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The DN method, referred to a gas chromatography (GC) method uses dinitrogen as a carrier gas, in combination with opaque static chamber, was widely used to measure grassland nitrous oxide (N 2 O) fluxes. However the N 2 O fluxes were positively biased by this method, as compared to the other GC methods. Currently, no study was conducted through simultaneous measurements of N 2 O fluxes by DN and other GC methods to correct the biased fluxes by the DN-based opaque static chamber measurement in grasslands. For this purpose, DN and DN-CO 2 methods (dinitrogen is also used as a carrier gas, and carbon dioxide as a make-up gas), both in combination with opaque static chambers, were compared through paired measurements in alpine pastures, including meadow as grazed pasture (MGP), ungrazed meadow (UGM), zokor mounds in meadow (ZMM), dung patches in meadow (DPM) and peat wetland as pasture (PWP). The DN method resulted in N 2 O fluxes about 11.1, 12.1 and 7.5 times higher (p < 0.05) in MGP, UGM and ZMM, respectively, while there was no significant difference between the two methods in DPM or PWP. All the paired fluxes with DN-CO 2 measurements >15 μg N m−2 h−1 showed positive correlations between the N 2 O fluxes measured by the two methods (p < 0.0001), whereas the other measurements showed a negative linear correlation of flux differences between the two methods versus DN-measured fluxes (p < 0.0001). We further developed correction approaches for DN-measured fluxes and validated these corrections using the data from this study or those observed previously in different terrestrial ecosystems by other studies. The estimated annual N 2 O emissions from grasslands in China would be reduced from 288.1 to 98.7–142.3 Gg N yr−1 (1 Gg = 109 g) if DN-measured fluxes were corrected using the approaches established in this study. We concluded that the DN method should be replaced by other GC methods or non-GC techniques to measure N 2 O fluxes from terrestrial ecosystems. Moreover, our study provides a valid approach to correct DN-measured N 2 O fluxes from global grasslands. X c denotes corrected DN-measured nitrous oxide (N 2 O) flux (μg N m−2 h−1). DN is a widely used gas chromatograph (GC) method that analyzes N 2 O with an electron capture detector (ECD), uses dinitrogen (N 2) as the carrier gas but does not use a make-up gas while not filtering samples using, e.g., ascarite. The correction approaches are established for measurements of DN in combination with opaque static chambers. In b, DN and Non-DN are the N 2 O fluxes obtained by DN and other GC-ECD methods, respectively, in different terrestrial ecosystems as non-hot cases. DN c1 , DN c2 and DN c3 are the DN-measured N 2 O fluxes corrected by (1) a previously developed approach for fertilized croplands, and the approaches established in this study based on (2) instantaneously fluxes and (3) annual and seasonal mean fluxes, respectively. Different capital letters above the bars indicate significant differences at p < 0.05. [Display omitted] • Measurements by DN, a widely used GC method, largely bias N 2 O fluxes of grasslands. • DN should be replaced by non-DN techniques to measure N 2 O emissions from soils. • Approach for correcting bias of DN-measured N 2 O fluxes is developed and validated. • This approach is applicable for correction of DN measurements from grasslands. [ABSTRACT FROM AUTHOR]

Fine particulate matter (PM 2.5 ) has attracted increasing attention due to its impacts on air quality and human health. As an important source of PM 2.5 , diesel vehicles are often the focus of research. In this study, we characterized the carbonaceous composition of PM 2.5 that is emitted from on-road China III diesel trucks (DTs). Organic carbon (OC), elemental carbon (EC), and PM 2.5 emission characteristics were determined for 17 China III DTs, including 6 light-duty diesel trucks (LDDTs), 5 medium-duty diesel trucks (MDDTs), and 6 heavy-duty diesel trucks (HDDTs), based on real-world measurements in Beijing, China, using a portable emissions measurement system (PEMS). The average distance-based PM 2.5 emission factors (EFs) (g km −1 ) generally increased and the average CO 2 -based PM 2.5 EFs (g (kg of CO 2 ) −1 ) generally decreased with increased vehicle size from LDDTs to MDDTs to HDDTs. The effects of driving conditions on the EFs for carbonaceous PM 2.5 were analyzed. The results show that distance-based and CO 2 -based EFs strongly depend on driving conditions. Generally, greater amounts of PM 2.5 and OC are emitted from non-highway driving cycles, and greater amounts of EC are emitted from highway driving cycles for vehicles of the same size. For LDDTs, MDDTs, and HDDTs, no significant differences were observed between vehicles with different EC/OC ratios; therefore, the EC/OC ratio is not useful for distinguishing between the emissions generated by differently sized vehicles. The EC/OC, OC/PM 2.5 , and EC/PM 2.5 mass ratios are strongly dependent on driving conditions for vehicles of the same size. The results of this study provide EFs for the carbonaceous composition of PM 2.5 that are more appropriate for China; these results will be helpful for improving policies that are designed to control the carbonaceous composition of PM 2.5 emitted from on-road DTs in China. [ABSTRACT FROM AUTHOR]

Primary nonferrous metal smelting is one of the most significant anthropogenic mercury emission sources. A spatially resolved mercury emission inventory over a long time span is essential for assessment of mercury source attribution and mercury transport modeling. In this study, based on updated technology-based emission factors, the atmospheric mercury emissions originating from primary zinc, lead and copper smelting in China were calculated. The inventory indicated that the total mercury emission from nonferrous metal smelting in China was 14.65 Mg in 2010, lower than the estimations in previous studies. The contributions of point and non-point sources were 23.3% and 76.7%, respectively. In 2010, the mercury emission from primary zinc, lead and copper smelting was 7.49, 6.05 and 1.10 Mg, respectively, and the Hg 2+ , Hg 0 and Hg P emissions were 8.10, 6.16 and 0.75 Mg, respectively. Spatially, the province with the largest emission was Sichuan, followed by Henan, Gansu, Shaanxi, Hunan and Yunnan provinces. The historical emissions were estimated based on dynamic emission factors that take the temporal technology changes into consideration. During 1949–2010, the cumulative mercury emission from China's nonferrous metal smelting was 323.0 Mg, of which the emission from lead smelting accounted for 44.6%, followed by zinc smelting (32.8%) and copper smelting (22.6%). From 1949 to 2010, the contribution of mercury emission from zinc smelting increased from 1.4% to 53.7%, while that from lead smelting showed a decreasing trend. For copper smelting, its contribution reached the maximum (40.1%) in 1987. [ABSTRACT FROM AUTHOR]

In order to investigate the effects of the Coronavirus Disease 2019 (COVID-19) lockdown on air quality in cities in southwest China, a single particle aerosol mass spectrometer (SPAMS) and other online equipments were used to measure the air pollution in Chengdu, one of the megacities in this area, before and during the lockdown period. It was found that the concentrations of fine particulate matter (PM 2.5), nitric oxide (NO), nitrogen dioxide (NO 2), sulfur dioxide (SO 2) and carbon monoxide (CO) decreased by 38.6%, 77.5%, 47.0%, 35.1% and 14.1%, respectively, while the concentration of ozone (O 3) increased by 57.5% from the time before to the time during lockdown. All particles collected during the study period could be divided into eight categories: biomass burning (BB), coal combustion (CC), vehicle emissions (VE), cooking emissions (CE), Dust, K-nitrate (K–NO 3), K-sulfate (K–SO 4) and K-sulfate-nitrate (K-SN) particles, and their contributions changed significantly after the beginning of lockdown. Compared to before lockdown, the contribution of VE particles experienced the largest reduction (by 14.9%), whereas the contributions of BB and CE particles increased by 7.0% and 7.3%, respectively, during the lockdown period. Regional transmission was critical for pollution formation before lockdown, whereas the pollution that occurred during the lockdown period was caused mainly by locally emitted particles (such as VE, CE and BB particles). Weighted potential source contribution function (WPSCF) analysis further verified and emphasized the difference in the contribution of regional transmission for pollution formation before and during lockdown. In addition, the potential source area and intensity of the particles emitted from different sources or formation mechanisms were quite different. • Single aerosol particles during the COVID-19 lockdown were measured based on SPAMS. • The lockdown caused reductions in PM 2.5 , NO, NO 2 , SO 2 and CO, while increase in O 3. • Vehicle emission particles decreased the most (by 14.9%) during lockdown period. • Pollution formation mechanism before and during lockdown was completely different. [ABSTRACT FROM AUTHOR]