Accurate estimation of emissions of greenhouse gases (GHGs) is required for making effective climate change mitigation policies at the national level. Among major sources, municipal solid waste (MSW) is an important source of GHGs, such as methane (CH₄), generated during the anaerobic decomposition of organic matter. In Viet Nam, the emissions of GHGs are not well quantified, in particular from the MSW management system. In this study, we estimated emissions of GHGs from the MSW management system of Ho Chi Minh City (HCMC), considering the current waste management practices. In HCMC, landfilling has been a common practice of solid waste management. About 85 percent of the total MSW generated in the city has been landfilled at two landfill sites. Our estimates show that landfilling was the significant source of GHGs in HCMC, with a net contribution of 781.05 kg CO₂-equivalent (CO₂-eq.) per tonne of MSW landfilled. From the whole MSW management system, the direct GHG emission was 768.61 (kg CO₂-eq. per tonne of MSW) with avoided emissions of 72.47 (kg CO₂-eq. per tonne of MSW) through composting and recycling of MSW. The net GHG emission from the MSW management system was 696.14 kg CO₂-eq. per tonne of MSW (≈1.665 million tonnes of CO₂-eq. per year). The GHG emission data of this study may be useful to policymakers for making effective climate change mitigation policies.

The COVID-19 pandemic spread all over the world in early 2020. India imposed a nationwide lockdown on March 25, 2020, for more than a month to contain the COVID-19 infection. During the nationwide lockdown, transport, industries, and commercial activities were suspended, except for essential services. We made a detailed analysis of the impacts of COVID-19 on air quality in India by using the data from more than 200 Continuous Ambient Air Quality Monitoring Stations (CAAQMS) and reported a change in the National Air Quality Index (NAQI), spatial distribution and concentration levels of PM10, PM2.5, CO, NO2, SO2, and O3 from January to April 2020 nationwide and in five major cities, namely, Delhi, Mumbai, Kolkata, Chennai, and Hyderabad. We defined the period between February 25 to March 24, 2020, as ‘before lockdown’ and March 25 to April 30, 2020, as ‘during lockdown’. The NAQI and satellite visual maps of AOD, NO2, CO, and SO2 from January to April 2020 showed a significant decrease in air pollution levels in India. The average concentration levels of PM10, PM2.5, CO, NO2, and SO2 have decreased nationwide by 33, 34, 21, 47, and 21%, respectively, during the nationwide lockdown compared to their concentration levels before the lockdown. While comparing their concentration levels of the nationwide lockdown period with those observed in April 2019 at the same CAAQMS, it was found that the nationwide average concentration levels of PM10, PM2.5, CO, NO2, and SO2 were decreased by 53, 45, 27, 54, and 35%, respectively. The trends of decreasing air pollutants during the lockdown in five major cities were almost the same as nationwide. The concentration levels of O3 have shown an increasing trend from January-April 2020 including during the nationwide lockdown. The COVID-19 has provided a rare opportunity for India for the collection of air pollution baseline data which could be useful in the formulation of air pollution reduction policies in the future.

Considering the well-documented impacts of land-use change on water resources and the rapid land-use conversions occurring throughout Africa, in this study, we conducted a spatiotemporal analysis of surface water quality and its relation with the land use and land cover (LULC) pattern in Mokopane, Limpopo province of South Africa. Various physico-chemical parameters were analyzed for surface water samples collected from five sampling locations from 2016 to 2020. Time-series analysis of key surface water quality parameters was performed to identify the essential hydrological processes governing water quality. The analyzed water quality data were also used to calculate the heavy metal pollution index (HPI), heavy metal evaluation index (HEI) and weighted water quality index (WQI). Also, the spatial trend of water quality is compared with LULC changes from 2015 to 2020. Results revealed that the concentration of most of the physico-chemical parameters in the water samples was beyond the World Health Organization (WHO) adopted permissible limit, except for a few parameters in some locations. Based on the calculated values of HPI and HEI, water quality samples were categorized as low to moderately polluted water bodies, whereas all water samples fell under the poor category (>100) and beyond based on the calculated WQI. Looking precisely at the water quality’s temporal trend, it is found that most of the sampling shows a deteriorating trend from 2016 to 2019. However, the year 2020 shows a slightly improving trend on water quality, which can be justified by lowering human activities during the lockdown period imposed by COVID-19. Land use has a significant relationship with surface water quality, and it was evident that built-up land had a more significant negative impact on water quality than the other land use classes. Both natural processes (rock weathering) and anthropogenic activities (wastewater discharge, industrial activities etc.) were found to be playing a vital role in water quality evolution. This study suggests that continuous assessment and monitoring of the spatial and temporal variability of water quality in Limpopo is important to control pollution and health safety in the future.

Climate change poses enormous challenges to human civilization in food security, water security, and health security. Anthropogenic emissions of Greenhouse Gases (GHGs) are made responsible for climate change. The climate change mitigation agreements and treaties, from the Kyoto Protocol (1997) to the Paris Agreement (2015), are mainly focusing on emission reduction of GHGs. The Copenhagen Accord (2009) set the target of emission reduction of GHGs to the level of 1990, intending to keep the global warming below 2-degree centigrade (°C) above the temperature level of the pre-industrial era. The Paris Agreement (2015) further pursued efforts to limit the temperature increase to 1.5°C by reducing emissions of GHGs to 40 Gigatonne (Gt CO-eq) by 2030. However, assuming the countries will achieve the target of emission reduction of GHGs by 2030, the target of keeping global warming below 1.5°C is unlikely to achieve because the Paris Agreement (2015) has not included emission reduction of black carbon (BC) particles in the intergovernmental negotiation. The BC particles are strong climate warming agents whose climate forcing is more than half of that of carbon dioxide (CO₂) – the main GHG. This article argues for the inclusion of BC mitigation measures in the climate change mitigation measures. As BC also causes severe health impacts, BC mitigation will bring multiple co-benefits for health and environment, including a quick fixing of climate change problems in a few weeks, since the residence time of BC in the atmosphere is about a week.