RESUMEN
Based on the typical city survey data and statistics of Guangdong Provinceï¼ a 2018-based 3 km×3 km gridded greenhouse gas emissions inventory was developed for Guangdong Province using the combination of top-down and bottom-up emission factor methods. The inventory covered the CO2ï¼ CH4ï¼ and N2O emissions from energyï¼ industrial processesï¼ agricultureï¼ land use change and forestï¼ waste managementï¼ and indirect sources. The results showed that estimates for CO2ï¼ CH4ï¼ and N2O in Guangdong Province for the year 2018 were 8.5×108ï¼ 1.9×106ï¼ and 1.1×105 tï¼ respectivelyï¼ and 8.5×108ï¼ 4.0×107ï¼ and 3.4×107 t by equivalent carbon dioxideï¼ totaling 9.2×108 t. CO2 was the main greenhouse gas in Guangdong Provinceï¼ accounting for 92.0% of the total emissions. Energy and indirect sources were the main emission sourcesï¼ accounting for 77.9% and 7.6%ï¼ respectivelyï¼ totaling 85.5%. Spatial distributions illustrated that most grids were greenhouse gas emissionsï¼ whereas some others were greenhouse gas sinksï¼ the greenhouse gas emissions were distributed mainly in the Pearl River Delta region and had certain characteristics of distribution along the road network and channels. The greenhouse gas grids of high emission were mainly the locations of high energy-consuming enterprises such as large power plantsï¼ steel millsï¼ and cement plants.
RESUMEN
Despite the alleviation of particulate matter (PM), the ambient ozone (O3) concentration is continuously increasing in Hunan province where the investigation of O3 pollution has been rarely reported. Accordingly, the spatio-temporal evolution of O3 pollution was first analyzed based on hourly air quality data observed by national monitoring stations from 2015 to 2020 over 14 cities in Hunan province. Afterwards, the combination of meteorological data from the European Center for Medium-range Weather Forecast (ECMWF) and the generalized additive model (GAM) was applied to investigate the driving factors of the O3 long-term trend during this period. The results presented obvious diurnal, monthly, and seasonal characteristics of O3 variations. High O3 concentrations occurred in May and September monthly, and the peak O3 season was autumn. Furthermore, the 90th percentile O3 increased at a rate of 4.7 µg·(m3·a)-1 temporally, and high O3 values mainly occurred in the north-eastern region spatially, in contrast to the low O3 values in the western region. The modeling results indicated that the increase in O3 was mainly ascribed to precursor emissions. Furthermore, meteorology promoted a rise in O3 with the impact magnitude of 1 µg·(m3·a)-1. Remarkably, meteorology accelerated the O3 increases in spring, summer, and the eastern region, whereas it restrained increases in autumn, winter, and the northwest. The effect of meteorology on PM10 was different from O3 during this period. Overall, this study highlighted the importance of meteorological impacts when regulating emission reduction measures for O3 abatement. It required greater effort regarding O3 mitigation to offset the side-effect from meteorology in meteorology-sensitive seasons and regions. Additionally, the regional corporation is indispensable to reduce O3 transportation from upwind.