Characteristics and reduction assessment of GHG emissions from crop residue open burning in China under the targets of carbon peak and carbon neutrality.

Driven by the goal of carbon peak and carbon neutrality, greenhouse gas (GHG) emissions from the crop residue open burning (CROB) in China cannot be ignored. In this study, we have established a high-resolution (0.05° × 0.05°) GHG emissions inventory (including CO2, CH4, and N2O) of CROB from 2012 to 2021 in China based on the VIIRS data and official statistics. To improve the results accuracy, we compared the two commonly used bases for grid allocation, fire counts (FC) and fire radiative power (FRP), in the construction of high-resolution inventory. In 2012, GHG emissions are overestimated by 599 t CO2e per grid on average in 24,577 grids, and underestimated by 1096 t CO2e per grid on average in 13,546 grids based on FC compared to FRP. Then, we characterized the spatial and temporal distribution of GHG emissions from CROB by using the FRP-based method. From 2012 to 2021, total GHG emissions from CROB in China have decreased by 31.2 %, of which the East and South-Central China contributed 22.51 and 9.12 Tg CO2e of GHG reductions, while the Northeast China contributed 10.73 Tg CO2e of GHG growth, respectively. In addition, GHG emissions from CROB on the time scale are mainly concentrated in April, June, and October, with variations between years and regions influenced by the policy, climate, and farmers' perceptions. Finally, we assessed the GHG emission reductions from CROB under different scenarios in the future. By 2060, GHG emissions would be significantly reduced by 57.3 %-77.9 % compared to 2021 under effective control measures. We believe the results will be of great significance for GHG policy formulation and emission reduction potential assessment.

Vehicle emissions of primary air pollutants from 2009 to 2019 and projection for the 14th Five-Year Plan period in Beijing, China.

Over the past decade, the emission standards and fuel standards in Beijing have been upgraded twice, and the vehicle structure has been improved by accelerating the elimination of 2.95 million old vehicles. Through the formulation and implementation of these policies, the emissions of carbon monoxide (CO), volatile organic compounds (VOCs), nitrogen oxides (NOx), and fine particulate matter (PM2.5) in 2019 were 147.9, 25.3, 43.4, and 0.91 kton in Beijing, respectively. The emission factor method was adopted to better understand the emissions characteristics of primary air pollutants from combustion engine vehicles and to improve pollution control. In combination with the air quality improvement goals and the status of social and economic development during the 14th Five-Year Plan period in Beijing, different vehicle pollution control scenarios were established, and emissions reductions were projected. The results show that the emissions of four air pollutants (CO, VOCs, NOx, and PM2.5) from vehicles in Beijing decreased by an average of 68% in 2019, compared to their levels in 2009. The contribution of NOx emissions from diesel vehicles increased from 35% in 2009 to 56% in 2019, which indicated that clean and energy-saving diesel vehicle fleets should be further improved. Electric vehicle adoption could be an important measure to reduce pollutant emissions. With the further upgrading of vehicle structure and the adoption of electric vehicles, it is expected that the total emissions of the four vehicle pollutants can be reduced by 20%-41% by the end of the 14th Five-Year Plan period.

Spatial-temporal heterogeneity and driving factors of PM2.5 in China: A natural and socioeconomic perspective.

Background: Fine particulate matter (PM2.5), one of the major atmospheric pollutants, has a significant impact on human health. However, the determinant power of natural and socioeconomic factors on the spatial-temporal variation of PM2.5 pollution is controversial in China. Methods: In this study, we explored spatial-temporal characteristics and driving factors of PM2.5 through 252 prefecture-level cities in China from 2015 to 2019, based on the spatial autocorrelation and geographically and temporally weighted regression model (GTWR). Results: PM2.5 concentrations showed a significant downward trend, with a decline rate of 3.58 µg m-3 a-1, and a 26.49% decrease in 2019 compared to 2015, Eastern and Central China were the two regions with the highest PM2.5 concentrations. The driving force of socioeconomic factors on PM2.5 concentrations was slightly higher than that of natural factors. Population density had a positive significant driving effect on PM2.5 concentrations, and precipitation was the negative main driving factor. The two main driving factors (population density and precipitation) showed that the driving capability in northern region was stronger than that in southern China. North China and Central China were the regions of largest decline, and the reason for the PM2.5 decline might be the transition from a high environmental pollution-based industrial economy to a resource-clean high-tech economy since the implementation the Air Pollution Prevention and Control Action Plan in 2013. Conclusion: We need to fully consider the coordinated development of population size and local environmental carrying capacity in terms of control of PM2.5 concentrations in the future. This research is helpful for policy-makers to understand the distribution characteristics of PM2.5 emission and put forward effective policy to alleviate haze pollution.

A quantitative assessment of atmospheric emissions and spatial distribution of trace elements from natural sources in China.

Natural sources, such as soil and wind-erosion dust (SWD), biomass open burning (BOB), sea salt spray (SSAS) and biogenic source (BIO), are major contributors to atmospheric emissions of trace elements (TEs) globally. In this study, we used a comprehensive approach to account for area-, production- and biofuel consumption-based emission factor calculation methods, and thus developed an integrated high-resolution emission inventory for 15 types of TEs (As, B, Cd, Co, Cr, Cu, Hg, Mn, Mo, Ni, Pb, Sb, Se, V and Zn) originated from natural sources in China for the year 2015. The results show that national emissions of TEs in 2015 range from 7.45 tons (Hg) to 1, 400 tons (Zn) except for the extremely high emissions of Mn (10, 677 tons). SWD and BIO are identified as the top two source contributors, accounting for approximately 67.7% and 26.1% of the total emissions, respectively. Absolute emissions of TEs from natural sources are high in the Xinjiang, Inner Mongolia and Tibet autonomous regions with large areas of bare soil and desert. However, emission intensity of TEs per unit area in the Southern provinces of China is higher than those in Northern China and Southwestern China, with the Yunnan and Sichuan provinces displaying the highest emission intensity. Our results suggest that controlling SWD can play a significant role in reducing fugitive particulate matter and the associated emissions of TEs from natural sources in China; and desertification control is particularly critical in the Northwest provinces where the majority of deserts are located.

Refined assessment of size-fractioned particulate matter (PM2.5/PM10/PMtotal) emissions from coal-fired power plants in China.

Chinese coal-fired power plants (CFPPs) are experiencing large-scale and rapid retrofitting of ultralow emission (ULE), causing significant changes in emission level of particulate matter (PM) from CFPPs. In this study, based on coal ash mass balance over the whole process, an integrated emission factors (EFs) database of three size-fractioned particulate matters (PM2.5, PM10, and PMtotal) for CFPPs is constructed, which covers almost all typical ULE technical routes installed in CFPPs. To verify the reliability of PM EFs established in this study, we compare those with related results based on field tests. Overall, the gaps in the EFs of PM2.5, PM10, and PMtotal obtained by the two methods are not outrageous within a reasonable range. By combined with the refined size-fractioned PM EFs and unit-based activity level database, a detailed high-resolution emission inventory of PM2.5, PM10, and PMtotal from Chinese CFPPs in 2017 is established, with the corresponding total emissions of 143, 207, and 267 kt, respectively. Our estimation of PMtotal emission is comparable to the official statistics announced by China Electricity Council (CEC), which further demonstrates the reliability of PM EFs constructed in this study. Moreover, potential reductions of PM from CFPPs at two stages before and after 2017 are assessed under three application scenarios of major ULE technical routes. We forecast the final annual emissions of PM2.5, PM10, and PMtotal until 2020 will be reduced further, which fall within the range of 86-111 kt, 120-157 kt, and 142-184 kt, respectively, if all CFPPs achieve ULE requirements under the three scenarios. We believe our integrated database of PM EFs of CFPPs has good universality, and the forecast results will be helpful for policy guidance of ULE technologies, emissions inventory compilation, and regional air quality simulation and management.