Decline in PM2.5 concentrations over major cities around the world associated with COVID-19.

The COVID-19 started from Wuhan city in China, slowly spread across the globe after December 2019. Due to movement of people from one city to other cities, one country to other countries, infection spreads and COVID-19 became a pandemic. Efforts were made at local, regional and national levels to lockdown the movement of people and to keep infected one in quarantine or isolation to stop the spread of COVID-19. The traffic, market and small industries were closed, as a result pronounced decline in the concentrations of particulate matters (PM) were observed. Normally these sources contribute to the high concentrations of particulate matters (PM2.5) which represents air quality of a location. In this short communication, we present analysis of PM2.5 of major cities (New York, Los Angeles, Zaragoza, Rome, Dubai, Delhi, Mumbai, Beijing and Shanghai) around the world suffered severely with the COVID-19. Our analysis shows decline in PM2.5 concentration due to lockdown, mainly due to less movement of people to keep "social distancing" to control the spread of CORONA-19. The low concentrations of PM2.5 reflect the efforts made in the cities to curb the spread of infection, that improve air quality.

Declining groundwater and its impacts along Ganga riverfronts using combined Sentinel-1, GRACE, water levels, and rainfall data.

The Indo-Gangetic Plains (IGP) in northern India are vast alluvial tracts with huge shallow aquifers, densely populated and agriculturally productive regions. In the last few decades, IGP has been facing water scarcity driven by erratic monsoon dynamics, anthropogenic activity, and hydroclimatic variability. In urban centers, continuous groundwater withdrawal leads to high stress, affecting surface deformation and a threat to buildings and infrastructures. An attempt has been made to explore the possible linkage and coupling between groundwater level, hydroclimatic variables, and subsidence in the Central Ganga Plains (CGP), in Varanasi metropolis using the combined multisensory multitemporal data, Sentinel-1 (2017-2023), GRACE (2003-2023), groundwater levels (1998-2023), and precipitation (2002-2023). Long-term hydrological response in the CGP shows continuous depletion (14.6 ± 5.6 mm/yr) in response to precipitation variability. Results show spatiotemporal variations between GWS, and precipitation estimate with nonlinear trend response due to associated inter-annual/inter-seasonal climate variability and anthropogenic water withdrawal, specifically during the observed drought years. The significant storage response in the urban center compared to a regional extent suggests the potential impact of exponentially increasing urbanization and building hydrological stress in the cities. The implications of reducing storage capacity show measured land subsidence (∼2-8 mm/yr) patterns developed along the meandering stretch of the Ganga riverfronts in Varanasi. The groundwater level data from the piezometric supports the hydroclimatic variables and subsidence coupling. Considering the vital link between water storage, food security, and socioeconomic growth, the results of this study require systematic inclusion in water management strategies as climate change seriously impacts water resources in the future.

Dynamics of land, ocean, and atmospheric parameters associated with Tauktae cyclone.

During the pre- and post-monsoon season, the eastern and western coasts are highly vulnerable to cyclones. The tropical cyclone "Tauktae" formed in the Arabian Sea on 14 May 2021 and moved along the west coast of India, and landfall occurred on 17 May 2021. During the cyclone, the maximum wind speed was 220 km/h with a pressure of 935 mb affecting meteorological, atmospheric parameters, and weather conditions of the northern and central parts of India causing devastating damage. Analysis of satellite, Argo, and ground data show pronounced changes in the oceanic, atmospheric, and meteorological parameters associated during the formation and landfall of the cyclone. During cyclone generation (before landfall), the air temperature (AT) was maximum (30.51 °C), and winds (220 km/h) were strong with negative omega values (0.3). The relative humidity (RH) and rainfall (RF) were observed to be higher at the location of the cyclone formation in the ocean and over the landfall location, with an average value of 81.28% and 21.45 mm/day, respectively. The concentration of total column ozone (TCO), CO volume mixing ratio (COVMR), H2O mass mixing ratio (H2O MMR), aerosol parameters (AOD, AE) and air quality parameter (PM) was increased over land and along the cyclone track, leading to a deterioration in the air quality. The strong wind mixes the air mass from the surroundings to the local anthropogenic emissions, and causing strong mixing of the aerosols. The detailed results show a pronounced change in the ocean, land, meteorological, and atmospheric parameters showing a strong land-ocean-atmosphere coupling associated with the cyclone.

Spatio-temporal evolution of groundwater quality and its health risk assessment in Punjab (India) during 2000-2020.

The state known as the bread basket of India has now been defamed as the cancer capital of the country. The toxicity of groundwater associated with the declining water level is reported in recent years. However, an extensive temporal and spatial analysis is required to identify hotspots. In this study, spatial tools are utilized to understand the evolution of groundwater in Punjab (> 315 sites) for the last two decades (2000-2020) for drinking purposes using the water quality index (WQI). The data for pH, electric conductivity (EC), bicarbonate (HCO3¯), chloride (Cl¯), sulfate (SO42¯), nitrate (NO3¯), fluoride (F¯), calcium (Ca2+), magnesium (Mg2+), sodium (Na+), and potassium (K+) collected from the Central Groundwater Board (CGWB) were analyzed. The results show that the average cation abundance is in declining order of Na > Mg > Ca > K, and anion abundance is in order of HCO3¯ > SO42¯ > Cl¯ > NO3 > F. The ions are compared with water quality standards defined by BIS and WHO. The study shows that in the year 2000, 69.52% of locations are above the acceptable limit for EC, 68.89% for Mg2, 84.76% for Na+, 51.75% for HCO3¯, 38.41% for NO3¯, and 17.20% for F¯. While in the year 2020, 48.89% exceed the acceptable limit for EC, 57.78% for Mg2+, 68.25% for Na+, 34.92% for HCO3¯, 27.30% for NO3¯, and 8.88% for F¯. WQI shows that in the year 2000, 13.01% of sampling locations are categorized as very poor and 20% as unsuitable for drinking. Meanwhile, in 2020, 6.35% of locations are categorized as very poor and 12.38% as unsuitable for drinking in the study area. In addition to the effect on plant growth, consumption of contaminated water can adversely affect human health. The health hazards for F¯ (HQF) and NO3¯ (HQN) and their total health index (THI) are also evaluated that depicts 244 groundwater sampling sites in the year 2000, and 152 sampling sites in the year 2020 show high non-carcinogenic effects on adults, children, and infants. Southwestern Punjab is found to be the worst affected, while north-eastern regions drained by the Himalayan rivers show better quality water. Shifting in agricultural practices in the last two decades and declining water levels due to excess pumping of water from deeper water tables deteriorated the quality of water in the Southern region as observed from the geospatial analysis.

Influence of coal-based thermal power plants on the spatial-temporal variability of tropospheric NO2 column over India.

The oxides of nitrogen--NO(x) (NO and NO(2))--are an important constituent of the troposphere. The availability of relatively higher spatial (0.25° grid) and temporal (daily) resolution data from ozone monitoring instrument (OMI) onboard Aura helps us to better differentiate between the point sources such as thermal power plants from large cities and rural areas compared to previous sensors. The annual and seasonal (summer and winter) distributions shows very high mean tropospheric NO(2) in specific pockets over India especially over the Indo-Gangetic plains (up to 14.2 × 10(15) molecules/cm(2)). These pockets correspond with the known locations of major thermal power plants. The tropospheric NO(2) over India show a large seasonal variability that is also observed in the ground NO(2) data. The multiple regression analysis show that the influence of a unit of power plant (in gigawatts) over tropospheric NO(2) (×10(15) molecules/cm(2)) is around ten times compared to a unit of population (in millions) over India. The OMI data show that the NO(2) increases by 0.794 ± 0.12 (×10(15) molecules/cm(2); annual) per GW compared to a previous estimate of 0.014 (×10(15) molecules/cm(2)) over India. The increase of tropospheric NO(2) per gigawatt is found to be 1.088 ± 0.18, 0.898 ± 0.14, and 0.395 ± 0.13 (×10(15) molecules/cm(2)) during winter, summer, and monsoon seasons, respectively. The strong seasonal variation is attributed to the enhancement or suppression of NO(2) due to various controlling factors which is discussed here. The recent increasing trend (2005-2007) over rural thermal power plants pockets like Agori and Korba is due to recent large capacity additions in these regions.

Improvement of atmospheric pollution in the capital cities of US during COVID-19.

The spread of COVID-19 during 2020 impacted the whole world and still affecting the lives of people living in some parts of the world. The spread of this epidemic started in the US in late March 2020 and became a major issue in April due to an outburst of COVID-19 cases. Most of the countries in the world imposed complete to partial lockdown, but in the US, few states imposed lockdowns. Even after the advisory of the various Government department, the mobility data suggest that there was an enhancement (10-15%) in mobility during March 2020. Later sudden drop in mobility was observed during April 2020. The fall in aerosols optical depth (AOD), particulate matter concentration, NO2, and Ozone are observed along with the positive shifts in the SO2. In some of the states, AOD shows pronounced decline during May and June (5-40.90%), in the month of  May more than 80% decline was observed compared to the month of June 2020. In the month of April 2020, up to 73.64% decline was observed in NO2, and 70-99% in the months of May and June 2020. We found a good relationship between the mobility data and improvement in the air quality of the US. The changes were not significant compared to other countries in the world due to scattered lockdown policy, but in the US a pronounced change is observed during April month compared to March and May.

Increased aerosols can reverse Twomey effect in water clouds through radiative pathway.

Aerosols play important roles in modulations of cloud properties and hydrological cycle by decreasing the size of cloud droplets with the increase of aerosols under the condition of fixed liquid water path, which is known as the first aerosol indirect effect or Twomey-effect or microphysical effect. Using high-quality aerosol data from surface observations and statistically decoupling the influence of meteorological factors, we show that highly loaded aerosols can counter this microphysical effect through the radiative effect to result both the decrease and increase of cloud droplet size depending on liquid water path in water clouds. The radiative effect due to increased aerosols reduces the moisture content, but increases the atmospheric stability at higher altitudes, generating conditions favorable for cloud top entrainment and cloud droplet coalescence. Such radiatively driven cloud droplet coalescence process is relatively stronger in thicker clouds to counter relatively weaker microphysical effect, resulting the increase of cloud droplet size with the increase of aerosol loading; and vice-versa in thinner clouds. Overall, the study suggests the prevalence of both negative and positive relationships between cloud droplet size and aerosol loading in highly polluted regions.

Analysis of Air and Soil Quality around Thermal Power Plants and Coal Mines of Singrauli Region, India.

Singrauli region is known as the energy capital of India, as it generates nearly 21 GW of electricity, supplied to various parts of the northern India. Many coal-based Thermal Power Plants (TPPs) using coal from several nearby coal mines, and numerous industries are set up in this region which has made it as one of the highly polluted regions of India. In the present study, detailed temporal analysis and forecast of carbon dioxide (CO2), nitrogen dioxide (NO2), sulfur dioxide (SO2), and methane (CH4) concentrations retrieved from satellite data have been carried out for the periods 2005-2020. Based on the classical multiplicative model and using linear regression, the maximum concentration of CO2, NO2, SO2, and CH4 in the year 2025 is found to be 422.59 ppm, 29.28 ppm, 0.23 DU, and 1901.35 ppbv, respectively. Detailed analysis shows that carbon dioxide has a 95% correlation with all other trace gases. We have also carried out the geo-accumulation index for the presence of various contaminants in the soil of this region. The geo-accumulation index shows that soil in and around thermal power plants and coal mines is contaminated by heavy metals. The cumulative index shows that soil around Hindalco industries, Bina coal mines, Khadia coal mines, and coal-based TPPs (Anpara and Vindhayachal) are highly polluted and a threat to human population living in the region.

Toward informatics-enabled preparedness for natural hazards to minimize health impacts of climate change.

Natural hazards (NHs) associated with climate change have been increasing in frequency and intensity. These acute events impact humans both directly and through their effects on social and environmental determinants of health. Rather than relying on a fully reactive incident response disposition, it is crucial to ramp up preparedness initiatives for worsening case scenarios. In this perspective, we review the landscape of NH effects for human health and explore the potential of health informatics to address associated challenges, specifically from a preparedness angle. We outline important components in a health informatics agenda for hazard preparedness involving hazard-disease associations, social determinants of health, and hazard forecasting models, and call for novel methods to integrate them toward projecting healthcare needs in the wake of a hazard. We describe potential gaps and barriers in implementing these components and propose some high-level ideas to address them.

Chamoli disaster: pronounced changes in water quality and flood plains using Sentinel data.

The Himalayan rivers are vulnerable to devastating flooding caused by landslides and outbreak of glacial lakes. On 7 February 2021, a deadly disaster occurred near the Rishi Ganga Hydropower Plant in the Rishi Ganga River, killing more than 100 people. During the event, a large volume of debris and broken glacial fragments flooded the Rishi Ganga River and washed away the Rishi Ganga Hydropower plant ongoing project. This study presents the impact of the Chamoli disaster on the water quality of Rishi Ganga River in upstream near Tapovan and Ganga River in downstream near Haridwar through remote sensing data. Five points have been used at different locations across the two study areas and three different indices were used such as Normalized difference water index (NDWI), Normalized difference turbidity Index (NDTI), and Normalized difference chlorophyll index (NDCI), to analyze changes in water quality. Spectral signatures and backscattering coefficients derived from Sentinel-2 Optical and Sentinel-1 Synthetic-aperture radar (SAR) data were also compared to study the changes in water quality. It was evident from the water quality indices and spectral signatures that the flood plains changed significantly. Using spectral signatures and different indices, the water level in the Chilla dam canal near Haridwar was found to decreased after the Chamoli disaster event as the flood gates were closed to stop the deposit of sediments in the canal. Results suggest changes in water quality parameters (turbidity, chlorophyll concentration, NDWI) at the five locations near the deadly site and far away at Haridwar along the Ganga River. This study is a preliminary qualitative analysis showing changes in river flood plain and water quality after the Chamoli disaster.

Impact of tropical cyclone "Fani" on land, ocean, atmospheric and meteorological parameters.

Every year, during the pre-monsoon season, tropical storms form in the Bay of Bengal (BoB) and hit the eastern coast of India, affecting the lives of people living in the coastal region. On 3 May 2019, deadly cyclone Fani impacted coastal areas of Odisha (eastern province) causing large scale damage and the impact was observed up to the Eastern Himalayan region. Detailed analyses of satellite, ground, and Argo data have provided information about the changes on land due to floods caused by heavy precipitation, weather conditions, atmospheric, and ocean parameters. Pronounced changes in ocean and atmospheric parameters were observed at the time of the formation of the cyclone and its movements towards the land, especially along its track. Changes in ocean parameters such as chlorophyll concentration, dissolved oxygen, salinity, and sea surface and sub-surface temperature are found to be associated with the cyclone Fani. Our analysis shows a strong coupling between the land-ocean-atmosphere associated with the cyclone Fani.

Air Quality Over Major Cities of Saudi Arabia During Hajj Periods of 2019 and 2020.

Mecca and Madinah are two holy cities where millions of people in general, visit throughout the years, during Hajj (Muslim's pilgrimage) time number of people visit these holy cities from different parts of the world is very high. However, the Government of Saudi Arabia only allowed 1000 pilgrims during the 2020 Hajj especially when the world is suffering from COVID-19. In the present paper, a detailed analysis of air quality parameters available from ground measurements have been carried over major cities of Saudi Arabia, Mecca, Madinah, and Jeddah from June to September 2019 and 2020. At Mecca and Jeddah, PM10, NO2 and CO concentrations are found to be higher in comparison to stations located close to Madinah. In addition, meteorological parameters, temperature, relative humidity, and wind directions are also analysed to understand changes associated with the meteorological parameters. Our detailed analysis shows a reduction in concentrations of pollutants during the 2020 Hajj, when the lockdown was observed in Saudi Arabia due to COVID-19. During June-August 2020 lockdown period, no major changes in PM10 concentration was observed since there were frequent dust events were observed. In contrast, our results show 44% reduction in NO2 (8.77 ppbv in 2019 to 4.97 ppbv in 2020) and 16% reduction in CO (0.85 ppm in 2019 to 0.72 ppm in 2020) concentrations during COVID-19 restrictions. The concentrations of NO2 and CO do not cause any issue for the air quality as NO2 and CO Indices lie within the green band (Air quality index 0-50). In Mecca, Madinah and Jeddah, the air quality is generally affected during Hajj, but during 2020, the concentration of particulate matter was influenced by local weather conditions.

Spatial Distribution of PM2.5-Related Premature Mortality in China.

PM2.5 is a major component of air pollution in China and has a serious threat to public health. It is very important to quantify spatial characteristics of the health effects caused by outdoor PM2.5 exposure. This study analyzed the spatial distribution of PM2.5 concentration (45.9 µg/m3 national average in 2016) and premature mortality attributed to PM2.5 in cities at the prefectural level and above in China in 2016. Using the Global Exposure Mortality Model (GEMM), the total premature mortality in China was estimated to be 1.55 million persons, and the per capita mortality was 11.2 per 10,000 persons in the year 2016, resulting in higher estimates compared to the integrated exposure-response model. We assessed the premature mortality attributed to PM2.5 through common diseases, including ischemic heart disease (IHD), cerebrovascular disease (CEV), chronic obstructive pulmonary disease (COPD), lung cancer (LC), and lower respiratory infections (LRI). The premature mortality due to IHD and CEV accounted for 68.5% of the total mortality, and the per capita mortality (per 10,000 persons) for all ages due to IHD was 3.86, the highest among diseases. For the spatial distribution of disease-specific premature mortality, the top two highest absolute numbers of premature mortality associated with IHD, CEV, LC, and LRI, respectively, were found in Chongqing and Beijing. In 338 cities of China, we have found a significant positive spatial autocorrelation of per capita premature mortality, indicating the necessity of coordinated regional governance for an efficient control of PM2.5.

Impact of lockdown on air quality in India during COVID-19 pandemic.

First time in India, total lockdown was announced on 22 March 2020 to stop the spread of COVID-19 and the lockdown was extended for 21 days on 24 March 2020 in the first phase. During the total lockdown, most of the sources for poor air quality were stopped in India. In this paper, we present an analysis of air quality (particulate matter-PM2.5, Air Quality Index, and tropospheric NO2) over India using ground and satellite observations. A pronounced decline in PM2.5 and AQI (Air Quality Index) is observed over Delhi, Mumbai, Hyderabad, Kolkata, and Chennai and also a declining trend was observed in tropospheric NO2 concentration during the lockdown period in 2020 compared with the same period in the year 2019. During the total lockdown period, the air quality has improved significantly which provides an important information to the cities' administration to develop rules and regulations on how they can improve air quality.

Optical properties of dust and crop burning emissions over India using ground and satellite data.

Dust storms during the pre-monsoon season (April-June) and crop residual burning events during the post-monsoon season (mid-October-mid-November) are common every year over the Indo-Gangetic plains (IGP). In this paper, we have compared dust storm and crop burning aerosols characteristics for the years 2016, 2017 and 2018 using ground and satellite data. CALIPSO data show that dust layers extended from the ground upto an altitude of about 5 km and the smoke from crop burning upto the height of 2 km. Characteristics of dust and crop burning aerosols show pronounced difference based on Kanpur AERONET data. Dominance of coarse particles (0.6-15 µm) during dust storms (pre-monsoon season), while fine particles (0.05-0.6 µm) dominate during crop residual burning. The spectral variations of single scattering albedo (SSA) during dusty days and crop burning days show low and high fractions of anthropogenic aerosols. We have also observed the impact of dust particles on Himalayan snow (cover, albedo and reflectance) and meteorological parameters (relative humidity and water vapor) on the surface and lower atmosphere using MODIS data and AIRS data at different pressure levels. Pronounced aerosols behaviors of the crop residual burning event coincided with Diwali festival on 30-31 October 2016 were observed. Our detailed analysis combining ground and satellite observations provides better understanding of aerosol optical and microphysical properties of dust storms and crop residual burnings. The results will be valuable in monitoring surrounding environment, identifying the emission source and dynamics of dust storms and crop burning emissions over India, especially in the IGP.

Impact of Deadly Dust Storms (May 2018) on Air Quality, Meteorological, and Atmospheric Parameters Over the Northern Parts of India.

The northern part of India, adjoining the Himalaya, is considered as one of the global hot spots of pollution because of various natural and anthropogenic factors. Throughout the year, the region is affected by pollution from various sources like dust, biomass burning, industrial and vehicular pollution, and myriad other anthropogenic emissions. These sources affect the air quality and health of millions of people who live in the Indo-Gangetic Plains. The dust storms that occur during the premonsoon months of March-June every year are one of the principal sources of pollution and originate from the source region of Arabian Peninsula and the Thar desert located in north-western India. In the year 2018, month of May, three back-to-back major dust storms occurred that caused massive damage, loss of human lives, and loss to property and had an impact on air quality and human health. In this paper, we combine observations from ground stations, satellites, and radiosonde networks to assess the impact of dust events in the month of May 2018, on meteorological parameters, aerosol properties, and air quality. We observed widespread changes associated with aerosol loadings, humidity, and vertical advection patterns with displacements of major trace and greenhouse gasses. We also notice drastic changes in suspended particulate matter concentrations, all of which can have significant ramifications in terms of human health and changes in weather pattern.

Coupling between Land⁻Ocean⁻Atmosphere and Pronounced Changes in Atmospheric/Meteorological Parameters Associated with the Hudhud Cyclone of October 2014.

India is vulnerable to all kinds of natural hazards associated with land, ocean, biosphere, atmosphere, and snow/glaciers. These natural hazards impact large areas and the population living in the affected regions. India is surrounded by ocean on three sides and is vulnerable to cyclonic activities. Every year cyclones hit the east and west coasts of India, affecting the population living along the coasts and infrastructure and inland areas. The extent of the affected inland areas depends on the intensity of the cyclone. On 12 October 2014, a strong cyclone "Hudhud" hit the east coast of India that caused a high degree of devastation along the coast. The impact of this cyclone was seen up to the Himalayan region. Detailed analysis of satellite and ground data show a strong coupling between land-ocean-atmosphere associated with the Hudhud cyclone. The contrast between land and ocean temperature was found to be closely related with the formation of the cyclone in the ocean and its movements towards land. Pronounced changes in the ocean, land, atmospheric, and meteorological parameters with the development of the cyclone and its landfall have been observed. Changes in total column ozone (TCO), relative humidity (RH), and volume mixing ratio of CO (CO VMR), water mixing ratio (H2O MMR), surface latent heat flux (SLHF), and aerosol optical properties derived from satellite data show characteristic behavior of the Hudhud cyclone.

Elevated Black Carbon Concentrations and Atmospheric Pollution around Singrauli Coal-Fired Thermal Power Plants (India) Using Ground and Satellite Data.

The tropospheric NO2 concentration from OMI AURA always shows high concentrations of NO2 at a few locations in India, one of the high concentrations of NO2 hotspots is associated with the locations of seven coal-fired Thermal Power plants (TPPs) in Singrauli. Emissions from TPPs are among the major sources of black carbon (BC) soot in the atmosphere. Knowledge of BC emissions from TPPs is important in characterizing regional carbonaceous particulate emissions, understanding the fog/haze/smog formation, evaluating regional climate forcing, modeling aerosol optical parameters and concentrations of black carbon, and evaluating human health. Furthermore, elevated BC concentrations, over the Indo-Gangetic Plain (IGP) and the Himalayan foothills, have emerged as an important subject to estimate the effects of deposition and atmospheric warming of BC on the accelerated melting of snow and glaciers in the Himalaya. For the first time, this study reports BC concentrations and aerosol optical parameters near dense coal-fired power plants and open cast coal mining adjacent to the east IGP. In-situ measurements were carried out in Singrauli (located in south-east IGP) at a fixed site about 10 km from power plants and in transit measurements in close proximity to the plants, for few days in the month of January and March 2013. At the fixed site, BC concentration up to the 95 µgm-3 is observed with strong diurnal variations. BC concentration shows two maxima peaks during early morning and evening hours. High BC concentrations are observed in close proximity to the coal-fired TPPs (>200 µgm-3), compared to the outside domain of our study region. Co-located ground-based sunphotometer measurements of aerosol optical depth (AOD) show strong spatial variability at the fixed site, with AOD in the range 0.38⁻0.58, and the highest AOD in the range 0.7⁻0.95 near the TPPs in transit measurements (similar to the peak of BC concentrations). Additionally, the Angstrom exponent was found to be in the range 0.4⁻1.0 (maximum in the morning time) and highest in the proximity of TPPs (~1.0), suggesting abundance of fine particulates, whereas there was low Angstrom exponent over the surrounding coal mining areas. Low Angstrom exponent is characterized by dust from the unpaved roads and nearby coal mining areas. MODIS derived daily AOD shows a good match with the MICROTOPS AOD. The CALIPSO derived subtypes of the aerosol plot shows that the aerosols over Singrauli region are mainly dust, polluted dust, and elevated smoke. The preliminary study for few days provides information about the BC concentrations and aerosol optical properties from Singrauli (one of the NO2 hotspot locations in India). This preliminary study suggests that long-term continuous monitoring of BC is needed to understand the BC concentrations and aerosol optical properties for better quantification and the estimation of the emission to evaluate radiative forcing in the region.

Association analysis between spatiotemporal variation of vegetation greenness and precipitation/temperature in the Yangtze River Basin (China).

The variation in vegetation greenness provides good understanding of the sustainable management and monitoring of land surface ecosystems. The present paper discusses the spatial-temporal changes in vegetation and controlling factors in the Yangtze River Basin (YRB) using Global Inventory Modeling and Mapping Studies (GIMMS) Normalized Difference Vegetation Index (NDVI) for the period 2001-2013. Theil-Sen Median trend analysis, Pearson correlation coefficients, and residual analysis have been used, which shows decreasing trend of the annual mean NDVI over the whole YRB. Spatially, the regions with significant decreasing trends were mainly located in parts of central YRB, and pronounced increasing trends were observed in parts of the eastern and western YRB. The mean NDVI during spring and summer seasons increased, while it decreased during autumn and winter seasons. The seasonal mean NDVI shows spatial heterogeneity due to the vegetation types. The correlation analysis shows a positive relation between NDVI and temperature over most of the YRB, whereas NDVI and precipitation show a negative correlation. The residual analysis shows an increase in NDVI in parts of eastern and western YRB and the decrease in NDVI in the small part of Yangtze River Delta (YRD) and the mid-western YRB due to human activities. In general, climate factors were the principal drivers of NDVI variation in YRB in recent years.