectively, indicating higher accuracy than the single RF model and previous studies. Daily max 8-h average ozone product across China was estimated during 2008–2019 with an improved spatial resolution of 0.0625°. The newly generated ozone product shows great potential in future studies to assess the short-term and long-term health effect of ozone pollution.
Atmospheric formaldehyde (HCHO) is a potential pollutant and very harmful to public health at higher doses. There are different sources for HCHO in the atmosphere, in which fuel combustion and biomass burning are predominant. The oxidation of hydroxyl radicals (OH) and methane are the chemical production pathways of HCHO in the troposphere. Here, we show a different source of HCHO emission to the atmosphere; the maritime shipping. The analyses using satellite measurements for the period 2005–2014 reveal large amounts of HCHO release along the ship routes in Indian Ocean, about 7–8 x1015 molec./cm2. This is nearly twice (150–200%) the ambient or background HCHO levels (about 4 × 1015 molec./cm2), when there is no ship emissions in the north Indian Ocean. The trend in HCHO concentrations over the Indian Ocean sea routes is about 0.008 × 1015 molec./cm2/year. The amount and the increasing trends of HCHO over the maritime routes in the north Indian Ocean are also comparable to those of the busiest sea-lanes in the world Oceans, such as the Panama Canal, Mediterranean Sea and Strait of Malacca. Our analyses, henceforth, suggest use of a better fuel for shipping to reduce the maritime pollution, as the polluted air can often be transported to the coastal regions and islands, which is a concern for public health in those regions.
Environmental chemistry is becoming increasingly important and is crucial in the understanding of a range of issues, ranging from climate change to local pollution problems. Principles of Environmental Chemistry draws upon sections of the authors' previous text (Understanding our Environment) and reflects the growing trend of a more sophisticated approach to teaching environmental science at university. This new, revised text book focuses on the chemistry involved in environmental problems. Written by leading experts in the field, the book provides an in depth introduction to the chemical processes influencing the atmosphere, freshwaters, salt waters and soils. Subsequent sections discuss the behaviour of organic chemicals in the environment and environmental transfer between compartments such as air, soil and water. Also included is a section on biogeochemical cycling, which is crucial in the understanding of the behaviour of chemicals in the environment. Complete with worked examples, the book is aimed at advanced undergraduate and graduate chemistry students studying environmental chemistry.
The G7 countries are facing the challenges of high urbanization, growing ecological footprint, and decreasing biocapacity. In these countries, urban areas are the center of economic activities and resource consumption. On this note, current study examines the effect of urbanization and human capital on the ecological footprint in G7 countries. The study uses advanced panel data estimators, such as CUP-FM and CUP-BC on data from 1971 to 2014. The findings reveal that urbanization increases the ecological footprint, whereas human capital reduces it. The reliability of long-run estimates is also examined by using CO2 emissions as a proxy of environmental impact. The results of causality test disclose unidirectional causality from human capital and urbanization to the ecological footprint. However, the causality between urbanization, human capital, and economic growth is bidirectional. Moreover, energy consumption, economic growth, and import increase environmental degradation, while export and foreign direct investment reduce environmental degradation. Finally, detailed policy options are proposed to combat environmental challenges of G7 countries.
Currently, urban air pollution becoming the major issue of urban physical environment in high density urban area. Many wind-calm zones or vortex zones can be formed where air pollution is retained or concentrated, which affects the environment and human health. To investigate this problem, the authors analyzed changes of wind velocity, direction, and air pollutant flow caused by changes in building height, volume, form, and density using a simulated three-dimensional (3D) conceptual model. The authors conducted an empirical study based on a representative high-density urban area. The results reveal that the actual 3D-simulated environment is complex. The wind environment changes continuously, and the retention or flow of the air pollutants changes drastically as well. The corner wind zones surrounding high-rise buildings may even generate new dust pollution due to the overly high wind speed. In this process, building height volume, layout, and orientation all significantly influence the flow and distribution of air pollution. Based on theoretical and empirical study, this paper discussed spatial planning strategies on the macroscopic city level, mesoscopic block level, and microscopic building level intended to promote the rapid dispersion of air pollutants by controlling the wind environment through optimizing the urban form.
While urbanization has boosted the global economy, it is putting increasing pressure on air quality. Previous studies on the link between urbanization and air pollution have tended to focus on individual aspects of urbanization. In addition, research into the global scale has been scarce. This study constructed an urbanization index system integrating demographic, spatial, economic, and social components and divided 190 countries into 4 subpanels according to the national income levels, in order to identify the heterogeneity effects of urbanization on PM2.5 pollutants for the period 1998–2014 from a global perspective. The results of the panel regression models prove that the effect of urbanization on atmospheric contamination varied significantly across the income-based subpanels. The model analysis shows that demographic urbanization has a significant positive effect on PM2.5 concentrations in all subpanels. Spatial urbanization had exerted a negative effect on air pollution in high-income countries and a positive influence on air pollution in other countries. Social urbanization, in contrast, presented the opposite trend. Additionally, the model analysis shows that the economic urbanization in upper-middle-income and high-income groups can effectively alleviate PM2.5 pollutants. This study indicated that the level of development needs to be taken into account when government policy makers formulate targeted measures to control haze and improve air quality.
China's economic growth has significantly increased emissions of tropospheric ozone (O 3) precursors, resulting in increased regional O 3 pollution. We analyzed data from > 1400 monitoring stations and estimated the exposure of population and vegetation (crops and forests) to O 3 pollution across China in 2015. Based on WHO metrics for human health protection, the current O 3 level leads to +0.9% premature mortality (59,844 additional cases a year) with 96% of populated areas showing O 3-induced premature death. For vegetation, O 3 reduces annual forest tree biomass growth by 11-13% and yield of rice and wheat by 8% and 6%, respectively, relative to conditions below the respective AOT40 critical levels (CL). These CLs are exceeded over 98%, 75% and 83% of the areas of forests, rice and wheat, respectively. Using O 3 exposure-response functions, we evaluated the costs of O 3-induced losses in rice (7.
India's increased pace of urbanisation is evident, but the question remains as to whether India can harness its developmental potential by providing social infrastructure to meet its projected growth. This paper investigates the urbanisation trajectory with respect to the provision of social infrastructure in the Capital Region of India. First, it applies the differential urbanisation model and predicts counter‐urbanisation to be the next stage of development. Second, using socio‐economic indicators, the paper finds high literacy rates and non‐agricultural employment in small towns. Third, it explains deconcentration of large cities as an outcome of congested social infrastructure provision. Fourth, it determines that small towns continue to have poor provision of social infrastructure. This paper recommends the integration of spatial planning with social infrastructure planning, the empowerment of lower‐tier authorities for social infrastructure delivery, and measures for raising local government revenue in the region and in similar regions throughout the Global South.