Decarbonizing road transportation is an important task in achieving China's climate goals. Illustrating the mitigation potentials of announced policies and identifying additional strategies for various vehicle fleets are fundamental in optimizing future control pathways. Herein, we developed a comprehensive analysis of carbon dioxide (CO) emissions from on-road vehicles as well as their mitigation potentials based on real-world databases and up-to-date policy scenarios. Total CO emissions of China's road transportation are estimated to be 1102 million tons (Mt) in 2022 and will continue to increase if future strategies are implemented as usual. Under current development trend and announced policy controls (i.e., integrated scenario), annual CO emissions are estimated to peak at 1235 Mt in 2025 and then decline to approximately 200 Mt around 2050. The scenario analysis indicates that electrification of passenger vehicles emerges as the most imperative decarbonization strategy for achieving carbon peak before 2030. Additionally, fuel economy improvement of conventional vehicles is identified to be effective for CO emission reduction for trucks until 2035 while new energy vehicle promotion shows great mitigation potentials in the long term. This study provides insight into heterogeneous low-carbon transportation transition strategies and valuable support for achieving China's dual-carbon goals.

The adoption of zero-emission vehicles (ZEVs) offers multiple benefits for the climate, air quality, and public health by reducing tailpipe emissions. However, the environmental justice implications of the nonexhaust emissions from future ZEV fleets for near-roadway communities remain unclear. Here, we model the on-road fine particulate matter (PM) emissions across all California counties and assess the near-roadway exposure disparities at the census block group level in the Los Angeles County in 2050, when almost all passenger vehicles are projected to be ZEVs. We found that promoting zero-emission heavy-duty trucks generates more air quality benefits for disadvantaged communities than light-duty passenger vehicles. Persistent disparities in near-roadway PM levels, however, exist due to the remaining brake and tire wear emissions and increased truck traffic in disadvantaged communities. We recommend implementing fleet-specific ZEV policies to address brake and tire wear emissions and optimizing freight structures to address these persistent environmental justice issues in California.

Air pollution poses a critical public health threat around many megacities but in an uneven manner. Conventional models are limited to depict the highly spatial- and time-varying patterns of ambient pollutant exposures at the community scale for megacities. Here, we developed a machine-learning approach that leverages the dynamic traffic profiles to continuously estimate community-level year-long air pollutant concentrations in Los Angeles, U.S. We found the introduction of real-world dynamic traffic data significantly improved the spatial fidelity of nitrogen dioxide (NO), maximum daily 8-h average ozone (MDA8 O), and fine particulate matter (PM) simulations by 47%, 4%, and 15%, respectively. We successfully captured PM levels exceeding limits due to heavy traffic activities and providing an "out-of-limit map" tool to identify exposure disparities within highly polluted communities. In contrast, the model without real-world dynamic traffic data lacks the ability to capture the traffic-induced exposure disparities and significantly underestimate residents' exposure to PM. The underestimations are more severe for disadvantaged communities such as black and low-income groups, showing the significance of incorporating real-time traffic data in exposure disparity assessment.

Real-world heavy-duty diesel trucks (HDTs) were found to emit far more excess nitrogen oxides (NO) and black carbon (BC) pollutants than regulation limits. It is essential to systematically evaluate on-road NO and BC emission levels for mitigating HDT emissions. This study launched 2109 plume chasing campaigns for NO and BC emissions of HDTs across several regions in China from 2017 to 2020. It was found that NO emissions had limited reductions from China III to China V, while BC emissions of HDTs exhibited high reductions with stricter emission standard implementation. This paper showed that previous studies underestimated 18% of NO emissions in China in 2019 and nearly half of the real-world NO emissions from HDTs (determined by updating the emission trends of HDTs) exceeded the regulation limits. Furthermore, the ambient temperature was identified as a primary driver of NO emissions for HDTs, and the low-temperature penalty has caused a 9-29% increase in NO emissions in winter in major regions of China. These results would provide important data support for the precise control of the NO and BC emissions from HDTs.

In response to climate change, China is making great efforts to increase the green area for carbon sequestration. Road verges, as marginal land with favorable conditions for plant growth and ease of transportation, can be used for biomass production, but the biomass production and carbon sequestration potential have not been assessed. Here, we mapped the biomass production potential of road verges in China by combining a biomass model and Geographic Information System and then evaluated the effect of road runoff and CO fertilization on the production according to the runoff coefficient and vehicle emission inventory. Nationwide, road verges can produce 15.86 Mt C yr of biomass. Road runoff contributes to a biomass production of 1.26 Mt C yr through increasing soil water availability, which mainly occurs in arid regions. The CO fertilization effect by vehicle emission is considerable in Eastern and Southern China, contributing to a production of 0.09 Mt C yr. Life cycle assessment shows that major road verges in China have a carbon sequestration potential of 6.87 Mt C yr currently. Our results revealed that road verges can make a significant contribution to carbon neutrality under proper management.

Vehicle emissions in China have been decoupled from rapid motorization owing to comprehensive control strategies. China's increasingly ambitious goals for better air quality are calling for deep emission mitigation, posing a need to develop an up-to-date emission inventory that can reflect the fast-developing policies on vehicle emission control. Herein, large-sample vehicle emission measurements were collected to update the vehicle emission inventory. For instance, ambient temperature correction modules were developed to depict the remarkable regional and seasonal emission variations, showing that the monthly emission disparities for total hydrocarbon (THC) and nitrogen oxide (NO) in January and July could be up to 1.7 times in northern China. Thus, the emission ratios of THC and NO can vary dramatically among various seasons and provinces, which have not been considered well by previous simulations regarding the nonlinear atmospheric chemistry of ozone (O) and fine particulate matter (PM) formation. The new emission results indicate that vehicular carbon monoxide (CO), THC, and PM emissions decreased by 69, 51, and 61%, respectively, during 2010-2019. However, the controls of NO and ammonia (NH) emissions were not as efficient as other pollutants. Under the most likely future scenario (PC [1]), CO, THC, NO, PM and NH emissions were anticipated to reduce by 35, 36, 35, 45, and 4%, respectively, from 2019 to 2025. These reductions will be expedited with expected decreases of 56, 58, 74, 53, and 51% from 2025 to 2035, which are substantially promoted by the massive deployment of new energy vehicles and more stringent emission standards. The updated vehicle emission inventory can serve as an important tool to develop season- and location-specific mitigation strategies of vehicular emission precursors to alleviate haze and O problems.

Ammonia (NH) plays a vital role in the formation of fine particulate matter (PM). Prior studies have primarily focused on the control of agricultural NH emissions, the dominant source of anthropogenic NH emissions. The air quality impact from vehicular NH emissions, which could be particularly important in urban areas, has not been adequately evaluated. We developed high-resolution vehicular NH emission inventories for Beijing and Shanghai based on detailed link-level traffic profiles and conducted atmospheric simulations of ambient PM concentrations contributed by vehicular NH emissions. We found that vehicular NH emissions shared high proportions among total anthropogenic NH emissions in the urban areas of Beijing (86%) and Shanghai (45%), where vehicular NH was primarily emitted by gasoline vehicles. Local vehicular NH emissions could be responsible for approximately 3% of urban PM concentrations during wintertime, and the contributions could be much higher during polluted periods (∼3 μg m). We also showed that controlling vehicular NH emissions will be effective and feasible to alleviate urban PM pollution for megacities in the near future.

The large fluctuations in traffic during the COVID-19 pandemic provide an unparalleled opportunity to assess vehicle emission control efficacy. Here we develop a random-forest regression model, based on the large volume of real-time observational data during COVID-19, to predict surface-level NO, O, and fine particle concentration in the Los Angeles megacity. Our model exhibits high fidelity in reproducing pollutant concentrations in the Los Angeles Basin and identifies major factors controlling each species. During the strictest lockdown period, traffic reduction led to decreases in NO and particulate matter with aerodynamic diameters <2.5 μm by -30.1% and -17.5%, respectively, but a 5.7% increase in O Heavy-duty truck emissions contribute primarily to these variations. Future traffic-emission controls are estimated to impose similar effects as observed during the COVID-19 lockdown, but with smaller magnitude. Vehicular electrification will achieve further alleviation of NO levels.

The lone star tick, , is an obligatory ectoparasite of many vertebrates and the primary vector of , the causative agent of human monocytic ehrlichiosis. This study aimed to investigate the comparative transcriptomes of underlying the processes of pathogen acquisition and of immunity towards the pathogen. Differential expression of the whole body transcripts in six different treatments were compared: females and males that were non-exposed, -exposed/uninfected, and -exposed/infected. The Trinity assembly pipeline produced 140,574 transcripts from trimmed and filtered total raw sequence reads (approximately 117M reads). The gold transcript set of the transcriptome data was established to minimize noise by retaining only transcripts homologous to official peptide sets of and ESTs and transcripts covered with high enough frequency from the raw data. Comparison of the gene ontology term enrichment analyses for the six groups tested here revealed an up-regulation of genes for defense responses against the pathogen and for the supply of intracellular Ca for pathogen proliferation in the pathogen-exposed ticks. Analyses of differential expression, focused on functional subcategories including immune, sialome, neuropeptides, and G protein-coupled receptor, revealed that -exposed ticks exhibited an upregulation of transcripts involved in the immune deficiency (IMD) pathway, antimicrobial peptides, Kunitz, an insulin-like peptide, and bursicon receptor over unexposed ones, while transcripts for metalloprotease were down-regulated in general. This study found that ticks exhibit enhanced expression of genes responsible for defense against .

Strains of exhibit varying levels of virulence against mosquito larvae. The most potent strain, 2362, which is the active ingredient in the commercial product VectoLex, together with another well-known larvicide subsp. , are used to control vector and nuisance mosquito larvae in many regions of the world. Although not all strains of are mosquitocidal, lethal strains produce one or two combinations of three different types of toxins. These are (1) the binary toxin (Bin) composed of two proteins of 42 kDa (BinA) and 51 kDa (BinB), which are synthesized during sporulation and co-crystallize, (2) the soluble mosquitocidal toxins (Mtx1, Mtx2 and Mtx3) produced during vegetative growth, and (3) the two-component crystal toxin (Cry48Aa1/Cry49Aa1). Non-mosquitocidal toxins are also produced by certain strains of , for examples sphaericolysin, a novel insecticidal protein toxic to cockroaches. Larvicides based on have the advantage of longer persistence in treated habitats compared to subsp. . However, resistance is a much greater threat, and has already emerged at significant levels in field populations in China and Thailand treated with . This likely occurred because toxicity depends principally on Bin rather than various combinations of crystal (Cry) and cytolytic (Cyt) toxins present in subsp. . Here we review both the general characteristics of , particularly as they relate to larvicidal isolates, and strategies or considerations for engineering more potent strains of this bacterium that contain built-in mechanisms that delay or overcome resistance to Bin in natural mosquito populations.

Permethrin resistance has been reported worldwide and clinical failures to commercial pediculicides containing permethrin have likewise occurred. Permethrin resistance in head lice populations from the U.S. is widespread but is not yet uniform and the level of resistance is relatively low (~4-8 fold). Permethrin-resistant lice are cross-resistant to pyrethrins, PBO-synergized pyrethrins and to DDT. Nix((R)), when applied to human hair tufts following manufacture's instructions, did not provide 100% control when assessed by the hair tuft bioassay in conjunction with the in vitro rearing system. Resistance to permethrin is due to knockdown resistance (kdr), which is the result of three point mutations within the alpha-subunit gene of the voltage-gated sodium channel that causes amino acid substitutions, leading to nerve insensitivity.A three-tiered resistance monitoring system has been established based on molecular resistance detection techniques. Quantitative sequencing (QS) has been developed to predict the kdr allele frequency in head lice at a population level. The speed, simplicity and accuracy of QS made it an ideal candidate for a routine primary resistance monitoring tool to screen a large number of louse populations as an alternative to conventional bioassay. As a secondary monitoring method, real-time PASA (rtPASA) has been devised for a more precise determination of low resistance allele frequencies. To obtain more detailed information on resistance allele zygosity, as well as allele frequency, serial invasive signal amplification reaction (SISAR) has been developed as an individual genotyping method. Our approach of using three tiers of molecular resistance detection should facilitate large-scale routine resistance monitoring of permethrin resistance in head lice using field-collected samples.