Lovleen Gupta

Electric vehicles are increasingly adopted in India to reduce transport‐related greenhouse gas emissions. The study evaluates the environmental impacts of two widely used lithium‐ion battery chemistries—Nickel Manganese Cobalt 8:1:1 (NMC811) and Lithium Ferro Phosphate (LFP)—using life cycle assessment under present Indian conditions and a projected 2040 scenario. Inventory data were obtained from established scientific literature and assessed across 10 environmental impact categories using the ReCiPe 2016 method. The comparative LCA showed that the Li‐ion battery with an LFP cathode has the lowest environmental impact compared to NMC811. The global warming potential of NMC811 is 9.31 kg CO₂‐eq, nearly twice that of LFP (4.44 kg CO₂‐eq per kg). NMC811 also exhibits higher impacts in fossil fuel potential, water consumption, marine eutrophication, ozone depletion, human toxicity, and ionizing radiation. LFP performs worse only in terrestrial acidification potential, mainly due to mining and material production. The 2040 scenario indicates increased impacts for both chemistries across all categories, with impacts rising by about 60–75% for LFP and nearly doubling for NMC811, driven by higher electricity demand and fossil fuel dependence. The impact can be decreased by increasing the share of renewables in the Indian energy grid.

Global air quality trends suggest decreased PM10 levels with increased precipitation, however, Peninsular India exhibits a distinct pattern. This research investigates the correlation between precipitation and PM10 concentrations in Peninsular India, with special focus on the anomalous relationship between the two variables, where rainfall does not consistently lead to lower PM10 concentration levels. The study examines data from 11 air quality monitoring stations across four states, considering PM10 concentrations, precipitation intensities and meteorological data of wind. Statistical analyses were employed to study the distribution patterns of PM10 mass concentrations corresponding to the type of rainfall during the monsoon season in every city of research. To investigate further, the correlation between PM10 levels before the rainfall and the average precipitation intensity during the rainfall duration was established. Results have revealed that the impact of precipitation on PM10 concentration levels varies depending upon the pollutant’s concentration before the rainfall duration and precipitation intensities. Light rainfall (precipitation intensity between 2.5 mm/day to 7.6 mm/day) leads to a decrease in PM10 concentration levels in particular meteorological conditions, whereas very light rainfall (precipitation intensity less than 2.5 mm/day) increases the PM10 concentration levels post rainfall. The scavenging effect of precipitation is investigated by measuring the difference in PM10 concentration levels before and after a certain precipitation intensity. When initial PM10 concentration is lower than the seasonal average, results show a little increase in PM10 concentration levels after a light rainfall lasting less than 10 hours. This research also explores the fluctuations in the PM10 concentration levels under different wind directions and speeds. It is observed that increasing wind speed in one direction improves the clearance effect on PM10 concentrations. The objective of this research is to close the knowledge gap between regional meteorological conditions (primarily related to precipitation and wind dynamics) and regional air quality by offering data-backed observations. This facilitates effective air pollution management for such disparate air quality patterns.

This study compares satellite-based observations of PM2.5 and Total Carbon (TC) concentrations derived from NASA’s MERRA-2 reanalysis dataset for the Ghaziabad region with ground-based observations at two sites (Site A and Site B) from June 2018 to May 2019. Results reveal consistent underestimation by MERRA-2, with daily mean biases of -85.34 (Site A) and -111.31 (Site B) for PM2.5, and -54.77 (Site A) to -59.08 (Site B) for TC, alongside monthly mean biases of -81.30 to -103.74 for PM2.5 and -54.77 to -59.08 for TC. The absolute error indicates a 49.01% to 53.85% underestimation for both PM2.5 and TC. Daily FAC2 values show around 39% agreement for PM2.5, reducing to 0.27 (Site A) and 0.3 (Site B) monthly, indicating reduced agreement over time. For TC, daily FAC2 is notably low at 0.04 (Site A) and 0.06 (Site B), with no monthly agreement within a factor of 2 of ground-level data. Strong correlations (R²=0.68-0.84 for PM_2.5; R²=0.94-0.96 for TC) between biases and ground-level data are observed, indicating proportional relationships. However, discrepancies increase with higher PM2.5 mass concentration, highlighting MERRA-2’s limitations during elevated pollution periods. Significant monthly variations are observed in GLC-PM_2.5 concentrations at Site A (F= 61.42, p= 1.68×10^-11) and Site B (F=25.15, p=2.96×10-06), and For GLC-TC concentrations at Site A (F=103.85, p=4.10×10^-16) and Site B (F=55.70, p=7.54×10^-11). Both GLC and MERRA-2 PM_2.5 and TC concentrations follow a consistent monthly pattern, with higher levels during post-monsoon and winter seasons and lower levels during monsoon and pre-monsoon periods. This study underscores MERRA-2’s limitations in estimating PM_2.5 and TC concentrations compared to ground-based observations and emphasises the necessity for further refinement and validation of the MERRA-2 model to enhance accuracy across different spatial and temporal scales.

Air pollution, specifically the presence of particulate matter (PM10) is a growing concern in many parts of the world, including Sri Lanka because of their ability to cause series health risks, destructive environmental damage and their negative effects on the nation’s economy. Since Colombo is the commercial capital of Sri Lanka, this study analyzed the PM10 concentrations in Colombo over one-year period; impact of meteorological parameters on the PM10 levels and potential source regions. To accomplish this, data on 24-hour average PM10 concentrations and meteorological parameters were collected at Colombo from Jan to Dec 2022. Colombo experienced 40.5 ± 26.6µgm^-3 average PM₁₀ concentrations in 2022 which is about 3 times higher than WHO guidelines (15µgm^-3). Seasonally, Northeast monsoon season experienced the highest average PM₁₀ concentration (~56.8 µgm^-3) in Colombo that may be attributed to low rainfall (~3.8mm) and low wind speed (~12.1mph). Conversely, minimum average PM10 level (~24.2 µgm^-3) occur during Southwest monsoon which may be caused by higher rainfall (~8.4mm) and wind speed (~17.9mph). CBPF was used to evaluate the potential source regions for high PM10 levels in Colombo, indicating potential sources could be vehicular emission, thermal power plant, waste combustion and industrial emissions. The results of this study assist policy makers in charting the control strategies in the region.

E-commerce packaging waste is a matter of concern, especially with the increasing popularity of online shopping due to the COVID-19 pandemic. This leads to the generation of a massive amount of e-commerce packaging waste as well as resource utilisation and CO₂ emissions that go into the production of packaging. The aim of this study is to analyse the impact of COVID-19 on consumer trends in the e-commerce industry, quantitatively analyse the carbon emissions of packaging used, and present a circular model to reduce the demand for virgin packaging. Using a convenience sampling method, an online questionnaire was administered to 285 respondents to gather data on changes in shopping practices due to the COVID-19 pandemic, consumer awareness levels and observations on packaging materials, and practices employed by e-commerce companies. It was found that the number of orders placed per month increased after the onset of the pandemic and that most households dispose of packaging with household wastes as opposed to reusing or recycling. Primary data (study participants packaging waste production) in combination with secondary data (emission factors) was further used to calculate emissions due to mixed packaging waste, which came out to be 2,705.94 kg CO₂e per metric tonne of waste produced. In addition, the paper presents a practical solution to reducing virgin packaging material production, as well as modifications in packaging used to ensure efficient working of the packaging reuse model when implemented by the e-commerce companies.